sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
4eaf3f6c7cc192284cbaa19ff15560346948ed529cca8f27d7841273c428fc4e | C++ | 257 | 13 | #include <iostream>
#include <Eigen/Dense>
using namespace std;
int main()
{
Eigen::MatrixXf mat(2,4);
mat << 1, 2, 6, 9,
3, 1, 7, 2;
std::cout << "Row's maximum: " << std::endl
<< mat.rowwise().maxCoeff() << std::endl;
}
|
4321d80a03630a3981873ecdf56f1be0f673a8c77d6188edd5f5ddb97597f56e | C++ | 259 | 16 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// create a JSON array
json j_array = {0, 1, 2, 3, 4, 5};
// call erase()
j_array.erase(2);
// print values
std::cout << j_array << '\n';
}
|
ba50938d5650ccac1a88c78f6bd663673eb318d065dac147b62e5324c8267924 | C++ | 259 | 14 | #include "../Eigen/SVD"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
BDCSVD<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
0585323842dcd0f9b5c7c0fbec8a074cc0f291e683ded09ad9de81de0fae9c83 | C++ | 260 | 13 | #include <iostream>
#include <Eigen/Dense>
using namespace std;
int main()
{
Eigen::MatrixXf mat(2,4);
mat << 1, 2, 6, 9,
3, 1, 7, 2;
std::cout << "Column's maximum: " << std::endl
<< mat.colwise().maxCoeff() << std::endl;
}
|
fd5a9991b62047fc5692fc6b37be5a6907e27c0fc7b30e8170b358312b980613 | C++ | 260 | 15 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(CV_QUALIFIER Matrix3d &m){
Block<Matrix3d,3,3> b(m.block<3,3>(0,0));
}
int main() {}
|
5b886ca91aca23ee834ade4fd57bc543580e85e12f2182edb9103af24b376d30 | C++ | 261 | 15 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(CV_QUALIFIER float *ptr, DenseIndex size){
Map<ArrayXf> m(ptr, size);
}
int main() {}
|
9849989c5f94bd9db6407e638056b784bad38d775df53f99d1b49260f4c674a9 | C++ | 261 | 14 | #include "../Eigen/LU"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
FullPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
58584ddf5eac3d862c3b5b4e3117f4cc8b201066b61cd7e8192f3f26b85ab1c5 | C++ | 262 | 14 | #include "../Eigen/SVD"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
JacobiSVD<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
f4635e368dd2989c4482d35faadabec66f489aa9b0235f94f1aaf70da969167b | C++ | 262 | 14 | #include "../Eigen/Cholesky"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
LLT<Matrix<SCALAR,Dynamic,Dynamic> > llt(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
1a23121b57cf1107979c6cab4b13759f3acf4f84c8f8d624a84ca008b9d0dafe | C++ | 264 | 14 | #include "../Eigen/LU"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
PartialPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
3f3156e8c1b00ad826b29b2eab92cd065731bb1a735d8f71018e62ac4c3fe6a2 | C++ | 264 | 14 | #include "../Eigen/Cholesky"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
LDLT<Matrix<SCALAR,Dynamic,Dynamic> > ldlt(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
89e347c975e4636c11aa4662f0b44566119acaadf8a349dd30281947e19ac6d8 | C++ | 264 | 15 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(float *ptr){
Map<CV_QUALIFIER MatrixXf>(ptr, 1, 1).coeffRef(0,0) = 1.0f;
}
int main() {}
|
7f3982490f762db542871e54b0ac4f01621ba2a14d910fcfbda606a821576bac | C++ | 265 | 10 | #include <iostream>
#include <iomanip>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
std::cout << std::boolalpha << std::is_same<nlohmann::byte_container_with_subtype<std::vector<std::uint8_t>>, json::binary_t>::value << std::endl;
}
|
b67c0289400e3c34a45d444febd60d1fa56c33efe2edc1cfb84802c0fa2ed25b | C++ | 265 | 14 | #include "../Eigen/QR"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
HouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
d330f805e816e707338bf0af3aa1a8163483d796eca0ac3708338bbb9d2052b0 | C++ | 265 | 9 | Matrix3f A;
Vector3f b;
A << 1,2,3, 4,5,6, 7,8,9;
b << 3, 3, 4;
cout << "Here is the matrix A:" << endl << A << endl;
cout << "Here is the vector b:" << endl << b << endl;
Vector3f x;
x = A.lu().solve(b);
cout << "The solution is:" << endl << x << endl;
|
