In [1]:
import pandas as pd
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

import netCDF4 as nc
import pandas as pd
import os
import csv
from glob import glob
import xarray as xr
import matplotlib.ticker as ticker 

import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from matplotlib.colors import LinearSegmentedColormap, Normalize
from mpl_toolkits.axes_grid1 import make_axes_locatable

import geopandas as gpd
import matplotlib.colors as mcolors
import matplotlib.lines as mlines
from matplotlib.font_manager import FontProperties
In [2]:
# Step 1: Data Preparation
# Load your dataset into a pandas DataFrame
os.chdir('/Users/chenchenren/postdoc/paper/2N and water-US/Figure 3 Yiled under warming scenario/')
In [3]:
# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

data1=data[data['sample'] == 1].copy()
data1=data1.sort_values(by=['geoid', 'scenario'])
print(data1)

data2015=data1[data1['scenario'] == 2015].copy()
print(data2015)


data1['tmp'] = data1.groupby(['geoid','scenario'])['tmp'].transform('mean')
data1['pre'] = data1.groupby(['geoid','scenario'])['pre'].transform('mean')
data1['tmp2015'] = data1.groupby(['geoid','scenario'])['tmp2015'].transform('mean')
data1['pre2015'] = data1.groupby(['geoid','scenario'])['pre2015'].transform('mean')
data1=data1.drop_duplicates(subset=['geoid','scenario'])
data1=data1.drop(['model','lnyield'], axis=1)
print(data1)
       geoid  year       tmp       pre       har  irrigation1  lnyield_obs  \
26081   1001  2015  25.44350  5.702415   779.625     0.377088     7.509678   
26084   1001  2015  24.71859  5.866428   779.625     0.377088     7.509678   
26086   1001  2015  25.15585  5.960842   779.625     0.377088     7.509678   
26087   1001  2015  24.83175  7.541522   779.625     0.377088     7.509678   
26089   1001  2015  25.34826  6.200767   779.625     0.377088     7.509678   
...      ...   ...       ...       ...       ...          ...          ...   
43802  55141  2015  15.16129  7.028600  6700.507     0.000000     7.921128   
43804  55141  2015  16.77098  5.360460  6700.507     0.000000     7.921128   
43805  55141  2015  16.46397  6.299626  6700.507     0.000000     7.921128   
43807  55141  2015  16.07257  6.365017  6700.507     0.000000     7.921128   
43809  55141  2015  18.05135  5.488240  6700.507     0.000000     7.921128   

          lnfer  lnyield  group  sample  scenario   pre2015   model   tmp2015  
26081  2.457656      NaN      1       1       1.5  4.174539    gfdl  26.21985  
26084  2.457656      NaN      1       1       1.5  6.327019    ipsl  24.13167  
26086  2.457656      NaN      1       1       1.5  4.268701     mpi  24.93584  
26087  2.457656      NaN      1       1       1.5  8.572182     mri  25.04051  
26089  2.457656      NaN      1       1       1.5  9.683448  ukesm1  24.72551  
...         ...      ...    ...     ...       ...       ...     ...       ...  
43802  2.556201      NaN      2       1    2015.0  7.028600    gfdl  15.16129  
43804  2.556201      NaN      2       1    2015.0  5.360460    ipsl  16.77098  
43805  2.556201      NaN      2       1    2015.0  6.299626     mpi  16.46397  
43807  2.556201      NaN      2       1    2015.0  6.365017     mri  16.07257  
43809  2.556201      NaN      2       1    2015.0  5.488240  ukesm1  18.05135  

[26595 rows x 15 columns]
       geoid  year       tmp       pre       har  irrigation1  lnyield_obs  \
17218   1001  2015  24.93584  4.268701   779.625     0.377088     7.509678   
26082   1001  2015  26.21985  4.174539   779.625     0.377088     7.509678   
26083   1001  2015  24.13167  6.327019   779.625     0.377088     7.509678   
26088   1001  2015  25.04051  8.572182   779.625     0.377088     7.509678   
26090   1001  2015  24.72551  9.683448   779.625     0.377088     7.509678   
...      ...   ...       ...       ...       ...          ...          ...   
43802  55141  2015  15.16129  7.028600  6700.507     0.000000     7.921128   
43804  55141  2015  16.77098  5.360460  6700.507     0.000000     7.921128   
43805  55141  2015  16.46397  6.299626  6700.507     0.000000     7.921128   
43807  55141  2015  16.07257  6.365017  6700.507     0.000000     7.921128   
43809  55141  2015  18.05135  5.488240  6700.507     0.000000     7.921128   

          lnfer  lnyield  group  sample  scenario   pre2015   model   tmp2015  
17218  2.457656      NaN      1       1    2015.0  4.268701     mpi  24.93584  
26082  2.457656      NaN      1       1    2015.0  4.174539    gfdl  26.21985  
26083  2.457656      NaN      1       1    2015.0  6.327019    ipsl  24.13167  
26088  2.457656      NaN      1       1    2015.0  8.572182     mri  25.04051  
26090  2.457656      NaN      1       1    2015.0  9.683448  ukesm1  24.72551  
...         ...      ...    ...     ...       ...       ...     ...       ...  
43802  2.556201      NaN      2       1    2015.0  7.028600    gfdl  15.16129  
43804  2.556201      NaN      2       1    2015.0  5.360460    ipsl  16.77098  
43805  2.556201      NaN      2       1    2015.0  6.299626     mpi  16.46397  
43807  2.556201      NaN      2       1    2015.0  6.365017     mri  16.07257  
43809  2.556201      NaN      2       1    2015.0  5.488240  ukesm1  18.05135  

[8865 rows x 15 columns]
       geoid  year        tmp       pre        har  irrigation1  lnyield_obs  \
26081   1001  2015  25.099590  6.254395    779.625     0.377088     7.509678   
17216   1001  2015  26.784940  6.208599    779.625     0.377088     7.509678   
17218   1001  2015  25.010676  6.605178    779.625     0.377088     7.509678   
17222   1003  2015  26.261318  9.274925   6358.433     0.738441     7.927428   
17221   1003  2015  27.808318  8.926058   6358.433     0.738441     7.927428   
...      ...   ...        ...       ...        ...          ...          ...   
26072  55139  2015  20.012748  5.680057  14541.420     0.000000     8.028848   
26071  55139  2015  17.287318  5.693542  14541.420     0.000000     8.028848   
26077  55141  2015  17.398562  5.719637   6700.507     0.000000     7.921128   
26076  55141  2015  19.304302  6.116161   6700.507     0.000000     7.921128   
43802  55141  2015  16.504032  6.108389   6700.507     0.000000     7.921128   

          lnfer  group  sample  scenario   pre2015    tmp2015  
26081  2.457656      1       1       1.5  6.605178  25.010676  
17216  2.457656      1       1       3.0  6.605178  25.010676  
17218  2.457656      1       1    2015.0  6.605178  25.010676  
17222  1.292553      1       1       1.5  9.548671  26.127096  
17221  1.292553      1       1       3.0  9.548671  26.127096  
...         ...    ...     ...       ...       ...        ...  
26072  1.255133      2       1       3.0  5.693542  17.287318  
26071  1.255133      2       1    2015.0  5.693542  17.287318  
26077  2.556201      2       1       1.5  6.108389  16.504032  
26076  2.556201      2       1       3.0  6.108389  16.504032  
43802  2.556201      2       1    2015.0  6.108389  16.504032  

[5319 rows x 13 columns]
In [4]:
import pandas as pd
import statsmodels.api as sm

# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

# Create interaction terms
data['tmp_tmp_interaction'] = data['tmp'] ** 2
data['pre_pre_interaction'] = data['pre'] ** 2
data['irrigation12'] = data['irrigation1'] ** 2
data['lnfer_irrigation1_tmp_interaction'] = data['lnfer'] * data['irrigation1'] * data['tmp']
data['lnfer_irrigation12_tmp_tmp_interaction'] = data['lnfer'] * data['irrigation12'] * data['tmp'] ** 2
data['lnfer_irrigation1_pre_interaction'] = data['lnfer'] * data['irrigation1'] * data['pre']
data['lnfer_irrigation12_pre_pre_interaction'] = data['lnfer'] * data['irrigation12'] * data['pre'] ** 2

data['lnfer_tmp_interaction'] = data['lnfer'] * data['tmp']
data['lnfer_tmp_tmp_interaction'] = data['lnfer'] * data['tmp'] ** 2
data['lnfer_pre_interaction'] = data['lnfer'] * data['pre']
data['lnfer_pre_pre_interaction'] = data['lnfer'] * data['pre'] ** 2

# Define predictor variables and response variable
predictor_variables1 = ['lnfer', 'tmp', 'irrigation1', 'irrigation12', 'tmp_tmp_interaction',
                        'pre', 'pre_pre_interaction', 'lnfer_irrigation1_pre_interaction', 'lnfer_irrigation12_pre_pre_interaction',
                        'lnfer_irrigation1_tmp_interaction', 'lnfer_irrigation12_tmp_tmp_interaction']

predictor_variables2 = ['lnfer', 'tmp', 'tmp_tmp_interaction', 'irrigation1', 'irrigation12', 'pre', 'pre_pre_interaction',
                        'lnfer_tmp_interaction', 'lnfer_tmp_tmp_interaction',
                        'lnfer_pre_interaction', 'lnfer_pre_pre_interaction']

response_variable = 'lnyield'

# Function to perform regression analysis
def perform_regression(group_data, predictor_variables):
    X = sm.add_constant(group_data[predictor_variables])
    y = group_data[response_variable]
    return sm.OLS(y, X).fit()

# Create a list to store data rows
data_rows = []

sample_data = data[data['sample'] == 0].copy()
print(sample_data)
project_data = data1
print(project_data)

# Iterate through 'results' and extract values
for group in sample_data['group'].unique():
    group_data = sample_data[sample_data['group'] == group].copy()
    predictor_variables = predictor_variables1 if group == 1 else predictor_variables2
    reg = perform_regression(group_data, predictor_variables)

    for group_proj in project_data['group'].unique():
        if group == group_proj:
            # Calculate y_temp_base based on regression parameters
            tmp_values = project_data[project_data['group'] == group_proj]['tmp'].values
            pre_values = project_data[project_data['group'] == group_proj]['pre'].values
            lnfer_values = project_data[project_data['group'] == group_proj]['lnfer'].values
            irrigation1_values = project_data[project_data['group'] == group_proj]['irrigation1'].values
            
            if group_proj == 1:
                print(reg.params['tmp_tmp_interaction'])
                print(reg.params['const'])
                y_temp_base = (
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 +
                    reg.params['tmp'] * tmp_values +
                    reg.params['pre_pre_interaction'] * pre_values**2 +
                    reg.params['pre'] * pre_values +
                    reg.params['lnfer'] * lnfer_values +
                    reg.params['irrigation1'] * irrigation1_values +
                    reg.params['irrigation12'] * irrigation1_values**2 +
                    reg.params['lnfer_irrigation1_tmp_interaction'] * irrigation1_values * tmp_values * lnfer_values +
                    reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * irrigation1_values**2 * lnfer_values * tmp_values**2 +
                    reg.params['lnfer_irrigation1_pre_interaction'] * irrigation1_values * pre_values * lnfer_values +
                    reg.params['lnfer_irrigation12_pre_pre_interaction'] * irrigation1_values**2 * lnfer_values * pre_values**2 +
                    reg.params['const']
                )
                print(len(y_temp_base))
            else:
                print(reg.params['tmp_tmp_interaction'])
                print(reg.params['const'])
                y_temp_base = (
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 +
                    reg.params['tmp'] * tmp_values +
                    reg.params['pre_pre_interaction'] * pre_values**2 +
                    reg.params['pre'] * pre_values +
                    reg.params['lnfer'] * lnfer_values +
                    reg.params['lnfer_tmp_interaction'] * tmp_values * lnfer_values +
                    reg.params['lnfer_tmp_tmp_interaction'] * lnfer_values * tmp_values**2 +
                    reg.params['lnfer_pre_interaction'] * pre_values * lnfer_values +
                    reg.params['lnfer_pre_pre_interaction'] * lnfer_values * pre_values**2 +
                    reg.params['const']
                )
                print(len(y_temp_base))
            
            # Extract 'geoid', 'scenario', and 'model' from the original data
            geoid_values = project_data[project_data['group'] == group_proj]['geoid'].values
            scenario_values = project_data[project_data['group'] == group_proj]['scenario'].values
            lnyield_obs_values= project_data[project_data['group'] == group_proj]['lnyield_obs'].values
            har_values= project_data[project_data['group'] == group_proj]['har'].values
            
            for tmp, pre, lnfer, irrigation1,y_temp_base_val, geoid, scenario, lnyield_obs,har in zip(
                tmp_values, pre_values, lnfer_values, irrigation1_values,
                 y_temp_base, geoid_values, scenario_values, lnyield_obs_values,har_values
            ):
                data_rows.append([tmp, pre, lnfer, irrigation1, y_temp_base_val, geoid, scenario,
                                  lnyield_obs,har])


# Create a DataFrame from the data
results_base = pd.DataFrame(data_rows, columns=['tmp','pre','lnfer','irrigation1',
                                               'y_temp_base', 'geoid', 'scenario', 
                                                'lnyield_obs','har'])

results_base_t = results_base[(results_base['scenario'] == 1.5)|(results_base['scenario'] == 3)]

# Rename the 'y_temp_base' column to 'y_temp_base2015'
results_base_t.rename(columns={'y_temp_base': 'y_temp_base_t'}, inplace=True)
results_base_t = results_base_t[['geoid', 'scenario','y_temp_base_t','lnyield_obs',
                                 'har','tmp','pre','lnfer','irrigation1']]

print(results_base_t)
       geoid  year       tmp       pre      har  irrigation1  lnyield_obs  \
0       1001  2009  24.14066  8.808839   1900.0     0.718851     7.609614   
1       1001  2010  25.67548  5.438990   1900.0     0.830087     7.035731   
2       1001  2011  24.54482  5.270162   1500.0     0.595086     7.466514   
3       1001  2013  24.03659  7.514143   2400.0     0.001241     7.926855   
4       1003  2008  24.72723  8.675528  19000.0     0.001980     7.934111   
...      ...   ...       ...       ...      ...          ...          ...   
17211  55141  2016  17.48690  7.304833  18200.0     0.000000     8.134343   
17212  55141  2017  16.59024  6.467205  19597.5     0.000000     7.978877   
17213  55141  2018  17.26666  8.373576  23000.0     0.000000     7.838077   
17214  55141  2019  16.23859  8.735889  10100.0     0.000000     7.912185   
17215  55141  2020  16.20263  6.832954  18500.0     0.000000     8.173033   

          lnfer   lnyield  group  ...  pre_pre_interaction  irrigation12  \
0      2.022537  7.900063      1  ...            77.595645      0.516747   
1      1.910005  7.661077      1  ...            29.582612      0.689044   
2      2.025641  7.785866      1  ...            27.774608      0.354128   
3      2.906756  8.084917      1  ...            56.462345      0.000002   
4      1.240602  7.807824      1  ...            75.264786      0.000004   
...         ...       ...    ...  ...                  ...           ...   
17211  2.860158  8.062482      2  ...            53.360585      0.000000   
17212  2.633171  7.905756      2  ...            41.824741      0.000000   
17213  2.639034  8.039181      2  ...            70.116775      0.000000   
17214  2.671287  7.918515      2  ...            76.315757      0.000000   
17215  2.625827  7.873821      2  ...            46.689260      0.000000   

       lnfer_irrigation1_tmp_interaction  \
0                              35.098172   
1                              40.707692   
2                              29.587092   
3                               0.086679   
4                               0.060734   
...                                  ...   
17211                           0.000000   
17212                           0.000000   
17213                           0.000000   
17214                           0.000000   
17215                           0.000000   

      lnfer_irrigation12_tmp_tmp_interaction  \
0                                 609.077444   
1                                 867.597822   
2                                 432.157531   
3                                   0.002585   
4                                   0.002973   
...                                      ...   
17211                               0.000000   
17212                               0.000000   
17213                               0.000000   
17214                               0.000000   
17215                               0.000000   

       lnfer_irrigation1_pre_interaction  \
0                              12.807195   
1                               8.623353   
2                               6.352818   
3                               0.027097   
4                               0.021308   
...                                  ...   
17211                           0.000000   
17212                           0.000000   
17213                           0.000000   
17214                           0.000000   
17215                           0.000000   

       lnfer_irrigation12_pre_pre_interaction  lnfer_tmp_interaction  \
0                                   81.098269              48.825378   
1                                   38.932997              49.040295   
2                                   19.923715              49.718994   
3                                    0.000253              69.868502   
4                                    0.000366              30.676651   
...                                       ...                    ...   
17211                                0.000000              50.015297   
17212                                0.000000              43.684939   
17213                                0.000000              45.567303   
17214                                0.000000              43.377934   
17215                                0.000000              42.545303   

       lnfer_tmp_tmp_interaction  lnfer_pre_interaction  \
0                    1178.676851              17.816203   
1                    1259.133118              10.388498   
2                    1220.343752              10.675456   
3                    1679.400541              21.841780   
4                     758.548605              10.762877   
...                          ...                    ...   
17211                 874.612496              20.892977   
17212                 724.743620              17.029257   
17213                 786.795125              22.098152   
17214                 704.396491              23.336067   
17215                 689.345808              17.942155   

       lnfer_pre_pre_interaction  
0                     156.940062  
1                      56.502937  
2                      56.261384  
3                     164.122260  
4                      93.373644  
...                          ...  
17211                 152.619705  
17212                 110.131694  
17213                 185.040553  
17214                 203.861289  
17215                 122.597920  

[17216 rows x 26 columns]
       geoid  year        tmp       pre        har  irrigation1  lnyield_obs  \
26081   1001  2015  25.099590  6.254395    779.625     0.377088     7.509678   
17216   1001  2015  26.784940  6.208599    779.625     0.377088     7.509678   
17218   1001  2015  25.010676  6.605178    779.625     0.377088     7.509678   
17222   1003  2015  26.261318  9.274925   6358.433     0.738441     7.927428   
17221   1003  2015  27.808318  8.926058   6358.433     0.738441     7.927428   
...      ...   ...        ...       ...        ...          ...          ...   
26072  55139  2015  20.012748  5.680057  14541.420     0.000000     8.028848   
26071  55139  2015  17.287318  5.693542  14541.420     0.000000     8.028848   
26077  55141  2015  17.398562  5.719637   6700.507     0.000000     7.921128   
26076  55141  2015  19.304302  6.116161   6700.507     0.000000     7.921128   
43802  55141  2015  16.504032  6.108389   6700.507     0.000000     7.921128   

          lnfer  group  sample  scenario   pre2015    tmp2015  
26081  2.457656      1       1       1.5  6.605178  25.010676  
17216  2.457656      1       1       3.0  6.605178  25.010676  
17218  2.457656      1       1    2015.0  6.605178  25.010676  
17222  1.292553      1       1       1.5  9.548671  26.127096  
17221  1.292553      1       1       3.0  9.548671  26.127096  
...         ...    ...     ...       ...       ...        ...  
26072  1.255133      2       1       3.0  5.693542  17.287318  
26071  1.255133      2       1    2015.0  5.693542  17.287318  
26077  2.556201      2       1       1.5  6.108389  16.504032  
26076  2.556201      2       1       3.0  6.108389  16.504032  
43802  2.556201      2       1    2015.0  6.108389  16.504032  

[5319 rows x 13 columns]
-0.013398123665888008
0.9408977132139006
3816
-0.00627099550076526
4.94855569752093
1503
      geoid  scenario  y_temp_base_t  lnyield_obs        har        tmp  \
0      1001       1.5       7.846458     7.509678    779.625  25.099590   
1      1001       3.0       7.622792     7.509678    779.625  26.784940   
3      1003       1.5       7.590898     7.927428   6358.433  26.261318   
4      1003       3.0       7.351790     7.927428   6358.433  27.808318   
6      1005       1.5       7.807509     8.161582    526.500  25.408514   
...     ...       ...            ...          ...        ...        ...   
5311  55137       3.0       8.006494     7.941248   5335.875  19.677776   
5313  55139       1.5       7.878360     8.028848  14541.420  18.099080   
5314  55139       3.0       7.962289     8.028848  14541.420  20.012748   
5316  55141       1.5       7.946194     7.921128   6700.507  17.398562   
5317  55141       3.0       8.128488     7.921128   6700.507  19.304302   

           pre     lnfer  irrigation1  
0     6.254395  2.457656     0.377088  
1     6.208599  2.457656     0.377088  
3     9.274925  1.292553     0.738441  
4     8.926058  1.292553     0.738441  
6     6.727813  2.114730     0.028216  
...        ...       ...          ...  
5311  5.922441  1.553310     0.000000  
5313  5.372444  1.255133     0.000000  
5314  5.680057  1.255133     0.000000  
5316  5.719637  2.556201     0.000000  
5317  6.116161  2.556201     0.000000  

[3546 rows x 9 columns]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3163514716.py:119: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  results_base_t.rename(columns={'y_temp_base': 'y_temp_base_t'}, inplace=True)
In [5]:
results_base_test = results_base_t[(results_base['scenario'] == 1.5)]
print(results_base_test)

results_base_test = results_base_t[(results_base['scenario'] == 3)]
print(results_base_test)
      geoid  scenario  y_temp_base_t  lnyield_obs        har        tmp  \
0      1001       1.5       7.846458     7.509678    779.625  25.099590   
3      1003       1.5       7.590898     7.927428   6358.433  26.261318   
6      1005       1.5       7.807509     8.161582    526.500  25.408514   
9      1009       1.5       8.252038     7.840701   1107.736  23.976584   
12     1011       1.5       8.183765     7.984614    870.750  25.246212   
...     ...       ...            ...          ...        ...        ...   
5304  55133       1.5       7.939076     7.974899   7837.872  18.514920   
5307  55135       1.5       7.859488     7.957613   9909.051  17.319042   
5310  55137       1.5       7.893858     7.941248   5335.875  17.765668   
5313  55139       1.5       7.878360     8.028848  14541.420  18.099080   
5316  55141       1.5       7.946194     7.921128   6700.507  17.398562   

           pre     lnfer  irrigation1  
0     6.254395  2.457656     0.377088  
3     9.274925  1.292553     0.738441  
6     6.727813  2.114730     0.028216  
9     6.790346  4.361742     0.056342  
12    6.448847  4.858469     0.030586  
...        ...       ...          ...  
5304  5.639188  1.516143     0.000000  
5307  5.592127  1.466300     0.000000  
5310  5.555818  1.553310     0.000000  
5313  5.372444  1.255133     0.000000  
5316  5.719637  2.556201     0.000000  

[1773 rows x 9 columns]
      geoid  scenario  y_temp_base_t  lnyield_obs        har        tmp  \
1      1001       3.0       7.622792     7.509678    779.625  26.784940   
4      1003       3.0       7.351790     7.927428   6358.433  27.808318   
7      1005       3.0       7.574791     8.161582    526.500  27.067738   
10     1009       3.0       8.067909     7.840701   1107.736  25.706190   
13     1011       3.0       7.957275     7.984614    870.750  26.923034   
...     ...       ...            ...          ...        ...        ...   
5305  55133       3.0       8.016329     7.974899   7837.872  20.450390   
5308  55135       3.0       7.978732     7.957613   9909.051  19.245958   
5311  55137       3.0       8.006494     7.941248   5335.875  19.677776   
5314  55139       3.0       7.962289     8.028848  14541.420  20.012748   
5317  55141       3.0       8.128488     7.921128   6700.507  19.304302   

           pre     lnfer  irrigation1  
1     6.208599  2.457656     0.377088  
4     8.926058  1.292553     0.738441  
7     6.742623  2.114730     0.028216  
10    6.658286  4.361742     0.056342  
13    6.491163  4.858469     0.030586  
...        ...       ...          ...  
5305  5.862562  1.516143     0.000000  
5308  5.878897  1.466300     0.000000  
5311  5.922441  1.553310     0.000000  
5314  5.680057  1.255133     0.000000  
5317  6.116161  2.556201     0.000000  

[1773 rows x 9 columns]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3619970064.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.
  results_base_test = results_base_t[(results_base['scenario'] == 1.5)]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3619970064.py:4: UserWarning: Boolean Series key will be reindexed to match DataFrame index.
  results_base_test = results_base_t[(results_base['scenario'] == 3)]
In [6]:
# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

# Create interaction terms
data['tmp_tmp_interaction'] = data['tmp'] ** 2
data['pre_pre_interaction'] = data['pre'] ** 2
data['irrigation12'] = data['irrigation1'] ** 2
data['lnfer_irrigation1_tmp_interaction'] = data['lnfer'] * data['irrigation1'] * data['tmp']
data['lnfer_irrigation12_tmp_tmp_interaction'] = data['lnfer'] * data['irrigation12'] * data['tmp'] ** 2
data['lnfer_irrigation1_pre_interaction'] = data['lnfer'] * data['irrigation1'] * data['pre']
data['lnfer_irrigation12_pre_pre_interaction'] = data['lnfer'] * data['irrigation12'] * data['pre'] ** 2

data['lnfer_tmp_interaction'] = data['lnfer'] * data['tmp']
data['lnfer_tmp_tmp_interaction'] = data['lnfer'] * data['tmp'] ** 2
data['lnfer_pre_interaction'] = data['lnfer'] * data['pre']
data['lnfer_pre_pre_interaction'] = data['lnfer'] * data['pre'] ** 2

# Define predictor variables and response variable
predictor_variables1 = ['lnfer', 'tmp', 'irrigation1', 'irrigation12', 'tmp_tmp_interaction',
                        'pre', 'pre_pre_interaction', 'lnfer_irrigation1_pre_interaction', 'lnfer_irrigation12_pre_pre_interaction',
                        'lnfer_irrigation1_tmp_interaction', 'lnfer_irrigation12_tmp_tmp_interaction']

predictor_variables2 = ['lnfer', 'tmp', 'tmp_tmp_interaction', 'irrigation1', 'irrigation12', 'pre', 'pre_pre_interaction',
                        'lnfer_tmp_interaction', 'lnfer_tmp_tmp_interaction',
                        'lnfer_pre_interaction', 'lnfer_pre_pre_interaction']

response_variable = 'lnyield'

# Function to perform regression analysis
def perform_regression(group_data, predictor_variables):
    X = sm.add_constant(group_data[predictor_variables])
    y = group_data[response_variable]
    return sm.OLS(y, X).fit()

# Create a list to store data rows
data_rows = []

sample_data = data[data['sample'] == 0].copy()
project_data = data1

# Iterate through 'results' and extract values
for group in sample_data['group'].unique():
    group_data = sample_data[sample_data['group'] == group].copy()
    predictor_variables = predictor_variables1 if group == 1 else predictor_variables2
    reg = perform_regression(group_data, predictor_variables)

    for group_proj in project_data['group'].unique():
        if group == group_proj:
            # Calculate y_temp_base based on regression parameters
            tmp_values = project_data[project_data['group'] == group_proj]['tmp'].values
            pre_values = project_data[project_data['group'] == group_proj]['pre'].values
            lnfer_values = project_data[project_data['group'] == group_proj]['lnfer'].values
            irrigation1_values = project_data[project_data['group'] == group_proj]['irrigation1'].values
            
            if group_proj == 1:
                print(reg.params['tmp_tmp_interaction'])
                print(reg.params['const'])
                y_temp_base = (
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 +
                    reg.params['tmp'] * tmp_values +
                    reg.params['pre_pre_interaction'] * pre_values**2 +
                    reg.params['pre'] * pre_values +
                    reg.params['lnfer'] * lnfer_values +
                    reg.params['irrigation1'] * irrigation1_values +
                    reg.params['irrigation12'] * irrigation1_values**2 +
                    reg.params['lnfer_irrigation1_tmp_interaction'] * irrigation1_values * tmp_values * lnfer_values +
                    reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * irrigation1_values**2 * lnfer_values * tmp_values**2 +
                    reg.params['lnfer_irrigation1_pre_interaction'] * irrigation1_values * pre_values * lnfer_values +
                    reg.params['lnfer_irrigation12_pre_pre_interaction'] * irrigation1_values**2 * lnfer_values * pre_values**2 +
                    reg.params['const']
                )
                print(len(y_temp_base))
            else:
                print(reg.params['tmp_tmp_interaction'])
                y_temp_base = (
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 +
                    reg.params['tmp'] * tmp_values +
                    reg.params['pre_pre_interaction'] * pre_values**2 +
                    reg.params['pre'] * pre_values +
                    reg.params['lnfer'] * lnfer_values +
                    reg.params['lnfer_tmp_interaction'] * tmp_values * lnfer_values +
                    reg.params['lnfer_tmp_tmp_interaction'] * lnfer_values * tmp_values**2 +
                    reg.params['lnfer_pre_interaction'] * pre_values * lnfer_values +
                    reg.params['lnfer_pre_pre_interaction'] * lnfer_values * pre_values**2 +
                    reg.params['const']
                )
                print(len(y_temp_base))
            
            # Extract 'geoid', 'scenario', and 'model' from the original data
            geoid_values = project_data[project_data['group'] == group_proj]['geoid'].values
            scenario_values = project_data[project_data['group'] == group_proj]['scenario'].values
            print(scenario_values)
            for tmp, pre, lnfer, irrigation1,y_temp_base_val, geoid, scenario in zip(
                tmp_values, pre_values, lnfer_values, irrigation1_values,
                 y_temp_base, geoid_values, scenario_values
            ):
                data_rows.append([tmp, pre, lnfer, irrigation1, y_temp_base_val, geoid, scenario])


# Create a DataFrame from the data
results_base = pd.DataFrame(data_rows, columns=['tmp','pre','lnfer','irrigation1',
                                               'y_temp_base', 'geoid', 'scenario'])
results_base = results_base.sort_values(by=['geoid', 'scenario'])
print(results_base)

results_base = results_base[results_base['scenario'] == 2015]
# Rename the 'y_temp_base' column to 'y_temp_base2015'
results_base.rename(columns={'y_temp_base': 'y_temp_base2015'}, inplace=True)

# Keep only the desired columns in results_2015
results_base2015 = results_base[['geoid', 'y_temp_base2015']]
print(results_base2015)
-0.013398123665888008
0.9408977132139006
3816
[1.500e+00 3.000e+00 2.015e+03 ... 1.500e+00 3.000e+00 2.015e+03]
-0.00627099550076526
1503
[1.500e+00 3.000e+00 2.015e+03 ... 1.500e+00 3.000e+00 2.015e+03]
            tmp       pre     lnfer  irrigation1  y_temp_base  geoid  scenario
0     25.099590  6.254395  2.457656     0.377088     7.846458   1001       1.5
1     26.784940  6.208599  2.457656     0.377088     7.622792   1001       3.0
2     25.010676  6.605178  2.457656     0.377088     7.871762   1001    2015.0
3     26.261318  9.274925  1.292553     0.738441     7.590898   1003       1.5
4     27.808318  8.926058  1.292553     0.738441     7.351790   1003       3.0
...         ...       ...       ...          ...          ...    ...       ...
5314  20.012748  5.680057  1.255133     0.000000     7.962289  55139       3.0
5315  17.287318  5.693542  1.255133     0.000000     7.849514  55139    2015.0
5316  17.398562  5.719637  2.556201     0.000000     7.946194  55141       1.5
5317  19.304302  6.116161  2.556201     0.000000     8.128488  55141       3.0
5318  16.504032  6.108389  2.556201     0.000000     7.871178  55141    2015.0

[5319 rows x 7 columns]
      geoid  y_temp_base2015
2      1001         7.871762
5      1003         7.599898
8      1005         7.821125
11     1009         8.285447
14     1011         8.201724
...     ...              ...
5306  55133         7.901357
5309  55135         7.816405
5312  55137         7.854962
5315  55139         7.849514
5318  55141         7.871178

[1773 rows x 2 columns]
In [7]:
data = results_base_t.merge(results_base2015, left_on=['geoid'], right_on=['geoid'], how='left')
data.rename(columns={'scenario_x': 'scenario'}, inplace=True)

data = data.sort_values(by=['geoid', 'scenario'])
print(data)

data['yield_warming']=np.exp(data['y_temp_base_t']-data['y_temp_base2015']+data['lnyield_obs'])
data['gap_yield_warming']=(data['yield_warming']-np.exp(data['lnyield_obs']))/1000 #tonne/ha
data['gap_production_warming']=data['gap_yield_warming']*data['har']/10000  #10000 tonne
print(data)

data = data[['geoid', 'scenario', 'tmp', 'pre', 'lnfer','irrigation1', 'y_temp_base_t','y_temp_base2015',
             'lnyield_obs','har','gap_yield_warming','gap_production_warming']]
data = data.drop_duplicates(subset=['geoid','scenario'])

data['group'] = np.where(data['irrigation1'] > 0, 1, 2)
yield_loss = data[data['gap_yield_warming'] < 0]
yield_loss['id'] = range(1, len(yield_loss) + 1)
print(yield_loss)
output_csv_file = "soybean_yield_loss.csv"
yield_loss.to_csv(output_csv_file, index=False)
print(f"Data saved to '{output_csv_file}'")

yield_gain = data[data['gap_yield_warming'] >= 0]
output_csv_file = "soybean_yield_gain.csv"
# Save the 'output_df' DataFrame to a CSV file
yield_gain.to_csv(output_csv_file, index=False)
print(f"Data saved to '{output_csv_file}'")
print(yield_gain)
      geoid  scenario  y_temp_base_t  lnyield_obs        har        tmp  \
0      1001       1.5       7.846458     7.509678    779.625  25.099590   
1      1001       3.0       7.622792     7.509678    779.625  26.784940   
2      1003       1.5       7.590898     7.927428   6358.433  26.261318   
3      1003       3.0       7.351790     7.927428   6358.433  27.808318   
4      1005       1.5       7.807509     8.161582    526.500  25.408514   
...     ...       ...            ...          ...        ...        ...   
3541  55137       3.0       8.006494     7.941248   5335.875  19.677776   
3542  55139       1.5       7.878360     8.028848  14541.420  18.099080   
3543  55139       3.0       7.962289     8.028848  14541.420  20.012748   
3544  55141       1.5       7.946194     7.921128   6700.507  17.398562   
3545  55141       3.0       8.128488     7.921128   6700.507  19.304302   

           pre     lnfer  irrigation1  y_temp_base2015  
0     6.254395  2.457656     0.377088         7.871762  
1     6.208599  2.457656     0.377088         7.871762  
2     9.274925  1.292553     0.738441         7.599898  
3     8.926058  1.292553     0.738441         7.599898  
4     6.727813  2.114730     0.028216         7.821125  
...        ...       ...          ...              ...  
3541  5.922441  1.553310     0.000000         7.854962  
3542  5.372444  1.255133     0.000000         7.849514  
3543  5.680057  1.255133     0.000000         7.849514  
3544  5.719637  2.556201     0.000000         7.871178  
3545  6.116161  2.556201     0.000000         7.871178  

[3546 rows x 10 columns]
      geoid  scenario  y_temp_base_t  lnyield_obs        har        tmp  \
0      1001       1.5       7.846458     7.509678    779.625  25.099590   
1      1001       3.0       7.622792     7.509678    779.625  26.784940   
2      1003       1.5       7.590898     7.927428   6358.433  26.261318   
3      1003       3.0       7.351790     7.927428   6358.433  27.808318   
4      1005       1.5       7.807509     8.161582    526.500  25.408514   
...     ...       ...            ...          ...        ...        ...   
3541  55137       3.0       8.006494     7.941248   5335.875  19.677776   
3542  55139       1.5       7.878360     8.028848  14541.420  18.099080   
3543  55139       3.0       7.962289     8.028848  14541.420  20.012748   
3544  55141       1.5       7.946194     7.921128   6700.507  17.398562   
3545  55141       3.0       8.128488     7.921128   6700.507  19.304302   

           pre     lnfer  irrigation1  y_temp_base2015  yield_warming  \
0     6.254395  2.457656     0.377088         7.871762    1780.009827   
1     6.208599  2.457656     0.377088         7.871762    1423.263948   
2     9.274925  1.292553     0.738441         7.599898    2747.448365   
3     8.926058  1.292553     0.738441         7.599898    2163.149263   
4     6.727813  2.114730     0.028216         7.821125    3456.341787   
...        ...       ...          ...              ...            ...   
3541  5.922441  1.553310     0.000000         7.854962    3270.766621   
3542  5.372444  1.255133     0.000000         7.849514    3157.999025   
3543  5.680057  1.255133     0.000000         7.849514    3434.487053   
3544  5.719637  2.556201     0.000000         7.871178    2969.485302   
3545  6.116161  2.556201     0.000000         7.871178    3563.285992   

      gap_yield_warming  gap_production_warming  
0             -0.045616               -0.003556  
1             -0.402362               -0.031369  
2             -0.024839               -0.015794  
3             -0.609138               -0.387316  
4             -0.047383               -0.002495  
...                 ...                     ...  
3541           0.459900                0.245397  
3542           0.089794                0.130573  
3543           0.366282                0.532626  
3544           0.214609                0.143799  
3545           0.808409                0.541675  

[3546 rows x 13 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0      1001       1.5  25.099590  6.254395  2.457656     0.377088   
1      1001       3.0  26.784940  6.208599  2.457656     0.377088   
2      1003       1.5  26.261318  9.274925  1.292553     0.738441   
3      1003       3.0  27.808318  8.926058  1.292553     0.738441   
4      1005       1.5  25.408514  6.727813  2.114730     0.028216   
...     ...       ...        ...       ...       ...          ...   
2538  51800       1.5  23.349492  7.419639  1.187985     0.008524   
2539  51800       3.0  25.061998  7.586472  1.187985     0.008524   
2540  51810       1.5  23.207888  7.236578  2.482080     0.010662   
2541  51810       3.0  24.859328  7.207139  2.482080     0.010662   
2543  54037       3.0  23.294406  5.721528  0.935788     0.000171   

      y_temp_base_t  y_temp_base2015  lnyield_obs       har  \
0          7.846458         7.871762     7.509678   779.625   
1          7.622792         7.871762     7.509678   779.625   
2          7.590898         7.599898     7.927428  6358.433   
3          7.351790         7.599898     7.927428  6358.433   
4          7.807509         7.821125     8.161582   526.500   
...             ...              ...          ...       ...   
2538       7.896463         7.928655     7.798817  7968.552   
2539       7.753334         7.928655     7.798817  7968.552   
2540       8.075677         8.111622     7.872881  4972.955   
2541       7.939772         8.111622     7.872881  4972.955   
2543       7.775021         7.820683     7.900531  3976.619   

      gap_yield_warming  gap_production_warming  group    id  
0             -0.045616               -0.003556      1     1  
1             -0.402362               -0.031369      1     2  
2             -0.024839               -0.015794      1     3  
3             -0.609138               -0.387316      1     4  
4             -0.047383               -0.002495      1     5  
...                 ...                     ...    ...   ...  
2538          -0.077225               -0.061537      1  1994  
2539          -0.392016               -0.312380      1  1995  
2540          -0.092685               -0.046092      1  1996  
2541          -0.414491               -0.206125      1  1997  
2543          -0.120458               -0.047901      1  1998  

[1998 rows x 14 columns]
Data saved to 'soybean_yield_loss.csv'
Data saved to 'soybean_yield_gain.csv'
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
50     1069       1.5  25.677906  7.390798  2.593498     0.121473   
2552  12059       1.5  25.725970  8.270085  4.063033     0.000000   
182   12079       1.5  26.184586  8.465425  2.237931     0.250696   
186   13001       1.5  25.463322  7.289039  2.390463     0.156666   
188   13005       1.5  25.477230  7.421095  2.430111     0.463811   
...     ...       ...        ...       ...       ...          ...   
3541  55137       3.0  19.677776  5.922441  1.553310     0.000000   
3542  55139       1.5  18.099080  5.372444  1.255133     0.000000   
3543  55139       3.0  20.012748  5.680057  1.255133     0.000000   
3544  55141       1.5  17.398562  5.719637  2.556201     0.000000   
3545  55141       3.0  19.304302  6.116161  2.556201     0.000000   

      y_temp_base_t  y_temp_base2015  lnyield_obs        har  \
50         7.856622         7.855991     7.600072   1158.260   
2552       8.488000         8.480298     7.819335   1620.000   
182        7.744525         7.743934     7.504254    810.000   
186        7.850894         7.826060     7.739274   1883.279   
188        7.833117         7.813368     7.649385    484.704   
...             ...              ...          ...        ...   
3541       8.006494         7.854962     7.941248   5335.875   
3542       7.878360         7.849514     8.028848  14541.420   
3543       7.962289         7.849514     8.028848  14541.420   
3544       7.946194         7.871178     7.921128   6700.507   
3545       8.128488         7.871178     7.921128   6700.507   

      gap_yield_warming  gap_production_warming  group  
50             0.001261                0.000146      1  
2552           0.019239                0.003117      2  
182            0.001073                0.000087      1  
186            0.057755                0.010877      1  
188            0.041872                0.002030      1  
...                 ...                     ...    ...  
3541           0.459900                0.245397      2  
3542           0.089794                0.130573      2  
3543           0.366282                0.532626      2  
3544           0.214609                0.143799      2  
3545           0.808409                0.541675      2  

[1548 rows x 13 columns]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3169964443.py:18: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  yield_loss['id'] = range(1, len(yield_loss) + 1)

N fertilizer only¶

In [8]:
import pandas as pd
import statsmodels.api as sm
import cmath 

# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

# Create interaction terms
data['tmp_tmp_interaction'] = data['tmp'] ** 2
data['pre_pre_interaction'] = data['pre'] ** 2
data['irrigation12'] = data['irrigation1'] ** 2
data['lnfer_irrigation1_tmp_interaction'] = data['lnfer'] * data['irrigation1'] * data['tmp']
data['lnfer_irrigation12_tmp_tmp_interaction'] = data['lnfer'] * data['irrigation12'] * data['tmp'] ** 2
data['lnfer_irrigation1_pre_interaction'] = data['lnfer'] * data['irrigation1'] * data['pre']
data['lnfer_irrigation12_pre_pre_interaction'] = data['lnfer'] * data['irrigation12'] * data['pre'] ** 2

data['lnfer_tmp_interaction'] = data['lnfer'] * data['tmp']
data['lnfer_tmp_tmp_interaction'] = data['lnfer'] * data['tmp'] ** 2
data['lnfer_pre_interaction'] = data['lnfer'] * data['pre']
data['lnfer_pre_pre_interaction'] = data['lnfer'] * data['pre'] ** 2

# Define predictor variables and response variable
predictor_variables1 = ['lnfer', 'tmp', 'irrigation1', 'irrigation12', 'tmp_tmp_interaction',
                        'pre', 'pre_pre_interaction', 'lnfer_irrigation1_pre_interaction', 'lnfer_irrigation12_pre_pre_interaction',
                        'lnfer_irrigation1_tmp_interaction', 'lnfer_irrigation12_tmp_tmp_interaction']

predictor_variables2 = ['lnfer', 'tmp', 'tmp_tmp_interaction', 'irrigation1', 'irrigation12', 'pre', 'pre_pre_interaction',
                        'lnfer_tmp_interaction', 'lnfer_tmp_tmp_interaction',
                        'lnfer_pre_interaction', 'lnfer_pre_pre_interaction']

response_variable = 'lnyield'

# Function to perform regression analysis
def perform_regression(group_data, predictor_variables):
    X = sm.add_constant(group_data[predictor_variables])
    y = group_data[response_variable]
    return sm.OLS(y, X).fit()

# Create a list to store data rows
data_rows = []

sample_data = data[data['sample'] == 0].copy()
print(sample_data)
project_data =  yield_loss.copy()
print(project_data)



# Iterate through 'results' and extract values
for group in sample_data['group'].unique():
    group_data = sample_data[sample_data['group'] == group].copy()
    predictor_variables = predictor_variables1 if group == 1 else predictor_variables2
    reg = perform_regression(group_data, predictor_variables)

    for group_proj in project_data['group'].unique():
        if group == group_proj:
            # Calculate y_temp_base based on regression parameters
            tmp_values = project_data[project_data['group'] == group_proj]['tmp'].values
            pre_values = project_data[project_data['group'] == group_proj]['pre'].values
            lnfer_values = project_data[project_data['group'] == group_proj]['lnfer'].values
            irrigation1_values = project_data[project_data['group'] == group_proj]['irrigation1'].values
            y_temp_base2015_values = project_data[project_data['group'] == group_proj]['y_temp_base2015'].values
            
            if group_proj == 1:
                print(reg.params['tmp_tmp_interaction'])
                print(reg.params['const'])
                lnfer_need = (
                    (y_temp_base2015_values-
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 -
                    reg.params['tmp'] * tmp_values -
                    reg.params['pre_pre_interaction'] * pre_values**2 -
                    reg.params['pre'] * pre_values -
                    reg.params['irrigation1'] * irrigation1_values -
                    reg.params['irrigation12'] * irrigation1_values**2 -
                    reg.params['const'])/
                    (reg.params['lnfer']+
                    reg.params['lnfer_irrigation1_tmp_interaction'] * irrigation1_values * tmp_values +
                    reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * irrigation1_values**2 * tmp_values**2 +
                    reg.params['lnfer_irrigation1_pre_interaction'] * irrigation1_values * pre_values  +
                    reg.params['lnfer_irrigation12_pre_pre_interaction'] * irrigation1_values**2 * pre_values**2
                    )
                )   
                print(len(lnfer_need))
            else:
                print(reg.params['tmp_tmp_interaction'])
                print(reg.params['const'])
                lnfer_need = (
                    (y_temp_base2015_values-
                    reg.params['tmp_tmp_interaction'] * tmp_values**2 -
                    reg.params['tmp'] * tmp_values -
                    reg.params['pre_pre_interaction'] * pre_values**2 -
                    reg.params['pre'] * pre_values -
                    reg.params['const'])/
                    (reg.params['lnfer']+
                    reg.params['lnfer_tmp_interaction'] * tmp_values +
                    reg.params['lnfer_tmp_tmp_interaction'] * tmp_values**2 +
                    reg.params['lnfer_pre_interaction']  * pre_values  +
                    reg.params['lnfer_pre_pre_interaction'] * pre_values**2
                    )
                )
                print(len(lnfer_need))
            
            # Extract 'geoid', 'scenario', and 'model' from the original data
            geoid_values = project_data[project_data['group'] == group_proj]['geoid'].values
            scenario_values = project_data[project_data['group'] == group_proj]['scenario'].values
            lnyield_obs_values= project_data[project_data['group'] == group_proj]['lnyield_obs'].values
            har_values= project_data[project_data['group'] == group_proj]['har'].values
            y_temp_base_t_values= project_data[project_data['group'] == group_proj]['y_temp_base_t'].values
            
            for tmp, pre, lnfer, irrigation1,y_temp_base2015, y_temp_base_t, geoid, scenario, lnyield_obs,har,lnfer_need in zip(
                tmp_values, pre_values, lnfer_values, irrigation1_values,
                 y_temp_base2015_values,y_temp_base_t_values, geoid_values, scenario_values, lnyield_obs_values,
                har_values,lnfer_need
            ):
                data_rows.append([tmp, pre, lnfer, irrigation1, y_temp_base2015, y_temp_base_t, geoid, scenario, 
                                  lnyield_obs,har,lnfer_need])


# Create a DataFrame from the data
results_lnfer = pd.DataFrame(data_rows, columns=['tmp','pre','lnfer','irrigation1',
                                               'y_temp_base2015', 'y_temp_base_t', 'geoid', 'scenario',
                                                'lnyield_obs','har','lnfer_need'])
print(results_lnfer)
       geoid  year       tmp       pre      har  irrigation1  lnyield_obs  \
0       1001  2009  24.14066  8.808839   1900.0     0.718851     7.609614   
1       1001  2010  25.67548  5.438990   1900.0     0.830087     7.035731   
2       1001  2011  24.54482  5.270162   1500.0     0.595086     7.466514   
3       1001  2013  24.03659  7.514143   2400.0     0.001241     7.926855   
4       1003  2008  24.72723  8.675528  19000.0     0.001980     7.934111   
...      ...   ...       ...       ...      ...          ...          ...   
17211  55141  2016  17.48690  7.304833  18200.0     0.000000     8.134343   
17212  55141  2017  16.59024  6.467205  19597.5     0.000000     7.978877   
17213  55141  2018  17.26666  8.373576  23000.0     0.000000     7.838077   
17214  55141  2019  16.23859  8.735889  10100.0     0.000000     7.912185   
17215  55141  2020  16.20263  6.832954  18500.0     0.000000     8.173033   

          lnfer   lnyield  group  ...  pre_pre_interaction  irrigation12  \
0      2.022537  7.900063      1  ...            77.595645      0.516747   
1      1.910005  7.661077      1  ...            29.582612      0.689044   
2      2.025641  7.785866      1  ...            27.774608      0.354128   
3      2.906756  8.084917      1  ...            56.462345      0.000002   
4      1.240602  7.807824      1  ...            75.264786      0.000004   
...         ...       ...    ...  ...                  ...           ...   
17211  2.860158  8.062482      2  ...            53.360585      0.000000   
17212  2.633171  7.905756      2  ...            41.824741      0.000000   
17213  2.639034  8.039181      2  ...            70.116775      0.000000   
17214  2.671287  7.918515      2  ...            76.315757      0.000000   
17215  2.625827  7.873821      2  ...            46.689260      0.000000   

       lnfer_irrigation1_tmp_interaction  \
0                              35.098172   
1                              40.707692   
2                              29.587092   
3                               0.086679   
4                               0.060734   
...                                  ...   
17211                           0.000000   
17212                           0.000000   
17213                           0.000000   
17214                           0.000000   
17215                           0.000000   

      lnfer_irrigation12_tmp_tmp_interaction  \
0                                 609.077444   
1                                 867.597822   
2                                 432.157531   
3                                   0.002585   
4                                   0.002973   
...                                      ...   
17211                               0.000000   
17212                               0.000000   
17213                               0.000000   
17214                               0.000000   
17215                               0.000000   

       lnfer_irrigation1_pre_interaction  \
0                              12.807195   
1                               8.623353   
2                               6.352818   
3                               0.027097   
4                               0.021308   
...                                  ...   
17211                           0.000000   
17212                           0.000000   
17213                           0.000000   
17214                           0.000000   
17215                           0.000000   

       lnfer_irrigation12_pre_pre_interaction  lnfer_tmp_interaction  \
0                                   81.098269              48.825378   
1                                   38.932997              49.040295   
2                                   19.923715              49.718994   
3                                    0.000253              69.868502   
4                                    0.000366              30.676651   
...                                       ...                    ...   
17211                                0.000000              50.015297   
17212                                0.000000              43.684939   
17213                                0.000000              45.567303   
17214                                0.000000              43.377934   
17215                                0.000000              42.545303   

       lnfer_tmp_tmp_interaction  lnfer_pre_interaction  \
0                    1178.676851              17.816203   
1                    1259.133118              10.388498   
2                    1220.343752              10.675456   
3                    1679.400541              21.841780   
4                     758.548605              10.762877   
...                          ...                    ...   
17211                 874.612496              20.892977   
17212                 724.743620              17.029257   
17213                 786.795125              22.098152   
17214                 704.396491              23.336067   
17215                 689.345808              17.942155   

       lnfer_pre_pre_interaction  
0                     156.940062  
1                      56.502937  
2                      56.261384  
3                     164.122260  
4                      93.373644  
...                          ...  
17211                 152.619705  
17212                 110.131694  
17213                 185.040553  
17214                 203.861289  
17215                 122.597920  

[17216 rows x 26 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0      1001       1.5  25.099590  6.254395  2.457656     0.377088   
1      1001       3.0  26.784940  6.208599  2.457656     0.377088   
2      1003       1.5  26.261318  9.274925  1.292553     0.738441   
3      1003       3.0  27.808318  8.926058  1.292553     0.738441   
4      1005       1.5  25.408514  6.727813  2.114730     0.028216   
...     ...       ...        ...       ...       ...          ...   
2538  51800       1.5  23.349492  7.419639  1.187985     0.008524   
2539  51800       3.0  25.061998  7.586472  1.187985     0.008524   
2540  51810       1.5  23.207888  7.236578  2.482080     0.010662   
2541  51810       3.0  24.859328  7.207139  2.482080     0.010662   
2543  54037       3.0  23.294406  5.721528  0.935788     0.000171   

      y_temp_base_t  y_temp_base2015  lnyield_obs       har  \
0          7.846458         7.871762     7.509678   779.625   
1          7.622792         7.871762     7.509678   779.625   
2          7.590898         7.599898     7.927428  6358.433   
3          7.351790         7.599898     7.927428  6358.433   
4          7.807509         7.821125     8.161582   526.500   
...             ...              ...          ...       ...   
2538       7.896463         7.928655     7.798817  7968.552   
2539       7.753334         7.928655     7.798817  7968.552   
2540       8.075677         8.111622     7.872881  4972.955   
2541       7.939772         8.111622     7.872881  4972.955   
2543       7.775021         7.820683     7.900531  3976.619   

      gap_yield_warming  gap_production_warming  group    id  
0             -0.045616               -0.003556      1     1  
1             -0.402362               -0.031369      1     2  
2             -0.024839               -0.015794      1     3  
3             -0.609138               -0.387316      1     4  
4             -0.047383               -0.002495      1     5  
...                 ...                     ...    ...   ...  
2538          -0.077225               -0.061537      1  1994  
2539          -0.392016               -0.312380      1  1995  
2540          -0.092685               -0.046092      1  1996  
2541          -0.414491               -0.206125      1  1997  
2543          -0.120458               -0.047901      1  1998  

[1998 rows x 14 columns]
-0.013398123665888008
0.9408977132139006
1454
-0.00627099550076526
4.94855569752093
544
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
0     25.099590  6.254395  2.457656     0.377088         7.871762   
1     26.784940  6.208599  2.457656     0.377088         7.871762   
2     26.261318  9.274925  1.292553     0.738441         7.599898   
3     27.808318  8.926058  1.292553     0.738441         7.599898   
4     25.408514  6.727813  2.114730     0.028216         7.821125   
...         ...       ...       ...          ...              ...   
1993  22.617856  6.753251  3.697080     0.000000         8.499517   
1994  24.369986  6.937165  3.697080     0.000000         8.499517   
1995  20.956338  7.018248  3.798184     0.000000         8.457635   
1996  22.735782  6.657891  1.348576     0.000000         8.031712   
1997  24.547064  6.747815  1.348576     0.000000         8.031712   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  lnfer_need  
0          7.846458   1001       1.5     7.509678   779.625    2.667937  
1          7.622792   1001       3.0     7.509678   779.625    4.505245  
2          7.590898   1003       1.5     7.927428  6358.433    1.404700  
3          7.351790   1003       3.0     7.927428  6358.433    4.202620  
4          7.807509   1005       1.5     8.161582   526.500    2.215152  
...             ...    ...       ...          ...       ...         ...  
1993       8.465001  51103       1.5     8.077533  2916.000    3.877447  
1994       8.441412  51103       3.0     8.077533  2916.000    3.975355  
1995       8.455265  51141       1.5     7.902284   243.000    3.812177  
1996       8.009433  51159       1.5     7.841456  5668.211    1.464794  
1997       7.935400  51159       3.0     7.841456  5668.211    1.812194  

[1998 rows x 11 columns]
In [9]:
results_lnfer['gap_fer']=(np.exp(results_lnfer['lnfer_need'])-np.exp(results_lnfer['lnfer'])) #kg/ha
print(np.min(results_lnfer['lnfer_need']),np.max(results_lnfer['lnfer_need']),
      np.mean(results_lnfer['lnfer_need']))
print(np.min(results_lnfer['gap_fer']),np.max(results_lnfer['gap_fer']),
      np.mean(results_lnfer['gap_fer']),np.sum(np.isnan(results_lnfer['gap_fer'])))
-0.4063629468457881 8.448517994776964 2.8843655717223564
0.0016115767952669113 4302.983035950181 51.56176822502462 0

Irrigation only¶

In [10]:
# Function to perform regression analysis
def perform_regression(group_data, predictor_variables, response_variable):
    X = sm.add_constant(group_data[predictor_variables])
    y = group_data[response_variable]
    return sm.OLS(y, X).fit()

# Function to solve quadratic equation
def quadratic_solver(a, b, c):
    # Calculate the discriminant
    discriminant = b**2 - 4*a*c

    # Print values for debugging
    print("a:", a)
    print("b:", b)
    print("c:", c)
    print("discriminant:", discriminant)

    # Check if the discriminant is negative
    if discriminant < 0:
        return np.array([9999])

    # Calculate the solutions using the quadratic formula
    solution1 = (-b + np.sqrt(discriminant)) / (2*a)
    solution2 = (-b - np.sqrt(discriminant)) / (2*a)

    # Check conditions and return the appropriate solution
    if solution1.real > 0 and solution2.real > 0:
        # Return the smaller solution as a length-1 array
        return np.array([min(solution1.real, solution2.real)])
    elif solution1.real > 0 and solution2.real < 0:
        # Return the larger solution if one is greater than 0
        return np.array([max(solution1.real, solution2.real)])
    elif solution2.real > 0 and solution1.real < 0:
        # Return the larger solution if one is greater than 0
        return np.array([max(solution1.real, solution2.real)])
    else:
        # Return 9999 if all solutions are less than 0
        return np.array([9999])  # cannot offset the yield loss

# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

# Create interaction terms
data['tmp_tmp_interaction'] = data['tmp'] ** 2
data['pre_pre_interaction'] = data['pre'] ** 2
data['irrigation12'] = data['irrigation1'] ** 2
data['lnfer_irrigation1_tmp_interaction'] = data['lnfer'] * data['irrigation1'] * data['tmp']
data['lnfer_irrigation12_tmp_tmp_interaction'] = data['lnfer'] * data['irrigation12'] * data['tmp'] ** 2
data['lnfer_irrigation1_pre_interaction'] = data['lnfer'] * data['irrigation1'] * data['pre']
data['lnfer_irrigation12_pre_pre_interaction'] = data['lnfer'] * data['irrigation12'] * data['pre'] ** 2

data['lnfer_tmp_interaction'] = data['lnfer'] * data['tmp']
data['lnfer_tmp_tmp_interaction'] = data['lnfer'] * data['tmp'] ** 2
data['lnfer_pre_interaction'] = data['lnfer'] * data['pre']
data['lnfer_pre_pre_interaction'] = data['lnfer'] * data['pre'] ** 2

