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PDS/homework_1/gtest/tests.cpp

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/**
* \file tests.cpp
* \brief PDS homework_1 tests
*
* \author
* Christos Choutouridis AEM:8997
* <cchoutou@ece.auth.gr>
*/
#include <gtest/gtest.h>
#include "matrix.hpp"
#include "v0.hpp"
#include "v1.hpp"
#include "utils.hpp"
#include "config.h"
using matrix_t = mtx::Matrix<int>;
extern void loadMtx(MatrixDst& Corpus, MatrixDst& Query);
extern void storeMtx(MatrixIdx& Idx, MatrixDst& Dst);
// =====================================
// C1, Q1
mtx::Matrix<double> C1(10,2, {
0.8147, 0.1576,
0.9058, 0.9706,
0.1270, 0.9572,
0.9134, 0.4854,
0.6324, 0.8003,
0.0975, 0.1419,
0.2785, 0.4218,
0.5469, 0.9157,
0.9575, 0.7922,
0.9649, 0.9595
});
mtx::Matrix<double> Q1(5,2, {
0.6557, 0.7577,
0.0357, 0.7431,
0.8491, 0.3922,
0.9340, 0.6555,
0.6787, 0.1712
});
// =====================================
// C2, Q2
mtx::Matrix<double> C2(16,4, {
0.7060, 0.4456, 0.5060, 0.6160,
0.0318, 0.6463, 0.6991, 0.4733,
0.2769, 0.7094, 0.8909, 0.3517,
0.0462, 0.7547, 0.9593, 0.8308,
0.0971, 0.2760, 0.5472, 0.5853,
0.8235, 0.6797, 0.1386, 0.5497,
0.6948, 0.6551, 0.1493, 0.9172,
0.3171, 0.1626, 0.2575, 0.2858,
0.9502, 0.1190, 0.8407, 0.7572,
0.0344, 0.4984, 0.2543, 0.7537,
0.4387, 0.9597, 0.8143, 0.3804,
0.3816, 0.3404, 0.2435, 0.5678,
0.7655, 0.5853, 0.9293, 0.0759,
0.7952, 0.2238, 0.3500, 0.0540,
0.1869, 0.7513, 0.1966, 0.5308,
0.4898, 0.2551, 0.2511, 0.7792
});
mtx::Matrix<double> Q2(8,4, {
0.9340, 0.3112, 0.4505, 0.0782,
0.1299, 0.5285, 0.0838, 0.4427,
0.5688, 0.1656, 0.2290, 0.1067,
0.4694, 0.6020, 0.9133, 0.9619,
0.0119, 0.2630, 0.1524, 0.0046,
0.3371, 0.6541, 0.8258, 0.7749,
0.1622, 0.6892, 0.5383, 0.8173,
0.7943, 0.7482, 0.9961, 0.8687
});
/*
* ==========================================
* pdist2
*/
TEST(Tv0_UT, pdist2_test1) {
mtx::Matrix<double> D1_exp(10, 5, {
0.6208, 0.9745, 0.2371, 0.5120, 0.1367,
0.3284, 0.8993, 0.5811, 0.3164, 0.8310,
0.5651, 0.2327, 0.9169, 0.8616, 0.9603,
0.3749, 0.9147, 0.1132, 0.1713, 0.3921,
0.0485, 0.5994, 0.4621, 0.3346, 0.6308,
0.8312, 0.6044, 0.7922, 0.9815, 0.5819,
0.5052, 0.4028, 0.5714, 0.6959, 0.4722,
0.1919, 0.5395, 0.6045, 0.4665, 0.7561,
0.3037, 0.9231, 0.4144, 0.1387, 0.6807,
0.3692, 0.9540, 0.5790, 0.3056, 0.8386
});
mtx::Matrix<double> D (10,5);
v0::pdist2(C1, Q1, D);
for (size_t i = 0 ; i< D.rows() ; ++i)
for (size_t j = 0 ; j<D.columns() ; ++j) {
EXPECT_EQ (D1_exp.get(i ,j) + 0.01 > D(i, j), true);
EXPECT_EQ (D1_exp.get(i ,j) - 0.01 < D(i, j), true);
}
}
TEST(Tv0_UT, pdist2_test2) {
mtx::Matrix<double> D2_exp(16, 8, {
