publicImage/gprMax
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镜像自地址 https://gitee.com/sunhf/gprMax.git 已同步 2025-08-08 15:27:57 +08:00
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Added a pre-commit config file and reformatted all the files accordingly by using it.

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Sai-Suraj-27
2023-06-26 16:09:39 +05:30
父节点 c71e87e34f
当前提交 f9dd7f2420
共有 155 个文件被更改，包括 11383 次插入 和 8802 次删除
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113
toolboxes/Plotting/plot_source_wave.py
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@@ -25,7 +25,7 @@ import numpy as np
from gprMax.utilities.utilities import fft_power, round_value
from gprMax.waveforms import Waveform
logging.basicConfig(format='%(message)s', level=logging.INFO)
logging.basicConfig(format="%(message)s", level=logging.INFO)
def check_timewindow(timewindow, dt):
@@ -53,7 +53,7 @@ def check_timewindow(timewindow, dt):
if timewindow > 0:
iterations = round_value((timewindow / dt)) + 1
else:
logging.exception('Time window must have a value greater than zero')
logging.exception("Time window must have a value greater than zero")
raise ValueError
return timewindow, iterations
@@ -76,36 +76,41 @@ def mpl_plot(w, timewindow, dt, iterations, fft=False, save=False):
time = np.linspace(0, (iterations - 1) * dt, num=iterations)
waveform = np.zeros(len(time))
timeiter = np.nditer(time, flags=['c_index'])
timeiter = np.nditer(time, flags=["c_index"])
while not timeiter.finished:
waveform[timeiter.index] = w.calculate_value(timeiter[0], dt)
timeiter.iternext()
logging.info('Waveform characteristics...')
logging.info(f'Type: {w.type}')
logging.info(f'Maximum (absolute) amplitude: {np.max(np.abs(waveform)):g}')
logging.info("Waveform characteristics...")
logging.info(f"Type: {w.type}")
logging.info(f"Maximum (absolute) amplitude: {np.max(np.abs(waveform)):g}")
if w.freq and not w.type == 'gaussian' and not w.type == 'impulse':
logging.info(f'Centre frequency: {w.freq:g} Hz')
if w.freq and not w.type == "gaussian" and not w.type == "impulse":
logging.info(f"Centre frequency: {w.freq:g} Hz")
if (w.type == 'gaussian' or w.type == 'gaussiandot' or w.type == 'gaussiandotnorm'
or w.type == 'gaussianprime' or w.type == 'gaussiandoubleprime'):
if (
w.type == "gaussian"
or w.type == "gaussiandot"
or w.type == "gaussiandotnorm"
or w.type == "gaussianprime"
or w.type == "gaussiandoubleprime"
):
delay = 1 / w.freq
logging.info(f'Time to centre of pulse: {delay:g} s')
elif w.type == 'gaussiandotdot' or w.type == 'gaussiandotdotnorm' or w.type == 'ricker':
logging.info(f"Time to centre of pulse: {delay:g} s")
elif w.type == "gaussiandotdot" or w.type == "gaussiandotdotnorm" or w.type == "ricker":
delay = np.sqrt(2) / w.freq
logging.info(f'Time to centre of pulse: {delay:g} s')
logging.info(f"Time to centre of pulse: {delay:g} s")
logging.info(f'Time window: {timewindow:g} s ({iterations} iterations)')
logging.info(f'Time step: {dt:g} s')
logging.info(f"Time window: {timewindow:g} s ({iterations} iterations)")
logging.info(f"Time step: {dt:g} s")
if fft:
# FFT
freqs, power = fft_power(waveform, dt)
# Set plotting range to 4 times frequency at max power of waveform or
# 4 times the centre frequency
# 4 times the centre frequency
freqmaxpower = np.where(np.isclose(power, 0))[0][0]
if freqs[freqmaxpower] > w.freq:
pltrange = np.where(freqs > 4 * freqs[freqmaxpower])[0][0]
@@ -113,73 +118,66 @@ def mpl_plot(w, timewindow, dt, iterations, fft=False, save=False):
pltrange = np.where(freqs > 4 * w.freq)[0][0]
pltrange = np.s_[0:pltrange]
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, num=w.type,
figsize=(20, 10), facecolor='w',
edgecolor='w')
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 [s]')
ax1.set_ylabel('Amplitude')
ax1.plot(time, waveform, "r", lw=2)
ax1.set_xlabel("Time [s]")
