|
@@ -0,0 +1,623 @@
|
|
|
+#include <Eigen/Dense>
|
|
|
+#include <Eigen/Sparse>
|
|
|
+
|
|
|
+#include "python.h"
|
|
|
+
|
|
|
+/// Creates Python bindings for a dynamic Eigen matrix
|
|
|
+template <typename Type>
|
|
|
+py::class_<Type> bind_eigen_2(py::module &m, const char *name,
|
|
|
+ py::object parent = py::object()) {
|
|
|
+ typedef typename Type::Scalar Scalar;
|
|
|
+
|
|
|
+ /* Many Eigen functions are templated and can't easily be referenced using
|
|
|
+ a function pointer, thus a big portion of the binding code below
|
|
|
+ instantiates Eigen code using small anonymous wrapper functions */
|
|
|
+ py::class_<Type> matrix(m, name, parent);
|
|
|
+
|
|
|
+ matrix
|
|
|
+ /* Constructors */
|
|
|
+ .def(py::init<>())
|
|
|
+ .def(py::init<size_t, size_t>())
|
|
|
+ .def("__init__", [](Type &m, Scalar f) {
|
|
|
+ new (&m) Type(1, 1);
|
|
|
+ m(0, 0) = f;
|
|
|
+ })
|
|
|
+ .def("__init__", [](Type &m, std::vector<std::vector< Scalar> >& b) {
|
|
|
+ if (b.size() == 0)
|
|
|
+ {
|
|
|
+ new (&m) Type(0, 0);
|
|
|
+ return;
|
|
|
+ }
|
|
|
+
|
|
|
+ // Size checks
|
|
|
+ unsigned rows = b.size();
|
|
|
+ unsigned cols = b[0].size();
|
|
|
+ for (unsigned i=0;i<rows;++i)
|
|
|
+ if (b[i].size() != cols)
|
|
|
+ throw std::runtime_error("All rows should have the same size!");
|
|
|
+
|
|
|
+ new (&m) Type(rows, cols);
|
|
|
+
|
|
|
+ m.resize(rows,cols);
|
|
|
+ for (unsigned i=0;i<rows;++i)
|
|
|
+ for (unsigned j=0;j<cols;++j)
|
|
|
+ m(i,j) = b[i][j];
|
|
|
+
|
|
|
+ return;
|
|
|
+ })
|
|
|
+ .def("__init__", [](Type &m, py::buffer b) {
|
|
|
+ py::buffer_info info = b.request();
|
|
|
+ if (info.format != py::format_descriptor<Scalar>::value())
|
|
|
+ throw std::runtime_error("Incompatible buffer format!");
|
|
|
+ if (info.ndim == 1) {
|
|
|
+ new (&m) Type(info.shape[0], 1);
|
|
|
+ memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ } else if (info.ndim == 2) {
|
|
|
+ if (info.strides[0] == sizeof(Scalar)) {
|
|
|
+ new (&m) Type(info.shape[0], info.shape[1]);
|
|
|
+ memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ } else {
|
|
|
+ new (&m) Type(info.shape[1], info.shape[0]);
|
|
|
+ memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ m.transposeInPlace();
|
|
|
+ }
|
|
|
+ } else {
|
|
|
+ throw std::runtime_error("Incompatible buffer dimension!");
|
|
|
+ }
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Size query functions */
|
|
|
+ .def("size", [](const Type &m) { return m.size(); })
|
|
|
+ .def("cols", [](const Type &m) { return m.cols(); })
|
|
|
+ .def("rows", [](const Type &m) { return m.rows(); })
|
|
|
+
|
|
|
+ /* Extract rows and colums */
|
|
|
+ .def("col", [](const Type &m, int i) {
|
|
|
+ if (i<0 || i>=m.cols())
|
|
|
+ throw std::runtime_error("Column index out of bound.");
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(m.col(i));
|
|
|
+ })
|
|
|
+ .def("row", [](const Type &m, int i) {
|
|
|
+ if (i<0 || i>=m.rows())
|
|
|
+ throw std::runtime_error("Row index out of bound.");
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(m.row(i));
|
|
|
+ })
|
|
|
+
|
|
|
+
|
|
|
+ /* Initialization */
|
|
|
+ .def("setZero", [](Type &m) { m.setZero(); })
|
|
|
+ .def("setIdentity", [](Type &m) { m.setIdentity(); })
|
|
|
+ .def("setConstant", [](Type &m, Scalar value) { m.setConstant(value); })
|
|
|
+ .def("setRandom", [](Type &m) { m.setRandom(); })
