--- /dev/null
+from numpy.testing import TestCase, run_module_suite
+from numpy.testing import assert_equal, assert_almost_equal
+# WARNING: numpy also has an fft object
+from _aubio import fft, fvec, cvec
+from numpy import array, shape
+from math import pi
+
+class aubio_fft_test_case(TestCase):
+
+ def test_members(self):
+ f = fft()
+ assert_equal ([f.win_s, f.channels], [1024, 1])
+ f = fft(2048, 4)
+ assert_equal ([f.win_s, f.channels], [2048, 4])
+
+ def test_output_dimensions(self):
+ """ check the dimensions of output """
+ win_s, chan = 1024, 3
+ timegrain = fvec(win_s, chan)
+ f = fft(win_s, chan)
+ fftgrain = f (timegrain)
+ assert_equal (array(fftgrain), 0)
+ assert_equal (shape(fftgrain), (chan * 2, win_s/2+1))
+ assert_equal (fftgrain.norm, 0)
+ assert_equal (shape(fftgrain.norm), (chan, win_s/2+1))
+ assert_equal (fftgrain.phas, 0)
+ assert_equal (shape(fftgrain.phas), (chan, win_s/2+1))
+
+ def test_zeros(self):
+ """ check the transform of zeros """
+ win_s, chan = 512, 3
+ timegrain = fvec(win_s, chan)
+ f = fft(win_s, chan)
+ fftgrain = f(timegrain)
+ assert_equal ( fftgrain.norm == 0, True )
+ assert_equal ( fftgrain.phas == 0, True )
+
+ def test_impulse(self):
+ """ check the transform of one impulse at a random place """
+ from random import random
+ from math import floor
+ win_s, chan = 256, 1
+ i = floor(random()*win_s)
+ impulse = pi * random()
+ f = fft(win_s, chan)
+ timegrain = fvec(win_s, chan)
+ timegrain[0][i] = impulse
+ fftgrain = f ( timegrain )
+ #self.plot_this ( fftgrain.phas[0] )
+ assert_almost_equal ( fftgrain.norm, impulse, decimal = 6 )
+ assert_equal ( fftgrain.phas <= pi, True)
+ assert_equal ( fftgrain.phas >= -pi, True)
+
+ def test_impulse_negative(self):
+ """ check the transform of one impulse at a random place """
+ from random import random
+ from math import floor
+ win_s, chan = 256, 1
+ i = 0
+ impulse = -10.
+ f = fft(win_s, chan)
+ timegrain = fvec(win_s, chan)
+ timegrain[0][i] = impulse
+ fftgrain = f ( timegrain )
+ #self.plot_this ( fftgrain.phas[0] )
+ assert_almost_equal ( fftgrain.norm, abs(impulse), decimal = 6 )
+ if impulse < 0:
+ # phase can be pi or -pi, as it is not unwrapped
+ assert_almost_equal ( abs(fftgrain.phas[0][1:-1]) , pi, decimal = 6 )
+ assert_almost_equal ( fftgrain.phas[0][0], pi, decimal = 6)
+ assert_almost_equal ( fftgrain.phas[0][-1], pi, decimal = 6)
+ else:
+ assert_equal ( fftgrain.phas[0][1:-1] == 0, True)
+ assert_equal ( fftgrain.phas[0][0] == 0, True)
+ assert_equal ( fftgrain.phas[0][-1] == 0, True)
+ # now check the resynthesis
+ synthgrain = f.rdo ( fftgrain )
+ #self.plot_this ( fftgrain.phas.T )
+ assert_equal ( fftgrain.phas <= pi, True)
+ assert_equal ( fftgrain.phas >= -pi, True)
+ #self.plot_this ( synthgrain - timegrain )
+ assert_almost_equal ( synthgrain, timegrain, decimal = 6 )
+
+ def test_impulse_at_zero(self):
+ """ check the transform of one impulse at a index 0 in one channel """
+ win_s, chan = 1024, 2
+ impulse = pi
+ f = fft(win_s, chan)
+ timegrain = fvec(win_s, chan)
+ timegrain[0][0] = impulse
+ fftgrain = f ( timegrain )
+ #self.plot_this ( fftgrain.phas )
+ assert_equal ( fftgrain.phas[0], 0)
+ assert_equal ( fftgrain.phas[1], 0)
+ assert_almost_equal ( fftgrain.norm[0], impulse, decimal = 6 )
+ assert_equal ( fftgrain.norm[0], impulse)
+
+ def test_rdo_before_do(self):
+ """ check running fft.rdo before fft.do works """
+ win_s, chan = 1024, 2
+ impulse = pi
+ f = fft(win_s, chan)
+ fftgrain = cvec(win_s, chan)
+ t = f.rdo( fftgrain )
+ assert_equal ( t, 0 )
+
+ def plot_this(self, this):
+ from pylab import plot, show
+ plot ( this )
+ show ()
+
+if __name__ == '__main__':
+ from unittest import main
+ main()
+
--- /dev/null
