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package Math::GSL::Fit::Test;
use base q{Test::Class};
use Test::More tests => 23;
use Test::Exception;
use Math::GSL qw/:all/;
use Math::GSL::Test qw/:all/;
use Math::GSL::Fit qw/:all/;
use Math::GSL::Errno qw/:all/;
use Data::Dumper;
use strict;
BEGIN { gsl_set_error_handler_off() }
sub make_fixture : Test(setup) {
}
sub teardown : Test(teardown) {
}
sub FIT_LINEAR_DIES : Tests {
dies_ok( sub { gsl_fit_linear(0,0,0,0) } );
}
sub GSL_FIT_LINEAR : Tests {
my @norris_x = (0.2, 337.4, 118.2, 884.6, 10.1, 226.5, 666.3, 996.3,
448.6, 777.0, 558.2, 0.4, 0.6, 775.5, 666.9, 338.0,
447.5, 11.6, 556.0, 228.1, 995.8, 887.6, 120.2, 0.3,
0.3, 556.8, 339.1, 887.2, 999.0, 779.0, 11.1, 118.3,
229.2, 669.1, 448.9, 0.5 ) ;
my @norris_y = ( 0.1, 338.8, 118.1, 888.0, 9.2, 228.1, 668.5, 998.5,
449.1, 778.9, 559.2, 0.3, 0.1, 778.1, 668.8, 339.3,
448.9, 10.8, 557.7, 228.3, 998.0, 888.8, 119.6, 0.3,
0.6, 557.6, 339.3, 888.0, 998.5, 778.9, 10.2, 117.6,
228.9, 668.4, 449.2, 0.2);
my ($xstride, $wstride, $ystride )= (2,3,5);
my ($x, $w, $y);
for my $i (0 .. 175)
{
$x->[$i] = $w->[$i] = $y->[$i] = 0;
}
for my $i (0 .. 35)
{
$x->[$i*$xstride] = $norris_x[$i];
$w->[$i*$wstride] = 1.0;
$y->[$i*$ystride] = $norris_y[$i];
}
my ($status, @results) = gsl_fit_linear($x, $xstride, $y, $ystride, 36);
# this way of writing the arrays works but it complains
# about a lot of unitialized entries even with the stride correctly set,
# is there any way to bypass this without having to initialize every element of the array like I do?
ok_status( $status);
ok(is_similar_relative($results[0], -0.262323073774029, 10**-10));
ok(is_similar_relative($results[1], 1.00211681802045, 1e-10));
ok(is_similar_relative($results[2], 0.232818234301152**2.0, 1e-10));
ok(is_similar_relative($results[3], -7.74327536339570e-05, 1e-10));
ok(is_similar_relative($results[4], 0.429796848199937E-03**2, 1e-10));
ok(is_similar_relative($results[5], 26.6173985294224, 1e-10));
}
sub GSL_FIT_WLINEAR : Tests {
my @norris_x = (0.2, 337.4, 118.2, 884.6, 10.1, 226.5, 666.3, 996.3,
448.6, 777.0, 558.2, 0.4, 0.6, 775.5, 666.9, 338.0,
447.5, 11.6, 556.0, 228.1, 995.8, 887.6, 120.2, 0.3,
0.3, 556.8, 339.1, 887.2, 999.0, 779.0, 11.1, 118.3,
229.2, 669.1, 448.9, 0.5 ) ;
my @norris_y = ( 0.1, 338.8, 118.1, 888.0, 9.2, 228.1, 668.5, 998.5,
449.1, 778.9, 559.2, 0.3, 0.1, 778.1, 668.8, 339.3,
448.9, 10.8, 557.7, 228.3, 998.0, 888.8, 119.6, 0.3,
0.6, 557.6, 339.3, 888.0, 998.5, 778.9, 10.2, 117.6,
228.9, 668.4, 449.2, 0.2);
my $xstride = 2;
my $wstride = 3;
my $ystride = 5;
my ($x, $w, $y);
for my $i (0 .. 175)
{
$x->[$i] = 0;
$w->[$i] = 0;
$y->[$i] = 0;
}
for my $i (0 .. 35)
{
$x->[$i*$xstride] = $norris_x[$i];
$w->[$i*$wstride] = 1.0;
$y->[$i*$ystride] = $norris_y[$i];
}
my $expected_c0 = -0.262323073774029;
my $expected_c1 = 1.00211681802045;
my $expected_cov00 = 6.92384428759429e-02; # computed from octave
my $expected_cov01 = -9.89095016390515e-05; # computed from octave
my $expected_cov11 = 2.35960747164148e-07; # computed from octave
my $expected_sumsq = 26.6173985294224;
my @got = gsl_fit_wlinear ($x, $xstride, $w, $wstride, $y, $ystride, 36);
ok_status($got[0]);
ok(is_similar_relative($got[1], $expected_c0, 1e-10), "norris gsl_fit_wlinear c0");
ok(is_similar_relative($got[2], $expected_c1, 1e-10), "norris gsl_fit_wlinear c1");
ok(is_similar_relative($got[3], $expected_cov00, 1e-10), "norris gsl_fit_wlinear cov00");
ok(is_similar_relative($got[4], $expected_cov01, 1e-10), "norris gsl_fit_wlinear cov01");
ok(is_similar_relative($got[5], $expected_cov11, 1e-10), "norris gsl_fit_wlinear cov11");
ok(is_similar_relative($got[6], $expected_sumsq, 1e-10), "norris gsl_fit_wlinear sumsq");
}
sub GSL_FIT_MUL : Tests {
my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
my $xstride = 2;
my $wstride = 3;
my $ystride = 5;
my ($x, $w, $y);
for my $i (0 .. 60)
{
$x->[$i] = 0;
$w->[$i] = 0;
$y->[$i] = 0;
}
for my $i (0 .. 10)
{
$x->[$i*$xstride] = $noint1_x[$i];
$w->[$i*$wstride] = 1.0;
$y->[$i*$ystride] = $noint1_y[$i];
}
my $expected_c1 = 2.07438016528926;
my $expected_cov11 = (0.165289256198347*(10**-1))**2.0;
my $expected_sumsq = 127.272727272727;
my @got = gsl_fit_mul ($x, $xstride, $y, $ystride, 11);
ok_status($got[0]);
ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_mul c1");
ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_mul cov11");
ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_mul sumsq");
}
sub GSL_FIT_WMUL : Tests {
my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
my $xstride = 2;
my $wstride = 3;
my $ystride = 5;
my ($x, $w, $y);
for my $i (0 .. 60)
{
$x->[$i] = 0;
$w->[$i] = 0;
$y->[$i] = 0;
}
for my $i (0 .. 10)
{
$x->[$i*$xstride] = $noint1_x[$i];
$w->[$i*$wstride] = 1.0;
$y->[$i*$ystride] = $noint1_y[$i];
}
my $expected_c1 = 2.07438016528926;
my $expected_cov11 = 2.14661371686165e-05; # computed from octave
my $expected_sumsq = 127.272727272727;
my @got = gsl_fit_wmul ($x, $xstride, $w, $wstride, $y, $ystride, 11);
ok_status($got[0]);
ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_wmul c1");
ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_wmul cov11");
ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_wmul sumsq");
}
Test::Class->runtests;
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