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Parameters_calculation_and_mapping.py
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Parameters_calculation_and_mapping.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Mar 15 15:22:41 2019
@author: alessio
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import datetime
from spacepy import coordinates
from spacepy.time import Ticktock
from apexpy import Apex
from Functions import *
from Terminal_interface import *
import warnings
warnings.filterwarnings("ignore")
print('\n**********Swarm data analysis module**********')
plt.ioff()
MEAN_EARTH_RADIUS=6371.007 #mean Earth radius IUGG
SHELL_HEIGHT=400 #height of the thin shell (above Swarm satellite) in km
###############################################################################
#Defining paths
###############################################################################
main_folder=os.getcwd()
path_initial = os.path.join(main_folder,str(YEAR).zfill(4)+str(MONTH).zfill(2)+str(DOM).zfill(2)+str(SAT))
path_organized_data_LP=os.path.join(path_initial,'Organized_data','LP')
path_organized_data_TEC=os.path.join(path_initial,'Organized_data','TEC')
path_output=os.path.join(path_initial,'Output')
###############################################################################
#Working on Langmuir Probes data
###############################################################################
filename_swarm=os.listdir(path_organized_data_LP)
filename_swarm.sort()
#Parameters for indices calculation
FLAG=np.nan
FREQUENCY=2 #frequency of the input time series
WINDOW=int(WINDOW_WIDTH*FREQUENCY+1) #number of points in the windows (it must be odd)
GAP=int(WINDOW/2) #number of missing data allowed in the window
for filename in filename_swarm:
SAT=filename[9:10]
YEAR=filename[11:15]
MONTH=filename[16:18]
DAY=filename[19:21]
print('Working on Swarm '+SAT+' '+YEAR+'/'+MONTH+'/'+DAY+' LP data...')
###############################################################################
#Reading variables in files
###############################################################################
#Time
year,month,day,hour,minute,second,msec,doy=\
np.genfromtxt(os.path.join(path_organized_data_LP,filename),unpack=True,usecols=(0,1,2,3,4,5,6,7),dtype=int,skip_header=1)
hourUT,hourLT,MLT=\
np.genfromtxt(os.path.join(path_organized_data_LP,filename),unpack=True,usecols=(8,9,10),dtype=float,skip_header=1)
#Position
lat_geo,lon_geo,radius,height,lat_mag,lon_mag=\
np.genfromtxt(os.path.join(path_organized_data_LP,filename),unpack=True,usecols=(11,12,13,14,15,16),dtype=float,skip_header=1)
#Values
Ne,Te,flag_LP,flag_Ne,flag_Te=\
np.genfromtxt(os.path.join(path_organized_data_LP,filename),unpack=True,usecols=(17,18,19,20,21),dtype=int,skip_header=1)
Ne=list(Ne)
#Ne filter based on flags
for i in range(len(Ne)):
if(flag_LP[i]!=1 or flag_Ne[i]>29):
Ne[i]=np.nan
Te=list(Te)
#Te filter based on flags
for i in range(len(Te)):
if(flag_LP[i]!=1 or (flag_Te[i]!=10 and flag_Te[i]!=20)):
Te[i]=np.nan
###############################################################################
#RODI, ROTEI, and other LP parameteres calculation
###############################################################################
date=[]
for i in range(len(Ne)):
if(msec[i]>=0 and msec[i]<500):
msec_2=0
if(msec[i]>=500 and msec[i]<=999):
msec_2=500
date.append(datetime(year[i],month[i],day[i],hour[i],minute[i],second[i],msec_2*1000))
date_list=[]
for i in range(len(date)):
#time in seconds from the beginning of the considered month
time=(date[i].day-1)*86400+date[i].hour*3600+date[i].minute*60+date[i].second+date[i].microsecond/1e6
date_list.append(time)
print(' Calculating RODI, ROTEI, and other LP parameters...')