# Define predictor variables and response variable
predictor_variables1 = ['lnfer', 'tmp', 'irrigation1', 'irrigation12', 'tmp_tmp_interaction',
                        'pre', 'pre_pre_interaction', 'lnfer_irrigation1_pre_interaction', 'lnfer_irrigation12_pre_pre_interaction',
                        'lnfer_irrigation1_tmp_interaction', 'lnfer_irrigation12_tmp_tmp_interaction']

response_variable = 'lnyield'

# Perform regression on group1_data
group1_data = data[(data['group'] == 1) & (data['sample'] == 0)].copy()
reg = perform_regression(group1_data, predictor_variables1, response_variable)

# Create a list to store data rows
data_rows = []

data= yield_loss.copy()

for id_ in data['id'].unique():
    subset_data = data[data['id'] == id_]
    print(reg.params['tmp_tmp_interaction'])

    tmp_values = subset_data['tmp']
    pre_values = subset_data['pre']
    lnfer_values = subset_data['lnfer']
    irrigation1_values = subset_data['irrigation1']
    y_values=subset_data['y_temp_base2015']

    c_result = (
        -y_values +
        reg.params['tmp_tmp_interaction'] * tmp_values**2 +
        reg.params['tmp'] * tmp_values +
        reg.params['pre_pre_interaction'] * pre_values**2 +
        reg.params['pre'] * pre_values +
        reg.params['lnfer'] * lnfer_values +
        reg.params['const']
    )

    b_result = (
        reg.params['irrigation1'] +
        reg.params['lnfer_irrigation1_tmp_interaction'] * tmp_values * lnfer_values +
        reg.params['lnfer_irrigation1_pre_interaction'] * pre_values * lnfer_values
    )

    a_result = (
        reg.params['irrigation12']  +
        reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * lnfer_values * tmp_values**2 +
        reg.params['lnfer_irrigation12_pre_pre_interaction'] * lnfer_values * pre_values**2
    )

    irri_need = []
    for a, b, c in zip(a_result, b_result, c_result):
        irri_need.append(quadratic_solver(a, b, c))

    # Extract relevant values from the original row
    geoid_values = subset_data['geoid']
    scenario_values = subset_data['scenario']
    lnyield_obs_values = subset_data['lnyield_obs']
    y_temp_base_t_values = subset_data['y_temp_base_t']

    data_rows.extend(zip(
        tmp_values, pre_values, lnfer_values, irrigation1_values,
        subset_data['y_temp_base2015'], y_temp_base_t_values, geoid_values, scenario_values,
         lnyield_obs_values, subset_data['har'], irri_need
    ))

# Create a DataFrame from the data_rows list
results_irri = pd.DataFrame(data_rows, columns=['tmp', 'pre', 'lnfer', 'irrigation1',
                                                 'y_temp_base2015', 'y_temp_base_t', 'geoid', 'scenario', 
                                                 'lnyield_obs', 'har', 'irri_need'])

results_irri.loc[results_irri['irri_need'] == 9999, 'irri_need'] = np.nan
# Print the resulting DataFrame
print(results_irri)
results_irri.loc[results_irri['irri_need'] == 9999, 'irri_need'] = np.nan
# Convert "irri_need" column to string type
results_irri['irri_need'] = results_irri['irri_need'].astype(str)
# Remove square brackets from the "irri_need" column
results_irri['irri_need'] = results_irri['irri_need'].str.strip('[]')
# Extract the first element from each array and convert to float with three digits after the decimal point
results_irri['irri_need'] = results_irri['irri_need'].str.extract(r'(\d+\.\d{3})', expand=False).astype(float)
print('results_irri')
print(results_irri)
print(np.min(results_irri['irri_need']),np.max(results_irri['irri_need']),
      np.mean(results_irri['irri_need']))
print(np.nanpercentile(results_irri['irri_need'], 5),np.nanpercentile(results_irri['irri_need'], 95))

