CartesianRepresentation¶

class
astropy.coordinates.
CartesianRepresentation
(x, y=None, z=None, unit=None, xyz_axis=None, differentials=None, copy=True)[source] [edit on github]¶ Bases:
astropy.coordinates.BaseRepresentation
Representation of points in 3D cartesian coordinates.
Parameters:  x, y, z :
Quantity
or array The x, y, and z coordinates of the point(s). If
x
,y
, andz
have different shapes, they should be broadcastable. If not quantity,unit
should be set. If onlyx
is given, it is assumed that it contains an array with the 3 coordinates stored alongxyz_axis
. unit :
Unit
or str 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
, andz
(default: 0). differentials : dict,
CartesianDifferential
, optional Any differential classes that should be associated with this representation. The input must either be a single
CartesianDifferential
instance, or a dictionary ofCartesianDifferential
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 rather than referenced.
Attributes Summary
attr_classes
x
The ‘x’ component of the points(s). xyz
Return a vector array of the x, y, and z coordinates. y
The ‘y’ component of the points(s). z
The ‘z’ component of the points(s). Methods Summary
cross
(other)Cross product of two representations. dot
(other)Dot product of two representations. from_cartesian
(other)get_xyz
([xyz_axis])Return a vector array of the x, y, and z coordinates. mean
(*args, **kwargs)Vector mean. norm
()Vector norm. scale_factors
()Scale factors for each component’s direction. sum
(*args, **kwargs)Vector sum. to_cartesian
()Convert the representation to its Cartesian form. transform
(matrix)Transform the cartesian coordinates using a 3x3 matrix. unit_vectors
()Cartesian unit vectors in the direction of each component. Attributes Documentation

attr_classes
= {'x': <class 'astropy.units.quantity.Quantity'>, 'y': <class 'astropy.units.quantity.Quantity'>, 'z': <class 'astropy.units.quantity.Quantity'>}¶

x
¶ The ‘x’ component of the points(s).

xyz
¶ 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 :
Quantity
With dimension 3 along
xyz_axis
. Note that, if possible, this will be a view.

y
¶ The ‘y’ component of the points(s).

z
¶ The ‘z’ component of the points(s).
Methods Documentation

cross
(other)[source] [edit on github]¶ Cross product of two representations.
Parameters:  other : representation
If not already cartesian, it is converted.
Returns:  cross_product :
CartesianRepresentation
With vectors perpendicular to both
self
andother
.

dot
(other)[source] [edit on github]¶ Dot product of two representations.
Note that any associated differentials will be dropped during this operation.
Parameters:  other : representation
If not already cartesian, it is converted.
Returns:  dot_product :
Quantity
The sum of the product of the x, y, and z components of
self
andother
.

classmethod
from_cartesian
(other)[source] [edit on github]¶

get_xyz
(xyz_axis=0)[source] [edit on github]¶ 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 :
Quantity
With dimension 3 along
xyz_axis
. Note that, if possible, this will be a view.

mean
(*args, **kwargs)[source] [edit on github]¶ Vector mean.
Returns a new CartesianRepresentation instance with the means of the x, y, and z components.
Refer to
mean
for full documentation of the arguments, noting thataxis
is the entry in theshape
of the representation, and that theout
argument cannot be used.

norm
()[source] [edit on github]¶ Vector norm.
The norm is the standard Frobenius norm, i.e., the square root of the sum of the squares of all components with nonangular 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.
 norm :

scale_factors
()[source] [edit on github]¶ Scale factors for each component’s direction.
Given unit vectors \(\hat{e}_c\) and scale factors \(f_c\), a change in one component of \(\delta c\) corresponds to a change in representation of \(\delta c \times f_c \times \hat{e}_c\).
Returns:  scale_factors : dict of
Quantity
The keys are the component names.
 scale_factors : dict of

sum
(*args, **kwargs)[source] [edit on github]¶ Vector sum.
Returns a new CartesianRepresentation instance with the sums of the x, y, and z components.
Refer to
sum
for full documentation of the arguments, noting thataxis
is the entry in theshape
of the representation, and that theout
argument cannot be used.

to_cartesian
()[source] [edit on github]¶ Convert the representation to its Cartesian form.
Note that any differentials get dropped.
Returns:  cartrepr :
CartesianRepresentation
The representation in Cartesian form.
 cartrepr :

transform
(matrix)[source] [edit on github]¶ 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.matrix_utilities 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 <Quantity [[ 1.8660254 , 3.23205081], [ 1.23205081, 1.59807621], [ 3. , 4. ]] pc>
 matrix :

unit_vectors
()[source] [edit on github]¶ Cartesian unit vectors in the direction of each component.
Given unit vectors \(\hat{e}_c\) and scale factors \(f_c\), a change in one component of \(\delta c\) corresponds to a change in representation of \(\delta c \times f_c \times \hat{e}_c\).
Returns:  unit_vectors : dict of
CartesianRepresentation
The keys are the component names.
 unit_vectors : dict of
 x, y, z :