plot_modelspace_ci.py

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import os
import sys
import numpy
import numpy as np
from netCDF4 import Dataset
import matplotlib
matplotlib.use('pdf')
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from copy import deepcopy
import datetime as dt
from datetime import datetime, timedelta
import numpy.random as npr
import var_utils as vu
import modelsp_utils as mu
 
expStats = 'expmgfsci.nc'
allmetrics = ['RMS'] #['MS']
 
def readdata():
 
    varNamesListAll = []
    varName = []
    for metrics in allmetrics:
        #only for 3dim variables
        for varName in mu.varNames3d:
            for latBand in mu.latBands:
                for fcTDelta in np.arange(0, mu.fcRange+mu.interval,mu.interval):
                    varNamesList = ['expmgfs_day'+str(fcTDelta)+'_'+ latBand +'_'+ varName + '_' + metrics]
                    varNamesListAll.append(varNamesList)
    for metrics in allmetrics:
        #for 2dim and 3dim variables:
        for varName in mu.varNames:
            for latBand in mu.latBands:
                #for all levels:
                varNamesList2 = ['expmgfs_'+ latBand +'_'+ varName + '_' + metrics]
                varNamesListAll.append(varNamesList2)
 
    for i in range(0,len(varNamesListAll)): 
        nc_file = mu.EXP_DIR2+'/'+mu.endDate+'/diagnostic_stats/expmgfsci.nc'
        nc_fid = Dataset(nc_file, "r", format="NETCDF4")
 
        data = np.array( nc_fid.variables[''.join(varNamesListAll[i])][:] )
        x, y = data.shape
        t = list(np.arange(0,x,1))
        varName = ''.join(varNamesListAll[i]) 
        if (x == 55 or x == 56):
           region = ''.join(varName.split("_")[2:][:-2])
           var    = '_'.join(varName.split("_")[3:][:-1])
           stats  = ''.join(varName.split("_")[4:])
           plt.title(stats+'  variable:'+vu.varDictModel[var][1]+'('+ vu.varDictModel[var][0]+')  '+region, fontsize = 12)
           plt.plot(data[:,0],t)
           plt.fill_betweenx( t, data[:,1],data[:,2],alpha=0.3,  linestyle='-.')
           plt.plot([0,0],[0, x], ls="--", c=".3")  # zero line
           plt.xlabel('RMS('+mu.exp2Name+')-RMS('+mu.exp1Name+')',fontsize=15)
           plt.ylabel('Levels',fontsize=15)
        else:
           region = ''.join(varName.split("_")[1:][:-2])
           var    = '_'.join(varName.split("_")[2:][:-1])
           stats  = ''.join(varName.split("_")[3:])
           plt.title(stats+'  variable:'+vu.varDictModel[var][1]+'('+ vu.varDictModel[var][0]+')  '+region, fontsize = 12)
           plt.plot(t,data[:,0])
           plt.fill_between( t,data[:,1],data[:,2],alpha=0.3,  linestyle='-.')
           plt.plot([0, x],[0,0], ls="--", c=".3")  # zero line
           plt.ylabel('RMS('+mu.exp2Name+')-RMS('+mu.exp1Name+')',fontsize=15)
           plt.xlabel('Lead Time (day)',fontsize=15)
     
        plt.grid(True)
        plt.savefig(''.join(varNamesListAll[i])+'_ci.png',dpi=200,bbox_inches='tight')
        plt.close() 
 
def main():
    readdata()
 
if __name__ == '__main__': main()