def __init__(self, state=Array.Vector(), CovarianceMatrix=Array.Matrix()):
self.state = state
self.CovarianceMatrix = CovarianceMatrix
return Array.Matrix([1., 0., 0., 0.], [0., 1., 0., 0.])
def MultipleScatteringMatrix(self, index):
return Array.Identity(4) * 1e-12
def NoiseMatrix(self, index):
return Array.Identity(2) * self.xyresolution**2
if __name__ == '__main__':
import ROOT
R = ROOT.TRandom3(0)
V = Array.Identity(2) * 0.01
Nhits = 500
hits = [
Array.Vector(
sin(0.01 * i) + R.Gaus(0, .1), -cos(0.1 * i) + R.Gaus(0, .1))
for i in range(Nhits)
]
runnings = map(float, range(Nhits))
measurements = [KalmanData(h, V) for h in hits]
istate = Array.Vector(hits[0][0], hits[0][1], 0., 0.)
istate = Array.Vector(0., 0., 0., 0.)
icvmatrix = Array.Identity(4) * 2
nextkf = NEXTKF()
nextkf = TrigoKF()
nextkf.SetMeasurements(runnings, measurements)
nextkf.SetInitialState(KalmanData(istate, icvmatrix))
track = nextkf.Fit()
p = track.Plot()
p3 = track.Plot3D()