/* This file is part of MAUS: http://micewww.pp.rl.ac.uk/projects/maus
*
* MAUS is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* MAUS is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with MAUS. If not, see .
*
*/
#ifndef _SRC_PY_CPP_PYCOVARIANCEMATRIX_HH_
#define _SRC_PY_CPP_PYCOVARIANCEMATRIX_HH_
// These ifdefs are required to avoid cpp compiler warning
#ifdef _POSIX_C_SOURCE
#undef _POSIX_C_SOURCE
#endif
#ifdef _XOPEN_SOURCE
#undef _XOPEN_SOURCE
#endif
#include
#ifdef MAUS_PYCOVARIANCEMATRIX_CC
namespace MAUS {
class CovarianceMatrix; // note this is just in MAUS namespace
namespace PyCovarianceMatrix {
/** PyCovarianceMatrix is the python implementation of the C++ CovarianceMatrix
*/
typedef struct {
PyObject_HEAD;
CovarianceMatrix* cov_mat;
} PyCovarianceMatrix;
/** @namespace C_API defines functions that can be accessed by other C libraries
*
* To access these functions call int import_PyCovarianceMatrix() otherwise you
* will get a segmentation fault. The import will place the C_API functions in
* the MAUS::PyCovarianceMatrix namespace.
*/
namespace C_API {
/** Allocate a new PyCovarianceMatrix
*
* \returns PyCovarianceMatrix* cast as a PyObject* with cm pointer set to
* NULL. Caller owns the memory allocated to PyCovarianceMatrix*
*/
static PyObject *create_empty_matrix();
/** Return the C++ covariance matrix associated with a PyCovarianceMatrix
*
* \param py_cm PyCovarianceMatrix* cast as a PyObject*. Python representation
* of the covariance matrix
*
* \returns NULL on failure and raises a TypeError. On success returns the
* CovarianceMatrix. PyCovarianceMatrix still owns the memory allocated to
* CovarianceMatrix.
*/
static CovarianceMatrix* get_covariance_matrix(PyObject* py_cm);
/** Set the C++ covariance matrix associated with a PyCovarianceMatrix
*
* \param py_cm PyCovarianceMatrix* cast as a PyObject*. Python representation
* of the covariance matrix
* \param cm C++ representation of the covariance matrix. PyCovarianceMatrix
* takes ownership of the memory allocated to cm
*
* \returns 1 on success, 0 on failure and raises a TypeError
*/
static int set_covariance_matrix(PyObject* py_cm, CovarianceMatrix* cm);
}
/** _alloc allocates memory for PyCovarianceMatrix
*
* @param type - pointer to a PyCovarianceMatrixType object, as defined in
* PyCovarianceMatrix.cc
*
* returns a PyCovarianceMatrix* (cast as a PyObject*); caller owns this memory
*/
static PyObject *_alloc(PyTypeObject *type, Py_ssize_t nitems);
/** _init initialises an allocated PyCovarianceMatrix object
*
* @param self an initialised PyCovarianceMatrix* cast as a PyObject*; caller
* owns this memory
* @param args not used
* @param kwds not used
*
* @returns 0 on success; -1 on failure
*/
static int _init(PyObject* self, PyObject *args, PyObject *kwds);
/** deallocate memory
*
* @params self an initialised PyCovarianceMatrix*; memory will be freed by
* this function
*/
static void _free(PyCovarianceMatrix * self);
/** Return a Python string representation of the PyCovarianceMatrix */
static PyObject* _str(PyObject * self);
/** Initialise covariance_matrix module
*
* This is called by import covariance_matrix; it initialises the
* CovarianceMatrix type allowing user to construct and call methods on
* CovarianceMatrix objects
*/
PyMODINIT_FUNC initcovariance_matrix(void);
/** Get the value of an element
*
* \param self - not used
* \param args - not used
* \param kwds - keyword arguments; row, column for matrix row, column
