def test_varying_transform_pc():
varying_matrix_lt = [
rotation_matrix(a)[:2, :2] for a in np.linspace(0, 90, 10)
] * u.arcsec
vct = VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=(0, 0) * u.arcsec,
pc_table=varying_matrix_lt,
lon_pole=180 * u.deg)
trans5 = vct.transform_at_index(5)
assert isinstance(trans5, CompoundModel)
# Verify that we have the 5th matrix in the series
affine = trans5.left.left.right
assert isinstance(affine, m.AffineTransformation2D)
assert u.allclose(affine.matrix, varying_matrix_lt[5])
# x.shape=(1,), y.shape=(1,), z.shape=(1,)
pixel = (0 * u.pix, 0 * u.pix, 5 * u.pix)
world = vct(*pixel)
assert np.array(world[0]).shape == ()
assert u.allclose(world, (359.99804329 * u.deg, 0.00017119 * u.deg))
assert u.allclose(vct.inverse(*world, 5 * u.pix),
pixel[:2],
atol=0.01 * u.pix)
def test_vct_errors():
with pytest.raises(ValueError, match="pc table should be"):
VaryingCelestialTransform(crpix=(5, 5),
cdelt=(1, 1),
crval_table=(0, 0),
pc_table=[[1, 2, 3], [4, 4, 6], [7, 8, 9]],
lon_pole=180)
with pytest.raises(ValueError, match="crval table should be"):
VaryingCelestialTransform(crpix=(5, 5),
cdelt=(1, 1),
crval_table=((0, 0, 0), ),
pc_table=[[1, 2], [4, 4]],
lon_pole=180)
with pytest.raises(
ValueError,
match="The shape of the pc and crval tables should match"):
VaryingCelestialTransform(crpix=(5, 5),
cdelt=(1, 1),
crval_table=((0, 0), (1, 1), (2, 2)),
pc_table=[[[1, 2], [4, 4]], [[1, 2], [3,
4]]],
lon_pole=180)
with pytest.raises(TypeError, match="projection keyword should"):
VaryingCelestialTransform(crpix=(5, 5),
cdelt=(1, 1),
crval_table=((0, 0), (1, 1)),
pc_table=[[[1, 2], [4, 4]], [[1, 2], [3,
4]]],
lon_pole=180,
projection=ValueError)
def test_varying_transform_pc_unitless():
varying_matrix_lt = [
rotation_matrix(a)[:2, :2] for a in np.linspace(0, 90, 10)
]
vct = VaryingCelestialTransform(
crpix=(5, 5),
# without units everything is deg, so make this arcsec in deg
cdelt=((1, 1) * u.arcsec).to_value(u.deg),
crval_table=(0, 0),
pc_table=varying_matrix_lt,
lon_pole=180)
trans5 = vct.transform_at_index(5)
assert isinstance(trans5, CompoundModel)
# Verify that we have the 5th matrix in the series
affine = trans5.left.left.right
assert isinstance(affine, m.AffineTransformation2D)
assert u.allclose(affine.matrix, varying_matrix_lt[5])
pixel = (0, 0, 5)
world = vct(*pixel)
assert np.allclose(world, (359.99804329, 0.00017119))
assert np.allclose(vct.inverse(*world, 5), pixel[:2], atol=0.01)
def test_varying_transform_pc_shapes(pixel, lon_shape):
varying_matrix_lt = [
rotation_matrix(a)[:2, :2] for a in np.linspace(0, 90, 10)
] * u.arcsec
vct = VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=(0, 0) * u.arcsec,
pc_table=varying_matrix_lt,
lon_pole=180 * u.deg)
world = vct(*pixel)
assert np.array(world[0]).shape == lon_shape
new_pixel = vct.inverse(*world, pixel[-1])
assert u.allclose(new_pixel,
np.broadcast_arrays(*pixel, subok=True)[:2],
atol=0.01 * u.pix)
def test_vct_shape_errors():
pc_table = [rotation_matrix(a)[:2, :2]
for a in np.linspace(0, 90, 15)] * u.arcsec
pc_table = pc_table.reshape((5, 3, 2, 2))
crval_table = list(zip(np.arange(1, 16), np.arange(16, 31))) * u.arcsec