#Ne
rod_parameters=rod_rodi_calculation(Ne,date_list,WINDOW,FREQUENCY,GAP,FLAG)
gradient=gradient_calculation(Ne,date_list,radius,lat_geo,lon_geo,FREQUENCY,FLAG)
#Te
roTe_parameters=rod_rodi_calculation(Te,date_list,WINDOW,FREQUENCY,GAP,FLAG)
gradient_Te=gradient_calculation(Te,date_list,radius,lat_geo,lon_geo,FREQUENCY,FLAG)
print(' Saving output file...')
filename_output='Swarm_LP_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_output.txt'
f=open(os.path.join(path_output,'data','LP',filename_output),'w')
f.write('year month day hour min sec msec doy hourUT hourLT MLT LatGeo LonGeo Radius [m] Height [km] LatMag_QD LonMag_QD Ne [cm^-3] Flag_LP Flag_Ne ROD [cm^-3/s] RODI [cm^-3/s] mean_ROD [cm^-3/s] Ne_grad [cm^-3/km] mean_Ne [cm^-3] Te [K] Flag_Te ROTE [K/s] ROTEI [K/s] mean_ROTE [K/s] Te_grad [K/km] mean_Te [K]\n')
for i in range(len(Ne)):
f.write('%4i\t\t%2i\t\t%2i\t\t%2i\t\t%2i\t\t%2i\t\t%3i\t\t%3i\t\t%8.5f\t\t%8.5f\t\t%8.5f\t\t%10.5f\t\t%10.5f\t\t%10.2f\t\t%10.2f\t\t%10.5f\t\t%10.5f\t\t%9.0f\t\t%3i\t\t%3i\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\t\t\t%8.0f\t\t%3i\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\t\t\t%9.1f\n' % \
(year[i],month[i],day[i],hour[i],minute[i],second[i],msec[i],doy[i],hourUT[i],hourLT[i],MLT[i],lat_geo[i],lon_geo[i],radius[i],height[i],lat_mag[i],lon_mag[i],Ne[i],flag_LP[i],flag_Ne[i],rod_parameters[1][i],rod_parameters[2][i],rod_parameters[3][i],gradient[1][i],rod_parameters[5][i],Te[i],flag_Te[i],roTe_parameters[1][i],roTe_parameters[2][i],roTe_parameters[3][i],gradient_Te[1][i],roTe_parameters[5][i]))
f.close()
if(FIGURE):
###########################################################################
#Binning in Magnetic coordinates
###########################################################################
print(' Binning data in magnetic coordinates...')
#North Pole
lat_QD_NP=np.ma.masked_less(lat_mag,40)
MLT_map_NP=np.ma.masked_array(MLT,lat_QD_NP.mask)#/24.*(2*np.pi)
lat_QD_NP=-1.*(lat_QD_NP-90.)
for i in range(len(lat_QD_NP)):
if(lat_QD_NP[i]>=50):
lat_QD_NP[i]=np.nan
MLT_map_NP[i]=np.nan
for i in range(len(MLT_map_NP)):
if(MLT_map_NP[i]>=24):
MLT_map_NP[i]=np.nan
lat_QD_NP[i]=np.nan
binned_rodi_QD_MLT_NP=binning_2D(MLT_map_NP,lat_QD_NP,rod_parameters[2],0,24,0.25,0,50,2)
binned_roTei_QD_MLT_NP=binning_2D(MLT_map_NP,lat_QD_NP,roTe_parameters[2],0,24,0.25,0,50,2)
binned_Ne_QD_MLT_NP=binning_2D(MLT_map_NP,lat_QD_NP,Ne,0,24,0.25,0,50,2)
binned_Te_QD_MLT_NP=binning_2D(MLT_map_NP,lat_QD_NP,Te,0,24,0.25,0,50,2)
#South Pole
lat_QD_SP=np.ma.masked_greater(lat_mag,-40)
MLT_map_SP=np.ma.masked_array(MLT,lat_QD_SP.mask)#/24.*(2*np.pi)
lat_QD_SP=lat_QD_SP+90.
