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Fix test for custom WCS for imaging #9017

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Fix test for custom WCS for imaging #9017

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142f804
Fix test for custom WCS for imaging
mcara Dec 18, 2024
2826d63
minor tweaks
mcara Dec 18, 2024
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46 changes: 29 additions & 17 deletions jwst/resample/tests/test_resample_step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -831,12 +831,13 @@ def test_resample_undefined_variance(nircam_rate, shape):

@pytest.mark.parametrize('ratio', [0.7, 1.2])
@pytest.mark.parametrize('rotation', [0, 15, 135])
@pytest.mark.parametrize('crpix', [(600, 550), (601, 551)])
@pytest.mark.parametrize('crval', [(22.04, 11.98), (22.041, 11.981)])
@pytest.mark.parametrize('shape', [(1205, 1100)])
@pytest.mark.parametrize('crpix', [(256, 488), (700, 124)])
@pytest.mark.parametrize('crval', [(22.04019, 11.98262), (22.0404, 11.983)])
@pytest.mark.parametrize('shape', [(1020, 1010)])
def test_custom_wcs_resample_imaging(nircam_rate, ratio, rotation, crpix, crval, shape):
im = AssignWcsStep.call(nircam_rate, sip_approx=False)
im.data += 5

result = ResampleStep.call(
im,
output_shape=shape,
Expand Down Expand Up @@ -884,15 +885,17 @@ def test_custom_refwcs_resample_imaging(nircam_rate, output_shape2, match,
rng = np.random.default_rng(seed=77)
im.data[:, :] = rng.random(im.data.shape)

crpix = (600, 550)
crval = (22.04, 11.98)
if output_shape2 is None:
crpix = None
else:
crpix = (output_shape2[-1] // 2, output_shape2[-2] // 2)
crval = tuple(np.mean(im.meta.wcs.footprint(), axis=0))
rotation = 15
ratio = 0.7

# first pass - create a reference output WCS:
result = ResampleStep.call(
im,
output_shape=(1205, 1100),
output_shape=output_shape2,
crpix=crpix,
crval=crval,
rotation=rotation,
Expand All @@ -901,11 +904,15 @@ def test_custom_refwcs_resample_imaging(nircam_rate, output_shape2, match,

# make sure results are nontrivial
data1 = result.data
weight1 = result.wht

assert not np.all(np.isnan(data1))

if crpix is not None:
assert np.allclose(result.meta.wcs(*crpix), crval, rtol=1e-12, atol=0)

refwcs = str(tmp_path / "resample_refwcs.asdf")
result.meta.wcs.bounding_box = [(-0.5, 1204.5), (-0.5, 1099.5)]
asdf.AsdfFile({"wcs": result.meta.wcs}).write_to(refwcs)
asdf.AsdfFile({"wcs": result.meta.wcs, "array_shape": data1.shape}).write_to(refwcs)

result = ResampleStep.call(
im,
Expand All @@ -914,6 +921,7 @@ def test_custom_refwcs_resample_imaging(nircam_rate, output_shape2, match,
)

data2 = result.data
weight2 = result.wht
assert not np.all(np.isnan(data2))

if output_shape2 is not None:
Expand All @@ -922,17 +930,21 @@ def test_custom_refwcs_resample_imaging(nircam_rate, output_shape2, match,
if match:
# test output image shape
assert data1.shape == data2.shape
assert np.allclose(data1, data2, equal_nan=True)
assert np.allclose(data1, data2, equal_nan=True, rtol=1.0e-7, atol=1e-7)

# make sure pixel values are similar, accounting for scale factor
# (assuming inputs are in surface brightness units)
iscale = np.sqrt(im.meta.photometry.pixelarea_steradians
/ compute_image_pixel_area(im.meta.wcs))
iscale2 = (
im.meta.photometry.pixelarea_steradians /
compute_image_pixel_area(im.meta.wcs)
)

input_mean = np.nanmean(im.data)
output_mean_1 = np.nanmean(data1)
output_mean_2 = np.nanmean(data2)
assert np.isclose(input_mean * iscale**2, output_mean_1, atol=1e-4)
assert np.isclose(input_mean * iscale**2, output_mean_2, atol=1e-4)
total_weight = np.sum(weight1)
output_mean_1 = np.nansum(data1 * weight1) / total_weight
output_mean_2 = np.nansum(data2 * weight2) / total_weight
assert np.isclose(input_mean * iscale2, output_mean_1)
assert np.isclose(input_mean * iscale2, output_mean_2)

im.close()
result.close()
Expand All @@ -946,7 +958,7 @@ def test_custom_refwcs_pixel_shape_imaging(nircam_rate, tmp_path):
im.data[:, :] = rng.random(im.data.shape)

crpix = (600, 550)
crval = (22.04, 11.98)
crval = (22.04019, 11.98262)
rotation = 15
ratio = 0.7

Expand Down
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