ScipyMinimize

class pmrf.optimize.ScipyMinimize(method: str | None = None, tol: float | None = None, options: dict = <factory>, show_progress: bool = True, use_grad: bool | None = None)

Bases: AbstractBoundedMinimizer

A wrapper around SciPy’s scipy.optimize.minimize().

run(fn: Callable[[PyTree, Any], Any], y0: PyTree, args: Any = None, bounds: tuple[PyTree, PyTree] | None = None, max_iter: int = 1024, **kwargs) → MinimizeResult

Execute the minimization algorithm.

Parameters:

  • fn (callable) – The objective function to minimize.

  • y0 (PyTree) – The initial parameter guess.

  • args (Any) – Args to pass to fn.

  • bounds (PyTree) – Bounds for y0, if any.

  • max_iter (int = 1024) – The maximum number of iterations to take.

  • **kwargs – Runtime arguments forward to the solver backend.

Returns:

An instance of pmrf.optimize.MinimizeResult.

Return type:

results

method: str | None = None
options: dict
show_progress: bool = True
tol: float | None = None
use_grad: bool | None = None