#! /usr/bin/env python # def bernoulli_poly_values ( n_data ): #*****************************************************************************80 # ## BERNOULLI_POLY_VALUES returns some values of the Bernoulli polynomials. # # Discussion: # # In Mathematica, the function can be evaluated by: # # BernoulliB[n,x] # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 26 December 2014 # # Author: # # John Burkardt # # Reference: # # Milton Abramowitz and Irene Stegun, # Handbook of Mathematical Functions, # US Department of Commerce, 1964. # # Stephen Wolfram, # The Mathematica Book, # Fourth Edition, # Wolfram Media / Cambridge University Press, 1999. # # Parameters: # # Input/output, integer N_DATA. The user sets N_DATA to 0 before the # first call. On each call, the routine increments N_DATA by 1, and # returns the corresponding data; when there is no more data, the # output value of N_DATA will be 0 again. # # Output, integer N, the order of the Bernoulli polynomial. # # Output, real X, the argument of the Bernoulli polynomial. # # Output, real FX, the value of the Bernoulli polynomial. # import numpy as np n_max = 27 fx_vec = np.array ( ( \ 0.1000000000000000E+01, \ -0.3000000000000000E+00, \ 0.6666666666666667E-02, \ 0.4800000000000000E-01, \ -0.7733333333333333E-02, \ -0.2368000000000000E-01, \ 0.6913523809523810E-02, \ 0.2490880000000000E-01, \ -0.1014997333333333E-01, \ -0.4527820800000000E-01, \ 0.2332631815757576E-01, \ -0.3125000000000000E+00, \ -0.1142400000000000E+00, \ -0.0176800000000000E+00, \ 0.0156800000000000E+00, \ 0.0147400000000000E+00, \ 0.0000000000000000E+00, \ -0.1524000000000000E-01, \ -0.2368000000000000E-01, \ -0.2282000000000000E-01, \ -0.1376000000000000E-01, \ 0.0000000000000000E+01, \ 0.1376000000000000E-01, \ 0.2282000000000000E-01, \ 0.2368000000000000E-01, \ 0.1524000000000000E-01, \ 0.0000000000000000E+01 ) ) n_vec = np.array ( ( \ 0, \ 1, \ 2, \ 3, \ 4, \ 5, \ 6, \ 7, \ 8, \ 9, \ 10, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5, \ 5 )) x_vec = np.array ( ( \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ 0.2E+00, \ -0.5E+00, \ -0.4E+00, \ -0.3E+00, \ -0.2E+00, \ -0.1E+00, \ 0.0E+00, \ 0.1E+00, \ 0.2E+00, \ 0.3E+00, \ 0.4E+00, \ 0.5E+00, \ 0.6E+00, \ 0.7E+00, \ 0.8E+00, \ 0.9E+00, \ 1.0E+00 ) ) if ( n_data < 0 ): n_data = 0 if ( n_max <= n_data ): n_data = 0 n = 0 x = 0.0 fx = 0.0 else: n = n_vec[n_data] x = x_vec[n_data] fx = fx_vec[n_data] n_data = n_data + 1 return n_data, n, x, fx def bernoulli_poly_values_test ( ): #*****************************************************************************80 # ## BERNOULLI_POLY_VALUES_TEST demonstrates the use of BERNOULLI_POLY_VALUES. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 26 December 2014 # # Author: # # John Burkardt # print ( '' ) print ( 'BERNOULLI_POLY_VALUES_TEST:' ) print ( ' BERNOULLI_POLY_VALUES stores values of the Bernoulli polynomials.' ) print ( '' ) print ( ' N X FX' ) print ( '' ) n_data = 0 while ( True ): n_data, n, x, fx = bernoulli_poly_values ( n_data ) if ( n_data == 0 ): break print ( ' %6d %12f %24.16g' % ( n, x, fx ) ) # # Terminate. # print ( '' ) print ( 'BERNOULLI_POLY_VALUES_TEST:' ) print ( ' Normal end of execution.' ) return if ( __name__ == '__main__' ): from timestamp import timestamp timestamp ( ) bernoulli_poly_values_test ( ) timestamp ( )