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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-07 04:56:51 +08:00
Added FFT function (uses np.fft.fft) to utilities module, to avoid repeating same code in several modules.
这个提交包含在:
@@ -30,6 +30,7 @@ from gprMax.constants import floattype
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from gprMax.constants import complextype
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from gprMax.materials import Material
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from gprMax.pml import PML
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from gprMax.utilities import fft_power
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from gprMax.utilities import round_value
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@@ -234,45 +235,32 @@ def dispersion_analysis(G):
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else:
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# User-defined waveform
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if waveform.type == 'user':
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waveformvalues = waveform.uservalues
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iterations = G.iterations
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# Built-in waveform
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else:
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# Time to analyse waveform - 4*pulse_width as using entire
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# time window can result in demanding FFT
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waveform.calculate_coefficients()
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time = np.arange(0, 4 * waveform.chi, G.dt)
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waveformvalues = np.zeros(len(time))
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timeiter = np.nditer(time, flags=['c_index'])
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iterations = round_value(4 * waveform.chi / G.dt)
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if iterations > G.iterations:
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iterations = G.iterations
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while not timeiter.finished:
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waveformvalues[timeiter.index] = waveform.calculate_value(timeiter[0], G.dt)
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timeiter.iternext()
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waveformvalues = np.zeros(G.iterations)
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for iteration in range(G.iterations):
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waveformvalues[iteration] = waveform.calculate_value(iteration * G.dt, G.dt)
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# Ensure source waveform is not being overly truncated before attempting any FFT
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if np.abs(waveformvalues[-1]) < np.abs(np.amax(waveformvalues)) / 100:
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# Calculate magnitude of frequency spectra of waveform
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mag = np.abs(np.fft.fft(waveformvalues))**2
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# Calculate power (ignore warning from taking a log of any zero values)
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with np.errstate(divide='ignore'):
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power = 10 * np.log10(mag)
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# Replace any NaNs or Infs from zero division
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power[np.invert(np.isfinite(power))] = 0
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# Frequency bins
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freqs = np.fft.fftfreq(power.size, d=G.dt)
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# Shift powers so that frequency with maximum power is at zero decibels
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power -= np.amax(power)
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# FFT
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freqs, power = fft_power(waveformvalues, G.dt)
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# Get frequency for max power
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freqmaxpower = np.where(np.isclose(power[1::], np.amax(power[1::])))[0][0]
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freqmaxpower = np.where(power == 0)[0][0]
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# Set maximum frequency to a threshold drop from maximum power, ignoring DC value
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try:
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freq = np.where((np.amax(power[freqmaxpower::]) - power[freqmaxpower::]) > G.highestfreqthres)[0][0] + 1
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results['maxfreq'].append(freqs[freq])
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freqthres = np.where(power[freqmaxpower:] < -G.highestfreqthres)[0][0]
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results['maxfreq'].append(freqs[freqthres])
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except:
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results['error'] = 'unable to calculate maximum power from waveform, most likely due to undersampling.'
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@@ -138,6 +138,35 @@ def round32(value):
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return int(32 * np.ceil(float(value) / 32))
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def fft_power(waveform, dt):
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"""Calculate a FFT of the given waveform of amplitude values;
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converted to decibels and shifted so that maximum power is 0dB
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Args:
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waveform (ndarray): time domain waveform
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dt (float): time step
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Returns:
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freqs (ndarray): frequency bins
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power (ndarray): power
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"""
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# Calculate magnitude of frequency spectra of waveform (ignore warning from taking a log of any zero values)
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with np.errstate(divide='ignore'): #
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power = 10 * np.log10(np.abs(np.fft.fft(waveform))**2)
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# Replace any NaNs or Infs from zero division
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power[np.invert(np.isfinite(power))] = 0
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# Frequency bins
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freqs = np.fft.fftfreq(power.size, d=dt)
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# Shift powers so that frequency with maximum power is at zero decibels
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power -= np.amax(power)
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return freqs, power
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def human_size(size, a_kilobyte_is_1024_bytes=False):
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"""Convert a file size to human-readable form.
