pylops.optimization.callback.Callbacks

class pylops.optimization.callback.Callbacks

This is a template class which a user must subclass when implementing callbacks for a solver. This class comprises of the following methods:

• on_setup_begin: a method that is invoked at the start of the setup method of the solver

• on_setup_end: a method that is invoked at the end of the setup method of the solver

• on_step_begin: a method that is invoked at the start of the step method of the solver

• on_step_end: a method that is invoked at the end of the setup step of the solver

• on_run_begin: a method that is invoked at the start of the run method of the solver

• on_run_end: a method that is invoked at the end of the run method of the solver

All methods take two input parameters: the solver itself, and the vector x.

Examples

>>> import numpy as np
>>> from pylops.basicoperators import MatrixMult
>>> from pylops.optimization.solver import CG
>>> from pylops.optimization.callback import Callbacks
>>> class StoreIterCallback(Callbacks):
...     def __init__(self):
...         self.stored = []
...     def on_step_end(self, solver, x):
...         self.stored.append(solver.iiter)
>>> cb_sto = StoreIterCallback()
>>> Aop = MatrixMult(np.random.normal(0., 1., 36).reshape(6, 6))
>>> Aop = Aop.H @ Aop
>>> y = Aop @ np.ones(6)
>>> cgsolve = CG(Aop, callbacks=[cb_sto, ])
>>> xest = cgsolve.solve(y=y, x0=np.zeros(6), tol=0, niter=6, show=False)[0]
>>> xest
array([1., 1., 1., 1., 1., 1.])

Methods

__init__()
on_run_begin(solver, x)	Callback before entire solver run
on_run_end(solver, x)	Callback after entire solver run
on_setup_begin(solver, x0)	Callback before setup
on_setup_end(solver, x)	Callback after setup
on_step_begin(solver, x)	Callback before step of solver
on_step_end(solver, x)	Callback after step of solver

Examples using pylops.optimization.callback.Callbacks

Linear Regression

Linear Regression

03. Solvers (Advanced)

03. Solvers (Advanced)