class MotorUnitPool(object):
'''
Class that implements a motor unit pool. Encompasses a set of motor
units that controls a single muscle.
'''
def __init__(self, conf, pool):
'''
Constructor
- Inputs:
+ **conf**: Configuration object with the simulation parameters.
+ **pool**: string with Motor unit pool to which the motor unit belongs.
'''
## Indicates that is Motor Unit pool.
self.kind = 'MU'
## Configuration object with the simulation parameters.
self.conf = conf
## String with Motor unit pool to which the motor unit belongs.
self.pool = pool
MUnumber_S = int(conf.parameterSet('MUnumber_' + pool + '-S', pool, 0))
MUnumber_FR = int(
conf.parameterSet('MUnumber_' + pool + '-FR', pool, 0))
MUnumber_FF = int(
conf.parameterSet('MUnumber_' + pool + '-FF', pool, 0))
## Number of motor units.
self.MUnumber = MUnumber_S + MUnumber_FR + MUnumber_FF
## List of MotorUnit objects.
self.unit = []
for i in xrange(0, self.MUnumber):
if i < MUnumber_S:
self.unit.append(MotorUnit(conf, pool, i, 'S'))
elif i < MUnumber_S + MUnumber_FR:
self.unit.append(MotorUnit(conf, pool, i, 'FR'))
else:
self.unit.append(MotorUnit(conf, pool, i, 'FF'))
## Vector with the instants of spikes in the soma compartment, in ms.
self.poolSomaSpikes = np.array([])
## Vector with the instants of spikes in the terminal, in ms.
self.poolTerminalSpikes = np.array([])
#activation signal
self.Activation = MuscularActivation(self.conf, self.pool,
self.MUnumber, self.unit)
#Force
## String indicating whther a Hill model is used or not. For now, it can be *No*.
self.hillModel = conf.parameterSet('hillModel', pool, 0)
if self.hillModel == 'No':
self.Muscle = MuscleNoHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
else:
self.Muscle = MuscleHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
##
#print 'Motor Unit Pool ' + pool + ' built'
# MP
# Spawn de dois processos no codigo cprc.py
self.comm = MPI.COMM_SELF.Spawn(sys.executable,
args=['cprc.py'],
maxprocs=1)
# Merge para juntar todos processos em um so grupo
self.common_comm = self.comm.Merge(False)
# Numero de processos (tamanho do comunicador)
self.size = self.common_comm.Get_size()
print 'size = ' + str(self.size)
# Porcao que cada processo recebe
# Processo pai nao participa (por isso - 1)
self.procSize = len(self.unit) / (self.size - 1)
def atualizeMotorUnitPool(self, t):
'''
Update all parts of the Motor Unit pool. It consists
to update all motor units, the activation signal and
the muscle force.
- Inputs:
+ **t**: current instant, in ms.
'''
t = self.common_comm.bcast(t, root=0)
for rank in xrange(1, self.size):
self.common_comm.send(self.unit[(rank - 1) * self.procSize:rank *
self.procSize],
dest=rank,
tag=rank)
for rank in xrange(1, self.size):
self.unit[(rank - 1) * self.procSize:rank *
self.procSize] = self.common_comm.recv(source=rank,
tag=rank)
#self.common_comm.Recv(self.unit[(rank - 1) * self.procSize:rank * self.procSize], source=rank,tag=rank)
# Forma original
#for i in self.unit: i.atualizeMotorUnit(t)
self.Activation.atualizeActivationSignal(t, self.unit)
self.Muscle.atualizeForce(self.Activation.activation_Sat)
def listSpikes(self):
'''
List the spikes that occurred in the soma and in
the terminal of the different motor units.
'''
for i in xrange(0, self.MUnumber):
if i == 0:
somaSpikeTrain = np.array(self.unit[i].somaSpikeTrain)
terminalSpikeTrain = np.array(self.unit[i].terminalSpikeTrain)
else:
somaSpikeTrain = np.append(
somaSpikeTrain, np.array(self.unit[i].somaSpikeTrain))
terminalSpikeTrain = np.append(
terminalSpikeTrain,
np.array(self.unit[i].terminalSpikeTrain))
self.poolSomaSpikes = somaSpikeTrain
self.poolTerminalSpikes = terminalSpikeTrain
self.poolSomaSpikes = np.reshape(self.poolSomaSpikes, (-1, 2))
self.poolTerminalSpikes = np.reshape(self.poolTerminalSpikes, (-1, 2))
class MotorUnitPool(object):
'''
Class that implements a motor unit pool. Encompasses a set of motor
units that controls a single muscle.