# adjust the irrigation intensity to not exceed the current maximum level
irri_max=np.nanpercentile(group1_data['irrigation1'], 95) 
print(irri_max)
results_irri.loc[results_irri['irri_need'] >irri_max, 'irri_need'] = irri_max
print(np.min(results_irri['irri_need']),np.max(results_irri['irri_need']),
      np.mean(results_irri['irri_need']))
-0.013398123665888008
a: 0.007539267124127302
b: -0.052007415160134046
c: -0.006764521565875703
discriminant: 0.002908769371846768
-0.013398123665888008
a: 0.007934525784724731
b: -0.04395375764594628
c: -0.2335237581010362
discriminant: 0.009343533931192551
-0.013398123665888008
a: 0.007796933202187457
b: -0.04877367411196573
c: 0.02276476238537406
discriminant: 0.0016688899596505116
-0.013398123665888008
a: 0.006974433691485055
b: -0.03940416676675143
c: -0.2228130269666998
discriminant: 0.007768667087295235
-0.013398123665888008
a: 0.006983143748826531
b: -0.048678867603898335
c: -0.0122480149654689
discriminant: 0.0027117507477644547
-0.013398123665888008
a: 0.007542864087127869
b: -0.04360707645012027
c: -0.2451092452446021
discriminant: 0.00929688001004074
-0.013398123665888008
a: 0.02444839175536971
b: -0.1816254507933956
c: -0.023253859216437522
discriminant: 0.03526188221569488
-0.013398123665888008
a: 0.024416137142115497
b: -0.16182879051244314
c: -0.2084982706359616
discriminant: 0.04655144691768641
-0.013398123665888008
a: 0.0261832568386221
b: -0.1769512105226534
c: -0.012570887342643222
discriminant: 0.03262831799335964
-0.013398123665888008
a: 0.027704835431358828
b: -0.167011965230436
c: -0.23936654999469054
discriminant: 0.05441944003163246
-0.013398123665888008
a: 0.012491511910259332
b: -0.09927792763479812
c: 0.06999662930259076
discriminant: 0.006358652001014933
-0.013398123665888008
a: 0.012225025163258733
b: -0.08378268546735301
c: -0.09365335512376471
discriminant: 0.011599196876167926
-0.013398123665888008
a: 0.010157291578837602
b: -0.08441307348573457
c: 0.002936437318463936
discriminant: 0.007006261975121552
-0.013398123665888008
a: 0.009599204716148422
b: -0.06700122926196558
c: -0.1567092622975571
discriminant: 0.010506301881457875
-0.013398123665888008
a: 0.012519163786472436
b: -0.08908170810357166
c: -0.02403700138992737
discriminant: 0.00913924334799461
-0.013398123665888008
a: 0.01298304656331054
b: -0.07888722639657303
c: -0.23398418793873954
discriminant: 0.01837450491689241
-0.013398123665888008
a: 0.013252346557443243
b: -0.09129059019971902
c: -0.010198229164232853
discriminant: 0.00887457372763959
-0.013398123665888008
a: 0.013409315678981381
b: -0.08144525370882533
c: -0.25063897295130777
discriminant: 0.02007691779073397
-0.013398123665888008
a: 0.0073122635334594115
b: -0.059774488693495054
c: -0.05258682959076433
discriminant: 0.005111104523995929
-0.013398123665888008
a: 0.007244322590742581
b: -0.04793087112798197
c: -0.22705885652550906
discriminant: 0.008876918822110912
-0.013398123665888008
a: 0.01023722778904099
b: -0.0700814107821868
c: -0.019395220471831176
discriminant: 0.005705617297176835
-0.013398123665888008
a: 0.00968609255702496
b: -0.05804189718439026
c: -0.27068790645614327
discriminant: 0.013856494292769403
-0.013398123665888008
a: 0.01617705057344911
b: -0.11014341104464687
c: -0.0017845296920872
discriminant: 0.012247044704864901
-0.013398123665888008
a: 0.016231463885176885
b: -0.10007091937267887
c: -0.24339453766037533
discriminant: 0.025816787495628025
-0.013398123665888008
a: 0.02011548843033615
b: -0.1375823049150076
c: -0.018587792810478843
discriminant: 0.020424500750624817
-0.013398123665888008
a: 0.020502718038870382
b: -0.12549426844519435
c: -0.2540524326902992
discriminant: 0.03658387299074771
-0.013398123665888008
a: 0.025075984591963408
b: -0.18628993074415956
c: -0.011493566351765794
discriminant: 0.03585678826763812
-0.013398123665888008
a: 0.024965070550009853
b: -0.16574010496093444
c: -0.19923443410644948
discriminant: 0.047365389206296765
-0.013398123665888008
a: 0.001143709427882618
b: -0.007160159032831376
c: -0.031302345418551925
discriminant: 0.00019447102765558116
-0.013398123665888008
a: 0.0012618770453877645
b: -0.0007359091286875397
c: -0.28619059553599635
discriminant: 0.001445090934696597
-0.013398123665888008
a: 0.014571693327218565
b: -0.1176765682918901
c: -0.013101367086764015
discriminant: 0.014611411138378435
-0.013398123665888008
a: 0.014086144413241646
b: -0.09760559235794375
c: -0.16830937170123172
discriminant: 0.019010172123087154
-0.013398123665888008
a: 0.00807035914252269
b: -0.057739225696069124
c: -0.01482589708403459
discriminant: 0.003812419440294565
-0.013398123665888008
a: 0.008460324583731926
b: -0.0495552341698095
c: -0.2266317139706696
discriminant: 0.010125232678262088
-0.013398123665888008
a: 0.01674727207294953
b: -0.11081369351473164
c: -0.007946849234692688
discriminant: 0.012812026855401313
-0.013398123665888008
a: 0.015599869117267053
b: -0.09478039993567766
c: -0.2590902194914798
discriminant: 0.025150418266491316
-0.013398123665888008
a: 0.014219237703329703
b: -0.11168909922598086
c: -0.01148231843717229
discriminant: 0.01312753414688491
-0.013398123665888008
a: 0.013808744944678951
b: -0.09364290215878174
c: -0.1815957207081632
discriminant: 0.01879942908593589
-0.013398123665888008
a: 0.01502998337638237
b: -0.10959277604654022
c: -0.04575133993630354
discriminant: 0.014761144076346563
-0.013398123665888008
a: 0.013864847376215506
b: -0.08763305094927687
c: -0.2685516893153167
discriminant: 0.022573264358605398
-0.013398123665888008
a: 0.03817405808585386
b: -0.28103958718045124
c: -0.022098614465343114
discriminant: 0.08235762473142605
-0.013398123665888008
a: 0.03721847921697738
b: -0.24486737596051023
c: -0.21117394319870042
discriminant: 0.09139832387421784
-0.013398123665888008
a: 0.014454514251702797
b: -0.09872757511470187
c: 0.0034983567946814675
discriminant: 0.009544865895444043
-0.013398123665888008
a: 0.014484477833476938
b: -0.08876441829931483
c: -0.2391776157211526
discriminant: 0.02173657344872334
-0.013398123665888008
a: 0.0353384751371999
b: -0.2367576775088962
c: -0.02964037650695861
discriminant: 0.0602439806924001
-0.013398123665888008
a: 0.03416495453651339
b: -0.19888474096938075
c: -0.29076008943727316
discriminant: 0.07929036113708568
-0.013398123665888008
a: 0.034480578277953894
b: -0.22970343420229983
c: -0.023094495678541604
discriminant: 0.05594891394846557
-0.013398123665888008
a: 0.03435008095395298
b: -0.2003060775613758
c: -0.27463662681231493
discriminant: 0.07785768616371827
-0.013398123665888008
a: 0.0064880182176906605
b: -0.04537953742620135
c: -0.0029312891233646
discriminant: 0.002135375445950841
-0.013398123665888008
a: 0.006787713456242109
b: -0.039243290294931066
c: -0.24479748837555382
discriminant: 0.008186496656776303
-0.013398123665888008
a: 0.01431011134183744
b: -0.08669894479095946
c: -0.23483743729021833
discriminant: 0.020958906527285007
-0.013398123665888008
a: -0.0006733420416164338
b: -0.004610874873792123
c: -0.028144168640531153
discriminant: -5.454244078628231e-05
-0.013398123665888008
a: -0.0006809961995401228
b: 0.0013203509791995388
c: -0.17030998375938922
discriminant: -0.0004621784800272632
-0.013398123665888008
a: 0.008701862978179098
b: -0.06454711416092282
c: -0.05111554416661679
discriminant: 0.0059455317920750475
-0.013398123665888008
a: 0.007838273475273256
b: -0.0473890903867393
c: -0.28367445884989906
discriminant: 0.011139797833345183
-0.013398123665888008
a: 0.0002214413991506424
b: -0.009472118105803284
c: -0.054704190639882966
discriminant: 0.00013817611146908304
-0.013398123665888008
a: 0.0002977211918921219
b: -0.0033597462163877656
c: -0.2126849587824008
discriminant: 0.00026457117234342465
-0.013398123665888008
a: -0.0012170594636407763
b: 0.0020037316906238722
c: -0.04612134252179034
discriminant: -0.00022051472487984034
-0.013398123665888008
a: -0.0012112423160089468
b: 0.007162433689312422
c: -0.2266131037254614
discriminant: -0.0010466330660238166
-0.013398123665888008
a: 0.004288452888442261
b: -0.03861076437324282
c: -0.042309880782895326
discriminant: 0.002216566847298297
-0.013398123665888008
a: 0.004532204771247991
b: -0.031645937304346505
c: -0.2086296812848104
discriminant: 0.004783675095642492
-0.013398123665888008
a: 0.013146644779836708
b: -0.08656025884033952
c: 0.001468175319188303
discriminant: 0.007415472092923009
-0.013398123665888008
a: 0.013435922261018265
b: -0.07441139880195285
c: -0.24857227601144405
discriminant: 0.018896247378599823
-0.013398123665888008
a: 0.019289181701483922
b: -0.13195375916875313
c: 0.012477463066971728
discriminant: 0.01644907434967581
-0.013398123665888008
a: 0.020707301403873002
b: -0.1247027127490134
c: -0.2027705215334018
discriminant: 0.032346087787813636
-0.013398123665888008
a: -0.0007306053755075223
b: -0.002838896972444993
c: -0.043267741080803
discriminant: -0.00011838724085865194
-0.013398123665888008
a: -0.0006272562075489343
b: 0.0019454430281536372
c: -0.2020445679400079
discriminant: -0.0005031500891918578
-0.013398123665888008
a: 0.01122879721632114
b: -0.07490946111284547
c: -0.025819745977778696
discriminant: 0.006771126131262508
-0.013398123665888008
a: 0.011162760638022122
b: -0.0609850287820472
c: -0.28412378249700143
discriminant: 0.01640559683788107
-0.013398123665888008
a: 0.031004051067489307
b: -0.22594278743145962
c: -0.037661595909630585
discriminant: 0.05572079136375908
-0.013398123665888008
a: 0.02953929372802595
b: -0.19232527963012852
c: -0.2441195093915124
discriminant: 0.06583348475543702
-0.013398123665888008
a: 0.018757016462968207
b: -0.145756111398802
c: -0.012594659560110189
discriminant: 0.022189796956957848
-0.013398123665888008
a: 0.018513474099911772
b: -0.1261213563621848
c: -0.1786656576601372
discriminant: 0.029137484633175826
-0.013398123665888008
a: 0.030392076316396982
b: -0.1931367964014949
c: 0.0031092244078939624
discriminant: 0.03692383898227442
-0.013398123665888008
a: 0.02886809852510046
b: -0.1737874400537901
c: -0.24369662849421425
discriminant: 0.05834230744687281
-0.013398123665888008
a: 0.012198738056970504
b: -0.0830110591202112
c: -0.01544839090547867
discriminant: 0.007644639432489678
-0.013398123665888008
a: 0.011141363113796186
b: -0.06608955469057967
c: -0.2733394316634371
discriminant: 0.016549324685123247
-0.013398123665888008
a: 0.013077726412908094
b: -0.08719371287829314
c: -0.02480098134776343
discriminant: 0.00890010536085297
-0.013398123665888008
a: 0.013687329052709444
b: -0.0775689569607636
c: -0.2624208109080651
discriminant: 0.020384303040690922
-0.013398123665888008
a: 0.009674339344556134
b: -0.07695054668389534
c: -0.04096243372907227
discriminant: 0.007506524572046105
-0.013398123665888008
a: 0.009775362442546724
b: -0.06614804935566382
c: -0.21911697170282973
discriminant: 0.012943355696392997
-0.013398123665888008
a: 0.0012940928449652646
b: -0.008931481918879436
c: -0.0414198919771579
discriminant: 0.0002941761126547671
-0.013398123665888008
a: 0.001459754557470075
b: -0.002838471590867697
c: -0.2872530666388532
discriminant: 0.0016853328136654474
-0.013398123665888008
a: 0.012307188987211027
b: -0.08566834631103126
c: 0.011837920085008169
discriminant: 0.006756299480859997
-0.013398123665888008
a: 0.011347788449162607
b: -0.06428347056768136
c: -0.2430883796987794
discriminant: 0.015166426617311806
-0.013398123665888008
a: 0.0006802572686188399
b: -0.006899906471830766
c: -0.020493302741371622
discriminant: 0.00010337158191130987
-0.013398123665888008
a: 0.0008844460320743246
b: -0.0028655357440662416
c: -0.2504307471173556
discriminant: 0.0008941812174899362
-0.013398123665888008
a: 0.024234445821210048
b: -0.17384907495291385
c: 0.08492210387363608
discriminant: 0.021991340360588637
-0.013398123665888008
a: 0.024093039935542453
b: -0.15284857750659214
c: -0.1212893934694711
discriminant: 0.03505160844825946
-0.013398123665888008
a: 0.029069271025035162
b: -0.1947032389038254
c: -0.004974816142848226
discriminant: 0.03848780835466481
-0.013398123665888008
a: 0.02767572322086533
b: -0.158878579166442
c: -0.2749763066711831
discriminant: 0.05568307554085716
-0.013398123665888008
a: 0.006919766469483132
b: -0.055177582450437274
c: -0.0038229582258486605
discriminant: 0.0031503815176566526
-0.013398123665888008
a: 0.006610630295862728
b: -0.04309657551199075
c: -0.1950269642508643
discriminant: 0.007014319454408324
-0.013398123665888008
a: 0.011096239045983548
b: -0.07973132128905847
c: 0.06115525454191906
discriminant: 0.0036427103012386477
-0.013398123665888008
a: 0.010369161660211039
b: -0.062110886242561614
c: -0.17406600470167588
discriminant: 0.011077436359031356
-0.013398123665888008
a: 0.034007594260725936
b: -0.24441864351336895
c: -0.01951136920588603
discriminant: 0.06239461220661531
-0.013398123665888008
a: 0.03273563541117103
b: -0.2115458661445222
c: -0.22939431292925072
discriminant: 0.07478912785662822
-0.013398123665888008
a: 0.021751054566762764
b: -0.14634116622239962
c: -0.012031320517973731
discriminant: 0.022462512567718633
-0.013398123665888008
a: 0.01994256275958995
b: -0.12227264246700603
c: -0.2679705507837017
discriminant: 0.036326677202767714
-0.013398123665888008
a: 0.0055447917757190995
b: -0.03073039674177483
c: -0.05770536504627366
discriminant: 0.0022242142180006713
-0.013398123665888008
a: 0.006365319215337923
b: -0.025299031506249098
c: -0.29327912098144504
discriminant: 0.008107301892116614
-0.013398123665888008
a: 0.010071034409783568
b: -0.06043882080059901
c: -0.024112959653451838
discriminant: 0.004624220845333465
-0.013398123665888008
a: 0.011646388988845808
b: -0.0596389724536992
c: -0.2626132284007693
discriminant: 0.015790790281620965
-0.013398123665888008
a: 0.025455740881313606
b: -0.19165152889222464
c: -0.4010094112324464
discriminant: 0.07756227517993236
-0.013398123665888008
a: 0.024297267412201073
b: -0.15976511709661406
c: -0.5900260412614006
discriminant: 0.08286897465965734
-0.013398123665888008
a: 0.008408497747430327
b: -0.04719341480470449
c: -0.05953734461323201
discriminant: 0.004229696913202279
-0.013398123665888008
a: 0.010055179710228079
b: -0.047740726522857574
c: -0.2947273500773203
discriminant: 0.014133322851117314
-0.013398123665888008
a: 0.0036046650033996815
b: -0.027017783749931856
c: -0.02417752253364558
discriminant: 0.0010785681161418394
-0.013398123665888008
a: 0.003889786293138368
b: -0.01886678446496004
c: -0.21585516822011808
discriminant: 0.0037144774546300253
-0.013398123665888008
a: 0.010880142403742615
b: -0.0735107005466751
c: -0.11696617357678185
discriminant: 0.010494257594607993
-0.013398123665888008
a: 0.010503451114490787
b: -0.055086168686911324
c: -0.35886998331620046
discriminant: 0.018111979285482194
-0.013398123665888008
a: 0.0037259675557667384
b: -0.02384942281005048
c: -0.06878411824289532
discriminant: 0.0015939445400727603
-0.013398123665888008
a: 0.003994030363317996
b: -0.015095519977828431
c: -0.275480649145445
discriminant: 0.004628987032174854
-0.013398123665888008
a: 0.009317047413783665
b: -0.07173068401023186
c: -0.10161239979710734
discriminant: 0.008932201215527697
-0.013398123665888008
a: 0.007793346945006288
b: -0.04847894667293293
c: -0.32121798210047847
discriminant: 0.012363660988452468
-0.013398123665888008
a: -0.0006768296104308416
b: 0.005044885130348106
c: -0.10448287323571159
discriminant: -0.00025741754357687933
-0.013398123665888008
a: -0.0002735349128757652
b: 0.008532119207321567
c: -0.3232629917826858
discriminant: -0.00028089779900499905
-0.013398123665888008
a: 0.006374037338165159
b: -0.03937484055453713
c: -0.049516451847459675
discriminant: 0.002812856920411883
-0.013398123665888008
a: 0.006836713180369649
b: -0.030203451603319248
c: -0.26609544857483247
discriminant: 0.008189121530785774
-0.013398123665888008
a: 0.008436720735567057
b: -0.04665573230970621
c: -0.030269629952549892
discriminant: 0.003198263016069441
-0.013398123665888008
a: 0.00964724866431958
b: -0.04268035004575868
c: -0.26263569934642506
discriminant: 0.011956459878918245
-0.013398123665888008
a: 0.009732286895965277
b: -0.05809266919608444
c: -0.11955292026165798
discriminant: 0.00802885149127336
-0.013398123665888008
a: 0.011062232370262447
b: -0.05510272984739867
c: -0.35137429648200336
discriminant: 0.018584247303121047
-0.013398123665888008
a: 0.011646168040767221
b: -0.07573653406338099
c: -0.1557811688999985
discriminant: 0.01299303727431976
-0.013398123665888008
a: 0.011612357577229827
b: -0.05900306617453949
c: -0.3985481695776273
discriminant: 0.021993697245540438
-0.013398123665888008
a: 0.03499027122342792
b: -0.2506978176548899
c: -0.11938007690086005
discriminant: 0.07955796085466353
-0.013398123665888008
a: 0.031520136858978996
b: -0.19548834817744776
c: -0.3476520851658761
discriminant: 0.0820478594880984
-0.013398123665888008
a: 0.00597585499461277
b: -0.040402301152125786
c: -0.03694167635132406
discriminant: 0.002515378342920778
-0.013398123665888008
a: 0.006312158659931082
b: -0.030545811323670513
c: -0.24052675077276164
discriminant: 0.0070060186407627685
-0.013398123665888008
a: 0.004692197111238033
b: -0.03191447849036372
c: -0.0920554459684787
discriminant: 0.002746303127899987
-0.013398123665888008
a: 0.0047035193326419675
b: -0.02043594531921586
c: -0.3021772544250544
discriminant: 0.006102814093381636
-0.013398123665888008
a: 0.005347754012341258
b: -0.032999337104863774
c: -0.09202060296261971
discriminant: 0.0030573704442060845
-0.013398123665888008
a: 0.005512099854174791
b: -0.021714240371112498
c: -0.3095519918195716
discriminant: 0.007296634190767159
-0.013398123665888008
a: 0.003088476751607716
b: -0.016972188764823926
c: -0.12381143122098648
discriminant: 0.0018176100991059933
-0.013398123665888008
a: 0.003786000121681418
b: -0.013010721485785248
c: -0.36744441213766155
discriminant: 0.005733857229838049
-0.013398123665888008
a: 0.022797482497968223
b: -0.16643625443028104
c: -0.4207462903390923
discriminant: 0.0660688515491433
-0.013398123665888008
a: 0.020793515130709768
b: -0.1299326591767762
c: -0.6352722163188803
discriminant: 0.06972066568933295
-0.013398123665888008
a: 0.008508352087812917
b: -0.04926083940572845
c: -0.0895020802327674
discriminant: 0.005472691143805232
-0.013398123665888008
a: 0.008730698048977616
b: -0.03844138646803846
c: -0.3548972409906147
discriminant: 0.013871742791602285
-0.013398123665888008
a: 0.00510144368867576
b: -0.03508431519702751
c: -0.08154108064344945
discriminant: 0.002894818097709681
-0.013398123665888008
a: 0.005329376324163376
b: -0.02531443458021701
c: -0.28673028105363996
discriminant: 0.006753194883188004
-0.013398123665888008
a: -0.003925050390919925
b: 0.02621643560938136
c: -0.13807782694705584
discriminant: -0.001480548218482822
-0.013398123665888008
a: -0.003689500633344659
b: 0.028775935358755833
c: -0.35982857435509963
discriminant: -0.004482296556143289
-0.013398123665888008
a: 0.008445449046786159
b: -0.05025859354415671
c: -0.05877087559613903
discriminant: 0.004511311966165552
-0.013398123665888008
a: 0.009590115813523349
b: -0.0462295716103627
c: -0.29196077867818426
discriminant: 0.013336924013398636
-0.013398123665888008
a: 0.007200809981542638
b: -0.043508575272620836
c: -0.10504946654783864
discriminant: 0.004918761111346937
-0.013398123665888008
a: 0.0073565012183489835
b: -0.033020252023040875
c: -0.3560142005114314
discriminant: 0.011566412642912673
-0.013398123665888008
a: 0.028985932563173653
b: -0.1988500032156389
c: -0.13531788836605185
discriminant: 0.055230584525937355
-0.013398123665888008
a: 0.026391460240181002
b: -0.15166577632993805
c: -0.3929368929738145
discriminant: 0.06448322126103753
-0.013398123665888008
a: 0.005649373551848158
b: -0.03283644860053969
c: -0.09398243009766294
discriminant: 0.003201999776424506
-0.013398123665888008
a: 0.005881436034070115
b: -0.022210645695999565
c: -0.34059411153434416
discriminant: 0.008506042704513973
-0.013398123665888008
a: 0.006350029099296413
b: -0.03584646735206959
c: -0.164192221092344
discriminant: 0.00545547074888097
-0.013398123665888008
a: 0.006601484615916942
b: -0.026632347558506242
c: -0.4248917506191022
discriminant: 0.011928947357045158
-0.013398123665888008
a: 0.006017274974278103
b: -0.04137863435270128
c: -0.03900659464770473
discriminant: 0.002651045004116326
-0.013398123665888008
a: 0.00649591880566815
b: -0.03332219150321683
c: -0.23881726583231966
discriminant: 0.007315718719530716
-0.013398123665888008
a: 0.0028116490984523377
b: -0.015582427403463855
c: -0.10185707661738286
discriminant: 0.001388357474353242
-0.013398123665888008
a: 0.003135767344887328
b: -0.0079315445987794
c: -0.331825920660365
discriminant: 0.0042250249444982105
-0.013398123665888008
a: 0.0075925569800682265
b: -0.051952241369279895
c: -0.15470665937526518
discriminant: 0.007397511889302746
-0.013398123665888008
a: 0.007271566751480711
b: -0.03723559904640292
c: -0.4038382422368626
discriminant: 0.013132636777248415
-0.013398123665888008
a: 0.005933770329163799
b: -0.035620377411648585
c: -0.06527166468882795
discriminant: 0.0028180395560110675
-0.013398123665888008
a: 0.006813942073026285
b: -0.030891777132395354
c: -0.29271855553451165
discriminant: 0.008932571018845944
-0.013398123665888008
a: 0.006504499587998712
b: -0.04083933260532474
c: -0.029175023445002002
discriminant: 0.0024269267995598136
-0.013398123665888008
a: 0.006894479313995426
b: -0.030916541362940975
c: -0.24054381283629256
discriminant: 0.007589529896684067
-0.013398123665888008
a: 0.02407943300761814
b: -0.16917204280034198
c: -0.10665006269974453
discriminant: 0.03889147222538783
-0.013398123665888008
a: 0.022793753442631674
b: -0.1352331753185298
c: -0.3327639593416917
discriminant: 0.04862777028204594
-0.013398123665888008
a: 0.004099898160236058
b: -0.023610700464584383
c: -0.10896249197356911
discriminant: 0.0023444056579370143
-0.013398123665888008
a: 0.0042886530651409524
b: -0.013617505069771968
c: -0.3448074625749752
discriminant: 0.006100474769347832
-0.013398123665888008
a: 0.011104482127908814
b: -0.06884543525740844
c: -0.10389615239890115
discriminant: 0.009354545825670371
-0.013398123665888008
a: 0.011282319786234736
b: -0.05432440657384857
c: -0.361099501604888
discriminant: 0.019247301356626122
-0.013398123665888008
a: 0.004836383480597905
b: -0.03627359366965788
c: -0.04152813906731512
discriminant: 0.0021191576207719855
-0.013398123665888008
a: 0.005164905328039119
b: -0.028040555558103503
c: -0.23165670003606975
discriminant: 0.005572212453176116
-0.013398123665888008
a: 0.008536438289334343
b: -0.05346149425209443
c: -0.022505928942991194
discriminant: 0.0036266132619306776
-0.013398123665888008
a: 0.009193677301730704
b: -0.04456937538173211
c: -0.24213415044099962
discriminant: 0.010890842193450812
-0.013398123665888008
a: 0.02411808995413254
b: -0.16938807222483854
c: -0.1176755218512161
discriminant: 0.040044754297675594
-0.013398123665888008
a: 0.021329622271277143
b: -0.12561015641174045
c: -0.37127813846775737
discriminant: 0.04745480119818269
-0.013398123665888008
a: 0.007313478626426819
b: -0.04662278880643306
c: -0.11102589669652885
discriminant: 0.005421626525969002
-0.013398123665888008
a: 0.00750847561179226
b: -0.034525526211281354
c: -0.33852333229656784
discriminant: 0.011359188698451582
-0.013398123665888008
a: 0.0045994530239030695
b: -0.02730607693990117
c: -0.10974413557215257
discriminant: 0.002764673822699665
-0.013398123665888008
a: 0.0048758671224729735
b: -0.017544562850980744
c: -0.3333699548395145
discriminant: 0.006809682095321168
-0.013398123665888008
a: 0.01578236549246079
b: -0.10864297227033176
c: -0.436693910710363
discriminant: 0.03937154705238402
-0.013398123665888008
a: 0.014736560552412658
b: -0.08283557251730894
c: -0.6869748924303235
discriminant: 0.04735632047541689
-0.013398123665888008
a: -0.0004450367595556859
b: -0.009480307678671585
c: -0.02442623314001946
discriminant: 4.639394710313554e-05
-0.013398123665888008
a: 0.000200676146858602
b: -0.007956846456776329
c: -0.10751763432894268
discriminant: 0.0001496163038426515
-0.013398123665888008
a: 0.00324002918044111
b: -0.040981933295618916
c: -0.00147596887033985
discriminant: 0.0016986475854838536
-0.013398123665888008
a: 0.0036361117703918814
b: -0.03544897270454547
c: -0.0678050877042059
discriminant: 0.0022428171757824774
-0.013398123665888008
a: -0.010182412087433042
b: 0.06686484549296479
c: -0.09584138096647699
discriminant: 0.0005673218186807321
-0.013398123665888008
a: -0.010228695529689738
b: 0.066942405844346
c: -0.17021291918243364
discriminant: -0.002482938801918068
-0.013398123665888008
a: 0.02361736044979071
b: -0.15085738340196378
c: -0.30108389435624405
discriminant: 0.05120117756143959
-0.013398123665888008
a: 0.022161258982434692
b: -0.13337090022187192
c: -0.5451685344448075
discriminant: 0.06611428134961551
-0.013398123665888008
a: 0.03542916609469421
b: -0.22105547874676001
c: -0.636818862189433
discriminant: 0.13911336964693366
-0.013398123665888008
a: 0.014875904248318982
b: -0.08887363275274598
c: -0.23736310297490915
discriminant: 0.022022485766424474
-0.013398123665888008
a: 0.02370901005668699
b: -0.15298362855672482
c: -0.005861724618184128
discriminant: 0.023959893358070177
-0.013398123665888008
a: 0.02268324129732819
b: -0.13744735099210742
c: -0.24813799677317727
discriminant: 0.04140607051811407
-0.013398123665888008
a: 0.011451702367273704
b: -0.06925394776228097
c: -0.20798639828130627
discriminant: 0.014323302598895808
-0.013398123665888008
a: 0.012229573700338383
b: -0.07438292793451057
c: -0.18909528119382302
discriminant: 0.014783038679094869
-0.013398123665888008
a: 0.008426376384876975
b: -0.057075913403230816
c: -0.14458785301513266
discriminant: 0.008131066571560212
-0.013398123665888008
a: 0.01196744154561583
b: -0.08247354766004611
c: -0.011923051475483004
discriminant: 0.007372639749946742
-0.013398123665888008
a: 0.011274088763755429
b: -0.06562912345042551
c: -0.2712137905141728
discriminant: 0.01653793523771661
-0.013398123665888008
a: 0.007209421531432438
b: -0.037154397550313994
c: -0.2099565352806546
discriminant: 0.007435109921796001
-0.013398123665888008
a: -0.002093916627164822
b: 0.012507460415025942
c: -0.012836994900849885
discriminant: 4.891817777056245e-05
-0.013398123665888008
a: -0.0022599146870171264
b: 0.016813831156253886
c: -0.2685238868238683
discriminant: -0.0021446593844417243
-0.013398123665888008
a: 0.009778787762852601
b: -0.0584323476621566
c: -0.17517158290696588
discriminant: 0.01026620217863177
-0.013398123665888008
a: -0.0002245354886659806
b: 0.004272396850540136
c: -0.2025463449139756
discriminant: -0.0001636619952825658
-0.013398123665888008
a: -0.002234254214164835
b: 0.013158458886972937
c: -0.027219392292583966
discriminant: -7.011512746668916e-05
-0.013398123665888008
a: -0.0019935145799370923
b: 0.015674847874588116
c: -0.26775733078814945
discriminant: -0.0018894117153533797
-0.013398123665888008
a: 0.00648470601690754
b: -0.03670490457571282
c: -0.1950499236083797
discriminant: 0.006406615672794648
-0.013398123665888008
a: 0.0012571990140017118
b: -0.018680122569032898
c: -0.013148118946617715
discriminant: 0.00041506618789675226
-0.013398123665888008
a: 0.0009281691280174816
b: -0.00881356203457867
c: -0.1705457687122961
discriminant: 0.0007108601454684184
-0.013398123665888008
a: 0.0032915603125325057
b: -0.024011192632461403
c: -0.008673057469415157
discriminant: 0.0006907289386517309
-0.013398123665888008
a: 0.003697367319455913
b: -0.019926222626347717
c: -0.24674506770561766
discriminant: 0.0040462829464415215
-0.013398123665888008
a: 0.007565018452491936
b: -0.04391563509321181
c: -0.2330724910595926
discriminant: 0.008981373788176455
-0.013398123665888008
a: 0.011687086166652804
b: -0.08132655768990651
c: -0.01278185297615686
discriminant: 0.007211539454097023
-0.013398123665888008
a: 0.011146030863260496
b: -0.06639595869540918
c: -0.26415892789181605
discriminant: 0.016185717583434425
-0.013398123665888008
a: 0.0041871698125348425
b: -0.030245416264825575
c: -0.02374313154563057
discriminant: 0.0013124512996842076
-0.013398123665888008
a: 0.00376673181002205
b: -0.02001291885069481
c: -0.2814449914877769
discriminant: 0.004641028129758073
-0.013398123665888008
a: 0.008467796588976674
b: -0.058237159812765976
c: 0.026656779914919215
discriminant: 0.0024886700229110248
-0.013398123665888008
a: 0.008189882872973297
b: -0.04434924673954155
c: -0.2225958416754351
discriminant: 0.009258991171695624
-0.013398123665888008
a: 0.0034210499424997924
b: -0.019208624972140237
c: -0.23103797992255248
discriminant: 0.003530541145037595
-0.013398123665888008
a: 0.014925266142683098
b: -0.08211284427186011
c: -0.19214048882548196
discriminant: 0.018213510924436932
-0.013398123665888008
a: 0.0031063482584227572
b: -0.021395801020283656
c: 0.0019054176101261922
discriminant: 0.00043410473860043693
-0.013398123665888008
a: 0.003033077915585679
b: -0.012324978888495264
c: -0.25556418800729597
discriminant: 0.003252489483239917
-0.013398123665888008
a: 0.00858427193065919
b: -0.05931278055146055
c: 0.031430576280718436
discriminant: 0.002438771481821662
-0.013398123665888008
a: 0.008977494941811454
b: -0.05259136548403867
c: -0.21589792035976274
discriminant: 0.010518741675385263
-0.013398123665888008
a: 0.009362753295562772
b: -0.0560519463819259
c: -0.19585175080993034
discriminant: 0.010476667194551953
-0.013398123665888008
a: 0.018668206092086057
b: -0.11640775224908179
c: -0.1828757904439967
discriminant: 0.027206616564730297
-0.013398123665888008
a: 0.007312137263941639
b: -0.041286113539408836
c: -0.20175499199454616
discriminant: 0.00760558395178723
-0.013398123665888008
a: 0.005792606791547679
b: -0.03337600968031293
c: -0.17748730961687575
discriminant: 0.005226414802581303
-0.013398123665888008
a: 0.00697300430099159
b: -0.06075556745146371
c: 0.0063165323728007206
discriminant: 0.0035150581467377887
-0.013398123665888008
a: 0.00632899116097866
b: -0.04478019255219723
c: -0.15883936804213838
discriminant: 0.006026437470428381
-0.013398123665888008
a: 0.04344798710017894
b: -0.2941501825578301
c: -0.1486569821932039
discriminant: 0.11235971647753219
-0.013398123665888008
a: 0.0015273564470112792
b: -0.006310672208776874
c: -0.19917762676103845
discriminant: 0.0012566855130621423
-0.013398123665888008
a: 0.01613951106368917
b: -0.12918541787567495
c: 0.03027630739467524
discriminant: 0.014734292999056696
-0.013398123665888008
a: 0.015142721739592479
b: -0.10480516148672586
c: -0.13559195320295758
discriminant: 0.019197046744179613
-0.013398123665888008
a: 0.00919611652994438
b: -0.06333505725110983
c: 0.0007230112694925905
discriminant: 0.003984733893454492
-0.013398123665888008
a: 0.008835501090331252
b: -0.053430178501358616
c: -0.24555262021185154
discriminant: 0.011533105749149085
-0.013398123665888008
a: 0.027745678592949005
b: -0.18286065060785667
c: -0.16933364290376962
discriminant: 0.052231124864653394
-0.013398123665888008
a: 0.028278798068606007
b: -0.17528726191268296
c: -0.1779576221536704
discriminant: 0.05085533483545724
-0.013398123665888008
a: 0.010783610669554397
b: -0.05873244864647384
c: -0.20789445619137703
discriminant: 0.012416912027716857
-0.013398123665888008
a: 0.007693661434168616
b: -0.0534425562608791
c: -0.023213357453781946
discriminant: 0.003570489671696159
-0.013398123665888008
a: 0.0071688521505368355
b: -0.03883059234175315
c: -0.27832457120171716
discriminant: 0.009488885704838109
-0.013398123665888008
a: -0.005072728131424306
b: 0.03449823894584172
c: -0.23829766106266204
discriminant: -0.00364514850533633
-0.013398123665888008
a: -0.004799825361317781
b: 0.03292224408354736
c: -0.22198593342478168
discriminant: -0.0031781006969356014
-0.013398123665888008
a: 0.0051476597117379765
b: -0.029338413170507033
c: -0.16761921963920468
discriminant: 0.004312129302762153
-0.013398123665888008
a: -0.004248958285033296
b: 0.029729268628705632
c: -0.2213818799166033
discriminant: -0.0028787400781138507
-0.013398123665888008
a: 0.009770194747321874
b: -0.06717388840955718
c: -0.0009085562297259653
discriminant: 0.0045478383692729015
-0.013398123665888008
a: 0.009021511852597693
b: -0.05285407328779346
c: -0.26095515234719924
discriminant: 0.012210393062698222
-0.013398123665888008
a: -0.0015779748425218372
b: 0.014466201818298163
c: -0.24038356936968863
discriminant: -0.0013080059050361531
-0.013398123665888008
a: -0.005008387660388391
b: 0.03197285040152965
c: -0.04131947975003947
discriminant: 0.00019448727274353188
-0.013398123665888008
a: -0.004890341700253763
b: 0.034114595028472555
c: -0.2793291016758729
discriminant: -0.004300253422123094
-0.013398123665888008
a: 0.012668319028258546
b: -0.07769907025837064
c: -0.19911836130232474
discriminant: 0.01612712522046282
-0.013398123665888008
a: 0.016209015112904516
b: -0.10898959217165718
c: 0.004026929779720412
discriminant: 0.011617640939111783
-0.013398123665888008
a: 0.015289203024174705
b: -0.09150715227848882
c: -0.25861588496472343
discriminant: 0.02418968200012761
-0.013398123665888008
a: 0.010459461386048547
b: -0.05729420135564808
c: -0.2030966083838962
discriminant: 0.01177975004109669
-0.013398123665888008
a: 0.03074753215006549
b: -0.19690761024826492
c: -0.19230423282555031
discriminant: 0.062424129299271755
-0.013398123665888008
a: 0.021338909394144824
b: -0.14073203779507693
c: 0.03760408443687091
discriminant: 0.016595785859362323
-0.013398123665888008
a: 0.022679460615208476
b: -0.13062114748278353
c: -0.20211891049300135
discriminant: 0.03539767565017857
-0.013398123665888008
a: 0.004947925049202555
b: -0.034992631613728425
c: 0.013018189360820442
discriminant: 0.0009668321663194434
-0.013398123665888008
a: 0.005185084612867161
b: -0.029324941560196688
c: -0.2372458707273054
discriminant: 0.005780511852606643
-0.013398123665888008
a: -0.0005001280478757891
b: 0.0012269721359099567
c: -0.022644514918276903
discriminant: -4.379516754238861e-05
-0.013398123665888008
a: -0.0005895616222288298
b: 0.006862512805324059
c: -0.27310939648159305
discriminant: -0.000596965193339262
-0.013398123665888008
a: 0.004941771352714138
b: -0.025579108243707793
c: -0.22476119382891413
discriminant: 0.00509716449400555
-0.013398123665888008
a: 0.03707288810510763
b: -0.25910083540312623
c: -0.13876403152230965
discriminant: 0.08771077656115876
-0.013398123665888008
a: 0.024028780554792885
b: -0.14895125022704803
c: -0.16592801655305622
discriminant: 0.03813466653478239
-0.013398123665888008
a: 0.008074533834799417
b: -0.04351944694146603
c: -0.20952285605197074
discriminant: 0.00866113982351286
-0.013398123665888008
a: 0.02546046006260855
b: -0.15835204113663448
c: -0.2073785672026084
discriminant: 0.046195183844550354
-0.013398123665888008
a: 0.034006233606187444
b: -0.23179281540209734
c: -0.15144866782408017
discriminant: 0.074328704381517
-0.013398123665888008
a: 0.008709159112094914
b: -0.04513670190680588
c: -0.18089757275319263
discriminant: 0.008339184835421135
-0.013398123665888008
a: 0.005234725773134273
b: -0.036779483681382424
c: 0.009307608156771452
discriminant: 0.0011578393146511308
-0.013398123665888008
a: 0.005910837417678723
b: -0.0331145745377964
c: -0.22448280385454333
discriminant: 0.006404100473414746
-0.013398123665888008
a: 0.006470044058921638
b: -0.038380790607865645
c: -0.1686350176924284
discriminant: 0.005837389065072994
-0.013398123665888008
a: -0.003161696470367616
b: 0.022198395557524897
c: -0.25335150981167753
discriminant: -0.002711313532007208
-0.013398123665888008
a: 0.0032506363793731686
b: -0.022491608276611647
c: 0.005324877480336165
discriminant: 0.00043663548105540287
-0.013398123665888008
a: 0.003588703522160351
b: -0.016604831380295476
c: -0.2368314125557075
discriminant: 0.00367539132275556
-0.013398123665888008
a: 0.01592549046121586
b: -0.09641664233445768
c: -0.17961207298130122
discriminant: 0.020737810338982414
-0.013398123665888008
a: 0.012446349707312922
b: -0.0712163730926419
c: -0.19864179865048437
discriminant: 0.014961232966444643
-0.013398123665888008
a: 0.003912123983910045
b: -0.01923725755771044
c: -0.24035754400317166
discriminant: 0.004131306128775774
-0.013398123665888008
a: -0.008029857036881038
b: 0.05206926986722597
c: -0.046907116194202736
discriminant: 0.0012045791162987455
-0.013398123665888008
a: -0.007954706993320796
b: 0.052575843825147614
c: -0.2814793642633818
discriminant: -0.006192124115599348
-0.013398123665888008
a: 0.0002793695417341608
b: -0.003528689267779772
c: -0.010266774152573821
discriminant: 2.3924543908914845e-05
-0.013398123665888008
a: 0.00011120663350277626
b: 0.001655623069656137
c: -0.2597300890615052
discriminant: 0.00011827592304440259
-0.013398123665888008
a: 0.009849559479217219
b: -0.06868047682766057
c: -0.0001319306385595409
discriminant: 0.004722205731961313
-0.013398123665888008
a: 0.009258173345955849
b: -0.05286679007897291
c: -0.25269597042250547
discriminant: 0.012152909885238539
-0.013398123665888008
a: 0.010367068439148249
b: -0.05998984544037303
c: -0.18552210969711502
discriminant: 0.011292063188780486
-0.013398123665888008
a: 0.015373306674576969
b: -0.10562380552832973
c: -0.0156403152597554
discriminant: 0.01211816174618756
-0.013398123665888008
a: 0.014678296819572959
b: -0.08454847999096343
c: -0.26298390807712557
discriminant: 0.0225890689148917
-0.013398123665888008
a: 0.029443184707730267
b: -0.23058272058410478
c: -0.015193368080852476
discriminant: 0.05495775560291563
-0.013398123665888008
a: 0.028818581852350124
b: -0.19981463238360742
c: -0.16316063557194116
discriminant: 0.058734119839842
-0.013398123665888008
a: 0.018701780681361996
b: -0.11527448121821396
c: -0.22391585883152787
discriminant: 0.030038707151912557
-0.013398123665888008
a: 0.0017162586270537492
b: -0.007208386692362817
c: -0.2028326609305796
discriminant: 0.0014444140553881342
-0.013398123665888008
a: 0.006515436414527771
b: -0.039053865899079665
c: -0.21447911388386987
discriminant: 0.007114904556681755
-0.013398123665888008
a: 0.018859877770842078
b: -0.10897162651032499
c: -0.1435669610174647
discriminant: 0.0227054367311883
-0.013398123665888008
a: 0.026389902430142227
b: -0.20729125830492912
c: -0.002122808601026427
discriminant: 0.04319374861707666
-0.013398123665888008
a: 0.025592548428211983
b: -0.17870832662249198
c: -0.15457683771366326
discriminant: 0.04776072682447844
-0.013398123665888008
a: 0.008466672769489621
b: -0.057247886271370396
c: 0.015160510241007952
discriminant: 0.002763884165623317
-0.013398123665888008
a: 0.008093609830486815
b: -0.04240352693473931
c: -0.2436505731040567
discriminant: 0.00968610979122012
-0.013398123665888008
a: 0.005064390771819817
b: -0.03648591217957298
c: -0.0032312283689599486
discriminant: 0.0013966786001091242
-0.013398123665888008
a: 0.0048072592323190515
b: -0.025716556158794007
c: -0.24849960173821362
discriminant: 0.005439749279402946
-0.013398123665888008
a: -0.011020234765202357
b: 0.07355709930886567
c: -0.03065583126624316
discriminant: 0.004059309028828606
-0.013398123665888008
a: -0.011008107416413554
b: 0.07248715447936066
c: -0.12236057843566883
discriminant: -0.00013344599930265738
-0.013398123665888008
a: -0.002189263446391896
b: 0.009747147546991228
c: -0.025473589874831615
discriminant: -0.00012806671134257317
-0.013398123665888008
a: -0.0018476372367381153
b: 0.012265217530932807
c: -0.18760433364955176
discriminant: -0.0012360634494163114
-0.013398123665888008
a: -0.001349764055655533
b: 0.0011215343282520163
c: -0.12257933164889956
discriminant: -0.0006605548640544055
-0.013398123665888008
a: -0.0003669071623621
b: -0.0004057904395929762
c: -0.21884110320378614
discriminant: -0.0003210128068579055
-0.013398123665888008
a: 0.004537680052625688
b: -0.05109914072692631
c: -0.11467396728631918
discriminant: 0.004692537278672544
-0.013398123665888008
a: 0.004488324725669789
b: -0.039052734295260766
c: -0.19154547882786532
discriminant: 0.004963989290789704
-0.013398123665888008
a: -0.0019272787611710638
b: -0.002979199543380051
c: -0.0035654211786342316
discriminant: -1.861061212956912e-05
-0.013398123665888008
a: -0.0020497333528422847
b: 0.004673468979198292
c: -0.030290583180346387
discriminant: -0.00022650916218766934
-0.013398123665888008
a: -0.005775381910674664
b: 0.033204085933497204
c: -0.09332586279869515
discriminant: -0.0010534586765436913
-0.013398123665888008
a: -0.005479332146522383
b: 0.0338878008898564
c: -0.18430047165104668
discriminant: -0.0028909909465967163
-0.013398123665888008
a: -0.0034680588985736404
b: 0.012834912646319002
c: -0.015584160956398363
discriminant: -5.14521696879255e-05
-0.013398123665888008
a: -0.0034810521324233823
b: 0.018134216078888807
c: -0.0870439448677377
discriminant: -0.0008831682467896971
-0.013398123665888008
a: -0.00735226584604776
b: 0.044065043490402724
c: -0.016237142388751624
discriminant: 0.0014642089081221517
-0.013398123665888008
a: -0.007324001931437872
b: 0.04582494612986138
c: -0.0814777030866195
discriminant: -0.00028704573129739383
-0.013398123665888008
a: -0.005419577579741696
b: 0.029946044793966925
c: -0.010007306787625181
discriminant: 0.0006798240968030323
-0.013398123665888008
a: -0.005251954072615774
b: 0.0321305494956359
c: -0.10151198782471049
discriminant: -0.0011001729806097362
-0.013398123665888008
a: -0.010005354286737763
b: 0.06547101956772587
c: -0.019358662291723228
discriminant: 0.0035116933042535375
-0.013398123665888008
a: -0.01001588108496928
b: 0.06538096244108332
c: -0.11659356920683217
discriminant: -0.00039647904806871994
-0.013398123665888008
a: -0.009796543020541192
b: 0.06384837575200772
c: -0.01719273050145753
discriminant: 0.0034028977901771696
-0.013398123665888008
a: -0.009798494216700452
b: 0.06384678652098777
c: -0.11430093791524232
discriminant: -0.00040349616744717216
-0.013398123665888008
a: -0.007340256398021608
b: 0.04578740405731286
c: -0.025367838782821672
discriminant: 0.0013516606065892805
-0.013398123665888008
a: -0.007018083742675088
b: 0.04498712619566748
c: -0.12602100873912814
discriminant: -0.0015138624473254505
-0.013398123665888008
a: -0.0031307042325104248
b: 0.012331372532406334
c: -0.10487285933206014
discriminant: -0.001161240869812419
-0.013398123665888008
a: -0.0027960879620788455
b: 0.015144063040351277
c: -0.1934456659445104
discriminant: -0.001934221746084951
-0.013398123665888008
a: -0.008491714466482603
b: 0.053807256730217086
c: -0.01468742425596381
discriminant: 0.0023963352247125505
-0.013398123665888008
a: -0.008428079834674512
b: 0.05421878799728326
c: -0.11919560506982518
discriminant: -0.0010786833299889355
-0.013398123665888008
a: -0.010350348912449625
b: 0.06807469771391844
c: -0.07033422226296515
discriminant: 0.0017222295052114864
-0.013398123665888008
a: -0.010386658956622928
b: 0.06789406373850462
c: -0.1659506875265605
discriminant: -0.0022850888888938017
-0.013398123665888008
a: -0.0018065792327822084
b: -0.0005885986757817041
c: -0.013890765621991985
discriminant: -0.00010003262639941104
-0.013398123665888008
a: -0.0018456658343164473
b: 0.006412743380570768
c: -0.08799620943538555
discriminant: -0.0006085231115519287
-0.013398123665888008
a: -0.005767307081910204
b: 0.032241050567126235
c: -0.026584976866978915
discriminant: 0.0004261904402426052
-0.013398123665888008
a: -0.005619056429956354
b: 0.034391984294709244
c: -0.10724052360087588
discriminant: -0.0012275536310380236
-0.013398123665888008
a: -0.0029049279393420207
b: 0.00949795967536246
c: -0.0241817755740511
discriminant: -0.00019077402395702652
-0.013398123665888008
a: -0.0026016899742030957
b: 0.0122344649602108
c: -0.10544865487274657
discriminant: -0.0009476966998398828
-0.013398123665888008
a: -0.009326661048839543
b: 0.060587609803016536
c: -0.10105663152437738
discriminant: -9.922533421877775e-05
-0.013398123665888008
a: -0.00965905831748074
b: 0.06280057488352848
c: -0.0196729712376692
discriminant: 0.003183822699850596
-0.013398123665888008
a: -0.009650021984756256
b: 0.06281761765706857
c: -0.1131390667135258
discriminant: -0.0004211248363716622
-0.013398123665888008
a: -0.008555593591932134
b: 0.05445673739246023
c: -0.017378208984345056
discriminant: 0.002370812673728496
-0.013398123665888008
a: -0.00844235415154493
b: 0.05449153742425202
c: -0.109665723563377
discriminant: -0.0007340198555711597
-0.013398123665888008
a: -0.0029150675421836802
b: 0.006923952116803592
c: -0.010455282215786954
discriminant: -7.397030241065434e-05
-0.013398123665888008
a: -0.0029442391659072363
b: 0.013058548311924698
c: -0.059474056572003664
discriminant: -0.0005298977028438321
-0.013398123665888008
a: 0.0018065040718453478
b: -0.021875992686893247
c: -0.0039359718516157605
discriminant: 0.0005070004527434571
-0.013398123665888008
a: 0.0029528529291493128
b: -0.02257103173064129
c: -0.11137899015588382
discriminant: 0.0018249945826955918
-0.013398123665888008
a: -0.008183435805706168
b: 0.05068482342441077
c: -0.008636599985059723
discriminant: 0.002286243079334502
-0.013398123665888008
a: -0.008221838894483826
b: 0.05233265509125576
c: -0.07736338595970127
discriminant: 0.00019442960613059394
-0.013398123665888008
a: -0.010910773604042787
b: 0.07116581198323106
c: -0.14126517731641497
discriminant: -0.0011006766761048632
-0.013398123665888008
a: -0.001742173916013682
b: 0.0016673373226564203
c: -0.10275394417825778
discriminant: -0.0007132809515120235
-0.013398123665888008
a: -0.0013393819227470807
b: 0.0048957027169035106
c: -0.1902873547180105
discriminant: -0.0009955018670543623
-0.013398123665888008
a: -0.007792972872492629
b: 0.046910758709181086
c: -0.0023789370377590435
discriminant: 0.0021264633154685123
-0.013398123665888008
a: -0.007809872130197119
b: 0.048741986108910694
c: -0.031460030331340705
discriminant: 0.0013929859534416676
-0.013398123665888008
a: -0.007869184001231213
b: 0.05075610909517414
c: -0.10195655578644847
discriminant: -0.0006330769799802122
-0.013398123665888008
a: -0.010078850156394235
b: 0.06614035498086297
c: -0.015011856977048987
discriminant: 0.0037693375288309727
-0.013398123665888008
a: -0.010069774051190814
b: 0.06583805290002838
c: -0.09613991058635396
discriminant: 0.00046222050204184663
-0.013398123665888008
a: -0.004275154677833936
b: 0.01855764942235448
c: -0.0038408309750439518
discriminant: 0.00027870576604409905
-0.013398123665888008
a: -0.004394422318162426
b: 0.02364503197335728
c: -0.06621772260126912
discriminant: -0.0006048670152065341
-0.013398123665888008
a: -0.010928293215710793
b: 0.07241415271572813
c: -0.034756898154705396
discriminant: 0.003724475216323923
-0.013398123665888008
a: -0.0022835992557982705
b: 0.0012546176403393644
c: -0.006651425262576116
discriminant: -5.918269369501582e-05
-0.013398123665888008
a: -0.002368151192872079
b: 0.008220219635337242
c: -0.05059351710840165
discriminant: -0.00041168038071423736
-0.013398123665888008
a: -0.007125644916193434
b: 0.04415611030318849
c: -0.01414138529930209
discriminant: 0.0015466961160437304
-0.013398123665888008
a: -0.006877521868614301
b: 0.04401513861060826
c: -0.12616919905739576
discriminant: -0.0015335932757401028
-0.013398123665888008
a: -0.010288671856861107
b: 0.06761112268803238
c: -0.017058527014784608
discriminant: 0.003869225563870089
-0.013398123665888008
a: -0.010323299625688927
b: 0.06749432589256316
c: -0.11613637509634922
discriminant: -0.00024015836255252172
-0.013398123665888008
a: -0.005315280865637836
b: 0.03030575309815641
c: -0.001673704779285079
discriminant: 0.0008828538268941745
-0.013398123665888008
a: -0.004813967614463578
b: 0.029599465756885587
c: -0.09720514351373921
discriminant: -0.0009956412782446571
-0.013398123665888008
a: -0.00177243710150114
b: 0.0037945060285290017
c: -0.016203865968819398
discriminant: -0.00010048305692300592
-0.013398123665888008
a: -0.0011457832063983915
b: 0.004927778476636571
c: -0.11987994477798469
discriminant: -0.000525142709327523
-0.013398123665888008
a: 0.0031926896776358765
b: -0.028618987281206987
c: -0.017299942476656116
discriminant: 0.001039979824077545
-0.013398123665888008
a: 0.00420877921612809
b: -0.027343652210489067
c: -0.16017299716720934
discriminant: 0.0034442064420573603
-0.013398123665888008
a: -0.0020562257631595617
b: 0.005045326604926251
c: -0.0321919342694893
discriminant: -0.00023932021789307563
-0.013398123665888008
a: -0.01138471083882154
b: 0.07703243390453604
c: -0.0016055055698915854
discriminant: 0.005860883006603381
-0.013398123665888008
a: -0.011338755945047367
b: 0.07530913465562844
c: -0.056910591013300316
discriminant: 0.0030902845538267032
-0.013398123665888008
a: -0.012253739237952978
b: 0.08464711576603748
c: -0.0047094279348004475
discriminant: 0.006934301800017047
-0.013398123665888008
a: -0.012232448106532115
b: 0.08225576440749738
c: -0.034126367157566784
discriminant: 0.005096214716984122
-0.013398123665888008
a: -0.011974061515387359
b: 0.08050761756435838
c: -0.02470955664651764
discriminant: 0.005297981480675583
-0.013398123665888008
a: -0.012104047633424191
b: 0.08001195410655845
c: -0.13268472194903136
discriminant: -2.2175978844863817e-05
-0.013398123665888008
a: -0.011116230154149935
b: 0.07485641695772535
c: -0.00753565389052302
discriminant: 0.005268410907712555
-0.013398123665888008
a: -0.01110022387346969
b: 0.07351083041504275
c: -0.05185155856865398
discriminant: 0.0031015865551076356
-0.013398123665888008
a: -0.005261155423386012
b: 0.027535745077682194
c: -0.011442858377679888
discriminant: 0.0005174066313320248
-0.013398123665888008
a: -0.005306966615358235
b: 0.031639087840483
c: -0.09391399348144602
discriminant: -0.0009925618331062206
-0.013398123665888008
a: -0.00396059557398778
b: 0.0161668813692179
c: -0.007234125918450629
discriminant: 0.00014676226482922147
-0.013398123665888008
a: -0.004102457553254676
b: 0.02186963820055253
c: -0.07550446203169658
discriminant: -0.0007607343272423917
-0.013398123665888008
a: -0.009187595831640907
b: 0.05887432956261961
c: -0.009952684418970903
discriminant: 0.003100421713922447
-0.013398123665888008
a: -0.009194191378579311
b: 0.05944056440779784
c: -0.07055380723474658
discriminant: 0.0009384398723029487
-0.013398123665888008
a: -0.006973339113799128
b: 0.041569547901421575
c: -0.01758443752114902
discriminant: 0.0012375383288870411
-0.013398123665888008
a: -0.006926494759980351
b: 0.043489949043078
c: -0.10216302524357046
discriminant: -0.0009391509682838035
-0.013398123665888008
a: -0.0024007652181047045
b: 0.007719544885024965
c: -0.008952792333585813
discriminant: -2.6382836525633986e-05
-0.013398123665888008
a: -0.0018787661688984894
b: 0.009430112724373357
c: -0.10244207287807161
discriminant: -0.0006809317771862295
-0.013398123665888008
a: -0.007909035240554427
b: 0.050052885358441906
c: -0.02421059561916572
discriminant: 0.0017393615169181511
-0.013398123665888008
a: -0.007691561373767276
b: 0.049679058312554564
c: -0.13590532765407215
discriminant: -0.0017132878398707914
-0.013398123665888008
a: -0.0059269049874536486
b: 0.03470933224248808
c: -0.017921050939914585
discriminant: 0.0007798722799346601
-0.013398123665888008
a: -0.005526407205120305
b: 0.034369433170224464
c: -0.11288014474343677
discriminant: -0.001314028644458082
-0.013398123665888008
a: -0.00890459079886177
b: 0.05643626351253296
c: -0.010235459751763654
discriminant: 0.0028204815163453607
-0.013398123665888008
a: -0.00892234485440421
b: 0.05735607878216289
c: -0.05803507898824456
discriminant: 0.0012184838197228532
-0.013398123665888008
a: -0.009687139598260916
b: 0.06297569242226489
c: -0.04323012449674413
discriminant: 0.0022908328326630744
-0.013398123665888008
a: -0.009688020349582533
b: 0.06305604646519807
c: -0.11795505648045712
discriminant: -0.0005949389542540852
-0.013398123665888008
a: -0.0016417855701353129
b: 0.006610181139901722
c: -0.020773618030467622
discriminant: -9.272881058538558e-05
-0.013398123665888008
a: -0.0009703455813229907
b: 0.007179228353377851
c: -0.17403192273338142
discriminant: -0.0006239431091839788
-0.013398123665888008
a: -0.009581184838707376
b: 0.062138064121490685
c: -0.01592704523494859
discriminant: 0.003250739155444504
-0.013398123665888008
a: -0.009580706375222679
b: 0.062295712760983855
c: -0.09518511375873262
discriminant: 0.00023299332354066423
-0.013398123665888008
a: -0.010201135811432045
b: 0.06718974788982418
c: -0.009019695544051465
discriminant: 0.004146417664607583
-0.013398123665888008
a: -0.010199752220568787
b: 0.06683435945817677
c: -0.06598070924296795
discriminant: 0.0017748840617221196
-0.013398123665888008
a: -0.005759403311156779
b: 0.03456243013712817
c: -0.01577260314683171
discriminant: 0.0008311984458261679
-0.013398123665888008
a: -0.005216677241182301
b: 0.03304774203608263
c: -0.1284928092981671
discriminant: -0.0015890688020018405
-0.013398123665888008
a: -0.010229706785656887
b: 0.06713953115434187
c: -0.006402924675790622
discriminant: 0.004245716475608902
-0.013398123665888008
a: -0.010264928185707725
b: 0.06705757594833721
c: -0.09790537468223992
discriminant: 0.00047675193163501314
-0.013398123665888008
a: -0.01025865804691022
b: 0.06754425189366024
c: -0.015748109646497754
discriminant: 0.00391600807687955
-0.013398123665888008
a: -0.01026478774909587
b: 0.06720134470211508
c: -0.08974798002864193
discriminant: 0.0008310448661560739
-0.013398123665888008
a: -0.003927063782411576
b: 0.018140298488160803
c: -0.024198914145232342
discriminant: -5.105228801414736e-05
-0.013398123665888008
a: -0.0036685450497973195
b: 0.0208869441819778
c: -0.10885881593752
discriminant: -0.0011611494440764902
-0.013398123665888008
a: -0.004359315137850813
b: 0.019017935582325354
c: -0.003213697192501419
discriminant: 0.0003056437985345164
-0.013398123665888008
a: -0.004524826859289861
b: 0.02500662454622954
c: -0.0634786660725889
discriminant: -0.0005235886217524793
-0.013398123665888008
a: -0.008002730640234391
b: 0.05062551976864452
c: -0.010854935686260392
discriminant: 0.0022154667461885776
-0.013398123665888008
a: -0.007792500893930648
b: 0.05020742057844441
c: -0.11658756687744909
discriminant: -0.0011132497953140817
-0.013398123665888008
a: -0.0023890360497789073
b: 0.004601902883403883
c: -0.019196141450662396
discriminant: -0.00016226358562086956
-0.013398123665888008
a: -0.002277561441794972
b: 0.009887073618226855
c: -0.0930586982417082
discriminant: -0.0007500333870235552
-0.013398123665888008
a: -0.01058880122669782
b: 0.07007189249474857
c: -0.030307501918802493
discriminant: 0.003626389663811752
-0.013398123665888008
a: -0.010608789597481589
b: 0.06957597155302493
c: -0.11335972260741267
discriminant: 3.037803366366231e-05
-0.013398123665888008
a: 0.022163558507270146
b: -0.1629860108575742
c: -0.009887803675129425
discriminant: 0.027441035396313818
-0.013398123665888008
a: 0.025047601383947057
b: -0.16261323950802004
c: -0.14955071133765918
discriminant: 0.041426612080378365
-0.013398123665888008
a: 0.0015568108251925146
b: -0.016162057173774586
c: -0.022329260437993992
discriminant: 0.00040026182956200655
-0.013398123665888008
a: 0.0021807739338737045
b: -0.013136462631502144
c: -0.18629982979271975
discriminant: 0.0017976779012571363
-0.013398123665888008
a: -0.005941797842076028
b: 0.03165092839766925
c: -0.01613066653398365
discriminant: 0.0006184006300228974
-0.013398123665888008
a: -0.005992545427337197
b: 0.03552288276563463
c: -0.05865966581052484
discriminant: -0.00014420764850693298
-0.013398123665888008
a: -0.005227171467939232
b: 0.030314377203415427
c: -0.01863867761424609
discriminant: 0.0005292512099297335
-0.013398123665888008
a: -0.004693448030152575
b: 0.02921141472972151
c: -0.13009869477317448
discriminant: -0.0015891391003225168
-0.013398123665888008
a: 0.0015782584041888646
b: -0.022995876244518265
c: -0.011759981975107081
discriminant: 0.0006030514857944887
-0.013398123665888008
a: 0.002421186804230195
b: -0.021537295669209894
c: -0.11398518583922124
discriminant: 0.0015677728160695629
-0.013398123665888008
a: -0.0015471725157752032
b: -0.004741888654020476
c: -0.0023050667307645822
discriminant: 8.220164435661076e-06
-0.013398123665888008
a: -0.0015111257054600136
b: 0.001600767299131542
c: -0.04526915814383947
discriminant: -0.0002710670981967925
-0.013398123665888008
a: -0.005350789001242646
b: 0.031704878247984035
c: -0.022890715451491683
discriminant: 0.0005152657508458241
-0.013398123665888008
a: -0.004767844737725778
b: 0.030193715231446275
c: -0.1404267964904381
discriminant: -0.0017664722112528254
-0.013398123665888008
a: 0.0036845705737209456
b: -0.03350007601976143
c: -0.003730101724775836
discriminant: 0.0011772303855381741
-0.013398123665888008
a: 0.004920568959446548
b: -0.0334925419207705
c: -0.12871473477834783
discriminant: 0.0036551492786095034
-0.013398123665888008
a: -0.0018117532170575552
b: 0.001142539535946105
c: -0.016823627147945053
discriminant: -0.00012061564584026515
-0.013398123665888008
a: -0.001654354901683544
b: 0.006442832968292941
c: -0.1019645805340893
discriminant: -0.000633232317761386
-0.013398123665888008
a: -0.005598762985189761
b: 0.02984687696011979
c: -0.01370865065411675
discriminant: 0.0005838301208358646
-0.013398123665888008
a: -0.005667020693386466
b: 0.03379438832156334
c: -0.0875275581246383
discriminant: -0.0008420212505070314
-0.013398123665888008
a: -0.008780309133969261
b: 0.055795639248356656
c: -0.02095363058612465
discriminant: 0.002377235943032086
-0.013398123665888008
a: -0.008760295481301304
b: 0.05643727137402547
c: -0.09668617831761395
discriminant: -0.00020283236393494773
-0.013398123665888008
a: -0.006752528468751434
b: 0.0404352959805384
c: -0.017926149478955322
discriminant: 0.0011508258222667866
-0.013398123665888008
a: -0.006561065838538882
b: 0.04135226208746256
c: -0.10681437193931209
discriminant: -0.0010932549274338334
-0.013398123665888008
a: -0.00019198326199623347
b: -0.016590736675530793
c: -0.0032791528140843074
discriminant: 0.00027273437362147437
-0.013398123665888008
a: -0.000537312637193821
b: -0.005532938247451824
c: -0.05035889672301974
discriminant: -7.762048076755277e-05
-0.013398123665888008
a: -0.011144224248818849
b: 0.07485096952346873
c: -0.018224955083012473
discriminant: 0.004790255693124277
-0.013398123665888008
a: -0.011115538742862658
b: 0.07344669693386248
c: -0.08667419272876431
discriminant: 0.001540695901362946
-0.013398123665888008
a: 0.00854187685175206
b: -0.06843453841916453
c: -0.017188256659016354
discriminant: 0.005270565935354605
-0.013398123665888008
a: 0.009788332344744854
b: -0.06557570044980068
c: -0.15617596672349954
discriminant: 0.010414981555687696
-0.013398123665888008
a: -0.006034376795106242
b: 0.033210919800186645
c: -0.008744220129243141
discriminant: 0.0008919015178176066
-0.013398123665888008
a: -0.0059779759461944144
b: 0.035657395979266725
c: -0.0679655172882182
discriminant: -0.0003537350220562895
-0.013398123665888008
a: -0.0009194800961572127
b: 0.0023262460813360114
c: -0.10303831208293623
discriminant: -0.0003735552875766492
-0.013398123665888008
a: -0.005891199199367347
b: 0.0317085747507866
c: -0.0029067358669314647
discriminant: 0.0009369370726780656
-0.013398123665888008
a: -0.005967848187669608
b: 0.03534633684123971
c: -0.062077536868636485
discriminant: -0.00023251373549156257
-0.013398123665888008
a: -0.009036164673827552
b: 0.058256515190009274
c: -0.014968640857529913
discriminant: 0.002852785147155687
-0.013398123665888008
a: -0.008938281450932138
b: 0.058007030249323265
c: -0.11869137999685708
discriminant: -0.0008787722824998775
-0.013398123665888008
a: -0.006959768362958433
b: 0.04246313456887977
c: -0.000731097464707342
discriminant: 0.001782764721394355
-0.013398123665888008
a: -0.00668032587633054
b: 0.042315227509615694
c: -0.10044205940996476
discriminant: -0.0008933642750027313
-0.013398123665888008
a: -0.0026513017577858558
b: 0.015528976315703352
c: -0.10566023803459512
discriminant: -0.0008793995939031003
-0.013398123665888008
a: -0.0024794581660068354
b: 0.007417660812073915
c: -0.013260361363810369
discriminant: -7.649235314782758e-05
-0.013398123665888008
a: -0.0010330276012465375
b: 4.012570041077301e-05
c: -0.010769496856880889
discriminant: -4.449913994694971e-05
-0.013398123665888008
a: -0.0002986183828917995
b: 0.0004893431376385843
c: -0.13259749504027318
discriminant: -0.00015814474147136516
-0.013398123665888008
a: -0.011450744080869062
b: 0.0775394275868097
c: -0.006218807295002571
discriminant: 0.0057275229471968414
-0.013398123665888008
a: -0.01141804402189621
b: 0.07577976164864432
c: -0.06009005251138533
discriminant: 0.002998128816113134
-0.013398123665888008
a: -0.005145898074276449
b: 0.027707373062398663
c: -0.07869172996999774
discriminant: -0.0008520599648374396
-0.013398123665888008
a: 0.0020658960769922366
b: -0.02478147089068586
c: -0.029494641975295166
discriminant: 0.0008578527601021219
-0.013398123665888008
a: -0.0059473652818250785
b: 0.034782913460164995
c: -0.03595906145301708
discriminant: 0.00035440437416657414
-0.013398123665888008
a: -0.007103665636192644
b: 0.04366293220384159
c: -0.04408974171792868
discriminant: 0.0006536565160362305
-0.013398123665888008
a: -0.007451566688514616
b: 0.04593734471156044
c: -0.09788528340629721
discriminant: -0.000807355229355977
-0.013398123665888008
a: -0.0006906061390345788
b: -0.006476864681223202
c: -0.007941652405029087
discriminant: 2.0011560478909264e-05
-0.013398123665888008
a: 0.0008073611650465176
b: -0.012434284439985066
c: -0.07044138960372803
discriminant: 0.0003820979990463008
-0.013398123665888008
a: -0.008431630585472928
b: 0.05303539357311824
c: -0.0019430455169169303
discriminant: 0.00274722080341794
-0.013398123665888008
a: -0.008383467868322038
b: 0.053565961006113064
c: -0.08236188684643986
discriminant: 0.00010739925070240913
-0.013398123665888008
a: -0.008182024171067507
b: 0.05163420959494821
c: -0.10118956718002636
discriminant: -0.0006456503376122986
-0.013398123665888008
a: 0.0004963324483036064
b: -0.00930245630084664
c: -0.10042919505763825
discriminant: 0.0002859207662856335
-0.013398123665888008
a: 0.007654020756627125
b: -0.06486913294527807
c: -0.035935832187749095
discriminant: 0.005308218830958964
-0.013398123665888008
a: -0.002580489623947744
b: 0.009576704576205547
c: -0.021284228185131426
discriminant: -0.00012798164940195484
-0.013398123665888008
a: 0.0017041308451891286
b: -0.018040920049124526
c: -0.1748594564577982
discriminant: 0.0015174083695098607
-0.013398123665888008
a: -0.004852820183686291
b: 0.025869489481643637
c: -0.08211886894221931
discriminant: -0.0009248019326162939
-0.013398123665888008
a: -0.005023190311989208
b: 0.03000858110266222
c: -0.07986424978447204
discriminant: -0.0007041783633715286
-0.013398123665888008
a: -0.0011696892680423052
b: 0.0002105809141996623
c: -0.061954923944345874
discriminant: -0.0002898276942388893
-0.013398123665888008
a: 0.0006899981594815389
b: -0.008743829117758312
c: -0.09861920083338604
discriminant: 0.00034864281589886456
-0.013398123665888008
a: 0.008090639281569369
b: -0.0660670289203674
c: -0.08028363386010884
discriminant: 0.006963035997467578
-0.013398123665888008
a: -0.006301112385996243
b: 0.0374173063739649
c: -0.026756015355174245
discriminant: 0.0007256841772655776
-0.013398123665888008
a: -0.005870520437864995
b: 0.03418643233224321
c: -0.03473617909442894
discriminant: 0.0003530343583783084
-0.013398123665888008
a: -0.0007245918510821415
b: -0.000764988943341427
c: -0.15780127720299475
discriminant: -0.0004567808701231418
-0.013398123665888008
a: 0.0022471178935031463
b: -0.025651205929494963
c: -0.14209407858709133
discriminant: 0.0019351929518529383
-0.013398123665888008
a: -0.00641477650770227
b: 0.03787539601753335
c: -0.08882770436982124
discriminant: -0.0008446938614136248
-0.013398123665888008
a: -0.004102074749595921
b: 0.02164751173784532
c: -0.0411427287898134
discriminant: -0.0002064674311525157
-0.013398123665888008
a: -0.01028207931460672
b: 0.06759554258388634
c: -0.014485016611640478
discriminant: 0.003973413018512858
-0.013398123665888008
a: -0.0018987319846195429
b: 0.005677743655429376
c: -0.12018223497493341
discriminant: -0.0008805386411031017
-0.013398123665888008
a: 0.0012282002402078263
b: -0.01795973044245415
c: -0.12117259126301605
discriminant: 0.0009178487403489786
-0.013398123665888008
a: -0.009281955403541375
b: 0.06000414039797553
c: -0.039348995549907784
discriminant: 0.002139554377426391
-0.013398123665888008
a: -0.008531305759561033
b: 0.05419486502482009
c: -0.004356180732644099
discriminant: 0.0027884277559620868
-0.013398123665888008
a: -0.00845610948081217
b: 0.05445223133341015
c: -0.11575400531947688
discriminant: -0.0009502686701088289
-0.013398123665888008
a: -0.004628427053283987
b: 0.025689489140781188
c: -0.11359565020702467
discriminant: -0.001443126869899996
-0.013398123665888008
a: -0.008072138513710197
b: 0.05063383684101666
c: -0.009574154643980926
discriminant: 0.002254649823491113
-0.013398123665888008
a: 0.004302441516046448
b: -0.041207561475627486
c: -0.049640907979620175
discriminant: 0.0025523715363106555
-0.013398123665888008
a: -0.00909754070034867
b: 0.05875775056428079
c: -0.07671405091014416
discriminant: 0.0006608364495996138
-0.013398123665888008
a: -0.008608246031176651
b: 0.05501036070961907
c: -0.060663675214921775
discriminant: 0.0009373084197806425
-0.013398123665888008
a: -0.007636503226160883
b: 0.046355900168622455
c: -0.04666619504921421
discriminant: 0.0007234032842593819
-0.013398123665888008
a: -0.007574402825408147
b: 0.04731869835303463
c: -0.10494214554139314
discriminant: -0.000940437120947003
-0.013398123665888008
a: -0.008050064726560934
b: 0.05049836012033213
c: -0.022570030999975454
discriminant: 0.001823323533121594
-0.013398123665888008
a: 0.020763798832095316
b: -0.1605782294354044
c: -0.04459805110780524
discriminant: 0.02948946761463327
-0.013398123665888008
a: -0.0019444458526753743
b: 0.006724990180540638
c: -0.13534658851179227
discriminant: -0.0010074709578936918
-0.013398123665888008
a: -0.004516431564827983
b: 0.021550601758679566
c: -0.05428331780981421
discriminant: -0.0005162391238381328
-0.013398123665888008
a: -0.00433815753551076
b: 0.023613869387440742
c: -0.12283285230779761
discriminant: -0.0015738582279422992
-0.013398123665888008
a: 0.0015241801957740792
b: -0.02634830764888954
c: -0.009496392766602635
discriminant: 0.000752130171105123
-0.013398123665888008
a: 0.0018265127270397138
b: -0.020961201641514104
c: -0.08679904800659977
discriminant: 0.0010735302377721558
-0.013398123665888008
a: -0.0003552025159087443
b: -0.0028434609487938134
c: -0.16707170819604122
discriminant: -0.00022929189418630628
-0.013398123665888008
a: -0.004657847534675397
b: 0.027907369861235
c: -0.16996089156070215
discriminant: -0.0023877863864172283
-0.013398123665888008
a: 0.0010511829337512008
b: -0.009255750957762515
c: -0.10025445154812129
discriminant: 0.0005072119997920088
-0.013398123665888008
a: -0.0040003324491216545
b: 0.018925787991577986
c: -0.00721741655947461
discriminant: 0.00024269718845538048
-0.013398123665888008
a: -0.0029402308941694124
b: 0.008600845781179853
c: -0.0672115970322823
discriminant: -0.0007164959080114871
-0.013398123665888008
a: -0.002844279949304744
b: 0.012429991009378819
c: -0.13440569735542607
discriminant: -0.0013746450437482018
-0.013398123665888008
a: -0.0030705059732359765
b: 0.013654579505180509
c: -0.1048904551920965
discriminant: -0.0011018195353477958
-0.013398123665888008
a: -5.456009679001214e-05
b: -0.010361986760354422
c: -0.014779349281064058
discriminant: 0.00010414531871268733
-0.013398123665888008
a: -0.0007916662051326295
b: -0.0019464067897528997
c: -0.13380418826203389
discriminant: -0.000419924516417829
-0.013398123665888008
a: -0.0017594350098570494
b: 0.003510690634877675
c: -0.03534918840583534
discriminant: -0.0002364534498712206
-0.013398123665888008
a: -0.0033944645400116854
b: 0.019583374524690986
c: -0.09172166652211067
discriminant: -0.0008618752204660105
-0.013398123665888008
a: -0.0040163483816924184
b: 0.019003856112215473
c: -0.003952000124840871
discriminant: 0.0002976561099103779
-0.013398123665888008
a: -0.0037555614426077527
b: 0.02096011051034806
c: -0.10351563489889559
discriminant: -0.0011157110759274118
-0.013398123665888008
a: 0.007383073827053508
b: -0.06229817932674536
c: -0.04934297087493544
discriminant: 0.005338274334690521
-0.013398123665888008
a: -0.0018998987964159398
b: 0.004495565669384152
c: -0.03989006669098194
discriminant: -0.00028293824809284726
-0.013398123665888008
a: -0.0033345664228620862
b: 0.014479799898124299
c: -0.09269674179411547
discriminant: -0.0010267491656917758
-0.013398123665888008
a: 0.0024161528641840043
b: -0.01890534941463004
c: -0.09989880131769968
discriminant: 0.0013228953362184879
-0.013398123665888008
a: 0.0012185085448887367
b: -0.02405338111323896
c: -0.01298230726724603
discriminant: 0.0006418413523287623
-0.013398123665888008
a: 0.0015491327839278366
b: -0.018746949672302032
c: -0.08824060684837176
discriminant: 0.0008982337897858248
-0.013398123665888008
a: 0.003060908587318143
b: -0.03720661712972856
c: -0.0064864638938481045
discriminant: 0.0014637502503742456
-0.013398123665888008
a: 0.0035774814908586623
b: -0.03228918385562471
c: -0.09468352664015589
discriminant: 0.0023975056502398583
-0.013398123665888008
a: -0.0013031273612645654
b: 0.0006063464456901313
c: -0.04867008825464103
discriminant: -0.00025332563870693445
-0.013398123665888008
a: 0.0020169704681620194
b: -0.0174579429025421
c: -0.21188858451620318
discriminant: 0.002014271840427756
-0.013398123665888008
a: -0.0017565833889221557
b: 0.005133213680299717
c: -0.05479760889844165
discriminant: -0.00035867639548700593
-0.013398123665888008
a: -0.003468078172674754
b: 0.015413606346956668
c: -0.02569630982961635
discriminant: -0.00011888798433457788
-0.013398123665888008
a: -0.0021017409015763574
b: 0.004314020589327561
c: -0.07740113943656068
discriminant: -0.0006320977886845955
-0.013398123665888008
a: 0.0050411004603695
b: -0.05568992643697723
c: -0.014294712933958231
discriminant: 0.0033896122423648424
-0.013398123665888008
a: 0.0054531656415332565
b: -0.04980567546289158
c: -0.07333100559797734
discriminant: 0.004080149789058772
-0.013398123665888008
a: -0.007850310959034748
b: 0.048750112455717046
c: -0.006847243799873115
discriminant: 0.0021615614922797515
-0.013398123665888008
a: -0.006400848118087
b: 0.035340133464466635
c: -0.07933096654187322
discriminant: -0.0007822168382959733
-0.013398123665888008
a: -0.006338298266643325
b: 0.03743648513549528
c: -0.10680342513865748
discriminant: -0.001306317438411532
-0.013398123665888008
a: 0.0004010790525811204
b: -0.014371094755563363
c: -0.08984230956164863
discriminant: 0.0003506638380761239
-0.013398123665888008
a: -0.008915574537454745
b: 0.0561168213629536
c: -0.09294412534990226
discriminant: -0.00016550346962071688
-0.013398123665888008
a: -0.008849848980564002
b: 0.05621598110739297
c: -0.050958323620570956
discriminant: 0.0013563426584877218
-0.013398123665888008
a: -0.007588714486943307
b: 0.045070290882190556
c: -0.07876548711983411
discriminant: -0.000359584052504457
-0.013398123665888008
a: -0.007534653680425432
b: 0.04633939918617136
c: -0.09074802521118464
discriminant: -0.0005876798516598301
-0.013398123665888008
a: -0.009744177583554763
b: 0.06344771949605502
c: -0.013940224348111596
discriminant: 0.0034822690228397063
-0.013398123665888008
a: -0.0025946237619739404
b: 0.0061984317046607645
c: -0.02145067808270429
discriminant: -0.00018420520065800887
-0.013398123665888008
a: -0.002552511305765506
b: 0.010298764818367459
c: -0.09420607184206331
discriminant: -0.0008557836970104531
-0.013398123665888008
a: 4.0466559730447174e-05
b: -0.017632396463642452
c: -0.004638490859358302
discriminant: 0.0003116522201207483
-0.013398123665888008
a: 0.00046514753337276345
b: -0.014547678908201855
c: -0.032689554143363275
discriminant: 0.00027245682352350446
-0.013398123665888008
a: 0.0013382917768169304
b: -0.027303977820165554
c: -0.005270983132334872
discriminant: 0.0007737236583310705
-0.013398123665888008
a: 0.0010549637392898237
b: -0.01669556597674826
c: -0.07102815216430114
discriminant: 0.000578470423292345
-0.013398123665888008
a: -0.009268950172386325
b: 0.05957178336057171
c: -0.0008393395270985815
discriminant: 0.003517678187741324
-0.013398123665888008
a: -0.00923204310711025
b: 0.05966333163640278
c: -0.04874426193116321
discriminant: 0.001759676632464293
-0.013398123665888008
a: -0.007273947121334927
b: 0.04473228473615271
c: -0.009354690362101459
discriminant: 0.0017287952055946912
-0.013398123665888008
a: -0.005921393269545756
b: 0.03240809520818239
c: -0.011299831065306742
discriminant: 0.000782641660554169
-0.013398123665888008
a: -0.005994739653695626
b: 0.035808012247151036
c: -0.08419368921571146
discriminant: -0.0007366632482372869
-0.013398123665888008
a: -0.0012647904873751203
b: -0.0015622529137772206
c: -0.02530167437736952
discriminant: -0.00012556463410203373
-0.013398123665888008
a: -0.008327970106976458
b: 0.05248806012404714
c: -0.003073088740253138
discriminant: 0.002652626090925931
-0.013398123665888008
a: -0.005954532707296685
b: 0.032839656146401615
c: -0.01638518215110618
discriminant: 0.0006881786036787908
-0.013398123665888008
a: -0.005958911624920977
b: 0.03553461261703121
c: -0.08900964985449022
discriminant: -0.0008588938551497966
-0.013398123665888008
a: -0.007710323351872595
b: 0.046502434137727366
c: -0.010987701095876767
discriminant: 0.0018236014673619326
-0.013398123665888008
a: -0.0076568709240002865
b: 0.04760125985612943
c: -0.045590948896983674
discriminant: 0.0008695438958631703
-0.013398123665888008
a: -0.007425568413805367
b: 0.043450127730906216
c: -0.08252496259108766
discriminant: -0.0005632654224353348
-0.013398123665888008
a: -0.007325690304299259
b: 0.04443059193415171
c: -0.0765728212995499
discriminant: -0.0002697175986487027
-0.013398123665888008
a: 0.002557760562915092
b: -0.0372041055965768
c: -0.009131116237832804
discriminant: 0.001477566309275327
-0.013398123665888008
a: 0.0028724645805073496
b: -0.03102107229327511
c: -0.06112456911850417
discriminant: 0.001664619565391307
-0.013398123665888008
a: -0.008768345718384163
b: 0.05553258445244103
c: -0.011807703591724894
discriminant: 0.0026697318270376942
-0.013398123665888008
a: -0.008795417190221737
b: 0.0564679392596861
c: -0.0880988128328829
discriminant: 8.916491292173612e-05
-0.013398123665888008
a: -0.004589063537890538
b: 0.021290484821646638
c: -0.014055325805985897
discriminant: 0.00019528161126307868
-0.013398123665888008
a: -0.004657041868259986
b: 0.025799519595174625
c: -0.07909748119156024
discriminant: -0.0008078259149902118
-0.013398123665888008
a: 0.005462033187000646
b: -0.06213849407815358
c: -0.0015848066421425555
discriminant: 0.0038958175121981747
-0.013398123665888008
a: 0.006132087260410395
b: -0.057087327058974124
c: -0.036009318764952725
discriminant: 0.004142212050156774
-0.013398123665888008
a: -0.0045212358622979095
b: 0.02321034266462646
c: -0.008574087568864575
discriminant: 0.00038365811779804643
-0.013398123665888008
a: 0.0028690588747200003
b: -0.040276325340479424
c: -0.0013245696661600137
discriminant: 0.0016373834563556701
-0.013398123665888008
a: 0.003357141055103611
b: -0.03538384064750702
c: -0.04349195090693192
discriminant: 0.0018360506347930175
-0.013398123665888008
a: -0.0023794725783431135
b: 0.007527530636763938
c: -0.03143867887434626
discriminant: -0.0002425661796359478
-0.013398123665888008
a: -0.005892420546710927
b: 0.034596735554928044
c: -0.034819127168712716
discriminant: 0.00037625834966776835
-0.013398123665888008
a: 0.0027638074093874615
b: -0.0382498892641044
c: -0.008087874116883942
discriminant: 0.0015524673343579967
-0.013398123665888008
a: 0.0032383453791384846
b: -0.033768611285728695
c: -0.059711441976970314
discriminant: 0.0019137841969979136
-0.013398123665888008
a: -0.006951466446094564
b: 0.04006969460415371
c: -0.06370598556099727
discriminant: -0.00016581965850048438
-0.013398123665888008
a: -0.006786481678309352
b: 0.04079382768374087
c: -0.08389953798447547
discriminant: -0.0006133943323103062
-0.013398123665888008
a: 0.000965600194464511
b: -0.025150416223364225
c: -0.011168191948840778
discriminant: 0.0006756794694789329
-0.013398123665888008
a: 0.0009899139444194379
b: -0.017007703413304806
c: -0.059760519812772306
discriminant: 0.0005258930629486096
-0.013398123665888008
a: -0.007539113728286206
b: 0.04680450107530819
c: -0.03085592064955156
discriminant: 0.0012601561410367495
-0.013398123665888008
a: 0.010333097399916506
b: -0.090413136766549
c: -0.016893242939293396
discriminant: 0.008872773398735375
-0.013398123665888008
a: 0.001452295127418994
b: -0.02182337192753464
c: -0.015351611007614285
discriminant: 0.0005654398417450671
-0.013398123665888008
a: 0.0031954089627876468
b: -0.03688575779972675
c: -0.004766948577703878
discriminant: 0.0014214885293014738
-0.013398123665888008
a: 0.0036858910243550477
b: -0.039386199445746506
c: -0.020967679415326512
discriminant: 0.0018604110322141467
-0.013398123665888008
a: -0.007051064896529381
b: 0.04089155997254603
c: -0.0003008186508559607
discriminant: 0.0016636353096712417
-0.013398123665888008
a: -0.007018173646735211
b: 0.0427756172123073
c: -0.03422366165941826
discriminant: 0.0008690030264821946
-0.013398123665888008
a: 0.002291745179035711
b: -0.030229745060243896
c: -0.0011135781516339316
discriminant: 0.0009240456358492865
-0.013398123665888008
a: -0.00039770690445995426
b: -0.008056610653947388
c: -0.012865862480483936
discriminant: 4.444160586801562e-05
-0.013398123665888008
a: 0.00243907194144319
b: -0.034578835303336636
c: -0.018342064779417577
discriminant: 0.0013746463131417233
-0.013398123665888008
a: 0.0022724043445431627
b: -0.025099285692676804
c: -0.09560616255121734
discriminant: 0.001498997578868555
-0.013398123665888008
a: 0.0027848299605020884
b: -0.037823830292164295
c: -0.015595837388813871
discriminant: 0.0016043691588483954
-0.013398123665888008
a: 0.0030641453016400644
b: -0.031738318843580415
c: -0.07848082307183446
discriminant: 0.0019692274641543986
-0.013398123665888008
a: 0.001143138092768484
b: -0.019778539357836827
c: -0.021182445392517124
discriminant: 0.00048804846003419876
-0.013398123665888008
a: -0.003558689232723621
b: 0.013108740832257562
c: -0.014586068324169643
discriminant: -3.5790050964677636e-05
-0.013398123665888008
a: -0.0035295349484434245
b: 0.017438649743005505
c: -0.07931767439876569
discriminant: -0.0008157115104195731
-0.013398123665888008
a: -0.001500469115547143
b: -0.004296584007766682
c: -0.006746885566267902
discriminant: -2.2033339537466726e-05
-0.013398123665888008
a: -0.0011897532748771497
b: -0.0013211604349476075
c: -0.04584322291836018
discriminant: -0.00021642303349729796
-0.013398123665888008
a: 0.0026738390309089784
b: -0.02690429502979025
c: -0.09406887327057223
discriminant: 0.0017299411908279416
-0.013398123665888008
a: 0.002807990996202679
b: -0.020423969130707292
c: -0.27201909441655336
discriminant: 0.0034724471867196376
-0.013398123665888008
a: -0.004078486180549809
b: 0.02205966984276944
c: -0.09669794890562844
discriminant: -0.0010908959596244768
-0.013398123665888008
a: -0.003945117892504084
b: 0.02486240037699748
c: -0.27626498696641855
discriminant: -0.0037414528201083768
-0.013398123665888008
a: 0.0031939911397291174
b: -0.034074225538543
c: -0.057348711691701415
discriminant: 0.001893737954124192
-0.013398123665888008
a: 0.0034711408667709815
b: -0.02700605656810276
c: -0.2034837795080774
discriminant: 0.0035546105424615784
-0.013398123665888008
a: -0.0022389960811863866
b: 0.01970132902413542
c: -0.10413972976868935
discriminant: -0.0005445314220743783
-0.013398123665888008
a: -0.002871647521219857
b: 0.03663761497458824
c: -0.4194617335379395
discriminant: -0.0034758701584170592
-0.013398123665888008
a: -0.0034135645051185538
b: 0.022842974691423865
c: -0.0597458227399329
discriminant: -0.00029398338658352826
-0.013398123665888008
a: -0.003565513772652803
b: 0.03302186487176394
c: -0.26245400400037944
discriminant: -0.00265268990419587
-0.013398123665888008
a: 0.011115658704299779
b: -0.08771229865359273
c: -0.23177736423927875
discriminant: 0.01799887964016104
-0.013398123665888008
a: 0.011005013918531235
b: -0.07531444100824233
c: -0.41532792047106637
discriminant: 0.023955023206538893
-0.013398123665888008
a: 0.0024862970977494276
b: -0.02958970296974084
c: -0.03987688735165629
discriminant: 0.0012721336789963053
-0.013398123665888008
a: 0.0028135860355143934
b: -0.02301919328431501
c: -0.17263641966276622
discriminant: 0.0024727929377980993
-0.013398123665888008
a: 0.002725591302106237
b: -0.025301651342726078
c: -0.09807523042555022
discriminant: 0.001709425540668651
-0.013398123665888008
a: 0.0025453782505036214
b: -0.014434441880472548
c: -0.3029341817849044
discriminant: 0.0032926814229983638
-0.013398123665888008
a: 0.022697298009414404
b: -0.17025519346569384
c: -0.382914543405224
discriminant: 0.06375133291726971
-0.013398123665888008
a: 0.02394386860220843
b: -0.15467133053692095
c: -0.55270972109436
discriminant: 0.07685925623824795
-0.013398123665888008
a: 0.009443552744408366
b: -0.07241169596126476
c: -0.2775217579671342
discriminant: 0.015726619148320905
-0.013398123665888008
a: 0.008219457231715119
b: -0.04921978388715387
c: -0.5073121555839285
discriminant: 0.01910190938970336
-0.013398123665888008
a: -0.0004563144809850428
b: -0.003976457738569333
c: -0.0870724118283227
discriminant: -0.00014311739349959996
-0.013398123665888008
a: -0.00047820196625271167
b: 0.0015547528894093166
c: -0.2663529299543851
discriminant: -0.0005070647227383043
-0.013398123665888008
a: -0.004403426272768149
b: 0.02795965348298904
c: -0.05015515613828636
discriminant: -0.00010167590612765443
-0.013398123665888008
a: -0.004318872551233447
b: 0.03713169809026204
c: -0.11497131667162452
discriminant: -0.0006074228519426209
-0.013398123665888008
a: -0.006623051892765162
b: 0.04094275957898959
c: -0.06735944725679233
discriminant: -0.00010819089665591052
-0.013398123665888008
a: -0.006407949988941883
b: 0.04197303672309573
c: -0.20365188342622587
discriminant: -0.003458228524837968
-0.013398123665888008
a: -0.0016987094878305907
b: 0.005942634591143622
c: -0.03378910575652916
discriminant: -0.00019427659225185252
-0.013398123665888008
a: -0.001132136627395604
b: 0.008859912140638956
c: -0.16452231362161285
discriminant: -0.0006665489059597368
-0.013398123665888008
a: 0.002548646161028836
b: -0.02666920544826812
c: -0.10485766807899
discriminant: 0.001780226892057749
-0.013398123665888008
a: 0.0029791948419976948
b: -0.021427948110609885
c: -0.2750129489000678
discriminant: 0.00373642559561362
-0.013398123665888008
a: -0.004801447694832148
b: 0.03643091534187404
c: -0.09667450201189476
discriminant: -0.0005294986666894385
-0.013398123665888008
a: -0.005259994892526593
b: 0.04926514404110802
c: -0.41945576761563086
discriminant: -0.006398286363805038
-0.013398123665888008
a: 0.0017949783795063942
b: -0.016426297443572047
c: -0.11275418118472491
discriminant: 0.001079388517406813
-0.013398123665888008
a: 0.0009352898089099665
b: -0.0002457075862010438
c: -0.3680183511751153
discriminant: 0.0013768756256016547
-0.013398123665888008
a: -0.0029358991570513394
b: 0.014054797664128246
c: -0.0813375030510387
discriminant: -0.0007576574891972363
-0.013398123665888008
a: -0.0029646734415883875
b: 0.017978162312425966
c: -0.25982908105689895
discriminant: -0.0027580191837148858
-0.013398123665888008
a: -0.008226024862532596
b: 0.05310628731458085
c: -0.04746476827295343
discriminant: 0.001258492296708158
-0.013398123665888008
a: -0.008220656509078366
b: 0.05563671286587422
c: -0.13788327820572388
discriminant: -0.0014385204553800553
-0.013398123665888008
a: -0.0078099373893866135
b: 0.049989246976624296
c: -0.09589804877376185
discriminant: -0.0004969062134597534
-0.013398123665888008
a: -0.007641069577818846
b: 0.05029971847258953
c: -0.25497732590933453
discriminant: -0.005263136273735904
-0.013398123665888008
a: 0.0018369667107282555
b: -0.025227584715901585
c: -0.045102859741985246
discriminant: 0.0009678408382166813
-0.013398123665888008
a: 0.002231637918712891
b: -0.02006350636717555
c: -0.16841802391325833
discriminant: 0.0019059364811837808
-0.013398123665888008
a: 0.003264459925859931
b: -0.032085473907953965
c: -0.08225061255235111
discriminant: 0.0021034929501163226
-0.013398123665888008
a: 0.003783749491667953
b: -0.026885465038849227
c: -0.25066050502045323
discriminant: 0.0045165744641646735
-0.013398123665888008
a: -0.009075846450346925
b: 0.05943520007810557
c: -0.10878747080545959
discriminant: -0.00041681051468335983
-0.013398123665888008
a: -0.009128427413971671
b: 0.061070474151713336
c: -0.3583587281091444
discriminant: -0.00935540373771505
-0.013398123665888008
a: 0.013027710723136073
b: -0.1001478142572711
c: -0.09890439851630684
discriminant: 0.015183576272973728
-0.013398123665888008
a: 0.012228006454373911
b: -0.07832734192604379
c: -0.30283094520131437
discriminant: 0.020947247503222674
-0.013398123665888008
a: -0.006383221141920595
b: 0.04223051122334541
c: -0.027867129384452127
discriminant: 0.0010718878803792167
-0.013398123665888008
a: -0.0063669809432570085
b: 0.04725884161311084
c: -0.18970128596485336
discriminant: -0.0025978997799851813
-0.013398123665888008
a: -0.002464350674639869
b: 0.015323982627613503
c: -0.06640722589275805
discriminant: -0.00041977832414772146
-0.013398123665888008
a: -0.0021975461474685242
b: 0.021091182805281966
c: -0.24811682053883322
discriminant: -0.0017361546602631872
-0.013398123665888008
a: -0.004122701018500671
b: 0.033740033426615565
c: -0.07818047803735328
discriminant: -0.00015086909009672704
-0.013398123665888008
a: -0.004455702595406998
b: 0.04986663732258076
c: -0.27335472121231275
discriminant: -0.0023852678452280286
-0.013398123665888008
a: -0.003698539146033055
b: 0.031195408181130133
c: -0.07727200373927079
discriminant: -0.00017002063130110157
-0.013398123665888008
a: -0.004116297864409388
b: 0.0471332348603844
c: -0.33364963074107334
discriminant: -0.0032720632215176896
-0.013398123665888008
a: 0.006635566152525832
b: -0.05621789434385413
c: -0.09137803760004004
discriminant: 0.00558583169798898
-0.013398123665888008
a: 0.007296169706491082
b: -0.049816623741999994
c: -0.26559767032507564
discriminant: 0.010233078706413686
-0.013398123665888008
a: -0.00013220276950694654
b: -0.006062129720973211
c: -0.08610746180533824
discriminant: -8.78516294961059e-06
-0.013398123665888008
a: 0.00038555557506871237
b: -0.0022774501399934755
c: -0.236992735727794
discriminant: 0.0003706822611827043
-0.013398123665888008
a: -0.0042449768593095325
b: 0.02996495593716582
c: -0.042571845452446855
discriminant: 0.00017503258910133443
-0.013398123665888008
a: -0.004320873615261607
b: 0.04131306665746469
c: -0.17491981400504064
discriminant: -0.0013164561598392706
-0.013398123665888008
a: -0.006828544643506625
b: 0.0443036421847415
c: -0.041966702244225385
discriminant: 0.0008165267115718355
-0.013398123665888008
a: -0.006815454979574537
b: 0.04890512679096366
c: -0.1691267712474539
discriminant: -0.0022189921546710615
-0.013398123665888008
a: -0.00680106672317108
b: 0.04791788442374728
c: -0.11458093292391103
discriminant: -0.0008209666324272332
-0.013398123665888008
a: -0.006984079594595911
b: 0.05594143323344601
c: -0.3403119348080984
discriminant: -0.006377618606550678
-0.013398123665888008
a: 0.003151200714517464
