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stringclasses 7
values | repo_name
stringlengths 8
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stringlengths 4
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stringclasses 29
values | file_size
int64 0
84.1M
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int64 0
1.6M
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stringlengths 1
84.1M
⌀ | language
stringclasses 14
values |
|---|---|---|---|---|---|---|---|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_topRows_int.cpp
|
.cpp
| 233
| 7
|
Array44i a = Array44i::Random();
cout << "Here is the array a:" << endl << a << endl;
cout << "Here is a.topRows(2):" << endl;
cout << a.topRows(2) << endl;
a.topRows(2).setZero();
cout << "Now the array a is:" << endl << a << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_block_int_int.cpp
|
.cpp
| 244
| 6
|
Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.block<2,2>(1,1):" << endl << m.block<2,2>(1,1) << endl;
m.block<2,2>(1,1).setZero();
cout << "Now the matrix m is:" << endl << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_applyOnTheRight.cpp
|
.cpp
| 292
| 10
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/EigenSolver_compute.cpp
|
.cpp
| 361
| 7
|
EigenSolver<MatrixXf> es;
MatrixXf A = MatrixXf::Random(4,4);
es.compute(A, /* computeEigenvectors = */ false);
cout << "The eigenvalues of A are: " << es.eigenvalues().transpose() << endl;
es.compute(A + MatrixXf::Identity(4,4), false); // re-use es to compute eigenvalues of A+I
cout << "The eigenvalues of A+I are: " << es.eigenvalues().transpose() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_noalias.cpp
|
.cpp
| 129
| 4
|
Matrix2d a, b, c; a << 1,2,3,4; b << 5,6,7,8;
c.noalias() = a * b; // this computes the product directly to c
cout << c << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/TopicAliasing_block_correct.cpp
|
.cpp
| 270
| 8
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_ones_int.cpp
|
.cpp
| 77
| 3
|
cout << 6 * RowVectorXi::Ones(4) << endl;
cout << VectorXf::Ones(2) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_quotient.cpp
|
.cpp
| 49
| 3
|
Array3d v(2,3,4), w(4,2,3);
cout << v/w << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_end_int.cpp
|
.cpp
| 226
| 6
|
RowVector4i v = RowVector4i::Random();
cout << "Here is the vector v:" << endl << v << endl;
cout << "Here is v.tail(2):" << endl << v.tail(2) << endl;
v.tail(2).setZero();
cout << "Now the vector v is:" << endl << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_homogeneous.cpp
|
.cpp
| 486
| 6
|
Vector3d v = Vector3d::Random(), w;
Projective3d P(Matrix4d::Random());
cout << "v = [" << v.transpose() << "]^T" << endl;
cout << "h.homogeneous() = [" << v.homogeneous().transpose() << "]^T" << endl;
cout << "(P * v.homogeneous()) = [" << (P * v.homogeneous()).transpose() << "]^T" << endl;
cout << "(P * v.homogeneous()).hnormalized() = [" << (P * v.homogeneous()).eval().hnormalized().transpose() << "]^T" << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_tan.cpp
|
.cpp
| 58
| 3
|
Array3d v(M_PI, M_PI/2, M_PI/3);
cout << v.tan() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_setRandom.cpp
|
.cpp
| 72
| 4
|
Matrix4i m = Matrix4i::Zero();
m.col(1).setRandom();
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/LeastSquaresNormalEquations.cpp
|
.cpp
| 192
| 5
|
MatrixXf A = MatrixXf::Random(3, 2);
VectorXf b = VectorXf::Random(3);
cout << "The solution using normal equations is:\n"
<< (A.transpose() * A).ldlt().solve(A.transpose() * b) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_product.cpp
