def confmat(L1, L2) :
"""computes the confusion matrix between two labelings
"""
if len(L1) != len(L2):
raise ValueError, "labels not the same length"
n = len(L1)
classes1 = misc.unique(L1)
classes2 = misc.unique(L2)
classes1.sort()
classes2.sort()
numClasses1 = len(classes1)
numClasses2 = len(classes2)
I1 = {} # a mapping from classes1 to 0..numclasses1-1
I2 = {}
for i in range(numClasses1) :
I1[classes1[i]] = i
for i in range(numClasses2) :
I2[classes2[i]] = i
confmat = numpy.zeros((numClasses1, numClasses2))
for i in range(n):
confmat[I1[L1[i]]][I2[L2[i]]] += 1
return confmat
def confmat(L1, L2) :
"""computes the confusion matrix between two labelings
"""
if len(L1) != len(L2):
raise ValueError, "labels not the same length"
n = len(L1)
classes1 = misc.unique(L1)
classes2 = misc.unique(L2)
classes1.sort()
classes2.sort()
numClasses1 = len(classes1)
numClasses2 = len(classes2)
I1 = {} # a mapping from classes1 to 0..numclasses1-1
I2 = {}
for i in range(numClasses1) :
I1[classes1[i]] = i
for i in range(numClasses2) :
I2[classes2[i]] = i
confmat = numpy.zeros((numClasses1, numClasses2))
for i in range(n):
confmat[I1[L1[i]]][I2[L2[i]]] += 1
return confmat
def postProcess(self) :
if len(self._featureDict.keys()) != len(misc.unique(self._featureDict.values())) :
print len(self._featureDict.keys()), len(misc.unique(self._featureDict.values()))
raise ValueError, 'non-unique hash'
featureKeyDict = {}
featureKey = self._featureDict.values()
featureKey.sort()
for i in range(len(featureKey)) :
featureKeyDict[featureKey[i]] = i
inverseFeatureDict = misc.invertDict(self._featureDict)
featureID = [str(inverseFeatureDict[key]) for key in featureKey]
return featureID, featureKey, featureKeyDict
def postProcess(self):
if len(self._featureDict.keys()) != len(
misc.unique(self._featureDict.values())):
print len(self._featureDict.keys()), len(
misc.unique(self._featureDict.values()))
raise ValueError, 'non-unique hash'
featureKeyDict = {}
featureKey = self._featureDict.values()
featureKey.sort()
for i in range(len(featureKey)):
featureKeyDict[featureKey[i]] = i
inverseFeatureDict = misc.invertDict(self._featureDict)
featureID = [str(inverseFeatureDict[key]) for key in featureKey]
return featureID, featureKey, featureKeyDict
