# -*- coding: utf-8 -*- # Licensed under a 3-clause BSD style license - see LICENSE.rst """ This includes tests for the Distance class and related calculations """ import pytest import numpy as np from numpy import testing as npt from astropy import units as u from astropy.units import allclose as quantity_allclose from astropy.coordinates import Longitude, Latitude, Distance, CartesianRepresentation from astropy.coordinates.builtin_frames import ICRS, Galactic from astropy.utils.exceptions import AstropyWarning from astropy.utils.compat.optional_deps import HAS_SCIPY # noqa def test_distances(): """ Tests functionality for Coordinate class distances and cartesian transformations. """ ''' Distances can also be specified, and allow for a full 3D definition of a coordinate. ''' # try all the different ways to initialize a Distance distance = Distance(12, u.parsec) Distance(40, unit=u.au) Distance(value=5, unit=u.kpc) # need to provide a unit with pytest.raises(u.UnitsError): Distance(12) # standard units are pre-defined npt.assert_allclose(distance.lyr, 39.138765325702551) npt.assert_allclose(distance.km, 370281309776063.0) # Coordinate objects can be assigned a distance object, giving them a full # 3D position c = Galactic(l=158.558650*u.degree, b=-43.350066*u.degree, distance=Distance(12, u.parsec)) assert quantity_allclose(c.distance, 12 * u.pc) # or initialize distances via redshifts - this is actually tested in the # function below that checks for scipy. This is kept here as an example # c.distance = Distance(z=0.2) # uses current cosmology # with whatever your preferred cosmology may be # c.distance = Distance(z=0.2, cosmology=WMAP5) # Coordinate objects can be initialized with a distance using special # syntax c1 = Galactic(l=158.558650*u.deg, b=-43.350066*u.deg, distance=12 * u.kpc) # Coordinate objects can be instantiated with cartesian coordinates # Internally they will immediately be converted to two angles + a distance cart = CartesianRepresentation(x=2 * u.pc, y=4 * u.pc, z=8 * u.pc) c2 = Galactic(cart) sep12 = c1.separation_3d(c2) # returns a *3d* distance between the c1 and c2 coordinates # not that this does *not* assert isinstance(sep12, Distance) npt.assert_allclose(sep12.pc, 12005.784163916317, 10) ''' All spherical coordinate systems with distances can be converted to cartesian coordinates. ''' cartrep2 = c2.cartesian assert isinstance(cartrep2.x, u.Quantity) npt.assert_allclose(cartrep2.x.value, 2) npt.assert_allclose(cartrep2.y.value, 4) npt.assert_allclose(cartrep2.z.value, 8) # with no distance, the unit sphere is assumed when converting to cartesian c3 = Galactic(l=158.558650*u.degree, b=-43.350066*u.degree, distance=None) unitcart = c3.cartesian npt.assert_allclose(((unitcart.x**2 + unitcart.y**2 + unitcart.z**2)**0.5).value, 1.0) # TODO: choose between these when CartesianRepresentation gets a definite # decision on whether or not it gets __add__ # # CartesianRepresentation objects can be added and subtracted, which are # vector/elementwise they can also be given as arguments to a coordinate # system # csum = ICRS(c1.cartesian + c2.cartesian) csumrep = CartesianRepresentation(c1.cartesian.xyz + c2.cartesian.xyz) csum = ICRS(csumrep) npt.assert_allclose(csumrep.x.value, -8.12016610185) npt.assert_allclose(csumrep.y.value, 3.19380597435) npt.assert_allclose(csumrep.z.value, -8.2294483707) npt.assert_allclose(csum.ra.degree, 158.529401774) npt.assert_allclose(csum.dec.degree, -43.3235825777) npt.assert_allclose(csum.distance.kpc, 11.9942200501) @pytest.mark.skipif('not HAS_SCIPY') def test_distances_scipy(): """ The distance-related tests that require scipy due to the cosmology module needing scipy integration routines """ from astropy.cosmology import WMAP5 # try different ways to initialize a Distance d4 = Distance(z=0.23) # uses default cosmology - as of writing, WMAP7 npt.assert_allclose(d4.z, 0.23, rtol=1e-8) d5 = Distance(z=0.23, cosmology=WMAP5) npt.assert_allclose(d5.compute_z(WMAP5), 0.23, rtol=1e-8) d6 = Distance(z=0.23, cosmology=WMAP5, unit=u.km) npt.assert_allclose(d6.value, 3.5417046898762366e+22) with pytest.raises(ValueError): Distance(cosmology=WMAP5, unit=u.km) with