|
.cpp
| 141
| 5
|
Array33i a = Array33i::Random(), b = Array33i::Random();
Array33i c = a * b;
cout << "a:\n" << a << "\nb:\n" << b << "\nc:\n" << c << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/ComplexEigenSolver_compute.cpp
|
.cpp
| 792
| 17
|
MatrixXcf A = MatrixXcf::Random(4,4);
cout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl;
ComplexEigenSolver<MatrixXcf> ces;
ces.compute(A);
cout << "The eigenvalues of A are:" << endl << ces.eigenvalues() << endl;
cout << "The matrix of eigenvectors, V, is:" << endl << ces.eigenvectors() << endl << endl;
complex<float> lambda = ces.eigenvalues()[0];
cout << "Consider the first eigenvalue, lambda = " << lambda << endl;
VectorXcf v = ces.eigenvectors().col(0);
cout << "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
cout << "... and A * v = " << endl << A * v << endl << endl;
cout << "Finally, V * D * V^(-1) = " << endl
<< ces.eigenvectors() * ces.eigenvalues().asDiagonal() * ces.eigenvectors().inverse() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_leftCols.cpp
|
.cpp
| 242
| 7
|
Array44i a = Array44i::Random();
cout << "Here is the array a:" << endl << a << endl;
cout << "Here is a.leftCols<2>():" << endl;
cout << a.leftCols<2>() << endl;
a.leftCols<2>().setZero();
cout << "Now the array a is:" << endl << a << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/PartialRedux_squaredNorm.cpp
|
.cpp
| 180
| 4
|
Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the square norm of each row:" << endl << m.rowwise().squaredNorm() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_isDiagonal.cpp
|
.cpp
| 241
| 7
|
Matrix3d m = 10000 * Matrix3d::Identity();
m(0,2) = 1;
cout << "Here's the matrix m:" << endl << m << endl;
cout << "m.isDiagonal() returns: " << m.isDiagonal() << endl;
cout << "m.isDiagonal(1e-3) returns: " << m.isDiagonal(1e-3) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_commainit_02.cpp
|
.cpp
| 215
| 8
|
int rows=5, cols=5;
MatrixXf m(rows,cols);
m << (Matrix3f() << 1, 2, 3, 4, 5, 6, 7, 8, 9).finished(),
MatrixXf::Zero(3,cols-3),
MatrixXf::Zero(rows-3,3),
MatrixXf::Identity(rows-3,cols-3);
cout << m;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_equal_equal.cpp
|
.cpp
| 52
| 3
|
Array3d v(1,2,3), w(3,2,1);
cout << (v==w) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/HessenbergDecomposition_compute.cpp
|
.cpp
| 339
| 7
|
MatrixXcf A = MatrixXcf::Random(4,4);
HessenbergDecomposition<MatrixXcf> hd(4);
hd.compute(A);
cout << "The matrix H in the decomposition of A is:" << endl << hd.matrixH() << endl;
hd.compute(2*A); // re-use hd to compute and store decomposition of 2A
cout << "The matrix H in the decomposition of 2A is:" << endl << hd.matrixH() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tridiagonalization_householderCoefficients.cpp
|
.cpp
| 303
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_computeInverseWithCheck.cpp
|
.cpp
| 318
| 12
|
Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
Matrix3d inverse;
bool invertible;
m.computeInverseWithCheck(inverse,invertible);
if(invertible) {
cout << "It is invertible, and its inverse is:" << endl << inverse << endl;
}
else {
cout << "It is not invertible." << endl;
}
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_ReshapeMat2Vec.cpp
|
.cpp
| 298
| 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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_AdvancedInitialization_Zero.cpp
|
.cpp
| 332
| 14
|
std::cout << "A fixed-size array:\n";
Array33f a1 = Array33f::Zero();
std::cout << a1 << "\n\n";
std::cout << "A one-dimensional dynamic-size array:\n";
