GCC Code Coverage Report

Directory: ./
File: tasks/luzan_e_double_sparse_matrix_mult/common/include/common.hpp
Date: 2026-06-04 20:25:32
Exec Total Coverage
Lines: 70 106 66.0%
Functions: 6 9 66.7%
Branches: 69 127 54.3%
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 {
14
15 const double kEPS = 1e-8;
16
17 struct 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
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 144 SparseMatrix(unsigned rows_out, unsigned cols_out) : cols(cols_out), rows(rows_out) {
26 col_index.clear();
27 row.clear();
28 value.clear();
29 }
30
31
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 24 SparseMatrix() : cols(0), rows(0) {
32 col_index.clear();
33 row.clear();
34 value.clear();
35 12 }
36
37 312 SparseMatrix(const std::vector<double> &matrix, unsigned rows_out, unsigned cols_out)
38
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 312 : cols(cols_out), rows(rows_out) {
39 col_index.clear();
40 row.clear();
41 value.clear();
42
43
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 312 Sparse(matrix);
44 312 }
45
46 ✗ void GenLineMatrix(unsigned rows_out, unsigned cols_out) {
47 col_index.clear();
48 row.clear();
49 value.clear();
50
51 ✗ rows = rows_out;
52 ✗ cols = cols_out;
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_out, unsigned cols_out) {
67 col_index.clear();
68 row.clear();
69 value.clear();
70
71 ✗ rows = rows_out;
72 ✗ cols = cols_out;
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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 150 return cols;
113 }
114
115 [[nodiscard]] unsigned GetRows() const {
116
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 300 return rows;
117 }
118
119 [[nodiscard]] std::vector<double> GetVal() const {
120 return value;
121 }
122
123
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 150 bool operator==(const SparseMatrix &b) const {
124 bool tmp = false;
125
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 150 if (value.size() == b.value.size()) {
126 tmp = true;
127
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 900 for (size_t long_i = 0; long_i < value.size(); long_i++) {
128
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 750 if (fabs(value[long_i] - b.value[long_i]) > kEPS) {
129 tmp = false;
130 break;
131 }
132 }
133 }
134
135
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 150 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 }
146 312 void Sparse(const std::vector<double> &matrix) {
147 312 col_index.push_back(0);
148 bool flag = false;
149
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 1222 for (unsigned j = 0; j < cols; j++) {
150 910 col_index.push_back(value.size());
151
152
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 4134 for (unsigned i = 0; i < rows; i++) {
153
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 3224 if (fabs(matrix[(i * cols) + j]) > kEPS) {
154
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 1222 value.push_back(matrix[(i * cols) + j]);
155
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 1222 row.push_back(i);
156 flag = true;
157 }
158 }
159
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 910 if (flag) {
160 col_index.pop_back();
161 572 col_index.push_back(value.size());
162 flag = false;
163 }
164 }
165 312 }
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
200 156 void GetSparsedMatrixFromFile(std::ifstream &file) {
201
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 156 if (!file) {
202 ✗ throw std::runtime_error("Cannot open file with sparsed matrix");
203 }
204 value.clear();
205 row.clear();
206 col_index.clear();
207 156 unsigned n = 0;
208 156 file >> n >> rows >> cols;
209
210 156 double tmp_val = 0;
211
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 936 for (unsigned i = 0; i < n; i++) {
212 file >> tmp_val;
213
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 780 value.push_back(tmp_val);
214 }
215
216 156 unsigned tmp = 0;
217
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 936 for (unsigned i = 0; i < n; i++) {
218 file >> tmp;
219
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 780 row.push_back(tmp);
220 }
221
222
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 728 for (unsigned i = 0; i < cols + 1; i++) {
223 file >> tmp;
224
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 572 col_index.push_back(tmp);
225 }
226 156 }
227 };
228
229 312 inline SparseMatrix GetFromFile(std::ifstream &file) {
230 312 size_t r = 0;
231 312 size_t c = 0;
232 312 file >> r >> c;
233
234 312 std::vector<double> dense(r * c);
235
236
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 1352 for (unsigned i = 0; i < r; i++) {
237
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 4264 for (unsigned j = 0; j < c; j++) {
238
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 3224 file >> dense[(i * c) + j];
239 }
240 }
241
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 312 SparseMatrix a(dense, r, c);
242 312 return a;
243 };
244
245 using InType = std::tuple<SparseMatrix, SparseMatrix>;
246 using OutType = SparseMatrix;
247 using TestType = std::tuple<std::string, std::string>;
248 using BaseTask = ppc::task::Task<InType, OutType>;
249
250 } // namespace luzan_e_double_sparse_matrix_mult
251