def __init__(
self,
context,
name,
parent, # Standard visr component constructor arguments
numberOfObjects, # The number of point source objects rendered.
hoaOrder, # The Ambisonics order for encoding the objects
channelAllocation=False # Whether to allocate object channels dynamically (not used at the moment)
):
"""
Constructor.
Parameters
----------
numberOfObjects: int
The maximum number of audio objects to be rendered.
hoaOrder: int
The Ambisonics order for encoding the objects.
channelAllocation: bool, optional
Whether to send dynamic channel allocation data. Not used at the moment.
Default value means that the object channels are allocated statically and correspond to the
obbject's channel id.
"""
# Call base class (AtomicComponent) constructor
super(HoaObjectEncoder, self).__init__(context, name, parent)
self.numberOfObjects = numberOfObjects
self.hoaOrder = hoaOrder
self.numHoaCoeffs = (self.hoaOrder + 1)**2
# %% Define parameter ports
self.objectInput = visr.ParameterInput(
"objectVector", self, pml.ObjectVector.staticType,
pml.DoubleBufferingProtocol.staticType, pml.EmptyParameterConfig())
self.objectInputProtocol = self.objectInput.protocolInput()
matrixConfig = pml.MatrixParameterConfig(self.numHoaCoeffs,
self.numberOfObjects)
self.coefficientOutput = visr.ParameterOutput(
"coefficientOutput", self, pml.MatrixParameterFloat.staticType,
pml.SharedDataProtocol.staticType, matrixConfig)
self.coefficientOutputProtocol = self.coefficientOutput.protocolOutput(
)
if channelAllocation:
self.channelAllocator = rbbl.ObjectChannelAllocator(
self.numberOfObjects)
self.usedChannels = set() # Initialised with an empty set.
self.routingOutput = visr.ParameterOutput(
"routingOutput", self, pml.SignalRoutingParameter.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig())
self.routingOutputProtocol = self.routingOutput.protocolOutput()
else:
self.routingOutputProtocol = None
self.channelAllocator = None
def __init__( self, context, name, parent,
processorConfig,
objectVectorInput = True, # receive input as pml.ObjectVector parameters (as opposed to JSON)
objectVectorOutput = True, # send output as pml.ObjectVector parameters (as opposed to JSON)
oscControlPort = False,
jsonControlPort = False,
alwaysProcess = True,
verbose = False):
""" Construction function. """
super( Component, self ).__init__( context, name, parent )
if objectVectorInput:
self.textInput = False
self.objectInput = visr.ParameterInput( "objectIn", self,
pml.ObjectVector.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
else:
self.textInput = True
self.objectInput = visr.ParameterInput( "objectIn", self,
pml.StringParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
if objectVectorOutput:
self.textOutput = False
self.objectOutput = visr.ParameterOutput( "objectOut", self,
pml.ObjectVector.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
else:
self.textOutput = True
self.objectOutput = visr.ParameterOutput( "objectOut", self,
pml.StringParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
if oscControlPort:
self.oscControlInput = visr.ParameterInput( "oscControlIn", self,
pml.StringParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
else:
self.oscControlInput = None
if jsonControlPort:
self.jsonControlInput = visr.ParameterInput( "jsonControlIn", self,
pml.StringParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
else:
self.jsonControlInput = None
self._engine = Engine( processorConfig, alwaysProcess, verbose )
def __init__(self, context, name, parent, *, calibrationPort, **razorArgs):
"""
Constructor.
context : visr.SignalFlowContext
Standard visr.Component construction argument, a structure holding the block size and the sampling frequency
name : string
Name of the component, Standard visr.Component construction argument
parent : visr.CompositeComponent
Containing component if there is one, None if this is a top-level component of the signal flow.
calibrationPort: int
A UDP port number. Packets sent to this port trigger the calibration.
razorArg: keyword list
Set of parameters to the RazorAHRS. See this class for parameter documentation.