|
|
|
+
|
|
|
+ .def("setZero", [](Type &m, const int& r, const int& c) { m.setZero(r,c); })
|
|
|
+ .def("setIdentity", [](Type &m, const int& r, const int& c) { m.setIdentity(r,c); })
|
|
|
+ .def("setConstant", [](Type &m, const int& r, const int& c, Scalar value) { m.setConstant(r,c,value); })
|
|
|
+ .def("setRandom", [](Type &m, const int& r, const int& c) { m.setRandom(r,c); })
|
|
|
+
|
|
|
+ .def("setCol", [](Type &m, int i, const Type& v) { m.col(i) = v; })
|
|
|
+ .def("setRow", [](Type &m, int i, const Type& v) { m.row(i) = v; })
|
|
|
+
|
|
|
+
|
|
|
+ .def("rightCols", [](Type &m, const int& k) { return Type(m.rightCols(k)); })
|
|
|
+ .def("leftCols", [](Type &m, const int& k) { return Type(m.leftCols(k)); })
|
|
|
+
|
|
|
+ .def("topRows", [](Type &m, const int& k) { return Type(m.topRows(k)); })
|
|
|
+ .def("bottomRows", [](Type &m, const int& k) { return Type(m.bottomRows(k)); })
|
|
|
+
|
|
|
+ .def("topLeftCorner", [](Type &m, const int& p, const int&q) { return Type(m.topLeftCorner(p,q)); })
|
|
|
+ .def("bottomLeftCorner", [](Type &m, const int& p, const int&q) { return Type(m.bottomLeftCorner(p,q)); })
|
|
|
+ .def("topRightCorner", [](Type &m, const int& p, const int&q) { return Type(m.topRightCorner(p,q)); })
|
|
|
+ .def("bottomRightCorner", [](Type &m, const int& p, const int&q) { return Type(m.bottomRightCorner(p,q)); })
|
|
|
+
|
|
|
+ /* Resizing */
|
|
|
+ .def("resize", [](Type &m, size_t s0, size_t s1) { m.resize(s0, s1); })
|
|
|
+ .def("resizeLike", [](Type &m, const Type &m2) { m.resizeLike(m2); })
|
|
|
+ .def("conservativeResize", [](Type &m, size_t s0, size_t s1) { m.conservativeResize(s0, s1); })
|
|
|
+
|
|
|
+
|
|
|
+ .def("mean", [](const Type &m) {return m.mean();})
|
|
|
+
|
|
|
+ .def("sum", [](const Type &m) {return m.sum();})
|
|
|
+ .def("prod", [](const Type &m) {return m.prod();})
|
|
|
+ .def("trace", [](const Type &m) {return m.trace();})
|
|
|
+ .def("norm", [](const Type &m) {return m.norm();})
|
|
|
+ .def("squaredNorm", [](const Type &m) {return m.squaredNorm();})
|
|
|
+
|
|
|
+ .def("minCoeff", [](const Type &m) {return m.minCoeff();} )
|
|
|
+ .def("maxCoeff", [](const Type &m) {return m.maxCoeff();} )
|
|
|
+
|
|
|
+ .def("castdouble", [](const Type &m) {return Eigen::MatrixXd(m.template cast<double>());})
|
|
|
+ .def("castint", [](const Type &m) {return Eigen::MatrixXi(m.template cast<int>());})
|
|
|
+
|
|
|
+ /* Component-wise operations */
|
|
|
+ .def("cwiseAbs", &Type::cwiseAbs)
|
|
|
+ .def("cwiseAbs2", &Type::cwiseAbs2)
|
|
|
+ .def("cwiseSqrt", &Type::cwiseSqrt)
|
|
|
+ .def("cwiseInverse", &Type::cwiseInverse)
|
|
|
+ .def("cwiseMin", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseMin(m2); })
|
|
|
+ .def("cwiseMax", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseMax(m2); })
|
|
|
+ .def("cwiseMin", [](const Type &m1, Scalar s) -> Type { return m1.cwiseMin(s); })
|
|
|
+ .def("cwiseMax", [](const Type &m1, Scalar s) -> Type { return m1.cwiseMax(s); })
|
|
|
+ .def("cwiseProduct", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseProduct(m2); })
|
|
|
+ .def("cwiseQuotient", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseQuotient(m2); })
|
|
|
+
|
|
|
+ /* Row and column-wise operations */
|
|
|
+ .def("rowwiseSum", [](const Type &m) {return Type(m.rowwise().sum());} )
|
|
|
+ .def("rowwiseProd", [](const Type &m) {return Type(m.rowwise().prod());} )
