Support the array_equals / array_equiv numpy function

[antonincms]

Feature request

Hello,

I'm trying to use numba inside of a personnal project, since I does a lot of numpy on very big arrays and python doesn't like that at all, even with numpy arrays. But I'm surprised and annoyed by the lack of several basic functions : array_equals, array_equiv.

For example :

def _get_color_bitmask2(color: np.ndarray, image: np.ndarray) -> np.ndarray:
    bitmask = []
    for line_idx in range(image.size):
        linemask = []
        for pixel_idx in range(image[line_idx].size):
            linemask.append(np.array_equal(image[line_idx,pixel_idx],color))
        bitmask.append(linemask)
    return np.array(bitmask)

won't work, Use of unsupported NumPy function 'numpy.array_equal' or unsupported use of the function. where this

def _get_color_bitmask2(color: np.ndarray, image: np.ndarray) -> np.ndarray:
    bitmask = []
    for line_idx in range(image.size):
        linemask = []
        for pixel_idx in range(image[line_idx].size):
            linemask.append(np.all(image[line_idx,pixel_idx]==color))
        bitmask.append(linemask)
    return np.array(bitmask)

will, even if the latest is a lot less safer. You should maybe consider binding or implementing them.

Thank you 👍

[stuartarchibald]

Thanks for the report. Numba supports a large number of commonly used NumPy functions, http://numba.pydata.org/numba-doc/dev/reference/numpysupported.html, and this set is continuously growing. The unsupported function list is in this issue: #4074 and indeed array_equals and array_equiv are on there. If these functions are important to you, contributions are very welcome.

The use of Numba's extension API @overload decorator is strongly recommended for this task. A guide to using @overload is here and API documentation is here.

It may be useful to take a look at examples of pull requests adding support for a NumPy function that have already been done if guidance is needed... here's a couple:

• np.roll: https://github.com/numba/numba/pull/3563/files
• np.roots: https://github.com/numba/numba/pull/2135/files