b: -0.030068983191902682
c: -0.0996875464641288
discriminant: 0.002160685620779948
-0.013398123665888008
a: 0.0033378507414948324
b: -0.02254883904202351
c: -0.2780477404774063
discriminant: 0.0042207775690369775
-0.013398123665888008
a: -0.008138933644562711
b: 0.05365464010313649
c: -0.13336378669912896
discriminant: -0.0014629356375302008
-0.013398123665888008
a: -0.008244179675268267
b: 0.0565381984251635
c: -0.4451925143640433
discriminant: -0.011484420432843326
-0.013398123665888008
a: 0.0007153769277488536
b: -0.007892582841217993
c: -0.09781071026372945
discriminant: 0.00034217896554308884
-0.013398123665888008
a: 0.0008718448374617641
b: 0.00036317599732624273
c: -0.31069223702259274
discriminant: 0.001083633588355411
-0.013398123665888008
a: -0.007437221563588016
b: 0.05213738469335917
c: -0.13375283621116763
discriminant: -0.0012606910279796837
-0.013398123665888008
a: -0.0075672617708986735
b: 0.05867968586016092
c: -0.35041381545681427
discriminant: -0.007163386746157204
-0.013398123665888008
a: -0.003082910118968993
b: 0.026628079629154755
c: -0.05710059505743603
discriminant: 4.910615529724743e-06
-0.013398123665888008
a: -0.0034836621048618707
b: 0.043657280741910734
c: -0.2874176000868639
discriminant: -0.0020991050449937973
-0.013398123665888008
a: -0.0017254679229442762
b: 0.0032735357767638557
c: -0.06313620764756289
discriminant: -0.00042504196780712255
-0.013398123665888008
a: -0.0014779233832595221
b: 0.007378524956934335
c: -0.2088426924706791
discriminant: -0.0011801713639610731
-0.013398123665888008
a: -0.004108722240769519
b: 0.021465103217838663
c: -0.07271507200122007
discriminant: -0.0007343134781298119
-0.013398123665888008
a: -0.003995785706420715
b: 0.024609338061568342
c: -0.23363028098087646
discriminant: -0.0031285266294932106
-0.013398123665888008
a: -0.0007848064691038477
b: -0.0007715690313144785
c: -0.0033140837570863058
discriminant: -9.808338716769705e-06
-0.013398123665888008
a: -0.0002711053326155781
b: 0.004159917801724838
c: -0.12391901523678406
discriminant: -0.00011707550725554571
-0.013398123665888008
a: -0.0006886602542994554
b: -0.003931961524631045
c: -0.0731303971308378
discriminant: -0.00018598767010939281
-0.013398123665888008
a: -0.0004308974342496375
b: 0.000128486882636919
c: -0.2293723564526967
discriminant: -0.00039532733065403145
-0.013398123665888008
a: -0.0020819054624346316
b: 0.01375403922698322
c: -0.09905765595017824
discriminant: -0.0006357411050171926
-0.013398123665888008
a: -0.0025429442053785728
b: 0.0263537464386763
c: -0.3740104847996829
discriminant: -0.0031098312289346937
-0.013398123665888008
a: -0.0033982682425963374
b: 0.026118042065705532
c: -0.08556290869687333
discriminant: -0.0004809107401290547
-0.013398123665888008
a: -0.003961456399754426
b: 0.04190933009286538
c: -0.36723954423748173
discriminant: -0.0040628218222171315
-0.013398123665888008
a: 0.0072205445941711174
b: -0.057741098052069756
c: -0.10679931242178309
discriminant: 0.006418631196131926
-0.013398123665888008
a: 0.0069630194038631825
b: -0.0450293612117528
c: -0.3075588213830135
discriminant: 0.010593795535615362
-0.013398123665888008
a: -0.004142515268580447
b: 0.03184731457848772
c: -0.042246574776091506
discriminant: 0.00031422312164041766
-0.013398123665888008
a: -0.004392020726434723
b: 0.046240178426040626
c: -0.2170551280429317
discriminant: -0.0016750883837019217
-0.013398123665888008
a: 0.0032306254575820443
b: -0.03342487209471939
c: -0.06899937693942715
discriminant: 0.0020088666493396023
-0.013398123665888008
a: 0.0034469444357394996
b: -0.026406858813323414
c: -0.22638935142164562
discriminant: 0.0038187282531608586
-0.013398123665888008
a: -0.0057674580710745695
b: 0.036920681749162694
c: -0.046628622197680825
discriminant: 0.000287422247074551
-0.013398123665888008
a: -0.005589003468685618
b: 0.039808920105564055
c: -0.21490799867438481
discriminant: -0.003219736080186501
-0.013398123665888008
a: 0.006267364708748547
b: -0.05304679371058332
c: -0.0851201519277508
discriminant: 0.004947878467754381
-0.013398123665888008
a: 0.006378743977586521
b: -0.04330971026157157
c: -0.27205329308348125
discriminant: 0.008817164222296626
-0.013398123665888008
a: -0.005879833197672699
b: 0.0350769356601053
c: -0.10621024754888053
discriminant: -0.0012676027425806056
-0.013398123665888008
a: -0.005704858438738313
b: 0.03661490200584285
c: -0.2607811461250399
discriminant: -0.004610227039643657
-0.013398123665888008
a: -0.009757920904269224
b: 0.06356932293272824
c: -0.11270154571886704
discriminant: -0.0003578722575288563
-0.013398123665888008
a: -0.009757317616451612
b: 0.06357960844235842
c: -0.31274467859702837
discriminant: -0.008163830038021513
-0.013398123665888008
a: -0.004349182708194155
b: 0.026020419131983774
c: -0.111288241831344
discriminant: -0.001258989376188736
-0.013398123665888008
a: -0.004056383609864175
b: 0.028345542751560066
c: -0.292679661924956
discriminant: -0.003945414140411397
-0.013398123665888008
a: -0.005546654187137057
b: 0.03168320602197014
c: -0.048702087803186744
discriminant: -7.670901311284447e-05
-0.013398123665888008
a: -0.005339450099906015
b: 0.03341747420608232
c: -0.16642656677285117
discriminant: -0.002437777812015084
-0.013398123665888008
a: -0.008557903593480388
b: 0.05754336975043063
c: -0.15604116596350182
discriminant: -0.0020303016174849126
-0.013398123665888008
a: -0.00864482093750518
b: 0.060911188240388395
c: -0.42464728263639706
discriminant: -0.010973826027103192
-0.013398123665888008
a: 0.007745725491460142
b: -0.06515492439550907
c: -0.08082354998889996
discriminant: 0.006749312298821805
-0.013398123665888008
a: 0.008161458174425698
b: -0.056427230101344095
c: -0.2519244213160513
discriminant: 0.011408314807659435
-0.013398123665888008
a: -0.008524891994860465
b: 0.05515580731411918
c: -0.03189585456007216
discriminant: 0.001954528219638672
-0.013398123665888008
a: -0.008464233825836599
b: 0.0559992187267387
c: -0.183217400611838
discriminant: -0.0030672671809571753
-0.013398123665888008
a: -0.004175823697241892
b: 0.023971504391749526
c: -0.11568848310137281
discriminant: -0.0013577458141270562
-0.013398123665888008
a: -0.004335199505057525
b: 0.028852300938020964
c: -0.3295631399746751
discriminant: -0.004882432575795536
-0.013398123665888008
a: -0.006349239000066646
b: 0.03874924526363304
c: -0.09619027896759624
discriminant: -0.0009414362740922221
-0.013398123665888008
a: -0.00615760359530713
b: 0.039922090546273714
c: -0.24620335434257445
discriminant: -0.00447031732592117
-0.013398123665888008
a: 0.0002803064499327188
b: -0.01240094247391843
c: -0.04727699255751383
discriminant: 0.00020679155803060323
-0.013398123665888008
a: 0.0006135535099078982
b: -0.007286495850924751
c: -0.17859277638312154
discriminant: 0.0004913979209617861
-0.013398123665888008
a: 0.006922757198339291
b: -0.05703577061435089
c: -0.09692008022193288
discriminant: 0.005936895861652882
-0.013398123665888008
a: 0.006891778766152556
b: -0.046925362740065646
c: -0.28088780735604113
discriminant: 0.009945256173916797
-0.013398123665888008
a: -0.005026313681002186
b: 0.03075128309396416
c: -0.048387846331329754
discriminant: -2.720856411245079e-05
-0.013398123665888008
a: -0.005025476965760577
b: 0.037913823865881754
c: -0.15946743597972934
discriminant: -0.0017681416650870121
-0.013398123665888008
a: -0.00020889690268192929
b: -0.007160601799375471
c: -0.09287138830194641
discriminant: -2.632796332697023e-05
-0.013398123665888008
a: 0.000316865466073484
b: -0.004289071581793966
c: -0.2440619179053588
discriminant: 0.0003277353085052322
-0.013398123665888008
a: -0.0025170180593188348
b: 0.014873232173508541
c: -0.011026116204554515
discriminant: 0.00011020130084304256
-0.013398123665888008
a: -0.0023820914460795503
b: 0.022732721737245373
c: -0.16859748317927792
discriminant: -0.001089681852464567
-0.013398123665888008
a: -0.001967483266241064
b: 0.00993940290664487
c: -0.058570234263959686
discriminant: -0.0003621520931160182
-0.013398123665888008
a: -0.0014602735747399828
b: 0.013285431191546987
c: -0.21663388972397046
discriminant: -0.0010888762962828686
-0.013398123665888008
a: -0.0040373314731326024
b: 0.028266539563841855
c: -0.072976290303996
discriminant: -0.0003795206356329015
-0.013398123665888008
a: -0.004348397608456083
b: 0.04037507866944719
c: -0.2994079945589111
discriminant: -0.0035776330524063538
-0.013398123665888008
a: 0.0005159082461111946
b: -0.008429901363481263
c: -0.02068821791895681
discriminant: 0.00011375612588496403
-0.013398123665888008
a: 0.0005262861705731389
b: 0.005373755160560656
c: -0.15023981711488277
discriminant: 0.00034515379659365384
-0.013398123665888008
a: -0.0047694961398340565
b: 0.02660378837058626
c: -0.08126038445582429
discriminant: -0.0008425228042670005
-0.013398123665888008
a: -0.0045643314978216585
b: 0.02896734196521783
c: -0.22329098611859022
discriminant: -0.00323758942395309
-0.013398123665888008
a: -0.001419160289615239
b: 0.010724750266425262
c: -0.071004854908023
discriminant: -0.000288048813544243
-0.013398123665888008
a: -0.0021251354173628875
b: 0.02865852742420648
c: -0.3409235814285779
discriminant: -0.00207672391590829
-0.013398123665888008
a: -0.0031924432766648383
b: 0.01826384502297984
c: -0.051471955700079675
discriminant: -0.0003237171606226135
-0.013398123665888008
a: -0.0031345149204883606
b: 0.02911916935989628
c: -0.12410747661117305
discriminant: -0.0007081409245172064
-0.013398123665888008
a: -0.0007177117625068851
b: 0.0035144812503704465
c: -0.08329076108989042
discriminant: -0.00022676345731025515
-0.013398123665888008
a: -0.0010350969768720209
b: 0.016080858536765844
c: -0.3233133612227549
discriminant: -0.001080048719856546
-0.013398123665888008
a: -0.0017249198821226103
b: 0.0037639841995165124
c: -0.010904904084941491
discriminant: -6.107276642081264e-05
-0.013398123665888008
a: -0.0010985938736893953
b: 0.005940386566114952
c: -0.11308947704149508
discriminant: -0.00046166943407121707
-0.013398123665888008
a: -0.00232825720708854
b: 0.014816858543242759
c: -0.0850146472410912
discriminant: -0.0005722045634981758
-0.013398123665888008
a: -0.00238355544671608
b: 0.02395327285867603
c: -0.2987939599364261
discriminant: -0.0022750086019671526
-0.013398123665888008
a: 0.0005726493406633844
b: -0.011612768038226806
c: -0.07795509723484384
discriminant: 0.0003134201216411954
-0.013398123665888008
a: 0.0010481275988969427
b: -0.006727394853061508
c: -0.22449105365975652
discriminant: 0.0009864389176939797
-0.013398123665888008
a: -0.0014178622188430207
b: 0.00760171817669536
c: -0.013064111377016574
discriminant: -1.6306320539015648e-05
-0.013398123665888008
a: -0.0013850749917251404
b: 0.019261480992835242
c: -0.15921081486332123
discriminant: -0.0005110710222801166
-0.013398123665888008
a: -0.002105433323482499
b: 0.016621233058965915
c: -0.04442930837599757
discriminant: -9.790639717596012e-05
-0.013398123665888008
a: -0.0022573054621865367
b: 0.03033661639306108
c: -0.2365213510211578
discriminant: -0.0012152934561554525
-0.013398123665888008
a: -0.006119055140781024
b: 0.03979813961873027
c: -0.029276539051840245
discriminant: 0.0008673128899541903
-0.013398123665888008
a: -0.006083158353577166
b: 0.04424026686669601
c: -0.20281548903964353
discriminant: -0.002977833733108902
-0.013398123665888008
a: 0.000994353146948429
b: -0.00816425134305443
c: -0.08422703898777051
discriminant: 0.00040166068509511657
-0.013398123665888008
a: 0.0018401366449963341
b: -0.004950891287487824
c: -0.25823588209430015
discriminant: 0.0019252685633192204
-0.013398123665888008
a: -0.007764025116217852
b: 0.05252650325961047
c: -0.06083464272862493
discriminant: 0.0008697467683571344
-0.013398123665888008
a: -0.007853340994503959
b: 0.05799323788056147
c: -0.21687989392913976
discriminant: -0.003449711407638144
-0.013398123665888008
a: -0.005564567303943838
b: 0.03497855440630514
c: -0.11212316322477134
discriminant: -0.0012721682840264345
-0.013398123665888008
a: -0.005648625644178374
b: 0.03934722581378411
c: -0.35239788231678115
discriminant: -0.0064140506807939725
-0.013398123665888008
a: -0.004516693930850083
b: 0.03912702360991423
c: -0.12895507254504068
discriminant: -0.0007988783974952846
-0.013398123665888008
a: -0.004769087229947471
b: 0.05321378580935715
c: -0.3667203917245411
discriminant: -0.004163979148375231
-0.013398123665888008
a: 0.0011496684150819024
b: -0.017837681413157364
c: -0.07419535958262868
discriminant: 0.0006593831240284699
-0.013398123665888008
a: 0.0016583873766380314
b: -0.013705189749697477
c: -0.2207832467141312
discriminant: 0.001652408823370714
-0.013398123665888008
a: -0.005037204099711761
b: 0.03294683323342981
c: -0.056996235896069725
discriminant: -6.291287238384922e-05
-0.013398123665888008
a: -0.0049949606223055765
b: 0.0408815636042688
c: -0.15921571279868785
discriminant: -0.0015098026207971639
-0.013398123665888008
a: -0.006483128942025986
b: 0.04140795624371731
c: -0.0670628696044343
discriminant: -2.4490083189683933e-05
-0.013398123665888008
a: -0.006483297107751482
b: 0.04766874504300957
c: -0.13354387273535206
discriminant: -0.0011909091614767109
-0.013398123665888008
a: -0.006860521143293035
b: 0.046499555734763935
c: -0.12945172836381935
discriminant: -0.0013902165943728197
-0.013398123665888008
a: -0.007143199461306629
b: 0.046738505463888205
c: -0.10570901742908434
discriminant: -0.000835914492420846
-0.013398123665888008
a: -0.007315072448964128
b: 0.05194185903955066
c: -0.34522334475673
discriminant: -0.007403378391392251
-0.013398123665888008
a: -0.005906307181722898
b: 0.0468293138421976
c: -0.13179367673205566
discriminant: -0.0009206711226217856
-0.013398123665888008
a: -0.0060263335964475685
b: 0.05693986735141154
c: -0.3400100077389999
discriminant: -0.004953906437067391
-0.013398123665888008
a: -0.009499972246219303
b: 0.06190168629933114
c: -0.13518665906522165
discriminant: -0.0013052592700140662
-0.013398123665888008
a: -0.009514128405903247
b: 0.06228852960502423
c: -0.42605339502912043
discriminant: -0.012334245911956308
-0.013398123665888008
a: -0.008534074045046853
b: 0.05548734733353885
c: -0.08920803994940474
discriminant: 3.3613640745909935e-05
-0.013398123665888008
a: -0.00852253696260117
b: 0.057651387391717754
c: -0.17062384425116306
discriminant: -0.0024929096091366567
-0.013398123665888008
a: -0.0044207996487733575
b: 0.030772665646973466
c: -0.04041176406864633
discriminant: 0.0002323477014164869
-0.013398123665888008
a: -0.004420308821785952
b: 0.039875603262691184
c: -0.1914952345995805
discriminant: -0.0017958085637584372
-0.013398123665888008
a: 9.791601848909391e-05
b: -0.009525774666449938
c: -0.08880794965961936
discriminant: 0.00012552326635937867
-0.013398123665888008
a: 0.0005735855193425956
b: -0.005662953752331681
c: -0.22934012564545225
discriminant: 0.0005582537454988189
-0.013398123665888008
a: -0.005723488505584141
b: 0.03297666351046612
c: -0.036763332513285896
discriminant: 0.00024580229201546925
-0.013398123665888008
a: -0.005450009235078903
b: 0.034220769179321105
c: -0.13762566076243454
discriminant: -0.0018291834453320447
-0.013398123665888008
a: -0.0066040713531043006
b: 0.04605792729944055
c: -0.06846447107469211
discriminant: 0.00031275565860130203
-0.013398123665888008
a: -0.006666939768976302
b: 0.053739118505163136
c: -0.19786834139992793
discriminant: -0.0023888123994902713
-0.013398123665888008
a: 0.0007732730901194428
b: -0.012403851936015134
c: -0.10406863298300018
discriminant: 0.0004757494364956693
-0.013398123665888008
a: 0.000719436643666159
b: -0.005519697607203791
c: -0.29252456407667304
discriminant: 0.0008722786239518829
-0.013398123665888008
a: 0.006610906369523176
b: -0.05563429584886395
c: -0.10206581786694835
discriminant: 0.005794165136387725
-0.013398123665888008
a: 0.006881573415972291
b: -0.04740866574529237
c: -0.27772149006696834
discriminant: 0.009892224880105105
-0.013398123665888008
a: 0.004002874731600494
b: -0.03966540291702622
c: -0.06432125575617775
discriminant: 0.002603223906054899
-0.013398123665888008
a: 0.004285833273681654
b: -0.03305504572408491
c: -0.2124855033977061
discriminant: 0.004735345810368884
-0.013398123665888008
a: 0.022184830089285217
b: -0.16523357006291117
c: -0.09168950642676943
discriminant: 0.0354385971599282
-0.013398123665888008
a: 0.020129397003625704
b: -0.1616971907980566
c: -0.013079568426604182
discriminant: 0.02719911681396394
-0.013398123665888008
a: 0.021086168806683077
b: -0.14968277985320888
c: -0.14301574064076605
discriminant: 0.03446755078124019
-0.013398123665888008
a: 0.01556732999786727
b: -0.12214464383598644
c: -0.05419770134379143
discriminant: 0.018294168025598603
-0.013398123665888008
a: 0.0029657369232301903
b: -0.025696919099682358
c: -0.02361986479583178
discriminant: 0.0009405328718024329
-0.013398123665888008
a: 0.0036497884207351682
b: -0.022066417860731935
c: -0.19227412227804652
discriminant: 0.0032939662575941575
-0.013398123665888008
a: 0.01673002343909908
b: -0.13902024025286935
c: -0.003138261903167461
discriminant: 0.01953663998075761
-0.013398123665888008
a: 0.018036224224868294
b: -0.13218263895124377
c: -0.11504332073783663
discriminant: 0.025772038553719116
-0.013398123665888008
a: 0.013953540797963643
b: -0.11032090298834779
c: -0.06014574766768421
discriminant: 0.015527686211784679
-0.013398123665888008
a: 0.010210789246947509
b: -0.08160477088595361
c: -0.05123526074958529
discriminant: 0.008751948429454651
-0.013398123665888008
a: 0.019519006386704927
b: -0.1499182385571215
c: -0.074771544469454
discriminant: 0.028313343268242246
-0.013398123665888008
a: 0.018891141256197126
b: -0.14480940608165077
c: -0.06324650754812022
discriminant: 0.02574895892193114
-0.013398123665888008
a: 0.014320016504578363
b: -0.11264996994749932
c: -0.04559142094911628
discriminant: 0.015301495331006599
-0.013398123665888008
a: 0.008290048609959634
b: -0.0630440921135745
c: -0.07289778874613717
discriminant: 0.006391862399481049
-0.013398123665888008
a: 0.00911029269178303
b: -0.07096590920902757
c: -0.07000028880843423
discriminant: 0.007587052748080662
-0.013398123665888008
a: 0.0188326641812301
b: -0.13299928957703266
c: -0.11113998226367172
discriminant: 0.026061058880313785
-0.013398123665888008
a: -0.0003458077982322477
b: -0.004084569707930336
c: -0.0038210707081955952
discriminant: 1.139828550497869e-05
-0.013398123665888008
a: 0.00041789817271011605
b: -0.0030661353008579473
c: -0.13445945173171714
discriminant: 0.00023416262241232182
-0.013398123665888008
a: 0.0035637175539008827
b: -0.03348823587259658
c: -0.012126335547554157
discriminant: 0.0012943212812799088
-0.013398123665888008
a: 0.004266185359684083
b: -0.029707336384965144
c: -0.1551430375761923
discriminant: 0.0035300016573473507
-0.013398123665888008
a: 0.002880868099026636
b: -0.025057422627601078
c: -0.024420337760589272
discriminant: 0.0009092815168259632
-0.013398123665888008
a: 0.003403052623233453
b: -0.02022650704500617
c: -0.20012876504177812
discriminant: 0.003133306462681262
-0.013398123665888008
a: 0.012936613647701833
b: -0.10326475124780571
c: -0.05016359213845678
discriminant: 0.013259396892975624
-0.013398123665888008
a: 0.015557094790517166
b: -0.11971166780709164
c: -0.06956538440587334
discriminant: 0.018659824526519205
-0.013398123665888008
a: 0.0044231583240414785
b: -0.040350066157577524
c: -0.007996860694087116
discriminant: 0.0017696133627018893
-0.013398123665888008
a: 0.0054305371966373445
b: -0.03801409051097532
c: -0.13675205526443268
discriminant: 0.004415619568697054
-0.013398123665888008
a: 0.017048209341963116
b: -0.1318602112742886
c: -0.07023739928949391
discriminant: 0.0221768028641894
-0.013398123665888008
a: 0.021708777704078558
b: -0.1806871982033298
c: -0.017917598362467424
discriminant: 0.03420374023393646
-0.013398123665888008
a: 0.023024842045549675
b: -0.17106865575746605
c: -0.11562762497019896
discriminant: 0.03991371618682997
-0.013398123665888008
a: 0.007164983709881713
b: -0.046979473978474295
c: -0.1304685223117098
discriminant: 0.005946290323357101
-0.013398123665888008
a: 0.018892586532415635
b: -0.15739285317013652
c: -0.01768832395132036
discriminant: 0.02610922299249103
-0.013398123665888008
a: 0.02011083332944181
b: -0.14860598749045345
c: -0.12194903226084486
discriminant: 0.0318937261679511
-0.013398123665888008
a: 0.0029502898614141935
b: -0.02161413097498885
c: -0.09778390566108752
discriminant: 0.0016211341197295262
-0.013398123665888008
a: 0.013999892970269155
b: -0.10287849054896647
c: -0.09700532292851116
discriminant: 0.016016240371815996
-0.013398123665888008
a: 0.010612075256759893
b: -0.08563615568061611
c: -0.055255111356151465
discriminant: 0.00967903675988323
-0.013398123665888008
a: 0.017498534712762987
b: -0.1352928324486623
c: -0.0682973039786593
discriminant: 0.023084561489816594
-0.013398123665888008
a: 0.02087820897686459
b: -0.16227406281109047
c: -0.05242227446491243
discriminant: 0.03071080426650171
-0.013398123665888008
a: 0.03415166945061454
b: -0.2595890661508784
c: -0.052396682123503124
discriminant: 0.07454421993784832
-0.013398123665888008
a: 0.001678766498054967
b: -0.016217528721182733
c: -0.03479542501917643
discriminant: 0.0004966618130534948
-0.013398123665888008
a: 0.001921799650370459
b: -0.010054761921121064
c: -0.2226407556334563
discriminant: 0.0018125819426287907
-0.013398123665888008
a: 0.012008990197726008
b: -0.095147007550752
c: -0.056734922662473486
discriminant: 0.011778269566352409
-0.013398123665888008
a: 0.02136365696226444
b: -0.16285467644912588
c: -0.06757108295658198
discriminant: 0.032295907388762
-0.013398123665888008
a: 0.014379776185909486
b: -0.11191689543499228
c: -0.060230734202337266
discriminant: 0.01598980939317745
-0.013398123665888008
a: 0.005636887037132736
b: -0.04576780157841953
c: -0.017386019289579946
discriminant: 0.002486703768364673
-0.013398123665888008
a: 0.006324155774442511
b: -0.040158348135197475
c: -0.18182768763653334
discriminant: 0.0062123194078281645
-0.013398123665888008
a: 0.00907616967774224
b: -0.06838145688817476
c: -0.08472731863955263
discriminant: 0.0077520217274001536
-0.013398123665888008
a: 0.017932170439497446
b: -0.13475841321654342
c: -0.07947000377710312
discriminant: 0.023860108542874736
-0.013398123665888008
a: 0.006074180342807458
b: -0.054719312476296134
c: -0.019649267545883142
discriminant: 0.0034716159365896096
-0.013398123665888008
a: 0.004067211089773065
b: -0.031728393601290095
c: -0.07992877116019448
discriminant: 0.0023070396983370925
-0.013398123665888008
a: 0.008474491571933241
b: -0.06623463963850634
c: -0.07005009581152877
discriminant: 0.006761583274314462
-0.013398123665888008
a: 0.015554440083433551
b: -0.12078590861560512
c: -0.06760323272404711
discriminant: 0.018795357451507733
-0.013398123665888008
a: 0.025402942284525484
b: -0.1866002574862337
c: -0.08167132101200603
discriminant: 0.04311842350980449
-0.013398123665888008
a: 0.003132447826353052
b: -0.021634377002121258
c: -0.10598393027555153
discriminant: 0.0017960027963499325
-0.013398123665888008
a: 0.011861766313381292
b: -0.095780359495514
c: -0.04706664659374982
discriminant: 0.011407051517288155
-0.013398123665888008
a: 0.0065982086732133665
b: -0.05112704466605256
c: -0.024980672487221578
discriminant: 0.003273285455756085
-0.013398123665888008
a: 0.007092916809768066
b: -0.04348262938372485
c: -0.2062710508268789
discriminant: 0.007742992673236342
-0.013398123665888008
a: 0.00459911414729044
b: -0.03084812510243215
c: -0.12733307377305658
discriminant: 0.003294084186365872
-0.013398123665888008
a: 0.01612813490908293
b: -0.12048743747755997
c: -0.0753510565840999
discriminant: 0.01937831061443014
-0.013398123665888008
a: 0.015121845419376362
b: -0.11781543390164295
c: -0.06610623150170036
discriminant: 0.017879069321537284
-0.013398123665888008
a: 0.007230679246737202
b: -0.058134901951668094
c: -0.07020570478648047
discriminant: 0.005410206555338715
-0.013398123665888008
a: 0.02363683526478801
b: -0.18043172291419957
c: -0.06477116335633648
discriminant: 0.03867954790643609
-0.013398123665888008
a: 0.006938580172491323
b: -0.0612979562731131
c: -0.026745986250211184
discriminant: 0.004499756122818249
-0.013398123665888008
a: 0.01499617382091993
b: -0.11638836315712492
c: -0.06671296669546145
discriminant: 0.01754800805709232
-0.013398123665888008
a: 0.005312923280156416
b: -0.043880776228157614
c: -0.006249364344962038
discriminant: 0.0020583320956437555
-0.013398123665888008
a: 0.0067100851178174
b: -0.04398551381057042
c: -0.14332203184347592
discriminant: 0.005781537556892918
-0.013398123665888008
a: 0.004299912358968899
b: -0.0408966243216535
c: -0.00841865977276568
discriminant: 0.0018173318777179386
-0.013398123665888008
a: 0.005205410990176159
b: -0.03832955389013684
c: -0.13927525776652916
discriminant: 0.004369094531166937
-0.013398123665888008
a: 0.0015781487625317232
b: -0.01837608630847845
c: -0.004369183351612738
discriminant: 0.0003652614332151366
-0.013398123665888008
a: 0.0024932997684614985
b: -0.01736879659786633
c: -0.13648371178223828
discriminant: 0.0016628543231997355
-0.013398123665888008
a: 0.002678691844897522
b: -0.023954915958514955
c: -0.018502402375647375
discriminant: 0.0007720869359981511
-0.013398123665888008
a: 0.00354057266482113
b: -0.02177864237147059
c: -0.17698990290165717
discriminant: 0.0029808917121962276
-0.013398123665888008
a: 0.004895266132299229
b: -0.03370728121339825
c: -0.11258465864266964
discriminant: 0.003340708272678832
-0.013398123665888008
a: 0.020220165256031652
b: -0.15451953969054716
c: -0.07031078403889401
discriminant: 0.029563070836368936
-0.013398123665888008
a: 0.01591421960427674
b: -0.1221783256418274
c: -0.06544738172399434
discriminant: 0.019093719277762714
-0.013398123665888008
a: 0.004609415861569396
b: -0.04022172611159977
c: -0.008671551417150813
discriminant: 0.0017776703979830648
-0.013398123665888008
a: 0.00560800537533575
b: -0.03790686060183998
c: -0.1497955130310754
discriminant: 0.004797146249805117
-0.013398123665888008
a: 0.011623198036742432
b: -0.09478676317141166
c: -0.03773631773559594
discriminant: 0.01073899724938635
-0.013398123665888008
a: 0.007536242537775245
b: -0.05933639966744941
c: -0.06798897482317001
discriminant: 0.005570333942143707
-0.013398123665888008
a: 0.02240710598720881
b: -0.17111093058146415
c: -0.0606246532662168
discriminant: 0.034712642689150267
-0.013398123665888008
a: 0.02306215078345475
b: -0.189591075086062
c: -0.003971149588748668
discriminant: 0.036311108754686294
-0.013398123665888008
a: 0.024841420679919186
b: -0.1824912592044186
c: -0.10606937288794904
discriminant: 0.04384271533867332
-0.013398123665888008
a: 0.02386229545478638
b: -0.19359213853862428
c: -0.0205273732822846
discriminant: 0.03943723708864815
-0.013398123665888008
a: 0.02508297273064935
b: -0.18187903731755856
c: -0.13507086839605076
discriminant: 0.046631899850294936
-0.013398123665888008
a: 0.022451890663946275
b: -0.17224951293662222
c: -0.0613679385008844
discriminant: 0.035181199688878124
-0.013398123665888008
a: 0.005309595375811858
b: -0.03783687518555462
c: -0.12250497541701211
discriminant: 0.00403343652775969
-0.013398123665888008
a: 0.005139355390430771
b: -0.04417148711987243
c: -0.060920207973207074
discriminant: 0.0032034826713141173
-0.013398123665888008
a: 0.018818976924687317
b: -0.1453870623716338
c: -0.06658014101105214
discriminant: 0.026149278454371004
-0.013398123665888008
a: 0.00902972135187004
b: -0.06448292267537489
c: -0.09928792634681838
discriminant: 0.00774421655082544
-0.013398123665888008
a: 0.00882757137403898
b: -0.07169524085592552
c: -0.05777522158265569
discriminant: 0.007180267130076414
-0.013398123665888008
a: 0.02460292324780792
b: -0.1880779953372571
c: -0.0566129003284942
discriminant: 0.04094470369655228
-0.013398123665888008
a: 0.02053122183930057
b: -0.15580171840730556
c: -0.056768941379722326
discriminant: 0.028936318374866647
-0.013398123665888008
a: 0.014455154620903961
b: -0.11422599795570926
c: -0.049581291056220556
discriminant: 0.01591439952306454
-0.013398123665888008
a: 0.01682350500489794
b: -0.129664922390621
c: -0.07376960891156725
discriminant: 0.02177724563749823
-0.013398123665888008
a: 0.024430145592664522
b: -0.18544617585490158
c: -0.07038846537315091
discriminant: 0.041268685967648294
-0.013398123665888008
a: 0.022692717137307066
b: -0.17666703561697306
c: -0.04743369045083268
discriminant: 0.035516838754406144
-0.013398123665888008
a: 0.015646247946590957
b: -0.13483971343136908
c: -0.0031345928409626245
discriminant: 0.018377926785458975
-0.013398123665888008
a: 0.016790017171453134
b: -0.12736962401784052
c: -0.09417032952270266
discriminant: 0.022547506921356368
-0.013398123665888008
a: 0.013717586274507618
b: -0.10833176163941483
c: -0.06385167136550562
discriminant: 0.015239333822810314
-0.013398123665888008
a: 0.010240823578152803
b: -0.08374830300995531
c: -0.04615096491756565
discriminant: 0.008904273815776527
-0.013398123665888008
a: 0.0012454295985569307
b: -0.01861434891039232
c: -0.013268798608910837
discriminant: 0.00041259540345713806
-0.013398123665888008
a: 0.0017788852278437187
b: -0.015390167342480499
c: -0.1462806889148066
discriminant: 0.0012777234773469607
-0.013398123665888008
a: 0.006003414783048538
b: -0.05152126869087373
c: -0.053334783699811594
discriminant: 0.003935204443173786
-0.013398123665888008
a: 0.01230176227087076
b: -0.09522807070967956
c: -0.07250806053928749
discriminant: 0.012636293144992611
-0.013398123665888008
a: 0.0037788487899427705
b: -0.03621136142280065
c: -0.013270527838151636
discriminant: 0.0015118519683450999
-0.013398123665888008
a: 0.004696679589722091
b: -0.03383358103212017
c: -0.14491367112474218
discriminant: 0.003867163531230146
-0.013398123665888008
a: 0.0018085507593515477
b: -0.021083973754687152
c: -0.005611261593661321
discriminant: 0.0004851269549528821
-0.013398123665888008
a: 0.0026280087074130685
b: -0.01921986506521181
c: -0.13298796493748977
discriminant: 0.0017673773324724173
-0.013398123665888008
a: 0.008084491928433503
b: -0.06762231372899152
c: -0.04916700677312458
discriminant: 0.0061627383916723994
-0.013398123665888008
a: 0.0006442435593799452
b: -0.00453473870863455
c: -0.11621517837424611
discriminant: 0.00032004737583478675
-0.013398123665888008
a: 0.0066408493248113175
b: -0.04984153228316565
c: -0.12236019398715292
discriminant: 0.005734480786827308
-0.013398123665888008
a: 0.015540419985052728
b: -0.12067649325927599
c: -0.05812231539373747
discriminant: 0.018175796792245586
-0.013398123665888008
a: 0.010734905441398315
b: -0.0972525571464434
c: -0.005526212161509725
discriminant: 0.00969535333153389
-0.013398123665888008
a: 0.01157974032599499
b: -0.09110028742143139
c: -0.09164545701058435
discriminant: 0.012544184745226228
-0.013398123665888008
a: 0.002720015133551421
b: -0.018014211581048045
c: -0.11961138860027354
discriminant: 0.0016258909674381412
-0.013398123665888008
a: 0.015745337343563977
b: -0.123227748872969
c: -0.060055092355220885
discriminant: 0.018967428845626886
-0.013398123665888008
a: 0.012348457354175807
b: -0.07855900152531523
c: -0.2951695688600019
discriminant: 0.02075107205392725
-0.013398123665888008
a: 0.013908650852444103
b: -0.08084775812454478
c: -0.5440543558137215
discriminant: 0.03680460831282268
-0.013398123665888008
a: 0.019546001010079472
b: -0.12594504320170802
c: -0.3639239856779565
discriminant: 0.04431518827369404
-0.013398123665888008
a: 0.020268337576842925
b: -0.11985649813554244
c: -0.6100565563027281
discriminant: 0.0638249090417552
-0.013398123665888008
a: 0.011153703374847378
b: -0.06979302962701542
c: -0.2473261262992491
discriminant: 0.015905475982884908
-0.013398123665888008
a: 0.012243735847590288
b: -0.07059182773100944
c: -0.4805952210696308
discriminant: 0.028520329887967787
-0.013398123665888008
a: 0.00493484735976182
b: -0.02988350989091884
c: -0.27669065143879334
discriminant: 0.006354728686294674
-0.013398123665888008
a: 0.005672191603061474
b: -0.027821926166339023
c: -0.5293793118763576
discriminant: 0.012785023126243366
-0.013398123665888008
a: 0.01780184762991725
b: -0.11440403121019249
c: -0.37158310039865905
discriminant: 0.039547745297739384
-0.013398123665888008
a: 0.01767297197235511
b: -0.1026576819374494
c: -0.6202278251423291
discriminant: 0.054383675541631114
-0.013398123665888008
a: 0.005017814301484117
b: -0.0267030469516919
c: -0.40226360197226485
discriminant: 0.008786988936276042
-0.013398123665888008
a: 0.005047770399958699
b: -0.016846060865542772
c: -0.6804888584373076
discriminant: 0.014023595835171678
-0.013398123665888008
a: 0.0038692904193054854
b: -0.018962602262684897
c: -0.39610856743319267
discriminant: 0.006490216624469075
-0.013398123665888008
a: 0.003912211792856246
b: -0.009770475583948834
c: -0.6745701086627006
discriminant: 0.010651706730010686
-0.013398123665888008
a: 0.01623062843420185
b: -0.10287200522550499
c: -0.3302883255438053
discriminant: 0.032025797811341135
-0.013398123665888008
a: 0.016716226536785582
b: -0.09754417106514146
c: -0.5798301416601813
discriminant: 0.04828515331217785
-0.013398123665888008
a: 0.004579816568263539
b: -0.02590068357331282
c: -0.3243294670666198
discriminant: 0.0066123232769560334
-0.013398123665888008
a: 0.005452610147003386
b: -0.023504979005213145
c: -0.5760372265917227
discriminant: 0.013116109745098376
-0.013398123665888008
a: 0.02501030919238984
b: -0.15926484932851737
c: -0.4036059832270128
discriminant: 0.06574253396125973
-0.013398123665888008
a: 0.027195326608800446
b: -0.16242850145867366
c: -0.6294839229098929
discriminant: 0.09485910160020435
-0.013398123665888008
a: 0.004288354917669799
b: -0.02541089996271892
c: -0.3017793142508439
discriminant: 0.005822261062189813
-0.013398123665888008
a: 0.005406216250960885
b: -0.025953736455458565
c: -0.5479301783006957
discriminant: 0.012522512573283863
-0.013398123665888008
a: -0.0020335143322487937
b: 0.014556138613927627
c: -0.2308535105838424
discriminant: -0.0016658945183408937
-0.013398123665888008
a: -0.00145412310813037
b: 0.014438218534279998
c: -0.4812819273885539
discriminant: -0.00259091053412125
-0.013398123665888008
a: 0.00186994131940033
b: -0.00927858727139158
c: -0.32016798710556926
discriminant: 0.0024808735747045736
-0.013398123665888008
a: 0.0031778573229627642
b: -0.012120605983347382
c: -0.5602618923770083
discriminant: 0.007268638519272564
-0.013398123665888008
a: 0.007449962486632957
b: -0.04770317045095537
c: -0.26899095834598585
discriminant: 0.010291482666757074
-0.013398123665888008
a: 0.008420438695730047
b: -0.04731932703973665
c: -0.5105806354787664
discriminant: 0.019436370472596925
-0.013398123665888008
a: 0.003190478683959089
b: -0.018385095455977746
c: -0.30838599302600256
discriminant: 0.004273607483649484
-0.013398123665888008
a: 0.004319784157710676
b: -0.019207376895629513
c: -0.5572244245249823
discriminant: 0.00999728029262063
-0.013398123665888008
a: 0.002806713185085097
b: -0.016091050154346476
c: -0.2752384837568628
discriminant: 0.003348983820682562
-0.013398123665888008
a: 0.003159761675951807
b: -0.011637123220679113
c: -0.5285508075674982
discriminant: 0.006815800979033906
-0.013398123665888008
a: 0.01696077249677823
b: -0.10771349071034056
c: -0.3098059945352972
discriminant: 0.0326203920468118
-0.013398123665888008
a: 0.018480710427103003
b: -0.10927620485235434
c: -0.5405790445961024
discriminant: 0.05190242809149599
-0.013398123665888008
a: 0.008357080477482253
b: -0.052740553817691826
c: -0.2604901659153661
discriminant: 0.011489315137586524
-0.013398123665888008
a: 0.00890265486986918
b: -0.05018854226960037
c: -0.515982726333816
discriminant: 0.020893354300603958
-0.013398123665888008
a: 0.014209706558464048
b: -0.09013094749176193
c: -0.3142540735266314
discriminant: 0.025985420374224417
-0.013398123665888008
a: 0.01586292374502763
b: -0.09247515751146945
c: -0.5630259598714055
discriminant: 0.04427660622841545
-0.013398123665888008
a: 0.011027221014414655
b: -0.06995590323332812
c: -0.27757524799221966
discriminant: 0.017137362828155422
-0.013398123665888008
a: 0.012172040437811256
b: -0.07029309322120289
c: -0.5278917022415274
discriminant: 0.03064319554048028
-0.013398123665888008
a: -0.0041596696691433704
b: 0.028786304126076023
c: -0.2452808469238802
discriminant: -0.003252497892245308
-0.013398123665888008
a: -0.003601153209911317
b: 0.02801530611476924
c: -0.49368236644837615
discriminant: -0.006326445977744512
-0.013398123665888008
a: 0.004881755480978869
b: -0.02888872283968172
c: -0.3585368831254069
discriminant: 0.00783571588463009
-0.013398123665888008
a: 0.006183593456301191
b: -0.02970404616581626
c: -0.599872642509112
discriminant: 0.015719804545954737
-0.013398123665888008
a: 0.00299111631155946
b: -0.015419950248740377
c: -0.3177104666005207
discriminant: 0.004039010701681566
-0.013398123665888008
a: 0.0031079064302116455
b: -0.008415755181933132
c: -0.579997928037583
discriminant: 0.007281142095511976
-0.013398123665888008
a: 0.0035283542680660217
b: -0.019407610057886104
c: -0.33063994446496536
discriminant: 0.005043114765143254
-0.013398123665888008
a: 0.004199511796421499
b: -0.015766544764272583
c: -0.5858575168585897
discriminant: 0.010089846146083228
-0.013398123665888008
a: 0.006549311255059906
b: -0.04161497725080038
c: -0.2664772577906026
discriminant: 0.008712776346246608
-0.013398123665888008
a: 0.0072499828564217
b: -0.03964935814174139
c: -0.5178106296337014
discriminant: 0.01658854435192112
-0.013398123665888008
a: 0.010797520590221158
b: -0.06841054243134118
c: -0.32418976409515154
discriminant: 0.018681784927575686
-0.013398123665888008
a: 0.011205888742690786
b: -0.061080096531137384
c: -0.5796355599531927
discriminant: 0.02971210457682407
-0.013398123665888008
a: 0.004194207404452115
b: -0.021187671956222315
c: -0.3605901383348519
discriminant: 0.006498476755630283
-0.013398123665888008
a: 0.004437168921374304
b: -0.01385140831989412
c: -0.6335274291545713
discriminant: 0.011436134390375732
-0.013398123665888008
a: 0.004997870707634831
b: -0.029575512082165023
c: -0.3427437031477495
discriminant: 0.007726665771675989
-0.013398123665888008
a: 0.006245093436659964
b: -0.02994723196059751
c: -0.5914292162361409
discriminant: 0.01567095956836291
-0.013398123665888008
a: 0.01331138511460508
b: -0.08538061250078674
c: -0.3158365068217962
discriminant: 0.0241067344932356
-0.013398123665888008
a: 0.014606142131476454
b: -0.08497872891662778
c: -0.5629309408648072
discriminant: 0.040110381698194274
-0.013398123665888008
a: 0.016249805404101755
b: -0.10331524935975106
c: -0.30972540104728796
discriminant: 0.030805950733170755
-0.013398123665888008
a: 0.017388956235550895
b: -0.10231874294784266
c: -0.555764989858161
discriminant: 0.049125817502006494
-0.013398123665888008
a: 0.018373255526831774
b: -0.11575795987803675
c: -0.298922741676135
discriminant: 0.03536864093751218
-0.013398123665888008
a: 0.020210019455328146
b: -0.1192034765648533
c: -0.5221561621557981
discriminant: 0.05642061360870016
-0.013398123665888008
a: 0.0009145190266673653
b: -0.003657483963211333
c: -0.27945042168297995
discriminant: 0.0010356280994983625
-0.013398123665888008
a: 0.0020088062722818274
b: -0.005676452537805438
c: -0.5225142128941572
discriminant: 0.004230741426286698
-0.013398123665888008
a: 0.009260773855534246
b: -0.05859387549396397
c: -0.26374802452427726
discriminant: 0.01320328548525508
-0.013398123665888008
a: 0.010905246308835107
b: -0.06299502123965525
c: -0.48965734188290455
discriminant: 0.025327708381634836
-0.013398123665888008
a: 0.0495608569816107
b: -0.32989184418812995
c: -0.0038995619095787415
discriminant: 0.10960169138221168
-0.013398123665888008
a: 0.05081355000564993
b: -0.3166801228843638
c: -0.23775344905994433
discriminant: 0.14861068732134866
-0.013398123665888008
a: 0.022480549943566325
b: -0.14427702553934396
c: -0.3804980602460918
discriminant: 0.055031082685650004
-0.013398123665888008
a: 0.02345695844111438
b: -0.13895325582715085
c: -0.6360521322653633
discriminant: 0.07898740103668889
-0.013398123665888008
a: 0.0015772520763897256
b: -0.007693931581795127
c: -0.31993827589814783
discriminant: 0.0020776898230929547
-0.013398123665888008
a: 0.0028208582000224507
b: -0.010219393500023044
c: -0.5586741811124133
discriminant: 0.006408198583235428
-0.013398123665888008
a: 0.023800724315267564
b: -0.15352892117888134
c: -0.41481657890260093
discriminant: 0.06306286978180412
-0.013398123665888008
a: 0.025367935535378115
b: -0.1499171801131846
c: -0.6644250967616369
discriminant: 0.08989553298403533
-0.013398123665888008
a: 0.004172585501377536
b: -0.044112508268681516
c: -0.011798409523930409
discriminant: 0.002142832875829962
-0.013398123665888008
a: 0.004473440268934045
b: -0.03686106148611315
c: -0.13008167048681607
discriminant: 0.003686388185906743
-0.013398123665888008
a: 0.0026423109544069755
b: -0.027668315748191508
c: -0.07121916381093396
discriminant: 0.0015182684031469647
-0.013398123665888008
a: 0.003304556221244672
b: -0.03516903256345405
c: -0.022783080978524994
discriminant: 0.001538012739396115
-0.013398123665888008
a: 0.003679453058635123
b: -0.029174831305628146
c: -0.1615966930579259
discriminant: 0.0032295205678610863
-0.013398123665888008
a: 0.0041705468895432245
b: -0.044220421681072125
c: -0.014368143837437786
discriminant: 0.0021951377640107767
-0.013398123665888008
a: 0.005205511079144338
b: -0.04268054890899958
c: -0.10967372521521856
discriminant: 0.004105260421968914
-0.013398123665888008
a: -0.0041772744916325905
b: 0.02216091992331469
c: -0.0454318070258789
discriminant: -0.00026801814254434706
-0.013398123665888008
a: 0.0021317555813567188
b: -0.03249942357898307
c: 0.0002290455337293773
discriminant: 0.001054259456586511
-0.013398123665888008
a: 0.0023327552058818642
b: -0.026224058956248672
c: -0.06411248342178244
discriminant: 0.001285936185997517
-0.013398123665888008
a: 0.0066260848181805615
b: -0.059799799833928496
c: -0.01701773441165133
discriminant: 0.004027059866677402
-0.013398123665888008
a: 0.007124811216745269
b: -0.05191808138555684
c: -0.16177024549621277
discriminant: 0.007305817013345515
-0.013398123665888008
a: 0.004943811642372816
b: -0.0485855565777302
c: -0.012839516051568745
discriminant: 0.002614460903720535
-0.013398123665888008
a: 0.006004942190673437
b: -0.04665483479622928
c: -0.12361676223889739
discriminant: 0.005145919654034655
-0.013398123665888008
a: 0.002946792197641915
b: -0.029536073886760023
c: -0.046783455433880516
discriminant: 0.0014238241464492969
-0.013398123665888008
a: -0.0001513218814412666
b: -0.014231177129239755
c: -0.001167345701062139
discriminant: 0.0002018198226926883
-0.013398123665888008
a: -0.00013290334163309526
b: -0.007760812262839964
c: -0.06951585189118592
discriminant: 2.3274650927807425e-05
-0.013398123665888008
a: 0.0001503877955445175
b: -0.014912228371269001
c: -0.0002077530105737413
discriminant: 0.00022249952906599183
-0.013398123665888008
a: 0.00042043409718463785
b: -0.010087538286757278
c: -0.0916101322258237
discriminant: 0.0002558225216281119
-0.013398123665888008
a: 0.002051564869983543
b: -0.02937235171734548
c: -0.018823635123559335
discriminant: 0.0010172066795869786
-0.013398123665888008
a: 0.002325900134170271
b: -0.02320266825666109
c: -0.11343793761191445
discriminant: 0.0015937450714748709
-0.013398123665888008
a: -0.0007401063833153594
b: -0.000554817950433717
c: -0.10059478354372875
discriminant: -0.0002974955427576386
-0.013398123665888008
a: 0.005755670728881755
b: -0.054542263956473186
c: -0.003262186923516208
discriminant: 0.003049962852648886
-0.013398123665888008
a: 0.0061900106378023605
b: -0.04714864862142737
c: -0.13831083165451596
discriminant: 0.005647577143885806
-0.013398123665888008
a: 0.0024735202846275645
b: -0.0314835994186663
c: -0.02162235575319038
discriminant: 0.0012051503745828444
-0.013398123665888008
a: 0.002929754627799968
b: -0.02640594979115196
c: -0.12510833729755377
discriminant: 0.0021634211050683082
-0.013398123665888008
a: 0.0044326773918685405
b: -0.04367296617343008
c: -0.026300963670127797
discriminant: 0.0023736627225652935
-0.013398123665888008
a: 0.004843465112001509
b: -0.03738503133257326
c: -0.16418740357683526
discriminant: 0.0045785844119555375
-0.013398123665888008
a: 0.003414150228778002
b: -0.03834389799372512
c: -0.05121673328041132
discriminant: 0.0021697009999395098
-0.013398123665888008
a: 0.004987289712121977
b: -0.0416603176059952
c: -0.13174452599590125
discriminant: 0.004363774539543372
-0.013398123665888008
a: 0.0022474218383644363
b: -0.027790459787907756
c: -0.03724131842207212
discriminant: 0.0011070974644683128
-0.013398123665888008
a: 0.0028615105423952817
b: -0.024017268212593812
c: -0.15652285044773484
discriminant: 0.0023683963191234825
-0.013398123665888008
a: -0.0005655012206186149
b: -0.004587372378103194
c: -0.004166134616530259
discriminant: 1.1620168491746844e-05
-0.013398123665888008
a: 0.0036257170481677394
b: -0.04022601148466737
c: -0.034394776618886014
discriminant: 0.002116954911784656
-0.013398123665888008
a: 0.005407197589812212
b: -0.044771589383963084
c: -0.11109845200086765
discriminant: 0.004407420343530033
-0.013398123665888008
a: 0.0029609997728032873
b: -0.03512809612150905
c: -0.05614121678716355
discriminant: 0.0018989196577287447
-0.013398123665888008
a: 0.0046965171106838795
b: -0.03963840448820566
c: -0.12475637236184178
discriminant: 0.00391488486022756
-0.013398123665888008
a: -0.002063298730299248
b: -0.005606912199366529
c: -0.0009775849234968659
discriminant: 2.336926548576212e-05
-0.013398123665888008
a: -0.0026535374864019726
b: -0.0006315029434654923
c: -0.10607875911545583
discriminant: -0.0011255370593278625
-0.013398123665888008
a: 0.004398148084774862
b: -0.027603703643043986
c: -0.2752429332087122
discriminant: 0.005604201172971851
-0.013398123665888008
a: 0.005580436637088423
b: -0.028891870405102743
c: -0.5207231485725402
discriminant: 0.012458190319802217
-0.013398123665888008
a: 0.002332500227393468
b: -0.022752084810997303
c: -0.18606107022359997
discriminant: 0.00225360731766929
-0.013398123665888008
a: 0.0022683508760813435
b: -0.014296776101865999
c: -0.3715865296017601
discriminant: 0.0035759523267556007
-0.013398123665888008
a: 0.005760334238979769
b: -0.04261291617686827
c: -0.23735409844489752
discriminant: 0.007284816385234073
-0.013398123665888008
a: 0.005536243309668679
b: -0.03161926528474998
c: -0.4747871749748057
discriminant: 0.011513927221030437
-0.013398123665888008
a: 0.004747840372865733
b: -0.03918275559782414
c: -0.20322899299627883
discriminant: 0.005394883607777138
-0.013398123665888008
a: 0.004616206195673394
b: -0.02929889043029124
c: -0.40099980735119123
discriminant: 0.008262816161079836
-0.013398123665888008
a: 0.003574454291243062
b: -0.020242697529927356
c: -0.3419415432595837
discriminant: 0.005298784469922103
-0.013398123665888008
a: 0.0045163973792564675
b: -0.018293770892606975
c: -0.5719588208296061
discriminant: 0.010667435331221005
-0.013398123665888008
a: 0.0032829637704175456
b: -0.02774485785700173
c: -0.19201383575780817
discriminant: 0.003291275002352388
-0.013398123665888008
a: 0.0030307024128794083
b: -0.01812274323640381
c: -0.40744067734035394
discriminant: 0.005267759598095145
-0.013398123665888008
a: 0.005038229829859386
b: -0.03719259697485616
c: -0.24137650495818164
discriminant: 0.006247730499764131
-0.013398123665888008
a: 0.00517621106831921
b: -0.02929825218347909
c: -0.47127695654219515
discriminant: 0.010616103575796745
-0.013398123665888008
a: 0.007567504145039401
b: -0.057046748324165286
c: -0.24136961557445835
discriminant: 0.010560593759745777
-0.013398123665888008
a: 0.007021924942521691
b: -0.04244292525187743
c: -0.4663895483753827
discriminant: 0.01490121151461056
-0.013398123665888008
a: 0.00012107389786728678
b: 5.5391505578275546e-05
c: -0.24885027323714948
discriminant: 0.00012052015848353442
-0.013398123665888008
a: 0.0010766430589440046
b: -0.001450520092478244
c: -0.48531640772283346
discriminant: 0.0020921541756043914
-0.013398123665888008
a: 0.004614026872959887
b: -0.03570723190030603
c: -0.21888872852856822
discriminant: 0.005314840312457573
-0.013398123665888008
a: 0.0040481237517900615
b: -0.02273824561660262
c: -0.4542206972332442
discriminant: 0.007871994185819102
-0.013398123665888008
a: 0.003427608353145808
b: -0.021576053300040282
c: -0.29517512953102776
discriminant: 0.004512505034491966
-0.013398123665888008
a: 0.0042357235827712725
b: -0.018680590467014008
c: -0.5216164298046845
discriminant: 0.009186656511734927
-0.013398123665888008
a: 0.03608709154419534
b: -0.24604157684354805
c: -0.49970333275708956
discriminant: 0.13266781719223797
-0.013398123665888008
a: 0.03651017535940648
b: -0.22564649236365975
c: -0.7338716453856765
discriminant: 0.15809146937333202
-0.013398123665888008
a: 0.003080826249310312
b: -0.02225255551921465
c: -0.2586308666314684
discriminant: 0.0036823632783361394
-0.013398123665888008
a: 0.0035884300637296423
b: -0.017590386489794246
c: -0.4767555614615063
discriminant: 0.007152637656055434
-0.013398123665888008
a: 0.02550640078609128
b: -0.1638400184587781
c: -0.016893776074197397
discriminant: 0.028567149341928583
-0.013398123665888008
a: 0.02450081878091817
b: -0.14833168295233545
c: -0.25872253688152236
discriminant: 0.04735794413016655
-0.013398123665888008
a: 0.005351926072086692
b: -0.040880847737902626
c: -0.22916523600474747
discriminant: 0.0065771453173284105
-0.013398123665888008
a: 0.005408656786427812
b: -0.032378679274782246
c: -0.44661507232456266
discriminant: 0.01071072943897599
-0.013398123665888008
a: 0.005492020038441012
b: -0.03454456122947841
c: -0.3035301126485478
discriminant: 0.007861300554281511
-0.013398123665888008
a: 0.006503447852215693
b: -0.032942773702718975
c: -0.5526466291330486
discriminant: 0.015461660472306824
-0.013398123665888008
a: 0.001945547747487687
b: -0.013961591502022669
c: -0.24337444033156996
discriminant: 0.002088912414002001
-0.013398123665888008
a: 0.002473650158638749
b: -0.010560882454244386
c: -0.47929038727841344
discriminant: 0.004853919208313465
-0.013398123665888008
a: 0.004361125283129697
b: -0.027448192686759493
c: -0.314493444906795
discriminant: 0.006239584537615798
-0.013398123665888008
a: 0.005500237237798146
b: -0.027168210704493462
c: -0.5496622527526743
discriminant: 0.012831202836092856
-0.013398123665888008
a: 0.0009093565917548188
b: -0.0036400659240022337
c: -0.3014805972076776
discriminant: 0.0011098635533590064
-0.013398123665888008
a: 0.0019668446414203428
b: -0.005112840573205657
c: -0.5435102164062228
discriminant: 0.0043021417655101785
-0.013398123665888008
a: 0.002541505904244139
b: -0.022500016135888784
c: -0.1933607421141298
discriminant: 0.0024719605970436125
-0.013398123665888008
a: 0.0021849802524213802
b: -0.011975435638883286
c: -0.412047511247961
discriminant: 0.0037446737592857215
-0.013398123665888008
a: 0.00836176897401361
b: -0.05412834133490535
c: -0.3128892186717457
discriminant: 0.013395106779639076
-0.013398123665888008
a: 0.01023183143657957
b: -0.058204159312962606
c: -0.5434906498694044
discriminant: 0.025631343028612058
-0.013398123665888008
a: 0.03668601054921869
b: -0.24995885670921142
c: -0.4929007318144122
discriminant: 0.13480967583562065
-0.013398123665888008
a: 0.03584326233913108
b: -0.2207645341272258
c: -0.7355546606429478
discriminant: 0.1541956941931939
-0.013398123665888008
a: 0.008643480243408247
b: -0.06523605290270709
c: -0.2449244052101972
discriminant: 0.01272373962857622
-0.013398123665888008
a: 0.00864244674252786
b: -0.05375145981544538
c: -0.4535361411530069
discriminant: 0.018567867215197282
-0.013398123665888008
a: 0.026176321612680194
b: -0.17775992091781156
c: -0.0223221454319541
discriminant: 0.03393583611635402
-0.013398123665888008
a: 0.027120750633141587
b: -0.16665785236875064
c: -0.2556199702175225
discriminant: 0.05550526163264631
-0.013398123665888008
a: 0.03190136304502766
b: -0.2185595617541743
c: -0.5060326475749798
discriminant: 0.11234080684588059
-0.013398123665888008
a: 0.031898217468263206
b: -0.1929446900050773
c: -0.7482423295314172
discriminant: 0.1326980395865674
-0.013398123665888008
a: -0.0005591430732416894
b: -0.0007373129807275586
c: -0.16395435474433506
discriminant: -0.00036615213670087335
-0.013398123665888008
a: -0.0007763026696909247
b: 0.006754478764474922
c: -0.3818601264630962
discriminant: -0.0011401331591075201
-0.013398123665888008
a: 0.004666508271501356
b: -0.032217807076212385
c: -0.2732689040708719
discriminant: 0.006138833497563378
-0.013398123665888008
a: 0.0054430669639924725
b: -0.029065549306871663
c: -0.5014234401056482
discriminant: 0.011761931603752237
-0.013398123665888008
a: 0.003225896793051755
b: -0.025123372967336438
c: -0.21610427453572034
discriminant: 0.0034197042140141167
-0.013398123665888008
a: 0.0026541553127960435
b: -0.012612048888946514
c: -0.46394883558371613
discriminant: 0.00508463284449741
-0.013398123665888008
a: -0.0015899019676668246
b: 0.010106760267428405
c: -0.21508806308134776
discriminant: -0.001265729135755454
-0.013398123665888008
a: -0.0011895814506824361
b: 0.01221306652819297
c: -0.4594871901465106
discriminant: -0.0020372307588758624
-0.013398123665888008
a: 0.005338993941505239
b: -0.04163272131536799
c: -0.2299117300957657
discriminant: 0.00664327282037222
-0.013398123665888008
a: 0.005398614967984427
b: -0.03263637081146109
c: -0.43747814176166233
discriminant: 0.010512236876865283
-0.013398123665888008
a: 0.002865287945471042
b: -0.023860908237301942
c: -0.20010738280040352
discriminant: 0.0028628040288599657
-0.013398123665888008
a: 0.002350619688301808
b: -0.012305333771504917
c: -0.43336419283175165
discriminant: 0.004226118854729486
-0.013398123665888008
a: 0.0014886288773926087
b: -0.014277402887697938
c: -0.18505883806036694
discriminant: 0.0013057799546311837
-0.013398123665888008
a: 0.001278911972039283
b: -0.006153441916121605
c: -0.41104836154524615
discriminant: 0.00214064353008447
-0.013398123665888008
a: 0.034511008321281886
b: -0.23724232008435941
c: -0.5035428382009853
discriminant: 0.12579500275611405
-0.013398123665888008
a: 0.03339253468994241
b: -0.20278209509477868
c: -0.7556394721906953
discriminant: 0.14205144724389812
-0.013398123665888008
a: 0.005337326042159769
b: -0.03875140917459047
c: -0.24038609150932333
discriminant: 0.0066337474985593845
-0.013398123665888008
a: 0.004778457926049244
b: -0.02475876367313906
c: -0.49404292388497917
discriminant: 0.010056049680409239
-0.013398123665888008
a: 0.003803323107796186
b: -0.029205624204513198
c: -0.23186333803171955
discriminant: 0.004380373250722436
-0.013398123665888008
a: 0.004243883553216068
b: -0.023811223664950948
c: -0.44394520322807807
discriminant: 0.008103181358457542
-0.013398123665888008
a: 0.008497224206885812
b: -0.0643544556860024
c: -0.04673285085570533
discriminant: 0.005729894012833181
-0.013398123665888008
a: 0.008093578568575212
b: -0.05000229677631912
c: -0.26326983322212427
discriminant: 0.011023410002582914
-0.013398123665888008
a: 0.006732161780525806
b: -0.05333966358193673
c: -0.22864819729834907
discriminant: 0.009002306331186465
-0.013398123665888008
a: 0.006547091165779448
b: -0.04127014775245294
c: -0.42539434058213443
discriminant: 0.01284360721230076
-0.013398123665888008
a: 0.004045579835371465
b: -0.028668764273624303
c: -0.25738389231923364
discriminant: 0.004986966383841086
-0.013398123665888008
a: 0.00471464300813862
b: -0.02474624897376501
c: -0.47798561136347784
discriminant: 0.009626502920694304
-0.013398123665888008
a: 0.021556466283830886
b: -0.14429806983647292
c: -0.4134490744693501
discriminant: 0.056471937094050136
-0.013398123665888008
a: 0.02246603134931103
b: -0.13268039640796625
c: -0.6626323088747322
discriminant: 0.0771509604879594
-0.013398123665888008
a: 0.033230674893572495
b: -0.2266299387781262
c: -0.5051006906023251
discriminant: 0.11850047650227649
-0.013398123665888008
a: 0.03313988526551023
b: -0.20069106195044223
c: -0.7551489536076045
discriminant: 0.14037910107050072
-0.013398123665888008
a: 0.001545978434201083
b: -0.00821543587091808
c: -0.30394784984747425
discriminant: 0.001947080670493104
-0.013398123665888008
a: 0.0025690308777389535
b: -0.008988823099501664
c: -0.5445879187423549
discriminant: 0.005677051656284943
-0.013398123665888008
a: 0.038604425536286006
b: -0.2609020474049272
c: -0.036667499276214266
discriminant: 0.0737319893217246
-0.013398123665888008
a: 0.04005732432446262
b: -0.2451372167863617
c: -0.27139318838533144
discriminant: 0.1035773949201685
-0.013398123665888008
a: 0.03251944805700032
b: -0.22197771504248576
c: -0.4816141571386646
discriminant: 0.11192141224183019
-0.013398123665888008
a: 0.03254388776457375
b: -0.19881492572529946
c: -0.7251243332322538
discriminant: 0.13392083435544372
-0.013398123665888008
a: 0.004018739680151335
b: -0.02591383939360639
c: -0.30882694492510987
discriminant: 0.005635907463599427
-0.013398123665888008
a: 0.004959176331939105
b: -0.02417491290209353
c: -0.5386202985572456
discriminant: 0.011268878559852074
-0.013398123665888008
a: 0.005011520563694355
b: -0.03631859375598781
c: -0.253440801631757
discriminant: 0.006399535408639405
-0.013398123665888008
a: 0.00555346779287019
b: -0.031175091342020456
c: -0.47426068782047015
discriminant: 0.011507052141125098
-0.013398123665888008
a: 0.004220666179976523
b: -0.031141483006986742
c: -0.25238521329681707
discriminant: 0.005230726900226591
-0.013398123665888008
a: 0.004669888916454299
b: -0.025491826583022847
c: -0.46903751815741057
discriminant: 0.009411245652317005
-0.013398123665888008
a: 0.008742622140900411
b: -0.06790601924366155
c: -0.23867249071636076
discriminant: 0.012957721056563346
-0.013398123665888008
a: 0.008621916516188922
b: -0.055604989367703056
c: -0.43293253429668577
discriminant: 0.018022747513974858
-0.013398123665888008
a: 0.00819653692544547
b: -0.0643719930695568
c: -0.24934701753369148
discriminant: 0.012318881637605472
-0.013398123665888008
a: 0.007979365870877067
b: -0.05017340853117466
c: -0.43586101667458743
discriminant: 0.016428949007232085
-0.013398123665888008
a: 0.0035831594181505062
b: -0.023692742285840007
c: -0.28227285200596
discriminant: 0.004607060549636669
-0.013398123665888008
a: 0.0043073826637926
b: -0.020140777729538734
c: -0.5032888392798137
discriminant: 0.009077081412327364
-0.013398123665888008
a: 0.023610959301639575
b: -0.17180949399711998
c: -0.37714703567203
discriminant: 0.06513771546749164
-0.013398123665888008
a: 0.02308711572477857
b: -0.14727661203767417
c: -0.5835926828759871
discriminant: 0.07558428767606326
-0.013398123665888008
a: 0.04340558609048412
b: -0.29282869083896906
c: -0.006340113148501136
discriminant: 0.08684942748682722
-0.013398123665888008
a: 0.0438560979103319
b: -0.27324785692439785
c: -0.24377347527574889
discriminant: 0.11742820491231665
-0.013398123665888008
a: 0.008062972066214782
b: -0.04865403015583153
c: -0.3671426393750611
discriminant: 0.014208258032794505
-0.013398123665888008
a: 0.009629244409403466
b: -0.049551729342881906
c: -0.6150477041464905
discriminant: 0.026145152547546346
-0.013398123665888008
a: -0.005036474004444506
b: 0.033937781358501534
c: -0.2437362779229323
discriminant: -0.0037585127072581855
-0.013398123665888008
a: -0.004630233287571195
b: 0.0339139286826273
c: -0.4789926749820791
discriminant: -0.007721236754128842
-0.013398123665888008
a: 0.011748006592895585
b: -0.08636746438059117
c: -0.27651626500484217
discriminant: 0.02045339852081168
-0.013398123665888008
a: 0.011134219396150577
b: -0.06929604744789195
c: -0.49899018264048645
discriminant: 0.027025406872078182
-0.013398123665888008
a: 0.005838504807697181
b: -0.044955706268082374
c: -0.22823450156970815
discriminant: 0.007351208464850545
-0.013398123665888008
a: 0.005961207048219556
b: -0.03632466110039331
c: -0.438780069665459
discriminant: 0.011782116379690434
-0.013398123665888008
a: 0.0026343698995467506
b: -0.015801706914542246
c: -0.29208866252275933
discriminant: 0.003327572263608397
-0.013398123665888008
a: 0.0035918294063794712
b: -0.015250768354144045
c: -0.5321274635806555
discriminant: 0.00787783022191624
-0.013398123665888008
a: 0.0055709887498725935
b: -0.058160529044754744
c: -0.09913017423185544
discriminant: 0.005591659480440067
-0.013398123665888008
a: 0.005907305526923816
b: -0.05164958950840823
c: -0.17436071170938183
discriminant: 0.006787688080223879
-0.013398123665888008
a: -0.0010477707905630143
b: -0.0047254049075661775
c: -0.0985352296066967
discriminant: -0.0003906398901528164
-0.013398123665888008
a: -0.0006672317336615793
b: -0.0017284822120270243
c: -0.19123976481557514
discriminant: -0.0005074173085344218
-0.013398123665888008
a: -0.002687349651981685
b: 0.007228295912994856
c: -0.08665340977419678
discriminant: -0.0008792237805930382
-0.013398123665888008
a: -0.0022054579351563058
b: 0.008751051627993722
c: -0.15849130955312674
discriminant: -0.0013216027606332195
-0.013398123665888008
a: 0.0020881932690725944
b: -0.028693028346409105
c: -0.11622542273021741
discriminant: 0.0017940944574492642
-0.013398123665888008
a: 0.0031722411186924145
b: -0.029014668741593336
c: -0.193853728623386
discriminant: 0.0033016540779881765
-0.013398123665888008
a: 0.022580598304418574
b: -0.17467286685967437
c: -0.32235274656608837
discriminant: 0.05962628194711707
-0.013398123665888008
a: 0.02118025295692776
b: -0.14459223685865275
c: -0.49352256989113774
discriminant: 0.06271864644077817
-0.013398123665888008
a: 0.005413661563071931
b: -0.04823735370520904
c: -0.14988123369549256
discriminant: 0.005572467388013803
-0.013398123665888008
a: 0.005306121377508447
b: -0.03968559158607379
c: -0.3077833278307823
discriminant: 0.008107488961311068
-0.013398123665888008
a: 0.004361609470489612
b: -0.04009947263349484
c: -0.06503477222786336
discriminant: 0.002742592819325136
-0.013398123665888008
a: 0.0045221942020349255
b: -0.03221042368361979
c: -0.2404878289130622
discriminant: 0.005387642056160763
-0.013398123665888008
a: 0.005257312025809443
b: -0.04871595777054594
c: -0.15167876938320457
discriminant: 0.005562935014854809
-0.013398123665888008
a: 0.0061309418221153975
b: -0.045822309867416644
c: -0.2840045794339442
discriminant: 0.009064546296481001
-0.013398123665888008
a: 0.0015136960969714796
b: -0.02101874089666486
c: -0.12592541558342074
discriminant: 0.0012042387091936741
-0.013398123665888008
a: 0.0021553685427063325
b: -0.01854574654925048
c: -0.23738278458628537
discriminant: 0.0023905342609782886
-0.013398123665888008
a: -0.002923064120500877
b: 0.01091036828509151
c: -0.09086088216367283
discriminant: -0.00094333260232243
-0.013398123665888008
a: -0.00226683031100437
b: 0.010280113788289927
c: -0.1805424628150195
discriminant: -0.0015313557690296736
-0.013398123665888008
a: -0.0012880118030452296
b: -0.0014780901461538265
c: -0.10746104292898673
discriminant: -0.0005514596161601831
-0.013398123665888008
a: -0.0010451126862366681
b: 0.0023222376025059666
c: -0.2257295790901005
discriminant: -0.0009382585995812168
-0.013398123665888008
a: 0.002811416589496873
b: -0.024956639959936106
c: -0.18151817461540254
discriminant: 0.002664126707725611
-0.013398123665888008
a: 0.0031383823621598684
b: -0.018133541234508
c: -0.3441858064050526
discriminant: 0.0046495719742131545
-0.013398123665888008
a: -0.0007572070860134162
b: -0.006677403311115576
c: -0.04896534498653693
discriminant: -0.0001037199097922918
-0.013398123665888008
a: -0.000252028580445195
b: -0.004777920024864629
c: -0.1393635306213027
discriminant: -0.00011766585138926712
-0.013398123665888008
a: -0.000149494317493417
b: -0.009959334429540459
c: -0.1086537747201296
discriminant: 3.421585469995294e-05
-0.013398123665888008
a: 0.0008694965126691094
b: -0.011577972639744707
c: -0.19959023806615905
discriminant: 0.0008282215142919676
-0.013398123665888008
a: 0.0024314446959396606
b: -0.02651379830831943
c: -0.14053902368981108
discriminant: 0.00206983295562676
-0.013398123665888008
a: 0.003161884426436456
b: -0.024172663303455272
c: -0.2662640378084452
discriminant: 0.003951902109048656
-0.013398123665888008
a: -0.006536753779173593
b: 0.038719244841343196
c: -0.050520021386581515
discriminant: 0.00017823215819321196
-0.013398123665888008
a: -0.006353737315257282
b: 0.03938786284933066
c: -0.15179299563049165
discriminant: -0.002306407542290879
-0.013398123665888008
a: 0.004927823125888953
b: -0.04575075066185069
c: -0.1673904003119987
discriminant: 0.005392612328959938
-0.013398123665888008
a: 0.005414480977840518
b: -0.040081050384824124
c: -0.3227039167744207
discriminant: 0.008595587475349732
-0.013398123665888008
a: 0.015713887620745
b: -0.1257987207314012
c: -0.2227214233005662
discriminant: 0.029824595803566965
-0.013398123665888008
a: 0.016397068783865723
b: -0.11658252649676687
c: -0.3675646725370104
discriminant: 0.037699418356803106
-0.013398123665888008
a: 9.563925017724677e-05
b: -0.013083118793403403
c: -0.04615574024901925
discriminant: 0.0001888251989174732
-0.013398123665888008
a: 0.0008047588459104841
b: -0.012112453315616709
c: -0.13322140606555155
discriminant: 0.000575555945306535
-0.013398123665888008
a: -0.0067119264282227975
b: 0.0392629636982036
c: -0.02549986783812075
discriminant: 0.0008569673709309687
-0.013398123665888008
a: -0.006745824869030453
b: 0.0415915183934761
c: -0.11301958270771217
discriminant: -0.001319786844593655
-0.013398123665888008
a: 0.0016456455303768443
b: -0.023181281070395673
c: -0.056262294107747746
discriminant: 0.000907722963373335
-0.013398123665888008
a: 0.0019809195076733333
b: -0.018713574078820627
c: -0.1839100805066881
discriminant: 0.0018074421193373942
-0.013398123665888008
a: -0.0032883526351056083
b: 0.013459096726814404
c: -0.05098004195520378
discriminant: -0.0004894141365030091
-0.013398123665888008
a: -0.002994446541923469
b: 0.015424591595174578
c: -0.15469068025652544
discriminant: -0.0016149338643698366
-0.013398123665888008
a: 0.006074474863064769
b: -0.05604078758770861
c: -0.026332524896120924
discriminant: 0.003780394915700731
-0.013398123665888008
a: 0.007780686518259883
b: -0.05906652138288715
c: -0.13205439979654587
discriminant: 0.007598749500970605
-0.013398123665888008
a: 0.0001406652412322077
b: -0.011895623186684412
c: -0.033357432231090556
discriminant: 0.00016027477600627732
-0.013398123665888008
a: 0.0010328293065137639
b: -0.012322047237572492
c: -0.13351729281395286
discriminant: 0.0007034351399034882
-0.013398123665888008
a: 0.008155430775370459
b: -0.07408136417058103
c: -0.012233152563239869
discriminant: 0.005887115032950441
-0.013398123665888008
a: 0.010078348554212541
b: -0.07750415922426784
c: -0.09479542751878778
discriminant: 0.0098284201365804
-0.013398123665888008
a: 0.007799189306341214
b: -0.06743424171714893
c: -0.16926064087232529
discriminant: 0.00982776007707047
-0.013398123665888008
a: 0.007915571887780387
b: -0.05831613479544043
c: -0.3148999131525295
discriminant: 0.01337122317753857
-0.013398123665888008
a: 0.025603030387317226
b: -0.18023513725234602
c: -0.3902537829375591
discriminant: 0.07245142255363532
-0.013398123665888008
a: 0.004039939569685978
b: -0.046286381088560535
c: -0.0412630219351966
discriminant: 0.0028092295345987393
-0.013398123665888008
a: 0.0049341369195993415
b: -0.04416412754699697
c: -0.10971941392890494
discriminant: 0.004115952606241065
-0.013398123665888008
a: 0.0030449450573079104
b: -0.03735684239678172
c: -0.12089377576475113
discriminant: 0.0028679932937546674
-0.013398123665888008
a: 0.003802287425191225
b: -0.03457315266372299
c: -0.2024861256545719
discriminant: 0.004274944682517373
-0.013398123665888008
a: 0.0011345617754150716
b: -0.010134770648364988
c: -0.20276317292994672
discriminant: 0.0010229029579677347
-0.013398123665888008
a: 0.0013576940934108645
b: -0.0034050080486330014
c: -0.39518849521350663
discriminant: 0.0021577744227524783
-0.013398123665888008
a: 0.0076260941466041714
b: -0.058028583408780005
c: -0.2310162915822197
discriminant: 0.010414324448451211
-0.013398123665888008
a: 0.00249862691383718
b: -0.02964641250229616
c: -0.02388651976903744
discriminant: 0.0011176437789475852
-0.013398123665888008
a: 0.004096178366807355
b: -0.03404956710731222
c: -0.11407151635686563
discriminant: 0.003028402130474976
-0.013398123665888008
a: 0.0012173277235908901
b: -0.024696261705701328
c: -0.09847924658601481
discriminant: 0.0010894314105064874
-0.013398123665888008
a: 0.001962793051281277
b: -0.022980690466521403
c: -0.1580712567390713
discriminant: 0.0017691567916570594
-0.013398123665888008
a: 0.03516129838485317
b: -0.27178604922075106
c: -0.3690124753939926
discriminant: 0.12576748757127038
-0.013398123665888008
a: 0.036044412787561514
b: -0.2506593611911512
c: -0.5105405804041036
discriminant: 0.13643865705230296
-0.013398123665888008
a: 0.0021807173828140153
b: -0.03231904122448789
c: -0.03383746322129899
discriminant: 0.0013396802026182145
-0.013398123665888008
a: 0.0028216598763569608
b: -0.02969039271174949
c: -0.09371253858003559
discriminant: 0.0019392190594692679
-0.013398123665888008
a: -0.0009328284668795065
b: -0.008435084455732753
c: -0.025548309895727428
discriminant: -2.4178113230231463e-05
-0.013398123665888008
a: -0.0003788116911773859
b: -0.006876124846537754
c: -0.06888230311045429
discriminant: -5.709259402868414e-05
-0.013398123665888008
a: 0.000492489579103533
b: -0.012797421282809335
c: -0.12429292886339904
discriminant: 0.0004086258803756243
-0.013398123665888008
a: 0.0007704816877180361
b: -0.008583747399135866
c: -0.27279672155987933
discriminant: 0.0009144202331377837
-0.013398123665888008
a: 0.02737533823476187
b: -0.1919794980054511
c: -0.41333239047097237
discriminant: 0.08211658362452715
-0.013398123665888008
a: -0.0020256215670718765
b: 0.003218305853836742
c: -0.0984217905429795
discriminant: -0.0007871037138059207
-0.013398123665888008
a: -0.0015967048961650718
b: 0.00550525248821572
c: -0.19626736389053911
discriminant: -0.0012232164385667372
-0.013398123665888008
a: -0.0061947090941595635
b: 0.036127670316545346
c: -0.03999045957731795
discriminant: 0.00031429150800806396
-0.013398123665888008
a: -0.005896318832938072
b: 0.03617318777922369
c: -0.13343581160057905
discriminant: -0.0018386208416045048
-0.013398123665888008
a: -0.002648630581727508
b: 0.010006141221634901
c: -0.06127161644834145
discriminant: -0.0005490206463205203
-0.013398123665888008
a: -0.0024133533489623816
b: 0.012603208594144336
c: -0.2007016303164405
discriminant: -0.0017786149397980525
-0.013398123665888008
a: 0.0019929129701875842
b: -0.023468835479217576
c: -0.1327011824789074
discriminant: 0.0016086338696363572
-0.013398123665888008
a: 0.0019541658790053675
b: -0.016784366975046733
c: -0.2876471314653618
discriminant: 0.002530155812766564
-0.013398123665888008
a: 0.001151348446781119
b: -0.017213226706229212
c: -0.12932789036856585
discriminant: 0.000891901036445351
-0.013398123665888008
a: 0.0026393847127442055
b: -0.021494717623792348
c: -0.2251215322656045
discriminant: 0.0028387522088121207
-0.013398123665888008
a: -0.0028149030736955277
b: 0.01113642116681808
c: -0.050028740772987135
discriminant: -0.00043928434829523924
-0.013398123665888008
a: -0.0025061573339580524
b: 0.013038749437111502
c: -0.17909466502481586
discriminant: -0.0016253486460150362
-0.013398123665888008
a: -0.005738686924114798
b: 0.03174069036130697
c: -0.02979652769373098
discriminant: 0.0003234996491722115
-0.013398123665888008
a: -0.005687810146439769
b: 0.033889323752574384
c: -0.11558190927328826
discriminant: -0.0014811455608311568
-0.013398123665888008
a: 0.02537369712143771
b: -0.17908967659230707
c: -0.3852398312064781
discriminant: 0.071172947446525
-0.013398123665888008
a: -0.007080104889206011
b: 0.04320316974257319
c: -0.0526577442459959
discriminant: 0.0003752244658430507
-0.013398123665888008
a: -0.006972438150891189
b: 0.04404350847225347
c: -0.17490076568925306
discriminant: -0.0029381084467018518
-0.013398123665888008
a: 0.0071687769900314145
b: -0.06253784330553494
c: -0.17475863564002425
discriminant: 0.0089222045892496
-0.013398123665888008
a: 0.006855480169275908
b: -0.05034283721567989
c: -0.3280595208733189
discriminant: 0.01153042341768122
-0.013398123665888008
a: -0.00779158417196794
b: 0.04802792022313877
c: -0.03505912022625457
discriminant: 0.001214016776008158
-0.013398123665888008
a: -0.007777640812071052
b: 0.04926592336432154
c: -0.1281359271910988
discriminant: -0.0015592496623170154
-0.013398123665888008
a: -0.005769602094626398
b: 0.033025706559516026
c: -0.09202031582960946
discriminant: -0.00103298513407953
-0.013398123665888008
a: -0.005432896139789532
b: 0.03327345820574354
c: -0.17912247315592678
discriminant: -0.0027854921508641923
-0.013398123665888008
a: 0.003791460902911788
b: -0.04343393033517426
c: -0.04193844571693994
discriminant: 0.0025225382134194353
-0.013398123665888008
a: 0.004630943332539364
b: -0.041205110598402345
c: -0.11745597905285454
discriminant: 0.003873589071673369
-0.013398123665888008
a: -0.0021635280639174873
b: 0.0038638515668291268
c: -0.04586066422330848
discriminant: -0.00038195398737761037
-0.013398123665888008
a: -0.0016759388503482572
b: 0.004973645177232311
c: -0.1255182127053066
discriminant: -0.000816706250047392
-0.013398123665888008
a: 0.00394907192297563
b: -0.0445833360387993
c: -0.03730640878835434
discriminant: 0.002576976618321066
-0.013398123665888008
a: 0.004592170741062479
b: -0.04082355718330985
c: -0.11644548337538507
discriminant: 0.003805512987840252
-0.013398123665888008
a: 0.02118225866132954
b: -0.15320669228102107
c: -0.32569449816033635
discriminant: 0.05106807097810813
-0.013398123665888008
a: -0.003110329822229841
b: 0.011547786040050204
c: -0.041647472816145004
discriminant: -0.00038479814445547135
-0.013398123665888008
a: -0.002929295925417452
b: 0.014868568319322775
c: -0.1343577747981518
discriminant: -0.0013532204051911578
-0.013398123665888008
a: 0.0015704053276310009
b: -0.028803610417624192
c: -0.02090138640989958
discriminant: 0.0009609425673821909
-0.013398123665888008
a: 0.0020817573910548517
b: -0.025565274910142363
c: -0.06527839131050939
discriminant: 0.0011971583755784495
-0.013398123665888008
a: 0.02476029859020535
b: -0.17570260033472102
c: -0.3694756379502676
discriminant: 0.06746471223420364
-0.013398123665888008
a: 0.0019900983130328002
b: -0.018512591464322742
c: -0.17678413030731577
discriminant: 0.0017499872407071547
-0.013398123665888008
a: 0.0023424139333638747
b: -0.013111795202386589
c: -0.3595096894884716
discriminant: 0.0035404011967777923
-0.013398123665888008
a: 0.002647023494558012
b: -0.030455178227123736
c: -0.12761327724995308
discriminant: 0.0022786992532385568
-0.013398123665888008
a: 0.0038909456533597698
b: -0.032061386148971
c: -0.23109538878772262
discriminant: 0.004624650875853731
-0.013398123665888008
a: -0.0021647911516896323
b: 0.004197644096170072
c: -0.0343507821152661
discriminant: -0.0002798288607488746
-0.013398123665888008
a: -0.001644905950537844
b: 0.005290609147548919
c: -0.11629177203821428
discriminant: -0.0007371655661448683
-0.013398123665888008
a: -0.00908894320565973
b: 0.05840807679691931
c: -0.06689390620430002
discriminant: 0.0009795237779323764
-0.013398123665888008
a: -0.009022522942690127
b: 0.058356537281890254
c: -0.15099563576627972
discriminant: -0.0020439609082567164
-0.013398123665888008
a: 0.0026841597572610943
b: -0.02991061726645336
c: -0.13139410970064935
discriminant: 0.002305376151658788
-0.013398123665888008
a: 0.0037870792823432786
b: -0.03043232709141591
c: -0.24908288586950122
discriminant: 0.004699313078849581
-0.013398123665888008
a: 0.0004434071183918153
b: -0.006980347021953381
c: -0.17776049085478773
discriminant: 0.00036400631260223766
-0.013398123665888008
a: 0.0006876983199768701
b: -0.001252785146366453
c: -0.3585940391331969
discriminant: 0.0009879875436854346
-0.013398123665888008
a: 0.010222045391048118
b: -0.0835929057432657
c: -0.21515968743410496
discriminant: 0.01578526225570309
-0.013398123665888008
a: 0.009957694695327347
b: -0.07020524304100345
c: -0.38005404812647725
discriminant: 0.020066624866313193
-0.013398123665888008
a: 5.274119128614516e-06
b: -0.015035867818664561
c: -0.08771983646303794
discriminant: 0.00022792790053014717
-0.013398123665888008
a: 0.0005713288824418551
b: -0.01261534893188429
c: -0.14952833043280023
discriminant: 0.0005008664443514668
-0.013398123665888008
a: 0.006947962676657763
b: -0.06306198495227891
c: -0.0285125773714211
discriminant: 0.004769231239689254
-0.013398123665888008
a: 0.008920218235837597
b: -0.06761949994747199
c: -0.12833477925765757
discriminant: 0.009151493726051563
-0.013398123665888008
a: -4.8159192382650484e-05
b: -0.0027773564786967575
c: -0.18973675321262606
discriminant: -2.8836566190346492e-05
-0.013398123665888008
a: 0.00013429162831930797
b: 0.0031167428748504478
c: -0.38208520467302864
discriminant: 0.00021495746331695934
-0.013398123665888008
a: -0.008428359893124281
b: 0.053613306604906555
c: -0.06658617744767048
discriminant: 0.0006295375753661071
-0.013398123665888008
a: -0.008313799520889564
b: 0.053602701750939306
c: -0.17164684575980182
discriminant: -0.00283490022116003
-0.013398123665888008
a: 0.0026889323168182476
b: -0.030795758574064025
c: -0.03823842791788956
discriminant: 0.0013596609244429913
-0.013398123665888008
a: 0.00358901850019669
b: -0.029694977154062524
c: -0.15236803490140216
discriminant: 0.0030691984525792844
-0.013398123665888008
a: 0.024377228091852512
b: -0.1965951350567356
c: -0.020379663847825857
discriminant: 0.04063684598419104
-0.013398123665888008
a: 0.026971528216144163
b: -0.19593173688557292
c: -0.1223892092291653
discriminant: 0.05159334155930139
-0.013398123665888008
a: -0.008839026881792491
b: 0.05638121724083204
c: -0.0769219359475749
discriminant: 0.0004591814189973571
-0.013398123665888008
a: -0.008792326720783799
b: 0.05672012008406329
c: -0.15914085018812762
discriminant: -0.0023797013755587444
-0.013398123665888008
a: 0.0003251912466543782
b: -0.012821723957406772
c: -0.05824290880916638
discriminant: 0.0002401569417376591
-0.013398123665888008
a: 0.0005365118613870606
b: -0.007985119329693174
c: -0.19422596109391865
discriminant: 0.000480580258374196
-0.013398123665888008
a: 0.034968290252234545
b: -0.2700908571763167
c: -0.04139561065343367
discriminant: 0.07873920604422854
-0.013398123665888008
a: 0.03778964136860788
b: -0.2640795790232247
c: -0.17339335520390964
discriminant: 0.09594791489250512
-0.013398123665888008
a: 0.007429851663561863
b: -0.07491421045878272
c: -0.018272701097239552
discriminant: 0.006155192763243166
-0.013398123665888008
a: 0.007947846613861935
b: -0.06839260962086025
c: -0.07686816910008465
discriminant: 0.0071212947207348835
-0.013398123665888008
a: 0.0008347896503022641
b: -0.019112495572852606
c: -0.03486514515636363
discriminant: 0.00048170773635358434
-0.013398123665888008
a: 0.0013517039919289063
b: -0.01543657518941069
c: -0.12044746764761227
discriminant: 0.0008895251449263508
-0.013398123665888008
a: 0.002270106958630745
b: -0.030274052816795516
c: -0.0390516027447918
discriminant: 0.001271123534500666
-0.013398123665888008
a: 0.003113412481993494
b: -0.028936831861390427
c: -0.123389122016755
discriminant: 0.0023739851686911135
-0.013398123665888008
a: 0.0013105379182770643
b: -0.02123734688284315
c: -0.05352747863034735
discriminant: 0.0007316240642815494
-0.013398123665888008
a: 0.0017191304724192063
b: -0.017507879625444256
c: -0.16872015329670964
discriminant: 0.0014667336763534995
-0.013398123665888008
a: 0.004837201869013308
b: -0.04026227076107031
c: -0.20710782919207416
discriminant: 0.005628339960658497
-0.013398123665888008
a: 0.005288202230538554
b: -0.033565599052489514
c: -0.36718731794106774
discriminant: 0.00889369261479818
-0.013398123665888008
a: -0.007249324637575054
b: 0.044979780647552085
c: -0.08902974375232653
discriminant: -0.0005584413923410371
-0.013398123665888008
a: -0.006961792686000644
b: 0.04446137718375531
c: -0.19415984050713597
discriminant: -0.003429988169154366
-0.013398123665888008
a: 0.0064475035598744145
b: -0.05672137949561534
c: -0.16504036799781663
discriminant: 0.0074737083326412365
-0.013398123665888008
a: 0.006915399910808133
b: -0.05055551839869776
c: -0.31481550329378527
discriminant: 0.01126416085415651
-0.013398123665888008
a: -0.0018803946288863047
b: 0.004273627500254645
c: -0.10151398563248792
discriminant: -0.0007452815213497544
-0.013398123665888008
a: -0.0010530271938259004
b: 0.0030865476263085556
c: -0.19213804023651193
discriminant: -0.0007997795491003774
-0.013398123665888008
a: -0.0022904870626134465
b: 0.009192868001333898
c: -0.12301682986229034
discriminant: -0.0010425650070432333
-0.013398123665888008
a: -0.0014021788585509912
b: 0.0073704961600190855
c: -0.23886215426233737
discriminant: -0.0012853856376135238
-0.013398123665888008
a: -0.0002915866154329424
b: -0.008872305174101966
c: -0.044974436618054114
discriminant: 2.626202408454937e-05
-0.013398123665888008
a: 0.00038974120257646676
b: -0.007921145366786897
c: -0.14925130183377855
discriminant: 0.0002954220713729698
-0.013398123665888008
a: 0.007566441848153246
b: -0.07442655695020173
c: -0.021747791621508528
discriminant: 0.006197525981981216
-0.013398123665888008
a: 0.007780480062044487
b: -0.06580298047013886
c: -0.09560317299088739
discriminant: 0.007305386564048633
-0.013398123665888008
a: 0.0006680838787767821
b: -0.01948928614971443
c: -0.024855743457573354
discriminant: 0.00044625516062151566
-0.013398123665888008
a: 0.0006414321906050091
b: -0.012761783818281469
c: -0.10689047943503505
discriminant: 0.00043711510373988763
-0.013398123665888008
a: -0.006934301991132782
b: 0.04332798451317704
c: -0.0935070314968044
discriminant: -0.0007163097367987163
-0.013398123665888008
a: -0.00682029044530345
b: 0.04439638324730211
c: -0.2487054253911859
discriminant: -0.0048139341005212135
-0.013398123665888008
a: -0.0013953001744048338
b: -0.0021013680109195076
c: -0.09790794674963876
discriminant: -0.0005420281531842448
-0.013398123665888008
a: -0.0010565636864550438
b: 0.0008260114089569809
c: -0.1841091040542907
discriminant: -0.0007774096799104195
-0.013398123665888008
a: 0.0007089668439829392
b: -0.010607475979536402
c: -0.16024399169265469
discriminant: 0.0005669492548867206
-0.013398123665888008
a: 0.0010233836638062384
b: -0.005280778931156721
c: -0.3170906667760002
discriminant: 0.0013259082594156931
-0.013398123665888008
a: 0.007601368114221772
b: -0.07547944164134165
c: -0.02690082637975777
discriminant: 0.006515078446045927
-0.013398123665888008
a: 0.008246512107499764
b: -0.06975127750462032
c: -0.09152288893067018
discriminant: 0.007884219160247063
-0.013398123665888008
a: -0.002864229310340187
b: 0.012988512308666031
c: -0.0959617846337043
discriminant: -0.0009307247728892647
-0.013398123665888008
a: -0.0029194152494816626
b: 0.01700341503852358
c: -0.26268534705564617
discriminant: -0.002778434309066256
-0.013398123665888008
a: 0.001074706707251124
b: -0.018674600892524346
c: -0.1268621248522307
discriminant: 0.0008940990243943584
-0.013398123665888008
a: 0.002305308569525096
b: -0.020947231368439206
c: -0.2149086430307804
discriminant: 0.002420509447778395
-0.013398123665888008
a: 0.01301308164847113
b: -0.1067714892524258
c: -0.2138543649681085
discriminant: 0.022531768166028636
-0.013398123665888008
a: 0.014101032843940486
b: -0.09975583241134695
c: -0.3273635264331368
discriminant: 0.028415881452648104
-0.013398123665888008
a: 0.023751488422331563
b: -0.18662237198984694
c: -0.04650525316092191
discriminant: 0.039246185655233745
-0.013398123665888008
a: 0.02520502566073915
b: -0.17659435351768332
c: -0.17894015079105763
discriminant: 0.04922633006402907
-0.013398123665888008
a: 0.0016872628384888896
b: -0.030314987758061046
c: -0.013910097683734635
discriminant: 0.0010128784463774544
-0.013398123665888008
a: 0.002393720754004326
b: -0.027876514457406798
c: -0.053473591947237886
discriminant: 0.001289103445635058
-0.013398123665888008
a: -0.012297472727525868
b: 0.0811344028651647
c: -0.042008008720123446
discriminant: 0.004516421961993298
-0.013398123665888008
a: -0.009332166716821669
b: 0.06029837301981204
c: -0.09132636381591952
discriminant: 0.0002268023777513132
-0.013398123665888008
a: -0.0036284318920246604
b: 0.02158766472123254
c: -0.03912407768211279
discriminant: -0.0001018089367149653
-0.013398123665888008
a: -0.002454977183499029
b: 0.009007141978043379
c: -0.007306048986845615
discriminant: 9.38387235570246e-06
-0.013398123665888008
a: -0.004330776003230328
b: 0.02436372173674653
c: -0.13177893286169418
discriminant: -0.0016892292238092875
-0.013398123665888008
a: -0.00619183823757136
b: 0.03735586926441588
c: -0.04502685682462759
discriminant: 0.00028026491328261047
-0.013398123665888008
a: -0.008864017541887002
b: 0.0561086620321128
c: -0.11021659293301778
discriminant: -0.0007596652976272975
-0.013398123665888008
a: -0.008794743378211883
b: 0.056425718062801535
c: -0.11272481618941221
discriminant: -0.0007816816640651716
-0.013398123665888008
a: -0.0043728266963383895
b: 0.026575683046422133
c: -0.14886061263075112
discriminant: -0.0018974997143962559
-0.013398123665888008
a: -0.004208699892288046
b: 0.03451104203902701
c: -0.2040699355489649
discriminant: -0.002244464440437139
-0.013398123665888008
a: -0.00590106919672594
b: 0.03516312105627571
c: -0.15814840465575564
discriminant: -0.002496533634483415
-0.013398123665888008
a: -0.012301789873555843
b: 0.08133809677823399
c: -0.04509451480403326
discriminant: 0.004396913005228677
-0.013398123665888008
a: -0.0026075657123787663
b: 0.010430837413702695
c: -0.004136217833048295
discriminant: 6.566052994955461e-05
-0.013398123665888008
a: -0.007665456035643234
b: 0.046863736452862854
c: -0.02274952845943712
discriminant: 0.0014986677533736677
-0.013398123665888008
a: -0.0076864234437775845
b: 0.050083941806768194
c: -0.0593040934387169
discriminant: 0.0006850557304264226
-0.013398123665888008
a: -0.004664782741361942
b: 0.028529918942581264
c: -0.14517797079026684
discriminant: -0.001894938495403282
-0.013398123665888008
a: -0.004436093918269407
b: 0.0355829906531923
c: -0.16168797180846395
discriminant: -0.0016029028897621984
-0.013398123665888008
a: -0.004052295008865072
b: 0.02095203501534415
c: -0.005713264177823363
discriminant: 0.0003463804436357225
-0.013398123665888008
a: -0.001826730718969629
b: 0.004963390670793724
c: -0.03193473366615951
discriminant: -0.00020870938900942652
-0.013398123665888008
a: -0.0044086572040677955
b: 0.02832236241010634
c: -0.1545063422042322
discriminant: -0.001922505782042005
-0.013398123665888008
a: -0.004288249202633408
b: 0.03711982915237269
c: -0.22494730500788773
discriminant: -0.0024806386890370968
-0.013398123665888008
a: -0.0040366815748511115
b: 0.023626420534620815
c: -0.06231800712301838
discriminant: -0.00044802405726096246
-0.013398123665888008
a: -0.0023049214005994223
b: 0.016095295324367917
c: -0.10095844265834042
discriminant: -0.0006717465686389741
-0.013398123665888008
a: -0.004068397612441904
b: 0.020962608473183125
c: -0.12673288702294683
discriminant: -0.0016229681459281366
-0.013398123665888008
a: -0.004022979274482485
b: 0.02946293973328884
c: -0.17556172048527718
discriminant: -0.0019570598338916187
-0.013398123665888008
a: -0.00369577563605146
b: 0.019515406691426734
c: -0.03483127987789025
discriminant: -0.00013406328384900172
