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# Source code for astropy.coordinates.representation.cartesian

    # Licensed under a 3-clause BSD style license - see LICENSE.rst
    """Cartesian representations and differentials."""

    import numpy as np
    from erfa import ufunc as erfa_ufunc

    import astropy.units as u

    from .base import BaseDifferential, BaseRepresentation

    class CartesianRepresentation(BaseRepresentation):
        """
        Representation of points in 3D cartesian coordinates.

        Parameters
        ----------
        x, y, z : `~astropy.units.Quantity` or array
            The x, y, and z coordinates of the point(s). If ``x``, ``y``, and ``z``
            have different shapes, they should be broadcastable. If not quantity,
            ``unit`` should be set.  If only ``x`` is given, it is assumed that it
            contains an array with the 3 coordinates stored along ``xyz_axis``.
        unit : unit-like
            If given, the coordinates will be converted to this unit (or taken to
            be in this unit if not given.
        xyz_axis : int, optional
            The axis along which the coordinates are stored when a single array is
            provided rather than distinct ``x``, ``y``, and ``z`` (default: 0).

        differentials : dict, `~astropy.coordinates.CartesianDifferential`, optional
            Any differential classes that should be associated with this
            representation. The input must either be a single
            `~astropy.coordinates.CartesianDifferential` instance, or a dictionary of
            `~astropy.coordinates.CartesianDifferential` s with keys set to a string representation of
            the SI unit with which the differential (derivative) is taken. For
            example, for a velocity differential on a positional representation, the
            key would be ``'s'`` for seconds, indicating that the derivative is a
            time derivative.

        copy : bool, optional
            If `True` (default), arrays will be copied. If `False`, arrays will
            be references, though possibly broadcast to ensure matching shapes.
        """

        attr_classes = {"x": u.Quantity, "y": u.Quantity, "z": u.Quantity}

        _xyz = None

        def __init__(
            self, x, y=None, z=None, unit=None, xyz_axis=None, differentials=None, copy=True
        ):
            if y is None and z is None:
                if isinstance(x, np.ndarray) and x.dtype.kind not in "OV":
                    # Short-cut for 3-D array input.
                    x = u.Quantity(x, unit, copy=copy, subok=True)
                    # Keep a link to the array with all three coordinates
                    # so that we can return it quickly if needed in get_xyz.
                    self._xyz = x
                    if xyz_axis:
                        x = np.moveaxis(x, xyz_axis, 0)
                        self._xyz_axis = xyz_axis
                    else:
                        self._xyz_axis = 0

                    self._x, self._y, self._z = x
                    self._differentials = self._validate_differentials(differentials)
                    return

                elif (
                    isinstance(x, CartesianRepresentation)
                    and unit is None
                    and xyz_axis is None
                ):
                    if differentials is None:
                        differentials = x._differentials

                    super().__init__(x, differentials=differentials, copy=copy)
                    return

                else:
                    x, y, z = x

            if xyz_axis is not None:
                raise ValueError(
                    "xyz_axis should only be set if x, y, and z are in a single array"
                    " passed in through x, i.e., y and z should not be not given."
                )

            if y is None or z is None:
                raise ValueError(
                    f"x, y, and z are required to instantiate {self.__class__.__name__}"
                )

            if unit is not None:
                x = u.Quantity(x, unit, copy=copy, subok=True)
                y = u.Quantity(y, unit, copy=copy, subok=True)
                z = u.Quantity(z, unit, copy=copy, subok=True)
                copy = False

            super().__init__(x, y, z, copy=copy, differentials=differentials)
            if not (
                self._x.unit.is_equivalent(self._y.unit)
                and self._x.unit.is_equivalent(self._z.unit)
            ):
                raise u.UnitsError("x, y, and z should have matching physical types")

        def unit_vectors(self):
            l = np.broadcast_to(1.0 * u.one, self.shape, subok=True)
            o = np.broadcast_to(0.0 * u.one, self.shape, subok=True)
            return {
                "x": CartesianRepresentation(l, o, o, copy=False),
                "y": CartesianRepresentation(o, l, o, copy=False),
                "z": CartesianRepresentation(o, o, l, copy=False),
            }

        def scale_factors(self):
            l = np.broadcast_to(1.0 * u.one, self.shape, subok=True)
            return {"x": l, "y": l, "z": l}

        def get_xyz(self, xyz_axis=0):
            """Return a vector array of the x, y, and z coordinates.

            Parameters
            ----------
            xyz_axis : int, optional
                The axis in the final array along which the x, y, z components
                should be stored (default: 0).

            Returns
            -------
            xyz : `~astropy.units.Quantity`
                With dimension 3 along ``xyz_axis``.  Note that, if possible,
                this will be a view.
            """
            if self._xyz is not None:
                if self._xyz_axis == xyz_axis:
                    return self._xyz
                else:
                    return np.moveaxis(self._xyz, self._xyz_axis, xyz_axis)

            # Create combined array.  TO DO: keep it in _xyz for repeated use?
            # But then in-place changes have to cancel it. Likely best to
            # also update components.
            return np.stack([self._x, self._y, self._z], axis=xyz_axis)

        xyz = property(get_xyz)

        @classmethod
        def from_cartesian(cls, other):
            return other

        def to_cartesian(self):
            return self

        def transform(self, matrix):
            """
            Transform the cartesian coordinates using a 3x3 matrix.