82fcf069676e1b716059261193f48a478a727399994455e0c8e4c61ed2dbf561 | C++ | 266 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
Diagonal<CV_QUALIFIER MatrixXf>(m).coeffRef(0) = 1.0f;
}
int main() {}
|
cbe323cf272e75d283c31b15ce14f504f351c373313e2b205d26ca634fbbb246 | C++ | 266 | 11 | #include <iostream>
#include <arbor/spike_event.hpp>
namespace arb {
ARB_ARBOR_API std::ostream& operator<<(std::ostream& o, const spike_event& ev) {
return o << "E[tgt " << ev.target << ", t " << ev.time << ", w " << ev.weight << "]";
}
} // namespace arb
|
2a4d2d15b3d0f1f90d4f63a77f5f81d95ddacd98c4e9e6a3e83e5816cda6484f | C++ | 267 | 4 | MatrixXcf A = MatrixXcf::Random(4,4);
cout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl;
ComplexSchur<MatrixXcf> schurOfA(A, false); // false means do not compute U
cout << "The triangular matrix T is:" << endl << schurOfA.matrixT() << endl;
|
076efe9c6746c47f63437ca92f3a682271cd124984e004cdf99669cbaa1d5e5e | C++ | 268 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topLeftCorner(2, 2):" << endl;
cout << m.topLeftCorner(2, 2) << endl;
m.topLeftCorner(2, 2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
94b0b128b6b6044f451fd52d1d2a6a96e076662c1e20485334756d1533578f7e | C++ | 268 | 13 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// create JSON array
const json array = {"first", "2nd", "third", "fourth"};
// output element at index 2 (third element)
std::cout << array.at(2) << '\n';
}
|
a3081600cc91dd05399a7c5482598fc1f2c2038d4fef30e6a5c5bf5d62697978 | C++ | 268 | 5 | Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
Matrix<ptrdiff_t, 3, 1> res = (m.array() >= 0.5).rowwise().count();
cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl;
cout << res << endl;
|
4b54ca35c86db8d24e68e6eb80860ff3aa9b9b06f5b71ada7a35ac3c94f39544 | C++ | 269 | 5 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the block:" << endl << m.block<2, Dynamic>(1, 1, 2, 3) << endl;
m.block<2, Dynamic>(1, 1, 2, 3).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
709060bd04d45d4d1955a132ce63f7684d65941d17edd40b8729010a7c662a4b | C++ | 270 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
Transpose<CV_QUALIFIER MatrixXf>(m).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
220831185fa1c5ddd7d4b15691dc03775ba3a19a23afcf2bc922d53416a407f6 | C++ | 271 | 14 | #include "../Eigen/QR"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
ColPivHouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
8bfad596e7b0d82eead3b9cac861cdd518ddb4a8fb1bc9ac7ed356a489f0e5a1 | C++ | 271 | 15 | // Cytosim was created by Francois Nedelec. Copyright 2007-2017 EMBL.
#include "line_disp.h"
void LineDisp::clear()
{
visible = 1;
color = 0xFFFFFFFF;
explode_shift = 0;
end_color[0] = 0xFFFFFFFF;
end_color[1] = 0xFFFFFFFF;
}
|
985fb136ed3f9c1e98fa8ef81f29d900e3e9b92589edca7fb45bac152a5535b5 | C++ | 271 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topRightCorner(2, 2):" << endl;
cout << m.topRightCorner(2, 2) << endl;
m.topRightCorner(2, 2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
f530b6749065453931c2cf802193d84ecf5e828f8e5e46072002b1c5792b0049 | C++ | 271 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topLeftCorner<2,2>():" << endl;
cout << m.topLeftCorner<2,2>() << endl;
m.topLeftCorner<2,2>().setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
e11b18c4c7e006f2807ee7249ffe9d3b368b6e12a22a2bb5e9708f46ec7e447f | C++ | 272 | 14 | #include "../Eigen/QR"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
FullPivHouseholderQR<Matrix<SCALAR,Dynamic,Dynamic> > qr(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
7815a02d05eb4bf9c46d34db13071de8644c295d62656fcd565adc17ad7dc503 | C++ | 273 | 14 | #include "../Eigen/Eigenvalues"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR int
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
EigenSolver<Matrix<SCALAR,Dynamic,Dynamic> > eig(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
0883fbbbc1288b942c505ddcea7dd31c87a90d7b316632a489c1edcd79ec5307 | C++ | 274 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topRightCorner<2,2>():" << endl;
