a ߙfb7@spdZddlZddlmZddlZgdZGdddZGdddeejd Z Gd d d e Z d d Z ddZ dS)z>The ShapedLikeNDArray mixin class and shape-related functions.N) zip_longest)NDArrayShapeMethodsShapedLikeNDArraycheck_broadcastIncompatibleShapeError unbroadcastc@sneZdZdZddZddZddZdd Zd d Zd d Z e ddZ ddZ ddZ ddZdddZdS)raMixin class to provide shape-changing methods. The class proper is assumed to have some underlying data, which are arrays or array-like structures. It must define a ``shape`` property, which gives the shape of those data, as well as an ``_apply`` method that creates a new instance in which a `~numpy.ndarray` method has been applied to those. Furthermore, for consistency with `~numpy.ndarray`, it is recommended to define a setter for the ``shape`` property, which, like the `~numpy.ndarray.shape` property allows in-place reshaping the internal data (and, unlike the ``reshape`` method raises an exception if this is not possible). This class only provides the shape-changing methods and is meant in particular for `~numpy.ndarray` subclasses that need to keep track of other arrays. For other classes, `~astropy.utils.shapes.ShapedLikeNDArray` is recommended. cCs |d|S)N __getitem___applyselfitemr3lib/python3.9/site-packages/astropy/utils/shapes.pyr)szNDArrayShapeMethods.__getitem__cOs|jdg|Ri|S)zReturn an instance containing copies of the internal data. Parameters are as for :meth:`~numpy.ndarray.copy`. copyr r argskwargsrrrr,szNDArrayShapeMethods.copycOs|jdg|Ri|S)aReturns an instance containing the same data with a new shape. Parameters are as for :meth:`~numpy.ndarray.reshape`. Note that it is not always possible to change the shape of an array without copying the data (see :func:`~numpy.reshape` documentation). If you want an error to be raise if the data is copied, you should assign the new shape to the shape attribute (note: this may not be implemented for all classes using ``NDArrayShapeMethods``). reshaper rrrrr3s zNDArrayShapeMethods.reshapecOs|jdg|Ri|S)ahReturn an instance with the array collapsed into one dimension. Parameters are as for :meth:`~numpy.ndarray.ravel`. Note that it is not always possible to unravel an array without copying the data. If you want an error to be raise if the data is copied, you should should assign shape ``(-1,)`` to the shape attribute. ravelr rrrrr?szNDArrayShapeMethods.ravelcOs|jdg|Ri|S)zReturn a copy with the array collapsed into one dimension. Parameters are as for :meth:`~numpy.ndarray.flatten`. flattenr rrrrrIszNDArrayShapeMethods.flattencOs|jdg|Ri|S)zReturn an instance with the data transposed. Parameters are as for :meth:`~numpy.ndarray.transpose`. All internal data are views of the data of the original. transposer rrrrrPszNDArrayShapeMethods.transposecCs|jdkr|S|SdS)zReturn an instance with the data transposed. Parameters are as for :attr:`~numpy.ndarray.T`. All internal data are views of the data of the original. N)ndimrr rrrTXs zNDArrayShapeMethods.TcOs|jdg|Ri|S)zReturn an instance with the given axes interchanged. Parameters are as for :meth:`~numpy.ndarray.swapaxes`: ``axis1, axis2``. All internal data are views of the data of the original. swapaxesr rrrrrdszNDArrayShapeMethods.swapaxescOs|jdg|Ri|S)zReturn an instance with the specified diagonals. Parameters are as for :meth:`~numpy.ndarray.diagonal`. All internal data are views of the data of the original. diagonalr rrrrrmszNDArrayShapeMethods.diagonalcOs|jdg|Ri|S)zReturn an instance with single-dimensional shape entries removed Parameters are as for :meth:`~numpy.ndarray.squeeze`. All internal data are views of the data of the original. squeezer rrrrruszNDArrayShapeMethods.squeezeNraisecCs"|durtdS|jd|||dS)zReturn a new instance formed from the elements at the given indices. Parameters are as for :meth:`~numpy.ndarray.take`, except that, obviously, no output array can be given. Nz$cannot pass 'out' argument to 'take.take)axismode)NotImplementedErrorr )r indicesr!outr"rrrr }szNDArrayShapeMethods.take)NNr)__name__ __module__ __qualname____doc__rrrrrrpropertyrrrrr rrrrr s    rc @seZdZdZeejddZejddZeddZ edd Z ed d Z d d Z ddZ ddZddZejejejejejejejejejejejejejh Zddejj j!DZ"de"ej#<ddZ$dS)raMixin class to provide shape-changing methods. The class proper is assumed to have some underlying data, which are arrays or array-like structures. It must define a ``shape`` property, which gives