0.6020, 0.7396, 0.6583, 0.6050, 1.0070, 0.5542, 0.6298, 0.6352,
1.0696, 0.6348, 0.9353, 0.6914, 0.8160, 0.4475, 0.4037, 0.9145,
0.9268, 0.8450, 0.9376, 0.6492, 0.9671, 0.4360, 0.5956, 0.7400,
1.3455, 0.9876, 1.2953, 0.4709, 1.2557, 0.3402, 0.4417, 0.7500,
0.9839, 0.5476, 0.7517, 0.7216, 0.7074, 0.5605, 0.4784, 0.9954,
0.6839, 0.7200, 0.7305, 0.9495, 1.0628, 0.8718, 0.8178, 0.9179,
0.9850, 0.7514, 0.9585, 0.7996, 1.2054, 0.7784, 0.6680, 0.8591,
0.6950, 0.4730, 0.3103, 1.0504, 0.4397, 0.8967, 0.8140, 1.2066,
0.8065, 1.2298, 0.9722, 0.7153, 1.3933, 0.8141, 1.0204, 0.6758,
1.1572, 0.3686, 0.9031, 0.8232, 0.7921, 0.6656, 0.3708, 1.0970,
0.9432, 0.9049, 1.0320, 0.6905, 1.1167, 0.5094, 0.6455, 0.6653,
0.7672, 0.3740, 0.5277, 0.8247, 0.6842, 0.6945, 0.5648, 0.9968,
0.5768, 1.1210, 0.8403, 0.9345, 1.1316, 0.8292, 1.0380, 0.8127,
0.1939, 0.8703, 0.2684, 1.1794, 0.8103, 1.0683, 1.1115, 1.1646,
1.0106, 0.2708, 0.8184, 0.8954, 0.7402, 0.6982, 0.4509, 1.0594,
0.8554, 0.5878, 0.6834, 0.7699, 0.9155, 0.7161, 0.6162, 0.9481
});
mtx::Matrix<double> D (16,8);
v0::pdist2(C2, Q2, D);
for (size_t i = 0 ; i< D.rows() ; ++i)
for (size_t j = 0 ; j<D.columns() ; ++j) {
EXPECT_EQ (D2_exp.get(i ,j) + 0.01 > D(i, j), true);
EXPECT_EQ (D2_exp.get(i ,j) - 0.01 < D(i, j), true);
}
}
TEST(Tv0_UT, pdist2_test3) {
mtx::Matrix<double> D2_exp(16, 16, {
0, 0.7433, 0.6868, 0.8846, 0.6342, 0.4561, 0.5118, 0.6341, 0.5461, 0.7322, 0.6974, 0.4330, 0.7028, 0.6303, 0.6826, 0.4179,
0.7433, 0, 0.3400, 0.4555, 0.4207, 0.9736, 0.9690, 0.7386, 1.1055, 0.5462, 0.5345, 0.6576, 0.8677, 1.0291, 0.5393, 0.8106,
0.6868, 0.3400, 0, 0.5380, 0.6268, 0.9512, 1.0234, 0.8403, 0.9843, 0.8187, 0.3091, 0.7829, 0.5759, 0.9411, 0.7239, 0.9186,
0.8846, 0.4555, 0.5380, 0, 0.6796, 1.1672, 1.0460, 1.1016, 1.1139, 0.7542, 0.6480, 0.9304, 1.0568, 1.3482, 0.8316, 0.9750,
0.6342, 0.4207, 0.6268, 0.6796, 0, 0.9267, 0.8772, 0.4847, 0.9317, 0.4093, 0.8351, 0.4215, 0.9736, 0.9007, 0.5999, 0.5291,
0.4561, 0.9736, 0.9512, 1.1672, 0.9267, 0, 0.3903, 0.7795, 0.9308, 0.8429, 0.8436, 0.5672, 0.9284, 0.7064, 0.6435, 0.5975,
0.5118, 0.9690, 1.0234, 1.0460, 0.8772, 0.3903, 0, 0.8920, 0.9253, 0.7060, 0.9427, 0.5728, 1.1515, 0.9907, 0.6471, 0.4811,
0.6341, 0.7386, 0.8403, 1.1016, 0.4847, 0.7795, 0.8920, 0, 0.9824, 0.6416, 0.9844, 0.3398, 0.9355, 0.5428, 0.6536, 0.5309,
0.5461, 1.1055, 0.9843, 1.1139, 0.9317, 0.9308, 0.9253, 0.9824, 0, 1.1517, 1.0541, 0.8746, 0.8506, 0.8777, 1.2036, 0.7607,
0.7322, 0.5462, 0.8187, 0.7542, 0.4093, 0.8429, 0.7060, 0.6416, 1.1517, 0, 0.9106, 0.4245, 1.2071, 1.0738, 0.3745, 0.5170,
0.6974, 0.5345, 0.3091, 0.6480, 0.8351, 0.8436, 0.9427, 0.9844, 1.0541, 0.9106, 0, 0.8647, 0.5941, 0.9954, 0.7148, 0.9876,