ArrayXf a2 = ArrayXf::Zero(3);
std::cout << a2 << "\n\n";
std::cout << "A two-dimensional dynamic-size array:\n";
ArrayXXf a3 = ArrayXXf::Zero(3, 4);
std::cout << a3 << "\n";
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Matrix_setRandom_int_int.cpp
|
.cpp
| 50
| 4
|
MatrixXf m;
m.setRandom(3, 3);
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_sinh.cpp
|
.cpp
| 64
| 3
|
ArrayXd v = ArrayXd::LinSpaced(5,0,1);
cout << sinh(v) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/HouseholderQR_solve.cpp
|
.cpp
| 357
| 10
|
typedef Matrix<float,3,3> Matrix3x3;
Matrix3x3 m = Matrix3x3::Random();
Matrix3f y = Matrix3f::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the matrix y:" << endl << y << endl;
Matrix3f x;
x = m.householderQr().solve(y);
assert(y.isApprox(m*x));
cout << "Here is a solution x to the equation mx=y:" << endl << x << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_bottomRightCorner_int_int.cpp
|
.cpp
| 274
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_abs.cpp
|
.cpp
| 45
| 3
|
Array3d v(1,-2,-3);
cout << v.abs() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_selfadjointView.cpp
|
.cpp
| 361
| 7
|
Matrix3i m = Matrix3i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the symmetric matrix extracted from the upper part of m:" << endl
<< Matrix3i(m.selfadjointView<Upper>()) << endl;
cout << "Here is the symmetric matrix extracted from the lower part of m:" << endl
<< Matrix3i(m.selfadjointView<Lower>()) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/JacobiSVD_basic.cpp
|
.cpp
| 614
| 10
|
MatrixXf m = MatrixXf::Random(3,2);
cout << "Here is the matrix m:" << endl << m << endl;
JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV);
cout << "Its singular values are:" << endl << svd.singularValues() << endl;
cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl;
cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl;
Vector3f rhs(1, 0, 0);
cout << "Now consider this rhs vector:" << endl << rhs << endl;
cout << "A least-squares solution of m*x = rhs is:" << endl << svd.solve(rhs) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_select.cpp
|
.cpp
| 115
| 7
|
MatrixXi m(3, 3);
m << 1, 2, 3,
4, 5, 6,
7, 8, 9;
m = (m.array() >= 5).select(-m, m);
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_round.cpp
|
.cpp
| 93
| 4
|
ArrayXd v = ArrayXd::LinSpaced(7,-2,2);
cout << v << endl << endl;
cout << round(v) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_identity.cpp
|
.cpp
| 50
| 2
|
cout << Matrix<double, 3, 4>::Identity() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_diagonal_template_int.cpp
|
.cpp
| 274
| 6
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_cos.cpp
|
.cpp
| 58
| 3
|
Array3d v(M_PI, M_PI/2, M_PI/3);
cout << v.cos() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/EigenSolver_pseudoEigenvectors.cpp
|
.cpp
| 430
| 10
|
MatrixXd A = MatrixXd::Random(6,6);
cout << "Here is a random 6x6 matrix, A:" << endl << A << endl << endl;
EigenSolver<MatrixXd> es(A);
MatrixXd D = es.pseudoEigenvalueMatrix();
MatrixXd V = es.pseudoEigenvectors();
cout << "The pseudo-eigenvalue matrix D is:" << endl << D << endl;
cout << "The pseudo-eigenvector matrix V is:" << endl << V << endl;
cout << "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_arg.cpp
|
.cpp
| 85
| 4
|
ArrayXcf v = ArrayXcf::Random(3);
cout << v << endl << endl;
cout << arg(v) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_Map_rowmajor.cpp
|
.cpp
| 299
| 8
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_eval.cpp
|
.cpp
| 467
| 13
|
Matrix2f M = Matrix2f::Random();
Matrix2f m;
m = M;