for i in range(len(lat_QD_SP)):
if(lat_QD_SP[i]>=50):
lat_QD_SP[i]=np.nan
MLT_map_SP[i]=np.nan
for i in range(len(MLT_map_SP)):
if(MLT_map_SP[i]>=24):
MLT_map_SP[i]=np.nan
lat_QD_SP[i]=np.nan
binned_rodi_QD_MLT_SP=binning_2D(MLT_map_SP,lat_QD_SP,rod_parameters[2],0,24,0.25,0,50,2)
binned_roTei_QD_MLT_SP=binning_2D(MLT_map_SP,lat_QD_SP,roTe_parameters[2],0,24,0.25,0,50,2)
binned_Ne_QD_MLT_SP=binning_2D(MLT_map_SP,lat_QD_SP,Ne,0,24,0.25,0,50,2)
binned_Te_QD_MLT_SP=binning_2D(MLT_map_SP,lat_QD_SP,Te,0,24,0.25,0,50,2)
binned_rodi_QD_MLT=binning_2D(MLT,lat_mag,rod_parameters[2],0,24,0.25,-90,90,2)
binned_roTei_QD_MLT=binning_2D(MLT,lat_mag,roTe_parameters[2],0,24,0.25,-90,90,2)
binned_Ne_QD_MLT=binning_2D(MLT,lat_mag,Ne,0,24,0.25,-90,90,2)
binned_Te_QD_MLT=binning_2D(MLT,lat_mag,Te,0,24,0.25,-90,90,2)
###############################################################################
#RODI figures
###############################################################################
logo = plt.imread(os.path.join(main_folder,'logo.png'))
print(' Making output figures...')
#Map scatter lat-lon Global
fig=plt.figure(figsize=(18,10))
m=Basemap(projection='robin',lon_0=0,llcrnrlat=-90,urcrnrlat=90,\
llcrnrlon=-180,urcrnrlon=180,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,30),labels=[1,1,0,0],fontsize=15)
m.drawmeridians(np.arange(-180,180,60),labels=[0,0,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(rod_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=3,vmax=5)
cbar=m.colorbar(fig,location='right',pad="5%",size="2.3%")#,format='%3.1e')
cbar.set_label('$log_{10}(RODI)\ (log_{10}(cm^{-3}/s))$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter RODI, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon North Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=40, projection='npstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(rod_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=3,vmax=5)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}(RODI)\ (log_{10}(cm^{-3}/s))$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter RODI, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon South Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=-40, projection='spstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(rod_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=3,vmax=5)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}(RODI)\ (log_{10}(cm^{-3}/s)])$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter RODI, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
###########################################################################
#QD-MLT polar plots
###########################################################################
#North Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_rodi_QD_MLT_NP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=3,vmax=5)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['90','80','70','60','50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(RODI) ($log_{10}$(el/cm$^{3}$/s))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot RODI, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#South Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_rodi_QD_MLT_SP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=3,vmax=5)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['-90','-80','-70','-60','-50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(RODI) ($log_{10}$(el/cm$^{3}$/s))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot RODI, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Global
fig=plt.figure(figsize=(18,10))
y=np.linspace(-90,90,91, endpoint='True')
x=np.linspace(0,24,97,endpoint='True')
X,Y = np.meshgrid(x,y)
z=np.log10(binned_rodi_QD_MLT[0])
plt.pcolormesh(X,Y,z,cmap=plt.cm.jet,vmin=3,vmax=5)
plt.grid()
plt.xticks(np.linspace(0,24,25,endpoint=True),fontsize=15)
plt.yticks(np.linspace(-90,90,7),fontsize=15)
plt.xlabel('MLT', fontsize=20)
plt.ylabel('Magnetic Latitude', fontsize=20)
cbar=plt.colorbar(orientation='vertical',fraction=0.05)
cbar.set_label('$log_{10}$(RODI) ($log_{10}$(el/cm$^{3}$/s))', fontsize=20)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic coordinates plot RODI, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','RODI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_magnetic_coordinates.png'), format='png',dpi=150)
plt.clf()
plt.close()
###############################################################################
#ROTEI figures
