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compute_indices.html
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compute_indices.html
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<html><head><title>Python: module compute_indices_object</title>
<meta charset="utf-8">
</head><body bgcolor="#f0f0f8">
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="heading">
<tr bgcolor="#7799ee">
<td valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong>compute_indices_object</strong></big></big> (version 0.2)</font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/Users/guyot/Documents/Workspaces/Python/Acoustic_Indices/compute_indices_object.py">/Users/guyot/Documents/Workspaces/Python/Acoustic_Indices/compute_indices_object.py</a></font></td></tr></table>
<p><tt>Set of functions to compute acoustic indices in the framework of Soundscape Ecology.<br>
<br>
Some features are inspired or ported from those proposed in:<br>
- seewave R package (<a href="http://rug.mnhn.fr/seewave/">http://rug.mnhn.fr/seewave/</a>) / Jerome Sueur, Thierry Aubin and Caroline Simonis<br>
- soundecology R package (<a href="http://cran.r-project.org/web/packages/soundecology/index.html">http://cran.r-project.org/web/packages/soundecology/index.html</a>) / Luis J. Villanueva-Rivera and Bryan C. Pijanowski<br>
<br>
This file use an object oriented type for audio files described in the file "acoustic_index.py".</tt></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
<td width="100%"><table width="100%" summary="list"><tr><td width="25%" valign=top><a href="numpy.html">numpy</a><br>
</td><td width="25%" valign=top><a href="scipy.signal.html">scipy.signal</a><br>
</td><td width="25%" valign=top></td><td width="25%" valign=top></td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Functions</strong></big></font></td></tr>
<tr><td bgcolor="#eeaa77"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt><a name="-compute_ACI"><strong>compute_ACI</strong></a>(spectro, j_bin)</dt><dd><tt>Compute the Acoustic Complexity Index from the spectrogram of an audio signal.<br>
<br>
Reference: Pieretti N, Farina A, Morri FD (2011) A new methodology to infer the singing activity of an avian community: the Acoustic Complexity Index (ACI). Ecological Indicators, 11, 868-873.<br>
<br>
Ported from the soundecology R package.<br>
<br>
spectro: the spectrogram of the audio signal<br>
j_bin: temporal size of the frame (in samples)</tt></dd></dl>
<dl><dt><a name="-compute_ADI"><strong>compute_ADI</strong></a>(spectro, freq_band_Hz, max_freq<font color="#909090">=10000</font>, db_threshold<font color="#909090">=-50</font>, freq_step<font color="#909090">=1000</font>)</dt><dd><tt>Compute Acoustic Diversity Index.<br>
<br>
spectro: spectrogram of the audio signal<br>
freq_band_Hz: frequency band (in Hertz)<br>
max_freq: the maximum frequency to consider (in Hertz)<br>
db_threshold: the minimum dB value to consider for the bins of the spectrogram<br>
freq_step: width of the frequency bands that are considered<br>
<br>
<br>
Ported from the soundecology R package.</tt></dd></dl>
<dl><dt><a name="-compute_AEI"><strong>compute_AEI</strong></a>(spectro, freq_band_Hz, max_freq<font color="#909090">=10000</font>, db_threshold<font color="#909090">=-50</font>, freq_step<font color="#909090">=1000</font>)</dt><dd><tt>Compute Acoustic Evenness Index of an audio signal.<br>
<br>
spectro: spectrogram of the audio signal<br>
freq_band_Hz: frequency band (in Hertz)<br>
max_freq: the maximum frequency to consider (in Hertz)<br>
db_threshold: the minimum dB value to consider for the bins of the spectrogram<br>
freq_step: width of the frequency bands that are considered<br>
<br>
Ported from the soundecology R package.</tt></dd></dl>
<dl><dt><a name="-compute_BI"><strong>compute_BI</strong></a>(spectro, frequencies, min_freq<font color="#909090">=2000</font>, max_freq<font color="#909090">=8000</font>)</dt><dd><tt>Compute the Bioacoustic Index from the spectrogram of an audio signal.<br>
In theis code, the Bioacoustic Index correspond to the area under the mean spectre (in dB) minus the minimum frequency value of this mean spectre.<br>
<br>
Reference: Boelman NT, Asner GP, Hart PJ, Martin RE. 2007. Multi-trophic invasion resistance in Hawaii: bioacoustics, field surveys, and airborne remote sensing. Ecological Applications 17: 2137-2144.<br>
<br>
spectro: the spectrogram of the audio signal<br>
min_freq: minimum frequency (in Hertz)<br>
max_freq: maximum frequency (in Hertz)<br>
<br>
Ported from the soundecology R package.</tt></dd></dl>
<dl><dt><a name="-compute_NDSI"><strong>compute_NDSI</strong></a>(file, windowLength<font color="#909090">=1024</font>, anthrophony<font color="#909090">=[1000, 2000]</font>, biophony<font color="#909090">=[2000, 11000]</font>)</dt><dd><tt>Compute Normalized Difference Sound Index from an audio signal.<br>
This function compute an estimate power spectral density using Welch's method.<br>
<br>
Reference: Kasten, Eric P., Stuart H. Gage, Jordan Fox, and Wooyeong Joo. 2012. The Remote Environ- mental Assessment Laboratory's Acoustic Library: An Archive for Studying Soundscape Ecology. Ecological Informatics 12: 50-67.<br>
<br>
windowLength: the length of the window for the Welch's method.<br>