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Now we want to copy a column into a row." << endl;
cout << "If we do m.col(1) = m.row(0), then m becomes:" << endl;
m.col(1) = m.row(0);
cout << m << endl << "which is wrong!" << endl;
cout << "Now let us instead do m.col(1) = m.row(0).eval(). Then m becomes" << endl;
m = M;
m.col(1) = m.row(0).eval();
cout << m << endl << "which is right." << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_topRows.cpp
|
.cpp
| 239
| 7
|
Array44i a = Array44i::Random();
cout << "Here is the array a:" << endl << a << endl;
cout << "Here is a.topRows<2>():" << endl;
cout << a.topRows<2>() << endl;
a.topRows<2>().setZero();
cout << "Now the array a is:" << endl << a << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_segment_int_int.cpp
|
.cpp
| 244
| 6
|
RowVector4i v = RowVector4i::Random();
cout << "Here is the vector v:" << endl << v << endl;
cout << "Here is v.segment(1, 2):" << endl << v.segment(1, 2) << endl;
v.segment(1, 2).setZero();
cout << "Now the vector v is:" << endl << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/HouseholderSequence_HouseholderSequence.cpp
|
.cpp
| 1,316
| 32
|
Matrix3d v = Matrix3d::Random();
cout << "The matrix v is:" << endl;
cout << v << endl;
Vector3d v0(1, v(1,0), v(2,0));
cout << "The first Householder vector is: v_0 = " << v0.transpose() << endl;
Vector3d v1(0, 1, v(2,1));
cout << "The second Householder vector is: v_1 = " << v1.transpose() << endl;
Vector3d v2(0, 0, 1);
cout << "The third Householder vector is: v_2 = " << v2.transpose() << endl;
Vector3d h = Vector3d::Random();
cout << "The Householder coefficients are: h = " << h.transpose() << endl;
Matrix3d H0 = Matrix3d::Identity() - h(0) * v0 * v0.adjoint();
cout << "The first Householder reflection is represented by H_0 = " << endl;
cout << H0 << endl;
Matrix3d H1 = Matrix3d::Identity() - h(1) * v1 * v1.adjoint();
cout << "The second Householder reflection is represented by H_1 = " << endl;
cout << H1 << endl;
Matrix3d H2 = Matrix3d::Identity() - h(2) * v2 * v2.adjoint();
cout << "The third Householder reflection is represented by H_2 = " << endl;
cout << H2 << endl;
cout << "Their product is H_0 H_1 H_2 = " << endl;
cout << H0 * H1 * H2 << endl;
HouseholderSequence<Matrix3d, Vector3d> hhSeq(v, h);
Matrix3d hhSeqAsMatrix(hhSeq);
cout << "If we construct a HouseholderSequence from v and h" << endl;
cout << "and convert it to a matrix, we get:" << endl;
cout << hhSeqAsMatrix << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/FullPivLU_solve.cpp
|
.cpp
| 413
| 12
|
Matrix<float,2,3> m = Matrix<float,2,3>::Random();
Matrix2f y = Matrix2f::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the matrix y:" << endl << y << endl;
Matrix<float,3,2> x = m.fullPivLu().solve(y);
if((m*x).isApprox(y))
{
cout << "Here is a solution x to the equation mx=y:" << endl << x << endl;
}
else
cout << "The equation mx=y does not have any solution." << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/RealSchur_compute.cpp
|
.cpp
| 343
| 7
|
MatrixXf A = MatrixXf::Random(4,4);
RealSchur<MatrixXf> schur(4);
schur.compute(A, /* computeU = */ false);
cout << "The matrix T in the decomposition of A is:" << endl << schur.matrixT() << endl;
schur.compute(A.inverse(), /* computeU = */ false);
cout << "The matrix T in the decomposition of A^(-1) is:" << endl << schur.matrixT() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_replicate.cpp
|
.cpp
| 170
| 5
|
MatrixXi m = MatrixXi::Random(2,3);
cout << "Here is the matrix m:" << endl << m << endl;
cout << "m.replicate<3,2>() = ..." << endl;
