Source code for astropy.coordinates.funcs

# Licensed under a 3-clause BSD style license - see LICENSE.rst

This module contains convenience functions for coordinate-related functionality.

This is generally just wrapping around the object-oriented coordinates
framework, but it is useful for some users who are used to more functional

import warnings
from import Sequence

import numpy as np

from astropy import units as u
from astropy.constants import c
from astropy import _erfa as erfa
from import ascii
from astropy.utils import isiterable, data
from .sky_coordinate import SkyCoord
from .builtin_frames import GCRS, PrecessedGeocentric
from .representation import SphericalRepresentation, CartesianRepresentation
from .builtin_frames.utils import get_jd12

__all__ = ['cartesian_to_spherical', 'spherical_to_cartesian', 'get_sun',
           'get_constellation', 'concatenate_representations', 'concatenate']

[docs]def cartesian_to_spherical(x, y, z): """ Converts 3D rectangular cartesian coordinates to spherical polar coordinates. Note that the resulting angles are latitude/longitude or elevation/azimuthal form. I.e., the origin is along the equator rather than at the north pole. .. note:: This function simply wraps functionality provided by the `~astropy.coordinates.CartesianRepresentation` and `~astropy.coordinates.SphericalRepresentation` classes. In general, for both performance and readability, we suggest using these classes directly. But for situations where a quick one-off conversion makes sense, this function is provided. Parameters ---------- x : scalar, array-like, or `~astropy.units.Quantity` The first cartesian coordinate. y : scalar, array-like, or `~astropy.units.Quantity` The second cartesian coordinate. z : scalar, array-like, or `~astropy.units.Quantity` The third cartesian coordinate. Returns ------- r : `~astropy.units.Quantity` The radial coordinate (in the same units as the inputs). lat : `~astropy.units.Quantity` The latitude in radians lon : `~astropy.units.Quantity` The longitude in radians """ if not hasattr(x, 'unit'): x = x * u.dimensionless_unscaled if not hasattr(y, 'unit'): y = y * u.dimensionless_unscaled if not hasattr(z, 'unit'): z = z * u.dimensionless_unscaled cart = CartesianRepresentation(x, y, z) sph = cart.represent_as(SphericalRepresentation) return sph.distance,, sph.lon
[docs]def spherical_to_cartesian(r, lat, lon): """ Converts spherical polar coordinates to rectangular cartesian coordinates. Note that the input angles should be in latitude/longitude or elevation/azimuthal form. I.e., the origin is along the equator rather than at the north pole. .. note:: This is a low-level function used internally in `astropy.coordinates`. It is provided for users if they really want to use it, but it is recommended that you use the `astropy.coordinates` coordinate systems. Parameters ---------- r : scalar, array-like, or `~astropy.units.Quantity` The radial coordinate (in the same units as the inputs). lat : scalar, array-like, or `~astropy.units.Quantity` The latitude (in radians if array or scalar) lon : scalar, array-like, or `~astropy.units.Quantity` The longitude (in radians if array or scalar) Returns ------- x : float or array The first cartesian coordinate. y : float or array The second cartesian coordinate. z : float or array The third cartesian coordinate. """ if not hasattr(r, 'unit'): r = r * u.dimensionless_unscaled if not hasattr(lat, 'unit'): lat = lat * u.radian if not hasattr(lon, 'unit'): lon = lon * u.radian sph = SphericalRepresentation(distance=r, lat=lat, lon=lon) cart = sph.represent_as(CartesianRepresentation) return cart.x, cart.y, cart.z
[docs]def get_sun(time): """ Determines the location of the sun at a given time (or times, if the input is an array `~astropy.time.Time` object), in geocentric coordinates. Parameters ---------- time : `~astropy.time.Time` The time(s) at which to compute the location of the sun. Returns ------- newsc : `~astropy.coordinates.SkyCoord` The location of the sun as a `~astropy.coordinates.SkyCoord` in the `~astropy.coordinates.GCRS` frame. Notes ----- The algorithm for determining the sun/earth relative position is based on the simplified version of VSOP2000 that is part of ERFA. Compared to JPL's ephemeris, it should be good to about 4 km (in the Sun-Earth vector) from 1900-2100 C.E., 8 km for the 1800-2200 span, and perhaps 250 km over the 1000-3000. """ earth_pv_helio, earth_pv_bary = erfa.epv00(*get_jd12(time, 'tdb')) # We have to manually do aberration because we're outputting directly into # GCRS earth_p = earth_pv_helio['p'] earth_v = earth_pv_bary['v'] # convert barycentric velocity to units of c, but keep as array for passing in to erfa earth_v /= c.to_value( dsun = np.sqrt(np.sum(earth_p**2, axis=-1)) invlorentz = (1-np.sum(earth_v**2, axis=-1))**0.5 properdir = erfa.ab(earth_p/dsun.reshape(dsun.shape + (1,)), -earth_v, dsun, invlorentz) cartrep = CartesianRepresentation(x=-dsun*properdir[..., 0] * u.AU, y=-dsun*properdir[..., 1] * u.AU, z=-dsun*properdir[..., 2] * u.AU) return SkyCoord(cartrep, frame=GCRS(obstime=time))