cout << m.topRightCorner<2,2>() << endl;
m.topRightCorner<2,2>().setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
d454cd45c41e009ad53cb40216115c5d1c807d01c853bf3c7efc80557ec85945 | C++ | 274 | 14 | #include <glm/gtx/exterior_product.hpp>
#include <glm/gtc/epsilon.hpp>
#include <glm/vec2.hpp>
int main()
{
int Error = 0;
float const f = glm::cross(glm::vec2(1.0f, 1.0f), glm::vec2(1.0f, 1.0f));
Error += glm::epsilonEqual(f, 0.0f, 0.001f) ? 0 : 1;
return Error;
}
|
d738181028a513834539d96c8ffe89ba3760a4fc50a80d242c9e82b0affef66f | C++ | 274 | 7 | MatrixXi mat(3,3);
mat << 1, 2, 3, 4, 5, 6, 7, 8, 9;
cout << "Here is the matrix mat:\n" << mat << endl;
// This assignment shows the aliasing problem
mat.bottomRightCorner(2,2) = mat.topLeftCorner(2,2);
cout << "After the assignment, mat = \n" << mat << endl;
|
3577d3380105534489e098d8db429cd140b8e34889a0c5546472a56566d7859d | C++ | 275 | 5 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here are the coefficients on the 1st super-diagonal and 2nd sub-diagonal of m:" << endl
<< m.diagonal(1).transpose() << endl
<< m.diagonal(-2).transpose() << endl;
|
0ffdff82f7ddc1404b13ea1aac877cb6eb92a9fdaff4df8b41a2517358916837 | C++ | 277 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(CV_QUALIFIER Matrix3d &m){
// row/column constructor
Block<Matrix3d,3,1> b(m,0);
}
int main() {}
|
2a7b736eaf37e8712de26d4e1918eb93d0501f8e8f33bd49cdcfe88dcefed416 | C++ | 277 | 11 | RowVectorXd vec1(3);
vec1 << 1, 2, 3;
std::cout << "vec1 = " << vec1 << std::endl;
RowVectorXd vec2(4);
vec2 << 1, 4, 9, 16;
std::cout << "vec2 = " << vec2 << std::endl;
RowVectorXd joined(7);
joined << vec1, vec2;
std::cout << "joined = " << joined << std::endl;
|
3ab22be686c1b43ffe3949a87a0d9b9d5f725081f80bc07926c025c56998acfd | C++ | 277 | 7 | MatrixXi mat(3,3);
mat << 1, 2, 3, 4, 5, 6, 7, 8, 9;
cout << "Here is the matrix mat:\n" << mat << endl;
// The eval() solves the aliasing problem
mat.bottomRightCorner(2,2) = mat.topLeftCorner(2,2).eval();
cout << "After the assignment, mat = \n" << mat << endl;
|
a0ac78d76c7c56c1ab33415b760cf3678494c0473efa9682d2df79c7403e7089 | C++ | 277 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomLeftCorner(2, 2):" << endl;
cout << m.bottomLeftCorner(2, 2) << endl;
m.bottomLeftCorner(2, 2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
bf7e4c26f521888ff046794a78f80919a18930df74dc24417e08009bd774b285 | C++ | 277 | 20 | #define GLM_ENABLE_EXPERIMENTAL
#include <glm/gtx/color_space.hpp>
int test_saturation()
{
int Error(0);
glm::vec4 Color = glm::saturation(1.0f, glm::vec4(1.0, 0.5, 0.0, 1.0));
return Error;
}
int main()
{
int Error(0);
Error += test_saturation();
return Error;
}
|
0f06a083591af51a2bbe15bd2eae3077bd2ba96691ca43ddef545ce9bb5a1617 | C++ | 278 | 6 | // This file is autogenerated. Changes will be overwritten.
#include "2LCCYRVYXB/moc_ScatterDataModifier.cpp"
#include "2LCCYRVYXB/moc_mainwindow.cpp"
#include "2LCCYRVYXB/moc_openglwindow.cpp"
#include "HFA4SCIXVZ/moc_qcustomplot.cpp"
#include "2LCCYRVYXB/moc_slidergroup.cpp"
|
6a8a527f09d66a07f75c3a2d1706fbea7a7816f85d9bd7ea1b6ede1ff1a1fb0e | C++ | 278 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
Block<CV_QUALIFIER MatrixXf, 3, 3>(m, 0, 0).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
c2f401c296a4ab796cdf5dedc0cf0466b85cc5d7c65988c8ceebd83471126ba6 | C++ | 278 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
Matrix3f m;
Block<CV_QUALIFIER Matrix3f>(m, 0, 0, 3, 3).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
0352b1741862d2e027fa7f3f10f82ec607d98a7fd2544c1010c325638a3c2686 | C++ | 279 | 7 | ArrayXXf table(10, 4);
table.col(0) = ArrayXf::LinSpaced(10, 0, 90);
table.col(1) = M_PI / 180 * table.col(0);
table.col(2) = table.col(1).sin();
table.col(3) = table.col(1).cos();
std::cout << " Degrees Radians Sine Cosine\n";
std::cout << table << std::endl;
|