|
|
|
+ .def("rowwiseMean", [](const Type &m) {return Type(m.rowwise().mean());} )
|
|
|
+ .def("rowwiseNorm", [](const Type &m) {return Type(m.rowwise().norm());} )
|
|
|
+ .def("rowwiseNormalized", [](const Type &m) {return Type(m.rowwise().normalized());} )
|
|
|
+ .def("rowwiseMinCoeff", [](const Type &m) {return Type(m.rowwise().minCoeff());} )
|
|
|
+ .def("rowwiseMaxCoeff", [](const Type &m) {return Type(m.rowwise().maxCoeff());} )
|
|
|
+
|
|
|
+ .def("colwiseSum", [](const Type &m) {return Type(m.colwise().sum());} )
|
|
|
+ .def("colwiseProd", [](const Type &m) {return Type(m.colwise().prod());} )
|
|
|
+ .def("colwiseMean", [](const Type &m) {return Type(m.colwise().mean());} )
|
|
|
+ .def("colwiseNorm", [](const Type &m) {return Type(m.colwise().norm());} )
|
|
|
+ .def("colwiseMinCoeff", [](const Type &m) {return Type(m.colwise().minCoeff());} )
|
|
|
+ .def("colwiseMaxCoeff", [](const Type &m) {return Type(m.colwise().maxCoeff());} )
|
|
|
+
|
|
|
+ .def("replicate", [](const Type &m, const int& r, const int& c) {return Type(m.replicate(r,c));} )
|
|
|
+ .def("asDiagonal", [](const Type &m) {return Eigen::DiagonalMatrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(m.asDiagonal());} )
|
|
|
+
|
|
|
+ .def("sparseView", [](Type &m) { return Eigen::SparseMatrix<Scalar>(m.sparseView()); })
|
|
|
+
|
|
|
+ /* Arithmetic operators (def_cast forcefully casts the result back to a
|
|
|
+ Type to avoid type issues with Eigen's crazy expression templates) */
|
|
|
+ .def_cast(-py::self)
|
|
|
+ .def_cast(py::self + py::self)
|
|
|
+ .def_cast(py::self - py::self)
|
|
|
+ .def_cast(py::self * py::self)
|
|
|
+ // .def_cast(py::self - Scalar())
|
|
|
+ // .def_cast(py::self * Scalar())
|
|
|
+ // .def_cast(py::self / Scalar())
|
|
|
+
|
|
|
+ .def("__mul__", []
|
|
|
+ (const Type &a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a * b);
|
|
|
+ })
|
|
|
+ .def("__rmul__", [](const Type& a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b * a);
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__add__", []
|
|
|
+ (const Type &a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a.array() + b);
|
|
|
+ })
|
|
|
+ .def("__radd__", [](const Type& a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b + a.array());
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__sub__", []
|
|
|
+ (const Type &a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a.array() - b);
|
|
|
+ })
|
|
|
+ .def("__rsub__", [](const Type& a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b - a.array());
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__div__", []
|
|
|
+ (const Type &a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a / b);
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__truediv__", []
|
|
|
+ (const Type &a, const Scalar& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a / b);
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Arithmetic in-place operators */
|
|
|
+ .def_cast(py::self += py::self)
|
|
|
+ .def_cast(py::self -= py::self)
|
|
|
+ .def_cast(py::self *= py::self)
|
|
|
+ // .def_cast(py::self *= Scalar())
|
|
|
+ // .def_cast(py::self /= Scalar())
|
|
|
+
|
|
|
+ /* Comparison operators */
|
|
|
+ .def(py::self == py::self)
|
|
|
+ .def(py::self != py::self)
|
|
|
+
|
|
|
+ .def("transposeInPlace", [](Type &m) { m.transposeInPlace(); })
