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pythonnumpylogicnumpy-ndarray

Why is numpy.ndarray([0]).all() returning True while numpy.array([0]).all() returning False?

This seems surprising to me:

import numpy as np
assert np.ndarray([0]).all()
assert not np.array([0]).all()

What is going on here?

Solution

  • Consider what those two calls produce:

    >>> np.ndarray([0])
array([], dtype=float64)

    This is an empty 1-D array, because you specified a single dimension of length 0.

    >>> np.array([0])
array([0])

    This is a 1-D array containing a single element, 0.

    The definition of all() isn't just "all elements are True", it's also "no elements are False", as seen here:

    >>> np.array([]).all()
True

    So:

    np.ndarray([0]).all()

    is True because it's an empty array, while:

    np.array([0]).all()

    is False because it's an array of one non-True element.