Updated name of module to better reflect functionality.

tools/plot_builtin_wave.py

@@ -0,0 +1,90 @@
+# Copyright (C) 2015: 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 <http://www.gnu.org/licenses/>.
+
+import os, argparse
+import numpy as np
+import matplotlib.pyplot as plt
+
+from gprMax.waveforms import Waveform
+
+
+"""Plot built-in waveforms that can be used for sources."""
+
+# Parse command line arguments
+parser = argparse.ArgumentParser(description='Plot built-in waveforms that can be used for sources.', usage='cd gprMax; python -m tools.plot_builtin_wave type amp freq timewindow dt')
+parser.add_argument('type', help='type of waveform, e.g. gaussian, ricker etc...')
+parser.add_argument('amp', type=float, help='amplitude of waveform')
+parser.add_argument('freq', type=float, help='centre frequency of waveform')
+parser.add_argument('timewindow', type=float, help='time window to view waveform')
+parser.add_argument('dt', type=float, help='time step to view waveform')
+parser.add_argument('-fft', action='store_true', default=False, help='plot FFT')
+args = parser.parse_args()
+
+w = Waveform()
+w.type = args.type
+w.amp = args.amp
+w.freq = args.freq
+timewindow = args.timewindow
+dt = args.dt
+
+time = np.arange(0, timewindow, dt)
+waveform = np.zeros(len(time))
+timeiter = np.nditer(time, flags=['c_index'])
+
+while not timeiter.finished:
+    waveform[timeiter.index] = w.calculate_value(timeiter[0], dt)
+    timeiter.iternext()
+
+if args.fft:
+    # Calculate frequency spectra of waveform
+    power = 20 * np.log10(np.abs(np.fft.fft(waveform))**2)
+    freqs = np.fft.fftfreq(power.size, d=dt)
+
+    # Shift powers so any spectra with negative DC component will start at zero
+    power -= np.amax(power)
+
+    # Set plotting range to 4 * centre frequency
+    pltrange = np.where(freqs > (4 * w.freq))[0][0]
+
+    fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, num=w.type, figsize=(20, 10), facecolor='w', edgecolor='w')
+    
+    # Plot waveform
+    ax1.plot(time, waveform, 'r', lw=2)
+    ax1.set_xlabel('Time [ns]')
+    ax1.set_ylabel('Amplitude')
+
+    # Plot frequency spectra
+    markerline, stemlines, baseline = ax2.stem(freqs[0:pltrange]/1e9, power[0:pltrange], '--')
+    plt.setp(stemlines, 'color', 'r')
+    plt.setp(markerline, 'markerfacecolor', 'r', 'markeredgecolor', 'r')
+    ax2.set_xlabel('Frequency [GHz]')
+    ax2.set_ylabel('Power [dB]')
+
+else:
+    fig, ax1 = plt.subplots(num=w.type, figsize=(20, 10), facecolor='w', edgecolor='w')
+
+    # Plot waveform
+    ax1.plot(time, waveform, 'r', lw=2)
+    ax1.set_xlabel('Time [ns]')
+    ax1.set_ylabel('Amplitude')
+
+[ax.grid() for ax in fig.axes] # Turn on grid
+plt.show()
+
+# Save a PDF of the figure
+fig.savefig(os.path.dirname(os.path.abspath(__file__)) + os.sep + w.type + '.png', dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)