def test_squash():
A = np.ones((3, 3), dtype=float)
B = np.asarray(A, object)
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
for ijk in np.ndindex(*B.shape):
B[ijk] = np.ones((2,))
A = np.ones((3, 3, 2))
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
# sub-arrays have different shapes ( (3,) and (2,) )
B[0, 0] = np.ones((3,))
npt.assert_(_squash(B) is B)
def test_squash():
A = np.ones((3, 3), dtype=float)
B = np.asarray(A, object)
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
for ijk in np.ndindex(*B.shape):
B[ijk] = np.ones((2, ))
A = np.ones((3, 3, 2))
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
# sub-arrays have different shapes ( (3,) and (2,) )
B[0, 0] = np.ones((3, ))
npt.assert_(_squash(B) is B)
# Check dtypes for arrays and scalars
arr_arr = np.zeros((2, ), dtype=object)
scalar_arr = np.zeros((2, ), dtype=object)
numeric_types = sum(
[np.sctypes[t] for t in ('int', 'uint', 'float', 'complex')],
[np.bool_])
for dt0 in numeric_types:
arr_arr[0] = np.zeros((3, ), dtype=dt0)
scalar_arr[0] = dt0(0)
for dt1 in numeric_types:
arr_arr[1] = np.zeros((3, ), dtype=dt1)
npt.assert_equal(
_squash(arr_arr).dtype,
reduce(np.add, arr_arr).dtype)
scalar_arr[1] = dt0(1)
npt.assert_equal(
_squash(scalar_arr).dtype,
reduce(np.add, scalar_arr).dtype)
# Check masks and Nones
arr = np.ones((3, 4), dtype=float)
obj_arr = arr.astype(object)
arr[1, 1] = 99
obj_arr[1, 1] = None
npt.assert_array_equal(_squash(obj_arr, mask=None, fill=99), arr)
msk = arr == 1
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), arr)
msk[1, 1] = 1 # unmask None - object array back
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), obj_arr)
msk[1, 1] = 0 # remask, back to fill again
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), arr)
obj_arr[2, 3] = None # add another unmasked None, object again
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), obj_arr)
# Check array of arrays
obj_arrs = np.zeros((3, ), dtype=object)
for i in range(3):
obj_arrs[i] = np.ones((4, 5))
arr_arrs = np.ones((3, 4, 5))
# No Nones
npt.assert_array_equal(_squash(obj_arrs, mask=None, fill=99), arr_arrs)
# None, implicit masking
obj_masked = obj_arrs.copy()
obj_masked[1] = None
arr_masked = arr_arrs.copy()
arr_masked[1] = 99
npt.assert_array_equal(_squash(obj_masked, mask=None, fill=99), arr_masked)
msk = np.array([1, 0, 1], dtype=np.bool_) # explicit mask
npt.assert_array_equal(_squash(obj_masked, mask=msk, fill=99), arr_masked)
msk[1] = True # unmask None, object array back
npt.assert_array_equal(_squash(obj_masked, mask=msk, fill=99), obj_masked)
def test_squash():
A = np.ones((3, 3), dtype=float)
B = np.asarray(A, object)
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
for ijk in np.ndindex(*B.shape):
B[ijk] = np.ones((2,))
A = np.ones((3, 3, 2))
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
B[2, 2] = None
A[2, 2] = 0
npt.assert_array_equal(A, _squash(B))
npt.assert_equal(_squash(B).dtype, A.dtype)
# sub-arrays have different shapes ( (3,) and (2,) )
B[0, 0] = np.ones((3,))
npt.assert_(_squash(B) is B)
# Check dtypes for arrays and scalars
arr_arr = np.zeros((2,), dtype=object)
scalar_arr = np.zeros((2,), dtype=object)
numeric_types = sum(
[np.sctypes[t] for t in ('int', 'uint', 'float', 'complex')],
[np.bool_])
for dt0 in numeric_types:
arr_arr[0] = np.zeros((3,), dtype=dt0)
scalar_arr[0] = dt0(0)
for dt1 in numeric_types:
arr_arr[1] = np.zeros((3,), dtype=dt1)
npt.assert_equal(_squash(arr_arr).dtype,
reduce(np.add, arr_arr).dtype)
scalar_arr[1] = dt0(1)
npt.assert_equal(_squash(scalar_arr).dtype,
reduce(np.add, scalar_arr).dtype)
# Check masks and Nones
arr = np.ones((3, 4), dtype=float)
obj_arr = arr.astype(object)
arr[1, 1] = 99
obj_arr[1, 1] = None
npt.assert_array_equal(_squash(obj_arr, mask=None, fill=99), arr)
msk = arr == 1
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), arr)
msk[1, 1] = 1 # unmask None - object array back
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), obj_arr)
msk[1, 1] = 0 # remask, back to fill again
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), arr)
obj_arr[2, 3] = None # add another unmasked None, object again
npt.assert_array_equal(_squash(obj_arr, mask=msk, fill=99), obj_arr)
# Check array of arrays
obj_arrs = np.zeros((3,), dtype=object)
for i in range(3):
obj_arrs[i] = np.ones((4, 5))
arr_arrs = np.ones((3, 4, 5))
# No Nones
npt.assert_array_equal(_squash(obj_arrs, mask=None, fill=99), arr_arrs)
# None, implicit masking
obj_masked = obj_arrs.copy()
obj_masked[1] = None
arr_masked = arr_arrs.copy()
arr_masked[1] = 99
npt.assert_array_equal(_squash(obj_masked, mask=None, fill=99),
arr_masked)
msk = np.array([1, 0, 1], dtype=np.bool_) # explicit mask
npt.assert_array_equal(_squash(obj_masked, mask=msk, fill=99),
arr_masked)
msk[1] = True # unmask None, object array back
npt.assert_array_equal(_squash(obj_masked, mask=msk, fill=99),
obj_masked)