            This returns a new representation and does not modify the original one.
            Any differentials attached to this representation will also be
            transformed.

            Parameters
            ----------
            matrix : ndarray
                A 3x3 transformation matrix, such as a rotation matrix.

            Examples
            --------
            We can start off by creating a cartesian representation object:

                >>> from astropy import units as u
                >>> from astropy.coordinates import CartesianRepresentation
                >>> rep = CartesianRepresentation([1, 2] * u.pc,
                ...                               [2, 3] * u.pc,
                ...                               [3, 4] * u.pc)

            We now create a rotation matrix around the z axis:

                >>> from astropy.coordinates import rotation_matrix
                >>> rotation = rotation_matrix(30 * u.deg, axis='z')

            Finally, we can apply this transformation:

                >>> rep_new = rep.transform(rotation)
                >>> rep_new.xyz  # doctest: +FLOAT_CMP
                <Quantity [[ 1.8660254 , 3.23205081],
                           [ 1.23205081, 1.59807621],
                           [ 3.        , 4.        ]] pc>
            """
            # erfa rxp: Multiply a p-vector by an r-matrix.
            p = erfa_ufunc.rxp(matrix, self.get_xyz(xyz_axis=-1))
            # transformed representation
            rep = self.__class__(p, xyz_axis=-1, copy=False)
            # Handle differentials attached to this representation
            new_diffs = {
                k: d.transform(matrix, self, rep) for k, d in self.differentials.items()
            }
            return rep.with_differentials(new_diffs)

        def _combine_operation(self, op, other, reverse=False):
            self._raise_if_has_differentials(op.__name__)

            try:
                other_c = other.to_cartesian()
            except Exception:
                return NotImplemented

            first, second = (self, other_c) if not reverse else (other_c, self)
            return self.__class__(
                *(
                    op(getattr(first, component), getattr(second, component))
                    for component in first.components
                )
            )

        def norm(self):
            """Vector norm.

            The norm is the standard Frobenius norm, i.e., the square root of the
            sum of the squares of all components with non-angular units.

            Note that any associated differentials will be dropped during this
            operation.

            Returns
            -------
            norm : `astropy.units.Quantity`
                Vector norm, with the same shape as the representation.
            """
            # erfa pm: Modulus of p-vector.
            return erfa_ufunc.pm(self.get_xyz(xyz_axis=-1))

        def mean(self, *args, **kwargs):
            """Vector mean.

            Returns a new CartesianRepresentation instance with the means of the
            x, y, and z components.

            Refer to `~numpy.mean` for full documentation of the arguments, noting
            that ``axis`` is the entry in the ``shape`` of the representation, and
            that the ``out`` argument cannot be used.
            """
            self._raise_if_has_differentials("mean")
            return self._apply("mean", *args, **kwargs)

        def sum(self, *args, **kwargs):
            """Vector sum.

            Returns a new CartesianRepresentation instance with the sums of the
            x, y, and z components.

            Refer to `~numpy.sum` for full documentation of the arguments, noting
            that ``axis`` is the entry in the ``shape`` of the representation, and
            that the ``out`` argument cannot be used.
            """
            self._raise_if_has_differentials("sum")
            return self._apply("sum", *args, **kwargs)

        def dot(self, other):
            """Dot product of two representations.

            Note that any associated differentials will be dropped during this
            operation.

            Parameters
            ----------
            other : `~astropy.coordinates.BaseRepresentation` subclass instance
                If not already cartesian, it is converted.

            Returns
            -------
            dot_product : `~astropy.units.Quantity`
                The sum of the product of the x, y, and z components of ``self``
                and ``other``.
            """
            try:
                other_c = other.to_cartesian()
            except Exception as err:
                raise TypeError(
                    "can only take dot product with another "
                    f"representation, not a {type(other)} instance."
                ) from err
            # erfa pdp: p-vector inner (=scalar=dot) product.
            return erfa_ufunc.pdp(self.get_xyz(xyz_axis=-1), other_c.get_xyz(xyz_axis=-1))

        def cross(self, other):
            """Cross product of two representations.

            Parameters
            ----------
            other : `~astropy.coordinates.BaseRepresentation` subclass instance
                If not already cartesian, it is converted.

