pycif.plugins.minimizers.scipy_conjugate — API reference

Contents

pycif.plugins.minimizers.scipy_conjugate — API reference#

Configuration reference: scipy_conjugate plugin

pycif.plugins.minimizers.scipy_conjugate.minimize.minimize(self, finit, gradinit, chi0, **kwargs)[source]#

Solve the Gauss-Newton linear system via sparse conjugate gradient.

Builds a LinearOperator whose matrix-vector product is evaluated by calling the TL/forward simulator, then dispatches to cg or lobpcg according to the method parameter.

Parameters:

  • self (Plugin) – scipy conjugate-gradient plugin instance.

  • finit (float) – initial cost value (unused; kept for interface consistency with other minimizers).

  • gradinit (np.ndarray) – initial gradient \(\nabla J_0\), shape (n,); used as the right-hand side of the linear system.

  • chi0 (np.ndarray) – initial iterate (starting guess for the solver), shape (n,).

  • **kwargs – forwarded to the simulator.

Returns:

solution \(\chi_\mathrm{opt}\), shape (n,).

Return type:

np.ndarray

Contents