def getComposition(self, normalize=False, boundaryMethod=None):
"""Return numbers of each particle in a dictionary
pass this dictionary to sensorProducers
>>> a = _Environment()
>>> a.fillSensorProducer()
>>> a.getComposition()
{}
>>> a.advance()
>>> a.getComposition()
{'a': 10}
>>> a.advance()
>>> a.getComposition()
{'a': 20}
"""
post = {}
for part in self._particleArray: # part is a particle object
state = part.getState()
if state not in post:
post[state] = 0
post[state] = post[state] + 1
if boundaryMethod != None:
for key in post.keys():
pre = post[key]
post[key] = unit.boundaryFit(self.range[0], self.range[1], pre,
boundaryMethod)
if normalize:
for key in post.keys():
pre = post[key]
post[key] = unit.unitNorm(pre, self.range)
return post
def getComposition(self, normalize=False, boundaryMethod=None):
"""Return numbers of each particle in a dictionary
pass this dictionary to sensorProducers
>>> a = _Environment()
>>> a.fillSensorProducer()
>>> a.getComposition()
{}
>>> a.advance()
>>> a.getComposition()
{'a': 10}
>>> a.advance()
>>> a.getComposition()
{'a': 20}
"""
post = {}
for part in self._particleArray: # part is a particle object
state = part.getState()
if state not in post:
post[state] = 0
post[state] = post[state] + 1
if boundaryMethod != None:
for key in post.keys():
pre = post[key]
post[key] = unit.boundaryFit(self.range[0],
self.range[1], pre, boundaryMethod)
if normalize:
for key in post.keys():
pre = post[key]
post[key] = unit.unitNorm(pre, self.range)
return post
def __call__(self, valArray, tArray, refDictArray):
# vale and time should always be the same length
assert (len(valArray) == len(tArray)
and len(tArray) == len(refDictArray))
# process each value
self.currentValue = []
for i in range(len(valArray)):
val = valArray[i]
t = tArray[i]
refDict = refDictArray[i]
# get parameter obj values
a = self.boundingPmtrObjA(t, refDict)
b = self.boundingPmtrObjB(t, refDict)
self.currentValue.append(
unit.boundaryFit(a, b, val, self.boundaryMethod))
# return list of values
return self.currentValue
def __call__(self, valArray, tArray, refDictArray):
# vale and time should always be the same length
assert (len(valArray) == len(tArray) and
len(tArray) == len(refDictArray))
# process each value
self.currentValue = []
for i in range(len(valArray)):
val = valArray[i]
t = tArray[i]
refDict = refDictArray[i]
# get parameter obj values
a = self.boundingPmtrObjA(t, refDict)
b = self.boundingPmtrObjB(t, refDict)
self.currentValue.append(unit.boundaryFit(a, b, val,
self.boundaryMethod))
# return list of values
return self.currentValue