# global dictionary that caches repeatedly-needed info for get_constellation _constellation_data = {}
[docs]def get_constellation(coord, short_name=False, constellation_list='iau'): """ Determines the constellation(s) a given coordinate object contains. Parameters ---------- coord : coordinate object The object to determine the constellation of. short_name : bool If True, the returned names are the IAU-sanctioned abbreviated names. Otherwise, full names for the constellations are used. constellation_list : str The set of constellations to use. Currently only ``'iau'`` is supported, meaning the 88 "modern" constellations endorsed by the IAU. Returns ------- constellation : str or string array If ``coords`` contains a scalar coordinate, returns the name of the constellation. If it is an array coordinate object, it returns an array of names. Notes ----- To determine which constellation a point on the sky is in, this precesses to B1875, and then uses the Delporte boundaries of the 88 modern constellations, as tabulated by `Roman 1987 <>`_. """ if constellation_list != 'iau': raise ValueError("only 'iau' us currently supported for constellation_list") # read the data files and cache them if they haven't been already if not _constellation_data: cdata = data.get_pkg_data_contents('data/constellation_data_roman87.dat') ctable =, names=['ral', 'rau', 'decl', 'name']) cnames = data.get_pkg_data_contents('data/constellation_names.dat', encoding='UTF8') cnames_short_to_long = dict([(l[:3], l[4:]) for l in cnames.split('\n') if not l.startswith('#')]) cnames_long = np.array([cnames_short_to_long[nm] for nm in ctable['name']]) _constellation_data['ctable'] = ctable _constellation_data['cnames_long'] = cnames_long else: ctable = _constellation_data['ctable'] cnames_long = _constellation_data['cnames_long'] isscalar = coord.isscalar # if it is geocentric, we reproduce the frame but with the 1875 equinox, # which is where the constellations are defined # this yields a "dubious year" warning because ERFA considers the year 1875 # "dubious", probably because UTC isn't well-defined then and precession # models aren't precisely calibrated back to then. But it's plenty # sufficient for constellations with warnings.catch_warnings(): warnings.simplefilter('ignore', erfa.ErfaWarning) constel_coord = coord.transform_to(PrecessedGeocentric(equinox='B1875')) if isscalar: rah = constel_coord.ra.ravel().hour decd = constel_coord.dec.ravel().deg else: rah = constel_coord.ra.hour decd = constel_coord.dec.deg constellidx = -np.ones(len(rah), dtype=int) notided = constellidx == -1 # should be all for i, row in enumerate(ctable): msk = (row['ral'] < rah) & (rah < row['rau']) & (decd > row['decl']) constellidx[notided & msk] = i notided = constellidx == -1 if np.sum(notided) == 0: break else: raise ValueError('Could not find constellation for coordinates {0}'.format(constel_coord[notided])) if short_name: names = ctable['name'][constellidx] else: names = cnames_long[constellidx] if isscalar: return names[0] else: return names
def _concatenate_components(reps_difs, names): """ Helper function for the concatenate function below. Gets and concatenates all of the individual components for an iterable of representations or differentials. """ values = [] for name in names: data_vals = [] for x in reps_difs: data_val = getattr(x, name) data_vals.append(data_val.reshape(1, ) if x.isscalar else data_val) concat_vals = np.concatenate(data_vals) # Hack because np.concatenate doesn't fully work with Quantity if isinstance(concat_vals, u.Quantity): concat_vals._unit = data_val.unit values.append(concat_vals) return values
[docs]def concatenate_representations(reps): """ Combine multiple representation objects into a single instance by concatenating the data in each component. Currently, all of the input representations have to be the same type. This properly handles differential or velocity data, but all input objects must have the same differential object type as well. Parameters ---------- reps : sequence of representation objects The objects to concatenate Returns ------- rep : `~astropy.coordinates.BaseRepresentation` subclass A single representation object with its data set to the concatenation of all the elements of the input sequence of representations. """ if not isinstance(reps, (Sequence, np.ndarray)): raise TypeError('Input must be a list or iterable of representation ' 'objects.') # First, validate that the represenations are the same, and # concatenate all of the positional data: rep_type = type(reps[0]) if any(type(r) != rep_type for r in reps): raise TypeError('Input representations must all have the same type.') # Construct the new representation with the concatenated data from the # representations passed in values = _concatenate_components(reps, rep_type.attr_classes.keys()) new_rep = rep_type(*values) has_diff = any('s' in rep.differentials for rep in reps) if has_diff and any('s' not in rep.differentials for rep in reps): raise ValueError('Input representations must either all contain ' 'differentials, or not contain differentials.') if has_diff: dif_type = type(reps[0].differentials['s']) if any('s' not in r.differentials or type(r.differentials['s']) != dif_type for r in reps): raise TypeError('All input representations must have the same ' 'differential type.') values = _concatenate_components([r.differentials['s'] for r in reps], dif_type.attr_classes.keys()) new_dif = dif_type(*values) new_rep = new_rep.with_differentials({'s': new_dif}) return new_rep
[docs]def concatenate(coords): """ Combine multiple coordinate objects into a single `~astropy.coordinates.SkyCoord`. "Coordinate objects" here mean frame objects with data, `~astropy.coordinates.SkyCoord`, or representation objects. Currently, they must all be in the same frame, but in a future version this may be relaxed to allow inhomogenous sequences of objects. Parameters ---------- coords : sequence of coordinate objects The objects to concatenate Returns ------- cskycoord : SkyCoord A single sky coordinate with its data set to the concatenation of all the elements in ``coords`` """ if getattr(coords, 'isscalar', False) or not isiterable(coords): raise TypeError('The argument to concatenate must be iterable') scs = [SkyCoord(coord, copy=False) for coord in coords] # Check that all frames are equivalent for sc in scs[1:]: if not sc.is_equivalent_frame(scs[0]): raise ValueError("All inputs must have equivalent frames: " "{0} != {1}".format(sc, scs[0])) # TODO: this can be changed to SkyCoord.from_representation() for a speed # boost when we switch to using classmethods return SkyCoord(concatenate_representations([ for c in coords]), frame=scs[0].frame)