def test_proj_separations():
"""
Test angular separation functionality
"""
c1 = ICRS(ra=0*u.deg, dec=0*u.deg)
c2 = ICRS(ra=0*u.deg, dec=1*u.deg)
sep = c2.separation(c1)
# returns an Angle object
assert isinstance(sep, Angle)
assert sep.degree == 1
assert_allclose(sep.arcminute, 60.)
# these operations have ambiguous interpretations for points on a sphere
with pytest.raises(TypeError):
c1 + c2
with pytest.raises(TypeError):
c1 - c2
ngp = Galactic(l=0*u.degree, b=90*u.degree)
ncp = ICRS(ra=0*u.degree, dec=90*u.degree)
# if there is a defined conversion between the relevant coordinate systems,
# it will be automatically performed to get the right angular separation
assert_allclose(ncp.separation(ngp.transform_to(ICRS)).degree,
ncp.separation(ngp).degree)
# distance from the north galactic pole to celestial pole
assert_allclose(ncp.separation(ngp.transform_to(ICRS)).degree,
62.87174758503201)
def test_proj_separations():
"""
Test angular separation functionality
"""
c1 = ICRS(ra=0 * u.deg, dec=0 * u.deg)
c2 = ICRS(ra=0 * u.deg, dec=1 * u.deg)
sep = c2.separation(c1)
# returns an Angle object
assert isinstance(sep, Angle)
assert_allclose(sep.degree, 1.)
assert_allclose(sep.arcminute, 60.)
# these operations have ambiguous interpretations for points on a sphere
with pytest.raises(TypeError):
c1 + c2
with pytest.raises(TypeError):
c1 - c2
ngp = Galactic(l=0 * u.degree, b=90 * u.degree)
ncp = ICRS(ra=0 * u.degree, dec=90 * u.degree)
# if there is a defined conversion between the relevant coordinate systems,
# it will be automatically performed to get the right angular separation
assert_allclose(
ncp.separation(ngp.transform_to(ICRS())).degree,
ncp.separation(ngp).degree)
# distance from the north galactic pole to celestial pole
assert_allclose(
ncp.separation(ngp.transform_to(ICRS())).degree, 62.87174758503201)
def test_sep():
from astropy.coordinates.builtin_frames import ICRS
i1 = ICRS(ra=0 * u.deg, dec=1 * u.deg)
i2 = ICRS(ra=0 * u.deg, dec=2 * u.deg)
sep = i1.separation(i2)
assert sep.deg == 1
i3 = ICRS(ra=[1, 2] * u.deg, dec=[3, 4] * u.deg, distance=[5, 6] * u.kpc)
i4 = ICRS(ra=[1, 2] * u.deg, dec=[3, 4] * u.deg, distance=[4, 5] * u.kpc)
sep3d = i3.separation_3d(i4)
assert_allclose(sep3d.to(u.kpc), np.array([1, 1]) * u.kpc)
# check that it works even with velocities
i5 = ICRS(ra=[1, 2] * u.deg,
dec=[3, 4] * u.deg,
distance=[5, 6] * u.kpc,
pm_ra_cosdec=[1, 2] * u.mas / u.yr,
pm_dec=[3, 4] * u.mas / u.yr,
radial_velocity=[5, 6] * u.km / u.s)
i6 = ICRS(ra=[1, 2] * u.deg,
dec=[3, 4] * u.deg,
distance=[7, 8] * u.kpc,
pm_ra_cosdec=[1, 2] * u.mas / u.yr,
pm_dec=[3, 4] * u.mas / u.yr,
radial_velocity=[5, 6] * u.km / u.s)
sep3d = i5.separation_3d(i6)
assert_allclose(sep3d.to(u.kpc), np.array([2, 2]) * u.kpc)
def test_sep():
from astropy.coordinates.builtin_frames import ICRS
i1 = ICRS(ra=0*u.deg, dec=1*u.deg)
i2 = ICRS(ra=0*u.deg, dec=2*u.deg)
sep = i1.separation(i2)
assert sep.deg == 1
i3 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc)
i4 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[4, 5]*u.kpc)
sep3d = i3.separation_3d(i4)
assert_allclose(sep3d.to(u.kpc), np.array([1, 1])*u.kpc)
