pybind11/tests/test_eigen.cpp
Jason Rhinelander 52f4be8946 Make test initialization self-registering
Adding or removing tests is a little bit cumbersome currently: the test
needs to be added to CMakeLists.txt, the init function needs to be
predeclared in pybind11_tests.cpp, then called in the plugin
initialization.  While this isn't a big deal for tests that are being
committed, it's more of a hassle when working on some new feature or
test code for which I temporarily only care about building and linking
the test being worked on rather than the entire test suite.

This commit changes tests to self-register their initialization by
having each test initialize a local object (which stores the
initialization function in a static variable).  This makes changing the
set of tests being build easy: one only needs to add or comment out
test names in tests/CMakeLists.txt.

A couple other minor changes that go along with this:

- test_eigen.cpp is now included in the test list, then removed if eigen
  isn't available.  This lets you disable the eigen tests by commenting
  it out, just like all the other tests, but keeps the build working
  without eigen eigen isn't available.  (Also, if it's commented out, we
  don't even bother looking for and reporting the building with/without
  eigen status message).

- pytest is now invoked with all the built test names (with .cpp changed
  to .py) so that it doesn't try to run tests that weren't built.
2016-09-03 17:34:41 -04:00

135 lines
4.9 KiB
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/*
tests/eigen.cpp -- automatic conversion of Eigen types
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "pybind11_tests.h"
#include <pybind11/eigen.h>
#include <Eigen/Cholesky>
Eigen::VectorXf double_col(const Eigen::VectorXf& x)
{ return 2.0f * x; }
Eigen::RowVectorXf double_row(const Eigen::RowVectorXf& x)
{ return 2.0f * x; }
Eigen::MatrixXf double_mat_cm(const Eigen::MatrixXf& x)
{ return 2.0f * x; }
// Different ways of passing via Eigen::Ref; the first and second are the Eigen-recommended
Eigen::MatrixXd cholesky1(Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky2(const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky3(const Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky4(Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky5(Eigen::Ref<Eigen::MatrixXd> x) { return x.llt().matrixL(); }
Eigen::MatrixXd cholesky6(Eigen::Ref<const Eigen::MatrixXd> x) { return x.llt().matrixL(); }
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> MatrixXfRowMajor;
MatrixXfRowMajor double_mat_rm(const MatrixXfRowMajor& x)
{ return 2.0f * x; }
test_initializer eigen([](py::module &m) {
typedef Eigen::Matrix<float, 5, 6, Eigen::RowMajor> FixedMatrixR;
typedef Eigen::Matrix<float, 5, 6> FixedMatrixC;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> DenseMatrixR;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic> DenseMatrixC;
typedef Eigen::SparseMatrix<float, Eigen::RowMajor> SparseMatrixR;
typedef Eigen::SparseMatrix<float> SparseMatrixC;
m.attr("have_eigen") = py::cast(true);
// Non-symmetric matrix with zero elements
Eigen::MatrixXf mat(5, 6);
mat << 0, 3, 0, 0, 0, 11, 22, 0, 0, 0, 17, 11, 7, 5, 0, 1, 0, 11, 0,
0, 0, 0, 0, 11, 0, 0, 14, 0, 8, 11;
m.def("double_col", &double_col);
m.def("double_row", &double_row);
m.def("double_mat_cm", &double_mat_cm);
m.def("double_mat_rm", &double_mat_rm);
m.def("cholesky1", &cholesky1);
m.def("cholesky2", &cholesky2);
m.def("cholesky3", &cholesky3);
m.def("cholesky4", &cholesky4);
m.def("cholesky5", &cholesky5);
m.def("cholesky6", &cholesky6);
// Returns diagonals: a vector-like object with an inner stride != 1
m.def("diagonal", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal(); });
m.def("diagonal_1", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal<1>(); });
m.def("diagonal_n", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int index) { return x.diagonal(index); });
// Return a block of a matrix (gives non-standard strides)
m.def("block", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int start_row, int start_col, int block_rows, int block_cols) {
return x.block(start_row, start_col, block_rows, block_cols);
});
// Returns a DiagonalMatrix with diagonal (1,2,3,...)
m.def("incr_diag", [](int k) {
Eigen::DiagonalMatrix<int, Eigen::Dynamic> m(k);
for (int i = 0; i < k; i++) m.diagonal()[i] = i+1;
return m;
});
// Returns a SelfAdjointView referencing the lower triangle of m
m.def("symmetric_lower", [](const Eigen::MatrixXi &m) {
return m.selfadjointView<Eigen::Lower>();
});
// Returns a SelfAdjointView referencing the lower triangle of m
m.def("symmetric_upper", [](const Eigen::MatrixXi &m) {
return m.selfadjointView<Eigen::Upper>();
});
m.def("fixed_r", [mat]() -> FixedMatrixR {
return FixedMatrixR(mat);
});
m.def("fixed_c", [mat]() -> FixedMatrixC {
return FixedMatrixC(mat);
});
m.def("fixed_passthrough_r", [](const FixedMatrixR &m) -> FixedMatrixR {
return m;
});
m.def("fixed_passthrough_c", [](const FixedMatrixC &m) -> FixedMatrixC {
return m;
});
m.def("dense_r", [mat]() -> DenseMatrixR {
return DenseMatrixR(mat);
});
m.def("dense_c", [mat]() -> DenseMatrixC {
return DenseMatrixC(mat);
});
m.def("dense_passthrough_r", [](const DenseMatrixR &m) -> DenseMatrixR {
return m;
});
m.def("dense_passthrough_c", [](const DenseMatrixC &m) -> DenseMatrixC {
return m;
});
m.def("sparse_r", [mat]() -> SparseMatrixR {
return Eigen::SparseView<Eigen::MatrixXf>(mat);
});
m.def("sparse_c", [mat]() -> SparseMatrixC {
return Eigen::SparseView<Eigen::MatrixXf>(mat);
});
m.def("sparse_passthrough_r", [](const SparseMatrixR &m) -> SparseMatrixR {
return m;
});
m.def("sparse_passthrough_c", [](const SparseMatrixC &m) -> SparseMatrixC {
return m;
});
});