'''
def __init__(self, conf, pool):
'''
Constructor
- Inputs:
+ **conf**: Configuration object with the simulation parameters.
+ **pool**: string with Motor unit pool to which the motor unit belongs.
'''
## Indicates that is Motor Unit pool.
self.kind = 'MU'
## Configuration object with the simulation parameters.
self.conf = conf
## String with Motor unit pool to which the motor unit belongs.
self.pool = pool
MUnumber_S = int(conf.parameterSet('MUnumber_' + pool + '-S', pool, 0))
MUnumber_FR = int(
conf.parameterSet('MUnumber_' + pool + '-FR', pool, 0))
MUnumber_FF = int(
conf.parameterSet('MUnumber_' + pool + '-FF', pool, 0))
## Number of motor units.
self.MUnumber = MUnumber_S + MUnumber_FR + MUnumber_FF
## List of MotorUnit objects.
self.unit = []
for i in xrange(0, self.MUnumber):
if i < MUnumber_S:
self.unit.append(MotorUnit(conf, pool, i, 'S'))
elif i < MUnumber_S + MUnumber_FR:
self.unit.append(MotorUnit(conf, pool, i, 'FR'))
else:
self.unit.append(MotorUnit(conf, pool, i, 'FF'))
## Vector with the instants of spikes in the soma compartment, in ms.
self.poolSomaSpikes = np.array([])
## Vector with the instants of spikes in the terminal, in ms.
self.poolTerminalSpikes = np.array([])
#activation signal
self.Activation = MuscularActivation(self.conf, self.pool,
self.MUnumber, self.unit)
#Force
## String indicating whther a Hill model is used or not. For now, it can be *No*.
self.hillModel = conf.parameterSet('hillModel', pool, 0)
if self.hillModel == 'No':
self.Muscle = MuscleNoHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
else:
self.Muscle = MuscleHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
##
#print 'Motor Unit Pool ' + pool + ' built'
# MPI
self.comm = MPI.COMM_WORLD
self.size = self.comm.Get_size()
self.rank = self.comm.Get_rank()
self.procSize = self.MUnumber / self.size
self.unitSlice = []
print 'size ' + str(self.size)
print 'rank ' + str(self.rank)
print 'procSize ' + str(self.procSize)
def atualizeMotorUnitPool(self, t):
'''
Update all parts of the Motor Unit pool. It consists
to update all motor units, the activation signal and
the muscle force.
- Inputs:
+ **t**: current instant, in ms.
'''
#### Primeira tentativa a falhar
#self.unitSlice = copy.deepcopy(self.unit[self.rank * self.procSize:(self.rank + 1) * self.procSize])
#for i in self.unitSlice: i.atualizeMotorUnit(t)
#self.aux = self.comm.allgather (self.unitSlice)
#self.unit = copy.deepcopy(list(itertools.chain.from_iterable(self.aux)))
####
####
# Forma original de se atualizar as unidades
# Forma original
#for i in self.unit: i.atualizeMotorUnit(t)
# Forma levemente alterada
#for i in xrange(self.rank * self.procSize,(self.rank + 1) * self.procSize):
# self.unit[i].atualizeMotorUnit(t)
####
#### Alteracoes principais
# Cada processo usa um pedaco de self.unit
unittest = []
for i in xrange(self.rank * self.procSize,
(self.rank + 1) * self.procSize):
self.unitSlice.append(self.unit[i])
for i in self.unitSlice:
i.atualizeMotorUnit(t)
# Fazer atualize MotorUnit normalmente e entao usar allgather reproduz
# o erro
aux = self.comm.allgather(self.unitSlice)
# Flattening, pois allgather retorna lista de listas
for i in xrange(len(aux)):
for j in xrange(len(aux[i])):
unittest.append((aux[i])[j])
# alternativa ao metodo acima
#self.unittest=list(itertools.chain.from_iterable(self.aux))
# Para checar se sao iguais
#if self.rank==0:
# print self.unittest[0]==self.unit[0]
# print vars(self.unittest[0])
# print vars(self.unit[0])
# Retornando valores para self.unit
self.unit = []
for i in xrange(len(unittest)):
#self.unit.append(copy.copy(self.unittest[i])) # alternativa
self.unit.append(unittest[i])
# Checando os objetos synapses
#if self.rank==0:
# print vars(self.unit[0].transmitSpikesThroughSynapses[0]), '1'
# print vars(self.unit[0].transmitSpikesThroughSynapses[1]), '2'
self.unitSlice = []
## O valor dessa variavel e sempre zero qnd o erro ocorre
#print self.unit[0].iIonic
####
self.Activation.atualizeActivationSignal(t, self.unit)
self.Muscle.atualizeForce(self.Activation.activation_Sat)
def listSpikes(self):
'''
List the spikes that occurred in the soma and in
the terminal of the different motor units.
