#! /usr/bin/env python3 # def wedge_exactness_test ( ): #*****************************************************************************80 # ## wedge_exactness_test() tests wedge_exactness(). # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 20 May 2023 # # Author: # # John Burkardt # import platform print ( '' ) print ( 'wedge_exactness_test():' ) print ( ' Python version: ' + platform.python_version ( ) ) print ( ' Test wedge_exactness()' ) wedge_exactness ( 'wedge_felippa_3x2', 4 ) # # Terminate. # print ( '' ) print ( 'wedge_exactness_test():' ) print ( ' Normal end of execution.' ) return def wedge_exactness ( quad_filename, degree_max ): #*****************************************************************************80 # ## wedge_exactness() determines exactness of unit wedge quadrature rules. # # Discussion: # # This program investigates the polynomial exactness of a quadrature # rule for the unit wedge. # # The interior of the unit wedge in 3D is defined by the constraints: # 0 <= X # 0 <= Y # X + Y <= 1 # -1 <= Z <= +1 # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 20 May 2023 # # Author: # # John Burkardt # # Input: # # character QUAD_FILENAME, the root name of the quadrature files. # # integer DEGREE_MAX, the maximum polynomial degree to check. # import numpy as np print ( '' ) print ( 'wedge_exactness():' ) print ( ' Investigate the polynomial exactness of' ) print ( ' a quadrature rule for the unit wedge.' ) # # Create the names of: # the quadrature X file # the quadrature W file # quad_x_filename = quad_filename + '_x.txt' quad_w_filename = quad_filename + '_w.txt' # # Summarize the input. # print ( '' ) print ( 'wedge_exactness(): User input:' ) print ( ' Quadrature rule X file = "' + quad_x_filename + '".' ) print ( ' Quadrature rule W file = "' + quad_w_filename + '".' ) print ( ' Maximum total degree to check = ', degree_max ) # # Read the X file. # x = np.loadtxt ( quad_x_filename ) order = x.shape[0] print ( ' Number of quadrature points = ', order ) # # Read the W file. # w = np.loadtxt ( quad_w_filename ) # # Explore the monomials. # print ( '' ) print ( ' Exponents Degree Error ' ) print ( '' ) dim_num = 3 expon = np.zeros ( dim_num, dtype = int ) for degree in range ( 0, degree_max + 1 ): more = False h = 0 t = 0 while ( True ): expon, more, h, t = comp_next ( degree, dim_num, expon, more, h, t ) v = monomial_value ( dim_num, order, expon, x ) quad = wedge01_volume ( ) * np.dot ( w, v ) exact = wedge01_integral ( expon ) quad_error = np.abs ( quad - exact ) print ( ' (%2d,%2d,%2d) %2d %24.16f' \ % ( expon[0], expon[1], expon[2], degree, quad_error ) ) if ( not more ): break print ( '' ) # # Terminate. # print ( '' ) print ( 'wedge_exactness():' ) print ( ' Normal end of execution.' ) return def comp_next ( n, k, a, more, h, t ): #*****************************************************************************80 # ## comp_next() computes the compositions of the integer N into K parts. # # Discussion: # # A composition of the integer N into K parts is an ordered sequence # of K nonnegative integers which sum to N. The compositions (1,2,1) # and (1,1,2) are considered to be distinct. # # The routine computes one composition on each call until there are no more. # For instance, one composition of 6 into 3 parts is # 3+2+1, another would be 6+0+0. # # On the first call to this routine, set MORE = FALSE. The routine # will compute the first element in the sequence of compositions, and # return it, as well as setting MORE = TRUE. If more compositions # are desired, call again, and again. Each time, the routine will # return with a new composition. # # However, when the LAST composition in the sequence is computed # and returned, the routine will reset MORE to FALSE, signaling that # the end of the sequence has been reached. # # This routine originally used a SAVE statement to maintain the # variables H and T. I have decided that it is safer # to pass these variables as arguments, even though the user should # never alter them. This allows this routine to safely shuffle # between several ongoing calculations. # # There are 28 compositions of 6 into three parts. This routine will # produce those compositions in the following order: # # I A # - --------- # 1 6 0 0 # 2 5 1 0 # 3 4 2 0 # 4 3 3 0 # 5 2 4 0 # 6 1 5 0 # 7 0 6 0 # 8 5 0 1 # 9 4 1 1 # 10 3 2 1 # 11 2 3 1 # 12 1 4 1 # 13 0 5 1 # 14 4 0 2 # 15 3 1 2 # 16 2 2 2 # 17 1 3 2 # 18 0 4 2 # 19 3 0 3 # 20 2 1 3 # 21 1 2 3 # 