def test_assign_broadcasting():
# https://numpy.org/doc/stable/user/basics.indexing.html#assigning-values-to-indexed-arrays
# Note that the above documentation does not fully capture the broadcasting behavior of NumPy.
# We therefore test our tools for broadcasting with array shapes, instead of arrays.
# Consider the permutations of a tuple of 10 integers ranging from 0 to 3.
# We partition this tuple into 2 tuples of 5 integers, and
# use the tuples to define the shapes of two arrays,
# to define the LHS and RHS of an assignment.
# A value of 0 means the axis is not specified in the resulting array shape.
# Because we're interested in valid assignment operations,
# we define empty arrays of size equal to the product of
# axis dims, excluding any axes which are set to 0.
# If all axes are set to 0,
# then create a dimensionless array with value 0.
# There is no formal proof that the proof for arrays with 5 axes
# is without loss of generality.
def get_array(shape):
shape = tuple(filter(lambda x: x > 0, shape))
if len(shape) == 0:
return np.array(0)
else:
return np.empty(np.product(shape)).reshape(shape)
perms = list(itertools.product([0, 1, 2, 3], repeat=10))
pbar = tqdm.tqdm(total=len(perms))
for shapes in perms:
A: np.ndarray = get_array(shapes[:5])
B: np.ndarray = get_array(shapes[5:])
try:
if A.shape == ():
continue
if B.shape == ():
A[:] = B
else:
A[:] = B[:]
# This should execute without error.
assert np.broadcast_to(
B, A.shape).shape == array_utils.broadcast_shape_to_alt(
B.shape, A.shape)
assert array_utils.can_broadcast_shape_to(
B.shape,
A.shape), "%s can be broadcast to %s" % (B.shape, A.shape)
except ValueError as _:
with pytest.raises(ValueError):
np.broadcast_to(B, A.shape)
with pytest.raises(ValueError):
array_utils.broadcast_shape_to_alt(B.shape, A.shape)
assert not array_utils.can_broadcast_shape_to(
B.shape,
A.shape), "%s cannot be broadcast to %s" % (B.shape, A.shape)
pbar.update(1)
def create(self, concrete_cls=None) -> BlockArrayBase:
if self.sel.basic_steps():
if self.sel.is_aligned(self._source.block_shape):
# Assertion below should form a conjunction with the above condition.
# This isn't currently an issue but an assumption that
# may not always hold true, depending on how the ArrayView
# is constructed.
assert array_utils.can_broadcast_shape_to(
self.sel.get_broadcastable_block_shape(self.block_shape),
self._source.block_shape)
return self.create_references(concrete_cls)
else:
return self.create_basic_single_step(concrete_cls)
else:
return self.create_basic_multi_step(concrete_cls)