|
|
|
+ /* Other transformations */
|
|
|
+ .def("transpose", [](Type &m) -> Type { return m.transpose(); })
|
|
|
+ /* Python protocol implementations */
|
|
|
+ .def("__repr__", [](const Type &v) {
|
|
|
+ std::ostringstream oss;
|
|
|
+ oss << v;
|
|
|
+ return oss.str();
|
|
|
+ })
|
|
|
+ .def("__getitem__", [](const Type &m, std::pair<size_t, size_t> i) {
|
|
|
+ if (i.first >= (size_t) m.rows() || i.second >= (size_t) m.cols())
|
|
|
+ throw py::index_error();
|
|
|
+ return m(i.first, i.second);
|
|
|
+ })
|
|
|
+ .def("__setitem__", [](Type &m, std::pair<size_t, size_t> i, Scalar v) {
|
|
|
+ if (i.first >= (size_t) m.rows() || i.second >= (size_t) m.cols())
|
|
|
+ throw py::index_error();
|
|
|
+ m(i.first, i.second) = v;
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Buffer access for interacting with NumPy */
|
|
|
+ .def_buffer([](Type &m) -> py::buffer_info {
|
|
|
+ return py::buffer_info(
|
|
|
+ m.data(), /* Pointer to buffer */
|
|
|
+ sizeof(Scalar), /* Size of one scalar */
|
|
|
+ /* Python struct-style format descriptor */
|
|
|
+ py::format_descriptor<Scalar>::value(),
|
|
|
+ 2, /* Number of dimensions */
|
|
|
+ { (size_t) m.rows(), /* Buffer dimensions */
|
|
|
+ (size_t) m.cols() },
|
|
|
+ { sizeof(Scalar), /* Strides (in bytes) for each index */
|
|
|
+ sizeof(Scalar) * m.rows() }
|
|
|
+ );
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Static initializers */
|
|
|
+ .def_static("Zero", [](size_t n, size_t m) { return Type(Type::Zero(n, m)); })
|
|
|
+ .def_static("Random", [](size_t n, size_t m) { return Type(Type::Random(n, m)); })
|
|
|
+ .def_static("Ones", [](size_t n, size_t m) { return Type(Type::Ones(n, m)); })
|
|
|
+ .def_static("Constant", [](size_t n, size_t m, Scalar value) { return Type(Type::Constant(n, m, value)); })
|
|
|
+ .def_static("Identity", [](size_t n, size_t m) { return Type(Type::Identity(n, m)); })
|
|
|
+ .def("MapMatrix", [](const Type& m, size_t r, size_t c)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(Eigen::Map<const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>>(m.data(),r,c));
|
|
|
+ })
|
|
|
+ ;
|
|
|
+ return matrix;
|
|
|
+}
|
|
|
+
|
|
|
+/// Creates Python bindings for a dynamic Eigen sparse order-2 tensor (i.e. a matrix)
|
|
|
+template <typename Type>
|
|
|
+py::class_<Type> bind_eigen_sparse_2(py::module &m, const char *name,
|
|
|
+ py::object parent = py::object()) {
|
|
|
+ typedef typename Type::Scalar Scalar;
|
|
|
+
|
|
|
+ /* Many Eigen functions are templated and can't easily be referenced using
|
|
|
+ a function pointer, thus a big portion of the binding code below
|
|
|
+ instantiates Eigen code using small anonymous wrapper functions */
|
|
|
+ py::class_<Type> matrix(m, name, parent);
|
|
|
+
|
|
|
+ matrix
|
|
|
+ /* Constructors */
|
|
|
+ .def(py::init<>())
|
|
|
+ .def(py::init<size_t, size_t>())
|
|
|
+ // .def("__init__", [](Type &m, Scalar f) {
|
|
|
+ // new (&m) Type(1, 1);
|
|
|
+ // m(0, 0) = f;
|
|
|
+ // })
|
|
|
+ // .def("__init__", [](Type &m, py::buffer b) {
|
|
|
+ // py::buffer_info info = b.request();
|
|
|
+ // if (info.format != py::format_descriptor<Scalar>::value())
|
|
|
+ // throw std::runtime_error("Incompatible buffer format!");
|
|
|
+ // if (info.ndim == 1) {
|
|
|
+ // new (&m) Type(info.shape[0], 1);
|
|
|
+ // memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ // } else if (info.ndim == 2) {
