def test_firstframe_single_group():
"""
Test that the firstframe code does nothing when passed a single
group integration
"""
# size of integration
ngroups = 1
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# the 'do_not_use' flag
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0,
0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize), 0, dtype=int),
dq_diff,
err_msg='groupdq changed for single group ' +
'when it should not')
def test_firstframe_add1_groupdq():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' by adding 1 to the flag, not overwritting to 1
"""
# size of integration
ngroups = 5
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# set a flag in the groupdq, first frame
dm_ramp.groupdq[0, 0, 500:510, 500:510] = 4
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# test if pixels in groupdq were incremented in value by 1
assert (dm_ramp_firstframe.groupdq[0, 0, 505, 505] == 5)
def test_firstframe_3groups():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' or left it as is, which it should do for 3 frames
"""
# size of integration
ngroups = 3
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# 0 since the step should not run if frames 3 or fewer
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0,
0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize), 0, dtype=int),
dq_diff,
err_msg='Diff in groupdq flags is not ' +
'equal to 0')
def test_firstframe_add1_groupdq():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' by adding 1 to the flag, not overwritting to 1
"""
# size of integration
ngroups = 5
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# set a flag in the groupdq, first frame
dm_ramp.groupdq[0, 0, 500:510, 500:510] = 4
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# test if pixels in groupdq were incremented in value by 1
assert(dm_ramp_firstframe.groupdq[0, 0, 505, 505] == 5)
def test_firstframe_single_group():
"""
Test that the firstframe code does nothing when passed a single
group integration
"""
# size of integration
ngroups = 1
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# the 'do_not_use' flag
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0, 0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize),
0,
dtype=int),
dq_diff,
err_msg='groupdq changed for single group '
+ 'when it should not')
def test_firstframe_3groups():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' or left it as is, which it should do for 3 frames
"""
# size of integration
ngroups = 3
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# 0 since the step should not run if frames 3 or fewer
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0, 0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize),
0,
dtype=int),
dq_diff,
err_msg='Diff in groupdq flags is not '
+ 'equal to 0')
def test_firstframe_set_groupdq():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' for 5 integrations
"""
# size of integration
ngroups = 5
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# the 'do_not_use' flag
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0,
0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize),
dqflags.group['DO_NOT_USE'],
dtype=int),
dq_diff,
err_msg='Diff in groupdq flags is not ' +
'equal to the DO_NOT_USE flag')
# test that the groupdq flags are not changed for the rest of the groups
dq_diff = (dm_ramp_firstframe.groupdq[0, 1:ngroups, :, :] -
dm_ramp.groupdq[0, 1:ngroups, :, :])
np.testing.assert_array_equal(np.full((ngroups - 1, ysize, xsize),
0,
dtype=int),
dq_diff,
err_msg='n >= 2 groupdq flags changes ' +
'and they should not be')
def test_firstframe_set_groupdq():
"""
Test if the firstframe code set the groupdq flag on the first
group to 'do_not_use' for 5 integrations
"""
# size of integration
ngroups = 5
xsize = 1032
ysize = 1024
# create the data and groupdq arrays
csize = (1, ngroups, ysize, xsize)
data = np.full(csize, 1.0)
groupdq = np.zeros(csize, dtype=int)
# create a JWST datamodel for MIRI data
dm_ramp = MIRIRampModel(data=data, groupdq=groupdq)
# run the first frame correction step
dm_ramp_firstframe = do_correction(dm_ramp)
# check that the difference in the groupdq flags is equal to
# the 'do_not_use' flag
dq_diff = dm_ramp_firstframe.groupdq[0, 0, :, :] - dm_ramp.groupdq[0, 0, :, :]
np.testing.assert_array_equal(np.full((ysize, xsize),
dqflags.group['DO_NOT_USE'],
dtype=int),
dq_diff,
err_msg='Diff in groupdq flags is not '
+ 'equal to the DO_NOT_USE flag')
# test that the groupdq flags are not changed for the rest of the groups
dq_diff = (dm_ramp_firstframe.groupdq[0, 1:ngroups, :, :]
- dm_ramp.groupdq[0, 1:ngroups, :, :])
np.testing.assert_array_equal(np.full((ngroups-1, ysize, xsize),
0,
dtype=int),
dq_diff,
err_msg='n >= 2 groupdq flags changes '
+ 'and they should not be')