# Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
"""
Provides a set of coordinate frames.
----
.. include license and copyright
.. include:: ../include/copy.rst
----
.. include common links, assuming primary doc root is up one directory
.. include:: ../include/links.rst
"""
import numpy
from scipy import linalg
[docs]class SemiMajorAxisCoo:
r"""
Calculate the semi-major axis coordinates given a set of input
parameters following :math:`{\mathbf x} = {\mathbf A}^{-1}\ {\mathbf
b}`, where
.. math::
{\mathbf A} = \left[
\begin{array}{rrrrrr}
1 & 0 & 0 & 0 & 0 & 0 \\
0 & 1 & 0 & 0 & 0 & 0 \\
\cos\psi & \sin\psi & -1 & 0 & 0 & 0 \\
-\sin\psi & \cos\psi & 0 & -1 & 0 & 0 \\
0 & 0 & \sin\phi_0 & \cos\phi_0 & -1 & 0 \\
0 & 0 & -\cos\phi_0 & \sin\phi_0 & 0 & \varepsilon-1
\end{array}
\right]
{\mathbf b} = \left[
\begin{array}{r}
x_f \\
y_f \\
-x_0 \\
-y_0 \\
0 \\
0
\end{array}
\right]
such that
.. math::
{\mathbf x} = \left[
\begin{array}{r}
x_f \\
y_f \\
x_s \\
y_s \\
x_a \\
y_a
\end{array}
\right]
and:
- :math:`\psi` is the Cartesian rotation of the focal-plane
relative to the sky-plane (+x toward East; +y toward North),
- :math:`\phi_0` is the on-sky position angle of the major axis
of the ellipse, defined as the angle from North through East
- :math:`\varepsilon=1-b/a` is the ellipticity based on the the
semi-minor to semi-major axis ratio (:math:`b/a`).
- :math:`(x_f,y_f)` is the sky-right, focal-plane position
relative to a reference on-sky position :math:`(x_0,y_0)`
relative to the center of the ellipse (galaxy center),
- :math:`(x_s,y_s)` is the on-sky position of :math:`(x_f,y_f)`
relative to the center of the ellipse, and
- :math:`(x_a,y_a)` is the Cartesian position of
:math:`(x_f,y_f)` in units of the semi-major axis.
This form is used such that :math:`{\mathbf A}` need only be defined
once per class instance.
The class also allows for inverse calculations, i.e., calculating
the focal-plane positions provide the semi-major axis coordinates.
In this case,
.. math::
{\mathbf C} = \left[
\begin{array}{rrrr}
\cos\psi & \sin\psi & -1 & 0 \\
-\sin\psi & \cos\psi & 0 & -1 \\
0 & 0 & \sin\phi_0 & \cos\phi_0 \\
0 & 0 & -\cos\phi_0 & \sin\phi_0
\end{array}
\right]
{\mathbf d} = \left[
\begin{array}{r}
-x_0 \\
-y_0 \\
x_a \\
y_a (1-\varepsilon)
\end{array}
\right]
such that
.. math::
{\mathbf f} = \left[
\begin{array}{r}
x_f \\
y_f \\
x_s \\
y_s
\end{array}
\right]
and :math:`{\mathbf f} = {\mathbf C}^{-1}\ {\mathbf d}`.
Args:
xc (float): Same as :math:`x_0`, defined above
yc (float): Same as :math:`y_0`, defined above
rot (float): Same as :math:`\psi`, defined above
pa (float): Same as :math:`\phi_0`, defined above
ell (float): Same as :math:`\varepsilon`, defined above
Attributes:
xc,yc (float,float): a reference on-sky position relative to the
center of the ellipse (galaxy center); same as
:math:`(x_0,y_0)` defined above
rot (float): Cartesian rotation of the focal-plane relative to
the sky-plane (+x toward East; +y toward North); same as
:math:`\psi` defined above
pa (float): On-sky position angle of the major axis of the
ellipse, defined as the angle from North through East and is
the same as :math:`\phi_0` defined above
ell (float): Ellipticity define as :math:`\varepsilon=1-b/a`,
based on the semi-minor to semi-major axis ratio
(:math:`b/a`) of the ellipse.