            Returns
            -------
            cross_product : `~astropy.coordinates.CartesianRepresentation`
                With vectors perpendicular to both ``self`` and ``other``.
            """
            self._raise_if_has_differentials("cross")
            try:
                other_c = other.to_cartesian()
            except Exception as err:
                raise TypeError(
                    "cannot only take cross product with another "
                    f"representation, not a {type(other)} instance."
                ) from err
            # erfa pxp: p-vector outer (=vector=cross) product.
            sxo = erfa_ufunc.pxp(self.get_xyz(xyz_axis=-1), other_c.get_xyz(xyz_axis=-1))
            return self.__class__(sxo, xyz_axis=-1)

    class CartesianDifferential(BaseDifferential):
        """Differentials in of points in 3D cartesian coordinates.

        Parameters
        ----------
        d_x, d_y, d_z : `~astropy.units.Quantity` or array
            The x, y, and z coordinates of the differentials. If ``d_x``, ``d_y``,
            and ``d_z`` have different shapes, they should be broadcastable. If not
            quantities, ``unit`` should be set.  If only ``d_x`` is given, it is
            assumed that it contains an array with the 3 coordinates stored along
            ``xyz_axis``.
        unit : `~astropy.units.Unit` or str
            If given, the differentials will be converted to this unit (or taken to
            be in this unit if not given.
        xyz_axis : int, optional
            The axis along which the coordinates are stored when a single array is
            provided instead of distinct ``d_x``, ``d_y``, and ``d_z`` (default: 0).
        copy : bool, optional
            If `True` (default), arrays will be copied. If `False`, arrays will
            be references, though possibly broadcast to ensure matching shapes.
        """

        base_representation = CartesianRepresentation
        _d_xyz = None

        def __init__(self, d_x, d_y=None, d_z=None, unit=None, xyz_axis=None, copy=True):
            if d_y is None and d_z is None:
                if isinstance(d_x, np.ndarray) and d_x.dtype.kind not in "OV":
                    # Short-cut for 3-D array input.
                    d_x = u.Quantity(d_x, unit, copy=copy, subok=True)
                    # Keep a link to the array with all three coordinates
                    # so that we can return it quickly if needed in get_xyz.
                    self._d_xyz = d_x
                    if xyz_axis:
                        d_x = np.moveaxis(d_x, xyz_axis, 0)
                        self._xyz_axis = xyz_axis
                    else:
                        self._xyz_axis = 0

                    self._d_x, self._d_y, self._d_z = d_x
                    return

                else:
                    d_x, d_y, d_z = d_x

            if xyz_axis is not None:
                raise ValueError(
                    "xyz_axis should only be set if d_x, d_y, and d_z are in a single array"
                    " passed in through d_x, i.e., d_y and d_z should not be not given."
                )

            if d_y is None or d_z is None:
                raise ValueError(
                    "d_x, d_y, and d_z are required to instantiate"
                    f" {self.__class__.__name__}"
                )

            if unit is not None:
                d_x = u.Quantity(d_x, unit, copy=copy, subok=True)
                d_y = u.Quantity(d_y, unit, copy=copy, subok=True)
                d_z = u.Quantity(d_z, unit, copy=copy, subok=True)
                copy = False

            super().__init__(d_x, d_y, d_z, copy=copy)
            if not (
                self._d_x.unit.is_equivalent(self._d_y.unit)
                and self._d_x.unit.is_equivalent(self._d_z.unit)
            ):
                raise u.UnitsError("d_x, d_y and d_z should have equivalent units.")

        def to_cartesian(self, base=None):
            return CartesianRepresentation(*[getattr(self, c) for c in self.components])

        @classmethod
        def from_cartesian(cls, other, base=None):
            return cls(*[getattr(other, c) for c in other.components])

        def transform(self, matrix, base=None, transformed_base=None):
            """Transform differentials using a 3x3 matrix in a Cartesian basis.

            This returns a new differential and does not modify the original one.

            Parameters
            ----------
            matrix : (3,3) array-like
                A 3x3 (or stack thereof) matrix, such as a rotation matrix.
            base, transformed_base : `~astropy.coordinates.CartesianRepresentation` or None, optional
                Not used in the Cartesian transformation.
            """
            # erfa rxp: Multiply a p-vector by an r-matrix.
            p = erfa_ufunc.rxp(matrix, self.get_d_xyz(xyz_axis=-1))

            return self.__class__(p, xyz_axis=-1, copy=False)

        def get_d_xyz(self, xyz_axis=0):
            """Return a vector array of the x, y, and z coordinates.

            Parameters
            ----------
            xyz_axis : int, optional
                The axis in the final array along which the x, y, z components
                should be stored (default: 0).

            Returns
            -------
            d_xyz : `~astropy.units.Quantity`
                With dimension 3 along ``xyz_axis``.  Note that, if possible,
                this will be a view.
            """
            if self._d_xyz is not None:
                if self._xyz_axis == xyz_axis:
                    return self._d_xyz
                else:
                    return np.moveaxis(self._d_xyz, self._xyz_axis, xyz_axis)

            # Create combined array.  TO DO: keep it in _d_xyz for repeated use?
            # But then in-place changes have to cancel it. Likely best to
            # also update components.
            return np.stack([self._d_x, self._d_y, self._d_z], axis=xyz_axis)

        d_xyz = property(get_d_xyz)