1 package Math::GSL::Fit::Test;
2 use base q{Test::Class};
3 use Test::More tests => 23;
5 use Math::GSL qw/:all/;
6 use Math::GSL::Test qw/:all/;
7 use Math::GSL::Fit qw/:all/;
8 use Math::GSL::Errno qw/:all/;
12 sub make_fixture : Test(setup) {
15 sub teardown : Test(teardown) {
18 sub FIT_LINEAR_DIES : Tests {
19 dies_ok( sub { gsl_fit_linear(0,0,0,0) } );
22 sub GSL_FIT_LINEAR : Tests {
23 my @norris_x = (0.2, 337.4, 118.2, 884.6, 10.1, 226.5, 666.3, 996.3,
24 448.6, 777.0, 558.2, 0.4, 0.6, 775.5, 666.9, 338.0,
25 447.5, 11.6, 556.0, 228.1, 995.8, 887.6, 120.2, 0.3,
26 0.3, 556.8, 339.1, 887.2, 999.0, 779.0, 11.1, 118.3,
27 229.2, 669.1, 448.9, 0.5 ) ;
28 my @norris_y = ( 0.1, 338.8, 118.1, 888.0, 9.2, 228.1, 668.5, 998.5,
29 449.1, 778.9, 559.2, 0.3, 0.1, 778.1, 668.8, 339.3,
30 448.9, 10.8, 557.7, 228.3, 998.0, 888.8, 119.6, 0.3,
31 0.6, 557.6, 339.3, 888.0, 998.5, 778.9, 10.2, 117.6,
32 228.9, 668.4, 449.2, 0.2);
34 my ($xstride, $wstride, $ystride )= (2,3,5);
38 $x->[$i] = $w->[$i] = $y->[$i] = 0;
43 $x->[$i*$xstride] = $norris_x[$i];
44 $w->[$i*$wstride] = 1.0;
45 $y->[$i*$ystride] = $norris_y[$i];
47 my ($status, @results) = gsl_fit_linear($x, $xstride, $y, $ystride, 36);
48 # this way of writing the arrays works but it complains
49 # about a lot of unitialized entries even with the stride correctly set,
50 # is there any way to bypass this without having to initialize every element of the array like I do?
53 ok(is_similar_relative($results[0], -0.262323073774029, 10**-10));
54 ok(is_similar_relative($results[1], 1.00211681802045, 1e-10));
55 ok(is_similar_relative($results[2], 0.232818234301152**2.0, 1e-10));
56 ok(is_similar_relative($results[3], -7.74327536339570e-05, 1e-10));
57 ok(is_similar_relative($results[4], 0.429796848199937E-03**2, 1e-10));
58 ok(is_similar_relative($results[5], 26.6173985294224, 1e-10));
60 sub GSL_FIT_WLINEAR : Tests {
61 my @norris_x = (0.2, 337.4, 118.2, 884.6, 10.1, 226.5, 666.3, 996.3,
62 448.6, 777.0, 558.2, 0.4, 0.6, 775.5, 666.9, 338.0,
63 447.5, 11.6, 556.0, 228.1, 995.8, 887.6, 120.2, 0.3,
64 0.3, 556.8, 339.1, 887.2, 999.0, 779.0, 11.1, 118.3,
65 229.2, 669.1, 448.9, 0.5 ) ;
66 my @norris_y = ( 0.1, 338.8, 118.1, 888.0, 9.2, 228.1, 668.5, 998.5,
67 449.1, 778.9, 559.2, 0.3, 0.1, 778.1, 668.8, 339.3,
68 448.9, 10.8, 557.7, 228.3, 998.0, 888.8, 119.6, 0.3,
69 0.6, 557.6, 339.3, 888.0, 998.5, 778.9, 10.2, 117.6,
70 228.9, 668.4, 449.2, 0.2);
84 $x->[$i*$xstride] = $norris_x[$i];
85 $w->[$i*$wstride] = 1.0;
86 $y->[$i*$ystride] = $norris_y[$i];
89 my $expected_c0 = -0.262323073774029;
90 my $expected_c1 = 1.00211681802045;
91 my $expected_cov00 = 6.92384428759429e-02; # computed from octave
92 my $expected_cov01 = -9.89095016390515e-05; # computed from octave
93 my $expected_cov11 = 2.35960747164148e-07; # computed from octave
94 my $expected_sumsq = 26.6173985294224;
96 my @got = gsl_fit_wlinear ($x, $xstride, $w, $wstride, $y, $ystride, 36);
99 ok(is_similar_relative($got[1], $expected_c0, 1e-10), "norris gsl_fit_wlinear c0");
100 ok(is_similar_relative($got[2], $expected_c1, 1e-10), "norris gsl_fit_wlinear c1");
101 ok(is_similar_relative($got[3], $expected_cov00, 1e-10), "norris gsl_fit_wlinear cov00");
102 ok(is_similar_relative($got[4], $expected_cov01, 1e-10), "norris gsl_fit_wlinear cov01");
103 ok(is_similar_relative($got[5], $expected_cov11, 1e-10), "norris gsl_fit_wlinear cov11");
104 ok(is_similar_relative($got[6], $expected_sumsq, 1e-10), "norris gsl_fit_wlinear sumsq");
107 sub GSL_FIT_MUL : Tests {
108 my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
109 my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
124 $x->[$i*$xstride] = $noint1_x[$i];
125 $w->[$i*$wstride] = 1.0;
126 $y->[$i*$ystride] = $noint1_y[$i];
129 my $expected_c1 = 2.07438016528926;
130 my $expected_cov11 = (0.165289256198347*(10**-1))**2.0;
131 my $expected_sumsq = 127.272727272727;
133 my @got = gsl_fit_mul ($x, $xstride, $y, $ystride, 11);
136 ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_mul c1");
137 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_mul cov11");
138 ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_mul sumsq");
141 sub GSL_FIT_WMUL : Tests {
142 my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
143 my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
158 $x->[$i*$xstride] = $noint1_x[$i];
159 $w->[$i*$wstride] = 1.0;
160 $y->[$i*$ystride] = $noint1_y[$i];
163 my $expected_c1 = 2.07438016528926;
164 my $expected_cov11 = 2.14661371686165e-05; # computed from octave
165 my $expected_sumsq = 127.272727272727;
167 my @got = gsl_fit_wmul ($x, $xstride, $w, $wstride, $y, $ystride, 11);
170 ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_wmul c1");
171 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_wmul cov11");
172 ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_wmul sumsq");
174 Test::Class->runtests;