cout << m.replicate<3,2>() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_boolean_or.cpp
|
.cpp
| 64
| 3
|
Array3d v(-1,2,1), w(-3,2,3);
cout << ((v<w) || (v<0)) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_solve_multiple_rhs.cpp
|
.cpp
| 318
| 11
|
Matrix3f A(3,3);
A << 1,2,3, 4,5,6, 7,8,10;
Matrix<float,3,2> B;
B << 3,1, 3,1, 4,1;
Matrix<float,3,2> X;
X = A.fullPivLu().solve(B);
cout << "The solution with right-hand side (3,3,4) is:" << endl;
cout << X.col(0) << endl;
cout << "The solution with right-hand side (1,1,1) is:" << endl;
cout << X.col(1) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_int_block_int_int_int_int.cpp
|
.cpp
| 264
| 6
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_greater.cpp
|
.cpp
| 51
| 3
|
Array3d v(1,2,3), w(3,2,1);
cout << (v>w) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_int_bottomLeftCorner_int_int.cpp
|
.cpp
| 301
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_ceil.cpp
|
.cpp
| 92
| 4
|
ArrayXd v = ArrayXd::LinSpaced(7,-2,2);
cout << v << endl << endl;
cout << ceil(v) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/SelfAdjointEigenSolver_compute_MatrixType2.cpp
|
.cpp
| 396
| 10
|
MatrixXd X = MatrixXd::Random(5,5);
MatrixXd A = X * X.transpose();
X = MatrixXd::Random(5,5);
MatrixXd B = X * X.transpose();
GeneralizedSelfAdjointEigenSolver<MatrixXd> es(A,B,EigenvaluesOnly);
cout << "The eigenvalues of the pencil (A,B) are:" << endl << es.eigenvalues() << endl;
es.compute(B,A,false);
cout << "The eigenvalues of the pencil (B,A) are:" << endl << es.eigenvalues() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/ComplexEigenSolver_eigenvalues.cpp
|
.cpp
| 216
| 5
|
MatrixXcf ones = MatrixXcf::Ones(3,3);
ComplexEigenSolver<MatrixXcf> ces(ones, /* computeEigenvectors = */ false);
cout << "The eigenvalues of the 3x3 matrix of ones are:"
<< endl << ces.eigenvalues() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_col.cpp
|
.cpp
| 82
| 4
|
Matrix3d m = Matrix3d::Identity();
m.col(1) = Vector3d(4,5,6);
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_int_topRightCorner_int_int.cpp
|
.cpp
| 295
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_set.cpp
|
.cpp
| 290
| 14
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_start_int.cpp
|
.cpp
| 226
| 6
|
RowVector4i v = RowVector4i::Random();
cout << "Here is the vector v:" << endl << v << endl;
cout << "Here is v.head(2):" << endl << v.head(2) << endl;
v.head(2).setZero();
cout << "Now the vector v is:" << endl << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/SelfAdjointView_operatorNorm.cpp
|
.cpp
| 157
| 4
|
MatrixXd ones = MatrixXd::Ones(3,3);
cout << "The operator norm of the 3x3 matrix of ones is "
<< ones.selfadjointView<Lower>().operatorNorm() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_asin.cpp
|
.cpp
| 55
| 3
|
Array3d v(0, sqrt(2.)/2, 1);
cout << v.asin() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_int_topLeftCorner_int_int.cpp
|
.cpp
| 292
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/TopicStorageOrders_example.cpp
|
.cpp
| 525
| 19
|
Matrix<int, 3, 4, ColMajor> Acolmajor;
Acolmajor << 8, 2, 2, 9,
9, 1, 4, 4,
3, 5, 4, 5;
cout << "The matrix A:" << endl;
cout << Acolmajor << endl << endl;
cout << "In memory (column-major):" << endl;
for (int i = 0; i < Acolmajor.size(); i++)
cout << *(Acolmajor.data() + i) << " ";
cout << endl << endl;
Matrix<int, 3, 4, RowMajor> Arowmajor = Acolmajor;
cout << "In memory (row-major):" << endl;
for (int i = 0; i < Arowmajor.size(); i++)
cout << *(Arowmajor.data() + i) << " ";
cout << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Matrix_resize_int_int.cpp
|
.cpp
| 407
