comparison utils/SegUtil.py @ 12:c23658e8ae38

fp feature notebook

 	feature_array[np.isinf(feature_array)] = 0.0
 
 	return feature_array		
 
 
+def getRolloff(data, tpower, filterbank, thresh=0.9):
+	nFrames = data.shape[0]
+	nFilters = len(filterbank)
+	rolloff = np.zeros(nFrames)
+	for i in xrange(nFrames):
+		rolloffE = thresh * tpower[i]
+		temp = 0.0
+		tempE = 0.0
+		for band in xrange(nFilters):
+			temp += data[i][band]
+			if temp > rolloffE: break
+		rolloff[i] = filterbank[nFilters-band-1]
+	
+	return rolloff
+
+
 def verifyPeaks(peak_canditates, dev_list):
 	'''Verify peaks from the 1st round detection by applying adaptive thresholding to the deviation list.'''
 	
 	final_peaks = copy(peak_canditates)
 	dev_list = np.array([np.mean(x) for x in dev_list]) # get average of devs of different features