###############################################################################
#Map scatter lat-lon Global
fig=plt.figure(figsize=(18,10))
m=Basemap(projection='robin',lon_0=0,llcrnrlat=-90,urcrnrlat=90,\
llcrnrlon=-180,urcrnrlon=180,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,30),labels=[1,1,0,0],fontsize=15)
m.drawmeridians(np.arange(-180,180,60),labels=[0,0,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(roTe_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=3.5)
cbar=m.colorbar(fig,location='right',pad="5%",size="2.3%")#,format='%3.1e')
cbar.set_label('$log_{10}(ROTEI)\ (log_{10}(K/s))$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter ROTEI, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon North Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=40, projection='npstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(roTe_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=3.5)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}(ROTEI)\ (log_{10}(K/s))$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter ROTEI, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon South Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=-40, projection='spstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(roTe_parameters[2]),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=3.5)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}(ROTEI)\ (log_{10}(K/s)])$', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter ROTEI, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
###########################################################################
#QD-MLT polar maps
###########################################################################
#North Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_roTei_QD_MLT_NP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=0,vmax=3.5)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['90','80','70','60','50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(ROTEI) ($log_{10}$(K/s))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot ROTEI, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#South Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_roTei_QD_MLT_SP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=0,vmax=3.5)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['-90','-80','-70','-60','-50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(ROTEI) ($log_{10}$(K/s))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot ROTEI, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Global
fig=plt.figure(figsize=(18,10))
y=np.linspace(-90,90,91, endpoint='True')
x=np.linspace(0,24,97,endpoint='True')
X,Y = np.meshgrid(x,y)
z=np.log10(binned_roTei_QD_MLT[0])
plt.pcolormesh(X,Y,z,cmap=plt.cm.jet,vmin=0,vmax=3.5)
plt.grid()
plt.xticks(np.linspace(0,24,25,endpoint=True),fontsize=15)
plt.yticks(np.linspace(-90,90,7),fontsize=15)
plt.xlabel('MLT', fontsize=20)
plt.ylabel('Magnetic Latitude', fontsize=20)
cbar=plt.colorbar(orientation='vertical',fraction=0.05)
cbar.set_label('$log_{10}$(ROTEI) ($log_{10}$(K/s))', fontsize=20)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic coordinates plot ROTEI, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','ROTEI_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_magnetic_coordinates.png'), format='png',dpi=150)
plt.clf()
plt.close()
###############################################################################
#Ne figures
###############################################################################
#Map scatter lat-lon Global
fig=plt.figure(figsize=(18,10))
m=Basemap(projection='robin',lon_0=0,llcrnrlat=-90,urcrnrlat=90,\
llcrnrlon=-180,urcrnrlon=180,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,30),labels=[1,1,0,0],fontsize=15)
m.drawmeridians(np.arange(-180,180,60),labels=[0,0,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(Ne),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=3,vmax=6)
cbar=m.colorbar(fig,location='right',pad="10%",size="2.3%")#,format='%3.1e')
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Ne, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon North Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=40, projection='npstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(Ne),edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=3,vmax=6)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Ne, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon South Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=-40, projection='spstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=np.log10(Ne),edgecolors='None', linewidths=None,cmap=plt.cm.jet)#,vmin=3,vmax=5)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Ne, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
