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#!/usr/bin/env python | |
# a script to analyse a set of files to illustrate how the panning tends to vary by frequency, via a simple FFT analysis. | |
# REQUIREMENTS: | |
# - Python (was tested on 2.7) | |
# - Python modules: | |
# - numpy | |
# - scikits.audiolab | |
# - matplotlib | |
# written by Dan Stowell 2014. public domain. | |
# modified by Daniel Jones with fixed FFT and wave for audio reading | |
# comments: http://mcld.co.uk/blog/blog.php?417 | |
import sys | |
import wave, struct | |
import numpy as np | |
import os, glob | |
import matplotlib.pyplot as plt | |
import matplotlib.cm as cm | |
from scikits.audiolab import Sndfile | |
from scikits.audiolab import Format | |
USE_WAVE = True | |
USE_STEREO_FFT = True | |
######################################### | |
# config | |
# this is the pattern to search for files. | |
globpattern = sys.argv[1] if len(sys.argv) > 1 else 'bette.1024.mono.wav' | |
framelen = 1024 | |
fs = 44100 | |
stereobins = 41 # odd number, we want to have a central bin | |
panlimit = 10.0 # +- extreme of the values we expect generally | |
# derived config | |
window = np.hamming(framelen) | |
window = np.vstack((window, window)).T | |
panmul = ((stereobins-1)/2) / panlimit | |
bintofreq = fs/framelen | |
######################################### | |
# functions | |
def analyse_file(audiopath): | |
print "opening file %s" % audiopath | |
if USE_WAVE: | |
fd = wave.open(file(audiopath)) | |
else: | |
sf = Sndfile(audiopath, "r") | |
if (sf.channels != 2): | |
raise ValueError("non-stereo file: %i channels." % sf.channels) | |
if sf.samplerate != fs: | |
raise ValueError("wanted sample rate %g - got %g." % (fs, sf.samplerate)) | |
histo = np.zeros((framelen/2, stereobins)) | |
while(True): | |
try: | |
if USE_WAVE: | |
frames = fd.readframes(framelen) | |
if len(frames) < framelen * 4: | |
break | |
# unpack int16 to float32 | |
chunk = np.array([ struct.unpack("<hh", frames[n*4:(n+1)*4]) for n in range(1024) ]) / 32768.0 | |
else: | |
# appears to give false results when tested with mono files... | |
chunk = sf.read_frames(framelen, dtype=np.float32) | |
if len(chunk) != framelen: | |
print("Not read sufficient samples (%i) - returning." % (len(chunk))) | |
break | |
# uncomment to test with mono input by assigning right channel to left | |
# chunk[:, 0] = chunk[:, 1] | |
if USE_STEREO_FFT: | |
# split our time series into two spectra and analyse separately | |
specL = np.fft.fft(window[:, 0] * chunk[:, 0]) | |
powspecL = np.abs(specL[:framelen/2]) ** 2 | |
powspecL = np.maximum(1e-3, powspecL) | |
specR = np.fft.fft(window[:, 1] * chunk[:, 1]) | |
powspecR = np.abs(specR[:framelen/2]) ** 2 | |
powspecR = np.maximum(1e-3, powspecR) | |
panpos = np.clip(np.log(powspecR / powspecL), -panlimit, panlimit) | |
else: | |
# incorrect code for stereo FFT | |
framespectrum = np.fft.fft(window * chunk) | |
powspec = np.maximum(1e-3, abs(framespectrum[:framelen/2]) ** 2) | |
panpos = np.clip(np.log(powspec[:, 0] / powspec[:, 1]), -panlimit, panlimit) | |
histo[range(len(panpos)), map(int, (panpos + panlimit) * panmul)] += 1 | |
except RuntimeError: | |
break | |
if not USE_WAVE: | |
sf.close() | |
return histo | |
def plot_histo(histo, plotpath): | |
histo = np.log(histo + 1) # log-scale the results | |
plt.imshow(histo, origin='lower', interpolation='nearest', aspect='auto', cmap=cm.hot) | |
plt.xlabel("Pan pos", fontsize='small') | |
plt.ylabel("Frequency (kHz)", fontsize='small') | |
plt.xticks([(stereobins-1)/2], ['0'], fontsize='small') | |
yticks = np.arange(0, histo.shape[0], histo.shape[0]/10) | |
plt.yticks(yticks, np.round(yticks * bintofreq * 0.001), fontsize='small') | |
plt.title("Histogram of pan positions per frequency", fontsize='small') | |
plt.savefig(plotpath) | |
plt.clf() | |
######################################### | |
# Let's go | |
if __name__ == '__main__': | |
bighisto = None | |
print("Searching for files matching '%s'" % globpattern) | |
for matched in glob.iglob(globpattern): | |
try: | |
histo = analyse_file(matched) | |
print("Analysed: %s" % matched) | |
except ValueError, e: | |
print("Skipping a file due to ValueError (presumably wasn't stereo): %s, %s" % (matched, e)) | |
continue | |
if bighisto == None: | |
bighisto = histo | |
else: | |
bighisto += histo | |
plot_histo(histo, "stereoscope.png") |
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