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69 lines
2.1 KiB
C++
69 lines
2.1 KiB
C++
//===- ReservoirSampler.cpp - Tests for the ReservoirSampler --------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/FuzzMutate/Random.h"
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#include "gtest/gtest.h"
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#include <random>
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using namespace llvm;
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TEST(ReservoirSamplerTest, OneItem) {
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std::mt19937 Rand;
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auto Sampler = makeSampler(Rand, 7, 1);
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ASSERT_FALSE(Sampler.isEmpty());
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ASSERT_EQ(7, Sampler.getSelection());
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}
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TEST(ReservoirSamplerTest, NoWeight) {
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std::mt19937 Rand;
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auto Sampler = makeSampler(Rand, 7, 0);
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ASSERT_TRUE(Sampler.isEmpty());
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}
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TEST(ReservoirSamplerTest, Uniform) {
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std::mt19937 Rand;
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// Run three chi-squared tests to check that the distribution is reasonably
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// uniform.
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std::vector<int> Items = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
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int Failures = 0;
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for (int Run = 0; Run < 3; ++Run) {
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std::vector<int> Counts(Items.size(), 0);
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// We need $np_s > 5$ at minimum, but we're better off going a couple of
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// orders of magnitude larger.
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int N = Items.size() * 5 * 100;
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for (int I = 0; I < N; ++I) {
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auto Sampler = makeSampler(Rand, Items);
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Counts[Sampler.getSelection()] += 1;
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}
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// Knuth. TAOCP Vol. 2, 3.3.1 (8):
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// $V = \frac{1}{n} \sum_{s=1}^{k} \left(\frac{Y_s^2}{p_s}\right) - n$
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double Ps = 1.0 / Items.size();
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double Sum = 0.0;
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for (int Ys : Counts)
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Sum += Ys * Ys / Ps;
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double V = (Sum / N) - N;
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assert(Items.size() == 10 && "Our chi-squared values assume 10 items");
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// Since we have 10 items, there are 9 degrees of freedom and the table of
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// chi-squared values is as follows:
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//
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// | p=1% | 5% | 25% | 50% | 75% | 95% | 99% |
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// v=9 | 2.088 | 3.325 | 5.899 | 8.343 | 11.39 | 16.92 | 21.67 |
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//
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// Check that we're in the likely range of results.
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//if (V < 2.088 || V > 21.67)
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if (V < 2.088 || V > 21.67)
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++Failures;
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}
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EXPECT_LT(Failures, 3) << "Non-uniform distribution?";
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}
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