GCC Code Coverage Report

Directory: ./
File: tasks/luzan_e_double_sparse_matrix_mult_seq/common/include/common.hpp
Date: 2026-04-02 17:12:27
Exec Total Coverage
Lines: 67 104 64.4%
Functions: 6 9 66.7%
Branches: 65 128 50.8%
Line Branch Exec Source
1 #pragma once
2
3 #include <cmath>
4 #include <cstddef>
5 #include <fstream>
6 #include <stdexcept>
7 #include <string>
8 #include <tuple>
9 #include <vector>
10
11 #include "task/include/task.hpp"
12
13 namespace luzan_e_double_sparse_matrix_mult_seq {
14
15 const double kEPS = 1e-8;
16
17 class SparseMatrix {
18 std::vector<double> value_;
19 std::vector<unsigned> row_;
20 std::vector<unsigned> col_index_;
21
22 unsigned cols_;
23 unsigned rows_;
24
25 public:
26 48 SparseMatrix(unsigned rows, unsigned cols) : cols_(cols), rows_(rows) {
27 col_index_.clear();
28 row_.clear();
29 value_.clear();
30 }
31
32 ✗ SparseMatrix() : cols_(0), rows_(0) {
33 col_index_.clear();
34 row_.clear();
35 value_.clear();
36 }
37
38
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 96 SparseMatrix(const std::vector<double> &matrix, unsigned rows, unsigned cols) : cols_(cols), rows_(rows) {
39 col_index_.clear();
40 row_.clear();
41 value_.clear();
42
43
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 96 Sparse(matrix);
44 96 }
45
46 ✗ void GenLineMatrix(unsigned rows, unsigned cols) {
47 col_index_.clear();
48 row_.clear();
49 value_.clear();
50
51 ✗ rows_ = rows;
52 ✗ cols_ = cols;
53
54 ✗ col_index_.push_back(0);
55 ✗ for (unsigned j = 0; j < cols_; j++) {
56 ✗ for (unsigned i = 0; i < rows_; i++) {
57 ✗ if (i % 5 == 0) {
58 ✗ value_.push_back(1.0);
59 ✗ row_.push_back(i);
60 }
61 }
62 ✗ col_index_.push_back(value_.size());
63 }
64 ✗ }
65
66 ✗ void GenColsMatrix(unsigned rows, unsigned cols) {
67 col_index_.clear();
68 row_.clear();
69 value_.clear();
70
71 ✗ rows_ = rows;
72 ✗ cols_ = cols;
73 ✗ col_index_.push_back(0);
74
75 ✗ for (unsigned j = 0; j < cols_; j++) {
76 ✗ if (j % 5 == 0) {
77 ✗ for (unsigned i = 0; i < rows_; i++) {
78 ✗ value_.push_back(1.0);
79 ✗ row_.push_back(i);
80 }
81 }
82
83 ✗ col_index_.push_back(value_.size());
84 }
85 ✗ }
86
87 ✗ void GenPerfAns(unsigned n, unsigned m, unsigned k) {
88 col_index_.clear();
89 row_.clear();
90 value_.clear();
91 ✗ rows_ = n;
92 ✗ cols_ = m;
93
94 ✗ col_index_.push_back(0);
95 ✗ for (unsigned j = 0; j < m; j++) {
96 ✗ if (j % 5 == 0) // только чётные столбцы ненулевые
97 {
98 ✗ for (unsigned i = 0; i < n; i++) {
99 ✗ if (i % 5 == 0) // только чётные строки
100 {
101 ✗ value_.push_back(static_cast<double>(k));
102 ✗ row_.push_back(i);
103 }
104 }
105 }
106
107 ✗ col_index_.push_back(value_.size());
108 }
109 ✗ }
110
111 [[nodiscard]] unsigned GetCols() const {
112
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 48 return cols_;
113 }
114
115 [[nodiscard]] unsigned GetRows() const {
116
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 96 return rows_;
117 }
118
119 std::vector<double> GetVal() {
120 return value_;
121 }
122
123
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 48 bool operator==(const SparseMatrix &b) const {
124 bool tmp = false;
125
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 48 if (value_.size() == b.value_.size()) {
126 tmp = true;
127
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 288 for (size_t long_i = 0; long_i < value_.size(); long_i++) {
128
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 240 if (fabs(value_[long_i] - b.value_[long_i]) > kEPS) {
129 tmp = false;
130 break;
131 }
132 }
133 }
134
135
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 48 return tmp && (row_ == b.row_) && (col_index_ == b.col_index_) && (cols_ == b.cols_) && (rows_ == b.rows_);
136 }
137
138 double GetXy(unsigned x = 1, unsigned y = 2) {
139 for (unsigned verylongs = col_index_[y]; verylongs < col_index_[y + 1]; verylongs++) {
140 if (row_[verylongs] == x) {
141 return value_[verylongs];
142 }
143 }
144 return 0.0;
145 }
146 96 void Sparse(std::vector<double> matrix) {
147 96 col_index_.push_back(0);
148 bool flag = false;
149
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 376 for (unsigned j = 0; j < cols_; j++) {
