#! /usr/bin/env python # def tridiagonal_f ( x, n ): #*****************************************************************************80 # ## TRIDIAGONAL_F evaluates the tridiagonal function. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 03 August 2016 # # Author: # # John Burkardt # # Parameters: # # Input, real X(N), the evaluation point. # # Input, integer N, the number of variables. # # Output, real VALUE, the function value. # value = x[0] ** 2 + 2.0 * sum ( x[1:n] ** 2 ) for i in range ( 0, n - 1 ): value = value - 2.0 * x[i] * x[i+1] value = value - 2.0 * x[0] return value def tridiagonal_test ( ): #*****************************************************************************80 # ## TRIDIAGONAL_TEST calls PRAXIS for the Tridiagonal function. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 03 August 2016 # # Author: # # John Burkardt # import numpy as np import platform from praxis import praxis from r8vec_print import r8vec_print n = 4 print ( '' ) print ( 'TRIDIAGONAL_TEST' ) print ( ' Python version: %s' % ( platform.python_version ( ) ) ) print ( ' The Tridiagonal function.' ) t0 = 0.00001 h0 = 8.0 prin = 0 x = np.zeros ( n ) r8vec_print ( n, x, ' Initial point:' ) print ( ' Function value = %g' % ( tridiagonal_f ( x, n ) ) ) pr, x = praxis ( t0, h0, n, prin, x, tridiagonal_f ) r8vec_print ( n, x, ' Computed minimizer:' ) print ( ' Function value = %g' % ( tridiagonal_f ( x, n ) ) ) # # Terminate. # print ( '' ) print ( 'TRIDIAGONAL_TEST:' ) print ( ' Normal end of execution.' ) return if ( __name__ == '__main__' ): from timestamp import timestamp timestamp ( ) tridiagonal_test ( ) timestamp ( )