`scipy.cluster.vq._vq_impl:_py_vq`

source: /scipy/cluster/vq/_vq_impl.py:160

Signature

def _py_vq(obs, code_book, check_finite = True)

Summary

Python version of vq algorithm.

Extended Summary

The algorithm computes the Euclidean distance between each observation and every frame in the code_book.

Parameters

obs : ndarray: Expects a rank 2 array. Each row is one observation.
code_book : ndarray: Code book to use. Same format than obs. Should have same number of features (e.g., columns) than obs.
check_finite : bool, optional: Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs. Default: True

Returns

code : ndarray: code[i] gives the label of the ith obversation; its code is code_book[code[i]].
mind_dist : ndarray: min_dist[i] gives the distance between the ith observation and its corresponding code.

Notes

This function is slower than the C version but works for all input types. If the inputs have the wrong types for the C versions of the function, this one is called as a last resort.

It is about 20 times slower than the C version.

Aliases

scipy.cluster.vq.py_vq