view Example VamPy plugins/PyZeroCrossing.py @ 37:27bab3a16c9a vampy2final

new branch Vampy2final

'''PyZeroCrossing.py - Example plugin demonstrates
how to write a Vampy plugin in pure Python without
using Numpy or the extensions provided by the embedded 
vampy module. 

This plugin is compatible with provious versions of vampy, 
apart from moving the inputSampleRate
argument from initialise to __init__()

Outputs: 
1) Zero crossing counts
2) Zero crossing locations

Centre for Digital Music, Queen Mary University of London.
Copyright (C) 2009 Gyorgy Fazekas, QMUL. (See Vamp sources 
for licence information.)

'''

class PyZeroCrossing: 
	
	def __init__(self,inputSampleRate): 
		self.m_inputSampleRate = inputSampleRate 
		self.m_stepSize = 0
		self.m_blockSize = 0
		self.m_channels = 0
		self.previousSample = 0.0
		self.threshold = 0.005
		self.counter = 0
		
	def initialise(self,channels,stepSize,blockSize):
		self.m_channels = channels
		self.m_stepSize = stepSize		
		self.m_blockSize = blockSize
		return True
	
	def getMaker(self):
		return 'Vampy Example Plugins'
	
	def getName(self):
		return 'Vampy Zero Crossings'
		
	def getIdentifier(self):
		return 'vampy-zc2'
	
	def getMaxChannelCount(self):
		return 1
		
	def getInputDomain(self):
		return 'TimeDomain'
			
	def getOutputDescriptors(self):
		
		#descriptors can be returned as python dictionaries
		output0={
		'identifier':'vampy-counts',
		'name':'Number of Zero Crossings',
		'description':'Number of zero crossings per audio frame',
		'unit':' ',
		'hasFixedBinCount':True,
		'binCount':1,
		#'binNames':['1 Hz',1.5,'2 Hz',3,'4 Hz'],
		'hasKnownExtents':False,
		#'minValue':0.0,
		#'maxValue':0.0,
		'isQuantized':True,
		'quantizeStep':1.0,
		'sampleType':'OneSamplePerStep'
		#'sampleRate':48000.0
		}

		output1={
		'identifier':'vampy-crossings',
		'name':'Zero Crossing Locations',
		'description':'The locations of zero crossing points',
		'unit':'discrete',
		'hasFixedBinCount':True,
		'binCount':0,
		'sampleType':'VariableSampleRate'
		}

		return [output0,output1]


	def getParameterDescriptors(self):
		paramlist1={
		'identifier':'threshold',
		'name':'Noise threshold',
		'description':'',
		'unit':'v',
		'minValue':0.0,
		'maxValue':0.5,
		'defaultValue':0.005,
		'isQuantized':False
		}
		return [paramlist1]


	def setParameter(self,paramid,newval):
		if paramid == 'threshold' :
			self.threshold = newval
		return

		
	def getParameter(self,paramid):
		if paramid == 'threshold' :
			return self.threshold
		else:
			return 0.0


	# legacy process type: the input is a python list of samples
	def process(self,inbuf,timestamp):
		crossing = False
		prev = self.previousSample
		count = 0.0;
		channel = inbuf[0]

		#we have two outputs defined thus we have to declare
		#them as empty dictionaries in our output list
		#in order to be able to return variable rate outputs
		output0=[]
		output1=[]

		if sum([abs(s) for s in channel]) > self.threshold : 

			for x in range(len(channel)-1) :
				crossing = False
				sample = channel[x]
				if sample <= 0.0 : 
					if prev > 0.0 : crossing = True
				else :
					if sample > 0.0 :
						if prev <= 0.0 : crossing = True		
			
				if crossing == True : 
					count = count + 1
					feature1={
					'hasTimestamp':True,	
					'timeStamp':long(timestamp + x),				
					'values':[count],			
					'label':str(count),				
					}				
					output1.append(feature1)
			
				prev = sample	
			self.previousSample = prev

		else :
			count = 0.0
			self.previousSample = channel[len(channel)-1]

		feature0={
		'hasTimestamp':False,		
		'values':[count],
		'label':str(count)				
		}
		output0.append(feature0)
		
		#return a LIST of list of dictionaries
		return [output0,output1]