"""
super(RazorAHRSWithUdpCalibrationTrigger,
self).__init__(context, name, parent)
self.trackingOutput = visr.ParameterOutput(
"orientation", self, pml.ListenerPosition.staticType,
pml.DoubleBufferingProtocol.staticType, pml.EmptyParameterConfig())
razorArgs[
'calibrationInput'] = True # Reset the keyword argument (if already present)
self.tracker = RazorAHRS(context, "Tracker", self, **razorArgs)
self.triggerReceiver = UdpReceiver(context,
"CalibrationTriggerReceiver",
self,
port=calibrationPort)
self.parameterConnection(
self.triggerReceiver.parameterPort("messageOutput"),
self.tracker.parameterPort("calibration"))
self.parameterConnection(self.tracker.parameterPort("orientation"),
self.trackingOutput)
def __init__(self,
context,
name,
parent,
numberOfChannels,
measurePeriod=0.4,
channelWeights=None,
audioOut=False):
# Call the base class constructor
super(LoudnessMeter, self).__init__(context, name, parent)
# Define an audio input port with name "audioIn" and width (number of signal waveforms) numberOfChannels
self.audioInput = visr.AudioInputFloat("audioIn", self,
numberOfChannels)
# If the option is set, add an audio output to put out the K-weigth input signals
# Some audio interfaces don't like configs with no outputs.
if audioOut:
self.audioOutput = visr.AudioOutputFloat("audioOut", self,
numberOfChannels)
else:
self.audioOutput = None
# Define a parameter output port with type "Float" and communication protocol "MessageQueue"
# MessageQueue means that all computed data are hold in a first-in-first-out queue,
# which decouples the parameter update rate from the buffer size.
self.loudnessOut = visr.ParameterOutput(
"loudnessOut", self, pml.Float.staticType,
pml.MessageQueueProtocol.staticType, pml.EmptyParameterConfig())
# %% Setup data used in the process() function.
# Round the measurement period to the next multiple of the buffer period
numMeanBlocks = int(
np.ceil(
(measurePeriod * context.samplingFrequency) / context.period))
self.pastPower = np.zeros(numMeanBlocks, dtype=np.float32)
# IIR filter state to be saved in betweem
self.filterState = np.zeros((2, numberOfChannels, 2), dtype=np.float32)
# IIR coefficients for K-weighting, taken from ITU-R BS.1770-4
# https://www.itu.int/dms_pubrec/itu-r/rec/bs/R-REC-BS.1770-4-201510-I!!PDF-E.pdf
self.Kweighting = np.asarray([[
1.53512485958697, -2.69169618940638, 1.19839281085285, 1.0,
-1.69065929318241, 0.73248077421585
], [1.0, -2.0, 1.0, 1.0, -1.99004745483398, 0.99007225036621]],
dtype=np.float32)
# Initialise weightings for the channels.
# Use unit weighting if none are given
if channelWeights is not None:
self.channelWeights = np.asarray(channelWeights, dtype=np.float32)
if self.channelWeights.shape[0] != numberOfChannels:
raise ValueError(
"The channelWeights argument does not match the number of channels"
)
else:
self.channelWeights = np.ones(numberOfChannels, dtype=np.float32)
def __init__( self,
context, name, parent,
numberOfObjects,
hoaOrder,
dynamicUpdates = False,
headOrientation = None
):
"""
Constructor.
Parameters
----------
context: visr.SignalFlowContext
Structure containing block size and sampling frequency, standard visr component construction parameter.
name: string
Name of the component, can be chosen freely as long as it is unique withion the containing component.
parent: visr.CompositeComponent or NoneType
The containing composite component, or None for a top-level component.
numberOfObjects: int
The number of objects to be rendered, i.e., columns in the received spherical harmonics matrices.
hoaOrder: int
The order of the spherical harmonics. Defines the number of rows of the processed matrices ((hoaOrder+1)^2)
headOrientation: array-like (2- or 3- element) or NoneType
The initial head rotation or the static head orientation if dynamic updates are deactivated. Given as yaw, pitch, roll.