0.4330, 0.6576, 0.7829, 0.9304, 0.4215, 0.5672, 0.5728, 0.3398, 0.8746, 0.4245, 0.8647, 0, 0.9590, 0.6782, 0.4586, 0.2525,
0.7028, 0.8677, 0.5759, 1.0568, 0.9736, 0.9284, 1.1515, 0.9355, 0.8506, 1.2071, 0.5941, 0.9590, 0, 0.6838, 1.0517, 1.0675,
0.6303, 1.0291, 0.9411, 1.3482, 0.9007, 0.7064, 0.9907, 0.5428, 0.8777, 1.0738, 0.9954, 0.6782, 0.6838, 0, 0.9482, 0.7937,
0.6826, 0.5393, 0.7239, 0.8316, 0.5999, 0.6435, 0.6471, 0.6536, 1.2036, 0.3745, 0.7148, 0.4586, 1.0517, 0.9482, 0, 0.6345,
0.4179, 0.8106, 0.9186, 0.9750, 0.5291, 0.5975, 0.4811, 0.5309, 0.7607, 0.5170, 0.9876, 0.2525, 1.0675, 0.7937, 0.6345, 0
});
mtx::Matrix<double> D (16,16);
v0::pdist2(C2, C2, D);
for (size_t i = 0 ; i< D.rows() ; ++i)
for (size_t j = 0 ; j<D.columns() ; ++j) {
EXPECT_EQ (D2_exp.get(i ,j) + 0.01 > D(i, j), true);
EXPECT_EQ (D2_exp.get(i ,j) - 0.01 < D(i, j), true);
}
}
/*
* ==========================================
* v0::knn
*/
TEST(Tv0_UT, knn_v0_test1) {
size_t k = 3;
mtx::Matrix<uint32_t> Idx_exp(5, k, {
5, 8, 9,
3, 7, 8,
4, 1, 9,
9, 4, 10,
1, 4, 7
});
mtx::Matrix<double> Dst_exp(5, k, {
0.0485, 0.1919, 0.3037,
0.2327, 0.4028, 0.5395,
0.1132, 0.2371, 0.4144,
0.1387, 0.1713, 0.3056,
0.1367, 0.3921, 0.4722
});
mtx::Matrix<uint32_t> Idx(5, k);
mtx::Matrix<double> Dst(5, k);
v0::knnsearch(C1, Q1, 0, k, 0, Idx, Dst);
for (size_t i = 0 ; i< Idx.rows() ; ++i)
for (size_t j = 0 ; j<Idx.columns() ; ++j) {
EXPECT_EQ (Idx_exp(i ,j) == Idx(i, j) + 1, true); // matlab starts from 1
EXPECT_EQ (Dst_exp.get(i ,j) + 0.01 > Dst(i, j), true);
EXPECT_EQ (Dst_exp.get(i ,j) - 0.01 < Dst(i, j), true);
}
}
TEST(Tv0_UT, knn_v0_test2) {
size_t k = 3;
mtx::Matrix<uint32_t> Idx_exp(8, k, {
14, 13, 1,
15, 10, 12,
14, 8, 12,
4, 1, 3,
8, 12, 5,
4, 3, 2,
10, 2, 4,
1, 11, 9
});
mtx::Matrix<double> Dst_exp(8, k, {
0.1939, 0.5768, 0.6020,
0.2708, 0.3686, 0.3740,
0.2684, 0.3103, 0.5277,
0.4709, 0.6050, 0.6492,
0.4397, 0.6842, 0.7074,
0.3402, 0.4360, 0.4475,
0.3708, 0.4037, 0.4417,
0.6352, 0.6653, 0.6758
});
mtx::Matrix<uint32_t> Idx(8, k);
mtx::Matrix<double> Dst(8, k);
v0::knnsearch(C2, Q2, 0, k, 0, Idx, Dst);
for (size_t i = 0 ; i< Idx.rows() ; ++i)
for (size_t j = 0 ; j<Idx.columns() ; ++j) {
EXPECT_EQ (Idx_exp(i ,j) == Idx(i, j) + 1, true); // matlab starts from 1
EXPECT_EQ (Dst_exp.get(i ,j) + 0.01 > Dst(i, j), true);
EXPECT_EQ (Dst_exp.get(i ,j) - 0.01 < Dst(i, j), true);
}
}
/*
* ==========================================
* v1::knn
*/
TEST(Tv1_UT, knn_v1_1slice) {
size_t k = 3;
mtx::Matrix<uint32_t> Idx_exp(8, k, {
14, 13, 1,
15, 10, 12,
14, 8, 12,
4, 1, 3,
8, 12, 5,
4, 3, 2,
