Revert "Gauss filter calculation"

This reverts commit 53ec7dc7cb523f220a9f5cd713b241c706779c81.

Reason for revert: Segv on very specific machines.

Original change's description:
> Gauss filter calculation
> 
> Change-Id: I921ef815d4f788c312aa729f353b6ea154140555
> Reviewed-on: https://skia-review.googlesource.com/67723
> Commit-Queue: Herb Derby <herb@google.com>
> Reviewed-by: Robert Phillips <robertphillips@google.com>

TBR=herb@google.com,robertphillips@google.com

Change-Id: I15164809d081dee0076e815b40fbfdbc6374cfba
No-Presubmit: true
No-Tree-Checks: true
No-Try: true
Reviewed-on: https://skia-review.googlesource.com/69641
Reviewed-by: Herb Derby <herb@google.com>
Commit-Queue: Herb Derby <herb@google.com>

1 files changed, 0 insertions, 88 deletions

diff --git a/tests/SkGaussFilterTest.cpp b/tests/SkGaussFilterTest.cpp
deleted file mode 100644
index 958e811ce5..0000000000
--- a/tests/SkGaussFilterTest.cpp
+++ /dev/null
@@ -1,88 +0,0 @@
-/*
- * Copyright 2017 Google Inc.
- *
- * Use of this source code is governed by a BSD-style license that can be
- * found in the LICENSE file.
- */
-
-#include "SkGaussFilter.h"
-
-#include <cmath>
-#include <tuple>
-#include <vector>
-#include "Test.h"
-
-// one part in a million
-static constexpr double kEpsilon = 0.000001;
-
-static double careful_add(int n, double* gauss) {
-    // Sum smallest to largest to retain precision.
-    double sum = 0;
-    for (int i = n - 1; i >= 1; i--) {
-        sum += 2.0 * gauss[i];
-    }
-    sum += gauss[0];
-    return sum;
-}
-
-DEF_TEST(SkGaussFilterCommon, r) {
-    using Test = std::tuple<double, SkGaussFilter::Type, std::vector<double>>;
-
-    auto golden_check = [&](const Test& test) {
-        double sigma; SkGaussFilter::Type type; std::vector<double> golden;
-        std::tie(sigma, type, golden) = test;
-        SkGaussFilter filter{sigma, type};
-        double result[5];
-        size_t n = filter.filterDouble(result);
-        REPORTER_ASSERT(r, n == golden.size());
-        double sum = careful_add(n, result);
-        REPORTER_ASSERT(r, sum == 1.0);
-        for (size_t i = 0; i < golden.size(); i++) {
-            REPORTER_ASSERT(r, std::abs(golden[i] - result[i]) < kEpsilon);
-        }
-    };
-
-    // The following two sigmas account for about 85% of all sigmas used for masks.
-    // Golden values generated using Mathematica.
-    auto tests = {
-        // 0.788675 - most common mask sigma.
-        // GaussianMatrix[{{Automatic}, {.788675}}, Method -> "Gaussian"]
-        Test{0.788675, SkGaussFilter::Type::Gaussian, {0.506205, 0.226579, 0.0203189}},
-
-        // GaussianMatrix[{{Automatic}, {.788675}}]
-        Test{0.788675, SkGaussFilter::Type::Bessel,   {0.593605, 0.176225, 0.0269721}},
-
-        // 1.07735 - second most common mask sigma.
-        // GaussianMatrix[{{Automatic}, {1.07735}}, Method -> "Gaussian"]
-        Test{1.07735, SkGaussFilter::Type::Gaussian,  {0.376362, 0.244636, 0.0671835}},
-
-        // GaussianMatrix[{{4}, {1.07735}}, Method -> "Bessel"]
-        Test{1.07735, SkGaussFilter::Type::Bessel,    {0.429537, 0.214955, 0.059143, 0.0111337}},
-    };
-
-    for (auto& test : tests) {
-        golden_check(test);
-    }
-}
-
-DEF_TEST(SkGaussFilterSweep, r) {
-    // The double just before 2.0.
-    const double maxSigma = nextafter(2.0, 0.0);
-    for (auto type : {SkGaussFilter::Type::Gaussian, SkGaussFilter::Type::Bessel}) {
-
-        auto check = [&](double sigma) {
-            SkGaussFilter filter{sigma, type};
-            double result[5];
-            int n = filter.filterDouble(result);
-            REPORTER_ASSERT(r, n <= 5);
-            double sum = careful_add(n, result);
-            REPORTER_ASSERT(r, sum == 1.0);
-        };
-
-        for (double sigma = 0.0; sigma < 2.0; sigma += 0.1) {
-            check(sigma);
-        }
-
-        check(maxSigma);
-    }
-}