tenzr::scipy::optimize¶

Classes¶

Functions¶

Functions Documentation¶

function MinimizeCg¶

TENZR_APIOptimizeResult MinimizeCg(
    const std::function< Array(const Array &)> & fn,
    const Array & x0,
    int maxiter =100,
    double tol =1.0e-5
)

Parameters:

• fn The objective function mapping an array to a scalar array.
• x0 The initial point.
• maxiter Maximum number of iterations.
• tol Convergence tolerance.
• fn Objective returning a scalar array.
• x0 Initial point.
• maxiter Maximum iterations.
• tol Gradient-norm termination threshold.

Return:

• The optimization result.
• Result containing the point, objective value, and convergence status.

Minimizes fn from x0 with the nonlinear conjugate-gradient method. Minimize a scalar function with nonlinear conjugate gradient and backtracking line search.

function MinimizeBfgs¶

TENZR_APIOptimizeResult MinimizeBfgs(
    const std::function< Array(const Array &)> & fn,
    const Array & x0,
    int maxiter =100,
    double tol =1.0e-5
)

Parameters:

• fn The objective function mapping an array to a scalar array.
• x0 The initial point.
• maxiter Maximum number of iterations.
• tol Convergence tolerance.
• fn Objective returning a scalar array.
• x0 Initial point.
• maxiter Maximum iterations.
• tol Gradient-norm termination threshold.

Return:

• The optimization result.
• Result containing the point, objective value, and convergence status.

Minimizes fn from x0 with the BFGS quasi-Newton method. Minimize a scalar function with BFGS and a backtracking line search.