| 10
|
MatrixXd m(2,3);
m << 1,2,3,4,5,6;
cout << "here's the 2x3 matrix m:" << endl << m << endl;
cout << "let's resize m to 3x2. This is a conservative resizing because 2*3==3*2." << endl;
m.resize(3,2);
cout << "here's the 3x2 matrix m:" << endl << m << endl;
cout << "now let's resize m to size 2x2. This is NOT a conservative resizing, so it becomes uninitialized:" << endl;
m.resize(2,2);
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_cube.cpp
|
.cpp
| 44
| 3
|
Array3d v(2,3,4);
cout << v.cube() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_sqrt.cpp
|
.cpp
| 44
| 3
|
Array3d v(1,2,4);
cout << v.sqrt() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Matrix_setConstant_int.cpp
|
.cpp
| 52
| 4
|
VectorXf v;
v.setConstant(3, 5);
cout << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_asDiagonal.cpp
|
.cpp
| 56
| 2
|
cout << Matrix3i(Vector3i(2,5,6).asDiagonal()) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_cwiseMin.cpp
|
.cpp
| 60
| 3
|
Vector3d v(2,3,4), w(4,2,3);
cout << v.cwiseMin(w) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_bottomRows_int.cpp
|
.cpp
| 242
| 7
|
Array44i a = Array44i::Random();
cout << "Here is the array a:" << endl << a << endl;
cout << "Here is a.bottomRows(2):" << endl;
cout << a.bottomRows(2) << endl;
a.bottomRows(2).setZero();
cout << "Now the array a is:" << endl << a << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_sign.cpp
|
.cpp
| 45
| 3
|
Array3d v(-3,5,0);
cout << v.sign() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Map_placement_new.cpp
|
.cpp
| 182
| 5
|
int data[] = {1,2,3,4,5,6,7,8,9};
Map<RowVectorXi> v(data,4);
cout << "The mapped vector v is: " << v << "\n";
new (&v) Map<RowVectorXi>(data+4,5);
cout << "Now v is: " << v << "\n";
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/HessenbergDecomposition_matrixH.cpp
|
.cpp
| 391
| 9
|
Matrix4f A = MatrixXf::Random(4,4);
cout << "Here is a random 4x4 matrix:" << endl << A << endl;
HessenbergDecomposition<MatrixXf> hessOfA(A);
MatrixXf H = hessOfA.matrixH();
cout << "The Hessenberg matrix H is:" << endl << H << endl;
MatrixXf Q = hessOfA.matrixQ();
cout << "The orthogonal matrix Q is:" << endl << Q << endl;
cout << "Q H Q^T is:" << endl << Q * H * Q.transpose() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_isUnitary.cpp
|
.cpp
| 231
| 6
|
Matrix3d m = Matrix3d::Identity();
m(0,2) = 1e-4;
cout << "Here's the matrix m:" << endl << m << endl;
cout << "m.isUnitary() returns: " << m.isUnitary() << endl;
cout << "m.isUnitary(1e-3) returns: " << m.isUnitary(1e-3) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/TopicAliasing_mult3.cpp
|
.cpp
| 86
| 5
|
MatrixXf matA(2,2);
matA << 2, 0, 0, 2;
matA.noalias() = matA * matA;
cout << matA;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/PartialRedux_prod.cpp
|
.cpp
| 169
| 4
|
Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the product of each row:" << endl << m.rowwise().prod() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_random.cpp
|
.cpp
| 42
| 2
|
cout << 100 * Matrix2i::Random() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/SelfAdjointEigenSolver_compute_MatrixType.cpp
|
.cpp
| 365
| 8
|
SelfAdjointEigenSolver<MatrixXf> es(4);
MatrixXf X = MatrixXf::Random(4,4);
MatrixXf A = X + X.transpose();
es.compute(A);
cout << "The eigenvalues of A are: " << es.eigenvalues().transpose() << endl;
es.compute(A + MatrixXf::Identity(4,4)); // re-use es to compute eigenvalues of A+I
cout << "The eigenvalues of A+I are: " << es.eigenvalues().transpose() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_start.cpp
|
.cpp
| 230
| 6
|