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@@ -27,6 +27,7 @@ import matplotlib.gridspec as gridspec
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from gprMax.exceptions import CmdInputError
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from gprMax.receivers import Rx
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from gprMax.utilities import fft_power
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def mpl_plot(filename, outputs=Rx.defaultoutputs, fft=False):
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@@ -83,22 +84,17 @@ def mpl_plot(filename, outputs=Rx.defaultoutputs, fft=False):
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# Plotting if FFT required
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if fft:
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# Calculate magnitude of frequency spectra of waveform (ignore warning from taking a log of any zero values)
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with np.errstate(divide='ignore'):
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power = 10 * np.log10(np.abs(np.fft.fft(outputdata))**2)
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# Replace any NaNs or Infs from zero division
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power[np.invert(np.isfinite(power))] = 0
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# FFT
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freqs, power = fft_power(outputdata, dt)
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freqmaxpower = np.where(power == 0)[0][0]
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# Frequency bins
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freqs = np.fft.fftfreq(power.size, d=dt)
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# Set plotting range to -60dB from maximum power or 4 times
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# frequency at maximum power
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try:
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pltrange = np.where(power[freqmaxpower:] < -60)[0][0] + freqmaxpower + 1
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except:
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pltrange = freqmaxpower * 4
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# Shift powers so that frequency with maximum power is at zero decibels
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power -= np.amax(power)
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# Set plotting range to -60dB from maximum power
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pltrange = np.where((np.amax(power[1::]) - power[1::]) > 60)[0][0] + 1
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# To a maximum frequency
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# pltrange = np.where(freqs > 2e9)[0][0]
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pltrange = np.s_[0:pltrange]
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# Plot time history of output component
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@@ -24,6 +24,7 @@ import numpy as np
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import matplotlib.pyplot as plt
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from gprMax.exceptions import CmdInputError
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from gprMax.utilities import fft_power
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from gprMax.utilities import round_value
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from gprMax.waveforms import Waveform
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@@ -83,12 +84,7 @@ def mpl_plot(w, timewindow, dt, iterations, fft=False):
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print('Waveform characteristics...')
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print('Type: {}'.format(w.type))
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if w.type == 'user':
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waveform = w.uservalues
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w.amp = np.max(np.abs(waveform))
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print('Maximum amplitude: {:g}'.format(w.amp))
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print('Maximum (absolute) amplitude: {:g}'.format(np.max(np.abs(waveform))))
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if w.freq and not w.type == 'gaussian':
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print('Centre frequency: {:g} Hz'.format(w.freq))
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@@ -100,43 +96,19 @@ def mpl_plot(w, timewindow, dt, iterations, fft=False):
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delay = np.sqrt(2) / w.freq
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print('Time to centre of pulse: {:g} s'.format(delay))
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# Calculate pulse width for gaussian
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if w.type == 'gaussian':
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powerdrop = -3 # dB
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with np.errstate(divide='ignore'): # Ignore warning from taking a log of any zero values
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startpower = 10 * np.log10(waveform / np.amax(waveform))
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stopower = 10 * np.log10(waveform[start:] / np.amax(waveform))
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# Replace any NaNs or Infs from zero division
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startpower[np.invert(np.isfinite(startpower))] = 0
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stoppower[np.invert(np.isfinite(stoppower))] = 0
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start = np.where(startpower > powerdrop)[0][0]
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stop = np.where(stoppower < powerdrop)[0][0] + start
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print('Pulse width at {:d}dB, i.e. full width at half maximum (FWHM): {:g} s'.format(powerdrop, time[stop] - time[start]))
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print('Time window: {:g} s ({} iterations)'.format(timewindow, iterations))
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print('Time step: {:g} s'.format(dt))
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if fft:
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# Calculate magnitude of frequency spectra of waveform (ignore warning from taking a log of any zero values)
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with np.errstate(divide='ignore'): #
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power = 10 * np.log10(np.abs(np.fft.fft(waveform))**2)
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# FFT
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freqs, power = fft_power(waveform, dt)
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# Replace any NaNs or Infs from zero division
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power[np.invert(np.isfinite(power))] = 0
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# Frequency bins
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freqs = np.fft.fftfreq(power.size, d=dt)
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# Shift powers so that frequency with maximum power is at zero decibels
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power -= np.amax(power)
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if w.type == 'user':
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freqmaxpower = np.where(np.isclose(power[1::], np.amax(power[1::])))[0][0]
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w.freq = freqs[freqmaxpower]
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# Set plotting range to 4 times centre frequency of waveform
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# Set plotting range to 4 times frequency at max power of waveform or
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# 4 times the centre frequency
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freqmaxpower = np.where(power == 0)[0][0]
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if freqs[freqmaxpower] > w.freq:
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pltrange = np.where(freqs > 4 * freqs[freqmaxpower])[0][0]
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else:
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pltrange = np.where(freqs > 4 * w.freq)[0][0]
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pltrange = np.s_[0:pltrange]
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