Inheritance diagram for lsst.scarlet.lite.models.parametric.EllipseFrame:

Public Member Functions
	__init__ (self, float y0, float x0, float major, float minor, float theta, Box bbox, float r_min=1e-20)

float	grad_x0 (self, np.ndarray input_grad, bool use_r2)

float	grad_y0 (self, np.ndarray input_grad, bool use_r2)

float	grad_major (self, np.ndarray input_grad, bool use_r2)

float	grad_minor (self, np.ndarray input_grad, bool use_r2)

float	grad_theta (self, np.ndarray input_grad, bool use_r2)

float	x0 (self)

float	y0 (self)

float	major (self)

float	minor (self)

float	theta (self)

Box	bbox (self)

np.ndarray	r_grid (self)

np.ndarray	r2_grid (self)

Public Member Functions inherited from lsst.scarlet.lite.models.parametric.CartesianFrame
	__init__ (self, Box bbox)

tuple[int,...]	shape (self)

np.ndarray	x_grid (self)

np.ndarray	y_grid (self)

Protected Attributes
tuple	_xMajor = (self._x - x0) * cos + (self._y - y0) * sin

	_xMinor = -(self._x - x0) * sin + (self._y - y0) * cos

tuple	_xa = self._xMajor / major

float	_yb = self._xMinor / minor

	_y0

float	_x0 = y0, x0

float	_theta = theta

float	_major = major

float	_minor = minor

	_sin

	_cos = sin, cos

	_rMin = r_min

tuple	_radius2 = self._xa2 + self._yb2

np.ndarray\|None	_radius = None

Protected Attributes inherited from lsst.scarlet.lite.models.parametric.CartesianFrame
Box	_bbox = bbox

	_x = np.linspace(xi, xf - 1, width)

	_y = np.meshgrid(x, y)

	_r = None

	_r2 = None

Detailed Description

Frame to scale the radius based on the parameters of an ellipse

This frame is used to calculate the coordinates of the
radius and radius**2 from a given center location,
based on the semi-major axis, semi-minor axis, and rotation angle.
It is also used to calculate the gradient wrt either the
radius**2 or radius for all of the model parameters.

Parameters
----------
y0: float
    The y-center of the ellipse.
x0: float
    The x-center of the ellipse.
major: float
    The length of the semi-major axis.
minor: float
    The length of the semi-minor axis.
theta: float
    The counter-clockwise rotation angle
    from the semi-major axis.
bbox: Box
    The bounding box that contains the entire frame.
r_min: float
    The minimum value of the radius.
    This is used to prevent divergences that occur
    when calculating the gradient at radius == 0.

Member Function Documentation

◆ bbox()

Box lsst.scarlet.lite.models.parametric.EllipseFrame.bbox ( self )

The bounding box to hold the model

Reimplemented from lsst.scarlet.lite.models.parametric.CartesianFrame.

◆ grad_major()

float lsst.scarlet.lite.models.parametric.EllipseFrame.grad_major	(		self,
		np.ndarray	input_grad,
		bool	use_r2 )

The gradient of either the radius or radius**2 wrt.
the semi-major axis

Parameters
----------
input_grad:
    Gradient of the likelihood wrt the component model
use_r2:
    Whether to calculate the gradient of the radius**2
    (``use_r2==True``) or the radius (``use_r2==False``).

Returns
-------
result:
    The gradient of the likelihood wrt the semi-major axis.

◆ grad_minor()

float lsst.scarlet.lite.models.parametric.EllipseFrame.grad_minor	(		self,
		np.ndarray	input_grad,
		bool	use_r2 )

The gradient of either the radius or radius**2 wrt.
the semi-minor axis

Parameters
----------
input_grad:
    Gradient of the likelihood wrt the component model
use_r2:
    Whether to calculate the gradient of the radius**2
    (``useR2==True``) or the radius (``useR2==False``).

Returns
-------
result:
    The gradient of the likelihood wrt the semi-minor axis.

◆ grad_theta()

float lsst.scarlet.lite.models.parametric.EllipseFrame.grad_theta	(		self,
		np.ndarray	input_grad,
		bool	use_r2 )

The gradient of either the radius or radius**2 wrt.
the rotation angle

Parameters
----------
input_grad:
    Gradient of the likelihood wrt the component model
use_r2:
    Whether to calculate the gradient of the radius**2
    (``useR2==True``) or the radius (``useR2==False``).

Returns
-------
result:
    The gradient of the likelihood wrt the rotation angle.

◆ grad_x0()

float lsst.scarlet.lite.models.parametric.EllipseFrame.grad_x0	(		self,
		np.ndarray	input_grad,
		bool	use_r2 )

The gradient of either the radius or radius**2 wrt. the x-center

Parameters
----------
input_grad:
    Gradient of the likelihood wrt the component model
use_r2:
    Whether to calculate the gradient of the radius**2
    (``useR2==True``) or the radius (``useR2==False``).

Returns
-------
result:
    The gradient of the likelihood wrt x0.

◆ grad_y0()

float lsst.scarlet.lite.models.parametric.EllipseFrame.grad_y0	(		self,
		np.ndarray	input_grad,
		bool	use_r2 )

The gradient of either the radius or radius**2 wrt. the y-center

Parameters
----------
input_grad:
    Gradient of the likelihood wrt the component model
use_r2:
    Whether to calculate the gradient of the radius**2
    (``useR2==True``) or the radius (``useR2==False``).

Returns
-------
result:
    The gradient of the likelihood wrt y0.

◆ major()

float lsst.scarlet.lite.models.parametric.EllipseFrame.major ( self )

The semi-major axis

◆ minor()

float lsst.scarlet.lite.models.parametric.EllipseFrame.minor ( self )

The semi-minor axis

◆ r2_grid()

np.ndarray lsst.scarlet.lite.models.parametric.EllipseFrame.r2_grid ( self )

The radius squared located at each pixel

◆ r_grid()

np.ndarray lsst.scarlet.lite.models.parametric.EllipseFrame.r_grid ( self )

The radial coordinates of each pixel

◆ theta()

float lsst.scarlet.lite.models.parametric.EllipseFrame.theta ( self )

The rotation angle

◆ x0()

float lsst.scarlet.lite.models.parametric.EllipseFrame.x0 ( self )

The x-center

◆ y0()

float lsst.scarlet.lite.models.parametric.EllipseFrame.y0 ( self )

The y-center

The documentation for this class was generated from the following file:

python/lsst/scarlet/lite/models/parametric.py

Public Member Functions

Protected Attributes