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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.
# fixed thanks to Daniel Jones - see blog and comments: http://mcld.co.uk/blog/blog.php?417
import numpy as np
import os, sys, glob
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from scikits.audiolab import Sndfile
from scikits.audiolab import Format
#########################################
# config
# this is the pattern to search for files.
globpattern = sys.argv[1] if len(sys.argv) > 1 else '/home/dan/Music/Rumour_Cubes/The_Narrow_State/*.wav'
framelen = 2048
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)
panmul = ((stereobins-1)/2) / panlimit
bintofreq = fs/framelen
#########################################
# functions
def analyse_file(audiopath):
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:
chunk = sf.read_frames(framelen, dtype=np.float32)
if len(chunk) != framelen:
print("Not read sufficient samples (%i) - returning." % (len(chunk)))
break
################################################################################
# NOTE: This is weird - why do I need to flip the data around to get it correct?
# Is this a bug in audiolab? I'm using scikits.audiolab-0.11.0 on ubuntu.
chunk = chunk.T.reshape((framelen, 2))
################################################################################
# uncomment this to force the data into pure-mono, for testing
#chunk[:,1] = chunk[:,0]
framespectrum = np.array([np.fft.fft(window * chunk[:,channel].flatten()) for channel in [1,0]])
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 # use pow rather than just 1? undecided.
except RuntimeError:
break
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:
print("Skipping a file due to ValueError (presumably wasn't stereo): %s" % matched)
continue
if bighisto == None:
bighisto = histo
else:
bighisto += histo
plot_histo(histo, "stereoscope.png")
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