|
|
|
+ // if (info.strides[0] == sizeof(Scalar)) {
|
|
|
+ // new (&m) Type(info.shape[0], info.shape[1]);
|
|
|
+ // memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ // } else {
|
|
|
+ // new (&m) Type(info.shape[1], info.shape[0]);
|
|
|
+ // memcpy(m.data(), info.ptr, sizeof(Scalar) * m.size());
|
|
|
+ // m.transposeInPlace();
|
|
|
+ // }
|
|
|
+ // } else {
|
|
|
+ // throw std::runtime_error("Incompatible buffer dimension!");
|
|
|
+ // }
|
|
|
+ // })
|
|
|
+
|
|
|
+ /* Size query functions */
|
|
|
+ .def("size", [](const Type &m) { return m.size(); })
|
|
|
+ .def("cols", [](const Type &m) { return m.cols(); })
|
|
|
+ .def("rows", [](const Type &m) { return m.rows(); })
|
|
|
+
|
|
|
+ /* Initialization */
|
|
|
+ .def("setZero", [](Type &m) { m.setZero(); })
|
|
|
+ .def("setIdentity", [](Type &m) { m.setIdentity(); })
|
|
|
+
|
|
|
+ .def("transpose", [](Type &m) { return Type(m.transpose()); })
|
|
|
+ .def("norm", [](Type &m) { return m.norm(); })
|
|
|
+
|
|
|
+ /* Resizing */
|
|
|
+ // .def("resize", [](Type &m, size_t s0, size_t s1) { m.resize(s0, s1); })
|
|
|
+ // .def("resizeLike", [](Type &m, const Type &m2) { m.resizeLike(m2); })
|
|
|
+ // .def("conservativeResize", [](Type &m, size_t s0, size_t s1) { m.conservativeResize(s0, s1); })
|
|
|
+
|
|
|
+ /* Component-wise operations */
|
|
|
+ // .def("cwiseAbs", &Type::cwiseAbs)
|
|
|
+ // .def("cwiseAbs2", &Type::cwiseAbs2)
|
|
|
+ // .def("cwiseSqrt", &Type::cwiseSqrt)
|
|
|
+ // .def("cwiseInverse", &Type::cwiseInverse)
|
|
|
+ // .def("cwiseMin", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseMin(m2); })
|
|
|
+ // .def("cwiseMax", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseMax(m2); })
|
|
|
+ // .def("cwiseMin", [](const Type &m1, Scalar s) -> Type { return m1.cwiseMin(s); })
|
|
|
+ // .def("cwiseMax", [](const Type &m1, Scalar s) -> Type { return m1.cwiseMax(s); })
|
|
|
+ // .def("cwiseProduct", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseProduct(m2); })
|
|
|
+ // .def("cwiseQuotient", [](const Type &m1, const Type &m2) -> Type { return m1.cwiseQuotient(m2); })
|
|
|
+
|
|
|
+ /* Arithmetic operators (def_cast forcefully casts the result back to a
|
|
|
+ Type to avoid type issues with Eigen's crazy expression templates) */
|
|
|
+ .def_cast(-py::self)
|
|
|
+ .def_cast(py::self + py::self)
|
|
|
+ .def_cast(py::self - py::self)
|
|
|
+ .def_cast(py::self * py::self)
|
|
|
+ .def_cast(py::self * Scalar())
|
|
|
+ .def_cast(Scalar() * py::self)
|
|
|
+ // Special case, sparse * dense produces a dense matrix
|
|
|
+
|
|
|
+ // .def("__mul__", []
|
|
|
+ // (const Type &a, const Scalar& b)
|
|
|
+ // {
|
|
|
+ // return Type(a * b);
|
|
|
+ // })
|
|
|
+ // .def("__rmul__", [](const Type& a, const Scalar& b)
|
|
|
+ // {
|
|
|
+ // return Type(b * a);
|
|
|
+ // })
|
|
|
+
|
|
|
+ .def("__mul__", []
|
|
|
+ (const Type &a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a * b);
|
|
|
+ })
|
|
|
+ .def("__rmul__", [](const Type& a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b * a);
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__mul__", []
|
|
|
+ (const Type &a, const Eigen::DiagonalMatrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Type(a * b);
|
|
|
+ })
|
|
|
+ .def("__rmul__", [](const Type& a, const Eigen::DiagonalMatrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Type(b * a);
