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AttributeError: 'list' object has no attribute 'shape'

See original GitHub issue

I’m trying to predict a next step position (using latitude and longitude as attributes and target). I’ve tried the following:

pred = gmm.predict(len(X)+i, np.array([X[(num-1)+i]])) where the first value is 10 and the second “array([[41.4051453, 2.1776344]])” with shape (1, 2)

however, I get this error:

`AttributeError: ‘list’ object has no attribute ‘shape’

What I’m doing wrong? `

Issue Analytics

  • State:closed
  • Created 2 years ago
  • Comments:12 (7 by maintainers)

github_iconTop GitHub Comments

1reaction
raul-paradacommented, May 5, 2021

It works!

0reactions
AlexanderFabischcommented, May 5, 2021

That’s because the predict function expects an array of shape (n_samples, n_features), but the shape is (n_features,). This version works for me:

    states = np.array([[41.4049364, 2.177356],
                       [41.4049656, 2.1773926],
                       [41.4049938, 2.1774287],
                       [41.4050204, 2.1774638],
                       [41.4050453, 2.1774975],
                       [41.4050682, 2.1775296],
                       [41.4050895, 2.1775597],
                       [41.4051093, 2.1775874],
                       [41.4051278, 2.1776125],
                       [41.4051453, 2.1776344]])
    state_tuples = np.hstack((states[:-1], states[1:]))

    gmm = GMM(n_components=3, random_state=0)
    gmm.from_samples(state_tuples)
    next_state = gmm.predict(np.array([0, 1]), [states[-1]])
    assert_array_almost_equal(next_state, [[41.405162, 2.177657]])

On the current master branch, otherwise you have to cast all lists to numpy arrays.

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