"""
# Call base class (AtomicComponent) constructor
super( HoaCoefficientRotation, self ).__init__( context, name, parent )
self.numberOfObjects = numberOfObjects
self.hoaOrder = hoaOrder
self.numHoaCoeffs = (self.hoaOrder+1)**2
# %% Define parameter ports
matrixConfig = pml.MatrixParameterConfig( self.numHoaCoeffs, self.numberOfObjects )
self.coefficientInput = visr.ParameterInput( "coefficientInput", self,
pml.MatrixParameterFloat.staticType,
pml.SharedDataProtocol.staticType,
matrixConfig )
self.coefficientInputProtocol = self.coefficientInput.protocolInput()
self.coefficientOutput = visr.ParameterOutput( "coefficientOutput", self,
pml.MatrixParameterFloat.staticType,
pml.SharedDataProtocol.staticType,
matrixConfig )
self.coefficientOutputProtocol = self.coefficientOutput.protocolOutput()
# Instantiate the head tracker input.
self.trackingInput = visr.ParameterInput( "tracking", self, pml.ListenerPosition.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
self.trackingInputProtocol = self.trackingInput.protocolInput()
if headOrientation is None:
headOrientation = np.zeros( (3), np.float32 )
R1 = rotationMatrixReorderingACN( calcRotationMatrix( headOrientation ) )
self.rotationMatrices = allSphericalHarmonicsRotationMatrices( self.hoaOrder, R1 )
def __init__(
self,
context,
name,
parent,
positions, # Either #points x 3 or 1x3 matrix of Cartesian object positions.
updateRateSamples=None,
objectId=0,
groupId=0,
priority=0,
objectLevel=1.0,
objectChannel=None,
diffuseness=None):
super(PointSourceTrajectoryGenerator,
self).__init__(context, name, parent)
if updateRateSamples % self.period() != 0:
raise ValueError(
"TrajectoryGenerator: The update rate must be a multiple of the period."
)
self.updateCycles = updateRateSamples // self.period()
self.positions = positions
self.numPositions = self.positions.shape[1]
self.objectOutput = visr.ParameterOutput(
"objectVectorOutput",
self,
parameterType=pml.ObjectVector.staticType,
protocolType=pml.DoubleBufferingProtocol.staticType,
parameterConfig=pml.EmptyParameterConfig())
self.cycleCounter = 0
self.positionCounter = 0
if diffuseness is None:
self.object = om.PointSource(objectId)
else:
ValueError("Diffuse point sources not currently supported.")
self.object.position = positions[:, 0]
self.object.level = objectLevel
self.groupId = groupId
self.object.priority = priority
if objectChannel is None:
objectChannel = objectId
self.object.channels = [objectChannel]
def __init__(
self,
context,
name,
parent,
arrayConfig,
numberOfObjects=1,
):
super(PythonPanner, self).__init__(context, name, parent)
self.numLsp = arrayConfig.numberOfRegularLoudspeakers
self.objectInput = visr.ParameterInput(
"objectVectorInput",
self,
parameterType=pml.ObjectVector.staticType,
protocolType=pml.DoubleBufferingProtocol.staticType,
parameterConfig=pml.EmptyParameterConfig())
self.gainOutput = visr.ParameterOutput(
"gainOutput",
self,
parameterType=pml.MatrixParameterFloat.staticType,
protocolType=pml.SharedDataProtocol.staticType,
parameterConfig=pml.MatrixParameterConfig(self.numLsp,
numberOfObjects))
self.vbap = panning.VBAP(arrayConfig)
def __init__( self,
context, name, parent,
port,
yawOffset=0,
pitchOffset=0,
rollOffset=0,
yawRightHand=False,
pitchRightHand=False,
rollRightHand=False,
calibrationInput = False # Whether to instantiate an input port to set the orientation.
):
"""
Constructor.
