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/* -*- mode: c++; c-basic-offset: 4 -*- */

#ifndef _NUMPY_CPP_H_

#define _NUMPY_CPP_H_

/***************************************************************************

* This file is based on original work by Mark Wiebe, available at:

* http://github.com/mwiebe/numpy-cpp

* However, the needs of matplotlib wrappers, such as treating an

* empty array as having the correct dimensions, have made this rather

* matplotlib-specific, so it's no longer compatible with the

* original.

#include "py_exceptions.h"

#include <complex>

#ifdef _POSIX_C_SOURCE

# undef _POSIX_C_SOURCE

#endif

#ifdef _XOPEN_SOURCE

# undef _XOPEN_SOURCE

#endif

#include <Python.h>

#include <numpy/ndarrayobject.h>

namespace numpy

{

// Type traits for the NumPy types

template <typename T>

struct type_num_of;

/* Be careful with bool arrays as python has sizeof(npy_bool) == 1, but it is

* not always the case that sizeof(bool) == 1. Using the array_view_accessors

* is always fine regardless of sizeof(bool), so do this rather than using

* array.data() and pointer arithmetic which will not work correctly if

* sizeof(bool) != 1. */

template <> struct type_num_of<bool>

{

enum {

value = NPY_BOOL

};

template <>

struct type_num_of<npy_byte>

{

enum {

value = NPY_BYTE

};

template <>

struct type_num_of<npy_ubyte>

{

enum {

value = NPY_UBYTE

};

template <>

struct type_num_of<npy_short>

{

enum {

value = NPY_SHORT

};

template <>

struct type_num_of<npy_ushort>

{

enum {

value = NPY_USHORT

};

template <>

struct type_num_of<npy_int>

{

enum {

value = NPY_INT

};

template <>

struct type_num_of<npy_uint>

{

enum {

value = NPY_UINT

};

template <>

struct type_num_of<npy_long>

{

enum {

value = NPY_LONG

};

template <>

struct type_num_of<npy_ulong>

{

enum {

value = NPY_ULONG

};

template <>

struct type_num_of<npy_longlong>

{

enum {

value = NPY_LONGLONG

};

template <>

struct type_num_of<npy_ulonglong>

{

enum {

value = NPY_ULONGLONG

};

template <>

struct type_num_of<npy_float>

{

enum {

value = NPY_FLOAT

};

template <>

struct type_num_of<npy_double>

{

enum {

value = NPY_DOUBLE

};

#if NPY_LONGDOUBLE != NPY_DOUBLE

template <>

struct type_num_of<npy_longdouble>

{

enum {

value = NPY_LONGDOUBLE

};

#endif

template <>

struct type_num_of<npy_cfloat>

{

enum {

value = NPY_CFLOAT

};

template <>

struct type_num_of<std::complex<npy_float> >

{

enum {

value = NPY_CFLOAT

};

template <>

struct type_num_of<npy_cdouble>

{

enum {

value = NPY_CDOUBLE

};

template <>

struct type_num_of<std::complex<npy_double> >

{

enum {

value = NPY_CDOUBLE

};

#if NPY_CLONGDOUBLE != NPY_CDOUBLE

template <>

struct type_num_of<npy_clongdouble>

{

enum {

value = NPY_CLONGDOUBLE

};

template <>

struct type_num_of<std::complex<npy_longdouble> >

{

enum {

value = NPY_CLONGDOUBLE

};

#endif

template <>

struct type_num_of<PyObject *>

{

enum {

value = NPY_OBJECT

};

template <typename T>

struct type_num_of<T &>

{

enum {

value = type_num_of<T>::value

};

template <typename T>

struct type_num_of<const T>

{

enum {

value = type_num_of<T>::value

};

template <typename T>

struct is_const

{

enum {

value = false

};

template <typename T>

struct is_const<const T>

{

enum {

value = true

};

namespace detail

{

template <template <typename, int> class AV, typename T, int ND>

class array_view_accessors;

template <template <typename, int> class AV, typename T>

class array_view_accessors<AV, T, 1>

{

public:

typedef AV<T, 1> AVC;

typedef T sub_t;