# check that it works even with velocities
i5 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
i6 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[7, 8]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
sep3d = i5.separation_3d(i6)
assert_allclose(sep3d.to(u.kpc), np.array([2, 2])*u.kpc)
# 3d separations of dimensionless distances should still work
i7 = ICRS(ra=1*u.deg, dec=2*u.deg, distance=3*u.one)
i8 = ICRS(ra=1*u.deg, dec=2*u.deg, distance=4*u.one)
sep3d = i7.separation_3d(i8)
assert_allclose(sep3d, 1*u.one)
# but should fail with non-dimensionless
with pytest.raises(ValueError):
i7.separation_3d(i3)
def test_sep():
from astropy.coordinates.builtin_frames import ICRS
i1 = ICRS(ra=0*u.deg, dec=1*u.deg)
i2 = ICRS(ra=0*u.deg, dec=2*u.deg)
sep = i1.separation(i2)
assert sep.deg == 1
i3 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc)
i4 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[4, 5]*u.kpc)
sep3d = i3.separation_3d(i4)
assert_allclose(sep3d.to(u.kpc), np.array([1, 1])*u.kpc)
# check that it works even with velocities
i5 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[5, 6]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
i6 = ICRS(ra=[1, 2]*u.deg, dec=[3, 4]*u.deg, distance=[7, 8]*u.kpc,
pm_ra_cosdec=[1, 2]*u.mas/u.yr, pm_dec=[3, 4]*u.mas/u.yr,
radial_velocity=[5, 6]*u.km/u.s)
sep3d = i5.separation_3d(i6)
assert_allclose(sep3d.to(u.kpc), np.array([2, 2])*u.kpc)
def test_frame_api():
from astropy.coordinates.representation import SphericalRepresentation, \
UnitSphericalRepresentation
from astropy.coordinates.builtin_frames import ICRS, FK5
# <--------------------Reference Frame/"Low-level" classes--------------------->
# The low-level classes have a dual role: they act as specifiers of coordinate
# frames and they *may* also contain data as one of the representation objects,
# in which case they are the actual coordinate objects themselves.
# They can always accept a representation as a first argument
icrs = ICRS(UnitSphericalRepresentation(lon=8 * u.hour, lat=5 * u.deg))
# which is stored as the `data` attribute
assert icrs.data.lat == 5 * u.deg
assert icrs.data.lon == 8 * u.hourangle
# Frames that require additional information like equinoxs or obstimes get them
# as keyword parameters to the frame constructor. Where sensible, defaults are
# used. E.g., FK5 is almost always J2000 equinox
fk5 = FK5(UnitSphericalRepresentation(lon=8 * u.hour, lat=5 * u.deg))
J2000 = time.Time('J2000')
fk5_2000 = FK5(UnitSphericalRepresentation(lon=8 * u.hour, lat=5 * u.deg),
equinox=J2000)
assert fk5.equinox == fk5_2000.equinox
# the information required to specify the frame is immutable
J2001 = time.Time('J2001')
with pytest.raises(AttributeError):
fk5.equinox = J2001
# Similar for the representation data.
with pytest.raises(AttributeError):
fk5.data = UnitSphericalRepresentation(lon=8 * u.hour, lat=5 * u.deg)
# There is also a class-level attribute that lists the attributes needed to
# identify the frame. These include attributes like `equinox` shown above.
assert all(nm in ('equinox', 'obstime')
for nm in fk5.get_frame_attr_names())