Parameters
----------
context : visr.SignalFlowContext
Standard visr.Component construction argument, a structure holding the block size and the sampling frequency
name : string
Name of the component, Standard visr.Component construction argument
parent : visr.CompositeComponent
Containing component if there is one, None if this is a top-level component of the signal flow.
yawOffset:
Initial offset for the yaw component, default 0.0
pitchOffset : float
Offset for the pitch value, in degree
rollOffset : float:
Initial value for the roll component, default 0.0
yawRightHand: bool
Whehther the yaw coordinate is interpreted as right-hand
(mathematically negative) rotation. Default: False
pitchRightHand: bool
Whehther the pitch coordinate is interpreted as right-hand
(mathematically negative) rotation. Default: False
rollRightHand: bool
Whehther the roll coordinate is interpreted as right-hand
(mathematically negative) rotation. Default: False
calibrationInput: bool
Flag to determine whehter the component has an additional input "calibration"
that resets the orientation offsets. At the moment, this input is of
type StringParameter, and the value is ignored.
TODO: Check whether to support ListenerPosition objects as calibration triggers
to set the orientation to an arbitrary value
"""
super( RazorAHRS, self ).__init__( context, name, parent )
self.yprVec = np.zeros( 3, dtype = np.float32 )
baudRate = 57600
self.ser = serial.Serial(port, baudRate, timeout=0)
self.message = ""
self.sent = False
self.trackingOutput = visr.ParameterOutput( "orientation", self,
pml.ListenerPosition.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
self.trackingOutputProtocol = self.trackingOutput.protocolOutput()
if calibrationInput:
self.calibrationInput = visr.ParameterInput( "calibration", self,
pml.StringParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
else:
self.calibrationInput = None
self.sentN = 0
self.parsedN = 0
self.ser.read() #necessary for the .in_waiting to work
self.procN =0
self.yawOffset = yawOffset
self.pitchOffset = pitchOffset
self.rollOffset = rollOffset
self.yawRightHand = yawRightHand
self.pitchRightHand = pitchRightHand
self.rollRightHand= rollRightHand
self.orientation = np.array( [0.0, 0.0, 0.0 ] ) # Current orientation, unadjusted, in radian
def __init__( self,
context, name, parent, # Standard visr component constructor arguments
numberOfObjects, # The number of point source objects rendered.
hrirPositions, # The directions of the HRTF measurements, given as a Nx3 array
hrirData, # The HRTF data as 3 Nx2xL matrix, with L as the FIR length.
headRadius = 0.0875, # Head radius, optional. Might be used in a dynamic ITD/ILD individualisation algorithm.
useHeadTracking = False, # Whether head tracking data is provided via a self.headOrientation port.
dynamicITD = False, # Whether ITD delays are calculated and sent via a "delays" port.
dynamicILD = False, # Whether ILD gains are calculated and sent via a "gains" port.
interpolatingConvolver = False, # Whether to transmit interpolation parameters (True) or complete interpolated filters
hrirInterpolation = False, # HRTF interpolation selection: False: Nearest neighbour, True: Barycentric (3-point) interpolation
channelAllocation = False, # Whether to allocate object channels dynamically (not tested yet)
hrirDelays = None, # Matrix of delays associated with filter dataset. Dimension: # filters * 2
):
"""
Constructor.
Parameters
----------
context : visr.SignalFlowContext
Standard visr.Component construction argument, a structure holding the block size and the sampling frequency
name : string
Name of the component, Standard visr.Component construction argument
parent : visr.CompositeComponent
Containing component if there is one, None if this is a top-level component of the signal flow.
numberOfObjects: int
The number of point source objects rendered.
hrirPositions : numpy.ndaarray
The directions of the HRTF measurements, given as a Nx3 array
hrirData : numpy.ndarray
The HRTF data as 3 Nx2xL matrix, with L as the FIR length.
headRadius: float
Head radius, optional and not currently used. Might be used in a dynamic ITD/ILD individualisation algorithm.
