normality.py

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#!/usr/bin/env python3
 
import argparse
from netCDF4 import Dataset
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import numpy.ma as ma
import os
 
def normality(testdata, test, mpi, omp, suffix, testfig):
   # Loop over files
   first = True
   for impi in range(0, int(mpi)):
      # Open file
      f = Dataset(testdata + "/" + test + "/test_" + mpi + "-" + omp + "_" + suffix + "_" + mpi.zfill(6) + "-" + format(impi+1, '06d') + ".nc", "r", format="NETCDF4")
 
      # Get data
      if "ens_norm" in f.variables:
         nloc = f["ens_norm"][:].shape[0]
         if first:
            ne = f["ens_norm"][:].shape[1]
            ens_norm = np.zeros((0, ne))
            ens_step = np.zeros((0, ne-1))
            first = False
         for iloc in range(0, nloc):
            ens_norm = np.append(ens_norm, [f["ens_norm"][iloc,:].data], axis=0)
            ens_step = np.append(ens_step, [f["ens_step"][iloc,:].data], axis=0)
 
   # X axis
   x_norm = np.linspace(1, ne, ne)
   x_step = np.linspace(1, ne-1, ne-1)
 
   # Plots
   fig, ax = plt.subplots(nrows=2)
   fig.subplots_adjust(hspace=0.5)
   ax[0].set_title("Normalized perturbation amplitude")
   ax[0].set_xlim([1.0,float(ne)])
   ax[0].set_ylim([-0.1,1.1])
   ax[0].set_xlabel("Ordered member")
   ax[0].plot(x_norm, ens_norm[0,:])
   ax[1].set_title("Normalized perturbation amplitude step")
   ax[1].set_xlim([1.0,float(ne-1)])
   ax[1].set_ylim([-0.1,1.1])
   ax[1].set_xlabel("Ordered member")
   ax[1].plot(x_step, ens_step[0,:])
 
   # Save and close figure
   plt.savefig(testfig + "/test_" + mpi + "-" + omp + "_" + suffix + ".jpg", format="jpg", dpi=300)
   plt.close()