def test_center_origin_joint_upsample_and_downsample_with_err_to_larger_False(self):
kwargs = dict(
image=np.array(
[
[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
]
),
new_resolution=[1 / 2, 2],
old_resolution=1,
err_to_larger=False,
extrapolation_fill_value=None,
origin="zero",
method="linear",
anti_aliasing=False,
)
correct_output = np.array(
[
[0, 2],
[2.5, 4.5],
[5.0, 7.0],
[7.5, 9.5],
[10.0, 12.0],
[12.5, 14.5],
]
)
assert np.array_equal(resample(**kwargs), correct_output)
def test_center_origin_downsample(self):
kwargs = dict(
image=np.array(
[
[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19],
]
),
new_resolution=2,
old_resolution=1,
err_to_larger=True,
extrapolation_fill_value=None,
origin="center",
method="linear",
anti_aliasing=False,
)
correct_output = np.array(
[
[2.5, 4.5, 6.5],
[12.5, 14.5, 16.5],
]
)
assert np.array_equal(resample(**kwargs), correct_output)
def test_center_origin_joint_upsample_and_downsample(self):
kwargs = dict(
image=np.array(
[
[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9],
]
),
new_resolution=[1 / 2, 2],
old_resolution=1,
err_to_larger=True,
extrapolation_fill_value=None,
origin="center",
method="linear",
anti_aliasing=False,
)
correct_output = np.array(
[
[-1.25, 0.75, 2.75],
[1.25, 3.25, 5.25],
[3.75, 5.75, 7.75],
[6.25, 8.25, 10.25],
]
)
assert np.array_equal(resample(**kwargs), correct_output)
def test_center_origin_upsample(self):
kwargs = dict(
image=np.array(
[
[0, 1, 2],
[3, 4, 5],
]
),
new_resolution=1 / 2,
old_resolution=1,
err_to_larger=True,
extrapolation_fill_value=None,
origin="center",
method="linear",
anti_aliasing=False,
)
correct_output = np.array(
[
[-1.0, -0.5, 0.0, 0.5, 1.0, 1.5],
[0.5, 1.0, 1.5, 2.0, 2.5, 3.0],
[2.0, 2.5, 3.0, 3.5, 4.0, 4.5],
[3.5, 4.0, 4.5, 5.0, 5.5, 6.0],
]
)
assert np.array_equal(resample(**kwargs), correct_output)