1 package Math::GSL::Fit::Test;
2 use Math::GSL::Test qw/:all/;
3 use base q{Test::Class};
6 use Math::GSL::Fit qw/:all/;
7 use Math::GSL 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);
46 $x->[$i*$xstride] = $norris_x[$i];
47 $w->[$i*$wstride] = 1.0;
48 $y->[$i*$ystride] = $norris_y[$i];
50 my ($status, @results) = gsl_fit_linear($x, $xstride, $y, $ystride, 36);
51 # this way of writing the arrays works but it complains
52 # about a lot of unitialized entries even with the stride correctly set,
53 # is there any way to bypass this without having to initialize every element of the array like I do?
56 ok(is_similar_relative($results[0], -0.262323073774029, 10**-10));
57 ok(is_similar_relative($results[1], 1.00211681802045, 1e-10));
58 ok(is_similar_relative($results[2], 0.232818234301152**2.0, 1e-10));
59 ok(is_similar_relative($results[3], -7.74327536339570e-05, 1e-10));
60 ok(is_similar_relative($results[4], 0.429796848199937E-03**2, 1e-10));
61 ok(is_similar_relative($results[5], 26.6173985294224, 1e-10));
63 sub GSL_FIT_WLINEAR : Tests {
64 my @norris_x = (0.2, 337.4, 118.2, 884.6, 10.1, 226.5, 666.3, 996.3,
65 448.6, 777.0, 558.2, 0.4, 0.6, 775.5, 666.9, 338.0,
66 447.5, 11.6, 556.0, 228.1, 995.8, 887.6, 120.2, 0.3,
67 0.3, 556.8, 339.1, 887.2, 999.0, 779.0, 11.1, 118.3,
68 229.2, 669.1, 448.9, 0.5 ) ;
69 my @norris_y = ( 0.1, 338.8, 118.1, 888.0, 9.2, 228.1, 668.5, 998.5,
70 449.1, 778.9, 559.2, 0.3, 0.1, 778.1, 668.8, 339.3,
71 448.9, 10.8, 557.7, 228.3, 998.0, 888.8, 119.6, 0.3,
72 0.6, 557.6, 339.3, 888.0, 998.5, 778.9, 10.2, 117.6,
73 228.9, 668.4, 449.2, 0.2);
87 $x->[$i*$xstride] = $norris_x[$i];
88 $w->[$i*$wstride] = 1.0;
89 $y->[$i*$ystride] = $norris_y[$i];
92 my $expected_c0 = -0.262323073774029;
93 my $expected_c1 = 1.00211681802045;
94 my $expected_cov00 = 6.92384428759429e-02; # computed from octave
95 my $expected_cov01 = -9.89095016390515e-05; # computed from octave
96 my $expected_cov11 = 2.35960747164148e-07; # computed from octave
97 my $expected_sumsq = 26.6173985294224;
99 my @got = gsl_fit_wlinear ($x, $xstride, $w, $wstride, $y, $ystride, 36);
102 ok(is_similar_relative($got[1], $expected_c0, 1e-10), "norris gsl_fit_wlinear c0");
103 ok(is_similar_relative($got[2], $expected_c1, 1e-10), "norris gsl_fit_wlinear c1");
104 ok(is_similar_relative($got[3], $expected_cov00, 1e-10), "norris gsl_fit_wlinear cov00");
105 ok(is_similar_relative($got[4], $expected_cov01, 1e-10), "norris gsl_fit_wlinear cov01");
106 ok(is_similar_relative($got[5], $expected_cov11, 1e-10), "norris gsl_fit_wlinear cov11");
107 ok(is_similar_relative($got[6], $expected_sumsq, 1e-10), "norris gsl_fit_wlinear sumsq");
110 sub GSL_FIT_MUL : Tests {
111 my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
112 my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
127 $x->[$i*$xstride] = $noint1_x[$i];
128 $w->[$i*$wstride] = 1.0;
129 $y->[$i*$ystride] = $noint1_y[$i];
132 my $expected_c1 = 2.07438016528926;
133 my $expected_cov11 = (0.165289256198347*(10**-1))**2.0;
134 my $expected_sumsq = 127.272727272727;
136 my @got = gsl_fit_mul ($x, $xstride, $y, $ystride, 11);
139 ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_mul c1");
140 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_mul cov11");
141 ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_mul sumsq");
144 sub GSL_FIT_WMUL : Tests {
145 my @noint1_x = ( 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 );
146 my @noint1_y = ( 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140);
161 $x->[$i*$xstride] = $noint1_x[$i];
162 $w->[$i*$wstride] = 1.0;
163 $y->[$i*$ystride] = $noint1_y[$i];
166 my $expected_c1 = 2.07438016528926;
167 my $expected_cov11 = 2.14661371686165e-05; # computed from octave
168 my $expected_sumsq = 127.272727272727;
170 my @got = gsl_fit_wmul ($x, $xstride, $w, $wstride, $y, $ystride, 11);
173 ok(is_similar_relative($got[1], $expected_c1, 1e-10), "noint1 gsl_fit_wmul c1");
174 ok(is_similar_relative($got[2], $expected_cov11, 1e-10), "noint1 gsl_fit_wmul cov11");
175 ok(is_similar_relative($got[3], $expected_sumsq, 1e-10), "noint1 gsl_fit_wmul sumsq");
177 Test::Class->runtests;