pykalman An implementation of the Kalman Filter, Kalman Smoother, and EM algorithm in Python
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Python filter Kalman Filter

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pykalman is a the dead-simple Kalman Filter, Kalman Smoother, and EM library for Python:>>> from pykalman import KalmanFilter>>> import numpy as np>>> kf = KalmanFilter(transition_matrices = , ], observation_matrices = , ])>>> measurements = np.asarray(, , ]) # 3 observations>>> kf = kf.em(measurements, n_iter=5)>>> (filtered_state_means, filtered_state_covariances) = kf.filter(measurements)>>> (smoothed_state_means, smoothed_state_covariances) = kf.smooth(measurements)Also included is support for missing measurements:>>> from numpy import ma>>> measurements = ma.asarray(measurements)>>> measurements = ma.masked # measurement at timestep 1 is unobserved>>> kf = kf.em(measurements, n_iter=5)>>> (filtered_state_means, filtered_state_covariances) = kf.filter(measurements)>>> (smoothed_state_means, smoothed_state_covariances) = kf.smooth(measurements)And for the non-linear dynamics via the UnscentedKalmanFilter:>>> I'll fill this in someday...InstallationFor a quick installation: easy_install pykalmanAll of these and pykalman can be installed using easy_install:easy_install numpy scipy Sphinx numpydoc nose pykalmanAlternatively, you can get the latest and greatest from github: git clone git@github.com:pykalman/pykalman.git pykalman cd pykalman sudo python setup.py installProduct's homepage

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