def mkgraphs(wname, prefix):
print wname
wav, wp = utilities.get_wav(wname)
sp = 1.0 / wp[2]
timevals = numpy.arange(0, wp[3] * sp, sp)
part = 4000
pylab.close()
pylab.plot(timevals[:part], wav[:part])
pylab.xlabel('Time (s)')
pylab.ylabel('Relative amplitude')
pylab.savefig('%stime.png' % prefix)
PSD_NFFT = 2**17
(pxx, fxx) = utilities.get_psd(wav, wp[2], PSD_NFFT)
part = 1700
lxx = 10 * numpy.log10(pxx)
pylab.close()
pylab.plot(fxx[:part], lxx[:part])
pylab.xlabel('Frequency (Hz)')
pylab.ylabel('Power (dB)')
pylab.savefig('%spsd.png' % prefix)
n = 5 # num peaks
p, c = utilities.get_peaks(pxx, n)
peak_freqs = [fxx[i] for i in p]
peak_db = [lxx[i] for i in p]
print peak_freqs
pylab.plot(peak_freqs, peak_db, 'ro', ms=4)
for i in range(n):
pylab.text(peak_freqs[i],
peak_db[i],
'%5.1fHz' % peak_freqs[i],
ha='center',
position=(peak_freqs[i], peak_db[i] + 1))
pylab.xlabel('Frequency (Hz)')
pylab.ylabel('Power (dB)')
pylab.savefig('%speaks.png' % prefix)
def mkgraphs(wname, prefix):
print wname
wav, wp = utilities.get_wav(wname)
sp = 1.0 / wp[2]
timevals = numpy.arange(0, wp[3] * sp, sp)
part = 4000
pylab.close()
pylab.plot(timevals[:part], wav[:part])
pylab.xlabel('Time (s)')
pylab.ylabel('Relative amplitude')
pylab.savefig('%stime.png' %prefix)
PSD_NFFT = 2**17
(pxx, fxx) = utilities.get_psd(wav, wp[2], PSD_NFFT)
part = 1700
lxx = 10 * numpy.log10(pxx)
pylab.close()
pylab.plot(fxx[:part], lxx[:part])
pylab.xlabel('Frequency (Hz)')
pylab.ylabel('Power (dB)')
pylab.savefig('%spsd.png' %prefix)
n = 5 # num peaks
p, c = utilities.get_peaks(pxx, n)
peak_freqs = [ fxx[i] for i in p ]
peak_db = [ lxx[i] for i in p ]
print peak_freqs
pylab.plot(peak_freqs, peak_db, 'ro', ms=4)
for i in range(n):
pylab.text(peak_freqs[i], peak_db[i], '%5.1fHz' %peak_freqs[i], ha='center', position=(peak_freqs[i], peak_db[i] + 1))
pylab.xlabel('Frequency (Hz)')
pylab.ylabel('Power (dB)')
pylab.savefig('%speaks.png' %prefix)
def __init__(self, fname, numpeaks, base=0): print '\t%s' %fname self.fname = fname self.wav, self.wp = utilities.get_wav(fname) self.psd, self.psd_freqs = utilities.get_psd(self.wav, self.wp[2]) self.peaks, self.peaks_energy = utilities.get_peaks(self.psd, numpeaks) self.peaks_freqs = numpy.array([self.psd_freqs[i] for i in self.peaks]) self.percs = self.peaks_energy / self.psd.sum() self.peaks_notes = utilities.get_note(self.peaks_freqs) if base: bi = None diff = 100 for i in self.peaks_freqs: d = abs(base - i) if d < diff: diff = d bi = i self.base = bi else: self.base = self.psd_freqs[self.peaks[0]]
def f(fname): wav, wp = utilities.get_wav(fname) pxx, fxx = utilities.get_psd(wav, wp[2]) p, c = utilities.get_peaks(pxx, n) pf = [ fxx[i] for i in p ] return wav, wp, pxx, fxx, p, c, pf
def f(fname):
wav, wp = utilities.get_wav(fname)
pxx, fxx = utilities.get_psd(wav, wp[2])
p, c = utilities.get_peaks(pxx, n)
pf = [fxx[i] for i in p]
return wav, wp, pxx, fxx, p, c, pf