ref: 6ff6d18ce7790aa8adc8889923f13eafc8414ab6
parent: e5afd475bc606e5c78a5dda82863bc412b6580f0
author: Paul Brossier <piem@piem.org>
date: Fri Mar 22 07:56:15 EDT 2013
python/demos/demo_{mel-energy,mfcc,specdesc}.py: use set_xlabels_sample2time
--- a/python/demos/demo_mel-energy.py
+++ b/python/demos/demo_mel-energy.py
@@ -3,7 +3,6 @@
import sys
from aubio import fvec, source, pvoc, filterbank
from numpy import vstack, zeros
-from demo_waveform_plot import set_xlabels_sample2time
win_s = 512 # fft size
hop_s = win_s / 4 # hop size
@@ -45,6 +44,7 @@
print "done computing, now plotting"
import matplotlib.pyplot as plt
from demo_waveform_plot import get_waveform_plot
+ from demo_waveform_plot import set_xlabels_sample2time
fig = plt.figure()
plt.rc('lines',linewidth='.8')
wave = plt.axes([0.1, 0.75, 0.8, 0.19])
--- a/python/demos/demo_mfcc.py
+++ b/python/demos/demo_mfcc.py
@@ -3,7 +3,6 @@
import sys
from aubio import source, pvoc, mfcc
from numpy import array, vstack, zeros
-from demo_waveform_plot import set_xlabels_sample2time
win_s = 512 # fft size
hop_s = win_s / 4 # hop size
@@ -41,6 +40,7 @@
# do plotting
from numpy import arange
from demo_waveform_plot import get_waveform_plot
+from demo_waveform_plot import set_xlabels_sample2time
import matplotlib.pyplot as plt
fig = plt.figure()
--- a/python/demos/demo_specdesc.py
+++ b/python/demos/demo_specdesc.py
@@ -21,9 +21,9 @@
pv = pvoc(win_s, hop_s)
-methods = ['default', 'energy', 'hfc', 'complex', 'phase', 'specdiff', 'kl', 'mkl',
- 'specflux', 'centroid', 'spread', 'skewness', 'kurtosis', 'slope', 'decrease',
- 'rolloff', ]
+methods = ['default', 'energy', 'hfc', 'complex', 'phase', 'specdiff', 'kl',
+ 'mkl', 'specflux', 'centroid', 'slope', 'rolloff', 'spread', 'skewness',
+ 'kurtosis', 'decrease',]
all_descs = {}
o = {}
@@ -39,12 +39,12 @@
while True:
samples, read = s()
fftgrain = pv(samples)
- print "%f" % ( total_frames / float(samplerate) ),
+ #print "%f" % ( total_frames / float(samplerate) ),
for method in methods:
specdesc_val = o[method](fftgrain)[0]
all_descs[method] = hstack ( [all_descs[method], specdesc_val] )
- print "%f" % specdesc_val,
+ #print "%f" % specdesc_val,
total_frames += read
if read < hop_s: break
@@ -52,10 +52,11 @@
print "done computing, now plotting"
import matplotlib.pyplot as plt
from demo_waveform_plot import get_waveform_plot
+ from demo_waveform_plot import set_xlabels_sample2time
fig = plt.figure()
plt.rc('lines',linewidth='.8')
wave = plt.axes([0.1, 0.75, 0.8, 0.19])
- get_waveform_plot(filename, samplerate, ax = wave )
+ get_waveform_plot(filename, samplerate, block_size = hop_s, ax = wave )
wave.yaxis.set_visible(False)
wave.xaxis.set_visible(False)
@@ -73,12 +74,7 @@
ax.annotate(method, xy=(-10, 10), xycoords='axes points',
horizontalalignment='right', verticalalignment='bottom',
)
- if all_desc_times[-1] / float(samplerate) > 60:
- plt.xlabel('time (mm:ss)')
- ax.set_xticklabels([ "%02d:%02d" % (t/float(samplerate)/60, (t/float(samplerate))%60) for t in ax.get_xticks()[:-1]], rotation = 50)
- else:
- plt.xlabel('time (ss.mm)')
- ax.set_xticklabels([ "%02d.%02d" % (t/float(samplerate), 100*((t/float(samplerate))%1) ) for t in ax.get_xticks()[:-1]], rotation = 50)
+ set_xlabels_sample2time(ax, all_desc_times[-1], samplerate)
#plt.ylabel('spectral descriptor value')
ax.xaxis.set_visible(True)
plt.show()