U \IdoQ@s~dZddlZddlmZddlmZddlm Z ddl m Z dd d d gZ dd dZ ddd Zddd Zddd ZdddZdS)zB This module contains functions for matching coordinate catalogs. N)units)Angle)UnitSphericalRepresentation)SkyCoordmatch_coordinates_3dmatch_coordinates_skysearch_around_3dsearch_around_sky kdtree_3dc Cs|jst|dkrtdt||}t|tr>|j|dd}n ||}|jjj }|jj |}| dt |jdf}t |jrtd||j|\}} |dkr|dddf}| dddf} || |} | |jdd| | |jdd|fS) a? Finds the nearest 3-dimensional matches of a coordinate or coordinates in a set of catalog coordinates. This finds the 3-dimensional closest neighbor, which is only different from the on-sky distance if ``distance`` is set in either ``matchcoord`` or ``catalogcoord``. Parameters ---------- matchcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The coordinate(s) to match to the catalog. catalogcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The base catalog in which to search for matches. Typically this will be a coordinate object that is an array (i.e., ``catalogcoord.isscalar == False``) nthneighbor : int, optional Which closest neighbor to search for. Typically ``1`` is desired here, as that is correct for matching one set of coordinates to another. The next likely use case is ``2``, for matching a coordinate catalog against *itself* (``1`` is inappropriate because each point will find itself as the closest match). storekdtree : bool or str, optional If a string, will store the KD-Tree used for the computation in the ``catalogcoord``, as in ``catalogcoord.cache`` with the provided name. This dramatically speeds up subsequent calls with the same catalog. If False, the KD-Tree is discarded after use. Returns ------- idx : int array Indices into ``catalogcoord`` to get the matched points for each ``matchcoord``. Shape matches ``matchcoord``. sep2d : `~astropy.coordinates.Angle` The on-sky separation between the closest match for each ``matchcoord`` and the ``matchcoord``. Shape matches ``matchcoord``. dist3d : `~astropy.units.Quantity` ['length'] The 3D distance between the closest match for each ``matchcoord`` and the ``matchcoord``. Shape matches ``matchcoord``. Notes ----- This function requires `SciPy `_ to be installed or it will fail. rCThe catalog for coordinate matching cannot be a scalar or length-0.FZmerge_attributesz0Matching coordinates cannot contain NaN entries.N)isscalarlen ValueError_get_cartesian_kdtree isinstancer transform_to cartesianxunitxyztoreshapenpprodshapeisnanvalueanyqueryT separation) matchcoord catalogcoord nthneighbor storekdtreekdtZcatunitZmatchxyzZ matchflatxyzdistidxsep2dr-@/tmp/pip-unpacked-wheel-1sxf5fhv/astropy/coordinates/matching.pyrs,0     kdtree_skyc Cs|jst|dkrtdt|tr4|j|dd}n ||}|jt}| |}|jt}| |}|j ||}t ||||\} } } t|jtst|jts||  |} t|tr|j ||j |<n|dkr|j d|j d<| | | fS)a Finds the nearest on-sky matches of a coordinate or coordinates in a set of catalog coordinates. This finds the on-sky closest neighbor, which is only different from the 3-dimensional match if ``distance`` is set in either ``matchcoord`` or ``catalogcoord``. Parameters ---------- matchcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The coordinate(s) to match to the catalog. catalogcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The base catalog in which to search for matches. Typically this will be a coordinate object that is an array (i.e., ``catalogcoord.isscalar == False``) nthneighbor : int, optional Which closest neighbor to search for. Typically ``1`` is desired here, as that is correct for matching one set of coordinates to another. The next likely use case is ``2``, for matching a coordinate catalog against *itself* (``1`` is inappropriate because each point will find itself as the closest match). storekdtree : bool or str, optional If a string, will store the KD-Tree used for the computation in the ``catalogcoord`` in ``catalogcoord.cache`` with the provided name. This dramatically speeds up subsequent calls with the same catalog. If False, the KD-Tree is discarded after use. Returns ------- idx : int array Indices into ``catalogcoord`` to get the matched points for each ``matchcoord``. Shape matches ``matchcoord``. sep2d : `~astropy.coordinates.Angle` The on-sky separation between the closest match for each ``matchcoord`` and the ``matchcoord``. Shape matches ``matchcoord``. dist3d : `~astropy.units.Quantity` ['length'] The 3D distance between the closest match for each ``matchcoord`` and the ``matchcoord``. Shape matches ``matchcoord``. If either ``matchcoord`` or ``catalogcoord`` don't have a distance, this is the 3D distance on the unit sphere, rather than a true distance. Notes ----- This function requires `SciPy `_ to be installed or it will fail. rr Fr Tkdtree)rrrrrrdata represent_asr realize_framecachegetr separation_3dstr) r%r&r'r(ZnewmatchZ match_ureprZ newmatch_uZ cat_ureprZnewcat_ur+r,Zsep3dr-r-r.rjs82          cCsZ|jstd|js|jr"tdt|dks:t|dkrntjgtdtjgtdtgtjt g|j j fSt ||}|j jj }||}t |||d}||}g}g} t|||D]&\} } | D]} || | | qqtj|td}tj| td} |jdkr*tgtj} t g|j j }n$|||| } |||| }|| | |fS)a Searches for pairs of points that are at least