def getParameter(self, parameterName, index=-1):
"""
Get the value of a NodeSpec parameter. Most parameters are handled
automatically by PyRegion's parameter get mechanism. The ones that need
special treatment are explicitly handled here.
"""
if parameterName == 'activeOutputCount':
return self.columnCount
elif parameterName == 'spatialPoolerInput':
return list(self._spatialPoolerInput.reshape(-1))
elif parameterName == 'spatialPoolerOutput':
return list(self._spatialPoolerOutput)
elif parameterName == 'spNumActiveOutputs':
return len(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spOutputNonZeros':
return [len(self._spatialPoolerOutput)] + \
list(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spInputNonZeros':
import pdb; pdb.set_trace()
return [len(self._spatialPoolerInput)] + \
list(self._spatialPoolerInput.nonzero()[0])
elif parameterName == 'spLearningStatsStr':
try:
return str(self._sfdr.getLearningStats())
except:
return str(dict())
else:
return PyRegion.getParameter(self, parameterName, index)
def getParameter(self, parameterName, index=-1):
"""
Get the value of a NodeSpec parameter. Most parameters are handled
automatically by PyRegion's parameter get mechanism. The ones that need
special treatment are explicitly handled here.
"""
if parameterName == 'activeOutputCount':
return self.columnCount
elif parameterName == 'spatialPoolerInput':
return list(self._spatialPoolerInput.reshape(-1))
elif parameterName == 'spatialPoolerOutput':
return list(self._spatialPoolerOutput)
elif parameterName == 'spNumActiveOutputs':
return len(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spOutputNonZeros':
return [len(self._spatialPoolerOutput)] + \
list(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spInputNonZeros':
import pdb
pdb.set_trace()
return [len(self._spatialPoolerInput)] + \
list(self._spatialPoolerInput.nonzero()[0])
elif parameterName == 'spLearningStatsStr':
try:
return str(self._sfdr.getLearningStats())
except:
return str(dict())
else:
return PyRegion.getParameter(self, parameterName, index)
def getParameter(self, parameterName, index=-1):
"""
Get the value of a NodeSpec parameter. Most parameters are handled
automatically by PyRegion's parameter get mechanism. The ones that need
special treatment are explicitly handled here.
"""
if parameterName == 'sparseCoincidenceMatrix':
if not self._sfdr:
return None
return self._sfdr.cm
elif parameterName == 'activeOutputCount':
return self.columnCount
elif parameterName == 'spatialPoolerInput':
return list(self._spatialPoolerInput.reshape(-1))
elif parameterName == 'spatialPoolerOutput':
return list(self._spatialPoolerOutput)
elif parameterName == 'spNumActiveOutputs':
return len(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spOverlapDistribution':
if not self._sfdr:
return []
# Get the dense output (will only work if you've done storeDenseOutput)
try:
denseOutput = self._sfdr.getDenseOutput()
if len(denseOutput) == 0:
raise Exception("storeDenseOutput wasn't set in PY version")
denseOutput = numpy.array(denseOutput)
except Exception:
print "WARNING: You must enable storing dense output in the SP using" \
"setStoreDenseOutput."
return []
winnerIndices = numpy.array(self._spatialPoolerOutput).nonzero()[0]
overlaps = denseOutput[winnerIndices]
# Sort descending and convert to list...
overlaps = sorted(overlaps, reverse=True)
return overlaps
elif parameterName == "denseOutput":
