# Copyright (C) 2015-2016: The University of Edinburgh # Authors: Craig Warren and Antonis Giannopoulos # # This file is part of gprMax. # # gprMax is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # gprMax is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with gprMax. If not, see . import sys, os, argparse import h5py import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt from gprMax.exceptions import CmdInputError """Plots a comparison of fields between given simulation output and experimental data files.""" # Parse command line arguments parser = argparse.ArgumentParser(description='Plots a comparison of fields between given simulation output and experimental data files.', usage='cd gprMax; python -m tests.test_compare_experimental modelfile realfile output') parser.add_argument('modelfile', help='name of model output file including path') parser.add_argument('realfile', help='name of file containing experimental data including path') parser.add_argument('output', help='output to be plotted, i.e. Ex Ey Ez', nargs='+') args = parser.parse_args() # Model results f = h5py.File(args.modelfile, 'r') path = '/rxs/rx1/' availablecomponents = list(f[path].keys()) # Check if requested output is in file if args.output[0] not in availablecomponents: raise CmdInputError('{} output requested to plot, but the available output for receiver 1 is {}'.format(args.output[0], ', '.join(availablecomponents))) floattype = f[path + args.output[0]].dtype model = np.zeros((f.attrs['Iterations']), dtype=floattype) timemodel = np.zeros((f.attrs['Iterations']), dtype=floattype) timemodel = np.arange(0, f.attrs['dt'] * f.attrs['Iterations'], f.attrs['dt']) / 1e-9 model = f[path + args.output[0]][:] * -1 model /= np.amax(np.abs(model)) f.close() # Find location of maximum value from model modelmax = np.where(np.abs(model) == 1)[0][0] # Real results with open(args.realfile, 'r') as f: real = np.loadtxt(f) real[:,1] = real[:,1] / np.amax(np.abs(real[:,1])) realmax = np.where(np.abs(real[:,1]) == 1)[0][0] difftime = - (timemodel[modelmax] - real[realmax,0]) # Plot modelled and real data fig, ax = plt.subplots(num=args.modelfile + ' versus ' + args.realfile, figsize=(20, 10), facecolor='w', edgecolor='w') ax.plot(timemodel + difftime, model, 'r', lw=2, label='Model') ax.plot(real[:,0], real[:,1], 'r', ls='--', lw=2, label='Experiment') ax.set_xlabel('Time [ns]') ax.set_ylabel('Amplitude') ax.set_xlim([0, timemodel[-1]]) ax.set_ylim([-1, 1]) ax.legend() ax.grid() # Show/print plots savename = os.path.abspath(os.path.dirname(args.modelfile)) + os.sep + os.path.splitext(os.path.split(args.modelfile)[1])[0] + '_vs_' + os.path.splitext(os.path.split(args.realfile)[1])[0] #fig.savefig(savename + '.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1) plt.show()