def test_flag_cr(sci_blot_image_pair):
"""Test the flag_cr function. Test logic, not the actual noise model."""
sci, blot = sci_blot_image_pair
assert (sci.dq == 0).all()
# Drop some CRs on the science array
sci.data[3, 3] += 100
sci.data[3, 7] += 1e3
sci.data[7, 3] += 1e4
sci.data[7, 7] += 1e5
# run flag_cr() which updates in-place. Copy sci first.
data_copy = sci.data.copy()
flag_cr(sci, blot)
# Make sure science data array is unchanged after flag_cr()
np.testing.assert_allclose(sci.data, data_copy)
# Verify that both DQ flags are set in the DQ array for all outliers
assert sci.dq[3, 3] == OUTLIER_DO_NOT_USE
assert sci.dq[3, 7] == OUTLIER_DO_NOT_USE
assert sci.dq[7, 3] == OUTLIER_DO_NOT_USE
assert sci.dq[7, 7] == OUTLIER_DO_NOT_USE
# Verify the source wasn't flagged
assert sci.dq[10, 10] == datamodels.dqflags.pixel["GOOD"]
def test_flag_cr_with_subtracted_background(sci_blot_image_pair):
"""Test the flag_cr function on background-subtracted data"""
sci, blot = sci_blot_image_pair
sci.meta.background.subtracted = True
sci.meta.background.level = 3
# Drop a CR on the science array
sci.data[5, 5] += 10
flag_cr(sci, blot)
assert sci.dq[5, 5] > 0
def test_flag_cr(sci_blot_image_pair):
"""Test the flag_cr function. Test logic, not the actual noise model."""
sci, blot = sci_blot_image_pair
assert (sci.dq == 0).all()
# Add some background
sci.data += 3
blot.data += 3
# Drop a CR on the science array
sci.data[5, 5] += 10
flag_cr(sci, blot)
assert sci.dq[5, 5] > 0