Added dimensions for x and z in Kalman filter __init__
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@ -12,7 +12,7 @@ import numpy.random as random
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class KalmanFilter:
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def __init__(self, dim, use_short_form=False):
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def __init__(self, dim_x, dim_z, use_short_form=False):
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""" Create a Kalman filter of dimension 'dim', where dimension is the
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number of state variables.
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@ -29,14 +29,14 @@ class KalmanFilter:
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"""
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self.x = 0 # state
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self.P = np.matrix(np.eye(dim)) # uncertainty covariance
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self.Q = np.matrix(np.eye(dim)) # process uncertainty
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self.u = np.matrix(np.zeros((dim,1))) # motion vector
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self.P = np.matrix(np.eye(dim_x)) # uncertainty covariance
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self.Q = np.matrix(np.eye(dim_x)) # process uncertainty
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self.u = np.matrix(np.zeros((dim_x,1))) # motion vector
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self.B = 0
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self.F = 0 # state transition matrix
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self.H = 0 # Measurement function (maps state to measurements)
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self.R = np.matrix(np.eye(1)) # state uncertainty
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self.I = np.matrix(np.eye(dim))
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self.R = np.matrix(np.eye(dim_z)) # state uncertainty
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self.I = np.matrix(np.eye(dim_x))
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if use_short_form:
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self.update = self.update_short_form
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@ -94,7 +94,7 @@ class KalmanFilter:
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if __name__ == "__main__":
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f = KalmanFilter (dim=2)
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f = KalmanFilter (dim_x=2, dim_z=2)
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f.x = np.matrix([[2.],
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[0.]]) # initial state (location and velocity)
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