|
|
|
+ })
|
|
|
+
|
|
|
+ //.def(py::self * Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>())
|
|
|
+// .def_cast(py::self / Scalar())
|
|
|
+
|
|
|
+ /* Arithmetic in-place operators */
|
|
|
+ // .def_cast(py::self += py::self)
|
|
|
+ // .def_cast(py::self -= py::self)
|
|
|
+ // .def_cast(py::self *= py::self)
|
|
|
+ // .def_cast(py::self *= Scalar())
|
|
|
+ // .def_cast(py::self /= Scalar())
|
|
|
+
|
|
|
+ /* Comparison operators */
|
|
|
+ // .def(py::self == py::self)
|
|
|
+ // .def(py::self != py::self)
|
|
|
+
|
|
|
+ // .def("transposeInPlace", [](Type &m) { m.transposeInPlace(); })
|
|
|
+ // /* Other transformations */
|
|
|
+ // .def("transpose", [](Type &m) -> Type { return m.transpose(); })
|
|
|
+
|
|
|
+ /* Python protocol implementations */
|
|
|
+ .def("__repr__", [](const Type &v) {
|
|
|
+ std::ostringstream oss;
|
|
|
+ oss << v;
|
|
|
+ return oss.str();
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Static initializers */
|
|
|
+ // .def_static("Zero", [](size_t n, size_t m) { return Type(Type::Zero(n, m)); })
|
|
|
+ // .def_static("Ones", [](size_t n, size_t m) { return Type(Type::Ones(n, m)); })
|
|
|
+ // .def_static("Constant", [](size_t n, size_t m, Scalar value) { return Type(Type::Constant(n, m, value)); })
|
|
|
+ // .def_static("Identity", [](size_t n, size_t m) { return Type(Type::Identity(n, m)); })
|
|
|
+ .def("toCOO",[](const Type& m)
|
|
|
+ {
|
|
|
+ Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic> t(m.nonZeros(),3);
|
|
|
+ int count = 0;
|
|
|
+ for (int k=0; k<m.outerSize(); ++k)
|
|
|
+ for (typename Type::InnerIterator it(m,k); it; ++it)
|
|
|
+ t.row(count++) << it.row(), it.col(), it.value();
|
|
|
+ return t;
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("fromCOO",[](Type& m, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& t, int rows, int cols)
|
|
|
+ {
|
|
|
+ typedef Eigen::Triplet<Scalar> T;
|
|
|
+ std::vector<T> tripletList;
|
|
|
+ tripletList.reserve(t.rows());
|
|
|
+ for(unsigned i=0;i<t.rows();++i)
|
|
|
+ tripletList.push_back(T(round(t(i,0)),round(t(i,1)),t(i,2)));
|
|
|
+
|
|
|
+ if (rows == -1)
|
|
|
+ rows = t.col(0).maxCoeff()+1;
|
|
|
+
|
|
|
+ if (cols == -1)
|
|
|
+ cols = t.col(1).maxCoeff()+1;
|
|
|
+
|
|
|
+ m.resize(rows,cols);
|
|
|
+ m.setFromTriplets(tripletList.begin(), tripletList.end());
|
|
|
+ }, py::arg("t"), py::arg("rows") = -1, py::arg("cols") = -1)
|
|
|
+
|
|
|
+ .def("insert",[](Type& m, const int row, const int col, const Scalar value)
|
|
|
+ {
|
|
|
+ return m.insert(row,col) = value;
|
|
|
+ }, py::arg("row"), py::arg("col"), py::arg("value"))
|
|
|
+
|
|
|
+ .def("makeCompressed",[](Type& m)
|
|
|
+ {
|
|
|
+ return m.makeCompressed();
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("diagonal", [](const Type &m) {return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(m.diagonal());} )
|
|
|
+
|
|
|
+ ;
|
|
|
+ return matrix;
|
|
|
+}
|
|
|
+
|
|
|
+/// Creates Python bindings for a diagonal Eigen sparse order-2 tensor (i.e. a matrix)
|
|
|
+template <typename Type>
|
|
|
+py::class_<Type> bind_eigen_diagonal_2(py::module &m, const char *name,
|
|
|
+ py::object parent = py::object()) {
|
|
|
+ typedef typename Type::Scalar Scalar;
|
|
|
+
|
|
|
+ /* Many Eigen functions are templated and can't easily be referenced using
|
|
|
