# -*- coding: utf-8 -*-
"""
Created on Mon May  1 16:33:31 2023

@author: Arka
"""
#clear all workspace variables
from IPython import get_ipython
get_ipython().magic('reset -sf')

import numpy as np

#input data path
#path=r'E:\tesseroid_data_creation\training_data_tesseroid\dj_training_data00070.txt'
path=r'C:\Users\Arka\Desktop\deep_learning2\training_data\dj_training_data00079.txt'
data= np.loadtxt(path)
min_x=np.amin(data[:,0]) 
max_x=np.amax(data[:,0]) 

min_y=np.amin(data[:,1]) 
max_y=np.amax(data[:,1]) 

density=data[0,2]
ref_depth=data[0,3]
gravity_anomaly=data[:,4]
gravity_anomaly=np.reshape(gravity_anomaly, [256,256])

vv=np.array([min_x, max_x, min_y, max_y, density, ref_depth])

depth=data[:,5]
depth=np.reshape(depth, [256,256])

#model_path=r"C:\Users\Arka\Desktop\deep_learning2\model_save\model_307200.h5"
model_path=r"C:\Users\Arka\Desktop\deep_learning2\model_save\model_288000.h5"
#model_path=r"C:\Users\Arka\Desktop\deep_learning2\model_save\model_264000.h5"
#model_path=r"C:\Users\Arka\Desktop\deep_learning2\model_save\model_240000.h5"
#model_path=r"C:\Users\Arka\Desktop\deep_learning2\model_save\model_192000.h5"

from depth_predict_function import depth_predict
XX,YY,final_depth=depth_predict(min_x,max_x,min_y,max_y, ref_depth, density, gravity_anomaly, model_path)

import matplotlib.pyplot as plt
fig, (ax1,ax2) = plt.subplots(1, 2)
# plots filled contour plot
ax1.contourf(XX, YY, np.transpose(final_depth)) 
ax1.set_title('predicted Moho')
ax1.set_xlabel('x')
ax1.set_ylabel('y')

ax2.contourf(XX, YY, np.transpose(depth)) 
ax2.set_title('True Mhoho')
ax2.set_xlabel('x')
ax2.set_ylabel('y')
  
plt.show()

np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\rho_rep3.txt', vv)
np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\grav_anomaly3.txt', np.transpose(gravity_anomaly))
np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\depth_predicted3.txt', np.transpose(final_depth))
np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\depth_true3.txt', np.transpose(depth))
np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\XX_predicted3.txt', XX)
np.savetxt(r'C:\Users\Arka\Desktop\deep_learning2\tested_data\YY_predicted3.txt', YY)


import matlab.engine
eng = matlab.engine.start_matlab()
eng.plot_data3(nargout=0)