the shape of those data, as well as an ``_apply`` method that creates a new instance in which a `~numpy.ndarray` method has been applied to those. Furthermore, for consistency with `~numpy.ndarray`, it is recommended to define a setter for the ``shape`` property, which, like the `~numpy.ndarray.shape` property allows in-place reshaping the internal data (and, unlike the ``reshape`` method raises an exception if this is not possible). This class also defines default implementations for ``ndim`` and ``size`` properties, calculating those from the ``shape``. These can be overridden by subclasses if there are faster ways to obtain those numbers. cCsdS)z!The shape of the underlying data.NrrrrrshapeszShapedLikeNDArray.shapecOsdS)aCreate a new instance, with ``method`` applied to underlying data. The method is any of the shape-changing methods for `~numpy.ndarray` (``reshape``, ``swapaxes``, etc.), as well as those picking particular elements (``__getitem__``, ``take``, etc.). It will be applied to the underlying arrays (e.g., ``jd1`` and ``jd2`` in `~astropy.time.Time`), with the results used to create a new instance. Parameters ---------- method : str Method to be applied to the instance's internal data arrays. args : tuple Any positional arguments for ``method``. kwargs : dict Any keyword arguments for ``method``. Nr)methodrrrrrr szShapedLikeNDArray._applycCs t|jS)z?The number of dimensions of the instance and underlying arrays.)lenr+rrrrrszShapedLikeNDArray.ndimcCsd}|jD] }||9}q |S)z5The size of the object, as calculated from its shape.r+)r sizeZshrrrr0s  zShapedLikeNDArray.sizecCs |jdkS)Nrr/rrrrisscalarszShapedLikeNDArray.isscalarcCs"|jrtd|jj|jdS)NzScalar {!r} object has no len()r)r1 TypeErrorformat __class__r&r+rrrr__len__s zShapedLikeNDArray.__len__cCs |jdkS)z>Any instance should evaluate to True, except when it is empty.r)r0rrrr__bool__szShapedLikeNDArray.__bool__cCsBz|d|WSty<|jr6td|jjnYn0dS)Nrz(scalar {!r} object is not subscriptable.)r IndexErrorr1r2r3r4r&r rrrrs zShapedLikeNDArray.__getitem__cs*jrtdjjfdd}|S)Nz#scalar {!r} object is not iterable.c3s ttD]}|Vq dSN)ranger-)idxrrr self_itersz-ShapedLikeNDArray.__iter__..self_iter)r1r2r3r4r&)r r;rrr__iter__s  zShapedLikeNDArray.__iter__c Cs6i|].}|dvrtt|ddddddd||qS))alensort partitionmaxminroundallany)ZamaxZaminZaroundZround_ZalltrueZsometrue)getattrnpget).0namerrr szShapedLikeNDArray.rcs|jvrtjur"ddn8tjtjtjhvrZt|dkrZtfdd|DS||durjt S|j g|ddRiS||dur܈|j vrt ||j d}|durt |r||ddiS|Sj|iS)z%Wrap numpy functions that make sense.ZsubokTr.c3s|]}|fiVqdSr8r)rHargfunctionrrr z7ShapedLikeNDArray.__array_function__..rN)_APPLICABLE_FUNCTIONSrF broadcast_to setdefault atleast_1d atleast_2d atleast_3dr-tupleNotImplementedr _METHOD_FUNCTIONSrEcallable __wrapped__)r rMtypesrrr,rrLr__array_function__ s(     z$ShapedLikeNDArray.__array_function__N)%r&r'r(r)r*abcabstractmethodr+r rr0r1r5r6rr<rFZmoveaxisZrollaxisrSrTrUZ expand_dimsrQZflipZfliplrZflipudZrot90ZrolldeleterPcoreZ fromnumeric__all__rXrr\rrrrrs4        r) metaclasscseZdZfddZZS)rcst||||dSr8)super__init__)r Zshape_aZ shape_a_idxZshape_bZ shape_b_idxr4rrrd0szIncompatibleShapeError.__init__)r&r'r(rd __classcell__rrrerr/srcGst|dkrdSt|dkr$|dSdd|D}g}t|ddiD]b}d}d}t|D]B\}}|dkrjqX|dkr||}|}qX||krXt||||||qX||qDt|dddS) a Determines whether two or more Numpy arrays can be broadcast with each other based on their shape tuple alone. Parameters ---------- *shapes : tuple All shapes to include in the comparison. If only one shape is given it is passed through unmodified. If no shapes are given returns an empty `tuple`. Returns ------- broadcast : `tuple` If all shapes are mutually broadcastable, returns a tuple of the full broadcast shape. rrr.css|]}t|VqdSr8)reversed)rHr+rrrrNLrOz"check_broadcast.. fillvalueN)r-r enumeraterappendrV)ZshapesZreversed_shapesZ full_shapeZdimsZmax_dimZ max_dim_idxr:Zdimrrrr4s*   rcCsV|jdkr|S|tdd|jD}tddt|jD|j}||j|dS)a Given an array, return a new array that is the smallest subset of the original array that can be re-broadcasted back to the original array. See https://stackoverflow.com/questions/40845769/un-broadcasting-numpy-arrays for more details. rcss(|] }|dkrtddntdVqdS)rr.N)slice)rHZstriderrrrNpszunbroadcast..css|]\}}|dkr|VqdS)r.Nr)rHisrrrrNtrON)rrVstridesnextrjr+r)ZarrayZfirst_not_unityrrrrds   r)r)r] itertoolsrZnumpyrFrarABCMetar ValueErrorrrrrrrrs |'0