PRAXIS
Scalar Function Optimization


PRAXIS is a Python library which minimizes a scalar function of a vector argument, without needing derivative information, by Richard Brent.

PRAXIS seeks an M-dimensional point X which minimizes a given scalar function F(X). The code is a refinement of Powell's method of conjugate search directions. The user does not need to supply the partial derivatives of the function F(X). In fact, the function F(X) need not be smoothly differentiable.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Languages:

PRAXIS is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

COMPASS_SEARCH, a Python library which seeks the minimizer of a scalar function of several variables using compass search, a direct search algorithm that does not use derivatives.

Author:

Original FORTRAN77 version by Richard Brent. Python translation by John Burkardt.

Reference:

Source Code:

Examples and Tests:

You can go up one level to the Python source codes.


Last revised on 04 August 2016.