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Minimal example to demonstrate how to use the sampler written in python to sample from a class method defined in C++. It also shows how get it to run with mpi4py to run on hundreds of processors.
Raw
a call C++ class method from python through swig.md

Minimal example to demonstrate how to use the emcee sampler written in python to sample from a class method defined in C++. It also shows how get it to run with mpi4py to run on hundreds of processors. The target density is a 1D unit Gaussian.

Download the gist, then run

python setup.py install

Build requirements are C++, swig, python, numpy, mpi4py, and emcee.

The example is an extension of the mpi.py example shipping with emcee. The two tricky parts are to pickle the call the right way such that the calculation can be spread to independent processes.

  1. We want to pickle a python class method, not a free standing function.
  2. The class is a swig interface class to a C++ class.
Raw
mpi.py
#!/usr/bin/env python
"""
Run this example with:
mpirun -np 2 python examples/mpi.py
"""
from __future__ import print_function
import sys
import numpy as np
import emcee
from emcee.utils import MPIPool
import swig_test
"""
Pickling a method
http://stackoverflow.com/questions/1816958/cant-pickle-type-instancemethod-when-using-pythons-multiprocessing-pool-ma
"""
def _pickle_method(method):
func_name = method.im_func.__name__
obj = method.im_self
cls = method.im_class
return _unpickle_method, (func_name, obj, cls)
def _unpickle_method(func_name, obj, cls):
for cls in cls.mro():
try:
func = cls.__dict__[func_name]
except KeyError:
pass
else:
break
return func.__get__(obj, cls)
import copy_reg
import types
copy_reg.pickle(types.MethodType, _pickle_method, _unpickle_method)
"""
Pickling a SWIG object
http://stackoverflow.com/questions/9310053/how-to-make-my-swig-extension-module-work-with-pickle
"""
class PickalableSWIG:
def __setstate__(self, state):
self.__init__(*state['args'])
def __getstate__(self):
return {'args': self.args}
class PickalableC(swig_test.Adapter, PickalableSWIG):
def __init__(self, *args):
self.args = args
swig_test.Adapter.__init__(self, *args)
# Initialize the MPI-based pool used for parallelization.
pool = MPIPool()
if not pool.is_master():
# Wait for instructions from the master process.
pool.wait()
sys.exit(0)
ndim = 1
nwalkers = 250
p0 = [np.random.rand(ndim) for i in xrange(nwalkers)]
ad = PickalableC(13, 2)
print("Adapter owns C++ object: %s" % ad.thisown)
# ad = swig_test.Adapter(0, 1)
# Initialize the sampler with the chosen specs.
sampler = emcee.EnsembleSampler(nwalkers, ndim, ad.llh, pool=pool)
# Run 100 steps as a burn-in.
pos, prob, state = sampler.run_mcmc(p0, 100)
# Reset the chain to remove the burn-in samples.
sampler.reset()
# Starting from the final position in the burn-in chain, sample for 1000
# steps.
sampler.run_mcmc(pos, 1000, rstate0=state)
# Close the processes.
pool.close()
# Print out the mean acceptance fraction. In general, acceptance_fraction
# has an entry for each walker so, in this case, it is a 250-dimensional
# vector.
print(u"Mean acceptance fraction: ", np.mean(sampler.acceptance_fraction))
if pool.is_master():
try:
import matplotlib.pyplot as pl
except ImportError:
print("Try installing matplotlib to generate some sweet plots...")
else:
pl.hist(sampler.flatchain[:,0], 100)
pl.savefig("mpi.pdf")
Raw
numpy.i
/* -*- C -*- (not really, but good for syntax highlighting) */
#ifdef SWIGPYTHON
%{
#ifndef SWIG_FILE_WITH_INIT
# define NO_IMPORT_ARRAY
#endif
#include "stdio.h"
#include <numpy/arrayobject.h>
%}
/**********************************************************************/
/* 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 (PyFile_Check( py_obj)) return "file" ;
if (PyModule_Check( py_obj)) return "module" ;
if (PyInstance_Check(py_obj)) return "instance" ;
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 */
Raw
PKG-INFO
Metadata-Version: 1.0
Name: fred_emcee_swig
Version: 1.0
Summary: UNKNOWN
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description: UNKNOWN
Platform: UNKNOWN
Raw
setup.py
from distutils.core import setup, Extension
import numpy
import os
os.environ['CC'] = 'g++';
setup(name='fred_emcee_swig', version='1.0',
ext_modules =[Extension('_swig_test', ['test.cc', 'test.i'],
include_dirs = [numpy.get_include(),'.'], swig_opts=['-c++'])],
scripts=['mpi.py'],
data_files=['numpy.i', 'test.h'],
depends=['test.h'])
# python setup.py build
# pip install -e . --user
Raw
test.cc
/*
* Sample classes to use from python
*
* compile with
* g++ -c -fPIC test.cc && g++ -shared -Wl,-soname,libfoo.so -o libfoo.so test.o
swig -c++ -python test.i
gcc -fPIC -c test_wrap.cxx -I/usr/include/python2.7/
g++ -c test.cc
# mark the '_' in the shared object!!
g++ -shared -o _example.so test.o test_wrap.o
ipython
In [5]: import example
*/
#include "test.h"
#include <iostream>
/*
* adapter class that calculates a log likelihood based on values of members
*/
Adapter::Adapter(double mu, double sigma) :
mu(mu),
sigma(sigma)
{
std::cout << "Adapter ctor called" << std::endl;
}
Adapter::~Adapter()
{
std::cout << "Adapter dtor called" << std::endl;
}
double Adapter::llh(double * x, int n) {
double res = -(x[0]-mu)*(x[0]-mu) / (2 * sigma * sigma);
return res;
}
Raw
test.h
/*
* Example taken from http://stackoverflow.com/questions/145270/calling-c-c-from-python
*/
class Adapter {
public:
Adapter(double mu, double sigma);
~Adapter();
double llh(double * x, int n);
private:
double mu, sigma;
};
Raw
test.i
%module swig_test
%{
#define SWIG_FILE_WITH_INIT
#include "test.h"
%}
%include "numpy.i"
%init %{
import_array();
%}
%apply (int DIM1, double* INPLACE_ARRAY1) {(int n0, double *a0)};
%apply (double* IN_ARRAY1, int DIM1) {(double * x, int n)};
%apply (int DIM1, double* ARGOUT_ARRAY1) {(int size, double *arr)};
%include "test.h"
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