# Saver¶

This is a helper class designed to allow you to save the state of the Kalman filter for each epoch. Each instance variable is stored in a list when you call save().

This class is deprecated as of version 1.3.2 and will be deleted soon. Instead, see the class filterpy.common.Saver, which works for any class, not just a KalmanFilter object.

Example

saver = Saver(kf)
for i in range(N):
kf.predict()
kf.update(zs[i])
saver.save()

saver.to_array() # convert all to np.array

# plot the 0th element of kf.x over all epoches
plot(saver.xs[:, 0])


Copyright 2015 Roger R Labbe Jr.

FilterPy library. http://github.com/rlabbe/filterpy

Supporting book at: https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python

Kalman filter saver

class filterpy.kalman.Saver(kf, save_current=True)[source]

Helper class to save the states of the KalmanFilter class. Each time you call save() the current states are appended to lists. Generally you would do this once per epoch - predict/update.

Once you are done filtering you can optionally call to_array() to convert all of the lists to numpy arrays. You cannot safely call save() after calling to_array().

Examples

kf = KalmanFilter(...whatever)
# initialize kf here

saver = Saver(kf) # save data for kf filter
for z in zs:
kf.predict()
kf.update(z)

saver.save()

saver.to_array()
# plot the 0th element of the state
plt.plot(saver.xs[:, 0, 0])

__init__(kf, save_current=True)[source]

Construct the save object, optionally saving the current state of the filter

save()[source]

save the current state of the Kalman filter

to_array()[source]

convert all of the lists into np.array