def __init__(self, Model):
self.input = Model.input
self.output = Model.output
self.input_test = Model.input_test
self.output_test = Model.output_test
self.gradient_ker = diff.gradient_ker(Model)
self.gradient_NL = diff.gradient_NL(Model)
self.hessian_ker = diff.hessian_ker(Model)
self.hessian_NL = diff.hessian_NL(Model)
self.paramKer = Model.paramKer
self.paramNL = Model.paramNL
self.lls = Model.lls
self.Mds = Model.Mds
self.switches = Model.switches
#self.neustd = Model.neustd
self.likelihood = diff.likelihood(Model)
self.sub_membrane_potential = diff.subMembPot(Model, 'training')
self.membrane_potential = diff.MembPot(Model)
def __init__(self,Model): self.input = Model.input self.output = Model.output self.input_test = Model.input_test self.output_test = Model.output_test self.gradient_ker = diff.gradient_ker(Model) self.gradient_NL = diff.gradient_NL(Model) self.hessian_ker = diff.hessian_ker(Model) self.hessian_NL = diff.hessian_NL(Model) self.paramKer = Model.paramKer self.paramNL = Model.paramNL self.lls = Model.lls self.Mds = Model.Mds self.switches = Model.switches #self.neustd = Model.neustd self.likelihood = diff.likelihood(Model) self.sub_membrane_potential = diff.subMembPot(Model,'training') self.membrane_potential = diff.MembPot(Model)
def update(self):
self.sub_membrane_potential = diff.subMembPot(self, 'training')
self.membrane_potential = diff.MembPot(self)
self.likelihood = diff.likelihood(self)
self.gradient_ker = diff.gradient_ker(self)
self.hessian_ker = diff.hessian_ker(self)
self.gradient_NL = diff.gradient_NL(self)
self.hessian_NL = diff.hessian_NL(self)
def update(self): self.sub_membrane_potential = diff.subMembPot(self,'training') self.membrane_potential = diff.MembPot(self) self.likelihood = diff.likelihood(self) self.gradient_ker = diff.gradient_ker(self) self.hessian_ker = diff.hessian_ker(self) self.gradient_NL = diff.gradient_NL(self) self.hessian_NL = diff.hessian_NL(self)
def add_data(self, neuron): #import data from neuron
Nsteps = neuron.total_time / self.dt
self.input = neuron.input
self.output = [neuron.output]
self.paramKer[-1] = -math.log(
len(neuron.output) /
float(neuron.total_time)) #initialize for fit.
#self.neustd = neuron.sub_memb_pot.std()
self.sub_membrane_potential = diff.subMembPot(self, 'training')
self.membrane_potential = diff.MembPot(self)
self.input_test = neuron.input_test
self.output_test = neuron.output_test
def test(self):
Nb = self.basisKer.shape[0]
self.out_model_test = []
self.sub_memb_pot_test = diff.subMembPot(self, 'test')
print "testing ..."
for i in range(100):
self.out_model_test = self.out_model_test + [
mech.run_model(self.input_test, self)
]
self.delta_md = 4.
self.Md = fun.SimMeas(self.out_model_test, self.output_test, self,
self.delta_md)
def membpot(self):
self.sub_membrane_potential = diff.subMembPot(self, 'training')
self.membrane_potential = diff.MembPot(self)
