source: trunk/src/scripts_Laura/ARCTIC/Travail_CEN/lire_arome_nc.py @ 56

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import string
import matplotlib.pyplot as pyplot #used to build contour and wind barbs plots
from numpy import *
import string
import numpy as np
import netCDF4
#from mpl_toolkits.basemap import shiftgrid, cm
from netCDF4 import Dataset
from pylab import *
from mpl_toolkits.basemap import Basemap
from mpl_toolkits.basemap import shiftgrid, cm

# ici je boucle sur les dates
list_anne=arange(2010,2011,1)
list_mois=arange(8,9,1)
list_jour=arange(15,32,1)

#pluie_mois=np.zeros([15,nbtotal],float)

for ian in range(0,1):
        for imo in range(0,1):
                for ijr in range(0,1):
                        if (list_mois[imo] <= 9):
                                nom_mois='0'+ str(list_mois[imo])
                        else:
                                nom_mois= str(list_mois[imo])
                                
                        if (list_jour[ijr] <= 9):
                                nom_jour='0'+ str(list_jour[ijr])
                        else:
                                nom_jour= str(list_jour[ijr])
                        
                        jour_an=str(list_anne[ian])+nom_mois+nom_jour
                        print jour_an
                        fichier_netcdf='z:/arome/arome_grib_'+jour_an+'.nc'
                        arome=Dataset(fichier_netcdf, 'r', format='NETCDF3_CLASSIC')
                        nc_surf1= arome.variables['prevision6h humidite relative 2m']
                        nc_surf2= arome.variables['prevision6h temperature 2m']
                        nc_surf3= arome.variables['prevision6h nebul']
                        nc_surf4= arome.variables['prevision30h nebul']
                        nc_surf5= arome.variables['prevision6h TCWV']
                        nc_surf6= arome.variables['prevision6h flux net solaire D']
                        nc_surf7= arome.variables['prevision6h flux net thermique D']
                        nc_surf8= arome.variables['analyse pression au sol']
                        nc_surf9= arome.variables['prevision6h pression au sol']
                        nc_surf10= arome.variables['analyse altitude']
                        nc_surf11= arome.variables['prevision6h neige']
                        nc_surf12= arome.variables['prevision30h neige']
                        nc_surf13= arome.variables['prevision6h eau']
                        nc_surf14= arome.variables['prevision30h eau']
                        nc_surf15= arome.variables['prevision6h graupel']
                        nc_surf16= arome.variables['prevision30h graupel']
                        nc_surf17= arome.variables['prevision6h Vvent 10m']
                        nc_surf18= arome.variables['prevision6h Uvent 10m']
                        eau6h = nc_surf13[:]
                        eau30h = nc_surf14[:]
                        eau24h = eau30h - eau6h
                        neige6h = nc_surf11[:]
                        neige30h = nc_surf12[:]
                        neige24h = neige30h - neige6h
                        graupel6h = nc_surf15[:]
                        graupel30h = nc_surf16[:]
                        graupel24h = graupel30h - graupel6h
                        rain = eau24h + graupel24h + neige24h

                        
                        lat=arome.variables['latitude'][:]
                        lon=arome.variables['longitude'][:]
                        m = Basemap(llcrnrlon=-7,urcrnrlon=11,llcrnrlat=40,urcrnrlat=52,projection='cyl',resolution='h',fix_aspect=True)
       
                        xii, yii = m(*np.meshgrid(lon,lat))
                        ax = plt.gca()
                        #clevs=arange(0,0.8,0.005)
                        clevs=arange(1,30,1)
                        m.drawcoastlines(linewidth=0.5)
                        m.drawlsmask(ocean_color='#F4EAF1', lakes=False)
                        cs=m.contourf(xii,yii,rain, clevs, cmap=cm.s3pcpn_l_r) # emissivity
                        cbar =colorbar(cs)
                        cbar.set_label('Precips 24h')
                        #cbar.set_clim(0.65,1)
                #       m.drawmapboundary(fill_color='aqua')
                        #m.drawparallels(np.arange(-90.,90.,10.), labels=[1,0,0,0])
                        #m.drawmeridians(np.arange(-180.,180.,30.), labels=[0,0,0,1])
                #       m.drawparallels(np.arange(-90.,90.,45.), color='#909090', linewidth=1.0, zorder=None, dashes=[1, 1])
                        plt.show()
                        plt.savefig('test_sorties_arome.png')
                        #close()