pyfebiopt.optimize.alignment

Utilities for selecting evaluation grids and aligning simulation data.

Attributes

Array
GridPolicy

Classes

EvaluationGrid	Policy-driven evaluation grid selection.
Aligner	Thin wrapper above scipy.interpolate.interp1d() style API.

Module Contents

pyfebiopt.optimize.alignment.Array

pyfebiopt.optimize.alignment.GridPolicy

class pyfebiopt.optimize.alignment.EvaluationGrid

Policy-driven evaluation grid selection.

exp_to_sim preserves the experimental sampling and ensures simulations are compared on that grid. fixed_user enforces a custom user-provided grid, enabling shared abscissa among multiple experiments.

policy: GridPolicy

common_grid: Array | None = None

select_grid(x_exp: Array, _x_sim: Array) → Array

Return the abscissa where residuals should be evaluated.

Parameters:

x_exp – Experimental sampling points.

Returns:

Evaluation grid matching the chosen policy.

class pyfebiopt.optimize.alignment.Aligner

Thin wrapper above scipy.interpolate.interp1d() style API.

map(x_src: Array, y_src: Array, x_tgt: Array) → Array

Project the (x_src, y_src) samples onto x_tgt.

Returns:

Aligned values with the same shape as x_tgt.