'''
for i in xrange(0, self.MUnumber):
if i == 0:
somaSpikeTrain = np.array(self.unit[i].somaSpikeTrain)
terminalSpikeTrain = np.array(self.unit[i].terminalSpikeTrain)
else:
somaSpikeTrain = np.append(
somaSpikeTrain, np.array(self.unit[i].somaSpikeTrain))
terminalSpikeTrain = np.append(
terminalSpikeTrain,
np.array(self.unit[i].terminalSpikeTrain))
self.poolSomaSpikes = somaSpikeTrain
self.poolTerminalSpikes = terminalSpikeTrain
self.poolSomaSpikes = np.reshape(self.poolSomaSpikes, (-1, 2))
self.poolTerminalSpikes = np.reshape(self.poolTerminalSpikes, (-1, 2))
class MotorUnitPool(object):
'''
Class that implements a motor unit pool. Encompasses a set of motor
units that controls a single muscle.
'''
def __init__(self, conf, pool):
'''
Constructor
- Inputs:
+ **conf**: Configuration object with the simulation parameters.
+ **pool**: string with Motor unit pool to which the motor unit belongs.
'''
self.t = 0
## Indicates that is Motor Unit pool.
self.kind = 'MU'
## Configuration object with the simulation parameters.
self.conf = conf
## String with Motor unit pool to which the motor unit belongs.
self.pool = pool
MUnumber_S = int(conf.parameterSet('MUnumber_' + pool + '-S', pool, 0))
MUnumber_FR = int(
conf.parameterSet('MUnumber_' + pool + '-FR', pool, 0))
MUnumber_FF = int(
conf.parameterSet('MUnumber_' + pool + '-FF', pool, 0))
## Number of motor units.
self.MUnumber = MUnumber_S + MUnumber_FR + MUnumber_FF
## Muscle thickness, in mm.
self.muscleThickness_mm = float(
self.conf.parameterSet('thickness:' + pool, pool, 0))
## Dictionary of MotorUnit objects.
self.unit = dict()
for i in xrange(0, self.MUnumber):
if i < MUnumber_S:
self.unit[i] = MotorUnit(conf, pool, i, 'S',
self.muscleThickness_mm,
conf.skinThickness_mm)
elif i < MUnumber_S + MUnumber_FR:
self.unit[i] = MotorUnit(conf, pool, i, 'FR',
self.muscleThickness_mm,
conf.skinThickness_mm)
else:
self.unit[i] = MotorUnit(conf, pool, i, 'FF',
self.muscleThickness_mm,
conf.skinThickness_mm)
# This is used to get values from MotorUnit.py and make computations
# in MotorUnitPool.py
# TODO create it all here instead?
self.totalNumberOfCompartments = 0
for i in xrange(self.MUnumber):
self.totalNumberOfCompartments = self.totalNumberOfCompartments \
+ self.unit[i].compNumber
self.v_mV = np.zeros((self.totalNumberOfCompartments), dtype=np.double)
self.G = lil_matrix(
(self.totalNumberOfCompartments, self.totalNumberOfCompartments),
dtype=float)
self.iInjected = np.zeros_like(self.v_mV, dtype='d')
self.capacitanceInv = np.zeros_like(self.v_mV, dtype='d')
self.iIonic = np.full_like(self.v_mV, 0.0)
self.EqCurrent_nA = np.zeros_like(self.v_mV, dtype='d')
# Retrieving data from Motorneuron class
# Vectors or matrices from Motorneuron compartments are copied,
# populating larger vectors or matrices that will be used for computations
for i in xrange(self.MUnumber):
self.v_mV[i*self.unit[i].compNumber:i*self.unit[i].compNumber \
+self.unit[i].v_mV.shape[0]] = self.unit[i].v_mV
# Consists of smaller matrices on its diagonal
self.G[i*self.unit[i].compNumber:i*self.unit[i].compNumber \
+self.unit[i].G.shape[0], \
i*self.unit[i].compNumber:i*self.unit[i].compNumber \
+self.unit[i].G.shape[1]] = self.unit[i].G
self.capacitanceInv[i*self.unit[i].compNumber: \
i*self.unit[i].compNumber \
+self.unit[i].capacitanceInv.shape[0]] \
= self.unit[i].capacitanceInv
self.EqCurrent_nA[i*self.unit[i].compNumber: \
i*self.unit[i].compNumber \
+self.unit[i].EqCurrent_nA.shape[0]] \
= self.unit[i].EqCurrent_nA
self.sizeOfBlock = int(self.totalNumberOfCompartments / self.MUnumber)
self.G = self.G.tobsr(blocksize=(self.sizeOfBlock, self.sizeOfBlock))
# TODO Conditional GPU use
#self.GGPU = pcu.csr_matrix(self.G)
#self.GPU = pcu.Sparse(0)
#self.m, self.n = self.GGPU.shape
#self.nnz = self.GGPU.nnz
#self.descr = self.GPU.matdescr()
#self.csrVal = self.GGPU.data
#self.csrRowPtr = self.GGPU.indptr
#self.csrColInd = self.GGPU.indices
self.dVdtValue = np.empty(self.totalNumberOfCompartments,
dtype=np.double)