-0.013398123665888008
a: -0.003836151554594048
b: 0.029717933477584252
c: -0.14580817113359534
discriminant: -0.0013542133992885043
-0.013398123665888008
a: -0.0022582610448453905
b: 0.004825781297007836
c: -0.09362970942003679
discriminant: -0.0008224731365672997
-0.013398123665888008
a: -0.0018465197117265714
b: 0.008007915165815768
c: -0.17473811068104206
discriminant: -0.001226502757746712
-0.013398123665888008
a: -0.004361739338937966
b: 0.022662847987052634
c: -0.03913350966796869
discriminant: -0.00016915599547369744
-0.013398123665888008
a: -0.00450898009642541
b: 0.0318323848994784
c: -0.12518329298420905
discriminant: -0.0012444951774946166
-0.013398123665888008
a: -0.004358093280069715
b: 0.02511471622963171
c: -0.0130935363844088
discriminant: 0.0004024975595779653
-0.013398123665888008
a: -0.012733268221465283
b: 0.08473297880018439
c: -0.022749861540433014
discriminant: 0.006020957340370374
-0.013398123665888008
a: -0.010066362585333777
b: 0.0658582027339732
c: -0.1130950353894139
discriminant: -0.0002165196639748665
-0.013398123665888008
a: -0.010058814673890044
b: 0.06541341079655325
c: -0.2319480323856059
discriminant: -0.005053574774922394
-0.013398123665888008
a: -0.0036153131671991575
b: 0.018444860354116188
c: -0.13174163429162034
discriminant: -0.0015649361870084771
-0.013398123665888008
a: -0.0035103762506349403
b: 0.027702108400625522
c: -0.17424421399884438
discriminant: -0.0016792441926883747
-0.013398123665888008
a: -0.004752711895461392
b: 0.02851692885488767
c: -0.14976484191365314
discriminant: -0.0020339413514249313
-0.013398123665888008
a: -0.004663342123220834
b: 0.03616171122682571
c: -0.21649911510489794
discriminant: -0.0027307684135824935
-0.013398123665888008
a: -0.011264211966556565
b: 0.07542529667038408
c: -0.07227563491983979
discriminant: 0.0024324630907973203
-0.013398123665888008
a: -0.011343873746351573
b: 0.07476685487810524
c: -0.14895025811506868
discriminant: -0.0011686091018116235
-0.013398123665888008
a: -0.009010884631318095
b: 0.057659748135893904
c: -0.07595715401366043
discriminant: 0.0005868819481333032
-0.013398123665888008
a: -0.008975347528164448
b: 0.058018342096823855
c: -0.15651090799128375
discriminant: -0.002252831145017285
-0.013398123665888008
a: -0.004252827015483379
b: 0.02683643710075906
c: -0.06915540472916948
discriminant: -0.00045622953773259884
-0.013398123665888008
a: -0.004615634547066164
b: 0.025894256360231266
c: -0.13501436036252146
discriminant: -0.0018221952717078008
-0.013398123665888008
a: -0.008255893513698934
b: 0.05251771448740587
c: -0.09760174623020179
discriminant: -0.00046504815952976876
-0.013398123665888008
a: -0.0039524748094394695
b: 0.022050119061169257
c: -0.06505961437370666
discriminant: -0.0005423781970839466
-0.013398123665888008
a: -0.009830495071172054
b: 0.06412533297241166
c: -0.19171340152483063
discriminant: -0.00342649226624724
-0.013398123665888008
a: -0.009832247347536661
b: 0.06404973470578501
c: -0.1808278940511091
discriminant: -0.003009409810697191
-0.013398123665888008
a: -0.009830388110526195
b: 0.06410658446587432
c: -0.09999282845449298
discriminant: 0.0001777809239725467
-0.013398123665888008
a: -0.0016025281087348265
b: -0.0005787822045635743
c: -0.021080499241871276
discriminant: -0.00013479338148472821
-0.013398123665888008
a: -0.0012037971371176561
b: 0.002741532076245959
c: -0.10877382384085299
discriminant: -0.0005162504728067509
-0.013398123665888008
a: -0.0008567941782446223
b: 0.002922819861086348
c: -0.07134070249569147
discriminant: -0.00023595431834039937
-0.013398123665888008
a: -0.002006227564947203
b: 0.007276539714323044
c: -0.14427626784847403
discriminant: -0.0011048560718871375
-0.013398123665888008
a: -0.0008473030441436208
b: -0.005342368895059235
c: -0.11222168881237782
discriminant: -0.00035180220878776693
-0.013398123665888008
a: -0.0004286047292936697
b: -0.0012975979689375805
c: -0.2124933774791148
discriminant: -0.0003626189056355433
-0.013398123665888008
a: -0.004890721176489754
b: 0.028458762774349305
c: -0.14594217493545847
discriminant: -0.0020451487633525857
-0.013398123665888008
a: -0.00471209589346164
b: 0.03496605250932153
c: -0.17772211356110523
discriminant: -0.0021271497378697987
-0.013398123665888008
a: -0.011486342427779756
b: 0.07687094618158394
c: -0.024446064957208247
discriminant: 0.0047859588744110105
-0.013398123665888008
a: -0.011452888092845682
b: 0.07434129220247226
c: -0.11167032448294789
discriminant: 0.00041083680795349353
-0.013398123665888008
a: -0.007063446875755685
b: 0.04351667005404473
c: -0.10278347275946287
discriminant: -0.0010103218255759971
-0.013398123665888008
a: -0.0006629709439271714
b: -0.0014409710640876372
c: -0.02889167068591003
discriminant: -7.454095513754517e-05
-0.013398123665888008
a: -0.004303686978581856
b: 0.024786069904356764
c: -0.13097466658958823
discriminant: -0.0016403466071991837
-0.013398123665888008
a: -0.004238904384876107
b: 0.03287799068958877
c: -0.2062759052187223
discriminant: -0.0024165730847190347
-0.013398123665888008
a: -0.00044025531118411197
b: -0.008458542305218864
c: -0.03410020290995153
discriminant: 1.1495756154928966e-05
-0.013398123665888008
a: -6.973165138070888e-05
b: -0.00415564915324089
c: -0.14428138368253285
discriminant: -2.2974496705874995e-05
-0.013398123665888008
a: -0.0015616369977123632
b: 0.0058078722576398595
c: -0.0721615559071408
discriminant: -0.00041702924190725803
-0.013398123665888008
a: -0.0032621143135660065
b: 0.015656574404688095
c: -0.03854970201576757
discriminant: -0.0002578858168278246
-0.013398123665888008
a: -0.0030735130656316164
b: 0.014241555527352692
c: -0.11938038284883812
discriminant: -0.0012648467620253638
-0.013398123665888008
a: -0.004630994449443003
b: 0.027492228981621833
c: -0.06616496844574538
discriminant: -0.00046981575210134556
-0.013398123665888008
a: -0.0024955755127531567
b: 0.01328003837296926
c: -0.07485194945041018
discriminant: -0.000570835349333587
-0.013398123665888008
a: -0.007226853658850136
b: 0.04272861855322352
c: -0.08261409817703214
discriminant: -0.0005624251472662789
-0.013398123665888008
a: -0.007073270082849042
b: 0.0436915317049554
c: -0.11334093467756301
discriminant: -0.0012978142269426934
-0.013398123665888008
a: -0.0044688818369117075
b: 0.02842620204148076
c: -0.07371337030917602
discriminant: -0.0005096164043458087
-0.013398123665888008
a: -0.01281306432303337
b: 0.08501650270350686
c: -0.05087809518859299
discriminant: 0.004620188506795962
-0.013398123665888008
a: 0.010058640176226265
b: -0.09714272209991473
c: -0.14894128209413682
discriminant: 0.015429295512864198
-0.013398123665888008
a: 0.0026635173889203653
b: -0.03807899536319179
c: -0.08424954997733802
discriminant: 0.0023476104533634023
-0.013398123665888008
a: 0.0030071126195359912
b: -0.03217063299522627
c: -0.13462046732697008
discriminant: 0.002654225251900598
-0.013398123665888008
a: -0.0031904055007954193
b: 0.01151142192322005
c: -0.0940497480908774
discriminant: -0.001067714499935844
-0.013398123665888008
a: -0.0028005443212323388
b: 0.013429570415340139
c: -0.16631925182418017
discriminant: -0.001682784383290697
-0.013398123665888008
a: 0.005958014732271251
b: -0.06265417168621892
c: -0.10587521297823577
discriminant: 0.0064487695445129365
-0.013398123665888008
a: 0.00637393722799894
b: -0.05511306766395069
c: -0.1761772615642362
discriminant: 0.007529221452175975
-0.013398123665888008
a: 0.0018421395829568855
b: -0.024207226138900917
c: -0.03758814368796626
discriminant: 0.0008629602266897824
-0.013398123665888008
a: 0.005488597839364232
b: -0.05144387644820317
c: -0.040636103096703624
discriminant: 0.0035386133346449913
-0.013398123665888008
a: 0.007189414329084012
b: -0.06723853448998543
c: -0.008551999298820223
discriminant: 0.004766955985565978
-0.013398123665888008
a: 0.014618029283726165
b: -0.12115555145864484
c: -0.01722042905408172
discriminant: 0.01568558259401192
-0.013398123665888008
a: 0.015173706135912152
b: -0.11057033620483772
c: -0.14683797268816778
discriminant: 0.021138104237104258
-0.013398123665888008
a: 0.021924949899667204
b: -0.18037452131731074
c: 0.010356669077241754
discriminant: 0.031626690137865156
-0.013398123665888008
a: 0.020679825431107073
b: -0.15351036193494944
c: -0.11072937341565436
discriminant: 0.03272488767072557
-0.013398123665888008
a: 0.016876801434086326
b: -0.12981274119846187
c: 0.00028286505677310725
discriminant: 0.016832252347875633
-0.013398123665888008
a: 0.016670345088415348
b: -0.11366179613109556
c: -0.17953674132121133
discriminant: 0.02489076163524334
-0.013398123665888008
a: 0.007742150973020343
b: -0.061040011024014795
c: -0.005326065606532482
discriminant: 0.0038908237618837903
-0.013398123665888008
a: 0.009101386966304153
b: -0.06299965018746254
c: -0.15842668855284547
discriminant: 0.009736566316981029
-0.013398123665888008
a: 0.011109636107773258
b: -0.08863093972044264
c: -0.011167671561938097
discriminant: 0.008351718544625778
-0.013398123665888008
a: 0.012608465504972436
b: -0.0891855406881184
c: -0.15721804731248568
discriminant: 0.015883173973026424
-0.013398123665888008
a: 0.022612290480108863
b: -0.14952404071061703
c: -0.1112558243016285
discriminant: 0.03242043481727977
-0.013398123665888008
a: 0.023997500150144326
b: -0.155618404683947
c: -0.15594647753768254
discriminant: 0.03918639034887676
-0.013398123665888008
a: 0.02100672784080984
b: -0.1768370323348385
c: 0.3651882861277044
discriminant: 0.000585692255646808
-0.013398123665888008
a: 0.019671659086401977
b: -0.15158770305758545
c: 0.27385874268477195
discriminant: 0.0014298084225726412
-0.013398123665888008
a: 0.010815199121559097
b: -0.08600969459773108
c: -0.01295565040629143
discriminant: 0.00795813932036837
-0.013398123665888008
a: 0.010311678064454023
b: -0.06903204751364675
c: -0.20573688549530422
discriminant: 0.013251393700770452
-0.013398123665888008
a: 0.02622376131751926
b: -0.2056016759116825
c: 0.1721740104737648
discriminant: 0.024211848514716246
-0.013398123665888008
a: 0.0005453399686860799
b: -0.011517321813047612
c: -0.0307879029349285
discriminant: 0.00019980819783507826
-0.013398123665888008
a: 0.0008806874734622093
b: -0.00909640208697364
c: -0.18087736612720284
discriminant: 0.0007199302532521595
-0.013398123665888008
a: 0.00413252354048134
b: -0.03281438964469527
c: -0.005541619880007009
discriminant: 0.0011683876661799973
-0.013398123665888008
a: 0.004566572303496106
b: -0.030901305359369136
c: -0.17441306342706098
discriminant: 0.004140770132168681
-0.013398123665888008
a: 0.017292815374609534
b: -0.14312840966897106
c: 0.014987607083689403
discriminant: 0.019449029965547083
-0.013398123665888008
a: 0.01733355560808328
b: -0.1258779686944651
c: -0.11460301555467456
discriminant: 0.023791173974528675
-0.013398123665888008
a: 0.015566135635392024
b: -0.12549249426470277
c: 0.008926189898250225
discriminant: 0.01519258098612274
-0.013398123665888008
a: 0.014313255683689262
b: -0.10122793947679687
c: -0.1566205077939976
discriminant: 0.019214093224176988
-0.013398123665888008
a: 0.019772145319692347
b: -0.15776823312875288
c: -0.016482498170247162
discriminant: 0.026194392780783275
-0.013398123665888008
a: 0.021565910227772465
b: -0.15440774738922292
c: -0.1448617741332464
discriminant: 0.03633805651938785
-0.013398123665888008
a: 0.01961832105601701
b: -0.1490545575970603
c: 0.0093270091289408
discriminant: 0.021485340102119516
-0.013398123665888008
a: 0.02143171882273733
b: -0.14830223572469503
c: -0.14232133707702477
discriminant: 0.03419431663578627
-0.013398123665888008
a: 0.01065895359125485
b: -0.08674991993350922
c: -0.005791911305561892
discriminant: 0.007772491463712855
-0.013398123665888008
a: 0.009561846045434244
b: -0.06675408915974398
c: -0.1896728041236483
discriminant: 0.011710597027691571
-0.013398123665888008
a: 0.014565696191824504
b: -0.09525585811016948
c: -0.18290581076099233
discriminant: 0.01973028038936058
-0.013398123665888008
a: 0.014085964177893507
b: -0.10390545044191729
c: 0.004764692113981561
discriminant: 0.010527881501792787
-0.013398123665888008
a: 0.015449853777757016
b: -0.10387024725716115
c: -0.15902577110848515
discriminant: 0.0206167279073484
-0.013398123665888008
a: 0.015161397613740902
b: -0.11532009426066636
c: 0.023309993511285376
discriminant: 0.011885075820295703
-0.013398123665888008
a: 0.01664081767080201
b: -0.11354199972377838
c: -0.14892411412840667
discriminant: 0.02280466182126059
-0.013398123665888008
a: 0.00578019676107399
b: -0.05061766878469648
c: -0.03118491732986317
discriminant: 0.003283168225774977
-0.013398123665888008
a: 0.005882147805820868
b: -0.044106361466762584
c: -0.1732384051658381
discriminant: 0.006021426741157284
-0.013398123665888008
a: 0.013269286835844026
b: -0.1078817962195665
c: 0.004553465434867232
discriminant: 0.011396796999750656
-0.013398123665888008
a: 0.013240748370331443
b: -0.09316206981551789
c: -0.15326529888185603
discriminant: 0.016796560277904618
-0.013398123665888008
a: 0.009114517625340863
b: -0.07820481565217155
c: -0.022534760705514967
discriminant: 0.0069375670857231555
-0.013398123665888008
a: 0.008679053174265242
b: -0.06307023438110634
c: -0.1768025615238472
discriminant: 0.010115769796134776
-0.013398123665888008
a: 0.024527191917768733
b: -0.16355757231587442
c: -0.13241559827555582
discriminant: 0.039742210629105386
-0.013398123665888008
a: 0.0222430844398966
b: -0.17715106088396754
c: 0.04869045854883747
discriminant: 0.027050394448638864
-0.013398123665888008
a: 0.02360110438504111
b: -0.1684085833545253
c: -0.08368520315087336
discriminant: 0.03626170380766663
-0.013398123665888008
a: 0.00974143195769284
b: -0.08071540672472227
c: -0.02030447474645114
discriminant: 0.007306155519454327
-0.013398123665888008
a: 0.011320858641218385
b: -0.0819778054947988
c: -0.15346755011953606
discriminant: 0.013669898357412526
-0.013398123665888008
a: 0.016161026257424837
b: -0.13323996459097098
c: 0.013637146904478148
discriminant: 0.016871327007404676
-0.013398123665888008
a: 0.015470626879592355
b: -0.11253731685792123
c: -0.12689410742554597
discriminant: 0.02051717324237829
-0.013398123665888008
a: 0.02698340823470621
b: -0.21338146060608265
c: 0.031145910204864458
discriminant: 0.042169956490787766
-0.013398123665888008
a: 0.028680055698984217
b: -0.20457663974446333
c: -0.09760312642913249
discriminant: 0.05304865393866601
-0.013398123665888008
a: 0.025033642571311694
b: -0.18837557855831882
c: -0.004650721636500377
discriminant: 0.03595105660976861
-0.013398123665888008
a: 0.02366565853321964
b: -0.15570943255613034
c: -0.2065530005099937
discriminant: 0.043798278503277915
-0.013398123665888008
a: 0.006961570821516879
b: -0.05848698069682401
c: -0.021587664612365276
discriminant: 0.004021863135311203
-0.013398123665888008
a: 0.00801753665877502
b: -0.05786841212676305
c: -0.169756985862611
discriminant: 0.008792884551019443
-0.013398123665888008
a: 0.018721870878974273
b: -0.15225576891083042
c: 0.012321521096709587
discriminant: 0.02225909145860758
-0.013398123665888008
a: 0.01964510071364488
b: -0.14144290523832703
c: -0.11725677356310038
discriminant: 0.029220179946274998
-0.013398123665888008
a: 0.02297567951652422
b: -0.17406394156205968
c: 0.023488701017010505
discriminant: 0.028139580284814968
-0.013398123665888008
a: 0.02577104820680455
b: -0.1782756446751098
c: -0.12183233549261285
discriminant: 0.04434119344883686
-0.013398123665888008
a: 0.012733108295966515
b: -0.10638561804922236
c: -0.016327602539418007
discriminant: 0.012149504253106656
-0.013398123665888008
a: 0.012867332870939897
b: -0.09358380930676846
c: -0.1546910379560601
discriminant: 0.016719773674492896
-0.013398123665888008
a: 0.00884696022181084
b: -0.07545661657946506
c: -0.0357222604603048
discriminant: 0.006957834654922333
-0.013398123665888008
a: 0.0100471945515512
b: -0.07347245058867027
c: -0.16854604126892758
discriminant: 0.012171860465595367
-0.013398123665888008
a: 0.017894367285183274
b: -0.13823643587220447
c: 0.01576434250319869
discriminant: 0.017980940463603448
-0.013398123665888008
a: 0.019891106357296108
b: -0.13800509471058536
c: -0.13998704687629482
discriminant: 0.03018339511831834
-0.013398123665888008
a: 0.010971736983241165
b: -0.08846416741960725
c: -0.009211773616134566
discriminant: 0.008230185546305856
-0.013398123665888008
a: 0.012323861756133266
b: -0.08762521225304601
c: -0.15655448855791831
discriminant: 0.015395601319551094
-0.013398123665888008
a: 0.011968644865383321
b: -0.09366704896113481
c: -0.006880735912184632
discriminant: 0.009102928399269336
-0.013398123665888008
a: 0.012752932966892347
b: -0.08828798619399394
c: -0.17501920749847344
discriminant: 0.016722801390777482
-0.013398123665888008
a: 0.007863661215194835
b: -0.06158825071870633
c: -0.010837795424794239
discriminant: 0.004134011632750912
-0.013398123665888008
a: 0.008344808171239929
b: -0.058378068538976896
c: -0.16111511625229535
discriminant: 0.008785897840791186
-0.013398123665888008
a: 0.01294328332535883
b: -0.10666915764997925
c: -0.009206808956481516
discriminant: 0.011854974541140893
-0.013398123665888008
a: 0.012181920445262274
b: -0.08688158837735316
c: -0.16791862998723295
discriminant: 0.015730695966099443
-0.013398123665888008
a: 0.013492553293453741
b: -0.10591990547076982
c: -0.01116205303106732
discriminant: 0.011821444756480944
-0.013398123665888008
a: 0.015459192736099202
b: -0.10791403503552893
c: -0.16452156575494337
discriminant: 0.02181892133465132
-0.013398123665888008
a: 0.01483436588698971
b: -0.10889494255167836
c: 0.010192765997456887
discriminant: 0.01125329563250636
-0.013398123665888008
a: 0.015919467214576745
b: -0.10696327505757852
c: -0.15502973060772518
discriminant: 0.021313105065820584
-0.013398123665888008
a: 0.007812301031566442
b: -0.06663080032709298
c: -0.0010087433723304784
discriminant: 0.004471185979781907
-0.013398123665888008
a: 0.008839285025434757
b: -0.06463625604145137
c: -0.14182008519704625
discriminant: 0.009192198216608589
-0.013398123665888008
a: 0.015847298318338334
b: -0.11935226098342966
c: 0.003079546907229558
discriminant: 0.014049752207759973
-0.013398123665888008
a: 0.01776528215424743
b: -0.12136772822487005
c: -0.15458465222307216
discriminant: 0.025715085308302275
-0.013398123665888008
a: 0.017566568680388934
b: -0.13774752096083082
c: -0.00866301204304254
discriminant: 0.0195830971149871
-0.013398123665888008
a: 0.016323725720650065
b: -0.11174141538915455
c: -0.19109931463396646
discriminant: 0.024963955103127895
-0.013398123665888008
a: 0.004525973088698973
b: -0.04064768973420366
c: -0.018193251353320283
discriminant: 0.0019816033448123403
-0.013398123665888008
a: 0.005722898188089164
b: -0.042305203097360994
c: -0.15836759184741978
discriminant: 0.005415016626851534
-0.013398123665888008
a: 0.018667960030635287
b: -0.141548439739139
c: 0.014852474783399905
discriminant: 0.018926899170134553
-0.013398123665888008
a: 0.017695195877191896
b: -0.11552512069163534
c: -0.18863458370393593
discriminant: 0.026697757142231698
-0.013398123665888008
a: 0.01996116397519663
b: -0.13884419017356686
c: 0.14692579656075166
discriminant: 0.007546469475611422
-0.013398123665888008
a: 0.023800459141258643
b: -0.16664601168149096
c: 0.011140046831221606
discriminant: 0.02671034029159483
-0.013398123665888008
a: 0.009763505398963233
b: -0.08212460865847043
c: -0.02065664004552381
discriminant: 0.007551176213742564
-0.013398123665888008
a: 0.011092346174735302
b: -0.08106126631984806
c: -0.15142200517749338
discriminant: 0.013289430096982604
-0.013398123665888008
a: 0.01079527794382859
b: -0.08914859101335398
c: -0.03339773099054233
discriminant: 0.009389622434610747
-0.013398123665888008
a: 0.012118359252407954
b: -0.08730517399857723
c: -0.172929298721349
discriminant: 0.01600467087561096
-0.013398123665888008
a: 0.021853107436853786
b: -0.14406219882907695
c: -0.11950446506224399
discriminant: 0.031200092788224332
-0.013398123665888008
a: 0.014397939668949747
b: -0.11938467516014861
c: -0.017929171026341284
discriminant: 0.015285273154100379
-0.013398123665888008
a: 0.015091647972328998
b: -0.11006153627291906
c: -0.1466001660302153
discriminant: 0.02096329416040705
-0.013398123665888008
a: 0.012365037702519292
b: -0.091078305990073
c: 1.7843351985846745e-05
discriminant: 0.008294375287141189
-0.013398123665888008
a: 0.013698476036477178
b: -0.09165184329334622
c: -0.1646780628254515
discriminant: 0.017423414368459816
-0.013398123665888008
a: 0.004517094915460352
b: -0.039903596262115704
c: -0.026575373778560896
discriminant: 0.0020724709377363177
-0.013398123665888008
a: 0.005141566922200537
b: -0.037691034571236584
c: -0.18180874154891924
discriminant: 0.005159741333909469
-0.013398123665888008
a: 0.024266167485534472
b: -0.15791071273873078
c: -0.160404522210294
discriminant: 0.04050540520322246
-0.013398123665888008
a: 0.008388055754914876
b: -0.06759193670378585
c: -0.020288939960422137
discriminant: 0.005249408945753159
-0.013398123665888008
a: 0.009360153166359426
b: -0.06607752860720392
c: -0.17626269652607973
discriminant: 0.010965623134834394
-0.013398123665888008
a: 0.009443273997750535
b: -0.08261325888323057
c: -0.034251680335622425
discriminant: 0.00811874255247826
-0.013398123665888008
a: 0.009788048277688973
b: -0.07286065923306737
c: -0.16341518820329048
discriminant: 0.011706738669642912
-0.013398123665888008
a: 0.012191799045874654
b: -0.0961421968580323
c: -0.00504187523792865
discriminant: 0.009489200135549426
-0.013398123665888008
a: 0.014085397629773289
b: -0.09913429486534459
c: -0.14649621706283333
discriminant: 0.01808143829279943
-0.013398123665888008
a: 0.019599869471179046
b: -0.15619459532490476
c: 0.02145170862424739
discriminant: 0.0227149488528347
-0.013398123665888008
a: 0.020668782306980743
b: -0.14697770865660081
c: -0.11597313690925704
discriminant: 0.031190540922885056
-0.013398123665888008
a: 0.006230729230832585
b: -0.052830782539506516
c: 4.973634920169001e-05
discriminant: 0.0027898520088374032
-0.013398123665888008
a: 0.006406484990376327
b: -0.0456969910389205
c: -0.16769998196598024
discriminant: 0.0063856846594169125
-0.013398123665888008
a: 0.010662287844665129
b: -0.08097903349300212
c: 0.006390456782525145
discriminant: 0.006285056306764057
-0.013398123665888008
a: 0.011270914389559546
b: -0.07565719854892933
c: -0.1826897406669189
discriminant: 0.013960333399902826
-0.013398123665888008
a: 0.011970837188708096
b: -0.10277723705456462
c: -0.0012464846758394321
discriminant: 0.010622846317020944
-0.013398123665888008
a: 0.011851823650721655
b: -0.08814283809148324
c: -0.13026203905966927
discriminant: 0.013944530768095893
-0.013398123665888008
a: 0.004903192610133137
b: -0.04448192922440841
c: -0.02205072526751639
discriminant: 0.0024111178402443285
-0.013398123665888008
a: 0.00465836258445348
b: -0.03316779492038249
c: -0.19691972273228664
discriminant: 0.0047693964939487
-0.013398123665888008
a: 0.02272720334283118
b: -0.1840975484919709
c: 0.011809882086413093
discriminant: 0.0328182849942225
-0.013398123665888008
a: 0.021062073575265815
b: -0.15663562608927767
c: -0.1068380335291651
discriminant: 0.033535641451691967
-0.013398123665888008
a: 0.020689083882242772
b: -0.1517274748042148
c: 0.05386669241800368
discriminant: 0.018563416538883444
-0.013398123665888008
a: 0.02272474932940764
b: -0.1520406769352868
c: -0.12749185634180582
discriminant: 0.0347052493505738
-0.013398123665888008
a: 0.019833093636155326
b: -0.14925501245637346
c: 0.023955221088148737
discriminant: 0.02037663417168797
-0.013398123665888008
a: 0.020271070066725766
b: -0.1374645631409266
c: -0.1532412813083429
discriminant: 0.0313219651215908
-0.013398123665888008
a: 0.005789965358031302
b: -0.04967263464946492
c: -0.019871420258645744
discriminant: 0.002927589972668984
-0.013398123665888008
a: 0.005611643151338733
b: -0.03892510906274799
c: -0.20512471477505823
discriminant: 0.006119510918897892
-0.013398123665888008
a: 0.022333048274861635
b: -0.1866259651682527
c: 0.0023635116819642477
discriminant: 0.034618113193015845
-0.013398123665888008
a: 0.02149176262588139
b: -0.1618579141800145
c: -0.1034671841374063
discriminant: 0.03509275302690292
-0.013398123665888008
a: 0.016366512219840493
b: -0.14554989683836722
c: 0.0023360743123221894
discriminant: 0.021031838914543032
-0.013398123665888008
a: 0.015768562965704985
b: -0.12540053388218853
c: -0.07370449758583442
discriminant: 0.020374149942089435
-0.013398123665888008
a: 0.0025930883671819657
b: -0.025075019620178454
c: -0.016243544773567153
discriminant: 0.0007972403969288801
-0.013398123665888008
a: 0.0029981796930004575
b: -0.02288552225601409
c: -0.16653258187604802
discriminant: 0.002520925549745329
-0.013398123665888008
a: 0.01122563043452779
b: -0.08805311746956085
c: -0.016313491095330868
discriminant: 0.008485868384640858
-0.013398123665888008
a: 0.010728012344672341
b: -0.0714334116924123
c: -0.20998191281729406
discriminant: 0.014113486517465034
-0.013398123665888008
a: 0.014098069834183762
b: -0.11787524000694163
c: 0.008942497362151247
discriminant: 0.013390284397479644
-0.013398123665888008
a: 0.014805546160895178
b: -0.10823252150152496
c: -0.117237712900362
discriminant: 0.018657352191154407
-0.013398123665888008
a: 0.01451688000798106
b: -0.11655131203203978
c: 0.015471098031648478
discriminant: 0.012685840041521288
-0.013398123665888008
a: 0.0162074888523999
b: -0.11550615605225759
c: -0.12249555954477909
discriminant: 0.021283053749130462
-0.013398123665888008
a: 0.02764889473194932
b: -0.22013117224781031
c: 0.005827747588520893
discriminant: 0.04781320987679759
-0.013398123665888008
a: 0.029127020494344395
b: -0.20788954121678144
c: -0.11964424518229799
discriminant: 0.0571575828731445
-0.013398123665888008
a: 0.0013339501941900724
b: -0.016127175492737525
c: -0.010556204928051094
discriminant: 0.00031641159582828965
-0.013398123665888008
a: 0.0020260594528449527
b: -0.016204030785894788
c: -0.15916010060665842
discriminant: 0.001552441919109722
-0.013398123665888008
a: 0.01037822588631667
b: -0.08151703669651114
c: -0.0037368562266515415
discriminant: 0.006800155023879859
-0.013398123665888008
a: 0.012147914543991202
b: -0.08422168459755541
c: -0.16292199501964333
discriminant: 0.015009942047790853
-0.013398123665888008
a: 0.011552701353398474
b: -0.09342606527300018
c: -0.013193530775420403
discriminant: 0.009338113355776105
-0.013398123665888008
a: 0.013330964745152288
b: -0.09535767626833119
c: -0.14926767767032645
discriminant: 0.017052615017751363
-0.013398123665888008
a: 0.011515192128409782
b: -0.09920709946736528
c: -0.019772285124077138
discriminant: 0.010752775232813495
-0.013398123665888008
a: 0.0107818297454503
b: -0.0810119219032393
c: -0.15281549507182468
discriminant: 0.013153454091780996
-0.013398123665888008
a: -0.0036691193118630946
b: 0.017630730248459445
c: -0.0014122683372601585
discriminant: 0.0002901155249748467
-0.013398123665888008
a: 0.01119638709952318
b: -0.0931841873698318
c: -0.013081506926886699
discriminant: 0.009269155237369991
-0.013398123665888008
a: 0.002308319162384132
b: -0.025765132555812642
c: -0.02136311956530712
discriminant: 0.0008610936486622037
-0.013398123665888008
a: 0.003563708731354741
b: -0.034132222940567586
c: -0.027601087074433095
discriminant: 0.001558457582872767
-0.013398123665888008
a: 0.007983479504682948
b: -0.06557051482294557
c: -0.0368755316711028
discriminant: 0.0054770726194282695
-0.013398123665888008
a: 0.0009087726591246285
b: -0.016273944146334984
c: -0.009613164857894207
discriminant: 0.0002997859836400785
-0.013398123665888008
a: 0.0006204088270639601
b: -0.013727212680449158
c: -0.00492290395995687
discriminant: 0.00020065322026046562
-0.013398123665888008
a: -0.002740314531039338
b: 0.024145375025016597
c: -0.3134766867287796
discriminant: -0.0028530997440410696
-0.013398123665888008
a: -0.0031890236806642078
b: 0.03757969419554237
c: -0.6558656015866887
discriminant: -0.006954050323341627
-0.013398123665888008
a: -0.002784479803993156
b: 0.024434399338365623
c: -0.32632323028748
discriminant: -0.0030375219062104613
-0.013398123665888008
a: -0.003136891824569907
b: 0.03623054661297408
c: -0.647861605815527
discriminant: -0.006816434591066945
-0.013398123665888008
a: 0.009248090926423893
b: -0.05493250191444704
c: -0.4387733859370627
discriminant: 0.019248844443544084
-0.013398123665888008
a: 0.0098032572942362
b: -0.04585590060022493
c: -0.7067388940394558
discriminant: 0.02981613649230859
-0.013398123665888008
a: -0.002800116197936197
b: 0.02302748412506453
c: -0.32844007703781186
discriminant: -0.0031484164939298586
-0.013398123665888008
a: -0.0029674488379576236
b: 0.03155617649617992
c: -0.6312489329100898
discriminant: -0.0064970033746460844
-0.013398123665888008
a: -0.0020031168528329545
b: 0.01753101784111491
c: -0.33837580679732404
discriminant: -0.002403888538201181
-0.013398123665888008
a: -0.0021781358914591794
b: 0.026840974959637054
c: -0.6393627881406435
discriminant: -0.004850038209266325
-0.013398123665888008
a: 0.00923229087107152
b: -0.059221650998112524
c: -0.40201723835802594
discriminant: 0.018353364265766985
-0.013398123665888008
a: 0.009152135838082547
b: -0.045690214684436986
c: -0.6668225875049955
discriminant: 0.026498999320899556
-0.013398123665888008
a: 0.005837295350039049
b: -0.03470788413384676
c: -0.39920488573087975
discriminant: 0.010525744513807469
-0.013398123665888008
a: 0.005850376028288933
b: -0.02218781533705666
c: -0.6814634357522394
discriminant: 0.016439568544152593
-0.013398123665888008
a: 0.00973050896506261
b: -0.07300273106898067
c: -0.30360591563138406
discriminant: 0.017146359079118816
-0.013398123665888008
a: 0.009288647833829124
b: -0.05656638033034833
c: -0.5270416452208256
discriminant: 0.02278177232855026
-0.013398123665888008
a: 0.01642708200127454
b: -0.10740825118560493
c: -0.48416849768980097
discriminant: 0.043350434878687054
-0.013398123665888008
a: 0.01503942536936974
b: -0.07670756217453917
c: -0.78418518580488
discriminant: 0.05305882840547213
-0.013398123665888008
a: -0.004764584992205679
b: 0.03611853897174133
c: -0.306700218749299
discriminant: -0.004540648179983238
-0.013398123665888008
a: -0.005058442780931522
b: 0.045248594976189264
c: -0.6220415395769404
discriminant: -0.010538810793930795
-0.013398123665888008
a: 0.01262613064453987
b: -0.09557819172791415
c: -0.309462406262737
discriminant: 0.02476444181816588
-0.013398123665888008
a: 0.012083798437381785
b: -0.07708434908301465
c: -0.5185795396823837
discriminant: 0.031007639398640676
-0.013398123665888008
a: -0.0037569852538540446
b: 0.03148558760519886
c: -0.31183037322269624
discriminant: -0.0036948262287612396
-0.013398123665888008
a: -0.004106134657070961
b: 0.043351099222439154
c: -0.6338723806725256
discriminant: -0.008531743597964374
-0.013398123665888008
a: -0.007492232729289736
b: 0.050313363398975575
c: -0.2768762662628165
discriminant: -0.0057662511597138776
-0.013398123665888008
a: -0.007577871033602816
b: 0.05357042432935862
c: -0.6123901210307606
discriminant: -0.015692663074866553
-0.013398123665888008
a: 0.010729027278676317
b: -0.061475600459395874
c: -0.4938130386295899
discriminant: 0.02497178369993492
-0.013398123665888008
a: 0.011284162974671916
b: -0.04976916281969834
c: -0.7768600080366105
discriminant: 0.037541829324533836
-0.013398123665888008
a: 0.0009590928199470694
b: -0.0010667253987301228
c: -0.37395037127736275
discriminant: 0.0014357503675109335
-0.013398123665888008
a: 0.0010003691968440854
b: 0.008112630353322908
c: -0.6632364315925406
discriminant: 0.0027197399568095245
-0.013398123665888008
a: -0.007395646163733378
b: 0.04953243892654975
c: -0.25750079677180115
discriminant: -0.005164076613202256
-0.013398123665888008
a: -0.0074999202334219695
b: 0.05306147567372177
c: -0.5870307561181142
discriminant: -0.014795215181132002
-0.013398123665888008
a: -0.0032449311206124327
b: 0.02206914168628657
c: -0.26849440865977947
discriminant: -0.0029979364347128114
-0.013398123665888008
a: -0.003628310041056005
b: 0.03139752138711065
c: -0.5785852695500905
discriminant: -0.007411342623208684
-0.013398123665888008
a: -0.0013233950124751856
b: 0.014738454523821859
c: -0.35399010211098225
discriminant: -0.0016566529006462574
-0.013398123665888008
a: -0.0015970538843572916
b: 0.0263936238246322
c: -0.6749264148639224
discriminant: -0.0036149520314588796
-0.013398123665888008
a: 0.012099243972447824
b: -0.08717496277757769
c: -0.343438784574558
discriminant: 0.024220872711946166
-0.013398123665888008
a: 0.01011687201508392
b: -0.05792511954717636
c: -0.5968097849043693
discriminant: 0.02750671231946374
-0.013398123665888008
a: 0.015775071282358256
b: -0.09881569123029244
c: -0.5064640326097484
discriminant: 0.04172256569879808
-0.013398123665888008
a: 0.015063311165846376
b: -0.07220371913578716
c: -0.8007921138944866
discriminant: 0.05346370022003381
-0.013398123665888008
a: 0.00803710967781278
b: -0.0424986463368677
c: -0.4560992841371342
discriminant: 0.016469014822794326
-0.013398123665888008
a: 0.007694466917522943
b: -0.02167925040190513
c: -0.7630448943478269
discriminant: 0.023954884682565073
-0.013398123665888008
a: 0.0053785871229414155
b: -0.030322307449271002
c: -0.41085308651078856
discriminant: 0.009758678811158767
-0.013398123665888008
a: 0.005543037931257791
b: -0.0193133806603914
c: -0.6938170232607567
discriminant: 0.015756422981680153
-0.013398123665888008
a: 0.013697645332327195
b: -0.09411006705113026
c: -0.40107343741849044
discriminant: 0.03083175151227147
-0.013398123665888008
a: 0.012934545890782696
b: -0.07345593951457763
c: -0.6496464045365647
discriminant: 0.03900729997900999
-0.013398123665888008
a: 0.02692616639358368
b: -0.17914918249962214
c: -0.5787260616393434
discriminant: 0.09442592651830023
-0.013398123665888008
a: 0.025470808057980673
b: -0.14248493766313303
c: -0.8539263110705625
discriminant: 0.10730273012061808
-0.013398123665888008
a: -0.0029417352669553042
b: 0.027532956497853034
c: -0.32014944035935533
discriminant: -0.00300911590409181
-0.013398123665888008
a: -0.0033163303515696767
b: 0.040857855654805195
c: -0.6651907055111103
discriminant: -0.00715460413636527
-0.013398123665888008
a: 0.010410223640717847
b: -0.07483397298438246
c: -0.3406177731027821
discriminant: 0.01978375228864028
-0.013398123665888008
a: 0.009566767611884708
b: -0.054756879519724744
c: -0.5955018855396973
discriminant: 0.025786428460327453
-0.013398123665888008
a: 0.01191994983436145
b: -0.08143485074025542
c: -0.3915792877100658
discriminant: 0.025302056777803575
-0.013398123665888008
a: 0.010791101576071951
b: -0.05801361117317966
c: -0.6630460611249019
discriminant: 0.03198556866220579
-0.013398123665888008
a: -0.007891639261965865
b: 0.052100260642671384
c: -0.25478320583744096
discriminant: -0.005328191442870826
-0.013398123665888008
a: -0.0079621361204635
b: 0.05453610686110711
c: -0.5750241994447934
discriminant: -0.015339496842593899
-0.013398123665888008
a: 0.013526329423410586
b: -0.09656779844657237
c: -0.37395222285668417
discriminant: 0.029558143516722465
-0.013398123665888008
a: 0.012798997124135222
b: -0.07420445975821194
c: -0.6165754834286766
discriminant: 0.037072493204871756
-0.013398123665888008
a: 0.015825504696177422
b: -0.10357103101929832
c: -0.47428641541721517
discriminant: 0.04075024604447363
-0.013398123665888008
a: 0.01485687545569284
b: -0.07735258824622565
c: -0.7627738463368171
discriminant: 0.051313167051933645
-0.013398123665888008
a: 0.003578344626787992
b: -0.01790442651673463
c: -0.39180858721202305
discriminant: 0.0059286731000112985
-0.013398123665888008
a: 0.003463204178465327
b: -0.004706767550967411
c: -0.6821334773200257
discriminant: 0.009471623696482025
-0.013398123665888008
a: 0.01751614032514639
b: -0.11553546942835197
c: -0.48432324946769023
discriminant: 0.047282340697657424
-0.013398123665888008
a: 0.01629928377170515
b: -0.086888595794337
c: -0.7716752758420745
discriminant: 0.057860645281346955
-0.013398123665888008
a: 0.012900784295196846
b: -0.08892486890751738
c: -0.39611883893386357
discriminant: 0.02834860709561754
-0.013398123665888008
a: 0.011408368813688587
b: -0.059233962607096236
c: -0.6775400153562375
discriminant: 0.03442716785100362
-0.013398123665888008
a: 0.010343776398616455
b: -0.08101388162193729
c: -0.2641695457317216
discriminant: 0.017493291864945314
-0.013398123665888008
a: 0.01009861263135025
b: -0.06683092740094213
c: -0.4558121172932942
discriminant: 0.022878652878152248
-0.013398123665888008
a: 0.012630993054558726
b: -0.08087522265216174
c: -0.45358357578972697
discriminant: 0.029457645620884546
-0.013398123665888008
a: 0.011488203328047935
b: -0.0525447795159647
c: -0.7626394710440082
discriminant: 0.03780638309177531
-0.013398123665888008
a: 0.003603960140284428
b: -0.0202124967693382
c: -0.3785976995702046
discriminant: 0.0058663490994680925
-0.013398123665888008
a: 0.003151453994659115
b: -0.004460401328220759
c: -0.687481940290649
discriminant: 0.008686166007948653
-0.013398123665888008
a: 0.008915042702855617
b: -0.05565440336090344
c: -0.4229307812211235
discriminant: 0.01817919651321175
-0.013398123665888008
a: 0.008834360013939328
b: -0.04064881183560193
c: -0.7048589428441688
discriminant: 0.02656023654416646
-0.013398123665888008
a: 0.01207375443634269
b: -0.08263415184962725
c: -0.4042399929145438
discriminant: 0.026351180683103697
-0.013398123665888008
a: 0.011129727425167083
b: -0.05920933231679548
c: -0.6797159023553044
discriminant: 0.03376595591246481
-0.013398123665888008
a: 0.007932327684758152
b: -0.05845137495807043
c: -0.30602002318134847
discriminant: 0.013126367642375911
-0.013398123665888008
a: 0.006322460372091075
b: -0.0342606675516379
c: -0.559074534531545
discriminant: 0.015312699699567679
-0.013398123665888008
a: -0.008276736491031679
b: 0.05704088624806955
c: -0.208490300658155
discriminant: -0.0036488144139688594
-0.013398123665888008
a: -0.008323244089765104
b: 0.060785173335414
c: -0.4227156311284851
discriminant: -0.010378624216349632
-0.013398123665888008
a: 0.010904397843824822
b: -0.07242182322407392
c: -0.41646344637309707
discriminant: 0.023410052905749632
-0.013398123665888008
a: 0.009847223100995457
b: -0.04860317554878413
c: -0.7106149453327776
discriminant: 0.030352604295800133
-0.013398123665888008
a: 0.005652160464789188
b: -0.03903847051721715
c: -0.3335583535822316
discriminant: 0.009065303535594283
-0.013398123665888008
a: 0.0049727496519974025
b: -0.023100509799395708
c: -0.6121545081748939
discriminant: 0.012709998022973356
-0.013398123665888008
a: 0.010421769096952888
b: -0.07387277016533172
c: -0.35859608588907077
discriminant: 0.02040600859672785
-0.013398123665888008
a: 0.009508377059675258
b: -0.0517007184502678
c: -0.6172907885470832
discriminant: 0.02615069858015361
-0.013398123665888008
a: -0.0031708602897982307
b: 0.027975332045489812
c: -0.3343156693727637
discriminant: -0.003457653918030235
-0.013398123665888008
a: -0.003395859599103212
b: 0.03805341104069107
c: -0.64574515269814
discriminant: -0.007323377409625605
-0.013398123665888008
a: -0.003649550137419204
b: 0.01720085323932928
c: -0.0034037787253221596
discriminant: 0.0002461803077019684
-0.013398123665888008
a: 0.0022460691265893066
b: -0.028573315296012758
c: -0.016137449787152813
discriminant: 0.000961417658000593
-0.013398123665888008
a: 0.009832197029283216
b: -0.08623509003719904
c: -0.019938232201577866
discriminant: 0.008220637263409875
-0.013398123665888008
a: 0.005200310418277602
b: -0.051557506888983695
c: -0.009942399210147723
discriminant: 0.0028649907653884262
-0.013398123665888008
a: -0.002611662283193432
b: 0.00890408131176583
c: -0.005826421565178763
discriminant: 1.841608221548863e-05
-0.013398123665888008
a: 0.013291756685488442
b: -0.08247916837635932
c: -0.1715324685643681
discriminant: 0.015922684559330935
-0.013398123665888008
a: 0.003879383125156812
b: -0.02231989429908987
c: -0.17744439494862407
discriminant: 0.003251676847191956
-0.013398123665888008
a: 0.020767404923105418
b: -0.13890860805857613
c: -0.18415224491917292
discriminant: 0.03459305834371251
-0.013398123665888008
a: 0.015759313238381995
b: -0.09832374830088797
c: -0.16164552905272156
discriminant: 0.019857249583639637
-0.013398123665888008
a: 0.009487085339553508
b: -0.05756724953215622
c: -0.19669992272164183
discriminant: 0.010778424031272726
-0.013398123665888008
a: 0.011465876786079318
b: -0.07331311192475543
c: -0.15955627186837795
discriminant: 0.012692622594847698
-0.013398123665888008
a: 0.0034241561856962945
b: -0.02215701614388868
c: -0.14900337673333797
discriminant: 0.0025317767009249217
-0.013398123665888008
a: 0.026992391254533014
b: -0.17780472699887662
c: -0.5421487191566009
discriminant: 0.09015008232562068
-0.013398123665888008
a: 0.03502588625266799
b: -0.25269456739475443
c: -0.45037232172205577
discriminant: 0.12695330323876897
-0.013398123665888008
a: 0.03404097320391
b: -0.21553281109564215
c: -0.6622657021158423
discriminant: 0.1366310687371659
-0.013398123665888008
a: 0.010567876028556078
b: -0.08265459795187388
c: 0.005841226917984721
discriminant: 0.0065848651148902055
-0.013398123665888008
a: 0.01034167909306673
b: -0.07019165216742454
c: -0.18155292695311853
discriminant: 0.012437116469817263
-0.013398123665888008
a: 0.00666305507165945
b: -0.04377603651087242
c: -0.16144584176758758
discriminant: 0.006219231511752649
-0.013398123665888008
a: 0.004474208548730228
b: -0.0270261511917827
c: -0.16660782648296546
discriminant: 0.0037121654943828835
-0.013398123665888008
a: 0.010361834807718646
b: -0.06774147280495713
c: -0.19859062250382375
discriminant: 0.012819960036771286
-0.013398123665888008
a: 0.012117864149864134
b: -0.07938405420412159
c: -0.193415298059337
discriminant: 0.015676949287437018
-0.013398123665888008
a: 0.020222741005277822
b: -0.129301776058256
c: -0.18309173787255106
discriminant: 0.03152941647263065
-0.013398123665888008
a: 0.008490308968796887
b: -0.06262902989560065
c: 0.05215631354838923
discriminant: 0.0021511025188669535
-0.013398123665888008
a: 0.009075207988202771
b: -0.05531640891352199
c: -0.14693146792079703
discriminant: 0.00839363962066068
-0.013398123665888008
a: 0.010881162811888782
b: -0.07055479311981738
c: -0.1895317639034516
discriminant: 0.01322728275641192
-0.013398123665888008
a: 0.014521323692213029
b: -0.09208897959242501
c: -0.17983796723588508
discriminant: 0.018926321499901623
-0.013398123665888008
a: 0.005540721900403088
b: -0.032994203604744976
c: -0.17086588035876515
discriminant: 0.004875498772853222
-0.013398123665888008
a: 0.014064862312095965
b: -0.09175108529865342
c: -0.1797806941334713
discriminant: 0.018532624490922023
-0.013398123665888008
a: 0.010842452446674263
b: -0.08447949386863637
c: -0.0015464868470432824
discriminant: 0.007203855724694866
-0.013398123665888008
a: 0.01083108283809122
b: -0.07204917830307414
c: -0.19014451893747786
discriminant: 0.01342896823743148
-0.013398123665888008
a: 0.02941921593883751
b: -0.2183209709336003
c: -0.3839800077277319
discriminant: 0.0928496094035445
-0.013398123665888008
a: 0.028651262499706245
b: -0.18773852840748978
c: -0.5757117709096379
discriminant: 0.10122523133862096
-0.013398123665888008
a: -0.006574237545586849
b: 0.042679991372098686
c: -0.19771611407334377
discriminant: -0.003377749138511618
-0.013398123665888008
a: 0.01469059209145478
b: -0.09318142022470971
c: -0.06307126516487271
discriminant: 0.012388993992010447
-0.013398123665888008
a: 0.013452990265745028
b: -0.08731950184537784
c: -0.1873258083350694
discriminant: 0.017705064506742973
-0.013398123665888008
a: 0.010682492589409875
b: -0.08163709805632804
c: 0.0022106949915886576
discriminant: 0.006570152847598155
-0.013398123665888008
a: 0.010673860315975333
b: -0.07145176992089575
c: -0.19098851617034096
discriminant: 0.013259694399059085
-0.013398123665888008
a: 0.013677765145833144
b: -0.09925779248406519
c: 0.006482702212797675
discriminant: 0.00949743385530167
-0.013398123665888008
a: 0.0138143100372967
b: -0.0847407876136877
c: -0.21347800190478627
discriminant: 0.018977206303209457
-0.013398123665888008
a: 0.041878699156097085
b: -0.32061548663826805
c: 0.029032339500244975
discriminant: 0.09793094382537972
-0.013398123665888008
a: 0.04032315960081124
b: -0.289072607071285
c: -0.09127589443240314
discriminant: 0.0982851019946079
-0.013398123665888008
a: 0.007101415829411466
b: -0.045110783273523275
c: -0.16614011658853778
discriminant: 0.006754302982919222
-0.013398123665888008
a: 0.027272091060109194
b: -0.17722397175210935
c: -0.18853840048822368
discriminant: 0.05197568186936114
-0.013398123665888008
a: 0.013253005516130748
b: -0.09604174843729546
c: 0.02488025286461404
discriminant: 0.007905064929062913
-0.013398123665888008
a: 0.01373705230444088
b: -0.08508071058367511
c: -0.18522747373072412
discriminant: 0.017416645292856713
-0.013398123665888008
a: 0.02003624937136658
b: -0.15490571978706752
c: 0.004700996796035306
discriminant: 0.02361902064635205
-0.013398123665888008
a: 0.019050446328941123
b: -0.1304421695438962
c: -0.1750667887295444
discriminant: 0.030355561446007606
-0.013398123665888008
a: 0.004170571766491337
b: -0.027863297805427206
c: -0.1645901589679254
discriminant: 0.003522103644729727
-0.013398123665888008
a: 0.009748766106066785
b: -0.06300188370708934
c: -0.17440715175439758
discriminant: 0.010770255469357278
-0.013398123665888008
a: 0.01708298339775511
b: -0.12792962700951072
c: -0.014879655770498768
discriminant: 0.0173827451167595
-0.013398123665888008
a: 0.01622848153701925
b: -0.10378038008796475
c: -0.22512058140761348
discriminant: 0.02538382808710841
-0.013398123665888008
a: 0.008944952052167148
b: -0.07640579196701883
c: -0.055074341948164296
discriminant: 0.007808394438231309
-0.013398123665888008
a: 0.009179378228801549
b: -0.06620908785591631
c: -0.1952524783990789
discriminant: 0.011552828712056644
-0.013398123665888008
a: 0.007146918719026535
b: -0.06058894990060806
c: -0.03814878341927774
discriminant: 0.0047616058673676945
-0.013398123665888008
a: 0.007619259745576731
b: -0.05237420670840595
c: -0.1821237464363058
discriminant: 0.00829365004807791
-0.013398123665888008
a: 0.015014867555288297
b: -0.12764188094694978
c: -0.013903311067988366
discriminant: 0.017127475268738576
-0.013398123665888008
a: 0.015675185464331866
b: -0.11661361227634048
c: -0.11994532320890794
discriminant: 0.021119395315652115
-0.013398123665888008
a: 0.010290972342582753
b: -0.08208943210646297
c: -0.07177874739385037
discriminant: 0.009693367280422985
-0.013398123665888008
a: 0.02299675521769179
b: -0.18165596587095528
c: -0.0013727207989457924
discriminant: 0.033125162433292034
-0.013398123665888008
a: 0.023189388914783098
b: -0.16232912553028955
c: -0.14626549363972952
discriminant: 0.03991797466272619
-0.013398123665888008
a: 0.005162755616202474
b: -0.048408141722222214
c: -0.05170879161865083
discriminant: 0.003411187602343683
-0.013398123665888008
a: 0.005467688142138315
b: -0.040991269512386186
c: -0.1873011440084732
discriminant: 0.00577670115265336
-0.013398123665888008
a: -0.003685450688979743
b: 0.019674837612389307
c: -0.04614607520134506
discriminant: -0.0002931771035041438
-0.013398123665888008
a: -0.003641848159795111
b: 0.023666503737420783
c: -0.2095420781717724
discriminant: -0.002492378328004698
-0.013398123665888008
a: 0.0074882625390165535
b: -0.061226012947424024
c: -0.040369758842956904
discriminant: 0.0049578220728495204
-0.013398123665888008
a: 0.0085477472171288
b: -0.0569150733181529
c: -0.18689958105359994
discriminant: 0.009629607066144512
-0.013398123665888008
a: 0.023457247281324606
b: -0.17462132572054384
c: -0.06377818050601014
discriminant: 0.03647684960153001
-0.013398123665888008
a: 0.02318449467384947
b: -0.14897465684507344
c: -0.2392567556483779
discriminant: 0.044381636290156665
-0.013398123665888008
a: 0.031073301118773544
b: -0.24951071320309215
c: -0.013393996594269653
discriminant: 0.06392037876054597
-0.013398123665888008
a: 0.03249507164114352
b: -0.23494304801600585
c: -0.12596824533961948
discriminant: 0.07157162443833154
-0.013398123665888008
a: 0.007333061926618969
b: -0.06538113158616057
c: -0.04172390691045613
discriminant: 0.005498548340266284
-0.013398123665888008
a: 0.007535594186954499
b: -0.056245724171274825
c: -0.17516113009815137
discriminant: 0.008443354262543171
-0.013398123665888008
a: 0.0016658379439432906
b: -0.017020113681028903
c: -0.05485078713916147
discriminant: 0.0006551743596014346
-0.013398123665888008
a: 0.0017045159900395566
b: -0.009708159442935127
c: -0.24242416948946677
discriminant: 0.0017471118528368734
-0.013398123665888008
a: 0.006200096657236719
b: -0.05284277734904158
c: -0.06080691435124008
discriminant: 0.0043003941035843945
-0.013398123665888008
a: 0.006253258263018442
b: -0.04147013713932335
c: -0.21347685597099442
discriminant: 0.007059475928609561
-0.013398123665888008
a: 0.028443542015699975
b: -0.22410814178749394
c: -0.02338337198812246
discriminant: 0.0528848829098951
-0.013398123665888008
a: 0.029632975796608764
b: -0.2083887263477215
c: -0.15432028292231503
discriminant: 0.061717738103876665
-0.013398123665888008
a: 0.018378138541472293
b: -0.14209433139058902
c: -0.030883339308730884
discriminant: 0.02246111216709515
-0.013398123665888008
a: 0.020036111442390758
b: -0.13474347890408056
c: -0.16922011998610154
discriminant: 0.03171785783651947
-0.013398123665888008
a: 0.0021246267360953246
b: -0.019005283852562865
c: -0.05012472547789526
discriminant: 0.0007871861418755859
-0.013398123665888008
a: 0.002250624175086294
b: -0.011648091089056428
c: -0.24369584992714033
discriminant: 0.00232954911087585
-0.013398123665888008
a: -0.002109296295042768
b: 0.01037530390232047
c: -0.07018514844774193
discriminant: -0.0004845181632858886
-0.013398123665888008
a: -0.0019210920047748707
b: 0.013840227261654195
c: -0.2685331765357589
discriminant: -0.0018719558631843454
-0.013398123665888008
a: 0.024051772919069493
b: -0.20207434613208003
c: -0.013495308335046863
discriminant: 0.042132385730897184
-0.013398123665888008
a: 0.025524523130487916
b: -0.19259880310056415
c: -0.09786098371713725
discriminant: 0.04708571872561136
-0.013398123665888008
a: 0.008887198743258171
b: -0.07714454809264815
c: -0.03519038284853593
discriminant: 0.007202257005324032
-0.013398123665888008
a: 0.009001721681159244
b: -0.06665489855558335
c: -0.17000384541274782
discriminant: 0.010564184705984614
-0.013398123665888008
a: -0.0005944029376889811
b: -0.0013963818593030752
c: -0.04999441194274379
discriminant: -0.00011691741901020925
-0.013398123665888008
a: -0.0005636237908746896
b: 0.0047019217463687285
c: -0.23350146948418338
discriminant: -0.0005043198655129693
-0.013398123665888008
a: 0.005899593738664102
b: -0.05328147672376235
c: -0.05096643864460271
discriminant: 0.0040416408911036535
-0.013398123665888008
a: 0.006253485831798113
b: -0.04601486935340671
c: -0.19088508288011308
discriminant: 0.00689215684678067
-0.013398123665888008
a: 0.021567523538394213
b: -0.17406949280602857
c: -0.006181719125823437
discriminant: 0.030833485816763786
-0.013398123665888008
a: 0.03255888871277126
b: -0.25889722514809477
c: 0.014475034039705958
discriminant: 0.06514260909973382
-0.013398123665888008
a: 0.03330970576989363
b: -0.23917704376650595
c: -0.10748695043633416
discriminant: 0.07152709303743482
-0.013398123665888008
a: 0.01563158499013322
b: -0.11738414936500952
c: -0.06256450681454984
discriminant: 0.017690968144696485
-0.013398123665888008
a: 0.003258179718730894
b: -0.02890571995950872
c: -0.0621941072536053
discriminant: 0.001646098961890624
-0.013398123665888008
a: 0.003287645198301513
b: -0.02074747545640987
c: -0.24962172509255154
discriminant: 0.003713128401383399
-0.013398123665888008
a: 0.008940157309632574
b: -0.07139331446879477
c: -0.06573103262820601
discriminant: 0.007447588438123234
-0.013398123665888008
a: 0.00886027027482918
b: -0.05657724630841726
c: -0.22931180877155433
discriminant: 0.011328043211546979
-0.013398123665888008
a: 0.01647884793670592
b: -0.1310015552251706
c: -0.02456922042305265
discriminant: 0.018780897260512998
-0.013398123665888008
a: -0.006401900091309042
b: 0.040014016757607795
c: -0.06631932440224231
discriminant: -9.715721870695864e-05
-0.013398123665888008
a: -0.006360835150731431
b: 0.041894221737758905
c: -0.2568988184929143
discriminant: -0.004781238324391902
-0.013398123665888008
a: 0.007228633391868533
b: -0.05879625655660137
c: -0.06356006350399601
discriminant: 0.00529480937480677
-0.013398123665888008
a: 0.0071625784494393175
b: -0.04563534696972674
c: -0.22816903018158896
discriminant: 0.00861969920667982
-0.013398123665888008
a: -0.003447200435804176
b: 0.017527013390831236
c: -0.0218998073733796
discriminant: 5.2240963162108285e-06
-0.013398123665888008
a: -0.0032440232332740784
b: 0.02032679893020109
c: -0.17303245861666505
discriminant: -0.0018321065087031636
-0.013398123665888008
a: 0.018686693460996186
b: -0.14800706622551385
c: -0.055684664525183725
discriminant: 0.02606834067852571
-0.013398123665888008
a: 0.01977903213829304
b: -0.13753405721619882
c: -0.19039502851577172
discriminant: 0.03397893444628732
-0.013398123665888008
a: 0.013944733914733883
b: -0.11189880960323989
c: -0.043929924349037086
discriminant: 0.014971708014388976
-0.013398123665888008
a: 0.014952723497087542
b: -0.10328762940026853
c: -0.17767921405946108
discriminant: 0.021295487023171022
-0.013398123665888008
a: 0.0333847274620427
b: -0.26471406784686863
c: 0.2219738610442552
discriminant: 0.04043139029739738
-0.013398123665888008
a: 0.03464581730165022
b: -0.24754294597083348
c: 0.09944647722012157
discriminant: 0.04749589217567478
-0.013398123665888008
a: 0.009498660722199953
b: -0.07725339825673783
c: -0.0552519745005976
discriminant: 0.008067366582265423
-0.013398123665888008
a: 0.016669797903262826
b: -0.14312274314801365
c: -0.00012580898785519157
discriminant: 0.02049250844782013
-0.013398123665888008
a: 0.018456001129864025
b: -0.13909888847200075
c: -0.08248319640836488
discriminant: 0.025437740638576418
-0.013398123665888008
a: -0.006341858021747013
b: 0.03993691544052783
c: -0.052280258345112074
discriminant: 0.0002687413118440496
-0.013398123665888008
a: -0.006289374747216612
b: 0.042016324877292274
c: -0.2444685251684281
discriminant: -0.0043848451185402315
-0.013398123665888008
a: -0.005395929298984704
b: 0.03353176890022383
c: -0.0782035158791533
discriminant: -0.0005635430448857376
-0.013398123665888008
a: -0.005313637156037886
b: 0.03593938064269245
c: -0.2717650358081781
discriminant: -0.0044846040869488705
-0.013398123665888008
a: 0.00028100510772824557
b: -0.011732155969006203
c: -0.05326806336405465
discriminant: 0.00019751787521745263
-0.013398123665888008
a: 0.0005115129794803878
b: -0.00702558007317787
c: -0.1866459231016092
discriminant: 0.0004312460242989199
-0.013398123665888008
a: 0.005228566375198181
b: -0.048290780631268904
c: -0.0439557422750223
discriminant: 0.003251301558201571
-0.013398123665888008
a: 0.005417482321375289
b: -0.04032040098683909
c: -0.18761342843808426
discriminant: 0.0056913044630032125
-0.013398123665888008
a: 0.025951311418118257
b: -0.21032069252672758
c: -0.0023349164285750845
discriminant: 0.04447717027841521
-0.013398123665888008
a: 0.027902933740358453
b: -0.20202926412703798
c: -0.10704089935000638
discriminant: 0.052762844051998894
-0.013398123665888008
a: 0.021102054326682496
b: -0.17134619496731712
c: -0.0008491228457809807
discriminant: 0.029431191475464642
-0.013398123665888008
a: 0.02170906486462653
b: -0.15645376727073929
c: -0.12342187631728485
discriminant: 0.03519527536795005
-0.013398123665888008
a: 0.004201828371599314
b: -0.03628270358289959
c: -0.06647522224494373
discriminant: 0.0024337044786332525
-0.013398123665888008
a: 0.004081841200629816
b: -0.025475394061303253
c: -0.2456376262044898
discriminant: 0.004659610834844255
-0.013398123665888008
a: 0.02972368238460425
b: -0.23378279021499426
c: -0.026256670256257886
discriminant: 0.0577761727094052
-0.013398123665888008
a: 0.030927895235695533
b: -0.21783788268794496
c: -0.15835442239869335
discriminant: 0.06704361907819034
-0.013398123665888008
a: 0.00943764561444223
b: -0.07373047197957328
c: -0.056229389133519825
discriminant: 0.007558874689365556
-0.013398123665888008
a: 0.009378996560588116
b: -0.060322216231459086
c: -0.23433745710317255
discriminant: 0.01243017058782539
-0.013398123665888008
a: 0.02182404733560632
b: -0.1764300286010323
c: -0.027477949244054334
discriminant: 0.03352627525211159
-0.013398123665888008
a: 0.022029611973282837
b: -0.1589580860225901
c: -0.15529231759279238
discriminant: 0.03895179110796923
-0.013398123665888008
a: 0.012377427845350078
b: -0.10163982821929066
c: -0.05909468238974391
discriminant: 0.013256415349738655
-0.013398123665888008
a: 0.012850841494671087
b: -0.09091363042179651
c: -0.19876936125433942
discriminant: 0.018482702418377135
-0.013398123665888008
a: 0.008557947557376037
b: -0.07287684259593788
c: -0.05946214474018274
discriminant: 0.007346529852095456
-0.013398123665888008
a: 0.009198109498024454
b: -0.06587456591462951
c: -0.19617379753475006
discriminant: 0.011557170715912512
-0.013398123665888008
a: 0.02327345293665224
b: -0.1873385655332751
c: -0.010963251488436798
discriminant: 0.03611634900626048
-0.013398123665888008
a: 0.023821543380949828
b: -0.17005435747434489
c: -0.13575866242159706
discriminant: 0.04185440796087547
-0.013398123665888008
a: 0.024983126091081803
b: -0.18762071868806895
c: -0.07972608596391051
discriminant: 0.043168761514566716
-0.013398123665888008
a: -0.0020788940096208098
b: 0.007379637214114637
c: -0.029089334711932757
discriminant: -0.00018743552929402114
-0.013398123665888008
a: -0.0015667523926541057
b: 0.008934779948643695
c: -0.16266668731636547
discriminant: -0.000939603393501446
-0.013398123665888008
a: -0.0016231427419468331
b: 0.006724393498719325
c: -0.03746423614371519
discriminant: -0.00019802174399139537
-0.013398123665888008
a: -0.0015161464812166459
b: 0.01162415227761708
c: -0.22884469805799046
discriminant: -0.0012527274186496017
-0.013398123665888008
a: 0.02629832676601432
b: -0.2155650602289525
c: -0.021954934039467244
discriminant: 0.04877780730949672
-0.013398123665888008
a: 0.027541151286914763
b: -0.20291852413707756
c: -0.12445032976260484
discriminant: 0.054885948876763055
-0.013398123665888008
a: 0.00247028035554167
b: -0.027445473740331544
c: -0.05473948733133194
discriminant: 0.001294141549739274
-0.013398123665888008
a: 0.002662697044561733
b: -0.020613114589458637
c: -0.19232411673787608
discriminant: 0.002473303922021706
-0.013398123665888008
a: 0.033763382259800925
b: -0.27556364245800596
c: -0.010593280043387998
discriminant: 0.07736598089868386
-0.013398123665888008
a: 0.03552978241150456
b: -0.26220807404464014
c: -0.10454630002217036
discriminant: 0.08361110326106183
-0.013398123665888008
a: 0.03601106920013736
b: -0.2603457886626122
c: -0.10007271244731764
discriminant: 0.08219483116630075
-0.013398123665888008
a: 0.03425189596905155
b: -0.27379269144542
c: -0.02529834427608668
discriminant: 0.07842850291426205
-0.013398123665888008
a: 0.03560993519607845
b: -0.2566168816297078
c: -0.13940613078366704
discriminant: 0.08570919706992515
-0.013398123665888008
a: 0.018187558855361493
b: -0.150555442583106
c: -0.01638195683007193
discriminant: 0.023858732507446623
-0.013398123665888008
a: 0.018704735742153276
b: -0.1362776909520806
c: -0.1315456917526282
discriminant: 0.028413718660237435
-0.013398123665888008
a: -0.0050200200803674645
b: 0.028859968986759077
c: -0.02917218330224447
discriminant: 0.00024711802605498505
-0.013398123665888008
a: -0.0047361338257741956
b: 0.02998260393084224
c: -0.1718096908649448
discriminant: -0.002355898215531335
-0.013398123665888008
a: 0.006223193478494337
b: -0.05522228082807651
c: -0.053638722428636876
discriminant: 0.00438471689030559
-0.013398123665888008
a: 0.006539878830948526
b: -0.04712150225604597
c: -0.1978240128240395
discriminant: 0.007395416269751448
-0.013398123665888008
a: 0.012345695030074804
b: -0.10492611710332911
c: -0.025009758780245916
discriminant: 0.01224454146908814
-0.013398123665888008
a: 0.012783309227230793
b: -0.0946004001562385
c: -0.14650465392817924
discriminant: 0.01644049288728984
-0.013398123665888008
a: 0.013087953929443237
b: -0.1074968349427213
c: -0.039529420820286876
discriminant: 0.013625006476916623
-0.013398123665888008
a: 0.005554869169203702
b: -0.03828349350391633
c: -0.08751727284867561
discriminant: 0.003410213877743989
-0.013398123665888008
a: 0.006252194040183322
b: -0.03318135469453809
c: -0.3005346067114393
discriminant: 0.008617005007165142
-0.013398123665888008
a: 0.011766949710547182
b: -0.09772062577061483
c: -0.03918134747718205
discriminant: 0.011393500482422455
-0.013398123665888008
a: 0.012388944806399346
b: -0.08876080139590431
c: -0.17749353708498006
discriminant: 0.016674310402196822
-0.013398123665888008
a: 0.002302622217622203
b: -0.025207738998303975
c: -0.01834560842310129
discriminant: 0.0008044021276099353
-0.013398123665888008
a: 0.003058948140690303
b: -0.022564908864678684
c: -0.14708821756673796
discriminant: 0.00230891603064415
-0.013398123665888008
a: 0.006982030615639226
b: -0.05987022086967564
c: -0.029414314143579978
discriminant: 0.004405929914537766
-0.013398123665888008
a: 0.007684066049651116
b: -0.05400466675212867
c: -0.17638636902673122
discriminant: 0.008337962070446627
-0.013398123665888008
a: 0.002268918228583442
b: -0.017979003419522632
c: -0.08310609168784688
discriminant: 0.0010774882693067372
-0.013398123665888008
a: 0.0026794417485783897
b: -0.012852095435232747
c: -0.28382561205460977
discriminant: 0.0032071531340960714
-0.013398123665888008
a: 0.016594125132096252
b: -0.13241756742354005
c: -0.01203062811077138
discriminant: 0.018332963155519195
-0.013398123665888008
a: 0.01741355597026944
b: -0.12162895440991944
c: -0.15645934398181793
discriminant: 0.025691656724846364
-0.013398123665888008
a: 0.031619101072992206
b: -0.254879667612551
c: 0.02754465346232904
discriminant: 0.06147989623490077
-0.013398123665888008
a: 0.03303409143024003
b: -0.23853472329280317
c: -0.07935892326595473
discriminant: 0.06738501392426598
-0.013398123665888008
a: 0.015937595333565452
b: -0.13087360127226227
c: -0.0005537943199728224
discriminant: 0.017163204109050104
-0.013398123665888008
a: 0.01673926703801831
b: -0.12026685074698129
c: -0.12561323819621484
discriminant: 0.02287480953930324
-0.013398123665888008
a: 0.010016176027105098
b: -0.0849341753652123
c: -0.05112164430862787
discriminant: 0.009261987697729726
-0.013398123665888008
a: 0.010235976826276541
b: -0.07329530049026972
c: -0.18326010796559478
discriminant: 0.012875585947225994
-0.013398123665888008
a: -0.0011630832667900793
b: 0.002485322579860852
c: -0.031402462614918636
discriminant: -0.0001399178868876854
-0.013398123665888008
a: -0.001026098341558884
b: 0.007538283253015282
c: -0.2088926210523242
discriminant: -0.0008005517737000225
-0.013398123665888008
a: 0.03291261044458911
b: -0.2649213371460321
c: -0.027485616102296495
discriminant: 0.07380180837765925
-0.013398123665888008
a: 0.034386784592497915
b: -0.24859682447403658
c: -0.13509722996081164
discriminant: 0.08038261852139729
-0.013398123665888008
a: 0.00706362662810894
b: -0.060116466062804824
c: -0.05757355890174398
discriminant: 0.005240701986813793
-0.013398123665888008
a: 0.007751927196741265
b: -0.05398387375581207
c: -0.2027541057102954
discriminant: 0.009201198890909824
-0.013398123665888008
a: 0.026218117870933665
b: -0.20169886868619213
c: -0.04020493096388145
discriminant: 0.044898824105304956
-0.013398123665888008
a: 0.027375327225159625
b: -0.18677609862091754
c: -0.19109331089897308
discriminant: 0.05581027868164492
-0.013398123665888008
a: 0.009178434780296993
b: -0.05291352983722308
c: -0.375804716729799
discriminant: 0.01659703797036448
-0.013398123665888008
a: 0.010016601473816118
b: -0.051401040812490945
c: -0.6182366234334452
discriminant: 0.027412586490409552
-0.013398123665888008
a: 0.0012681079398208757
b: 0.008219418361656017
c: -0.4797004988857899
discriminant: 0.0025008068836963496
-0.013398123665888008
a: 0.0012876123979438537
b: 0.016863562115475905
c: -0.8078728871271709
discriminant: 0.004445288308933077
-0.013398123665888008
a: -0.005684289612252577
b: 0.04108213388044714
c: -0.3375849705816202
discriminant: -0.0059879812419477985
-0.013398123665888008
a: -0.005567881762579817
b: 0.042425024401770046
c: -0.6032640534113011
discriminant: -0.011635728988544257
-0.013398123665888008
a: -0.009028215462733184
b: 0.0619651465747106
c: -0.6905752967051652
discriminant: -0.021098970897555146
-0.013398123665888008
a: -0.006088719436753202
b: 0.04435284743771524
c: -0.2515974412033587
discriminant: -0.004160449846135801
-0.013398123665888008
a: -0.006187061618833778
b: 0.0514613706176792
c: -0.46166208129560593
discriminant: -0.008777054310369717
-0.013398123665888008
a: 0.0008211839320307474
b: 0.004684226548512499
c: -0.4211423371577786
discriminant: 0.0014052832598451625
-0.013398123665888008
a: 0.0007091508082676242
b: 0.012296912398430962
c: -0.7236918149854131
discriminant: 0.002204040596668964
-0.013398123665888008
a: -0.0003094158469934827
b: 0.012073814305492397
c: -0.4123379971896063
discriminant: -0.00036455865070856035
-0.013398123665888008
a: 0.0006871117822472763
b: 0.011051472213261138
c: -0.6701468809877807
discriminant: 0.0019639983091323527
-0.013398123665888008
a: -0.005719002671612302
b: 0.04360756228914592
c: -0.3768601664971275
discriminant: -0.006719437707283575
-0.013398123665888008
a: -0.0053687614287422185
b: 0.044000076089963314
c: -0.6596244980514147
discriminant: -0.012229459554444965
-0.013398123665888008
a: -0.005539009197154743
b: 0.038029036741577225
c: -0.276203613164525
discriminant: -0.00467336977893047
-0.013398123665888008
a: -0.005364423049128299
b: 0.03977589901975332
c: -0.5332935035139098
discriminant: -0.009861125705971991
-0.013398123665888008
a: -0.0013345316453489148
b: 0.019896473939280998
c: -0.42056050830024583
discriminant: -0.0018491355532263241
-0.013398123665888008
a: -0.0003664186984898123
b: 0.018297905425093977
c: -0.6902380529183024
discriminant: -0.0006768511730481826
-0.013398123665888008
a: -0.009450452306509259
b: 0.06211842401592205
c: -0.3372263646515413
discriminant: -0.008889068100325683
-0.013398123665888008
a: -0.009426379014537242
b: 0.062191529127788664
c: -0.6280107152824178
discriminant: -0.01981168181451824
-0.013398123665888008
a: -0.0029143385276187627
b: 0.0302527297031171
c: -0.4324729351740281
discriminant: -0.004126262494030303
-0.013398123665888008
a: -0.0025646263687970567
b: 0.03285964325028019
c: -0.7356198150312362
discriminant: -0.006466603745619202
-0.013398123665888008
a: -0.001784652954726019
b: 0.014834593362031454
c: -0.3169614061401419
discriminant: -0.0020425992797916443
-0.013398123665888008
a: -0.0014486796754931948
b: 0.017960064279331292
c: -0.5746746720456831
discriminant: -0.0030075141607354815
-0.013398123665888008
a: 0.006463293970165521
b: -0.03392282789525372
c: -0.39552346333340205
discriminant: 0.011376295914898048
-0.013398123665888008
a: 0.006823705179556771
b: -0.029061967056739385
c: -0.652998717923284
discriminant: 0.01866808086415518
-0.013398123665888008
a: -0.0035759958478880968
b: 0.02804477295615994
c: -0.332911335964197
discriminant: -0.00397544893032883
-0.013398123665888008
a: -0.003063752438388684
b: 0.028484686978790266
c: -0.5907048232571656
discriminant: -0.006427715978208727
-0.013398123665888008
a: -0.0038443778245744508
b: 0.036204719967107946
c: -0.25724607959880574
discriminant: -0.0026450227475767465
-0.013398123665888008
a: -0.004030118838001876
b: 0.05004591883050542
c: -0.48597616680428557
discriminant: -0.005329572827042037
-0.013398123665888008
a: -0.01063146479022574
b: 0.06519220823668559
c: -0.7459751281916335
discriminant: -0.02747320922423856
-0.013398123665888008
a: -0.0006732184969466442
b: 0.011627250732219846
c: -0.3693161528568595
discriminant: -0.0008593289017077412
-0.013398123665888008
a: -4.524179542598431e-05
b: 0.013601994267938872
c: -0.6250305711534966
discriminant: 7.190422712459143e-05
-0.013398123665888008
a: -0.008990331118761798
b: 0.05911422910836594
c: -0.2737073816624941
discriminant: -0.006348387880104153
-0.013398123665888008
a: -0.008993831257680076
b: 0.059551884455759305
c: -0.5568348572285585
discriminant: -0.01648588803500002
-0.013398123665888008
a: 0.001097790051352859
b: 0.00781491725745842
c: -0.4415912728454451
discriminant: 0.0020001709561168236
-0.013398123665888008
a: 0.0018327953259205448
b: 0.010869923611937282
c: -0.7170679586247669
discriminant: 0.005375110451068789
-0.013398123665888008
a: 0.0026763672907808306
b: -0.014641441125849392
c: -0.3536774293969437
discriminant: 0.004000654612343421
-0.013398123665888008
a: 0.0029830352523719864
b: -0.008367365985770675
c: -0.6099379605361542
discriminant: 0.007347878565696718
-0.013398123665888008
a: 0.012784311752479162
b: -0.07939770573139768
c: -0.35388834602329633
discriminant: 0.024400871439933778
-0.013398123665888008
a: 0.013653997661113563
b: -0.07671342873330614
c: -0.6078802243879317
discriminant: 0.03908493079614007
-0.013398123665888008
a: 0.008189795166497076
b: -0.044704808730168744
c: -0.4063897867829923
discriminant: 0.015311516369637485
-0.013398123665888008
a: 0.008662166854593575
b: -0.04049032282736573
c: -0.660229580233162
discriminant: 0.024515541387935998
-0.013398123665888008
a: -0.0027807851563051364
b: 0.03086426506657773
c: -0.45614609002104556
discriminant: -0.004121174246848629
-0.013398123665888008
a: -0.002643973426161514
b: 0.03575737468930652
c: -0.7823439509762474
discriminant: -0.006995396621326159
-0.013398123665888008
a: -0.011766279630374602
b: 0.07221190220642416
c: -0.24450978143767876
discriminant: -0.0062933230227598565
-0.013398123665888008
a: -0.011758061390158054
b: 0.06820620362844049
c: -0.4383261923075895
discriminant: -0.01596337889886316
-0.013398123665888008
a: -0.004511200177140269
b: 0.039345401507599784
c: -0.24721138082838656
discriminant: -0.0029128194801421965
-0.013398123665888008
a: -0.004622279623466785
b: 0.05061084168322036
c: -0.48653773049385174
discriminant: -0.0064341964549540255
-0.013398123665888008
a: 0.011117421663274224
b: -0.06728631521743672
c: -0.47625013265272076
discriminant: 0.02570614238310258
-0.013398123665888008
a: 0.011450150575179592
b: -0.0550140174847894
c: -0.7308479155493336
discriminant: 0.036499816842200744
-0.013398123665888008
a: -0.007198959698776762
b: 0.053075879181060506
c: -0.24594370167479684
discriminant: -0.004265106235256817
-0.013398123665888008
a: -0.007199753730797456
b: 0.058587761474583555
c: -0.4331353327304751
discriminant: -0.009041345116463047
-0.013398123665888008
a: -0.007849367194920092
b: 0.05303619053272937
c: -0.3163772142026148
discriminant: -0.007120606199304873
-0.013398123665888008
a: -0.007873424033133208
b: 0.05443064311711859
c: -0.6070919206161293
discriminant: -0.01615687356225699
-0.013398123665888008
a: 0.005822762741113009
b: -0.028319555369726412
c: -0.41873916040152614
discriminant: 0.0105548723420628
-0.013398123665888008
a: 0.005842615093860551
b: -0.020493485702613307
c: -0.7057869401858871
discriminant: 0.016914548675362087
-0.013398123665888008
a: 0.0022327786461223175
b: -0.028558917100065362
c: -0.039570923987821804
discriminant: 0.0011690242022777573
-0.013398123665888008
a: 0.0031710979164619527
b: -0.027950888245949046
c: -0.12561769397638056
discriminant: 0.0023746361842945547
-0.013398123665888008
a: 0.011137173581321354
b: -0.09436318682073844
c: -0.03832829637419455
discriminant: 0.010611886586148521
-0.013398123665888008
a: 0.011858736625997231
b: -0.08563577610309961
c: -0.17097049209353432
discriminant: 0.015443462294997667
-0.013398123665888008
a: 0.014891793079001587
b: -0.12608200074274073
c: -0.03595248094654202
discriminant: 0.018038258539023078
-0.013398123665888008
a: 0.015264860929895329
b: -0.11152426202866955
c: -0.15649507903380766
discriminant: 0.021993163491695555
-0.013398123665888008
a: 0.03177587174795557
b: -0.2627025479577272
c: -0.027815001500991032
discriminant: 0.07254801238494067
-0.013398123665888008
a: 0.033066550860704175
b: -0.24450168632646835
c: -0.12123320052089992
discriminant: 0.07581612978060787
-0.013398123665888008
a: 0.01530760087652983
b: -0.14114642197221156
c: -0.013004432633373697
discriminant: 0.02071857909306722
-0.013398123665888008
a: 0.0163195829005666
b: -0.1310598184182321
c: -0.061958183315398485
discriminant: 0.021221202839756564
-0.013398123665888008
a: 0.011791280135340997
b: -0.09927339522504153
c: -0.040427817272032596
discriminant: 0.011761989874366953
-0.013398123665888008
a: 0.013006655155918742
b: -0.09485372668299838
c: -0.16436559719914812
discriminant: 0.017548616034716812
-0.013398123665888008
a: 0.031539320488605596
b: -0.2543109707265342
c: -0.036061675469923116
discriminant: 0.06922351279188009
-0.013398123665888008
a: 0.03262447803926947
b: -0.23374399000638912
c: -0.15279391858541091
discriminant: 0.0745755402298016
-0.013398123665888008
a: 0.014231685167664663
b: -0.11914049547588823
c: -0.004315222334890456
discriminant: 0.014440109205034687
-0.013398123665888008
a: 0.015389211605811585
b: -0.11114697544290109
c: -0.12860564363094962
discriminant: 0.02027020800425797
-0.013398123665888008
a: 0.005159795426077604
b: -0.04835411334832085
c: -0.03728287257245222
discriminant: 0.003107608259183753
-0.013398123665888008
a: 0.006224321322058213
b: -0.04755426105675678
c: -0.16649330798908057
discriminant: 0.006406639132239931
-0.013398123665888008
a: 0.01433014588961055
b: -0.11951955664370861
c: -0.04577127207494136
discriminant: 0.016908560445856542
-0.013398123665888008
a: 0.015074433713821007
b: -0.10821819359419343
c: -0.1732835199675088
discriminant: 0.022159781166581488
-0.013398123665888008
a: 0.022850726267297686
b: -0.1828493182362977
c: -0.024446996264364085
discriminant: 0.035668399658257396
-0.013398123665888008
a: 0.024295611384389546
b: -0.1732568375836976
c: -0.15464574719635837
discriminant: 0.045046783674028854
-0.013398123665888008
a: 1.39581371611441e-05
b: -0.006482269172937344
c: -0.05425127211805392
discriminant: 4.504880041997519e-05
-0.013398123665888008
a: 0.004816769324965308
b: -0.03921517862174809
c: -0.11298711045360477
discriminant: 0.0037147616253331707
-0.013398123665888008
a: 0.016943378823801033
b: -0.13798139040636853
c: -0.24300940030191798
discriminant: 0.03550846540671511
-0.013398123665888008
a: 0.017650070682408776
b: -0.1241879690942187
c: -0.3788209840712119
discriminant: 0.04216752024709278
-0.013398123665888008
a: 0.004594666668366098
b: -0.04462412690197132
c: -0.03957036891620891
discriminant: 0.0027185633222202603
-0.013398123665888008
a: 0.005274503693572203
b: -0.04090686441665947
c: -0.17029653836458036
discriminant: 0.005266290438829119
-0.013398123665888008
a: -0.005614619219302425
b: 0.03215598051098637
c: -0.036231384167425995
discriminant: 0.0002203053790694971
-0.013398123665888008
a: -0.005387057936507671
b: 0.033096513702411165
c: -0.1606470515846915
discriminant: -0.0023662806776095884
-0.013398123665888008
a: 0.005237977170069472
b: -0.040614790583457294
c: -0.11395821928589267
discriminant: 0.004037203417983196
-0.013398123665888008
a: 0.033053864626163124
b: -0.27820775844230966
c: -0.02376387597880436
discriminant: 0.08054150861587984
-0.013398123665888008
a: 0.03396248414385728
b: -0.25747196421544827
c: -0.09955270611050115
discriminant: 0.07981604116798499
-0.013398123665888008
a: 0.011447429569924545
b: -0.09255853245567602
c: -0.01182479537254133
discriminant: 0.009108535979172178
-0.013398123665888008
a: 0.009145770198635078
b: -0.07894214590391957
c: -0.04594322450975963
discriminant: 0.007912607094117965
-0.013398123665888008
a: 0.010721267257533161
b: -0.07979592384793155
c: -0.16233111708853276
discriminant: 0.013328970624825163
-0.013398123665888008
a: 0.007287369940021719
b: -0.06582512917144981
c: -0.021054336919201222
discriminant: 0.004946670598326358
-0.013398123665888008
a: 0.007903633789945054
b: -0.0589084709624704
c: -0.14877850029100037
discriminant: 0.008173771079605421
-0.013398123665888008
a: 0.008226485142127345
b: -0.07132387055962225
c: -0.04407850335441876
discriminant: 0.006537539123335094
-0.013398123665888008
a: 0.009380139093769852
b: -0.06926430304908263
c: -0.17386824462751138
discriminant: 0.011321176951257795
-0.013398123665888008
a: 0.015043061179421672
b: -0.1255920308707283
c: -0.042140982839550256
discriminant: 0.01830907575029922
-0.013398123665888008
a: 0.015803658678442627
b: -0.11445495878224726
c: -0.16626584881094242
discriminant: 0.023610372487804638
-0.013398123665888008
a: 0.01999403970028062
b: -0.16263675724749566
c: -0.007488905651805489
discriminant: 0.02704964871563625
-0.013398123665888008
a: 0.021746235717841733
b: -0.15622017953855194
c: -0.1280961884010433
discriminant: 0.035547184125162015
-0.013398123665888008
a: 0.006678176114805928
b: -0.06075371900073323
c: -0.03451656310150353
discriminant: 0.004613045121498664
-0.013398123665888008
a: 0.00766276246656976
b: -0.05777400979675129
c: -0.16019589169033355
discriminant: 0.008248008472568564
-0.013398123665888008
a: 0.007715200707136178
b: -0.06564559873114922
c: -0.03461571097638827
discriminant: 0.00537761326398327
-0.013398123665888008
a: 0.008962288572902766
b: -0.0656421807448399
c: -0.17074183620518546
discriminant: 0.010429846323090908
-0.013398123665888008
a: 0.0015082153300562855
b: -0.021626464055555628
c: -0.03797633844649362
discriminant: 0.0006968099308438699
-0.013398123665888008
a: 0.0022965191045330752
b: -0.020705959190914308
c: -0.1580418822449886
discriminant: 0.0018805215535837405
-0.013398123665888008
a: 9.408677804677648e-07
b: -0.010529313876626548
c: -0.021715519372337178
discriminant: 0.00011094817644257459
-0.013398123665888008
a: 0.0003154088705605738
b: -0.005803360079249531
c: -0.15578675981437973
discriminant: 0.0002302250920548067
-0.013398123665888008
a: -0.0009772574800317995
b: -0.0029648662699520295
c: -0.03555789622180938
discriminant: -0.00013020644822913147
-0.013398123665888008
a: -0.00035671386654609425
b: -0.002101223418320683
c: -0.1552802760888209
discriminant: -0.00021714737087425405
-0.013398123665888008
a: 0.018342163438222564
b: -0.15023112426954743
c: -0.2460046853514578
discriminant: 0.040618423280432026
-0.013398123665888008
a: 0.020439839237849512
b: -0.14946658366494098
c: -0.35539308575991535
discriminant: 0.05139696978917254
-0.013398123665888008
a: 0.004265764603926386
b: -0.03464032054922195
c: -0.09005580457310935
discriminant: 0.002736579261857176
-0.013398123665888008
a: 0.006786325987693973
b: -0.06308217806686747
c: -0.012278375086042903
discriminant: 0.004312661413392245
-0.013398123665888008
a: 0.007232937267122477
b: -0.05505712436483223
c: -0.13711938905042043
discriminant: 0.00699839069975601
-0.013398123665888008
a: 0.01457830971902081
b: -0.1207651127022566
c: -0.04189858736340202
discriminant: 0.01702745477948124
-0.013398123665888008
a: 0.015537522183211788
b: -0.11141082035605465
c: -0.16959118029088394
discriminant: 0.022952477795795796
-0.013398123665888008
a: 0.0008264512230771546
b: -0.012828885260972117
c: -0.087570133121888
discriminant: 0.00045407007153364196
-0.013398123665888008
a: 0.017239176195099806
b: -0.14144421368949062
c: -0.034031953601939
discriminant: 0.022353196963867436
-0.013398123665888008
a: 0.018279435742124865
b: -0.13151324212867688
c: -0.1593895058090612
discriminant: 0.02894993377281908
-0.013398123665888008
a: 0.004558908483427302
b: -0.04491752571244137
c: -0.04082472295081463
discriminant: 0.002762048819303984
-0.013398123665888008
a: 0.005649495540007611
b: -0.044718734359543044
c: -0.15404574544324723
discriminant: 0.005480888210074468
-0.013398123665888008
a: 0.012869699691537916
b: -0.1159463529844148
c: -0.008641326757315437
discriminant: 0.01388840189159892
-0.013398123665888008
a: 0.013132494780456408
b: -0.10281789200768238
c: -0.09570945416832488
discriminant: 0.015599134546126868
-0.013398123665888008
a: 0.0015861652588263653
b: -0.021877751360161984
c: -0.04074911721054009
discriminant: 0.0007371753407658785
-0.013398123665888008
a: 0.0024139769396149865
b: -0.021305664907897814
c: -0.16497083511826383
discriminant: 0.0020468745239056885
-0.013398123665888008
a: 0.004873943753119456
b: -0.048036804659537136
c: -0.048915438402286404
discriminant: 0.003261178983626222
-0.013398123665888008
a: 0.005815729232686634
b: -0.04646162392441597
c: -0.1423966352925511
discriminant: 0.005471243595722288
-0.013398123665888008
a: 0.006834619811999084
b: -0.06271343313833147
c: -0.03875398081898396
discriminant: 0.004992449596393013
-0.013398123665888008
a: 0.007871350330463088
b: -0.06049115542997341
c: -0.1529450478679958
discriminant: 0.008474716097566967
-0.013398123665888008
a: 0.022795051057174033
b: -0.18238010186123155
c: -0.04255626459608797
discriminant: 0.03714279045199492
-0.013398123665888008
a: 0.024095601630131802
b: -0.17008461863890179
c: -0.1733822129378687
discriminant: 0.04563977242834693
-0.013398123665888008
a: 0.004657187250714821
b: -0.04784098310794871
c: -0.0045132117020491025
discriminant: 0.0023728351527292735
-0.013398123665888008
a: 0.00489839285372825
b: -0.039645887236736094
c: -0.12504337678694377
discriminant: 0.004021842707824851
-0.013398123665888008
a: 0.012038751720638681
b: -0.0986204649190901
c: -0.030526291025161356
discriminant: 0.011195989855272995
-0.013398123665888008
a: 0.02024809613028642
b: -0.17989260562162523
c: -0.14266569024232545
discriminant: 0.04391618399941868
-0.013398123665888008
a: 0.015026116107471205
b: -0.12764469009069757
c: -0.033378137280376974
discriminant: 0.018299341973254456
-0.013398123665888008
a: 0.015446047885486314
b: -0.11414913626648365
c: -0.14946623431632522
discriminant: 0.022264675760437364
-0.013398123665888008
a: 0.008802322494884756
b: -0.0770680518422937
c: -0.028652425924920233
discriminant: 0.006948316187774249
-0.013398123665888008
a: 0.009469694053056848
b: -0.06959381770946449
c: -0.15813946494598696
discriminant: 0.010833428866388592
-0.013398123665888008
a: 0.00541053349023899
b: -0.04994826908068245
c: -0.03982638692683971
discriminant: 0.0033567575852077886
-0.013398123665888008
a: 0.0063363192527796965
b: -0.0480078988581055
c: -0.17506884237404574
discriminant: 0.006741926658756167
-0.013398123665888008
a: 0.0058368471502887875
b: -0.05326536953172248
c: -0.0002851964149631625
discriminant: 0.0028438581828787507
-0.013398123665888008
a: 0.006353643057881555
b: -0.04513785549063917
c: -0.1478871656682882
discriminant: 0.00579591505228622
-0.013398123665888008
a: 0.005968247321224963
b: -0.050359859048012684
c: -0.07305578948695979
discriminant: 0.004280175482957795
-0.013398123665888008
a: 0.0002671530639600274
b: -0.012326250699747618
c: -0.11021423851650913
discriminant: 0.00026971274235985536
-0.013398123665888008
a: 0.0008035473869753588
b: -0.010170305491075865
c: -0.23470386658641462
discriminant: 0.0008578178286159147
-0.013398123665888008
a: 0.011751012028508603
b: -0.11531377090050751
c: -0.002721029465458269
discriminant: 0.01342516515920884
-0.013398123665888008
a: 0.01244546826405421
b: -0.10552505591350331
c: -0.03414836033934576
discriminant: 0.01283550676503926
-0.013398123665888008
a: 0.008878219956047475
b: -0.07450332436718668
c: -0.03659759895807946
discriminant: 0.0068504314754144055
-0.013398123665888008
a: 0.010068067124546616
b: -0.07319815425512591
c: -0.17646025737154114
discriminant: 0.012464424650482999
-0.013398123665888008
a: 0.010404271740982438
b: -0.09084849818554097
c: -0.01374163893882574
discriminant: 0.008825336605312276
-0.013398123665888008
a: 0.011142731112908826
b: -0.08213909317368528
c: -0.13910887536855643
discriminant: 0.012947041801999232
-0.013398123665888008
a: 0.006758130461838543
b: -0.06156346960488909
c: -0.012093264803167414
discriminant: 0.004116972234789565
-0.013398123665888008
a: 0.007310491245482557
b: -0.053423830630805275
c: -0.14939659330754618
discriminant: 0.007222755629187906
-0.013398123665888008
a: 0.009110519411167499
b: -0.07695252490243859
c: -0.040116818174483204
discriminant: 0.007383631291632057
-0.013398123665888008
a: 0.01055417508949296
b: -0.07720606120504989
c: -0.17204747738601422
discriminant: 0.013224052686948208
-0.013398123665888008
a: 0.0019792325276098924
b: -0.02400821641197473
c: -0.041378012175245504
discriminant: 0.0009039812857845491
-0.013398123665888008
a: 0.002706547030196089
b: -0.022743810273786275
c: -0.17740646476314492
discriminant: 0.002437916667139094
-0.013398123665888008
a: -0.0004163319964114575
b: -0.007158573301065577
c: -0.030390832605024287
discriminant: 6.344676625042025e-07
-0.013398123665888008
a: -5.228898664039975e-05
b: -0.003822393803740526
c: -0.16239793905529576
discriminant: -1.9355800271889284e-05
-0.013398123665888008
a: 0.004318088151548824
b: -0.03930698876755698
c: -0.029373345938329076
discriminant: 0.0020523861542434247
-0.013398123665888008
a: 0.005025785302261114
b: -0.037574184319230375
c: -0.1772571849608765
discriminant: 0.00497524554684171
-0.013398123665888008
a: 0.0008976312650327868
b: -0.01464023200945963
c: -0.03206711927370176
discriminant: 0.00032947418864924706
-0.013398123665888008
a: 0.0015712275636166912
b: -0.014187956547250247
c: -0.17520044008320956
discriminant: 0.001302417153452715
-0.013398123665888008
a: 0.011570416388521994
b: -0.09421815475294626
c: -0.03494204238543219
discriminant: 0.010494236604509469
-0.013398123665888008
a: 0.011964189772709629
b: -0.08677762981568563
c: -0.1709260365075057
discriminant: 0.01571032318791974
-0.013398123665888008
a: -0.004217379958058443
b: 0.02386717075656483
c: -0.04566612465607378
discriminant: -0.0002007237556238728
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
0     25.099590  6.254395  2.457656     0.377088         7.871762   
1     26.784940  6.208599  2.457656     0.377088         7.871762   
2     26.261318  9.274925  1.292553     0.738441         7.599898   
3     27.808318  8.926058  1.292553     0.738441         7.599898   
4     25.408514  6.727813  2.114730     0.028216         7.821125   
...         ...       ...       ...          ...              ...   
1993  23.349492  7.419639  1.187985     0.008524         7.928655   
1994  25.061998  7.586472  1.187985     0.008524         7.928655   
1995  23.207888  7.236578  2.482080     0.010662         8.111622   
1996  24.859328  7.207139  2.482080     0.010662         8.111622   
1997  23.294406  5.721528  0.935788     0.000171         7.820683   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  \
0          7.846458   1001       1.5     7.509678   779.625   
1          7.622792   1001       3.0     7.509678   779.625   
2          7.590898   1003       1.5     7.927428  6358.433   
3          7.351790   1003       3.0     7.927428  6358.433   
4          7.807509   1005       1.5     8.161582   526.500   
...             ...    ...       ...          ...       ...   
1993       7.896463  51800       1.5     7.798817  7968.552   
1994       7.753334  51800       3.0     7.798817  7968.552   
1995       8.075677  51810       1.5     7.872881  4972.955   
1996       7.939772  51810       3.0     7.872881  4972.955   
1997       7.775021  54037       3.0     7.900531  3976.619   