T &operator()(npy_intp i)

{

AVC *self = static_cast<AVC *>(this);

return *reinterpret_cast<T *>(self->m_data + self->m_strides[0] * i);

}

const T &operator()(npy_intp i) const

{

const AVC *self = static_cast<const AVC *>(this);

return *reinterpret_cast<const T *>(self->m_data + self->m_strides[0] * i);

}

T &operator[](npy_intp i)

{

AVC *self = static_cast<AVC *>(this);

return *reinterpret_cast<T *>(self->m_data + self->m_strides[0] * i);

}

const T &operator[](npy_intp i) const

{

const AVC *self = static_cast<const AVC *>(this);

return *reinterpret_cast<const T *>(self->m_data + self->m_strides[0] * i);

}

};

template <template <typename, int> class AV, typename T>

class array_view_accessors<AV, T, 2>

{

public:

typedef AV<T, 2> AVC;

typedef AV<T, 1> sub_t;

T &operator()(npy_intp i, npy_intp j)

{

AVC *self = static_cast<AVC *>(this);

return *reinterpret_cast<T *>(self->m_data + self->m_strides[0] * i +

self->m_strides[1] * j);

}

const T &operator()(npy_intp i, npy_intp j) const

{

const AVC *self = static_cast<const AVC *>(this);

return *reinterpret_cast<const T *>(self->m_data + self->m_strides[0] * i +

self->m_strides[1] * j);

}

sub_t operator[](npy_intp i) const

{

const AVC *self = static_cast<const AVC *>(this);

return sub_t(self->m_arr,

self->m_data + self->m_strides[0] * i,

self->m_shape + 1,

self->m_strides + 1);

}

};

template <template <typename, int> class AV, typename T>

class array_view_accessors<AV, T, 3>

{

public:

typedef AV<T, 3> AVC;

typedef AV<T, 2> sub_t;

T &operator()(npy_intp i, npy_intp j, npy_intp k)

{

AVC *self = static_cast<AVC *>(this);

return *reinterpret_cast<T *>(self->m_data + self->m_strides[0] * i +

self->m_strides[1] * j + self->m_strides[2] * k);

}

const T &operator()(npy_intp i, npy_intp j, npy_intp k) const

{

const AVC *self = static_cast<const AVC *>(this);

return *reinterpret_cast<const T *>(self->m_data + self->m_strides[0] * i +

self->m_strides[1] * j + self->m_strides[2] * k);

}

sub_t operator[](npy_intp i) const

{

const AVC *self = static_cast<const AVC *>(this);

return sub_t(self->m_arr,

self->m_data + self->m_strides[0] * i,

self->m_shape + 1,

self->m_strides + 1);

}

};

// When adding instantiations of array_view_accessors, remember to add entries

// to zeros[] below.

}

static npy_intp zeros[] = { 0, 0, 0 };

template <typename T, int ND>

class array_view : public detail::array_view_accessors<array_view, T, ND>

{

friend class detail::array_view_accessors<numpy::array_view, T, ND>;

private:

// Copies of the array data

PyArrayObject *m_arr;

npy_intp *m_shape;

npy_intp *m_strides;

char *m_data;

public:

typedef T value_type;

enum {

ndim = ND

};

array_view() : m_arr(NULL), m_data(NULL)

{

m_shape = zeros;

m_strides = zeros;

}

array_view(PyObject *arr, bool contiguous = false) : m_arr(NULL), m_data(NULL)

{

if (!set(arr, contiguous)) {

throw py::exception();

}

array_view(const array_view &other) : m_arr(NULL), m_data(NULL)

{

m_arr = other.m_arr;

Py_XINCREF(m_arr);

m_data = other.m_data;

m_shape = other.m_shape;

m_strides = other.m_strides;