# Must be a list, not a numpy array to make NuPIC happy...
denseOutput = self._sfdr.getDenseOutput()
if not isinstance(denseOutput, list):
assert isinstance(denseOutput, numpy.ndarray)
denseOutput = list(denseOutput)
return denseOutput
elif parameterName == 'spOutputNonZeros':
return [len(self._spatialPoolerOutput)] + \
list(self._spatialPoolerOutput.nonzero()[0])
elif parameterName == 'spInputNonZeros':
import pdb; pdb.set_trace()
return [len(self._spatialPoolerInput)] + \
list(self._spatialPoolerInput.nonzero()[0])
elif parameterName == 'spLearningStatsStr':
try:
return str(self._sfdr.getLearningStats())
except:
return str(dict())
else:
return PyRegion.getParameter(self, parameterName, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "patternCount":
return self._knn._numPatterns
elif name == "patternMatrix":
return self._getPatternMatrix()
elif name == "k":
return self._knn.k
elif name == "distanceNorm":
return self._knn.distanceNorm
elif name == "distanceMethod":
return self._knn.distanceMethod
elif name == "distThreshold":
return self._knn.distThreshold
elif name == "inputThresh":
return self._knn.binarizationThreshold
elif name == "doBinarization":
return self._knn.doBinarization
elif name == "useSparseMemory":
return self._knn.useSparseMemory
elif name == "sparseThreshold":
return self._knn.sparseThreshold
elif name == "winnerCount":
return self._knn.numWinners
elif name == "relativeThreshold":
return self._knn.relativeThreshold
elif name == "SVDSampleCount":
v = self._knn.numSVDSamples
return v if v is not None else 0
elif name == "SVDDimCount":
v = self._knn.numSVDDims
return v if v is not None else 0
elif name == "fractionOfMax":
v = self._knn.fractionOfMax
return v if v is not None else 0
elif name == "useAuxiliary":
return self._useAuxiliary
elif name == "justUseAuxiliary":
return self._justUseAuxiliary
elif name == "doSphering":
return self._doSphering
elif name == "cellsPerCol":
return self._knn.cellsPerCol
elif name == "maxStoredPatterns":
return self.maxStoredPatterns
elif name == 'categoryRecencyList':
return self._knn._categoryRecencyList
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "patternCount":
return self._knn._numPatterns
elif name == "patternMatrix":
return self._getPatternMatrix()
elif name == "k":
return self._knn.k
elif name == "distanceNorm":
return self._knn.distanceNorm
elif name == "distanceMethod":
return self._knn.distanceMethod
elif name == "distThreshold":
return self._knn.distThreshold
elif name == "inputThresh":
return self._knn.binarizationThreshold
elif name == "doBinarization":
return self._knn.doBinarization
elif name == "useSparseMemory":
return self._knn.useSparseMemory
elif name == "sparseThreshold":
return self._knn.sparseThreshold
elif name == "winnerCount":
return self._knn.numWinners
elif name == "relativeThreshold":
return self._knn.relativeThreshold
elif name == "SVDSampleCount":
v = self._knn.numSVDSamples
return v if v is not None else 0
elif name == "SVDDimCount":
v = self._knn.numSVDDims
return v if v is not None else 0
elif name == "fractionOfMax":
v = self._knn.fractionOfMax
return v if v is not None else 0
elif name == "useAuxiliary":
return self._useAuxiliary
elif name == "justUseAuxiliary":
return self._justUseAuxiliary
elif name == "doSphering":
return self._doSphering
elif name == "cellsPerCol":
return self._knn.cellsPerCol
elif name == "maxStoredPatterns":
return self.maxStoredPatterns
elif name == 'categoryRecencyList':
return self._knn._categoryRecencyList
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, parameterName, index=-1):
"""
Get the value of a parameter. Most parameters are handled automatically by
PyRegion's parameter get mechanism. The ones that need special treatment
are explicitly handled here.
"""
if parameterName in self._temporalArgNames:
return getattr(self._tfdr, parameterName)
else:
return PyRegion.getParameter(self, parameterName, index)
def getParameter(self, parameterName, index=-1):
"""
Get the value of a parameter. Most parameters are handled automatically by
PyRegion's parameter get mechanism. The ones that need special treatment
are explicitly handled here.
"""
if parameterName in self._temporalArgNames:
return getattr(self._tfdr, parameterName)
else:
return PyRegion.getParameter(self, parameterName, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "trainRecords":
return self.trainRecords
elif name == "anomalyThreshold":
return self.anomalyThreshold
elif name == "activeColumnCount":
return self._activeColumnCount
elif name == "classificationMaxDist":
return self._classificationMaxDist
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of the parameter.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "trainRecords":
return self.trainRecords
elif name == "anomalyThreshold":
return self.anomalyThreshold
elif name == "activeColumnCount":
return self._activeColumnCount
elif name == "classificationMaxDist":
return self._classificationMaxDist
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of a parameter.
Note: this method may be overridden by derived classes, but if so, then
the derived class should invoke this base method if 'name'
is unknown to the derived class.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "SVDSampleCount":
return self._SVDSampleCount
elif name == "SVDDimCount":
return self._SVDDimCount
elif name == "fractionOfMax":
return self._fractionOfMax
elif name == "trainingSampleCount":
return self.gettrainingSampleCount()
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
def getParameter(self, name, index=-1):
"""
Get the value of a parameter.
Note: this method may be overridden by derived classes, but if so, then
the derived class should invoke this base method if 'name'
is unknown to the derived class.
@param name -- the name of the parameter to retrieve, as defined
by the Node Spec.
"""
if name == "SVDSampleCount":
return self._SVDSampleCount
elif name == "SVDDimCount":
return self._SVDDimCount
elif name == "fractionOfMax":
return self._fractionOfMax
elif name == "trainingSampleCount":
return self.gettrainingSampleCount()
else:
# If any spec parameter name is the same as an attribute, this call
# will get it automatically, e.g. self.learningMode
return PyRegion.getParameter(self, name, index)