A (numpy.ndarray): The coordinate transformation matrix
Alu (numpy.ndarray): The **lu** array returned by
`scipy.linalg.lu_factor`_, which is used to calculate the LU
decomposition of :math:`{\mathbf A}`
Apiv (numpy.ndarray): The **piv** array returned by
`scipy.linalg.lu_factor`_, which is used to calculate the LU
decomposition of :math:`{\mathbf A}`
B (numpy.ndarray): The vector :math:`{\mathbf b}`, as defined
above, used to calculate :math:`{\mathbf x} = {\mathbf
A}^{-1}\ {\mathbf b}`
C (numpy.ndarray): The coordinate transformation matrix use for
the inverse operations
Clu (numpy.ndarray): The **lu** array returned by
`scipy.linalg.lu_factor`_, which is used to calculate the LU
decomposition of :math:`{\mathbf C}`
Cpiv (numpy.ndarray): The **piv** array returned by
`scipy.linalg.lu_factor`_, which is used to calculate the LU
decomposition of :math:`{\mathbf C}`
D (numpy.ndarray): The vector :math:`{\mathbf d}`, as defined
above, used to calculate :math:`{\mathbf f} = {\mathbf
C}^{-1}\ {\mathbf d}`
"""
def __init__(self, xc=None, yc=None, rot=None, pa=None, ell=None):
self.xc = 0.0 if xc is None else xc
self.yc = 0.0 if yc is None else yc
self.rot = 0.0 if rot is None else rot
self.pa = 0.0 if pa is None else pa
self.ell = 0.0 if ell is None else ell
self.A = None
self.Alu = None
self.Apiv = None
self._setA()
self.C = None
self.Clu = None
self.Cpiv = None
self.D = None
self._setC()
[docs] def _defined(self):
"""
Determine if the object is defined such that its methods can be
used to convert between coordinate systems.
"""
if self.A is None:
return False
if self.Alu is None:
return False
if self.Apiv is None:
return False
if self.C is None:
return False
if self.Clu is None:
return False
if self.Cpiv is None:
return False
return True
[docs] def _setA(self):
"""
Set the transformation matrix and calculate its LU
decomposition for forward operations.
"""
cosr = numpy.cos( numpy.radians(self.rot) )
sinr = numpy.sin( numpy.radians(self.rot) )
cosp = numpy.cos( numpy.radians(self.pa) )
sinp = numpy.sin( numpy.radians(self.pa) )
#cosi = numpy.cos( numpy.radians(self.inc) )
self.A = numpy.array([ [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ],
[ cosr, sinr, -1.0, 0.0, 0.0, 0.0 ],
[ -sinr, cosr, 0.0, -1.0, 0.0, 0.0 ],
[ 0.0, 0.0, sinp, cosp, -1.0, 0.0 ],
[ 0.0, 0.0, -cosp, sinp, 0.0, self.ell-1. ] ])
self.Alu, self.Apiv = linalg.lu_factor(self.A)
[docs] def _get_B(self, x, y):
"""
Set the on-sky coordinate vector for forward operations.
Args:
x (`numpy.ndarray`_):
On-sky Cartesian coordinate.
y (`numpy.ndarray`_):
On-sky Cartesian coordinate.
Returns:
`numpy.ndarray`_: Array prepared for the matrix solution.
"""
return numpy.vstack((x.ravel(), y.ravel(), numpy.full(x.size, -self.xc, dtype=float),
numpy.full(x.size, -self.yc, dtype=float),
numpy.zeros(x.size, dtype=float),
numpy.zeros(x.size, dtype=float)))
[docs] def _setC(self):
"""
Set the transformation matrix and calculate its LU
decomposition for inverse operations.
"""
cosr = numpy.cos( numpy.radians(self.rot) )
sinr = numpy.sin( numpy.radians(self.rot) )
cosp = numpy.cos( numpy.radians(self.pa) )
sinp = numpy.sin( numpy.radians(self.pa) )
self.C = numpy.array([ [ cosr, sinr, -1.0, 0.0 ],
[ -sinr, cosr, 0.0, -1.0 ],
[ 0.0, 0.0, sinp, cosp ],
[ 0.0, 0.0, -cosp, sinp ] ])
self.Clu, self.Cpiv = linalg.lu_factor(self.C)
[docs] def _get_D(self, x, y):
"""
Set the semi-major-axis coordinate vector for inverse operations.
Args:
x (`numpy.ndarray`_):
Semi-major axis Cartesian coordinate.
y (`numpy.ndarray`_):
Semi-major axis Cartesian coordinate.
Returns:
`numpy.ndarray`_: Array prepared for the matrix solution.
