def test_transform_image_does_not_change_input():
ccd_data = ccd_data_func()
original = ccd_data.copy()
with np.errstate(invalid="ignore"):
_ = transform_image(ccd_data, np.sqrt)
np.testing.assert_array_equal(original.data, ccd_data)
assert original.unit == ccd_data.unit
def test_catch_transform_wcs_warning():
ccd_data = ccd_data_func()
def tran(arr):
return 10 * arr
with catch_warnings() as w:
tran = transform_image(ccd_data, tran)
def test_transform_image(mask_data, uncertainty):
ccd_data = ccd_data_func(data_size=50)
if mask_data:
ccd_data.mask = np.zeros_like(ccd_data)
ccd_data.mask[10, 10] = 1
if uncertainty:
err = np.random.normal(size=ccd_data.shape)
ccd_data.uncertainty = StdDevUncertainty(err)
def tran(arr):
return 10 * arr
tran = transform_image(ccd_data, tran)
assert_array_equal(10 * ccd_data.data, tran.data)
if mask_data:
assert tran.shape == tran.mask.shape
assert_array_equal(ccd_data.mask, tran.mask)
if uncertainty:
assert tran.shape == tran.uncertainty.array.shape
assert_array_equal(10 * ccd_data.uncertainty.array,
tran.uncertainty.array)
def test_transform_isfunc():
ccd_data = ccd_data_func()
with pytest.raises(TypeError):
transform_image(ccd_data, 1)
def test_transform_isccd():
with pytest.raises(TypeError):
transform_image(1, 1)
def test_transform_image_does_not_change_input():
ccd_data = ccd_data_func()
original = ccd_data.copy()
ccd = transform_image(ccd_data, np.sqrt)
np.testing.assert_array_equal(original.data, ccd_data)
assert original.unit == ccd_data.unit