GCC Code Coverage Report

Directory: ./
File: tasks/gaivoronskiy_m_gauss_jordan/seq/src/ops_seq.cpp
Date: 2026-01-27 01:59:34
Exec Total Coverage
Lines: 62 70 88.6%
Functions: 9 9 100.0%
Branches: 67 100 67.0%
Line Branch Exec Source
1 #include "gaivoronskiy_m_gauss_jordan/seq/include/ops_seq.hpp"
2
3 #include <algorithm>
4 #include <cmath>
5 #include <cstddef>
6 #include <vector>
7
8 #include "gaivoronskiy_m_gauss_jordan/common/include/common.hpp"
9
10 namespace gaivoronskiy_m_gauss_jordan {
11
12 namespace {
13
14 bool IsZero(double value) {
15
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 3120 return std::fabs(value) < 1e-10;
16 }
17
18 int FindPivot(const std::vector<std::vector<double>> &matrix, int row, int col, int n) {
19
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 384 for (int i = row; i < n; i++) {
20
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 384 if (!IsZero(matrix[i][col])) {
21 return i;
22 }
23 }
24 return -1;
25 }
26
27 void SwapRows(std::vector<std::vector<double>> &matrix, int row1, int row2, int m) {
28
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 112 for (int j = 0; j < m; j++) {
29 88 std::swap(matrix[row1][j], matrix[row2][j]);
30 }
31 }
32
33 void DivideRow(std::vector<std::vector<double>> &matrix, int row, double divisor, int m) {
34
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 1728 for (int j = 0; j < m; j++) {
35 1376 matrix[row][j] /= divisor;
36 }
37 }
38
39 void SubtractRows(std::vector<std::vector<double>> &matrix, int target_row, int source_row, double coefficient, int m) {
40
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 960 for (int j = 0; j < m; j++) {
41 744 matrix[target_row][j] -= coefficient * matrix[source_row][j];
42 }
43 }
44
45 136 void PerformGaussJordanElimination(std::vector<std::vector<double>> &matrix, int n, int m) {
46 int row = 0;
47 int col = 0;
48
49
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 488 while (row < n && col < m - 1) {
50 int pivot_row = FindPivot(matrix, row, col, n);
51
52
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 352 if (pivot_row == -1) {
53 ✗ col++;
54 ✗ continue;
55 }
56
57
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 352 if (pivot_row != row) {
58 SwapRows(matrix, row, pivot_row, m);
59 }
60
61
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 352 double pivot_value = matrix[row][col];
62
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 352 if (!IsZero(pivot_value)) {
63 DivideRow(matrix, row, pivot_value, m);
64 }
65
66
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 1376 for (int i = 0; i < n; i++) {
67
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 1024 if (i != row && !IsZero(matrix[i][col])) {
68 double coeff = matrix[i][col];
69 SubtractRows(matrix, i, row, coeff, m);
70 }
71 }
72
73 352 row++;
74 352 col++;
75 }
76 136 }
77
78 bool IsRowAllZeros(const std::vector<double> &row, int cols) {
79
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 1376 for (int j = 0; j < cols; j++) {
80
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 1376 if (!IsZero(row[j])) {
81 return false;
82 }
83 }
84 return true;
85 }
86
87 136 bool CheckInconsistency(const std::vector<std::vector<double>> &matrix, int n, int m) {
88
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 488 for (int i = 0; i < n; i++) {
89
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 704 if (IsRowAllZeros(matrix[i], m - 1) && !IsZero(matrix[i][m - 1])) {
90 return true;
91 }
92 }
93 return false;
94 }
95
96 136 int CalculateRank(const std::vector<std::vector<double>> &matrix, int n, int m) {
97 int rank = 0;
98
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 488 for (int i = 0; i < n; i++) {
99
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 704 if (!IsRowAllZeros(matrix[i], m - 1)) {
100 352 rank++;
101 }
102 }
103 136 return rank;
104 }
105
106 136 std::vector<double> ExtractSolution(const std::vector<std::vector<double>> &matrix, int n, int m) {
107 136 std::vector<double> solution(m - 1, 0.0);
108
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 488 for (int i = 0; i < std::min(n, m - 1); i++) {
109 bool found = false;
110
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 688 for (int j = 0; j < m - 1; j++) {
111
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 688 if (!IsZero(matrix[i][j])) {
112 352 solution[j] = matrix[i][m - 1];
113 found = true;
114 break;
115 }
116 }
117 ✗ if (!found && i < m - 1) {
118 ✗ solution[i] = 0.0;
119 }
120 }
121 136 return solution;
122 }
123
124 } // namespace
125
126
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 136 GaivoronskiyMGaussJordanSEQ::GaivoronskiyMGaussJordanSEQ(const InType &in) {
127 SetTypeOfTask(GetStaticTypeOfTask());
128
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 136 InType tmp(in);
129 GetInput().swap(tmp);
130 136 }
131
132
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 136 bool GaivoronskiyMGaussJordanSEQ::ValidationImpl() {
133
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 136 if (GetInput().empty()) {
134 return true;
135 }
136 size_t cols = GetInput()[0].size();
137 std::size_t total = 0;
138
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 488 for (const auto &row : GetInput()) {
139 352 total += row.size();
140 }
141
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 136 return GetOutput().empty() && (cols != 0) && ((cols * GetInput().size()) == total);
142 }
143
144
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 136 bool GaivoronskiyMGaussJordanSEQ::PreProcessingImpl() {
145 GetOutput().clear();
146 136 return true;
147 }
148
149
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 136 bool GaivoronskiyMGaussJordanSEQ::RunImpl() {
150
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 136 if (GetInput().empty()) {
151 return true;
152 }
153
154 136 std::vector<std::vector<double>> matrix = GetInput();
155 136 int n = static_cast<int>(matrix.size());
156
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 136 int m = (n > 0) ? static_cast<int>(matrix[0].size()) : 0;
157
158
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 136 if (m == 0) {
159 return false;
160 }
161
162 136 PerformGaussJordanElimination(matrix, n, m);
163
164
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 136 if (CheckInconsistency(matrix, n, m)) {
165 ✗ GetOutput() = std::vector<double>();
166 ✗ return false;
167 }
168
169 136 int rank = CalculateRank(matrix, n, m);
170
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 136 if (rank < m - 1 && rank < n) {
171 ✗ GetOutput() = std::vector<double>();
172 ✗ return false;
173 }
174
175
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 136 GetOutput() = ExtractSolution(matrix, n, m);
176 136 return true;
177 136 }
178
179 136 bool GaivoronskiyMGaussJordanSEQ::PostProcessingImpl() {
180 136 return true;
181 }
182
183 } // namespace gaivoronskiy_m_gauss_jordan
184