"""
return numpy.vstack((numpy.full(x.size, -self.xc, dtype=float),
numpy.full(x.size, -self.yc, dtype=float),
x.ravel(), (1-self.ell)*y.ravel()))
# self.D = numpy.array([ -self.xc, -self.yc, x, (1-self.ell)*y ])
[docs] def _calculate_polar(self, x, y):
r"""
Calculate the polar coordinates (radius and azimuth) provided
the Cartesian semi-major-axis coordinates :math:`(x_a,y_a)`
using
.. math::
R &= \sqrt{x_a^2 + y_a^2} \\
\theta &= \tan^{-1}\left(\frac{-y_a}{x_a}\right)
Args:
x,y (array-like): The semi-major-axis Cartesian coordinates
:math:`(x_a,y_a)`.
Returns:
numpy.ndarray: The semi-major-axis polar coordinates:
:math:`R, \theta`.
"""
_x = numpy.atleast_1d(x)
_y = numpy.atleast_1d(y)
if _x.size != _y.size:
raise ValueError('X and Y arrays must have the same size')
R = numpy.sqrt( _x*_x + _y*_y)
theta = numpy.degrees( numpy.arctan2(-_y, _x) )
if hasattr(theta, '__len__'):
theta[theta < 0] += 360.
elif theta < 0:
theta += 360.
# Returned range in theta is -pi,pi: convert to 0,2pi
return R, theta
[docs] def _calculate_cartesian(self, r, theta):
r"""
Invert the calculation of the semi-major-axis polar coordinates
to calculate the semi-major-axis Cartesian coordinates
:math:`(x_a,y_a)` using
.. math::
x_a &= \pm R / \sqrt{1 + \tan^2\theta}\\
y_a &= -x_a\ \tan\theta
where :math:`x_a` is negative when :math:`\pi/2 \leq \theta <
3\pi/2`.
Args:
r,theta (array-like): The semi-major-axis polar coordinates
:math:`(R,\theta)`.
Returns:
numpy.ndarray: The semi-major-axis Cartesian coordinates:
:math:`x_a, y_a`.
"""
_r = numpy.atleast_1d(r)
_theta = numpy.atleast_1d(theta)
if _r.size != _theta.size:
raise ValueError('R and THETA arrays must have the same size')
tant = numpy.tan(numpy.radians(_theta))
xd = _r/numpy.sqrt(1.0 + numpy.square(tant))
if hasattr(xd, '__len__'):
xd[(_theta > 90) & (_theta <= 270)] *= -1.
elif _theta > 90 and _theta <= 270:
xd *= -1.
yd = -xd*tant
return xd, yd
[docs] def solve(self, x, y):
r"""
Use `scipy.linalg.lu_solve`_ to solve :math:`{\mathbf x} =
{\mathbf A}^{-1}\ {\mathbf b}`.
Args:
x,y (array-like): The coordinates :math:`(x_f,y_f)`, which
are the sky-right, focal-plane Cartesian coordinates
relative to a reference on-sky position
:math:`(x_0,y_0)`, which is relative to the center of
the ellipse (galaxy center).
Returns:
numpy.ndarray: The :math:`{\mathbf x}` vectors (separated by
rows) as defined by the solution to :math:`{\mathbf A}^{-1}\
{\mathbf b}`
Raises:
ValueError: Raised if object was not properly defined or if
the X and Y arrays do not have the same size.
"""
if not self._defined():
raise ValueError('SemiMajorAxisCoo object not fully defined!')
_x = numpy.atleast_1d(x)
_y = numpy.atleast_1d(y)
if _x.size != _y.size:
raise ValueError('X and Y arrays must have the same size')
out = linalg.lu_solve((self.Alu, self.Apiv), self._get_B(_x,_y)).T.reshape(_x.shape + (6,))
return out[0] if isinstance(x, float) else out
# out = numpy.empty((_x.size, 6), dtype=numpy.float)
# for i, (xx, yy) in enumerate(zip(_x.ravel(),_y.ravel())):
# self._setB(xx,yy)
# out[i,:] = linalg.lu_solve((self.Alu, self.Apiv), self.B)
# return out.reshape(_x.shape + (6,))
[docs] def solve_inverse(self, x, y):
r"""
Use `scipy.linalg.lu_solve`_ to solve :math:`{\mathbf f} =
{\mathbf C}^{-1}\ {\mathbf d}`.
Args:
x,y (array-like): The semi-major-axis Cartesian coordinates
:math:`(x_a,y_a)`.
Returns:
numpy.ndarray: The :math:`{\mathbf f}` vector as defined by
the solution to :math:`{\mathbf C}^{-1}\ {\mathbf d}`
Raises:
ValueError: Raised if object was not properly defined or if
the X and Y arrays do not have the same size.