273a0b992e86d3ae2aa78fbf3be1109b76878183cce6353a2fc5394cb08b2b28 | C++ | 279 | 5 | Matrix4d m = Vector4d(1,2,3,4).asDiagonal();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.fixed<2, 2>(2, 2):" << endl << m.block<2, 2>(2, 2) << endl;
m.block<2, 2>(2, 0) = m.block<2, 2>(2, 2);
cout << "Now the matrix m is:" << endl << m << endl;
|
5483fd4f2407319c33dd00858453a1ae83dd8dae8b944c3d90e12b92415ffdec | C++ | 279 | 5 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here are the coefficients on the 1st super-diagonal and 2nd sub-diagonal of m:" << endl
<< m.diagonal<1>().transpose() << endl
<< m.diagonal<-2>().transpose() << endl;
|
3c093e91384f416ee762d7933144ac2df544c6c3e85a205ab2c31970319e273d | C++ | 280 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomLeftCorner<2,2>():" << endl;
cout << m.bottomLeftCorner<2,2>() << endl;
m.bottomLeftCorner<2,2>().setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
9eef836e1760d83a65d268c2871f9b8726b4369fec0941444afadfdfaf6b973d | C++ | 280 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomRightCorner(2, 2):" << endl;
cout << m.bottomRightCorner(2, 2) << endl;
m.bottomRightCorner(2, 2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
45c973f7af982e3a9949758e17109346393eeffe0e811be59655b09efa22f911 | C++ | 281 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
TriangularView<CV_QUALIFIER MatrixXf,Upper>(m).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
cc65ebba2801c0f246fb9d9f73e84e5e04d120444c0e3440259c490cb419e4e4 | C++ | 281 | 8 | Matrix3f A;
Vector3f b;
A << 1,2,3, 0,5,6, 0,0,10;
b << 3, 3, 4;
cout << "Here is the matrix A:" << endl << A << endl;
cout << "Here is the vector b:" << endl << b << endl;
Vector3f x = A.triangularView<Upper>().solve(b);
cout << "The solution is:" << endl << x << endl;
|
f5112014d3eb41d83f8eee4fcd7500981c491a6839af1c3766324856e58af974 | C++ | 281 | 18 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void call_ref(Ref<VectorXf> a) { }
int main()
{
VectorXf a(10);
CV_QUALIFIER VectorXf& ac(a);
call_ref(ac);
}
|
ea02649fd78d6cf8fdca3f31fcc2dcafc7558fa8a439f8966de3393c9c761b3b | C++ | 282 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
SelfAdjointView<CV_QUALIFIER MatrixXf,Upper>(m).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
0a79e9deb1d2d19e17568b7cf0a96adda5d2ef8d57e5b648c569c6bf28aab607 | C++ | 283 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomRightCorner<2,2>():" << endl;
cout << m.bottomRightCorner<2,2>() << endl;
m.bottomRightCorner<2,2>().setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
9f5abf42324b987b950cdae717c9e726cbcc35bfa01d59c12a5b4b08fd8c903c | C++ | 283 | 7 | MatrixXi m(2,2);
m << 1, 0,
1, 1;
cout << "Comparing m with identity matrix:" << endl;
cout << m.cwiseEqual(MatrixXi::Identity(2,2)) << endl;
Index count = m.cwiseEqual(MatrixXi::Identity(2,2)).count();
cout << "Number of coefficients that are equal: " << count << endl;
|
f5e2893dad76af7e363954765461808f6adea67c337c0b6b2fc3709bfd126981 | C++ | 283 | 18 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// create JSON values
json a = 23;
json b = 42;
// copy-assign a to b
b = a;
// serialize the JSON arrays
std::cout << a << '\n';
std::cout << b << '\n';
}
|
6659068e79d60214231ee68d589866f6d19f97f17397717849611336b6acf38a | C++ | 284 | 13 | #include <iostream>
#define NLOHMANN_JSON_NAMESPACE_NO_VERSION 1
#include <nlohmann/json.hpp>
// macro needed to output the NLOHMANN_JSON_NAMESPACE as string literal
#define Q(x) #x
#define QUOTE(x) Q(x)
int main()
{
std::cout << QUOTE(NLOHMANN_JSON_NAMESPACE) << std::endl;
}
|
72a02988647ee8a1ff7da932aa5d6f660422686fdad5845076a8efaf8c6dc568 | C++ | 284 | 11 | // This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
// This test should not be instrumented.
#include <cstdint>
#include <cstddef>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) {
return 0;
}
|
6c8edf440fadbbb5a4e9f8982329bf881a146ba0f36a92299f80826996823165 | C++ | 285 | 11 | // This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
// A fuzzer with empty target function.
