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Plot Discrete Wavelet Transform Coefficients and Transmitted Energy signal feature #264

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Plot Discrete Wavelet Transform Coefficients and Transmitted Energy signal feature #264

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7647ceb
Add plot Discrete Wavelet Transform Coefficients
nrmarinho Jul 13, 2023
4aad1b6
Add Plot Discrete Wavelet Transform Coefficients
nrmarinho Jul 13, 2023
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35 changes: 35 additions & 0 deletions acoustics/imaging.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,3 +325,38 @@ def _set_separator(ticklabels, separator):
decimal_number_format = item.replace('.', separator)
bands_sep.append(decimal_number_format)
return bands_sep

def plotDWTcoeff(signal,wavelet,fs):
"""
Plot Discrete Wavelet Transform Coefficients (Level 1)

:param signal: signal
:param fs: sample frequency
:param fwavelet : Wavelet to use in the transform

"""
[cA, cD] = pywt.wavedec(signal, wavelet, level= 1)

L = len(signal);
t= np.arange(0,(len(signal))/fs, 1/fs)
plt.figure(figsize=(30, 20));

plt.subplot(3, 1, 1)
plt.plot(t, signal, color='k');
plt.xlabel('Time');
plt.ylabel('S');
plt.title('Original Signal');

plt.subplot(3, 1, 2)
plt.plot(cA, color='r');
plt.xlabel('Samples');
plt.ylabel('cA');
plt.title('Approximation Coeff. (cA)');

plt.subplot(3, 1, 3)
plt.plot(cD, color='g');
plt.xlabel('Samples');
plt.ylabel('cD');
plt.title('Detailed Coeff. (cD)');

plt.show()
16 changes: 16 additions & 0 deletions acoustics/signal.py
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Expand Up @@ -80,6 +80,7 @@
import numpy as np
from scipy.sparse import spdiags
from scipy.signal import butter, lfilter, freqz, filtfilt, sosfilt
from scipy.integrate import simpson

import acoustics.octave
#from acoustics.octave import REFERENCE
Expand Down Expand Up @@ -1283,6 +1284,21 @@ def linear_phase(ntaps, steepness=1):
return np.exp(-1j * 2. * np.pi * f * alpha)



def transmitted_energy(signal, fs):
"""Compute the integration over time of the amplitude envelope in a time-domain input signal

:param signal: signal
:param fs: sample frequency

The transmitted energy is the signal feature used to compare the signal response to different impact energies.
"""
analytic_signal= hilbert(signal)
amplitude_envelope = np.abs(analytic_signal)
area = simpson(amplitude_envelope, dx=1/fs)
return area


__all__ = [
'bandpass',
'bandpass_frequencies',
Expand Down