simpeg.optimization.ProjectedGNCG.minimize#
- ProjectedGNCG.minimize(evalFunction, x0)[source]#
Minimizes the function (evalFunction) starting at the location x0.
- Parameters:
- evalFunction
callable()
The objective function to be minimized:
evalFunction( x: numpy.ndarray, return_g: bool, return_H: bool ) -> ( float | tuple[float, numpy.ndarray] | tuple[float, LinearOperator] | tuple[float, numpy.ndarray, LinearOperator] )
That will optionally return the gradient as a
numpy.ndarray
and the Hessian as any class that supports matrix vector multiplication using the * operator.- x0
numpy.ndarray
Initial guess.
- evalFunction
- Returns:
- x_min
numpy.ndarray
The last iterate of the optimization algorithm.
- x_min