#include <cstdint>
#include <cstdlib>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) {
return 0;
}
|
bb47bdc632eff2adec214f7c127d6406e48085349005123934afafa0d6f8bbcf | C++ | 285 | 15 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(CV_QUALIFIER float *ptr, DenseIndex rows, DenseIndex cols){
Map<MatrixXf> m(ptr, rows, cols);
}
int main() {}
|
edc736a533042f558d1160c250f99b74cc8aedf38c0b5bb6017829cef1d8d6dc | C++ | 285 | 16 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// create a JSON object
const json object =
{
{"one", 1}, {"two", 2}, {"three", 2.9}
};
// output element with key "two"
std::cout << object["two"] << '\n';
}
|
32c933934eb9093c880d79aed65e19fe631e211eee0518c2344057f573bd01d6 | C++ | 286 | 15 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(CV_QUALIFIER Matrix3d &m){
CwiseUnaryView<internal::scalar_real_ref_op<double>,Matrix3d> t(m);
}
int main() {}
|
bec61ceb345a5b836cc3129b49787bb53129b10296c9b821e97bf6f584627c9e | C++ | 286 | 15 | #include "../Eigen/Sparse"
using namespace Eigen;
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
void call_ref(Ref<SparseMatrix<float> > a) { }
#else
void call_ref(const Ref<const SparseMatrix<float> > &a) { }
#endif
int main()
{
SparseMatrix<float> a(10,10);
call_ref(a+a);
}
|
c90025f7786e9707868f26ddb755cd07db9dd1ce8d89c605accb7fa282108534 | C++ | 286 | 5 | Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the sum of each row:" << endl << m.rowwise().sum() << endl;
cout << "Here is the maximum absolute value of each row:"
<< endl << m.cwiseAbs().rowwise().maxCoeff() << endl;
|
747a57468b5a24d5b12af1267817670be8bb31416835a37330a25faa53c61995 | C++ | 287 | 17 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// create a JSON value
json a = 23;
// move contents of a to b
json b(std::move(a));
// serialize the JSON arrays
std::cout << a << '\n';
std::cout << b << '\n';
}
|
a55c8840aa98d31cdc34c9e42a639bdaee37fcd08142545b1000b4068d7a07f7 | C++ | 288 | 9 | #include "cpu_numa_info.h"
/// Based on http://stackoverflow.com/questions/16862620/numa-get-current-node-core
void get_cpu_and_node_(int& cpu, int& node) {
unsigned long a,d,c;
__asm__ volatile("rdtscp" : "=a" (a), "=d" (d), "=c" (c));
node = (c & 0xFFF000)>>12;
cpu = c & 0xFFF;
}
|
de5803239cda6494b8c0cb20e9ecdb90b649c19de77edf4b6da7f2115f115589 | C++ | 289 | 12 | MatrixXcf a = MatrixXcf::Random(2,2);
cout << "Here is the matrix a\n" << a << endl;
cout << "Here is the matrix a^T\n" << a.transpose() << endl;
cout << "Here is the conjugate of a\n" << a.conjugate() << endl;
cout << "Here is the matrix a^*\n" << a.adjoint() << endl;
|
15bfa716deb83d3c33d79beb4b3c984fa09accca81180923e1e22316ae737a67 | C++ | 290 | 14 | #include "../Eigen/Eigenvalues"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define SCALAR std::complex<double>
#else
#define SCALAR float
#endif
using namespace Eigen;
int main()
{
EigenSolver<Matrix<SCALAR,Dynamic,Dynamic> > eig(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
}
|
fea144f33c23987543759f641177197a5d32a0884fe0342bccad102fdcad4454 | C++ | 291 | 4 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped().transpose():" << endl << m.reshaped().transpose() << endl;
cout << "Here is m.reshaped<RowMajor>().transpose(): " << endl << m.reshaped<RowMajor>().transpose() << endl;
|
6324edeb3e201160cc343e4b3c404cc1d9157e0d41a47fac67df16d1c96e2f1e | C++ | 292 | 5 | Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the sum of each column:" << endl << m.colwise().sum() << endl;
cout << "Here is the maximum absolute value of each column:"
<< endl << m.cwiseAbs().colwise().maxCoeff() << endl;
|
49ae8f2f5f972aba37b8cd8b5ef5aea4dfd351afdea594ea9e0ec6fc67d2ac01 | C++ | 293 | 7 | MatrixXi m(2,2);
m << 1, 0,
1, 1;
cout << "Comparing m with identity matrix:" << endl;
cout << m.cwiseNotEqual(MatrixXi::Identity(2,2)) << endl;
Index count = m.cwiseNotEqual(MatrixXi::Identity(2,2)).count();
