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t/AI-Calibrate-1.t  view on Meta::CPAN

             ];

my $calibrated_expected =
  [
   [0.8, 1],
   [0.5, 0.75],
   [0.35, 0.666666666666667],
   [0.27, 0.5],
   [0.1, 0.333333333333333]
  ];

my $calibrated_got = calibrate( $points, 1 );

pass("ran_ok");

ok(deeply_approx($calibrated_got, $calibrated_expected),
   "pre-sorted calibration");

#  Shuffle the arrays a bit and try calibrating again

for (1 .. 10) {
    shuffle_array($points);
    my $calibrated_got = calibrate($points, 0);
    ok(deeply_approx($calibrated_got, $calibrated_expected),
       "unsorted cal $_");
}

#  Tweak the thresholds

for (1 .. 10) {
    my $delta = rand;
    my @delta_points;
    for my $point (@$points) {
        my($thresh, $class) = @$point;
        push(@delta_points, [ $thresh+$delta, $class]);
    }
    my @delta_expected;
    for my $point (@$calibrated_expected) {
        my($thresh, $class) = @$point;
        push(@delta_expected, [ $thresh+$delta, $class]);
    }
    my $delta_got = calibrate(\@delta_points, 0);
    ok(deeply_approx($delta_got, \@delta_expected), "unsorted cal $_");
}

my @test_estimates =
  ( [100, 1],
    [.9,    1 ],
    [.8,   1],
    [.7,  3/4 ],
    [.5,  3/4 ],
    [.45, 2/3 ],
    [.35, 2/3 ],
    [.3,  1/2 ],
    [.2,  1/3 ],
    [.02,   0 ],
    [.00001, 0]
);


print "Using this mapping:\n";
print_mapping($calibrated_got);
print;

for my $pair (@test_estimates) {
    my($score, $prob_expected) = @$pair;
    my $prob_got = score_prob($calibrated_got, $score);
    is($prob_got, $prob_expected, "score_prob test @$pair");
}