"""
if not self._defined():
raise ValueError('SemiMajorAxisCoo object not fully defined!')
_x = numpy.atleast_1d(x)
_y = numpy.atleast_1d(y)
if _x.size != _y.size:
raise ValueError('X and Y arrays must have the same size')
out = linalg.lu_solve((self.Clu, self.Cpiv), self._get_D(_x,_y)).T.reshape(_x.shape + (4,))
return out[0] if isinstance(x, float) else out
# out = numpy.empty((_x.size, 4), dtype=numpy.float)
# for i, (xx, yy) in enumerate(zip(_x.ravel(),_y.ravel())):
# self._setD(xx,yy)
# out[i,:] = linalg.lu_solve((self.Clu, self.Cpiv), self.D)
# return out.reshape(_x.shape + (4,))
[docs] def coo(self, x, y):
r"""
Calculate :math:`{\mathbf x}` using :func:`solve` for the
provided :math:`(x_f,y_f)` and return the semi-major-axis
Cartesian and polar coordinates, :math:`(x_a,y_a)` and
:math:`(R,\theta)`. This combines the functionality of
:func:`cartesian` and :func:`polar`, and so is more efficient
than using these both separately.
Args:
x,y (array-like): The coordinates :math:`(x_f,y_f)`, which
are the sky-right, focal-plane position relative to a
reference on-sky position :math:`(x_0,y_0)` relative to
the center of the ellipse (galaxy center),
Returns:
numpy.ndarray: Four arrays with the semi-major-axis
Cartesian and polar coordinates: :math:`x_a, y_a, R,
\theta`.
"""
coo = self.solve(x, y)
return (coo[...,4], coo[...,5]) + self._calculate_polar(coo[...,4], coo[...,5])
[docs] def polar(self, x, y):
r"""
Calculate :math:`{\mathbf x}` using :func:`solve` for the
provided :math:`(x_f,y_f)` and return the semi-major-axis polar
coordinates, :math:`(R,\theta)`, where
.. math::
R &= \sqrt{x_a^2 + y_a^2} \\
\theta &= \tan^{-1}\left(\frac{-y_a}{x_a}\right)
Args:
x,y (array-like): The coordinate :math:`(x_f,y_f)`, which
is the sky-right, focal-plane position relative to a
reference on-sky position :math:`(x_0,y_0)` relative to
the center of the ellipse (galaxy center),
Returns:
numpy.ndarray: Two arrays with the semi-major-axis polar
coordinates: :math:`R, \theta`.
"""
coo = self.solve(x, y)
return self._calculate_polar(coo[...,4], coo[...,5])
[docs] def polar_invert(self, r, theta):
r"""
Calculate :math:`{\mathbf f}` using :func:`solve` for the
provided :math:`(R,\theta)` and return focal-plane cartesian
coordinates :math:`(x_f,y_f)`.
Args:
r,theta (array-like): The semi-major-axis polar coordinates
:math:`(R,\theta)`.
Returns:
numpy.ndarray: Two arrays with the focal-plane Cartesian
coordinates :math:`(x_f,y_f)`.
"""
xd, yd = self._calculate_cartesian(r, theta)
coo = self.solve_inverse(xd, yd)
return coo[...,0], coo[...,1]
[docs] def cartesian(self, x, y):
r"""
Calculate :math:`{\mathbf x}` using :func:`solve` for the
provided :math:`(x_f,y_f)` and return the semi-major-axis
Cartesian and coordinates, :math:`(x_a,y_a)`.
Args:
x,y (array-like): The coordinate :math:`(x_f,y_f)`, which
is the sky-right, focal-plane position relative to a
reference on-sky position :math:`(x_0,y_0)` relative to
the center of the ellipse (galaxy center),
Returns:
numpy.ndarray: Two arrays with the semi-major-axis Cartesian
coordinates, :math:`x_a, y_a`.
"""
coo = self.solve(x, y)
return coo[...,4], coo[...,5]
[docs] def cartesian_invert(self, x, y):
r"""
Calculate :math:`{\mathbf f}` using :func:`solve` for the
provided :math:`(x_a,y_a)` and return focal-plane cartesian
coordinates :math:`(x_f,y_f)`.
Args:
x,y (array-like): The semi-major-axis Cartesian coordinates
:math:`(x_a,y_a)`.
Returns:
numpy.ndarray: The focal-plane Cartesian coordinates
:math:`(x_f,y_f)`.
"""
coo = self.solve_inverse(x, y)
return coo[...,0], coo[...,1]