A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from https://TheAlgorithms.github.io/C-Plus-Plus/de/d75/qr__eigen__values_8cpp_source.html below:

TheAlgorithms/C++: numerical_methods/qr_eigen_values.cpp Source File

Go to the documentation of this file. 18using

qr_algorithm::operator<<;

29 int

i, j, tmp, lim2 =

LIMS

>> 1;

35 for

(i = 0; i < N; i++) {

36

A[0][i][i] = (std::rand() %

LIMS

) - lim2;

37 for

(j = i + 1; j < N; j++) {

38

tmp = (std::rand() %

LIMS

) - lim2;

54void mat_mul

(

const

std::valarray<std::valarray<double>> &A,

55 const

std::valarray<std::valarray<double>> &B,

56

std::valarray<std::valarray<double>> *OUT) {

62

perror(

"Matrix dimensions mismatch!"

);

66 for

(

int

i = 0; i < R1; i++) {

67 for

(

int

j = 0; j < C2; j++) {

69 for

(

int

k = 0; k < C1; k++) {

70

OUT[0][i][j] += A[i][k] * B[k][j];

98

std::valarray<double>

eigen_values

(std::valarray<std::valarray<double>> *A,

99 bool

print_intermediates =

false

) {

100 int

rows = A->size();

102 int

counter = 0, num_eigs = rows - 1;

105

std::valarray<std::valarray<double>> Q(rows);

106

std::valarray<std::valarray<double>> R(columns);

109

std::valarray<double> eigen_vals(rows);

110 for

(

int

i = 0; i < rows; i++) {

111

Q[i] = std::valarray<double>(columns);

112

R[i] = std::valarray<double>(columns);

116 while

(num_eigs > 0) {

118 while

(std::abs(A[0][num_eigs][num_eigs - 1]) >

119

std::numeric_limits<double>::epsilon()) {

121

last_eig = A[0][num_eigs][num_eigs];

122 for

(

int

i = 0; i < rows; i++) {

123

A[0][i][i] -= last_eig;

128 if

(print_intermediates) {

129

std::cout << *A <<

"\n"

;

130

std::cout << Q <<

"\n"

;

131

std::cout << R <<

"\n"

;

132

printf(

"-------------------- %d ---------------------\n"

,

139 for

(

int

i = 0; i < rows; i++) {

140

A[0][i][i] += last_eig;

145

eigen_vals[num_eigs] = last_eig;

147 if

(print_intermediates) {

148

std::cout <<

"========================\n"

;

149

std::cout <<

"Eigen value: "

<< last_eig <<

",\n"

;

150

std::cout <<

"========================\n"

;

157

eigen_vals[0] = A[0][0][0];

159 if

(print_intermediates) {

160

std::cout << Q <<

"\n"

;

161

std::cout << R <<

"\n"

;

178

std::valarray<std::valarray<double>> X = {{5, 7}, {7, 11}};

179 double

y[] = {15.56158, 0.384227};

181

std::cout <<

"------- Test 1 -------"

<< std::endl;

184 for

(

int

i = 0; i < 2; i++) {

185

std::cout << i + 1 <<

"/2 Checking for "

<< y[i] <<

" --> "

;

186 bool

result =

false

;

187 for

(

int

j = 0; j < 2 && !result; j++) {

188 if

(std::abs(y[i] - eig_vals[j]) < 0.1) {

190

std::cout <<

"("

<< eig_vals[j] <<

") "

;

194

std::cout <<

"found\n"

;

196

std::cout <<

"Test 1 Passed\n\n"

;

211

std::valarray<std::valarray<double>> X = {{-4, 4, 2, 0, -3},

215

{-3, -1, -3, -3, 0}};

216 double

y[] = {9.27648, -9.26948, 2.0181, -1.03516,

219

std::cout <<

"------- Test 2 -------"

<< std::endl;

222

std::cout << X <<

"\n" 223

<<

"Eigen values: "

<< eig_vals <<

"\n"

;

225 for

(

int

i = 0; i < 5; i++) {

226

std::cout << i + 1 <<

"/5 Checking for "

<< y[i] <<

" --> "

;

227 bool

result =

false

;

228 for

(

int

j = 0; j < 5 && !result; j++) {

229 if

(std::abs(y[i] - eig_vals[j]) < 0.1) {

231

std::cout <<

"("

<< eig_vals[j] <<

") "

;

235

std::cout <<

"found\n"

;

237

std::cout <<

"Test 2 Passed\n\n"

;

243int main

(

int

argc,

char

**argv) {

250

std::cout <<

"Usage: ./qr_eigen_values [mat_size]\n"

;

255

fprintf(stderr,

"Matrix size should be > 2\n"

);

260

std::srand(std::time(

nullptr

));

264

std::valarray<std::valarray<double>> A(rows);

266 for

(

int

i = 0; i < rows; i++) {

267

A[i] = std::valarray<double>(columns);

273

std::cout << A <<

"\n"

;

275

clock_t t1 = clock();

277 double

dtime =

static_cast<double>

(clock() - t1) / CLOCKS_PER_SEC;

279

std::cout <<

"Eigen vals: "

;

280 for

(i = 0; i <

mat_size

; i++) std::cout << eigen_vals[i] <<

"\t"

;

281

std::cout <<

"\nTime taken to compute: "

<< dtime <<

" sec\n"

;

int main()

Main function.

Functions to compute QR decomposition of any rectangular matrix.

std::valarray< double > eigen_values(std::valarray< std::valarray< double > > *A, bool print_intermediates=false)

void qr_decompose(const std::valarray< std::valarray< T > > &A, std::valarray< std::valarray< T > > *Q, std::valarray< std::valarray< T > > *R)

Library functions to compute QR decomposition of a given matrix.

void create_matrix(std::valarray< std::valarray< double > > *A)

void mat_mul(const std::valarray< std::valarray< double > > &A, const std::valarray< std::valarray< double > > &B, std::valarray< std::valarray< double > > *OUT)

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4