pytest.raises(ValueError): Distance() # Regression test for #12531 with pytest.raises(ValueError, match='more than one'): Distance(z=0.23, parallax=1*u.mas) # vectors! regression test for #11949 d4 = Distance(z=[0.23, 0.45]) # as of writing, Planck18 npt.assert_allclose(d4.z, [0.23, 0.45], rtol=1e-8) def test_distance_change(): ra = Longitude("4:08:15.162342", unit=u.hour) dec = Latitude("-41:08:15.162342", unit=u.degree) c1 = ICRS(ra, dec, Distance(1, unit=u.kpc)) oldx = c1.cartesian.x.value assert (oldx - 0.35284083171901953) < 1e-10 # first make sure distances are immutable with pytest.raises(AttributeError): c1.distance = Distance(2, unit=u.kpc) # now x should increase with a bigger distance increases c2 = ICRS(ra, dec, Distance(2, unit=u.kpc)) assert c2.cartesian.x.value == oldx * 2 def test_distance_is_quantity(): """ test that distance behaves like a proper quantity """ Distance(2 * u.kpc) d = Distance([2, 3.1], u.kpc) assert d.shape == (2,) a = d.view(np.ndarray) q = d.view(u.Quantity) a[0] = 1.2 q.value[1] = 5.4 assert d[0].value == 1.2 assert d[1].value == 5.4 q = u.Quantity(d, copy=True) q.value[1] = 0 assert q.value[1] == 0 assert d.value[1] != 0 # regression test against #2261 d = Distance([2 * u.kpc, 250. * u.pc]) assert d.unit is u.kpc assert np.all(d.value == np.array([2., 0.25])) def test_distmod(): d = Distance(10, u.pc) assert d.distmod.value == 0 d = Distance(distmod=20) assert d.distmod.value == 20 assert d.kpc == 100 d = Distance(distmod=-1., unit=u.au) npt.assert_allclose(d.value, 1301442.9440836983) with pytest.raises(ValueError): d = Distance(value=d, distmod=20) with pytest.raises(ValueError): d = Distance(z=.23, distmod=20) # check the Mpc/kpc/pc behavior assert Distance(distmod=1).unit == u.pc assert Distance(distmod=11).unit == u.kpc assert Distance(distmod=26).unit == u.Mpc assert Distance(distmod=-21).unit == u.AU # if an array, uses the mean of the log of the distances assert Distance(distmod=[1, 11, 26]).unit == u.kpc def test_parallax(): d = Distance(parallax=1*u.arcsecond) assert d.pc == 1. with pytest.raises(ValueError): d = Distance(15*u.pc, parallax=20*u.milliarcsecond) with pytest.raises(ValueError): d = Distance(parallax=20*u.milliarcsecond, distmod=20) # array plx = [1, 10, 100.]*u.mas d = Distance(parallax=plx) assert quantity_allclose(d.pc, [1000., 100., 10.]) assert quantity_allclose(plx, d.parallax) # check behavior for negative parallax with pytest.raises(ValueError): Distance(parallax=-1 * u.mas) with pytest.raises(ValueError): Distance(parallax=[10, 1, -1] * u.mas) with pytest.warns(AstropyWarning): Distance(parallax=-1 * u.mas, allow_negative=True) with pytest.warns(AstropyWarning): Distance(parallax=[10, 1, -1] * u.mas, allow_negative=True) # Regression test for #12569; `unit` was ignored if `parallax` was given. d = Distance(parallax=1*u.mas, unit=u.kpc) assert d.value == 1. assert d.unit is u.kpc def test_distance_in_coordinates(): """ test that distances can be created from quantities and that cartesian representations come out right """ ra = Longitude("4:08:15.162342", unit=u.hour) dec = Latitude("-41:08:15.162342", unit=u.degree) coo = ICRS(ra, dec, distance=2*u.kpc) cart = coo.cartesian assert isinstance(cart.xyz, u.Quantity) def test_negative_distance(): """ Test optional kwarg allow_negative """ with pytest.raises(ValueError): Distance([-2, 3.1], u.kpc) with pytest.raises(ValueError): Distance([-2, -3.1], u.kpc) with pytest.raises(ValueError): Distance(-2, u.kpc) d = Distance(-2, u.kpc, allow_negative=True) assert d.value == -2 def test_distance_comparison(): """Ensure comparisons of distances work (#2206, #2250)""" a = Distance(15*u.kpc) b = Distance(15*u.kpc) assert a == b c = Distance(1.*u.Mpc) assert a < c def test_distance_to_quantity_when_not_units_of_length(): """Any operation that leaves units other than those of length should turn a distance into a quantity (#2206, #2250)""" d = Distance(15*u.kpc) twice = 2.*d assert isinstance(twice, Distance) area = 4.*np.pi*d**2 assert area.unit.is_equivalent(u.m**2) assert not isinstance(area, Distance) assert type(area) is u.Quantity def test_distance_nan(): # Check that giving NaNs to Distance doesn't emit a warning Distance([0, np.nan, 1] * u.m)