150 280 col_index_.push_back(value_.size());
151
152
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 1272 for (unsigned i = 0; i < rows_; i++) {
153
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 992 if (fabs(matrix[(i * cols_) + j]) > kEPS) {
154
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 376 value_.push_back(matrix[(i * cols_) + j]);
155
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 376 row_.push_back(i);
156 flag = true;
157 }
158 }
159
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 280 if (flag) {
160 col_index_.pop_back();
161 176 col_index_.push_back(value_.size());
162 flag = false;
163 }
164 }
165 96 }
166
167 48 SparseMatrix operator*(const SparseMatrix &b) const {
168
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 48 SparseMatrix c(rows_, b.cols_);
169
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 48 c.col_index_.push_back(0);
170
171
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 176 for (unsigned b_col = 0; b_col < b.cols_; b_col++) {
172
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 128 std::vector<double> tmp_col(rows_, 0);
173 128 unsigned b_rows_start = b.col_index_[b_col];
174 128 unsigned b_rows_end = b.col_index_[b_col + 1];
175
176
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 288 for (unsigned b_pos = b_rows_start; b_pos < b_rows_end; b_pos++) {
177 160 double b_val = b.value_[b_pos];
178 160 unsigned b_row = b.row_[b_pos];
179
180 160 unsigned a_rows_start = col_index_[b_row];
181 160 unsigned a_rows_end = col_index_[b_row + 1];
182
183
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 536 for (unsigned a_pos = a_rows_start; a_pos < a_rows_end; a_pos++) {
184 376 double a_val = value_[a_pos];
185 376 unsigned a_row = row_[a_pos];
186 376 tmp_col[a_row] += a_val * b_val;
187 }
188 }
189
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 608 for (unsigned i = 0; i < rows_; i++) {
190
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 480 if (fabs(tmp_col[i]) > kEPS) {
191
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 240 c.value_.push_back(tmp_col[i]);
192
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 240 c.row_.push_back(i);
193 }
194 }
195
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 128 c.col_index_.push_back(c.value_.size());
196 }
197 48 return c;
198 ✗ }
199
200 48 void GetSparsedMatrixFromFile(std::ifstream &file) {
201
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 48 if (!file) {
202 ✗ throw std::runtime_error("Cannot open file with sparsed matrix");
203 }
204 48 unsigned n = 0;
205 48 file >> n >> rows_ >> cols_;
206
207 48 double tmp_val = 0;
208
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 288 for (unsigned i = 0; i < n; i++) {
209 file >> tmp_val;
210
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 240 value_.push_back(tmp_val);
211 }
212
213 48 unsigned tmp = 0;
214
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 288 for (unsigned i = 0; i < n; i++) {
215 file >> tmp;
216
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 240 row_.push_back(tmp);
217 }
218
219
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 224 for (unsigned i = 0; i < cols_ + 1; i++) {
220 file >> tmp;
221
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 176 col_index_.push_back(tmp);
222 }
223 48 }
224 };
225
226 96 inline SparseMatrix GetFromFile(std::ifstream &file) {
227 96 size_t r = 0;
228 96 size_t c = 0;
229 96 file >> r >> c;
230
231 96 std::vector<double> dense(r * c);
232
233
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 416 for (unsigned i = 0; i < r; i++) {
234
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 1312 for (unsigned j = 0; j < c; j++) {
235
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 992 file >> dense[(i * c) + j];
236 }
237 }
238
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 96 SparseMatrix a(dense, r, c);
239 96 return a;
240 };
241
242 using InType = std::tuple<SparseMatrix, SparseMatrix>;
243 using OutType = SparseMatrix;
244 using TestType = std::tuple<std::string, std::string>;
245 using BaseTask = ppc::task::Task<InType, OutType>;
246
247 } // namespace luzan_e_double_sparse_matrix_mult_seq
248