+from numpy.testing import TestCase, run_module_suite
+from numpy.testing import assert_equal, assert_almost_equal
+from numpy import array, shape
+from _aubio import *
+
+class aubio_filter_test_case(TestCase):
+
+ def test_slaney(self):
+ f = filterbank(40, 512)
+ f.set_mel_coeffs_slaney(16000)
+ a = f.get_coeffs()
+ a.T
+
+ def test_other_slaney(self):
+ f = filterbank(40, 512*2)
+ f.set_mel_coeffs_slaney(44100)
+ a = f.get_coeffs()
+ #print "sum is", sum(sum(a))
+ for win_s in [256, 512, 1024, 2048, 4096]:
+ f = filterbank(40, win_s)
+ f.set_mel_coeffs_slaney(320000)
+ a = f.get_coeffs()
+ #print "sum is", sum(sum(a))
+
+ def test_triangle_freqs(self):
+ f = filterbank(9, 1024)
+ freq_list = [40, 80, 200, 400, 800, 1600, 3200, 6400, 12800, 15000, 24000]
+ freqs = array(freq_list, dtype = 'float32')
+ f.set_triangle_bands(freqs, 48000)
+ f.get_coeffs().T
+ assert_equal ( f(cvec(1024)), [0] * 9)
+ spec = cvec(1024)
+ spec[0][40:100] = 100
+ #print f(spec)
+
+if __name__ == '__main__':
+ from unittest import main
+ main()
+
--- /dev/null
+from numpy.testing import TestCase, run_module_suite
+from numpy.testing import assert_equal, assert_almost_equal
+# WARNING: numpy also has an fft object
+from _aubio import cvec, specdesc
+from numpy import array, shape, arange, zeros, log
+from math import pi
+
+class aubio_specdesc(TestCase):
+
+ def test_members(self):
+ o = specdesc()
+ assert_equal ([o.buf_size, o.channels, o.method],
+ [1024, 1, "default"])
+ o = specdesc("complex", 512, 2)
+ assert_equal ([o.buf_size, o.channels, o.method],
+ [512, 2, "complex"])
+
+ def test_hfc(self):
+ o = specdesc("hfc")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ assert_equal (a, c.norm[0])
+ assert_equal ( sum(a*(a+1)), o(c))
+
+ def test_complex(self):
+ o = specdesc("complex")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ assert_equal (a, c.norm[0])
+ # the previous run was on zeros, so previous frames are still 0
+ # so we have sqrt ( abs ( r2 ^ 2) ) == r2
+ assert_equal ( sum(a), o(c))
+ # second time. c.norm = a, so, r1 = r2, and the euclidian distance is 0
+ assert_equal ( 0, o(c))
+
+ def test_phase(self):
+ o = specdesc("phase")
+ c = cvec()
+ assert_equal( 0., o(c))
+
+ def test_kl(self):
+ o = specdesc("kl")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ assert_almost_equal( sum(a * log(1.+ a/1.e-10 ) ) / o(c), 1., decimal=6)
+
+ def test_mkl(self):
+ o = specdesc("mkl")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ assert_almost_equal( sum(log(1.+ a/1.e-10 ) ) / o(c), 1, decimal=6)
+
+ def test_specflux(self):
+ o = specdesc("specflux")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ assert_equal( sum(a), o(c))
+ assert_equal( 0, o(c))
+ c.norm = zeros(c.length, dtype='float32')
+ assert_equal( 0, o(c))
+
+ def test_centroid(self):
+ o = specdesc("centroid")
+ c = cvec()
+ # make sure centroid of zeros is zero
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ centroid = sum(a*a) / sum(a)
+ assert_almost_equal (centroid, o(c), decimal = 2)
+
+ c.norm = a * .5
+ assert_almost_equal (centroid, o(c), decimal = 2)
+
+ def test_spread(self):
+ o = specdesc("spread")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ centroid = sum(a*a) / sum(a)
+ spread = sum( (a - centroid)**2 *a) / sum(a)
+ assert_almost_equal (spread, o(c), decimal = 2)
+
+ c.norm = a * 3
+ assert_almost_equal (spread, o(c), decimal = 2)
+
+ def test_skewness(self):
+ o = specdesc("skewness")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ centroid = sum(a*a) / sum(a)
+ spread = sum( (a - centroid)**2 *a) / sum(a)
+ skewness = sum( (a - centroid)**3 *a) / sum(a) / spread **1.5
+ assert_almost_equal (skewness, o(c), decimal = 2)
+
+ c.norm = a * 3
+ assert_almost_equal (skewness, o(c), decimal = 2)