22 0 3 3 # 23 2 0 4 # 24 1 1 4 # 25 0 2 4 # 26 1 0 5 # 27 0 1 5 # 28 0 0 6 # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 20 May 2015 # # Author: # # John Burkardt. # # Reference: # # Albert Nijenhuis, Herbert Wilf, # Combinatorial Algorithms for Computers and Calculators, # Second Edition, # Academic Press, 1978, # ISBN: 0-12-519260-6, # LC: QA164.N54. # # Input: # # integer N, the integer whose compositions are desired. # # integer K, the number of parts in the composition. # # integer A(K), the previous composition. On the first call, # with MORE = FALSE, set A = []. Thereafter, A should be the # value of A output from the previous call. # # bool MORE. The input value of MORE on the first # call should be FALSE, which tells the program to initialize. # On subsequent calls, MORE should be TRUE, or simply the # output value of MORE from the previous call. # # integer H, T, two internal parameters needed for the # computation. The user may need to initialize these before the # very first call, but these initial values are not important. # The user should not alter these parameters once the computation # begins. # # Output: # # integer A(K), the next composition. # # bool MORE, will be TRUE unless the composition # that is being returned is the final one in the sequence. # # integer H, T, the updated values of the two internal # variables. # if ( not more ): t = n h = 0 a[0] = n for i in range ( 1, k ): a[i] = 0 else: if ( 1 < t ): h = 0 t = a[h] a[h] = 0 a[0] = t - 1 a[h+1] = a[h+1] + 1 h = h + 1 more = ( a[k-1] != n ) return a, more, h, t def monomial_value ( d, n, e, x ): #*****************************************************************************80 # ## monomial_value() evaluates a monomial. # # Discussion: # # This routine evaluates a monomial of the form # # product ( 1 <= i <= d ) x(i)^e(i) # # The combination 0.0^0, if encountered, is treated as 1.0. # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 01 October 2021 # # Author: # # John Burkardt # # Input: # # integer D, the spatial dimension. # # integer N, the number of evaluation points. # # integer E(D), the exponents. # # real X(N,D), the point coordinates. # # Output: # # real V(N), the monomial values. # import numpy as np v = np.ones ( n ) for j in range ( 0, d ): if ( 0 != e[j] ): for i in range ( 0, n ): if ( x[i,j] == 0.0 ): v[i] = 0.0 elif ( e[j] != 0 ): v[i] = v[i] * x[i,j] ** e[j] return v def wedge01_integral ( e ): #*****************************************************************************80 # ## wedge01_integral() returns the integral of a monomial in the unit wedge in 3D. # # Discussion: # # This routine returns the integral of # # product ( 1 <= I <= 3 ) X(I)^E(I) # # over the unit wedge. # # The integration region is: # # 0 <= X # 0 <= Y # X + Y <= 1 # -1 <= Z <= 1. # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 20 May 2023 # # Author: # # John Burkardt # # Reference: # # Arthur Stroud, # Approximate Calculation of Multiple Integrals, # Prentice Hall, 1971, # ISBN: 0130438936, # LC: QA311.S85. # # Input: # # integer E(3), the exponents. # # Output: # # real VALUE, the integral of the monomial. # value = 1.0 k = e[0] for i in range ( 1, e[1] + 1 ): k = k + 1 value = value * i / k k = k + 1 value = value / k k = k + 1 value = value / k # # Now account for integration in Z. # if ( e[2] == - 1 ): print ( '' ) print ( 'wedge01_integral(): Fatal error!' ) print ( ' E[2] = -1 is not a legal input.' ) raise Exception ( 'wedge01_integral(): Fatal error!' ) elif ( ( e[2] % 2 ) == 1 ): value = 0.0 else: value = value * 2.0 / ( e[2] + 1 ) return value def wedge01_volume ( ): #*****************************************************************************80 # ## wedge01_volume() returns the volume of the unit wedge in 3D. # # Discussion: # # The unit wedge is: # # 0 <= X # 0 <= Y # X + Y <= 1 # -1 <= Z <= 1. # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 20 May 2023 # # Author: # # John Burkardt # # Output: # # real VALUE, the volume of the unit wedge. # value = 1.0 return value def timestamp ( ): #*****************************************************************************80 # ## timestamp() prints the date as a timestamp. # # Licensing: # # This code is distributed under the MIT license. # # Modified: # # 21 August 2019 # # Author: # # John Burkardt # import time t = time.time ( ) print ( time.ctime ( t ) ) return if ( __name__ == '__main__' ): timestamp ( ) wedge_exactness_test ( ) timestamp ( )