def test_guider_cds_id_modes(exptype, make_guider_image):
"""Test fgs id exptypes"""
model = make_guider_image
model.meta.exposure.type = exptype
result = guider_cds(model)
n_int = model.data.shape[0]
imshape = (model.data.shape[2], model.data.shape[3])
truth = np.zeros((1,) + imshape)
for num_int in range(0, n_int):
data_sect = model.data[num_int, :, :, :]
grp_last = data_sect[1, :, :]
grp_first = data_sect[0, :, :]
if num_int == 0:
diff_int0 = grp_last - grp_first
if num_int == 1:
diff_int1 = grp_last - grp_first
truth[0, :, :] = np.minimum(diff_int1, diff_int0) / model.meta.exposure.group_time
assert np.allclose(result.data[0,:,:], truth[0,:,:])
def test_unit_assignment(make_guider_image):
"""Test that correct units are returned"""
model = make_guider_image
result = guider_cds(model)
assert result.meta.bunit_data == 'DN/s'
def test_table_extensions(make_guider_image):
"""Test that tables are assigned to result of pipeline"""
model = make_guider_image
model.planned_star_table = np.arange(0, 11)
model.flight_star_table = np.arange(0, 11)
model.pointing_table = np.arange(0, 11)
model.centroid_table = np.arange(0, 11)
model.track_sub_table = np.arange(0, 11)
result = guider_cds(model)
assert 'planned_star_table' in result
assert 'flight_star_table' in result
assert 'pointing_table' in result
assert 'centroid_table' in result
assert 'track_sub_table' in result
def test_guider_cds_acq_track_modes(exptype, make_guider_image):
"""Test acq and track exptypes"""
model = make_guider_image
model.meta.exposure.type = exptype
truth = np.zeros(model.data.shape)
result = guider_cds(model)
n_int = model.data.shape[0]
imshape = (model.data.shape[2], model.data.shape[3])
slope_int_cube = np.zeros((n_int,) + imshape, dtype=np.float32)
for num_int in range(0, n_int):
data_sect = model.data[num_int, :, :, :]
grp_last = data_sect[1, :, :]
grp_first = data_sect[0, :, :]
slope_int_cube[num_int, :, :] = grp_last - grp_first
truth = slope_int_cube / model.meta.exposure.group_time
assert np.allclose(result.data, truth)
def test_guider_cds_fineguide_mode(make_guider_image):
"""Test the fine guiding mode"""
model = make_guider_image
truth = np.zeros(model.data.shape)
result = guider_cds(model)
n_int = model.data.shape[0]
imshape = (model.data.shape[2], model.data.shape[3])
slope_int_cube = np.zeros((n_int,) + imshape, dtype=np.float32)
for num_int in range(0, n_int):
data_sect = model.data[num_int, :, :, :]
first_4 = data_sect[:4, :, :].mean(axis=0)
last_4 = data_sect[-4:, :, :].mean(axis=0)
slope_int_cube[num_int, :, :] = last_4 - first_4
truth = slope_int_cube / model.meta.exposure.group_time
assert np.allclose(result.data, truth)