plotOdf = True
order = 10
filename = sys.argv[1]
frameSize = 1024
frameStep = 256
fftSize = 2048
stream, sampleRate, nframes, nchannels, loader = get_framer_audio(
filename, frameSize, frameStep)
ffter = loudia.FFT(fftSize)
windower = loudia.Window(frameSize, loudia.Window.HAMMING)
subplots = {
1: ['mag', 'peaki_mags', 'resid_mag', 'synth_mag', 'traj_mags'],
2: ['phase', 'peak_phases']
}
all_processes = set()
for values in subplots.values():
all_processes |= set(values)
plotSize = fftSize / 4
subplotCount = max(subplots)
pylab.ion()
frameStep = 1024
fftSize = 4096
plotSize = fftSize / 4
bandwidth = 4 * fftSize / frameSize
minPeakWidth = 8
peakCandidateCount = 4
stream, sampleRate, nframes, nchannels, loader = get_framer_audio(
filename, frameSize, frameStep)
ffter = loudia.FFT(fftSize)
windower = loudia.Window(frameSize, loudia.Window.BLACKMANHARRIS)
whitening = loudia.SpectralWhitening(fftSize, 50.0, 6000.0, sampleRate)
pitchACF = loudia.PitchACF(fftSize, sampleRate, minPeakWidth,
peakCandidateCount)
acorr = loudia.Autocorrelation(fftSize / 2 + 1, fftSize / 2 + 1)
specs = []
wspecs = []
pitches = []
saliencies = []
if interactivePlot:
pylab.ion()
pylab.figure()
pylab.title('Interactive plot of the FFT vs LPC frequency response')
pylab.gca().set_ylim([-100, 40])
#!/usr/bin/env python
# Create input
import scipy
import loudia
frameSize = 121
fftSize = 512
sampleRate = 8000
# Loudia's solution # --------------------------------- #
w = loudia.Window(frameSize, 0)
m = loudia.FFT(fftSize, True)
for i in range(100000):
a_random = scipy.random.random(frameSize)
r_random = m.process(w.process(a_random))
# -------------------------------------------------------- #
import loudia
import pylab
plot = False
frameSize = 121
fftSize = 512
sampleRate = 8000
a_zeros = scipy.zeros(frameSize)
a_ones = scipy.ones(frameSize)
a_random = scipy.random.random(frameSize)
a_sine = scipy.cos(2 * scipy.pi * 440 * scipy.arange(frameSize) / sampleRate +
scipy.pi / 4.0)
# Loudia's solution # --------------------------------- #
w = loudia.Window(frameSize, loudia.Window.RECTANGULAR)
m = loudia.FFT(fftSize, False)
r_zeros = m.process(w.process(a_zeros))
r_ones = m.process(w.process(a_ones))
r_random = m.process(w.process(a_random))
r_sine = m.process(w.process(a_sine))
# -------------------------------------------------------- #
# Scipy solution # ---------------------------------- #
s_zeros = scipy.fft(a_zeros, fftSize)[:fftSize / 2 + 1]
s_ones = scipy.fft(a_ones, fftSize)[:fftSize / 2 + 1]
s_random = scipy.fft(a_random, fftSize)[:fftSize / 2 + 1]
s_sine = scipy.fft(a_sine, fftSize)[:fftSize / 2 + 1]
# -------------------------------------------------------- #
#!/usr/bin/env python # Create input import scipy.signal import loudia frameSize = 256 a_ones = scipy.ones(frameSize) # Loudia's solution # --------------------------------- # m_hanning = loudia.Window(frameSize, 1) m_hamming = loudia.Window(frameSize, 3) r_hanning = m_hanning.process(a_ones) r_hamming = m_hamming.process(a_ones) # -------------------------------------------------------- # # Scipy solution # ---------------------------------- # s_hanning = scipy.signal.hanning(frameSize) s_hamming = scipy.signal.hamming(frameSize) # -------------------------------------------------------- # print 'Hann match: ', scipy.allclose(r_hanning, s_hanning) print 'Hamming match: ', scipy.allclose(r_hamming, s_hamming) print(r_hamming - s_hamming).sum() #import pylab #pylab.hold(True)
fftSize = frameSize*2 # samples
miniHopSize = frameSize/4 # samples
print miniHopSize
plotSize = 256
frameCount = 0
#windowType = loudia.Window.BLACKMANHARRIS
#windowType = loudia.Window.HANNING
windowType = loudia.Window.HAMMING
#windowType = loudia.Window.RECTANGULAR
window = loudia.Window(frameSize, windowType)
fft = loudia.FFT(fftSize, True)
unwrapper = loudia.Unwrap()
def process(frame):
spec = fft.process(window.process(frame))
return scipy.absolute(spec), scipy.angle(spec)
print 'fftSize: ', fftSize
def mapError(error):
error[error > scipy.pi] = (2*scipy.pi - error[error>scipy.pi])
return error