anthrophony: list of two values containing the minimum and maximum frequencies (in Hertz) for antrophony.<br>
biophony: list of two values containing the minimum and maximum frequencies (in Hertz) for biophony.<br>
<br>
Inspired by the seewave R package, the soundecology R package and the original matlab code from the authors.</tt></dd></dl>
<dl><dt><a name="-compute_SH"><strong>compute_SH</strong></a>(spectro)</dt><dd><tt>Compute Spectral Entropy of Shannon from the spectrogram of an audio signal.<br>
<br>
spectro: the spectrogram of the audio signal<br>
<br>
Ported from the seewave R package.</tt></dd></dl>
<dl><dt><a name="-compute_TH"><strong>compute_TH</strong></a>(file, integer<font color="#909090">=True</font>)</dt><dd><tt>Compute Temporal Entropy of Shannon from an audio signal.<br>
<br>
file: an instance of the AudioFile class.<br>
integer: if set as True, the Temporal Entropy will be compute on the Integer values of the signal. If not, the signal will be set between -1 and 1.<br>
<br>
Ported from the seewave R package.</tt></dd></dl>
<dl><dt><a name="-compute_rms_energy"><strong>compute_rms_energy</strong></a>(file, windowLength<font color="#909090">=512</font>, windowHop<font color="#909090">=256</font>, integer<font color="#909090">=False</font>)</dt><dd><tt>Compute the RMS short time energy.<br>
<br>
file: an instance of the AudioFile class.<br>
windowLength: size of the sliding window (samples)<br>
windowHop: size of the lag window (samples)<br>
integer: if set as True, the Temporal Entropy will be compute on the Integer values of the signal. If not, the signal will be set between -1 and 1.<br>
<br>
return: a list of values (rms energy for each window)</tt></dd></dl>
<dl><dt><a name="-compute_spectral_centroid"><strong>compute_spectral_centroid</strong></a>(spectro, frequencies)</dt><dd><tt>Compute the spectral centroid of an audio signal from its spectrogram</tt></dd></dl>
<dl><dt><a name="-compute_spectrogram"><strong>compute_spectrogram</strong></a>(file, windowLength<font color="#909090">=512</font>, windowHop<font color="#909090">=256</font>, scale_audio<font color="#909090">=True</font>, square<font color="#909090">=True</font>, windowType<font color="#909090">='hanning'</font>, centered<font color="#909090">=False</font>, normalized<font color="#909090">=False</font>)</dt><dd><tt>Compute a spectrogram of an audio signal.<br>
Return a list of list of values as the spectrogram, and a list of frequencies.<br>
<br>
Keyword arguments:<br>
file -- the real part (default 0.0)<br>
<br>
Parameters:<br>
@param sig: the audio signal samples (read for example from a .wav with scipy.io.wavfile)<br>
wLen: length of the fft window (in samples)<br>
wHop: hop size of the fft window (in samples)<br>
scale_audio: if set as True, the signal samples are scale between -1 and 1 (as the audio convention). If false the signal samples remains Integers (as output from scipy.io.wavfile)<br>
square: if set as True, the spectrogram is computed as the square of the magnitude of the fft. If not, it is the magnitude of the fft.<br>
hamming: if set as True, the spectrogram use a correlation with a hamming window.<br>
centered: if set as true, each resulting fft is centered on the corresponding sliding window<br>
normalized: if set as true, divide all values by the maximum value</tt></dd></dl>
<dl><dt><a name="-compute_zcr"><strong>compute_zcr</strong></a>(file, windowLength<font color="#909090">=512</font>, windowHop<font color="#909090">=256</font>)</dt><dd><tt>Compute the Zero Crossing Rate of an audio signal.<br>
<br>
file: an instance of the AudioFile class.<br>
windowLength: size of the sliding window (samples)<br>
windowHop: size of the lag window (samples)<br>
<br>
return: a list of values (number of zero crossing for each window)</tt></dd></dl>
<dl><dt><a name="-gini"><strong>gini</strong></a>(values)</dt><dd><tt>Compute the Gini index of values.<br>
<br>
values: a list of values<br>
<br>
Inspired by <a href="http://mathworld.wolfram.com/GiniCoefficient.html">http://mathworld.wolfram.com/GiniCoefficient.html</a> and <a href="http://en.wikipedia.org/wiki/Gini_coefficient">http://en.wikipedia.org/wiki/Gini_coefficient</a></tt></dd></dl>
</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Data</strong></big></font></td></tr>
<tr><td bgcolor="#55aa55"><tt> </tt></td><td> </td>
<td width="100%"><strong>__author__</strong> = 'Patrice Guyot'<br>
<strong>__credits__</strong> = ['Patrice Guyot', 'Alice Eldridge', 'Mika Peck']<br>
<strong>__email__</strong> = ['guyot.patrice@gmail.com', 'alicee@sussex.ac.uk', 'm.r.peck@sussex.ac.uk']<br>
<strong>__status__</strong> = 'Development'<br>
<strong>__version__</strong> = '0.2'</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#7799ee">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Author</strong></big></font></td></tr>
<tr><td bgcolor="#7799ee"><tt> </tt></td><td> </td>
<td width="100%">Patrice Guyot</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#7799ee">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Credits</strong></big></font></td></tr>
<tr><td bgcolor="#7799ee"><tt> </tt></td><td> </td>
<td width="100%">['Patrice Guyot', 'Alice Eldridge', 'Mika Peck']</td></tr></table>
</body></html>