###########################################################################
#QD-MLT polar plots
###########################################################################
#North Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_Ne_QD_MLT_NP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=3,vmax=6)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['90','80','70','60','50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot Ne, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#South Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=np.log10(binned_Ne_QD_MLT_SP[0].T)
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=3,vmax=6)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['-90','-80','-70','-60','-50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot Ne, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Global
fig=plt.figure(figsize=(18,10))
y=np.linspace(-90,90,91, endpoint='True')
x=np.linspace(0,24,97,endpoint='True')
X,Y = np.meshgrid(x,y)
z=np.log10(binned_Ne_QD_MLT[0])
plt.pcolormesh(X,Y,z,cmap=plt.cm.jet,vmin=3,vmax=6)
plt.grid()
plt.xticks(np.linspace(0,24,25,endpoint=True),fontsize=15)
plt.yticks(np.linspace(-90,90,7),fontsize=15)
plt.xlabel('MLT', fontsize=20)
plt.ylabel('Magnetic Latitude', fontsize=20)
cbar=plt.colorbar(orientation='vertical',fraction=0.05)
cbar.set_label('$log_{10}$(Ne) ($log_{10}$(el/cm$^{3}$))', fontsize=20)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic coordinates plot Ne, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Ne_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_magnetic_coordinates.png'), format='png',dpi=150)
plt.clf()
plt.close()
###############################################################################
#Te figures
###############################################################################
#Map scatter lat-lon Global
fig=plt.figure(figsize=(18,10))
m=Basemap(projection='robin',lon_0=0,llcrnrlat=-90,urcrnrlat=90,\
llcrnrlon=-180,urcrnrlon=180,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,30),labels=[1,1,0,0],fontsize=15)
m.drawmeridians(np.arange(-180,180,60),labels=[0,0,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=Te,edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=6000)
cbar=m.colorbar(fig,location='right',pad="10%",size="2.3%")#,format='%3.1e')
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Te, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon North Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=40, projection='npstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=Te,edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=6000)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Te, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Map scatter lat-lon South Pole
fig=plt.figure(figsize=(12,10))
m = Basemap(lon_0=0, boundinglat=-40, projection='spstere',round=True,resolution='l')
m.drawcoastlines(linewidth=1)
m.drawparallels(np.arange(-90,90,10),labels=[1,1,1,1],fontsize=15)
m.drawmeridians(np.arange(0,360,30),labels=[1,1,1,1],fontsize=15)
m.drawcountries()
m.shadedrelief(scale=0.25,alpha=0.5)
x, y = m(lon_geo,lat_geo)
fig=m.scatter(x,y,s=50,c=Te,edgecolors='None', linewidths=None,cmap=plt.cm.jet,vmin=0,vmax=6000)
cbar=m.colorbar(fig,location='right',pad="10%",size="5%")#,format='%3.1e')
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Scatter Te, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_scatter.png'), format='png',dpi=150)
plt.clf()
plt.close()
###########################################################################
#QD-MLT polar plots
###########################################################################
#North Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=binned_Te_QD_MLT_NP[0].T
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=0,vmax=6000)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['90','80','70','60','50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot Te, North Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_North_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#South Pole
fig=plt.figure(figsize=(12,12))
rad=np.linspace(0,50,26, endpoint='True')
azm=np.linspace(0,24,97, endpoint='True')/24.*(2*np.pi)
r, th = np.meshgrid(rad, azm)
z=binned_Te_QD_MLT_SP[0].T
