1 /*
2  * Copyright 2017 Google Inc.
3  *
4  * Use of this source code is governed by a BSD-style license that can be
5  * found in the LICENSE file.
6  */
7 
8 #include "src/core/SkGaussFilter.h"
9 
10 #include <cmath>
11 #include <tuple>
12 #include <vector>
13 #include "tests/Test.h"
14 
15 // one part in a million
16 static constexpr double kEpsilon = 0.000001;
17 
careful_add(int n,double * gauss)18 static double careful_add(int n, double* gauss) {
19     // Sum smallest to largest to retain precision.
20     double sum = 0;
21     for (int i = n - 1; i >= 1; i--) {
22         sum += 2.0 * gauss[i];
23     }
24     sum += gauss[0];
25     return sum;
26 }
27 
DEF_TEST(SkGaussFilterCommon,r)28 DEF_TEST(SkGaussFilterCommon, r) {
29     using Test = std::tuple<double, std::vector<double>>;
30 
31     auto golden_check = [&](const Test& test) {
32         double sigma; std::vector<double> golden;
33         std::tie(sigma, golden) = test;
34         SkGaussFilter filter{sigma};
35         double result[SkGaussFilter::kGaussArrayMax];
36         int n = 0;
37         for (auto d : filter) {
38             result[n++] = d;
39         }
40         REPORTER_ASSERT(r, static_cast<size_t>(n) == golden.size());
41         double sum = careful_add(n, result);
42         REPORTER_ASSERT(r, sum == 1.0);
43         for (size_t i = 0; i < golden.size(); i++) {
44             REPORTER_ASSERT(r, std::abs(golden[i] - result[i]) < kEpsilon);
45         }
46     };
47 
48     // The following two sigmas account for about 85% of all sigmas used for masks.
49     // Golden values generated using Mathematica.
50     auto tests = {
51         // GaussianMatrix[{{Automatic}, {.788675}}]
52         Test{0.788675,   {0.593605, 0.176225, 0.0269721}},
53 
54         // GaussianMatrix[{{4}, {1.07735}}, Method -> "Bessel"]
55         Test{1.07735,  {0.429537, 0.214955, 0.059143, 0.0111337}},
56     };
57 
58     for (auto& test : tests) {
59         golden_check(test);
60     }
61 }
62 
DEF_TEST(SkGaussFilterSweep,r)63 DEF_TEST(SkGaussFilterSweep, r) {
64     // The double just before 2.0.
65     const double maxSigma = nextafter(2.0, 0.0);
66     auto check = [&](double sigma) {
67         SkGaussFilter filter{sigma};
68         double result[SkGaussFilter::kGaussArrayMax];
69         int n = 0;
70         for (auto d : filter) {
71             result[n++] = d;
72         }
73         REPORTER_ASSERT(r, n <= SkGaussFilter::kGaussArrayMax);
74         double sum = careful_add(n, result);
75         REPORTER_ASSERT(r, sum == 1.0);
76     };
77 
78     for (double sigma = 0.0; sigma < 2.0; sigma += 0.1) {
79         check(sigma);
80     }
81     check(maxSigma);
82 }
83