+
+ def test_kurtosis(self):
+ o = specdesc("kurtosis")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length, dtype='float32')
+ c.norm = a
+ centroid = sum(a*a) / sum(a)
+ spread = sum( (a - centroid)**2 *a) / sum(a)
+ kurtosis = sum( (a - centroid)**4 *a) / sum(a) / spread **2
+ assert_almost_equal (kurtosis, o(c), decimal = 2)
+
+ def test_slope(self):
+ o = specdesc("slope")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length * 2, 0, -2, dtype='float32')
+ k = arange(c.length, dtype='float32')
+ c.norm = a
+ num = len(a) * sum(k*a) - sum(k)*sum(a)
+ den = (len(a) * sum(k**2) - sum(k)**2)
+ slope = num/den/sum(a)
+ assert_almost_equal (slope, o(c), decimal = 5)
+
+ a = arange(0, c.length * 2, +2, dtype='float32')
+ c.norm = a
+ num = len(a) * sum(k*a) - sum(k)*sum(a)
+ den = (len(a) * sum(k**2) - sum(k)**2)
+ slope = num/den/sum(a)
+ assert_almost_equal (slope, o(c), decimal = 5)
+
+ a = arange(0, c.length * 2, +2, dtype='float32')
+ c.norm = a * 2
+ assert_almost_equal (slope, o(c), decimal = 5)
+
+ def test_decrease(self):
+ o = specdesc("decrease")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length * 2, 0, -2, dtype='float32')
+ k = arange(c.length, dtype='float32')
+ c.norm = a
+ decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:])
+ assert_almost_equal (decrease, o(c), decimal = 5)
+
+ a = arange(0, c.length * 2, +2, dtype='float32')
+ c.norm = a
+ decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:])
+ assert_almost_equal (decrease, o(c), decimal = 5)
+
+ a = arange(0, c.length * 2, +2, dtype='float32')
+ c.norm = a * 2
+ decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:])
+ assert_almost_equal (decrease, o(c), decimal = 5)
+
+ def test_rolloff(self):
+ o = specdesc("rolloff")
+ c = cvec()
+ assert_equal( 0., o(c))
+ a = arange(c.length * 2, 0, -2, dtype='float32')
+ k = arange(c.length, dtype='float32')
+ c.norm = a
+ cumsum = .95*sum(a*a)
+ i = 0; rollsum = 0
+ while rollsum < cumsum:
+ rollsum += a[i]*a[i]
+ i+=1
+ rolloff = i
+ assert_equal (rolloff, o(c))
+
+if __name__ == '__main__':
+ from unittest import main
+ main()
--- /dev/null
+from numpy.testing import TestCase, run_module_suite
+from numpy.testing import assert_equal, assert_almost_equal
+from _aubio import *
+from numpy import array, shape
+
+class aubio_pvoc_test_case(TestCase):
+
+ def test_members(self):
+ f = pvoc()
+ assert_equal ([f.win_s, f.hop_s], [1024, 512])
+ f = pvoc(2048, 128)
+ assert_equal ([f.win_s, f.hop_s], [2048, 128])
+
+ def test_zeros(self):
+ win_s, hop_s = 1024, 256
+ f = pvoc (win_s, hop_s)
+ t = fvec (hop_s)
+ for time in range( 4 * win_s / hop_s ):
+ s = f(t)
+ r = f.rdo(s)
+ assert_equal ( array(t), 0)
+ assert_equal ( s.norm, 0)
+ assert_equal ( s.phas, 0)
+ assert_equal ( r, 0)
+
+ def test_steps_two_channels(self):
+ """ check the resynthesis of steps is correct """
+ f = pvoc(1024, 512, 2)
+ t1 = fvec(512, 2)
+ t2 = fvec(512, 2)
+ # positive step in first channel
+ t1[0][100:200] = .1
+ # positive step in second channel
+ t1[1][20:50] = -.1
+ s1 = f(t1)
+ r1 = f.rdo(s1)
+ s2 = f(t2)
+ r2 = f.rdo(s2)
+ #self.plot_this ( s1.norm.T )
+ assert_almost_equal ( t1, r2, decimal = 6 )
+
+ def test_steps_three_random_channels(self):
+ from random import random
+ f = pvoc(64, 16, 3)
+ t0 = fvec(16, 3)
+ t1 = fvec(16, 3)
+ for i in xrange(3):
+ for j in xrange(16):
+ t1[i][j] = random() * 2. - 1.
+ t2 = f.rdo(f(t1))
+ t2 = f.rdo(f(t0))
+ t2 = f.rdo(f(t0))
+ t2 = f.rdo(f(t0))
+ assert_almost_equal( t1, t2, decimal = 6 )
+
+ def plot_this( self, this ):
+ from pylab import semilogy, show
+ semilogy ( this )
+ show ()
+
+if __name__ == '__main__':
+ from unittest import main
+ main()
+
projects / aubio.git / commitdiff