                 irri_need  
0      [7.025909919398073]  
1      [8.861003068216714]  
2      [0.507996174152075]  
3      [9.143696454977805]  
4      [7.214038856954462]  
...                    ...  
1993  [18.265660500440294]  
1994   [15.99926541089394]  
1995   [8.498377649446617]  
1996   [8.864723058641308]  
1997                   NaN  

[1998 rows x 11 columns]
results_irri
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
0     25.099590  6.254395  2.457656     0.377088         7.871762   
1     26.784940  6.208599  2.457656     0.377088         7.871762   
2     26.261318  9.274925  1.292553     0.738441         7.599898   
3     27.808318  8.926058  1.292553     0.738441         7.599898   
4     25.408514  6.727813  2.114730     0.028216         7.821125   
...         ...       ...       ...          ...              ...   
1993  23.349492  7.419639  1.187985     0.008524         7.928655   
1994  25.061998  7.586472  1.187985     0.008524         7.928655   
1995  23.207888  7.236578  2.482080     0.010662         8.111622   
1996  24.859328  7.207139  2.482080     0.010662         8.111622   
1997  23.294406  5.721528  0.935788     0.000171         7.820683   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  irri_need  
0          7.846458   1001       1.5     7.509678   779.625      7.025  
1          7.622792   1001       3.0     7.509678   779.625      8.861  
2          7.590898   1003       1.5     7.927428  6358.433      0.507  
3          7.351790   1003       3.0     7.927428  6358.433      9.143  
4          7.807509   1005       1.5     8.161582   526.500      7.214  
...             ...    ...       ...          ...       ...        ...  
1993       7.896463  51800       1.5     7.798817  7968.552     18.265  
1994       7.753334  51800       3.0     7.798817  7968.552     15.999  
1995       8.075677  51810       1.5     7.872881  4972.955      8.498  
1996       7.939772  51810       3.0     7.872881  4972.955      8.864  
1997       7.775021  54037       3.0     7.900531  3976.619        NaN  