10, 2, 4,
1, 11, 9
});
mtx::Matrix<double> Dst_exp(8, k, {
0.1939, 0.5768, 0.6020,
0.2708, 0.3686, 0.3740,
0.2684, 0.3103, 0.5277,
0.4709, 0.6050, 0.6492,
0.4397, 0.6842, 0.7074,
0.3402, 0.4360, 0.4475,
0.3708, 0.4037, 0.4417,
0.6352, 0.6653, 0.6758
});
mtx::Matrix<uint32_t> Idx(8, k);
mtx::Matrix<double> Dst(8, k);
v1::knnsearch(C2, Q2, 1, k, k, Idx, Dst);
for (size_t i = 0 ; i< Idx.rows() ; ++i)
for (size_t j = 0 ; j<Idx.columns() ; ++j) {
EXPECT_EQ (Idx_exp(i ,j) == Idx(i, j) + 1, true); // matlab starts from 1
EXPECT_EQ (Dst_exp.get(i ,j) + 0.01 > Dst(i, j), true);
EXPECT_EQ (Dst_exp.get(i ,j) - 0.01 < Dst(i, j), true);
}
}
TEST(Tv1_UT, knn_v1_2slice) {
size_t k = 3;
mtx::Matrix<uint32_t> Idx_exp(8, k, {
14, 13, 1,
15, 10, 12,
14, 8, 12,
4, 1, 3,
8, 12, 5,
4, 3, 2,
10, 2, 4,
1, 11, 9
});
mtx::Matrix<double> Dst_exp(8, k, {
0.1939, 0.5768, 0.6020,
0.2708, 0.3686, 0.3740,
0.2684, 0.3103, 0.5277,
0.4709, 0.6050, 0.6492,
0.4397, 0.6842, 0.7074,
0.3402, 0.4360, 0.4475,
0.3708, 0.4037, 0.4417,
0.6352, 0.6653, 0.6758
});
mtx::Matrix<uint32_t> Idx(8, k);
mtx::Matrix<double> Dst(8, k);
v1::knnsearch(C2, Q2, 2, k, k, Idx, Dst);
for (size_t i = 0 ; i< Idx.rows() ; ++i)
for (size_t j = 0 ; j<Idx.columns() ; ++j) {
EXPECT_EQ (Idx_exp(i ,j) == Idx(i, j) + 1, true); // matlab starts from 1
EXPECT_EQ (Dst_exp.get(i ,j) + 0.01 > Dst(i, j), true);
EXPECT_EQ (Dst_exp.get(i ,j) - 0.01 < Dst(i, j), true);
}
}
// all-to-all
TEST(Tv1_UT, knn_v1_4slice) {
size_t k = 3;
mtx::Matrix<uint32_t> Idx_exp(16, k, {
1, 16, 12,
2, 3, 5,
3, 11, 2,
4, 2, 3,
5, 10, 2,
6, 7, 1,
7, 6, 16,
8, 12, 5,
9, 1, 16,
10, 15, 5,
11, 3, 2,
12, 16, 8,
13, 3, 11,
14, 8, 1,
15, 10, 12,
16, 12, 1
});
mtx::Matrix<double> Dst_exp(16, k, {
0, 0.4179, 0.4331,
0, 0.3401, 0.4207,
0, 0.3092, 0.3401,
0, 0.4555, 0.5381,
0, 0.4093, 0.4207,
0, 0.3903, 0.4560,
0, 0.3903, 0.4811,
0, 0.3398, 0.4846,
0, 0.5461, 0.7607,
0, 0.3745, 0.4093,
0, 0.3092, 0.5345,
0, 0.2524, 0.3398,
0, 0.5759, 0.5941,
0, 0.5428, 0.6304,
0, 0.3745, 0.4586,
0, 0.2524, 0.4179
});
mtx::Matrix<uint32_t> Idx(16, k);
mtx::Matrix<double> Dst(16, k);
v1::knnsearch(C2, C2, 4, k, k, Idx, Dst);
for (size_t i = 0 ; i< Idx.rows() ; ++i)
for (size_t j = 0 ; j<Idx.columns() ; ++j) {
EXPECT_EQ (Idx_exp(i ,j) == Idx(i, j) + 1, true); // matlab starts from 1
EXPECT_EQ (Dst_exp.get(i ,j) + 0.01 > Dst(i, j), true);
EXPECT_EQ (Dst_exp.get(i ,j) - 0.01 < Dst(i, j), true);
}
}
/*
* ============== Live hdf5 tests ===============
*
* In order to run these test we need the followin hdf5 files in ./mtx directory:
*
* - fasion-mnist-784-euclidean.hdf5
* - mnist-784-euclidean.hdf5
* - sift-128-euclidean.hdf5
