view Example VamPy plugins/obsolete/PySpectralCentroid.py @ 46:af9c4cee95a8

VC++ fixes.
Much of this is changing "and" to "&&".  I had never realised
until today that "and" is in fact a keyword in C++, albeit not
one that has been there since the start, so this should compile
(I eventually looked this up having been puzzled by how this
code could ever build with any other compiler).  However,
despite its keywordness, "and" still doesn't seem to be acceptable
to VC++.  Possibly there's an option to change this, or one could
use a macro -- but why not just stick with the token that compilers
are known to like?

'''PySpectralCentroid.py - Example plugin demonstrates 
how to write a C style plugin using VamPy.

Obsolete warning: this plugin will no longer be supported 
since the legacy interface should pass a list of complex
numbers for frequency domain plugins and a list of floats
for time domin plugins.

'''

from numpy import *

class PySpectralCentroid: 
	
	def __init__(self,inputSampleRate): 
		self.m_imputSampleRate = 0.0 
		self.m_stepSize = 0
		self.m_blockSize = 0
		self.m_channels = 0
		self.previousSample = 0.0
		self.m_inputSampleRate = inputSampleRate
		self.threshold = 0.00
		
	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 'Spectral Centroid (legacy process interface)'
		
	def getIdentifier(self):
		return 'vampy-sc2'
	
	def getMaxChannelCount(self):
		return 1
		
	def getInputDomain(self):
		return 'FrequencyDomain'
			
	def getOutputDescriptors(self):
		
		output0={
		'identifier':'vampy-sf1',
		'name':'Spectral Centroid',
		'description':'Spectral Centroid (Brightness)',
		'unit':' ',
		'hasFixedBinCount':True,
		'binCount':1,
		'hasKnownExtents':False,
		'isQuantized':True,
		'quantizeStep':1.0,
		'sampleType':'OneSamplePerStep'
		}

		return [output0]

	def getParameterDescriptors(self):
		paramlist1={
		'identifier':'threshold',
		'name':'Noise threshold: ',
		'description':'Return null or delete this function if not needed.',
		'unit':'v',
		'minValue':0.0,
		'maxValue':0.5,
		'defaultValue':0.05,
		'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
			
	def process(self,inbuf,timestamp):
		
		inArray = array(inbuf[0])
		crossing = False
		prev = self.previousSample
		count = 0.0
		numLin = 0.0
		denom = 0.0
		centroid = 0.0
		
		# re = array(inbuf[2:len(inArray):2])
		# im = array(inbuf[3:len(inArray):2])

		output0=[]
		output1=[]

		# pw = 0
		# for i in xrange(1,len(inbuf[0])) : 
		# 	pw = pw + abs(inbuf[0][i])
		
		if sum(abs(inArray)) > self.threshold : 
			for i in range(1,(len(inArray)/2)) :
			# for i in range(1,len(inbuf[0])) :
				
				re = inArray[i*2]
				im = inArray[i*2+1]
				# re = inbuf[0][i].real
				# im = inbuf[0][i].imag
				freq = i * self.m_inputSampleRate / self.m_blockSize
				power = sqrt (re*re + im*im) / (self.m_blockSize/2)
				denom = denom + power
				numLin = numLin + freq * power
				
			if denom != 0 :
				centroid = numLin / denom 
				
		else :
			centroid = 0.0

		feature0={
		'hasTimestamp':False,		
		'values':[centroid],		#strictly must be a list
		'label':str(centroid)				
		}
		output0.append(feature0)
		
		return [output0]