[1998 rows x 11 columns]
0.0 11193.128 19.681586551264978
0.2274 19.034250000000004
0.8374538099999997
0.0 0.8374538099999997 0.7816953786551261
In [11]:
ds1=results_irri[results_irri['scenario']==1.5]
print(np.sum(~np.isnan(ds1['scenario'])))
print(np.sum(np.isnan(ds1['irri_need'])))
ds2=results_irri[results_irri['scenario']==3]
print(np.sum(~np.isnan(ds2['scenario'])))
print(np.sum(np.isnan(ds2['irri_need'])))

ds1=results_irri[(results_irri['scenario']==1.5)&(np.isnan(results_irri['irri_need']))]
ds1['production']=(np.exp(ds1['lnyield_obs']))*ds1['har']/10000000 #10 4 tonnes
print(np.sum(ds1['production']))
ds2=results_irri[(results_irri['scenario']==3)&(np.isnan(results_irri['irri_need']))]
ds2['production']=(np.exp(ds2['lnyield_obs']))*ds2['har']/10000000 #10 4 tonnes
print(np.sum(ds2['production']))                                
852
183
1146
313
1174.758696805632
2400.8085365818906
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3908623574.py:9: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  ds1['production']=(np.exp(ds1['lnyield_obs']))*ds1['har']/10000000 #10 4 tonnes
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3908623574.py:12: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  ds2['production']=(np.exp(ds2['lnyield_obs']))*ds2['har']/10000000 #10 4 tonnes
In [12]:
results_irri['irri_need_1']=results_irri['irri_need']
results_irri.loc[np.isnan(results_irri['irri_need_1']), 'irri_need_1'] =irri_max
results_irri.loc[(results_irri['irri_need_1']<results_irri['irrigation1']), 'irri_need_1'] = results_irri['irrigation1']

print(reg.params['tmp_tmp_interaction'])
results_irri['y_temp_irri'] = (reg.params['tmp_tmp_interaction'] * results_irri['tmp']**2 +
               reg.params['tmp'] * results_irri['tmp'] +
               reg.params['pre_pre_interaction'] * results_irri['pre']**2 +
               reg.params['pre'] * results_irri['pre'] +
               reg.params['lnfer'] * results_irri['lnfer'] +
               reg.params['irrigation1'] * results_irri['irri_need_1'] + 
               reg.params['irrigation12'] * results_irri['irri_need_1']**2 +
               reg.params['lnfer_irrigation1_tmp_interaction'] * results_irri['irri_need_1'] * results_irri['tmp'] * results_irri['lnfer'] +
               reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * results_irri['irri_need_1']**2 * results_irri['lnfer'] * results_irri['tmp']**2 +
               reg.params['lnfer_irrigation1_pre_interaction'] * results_irri['irri_need_1'] * results_irri['pre'] * results_irri['lnfer']  +
               reg.params['lnfer_irrigation12_pre_pre_interaction'] * results_irri['irri_need_1']**2 * results_irri['lnfer'] * results_irri['pre']**2 +
               reg.params['const'])                          

# For the county that with solution less the current irrigation, we expext maintaining current level irrigation can offeset the yield loss
results_irri.loc[(results_irri['irri_need_1']<results_irri['irrigation1']), 'y_temp_irri'] = results_irri['y_temp_base2015']
# For the county that without solution due to far over the current level yield, we set their irrigation need to the minimum level 
# that means just transforming to irrigated cropland can offset yield loss
results_irri.loc[(results_irri['y_temp_base2015']<results_irri['y_temp_irri']), 'irri_need_1'] = 0.00002
results_irri1=results_irri[['geoid', 'scenario','irri_need','irri_need_1','y_temp_irri']]
print(results_irri1)
print(np.min(results_irri1['irri_need_1']),np.max(results_irri1['irri_need_1']),
      np.mean(results_irri1['irri_need_1']))
-0.013398123665888008
      geoid  scenario  irri_need  irri_need_1  y_temp_irri
0      1001       1.5   0.837454     0.837454     7.826731
1      1001       3.0   0.837454     0.837454     7.606994
2      1003       1.5   0.507000     0.738441     7.590898
3      1003       3.0   0.837454     0.837454     7.348977
4      1005       1.5   0.837454     0.837454     7.773008
...     ...       ...        ...          ...          ...
1993  51800       1.5   0.837454     0.837454     7.884957
1994  51800       3.0   0.837454     0.837454     7.742675
1995  51810       1.5   0.837454     0.837454     8.005891
1996  51810       3.0   0.837454     0.837454     7.876415
1997  54037       3.0        NaN     0.837454     7.792047

[1998 rows x 5 columns]
0.007 4.094071 0.8281153848898896

Integrated Irrigation and fertilizer¶

In [13]:
excel_file = "/Users/chenchenren/postdoc/paper/2N and water-US/Figure 6 sustain and unsustain/mean_sus_unsus15.csv"
mean_sus_unsus15 = pd.read_csv(excel_file)
mean_sus_unsus15['scenario']=1.5
print(mean_sus_unsus15)

excel_file = "/Users/chenchenren/postdoc/paper/2N and water-US/Figure 6 sustain and unsustain/mean_sus_unsus3.csv"
mean_sus_unsus3 = pd.read_csv(excel_file)
mean_sus_unsus3['scenario']=3
print(mean_sus_unsus3)

sus_irri=pd.concat([mean_sus_unsus15, mean_sus_unsus3])
sus_irri.rename(columns={ 'GEOID':'geoid'}, inplace=True)
print(sus_irri)

ds=yield_loss.merge(sus_irri, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')
ds = ds.sort_values(by='sus_unsus')
ds['sus_unsus'] = ds['sus_unsus'].fillna(1) # unsustainbale irrigation is 1
print(ds)
      GEOID  sus_unsus  scenario
0      1001          0       1.5
1      1003          0       1.5
2      1005          0       1.5
3      1007          0       1.5
4      1009          0       1.5
...     ...        ...       ...
1992  56037          1       1.5
1993  56039          0       1.5
1994  56041          1       1.5
1995  56043          1       1.5
1996  56045          1       1.5

[1997 rows x 3 columns]
      GEOID  sus_unsus  scenario
0      1001        0.0         3
1     28031        0.0         3
2     28037        0.0         3
3     28041        0.0         3
4     28045        0.0         3
...     ...        ...       ...
1992  29121        1.0         3
1993  29115        1.0         3
1994  29107        1.0         3
1995  29145        1.0         3
1996  56045        1.0         3

[1997 rows x 3 columns]
      geoid  sus_unsus  scenario
0      1001        0.0       1.5
1      1003        0.0       1.5
2      1005        0.0       1.5
3      1007        0.0       1.5
4      1009        0.0       1.5
...     ...        ...       ...
1992  29121        1.0       3.0
1993  29115        1.0       3.0
1994  29107        1.0       3.0
1995  29145        1.0       3.0
1996  56045        1.0       3.0

[3994 rows x 3 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0      1001       1.5  25.099590  6.254395  2.457656     0.377088   
1122  28155       1.5  24.597372  6.798732  2.709249     0.000000   
1123  28155       3.0  26.340148  6.540652  2.709249     0.000000   
1136  29009       1.5  23.353156  6.747682  4.209049     0.000000   
1137  29009       3.0  25.124780  6.431704  4.209049     0.000000   
...     ...       ...        ...       ...       ...          ...   
1993  51800       1.5  23.349492  7.419639  1.187985     0.008524   
1994  51800       3.0  25.061998  7.586472  1.187985     0.008524   
1995  51810       1.5  23.207888  7.236578  2.482080     0.010662   
1996  51810       3.0  24.859328  7.207139  2.482080     0.010662   
1997  54037       3.0  23.294406  5.721528  0.935788     0.000171   

      y_temp_base_t  y_temp_base2015  lnyield_obs       har  \
0          7.846458         7.871762     7.509678   779.625   
1122       8.217792         8.257644     7.753458  1499.437   
1123       8.080269         8.257644     7.753458  1499.437   
1136       8.562132         8.606349     7.585869  1176.583   
1137       8.478483         8.606349     7.585869  1176.583   
...             ...              ...          ...       ...   
1993       7.896463         7.928655     7.798817  7968.552   
1994       7.753334         7.928655     7.798817  7968.552   
1995       8.075677         8.111622     7.872881  4972.955   
1996       7.939772         8.111622     7.872881  4972.955   
1997       7.775021         7.820683     7.900531  3976.619   

      gap_yield_warming  gap_production_warming  group    id  sus_unsus  
0             -0.045616               -0.003556      1     1        0.0  
1122          -0.091012               -0.013647      2  1123        0.0  
1123          -0.378641               -0.056775      2  1124        0.0  
1136          -0.085216               -0.010026      2  1137        0.0  
1137          -0.236475               -0.027823      2  1138        0.0  
...                 ...                     ...    ...   ...        ...  
1993          -0.077225               -0.061537      1  1994        1.0  
1994          -0.392016               -0.312380      1  1995        1.0  
1995          -0.092685               -0.046092      1  1996        1.0  
1996          -0.414491               -0.206125      1  1997        1.0  
1997          -0.120458               -0.047901      1  1998        1.0  

[1998 rows x 15 columns]
In [14]:
# Load data from an Excel file
excel_file = "scenario_management.xlsx"
sheet_name = "soybean"
data = pd.read_excel(excel_file, sheet_name=sheet_name)

# Create interaction terms
data['tmp_tmp_interaction'] = data['tmp'] ** 2
data['pre_pre_interaction'] = data['pre'] ** 2
data['irrigation12'] = data['irrigation1'] ** 2
data['lnfer_irrigation1_tmp_interaction'] = data['lnfer'] * data['irrigation1'] * data['tmp']
data['lnfer_irrigation12_tmp_tmp_interaction'] = data['lnfer'] * data['irrigation12'] * data['tmp'] ** 2
data['lnfer_irrigation1_pre_interaction'] = data['lnfer'] * data['irrigation1'] * data['pre']
data['lnfer_irrigation12_pre_pre_interaction'] = data['lnfer'] * data['irrigation12'] * data['pre'] ** 2

data['lnfer_tmp_interaction'] = data['lnfer'] * data['tmp']
data['lnfer_tmp_tmp_interaction'] = data['lnfer'] * data['tmp'] ** 2
data['lnfer_pre_interaction'] = data['lnfer'] * data['pre']
data['lnfer_pre_pre_interaction'] = data['lnfer'] * data['pre'] ** 2

# Define predictor variables and response variable
predictor_variables1 = ['lnfer', 'tmp', 'irrigation1', 'irrigation12', 'tmp_tmp_interaction',
                        'pre', 'pre_pre_interaction', 'lnfer_irrigation1_pre_interaction', 'lnfer_irrigation12_pre_pre_interaction',
                        'lnfer_irrigation1_tmp_interaction', 'lnfer_irrigation12_tmp_tmp_interaction']

predictor_variables2 = ['lnfer', 'tmp', 'tmp_tmp_interaction', 'irrigation1', 'irrigation12', 'pre', 'pre_pre_interaction',
                        'lnfer_tmp_interaction', 'lnfer_tmp_tmp_interaction',
                        'lnfer_pre_interaction', 'lnfer_pre_pre_interaction']

response_variable = 'lnyield'

# Function to perform regression analysis
def perform_regression(group_data, predictor_variables):
    X = sm.add_constant(group_data[predictor_variables])
    y = group_data[response_variable]
    return sm.OLS(y, X).fit()

# Perform regression for group 1 data
group1_data = data[(data['group'] == 1) & (data['sample'] == 0)].copy()
reg = perform_regression(group1_data, predictor_variables1)
In [15]:
print(np.percentile(group1_data['lnfer'], 5))
print(np.percentile(group1_data['lnfer'], 95))
print(np.percentile(group1_data['irrigation1'], 5))
print(np.percentile(group1_data['irrigation1'], 95))
0.08624334000000018
4.112335099999999
2.388000000000001e-05
0.8374538099999997
In [16]:
# for unsustainable irrigation we first select the minimum irrigation requirement
results_df1=ds[ds['sus_unsus']==1]
print(results_df1)

#for irrigated croplands, setting the minium irrigation intensity
results_df1_1=results_df1[results_df1['group']==1]
irrigation1_values=2.388000000000001e-05
results_df1_1['irrigation1_values']=2.388000000000001e-05
results_df1_1['lnfer_values'] = (
    (results_df1_1['y_temp_base2015']-reg.params['tmp_tmp_interaction'] * results_df1_1['tmp']**2 -
    reg.params['tmp'] * results_df1_1['tmp'] -reg.params['pre_pre_interaction'] * results_df1_1['pre']**2 
    -reg.params['pre'] * results_df1_1['pre'] -reg.params['irrigation1'] * irrigation1_values -
    reg.params['irrigation12'] * irrigation1_values**2 -reg.params['const'])
    / (reg.params['lnfer']+reg.params['lnfer_irrigation1_tmp_interaction'] * irrigation1_values 
       * results_df1_1['tmp'] +reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * 
       irrigation1_values**2 * results_df1_1['tmp']**2 +
       reg.params['lnfer_irrigation1_pre_interaction'] * irrigation1_values * results_df1_1['pre']  +
       reg.params['lnfer_irrigation12_pre_pre_interaction'] * irrigation1_values**2 * results_df1_1['pre']**2)
)   
print(results_df1_1)
results_df1_1['gap_irrigation']=((results_df1_1['irrigation1_values'])-(results_df1_1['irrigation1']))
results_df1_1['gap_fer']=(np.exp(results_df1_1['lnfer_values'])-np.exp(results_df1_1['lnfer'])) #kg/ha

#for rainfed croplands, no addtional irrigation
results_df1_2=results_df1[results_df1['group']==2]
results_lnfer1=results_lnfer[['geoid','scenario','lnfer_need']]
print(results_lnfer1)
results_df1_2 = results_df1_2.merge(results_lnfer1, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')

results_df1_2['irrigation1_values']=0
results_df1_2['gap_irrigation']=0
results_df1_2.rename(columns={'lnfer_need': 'lnfer_values'}, inplace=True)
results_df1_2['gap_fer']=(np.exp(results_df1_2['lnfer_values'])-np.exp(results_df1_2['lnfer'])) #kg/ha


results_df1 = pd.concat([results_df1_1, results_df1_2])
results_df1['mana_group']=1
print(results_df1)
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
1558  40017       3.0  27.447118  5.058816  1.371145     0.000000   
1551  40011       1.5  25.475696  4.985124  1.356024     0.000000   
1552  40011       3.0  27.391148  4.573153  1.356024     0.000000   
1550  40003       3.0  27.424982  4.487021  1.373776     0.000000   
1549  40003       1.5  25.412738  4.966147  1.373776     0.000000   
...     ...       ...        ...       ...       ...          ...   
1993  51800       1.5  23.349492  7.419639  1.187985     0.008524   
1994  51800       3.0  25.061998  7.586472  1.187985     0.008524   
1995  51810       1.5  23.207888  7.236578  2.482080     0.010662   
1996  51810       3.0  24.859328  7.207139  2.482080     0.010662   
1997  54037       3.0  23.294406  5.721528  0.935788     0.000171   

      y_temp_base_t  y_temp_base2015  lnyield_obs       har  \
1558       7.613589         7.929552     7.234388  1045.652   
1551       7.785913         7.896766     8.022673  1057.050   
1552       7.581114         7.896766     8.022673  1057.050   
1550       7.573723         7.892049     7.510295  5361.924   
1549       7.792547         7.892049     7.510295  5361.924   
...             ...              ...          ...       ...   
1993       7.896463         7.928655     7.798817  7968.552   
1994       7.753334         7.928655     7.798817  7968.552   
1995       8.075677         8.111622     7.872881  4972.955   
1996       7.939772         8.111622     7.872881  4972.955   
1997       7.775021         7.820683     7.900531  3976.619   

      gap_yield_warming  gap_production_warming  group    id  sus_unsus  
1558          -0.375566               -0.039271      2  1559        1.0  
1551          -0.319964               -0.033822      2  1552        1.0  
1552          -0.825409               -0.087250      2  1553        1.0  
1550          -0.498036               -0.267043      2  1551        1.0  
1549          -0.173015               -0.092769      2  1550        1.0  
...                 ...                     ...    ...   ...        ...  
1993          -0.077225               -0.061537      1  1994        1.0  
1994          -0.392016               -0.312380      1  1995        1.0  
1995          -0.092685               -0.046092      1  1996        1.0  
1996          -0.414491               -0.206125      1  1997        1.0  
1997          -0.120458               -0.047901      1  1998        1.0  

[1411 rows x 15 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
1544  39017       3.0  22.760628  5.757780  2.038479     0.001818   
205   13043       3.0  27.027358  6.635976  2.035268     0.126456   
1525  37177       3.0  25.319158  7.937325  1.236794     0.000507   
349   17065       3.0  24.492824  5.942823  0.295453     0.000797   
350   17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...     ...       ...        ...       ...       ...          ...   
1993  51800       1.5  23.349492  7.419639  1.187985     0.008524   
1994  51800       3.0  25.061998  7.586472  1.187985     0.008524   
1995  51810       1.5  23.207888  7.236578  2.482080     0.010662   
1996  51810       3.0  24.859328  7.207139  2.482080     0.010662   
1997  54037       3.0  23.294406  5.721528  0.935788     0.000171   

      y_temp_base_t  y_temp_base2015  lnyield_obs        har  \
1544       7.958094         7.979504     7.994525  14757.740   
205        7.561807         7.761395     7.499042   1336.500   
1525       7.738559         7.905103     7.918210  12818.760   
349        7.610054         7.711970     7.946740  37450.040   
350        7.748190         7.763110     8.213926  58447.890   
...             ...              ...          ...        ...   
1993       7.896463         7.928655     7.798817   7968.552   
1994       7.753334         7.928655     7.798817   7968.552   
1995       8.075677         8.111622     7.872881   4972.955   
1996       7.939772         8.111622     7.872881   4972.955   
1997       7.775021         7.820683     7.900531   3976.619   

      gap_yield_warming  gap_production_warming  group    id  sus_unsus  \
1544          -0.062799               -0.092677      1  1545        1.0   
205           -0.326819               -0.043679      1   206        1.0   
1525          -0.421407               -0.540191      1  1526        1.0   
349           -0.273858               -1.025599      1   350        1.0   
350           -0.054676               -0.319568      1   351        1.0   
...                 ...                     ...    ...   ...        ...   
1993          -0.077225               -0.061537      1  1994        1.0   
1994          -0.392016               -0.312380      1  1995        1.0   
1995          -0.092685               -0.046092      1  1996        1.0   
1996          -0.414491               -0.206125      1  1997        1.0   
1997          -0.120458               -0.047901      1  1998        1.0   

      irrigation1_values  lnfer_values  
1544            0.000024      2.194328  
205             0.000024      3.458172  
1525            0.000024      2.451664  
349             0.000024      1.039221  
350             0.000024      0.063104  
...                  ...           ...  
1993            0.000024      1.421919  
1994            0.000024      2.466086  
1995            0.000024      2.737001  
1996            0.000024      3.729010  
1997            0.000024      1.268919  

[994 rows x 17 columns]
      geoid  scenario  lnfer_need
0      1001       1.5    2.667937
1      1001       3.0    4.505245
2      1003       1.5    1.404700
3      1003       3.0    4.202620
4      1005       1.5    2.215152
...     ...       ...         ...
1993  51103       1.5    3.877447
1994  51103       3.0    3.975355
1995  51141       1.5    3.812177
1996  51159       1.5    1.464794
1997  51159       3.0    1.812194

[1998 rows x 3 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
1544  39017       3.0  22.760628  5.757780  2.038479     0.001818   
205   13043       3.0  27.027358  6.635976  2.035268     0.126456   
1525  37177       3.0  25.319158  7.937325  1.236794     0.000507   
349   17065       3.0  24.492824  5.942823  0.295453     0.000797   
350   17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...     ...       ...        ...       ...       ...          ...   
412   51103       1.5  22.617856  6.753251  3.697080     0.000000   
413   51103       3.0  24.369986  6.937165  3.697080     0.000000   
414   51141       1.5  20.956338  7.018248  3.798184     0.000000   
415   51159       1.5  22.735782  6.657891  1.348576     0.000000   
416   51159       3.0  24.547064  6.747815  1.348576     0.000000   

      y_temp_base_t  y_temp_base2015  lnyield_obs        har  \
1544       7.958094         7.979504     7.994525  14757.740   
205        7.561807         7.761395     7.499042   1336.500   
1525       7.738559         7.905103     7.918210  12818.760   
349        7.610054         7.711970     7.946740  37450.040   
350        7.748190         7.763110     8.213926  58447.890   
...             ...              ...          ...        ...   
412        8.465001         8.499517     8.077533   2916.000   
413        8.441412         8.499517     8.077533   2916.000   
414        8.455265         8.457635     7.902284    243.000   
415        8.009433         8.031712     7.841456   5668.211   
416        7.935400         8.031712     7.841456   5668.211   

      gap_yield_warming  gap_production_warming  group    id  sus_unsus  \
1544          -0.062799               -0.092677      1  1545        1.0   
205           -0.326819               -0.043679      1   206        1.0   
1525          -0.421407               -0.540191      1  1526        1.0   
349           -0.273858               -1.025599      1   350        1.0   
350           -0.054676               -0.319568      1   351        1.0   
...                 ...                     ...    ...   ...        ...   
412           -0.109290               -0.031869      2  1941        1.0   
413           -0.181838               -0.053024      2  1942        1.0   
414           -0.006400               -0.000156      2  1966        1.0   
415           -0.056049               -0.031770      2  1976        1.0   
416           -0.233580               -0.132398      2  1977        1.0   

      irrigation1_values  lnfer_values  gap_irrigation    gap_fer  mana_group  
1544            0.000024      2.194328       -0.001794   1.295049           1  
205             0.000024      3.458172       -0.126432  24.104553           1  
1525            0.000024      2.451664       -0.000484   8.163098           1  
349             0.000024      1.039221       -0.000773   1.483279           1  
350             0.000024      0.063104       -0.001366   0.110474           1  
...                  ...           ...             ...        ...         ...  
412             0.000000      3.877447        0.000000   7.971392           1  
413             0.000000      3.975355        0.000000  12.939640           1  
414             0.000000      3.812177        0.000000   0.628742           1  
415             0.000000      1.464794        0.000000   0.474716           1  
416             0.000000      1.812194        0.000000   2.271934           1  

[1411 rows x 20 columns]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1835122829.py:8: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  results_df1_1['irrigation1_values']=2.388000000000001e-05
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1835122829.py:9: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  results_df1_1['lnfer_values'] = (
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1835122829.py:21: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  results_df1_1['gap_irrigation']=((results_df1_1['irrigation1_values'])-(results_df1_1['irrigation1']))
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1835122829.py:22: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  results_df1_1['gap_fer']=(np.exp(results_df1_1['lnfer_values'])-np.exp(results_df1_1['lnfer'])) #kg/ha
In [17]:
print(np.min(results_df1['gap_irrigation']),np.max(results_df1['gap_irrigation']),
      np.mean(results_df1['gap_irrigation']),np.sum(np.isnan(results_df1['gap_irrigation'])))
print(np.min(results_df1['gap_fer']),np.max(results_df1['gap_fer']),
      np.mean(results_df1['gap_fer']),np.sum(np.isnan(results_df1['gap_fer'])))
-4.09404712 2.387998780000001e-05 -0.131691245861224 0
-276.9264724031997 3502.810511239282 31.829417581299115 0
In [18]:
# for sustainable irrigation we first select the minimum N requirement
results_df0 = ds[ds['sus_unsus'] == 0]
print(results_df0)

# Define ranges and step sizes for variables
lnfer_range = np.linspace(0.086, 4.112, 100)  # Determined by the 5th and 95th percentiles of current input.
irrigation1_range = np.linspace(2.388000000000001e-05, 0.837, 100)  # Determined by the 5th and 95th percentiles of current input.

# Create a list to store data rows
data_rows = []

data = results_df0.copy()
for scenario in data['scenario'].unique():
    for lnfer_value in lnfer_range:
        for irrigation1_value in irrigation1_range:
            print(reg.params['tmp_tmp_interaction']) 
            # Calculate y_temp based on the equation for this group
            tmp_values = data['tmp'].values
            pre_values = data['pre'].values
            lnfer = data['lnfer'].values
            irrigation1 = data['irrigation1'].values
            lnfer_values = lnfer_value * np.ones(len(tmp_values))
            irrigation1_values = irrigation1_value * np.ones(len(tmp_values))
            y_temp = (
                reg.params['tmp_tmp_interaction'] * tmp_values**2 +
                reg.params['tmp'] * tmp_values +
                reg.params['pre_pre_interaction'] * pre_values**2 +
                reg.params['pre'] * pre_values +
                reg.params['lnfer'] * lnfer_values +
                reg.params['irrigation1'] * irrigation1_values + 
                reg.params['irrigation12'] * irrigation1_values**2 +
                reg.params['lnfer_irrigation1_tmp_interaction'] * irrigation1_values * tmp_values * lnfer_values +
                reg.params['lnfer_irrigation12_tmp_tmp_interaction'] * irrigation1_values**2 * lnfer_values * tmp_values**2 +
                reg.params['lnfer_irrigation1_pre_interaction'] * irrigation1_values * pre_values * lnfer_values +
                reg.params['lnfer_irrigation12_pre_pre_interaction'] * irrigation1_values**2 * lnfer_values * pre_values**2 +
                reg.params['const']
            )                               
            # Append data to the list
            data_rows.extend(zip(lnfer_values, irrigation1_values, tmp_values, pre_values,
                                  data['lnfer'].values, data['irrigation1'].values,
                                  y_temp,  data['geoid'].values, data['y_temp_base2015'].values,
                                   data['y_temp_base_t'].values,data['lnyield_obs'].values, data['scenario'].values,
                                   data['har'].values))

# Create a DataFrame from the data
results_df = pd.DataFrame(data_rows, columns=['lnfer_values', 'irrigation1_values', 'tmp', 'pre', 'lnfer', 
                                              'irrigation1', 'y_temp','geoid','y_temp_base2015', 'y_temp_base_t',
                                              'lnyield_obs','scenario', 'har'])

# Drop duplicate rows based on specific columns
results_df = results_df.drop_duplicates(subset=['lnfer_values', 'irrigation1_values','geoid', 'scenario'])
# Print the updated DataFrame
print(results_df)

# Drop duplicate rows based on specific columns
df = results_df.drop_duplicates(subset=['lnfer_values', 'irrigation1_values', 'geoid', 'scenario'])

# Print the updated DataFrame
df['dif_lny_less'] = (df['y_temp'] - df['y_temp_base2015'])
df['gap_irrigation'] = (df['irrigation1_values'] - df['irrigation1'])
df['gap_fer'] = (np.exp(df['lnfer_values']) - np.exp(df['lnfer']))  # kg/ha
print(df)
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0      1001       1.5  25.099590  6.254395  2.457656     0.377088   
1122  28155       1.5  24.597372  6.798732  2.709249     0.000000   
1123  28155       3.0  26.340148  6.540652  2.709249     0.000000   
1136  29009       1.5  23.353156  6.747682  4.209049     0.000000   
1137  29009       3.0  25.124780  6.431704  4.209049     0.000000   
...     ...       ...        ...       ...       ...          ...   
320   17027       3.0  24.524190  5.967095  0.424643     0.008192   
390   17123       1.5  20.623212  5.795630  0.151525     0.002031   
391   17123       3.0  22.540752  5.574082  0.151525     0.002031   
334   17049       1.5  22.205882  5.712175  0.019746     0.000821   
319   17027       1.5  22.761176  5.630632  0.424643     0.008192   

      y_temp_base_t  y_temp_base2015  lnyield_obs        har  \
0          7.846458         7.871762     7.509678    779.625   
1122       8.217792         8.257644     7.753458   1499.437   
1123       8.080269         8.257644     7.753458   1499.437   
1136       8.562132         8.606349     7.585869   1176.583   
1137       8.478483         8.606349     7.585869   1176.583   
...             ...              ...          ...        ...   
320        7.626825         7.752478     8.027052  41975.030   
390        7.742939         7.753060     8.232135  29476.430   
391        7.695141         7.753060     8.232135  29476.430   
334        7.700286         7.719907     8.142404  39724.610   
319        7.727484         7.752478     8.027052  41975.030   

      gap_yield_warming  gap_production_warming  group    id  sus_unsus  
0             -0.045616               -0.003556      1     1        0.0  
1122          -0.091012               -0.013647      2  1123        0.0  
1123          -0.378641               -0.056775      2  1124        0.0  
1136          -0.085216               -0.010026      2  1137        0.0  
1137          -0.236475               -0.027823      2  1138        0.0  
...                 ...                     ...    ...   ...        ...  
320           -0.361641               -1.517989      1   321        0.0  
390           -0.037861               -0.111601      1   391        0.0  
391           -0.211579               -0.623660      1   392        0.0  
334           -0.066785               -0.265300      1   335        0.0  
319           -0.075598               -0.317324      1   320        0.0  

[587 rows x 15 columns]
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
-0.013398123665888008
         lnfer_values  irrigation1_values        tmp       pre     lnfer  \
0               0.086            0.000024  25.099590  6.254395  2.457656   
1               0.086            0.000024  24.597372  6.798732  2.709249   
2               0.086            0.000024  26.340148  6.540652  2.709249   
3               0.086            0.000024  23.353156  6.747682  4.209049   
4               0.086            0.000024  25.124780  6.431704  4.209049   
...               ...                 ...        ...       ...       ...   
5869995         4.112            0.837000  24.524190  5.967095  0.424643   
5869996         4.112            0.837000  20.623212  5.795630  0.151525   
5869997         4.112            0.837000  22.540752  5.574082  0.151525   
5869998         4.112            0.837000  22.205882  5.712175  0.019746   
5869999         4.112            0.837000  22.761176  5.630632  0.424643   

         irrigation1    y_temp  geoid  y_temp_base2015  y_temp_base_t  \
0           0.377088  7.539891   1001         7.871762       7.846458   
1           0.000000  7.621532  28155         8.257644       8.217792   
2           0.000000  7.399058  28155         8.257644       8.080269   
3           0.000000  7.718807  29009         8.606349       8.562132   
4           0.000000  7.547638  29009         8.606349       8.478483   
...              ...       ...    ...              ...            ...   
5869995     0.008192  8.045621  17027         7.752478       7.626825   
5869996     0.002031  8.184346  17123         7.753060       7.742939   
5869997     0.002031  8.157101  17123         7.753060       7.695141   
5869998     0.000821  8.172492  17049         7.719907       7.700286   
5869999     0.008192  8.150574  17027         7.752478       7.727484   

         lnyield_obs  scenario        har  
0           7.509678       1.5    779.625  
1           7.753458       1.5   1499.437  
2           7.753458       3.0   1499.437  
3           7.585869       1.5   1176.583  
4           7.585869       3.0   1176.583  
...              ...       ...        ...  
5869995     8.027052       3.0  41975.030  
5869996     8.232135       1.5  29476.430  
5869997     8.232135       3.0  29476.430  
5869998     8.142404       1.5  39724.610  
5869999     8.027052       1.5  41975.030  

[5870000 rows x 13 columns]
         lnfer_values  irrigation1_values        tmp       pre     lnfer  \
0               0.086            0.000024  25.099590  6.254395  2.457656   
1               0.086            0.000024  24.597372  6.798732  2.709249   
2               0.086            0.000024  26.340148  6.540652  2.709249   
3               0.086            0.000024  23.353156  6.747682  4.209049   
4               0.086            0.000024  25.124780  6.431704  4.209049   
...               ...                 ...        ...       ...       ...   
5869995         4.112            0.837000  24.524190  5.967095  0.424643   
5869996         4.112            0.837000  20.623212  5.795630  0.151525   
5869997         4.112            0.837000  22.540752  5.574082  0.151525   
5869998         4.112            0.837000  22.205882  5.712175  0.019746   
5869999         4.112            0.837000  22.761176  5.630632  0.424643   

         irrigation1    y_temp  geoid  y_temp_base2015  y_temp_base_t  \
0           0.377088  7.539891   1001         7.871762       7.846458   
1           0.000000  7.621532  28155         8.257644       8.217792   
2           0.000000  7.399058  28155         8.257644       8.080269   
3           0.000000  7.718807  29009         8.606349       8.562132   
4           0.000000  7.547638  29009         8.606349       8.478483   
...              ...       ...    ...              ...            ...   
5869995     0.008192  8.045621  17027         7.752478       7.626825   
5869996     0.002031  8.184346  17123         7.753060       7.742939   
5869997     0.002031  8.157101  17123         7.753060       7.695141   
5869998     0.000821  8.172492  17049         7.719907       7.700286   
5869999     0.008192  8.150574  17027         7.752478       7.727484   

         lnyield_obs  scenario        har  dif_lny_less  gap_irrigation  \
0           7.509678       1.5    779.625     -0.331871       -0.377064   
1           7.753458       1.5   1499.437     -0.636111        0.000024   
2           7.753458       3.0   1499.437     -0.858585        0.000024   
3           7.585869       1.5   1176.583     -0.887541        0.000024   
4           7.585869       3.0   1176.583     -1.058711        0.000024   
...              ...       ...        ...           ...             ...   
5869995     8.027052       3.0  41975.030      0.293143        0.828808   
5869996     8.232135       1.5  29476.430      0.431286        0.834969   
5869997     8.232135       3.0  29476.430      0.404042        0.834969   
5869998     8.142404       1.5  39724.610      0.452584        0.836179   
5869999     8.027052       1.5  41975.030      0.398097        0.828808   

           gap_fer  
0       -10.587601  
1       -13.928186  
2       -13.928186  
3       -66.202708  
4       -66.202708  
...            ...  
5869995  59.539689  
5869996  59.905126  
5869997  59.905126  
5869998  60.048790  
5869999  59.539689  

[5870000 rows x 16 columns]
In [19]:
df1=df[df['dif_lny_less']>=0]
print(df1)
df1= df1.sort_values(by=['scenario',  'geoid','gap_fer', 'gap_irrigation'])
df1['min_gap_fer'] = df1.loc[df1.groupby(['scenario',  'geoid'])['gap_fer'].idxmin(), 'gap_fer']

# Filter rows where 'gap_fer' == 'min_gap_fer'
df2 = df1[df1['gap_fer'] == df1['min_gap_fer']]
print(df2)
#Then select min N requirement
df2['min_gap_irrigation'] = df2.loc[df2.groupby(['scenario',  'geoid'])['gap_irrigation'].idxmin(), 'gap_irrigation']
results_df2= df2[df2['gap_irrigation'] == df2['min_gap_irrigation']]
results_df2['mana_group']=2
print(results_df2)
         lnfer_values  irrigation1_values        tmp       pre     lnfer  \
396             0.086            0.000024  21.719492  5.769740 -0.140132   
495             0.086            0.000024  20.601038  5.724906 -0.238950   
499             0.086            0.000024  20.747524  5.986479 -0.266186   
505             0.086            0.000024  22.257840  5.857302 -0.085569   
507             0.086            0.000024  22.378038  5.774409 -0.195562   
...               ...                 ...        ...       ...       ...   
5869995         4.112            0.837000  24.524190  5.967095  0.424643   
5869996         4.112            0.837000  20.623212  5.795630  0.151525   
5869997         4.112            0.837000  22.540752  5.574082  0.151525   
5869998         4.112            0.837000  22.205882  5.712175  0.019746   
5869999         4.112            0.837000  22.761176  5.630632  0.424643   

         irrigation1    y_temp  geoid  y_temp_base2015  y_temp_base_t  \
396         0.001343  7.726423  17149         7.725731       7.695517   
495         0.000014  7.728309  17105         7.691298       7.683764   
499         0.000087  7.748505  17095         7.701831       7.700232   
505         0.000008  7.718389  17079         7.711927       7.694869   
507         0.010316  7.707990  17073         7.704149       7.670138   
...              ...       ...    ...              ...            ...   
5869995     0.008192  8.045621  17027         7.752478       7.626825   
5869996     0.002031  8.184346  17123         7.753060       7.742939   
5869997     0.002031  8.157101  17123         7.753060       7.695141   
5869998     0.000821  8.172492  17049         7.719907       7.700286   
5869999     0.008192  8.150574  17027         7.752478       7.727484   

         lnyield_obs  scenario        har  dif_lny_less  gap_irrigation  \
396         8.133454       1.5   42870.55      0.000692       -0.001319   
495         8.202496       1.5  109809.70      0.037010        0.000010   
499         8.278972       1.5   49034.61      0.046674       -0.000063   
505         8.088742       1.5   47020.59      0.006462        0.000016   
507         8.238276       3.0   65284.08      0.003841       -0.010292   
...              ...       ...        ...           ...             ...   
5869995     8.027052       3.0   41975.03      0.293143        0.828808   
5869996     8.232135       1.5   29476.43      0.431286        0.834969   
5869997     8.232135       3.0   29476.43      0.404042        0.834969   
5869998     8.142404       1.5   39724.61      0.452584        0.836179   
5869999     8.027052       1.5   41975.03      0.398097        0.828808   

           gap_fer  
396       0.220563  
495       0.302352  
499       0.323509  
505       0.171816  
507       0.267434  
...            ...  
5869995  59.539689  
5869996  59.905126  
5869997  59.905126  
5869998  60.048790  
5869999  59.539689  

[1328664 rows x 16 columns]
         lnfer_values  irrigation1_values        tmp       pre     lnfer  \
3522000      2.526000            0.000024  25.099590  6.254395  2.457656   
1526713      1.143333            0.000024  26.261318  9.274925  1.292553   
3111615      2.241333            0.000024  25.408514  6.727813  2.114730   
3874719      2.770000            0.000024  23.114532  6.486805  2.773365   
3757321      2.688667            0.000024  25.540484  7.249442  2.577108   
...               ...                 ...        ...       ...       ...   
5048441      3.583333            0.000024  22.923516  6.107724  3.349302   
5400645      3.827333            0.000024  24.528476  6.405407  2.662537   
4989747      3.542667            0.000024  22.539126  6.282785  3.286767   
5048449      3.583333            0.000024  24.569916  6.204955  2.479970   
3874569      2.770000            0.000024  24.838466  7.128091  1.451035   

         irrigation1    y_temp  geoid  y_temp_base2015  y_temp_base_t  \
3522000     0.377088  7.874365   1001         7.871762       7.846458   
1526713     0.738441  7.602207   1003         7.599898       7.590898   
3111615     0.028216  7.826231   1005         7.821125       7.807509   
3874719     0.182637  8.087544   1019         8.085071       8.072930   
3757321     0.045782  7.893573   1031         7.888481       7.874131   
...              ...       ...    ...              ...            ...   
5048441     0.007355  8.186462  51139         8.184910       8.153659   
5400645     0.004153  8.120382  51145         8.118854       7.960425   
4989747     0.000534  8.209979  51163         8.209051       8.174846   
5048449     0.013820  8.070864  51179         8.069013       7.918880   
3874569     0.047134  7.979385  51183         7.975989       7.797517   

         lnyield_obs  scenario         har  dif_lny_less  gap_irrigation  \
3522000     7.509678       1.5    779.6250      0.002603       -0.377064   
1526713     7.927428       1.5   6358.4330      0.002309       -0.738418   
3111615     8.161582       1.5    526.5000      0.005106       -0.028192   
3874719     7.779649       1.5   5017.9500      0.002473       -0.182613   
3757321     7.785782       1.5   1655.9780      0.005092       -0.045758   
...              ...       ...         ...           ...             ...   
5048441     7.900331       3.0    308.1206      0.001552       -0.007331   
5400645     7.903108       3.0    833.2875      0.001528       -0.004129   
4989747     8.017239       3.0    255.5550      0.000928       -0.000511   
5048449     7.831026       3.0    586.0350      0.001851       -0.013796   
3874569     7.653934       3.0  10258.0700      0.003396       -0.047110   

           gap_fer  min_gap_fer  
3522000   0.825985     0.825985  
1526713  -0.504865    -0.504865  
3111615   1.118516     1.118516  
3874719  -0.053791    -0.053791  
3757321   1.553020     1.553020  
...            ...          ...  
5048441   7.510473     7.510473  
5400645  31.607264    31.607264  
4989747   7.802733     7.802733  
5048449  24.052413    24.052413  
3874569  11.691105    11.691105  

[392 rows x 17 columns]
         lnfer_values  irrigation1_values        tmp       pre     lnfer  \
3522000      2.526000            0.000024  25.099590  6.254395  2.457656   
1526713      1.143333            0.000024  26.261318  9.274925  1.292553   
3111615      2.241333            0.000024  25.408514  6.727813  2.114730   
3874719      2.770000            0.000024  23.114532  6.486805  2.773365   
3757321      2.688667            0.000024  25.540484  7.249442  2.577108   
...               ...                 ...        ...       ...       ...   
5048441      3.583333            0.000024  22.923516  6.107724  3.349302   
5400645      3.827333            0.000024  24.528476  6.405407  2.662537   
4989747      3.542667            0.000024  22.539126  6.282785  3.286767   
5048449      3.583333            0.000024  24.569916  6.204955  2.479970   
3874569      2.770000            0.000024  24.838466  7.128091  1.451035   

         irrigation1    y_temp  geoid  y_temp_base2015  y_temp_base_t  \
3522000     0.377088  7.874365   1001         7.871762       7.846458   
1526713     0.738441  7.602207   1003         7.599898       7.590898   
3111615     0.028216  7.826231   1005         7.821125       7.807509   
3874719     0.182637  8.087544   1019         8.085071       8.072930   
3757321     0.045782  7.893573   1031         7.888481       7.874131   
...              ...       ...    ...              ...            ...   
5048441     0.007355  8.186462  51139         8.184910       8.153659   
5400645     0.004153  8.120382  51145         8.118854       7.960425   
4989747     0.000534  8.209979  51163         8.209051       8.174846   
5048449     0.013820  8.070864  51179         8.069013       7.918880   
3874569     0.047134  7.979385  51183         7.975989       7.797517   

         lnyield_obs  scenario         har  dif_lny_less  gap_irrigation  \
3522000     7.509678       1.5    779.6250      0.002603       -0.377064   
1526713     7.927428       1.5   6358.4330      0.002309       -0.738418   
3111615     8.161582       1.5    526.5000      0.005106       -0.028192   
3874719     7.779649       1.5   5017.9500      0.002473       -0.182613   
3757321     7.785782       1.5   1655.9780      0.005092       -0.045758   
...              ...       ...         ...           ...             ...   
5048441     7.900331       3.0    308.1206      0.001552       -0.007331   
5400645     7.903108       3.0    833.2875      0.001528       -0.004129   
4989747     8.017239       3.0    255.5550      0.000928       -0.000511   
5048449     7.831026       3.0    586.0350      0.001851       -0.013796   
3874569     7.653934       3.0  10258.0700      0.003396       -0.047110   

           gap_fer  min_gap_fer  min_gap_irrigation  mana_group  
3522000   0.825985     0.825985           -0.377064           2  
1526713  -0.504865    -0.504865           -0.738418           2  
3111615   1.118516     1.118516           -0.028192           2  
3874719  -0.053791    -0.053791           -0.182613           2  
3757321   1.553020     1.553020           -0.045758           2  
...            ...          ...                 ...         ...  
5048441   7.510473     7.510473           -0.007331           2  
5400645  31.607264    31.607264           -0.004129           2  
4989747   7.802733     7.802733           -0.000511           2  
5048449  24.052413    24.052413           -0.013796           2  
3874569  11.691105    11.691105           -0.047110           2  

