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Error in documentation of experimental.sequential.extended_kalman_filter #1811

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beat-247 opened this issue Jun 3, 2024 · 0 comments
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@beat-247
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beat-247 commented Jun 3, 2024

Hi all,

there are two small issues with the documentation of experimental.sequential.extended_kalman_filter.

  1. The code in the example does not run, giving

InvalidArgumentError: cannot compute Sub as input #1(zero-based) was expected to be a double tensor but is a float tensor [Op:Sub] name.

Changing

x = [np.zeros((2,), dtype=np.float32)]
to
x = [tf.zeros((2,), dtype=tf.float32)]
solves this.

  1. The documentation states

    observation_jacobian_fn: a Python callable that accepts a (batched) vector
    of length state_size and returns a (batched) matrix of size
    [state_size, event_size], representing the Jacobian of observation_fn.

but the correct matrix size to be returned should be [event_size, state_size].

In the example, making observation_jacobian_fn return a Tensor of size [state_size, event_size] will cause the Kalman Filter to fail, while [event_size, state_size] works.

See also this colab https://colab.research.google.com/drive/1vUNMHQ1Fc3CwdpOMnKXqzqmQ2zM4A8Pp?usp=sharing

Thank you for the great package!

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