## Vector with the instants of spikes in the soma compartment, in ms.
self.poolSomaSpikes = np.array([])
## Vector with the instants of spikes in the last dynamical compartment, in ms.
self.poolLastCompSpikes = np.array([])
## Vector with the instants of spikes in the terminal, in ms.
self.poolTerminalSpikes = np.array([])
#activation signal
self.Activation = MuscularActivation(self.conf, self.pool,
self.MUnumber, self.unit)
#Force
## String indicating whther a Hill model is used or not. For now, it can be *No*.
self.hillModel = conf.parameterSet('hillModel', pool, 0)
if self.hillModel == 'No':
self.Muscle = MuscleNoHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
else:
self.Muscle = MuscleHill(self.conf, self.pool, self.MUnumber,
MUnumber_S, self.unit)
# EMG
## EMG along time, in mV.
self.emg = np.zeros(
(int(np.rint(conf.simDuration_ms / conf.timeStep_ms)), 1),
dtype=float)
# Spindle
self.spindle = MuscleSpindle(self.conf, self.pool)
##
print 'Motor Unit Pool ' + pool + ' built'
def atualizeMotorUnitPool(self, t):
'''
Update all parts of the Motor Unit pool. It consists
to update all motor units, the activation signal and
the muscle force.
- Inputs:
+ **t**: current instant, in ms.
'''
np.clip(
runge_kutta(self.dVdt, t, self.v_mV, self.conf.timeStep_ms,
self.conf.timeStepByTwo_ms,
self.conf.timeStepBySix_ms), -30.0, 120.0, self.v_mV)
for i in xrange(self.MUnumber):
self.unit[i].atualizeMotorUnit(
t, self.v_mV[i * self.unit[i].compNumber:(i + 1) *
self.unit[i].compNumber])
self.Activation.atualizeActivationSignal(t, self.unit)
self.Muscle.atualizeForce(self.Activation.activation_Sat)
self.spindle.atualizeMuscleSpindle(t, self.Muscle.lengthNorm,
self.Muscle.velocityNorm,
self.Muscle.accelerationNorm, 31,
33)
def dVdt(self, t, V):
#k = 0
for i in xrange(self.MUnumber):
for j in xrange(self.unit[i].compNumber):
self.iIonic.itemset(
i * self.unit[0].compNumber + j,
self.unit[i].compartment[j].computeCurrent(
t, V.item(i * self.unit[0].compNumber + j)))
#k += 1
return (self.iIonic + self.G.dot(V) + self.iInjected +
self.EqCurrent_nA) * self.capacitanceInv
'''
# TODO Conditional GPU use
self.GPU.csrmv('N', self.m, self.n, self.nnz, 1.0, self.descr, self.csrVal, self.csrRowPtr, self.csrColInd, V, 0.0, self.dVdtValue)
return (self.iIonic + self.dVdtValue + self.iInjected
+ self.EqCurrent_nA) * self.capacitanceInv
return (self.iIonic + SpMV_viaMKL(self.G,V,self.MUnumber, self.sizeOfBlock) + self.iInjected
+ self.EqCurrent_nA) * self.capacitanceInv
'''
def listSpikes(self):
'''
List the spikes that occurred in the soma and in
the terminal of the different motor units.
