lsst.scarlet.lite.parameters.FistaParameter Class Reference

Inheritance diagram for lsst.scarlet.lite.parameters.FistaParameter:

Public Member Functions
	__init__ (self, np.ndarray x, float step, Callable|None grad=None, Callable|None prox=None, float t0=1, np.ndarray|None z0=None)
	update (self, int it, np.ndarray input_grad, *args)
FistaParameter	__deepcopy__ (self, dict[int, Any]|None memo=None)
FistaParameter	__copy__ (self)
Public Member Functions inherited from lsst.scarlet.lite.parameters.Parameter
	__init__ (self, np.ndarray x, dict[str, np.ndarray] helpers, Callable|float step, Callable|None grad=None, Callable|None prox=None)
float	step (self)
tuple[int,...]	shape (self)
npt.DTypeLike	dtype (self)
Parameter	__copy__ (self)
Parameter	__deepcopy__ (self, dict[int, Any]|None memo=None)
Parameter	copy (self, bool deep=False)
	resize (self, Box old_box, Box new_box)

Public Attributes
	t = t0
Public Attributes inherited from lsst.scarlet.lite.parameters.Parameter
	x = x
	helpers = helpers
	grad = grad
	prox = prox

Additional Inherited Members
Protected Attributes inherited from lsst.scarlet.lite.parameters.Parameter
	_step = _step

Detailed Description

A `Parameter` that updates itself using the Beck-Teboulle 2009
FISTA proximal gradient method.

See https://www.ceremade.dauphine.fr/~carlier/FISTA

Parameters
----------
x:
    The array of values that is being fit.
step:
    A numerical step value or function to calculate the step for a
    given `x`.
grad:
    A function to calculate the gradient of `x`.
prox:
    A function to take the proximal operator of `x`.
t0:
    The initial value of the FISTA momentum term.
z0:
    The initial value of the extrapolation array.
    If `None` then a copy of `x` is used.

Member Function Documentation

__copy__()

FistaParameter lsst.scarlet.lite.parameters.FistaParameter.__copy__

(

self

)

Create a shallow copy of this parameter.

Returns
-------
parameter:
    A shallow copy of this parameter.

__deepcopy__()

FistaParameter lsst.scarlet.lite.parameters.FistaParameter.__deepcopy__	(		self,
		dict[int, Any] | None	memo = None )

Create a deep copy of this parameter.

Parameters
----------
memo:
    A memoization dictionary used by `copy.deepcopy`.
Returns
-------
parameter:
    A deep copy of this parameter.

update()

lsst.scarlet.lite.parameters.FistaParameter.update	(		self,
		int	it,
		np.ndarray	input_grad,
		*	args )

Update the parameter and meta-parameters using the PGM

See `Parameter` for the full description.

Reimplemented from lsst.scarlet.lite.parameters.Parameter.

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

• python/lsst/scarlet/lite/parameters.py