crval_table = crval_table.reshape((5, 3, 2))
kwargs = dict(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
lon_pole=180 * u.deg)
with pytest.raises(ValueError,
match="only be constructed with a one dimensional"):
VaryingCelestialTransform(crval_table=crval_table,
pc_table=pc_table,
**kwargs)
with pytest.raises(ValueError,
match="only be constructed with a one dimensional"):
VaryingCelestialTransformSlit(crval_table=crval_table,
pc_table=pc_table,
**kwargs)
with pytest.raises(ValueError,
match="only be constructed with a two dimensional"):
VaryingCelestialTransform2D(crval_table=crval_table[0],
pc_table=pc_table[0],
**kwargs)
with pytest.raises(ValueError,
match="only be constructed with a two dimensional"):
VaryingCelestialTransformSlit2D(crval_table=crval_table[0],
pc_table=pc_table[0],
**kwargs)
def vct_crval():
crval_table = ((0, 1), (2, 3), (4, 5)) * u.arcsec
return VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=crval_table,
pc_table=np.identity(2) * u.arcsec,
lon_pole=180 * u.deg)
def test_roundtrip_vct():
varying_matrix_lt = [
rotation_matrix(a)[:2, :2] for a in np.linspace(0, 90, 10)
] * u.arcsec
vct = VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=(0, 0) * u.arcsec,
pc_table=varying_matrix_lt,
lon_pole=180 * u.deg)
new_vct = roundtrip_object(vct)
assert isinstance(new_vct, VaryingCelestialTransform)
new_ivct = roundtrip_object(vct.inverse)
assert isinstance(new_ivct, InverseVaryingCelestialTransform)
assert u.allclose(u.Quantity(new_vct.crpix), (5, 5) * u.pix)
assert u.allclose(u.Quantity(new_ivct.crpix), (5, 5) * u.pix)
assert u.allclose(u.Quantity(new_vct.pc_table), varying_matrix_lt)
assert u.allclose(u.Quantity(new_ivct.pc_table), varying_matrix_lt)
pixel = (0 * u.pix, 0 * u.pix, 5 * u.pix)
world = new_vct(*pixel)
assert u.allclose(world, (359.99804329 * u.deg, 0.00017119 * u.deg))
assert u.allclose(new_ivct(*world, 5 * u.pix),
pixel[:2],
atol=0.01 * u.pix)
def test_varying_transform_crval():
crval_table = ((0, 1), (2, 3), (4, 5)) * u.arcsec
vct = VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=crval_table,
pc_table=np.identity(2) * u.arcsec,
lon_pole=180 * u.deg)
trans2 = vct.transform_at_index(2)
assert isinstance(trans2, CompoundModel)
# Verify that we have the 2nd crval pair in the series
crval1 = trans2.right.lon
crval2 = trans2.right.lat
assert u.allclose(crval1, crval_table[2][0])
assert u.allclose(crval2, crval_table[2][1])
pixel = (0 * u.pix, 0 * u.pix, 2 * u.pix)
world = vct(*pixel)
assert u.allclose(world, (3.59999722e+02, 2.78325906e-13) * u.deg)
assert u.allclose(vct.inverse(*world, 2 * u.pix),
pixel[:2],
atol=0.01 * u.pix)
def test_coupled_sep(linear_time):
if not hasattr(Model, "_calculate_separability_matrix"):
pytest.skip()
crval_table = ((0, 1), (2, 3), (4, 5)) * u.arcsec
vct = VaryingCelestialTransform(crpix=(5, 5) * u.pix,
cdelt=(1, 1) * u.arcsec / u.pix,
crval_table=crval_table,
pc_table=np.identity(2) * u.arcsec,
lon_pole=180 * u.deg)
tfrm = CoupledCompoundModel("&", vct, linear_time, shared_inputs=1)
smatrix = separability_matrix(tfrm)
assert np.allclose(
smatrix,
np.array([[True, True, True], [True, True, True], [False, False,
True]]))