Lines Matching refs:np
29 import numpy as np namespace
46 return 1127.0 * np.log(1.0 + freq / 700.0)
49 return 700.0 * (np.exp(mels / 1127.0) - 1.0)
53 filters = np.zeros((numOfMelFilters,int(FFTSize/2+1)))
54 zeros = np.zeros(int(FFTSize // 2 ))
59 mels = np.linspace(fmin_mel, fmax_mel, num=numOfMelFilters+2)
62 linearfreqs = np.linspace( 0, fs/2.0, int(FFTSize // 2 + 1) )
73 filters[n, :] = np.hstack([0,np.maximum(zeros,np.minimum(upper,lower))])
80 result = np.zeros((numOfDctOutputs,numOfMelFilters))
81 s=(np.linspace(1,numOfMelFilters,numOfMelFilters) - 0.5)/numOfMelFilters
84 result[i,:]=np.cos(i * np.pi*s) * np.sqrt(2.0/numOfMelFilters)
124 audioPower = np.abs(audioFFT)
133 audioFiltered = np.dot(self._filters,audioPower)
137 audioLog = np.log(audioFiltered + 1e-6)
139 cepstral_coefficents = np.dot(self._dctMatrixFilters, audioLog)
144 debug=np.array([ 0.65507051 ,-0.94647589 ,0.00627239 ,0.14151286 ,-0.10863318 ,-0.36370327
189 return(2.0*np.random.rand(nb)-1.0)
194 time = np.arange(0,nb)
195 return(np.sin(2 * np.pi * f * time/nb))
229 audio=np.random.randn(nb)