+ a function pointer, thus a big portion of the binding code below
|
|
|
+ instantiates Eigen code using small anonymous wrapper functions */
|
|
|
+ py::class_<Type> matrix(m, name, parent);
|
|
|
+
|
|
|
+ matrix
|
|
|
+ /* Constructors */
|
|
|
+ .def(py::init<>())
|
|
|
+ //.def(py::init<size_t, size_t>())
|
|
|
+
|
|
|
+ /* Size query functions */
|
|
|
+ .def("size", [](const Type &m) { return m.size(); })
|
|
|
+ .def("cols", [](const Type &m) { return m.cols(); })
|
|
|
+ .def("rows", [](const Type &m) { return m.rows(); })
|
|
|
+
|
|
|
+ /* Initialization */
|
|
|
+ .def("setZero", [](Type &m) { m.setZero(); })
|
|
|
+ .def("setIdentity", [](Type &m) { m.setIdentity(); })
|
|
|
+
|
|
|
+ /* Arithmetic operators (def_cast forcefully casts the result back to a
|
|
|
+ Type to avoid type issues with Eigen's crazy expression templates) */
|
|
|
+ // .def_cast(-py::self)
|
|
|
+ // .def_cast(py::self + py::self)
|
|
|
+ // .def_cast(py::self - py::self)
|
|
|
+ // .def_cast(py::self * py::self)
|
|
|
+ .def_cast(py::self * Scalar())
|
|
|
+ .def_cast(Scalar() * py::self)
|
|
|
+
|
|
|
+ // // Special case, sparse * dense produces a dense matrix
|
|
|
+ // .def("__mul__", []
|
|
|
+ // (const Type &a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ // {
|
|
|
+ // return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a * b);
|
|
|
+ // })
|
|
|
+ // .def("__rmul__", [](const Type& a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ // {
|
|
|
+ // return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b * a);
|
|
|
+ // })
|
|
|
+
|
|
|
+ .def("__mul__", []
|
|
|
+ (const Type &a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(a * b);
|
|
|
+ })
|
|
|
+ .def("__rmul__", [](const Type& a, const Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>& b)
|
|
|
+ {
|
|
|
+ return Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic>(b * a);
|
|
|
+ })
|
|
|
+
|
|
|
+ .def("__mul__", []
|
|
|
+ (const Type &a, const Eigen::SparseMatrix<Scalar>& b)
|
|
|
+ {
|
|
|
+ return Eigen::SparseMatrix<Scalar>(a * b);
|
|
|
+ })
|
|
|
+ .def("__rmul__", [](const Type& a, const Eigen::SparseMatrix<Scalar>& b)
|
|
|
+ {
|
|
|
+ return Eigen::SparseMatrix<Scalar>(b * a);
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Python protocol implementations */
|
|
|
+ .def("__repr__", [](const Type &/*v*/) {
|
|
|
+ std::ostringstream oss;
|
|
|
+ oss << "<< operator undefined for diagonal matrices";
|
|
|
+ return oss.str();
|
|
|
+ })
|
|
|
+
|
|
|
+ /* Other transformations */
|
|
|
+
|
|
|
+ ;
|
|
|
+ return matrix;
|
|
|
+}
|
|
|
+
|
|
|
+
|
|
|
+void python_export_vector(py::module &m) {
|
|
|
+
|
|
|
+ py::module me = m.def_submodule(
|
|
|
+ "eigen", "Wrappers for Eigen types");
|
|
|
+
|
|
|
+ /* Bindings for VectorXd */
|
|
|
+ // bind_eigen_1<Eigen::VectorXd> (me, "VectorXd");
|
|
|
+ // py::implicitly_convertible<py::buffer, Eigen::VectorXd>();
|
|
|
+ // py::implicitly_convertible<double, Eigen::VectorXd>();
|
|
|
+
|
|
|
+ /* Bindings for VectorXi */
|
|
|
+ // bind_eigen_1<Eigen::VectorXi> (me, "VectorXi");
|
|
|
+ // py::implicitly_convertible<py::buffer, Eigen::VectorXi>();
|
|
|
+ // py::implicitly_convertible<double, Eigen::VectorXi>();
|
|
|
+
|
|
|
+ /* Bindings for MatrixXd */
|
|
|
+ bind_eigen_2<Eigen::MatrixXd> (me, "MatrixXd");
|
|
|
+ //py::implicitly_convertible<py::buffer, Eigen::MatrixXd>();
|
|
