def __init__(self): fitglobals.debugoff() P = noise.NoiseParams() P.tstop = 20 P.dt = 0.1 A0 = 0.5 A1 = 0.1 P.A = numpy.matrix([[A0, 0], [0, A1]]) # P.B, next line define noise injected to each component, uncorrelated P.B = numpy.matrix([[0.5, 0], [0, 0.4]]) P.InitialCov = numpy.matrix([[1, 0], [0, 1]]) elist = numpy.arange(0.1, 20, 0.1).tolist() elist2 = numpy.arange(0.05, 20.0, 0.05).tolist() O1 = models.ObserveState0(P, 5) O2 = models.ObserveStateSum(P, 6) # O1.Times.set([2,4,6,8,10,12,14,16,18,20]) # O2.Times.set([3,6,9,12,15,18]) O1.Times.set(elist) O2.Times.set(elist) O1.sigma = 0.001 O2.sigma = 0.0001 Obs = models.ObservationModel(P, 5, [O1, O2]) Sys = models.DecayModel(P, 0, 2) # Sys.Injection.set([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]) Sys.Injection.set(elist2) Initial = numpy.matrix([[1.0], [2.0]]) self.M = models.Model(Sys, Obs, P, Initial) self.sim(False)
def __init__(self): P = noise.NoiseParams() P.tstop = 20 P.dt = 0.1 P.A = numpy.matrix(0.5) P.B = numpy.matrix([0.1]) P.InitialCov = numpy.matrix(1) O1 = models.ObserveState0(P, 5) elist = numpy.arange(0.1, 20, 0.1).tolist() elist2 = numpy.arange(0.05, 20.0, 0.05) # O1.Times.set([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]) O1.Times.set([2, 4, 6, 8, 10, 12, 14, 16, 18, 20]) # O1.Times.set(elist) O1.sigma = 0.001 Obs = models.ObservationModel(P, 5, [O1]) Sys = models.DecayModel(P, 0, 1) # Sys.Injection.set(elist2) Sys.Injection.set([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ]) self.M = models.Model(Sys, Obs, P, numpy.matrix(2)) self.sim(False)
import noise import models import fitEKF import numpy import fitglobals fitglobals.debugon() P = noise.NoiseParams() P.tstop = 20 P.dt = 0.1 P.A = numpy.matrix(0.5) P.B = numpy.matrix([0.5, 0.4, 0.3]) P.InitialCov = numpy.matrix(1) O1 = models.ObserveState0(P,5) O2 = models.ObserveState0(P,6) O1.Times.set([2,4,6,8,10,12,14,16,18,20]) O2.Times.set([3,6,9,12,15,18]) O1.sigma = 0.001 O2.sigma = 0.0001 Obs = models.ObservationModel(P,5,[O1,O2]) #Sys = models.DecayModel(P,0,3) Sys = models.NeuronModel(P,0,3) Sys.Injection.set([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]) M = models.Model(Sys,Obs,P) # Turn noise off and simulate P.B = numpy.matrix([0.,0.,0.]) # Not needed: change(P) M.Obs.C[0].sigma = 0