Test if an array is broadcastable to a shape?

Question

What is the best way to test whether an array can be broadcast to a given shape?

The "pythonic" approach of trying doesn't work for my case, because the intent is to have lazy evaluation of the operation.

I'm asking how to implement is_broadcastable below:

>>> x = np.ones([2,2,2])
>>> y = np.ones([2,2])
>>> is_broadcastable(x,y)
True
>>> y = np.ones([2,3])
>>> is_broadcastable(x,y)
False

or better yet:

>>> is_broadcastable(x.shape, y.shape)

Answer 1

I really think you guys are over thinking this, why not just keep it simple?

def is_broadcastable(shp1, shp2):
    for a, b in zip(shp1[::-1], shp2[::-1]):
        if a == 1 or b == 1 or a == b:
            pass
        else:
            return False
    return True

Answer 2

If you just want to avoid materializing an array with a given shape, you can use as_strided:

import numpy as np
from numpy.lib.stride_tricks import as_strided

def is_broadcastable(shp1, shp2):
    x = np.array([1])
    a = as_strided(x, shape=shp1, strides=[0] * len(shp1))
    b = as_strided(x, shape=shp2, strides=[0] * len(shp2))
    try:
        c = np.broadcast_arrays(a, b)
        return True
    except ValueError:
        return False

is_broadcastable((1000, 1000, 1000), (1000, 1, 1000))  # True
is_broadcastable((1000, 1000, 1000), (3,))  # False

This is memory efficient, since a and b are both backed by a single record