// ascee_python.h
//
// Author: J.A. de Jong - ASCEE - Redu-Sone
//
// Description:
// Some routines to generate numpy arrays from matrices and vectors.
//////////////////////////////////////////////////////////////////////
#pragma once
#ifndef LASP_PYTHON_H
#define LASP_PYTHON_H

#ifdef __cplusplus
#error "Cannot compile this file with C++"
#endif
#include "lasp_types.h"
#include "lasp_mat.h"
#include "lasp_pyarray.h"

/**
 * @brief Create a Numpy array from a dmat structure
 *
 * @param mat Pointer to the dmat 
 * @param transfer_ownership If set to true, the created Numpy array will
 * obtain ownership of the data and calls free() on destruction. The dmat will
 * have the foreign_data flag set, such that it won't free the data.
 *
 * @return 
 */
static inline PyObject* dmat_to_ndarray(dmat* mat,bool transfer_ownership) {
    dbgassert(mat,NULLPTRDEREF);
    dbgassert(mat->_data,NULLPTRDEREF);
    /* fprintf(stderr, "Enter dmat_to_ndarray\n"); */

    // Dimensions given in wrong order, as mat is
    // Fortran-contiguous. Later on we transpose the result. This is
    // more easy than using the PyArray_New syntax.
    PyObject* arr = data_to_ndarray(mat->_data,
            mat->n_rows,
            mat->n_cols,
            LASP_NUMPY_FLOAT_TYPE,
            transfer_ownership,
            true); // Fortran-contiguous

    if(transfer_ownership) {
        mat->_foreign_data = true;
    }

    if(!arr) {
        WARN("Array creation failure");
        feTRACE(15);
        return NULL;
    }
    /* fprintf(stderr, "Exit dmat_to_ndarray\n"); */

    return arr;
}

#endif // LASP_PYTHON_H
//////////////////////////////////////////////////////////////////////