cout << "Number of coefficients that are not equal: " << count << endl;
|
f2a95caa6b2b2bd34ffdb0fb8a1191ba17a556087969fc35f3dd430c3f166148 | C++ | 293 | 12 | #include <torch/extension.h>
at::Tensor multi_tensor_l2norm_cuda(
int chunk_size,
std::vector<std::vector<at::Tensor>> tensor_lists);
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("l2norm", &multi_tensor_l2norm_cuda,
"Computes L2 norm for a list of contiguous tensors");
} |
6ce7a04f8f6711ea177f46c96f32dea8877a0c50adadddcedb365181614ccf88 | C++ | 295 | 4 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped(2, AutoSize):" << endl << m.reshaped(2, AutoSize) << endl;
cout << "Here is m.reshaped<RowMajor>(AutoSize, fix<8>):" << endl << m.reshaped<RowMajor>(AutoSize, fix<8>) << endl;
|
15b3ac169fc0b7fdceed2b799a9439562638b1b127a27b6b27d86f7862d0795c | C++ | 297 | 15 | #include <Eigen/Core>
#include <iostream>
using namespace Eigen;
using namespace std;
int main(void)
{
int const N = 5;
MatrixXi A(N,N);
A.setRandom();
cout << "A =\n" << A << '\n' << endl;
cout << "A(1..3,:) =\n" << A.middleCols(1,3) << endl;
return 0;
}
|
32f30e81c422f5b0a4855673771312703dc4bb06b8d266fcdc1e339954f32a1f | C++ | 297 | 14 | #include <iostream>
#include <iomanip>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
using namespace nlohmann::literals;
int main()
{
json j = R"( {"hello": "world", "answer": 42} )"_json;
auto val = j["/hello"_json_pointer];
std::cout << std::setw(2) << val << '\n';
}
|
72ae2ada2942bd34444cc78101a340c991034b81057cc714b1d86a31a9e02873 | C++ | 297 | 15 | #include <Eigen/Core>
#include <iostream>
using namespace Eigen;
using namespace std;
int main(void)
{
int const N = 5;
MatrixXi A(N,N);
A.setRandom();
cout << "A =\n" << A << '\n' << endl;
cout << "A(2..3,:) =\n" << A.middleRows(2,2) << endl;
return 0;
}
|
9a1c66f0db868d3769226bc4db90708b2465f0a4d01b002c01291649e9aa667a | C++ | 297 | 15 | #include <Eigen/Core>
#include <iostream>
using namespace Eigen;
int main()
{
Matrix3f m3;
m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9;
Matrix4f m4 = Matrix4f::Identity();
Vector4i v4(1, 2, 3, 4);
std::cout << "m3\n" << m3 << "\nm4:\n"
<< m4 << "\nv4:\n" << v4 << std::endl;
}
|
f4418ad1d8e76b22ffd5ea42f7afd65e944d657afee23e1e8f98395298b167f8 | C++ | 297 | 18 |
// This is a regression unit regarding a weird linking issue with gcc.
#include "bug1213.h"
int main()
{
return 0;
}
template<typename T, int dim>
bool bug1213_2(const Eigen::Matrix<T,dim,1>& )
{
return true;
}
template bool bug1213_2<float,3>(const Eigen::Vector3f&);
|
7010a8532ecded49d7370fa2a1daa7c18c5d8748fb4e4acf511bf57331bb531b | C++ | 298 | 15 | #include <Eigen/Core>
#include <iostream>
using namespace Eigen;
using namespace std;
int main(void)
{
int const N = 5;
MatrixXi A(N,N);
A.setRandom();
cout << "A =\n" << A << '\n' << endl;
cout << "A(1..3,:) =\n" << A.middleRows<3>(1) << endl;
return 0;
}
|
8a78a897e5bcb50f1634274c7a575cca8be4f5142df896260a010d94463e1807 | C++ | 298 | 16 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
// implicitly create a JSON null value
json j1;
// explicitly create a JSON null value
json j2(nullptr);
// serialize the JSON null value
std::cout << j1 << '\n' << j2 << '\n';
}
|
b78b60fd63eddf542648c3276fb8c4f5a445ac00d531651f7a99d7d1c0e2c67d | C++ | 298 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topLeftCorner<2,Dynamic>(2,2):" << endl;
cout << m.topLeftCorner<2,Dynamic>(2,2) << endl;
m.topLeftCorner<2,Dynamic>(2,2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
d1769b37eff521875c72c8b65c3acb64782f358a314b4e841ad39bee9425d7cc | C++ | 298 | 15 | #include <Eigen/Core>
#include <iostream>
using namespace Eigen;
using namespace std;
int main(void)
{
int const N = 5;
MatrixXi A(N,N);
A.setRandom();
cout << "A =\n" << A << '\n' << endl;
cout << "A(:,1..3) =\n" << A.middleCols<3>(1) << endl;
return 0;
}
|