ax1.set_ylabel("Amplitude")
# Plot frequency spectra
markerline, stemlines, baseline = ax2.stem(freqs[pltrange], power[pltrange],
'-.', use_line_collection=True)
plt.setp(baseline, 'linewidth', 0)
plt.setp(stemlines, 'color', 'r')
plt.setp(markerline, 'markerfacecolor', 'r', 'markeredgecolor', 'r')
ax2.plot(freqs[pltrange], power[pltrange], 'r', lw=2)
ax2.set_xlabel('Frequency [Hz]')
ax2.set_ylabel('Power [dB]')
markerline, stemlines, baseline = ax2.stem(freqs[pltrange], power[pltrange], "-.", use_line_collection=True)
plt.setp(baseline, "linewidth", 0)
plt.setp(stemlines, "color", "r")
plt.setp(markerline, "markerfacecolor", "r", "markeredgecolor", "r")
ax2.plot(freqs[pltrange], power[pltrange], "r", lw=2)
ax2.set_xlabel("Frequency [Hz]")
ax2.set_ylabel("Power [dB]")
else:
fig, ax1 = plt.subplots(num=w.type, figsize=(10, 10), facecolor='w',
edgecolor='w')
fig, ax1 = plt.subplots(num=w.type, figsize=(10, 10), facecolor="w", edgecolor="w")
# Plot waveform
ax1.plot(time, waveform, 'r', lw=2)
ax1.set_xlabel('Time [s]')
ax1.set_ylabel('Amplitude')
ax1.plot(time, waveform, "r", lw=2)
ax1.set_xlabel("Time [s]")
ax1.set_ylabel("Amplitude")
# Turn on grid
[ax.grid(which='both', axis='both', linestyle='-.') for ax in fig.axes]
[ax.grid(which="both", axis="both", linestyle="-.") for ax in fig.axes]
if save:
savefile = Path(__file__).parent / w.type
# Save a PDF of the figure
fig.savefig(savefile.with_suffix('.pdf'), dpi=None, format='pdf',
bbox_inches='tight', pad_inches=0.1)
fig.savefig(savefile.with_suffix(".pdf"), dpi=None, format="pdf", bbox_inches="tight", pad_inches=0.1)
# Save a PNG of the figure
fig.savefig(savefile.with_suffix('.png'), dpi=150, format='png',
bbox_inches='tight', pad_inches=0.1)
fig.savefig(savefile.with_suffix(".png"), dpi=150, format="png", bbox_inches="tight", pad_inches=0.1)
return plt
if __name__ == "__main__":
# Parse command line arguments
parser = argparse.ArgumentParser(description='Plot built-in waveforms that can be used for sources.',
usage='cd gprMax; python -m toolboxes.Plotting.plot_source_wave type amp freq timewindow dt')
parser.add_argument('type', help='type of waveform', choices=Waveform.types)
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', 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 of waveform')
parser.add_argument('-save', action='store_true', default=False,
help='save plot directly to file, i.e. do not display')
parser = argparse.ArgumentParser(
description="Plot built-in waveforms that can be used for sources.",
usage="cd gprMax; python -m toolboxes.Plotting.plot_source_wave type amp freq timewindow dt",
)
parser.add_argument("type", help="type of waveform", choices=Waveform.types)
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", 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 of waveform")
parser.add_argument(
"-save", action="store_true", default=False, help="save plot directly to file, i.e. do not display"
)
args = parser.parse_args()
# Check waveform parameters
if args.type.lower() not in Waveform.types:
logging.exception(f"The waveform must have one of the following types " +
f"{', '.join(Waveform.types)}")
logging.exception(f"The waveform must have one of the following types " + f"{', '.join(Waveform.types)}")
raise ValueError
if args.freq <= 0:
logging.exception('The waveform requires an excitation frequency value of ' +
'greater than zero')
logging.exception("The waveform requires an excitation frequency value of " + "greater than zero")
raise ValueError
# Create waveform instance
@@ -189,6 +187,5 @@ if __name__ == "__main__":
w.freq = args.freq
timewindow, iterations = check_timewindow(args.timewindow, args.dt)
plthandle = mpl_plot(w, timewindow, args.dt, iterations, fft=args.fft,
save=args.save)
plthandle = mpl_plot(w, timewindow, args.dt, iterations, fft=args.fft, save=args.save)
plthandle.show()