diff --git a/.gitignore b/.gitignore index 0c95bf7..68e841f 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,5 @@ *.so test_swig.py test_swig_wrap.c +test_swig_opencv.py +test_swig_opencv_wrap.cxx diff --git a/Makefile b/Makefile index 6e4c498..fc40933 100644 --- a/Makefile +++ b/Makefile @@ -2,7 +2,7 @@ default: all test .PHONY: all -all: _test_swig.so +all: _test_swig.so _test_swig_opencv.so .PHONY: test test: @@ -17,6 +17,11 @@ test_swig.o: test_swig_wrap.c test_swig_wrap.c: test_swig.i swig -python $< +_test_swig_opencv.so: test_swig_opencv.cpp test_swig_opencv.i okapi-typemaps.i numpy.i + swig -python -c++ test_swig_opencv.i + g++ -fpic -c test_swig_opencv.cpp test_swig_opencv_wrap.cxx -I/usr/include/python2.7 + g++ -shared test_swig_opencv.o test_swig_opencv_wrap.o -lopencv_core -o _test_swig_opencv.so + .PHONY: clean clean: rm -f *.o *.so test_swig_wrap.c *.pyc test_swig.py diff --git a/numpy.i b/numpy.i new file mode 100644 index 0000000..96601ae --- /dev/null +++ b/numpy.i @@ -0,0 +1,1636 @@ +/* -*- C -*- (not really, but good for syntax highlighting) */ +#ifdef SWIGPYTHON + +%{ +#ifndef SWIG_FILE_WITH_INIT +# define NO_IMPORT_ARRAY +#endif +#include "stdio.h" +#include +%} + +/**********************************************************************/ + +%fragment("NumPy_Backward_Compatibility", "header") +{ +/* Support older NumPy data type names +*/ +%#if NDARRAY_VERSION < 0x01000000 +%#define NPY_BOOL PyArray_BOOL +%#define NPY_BYTE PyArray_BYTE +%#define NPY_UBYTE PyArray_UBYTE +%#define NPY_SHORT PyArray_SHORT +%#define NPY_USHORT PyArray_USHORT +%#define NPY_INT PyArray_INT +%#define NPY_UINT PyArray_UINT +%#define NPY_LONG PyArray_LONG +%#define NPY_ULONG PyArray_ULONG +%#define NPY_LONGLONG PyArray_LONGLONG +%#define NPY_ULONGLONG PyArray_ULONGLONG +%#define NPY_FLOAT PyArray_FLOAT +%#define NPY_DOUBLE PyArray_DOUBLE +%#define NPY_LONGDOUBLE PyArray_LONGDOUBLE +%#define NPY_CFLOAT PyArray_CFLOAT +%#define NPY_CDOUBLE PyArray_CDOUBLE +%#define NPY_CLONGDOUBLE PyArray_CLONGDOUBLE +%#define NPY_OBJECT PyArray_OBJECT +%#define NPY_STRING PyArray_STRING +%#define NPY_UNICODE PyArray_UNICODE +%#define NPY_VOID PyArray_VOID +%#define NPY_NTYPES PyArray_NTYPES +%#define NPY_NOTYPE PyArray_NOTYPE +%#define NPY_CHAR PyArray_CHAR +%#define NPY_USERDEF PyArray_USERDEF +%#define npy_intp intp + +%#define NPY_MAX_BYTE MAX_BYTE +%#define NPY_MIN_BYTE MIN_BYTE +%#define NPY_MAX_UBYTE MAX_UBYTE +%#define NPY_MAX_SHORT MAX_SHORT +%#define NPY_MIN_SHORT MIN_SHORT +%#define NPY_MAX_USHORT MAX_USHORT +%#define NPY_MAX_INT MAX_INT +%#define NPY_MIN_INT MIN_INT +%#define NPY_MAX_UINT MAX_UINT +%#define NPY_MAX_LONG MAX_LONG +%#define NPY_MIN_LONG MIN_LONG +%#define NPY_MAX_ULONG MAX_ULONG +%#define NPY_MAX_LONGLONG MAX_LONGLONG +%#define NPY_MIN_LONGLONG MIN_LONGLONG +%#define NPY_MAX_ULONGLONG MAX_ULONGLONG +%#define NPY_MAX_INTP MAX_INTP +%#define NPY_MIN_INTP MIN_INTP + +%#define NPY_FARRAY FARRAY +%#define NPY_F_CONTIGUOUS F_CONTIGUOUS +%#endif +} + +/**********************************************************************/ + +/* The following code originally appeared in + * enthought/kiva/agg/src/numeric.i written by Eric Jones. It was + * translated from C++ to C by John Hunter. Bill Spotz has modified + * it to fix some minor bugs, upgrade from Numeric to numpy (all + * versions), add some comments and functionality, and convert from + * direct code insertion to SWIG fragments. + */ + +%fragment("NumPy_Macros", "header") +{ +/* Macros to extract array attributes. + */ +%#define is_array(a) ((a) && PyArray_Check((PyArrayObject *)a)) +%#define array_type(a) (int)(PyArray_TYPE(a)) +%#define array_numdims(a) (((PyArrayObject *)a)->nd) +%#define array_dimensions(a) (((PyArrayObject *)a)->dimensions) +%#define array_size(a,i) (((PyArrayObject *)a)->dimensions[i]) +%#define array_data(a) (((PyArrayObject *)a)->data) +%#define array_is_contiguous(a) (PyArray_ISCONTIGUOUS(a)) +%#define array_is_native(a) (PyArray_ISNOTSWAPPED(a)) +%#define array_is_fortran(a) (PyArray_ISFORTRAN(a)) +} + +/**********************************************************************/ + +%fragment("NumPy_Utilities", "header") +{ + /* Given a PyObject, return a string describing its type. + */ + const char* pytype_string(PyObject* py_obj) { + if (py_obj == NULL ) return "C NULL value"; + if (py_obj == Py_None ) return "Python None" ; + if (PyCallable_Check(py_obj)) return "callable" ; + if (PyString_Check( py_obj)) return "string" ; + if (PyInt_Check( py_obj)) return "int" ; + if (PyFloat_Check( py_obj)) return "float" ; + if (PyDict_Check( py_obj)) return "dict" ; + if (PyList_Check( py_obj)) return "list" ; + if (PyTuple_Check( py_obj)) return "tuple" ; + if (PyModule_Check( py_obj)) return "module" ; +%#if PY_MAJOR_VERSION < 3 + if (PyFile_Check( py_obj)) return "file" ; + if (PyInstance_Check(py_obj)) return "instance" ; +%#endif + + return "unkown type"; + } + + /* Given a NumPy typecode, return a string describing the type. + */ + const char* typecode_string(int typecode) { + static const char* type_names[25] = {"bool", "byte", "unsigned byte", + "short", "unsigned short", "int", + "unsigned int", "long", "unsigned long", + "long long", "unsigned long long", + "float", "double", "long double", + "complex float", "complex double", + "complex long double", "object", + "string", "unicode", "void", "ntypes", + "notype", "char", "unknown"}; + return typecode < 24 ? type_names[typecode] : type_names[24]; + } + + /* Make sure input has correct numpy type. Allow character and byte + * to match. Also allow int and long to match. This is deprecated. + * You should use PyArray_EquivTypenums() instead. + */ + int type_match(int actual_type, int desired_type) { + return PyArray_EquivTypenums(actual_type, desired_type); + } +} + +/**********************************************************************/ + +%fragment("NumPy_Object_to_Array", "header", + fragment="NumPy_Backward_Compatibility", + fragment="NumPy_Macros", + fragment="NumPy_Utilities") +{ + /* Given a PyObject pointer, cast it to a PyArrayObject pointer if + * legal. If not, set the python error string appropriately and + * return NULL. + */ + PyArrayObject* obj_to_array_no_conversion(PyObject* input, int typecode) + { + PyArrayObject* ary = NULL; + if (is_array(input) && (typecode == NPY_NOTYPE || + PyArray_EquivTypenums(array_type(input), typecode))) + { + ary = (PyArrayObject*) input; + } + else if is_array(input) + { + const char* desired_type = typecode_string(typecode); + const char* actual_type = typecode_string(array_type(input)); + PyErr_Format(PyExc_TypeError, + "Array of type '%s' required. Array of type '%s' given", + desired_type, actual_type); + ary = NULL; + } + else + { + const char * desired_type = typecode_string(typecode); + const char * actual_type = pytype_string(input); + PyErr_Format(PyExc_TypeError, + "Array of type '%s' required. A '%s' was given", + desired_type, actual_type); + ary = NULL; + } + return ary; + } + + /* Convert the given PyObject to a NumPy array with the given + * typecode. On success, return a valid PyArrayObject* with the + * correct type. On failure, the python error string will be set and + * the routine returns NULL. + */ + PyArrayObject* obj_to_array_allow_conversion(PyObject* input, int typecode, + int* is_new_object) + { + PyArrayObject* ary = NULL; + PyObject* py_obj; + if (is_array(input) && (typecode == NPY_NOTYPE || + PyArray_EquivTypenums(array_type(input),typecode))) + { + ary = (PyArrayObject*) input; + *is_new_object = 0; + } + else + { + py_obj = PyArray_FROMANY(input, typecode, 0, 0, NPY_DEFAULT); + /* If NULL, PyArray_FromObject will have set python error value.*/ + ary = (PyArrayObject*) py_obj; + *is_new_object = 1; + } + return ary; + } + + /* Given a PyArrayObject, check to see if it is contiguous. If so, + * return the input pointer and flag it as not a new object. If it is + * not contiguous, create a new PyArrayObject using the original data, + * flag it as a new object and return the pointer. + */ + PyArrayObject* make_contiguous(PyArrayObject* ary, int* is_new_object, + int min_dims, int max_dims) + { + PyArrayObject* result; + if (array_is_contiguous(ary)) + { + result = ary; + *is_new_object = 0; + } + else + { + result = (PyArrayObject*) PyArray_ContiguousFromObject((PyObject*)ary, + array_type(ary), + min_dims, + max_dims); + *is_new_object = 1; + } + return result; + } + + /* Given a PyArrayObject, check to see if it is Fortran-contiguous. + * If so, return the input pointer, but do not flag it as not a new + * object. If it is not Fortran-contiguous, create a new + * PyArrayObject using the original data, flag it as a new object + * and return the pointer. + */ + PyArrayObject* make_fortran(PyArrayObject* ary, int* is_new_object, + int min_dims, int max_dims) + { + PyArrayObject* result; + if (array_is_fortran(ary)) + { + result = ary; + *is_new_object = 0; + } + else + { + Py_INCREF(ary->descr); + result = (PyArrayObject*) PyArray_FromArray(ary, ary->descr, NPY_FORTRAN); + *is_new_object = 1; + } + return result; + } + + /* Convert a given PyObject to a contiguous PyArrayObject of the + * specified type. If the input object is not a contiguous + * PyArrayObject, a new one will be created and the new object flag + * will be set. + */ + PyArrayObject* obj_to_array_contiguous_allow_conversion(PyObject* input, + int typecode, + int* is_new_object) + { + int is_new1 = 0; + int is_new2 = 0; + PyArrayObject* ary2; + PyArrayObject* ary1 = obj_to_array_allow_conversion(input, typecode, + &is_new1); + if (ary1) + { + ary2 = make_contiguous(ary1, &is_new2, 0, 0); + if ( is_new1 && is_new2) + { + Py_DECREF(ary1); + } + ary1 = ary2; + } + *is_new_object = is_new1 || is_new2; + return ary1; + } + + /* Convert a given PyObject to a Fortran-ordered PyArrayObject of the + * specified type. If the input object is not a Fortran-ordered + * PyArrayObject, a new one will be created and the new object flag + * will be set. + */ + PyArrayObject* obj_to_array_fortran_allow_conversion(PyObject* input, + int typecode, + int* is_new_object) + { + int is_new1 = 0; + int is_new2 = 0; + PyArrayObject* ary2; + PyArrayObject* ary1 = obj_to_array_allow_conversion(input, typecode, + &is_new1); + if (ary1) + { + ary2 = make_fortran(ary1, &is_new2, 0, 0); + if (is_new1 && is_new2) + { + Py_DECREF(ary1); + } + ary1 = ary2; + } + *is_new_object = is_new1 || is_new2; + return ary1; + } + +} /* end fragment */ + + +/**********************************************************************/ + +%fragment("NumPy_Array_Requirements", "header", + fragment="NumPy_Backward_Compatibility", + fragment="NumPy_Macros") +{ + /* Test whether a python object is contiguous. If array is + * contiguous, return 1. Otherwise, set the python error string and + * return 0. + */ + int require_contiguous(PyArrayObject* ary) + { + int contiguous = 1; + if (!array_is_contiguous(ary)) + { + PyErr_SetString(PyExc_TypeError, + "Array must be contiguous. A non-contiguous array was given"); + contiguous = 0; + } + return contiguous; + } + + /* Require that a numpy array is not byte-swapped. If the array is + * not byte-swapped, return 1. Otherwise, set the python error string + * and return 0. + */ + int require_native(PyArrayObject* ary) + { + int native = 1; + if (!array_is_native(ary)) + { + PyErr_SetString(PyExc_TypeError, + "Array must have native byteorder. " + "A byte-swapped array was given"); + native = 0; + } + return native; + } + + /* Require the given PyArrayObject to have a specified number of + * dimensions. If the array has the specified number of dimensions, + * return 1. Otherwise, set the python error string and return 0. + */ + int require_dimensions(PyArrayObject* ary, int exact_dimensions) + { + int success = 1; + if (array_numdims(ary) != exact_dimensions) + { + PyErr_Format(PyExc_TypeError, + "Array must have %d dimensions. Given array has %d dimensions", + exact_dimensions, array_numdims(ary)); + success = 0; + } + return success; + } + + /* Require the given PyArrayObject to have one of a list of specified + * number of dimensions. If the array has one of the specified number + * of dimensions, return 1. Otherwise, set the python error string + * and return 0. + */ + int require_dimensions_n(PyArrayObject* ary, int* exact_dimensions, int n) + { + int success = 0; + int i; + char dims_str[255] = ""; + char s[255]; + for (i = 0; i < n && !success; i++) + { + if (array_numdims(ary) == exact_dimensions[i]) + { + success = 1; + } + } + if (!success) + { + for (i = 0; i < n-1; i++) + { + sprintf(s, "%d, ", exact_dimensions[i]); + strcat(dims_str,s); + } + sprintf(s, " or %d", exact_dimensions[n-1]); + strcat(dims_str,s); + PyErr_Format(PyExc_TypeError, + "Array must have %s dimensions. Given array has %d dimensions", + dims_str, array_numdims(ary)); + } + return success; + } + + /* Require the given PyArrayObject to have a specified shape. If the + * array has the specified shape, return 1. Otherwise, set