*
*/
static PyObject* get_element(PyObject* self, PyObject *args, PyObject *kwds);
/** Create a PyCovarianceMatrix from penn parameters
*
* \param self - not used
* \param args - value arguments
* \param kwds - keyword arguments
*
* \returns PyCovarianceMatrix cast to a PyObject - caller owns this memory
*/
static PyObject* create_from_penn_parameters
(PyObject *self, PyObject *args, PyObject *kwds);
/** Create a PyCovarianceMatrix from twiss parameters
*
* \param self - not used
* \param args - value arguments
* \param kwds - keyword arguments
*
* \returns PyCovarianceMatrix cast to a PyObject - caller owns this memory
*/
static PyObject* create_from_twiss_parameters
(PyObject *self, PyObject *args, PyObject *kwds);
/** Create a PyCovarianceMatrix from a numpy matrix
*
* \param self - not used
* \param args - value arguments
* \param kwds - keyword arguments; takes one keywd, matrix which is a 6x6
* numpy matrix
*
* \returns PyCovarianceMatrix cast to a PyObject - caller owns this memory
*/
static PyObject* create_from_matrix
(PyObject* self, PyObject *args, PyObject *kwds);
/** Create a PyCovarianceMatrix from a numpy matrix
*
* \param numpy_array borrowed reference to a numpy array. Should be 6x6
* matrix, assumed to be symmetric. Borrowed reference means caller
* still owns the array.
*
* \returns new CovarianceMatrix; caller owns the memory
*
* \throws MAUS::Exception if array has wrong shape or is not a numpy_array
*/
static CovarianceMatrix* create_from_numpy_matrix(PyObject *numpy_array);
}
}
#else
/** MAUS::PyOpticsModel::PyCovarianceMatrix C API objects
*
* Because of the way python does share libraries, we have to explicitly import
* C functions via the Python API, which is done at import time. This mimics
* the functions in MAUS::PyCovarianceMatrix. Full documentation is found
* there.
*/
namespace MAUS {
namespace PyCovarianceMatrix {
/** import the PyCovarianceMatrix C_API
*
* Makes the functions in C_API available in the MAUS::PyCovarianceMatrix
* namespace, for other python/C code
*
* @returns 0 if the import fails; return 1 if it is a success
*/
int import_PyCovarianceMatrix();
PyObject* (*create_empty_matrix)() = NULL;
int (*set_covariance_matrix)(PyObject* py_cm, CovarianceMatrix* cm) = NULL;
CovarianceMatrix* (*get_covariance_matrix)(PyObject* py_cm) = NULL;
}
}
int MAUS::PyCovarianceMatrix::import_PyCovarianceMatrix() {
PyObject* cm_module = PyImport_ImportModule("maus_cpp.covariance_matrix");
if (cm_module == NULL) {
return 0;
} else {
PyObject *cm_dict = PyModule_GetDict(cm_module);
PyObject* cem_c_api = PyDict_GetItemString(cm_dict,
"C_API_CREATE_EMPTY_MATRIX");
void* cem_void = reinterpret_cast(PyCObject_AsVoidPtr(cem_c_api));
PyCovarianceMatrix::create_empty_matrix =
reinterpret_cast(cem_void);
PyObject* gcm_c_api = PyDict_GetItemString(cm_dict,
"C_API_GET_COVARIANCE_MATRIX");
void* gcm_void = reinterpret_cast(PyCObject_AsVoidPtr(gcm_c_api));
PyCovarianceMatrix::get_covariance_matrix =
reinterpret_cast(gcm_void);
PyObject* scm_c_api = PyDict_GetItemString(cm_dict,
"C_API_SET_COVARIANCE_MATRIX");
void* scm_void = reinterpret_cast(PyCObject_AsVoidPtr(scm_c_api));
PyCovarianceMatrix::set_covariance_matrix =
reinterpret_cast(scm_void);
if ((create_empty_matrix == NULL) ||
(set_covariance_matrix == NULL) ||
(get_covariance_matrix == NULL))
return 0;
}
return 1;
}
#endif // MAUS_PYCOVARIANCEMATRIX_CC
#endif // _SRC_PY_CPP_PYCOVARIANCEMATRIX_HH_