RowVector4i v = RowVector4i::Random();
cout << "Here is the vector v:" << endl << v << endl;
cout << "Here is v.head(2):" << endl << v.head<2>() << endl;
v.head<2>().setZero();
cout << "Now the vector v is:" << endl << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp
|
.cpp
| 816
| 18
|
MatrixXd X = MatrixXd::Random(5,5);
MatrixXd A = X + X.transpose();
cout << "Here is a random symmetric 5x5 matrix, A:" << endl << A << endl << endl;
SelfAdjointEigenSolver<MatrixXd> es(A);
cout << "The eigenvalues of A are:" << endl << es.eigenvalues() << endl;
cout << "The matrix of eigenvectors, V, is:" << endl << es.eigenvectors() << endl << endl;
double lambda = es.eigenvalues()[0];
cout << "Consider the first eigenvalue, lambda = " << lambda << endl;
VectorXd v = es.eigenvectors().col(0);
cout << "If v is the corresponding eigenvector, then lambda * v = " << endl << lambda * v << endl;
cout << "... and A * v = " << endl << A * v << endl << endl;
MatrixXd D = es.eigenvalues().asDiagonal();
MatrixXd V = es.eigenvectors();
cout << "Finally, V * D * V^(-1) = " << endl << V * D * V.inverse() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_cwiseMax.cpp
|
.cpp
| 60
| 3
|
Vector3d v(2,3,4), w(4,2,3);
cout << v.cwiseMax(w) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_colwise.cpp
|
.cpp
| 287
| 6
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_times_equal.cpp
|
.cpp
| 55
| 4
|
Array3d v(1,2,3), w(2,3,0);
v *= w;
cout << v << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_SlicingCol.cpp
|
.cpp
| 610
| 11
|
MatrixXf M1 = MatrixXf::Random(3,8);
cout << "Column major input:" << endl << M1 << "\n";
Map<MatrixXf,0,OuterStride<> > M2(M1.data(), M1.rows(), (M1.cols()+2)/3, OuterStride<>(M1.outerStride()*3));
cout << "1 column over 3:" << endl << M2 << "\n";
typedef Matrix<float,Dynamic,Dynamic,RowMajor> RowMajorMatrixXf;
RowMajorMatrixXf M3(M1);
cout << "Row major input:" << endl << M3 << "\n";
Map<RowMajorMatrixXf,0,Stride<Dynamic,3> > M4(M3.data(), M3.rows(), (M3.cols()+2)/3,
Stride<Dynamic,3>(M3.outerStride(),3));
cout << "1 column over 3:" << endl << M4 << "\n";
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_isFinite.cpp
|
.cpp
| 104
| 6
|
Array3d v(1,2,3);
v(1) *= 0.0/0.0;
v(2) /= 0.0;
cout << v << endl << endl;
cout << isfinite(v) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_zero_int.cpp
|
.cpp
| 73
| 3
|
cout << RowVectorXi::Zero(4) << endl;
cout << VectorXf::Zero(2) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_solve_triangular.cpp
|
.cpp
| 273
| 9
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_commainit_01.cpp
|
.cpp
| 70
| 6
|
Matrix3f m;
m << 1, 2, 3,
4, 5, 6,
7, 8, 9;
std::cout << m;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/IOFormat.cpp
|
.cpp
| 603
| 15
|
std::string sep = "\n----------------------------------------\n";
Matrix3d m1;
m1 << 1.111111, 2, 3.33333, 4, 5, 6, 7, 8.888888, 9;
IOFormat CommaInitFmt(StreamPrecision, DontAlignCols, ", ", ", ", "", "", " << ", ";");
IOFormat CleanFmt(4, 0, ", ", "\n", "[", "]");
IOFormat OctaveFmt(StreamPrecision, 0, ", ", ";\n", "", "", "[", "]");
IOFormat HeavyFmt(FullPrecision, 0, ", ", ";\n", "[", "]", "[", "]");
std::cout << m1 << sep;
std::cout << m1.format(CommaInitFmt) << sep;
std::cout << m1.format(CleanFmt) << sep;
std::cout << m1.format(OctaveFmt) << sep;
std::cout << m1.format(HeavyFmt) << sep;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Cwise_minus.cpp
|
.cpp
| 39
| 3
|
Array3d v(1,2,3);
cout << v-5 << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Matrix_setZero_int_int.cpp
|
.cpp
| 48
| 4
|
MatrixXf m;
m.setZero(3, 3);