the python + * error string and return 0. + */ + int require_size(PyArrayObject* ary, npy_intp* size, int n) + { + int i; + int success = 1; + int len; + char desired_dims[255] = "["; + char s[255]; + char actual_dims[255] = "["; + for(i=0; i < n;i++) + { + if (size[i] != -1 && size[i] != array_size(ary,i)) + { + success = 0; + } + } + if (!success) + { + for (i = 0; i < n; i++) + { + if (size[i] == -1) + { + sprintf(s, "*,"); + } + else + { + sprintf(s, "%ld,", (long int)size[i]); + } + strcat(desired_dims,s); + } + len = strlen(desired_dims); + desired_dims[len-1] = ']'; + for (i = 0; i < n; i++) + { + sprintf(s, "%ld,", (long int)array_size(ary,i)); + strcat(actual_dims,s); + } + len = strlen(actual_dims); + actual_dims[len-1] = ']'; + PyErr_Format(PyExc_TypeError, + "Array must have shape of %s. Given array has shape of %s", + desired_dims, actual_dims); + } + return success; + } + + /* Require the given PyArrayObject to to be FORTRAN ordered. If the + * the PyArrayObject is already FORTRAN ordered, do nothing. Else, + * set the FORTRAN ordering flag and recompute the strides. + */ + int require_fortran(PyArrayObject* ary) + { + int success = 1; + int nd = array_numdims(ary); + int i; + if (array_is_fortran(ary)) return success; + /* Set the FORTRAN ordered flag */ + ary->flags = NPY_FARRAY; + /* Recompute the strides */ + ary->strides[0] = ary->strides[nd-1]; + for (i=1; i < nd; ++i) + ary->strides[i] = ary->strides[i-1] * array_size(ary,i-1); + return success; + } +} + +/* Combine all NumPy fragments into one for convenience */ +%fragment("NumPy_Fragments", "header", + fragment="NumPy_Backward_Compatibility", + fragment="NumPy_Macros", + fragment="NumPy_Utilities", + fragment="NumPy_Object_to_Array", + fragment="NumPy_Array_Requirements") { } + +/* End John Hunter translation (with modifications by Bill Spotz) + */ + +/* %numpy_typemaps() macro + * + * This macro defines a family of 41 typemaps that allow C arguments + * of the form + * + * (DATA_TYPE IN_ARRAY1[ANY]) + * (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1) + * (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1) + * + * (DATA_TYPE IN_ARRAY2[ANY][ANY]) + * (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2) + * (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2) + * + * (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY]) + * (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3) + * (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3) + * + * (DATA_TYPE INPLACE_ARRAY1[ANY]) + * (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1) + * (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1) + * + * (DATA_TYPE INPLACE_ARRAY2[ANY][ANY]) + * (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2) + * (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2) + * + * (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY]) + * (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3) + * (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + * (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3) + * + * (DATA_TYPE ARGOUT_ARRAY1[ANY]) + * (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1) + * (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1) + * + * (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY]) + * + * (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY]) + * + * (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1) + * (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1) + * + * (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) + * (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2) + * (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) + * (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2) + * + * (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) + * (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3) + * (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) + * (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3) + * + * where "DATA_TYPE" is any type supported by the NumPy module, and + * "DIM_TYPE" is any int-like type suitable for specifying dimensions. + * The difference between "ARRAY" typemaps and "FARRAY" typemaps is + * that the "FARRAY" typemaps expect FORTRAN ordering of + * multidimensional arrays. In python, the dimensions will not need + * to be specified (except for the "DATA_TYPE* ARGOUT_ARRAY1" + * typemaps). The IN_ARRAYs can be a numpy array or any sequence that + * can be converted to a numpy array of the specified type. The + * INPLACE_ARRAYs must be numpy arrays of the appropriate type. The + * ARGOUT_ARRAYs will be returned as new numpy arrays of the + * appropriate type. + * + * These typemaps can be applied to existing functions using the + * %apply directive. For example: + * + * %apply (double* IN_ARRAY1, int DIM1) {(double* series, int length)}; + * double prod(double* series, int length); + * + * %apply (int DIM1, int DIM2, double* INPLACE_ARRAY2) + * {(int rows, int cols, double* matrix )}; + * void floor(int rows, int cols, double* matrix, double f); + * + * %apply (double IN_ARRAY3[ANY][ANY][ANY]) + * {(double tensor[2][2][2] )}; + * %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY]) + * {(double low[2][2][2] )}; + * %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY]) + * {(double upp[2][2][2] )}; + * void luSplit(double tensor[2][2][2], + * double low[2][2][2], + * double upp[2][2][2] ); + * + * or directly with + * + * double prod(double* IN_ARRAY1, int DIM1); + * + * void floor(int DIM1, int DIM2, double* INPLACE_ARRAY2, double f); + * + * void luSplit(double IN_ARRAY3[ANY][ANY][ANY], + * double ARGOUT_ARRAY3[ANY][ANY][ANY], + * double ARGOUT_ARRAY3[ANY][ANY][ANY]); + */ + +%define %numpy_typemaps(DATA_TYPE, DATA_TYPECODE, DIM_TYPE) + +/************************/ +/* Input Array Typemaps */ +/************************/ + +/* Typemap suite for (DATA_TYPE IN_ARRAY1[ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE IN_ARRAY1[ANY]) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE IN_ARRAY1[ANY]) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[1] = { $1_dim0 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 1) || + !require_size(array, size, 1)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(freearg) + (DATA_TYPE IN_ARRAY1[ANY]) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[1] = { -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 1) || + !require_size(array, size, 