def create_slit(model, x0, y0, order):
""" Create a SlitModel representing a grism slit."""
ymin = 0
xmin = 0
# ymax = 58
# xmax = 1323
model = Mapping((0, 1, 0, 0, 0)) | (Shift(xmin) & Shift(ymin) & Const1D(x0)
& Const1D(y0) & Const1D(order)) | model
wcsobj = wcs.WCS([('det', model), ('world', None)])
wcsobj.bounding_box = ((20, 25), (800, 805))
slit = SlitModel()
slit.meta.wcs = wcsobj
slit.source_xpos = x0
slit.source_ypos = y0
return slit
def test_interpolate_response():
wavelength = np.array([0.5, 5., 7., 18., 26.], dtype=np.float32)
wl1 = np.arange(1, 21, dtype=np.float64)
wl2 = np.arange(1, 21, dtype=np.float64)[::-1] # decreasing order
response = np.arange(20, dtype=np.float64) * 2. + 5.
slit = SlitModel() # this is only used for the dtype of relsens
tbl1 = np.array(list(zip(wl1, response)), dtype=slit.relsens.dtype)
tbl2 = np.array(list(zip(wl2, response)), dtype=slit.relsens.dtype)
reciprocal_r1 = extract.interpolate_response(wavelength,
tbl1,
verbose=False)
assert len(reciprocal_r1) == len(wavelength)
assert math.isclose(1. / reciprocal_r1[1], 13.0, rel_tol=1.e-6)
assert reciprocal_r1[0] == 0. # because wavelength is out of range
assert reciprocal_r1[4] == 0.
reciprocal_r2 = extract.interpolate_response(wavelength,
tbl2,
verbose=False)
assert len(reciprocal_r2) == len(wavelength)
assert math.isclose(1. / reciprocal_r2[1], 35.0, rel_tol=1.e-6)
assert reciprocal_r2[0] == 0. # because wavelength is out of range
assert reciprocal_r2[4] == 0.
def test_find_dispersion_axis():
"""
Test the find_dispersion_axis() function
"""
dm = SlitModel()
dm.meta.wcsinfo.dispersion_direction = 1 # horizontal
assert find_dispersion_axis(dm) == 0 # X axis for wcs functions
dm.meta.wcsinfo.dispersion_direction = 2 # vertical
assert find_dispersion_axis(dm) == 1 # Y axis for wcs functions
def test_interpolate_response():
wavelength = np.array([0.5, 5., 7., 18., 26.], dtype=np.float32)
wl1 = np.arange(1, 21, dtype=np.float64)
wl2 = np.arange(1, 21, dtype=np.float64)[::-1] # decreasing order
response = np.arange(20, dtype=np.float64) * 2. + 5.
slit = SlitModel() # this is only used for the dtype of relsens
tbl1 = np.array(list(zip(wl1, response)), dtype=slit.relsens.dtype)
tbl2 = np.array(list(zip(wl2, response)), dtype=slit.relsens.dtype)
r1 = extract.interpolate_response(wavelength, tbl1, verbose=False)
assert len(r1) == len(wavelength)
assert r1[1] == 13.0
r2 = extract.interpolate_response(wavelength, tbl2, verbose=False)
assert len(r2) == len(wavelength)
assert r2[1] == 35.0
def s2d_single(generate_wcs_transform):
pytest.importorskip("jwst")
from jwst.datamodels import MultiSlitModel, SlitModel
from jwst.assign_wcs.util import wcs_bbox_from_shape
shape = (10, 100)
dispaxis = 1
model = MultiSlitModel()
sm = SlitModel(shape)
sm.data
model.slits.append(sm)
for slit in model.slits:
slit.meta.wcs = generate_wcs_transform(dispaxis)
slit.meta.wcs.bounding_box = wcs_bbox_from_shape(shape)
slit.meta.wcsinfo.dispersion_direction = dispaxis
model.meta.telescope = "JWST"
return model
def test_slit_from_image():
data = np.arange(24, dtype=np.float32).reshape((6, 4))
im = ImageModel(data=data, err=data / 2, dq=data)
im.meta.instrument.name = "MIRI"
slit_dm = SlitDataModel(im)
assert_allclose(im.data, slit_dm.data)
assert hasattr(slit_dm, 'wavelength')
# this should be enabled after gwcs starts using non-coordinate inputs
# assert not hasattr(slit_dm, 'meta')
slit = SlitModel(im)
assert_allclose(im.data, slit.data)
assert_allclose(im.err, slit.err)
assert hasattr(slit, 'wavelength')
assert slit.meta.instrument.name == "MIRI"
im = ImageModel(slit)
assert type(im) == ImageModel
im = ImageModel(slit_dm)
assert type(im) == ImageModel
def s2d_multi(generate_wcs_transform, request):
pytest.importorskip("jwst")
from jwst.datamodels import SlitModel, MultiSlitModel
from jwst.assign_wcs.util import wcs_bbox_from_shape
shape = request.param
if shape[0] < shape[1]:
dispaxis = 1
else:
dispaxis = 2
model = MultiSlitModel()
sm = SlitModel(shape)
sm.data
model.slits.append(sm)
model.slits.append(sm)
for slit in model.slits:
slit.meta.wcs = generate_wcs_transform(dispaxis)
slit.meta.wcs.bounding_box = wcs_bbox_from_shape(shape)
slit.meta.wcsinfo.dispersion_direction = dispaxis
slit.meta.bunit_data = "Jy"
slit.meta.bunit_err = "Jy"
return model