useHeadTracking: bool
Whether head tracking data is provided via a self.headOrientation port.
dynamicITD: bool
Whether ITD delays are calculated and sent via a "delays" port.
dynamicILD: bool
Whether ILD gains are calculated and sent via a "gains" port.
hrirInterpolation: bool
HRTF interpolation selection: False: Nearest neighbour, True: Barycentric (3-point) interpolation
channelAllocation: bool
Whether to allocate object channels dynamically (not tested yet)
hrirDelays: numpy.ndarray
Matrix of delays associated with filter dataset. Dimension: # filters * 2. Default None means there are no separate
delays, i.e., they must be contained in the HRIR data.
"""
# Call base class (AtomicComponent) constructor
super( DynamicHrirController, self ).__init__( context, name, parent )
self.numberOfObjects = numberOfObjects
self.dynamicITD = dynamicITD
self.dynamicILD = dynamicILD
# %% Define parameter ports
self.objectInput = visr.ParameterInput( "objectVector", self, pml.ObjectVector.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
self.objectInputProtocol = self.objectInput.protocolInput()
if useHeadTracking:
self.useHeadTracking = True
self.trackingInput = visr.ParameterInput( "headTracking", self, pml.ListenerPosition.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
self.trackingInputProtocol = self.trackingInput.protocolInput()
else:
self.useHeadTracking = False
self.trackingInputProtocol = None # Flag that head tracking is not used.
self.rotationMatrix = np.identity( 3, dtype=np.float32 )
self.interpolatingConvolver = interpolatingConvolver
if interpolatingConvolver:
self.filterOutputProtocol = None # Used as flag to distinguish between the output modes.
if not hrirInterpolation:
numInterpolants = 1
elif hrirPositions.shape[-1] == 2:
numInterpolants = 2
else:
numInterpolants = 3
self.interpolationOutput = visr.ParameterOutput( "interpolatorOutput", self,
pml.InterpolationParameter.staticType,
pml.MessageQueueProtocol.staticType,
pml.InterpolationParameterConfig(numInterpolants) )
self.interpolationOutputProtocol = self.interpolationOutput.protocolOutput()
else:
self.filterOutput = visr.ParameterOutput( "filterOutput", self,
pml.IndexedVectorFloat.staticType,
pml.MessageQueueProtocol.staticType,
pml.EmptyParameterConfig() )
self.filterOutputProtocol = self.filterOutput.protocolOutput()
self.interpolationOutputProtocol = None
if self.dynamicITD:
if (hrirDelays is None) or (hrirDelays.ndim != 2) or (hrirDelays.shape != (hrirData.shape[0], 2 ) ):
raise ValueError( 'If the "dynamicITD" option is given, the parameter "delays" must be a #hrirs x 2 matrix.' )
self.dynamicDelays = np.array(hrirDelays, copy=True)
self.delayOutput = visr.ParameterOutput( "delayOutput", self,
pml.VectorParameterFloat.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.VectorParameterConfig( 2*self.numberOfObjects) )
self.delayOutputProtocol = self.delayOutput.protocolOutput()
# If we use dynamic ILD, only the object level is set at the moment.
if self.dynamicILD:
self.gainOutput = visr.ParameterOutput( "gainOutput", self,
pml.VectorParameterFloat.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.VectorParameterConfig( 2*self.numberOfObjects) )
self.gainOutputProtocol = self.gainOutput.protocolOutput()
if channelAllocation:
self.routingOutput = visr.ParameterOutput( "routingOutput", self,
pml.SignalRoutingParameter.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig() )
self.routingOutputProtocol = self.routingOutput.protocolOutput()
else:
self.routingOutputProtocol = None
# HRIR selection and interpolation data
# If the interpolatingconvolver is used, only interpolation parameters are transmitted.
if interpolatingConvolver:
self.hrirs = None
else:
self.hrirs = np.array( hrirData, copy = True, dtype = np.float32 )