cd5a8759f49133fbe6515b84f4e8eff528d903b4ed6f4d8162a727b7673b8c0d | C++ | 299 | 6 | Vector3d v(1,0,0);
Vector3d w(1e-4,0,1);
cout << "Here's the vector v:" << endl << v << endl;
cout << "Here's the vector w:" << endl << w << endl;
cout << "v.isOrthogonal(w) returns: " << v.isOrthogonal(w) << endl;
cout << "v.isOrthogonal(w,1e-3) returns: " << v.isOrthogonal(w,1e-3) << endl;
|
87307097a69c3d4be3d23ffcbbdb6b4b04e2c73bce9691e14e940dfc0a1e6d62 | C++ | 301 | 16 | #include "../Eigen/Sparse"
using namespace Eigen;
void call_ref(Ref<SparseMatrix<float> > a) { }
int main()
{
SparseMatrix<float> a(10,10);
SparseMatrixBase<SparseMatrix<float> > &ac(a);
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
call_ref(ac);
#else
call_ref(ac.derived());
#endif
}
|
92160665bdcc42a5109db11a9b56ca086f1b5b91e39516170d544670aa1aef3e | C++ | 301 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.topRightCorner<2,Dynamic>(2,2):" << endl;
cout << m.topRightCorner<2,Dynamic>(2,2) << endl;
m.topRightCorner<2,Dynamic>(2,2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
99a99a1aacd84785f47a309901a076bbea8b8386d39dba6600e7c7bc765478c1 | C++ | 301 | 9 | Matrix3f A = Matrix3f::Random(3,3), B;
B << 0,1,0,
0,0,1,
1,0,0;
cout << "At start, A = " << endl << A << endl;
A *= B;
cout << "After A *= B, A = " << endl << A << endl;
A.applyOnTheRight(B); // equivalent to A *= B
cout << "After applyOnTheRight, A = " << endl << A << endl;
|
f18afbdc8b7feb44cffcbf3e3e5a15022ba1ef12e2a513db69ecbc547e67835d | C++ | 301 | 8 | Matrix2f m = Matrix2f::Random();
m = (m + m.adjoint()).eval();
JacobiRotation<float> J;
J.makeJacobi(m, 0, 1);
cout << "Here is the matrix m:" << endl << m << endl;
m.applyOnTheLeft(0, 1, J.adjoint());
m.applyOnTheRight(0, 1, J);
cout << "Here is the matrix J' * m * J:" << endl << m << endl;
|
1e606e80154fd2c5e3140aabc78d39284687ca4302d1b852dd5589b2d21abd18 | C++ | 303 | 13 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
json::json_pointer::string_t s = "This is a string.";
std::cout << s << std::endl;
std::cout << std::boolalpha << std::is_same<json::json_pointer::string_t, json::string_t>::value << std::endl;
}
|
30dcc9c4693cc762c3c9851f2b84e5b0e8fe6288a4f360ab78986c6f6e082de1 | C++ | 303 | 13 | Matrix3i m1;
m1 << 1, 2, 3,
4, 5, 6,
7, 8, 9;
cout << m1 << endl << endl;
Matrix3i m2 = Matrix3i::Identity();
m2.block(0,0, 2,2) << 10, 11, 12, 13;
cout << m2 << endl << endl;
Vector2i v1;
v1 << 14, 15;
m2 << v1.transpose(), 16,
v1, m1.block(1,1,2,2);
cout << m2 << endl;
|
860eb5cb73f2c09641217f8d36a415389002872ae371d6675dc60dc8f020c67d | C++ | 304 | 15 | #include <iostream>
#include <Eigen/Dense>
using namespace Eigen;
using namespace std;
int main()
{
Matrix3d m = Matrix3d::Random();
m = (m + Matrix3d::Constant(1.2)) * 50;
cout << "m =" << endl << m << endl;
Vector3d v(1,2,3);
cout << "m * v =" << endl << m * v << endl;
}
|
a922e566fc177d9b9d4a8a05f2c9acd8279a4cf599f1663f93934ab8a250a982 | C++ | 306 | 16 | #include "../Eigen/Sparse"
using namespace Eigen;
typedef SparseMatrix<double,ColMajor> Mat1;
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
typedef SparseMatrix<double,RowMajor> Mat2;
#else
typedef SparseMatrix<double,ColMajor> Mat2;
#endif
int main()
{
Mat1 a(10,10);
Mat2 b(10,10);
a += b;
}
|
bbdd3ace760b0fc7b60724c1e0ecc554769b970bd2e8e11b7eab103c8633f884 | C++ | 306 | 7 | int array[8];
for(int i = 0; i < 8; ++i) array[i] = i;
cout << "Column-major:\n" << Map<Matrix<int,2,4> >(array) << endl;
cout << "Row-major:\n" << Map<Matrix<int,2,4,RowMajor> >(array) << endl;
cout << "Row-major using stride:\n" <<
Map<Matrix<int,2,4>, Unaligned, Stride<1,4> >(array) << endl;
|
dbf549c768b799ac096fd434b4a2678b61d1b18a5db8df07b999c5990282f470 | C++ | 306 | 12 | #include <iostream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;
int main()
{
std::cout << "JSON for Modern C++ version "
<< NLOHMANN_JSON_VERSION_MAJOR << "."
<< NLOHMANN_JSON_VERSION_MINOR << "."
