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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-06 12:36:51 +08:00
Overhauled to simplify.
这个提交包含在：
Craig Warren
@@ -16,109 +16,113 @@
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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 sys, os, argparse
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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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import matplotlib.gridspec as gridspec
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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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"""Plots a comparison of analytical solutions and given simulated output."""
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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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# Parse command line arguments
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parser = argparse.ArgumentParser(description='Plots a comparison of analytical solutions and given simulated output.', usage='cd gprMax; python -m tests.test_compare_analytical modelfile')
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parser.add_argument('modelfile', help='name of model output file including path')
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args = parser.parse_args()
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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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f = h5py.File(args.modelfile, 'r')
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path = '/rxs/rx1/'
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availablecomponents = list(f[path].keys())
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floattype = f[path + availablecomponents[0]].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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time = np.linspace(0, 1, iterations)
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time *= (iterations * dt)
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rxpos = f[path].attrs['Position']
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txpos = f['/srcs/src1/'].attrs['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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model = np.zeros((iterations, len(availablecomponents)), dtype=floattype)
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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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analytical = hertzian_dipole_fs(iterations, dt, dxdydz, rxposrelative)
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# Differences
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# Read modelled fields and calculate 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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diffs = np.zeros((iterations, len(availablecomponents)), dtype=floattype)
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for index in range(len(availablecomponents)):
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model[:,index] = f[path + availablecomponents[index]][:]
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max = np.amax(np.abs(analytical[:,index]))
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if max < threshold:
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diffs[:,ID] = 0
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diffs[:,index] = 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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print('Detected differences of less than threshold {}, when comparing {} field component, therefore set as zero.'.format(threshold, availablecomponents[index]))
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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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diffs[:,index] = (np.abs(analytical[:,index] - model[:,index]) / max) * 100
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diffsum = (np.sum(np.abs(analytical[:,index] - model[:,index])) / np.sum(np.abs(analytical[:,index]))) * 100
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print('Total differences in field component {}: {:.1f}%'.format(availablecomponents[index], 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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f.close()
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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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# Plot modelled and analytical solutions
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fig1, ax = plt.subplots(subplot_kw=dict(xlabel='Time [s]'), num=args.modelfile + ' versus analytical solution', figsize=(20, 10), facecolor='w', edgecolor='w')
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gs1 = gridspec.GridSpec(3, 2, hspace=0.3, wspace=0.3)
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for index in range(len(availablecomponents)):
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i = int(index % 3)
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j = int((index - i) / 3 % 2)
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ax = plt.subplot(gs1[i, j])
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line1, = ax.plot(time, model[:,index],'r', lw=2, label='Model')
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line2, = ax.plot(time, analytical[:,index],'r', lw=2, ls='--', label='Analytical')
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ax.set_ylim(1.1 * np.amin(np.amin(model[:, 0:3], axis=1)), 1.1 * np.amax(np.amax(model[:, 0:3], axis=1)))
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if index > 2:
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plt.setp(line1, color='g')
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plt.setp(line2, color='g')
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ax.set_ylim(1.1 * np.amin(np.amin(model[:, 3:6], axis=1)), 1.1 * np.amax(np.amax(model[:, 3:6], axis=1)))
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ax.set_xlim(0, time[-1])
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ax.grid()
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ax.legend()
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# Set axes labels, limits and turn on grid
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ylabels = ['Ex, field strength [V/m]', 'Ey, field strength [V/m]', 'Ez, field strength [V/m]', 'Hx, field strength [A/m]', 'Hy, field strength [A/m]', 'Hz, 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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# Plot differences of modelled and analytical solutions
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fig2, ax = plt.subplots(subplot_kw=dict(xlabel='Time [s]'), num=args.modelfile + ' versus analytical solution differences', figsize=(20, 10), facecolor='w', edgecolor='w')
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gs2 = gridspec.GridSpec(3, 2, hspace=0.3, wspace=0.3)
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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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for index in range(len(availablecomponents)):
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i = int(index % 3)
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j = int((index - i) / 3 % 2)
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ax = plt.subplot(gs2[i, j])
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line1, = ax.plot(time, diffs[:, index],'r', lw=2)
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ax.set_ylim(0, 1.1 * np.amax(np.amax(diffs[:, 0:3], axis=1)))
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if index > 2:
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plt.setp(line1, color='g')
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ax.set_ylim(0, 1.1 * np.amax(np.amax(diffs[:, 3:6], axis=1)))
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ax.set_ylim(0, 2)
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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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ax.grid()
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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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# Set axes labels, limits and turn on grid
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ylabels = ['Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz']
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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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# Save a PDF/PNG of the figure
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savename = os.path.abspath(os.path.dirname(args.modelfile)) + os.sep + os.path.splitext(os.path.split(args.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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fig1.savefig(savename + '.png', dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)
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fig2.savefig(savename + '_diffs.png', dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)
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plt.show()
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