as close as a specified distance in 3D space. This is intended for use on coordinate objects with arrays of coordinates, not scalars. For scalar coordinates, it is better to use the ``separation_3d`` methods. Parameters ---------- coords1 : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The first set of coordinates, which will be searched for matches from ``coords2`` within ``seplimit``. Cannot be a scalar coordinate. coords2 : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The second set of coordinates, which will be searched for matches from ``coords1`` within ``seplimit``. Cannot be a scalar coordinate. distlimit : `~astropy.units.Quantity` ['length'] The physical radius to search within. storekdtree : bool or str, optional If a string, will store the KD-Tree used in the search with the name ``storekdtree`` in ``coords2.cache``. This speeds up subsequent calls to this function. If False, the KD-Trees are not saved. Returns ------- idx1 : int array Indices into ``coords1`` that matches to the corresponding element of ``idx2``. Shape matches ``idx2``. idx2 : int array Indices into ``coords2`` that matches to the corresponding element of ``idx1``. Shape matches ``idx1``. sep2d : `~astropy.coordinates.Angle` The on-sky separation between the coordinates. Shape matches ``idx1`` and ``idx2``. dist3d : `~astropy.units.Quantity` ['length'] The 3D distance between the coordinates. Shape matches ``idx1`` and ``idx2``. The unit is that of ``coords1``. Notes ----- This function requires `SciPy `_ to be installed or it will fail. If you are using this function to search in a catalog for matches around specific points, the convention is for ``coords2`` to be the catalog, and ``coords1`` are the points to search around. While these operations are mathematically the same if ``coords1`` and ``coords2`` are flipped, some of the optimizations may work better if this convention is obeyed. In the current implementation, the return values are always sorted in the same order as the ``coords1`` (so ``idx1`` is in ascending order). This is considered an implementation detail, though, so it could change in a future release. z.distlimit must be a scalar in search_around_3dzOne of the inputs to search_around_3d is a scalar. search_around_3d is intended for use with array coordinates, not scalars. Instead, use ``coord1.separation_3d(coord2) < distlimit`` to find the coordinates near a scalar coordinate.rZdtype) forceunit)rrrrarrayintrudegQuantitydistancerrrrrZto_value enumeratequery_ball_treeappendsizer$r6)coords1coords2Z distlimitr(kdt2Zcunitkdt1didxs1idxs2imatchesmatchd2dsd3dsr-r-r.r s>7           cCs(|jstd|js|jr"tdt|dks:t|dkr|jjtjkrPtj}n|jj}tjgt dtjgt dt gtj t g|fS| |}|jt}||}t||}|r|j|r|j|}n>|jt} || } t| |}|r ||j|dkrdn|<dtt |dj} g} g} t||| D]*\}}|D]}| || |qHq`_ to be installed or it will fail. In the current implementation, the return values are always sorted in the same order as the ``coords1`` (so ``idx1`` is in ascending order). This is considered an implementation detail, though, so it could change in a future release. z.seplimit must be a scalar in search_around_skyzOne of the inputs to search_around_sky is a scalar. search_around_sky is intended for use with array coordinates, not scalars. Instead, use ``coord1.separation(coord2) < seplimit`` to find the coordinates near a scalar coordinate.rr8Tr0g@)rrrr?rr<Zdimensionless_unscaledrr:r;rr=r>rr1r2rr3rr4r5sinr r@rArBrCr$r6)rDrEZseplimitr(ZdistunitZurepr1Zucoords1rGrFZurepr2Zucoords2rrIrJrKrLrMrNrOr-r-r.r 3s^4                r0c Cshddlm}ddlm}z |j}Wn"tk rD|d|j}YnX|dkrRd}t|tr|j |d}|dk rt||st d|d n.t||r|}d}n|sd}nt d t||dkrT|dkr|j j }n|j j |}|d t|jd f}t|jrtd z||jjd d d}Wn"t k rR||jj}YnX|rd||j |<|S)a This is a utility function to retrieve (and build/cache, if necessary) a 3D cartesian KD-Tree from various sorts of astropy coordinate objects. Parameters ---------- coord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord` The coordinates to build the KD-Tree for. attrname_or_kdt : bool or str or KDTree If a string, will store the KD-Tree used for the computation in the ``coord``, in ``coord.cache`` with the provided name. If given as a KD-Tree, it will just be used directly. forceunit : unit or None If a unit, the cartesian coordinates will convert to that unit before being put in the KD-Tree. If None, whatever unit it's already in will be used Returns ------- kdt : `~scipy.spatial.cKDTree` or `~scipy.spatial.KDTree` The KD-Tree representing the 3D cartesian representation of the input coordinates. r)warn)spatialzNC-based KD tree not found, falling back on (much slower) python implementationTr0NzThe `attrname_or_kdt` "z" is not a scipy KD tree!z/Invalid `attrname_or_kdt` argument for KD-Tree:rz/Catalog coordinates cannot contain NaN entries.F)Z compact_nodesZ balanced_tree)warningsrSZscipyrTZcKDTree ExceptionKDTreerr7r4r5 TypeErrorrrrrrrrrr r!rr#) ZcoordZattrname_or_kdtr9rSrTrWr)ZcartxyzZflatxyzr-r-r.rsN           r)rr )rr/)r )r/)r0N)__doc__ZnumpyrZastropyrr<rZrepresentationrZsky_coordinater__all__rrr r rr-r-r-r.s(     T ^ k