'''
for i in xrange(0, self.MUnumber):
if i == 0:
somaSpikeTrain = np.array(self.unit[i].somaSpikeTrain)
lastCompSpikeTrain = np.array(self.unit[i].lastCompSpikeTrain)
terminalSpikeTrain = np.array(self.unit[i].terminalSpikeTrain)
else:
somaSpikeTrain = np.append(
somaSpikeTrain, np.array(self.unit[i].somaSpikeTrain))
lastCompSpikeTrain = np.append(
lastCompSpikeTrain,
np.array(self.unit[i].lastCompSpikeTrain))
terminalSpikeTrain = np.append(
terminalSpikeTrain,
np.array(self.unit[i].terminalSpikeTrain))
self.poolSomaSpikes = np.reshape(somaSpikeTrain, (-1, 2))
self.poolLastCompSpikes = np.reshape(lastCompSpikeTrain, (-1, 2))
self.poolTerminalSpikes = np.reshape(terminalSpikeTrain, (-1, 2))
def getMotorUnitPoolInstantEMG(self, t):
'''
'''
emg = 0
for i in xrange(self.MUnumber):
emg += self.unit[i].getEMG(t)
return emg
def getMotorUnitPoolEMG(self):
'''
'''
for i in xrange(0, len(self.emg)):
self.emg[i] = self.getMotorUnitPoolInstantEMG(
i * self.conf.timeStep_ms)
def reset(self):
'''
'''
self.poolSomaSpikes = np.array([])
self.poolLastCompSpikes = np.array([])
self.poolTerminalSpikes = np.array([])
self.emg = np.zeros((int(
np.rint(self.conf.simDuration_ms / self.conf.timeStep_ms)), 1),
dtype=float)
for i in xrange(self.MUnumber):
self.unit[i].reset()
self.Activation.reset()
self.Muscle.reset()
class MotorUnitPool(object):
'''
Class that implements a motor unit pool. Encompasses a set of motor
units that controls a single muscle.
'''
def __init__(self, conf, pool):
'''
Constructor
- Inputs:
+ **conf**: Configuration object with the simulation parameters.
+ **pool**: string with Motor unit pool to which the motor unit belongs.
'''
## Indicates that is Motor Unit pool.
self.kind = 'MU'
## Configuration object with the simulation parameters.
self.conf = conf
## String with Motor unit pool to which the motor unit belongs.
self.pool = pool
MUnumber_S = int(conf.parameterSet('MUnumber_S_' + pool, pool, 0))
MUnumber_FR = int(conf.parameterSet('MUnumber_FR_' + pool, pool, 0))
MUnumber_FF = int(conf.parameterSet('MUnumber_FF_' + pool, pool, 0))
## Number of motor units.
self.MUnumber = MUnumber_S + MUnumber_FR + MUnumber_FF
## List of MotorUnit objects.
self.unit = []
for i in xrange(0, self.MUnumber):
if i < MUnumber_S:
self.unit.append(MotorUnit(conf, pool, i, 'S'))
elif i < MUnumber_S + MUnumber_FR:
self.unit.append(MotorUnit(conf, pool, i, 'FR'))
else:
self.unit.append(MotorUnit(conf, pool, i, 'FF'))
## Vector with the instants of spikes in the soma compartment, in ms.
self.poolSomaSpikes = np.array([])
## Vector with the instants of spikes in the terminal, in ms.
self.poolTerminalSpikes = np.array([])
#activation signal
self.Activation = MuscularActivation(self.conf,self.pool, self.MUnumber,self.unit)
#Force
## String indicating whther a Hill model is used or not. For now, it can be *No*.
self.hillModel = conf.parameterSet('hillModel',pool, 0)
if self.hillModel == 'No':
self.Muscle = MuscleNoHill(self.conf, self.pool, self.MUnumber, MUnumber_S, self.unit)
else:
self.Muscle = MuscleHill(self.conf, self.pool, self.MUnumber, MUnumber_S, self.unit)
##
print 'Motor Unit Pool ' + pool + ' built'
def atualizeMotorUnitPool(self, t):
'''
Update all parts of the Motor Unit pool. It consists
to update all motor units, the activation signal and
the muscle force.
- Inputs:
+ **t**: current instant, in ms.
'''
for i in self.unit: i.atualizeMotorUnit(t)
self.Activation.atualizeActivationSignal(t, self.unit)
self.Muscle.atualizeForce(self.Activation.activation_Sat)
def listSpikes(self):
'''
List the spikes that occurred in the soma and in
the terminal of the different motor units.
'''
for i in xrange(0,self.MUnumber):
if i == 0:
somaSpikeTrain = np.array(self.unit[i].somaSpikeTrain)
terminalSpikeTrain = np.array(self.unit[i].terminalSpikeTrain)
else:
somaSpikeTrain = np.append(somaSpikeTrain, np.array(self.unit[i].somaSpikeTrain))
terminalSpikeTrain = np.append(terminalSpikeTrain, np.array(self.unit[i].terminalSpikeTrain))
self.poolSomaSpikes = somaSpikeTrain
self.poolTerminalSpikes = terminalSpikeTrain
self.poolSomaSpikes = np.reshape(self.poolSomaSpikes, (-1, 2))
self.poolTerminalSpikes = np.reshape(self.poolTerminalSpikes, (-1, 2))