[392 rows x 19 columns]
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/545454127.py:10: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  df2['min_gap_irrigation'] = df2.loc[df2.groupby(['scenario',  'geoid'])['gap_irrigation'].idxmin(), 'gap_irrigation']
In [20]:
print(np.min(results_df2['gap_irrigation']),np.max(results_df2['gap_irrigation']),
      np.mean(results_df2['gap_irrigation']),np.sum(np.isnan(results_df2['gap_irrigation'])))
print(np.min(results_df2['gap_fer']),np.max(results_df2['gap_fer']),
      np.mean(results_df2['gap_fer']),np.sum(np.isnan(results_df2['gap_fer'])))
-3.7462991199999998 0.8369975599999999 -0.04949858193797928 0
-59.33647186383185 54.39053625288224 10.072200823313318 0
In [21]:
ds3=results_df0.merge(results_df2, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')
ds3 = ds3[ds3['min_gap_fer'].isna()]
print(ds3)

ds3=ds3[['geoid', 'scenario']]


results_df3=ds3.merge(results_lnfer, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')

results_df3['gap_fer']=(np.exp(results_df3['lnfer_need'])-np.exp(results_df3['lnfer'])) 
results_df3['gap_irrigation']=0
results_df3['irrigation1_values']=results_df3['irrigation1']
results_df3['lnfer_values']=results_df3['lnfer_need']
results_df3['y_temp']=results_df3['y_temp_base2015']
results_df3 = results_df3.drop(columns=['lnfer_need'])
results_df3['mana_group']=3
print(results_df3)
     geoid  scenario      tmp_x     pre_x   lnfer_x  irrigation1_x  \
1    28155       1.5  24.597372  6.798732  2.709249       0.000000   
2    28155       3.0  26.340148  6.540652  2.709249       0.000000   
3    29009       1.5  23.353156  6.747682  4.209049       0.000000   
4    29009       3.0  25.124780  6.431704  4.209049       0.000000   
7    29023       3.0  25.334522  5.720488  2.080452       0.000000   
..     ...       ...        ...       ...       ...            ...   
530   1043       3.0  25.723312  6.718675  4.369129       0.149384   
540   1075       3.0  26.457528  6.493699  2.301965       0.027715   
550   1085       3.0  27.248052  6.264505  3.149844       0.318468   
552   1087       3.0  26.679214  6.355030  4.096728       0.210819   
559   1091       3.0  27.222396  6.256731  2.847938       0.009984   

     y_temp_base_t_x  y_temp_base2015_x  lnyield_obs_x       har_x  ...  \
1           8.217792           8.257644       7.753458   1499.4370  ...   
2           8.080269           8.257644       7.753458   1499.4370  ...   
3           8.562132           8.606349       7.585869   1176.5830  ...   
4           8.478483           8.606349       7.585869   1176.5830  ...   
7           7.985208           8.093990       8.002616  43566.9400  ...   
..               ...                ...            ...         ...  ...   
530         8.054614           8.278050       7.978103   2906.2460  ...   
540         7.681917           7.966898       7.625159    564.0975  ...   
550         7.639415           7.910322       7.784370   1699.6330  ...   
552         7.862778           8.090918       7.847030    598.4888  ...   
559         7.623575           7.908306       7.563227   1578.0490  ...   

     y_temp_base2015_y  y_temp_base_t_y  lnyield_obs_y  har_y  dif_lny_less  \
1                  NaN              NaN            NaN    NaN           NaN   
2                  NaN              NaN            NaN    NaN           NaN   
3                  NaN              NaN            NaN    NaN           NaN   
4                  NaN              NaN            NaN    NaN           NaN   
7                  NaN              NaN            NaN    NaN           NaN   
..                 ...              ...            ...    ...           ...   
530                NaN              NaN            NaN    NaN           NaN   
540                NaN              NaN            NaN    NaN           NaN   
550                NaN              NaN            NaN    NaN           NaN   
552                NaN              NaN            NaN    NaN           NaN   
559                NaN              NaN            NaN    NaN           NaN   

     gap_irrigation  gap_fer  min_gap_fer  min_gap_irrigation  mana_group  
1               NaN      NaN          NaN                 NaN         NaN  
2               NaN      NaN          NaN                 NaN         NaN  
3               NaN      NaN          NaN                 NaN         NaN  
4               NaN      NaN          NaN                 NaN         NaN  
7               NaN      NaN          NaN                 NaN         NaN  
..              ...      ...          ...                 ...         ...  
530             NaN      NaN          NaN                 NaN         NaN  
540             NaN      NaN          NaN                 NaN         NaN  
550             NaN      NaN          NaN                 NaN         NaN  
552             NaN      NaN          NaN                 NaN         NaN  
559             NaN      NaN          NaN                 NaN         NaN  

[195 rows x 32 columns]
     geoid  scenario        tmp       pre     lnfer  irrigation1  \
0    28155       1.5  24.597372  6.798732  2.709249     0.000000   
1    28155       3.0  26.340148  6.540652  2.709249     0.000000   
2    29009       1.5  23.353156  6.747682  4.209049     0.000000   
3    29009       3.0  25.124780  6.431704  4.209049     0.000000   
4    29023       3.0  25.334522  5.720488  2.080452     0.000000   
..     ...       ...        ...       ...       ...          ...   
190   1043       3.0  25.723312  6.718675  4.369129     0.149384   
191   1075       3.0  26.457528  6.493699  2.301965     0.027715   
192   1085       3.0  27.248052  6.264505  3.149844     0.318468   
193   1087       3.0  26.679214  6.355030  4.096728     0.210819   
194   1091       3.0  27.222396  6.256731  2.847938     0.009984   

     y_temp_base2015  y_temp_base_t  lnyield_obs         har     gap_fer  \
0           8.257644       8.217792     7.753458   1499.4370    3.162361   
1           8.257644       8.080269     7.753458   1499.4370   20.099739   
2           8.606349       8.562132     7.585869   1176.5830   16.730996   
3           8.606349       8.478483     7.585869   1176.5830   57.701358   
4           8.093990       7.985208     8.002616  43566.9400    5.863311   
..               ...            ...          ...         ...         ...   
190         8.278050       8.054614     7.978103   2906.2460  364.946897   
191         7.966898       7.681917     7.625159    564.0975   71.562105   
192         7.910322       7.639415     7.784370   1699.6330  184.540509   
193         8.090918       7.862778     7.847030    598.4888  298.745838   
194         7.908306       7.623575     7.563227   1578.0490  121.360035   

     gap_irrigation  irrigation1_values  lnfer_values    y_temp  mana_group  
0                 0            0.000000      2.900342  8.257644           3  
1                 0            0.000000      3.558706  8.257644           3  
2                 0            0.000000      4.431097  8.606349           3  
3                 0            0.000000      4.828265  8.606349           3  
4                 0            0.000000      2.629829  8.093990           3  
..              ...                 ...           ...       ...         ...  
190               0            0.149384      6.095648  8.278050           3  
191               0            0.027715      4.401289  7.966898           3  
192               0            0.318468      5.336927  7.910322           3  
193               0            0.210819      5.883013  8.090918           3  
194               0            0.009984      4.931680  7.908306           3  

[195 rows x 16 columns]
In [22]:
print(np.min(results_df3['gap_irrigation']),np.max(results_df3['gap_irrigation']),
      np.mean(results_df3['gap_irrigation']),np.sum(np.isnan(results_df3['gap_irrigation'])))
print(np.min(results_df3['gap_fer']),np.max(results_df3['gap_fer']),
      np.mean(results_df3['gap_fer']),np.sum(np.isnan(results_df3['gap_fer'])))
0 0 0.0 0
0.6536715793407293 4302.983035950181 215.2738204700021 0
In [23]:
results_df13=pd.concat([results_df1, results_df3])
print(np.min(results_df13['gap_irrigation']),np.max(results_df13['gap_irrigation']),
      np.mean(results_df13['gap_irrigation']),np.sum(np.isnan(results_df13['gap_irrigation'])))
print(np.min(results_df13['gap_fer']),np.max(results_df13['gap_fer']),
      np.mean(results_df13['gap_fer']),np.sum(np.isnan(results_df13['gap_fer'])))
-4.09404712 2.387998780000001e-05 -0.11570133742851003 0
-276.9264724031997 4302.983035950181 54.10317758335209 0
In [24]:
results1=pd.concat([results_df1, results_df2])
results1 = results1.drop(['id','dif_lny_less','min_gap_fer','min_gap_irrigation'], axis=1)
results1['y_temp'] = results1['y_temp'].fillna(results1['y_temp_base2015'])
print(results1)

results=pd.concat([results1, results_df3])
print(results)
         geoid  scenario        tmp       pre     lnfer  irrigation1  \
1544     39017       3.0  22.760628  5.757780  2.038479     0.001818   
205      13043       3.0  27.027358  6.635976  2.035268     0.126456   
1525     37177       3.0  25.319158  7.937325  1.236794     0.000507   
349      17065       3.0  24.492824  5.942823  0.295453     0.000797   
350      17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...        ...       ...        ...       ...       ...          ...   
5048441  51139       3.0  22.923516  6.107724  3.349302     0.007355   
5400645  51145       3.0  24.528476  6.405407  2.662537     0.004153   
4989747  51163       3.0  22.539126  6.282785  3.286767     0.000534   
5048449  51179       3.0  24.569916  6.204955  2.479970     0.013820   
3874569  51183       3.0  24.838466  7.128091  1.451035     0.047134   

         y_temp_base_t  y_temp_base2015  lnyield_obs         har  \
1544          7.958094         7.979504     7.994525  14757.7400   
205           7.561807         7.761395     7.499042   1336.5000   
1525          7.738559         7.905103     7.918210  12818.7600   
349           7.610054         7.711970     7.946740  37450.0400   
350           7.748190         7.763110     8.213926  58447.8900   
...                ...              ...          ...         ...   
5048441       8.153659         8.184910     7.900331    308.1206   
5400645       7.960425         8.118854     7.903108    833.2875   
4989747       8.174846         8.209051     8.017239    255.5550   
5048449       7.918880         8.069013     7.831026    586.0350   
3874569       7.797517         7.975989     7.653934  10258.0700   

         gap_yield_warming  gap_production_warming  group  sus_unsus  \
1544             -0.062799               -0.092677    1.0        1.0   
205              -0.326819               -0.043679    1.0        1.0   
1525             -0.421407               -0.540191    1.0        1.0   
349              -0.273858               -1.025599    1.0        1.0   
350              -0.054676               -0.319568    1.0        1.0   
...                    ...                     ...    ...        ...   
5048441                NaN                     NaN    NaN        NaN   
5400645                NaN                     NaN    NaN        NaN   
4989747                NaN                     NaN    NaN        NaN   
5048449                NaN                     NaN    NaN        NaN   
3874569                NaN                     NaN    NaN        NaN   

         irrigation1_values  lnfer_values  gap_irrigation    gap_fer  \
1544               0.000024      2.194328       -0.001794   1.295049   
205                0.000024      3.458172       -0.126432  24.104553   
1525               0.000024      2.451664       -0.000484   8.163098   
349                0.000024      1.039221       -0.000773   1.483279   
350                0.000024      0.063104       -0.001366   0.110474   
...                     ...           ...             ...        ...   
5048441            0.000024      3.583333       -0.007331   7.510473   
5400645            0.000024      3.827333       -0.004129  31.607264   
4989747            0.000024      3.542667       -0.000511   7.802733   
5048449            0.000024      3.583333       -0.013796  24.052413   
3874569            0.000024      2.770000       -0.047110  11.691105   

         mana_group    y_temp  
1544              1  7.979504  
205               1  7.761395  
1525              1  7.905103  
349               1  7.711970  
350               1  7.763110  
...             ...       ...  
5048441           2  8.186462  
5400645           2  8.120382  
4989747           2  8.209979  
5048449           2  8.070864  
3874569           2  7.979385  

[1803 rows x 20 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
1544  39017       3.0  22.760628  5.757780  2.038479     0.001818   
205   13043       3.0  27.027358  6.635976  2.035268     0.126456   
1525  37177       3.0  25.319158  7.937325  1.236794     0.000507   
349   17065       3.0  24.492824  5.942823  0.295453     0.000797   
350   17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...     ...       ...        ...       ...       ...          ...   
190    1043       3.0  25.723312  6.718675  4.369129     0.149384   
191    1075       3.0  26.457528  6.493699  2.301965     0.027715   
192    1085       3.0  27.248052  6.264505  3.149844     0.318468   
193    1087       3.0  26.679214  6.355030  4.096728     0.210819   
194    1091       3.0  27.222396  6.256731  2.847938     0.009984   

      y_temp_base_t  y_temp_base2015  lnyield_obs         har  \
1544       7.958094         7.979504     7.994525  14757.7400   
205        7.561807         7.761395     7.499042   1336.5000   
1525       7.738559         7.905103     7.918210  12818.7600   
349        7.610054         7.711970     7.946740  37450.0400   
350        7.748190         7.763110     8.213926  58447.8900   
...             ...              ...          ...         ...   
190        8.054614         8.278050     7.978103   2906.2460   
191        7.681917         7.966898     7.625159    564.0975   
192        7.639415         7.910322     7.784370   1699.6330   
193        7.862778         8.090918     7.847030    598.4888   
194        7.623575         7.908306     7.563227   1578.0490   

      gap_yield_warming  gap_production_warming  group  sus_unsus  \
1544          -0.062799               -0.092677    1.0        1.0   
205           -0.326819               -0.043679    1.0        1.0   
1525          -0.421407               -0.540191    1.0        1.0   
349           -0.273858               -1.025599    1.0        1.0   
350           -0.054676               -0.319568    1.0        1.0   
...                 ...                     ...    ...        ...   
190                 NaN                     NaN    NaN        NaN   
191                 NaN                     NaN    NaN        NaN   
192                 NaN                     NaN    NaN        NaN   
193                 NaN                     NaN    NaN        NaN   
194                 NaN                     NaN    NaN        NaN   

      irrigation1_values  lnfer_values  gap_irrigation     gap_fer  \
1544            0.000024      2.194328       -0.001794    1.295049   
205             0.000024      3.458172       -0.126432   24.104553   
1525            0.000024      2.451664       -0.000484    8.163098   
349             0.000024      1.039221       -0.000773    1.483279   
350             0.000024      0.063104       -0.001366    0.110474   
...                  ...           ...             ...         ...   
190             0.149384      6.095648        0.000000  364.946897   
191             0.027715      4.401289        0.000000   71.562105   
192             0.318468      5.336927        0.000000  184.540509   
193             0.210819      5.883013        0.000000  298.745838   
194             0.009984      4.931680        0.000000  121.360035   

      mana_group    y_temp  
1544           1  7.979504  
205            1  7.761395  
1525           1  7.905103  
349            1  7.711970  
350            1  7.763110  
...          ...       ...  
190            3  8.278050  
191            3  7.966898  
192            3  7.910322  
193            3  8.090918  
194            3  7.908306  

[1998 rows x 20 columns]
In [25]:
results_lnfer1=results_lnfer[['geoid','scenario','lnfer_need']]
print(results_lnfer1)

results_ok = results.merge(results_lnfer1, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')
results_ok = results_ok.merge(results_irri1, left_on=['geoid', 'scenario'], 
                                right_on=['geoid', 'scenario'], how='left')
print(results_ok)
      geoid  scenario  lnfer_need
0      1001       1.5    2.667937
1      1001       3.0    4.505245
2      1003       1.5    1.404700
3      1003       3.0    4.202620
4      1005       1.5    2.215152
...     ...       ...         ...
1993  51103       1.5    3.877447
1994  51103       3.0    3.975355
1995  51141       1.5    3.812177
1996  51159       1.5    1.464794
1997  51159       3.0    1.812194

[1998 rows x 3 columns]
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0     39017       3.0  22.760628  5.757780  2.038479     0.001818   
1     13043       3.0  27.027358  6.635976  2.035268     0.126456   
2     37177       3.0  25.319158  7.937325  1.236794     0.000507   
3     17065       3.0  24.492824  5.942823  0.295453     0.000797   
4     17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...     ...       ...        ...       ...       ...          ...   
1993   1043       3.0  25.723312  6.718675  4.369129     0.149384   
1994   1075       3.0  26.457528  6.493699  2.301965     0.027715   
1995   1085       3.0  27.248052  6.264505  3.149844     0.318468   
1996   1087       3.0  26.679214  6.355030  4.096728     0.210819   
1997   1091       3.0  27.222396  6.256731  2.847938     0.009984   

      y_temp_base_t  y_temp_base2015  lnyield_obs         har  ...  \
0          7.958094         7.979504     7.994525  14757.7400  ...   
1          7.561807         7.761395     7.499042   1336.5000  ...   
2          7.738559         7.905103     7.918210  12818.7600  ...   
3          7.610054         7.711970     7.946740  37450.0400  ...   
4          7.748190         7.763110     8.213926  58447.8900  ...   
...             ...              ...          ...         ...  ...   
1993       8.054614         8.278050     7.978103   2906.2460  ...   
1994       7.681917         7.966898     7.625159    564.0975  ...   
1995       7.639415         7.910322     7.784370   1699.6330  ...   
1996       7.862778         8.090918     7.847030    598.4888  ...   
1997       7.623575         7.908306     7.563227   1578.0490  ...   

      irrigation1_values  lnfer_values  gap_irrigation     gap_fer  \
0               0.000024      2.194328       -0.001794    1.295049   
1               0.000024      3.458172       -0.126432   24.104553   
2               0.000024      2.451664       -0.000484    8.163098   
3               0.000024      1.039221       -0.000773    1.483279   
4               0.000024      0.063104       -0.001366    0.110474   
...                  ...           ...             ...         ...   
1993            0.149384      6.095648        0.000000  364.946897   
1994            0.027715      4.401289        0.000000   71.562105   
1995            0.318468      5.336927        0.000000  184.540509   
1996            0.210819      5.883013        0.000000  298.745838   
1997            0.009984      4.931680        0.000000  121.360035   

      mana_group    y_temp  lnfer_need  irri_need  irri_need_1  y_temp_irri  
0              1  7.979504    2.194755   0.837454     0.837454     7.938183  
1              1  7.761395    3.559168   0.837454     0.837454     7.540154  
2              1  7.905103    2.452045   0.837454     0.837454     7.721508  
3              1  7.711970    1.039118        NaN     0.837454     7.647000  
4              1  7.763110    0.062503   0.235000     0.235000     7.763084  
...          ...       ...         ...        ...          ...          ...  
1993           3  8.278050    6.095648   0.837454     0.837454     7.957525  
1994           3  7.966898    4.401289   0.837454     0.837454     7.649035  
1995           3  7.910322    5.336927   0.837454     0.837454     7.608856  
1996           3  8.090918    5.883013   0.837454     0.837454     7.798237  
1997           3  7.908306    4.931680   0.837454     0.837454     7.580939  

[1998 rows x 24 columns]
In [26]:
#if under management strategy, gap_irrigaton>0, ['gap_fer']>['gap_fer1']
# that means more  N and irrigation are needed under integrated strategy
# replace them into 'N only'
results_ok['gap_fer1']=(np.exp(results_ok['lnfer_need'])-np.exp(results_ok['lnfer']))
condition = (results_ok['gap_fer'] > results_ok['gap_fer1']) & (results_ok['gap_irrigation'] > 0)
# Assign values to 'gap_fer' based on the condition
results_ok['gap_fer1']=(np.exp(results_ok['lnfer_need'])-np.exp(results_ok['lnfer']))
condition = (results_ok['gap_fer'] > results_ok['gap_fer1']) & (results_ok['gap_irrigation'] > 0)
# Assign values to 'gap_fer' based on the condition
results_ok['gap_fer'] = np.where(condition, results_ok['gap_fer1'], results_ok['gap_fer'])
results_ok['gap_irrigation'] = np.where(condition, 0, results_ok['gap_irrigation'])
results_ok['y_temp'] = np.where(condition, results_ok['y_temp_base2015'], results_ok['y_temp'])
results_ok['lnfer_values'] = np.where(condition, results_ok['lnfer_need'], results_ok['lnfer_values'])
print(np.min(results_ok['mana_group']),np.max(results_ok['mana_group']),
      np.mean(results_ok['mana_group']),np.sum(np.isnan(results_ok['mana_group'])))
results_ok['mana_group'] = np.where(condition, 1, results_ok['mana_group'])
print(np.min(results_ok['mana_group']),np.max(results_ok['mana_group']),
      np.mean(results_ok['mana_group']),np.sum(np.isnan(results_ok['mana_group'])))
print(results_ok)
1 3 1.3913913913913913 0
1 3 1.354854854854855 0
      geoid  scenario        tmp       pre     lnfer  irrigation1  \
0     39017       3.0  22.760628  5.757780  2.038479     0.001818   
1     13043       3.0  27.027358  6.635976  2.035268     0.126456   
2     37177       3.0  25.319158  7.937325  1.236794     0.000507   
3     17065       3.0  24.492824  5.942823  0.295453     0.000797   
4     17067       1.5  21.297634  6.267068 -0.046396     0.001389   
...     ...       ...        ...       ...       ...          ...   
1993   1043       3.0  25.723312  6.718675  4.369129     0.149384   
1994   1075       3.0  26.457528  6.493699  2.301965     0.027715   
1995   1085       3.0  27.248052  6.264505  3.149844     0.318468   
1996   1087       3.0  26.679214  6.355030  4.096728     0.210819   
1997   1091       3.0  27.222396  6.256731  2.847938     0.009984   

      y_temp_base_t  y_temp_base2015  lnyield_obs         har  ...  \
0          7.958094         7.979504     7.994525  14757.7400  ...   
1          7.561807         7.761395     7.499042   1336.5000  ...   
2          7.738559         7.905103     7.918210  12818.7600  ...   
3          7.610054         7.711970     7.946740  37450.0400  ...   
4          7.748190         7.763110     8.213926  58447.8900  ...   
...             ...              ...          ...         ...  ...   
1993       8.054614         8.278050     7.978103   2906.2460  ...   
1994       7.681917         7.966898     7.625159    564.0975  ...   
1995       7.639415         7.910322     7.784370   1699.6330  ...   
1996       7.862778         8.090918     7.847030    598.4888  ...   
1997       7.623575         7.908306     7.563227   1578.0490  ...   

      lnfer_values  gap_irrigation     gap_fer  mana_group    y_temp  \
0         2.194328       -0.001794    1.295049           1  7.979504   
1         3.458172       -0.126432   24.104553           1  7.761395   
2         2.451664       -0.000484    8.163098           1  7.905103   
3         1.039221       -0.000773    1.483279           1  7.711970   
4         0.063104       -0.001366    0.110474           1  7.763110   
...            ...             ...         ...         ...       ...   
1993      6.095648        0.000000  364.946897           3  8.278050   
1994      4.401289        0.000000   71.562105           3  7.966898   
1995      5.336927        0.000000  184.540509           3  7.910322   
1996      5.883013        0.000000  298.745838           3  8.090918   
1997      4.931680        0.000000  121.360035           3  7.908306   

      lnfer_need  irri_need  irri_need_1  y_temp_irri    gap_fer1  
0       2.194755   0.837454     0.837454     7.938183    1.298881  
1       3.559168   0.837454     0.837454     7.540154   27.479654  
2       2.452045   0.837454     0.837454     7.721508    8.167518  
3       1.039118        NaN     0.837454     7.647000    1.482988  
4       0.062503   0.235000     0.235000     7.763084    0.109834  
...          ...        ...          ...          ...         ...  
1993    6.095648   0.837454     0.837454     7.957525  364.946897  
1994    4.401289   0.837454     0.837454     7.649035   71.562105  
1995    5.336927   0.837454     0.837454     7.608856  184.540509  
1996    5.883013   0.837454     0.837454     7.798237  298.745838  
1997    4.931680   0.837454     0.837454     7.580939  121.360035  

[1998 rows x 25 columns]
In [27]:
# Extract the corresponding lnfer_value and irrigation1_value
output_df = results_ok[['tmp', 'pre', 'lnfer','irrigation1', 'y_temp','mana_group',
                           'geoid','scenario', 'lnyield_obs','scenario', 'har','gap_fer','gap_irrigation','lnfer_need',
                           'lnfer_values','irri_need','y_temp_base2015','y_temp_base_t','irri_need_1','y_temp_irri']]

# Rename the columns to match your desired output
output_df.columns = [ 'tmp', 'pre', 'lnfer','irrigation1', 'y_temp','mana_group',
                           'geoid','scenario', 'lnyield_obs','scenario', 'har','gap_fer','gap_irrigation','lnfer_need',
                           'lnfer_values','irri_need','y_temp_base2015','y_temp_base_t','irri_need_1','y_temp_irri']

# Define the output CSV file path
output_csv_file = "off_soybean_mana_lnfer_irri.csv"

# Save the 'output_df' DataFrame to a CSV file
output_df.to_csv(output_csv_file, index=False)

print(f"Data saved to '{output_csv_file}'")
Data saved to 'off_soybean_mana_lnfer_irri.csv'

spartial figures¶

In [28]:
data = results_irri[results_irri['scenario'] == 1.5]

# Calculate the mean of 'gap_production' within each unique combination of 'scenario' and 'geoid'
data['gap_irrigation']=(data['irri_need'])-(data['irrigation1'])
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))

data.loc[pd.isna(data['gap_irrigation']), 'gap_irrigation'] = 9999
count_missing_values = (data['gap_irrigation'] == 9999).sum()
print(f"Count of values equal to 9999: {count_missing_values}")
print(data)
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))
print(np.percentile(data['gap_irrigation'], 5),np.percentile(data['gap_irrigation'], 95))

data.loc[(data['gap_irrigation'] > 2.65)&(data['gap_irrigation'] != 9999), 
         'gap_irrigation'] = 2.65
data.loc[(data['gap_irrigation'] < -2.65)&(data['gap_irrigation'] != 9999),
         'gap_irrigation'] = -2.65

data['geoid'] = data['geoid'].astype(float)

# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in the 'data' DataFrame
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)

# Merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

# Plot the county boundaries
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey

# Create a ScalarMappable without plotting the data
cmap = mcolors.ListedColormap(['white'] + list(plt.cm.BrBG_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-2.7, vmax=2.7)
sc = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
sc.set_array([])
# Add colorbar
custom_ticks = [-2.6, -1.3, 0, 1.3, 2.6]

cbar = plt.colorbar(sc, ax=ax, label='Irrigation\n($10^{3}$ m$^{3}$/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)
cbar.ax.set_ylabel('Irrigation ($10^{3}$ m$^{3}$/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

# Plot the mean_gap_irrigation values
filtered_data.plot(column='gap_irrigation', cmap=cmap, ax=ax, norm=norm)

# Highlight counties with red 'x' (without filled color)
highlighted_county = filtered_data[filtered_data['gap_irrigation'] == 9999]
highlighted_county_centroids = highlighted_county.geometry.centroid
ax.scatter(highlighted_county_centroids.x, highlighted_county_centroids.y, 
           marker='x', color='red', s=15, label='Irrigation cannot offset yield loss')  # Adjust the marker size

# Add custom legend for highlighted county
legend_line = mlines.Line2D([], [], color='red', marker='x', linestyle='None',
                            markersize=10, markeredgewidth=3, label='Irrigation cannot offset yield loss')
# Set font properties for the legend
font_prop = FontProperties(family='Arial', size=16)
font_prop.set_weight('bold')
# Add legend with font family

# Additional plot configurations
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.25, '(c) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')

# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_irri_15.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
-3.25661719 0.8374538099999997 0.6173081431683627
Count of values equal to 9999: 183
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
0     25.099590  6.254395  2.457656     0.377088         7.871762   
2     26.261318  9.274925  1.292553     0.738441         7.599898   
4     25.408514  6.727813  2.114730     0.028216         7.821125   
6     23.976584  6.790346  4.361742     0.056342         8.285447   
8     25.246212  6.448847  4.858469     0.030586         8.201724   
...         ...       ...       ...          ...              ...   
1987  23.054028  6.988594  1.451035     0.047134         7.975989   
1989  22.726178  6.559806  1.287505     0.055504         7.938844   
1991  23.445478  7.457666  1.553341     0.022453         7.970973   
1993  23.349492  7.419639  1.187985     0.008524         7.928655   
1995  23.207888  7.236578  2.482080     0.010662         8.111622   

      y_temp_base_t  geoid  scenario  lnyield_obs        har  irri_need  \
0          7.846458   1001       1.5     7.509678    779.625   0.837454   
2          7.590898   1003       1.5     7.927428   6358.433   0.507000   
4          7.807509   1005       1.5     8.161582    526.500   0.837454   
6          8.252038   1009       1.5     7.840701   1107.736   0.837454   
8          8.183765   1011       1.5     7.984614    870.750   0.837454   
...             ...    ...       ...          ...        ...        ...   
1987       7.933484  51183       1.5     7.653934  10258.070   0.837454   
1989       7.908054  51193       1.5     7.805104   7122.953        NaN   
1991       7.940719  51550       1.5     7.885281   9798.216   0.837454   
1993       7.896463  51800       1.5     7.798817   7968.552   0.837454   
1995       8.075677  51810       1.5     7.872881   4972.955   0.837454   

      irri_need_1  y_temp_irri  gap_irrigation  
0        0.837454     7.826731        0.460366  
2        0.738441     7.590898       -0.231441  
4        0.837454     7.773008        0.809238  
6        0.837454     8.127237        0.781112  
8        0.837454     8.059327        0.806867  
...           ...          ...             ...  
1987     0.837454     7.915894        0.790320  
1989     0.837454     7.902166     9999.000000  
1991     0.837454     7.911710        0.815001  
1993     0.837454     7.884957        0.828930  
1995     0.837454     8.005891        0.826792  

[852 rows x 14 columns]
-3.25661719 9999.0 2148.157252520868
-0.11556065 9999.0
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/562872921.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['gap_irrigation']=(data['irri_need'])-(data['irrigation1'])
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/562872921.py:19: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['geoid'] = data['geoid'].astype(float)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/562872921.py:29: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data.rename(columns={'geoid': 'GEOID'}, inplace=True)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/562872921.py:32: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['GEOID'] = data['GEOID'].astype(float)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/562872921.py:66: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  highlighted_county_centroids = highlighted_county.geometry.centroid
In [29]:
data = results_irri[results_irri['scenario'] == 3]

# Calculate the mean of 'gap_production' within each unique combination of 'scenario' and 'geoid'
data['gap_irrigation']=(data['irri_need'])-(data['irrigation1'])
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))

data.loc[pd.isna(data['gap_irrigation']), 'gap_irrigation'] = 9999
count_missing_values = (data['gap_irrigation'] == 9999).sum()
print(f"Count of values equal to 9999: {count_missing_values}")
print(data)
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))
print(np.percentile(data['gap_irrigation'], 5),np.percentile(data['gap_irrigation'], 95))

data.loc[(data['gap_irrigation'] > 2.65)&(data['gap_irrigation'] != 9999), 
         'gap_irrigation'] = 2.65
data.loc[(data['gap_irrigation'] < -2.65)&(data['gap_irrigation'] != 9999),
         'gap_irrigation'] = -2.65

data['geoid'] = data['geoid'].astype(float)

# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in the 'data' DataFrame
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)

# Merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

# Plot the county boundaries
fig, ax = plt.subplots(figsize=(10, 4))

shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey

# Create a ScalarMappable without plotting the data
cmap = mcolors.ListedColormap(['white'] + list(plt.cm.BrBG_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-2.7, vmax=2.7)
sc = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
sc.set_array([])
# Add colorbar
custom_ticks = [-2.6, -1.3, 0, 1.3, 2.6]

cbar = plt.colorbar(sc, ax=ax, label='Irrigation\n($10^{3}$ m$^{3}$/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)
cbar.ax.set_ylabel('Irrigation ($10^{3}$ m$^{3}$/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

# Plot the mean_gap_irrigation values
filtered_data.plot(column='gap_irrigation', cmap=cmap, ax=ax, norm=norm)

# Highlight counties with red 'x' (without filled color)
highlighted_county = filtered_data[filtered_data['gap_irrigation'] == 9999]
highlighted_county_centroids = highlighted_county.geometry.centroid
ax.scatter(highlighted_county_centroids.x, highlighted_county_centroids.y, 
           marker='x', color='red', s=15, label='Irrigation cannot offset yield loss')  # Adjust the marker size

# Add custom legend for highlighted county
legend_line = mlines.Line2D([], [], color='red', marker='x', linestyle='None',
                            markersize=10, markeredgewidth=3, label='Irrigation cannot offset yield loss')
# Set font properties for the legend
font_prop = FontProperties(family='Arial', size=16)
font_prop.set_weight('bold')

# Additional plot configurations
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.25, '(d) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')

# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_irri_3.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3272060730.py:4: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['gap_irrigation']=(data['irri_need'])-(data['irrigation1'])
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3272060730.py:19: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['geoid'] = data['geoid'].astype(float)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3272060730.py:29: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data.rename(columns={'geoid': 'GEOID'}, inplace=True)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3272060730.py:32: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['GEOID'] = data['GEOID'].astype(float)
-3.25661719 0.8374538099999997 0.7062786188093132
Count of values equal to 9999: 313
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
1     26.784940  6.208599  2.457656     0.377088         7.871762   
3     27.808318  8.926058  1.292553     0.738441         7.599898   
5     27.067738  6.742623  2.114730     0.028216         7.821125   
7     25.706190  6.658286  4.361742     0.056342         8.285447   
9     26.923034  6.491163  4.858469     0.030586         8.201724   
...         ...       ...       ...          ...              ...   
1990  24.587320  6.583579  1.287505     0.055504         7.938844   
1992  25.147098  7.570098  1.553341     0.022453         7.970973   
1994  25.061998  7.586472  1.187985     0.008524         7.928655   
1996  24.859328  7.207139  2.482080     0.010662         8.111622   
1997  23.294406  5.721528  0.935788     0.000171         7.820683   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  irri_need  \
1          7.622792   1001       3.0     7.509678   779.625   0.837454   
3          7.351790   1003       3.0     7.927428  6358.433   0.837454   
5          7.574791   1005       3.0     8.161582   526.500   0.837454   
7          8.067909   1009       3.0     7.840701  1107.736   0.837454   
9          7.957275   1011       3.0     7.984614   870.750   0.837454   
...             ...    ...       ...          ...       ...        ...   
1990       7.776233  51193       3.0     7.805104  7122.953        NaN   
1992       7.792875  51550       3.0     7.885281  9798.216   0.837454   
1994       7.753334  51800       3.0     7.798817  7968.552   0.837454   
1996       7.939772  51810       3.0     7.872881  4972.955   0.837454   
1997       7.775021  54037       3.0     7.900531  3976.619        NaN   

      irri_need_1  y_temp_irri  gap_irrigation  
1        0.837454     7.606994        0.460366  
3        0.837454     7.348977        0.099012  
5        0.837454     7.544787        0.809238  
7        0.837454     7.958548        0.781112  
9        0.837454     7.841922        0.806867  
...           ...          ...             ...  
1990     0.837454     7.773208     9999.000000  
1992     0.837454     7.765774        0.815001  
1994     0.837454     7.742675        0.828930  
1996     0.837454     7.876415        0.826792  
1997     0.837454     7.792047     9999.000000  

[1146 rows x 14 columns]
-3.25661719 9999.0 2731.4793456278085
0.20102022749999993 9999.0
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3272060730.py:67: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.

  highlighted_county_centroids = highlighted_county.geometry.centroid
In [30]:
excel_file = "off_soybean_mana_lnfer_irri.csv"
data = pd.read_csv(excel_file)
data = data[data['scenario'] == 1.5]

print(data)
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))
print(np.percentile(data['gap_irrigation'], 5),np.percentile(data['gap_irrigation'], 95))


data.loc[data['gap_irrigation'] > 2.65, 'gap_irrigation'] = 2.65
data.loc[data['gap_irrigation'] < -2.65, 'gap_irrigation'] = -2.65

data['geoid'] = data['geoid'].astype(float)


# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.BrBG_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-2.7, vmax=2.7)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey

sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-2.6, -1.3, 0, 1.3, 2.6]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='Irrigation\n($10^{3}$ m$^{3}$/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('Irrigation ($10^{3}$ m$^{3}$/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_irrigation', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(g) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')

# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_mana_irri_15.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
            tmp       pre     lnfer  irrigation1    y_temp  mana_group  geoid  \
4     21.297634  6.267068 -0.046396     0.001389  7.763110           1  17067   
6     23.368236  7.039531  2.480696     0.042775  8.064906           1  37045   
8     20.636286  5.911292  1.265328     0.007367  7.910679           1  17075   
11    24.389220  8.362195  1.247938     0.009316  7.846596           1  37031   
13    21.414218  5.922644  0.748695     0.001327  7.844605           1  17107   
...         ...       ...       ...          ...       ...         ...    ...   
1979  23.881700  6.681210  6.281323     0.091063  8.549590           3   1059   
1981  25.374776  6.487229  6.026028     0.058274  8.366090           3   1063   
1983  25.375840  6.385456  6.055595     0.081476  8.357682           3   1065   
1988  23.976584  6.790346  4.361742     0.056342  8.285447           3   1009   
1992  23.975426  6.860577  4.369129     0.149384  8.278050           3   1043   

      scenario  lnyield_obs  scenario.1         har     gap_fer  \
4          1.5     8.213926         1.5   58447.890    0.110474   
6          1.5     7.648014         1.5    5522.715    0.515904   
8          1.5     8.143628         1.5  108519.700    0.176216   
11         1.5     7.732798         1.5    8839.125    0.143718   
13         1.5     8.279940         1.5   53825.450    0.184053   
...        ...          ...         ...         ...         ...   
1979       1.5     7.841934         1.5    1782.427  230.462736   
1981       1.5     7.382296         1.5     931.500  157.742963   
1983       1.5     7.649490         1.5    1608.660  156.285995   
1988       1.5     7.840701         1.5    1107.736   22.209510   
1992       1.5     7.978103         1.5    2906.246   27.753527   

      gap_irrigation  lnfer_need  lnfer_values  irri_need  y_temp_base2015  \
4          -0.001366    0.062503      0.063104   0.235000         7.763110   
6          -0.042751    2.551202      2.522963   0.837454         8.064906   
8          -0.007344    1.313912      1.313850        NaN         7.910679   
11         -0.009292    1.290816      1.288370   0.837454         7.846596   
13         -0.001303    0.831943      0.832166   0.455000         7.844605   
...              ...         ...           ...        ...              ...   
1979        0.000000    6.639821      6.639821   0.837454         8.549590   
1981        0.000000    6.348807      6.348807   0.837454         8.366090   
1983        0.000000    6.367807      6.367807   0.837454         8.357682   
1988        0.000000    4.611183      4.611183   0.837454         8.285447   
1992        0.000000    4.670287      4.670287   0.837454         8.278050   

      y_temp_base_t  irri_need_1  y_temp_irri  
4          7.748190     0.235000     7.763084  
6          8.055423     0.837454     7.993940  
8          7.904037     0.837454     7.903477  
11         7.840749     0.837454     7.816472  
13         7.833198     0.455000     7.844601  
...             ...          ...          ...  
1979       8.502215     0.837454     8.318906  
1981       8.322773     0.837454     8.162960  
1983       8.316101     0.837454     8.166404  
1988       8.252038     0.837454     8.127237  
1992       8.239287     0.837454     8.128134  

[852 rows x 20 columns]
-4.09404712 0.8369975599999999 -0.109864623684242
-0.7312366549999999 0.0
In [31]:
excel_file = "off_soybean_mana_lnfer_irri.csv"
data = pd.read_csv(excel_file)
data = data[data['scenario'] == 3]
print(data)
print(np.min(data['gap_irrigation']),np.max(data['gap_irrigation']),np.mean(data['gap_irrigation']))
print(np.percentile(data['gap_irrigation'], 5),np.percentile(data['gap_irrigation'], 95))


data.loc[data['gap_irrigation'] > 2.65, 'gap_irrigation'] = 2.65
data.loc[data['gap_irrigation'] < -2.65, 'gap_irrigation'] = -2.65

data['geoid'] = data['geoid'].astype(float)


# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.BrBG_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-2.7, vmax=2.7)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey
sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-2.6, -1.3, 0, 1.3, 2.6]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='Irrigation\n($10^{3}$ m$^{3}$/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('Irrigation ($10^{3}$ m$^{3}$/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_irrigation', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(h) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')

# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_mana_irri_3.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
            tmp       pre     lnfer  irrigation1    y_temp  mana_group  geoid  \
0     22.760628  5.757780  2.038479     0.001818  7.979504           1  39017   
1     27.027358  6.635976  2.035268     0.126456  7.761395           1  13043   
2     25.319158  7.937325  1.236794     0.000507  7.905103           1  37177   
3     24.492824  5.942823  0.295453     0.000797  7.711970           1  17065   
5     25.244316  6.669287  2.480696     0.042775  8.064906           1  37045   
...         ...       ...       ...          ...       ...         ...    ...   
1993  25.723312  6.718675  4.369129     0.149384  8.278050           3   1043   
1994  26.457528  6.493699  2.301965     0.027715  7.966898           3   1075   
1995  27.248052  6.264505  3.149844     0.318468  7.910322           3   1085   
1996  26.679214  6.355030  4.096728     0.210819  8.090918           3   1087   
1997  27.222396  6.256731  2.847938     0.009984  7.908306           3   1091   

      scenario  lnyield_obs  scenario.1         har     gap_fer  \
0          3.0     7.994525         3.0  14757.7400    1.295049   
1          3.0     7.499042         3.0   1336.5000   24.104553   
2          3.0     7.918210         3.0  12818.7600    8.163098   
3          3.0     7.946740         3.0  37450.0400    1.483279   
5          3.0     7.648014         3.0   5522.7150   35.724095   
...        ...          ...         ...         ...         ...   
1993       3.0     7.978103         3.0   2906.2460  364.946897   
1994       3.0     7.625159         3.0    564.0975   71.562105   
1995       3.0     7.784370         3.0   1699.6330  184.540509   
1996       3.0     7.847030         3.0    598.4888  298.745838   
1997       3.0     7.563227         3.0   1578.0490  121.360035   

      gap_irrigation  lnfer_need  lnfer_values  irri_need  y_temp_base2015  \
0          -0.001794    2.194755      2.194328   0.837454         7.979504   
1          -0.126432    3.559168      3.458172   0.837454         7.761395   
2          -0.000484    2.452045      2.451664   0.837454         7.905103   
3          -0.000773    1.039118      1.039221        NaN         7.711970   
5          -0.042751    3.908331      3.864379   0.837454         8.064906   
...              ...         ...           ...        ...              ...   
1993        0.000000    6.095648      6.095648   0.837454         8.278050   
1994        0.000000    4.401289      4.401289   0.837454         7.966898   
1995        0.000000    5.336927      5.336927   0.837454         7.910322   
1996        0.000000    5.883013      5.883013   0.837454         8.090918   
1997        0.000000    4.931680      4.931680   0.837454         7.908306   

      y_temp_base_t  irri_need_1  y_temp_irri  
0          7.958094     0.837454     7.938183  
1          7.561807     0.837454     7.540154  
2          7.738559     0.837454     7.721508  
3          7.610054     0.837454     7.647000  
5          7.872395     0.837454     7.826035  
...             ...          ...          ...  
1993       8.054614     0.837454     7.957525  
1994       7.681917     0.837454     7.649035  
1995       7.639415     0.837454     7.608856  
1996       7.862778     0.837454     7.798237  
1997       7.623575     0.837454     7.580939  

[1146 rows x 20 columns]
-4.09404712 0.8356570999999999 -0.10222283480325053
-0.682878195 0.0
In [32]:
# Filter rows where 'scenario' is equal to 1.5
data = results_lnfer[results_lnfer['scenario'] == 1.5]

# Calculate the mean of 'gap_production' within each unique combination of 'scenario' and 'geoid'
data['gap_fer']=(np.exp(data['lnfer_need'])-np.exp(data['lnfer']))/1000

print(data)
print(np.min(data['gap_fer']),np.max(data['gap_fer']),np.mean(data['gap_fer']))
print(np.percentile(data['gap_fer'], 5),np.percentile(data['gap_fer'], 95))


data.loc[data['gap_fer'] > 0.21, 'gap_fer'] = 0.21
data.loc[data['gap_fer'] < -0.21, 'gap_fer'] = -0.21

data['geoid'] = data['geoid'].astype(float)


# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.seismic_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-0.22, vmax=0.22)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey
sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-0.2, -0.1,  0, 0.1, 0.2]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='N input (tonnes/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('N input (tonne/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_fer', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(c) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')


# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_fer_15.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3578493828.py:5: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['gap_fer']=(np.exp(data['lnfer_need'])-np.exp(data['lnfer']))/1000
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3578493828.py:15: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['geoid'] = data['geoid'].astype(float)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3578493828.py:26: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data.rename(columns={'geoid': 'GEOID'}, inplace=True)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/3578493828.py:29: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['GEOID'] = data['GEOID'].astype(float)
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
0     25.099590  6.254395  2.457656     0.377088         7.871762   
2     26.261318  9.274925  1.292553     0.738441         7.599898   
4     25.408514  6.727813  2.114730     0.028216         7.821125   
6     23.976584  6.790346  4.361742     0.056342         8.285447   
8     25.246212  6.448847  4.858469     0.030586         8.201724   
...         ...       ...       ...          ...              ...   
1989  27.663632  6.442080  2.015563     0.000000         7.863435   
1991  22.704868  6.240907  3.982144     0.000000         8.503382   
1993  22.617856  6.753251  3.697080     0.000000         8.499517   
1995  20.956338  7.018248  3.798184     0.000000         8.457635   
1996  22.735782  6.657891  1.348576     0.000000         8.031712   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  lnfer_need  \
0          7.846458   1001       1.5     7.509678   779.625    2.667937   
2          7.590898   1003       1.5     7.927428  6358.433    1.404700   
4          7.807509   1005       1.5     8.161582   526.500    2.215152   
6          8.252038   1009       1.5     7.840701  1107.736    4.611183   
8          8.183765   1011       1.5     7.984614   870.750    4.990935   
...             ...    ...       ...          ...       ...         ...   
1989       7.794389  48481       1.5     7.793029  4401.709    2.355986   
1991       8.485417  51049       1.5     7.653916   753.030    4.078495   
1993       8.465001  51103       1.5     8.077533  2916.000    3.877447   
1995       8.455265  51141       1.5     7.902284   243.000    3.812177   
1996       8.009433  51159       1.5     7.841456  5668.211    1.464794   

       gap_fer  
0     0.002733  
2     0.000432  
4     0.000875  
6     0.022210  
8     0.018247  
...        ...  
1989  0.003044  
1991  0.005425  
1993  0.007971  
1995  0.000629  
1996  0.000475  

[852 rows x 12 columns]
1.6115767952669113e-06 0.5174582728124076 0.009025892207889354
8.720033687829001e-05 0.0372150808838462
In [33]:
# Filter rows where 'scenario' is equal to 3.0
data = results_lnfer[results_lnfer['scenario'] == 3]

# Calculate the mean of 'gap_production' within each unique combination of 'scenario' and 'geoid'
data['gap_fer']=(np.exp(data['lnfer_need'])-np.exp(data['lnfer']))/1000

print(data)
print(np.min(data['gap_fer']),np.max(data['gap_fer']),np.mean(data['gap_fer']))
print(np.percentile(data['gap_fer'], 5),np.percentile(data['gap_fer'], 95))

data.loc[data['gap_fer'] > 0.21, 'gap_fer'] = 0.21
data.loc[data['gap_fer'] < -0.21, 'gap_fer'] = -0.21

data['geoid'] = data['geoid'].astype(float)

# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.seismic_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-0.22, vmax=0.22)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey
sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-0.2, -0.1,  0, 0.1, 0.2]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='N input (tonnes/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('N input (tonne/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_fer', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(d) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')


# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_fer_3.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1754602407.py:5: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['gap_fer']=(np.exp(data['lnfer_need'])-np.exp(data['lnfer']))/1000
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1754602407.py:14: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['geoid'] = data['geoid'].astype(float)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1754602407.py:24: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data.rename(columns={'geoid': 'GEOID'}, inplace=True)
/var/folders/vd/0_phd7hx2n51y4412862zww00000gp/T/ipykernel_2258/1754602407.py:27: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  data['GEOID'] = data['GEOID'].astype(float)
            tmp       pre     lnfer  irrigation1  y_temp_base2015  \
1     26.784940  6.208599  2.457656     0.377088         7.871762   
3     27.808318  8.926058  1.292553     0.738441         7.599898   
5     27.067738  6.742623  2.114730     0.028216         7.821125   
7     25.706190  6.658286  4.361742     0.056342         8.285447   
9     26.923034  6.491163  4.858469     0.030586         8.201724   
...         ...       ...       ...          ...              ...   
1988  29.057906  5.624428  0.287418     0.000000         7.483895   
1990  29.078382  6.321736  2.015563     0.000000         7.863435   
1992  24.578756  6.202993  3.982144     0.000000         8.503382   
1994  24.369986  6.937165  3.697080     0.000000         8.499517   
1997  24.547064  6.747815  1.348576     0.000000         8.031712   

      y_temp_base_t  geoid  scenario  lnyield_obs       har  lnfer_need  \
1          7.622792   1001       3.0     7.509678   779.625    4.505245   
3          7.351790   1003       3.0     7.927428  6358.433    4.202620   
5          7.574791   1005       3.0     8.161582   526.500    3.930603   
7          8.067909   1009       3.0     7.840701  1107.736    5.982833   
9          7.957275   1011       3.0     7.984614   870.750    6.660717   
...             ...    ...       ...          ...       ...         ...   
1988       7.255714  48469       3.0     7.699628  2669.529    1.551669   
1990       7.604456  48481       3.0     7.793029  4401.709    3.383518   
1992       8.443910  51049       3.0     7.653916   753.030    4.277212   
1994       8.441412  51103       3.0     8.077533  2916.000    3.975355   
1997       7.935400  51159       3.0     7.841456  5668.211    1.812194   

       gap_fer  
1     0.078813  
3     0.063219  
5     0.042650  
7     0.318169  
9     0.652284  
...        ...  
1988  0.003386  
1990  0.021969  
1992  0.018407  
1994  0.012940  
1997  0.002272  

[1146 rows x 12 columns]
2.8660999604701586e-06 4.302983035950181 0.08318529908593147
0.00042777415800521743 0.36307561938201366
In [34]:
# Filter rows where 'scenario' is equal to 1.5
excel_file = "off_soybean_mana_lnfer_irri.csv"
data = pd.read_csv(excel_file)
data = data[data['scenario'] == 1.5]

data['gap_fer']=data['gap_fer']/1000

print(data)
print(np.min(data['gap_fer']),np.max(data['gap_fer']),np.mean(data['gap_fer']))
print(np.percentile(data['gap_fer'], 5),np.percentile(data['gap_fer'], 95))

data.loc[data['gap_fer'] > 0.21, 'gap_fer'] = 0.21
data.loc[data['gap_fer'] < -0.21, 'gap_fer'] = -0.21

data['geoid'] = data['geoid'].astype(float)


# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.seismic_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-0.22, vmax=0.22)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey
sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-0.2, -0.1,  0, 0.1, 0.2]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='N input (tonnes/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('N input (tonne/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_fer', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(g) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')


# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_mana_fer_15.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
            tmp       pre     lnfer  irrigation1    y_temp  mana_group  geoid  \
4     21.297634  6.267068 -0.046396     0.001389  7.763110           1  17067   
6     23.368236  7.039531  2.480696     0.042775  8.064906           1  37045   
8     20.636286  5.911292  1.265328     0.007367  7.910679           1  17075   
11    24.389220  8.362195  1.247938     0.009316  7.846596           1  37031   
13    21.414218  5.922644  0.748695     0.001327  7.844605           1  17107   
...         ...       ...       ...          ...       ...         ...    ...   
1979  23.881700  6.681210  6.281323     0.091063  8.549590           3   1059   
1981  25.374776  6.487229  6.026028     0.058274  8.366090           3   1063   
1983  25.375840  6.385456  6.055595     0.081476  8.357682           3   1065   
1988  23.976584  6.790346  4.361742     0.056342  8.285447           3   1009   
1992  23.975426  6.860577  4.369129     0.149384  8.278050           3   1043   

      scenario  lnyield_obs  scenario.1         har   gap_fer  gap_irrigation  \
4          1.5     8.213926         1.5   58447.890  0.000110       -0.001366   
6          1.5     7.648014         1.5    5522.715  0.000516       -0.042751   
8          1.5     8.143628         1.5  108519.700  0.000176       -0.007344   
11         1.5     7.732798         1.5    8839.125  0.000144       -0.009292   
13         1.5     8.279940         1.5   53825.450  0.000184       -0.001303   
...        ...          ...         ...         ...       ...             ...   
1979       1.5     7.841934         1.5    1782.427  0.230463        0.000000   
1981       1.5     7.382296         1.5     931.500  0.157743        0.000000   
1983       1.5     7.649490         1.5    1608.660  0.156286        0.000000   
1988       1.5     7.840701         1.5    1107.736  0.022210        0.000000   
1992       1.5     7.978103         1.5    2906.246  0.027754        0.000000   

      lnfer_need  lnfer_values  irri_need  y_temp_base2015  y_temp_base_t  \
4       0.062503      0.063104   0.235000         7.763110       7.748190   
6       2.551202      2.522963   0.837454         8.064906       8.055423   
8       1.313912      1.313850        NaN         7.910679       7.904037   
11      1.290816      1.288370   0.837454         7.846596       7.840749   
13      0.831943      0.832166   0.455000         7.844605       7.833198   
...          ...           ...        ...              ...            ...   
1979    6.639821      6.639821   0.837454         8.549590       8.502215   
1981    6.348807      6.348807   0.837454         8.366090       8.322773   
1983    6.367807      6.367807   0.837454         8.357682       8.316101   
1988    4.611183      4.611183   0.837454         8.285447       8.252038   
1992    4.670287      4.670287   0.837454         8.278050       8.239287   

      irri_need_1  y_temp_irri  
4        0.235000     7.763084  
6        0.837454     7.993940  
8        0.837454     7.903477  
11       0.837454     7.816472  
13       0.455000     7.844601  
...           ...          ...  
1979     0.837454     8.318906  
1981     0.837454     8.162960  
1983     0.837454     8.166404  
1988     0.837454     8.127237  
1992     0.837454     8.128134  

[852 rows x 20 columns]
-0.2769264724031997 0.5174582728124076 0.006923248550680371
-0.000290229304400566 0.029732596439108423
In [35]:
# Filter rows where 'scenario' is equal to 3.0
excel_file = "off_soybean_mana_lnfer_irri.csv"
data = pd.read_csv(excel_file)
data = data[data['scenario'] == 3]

data['gap_fer']=data['gap_fer']/1000

print(np.min(data['gap_fer']),np.max(data['gap_fer']),np.mean(data['gap_fer']))
print(np.percentile(data['gap_fer'], 5),np.percentile(data['gap_fer'], 95))

data.loc[data['gap_fer'] > 0.21, 'gap_fer'] = 0.21
data.loc[data['gap_fer'] < -0.21, 'gap_fer'] = -0.21

data['geoid'] = data['geoid'].astype(float)


# Load US county boundaries shapefile using geopandas
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_county_20m/surface_shapefile.shp'
gdf_county = gpd.read_file(shapefile_path)

# Ensure 'GEOID' column in the shapefile has the 'object' data type
gdf_county['GEOID'] = gdf_county['GEOID'].astype(float)

# Rename the 'geoid' column to 'GEOID' in year_2020_data
data.rename(columns={'geoid': 'GEOID'}, inplace=True)

# Convert the 'GEOID' column in the 'data' DataFrame to 'object' data type
data['GEOID'] = data['GEOID'].astype(float)
# Now, merge 'data' with county boundaries based on 'GEOID' attribute
merged_data = gdf_county.merge(data, on='GEOID', how='left')

# Filter the data to include only geometries within the specified longitude and latitude range
filtered_data = merged_data.cx[-130:-60, 25:50]

cmap = mcolors.ListedColormap(['white'] + list(plt.cm.seismic_r(np.linspace(0, 1, 255))))
norm = mcolors.Normalize(vmin=-0.22, vmax=0.22)

# Plot both county boundaries and 'y_temp' values on the same map within the specified range
fig, ax = plt.subplots(figsize=(10, 4))
shapefile_path = '/Users/chenchenren/postdoc/paper/2N and water-US/Data/cb_2018_us_state_20m/cb_2018_us_state_20m.shp'
gdf_state = gpd.read_file(shapefile_path)
gdf_state.rename(columns={'GEOID': 'GEOID_state'}, inplace=True)
gdf_state = gdf_state.cx[-130:-60, 25:50]
gdf_state.boundary.plot(ax=ax, linewidth=0.3, color='grey')  # Plot county boundaries in grey
sc = plt.scatter([], [], c=[], cmap=cmap, norm=norm)  # Create an empty ScalarMappable for the colorbar

# Define custom colorbar ticks
custom_ticks = [-0.2, -0.1,  0, 0.1, 0.2]

# Adjust the height of the colorbar by setting the shrink parameter
cbar = plt.colorbar(sc, ax=ax, label='N input (tonnes/ha/yr)', orientation='vertical', pad=-0.02, shrink=0.8, ticks=custom_ticks)

# Set the font size of the colorbar label
# Set the colorbar label text, font size, and padding
cbar.ax.set_ylabel('N input (tonne/ha/yr)', fontsize=16, fontfamily='Arial')
cbar.ax.tick_params(labelsize=16)  # Adjust tick label fontsize
cbar.ax.set_yticklabels(custom_ticks, fontsize=16, fontfamily='Arial')

filtered_data.plot(column='gap_fer', cmap=cmap, ax=ax, norm=norm)

# Add labels, titles, or other plot configurations as needed
ax.set_xticks([])  # Remove x-axis ticks
ax.set_yticks([])  # Remove y-axis ticks
ax.set_frame_on(False)  # Turn off the frame
plt.text(0.25, 0.2, '(h) Soybean', transform=plt.gcf().transFigure,
         fontsize=18, fontweight='bold', fontfamily='Arial', ha='left', va='bottom')


# Save the entire figure as a JPG with DPI 300
plt.savefig('off_soybean_mana_fer_3.png', format='png', 
            dpi=300, bbox_inches='tight', pad_inches=0.1, transparent=True)

# Show the plot
plt.show()
-0.17814073595870636 4.302983035950181 0.07332297895275802
0.00039066123990304745 0.3054000611491717
In [ ]:
 
In [ ]:
 
In [ ]: