Mercurial > hg > vampy
view Example VamPy plugins/PyZeroCrossing.py @ 24:7d28bed0864e
* Rearrange Python plugin construction.
Formerly, the PyPluginAdapter has retained a single plugin instance pointer
for each plugin found, and its createPlugin method has simply returned a new
PyPlugin object wrapping the same instance pointer. This has a couple of
negative consequences:
- Because construction of the actual Python instance occurred before the
wrapper was constructed, it was not possible to pass arguments (i.e.
the sample rate) from the wrapper constructor to the Python plugin
instance constructor -- they had to be passed later, to initialise,
disadvantaging those plugins that would like to use the sample rate
for parameter & step/block size calculations etc
- Because there was only a single Python plugin instance, it was not
possible to run more than one instance at once with any isolation
This rework instead stores the Python class pointer (rather than instance
pointer) in the PyPluginAdapter, and each PyPlugin wrapper instance creates
its own Python plugin instance. What could possibly go wrong?
author | cannam |
---|---|
date | Mon, 17 Aug 2009 15:22:06 +0000 |
parents | 535d559300dc |
children | ba3686eb697c |
line wrap: on
line source
'''PyZeroCrossing.py - Example plugin demonstrates''' '''how to call a python class using the VamPy Vamp plugin''' from random import * 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.identity = random() 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 'python-zc' def getMaxChannelCount(self): return 1 def getInputDomain(self): return 'TimeDomain' def getOutputDescriptors(self): #descriptors are 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' #'sampleRate':48000.0 } #return a list of dictionaries 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 def process(self,inbuf,timestamp): crossing = False prev = self.previousSample count = 0.0; channel = inbuf[0] print "Identity ", self.identity, ", counter ", self.counter self.counter = self.counter + 1 #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, #for now return sample position and convert to RealTime in C code '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, #'timeStamp':timestamp, 'values':[count], #strictly must be a list 'label':str(count) } output0.append(feature0) #return a LIST of list of dictionaries return [output0,output1]