ax=plt.subplot(projection="polar")
plt.pcolormesh(th-np.pi/2., r, z,cmap=plt.cm.jet,vmin=0,vmax=6000)
plt.plot(azm, r, color='k', ls='none')
plt.grid()
plt.xticks(np.linspace(0,2*np.pi,24,endpoint=False),(np.concatenate((np.linspace(6,23,18,dtype=int),np.linspace(0,5,6,dtype=int)))),fontsize=15)
ax.set_rorigin(0)
ax.set_theta_zero_location('E', offset=0)
plt.yticks(np.linspace(0,40,5),['-90','-80','-70','-60','-50'],fontsize=15,alpha=1,color='black')
plt.xlabel('MLT-Magnetic Latitude ', fontsize=20)
cbar=plt.colorbar(orientation='horizontal',fraction=0.05)
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic polar plot Te, South Pole, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_South_Pole_magnetic_polar_plot.png'), format='png',dpi=150)
plt.clf()
plt.close()
#Global
fig=plt.figure(figsize=(18,10))
y=np.linspace(-90,90,91, endpoint='True')
x=np.linspace(0,24,97,endpoint='True')
X,Y = np.meshgrid(x,y)
z=binned_Te_QD_MLT[0]
plt.pcolormesh(X,Y,z,cmap=plt.cm.jet,vmin=0,vmax=6000)
plt.grid()
plt.xticks(np.linspace(0,24,25,endpoint=True),fontsize=15)
plt.yticks(np.linspace(-90,90,7),fontsize=15)
plt.xlabel('MLT', fontsize=20)
plt.ylabel('Magnetic Latitude', fontsize=20)
cbar=plt.colorbar(orientation='vertical',fraction=0.05)
cbar.set_label('Te (K)', fontsize=15)
cbar.ax.tick_params(labelsize=15)
plt.figimage(logo,0,0,zorder=-1,alpha=1)
plt.title('Magnetic coordinates plot Te, Global, Swarm '+SAT+', '+YEAR+'/'+MONTH+'/'+DAY+'\n\n',fontsize=20, fontweight='bold')
plt.savefig(os.path.join(path_output,'figures','LP','Te_Swarm_'+SAT+'_'+YEAR+'_'+MONTH+'_'+DAY+'_Global_magnetic_coordinates.png'), format='png',dpi=150)
plt.clf()
plt.close()
###############################################################################
#Working on TEC data
###############################################################################
PRN_index=np.linspace(1,32,32,dtype=int)
filename_swarm=os.listdir(path_organized_data_TEC)
filename_swarm.sort()
#Parameters for indices calculation
FLAG=np.nan
if(FREQUENCY_CHANGE_TEC):
FREQUENCY=0.1 #frequency of the input time series
WINDOW=int((WINDOW_WIDTH*10)*FREQUENCY+1) #number of points in the windows (it must be odd)
else:
FREQUENCY=1 #frequency of the input time series
WINDOW=int(WINDOW_WIDTH*FREQUENCY+1) #number of points in the windows (it must be odd)
GAP=int(WINDOW/2) #number of missing data allowed in the window
lat_mag_complete=[]
MLT_complete=[]
TEC_for_ROTI_complete=[]
ROTI_complete=[]
for filename in filename_swarm:
SAT=filename[10:11]
YEAR=filename[12:16]
MONTH=filename[17:19]
DAY=filename[20:22]
PRN=filename[26:28]
print('Working on Swarm '+SAT+' '+YEAR+'/'+MONTH+'/'+DAY+' PRN='+PRN+' TEC data...')
if(os.stat(os.path.join(path_organized_data_TEC,filename)).st_size<1000):
print(' GPS satellite outside FOV')
continue
###############################################################################
#Reading variables in files
###############################################################################
#Time
year,month,day,hour,minute,second,msec,doy=\
np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(0,1,2,3,4,5,6,7),dtype=int,skip_header=1)
hourUT,hourLT,MLT=\
np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(8,9,10),dtype=float,skip_header=1)
#Position
lat_geo,lon_geo,radius,height,lat_mag,lon_mag=\
np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(11,12,13,14,15,16),dtype=float,skip_header=1)
#Values
abs_sTEC,abs_vTEC,rel_sTEC,rel_sTEC_RMS,elev_angle=\
np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(17,18,19,20,21),dtype=float,skip_header=1)
#PRN
prn=np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(22),dtype=int,skip_header=1)
#GPS and LEO position
GPS_Position_X,GPS_Position_Y,GPS_Position_Z,LEO_Position_X,LEO_Position_Y,LEO_Position_Z=\
np.genfromtxt(os.path.join(path_organized_data_TEC,filename),unpack=True,usecols=(23,24,25,26,27,28),dtype=float,skip_header=1)
#Control on prn
for i in range(len(prn)):
if(prn[i]!=int(PRN)):
raise Exception('PRN not coincidents')
#lat_mag_complete.append(lat_mag)
#MLT_complete.append(MLT)
###############################################################################
#ROTI and other TEC paramaters calculation
###############################################################################
date=[]
date_str=[]
for i in range(len(prn)):
date.append(datetime(year[i],month[i],day[i],hour[i],minute[i],second[i]))
date_str.append(str(datetime(year[i],month[i],day[i],hour[i],minute[i],second[i])))
date_list=[]