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 vote167 views1 answer
Unique id on duplicate ids values pandas
Python
0 vote199 views1 answer
Compress tarfile python
Python
-2 votes223 views5 answers
Wow
Python
1 vote182 views1 answer
Pandas python group by for one column and sum another column
Python
0 vote162 views1 answer
Python django if key exists
Python Django
0 vote194 views1 answer
Python oops
Python
0 vote204 views1 answer
Django model plural
Python Django
0 vote186 views1 answer
How to get the current url path in django template
Python
0 vote198 views1 answer
Run ipython inside pipenv
Python
4 votes196 views3 answers
How to convert a list into a dataframe in python
Python