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Up-> cppad_swig library sparse sparse_rcv sparse_rcv_xam.pm

cppad_swig-> testing swig_xam.i library whats_new_2018

library-> module a_double vector a_fun sparse error xam.m4

sparse-> sparse_rc sparse_rcv jac_sparsity hes_sparsity sparse_jac sparse_hes

sparse_rcv-> sparse_rcv_xam.cpp sparse_rcv_xam.m sparse_rcv_xam.pm sparse_rcv_xam.py

sparse_rcv_xam.pm

Headings

package sparse_rcv_xam;
sub sparse_rcv_xam() {
     # check for standard perl programming conventions
     use strict;
     use warnings;
     #
     # load the Cppad Swig library
     use pm_cppad;
     #
     # initilaize return variable
     my $ok = 1;
     # ---------------------------------------------------------------------
     #
     # create sparsity pattern for n by n identity matrix
     my $pattern = new pm_cppad::sparse_rc();
     my $n = 5;
     $pattern->resize($n, $n, $n);
     for(my $k = 0; $k < $n; $k++) {
          $pattern->put($k, $k, $k);
     }
     #
     # create n by n sparse representation of identity matrix
     my $matrix = new pm_cppad::sparse_rcv($pattern);
     for(my $k = 0; $k < $n; $k++) {
          $matrix->put($k, 1.0);
     }
     #
     # row, column indices
     my $row = $matrix->row();
     my $col = $matrix->col();
     my $val = $matrix->val();
     #
     # check results
     for(my $k = 0; $k < $n; $k++) {
          $ok = $ok && $row->get($k) == $k;
          $ok = $ok && $col->get($k) == $k;
          $ok = $ok && $val->get($k) == 1.0;
     }
     #
     # For this case, row_major and col_major order are same as original order
     my $row_major = $matrix->row_major();
     my $col_major = $matrix->col_major();
     for(my $k = 0; $k < $n; $k++) {
          $ok = $ok && $row_major->get($k) == $k;
          $ok = $ok && $col_major->get($k) == $k;
     }
     #
     return( $ok );
}