# the result of `get_frame_attr_names` is called for particularly in the
# high-level class (discussed below) to allow round-tripping between various
# frames. It is also part of the public API for other similar developer /
# advanced users' use.
# The actual position information is accessed via the representation objects
assert_allclose(icrs.represent_as(SphericalRepresentation).lat, 5 * u.deg)
# shorthand for the above
assert_allclose(icrs.spherical.lat, 5 * u.deg)
assert icrs.cartesian.z.value > 0
# Many frames have a "default" representation, the one in which they are
# conventionally described, often with a special name for some of the
# coordinates. E.g., most equatorial coordinate systems are spherical with RA and
# Dec. This works simply as a shorthand for the longer form above
assert_allclose(icrs.dec, 5 * u.deg)
assert_allclose(fk5.ra, 8 * u.hourangle)
assert icrs.representation_type == SphericalRepresentation
# low-level classes can also be initialized with names valid for that representation
# and frame:
icrs_2 = ICRS(ra=8 * u.hour, dec=5 * u.deg, distance=1 * u.kpc)
assert_allclose(icrs.ra, icrs_2.ra)
# and these are taken as the default if keywords are not given:
# icrs_nokwarg = ICRS(8*u.hour, 5*u.deg, distance=1*u.kpc)
# assert icrs_nokwarg.ra == icrs_2.ra and icrs_nokwarg.dec == icrs_2.dec
# they also are capable of computing on-sky or 3d separations from each other,
# which will be a direct port of the existing methods:
coo1 = ICRS(ra=0 * u.hour, dec=0 * u.deg)
coo2 = ICRS(ra=0 * u.hour, dec=1 * u.deg)
# `separation` is the on-sky separation
assert coo1.separation(coo2).degree == 1.0
# while `separation_3d` includes the 3D distance information
coo3 = ICRS(ra=0 * u.hour, dec=0 * u.deg, distance=1 * u.kpc)
coo4 = ICRS(ra=0 * u.hour, dec=0 * u.deg, distance=2 * u.kpc)
assert coo3.separation_3d(coo4).kpc == 1.0
# The next example fails because `coo1` and `coo2` don't have distances
with pytest.raises(ValueError):
assert coo1.separation_3d(coo2).kpc == 1.0
def test_frame_api():
from astropy.coordinates.representation import SphericalRepresentation, \
UnitSphericalRepresentation
from astropy.coordinates.builtin_frames import ICRS, FK5
# <--------------------Reference Frame/"Low-level" classes--------------------->
# The low-level classes have a dual role: they act as specifiers of coordinate
# frames and they *may* also contain data as one of the representation objects,
# in which case they are the actual coordinate objects themselves.
# They can always accept a representation as a first argument
icrs = ICRS(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg))
# which is stored as the `data` attribute
assert icrs.data.lat == 5*u.deg
assert icrs.data.lon == 8*u.hourangle
# Frames that require additional information like equinoxs or obstimes get them
# as keyword parameters to the frame constructor. Where sensible, defaults are
# used. E.g., FK5 is almost always J2000 equinox
fk5 = FK5(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg))
J2000 = time.Time('J2000')
fk5_2000 = FK5(UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg), equinox=J2000)
assert fk5.equinox == fk5_2000.equinox
# the information required to specify the frame is immutable
J2001 = time.Time('J2001')
with raises(AttributeError):
fk5.equinox = J2001
# Similar for the representation data.
with raises(AttributeError):
fk5.data = UnitSphericalRepresentation(lon=8*u.hour, lat=5*u.deg)
# There is also a class-level attribute that lists the attributes needed to
# identify the frame. These include attributes like `equinox` shown above.
assert all(nm in ('equinox', 'obstime') for nm in fk5.get_frame_attr_names())
# the result of `get_frame_attr_names` is called for particularly in the
# high-level class (discussed below) to allow round-tripping between various
# frames. It is also part of the public API for other similar developer /
# advanced users' use.
# The actual position information is accessed via the representation objects
assert_allclose(icrs.represent_as(SphericalRepresentation).lat, 5*u.deg)
# shorthand for the above
assert_allclose(icrs.spherical.lat, 5*u.deg)
assert icrs.cartesian.z.value > 0
# Many frames have a "default" representation, the one in which they are
# conventionally described, often with a special name for some of the
# coordinates. E.g., most equatorial coordinate systems are spherical with RA and
# Dec. This works simply as a shorthand for the longer form above
assert_allclose(icrs.dec, 5*u.deg)
assert_allclose(fk5.ra, 8*u.hourangle)
assert icrs.representation_type == SphericalRepresentation
# low-level classes can also be initialized with names valid for that representation
# and frame:
icrs_2 = ICRS(ra=8*u.hour, dec=5*u.deg, distance=1*u.kpc)
assert_allclose(icrs.ra, icrs_2.ra)
# and these are taken as the default if keywords are not given:
# icrs_nokwarg = ICRS(8*u.hour, 5*u.deg, distance=1*u.kpc)
# assert icrs_nokwarg.ra == icrs_2.ra and icrs_nokwarg.dec == icrs_2.dec
# they also are capable of computing on-sky or 3d separations from each other,
# which will be a direct port of the existing methods:
coo1 = ICRS(ra=0*u.hour, dec=0*u.deg)
coo2 = ICRS(ra=0*u.hour, dec=1*u.deg)
# `separation` is the on-sky separation
assert coo1.separation(coo2).degree == 1.0
# while `separation_3d` includes the 3D distance information
coo3 = ICRS(ra=0*u.hour, dec=0*u.deg, distance=1*u.kpc)
coo4 = ICRS(ra=0*u.hour, dec=0*u.deg, distance=2*u.kpc)
assert coo3.separation_3d(coo4).kpc == 1.0
# The next example fails because `coo1` and `coo2` don't have distances
with raises(ValueError):
assert coo1.separation_3d(coo2).kpc == 1.0