<< NLOHMANN_JSON_VERSION_PATCH << std::endl;
}
|
4b8ed9eda695501ab8c79615478db5ad4ce95e1d16ef55c97d915186718484b2 | C++ | 307 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomLeftCorner<2,Dynamic>(2,2):" << endl;
cout << m.bottomLeftCorner<2,Dynamic>(2,2) << endl;
m.bottomLeftCorner<2,Dynamic>(2,2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
4cbacc5694220b97ed0a4315228a83417197f2194e08989ff295c7311f3f6632 | C++ | 307 | 6 | MatrixXcf A = MatrixXcf::Random(4,4);
ComplexSchur<MatrixXcf> schur(4);
schur.compute(A);
cout << "The matrix T in the decomposition of A is:" << endl << schur.matrixT() << endl;
schur.compute(A.inverse());
cout << "The matrix T in the decomposition of A^(-1) is:" << endl << schur.matrixT() << endl;
|
75b294609786098a3c9e130ddfaca086388eedbf71a4bf791782b5eeebda711d | C++ | 307 | 7 | MatrixXf A(MatrixXf::Random(5,3)), thinQ(MatrixXf::Identity(5,3)), Q;
A.setRandom();
HouseholderQR<MatrixXf> qr(A);
Q = qr.householderQ();
thinQ = qr.householderQ() * thinQ;
std::cout << "The complete unitary matrix Q is:\n" << Q << "\n\n";
std::cout << "The thin matrix Q is:\n" << thinQ << "\n\n";
|
6373c509340636e3a757fd45a900ada07adbf1e00d2f856bc553809d15c243e8 | C++ | 309 | 11 | // Used to extract SVE vector register size (in bits)
#include <iostream>
#ifdef __ARM_FEATURE_SVE
#include <arm_sve.h>
inline int sve_length() noexcept { std::cout << svcntb()*8; return 1; }
#else
inline int sve_length() noexcept { std::cout << 16*8; return 0; }
#endif
int main() { return sve_length(); }
|
d1ab4161f30e9fd65609b072aa8c72c4d15ed59a38c05496e5ad8bf5081a31e3 | C++ | 309 | 6 | Matrix4d X = Matrix4d::Random(4,4);
Matrix4d A = X + X.transpose();
cout << "Here is a random symmetric 4x4 matrix:" << endl << A << endl;
Tridiagonalization<Matrix4d> triOfA(A);
Vector3d hc = triOfA.householderCoefficients();
cout << "The vector of Householder coefficients is:" << endl << hc << endl;
|
ad8b2b2555af8f7d6b29b4a740d14e139b94d2fbbee6c528ae43e127d5ae9f81 | C++ | 310 | 11 | MatrixXf M1(3,3); // Column-major storage
M1 << 1, 2, 3,
4, 5, 6,
7, 8, 9;
Map<RowVectorXf> v1(M1.data(), M1.size());
cout << "v1:" << endl << v1 << endl;
Matrix<float,Dynamic,Dynamic,RowMajor> M2(M1);
Map<RowVectorXf> v2(M2.data(), M2.size());
cout << "v2:" << endl << v2 << endl;
|
bd34e7cd7ee89f7146d6c9cef58897c5e64c457afc3b22fe03c1c385d838ce71 | C++ | 310 | 6 | Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.bottomRightCorner<2,Dynamic>(2,2):" << endl;
cout << m.bottomRightCorner<2,Dynamic>(2,2) << endl;
m.bottomRightCorner<2,Dynamic>(2,2).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
2c02b53b5900b4972a5e1e15d7690a9eb9b94cf51c6324a9e0ed38d90e53e22b | C++ | 312 | 16 | #include "../Eigen/Core"
#ifdef EIGEN_SHOULD_FAIL_TO_BUILD
#define CV_QUALIFIER const
#else
#define CV_QUALIFIER
#endif
using namespace Eigen;
void foo(){
MatrixXf m;
CwiseUnaryView<internal::scalar_real_ref_op<double>,CV_QUALIFIER MatrixXf>(m).coeffRef(0, 0) = 1.0f;
}
int main() {}
|
8e7377315db6afccfeba2e8bae31ecb0f18f6f3d215301c97d3045bfc00fa7e1 | C++ | 313 | 15 | #include "gemm_common.h"
#include <Eigen/Cholesky>
EIGEN_DONT_INLINE
void llt(const Mat &A, const Mat &B, Mat &C)
{
C = A;
C.diagonal().array() += 1000;
Eigen::internal::llt_inplace<Mat::Scalar, Lower>::blocked(C);
}
int main(int argc, char **argv)
{
return main_gemm(argc, argv, llt);
}
|
a786a6a080d29b5108ab8e5530cdc3ddafbb6e939f5e1ce4850ec6b4884daceb | C++ | 320 | 15 | #include <iostream>
#include <Eigen/Dense>
using namespace Eigen;
using namespace std;
int main()
{
MatrixXd m = MatrixXd::Random(3,3);
m = (m + MatrixXd::Constant(3,3,1.2)) * 50;
cout << "m =" << endl << m << endl;
VectorXd v(3);
v << 1, 2, 3;
cout << "m * v =" << endl << m * v << endl;
}
|
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