你已经派生过 gprMax
镜像自地址
https://gitee.com/sunhf/gprMax.git
已同步 2025-08-07 04:56:51 +08:00
78 行
2.9 KiB
Python
78 行
2.9 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 os, argparse
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import numpy as np
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import matplotlib.pyplot as plt
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from gprMax.waveforms import Waveform
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"""Plot waveforms that can be used for sources."""
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# Parse command line arguments
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parser = argparse.ArgumentParser(description='Plot waveforms that can be used for sources.', usage='cd gprMax; python -m tools.plot_waveform type amp freq timewindow dt')
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parser.add_argument('type', help='type of waveform, e.g. gaussian, ricker etc...')
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parser.add_argument('amp', type=float, help='amplitude of waveform')
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parser.add_argument('freq', type=float, help='centre frequency of waveform')
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parser.add_argument('timewindow', type=float, help='time window to view waveform')
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parser.add_argument('dt', type=float, help='time step to view waveform')
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args = parser.parse_args()
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w = Waveform()
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w.type = args.type
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w.amp = args.amp
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w.freq = args.freq
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timewindow = args.timewindow
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dt = args.dt
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time = np.arange(0, timewindow, dt)
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waveform = np.zeros(len(time))
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timeiter = np.nditer(time, flags=['c_index'])
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while not timeiter.finished:
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waveform[timeiter.index] = w.calculate_value(timeiter[0], dt)
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timeiter.iternext()
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# Calculate frequency spectra of waveform
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fs = 1/dt
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power = 20*np.log10(np.abs(np.fft.rfft(waveform)))
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f = np.linspace(0, fs/2, len(power))
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# Shift powers so any spectra with negative DC component will start at zero
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power -= np.amax(power)
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# Set plotting range to 4 * centre frequency
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pltrange = np.where(f > (4 * w.freq))[0][0]
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# Plot waveform
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fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, num=w.type, figsize=(20, 10), facecolor='w', edgecolor='w')
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ax1.plot(time, waveform,'r', lw=2)
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ax1.set_xlabel('Time [ns]')
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ax1.set_ylabel('Amplitude')
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[label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65 )) for label in ax1.get_xticklabels() + ax1.get_yticklabels()]
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# Plot frequency spectra
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ax2.stem(f[0:pltrange]/1e9, power[0:pltrange],'b', lw=2)
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ax2.set_xlabel('Frequency [GHz]')
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ax2.set_ylabel('Power [dB]')
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[ax.grid() for ax in fig.axes] # Turn on grid
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plt.show()
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# Save a PDF of the figure
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#fig.savefig(os.path.dirname(os.path.abspath(__file__)) + os.sep + w.type + '.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1) |