1)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); +} +%typemap(freearg) + (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[1] = {-1}; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 1) || + !require_size(array, size, 1)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DATA_TYPE*) array_data(array); +} +%typemap(freearg) + (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE IN_ARRAY2[ANY][ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE IN_ARRAY2[ANY][ANY]) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE IN_ARRAY2[ANY][ANY]) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[2] = { $1_dim0, $1_dim1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 2) || + !require_size(array, size, 2)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(freearg) + (DATA_TYPE IN_ARRAY2[ANY][ANY]) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[2] = { -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 2) || + !require_size(array, size, 2)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); +} +%typemap(freearg) + (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[2] = { -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 2) || + !require_size(array, size, 2)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DATA_TYPE*) array_data(array); +} +%typemap(freearg) + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[2] = { -1, -1 }; + array = obj_to_array_fortran_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 2) || + !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); +} +%typemap(freearg) + (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[2] = { -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 2) || + !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DATA_TYPE*) array_data(array); +} +%typemap(freearg) + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY]) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY]) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[3] = { $1_dim0, $1_dim1, $1_dim2 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 3) || + !require_size(array, size, 3)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(freearg) + (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY]) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, + * DIM_TYPE DIM3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[3] = { -1, -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 3) || + !require_size(array, size, 3)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); + $4 = (DIM_TYPE) array_size(array,2); +} +%typemap(freearg) + (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, + * DATA_TYPE* IN_ARRAY3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[3] = { -1, -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 3) || + !require_size(array, size, 3)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DIM_TYPE) array_size(array,2); + $4 = (DATA_TYPE*) array_data(array); +} +%typemap(freearg) + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, + * DIM_TYPE DIM3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[3] = { -1, -1, -1 }; + array = obj_to_array_fortran_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 3) || + !require_size(array, size, 3) | !require_fortran(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); + $4 = (DIM_TYPE) array_size(array,2); +} +%typemap(freearg) + (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, + * DATA_TYPE* IN_FARRAY3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3) +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3) + (PyArrayObject* array=NULL, int is_new_object=0) +{ + npy_intp size[3] = { -1, -1, -1 }; + array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE, + &is_new_object); + if (!array || !require_dimensions(array, 3) || + !require_size(array, size, 3) || !require_fortran(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DIM_TYPE) array_size(array,2); + $4 = (DATA_TYPE*) array_data(array); +} +%typemap(freearg) + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3) +{ + if (is_new_object$argnum && array$argnum) + { Py_DECREF(array$argnum); } +} + +/***************************/ +/* In-Place Array Typemaps */ +/***************************/ + +/* Typemap suite for (DATA_TYPE INPLACE_ARRAY1[ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE INPLACE_ARRAY1[ANY]) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE INPLACE_ARRAY1[ANY]) + (PyArrayObject* array=NULL) +{ + npy_intp size[1] = { $1_dim0 }; + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,1) || !require_size(array, size, 1) || + !require_contiguous(array) || !require_native(array)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} + +/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1) + (PyArrayObject* array=NULL, int i=1) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,1) || !require_contiguous(array) + || !require_native(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = 1; + for (i=0; i < array_numdims(array); ++i) $2 *= array_size(array,i); +} + +/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1) + (PyArrayObject* array=NULL, int i=0) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,1) || !require_contiguous(array) + || !require_native(array)) SWIG_fail; + $1 = 1; + for (i=0; i < array_numdims(array); ++i) $1 *= array_size(array,i); + $2 = (DATA_TYPE*) array_data(array); +} + +/* Typemap suite for (DATA_TYPE INPLACE_ARRAY2[ANY][ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE INPLACE_ARRAY2[ANY][ANY]) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE INPLACE_ARRAY2[ANY][ANY]) + (PyArrayObject* array=NULL) +{ + npy_intp size[2] = { $1_dim0, $1_dim1 }; + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,2) || !require_size(array, size, 2) || + !require_contiguous(array) || !require_native(array)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} + +/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,2) || !require_contiguous(array) + || !require_native(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,2) || !require_contiguous(array) || + !require_native(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DATA_TYPE*) array_data(array); +} + +/* Typemap suite for (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,2) || !require_contiguous(array) + || !require_native(array) || !require_fortran(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,2) || !require_contiguous(array) || + !require_native(array) || !require_fortran(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DATA_TYPE*) array_data(array); +} + +/* Typemap suite for (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY]) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY]) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY]) + (PyArrayObject* array=NULL) +{ + npy_intp size[3] = { $1_dim0, $1_dim1, $1_dim2 }; + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,3) || !require_size(array, size, 3) || + !require_contiguous(array) || !require_native(array)) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} + +/* Typemap suite for (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, + * DIM_TYPE DIM3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,3) || !require_contiguous(array) || + !require_native(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); + $4 = (DIM_TYPE) array_size(array,2); +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, + * DATA_TYPE* INPLACE_ARRAY3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,3) || !require_contiguous(array) + || !require_native(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DIM_TYPE) array_size(array,2); + $4 = (DATA_TYPE*) array_data(array); +} + +/* Typemap suite for (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, + * DIM_TYPE DIM3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,3) || !require_contiguous(array) || + !require_native(array) || !require_fortran(array)) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); + $2 = (DIM_TYPE) array_size(array,0); + $3 = (DIM_TYPE) array_size(array,1); + $4 = (DIM_TYPE) array_size(array,2); +} + +/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, + * DATA_TYPE* INPLACE_FARRAY3) + */ +%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY, + fragment="NumPy_Macros") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3) +{ + $1 = is_array($input) && PyArray_EquivTypenums(array_type($input), + DATA_TYPECODE); +} +%typemap(in, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3) + (PyArrayObject* array=NULL) +{ + array = obj_to_array_no_conversion($input, DATA_TYPECODE); + if (!array || !require_dimensions(array,3) || !require_contiguous(array) + || !require_native(array) || !require_fortran(array)) SWIG_fail; + $1 = (DIM_TYPE) array_size(array,0); + $2 = (DIM_TYPE) array_size(array,1); + $3 = (DIM_TYPE) array_size(array,2); + $4 = (DATA_TYPE*) array_data(array); +} + +/*************************/ +/* Argout Array Typemaps */ +/*************************/ + +/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY1[ANY]) + */ +%typemap(in,numinputs=0, + fragment="NumPy_Backward_Compatibility,NumPy_Macros") + (DATA_TYPE ARGOUT_ARRAY1[ANY]) + (PyObject * array = NULL) +{ + npy_intp dims[1] = { $1_dim0 }; + array = PyArray_SimpleNew(1, dims, DATA_TYPECODE); + if (!array) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(argout) + (DATA_TYPE ARGOUT_ARRAY1[ANY]) +{ + $result = SWIG_Python_AppendOutput($result,array$argnum); +} + +/* Typemap suite for (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1) + */ +%typemap(in,numinputs=1, + fragment="NumPy_Fragments") + (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1) + (PyObject * array = NULL) +{ + npy_intp dims[1]; + if (!PyInt_Check($input)) + { + const char* typestring = pytype_string($input); + PyErr_Format(PyExc_TypeError, + "Int dimension expected. '%s' given.", + typestring); + SWIG_fail; + } + $2 = (DIM_TYPE) PyInt_AsLong($input); + dims[0] = (npy_intp) $2; + array = PyArray_SimpleNew(1, dims, DATA_TYPECODE); + if (!array) SWIG_fail; + $1 = (DATA_TYPE*) array_data(array); +} +%typemap(argout) + (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1) +{ + $result = SWIG_Python_AppendOutput($result,array$argnum); +} + +/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1) + */ +%typemap(in,numinputs=1, + fragment="NumPy_Fragments") + (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1) + (PyObject * array = NULL) +{ + npy_intp dims[1]; + if (!PyInt_Check($input)) + { + const char* typestring = pytype_string($input); + PyErr_Format(PyExc_TypeError, + "Int dimension expected. '%s' given.", + typestring); + SWIG_fail; + } + $1 = (DIM_TYPE) PyInt_AsLong($input); + dims[0] = (npy_intp) $1; + array = PyArray_SimpleNew(1, dims, DATA_TYPECODE); + if (!array) SWIG_fail; + $2 = (DATA_TYPE*) array_data(array); +} +%typemap(argout) + (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1) +{ + $result = SWIG_Python_AppendOutput($result,array$argnum); +} + +/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY]) + */ +%typemap(in,numinputs=0, + fragment="NumPy_Backward_Compatibility,NumPy_Macros") + (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY]) + (PyObject * array = NULL) +{ + npy_intp dims[2] = { $1_dim0, $1_dim1 }; + array = PyArray_SimpleNew(2, dims, DATA_TYPECODE); + if (!array) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(argout) + (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY]) +{ + $result = SWIG_Python_AppendOutput($result,array$argnum); +} + +/* Typemap suite for (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY]) + */ +%typemap(in,numinputs=0, + fragment="NumPy_Backward_Compatibility,NumPy_Macros") + (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY]) + (PyObject * array = NULL) +{ + npy_intp dims[3] = { $1_dim0, $1_dim1, $1_dim2 }; + array = PyArray_SimpleNew(3, dims, DATA_TYPECODE); + if (!array) SWIG_fail; + $1 = ($1_ltype) array_data(array); +} +%typemap(argout) + (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY]) +{ + $result = SWIG_Python_AppendOutput($result,array$argnum); +} + +/*****************************/ +/* Argoutview Array Typemaps */ +/*****************************/ + +/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1) + */ +%typemap(in,numinputs=0) + (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1 ) + (DATA_TYPE* data_temp , DIM_TYPE dim_temp) +{ + $1 = &data_temp; + $2 = &dim_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1) +{ + npy_intp dims[1] = { *$2 }; + PyObject * array = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$1)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1) + */ +%typemap(in,numinputs=0) + (DIM_TYPE* DIM1 , DATA_TYPE** ARGOUTVIEW_ARRAY1) + (DIM_TYPE dim_temp, DATA_TYPE* data_temp ) +{ + $1 = &dim_temp; + $2 = &data_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1) +{ + npy_intp dims[1] = { *$1 }; + PyObject * array = PyArray_SimpleNewFromData(1, dims, DATA_TYPECODE, (void*)(*$2)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) + */ +%typemap(in,numinputs=0) + (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 ) + (DATA_TYPE* data_temp , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp) +{ + $1 = &data_temp; + $2 = &dim1_temp; + $3 = &dim2_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) +{ + npy_intp dims[2] = { *$2, *$3 }; + PyObject * array = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2) + */ +%typemap(in,numinputs=0) + (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEW_ARRAY2) + (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp ) +{ + $1 = &dim1_temp; + $2 = &dim2_temp; + $3 = &data_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2) +{ + npy_intp dims[2] = { *$1, *$2 }; + PyObject * array = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) + */ +%typemap(in,numinputs=0) + (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1 , DIM_TYPE* DIM2 ) + (DATA_TYPE* data_temp , DIM_TYPE dim1_temp, DIM_TYPE dim2_temp) +{ + $1 = &data_temp; + $2 = &dim1_temp; + $3 = &dim2_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements") + (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2) +{ + npy_intp dims[2] = { *$2, *$3 }; + PyObject * obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$1)); + PyArrayObject * array = (PyArrayObject*) obj; + if (!array || !require_fortran(array)) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,obj); +} + +/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2) + */ +%typemap(in,numinputs=0) + (DIM_TYPE* DIM1 , DIM_TYPE* DIM2 , DATA_TYPE** ARGOUTVIEW_FARRAY2) + (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DATA_TYPE* data_temp ) +{ + $1 = &dim1_temp; + $2 = &dim2_temp; + $3 = &data_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements") + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2) +{ + npy_intp dims[2] = { *$1, *$2 }; + PyObject * obj = PyArray_SimpleNewFromData(2, dims, DATA_TYPECODE, (void*)(*$3)); + PyArrayObject * array = (PyArrayObject*) obj; + if (!array || !require_fortran(array)) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,obj); +} + +/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, + DIM_TYPE* DIM3) + */ +%typemap(in,numinputs=0) + (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) + (DATA_TYPE* data_temp, DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp) +{ + $1 = &data_temp; + $2 = &dim1_temp; + $3 = &dim2_temp; + $4 = &dim3_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) +{ + npy_intp dims[3] = { *$2, *$3, *$4 }; + PyObject * array = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, + DATA_TYPE** ARGOUTVIEW_ARRAY3) + */ +%typemap(in,numinputs=0) + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3) + (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp) +{ + $1 = &dim1_temp; + $2 = &dim2_temp; + $3 = &dim3_temp; + $4 = &data_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility") + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3) +{ + npy_intp dims[3] = { *$1, *$2, *$3 }; + PyObject * array = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$3)); + if (!array) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,array); +} + +/* Typemap suite for (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, + DIM_TYPE* DIM3) + */ +%typemap(in,numinputs=0) + (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) + (DATA_TYPE* data_temp, DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp) +{ + $1 = &data_temp; + $2 = &dim1_temp; + $3 = &dim2_temp; + $4 = &dim3_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements") + (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3) +{ + npy_intp dims[3] = { *$2, *$3, *$4 }; + PyObject * obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$1)); + PyArrayObject * array = (PyArrayObject*) obj; + if (!array || require_fortran(array)) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,obj); +} + +/* Typemap suite for (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, + DATA_TYPE** ARGOUTVIEW_FARRAY3) + */ +%typemap(in,numinputs=0) + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3) + (DIM_TYPE dim1_temp, DIM_TYPE dim2_temp, DIM_TYPE dim3_temp, DATA_TYPE* data_temp) +{ + $1 = &dim1_temp; + $2 = &dim2_temp; + $3 = &dim3_temp; + $4 = &data_temp; +} +%typemap(argout, + fragment="NumPy_Backward_Compatibility,NumPy_Array_Requirements") + (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3) +{ + npy_intp dims[3] = { *$1, *$2, *$3 }; + PyObject * obj = PyArray_SimpleNewFromData(3, dims, DATA_TYPECODE, (void*)(*$3)); + PyArrayObject * array = (PyArrayObject*) obj; + if (!array || require_fortran(array)) SWIG_fail; + $result = SWIG_Python_AppendOutput($result,obj); +} + +%enddef /* %numpy_typemaps() macro */ +/* *************************************************************** */ + +/* Concrete instances of the %numpy_typemaps() macro: Each invocation + * below applies all of the typemaps above to the specified data type. + */ +%numpy_typemaps(signed char , NPY_BYTE , int) +%numpy_typemaps(unsigned char , NPY_UBYTE , int) +%numpy_typemaps(short , NPY_SHORT , int) +%numpy_typemaps(unsigned short , NPY_USHORT , int) +%numpy_typemaps(int , NPY_INT , int) +%numpy_typemaps(unsigned int , NPY_UINT , int) +%numpy_typemaps(long , NPY_LONG , int) +%numpy_typemaps(unsigned long , NPY_ULONG , int) +%numpy_typemaps(long long , NPY_LONGLONG , int) +%numpy_typemaps(unsigned long long, NPY_ULONGLONG, int) +%numpy_typemaps(float , NPY_FLOAT , int) +%numpy_typemaps(double , NPY_DOUBLE , int) + +/* *************************************************************** + * The follow macro expansion does not work, because C++ bool is 4 + * bytes and NPY_BOOL is 1 byte + * + * %numpy_typemaps(bool, NPY_BOOL, int) + */ + +/* *************************************************************** + * On my Mac, I get the following warning for this macro expansion: + * 'swig/python detected a memory leak of type 'long double *', no destructor found.' + * + * %numpy_typemaps(long double, NPY_LONGDOUBLE, int) + */ + +/* *************************************************************** + * Swig complains about a syntax error for the following macro + * expansions: + * + * %numpy_typemaps(complex float, NPY_CFLOAT , int) + * + * %numpy_typemaps(complex double, NPY_CDOUBLE, int) + * + * %numpy_typemaps(complex long double, NPY_CLONGDOUBLE, int) + */ + +#endif /* SWIGPYTHON */ diff --git a/okapi-typemaps.i b/okapi-typemaps.i new file mode 100644 index 0000000..e5708ea --- /dev/null +++ b/okapi-typemaps.i @@ -0,0 +1,458 @@ +%{ +#define SWIG_FILE_WITH_INIT + +#if ((PY_MAJOR_VERSION == 2 && PY_MINOR_VERSION > 6) || \ + (PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION > 0) || \ + (PY_MAJOR_VERSION > 3)) +#define CAPSULES_SUPPORTED +#endif +%} + +%include "numpy.i" +%init %{ +import_array(); +%} + +%fragment("OKAPI_Fragments", "header", + fragment="NumPy_Fragments") +{ + // convert NumPy type to OpenCV type + int numpy_type_to_mat_type(PyArrayObject *array, int channels) + { + switch (array_type(array)) { + case NPY_BYTE: return CV_MAKETYPE(CV_8S, channels); + case NPY_UBYTE: return CV_MAKETYPE(CV_8U, channels); + case NPY_SHORT: return CV_MAKETYPE(CV_16S, channels); + case NPY_USHORT: return CV_MAKETYPE(CV_16U, channels); + case NPY_INT: return CV_MAKETYPE(CV_32S, channels); + //case NPY_UINT: // does not exist + //case NPY_LONG: // does not exist + //case NPY_ULONG: // does not exist + case NPY_FLOAT: return CV_MAKETYPE(CV_32F, channels); + case NPY_DOUBLE: return CV_MAKETYPE(CV_64F, channels); + default: + PyErr_Format(PyExc_TypeError, + "Unsupported datatype: %s.", + typecode_string(array_type(array))); + } + return -1; + } + + // convert OpenCV type to NumPy type + int mat_type_to_numpy_type(int type) + { + // convert numpy type to CV type + switch (CV_MAT_DEPTH(type)) { + case CV_8S: return NPY_BYTE; + case CV_8U: return NPY_UBYTE; + case CV_16S: return NPY_SHORT; + case CV_16U: return NPY_USHORT; + case CV_32S: return NPY_INT; + //case NPY_UINT: // does not exist + //case NPY_LONG: // does not exist + //case NPY_ULONG: // does not exist + case CV_32F: return NPY_FLOAT; + case CV_64F: return NPY_DOUBLE; + default: + PyErr_Format(PyExc_TypeError, + "Unsupported OpenCV datatype: %d (depth: %d).", + type, CV_MAT_DEPTH(type)); + } + return -1; + } + + void delete_mat(void *ptr) + { + // printf("deleting underlying mat at %p\n", ptr); + cv::Mat *m = static_cast(ptr); + assert (m != NULL); + delete m; + } + +%#ifdef CAPSULES_SUPPORTED + void delete_mat_capsule(PyObject *obj) + { + // printf("deleting underlying mat at %p\n", ptr); + cv::Mat *m = static_cast(PyCapsule_GetPointer(obj, NULL)); + assert (m != NULL); + delete m; + } +%#endif + + cv::Mat* array_to_mat(PyObject* input) + { + PyArrayObject* array = obj_to_array_no_conversion(input, NPY_NOTYPE); + if (array == NULL) { + // error message is set by obj_to_array_no_conversion + return NULL; + } + + // check if array has 2 or 3 dimensions + int ndims = array_numdims(array); + int channels, type; + if (ndims == 2) + channels = 1; + else if (ndims == 3) { + channels = array_size(array, 2); + // check number of channels + if (channels > 4) { + PyErr_Format(PyExc_TypeError, + "Array can have a maximum of 4 channels. Input as %d.", channels); + return NULL; + } + } + else { + PyErr_Format(PyExc_TypeError, + "Array must be 2- or 3-dimensional. Input is %d-dimensional.", ndims); + return NULL; + } + + // convert NumPy type to OpenCV type + if ((type = numpy_type_to_mat_type(array, channels)) == -1) + return NULL; + + // check that array is in C order + for (int i = 0; i < ndims-1; ++i) { + if (PyArray_STRIDE(array, i) < PyArray_STRIDE(array, i+1)) { + PyErr_Format(PyExc_TypeError, + "Array is not in C order: stride of dim %d: %ld < stride of dim %d: %ld", + i, PyArray_STRIDE(array, i), i+1, PyArray_STRIDE(array, i+1)); + return NULL; + } + } + + // use stride of first dimension as stepsize + // and check strides of other dimensions + int step = ((PyArrayObject *)array)->strides[0]; + if (PyArray_STRIDE(array, 1) != channels * PyArray_ITEMSIZE(array)) { + PyErr_Format(PyExc_TypeError, + "Array cannot have strides in other than 1st dimension (rows). Dim 2: %ld vs %d", + PyArray_STRIDE(array, 1), channels * PyArray_ITEMSIZE(array)); + return NULL; + } + + // create new view onto the data + return new cv::Mat(array_size(array, 0), array_size(array, 1), type, array_data(array), step); + } + + PyObject* mat_to_array(const cv::Mat& mat) + { + // handle empty mat + if (mat.empty()) { + npy_intp dims[1] = { 0 }; + int type = mat_type_to_numpy_type(mat.type()); + PyObject* array = PyArray_EMPTY(1, dims, type, 0); + return array; + } + + npy_intp dims[3] = { mat.rows, mat.cols, mat.channels() }; + npy_intp strides[3] = { mat.step, mat.elemSize(), mat.elemSize1()}; + int ndims = (mat.channels() > 1) ? 3 : 2; + int type = mat_type_to_numpy_type(mat.type()); + int flags = NPY_WRITEABLE; + if (mat.isContinuous()) + flags |= NPY_C_CONTIGUOUS; + PyObject* array = PyArray_New(&PyArray_Type, ndims, dims, type, + strides, mat.data, 0, flags, NULL); + return array; + } + +} + +/////////////////////////////////////// +/// const cv::Mat& +/////////////////////////////////////// +%typecheck(SWIG_TYPECHECK_POINTER, + fragment="OKAPI_Fragments") + const cv::Mat& +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, numinputs=1, + fragment="OKAPI_Fragments") + const cv::Mat& +{ + $1 = array_to_mat($input); + if ($1 == NULL) + SWIG_fail; +} +%typemap(freearg, + fragment="OKAPI_Fragments") + const cv::Mat& +{ + if ($1 != NULL) + delete $1; +} +%typemap(argout, + fragment="OKAPI_Fragments") + const cv::Mat& +{ +} + +/////////////////////////////////////// +/// cv::Mat +/////////////////////////////////////// +%typecheck(SWIG_TYPECHECK_POINTER, + fragment="OKAPI_Fragments") + cv::Mat +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, numinputs=1, + fragment="OKAPI_Fragments") + cv::Mat + (cv::Mat* mat) +{ + mat = array_to_mat($input); + if (mat == NULL) + SWIG_fail; + $1 = *mat; +} +%typemap(freearg, + fragment="OKAPI_Fragments") + cv::Mat +{ + if (mat$argnum != NULL) + delete mat$argnum; +} +%typemap(argout, + fragment="OKAPI_Fragments") + cv::Mat +{ +} + +/////////////////////////////////////// +/// cv::Mat* +/////////////////////////////////////// +%typecheck(SWIG_TYPECHECK_POINTER, + fragment="OKAPI_Fragments") + cv::Mat* +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, numinputs=1, + fragment="OKAPI_Fragments") + cv::Mat* + (uchar* data_ptr) +{ + $1 = array_to_mat($input); + if ($1 == NULL) + SWIG_fail; + // save dataptr to check whether it changed + data_ptr = $1->data; +} +%typemap(freearg, + fragment="OKAPI_Fragments") + cv::Mat* +{ + if ($1 != NULL) + delete $1; +} +%typemap(argout, + fragment="OKAPI_Fragments") + cv::Mat* +{ + // check if the underlying data changed + if (data_ptr$argnum != $1->data) { + // TODO don't fail if we can reallocate the underlying memory + // (not always possible due to the way NumPy does reference counting) + PyErr_Format(PyExc_RuntimeError, + "Underlying data changed. Please make sure that the " + "input data is of correct size and type: %d %d %d", + $1->rows, $1->cols, $1->type()); + SWIG_fail; + } +} + +/////////////////////////////////////// +/// cv::Mat& +/////////////////////////////////////// +%typecheck(SWIG_TYPECHECK_POINTER, + fragment="OKAPI_Fragments") + cv::Mat& +{ + $1 = is_array($input) || PySequence_Check($input); +} +%typemap(in, numinputs=1, + fragment="OKAPI_Fragments") + cv::Mat& + (uchar* data_ptr) +{ + $1 = array_to_mat($input); + if ($1 == NULL) + SWIG_fail; + // save dataptr to check whether it changed + data_ptr = $1->data; +} +%typemap(freearg, + fragment="OKAPI_Fragments") + cv::Mat& +{ + if ($1 != NULL) + delete $1; +} +%typemap(argout, + fragment="OKAPI_Fragments") + cv::Mat& +{ + // check if the underlying data changed + if (data_ptr$argnum != $1->data) { + // TODO don't fail if we can reallocate the underlying memory + // (not always possible due to the way NumPy does reference counting) + PyErr_Format(PyExc_RuntimeError, + "Underlying data changed. Please make sure that the " + "input data is of correct size and type: %d %d %d", + $1->rows, $1->cols, $1->type()); + SWIG_fail; + } +} + +/////////////////////////////////////// +/// return cv::Mat +/////////////////////////////////////// +%typemap(out, + fragment="NumPy_Fragments") + cv::Mat +{ + PyObject* array = mat_to_array($1); + if (array == NULL) + SWIG_fail; + + // add a reference to the underlying cv::Mat so + // that the memory is not freed before the NumPy array + // is released or reassigned + cv::Mat *m = new cv::Mat($1); + // printf("created new mat object at %p\n", m); + %#ifdef CAPSULES_SUPPORTED + PyArray_BASE(array) = PyCapsule_New(m, NULL, delete_mat_capsule); + %#else + PyArray_BASE(array) = PyCObject_FromVoidPtr(m, delete_mat); + %#endif + + $result = array; +} + +%typemap(out, + fragment="NumPy_Fragments") + const cv::Mat& +{ + PyObject* array = mat_to_array(*$1); + if (array == NULL) + SWIG_fail; + + // add a reference to the underlying cv::Mat so + // that the memory is not freed before the NumPy array + // is released or reassigned + cv::Mat *m = new cv::Mat(*$1); + // printf("created new mat object at %p\n", m); + %#ifdef CAPSULES_SUPPORTED + PyArray_BASE(array) = PyCapsule_New(m, NULL, delete_mat_capsule); + %#else + PyArray_BASE(array) = PyCObject_FromVoidPtr(m, delete_mat); + %#endif + + $result = array; +} + +/////////////////////////////////////// +// vector +/////////////////////////////////////// +%define %vector_typemap(T) +%typecheck(SWIG_TYPECHECK_POINTER, + fragment="OKAPI_Fragments") + const std::vector & +{ + $1 = PySequence_Check($input); +} +%typemap(in, + fragment="OKAPI_Fragments") + const std::vector & + (std::vector relvec) +{ + if (!PySequence_Check($input)) { + printf("NO SEQUENCE\n"); + SWIG_fail; + } + + Py_ssize_t length = PySequence_Size($input); + $1 = new std::vector(length); + for (Py_ssize_t ii = 0; ii < length; ++ii) { + cv::Mat *tmp = array_to_mat(PySequence_GetItem($input, ii)); + if (tmp == NULL) { + printf("%ld no array\n", ii); + SWIG_fail; + } + $1->at(ii) = *tmp; + relvec.push_back(tmp); + } +} +%typemap(freearg, + fragment="OKAPI_Fragments") + const std::vector & +{ + if ($1 != NULL) + delete $1; + for (size_t ii = 0; ii < relvec$argnum.size(); ++ii) + delete relvec$argnum[ii]; +} +%enddef + + +/////////////////////////////////////// +// okapi::bstring +/////////////////////////////////////// +%typemap(out) okapi::bstring +{ + $result = PyByteArray_FromStringAndSize((const char*) &$1[0], $1.size()); +} + + +/////////////////////////////////////// +// buffers +/////////////////////////////////////// +%typemap(in) (const void *buffer, std::size_t buffer_size) { + if (PyByteArray_Check($input)) { + $1 = (void *) PyByteArray_AsString($input); + $2 = PyByteArray_Size($input); + } +%#if PY_MAJOR_VERSION < 3 + else if (PyString_Check($input)) { + $1 = (void *) PyString_AsString($input); + $2 = PyString_Size($input); + } +%#endif + else { + PyErr_SetString(PyExc_ValueError, "Expecting a bytearray"); + return NULL; + } +} +%typemap(typecheck) (const void *buffer, std::size_t buffer_size) { + $1 = (PyByteArray_Check($input) || PyString_Check($input)) ? 1 : 0; +} + + +/////////////////////////////////////// +// boost::filesystem::path +/////////////////////////////////////// +%typecheck(SWIG_TYPECHECK_POINTER) + const boost::filesystem::path & +{ + $1 = PyUnicode_Check($input) || PyBytes_Check($input); +} +%typemap(in) const boost::filesystem::path & +{ + if (PyUnicode_Check($input)) + { + PyObject *bytes = PyUnicode_AsEncodedString($input, Py_FileSystemDefaultEncoding, "surrogateescape"); + $1 = new boost::filesystem::path(PyBytes_AsString(bytes)); + Py_CLEAR(bytes); + } + else if (PyBytes_Check($input)) + { + $1 = new boost::filesystem::path(PyBytes_AsString($input)); + } +} +%typemap(freearg) const boost::filesystem::path +{ + delete $1; +} diff --git a/test_swig_opencv.cpp b/test_swig_opencv.cpp new file mode 100644 index 0000000..90ba61c --- /dev/null +++ b/test_swig_opencv.cpp @@ -0,0 +1,8 @@ +#include "test_swig_opencv.hpp" + +#include + +void UsefulStuffUsingOpenCV::doit(cv::Mat& input) { + // Draw a circle + cv::circle(input, cv::Point2f(input.cols/2, input.rows/2), input.cols/5, 0, -1); +} diff --git a/test_swig_opencv.hpp b/test_swig_opencv.hpp new file mode 100644 index 0000000..90d6119 --- /dev/null +++ b/test_swig_opencv.hpp @@ -0,0 +1,8 @@ +// #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION + +#include + +class UsefulStuffUsingOpenCV { + public: + void doit(cv::Mat& input); +}; diff --git a/test_swig_opencv.i b/test_swig_opencv.i new file mode 100644 index 0000000..76d03e5 --- /dev/null +++ b/test_swig_opencv.i @@ -0,0 +1,12 @@ +%module test_swig_opencv +%{ +#include "test_swig_opencv.hpp" +%} + +%include "typemaps.i" +%include "okapi-typemaps.i" +%include "numpy.i" + +// Parse the original header file +%include "test_swig_opencv.hpp" + diff --git a/test_swig_opencv.jpg b/test_swig_opencv.jpg new file mode 100644 index 0000000..979d277 Binary files /dev/null and b/test_swig_opencv.jpg differ diff --git a/test_swig_opencv_test.py b/test_swig_opencv_test.py new file mode 100644 index 0000000..1b46342 --- /dev/null +++ b/test_swig_opencv_test.py @@ -0,0 +1,13 @@ +#!/usr/bin/python2.7 + +import cv2 +import test_swig_opencv + +img = cv2.imread("test_swig_opencv.jpg") + +o = test_swig_opencv.UsefulStuffUsingOpenCV() +o.doit(img) + +cv2.namedWindow("test", flags=cv2.WINDOW_NORMAL) +cv2.imshow("test", img) +cv2.waitKey(0)