GCC Code Coverage Report

Directory: ./
File: tasks/tsyplakov_k_mul_double_crs_matrix/seq/src/ops_seq.cpp
Date: 2026-06-04 20:25:32
Exec Total Coverage
Lines: 58 58 100.0%
Functions: 6 6 100.0%
Branches: 38 56 67.9%
Line Branch Exec Source
1 #include "tsyplakov_k_mul_double_crs_matrix/seq/include/ops_seq.hpp"
2
3 #include <cmath>
4 #include <cstdlib>
5 #include <limits>
6 #include <map>
7 #include <vector>
8
9 #include "tsyplakov_k_mul_double_crs_matrix/common/include/common.hpp"
10
11 namespace tsyplakov_k_mul_double_crs_matrix {
12
13
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 32 TsyplakovKTestTaskSEQ::TsyplakovKTestTaskSEQ(const InType &in) {
14 SetTypeOfTask(GetStaticTypeOfTask());
15 GetInput() = in;
16 32 }
17
18 32 bool TsyplakovKTestTaskSEQ::ValidationImpl() {
19
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 32 return (GetInput().a.cols == GetInput().b.rows) && (GetInput().a.rows > 0) && (GetInput().a.cols > 0) &&
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 64 (GetInput().b.rows > 0) && (GetInput().b.cols > 0);
21 }
22
23 32 bool TsyplakovKTestTaskSEQ::PreProcessingImpl() {
24 32 GetOutput() = SparseMatrixCRS(GetInput().a.rows, GetInput().b.cols);
25 32 return true;
26 }
27
28 72 std::vector<double> TsyplakovKTestTaskSEQ::MultiplyRowByMatrix(const std::vector<double> &row_values,
29 const std::vector<int> &row_cols,
30 const SparseMatrixCRS &b, int &result_nnz) {
31 std::map<int, double> temp_result;
32
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 160 for (size_t i = 0; i < row_cols.size(); ++i) {
33 88 int col_a = row_cols[i];
34 88 double val_a = row_values[i];
35
36 88 int start = b.row_ptr[col_a];
37 88 int end = b.row_ptr[col_a + 1];
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 176 for (int j = start; j < end; ++j) {
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 88 int col_b = b.col_index[j];
41 88 double val_b = b.values[j];
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 88 temp_result[col_b] += val_a * val_b;
44 }
45 }
46
47 const double eps = std::numeric_limits<double>::epsilon() * 100;
48 72 std::vector<double> result_values;
49 72 result_nnz = 0;
50
51
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 144 for (auto it = temp_result.begin(); it != temp_result.end();) {
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 72 if (std::abs(it->second) < eps) {
53 it = temp_result.erase(it);
54 } else {
55
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 72 result_values.push_back(it->second);
56 ++it;
57 72 ++result_nnz;
58 }
59 }
60
61 72 return result_values;
62 }
63
64 32 bool TsyplakovKTestTaskSEQ::RunImpl() {
65 const SparseMatrixCRS &a = GetInput().a;
66
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 32 const SparseMatrixCRS &b = GetInput().b;
67 SparseMatrixCRS &c = GetOutput();
68
69 c.values.clear();
70 c.col_index.clear();
71 32 c.row_ptr.assign(a.rows + 1, 0);
72
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 104 for (int i = 0; i < a.rows; ++i) {
74 72 int start_a = a.row_ptr[i];
75 72 int end_a = a.row_ptr[i + 1];
76
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 72 std::vector<double> row_values(a.values.begin() + start_a, a.values.begin() + end_a);
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 72 std::vector<int> row_cols(a.col_index.begin() + start_a, a.col_index.begin() + end_a);
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80 72 int row_nnz = 0;
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 72 std::vector<double> row_result = MultiplyRowByMatrix(row_values, row_cols, b, row_nnz);
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 72 c.row_ptr[i + 1] = c.row_ptr[i] + row_nnz;
84 }
85
86 c.values.clear();
87 c.col_index.clear();
88 32 c.row_ptr.assign(a.rows + 1, 0);
89
90
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 104 for (int i = 0; i < a.rows; ++i) {
91 72 int start_a = a.row_ptr[i];
92 72 int end_a = a.row_ptr[i + 1];
93
94 std::map<int, double> temp_result;
95
96
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 160 for (int k_idx = start_a; k_idx < end_a; ++k_idx) {
97 88 int k = a.col_index[k_idx];
98 88 double a_ik = a.values[k_idx];
99
100 88 int start_b = b.row_ptr[k];
101 88 int end_b = b.row_ptr[k + 1];
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 176 for (int j_idx = start_b; j_idx < end_b; ++j_idx) {
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 88 int j = b.col_index[j_idx];
105 88 double b_kj = b.values[j_idx];
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 88 temp_result[j] += a_ik * b_kj;
107 }
108 }
109
110 const double eps = std::numeric_limits<double>::epsilon() * 100;
111 72 c.row_ptr[i] = static_cast<int>(c.values.size());
112
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 144 for (const auto &[col, val] : temp_result) {
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 72 if (std::abs(val) > eps) {
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 72 c.col_index.push_back(col);
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 72 c.values.push_back(val);
117 }
118 }
119 }
120 32 c.row_ptr[a.rows] = static_cast<int>(c.values.size());
121
122 32 return true;
123 }
124
125 32 bool TsyplakovKTestTaskSEQ::PostProcessingImpl() {
126 32 return true;
127 }
128
129 } // namespace tsyplakov_k_mul_double_crs_matrix
130