def test_nis_wfss_background(filters, pupils, make_wfss_datamodel):
"""Test background subtraction for NIRISS WFSS modes."""
data = make_wfss_datamodel
data.meta.instrument.filter = filters
data.meta.instrument.pupil = pupils
data.meta.instrument.detector = 'NIS'
data.meta.instrument.name = 'NIRISS'
data.meta.exposure.type = 'NIS_WFSS'
wcs_corrected = AssignWcsStep.call(data)
# Get References
wavelenrange = Step().get_reference_file(wcs_corrected, "wavelengthrange")
bkg_file = Step().get_reference_file(wcs_corrected, 'wfssbkg')
mask = mask_from_source_cat(wcs_corrected, wavelenrange)
with datamodels.open(bkg_file) as bkg_ref:
bkg_ref = no_NaN(bkg_ref)
# calculate backgrounds
pipeline_data_mean = robust_mean(wcs_corrected.data[mask])
test_data_mean, _, _ = sigma_clipped_stats(wcs_corrected.data, sigma=2)
pipeline_reference_mean = robust_mean(bkg_ref.data[mask])
test_reference_mean, _, _ = sigma_clipped_stats(bkg_ref.data, sigma=2)
assert np.isclose([pipeline_data_mean], [test_data_mean], rtol=1e-3)
assert np.isclose([pipeline_reference_mean], [test_reference_mean],
rtol=1e-1)
def test_robust_mean():
"""Test robust mean calculation"""
data = np.random.rand(2048, 2048)
result = robust_mean(data)
test = np.mean(data)
assert np.isclose([test], [result], rtol=1e-3)