#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sun May 7 14:21:04 2023 @author: jtitus@TAE.COM THIS CODE PLOTS THE DATA FROM 10.5281/zenodo.7464646 AND FROM THE PAPER: Estimates of the Wavenumber Wavelet Power Spectrum of Magnetic Fluctuations during Magnetic Reconnection """ import matplotlib.pyplot as plt import numpy as np # Plot individual figures from paper which_figure = 'all'# 1,2,3,4,5,6a,6b,6c,6d,7a,7b,7c, all data_and_figures = '/Users/jtitus/Desktop/James/Mag/05-05-23 Data and Figures/' #directory where files are located if which_figure == '1' or which_figure == 'all': wave_frequency = np.genfromtxt(data_and_figures+'Fig.1-wave_frequency.csv',delimiter=',') avg_wave_power = np.genfromtxt(data_and_figures+'Fig.1-wave_power.csv', delimiter=',') Fourier_frequency = np.genfromtxt(data_and_figures+'Fig.1-Fourier_frequency.csv', delimiter=',') Fourier_power = np.genfromtxt(data_and_figures+'Fig.1-Fourier_pwr.csv',delimiter=',') ave_wave_power = np.genfromtxt(data_and_figures+'Fig.1-ave_wave_power.csv', delimiter=',') ave_wave_power_frequency = np.genfromtxt(data_and_figures+'Fig.1-ave_wave_power_frequency.csv', delimiter=',') plt.figure(1) for vvv in range(2048): if vvv == 0: plt.plot(wave_frequency,avg_wave_power[:,vvv],'.', color= 'blue',alpha=.2,label='$H_{W}^{(0)(0)}(\chi,f,\\tau)$') else: plt.plot(wave_frequency,avg_wave_power[:,vvv],'.', color= 'blue',alpha=0.05) plt.plot(Fourier_frequency,Fourier_power,'*',color='red',label='$H^{(0)(0)}(\chi,f)$') plt.plot(ave_wave_power_frequency,ave_wave_power,'-',color='black', label='$$') plt.xlabel('$f$ [kHz]') plt.ylabel('PSD [log10 T$^{2}$/kHz]') plt.ylim(1e-24,1e-5) plt.yscale("log") plt.xscale("log") plt.legend() if which_figure == '2' or which_figure == 'all': wave_frequency = np.genfromtxt(data_and_figures+'Fig.2-'+'wave_frequency.csv',delimiter=',') wave_wavenumber = np.genfromtxt(data_and_figures+'Fig.2-'+'wave_wavenumber.csv', delimiter=',') Fourier_frequency = np.genfromtxt(data_and_figures+'Fig.2-'+'Fourier_frequency.csv', delimiter=',') Fourier_phase = np.genfromtxt(data_and_figures+'Fig.2-'+'Fourier_phase.csv', delimiter=',') ave_wave_wavenumber = np.genfromtxt(data_and_figures+'Fig.2-'+'ave_wave_wavenumber.csv', delimiter=',') plt.figure(2) for vvv in range(2000): if vvv == 0: plt.plot(wave_frequency, wave_wavenumber[:,vvv],'.', color='blue',alpha=0.2, label=r'$S_{W}^{(0)(0)}(k_{\perp},f,\tau)$') else: plt.plot(wave_frequency, wave_wavenumber[:,vvv],'.', color='blue',alpha=.05) plt.plot(Fourier_frequency, Fourier_phase,color='red',label=r'$S^{(0)(0)}(k_{\perp},f)$' ) plt.plot(wave_frequency, ave_wave_wavenumber,'-',color='black',label=r'$$') plt.xlabel('$f$ [kHz]') plt.ylabel('$k_{\perp}$ [cm$^{-1}$]') plt.legend(loc='upper left') plt.pause(0.1) if which_figure == '3' or which_figure == 'all': wave_wavenumber = np.genfromtxt(data_and_figures+'Fig.3-'+'wave_wavenumber.csv',delimiter=',') wave_power = np.genfromtxt(data_and_figures+'Fig.3-'+'wave_power.csv',delimiter=',') Fourier_wavenumber = np.genfromtxt(data_and_figures+'Fig.3-'+'Fourier_wavenumber.csv', delimiter=',') Fourier_power = np.genfromtxt(data_and_figures+'Fig.3-'+'Fourier_power.csv', delimiter=',') ave_wave_power = np.genfromtxt(data_and_figures+'Fig.3-'+'ave_wave_power.csv', delimiter=',') ave_wave_wavenumber = np.genfromtxt(data_and_figures+'Fig.3-'+'ave_wave_power_wavenumber.csv', delimiter=',') plt.figure(3) for vvv in range(2000): if vvv == 0: plt.plot( wave_wavenumber[:,vvv],wave_power[:,vvv],'.',color='blue', alpha=.2,label=r'$S_{W}^{(0)(0)}(k_{\perp},\tau)$') else: plt.plot(wave_wavenumber[:,vvv],wave_power[:,vvv],'.',color='blue', alpha=.05) plt.plot(Fourier_wavenumber,Fourier_power,'*',color='red',label=r'$S^{(0)(0)}(k_{\perp})$') plt.plot(ave_wave_wavenumber,ave_wave_power,'-',color='black',label=r'$$') plt.ylabel('PSD [T$^{2}$ cm]') plt.xlabel('$k_{\perp}$ [cm$^{-1}$]') plt.yscale("log") plt.legend(loc='upper left') plt.ylim(1e-23,1e-5) if which_figure == '4' or which_figure == 'all': Z = np.genfromtxt(data_and_figures+'Fig.4-'+'power.csv', delimiter=',') time = np.genfromtxt(data_and_figures+'Fig.4-'+'time.csv', delimiter=',') frequency = np.genfromtxt(data_and_figures+'Fig.4-'+'frequency.csv', delimiter=',') coi = np.genfromtxt(data_and_figures+'Fig.4-'+'coi.csv', delimiter=',') X,Y = np.meshgrid(time,frequency) plt.figure(4) plt.pcolor(X,Y,Z,cmap=plt.cm.jet) plt.colorbar() plt.plot(time, 1/coi, 'k') plt.yscale("log") plt.ylim(3e0,1e3) plt.clim(-15, -4.5) plt.xlabel('Time [ms]') plt.ylabel('Frequency [kHz]') if which_figure == '5' or which_figure == 'all': wavenumber = np.genfromtxt(data_and_figures+'Fig.5-'+'wavenumber.csv', delimiter=',') wave_power = np.genfromtxt(data_and_figures+'Fig.5-'+'wave_pwr.csv',delimiter=',') Fourier_power = np.genfromtxt(data_and_figures+'Fig.5-'+'Fourier_pwr.csv',delimiter=',') ave_wave_power = np.genfromtxt(data_and_figures+'Fig.5-'+'ave_wave_pwr.csv',delimiter=',') plt.figure(5) for vvv in range(2048): if vvv == 0: plt.plot(wavenumber,wave_power[:,vvv],'o', color='blue',alpha=.2,label = '$\hat{S}_{W}(k,\\tau)$') else: plt.plot(wavenumber,wave_power[:,vvv],'o', color='blue',alpha=0.5) plt.plot(wavenumber,Fourier_power,'*',color='red',label='$\hat{S}(k)$')# does not need events plt.plot(wavenumber,ave_wave_power,'*',color='black',label='$<\hat{S}_{W}(k,\\tau)>$')# plt.ylabel('PSD [T$^{2}$cm]') plt.xlabel('$k_{\perp}$ [cm$^{-1}$]') plt.yscale("log") plt.legend() if which_figure == '6a' or which_figure == 'all': Z = np.genfromtxt(data_and_figures+'Fig.6-'+'power.csv',delimiter=',') time = np.genfromtxt(data_and_figures+'Fig.6-'+'time.csv',delimiter=',') wavenumber = np.genfromtxt(data_and_figures+'Fig.6-'+'wavenumber.csv',delimiter=',') st=np.argmin(np.absolute(wavenumber+7.85)) et=np.argmin(np.absolute(wavenumber-7.85)) X,Y = np.meshgrid(time,wavenumber[st:et]) plt.figure(61) plt.pcolormesh(X,Y,Z,cmap=plt.cm.jet) cbar = plt.colorbar() CS = plt.contour(X,Y, Z, 20,colors='black', linewidths=0.1) cbar.set_label('Power (log10 T$^{2}$cm)') plt.xlabel('Time [ms]') plt.ylabel('k [cm$^{-1}$]') plt.xlim(-0.35,0.35) if which_figure == '6b' or which_figure == 'all': Z = np.genfromtxt(data_and_figures+'Fig.6-'+'power.csv',delimiter=',') time = np.genfromtxt(data_and_figures+'Fig.6-'+'time.csv',delimiter=',') wavewnumber = np.genfromtxt(data_and_figures+'Fig.6-'+'wavenumber.csv',delimiter=',') st=np.argmin(np.absolute(wavenumber+2.0)) et=np.argmin(np.absolute(wavenumber-2.0)) X,Y = np.meshgrid(time,wavenumber[st:et]) Z = Z[st:et,:] plt.figure(62) plt.pcolormesh(X,Y,Z,cmap=plt.cm.jet) cbar = plt.colorbar() CS = plt.contour(X,Y, Z, 20,colors='black', linewidths=0.1) cbar.set_label('Power (log10 T$^{2}$cm)') plt.xlabel('Time [ms]') plt.ylabel('k [cm$^{-1}$]') plt.xlim(-0.35,0.35) if which_figure == '6c' or which_figure == 'all': Z = np.genfromtxt(data_and_figures+'Fig.6-'+'power.csv',delimiter=',') time = np.genfromtxt(data_and_figures+'Fig.6-'+'time.csv',delimiter=',') wavenumber = np.genfromtxt(data_and_figures+'Fig.6-'+'wavenumber.csv',delimiter=',') st=np.argmin(np.absolute(wavenumber+0.5)) et=np.argmin(np.absolute(wavenumber-0.5)) X,Y = np.meshgrid(time,wavenumber[st:et]) Z = Z[st:et,:] plt.figure(63) plt.pcolormesh(X,Y,Z,cmap=plt.cm.jet) cbar = plt.colorbar() CS = plt.contour(X,Y, Z, 20,colors='black', linewidths=0.1) cbar.set_label('Power (log10 T$^{2}$cm)') plt.xlabel('Time [ms]') plt.ylabel('k [cm$^{-1}$]') plt.xlim(-0.35,0.35) if which_figure == '6d' or which_figure == 'all': time = np.genfromtxt(data_and_figures+'Fig.6d-'+'time.csv', delimiter=',') _m0 = np.genfromtxt(data_and_figures+'Fig.6d-'+'m0.csv', delimiter=',') _n6 = np.genfromtxt(data_and_figures+'Fig.6d-'+'n6.csv', delimiter=',') _n10 = np.genfromtxt(data_and_figures+'Fig.6d-'+'n10.csv', delimiter=',') plt.figure(64) plt.plot(time, _m0, color='black', label='$(m,n)=(0,1)$') plt.plot(time, _n6, color='orange',label='$(m,n)=(1,6)$') plt.plot(time, _n10, color='green',label='$(m,n)=(1,10)$') plt.xlim(-0.35,0.35) plt.xlabel('Time [ms]') plt.ylabel('mode amplitude (G)') plt.yscale("log") plt.legend() if which_figure == '7a' or which_figure == 'all': time = np.genfromtxt(data_and_figures+'Fig.7a-'+'time.csv',delimiter=',') kd = np.genfromtxt(data_and_figures+'Fig.7a-'+'kd.csv',delimiter=',') kd_unc = np.genfromtxt(data_and_figures+'Fig.7a-'+'kd_unc.csv', delimiter=',') plt.figure(71) plt.errorbar(time,kd,yerr=kd_unc,fmt='.',capsize=0.5,color='orange', alpha=.02) plt.plot(time,kd,'.',color ='green',markersize=10) plt.xlabel('Time [ms]') plt.ylabel('$k_{d}$') if which_figure == '7b' or which_figure == 'all': time = np.genfromtxt(data_and_figures+'Fig.7b-'+'time.csv', delimiter=',') fit_unc = np.genfromtxt(data_and_figures+'Fig.7b-'+'R2.csv', delimiter=',') plt.figure(72) plt.plot(time,fit_unc,'.',color='black') plt.xlabel('Time [ms]') plt.ylabel('$R^{2}$') if which_figure == '7c' or which_figure == 'all': wavenumber = np.genfromtxt(data_and_figures+'Fig.7c-'+'wavenumber.csv', delimiter=',') pwr1 = np.genfromtxt(data_and_figures+'Fig.7c-'+'-0.26_pwr.csv', delimiter=',') pwr1_fit = np.genfromtxt(data_and_figures+'Fig.7c-'+'-0.26_pwr_fit.csv', delimiter=',') pwr2 = np.genfromtxt(data_and_figures+'Fig.7c-'+'0.31_pwr.csv',delimiter=',') pwr2_fit = np.genfromtxt(data_and_figures+'Fig.7c-'+'0.31_pwr_fit.csv',delimiter=',') plt.figure(73) plt.plot(wavenumber, pwr1,'*',color='black',label='-0.26 ms') plt.plot(wavenumber, pwr1_fit, color = 'red',label = 'fit') plt.plot(wavenumber, pwr2,'*',color='green',label='0.31 ms') plt.plot(wavenumber, pwr2_fit, color = 'orange',label = 'fit') plt.xlabel('$k_{\perp}$ (cm$^{-1}$)') plt.ylabel('Power (T$^{2}$ cm)') plt.yscale("log") plt.ylim(2e-9,1e-5) plt.legend()