Update map_seul.py

4-pollution/code/map_seul.py

-import numpy as np
-import matplotlib.pyplot as plt
-from netCDF4 import Dataset
-from matplotlib.colors import LogNorm
-import os
-
-os.environ['PROJ_LIB'] = r'C:\Users\gauth_000\Documents\miniconda3\pkgs\proj4-5.2.0-ha925a31_1\Library\share'
-from mpl_toolkits.basemap import Basemap
-
-
-#Carte à faire
-
-nom_fichier='S5P_OFFL_L2__NO2____100320.nc'
-
-
-fh=Dataset(nom_fichier, mode = 'r' )
-
-    
-long = fh.groups['PRODUCT'].variables['longitude'][:][0,:,:]
-lat = fh.groups['PRODUCT'].variables['latitude'][:][0,:,:]
-    
-
-#shape pour faire les for
-shape_long=fh.groups['PRODUCT'].variables['longitude'].shape
-    
-#donnée
-no=fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'][0,:,:]
-qa=fh.groups['PRODUCT'].variables['qa_value'][:][0,:,:]
-
-shape=fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'].shape
-
-#nombre de pixel pris en compte (qa valide)
-pix=np.zeros([shape[1],shape[2]]) 
-
-
-#on fait la moyenne
-for i in range (0,shape[1]):
-    #pourcentage pour voir l'avancement
-    print(float (i/shape[1]))
-    for j in range (0,shape[2]):
-        if no[i][j]!=0: #pixel nul?
-            pix[i][j]=1
-
-
-  
-m = Basemap(width=1000000,height=1000000,resolution='l',projection='stere',lat_0=45.1667,lon_0=5.717)   
-xi, yi = m(long, lat)
-
-
-# Plot Data
-cs = m.pcolor(xi,yi,np.squeeze(no),vmin=1e-5, vmax=9e-4,norm=LogNorm(), cmap='jet')
-
-
-#add grid    
-m.drawparallels(np.arange(-80., 81., 10.), labels=[1,0,0,0], fontsize=5)
-m.drawmeridians(np.arange(-180., 181., 10.), labels=[0,0,0,1], fontsize=5)
-
-
-#Add coastlines, states and country
-m.drawcoastlines()
-m.drawcountries()
-
-
-# Add Colorbar
-no2_units = fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'].units
-cbar = m.colorbar(cs, location='bottom', pad="10%")
-cbar.set_label(no2_units)
-
-# Add Title
-plt.title('NO2 in atmosphere')
-plt.savefig('No1', dpi = 600)
-plt.show()
-
-
+import numpy as np
+import matplotlib.pyplot as plt
+from netCDF4 import Dataset
+from matplotlib.colors import LogNorm
+import os
+
+os.environ['PROJ_LIB'] = r'C:\Users\gauth_000\Documents\miniconda3\pkgs\proj4-5.2.0-ha925a31_1\Library\share'
+from mpl_toolkits.basemap import Basemap
+
+
+#Carte à faire
+
+nom_fichier='S5P_OFFL_L2__NO2____100320.nc'
+
+
+fh=Dataset(nom_fichier, mode = 'r' )
+
+    
+long = fh.groups['PRODUCT'].variables['longitude'][:][0,:,:]
+lat = fh.groups['PRODUCT'].variables['latitude'][:][0,:,:]
+    
+
+#shape pour faire les for
+shape_long=fh.groups['PRODUCT'].variables['longitude'].shape
+    
+#donnée
+no=fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'][0,:,:]
+qa=fh.groups['PRODUCT'].variables['qa_value'][:][0,:,:]
+
+shape=fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'].shape
+
+#nombre de pixel pris en compte (qa valide)
+pix=np.zeros([shape[1],shape[2]]) 
+
+
+#on fait la moyenne
+for i in range (0,shape[1]):
+    #pourcentage pour voir l'avancement
+    print(float (i/shape[1]))
+    for j in range (0,shape[2]):
+        if no[i][j]!=0: #pixel nul?
+            pix[i][j]=1
+
+
+  
+m = Basemap(width=1000000,height=1000000,resolution='l',projection='stere',lat_0=45.1667,lon_0=5.717)   
+xi, yi = m(long, lat)
+
+
+# Plot Data
+cs = m.pcolor(xi,yi,np.squeeze(no),vmin=1e-5, vmax=9e-4,norm=LogNorm(), cmap='jet')
+
+
+#add grid    
+m.drawparallels(np.arange(-80., 81., 10.), labels=[1,0,0,0], fontsize=5)
+m.drawmeridians(np.arange(-180., 181., 10.), labels=[0,0,0,1], fontsize=5)
+
+
+#Add coastlines, states and country
+m.drawcoastlines()
+m.drawcountries()
+
+
+# Add Colorbar
+no2_units = fh.groups['PRODUCT'].variables['nitrogendioxide_tropospheric_column_precision'].units
+cbar = m.colorbar(cs, location='bottom', pad="10%")
+cbar.set_label(no2_units)
+
+# Add Title
+plt.title('NO2 in atmosphere')
+plt.savefig('No1', dpi = 600)
+plt.show()
+
+