Adding a 2D Array to a 3D Array

Question

Im struggling a little with stacking two matrices on top of each other. I'm using the pyKalman package, which when updated, returns a tuple of matrices. One with an updated estimate (new_pred a 1 x 2 vector) and the corresponding covariance matrix (new_cov a 2 x 2 matrix).

After the update, I want to stack the returned values to their corresponding outputs, for a recursive smoothing of the data, through these estimates.

The following is how it is currently implemented.

for meas in onlineObservations:
    (new_pred, new_cov) = kf.filter_update(states_pred[-1], cov_pred[-1], meas)
    states_pred = np.vstack((states_pred, new_pred))
    cov_pred = np.stack((cov_pred, new_cov), axis=0)

Which works really well for the updated estimate (the 1x2 vector), but fails when i try to add new_cov to the array called cov_pred. For good measure:

states_pred.shape = (900,2)
cov_pred.shape = (900, 2, 2)

I've tried changing the axis of "stack" to no avail. It's probably something elementary, but i've been struggling with it for the past hour, and cannot seem to find a "simple" solution.

Thanks in advance.

Aritesh · Accepted Answer · 2018-03-28 11:49:15Z

2

This should work -

cov_pred = []
for meas in onlineObservations:
    (new_pred, new_cov) = kf.filter_update(states_pred[-1], cov_pred[-1], meas)
    states_pred = np.vstack((states_pred, new_pred))
    cov_pred.append[new_cov]
cov_pred = np.stack(cov_pred, axis=0)

But since you want to update array which you are using already in code, you should use np.concatenate

for meas in onlineObservations:
    (new_pred, new_cov) = kf.filter_update(states_pred[-1], cov_pred[-1], meas)
    states_pred = np.vstack((states_pred, new_pred))
    cov_pred = np.concatenate((cov_pred, np.reshape(new_cov, (1,2,2))), axis=0)

edited Mar 28, 2018 at 11:49

answered Mar 28, 2018 at 11:22

Aritesh

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4 Comments

rlunde Over a year ago

But i call the last element of cov_pred, which does not allow me to perform the last line?

Aritesh Over a year ago

Till the time you have all the arrays of same dimension, np.stack will work, thats why I have saved everything in a list first and then stacking.

rlunde Over a year ago

it returns "all the input arrays must have the same number of dimensions".

Aritesh Over a year ago

fixed the number of dim

rlunde · Accepted Answer · 2018-03-28 11:45:06Z

0

I've been able to make it work by converting cov_pred to a list, and then use:

cov_pred.append(new_cov)

And then re-convert it back again after the for loop. But it seems tedious - at least if there's an even better way!

answered Mar 28, 2018 at 11:45

rlunde

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1 Comment

Aritesh Over a year ago

use np.concatenate

alaa saeed · Accepted Answer · 2018-03-28 18:11:05Z

0

You can keep your code inside a For Loop (While Loop will also do) and use 'Auto-index Enabled' and thats it.... At the output of Loop, LabVIEW will create a 3D data exactly as your requirement.

answered Mar 28, 2018 at 18:11

alaa saeed

11 bronze badge

1 Comment

ViG Over a year ago

I'm not sure why LabVIEW is involved here... Can you elaborate your answer more?

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