}

array_view(PyArrayObject *arr, char *data, npy_intp *shape, npy_intp *strides)

{

m_arr = arr;

Py_XINCREF(arr);

m_data = data;

m_shape = shape;

m_strides = strides;

}

array_view(npy_intp shape[ND]) : m_arr(NULL), m_shape(NULL), m_strides(NULL), m_data(NULL)

{

PyObject *arr = PyArray_SimpleNew(ND, shape, type_num_of<T>::value);

if (arr == NULL) {

throw py::exception();

}

if (!set(arr, true)) {

Py_DECREF(arr);

throw py::exception();

}

Py_DECREF(arr);

}

~array_view()

{

Py_XDECREF(m_arr);

}

array_view& operator=(const array_view &other)

{

if (this != &other)

{

Py_XDECREF(m_arr);

m_arr = other.m_arr;

Py_XINCREF(m_arr);

m_data = other.m_data;

m_shape = other.m_shape;

m_strides = other.m_strides;

}

return *this;

}

int set(PyObject *arr, bool contiguous = false)

{

PyArrayObject *tmp;

if (arr == NULL || arr == Py_None) {

Py_XDECREF(m_arr);

m_arr = NULL;

m_data = NULL;

m_shape = zeros;

m_strides = zeros;

} else {

if (contiguous) {

tmp = (PyArrayObject *)PyArray_ContiguousFromAny(arr, type_num_of<T>::value, 0, ND);

} else {

tmp = (PyArrayObject *)PyArray_FromObject(arr, type_num_of<T>::value, 0, ND);

}

if (tmp == NULL) {

return 0;

}

if (PyArray_NDIM(tmp) == 0 || PyArray_DIM(tmp, 0) == 0) {

Py_XDECREF(m_arr);

m_arr = NULL;

m_data = NULL;

m_shape = zeros;

m_strides = zeros;

if (PyArray_NDIM(tmp) == 0 && ND == 0) {

m_arr = tmp;

return 1;

}

if (PyArray_NDIM(tmp) != ND) {

PyErr_Format(PyExc_ValueError,

"Expected %d-dimensional array, got %d",

ND,

PyArray_NDIM(tmp));

Py_DECREF(tmp);

return 0;

}

/* Copy some of the data to the view object for faster access */

Py_XDECREF(m_arr);

m_arr = tmp;

m_shape = PyArray_DIMS(m_arr);

m_strides = PyArray_STRIDES(m_arr);

m_data = (char *)PyArray_BYTES(tmp);

}

return 1;

}

npy_intp dim(size_t i) const

{

if (i >= ND) {

return 0;

}

return m_shape[i];

}

In most cases, code should use size() instead of dim(0), since

size() == 0 when any dimension is 0.

size_t size() const

{

bool empty = (ND == 0);

for (size_t i = 0; i < ND; i++) {

if (m_shape[i] == 0) {

empty = true;

}

if (empty) {

return 0;

} else {

return (size_t)dim(0);

}

bool empty() const

{

return size() == 0;

}

// Do not use this for array_view<bool, ND>. See comment near top of file.

const T *data() const

{

return (const T *)m_data;

}

// Do not use this for array_view<bool, ND>. See comment near top of file.

T *data()

{

return (T *)m_data;

}

PyObject *pyobj()

{

Py_XINCREF(m_arr);

return (PyObject *)m_arr;

}

static int converter(PyObject *obj, void *arrp)

{

array_view<T, ND> *arr = (array_view<T, ND> *)arrp;

if (!arr->set(obj)) {

return 0;

}

return 1;

}

static int converter_contiguous(PyObject *obj, void *arrp)

{

array_view<T, ND> *arr = (array_view<T, ND> *)arrp;

if (!arr->set(obj, true)) {

return 0;

}

return 1;

}

};

} // namespace numpy

#endif

matplotlib/src/numpy_cpp.h at master · flothesof/matplotlib · GitHub

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