# Normalise the hrir positions to unit radius (to let the k-d tree
# lookup work as expected.)
hrirPositions[:,2] = 1.0
self.hrirPos = sph2cart(np.array( hrirPositions, copy = True, dtype = np.float32 ))
self.hrirInterpolation = hrirInterpolation
if self.hrirInterpolation:
self.lastPosition = np.repeat( [[np.NaN, np.NaN, np.NaN]], self.numberOfObjects, axis=0 )
self.hrirLookup = ConvexHull( self.hrirPos )
self.triplets = np.transpose(self.hrirLookup.points[self.hrirLookup.simplices], axes=(0, 2, 1))
self.inverted = np.asarray( inv(self.triplets), dtype=np.float32 )
else:
self.lastFilters = np.repeat( -1, self.numberOfObjects, axis=0 )
# %% Dynamic allocation of objects to channels
if channelAllocation:
self.channelAllocator = rbbl.ObjectChannelAllocator( self.numberOfObjects )
self.usedChannels = set()
else:
self.channelAllocator = None
self.sourcePos = np.repeat( np.array([[1.0,0.0,0.0]],
dtype = np.float32 ), self.numberOfObjects, axis = 0 )
self.levels = np.zeros( (self.numberOfObjects), dtype = np.float32 )
def __init__(self,
context,
name,
parent,
hoaOrder,
dynamicOrientation=False,
initialOrientation=None):
"""
Constructor.
Parameters
----------
context: visr.SignalFlowContext
Structure containing block size and sampling frequency, standard visr component construction parameter.
name: string
Name of the component, can be chosen freely as long as it is unique withion the containing component.
parent: visr.CompositeComponent or NoneType
The containing composite component, or None for a top-level component.
hoaOrder: int
The spherical harmonics order, determines the size of the output matrix.
dynamicOrientation: bool
Whether the orientation is updated at runtime. If True, a parmater input
"orientation" is instantiated that receivers pml.ListenerPositions
initialOrientation: array-like (2- or 3- element) or NoneType
The initial head rotation or the static head orientation if dynamic updates are deactivated. Given as yaw, pitch, roll.
"""
# Call base class (AtomicComponent) constructor
super(HoaRotationMatrixCalculator,
self).__init__(context, name, parent)
self.hoaOrder = hoaOrder
self.numHoaCoeffs = (self.hoaOrder + 1)**2
# Number of nonzero matrix coefficients.
# Explisit formula sum( (2i+1)^2 ) for i = 0 .. hoaOrder
# This is always an integer (i.e., multiple of 3 before division).
self.numMatrixCoeffs = ((hoaOrder + 1) * (2 * hoaOrder + 1) *
(2 * hoaOrder + 3)) // 3
# %% Define parameter ports
outConfig = pml.VectorParameterConfig(self.numMatrixCoeffs)
self.coeffOutput = visr.ParameterOutput(
"coefficients", self, pml.VectorParameterFloat.staticType,
pml.DoubleBufferingProtocol.staticType, outConfig)
self.coeffOutputProtocol = self.coeffOutput.protocolOutput()
if dynamicOrientation:
self.orientationInput = visr.ParameterInput(
"orientation", self, pml.ListenerPosition.staticType,
pml.DoubleBufferingProtocol.staticType,
pml.EmptyParameterConfig())
self.orientationInputProtocol = self.orientationInput.protocolInput(
)
else:
self.orientationInputProtocol is None
if initialOrientation is None:
initialOrientation = np.zeros((3), np.float32)
else:
initialOrientation = np.asarray(initialOrientation,
dtype=np.float32)
if initialOrientation.size < 3:
initialOrientation = np.concatenate(
(initialOrientation,
np.zeros(3 - initialOrientation.size, dtype=np.float32)))
R1 = rotationMatrixReorderingACN(
calcRotationMatrix(initialOrientation))
self.rotationMatrices = allSphericalHarmonicsRotationMatrices(
self.hoaOrder, R1)