Na.kalman in python

>>> from pykalman import KalmanFilter
>>> import numpy as np
>>> kf = KalmanFilter(transition_matrices = [[1, 1], [0, 1]], observation_matrices = [[0.1, 0.5], [-0.3, 0.0]])
>>> measurements = np.asarray([[1,0], [0,0], [0,1]])  # 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)

Source: pykalman.github.io

Similar codes

0 vote326 views1 answer
Django create view class
Python
1 vote318 views1 answer
Python iterate over multidimensional dictionary
Python
11 votes342 views2 answers
Save machine learning model
Python
0 vote334 views1 answer
Django choicefield empty label
Python
0 vote293 views2 answers
Python union type
Python
0 vote322 views1 answer
Class has no object members
Python
-2 votes341 views4 answers
Merge multiple dataframs
Python
0 vote324 views1 answer
Python strong type
Python
1 vote421 views1 answer
How to add captcha in django forms
Python Django
0 vote337 views1 answer
OneHotEncoder pyspark
Python