* - gist-960-euclidean.hdf5
*
*/
TEST(Tlive_UT, knn_v0_sift_test) {
// Instantiate matrixes
MatrixDst Corpus;
MatrixDst Query;
MatrixIdx Idx;
MatrixDst Dst;
// setup environment
session.corpusMtxFile = "mtx/sift-128-euclidean.hdf5";
session.corpusDataSet = "/test";
session.queryMtx = false;
session.k = 100;
size_t m = session.k;
session.timing = true;
session.outMtxFile = "test/knn_v0.hdf5";
loadMtx(Corpus, Query);
// Prepare output memory (There is no Query, so from Corpus
Idx.resize(Corpus.rows(), session.k);
Dst.resize(Corpus.rows(), session.k);
v0::knnsearch(Corpus, Corpus, 0, session.k, m, Idx, Dst);
storeMtx(Idx, Dst);
EXPECT_EQ(true, true);
}
TEST(Tlive_UT, knn_v1_sift_test_1slice) {
// Instantiate matrixes
MatrixDst Corpus;
MatrixDst Query;
MatrixIdx Idx;
MatrixDst Dst;
// setup environment
session.corpusMtxFile = "mtx/sift-128-euclidean.hdf5";
session.corpusDataSet = "/test";
session.queryMtx = false;
session.k = 100;
size_t m = session.k;
session.timing = true;
session.outMtxFile = "test/knn_v1ser.hdf5";
loadMtx(Corpus, Query);
// Prepare output memory (There is no Query, so from Corpus
Idx.resize(Corpus.rows(), session.k);
Dst.resize(Corpus.rows(), session.k);
v1::knnsearch(Corpus, Corpus, 0, session.k, m, Idx, Dst);
storeMtx(Idx, Dst);
EXPECT_EQ(true, true);
}
TEST(Tlive_UT, knn_v1_sift_test_2slice) {
// Instantiate matrixes
MatrixDst Corpus;
MatrixDst Query;
MatrixIdx Idx;
MatrixDst Dst;
// setup environment
session.corpusMtxFile = "mtx/sift-128-euclidean.hdf5";
session.corpusDataSet = "/test";
session.queryMtx = false;
session.k = 100;
size_t m = session.k;
session.timing = true;
session.outMtxFile = "test/knn_v1ser.hdf5";
loadMtx(Corpus, Query);
// Prepare output memory (There is no Query, so from Corpus
Idx.resize(Corpus.rows(), session.k);
Dst.resize(Corpus.rows(), session.k);
v1::knnsearch(Corpus, Corpus, 2, session.k, m, Idx, Dst);
storeMtx(Idx, Dst);
EXPECT_EQ(true, true);
}
TEST(Tlive_UT, knn_v1_sift_test_4slice) {
// Instantiate matrixes
MatrixDst Corpus;
MatrixDst Query;
MatrixIdx Idx;
MatrixDst Dst;
// setup environment
session.corpusMtxFile = "mtx/sift-128-euclidean.hdf5";
session.corpusDataSet = "/test";
session.queryMtx = false;
session.k = 100;
size_t m = session.k;
session.timing = true;
session.outMtxFile = "test/knn_v1ser.hdf5";
loadMtx(Corpus, Query);
// Prepare output memory (There is no Query, so from Corpus
Idx.resize(Corpus.rows(), session.k);
Dst.resize(Corpus.rows(), session.k);
v1::knnsearch(Corpus, Corpus, 4, session.k, m, Idx, Dst);
storeMtx(Idx, Dst);
EXPECT_EQ(true, true);
}
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