|
+ //py::implicitly_convertible<double, Eigen::MatrixXd>();
|
|
|
+
|
|
|
+ /* Bindings for MatrixXi */
|
|
|
+ bind_eigen_2<Eigen::MatrixXi> (me, "MatrixXi");
|
|
|
+// py::implicitly_convertible<py::buffer, Eigen::MatrixXi>();
|
|
|
+ //py::implicitly_convertible<double, Eigen::MatrixXi>();
|
|
|
+
|
|
|
+ /* Bindings for MatrixXuc */
|
|
|
+ bind_eigen_2<Eigen::Matrix<unsigned char,Eigen::Dynamic,Eigen::Dynamic> > (me, "MatrixXuc");
|
|
|
+ // py::implicitly_convertible<py::buffer, Eigen::Matrix<unsigned char,Eigen::Dynamic,Eigen::Dynamic> >();
|
|
|
+ // py::implicitly_convertible<double, Eigen::Matrix<unsigned char,Eigen::Dynamic,Eigen::Dynamic> >();
|
|
|
+
|
|
|
+ // /* Bindings for Vector3d */
|
|
|
+ // auto vector3 = bind_eigen_1_3<Eigen::Vector3d>(me, "Vector3d");
|
|
|
+ // vector3
|
|
|
+ // .def("norm", [](const Eigen::Vector3d &v) { return v.norm(); })
|
|
|
+ // .def("squaredNorm", [](const Eigen::Vector3d &v) { return v.squaredNorm(); })
|
|
|
+ // .def("normalize", [](Eigen::Vector3d &v) { v.normalize(); })
|
|
|
+ // .def("normalized", [](const Eigen::Vector3d &v) -> Eigen::Vector3d { return v.normalized(); })
|
|
|
+ // .def("dot", [](const Eigen::Vector3d &v1, const Eigen::Vector3d &v2) { return v1.dot(v2); })
|
|
|
+ // .def("cross", [](const Eigen::Vector3d &v1, const Eigen::Vector3d &v2) -> Eigen::Vector3d { return v1.cross(v2); })
|
|
|
+ // .def_property("x", [](const Eigen::Vector3d &v) -> double { return v.x(); },
|
|
|
+ // [](Eigen::Vector3d &v, double x) { v.x() = x; }, "X coordinate")
|
|
|
+ // .def_property("y", [](const Eigen::Vector3d &v) -> double { return v.y(); },
|
|
|
+ // [](Eigen::Vector3d &v, double y) { v.y() = y; }, "Y coordinate")
|
|
|
+ // .def_property("z", [](const Eigen::Vector3d &v) -> double { return v.z(); },
|
|
|
+ // [](Eigen::Vector3d &v, double z) { v.z() = z; }, "Z coordinate");
|
|
|
+ //
|
|
|
+ // py::implicitly_convertible<py::buffer, Eigen::Vector3d>();
|
|
|
+ // py::implicitly_convertible<double, Eigen::Vector3d>();
|
|
|
+
|
|
|
+ /* Bindings for SparseMatrix<double> */
|
|
|
+ bind_eigen_sparse_2< Eigen::SparseMatrix<double> > (me, "SparseMatrixd");
|
|
|
+
|
|
|
+ /* Bindings for SparseMatrix<int> */
|
|
|
+ bind_eigen_sparse_2< Eigen::SparseMatrix<int> > (me, "SparseMatrixi");
|
|
|
+
|
|
|
+ /* Bindings for DiagonalMatrix<double> */
|
|
|
+ bind_eigen_diagonal_2< Eigen::DiagonalMatrix<double,Eigen::Dynamic,Eigen::Dynamic> > (me, "DiagonalMatrixd");
|
|
|
+
|
|
|
+ /* Bindings for DiagonalMatrix<int> */
|
|
|
+ bind_eigen_diagonal_2< Eigen::DiagonalMatrix<int,Eigen::Dynamic,Eigen::Dynamic> > (me, "DiagonalMatrixi");
|
|
|
+
|
|
|
+ /* Bindings for SimplicialLLT*/
|
|
|
+
|
|
|
+ py::class_<Eigen::SimplicialLLT<Eigen::SparseMatrix<double > >> simpliciallltsparse(me, "SimplicialLLTsparse");
|
|
|
+
|
|
|
+ simpliciallltsparse
|
|
|
+ .def(py::init<>())
|
|
|
+ .def(py::init<Eigen::SparseMatrix<double>>())
|
|
|
+ .def("info",[](const Eigen::SimplicialLLT<Eigen::SparseMatrix<double > >& s)
|
|
|
+ {
|
|
|
+ if (s.info() == Eigen::Success)
|
|
|
+ return "Success";
|
|
|
+ else
|
|
|
+ return "Numerical Issue";
|
|
|
+ })
|
|
|
+ .def("solve",[](const Eigen::SimplicialLLT<Eigen::SparseMatrix<double > >& s, const Eigen::MatrixXd& rhs) { return Eigen::MatrixXd(s.solve(rhs)); })
|
|
|
+
|
|
|
+ ;
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+}
|