cout << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.cpp
|
.cpp
| 826
| 17
|
MatrixXd X = MatrixXd::Random(5,5);
MatrixXd A = X + X.transpose();
cout << "Here is a random symmetric matrix, A:" << endl << A << endl;
X = MatrixXd::Random(5,5);
MatrixXd B = X * X.transpose();
cout << "and a random postive-definite matrix, B:" << endl << B << endl << endl;
GeneralizedSelfAdjointEigenSolver<MatrixXd> es(A,B);
cout << "The eigenvalues of the pencil (A,B) are:" << endl << es.eigenvalues() << endl;
cout << "The matrix of eigenvectors, V, is:" << endl << es.eigenvectors() << endl << endl;
double lambda = es.eigenvalues()[0];
cout << "Consider the first eigenvalue, lambda = " << lambda << endl;
VectorXd v = es.eigenvectors().col(0);
cout << "If v is the corresponding eigenvector, then A * v = " << endl << A * v << endl;
cout << "... and lambda * B * v = " << endl << lambda * B * v << endl << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/DenseBase_LinSpaced.cpp
|
.cpp
| 117
| 3
|
cout << VectorXi::LinSpaced(4,7,10).transpose() << endl;
cout << VectorXd::LinSpaced(5,0.0,1.0).transpose() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/ComplexSchur_matrixU.cpp
|
.cpp
| 221
| 5
|
MatrixXcf A = MatrixXcf::Random(4,4);
cout << "Here is a random 4x4 matrix, A:" << endl << A << endl << endl;
ComplexSchur<MatrixXcf> schurOfA(A);
cout << "The unitary matrix U is:" << endl << schurOfA.matrixU() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Vectorwise_reverse.cpp
|
.cpp
| 536
| 11
|
MatrixXi m = MatrixXi::Random(3,4);
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the rowwise reverse of m:" << endl << m.rowwise().reverse() << endl;
cout << "Here is the colwise reverse of m:" << endl << m.colwise().reverse() << endl;
cout << "Here is the coefficient (1,0) in the rowise reverse of m:" << endl
<< m.rowwise().reverse()(1,0) << endl;
cout << "Let us overwrite this coefficient with the value 4." << endl;
//m.colwise().reverse()(1,0) = 4;
cout << "Now the matrix m is:" << endl << m << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_template_int_int_bottomLeftCorner.cpp
|
.cpp
| 274
| 7
|
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;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_isZero.cpp
|
.cpp
| 215
| 6
|
Matrix3d m = Matrix3d::Zero();
m(0,2) = 1e-4;
cout << "Here's the matrix m:" << endl << m << endl;
cout << "m.isZero() returns: " << m.isZero() << endl;
cout << "m.isZero(1e-3) returns: " << m.isZero(1e-3) << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tutorial_SlicingVec.cpp
|
.cpp
| 179
| 4
|
RowVectorXf v = RowVectorXf::LinSpaced(20,0,19);
cout << "Input:" << endl << v << endl;
Map<RowVectorXf,0,InnerStride<2> > v2(v.data(), v.size()/2);
cout << "Even:" << v2 << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/MatrixBase_cast.cpp
|
.cpp
| 119
| 4
|
Matrix2d md = Matrix2d::Identity() * 0.45;
Matrix2f mf = Matrix2f::Identity();
cout << md + mf.cast<double>() << endl;
|
C++
|
2D
|
JaeHyunLee94/mpm2d
|
external/eigen-3.3.9/doc/snippets/Tridiagonalization_decomposeInPlace.cpp
|
.cpp
| 475
| 11
|
MatrixXd X = MatrixXd::Random(5,5);
MatrixXd A = X + X.transpose();
cout << "Here is a random symmetric 5x5 matrix:" << endl << A << endl << endl;
VectorXd diag(5);
VectorXd subdiag(4);
internal::tridiagonalization_inplace(A, diag, subdiag, true);
cout << "The orthogonal matrix Q is:" << endl << A << endl;
cout << "The diagonal of the tridiagonal matrix T is:" << endl << diag << endl;
cout << "The subdiagonal of the tridiagonal matrix T is:" << endl << subdiag << endl;
|
C++
|
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