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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-07 04:56:51 +08:00
125 行
5.2 KiB
Python
125 行
5.2 KiB
Python
# Copyright (C) 2015: The University of Edinburgh
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# Authors: Craig Warren and Antonis Giannopoulos
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#
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# This file is part of gprMax.
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#
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# gprMax is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# gprMax is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with gprMax. If not, see <http://www.gnu.org/licenses/>.
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import sys, os
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import h5py
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import numpy as np
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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from tools.plot_fields import plot_Ascan
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from tests.analytical_solutions import hertzian_dipole_fs
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"""Compare field outputs
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Usage:
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cd gprMax
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python -m tests.test_compare_analytical path_to_model_output
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"""
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modelfile = sys.argv[1]
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path = '/rxs/rx1/'
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# Key refers to subplot location
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fields = {0: 'Ex', 1: 'Ey', 2: 'Ez', 3: 'Hx', 4: 'Hy', 5: 'Hz'}
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plotorder = {0: 0, 1: 3, 2: 1, 3: 4, 4: 2, 5: 5}
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# Model results
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f = h5py.File(modelfile, 'r')
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# Get model/file attributes
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floattype = f[path + 'Ex'].dtype
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iterations = f.attrs['Iterations']
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dt = f.attrs['dt']
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dxdydz = f.attrs['dx, dy, dz']
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model = np.zeros((iterations, 6), dtype=floattype)
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time = np.arange(0, dt * iterations, dt) / 1e-9
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rxpos = f[path + 'Position']
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txpos = f['/txs/tx1/Position']
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rxposrelative = ((rxpos[0] - txpos[0]), (rxpos[1] - txpos[1]), (rxpos[2] - txpos[2]))
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# Read fields
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for ID, name in fields.items():
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model[:,ID] = f[path + str(name)][:]
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f.close()
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# Analytical solution of a dipole in free space
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analytical = hertzian_dipole_fs(iterations * dt, dt, dxdydz, rxposrelative)
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# Differences
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threshold = 1e-4 # Threshold, below which ignore differences
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diffs = np.zeros((iterations, 6), dtype=floattype)
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for ID, name in fields.items():
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max = np.amax(np.abs(analytical[:,ID]))
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if max < threshold:
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diffs[:,ID] = 0
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diffsum = 0
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print('Detected differences of less than {} when comparing {} field component, therefore set as zero.'.format(threshold, fields[ID]))
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else:
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diffs[:,ID] = (np.abs(analytical[:,ID] - model[:,ID]) / max) * 100
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diffsum = (np.sum(np.abs(analytical[:,ID] - model[:,ID])) / np.sum(np.abs(analytical[:,ID]))) * 100
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print('Total differences in field component {}: {:.1f}%'.format(name, diffsum))
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# Plot model
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fig1, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(nrows=3, ncols=2, sharex=False, sharey='col', subplot_kw=dict(xlabel='Time [ns]'), num=modelfile + ' versus analytical solution', figsize=(20, 10), facecolor='w', edgecolor='w')
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ax1.plot(time, model[:,0],'r', lw=2, label='Ex')
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ax3.plot(time, model[:,1],'r', lw=2, label='Ey')
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ax5.plot(time, model[:,2],'r', lw=2, label='Ez')
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ax2.plot(time, model[:,3],'b', lw=2, label='Hx')
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ax4.plot(time, model[:,4],'b', lw=2, label='Hy')
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ax6.plot(time, model[:,5],'b', lw=2, label='Hz')
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# Set ylabels
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ylabels = ['$E_x$, field strength [V/m]', '$H_x$, field strength [A/m]', '$E_y$, field strength [V/m]', '$H_y$, field strength [A/m]', '$E_z$, field strength [V/m]', '$H_z$, field strength [A/m]']
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[ax.set_ylabel(ylabels[index]) for index, ax in enumerate(fig1.axes)]
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# Turn on grid
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[ax.grid() for ax in fig1.axes]
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# Add analytical solution and set legend
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for index, ax in enumerate(fig1.axes):
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if index in [0, 2, 4]:
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ax.plot(time, analytical[:,plotorder[index]], 'r', label='analytical', lw=2, ls='--')
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else:
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ax.plot(time, analytical[:,plotorder[index]], label='analytical', lw=2, ls='--')
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ax.set_xlim(0, time[-1])
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handles, existlabels = ax.get_legend_handles_labels()
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ax.legend(handles, ['Model', 'Analytical'])
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# Plots of differences
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fig2, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(nrows=3, ncols=2, sharex=False, sharey='col', subplot_kw=dict(xlabel='Time [ns]'), num='Deltas: ' + modelfile + ' versus analytical solution', figsize=(20, 10), facecolor='w', edgecolor='w')
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ax1.plot(time, diffs[:,0],'r', lw=2, label='Ex')
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ax3.plot(time, diffs[:,1],'r', lw=2, label='Ey')
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ax5.plot(time, diffs[:,2],'r', lw=2, label='Ez')
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ax2.plot(time, diffs[:,3],'b', lw=2, label='Hx')
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ax4.plot(time, diffs[:,4],'b', lw=2, label='Hy')
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ax6.plot(time, diffs[:,5],'b', lw=2, label='Hz')
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# Set ylabels
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ylabels = ['$E_x$', '$H_x$', '$E_y$', '$H_y$', '$E_z$', '$H_z$']
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ylabels = [ylabel + ', percentage difference [%]' for ylabel in ylabels]
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[ax.set_ylabel(ylabels[index]) for index, ax in enumerate(fig2.axes)]
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# Set axes limits and turn on grid
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[ax.grid() for ax in fig2.axes]
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[ax.set_xlim(0, time[-1]) for ax in fig2.axes]
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[ax.set_ylim(0, np.ceil(np.amax(np.abs(diffs)))) for ax in fig2.axes]
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# Show/print plots
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savename = os.path.abspath(os.path.dirname(modelfile)) + os.sep + os.path.splitext(os.path.split(modelfile)[1])[0] + '_vs_analytical'
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#fig1.savefig(savename + '.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
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#fig2.savefig(savename + '_diffs.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
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plt.show()
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