eigenpy.cpp

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/*
 * Copyright 2014-2019, CNRS
 * Copyright 2018-2023, INRIA
 */
 
#include "eigenpy/eigenpy.hpp"
 
#include <stdlib.h>
 
namespace eigenpy {
 
void seed(unsigned int seed_value) { srand(seed_value); }
 
void exposeMatrixBool();
void exposeMatrixInt8();
void exposeMatrixChar();
void exposeMatrixUInt8();
void exposeMatrixInt16();
void exposeMatrixUInt16();
void exposeMatrixInt32();
void exposeMatrixUInt32();
void exposeMatrixWindowsLong();
void exposeMatrixWindowsULong();
void exposeMatrixMacLong();
void exposeMatrixMacULong();
void exposeMatrixInt64();
void exposeMatrixUInt64();
void exposeMatrixLinuxLongLong();
void exposeMatrixLinuxULongLong();
void exposeMatrixFloat();
void exposeMatrixDouble();
void exposeMatrixLongDouble();
 
void exposeMatrixComplexFloat();
void exposeMatrixComplexDouble();
void exposeMatrixComplexLongDouble();
 
void exposeNoneType();
 
/* Enable Eigen-Numpy serialization for a set of standard MatrixBase instances.
 */
void enableEigenPy() {
  using namespace Eigen;
  import_numpy();
 
  Exception::registerException();
 
  bp::def("sharedMemory", (void (*)(const bool))NumpyType::sharedMemory,
          bp::arg("value"),
          "Share the memory when converting from Eigen to Numpy.");
 
  bp::def("sharedMemory", (bool (*)())NumpyType::sharedMemory,
          "Status of the shared memory when converting from Eigen to Numpy.\n"
          "If True, the memory is shared when converting an Eigen::Matrix to a "
          "numpy.array.\n"
          "Otherwise, a deep copy of the Eigen::Matrix is performed.");
 
  bp::def("seed", &seed, bp::arg("seed_value"),
          "Initialize the pseudo-random number generator with the argument "
          "seed_value.");
 
  exposeMatrixBool();
  exposeMatrixInt8();
  exposeMatrixChar();
  exposeMatrixUInt8();
  exposeMatrixInt16();
  exposeMatrixUInt16();
  exposeMatrixInt32();
  exposeMatrixUInt32();
  exposeMatrixWindowsLong();
  exposeMatrixWindowsULong();
  exposeMatrixMacLong();
  exposeMatrixMacULong();
  exposeMatrixInt64();
  exposeMatrixUInt64();
  exposeMatrixLinuxLongLong();
  exposeMatrixLinuxULongLong();
  exposeMatrixFloat();
  exposeMatrixDouble();
  exposeMatrixLongDouble();
 
  exposeMatrixComplexFloat();
  exposeMatrixComplexDouble();
  exposeMatrixComplexLongDouble();
 
  exposeNoneType();
}
 
bool withTensorSupport() {
#ifdef EIGENPY_WITH_TENSOR_SUPPORT
  return true;
#else
  return false;
#endif
}
 
}  // namespace eigenpy