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from __future__ import absolute_import, print_function
from .c_spec import common_base_converter
from .c_spec import num_to_c_types
import numpy
num_typecode = {'?': 'PyArray_BOOL',
'b': 'PyArray_BYTE',
'B': 'PyArray_UBYTE',
'h': 'PyArray_SHORT',
'H': 'PyArray_USHORT',
'i': 'PyArray_INT',
'I': 'PyArray_UINT',
'l': 'PyArray_LONG',
'L': 'PyArray_ULONG',
'q': 'PyArray_LONGLONG',
'Q': 'PyArray_ULONGLONG',
'f': 'PyArray_FLOAT',
'd': 'PyArray_DOUBLE',
'g': 'PyArray_LONGDOUBLE',
'F': 'PyArray_CFLOAT',
'D': 'PyArray_CDOUBLE',
'G': 'PyArray_CLONGDOUBLE'}
type_check_code = \
"""
class numpy_type_handler
{
public:
void conversion_numpy_check_type(PyArrayObject* arr_obj, int numeric_type,
const char* name)
{
// Make sure input has correct numeric type.
int arr_type = arr_obj->descr->type_num;
if (PyTypeNum_ISEXTENDED(numeric_type))
{
char msg[80];
sprintf(msg, "Conversion Error: extended types not supported for variable '%s'",
name);
throw_error(PyExc_TypeError, msg);
}
if (!PyArray_EquivTypenums(arr_type, numeric_type))
{
const char* type_names[23] = {"bool", "byte", "ubyte","short", "ushort",
"int", "uint", "long", "ulong", "longlong", "ulonglong",
"float", "double", "longdouble", "cfloat", "cdouble",
"clongdouble", "object", "string", "unicode", "void", "ntype",
"unknown"};
char msg[500];
sprintf(msg,"Conversion Error: received '%s' typed array instead of '%s' typed array for variable '%s'",
type_names[arr_type],type_names[numeric_type],name);
throw_error(PyExc_TypeError,msg);
}
}
void numpy_check_type(PyArrayObject* arr_obj, int numeric_type, const char* name)
{
// Make sure input has correct numeric type.
int arr_type = arr_obj->descr->type_num;
if (PyTypeNum_ISEXTENDED(numeric_type))
{
char msg[80];
sprintf(msg, "Conversion Error: extended types not supported for variable '%s'",
name);
throw_error(PyExc_TypeError, msg);
}
if (!PyArray_EquivTypenums(arr_type, numeric_type))
{
const char* type_names[23] = {"bool", "byte", "ubyte","short", "ushort",
"int", "uint", "long", "ulong", "longlong", "ulonglong",
"float", "double", "longdouble", "cfloat", "cdouble",
"clongdouble", "object", "string", "unicode", "void", "ntype",
"unknown"};
char msg[500];
sprintf(msg,"received '%s' typed array instead of '%s' typed array for variable '%s'",
type_names[arr_type],type_names[numeric_type],name);
throw_error(PyExc_TypeError,msg);
}
}
};
numpy_type_handler x__numpy_type_handler = numpy_type_handler();
#define conversion_numpy_check_type x__numpy_type_handler.conversion_numpy_check_type
#define numpy_check_type x__numpy_type_handler.numpy_check_type
"""
size_check_code = \
"""
class numpy_size_handler
{
public:
void conversion_numpy_check_size(PyArrayObject* arr_obj, int Ndims,
const char* name)
{
if (arr_obj->nd != Ndims)
{
char msg[500];
sprintf(msg,"Conversion Error: received '%d' dimensional array instead of '%d' dimensional array for variable '%s'",
arr_obj->nd,Ndims,name);
throw_error(PyExc_TypeError,msg);
}
}
void numpy_check_size(PyArrayObject* arr_obj, int Ndims, const char* name)
{
if (arr_obj->nd != Ndims)
{
char msg[500];
sprintf(msg,"received '%d' dimensional array instead of '%d' dimensional array for variable '%s'",
arr_obj->nd,Ndims,name);
throw_error(PyExc_TypeError,msg);
}
}
};
numpy_size_handler x__numpy_size_handler = numpy_size_handler();
#define conversion_numpy_check_size x__numpy_size_handler.conversion_numpy_check_size
#define numpy_check_size x__numpy_size_handler.numpy_check_size
"""
numeric_init_code = \
"""
Py_Initialize();
import_array();
PyImport_ImportModule("numpy");
"""
class array_converter(common_base_converter):
def init_info(self):
common_base_converter.init_info(self)
self.type_name = 'numpy'
self.check_func = 'PyArray_Check'
self.c_type = 'PyArrayObject*'
self.return_type = 'PyArrayObject*'
self.to_c_return = '(PyArrayObject*) py_obj'
self.matching_types = [numpy.ndarray]
self.headers = ['"numpy/arrayobject.h"',
'<complex>','<math.h>']
self.support_code = [size_check_code, type_check_code]
self.module_init_code = [numeric_init_code]
def get_var_type(self,value):
return value.dtype.char
def template_vars(self,inline=0):
res = common_base_converter.template_vars(self,inline)
if hasattr(self,'var_type'):
res['num_type'] = num_to_c_types[self.var_type]
res['num_typecode'] = num_typecode[self.var_type]
res['array_name'] = self.name + "_array"
res['cap_name'] = self.name.upper()
return res
def declaration_code(self,templatize=0,inline=0):
res = self.template_vars(inline=inline)
cap_name = self.name.upper()
res['cap_name'] = cap_name
code2 = '#define %(cap_name)s1(i) (*((%(num_type)s*)(%(array_name)s->data + (i)*S%(name)s[0])))\n' \
'#define %(cap_name)s2(i,j) (*((%(num_type)s*)(%(array_name)s->data + (i)*S%(name)s[0] + (j)*S%(name)s[1])))\n' \
'#define %(cap_name)s3(i,j,k) (*((%(num_type)s*)(%(array_name)s->data + (i)*S%(name)s[0] + (j)*S%(name)s[1] + (k)*S%(name)s[2])))\n' \
'#define %(cap_name)s4(i,j,k,l) (*((%(num_type)s*)(%(array_name)s->data + (i)*S%(name)s[0] + (j)*S%(name)s[1] + (k)*S%(name)s[2] + (l)*S%(name)s[3])))\n'
res['_code2_'] = code2 % res
code = '%(py_var)s = %(var_lookup)s;\n' \
'%(c_type)s %(array_name)s = %(var_convert)s;\n' \
'conversion_numpy_check_type(%(array_name)s,%(num_typecode)s,"%(name)s");\n' \
'%(_code2_)s' \
'npy_intp* N%(name)s = %(array_name)s->dimensions;\n' \
'npy_intp* S%(name)s = %(array_name)s->strides;\n' \
'int D%(name)s = %(array_name)s->nd;\n' \
'%(num_type)s* %(name)s = (%(num_type)s*) %(array_name)s->data;\n'
code = code % res
self.__doundef = 1
return code
def cleanup_code(self):
code = common_base_converter.cleanup_code(self)
try:
if self.__doundef != 1:
return code
cap_name = self.name.upper()
newcode = "#undef %(cap_name)s1\n#undef %(cap_name)s2\n"\
"#undef %(cap_name)s3\n#undef %(cap_name)s4\n"\
% {'cap_name':cap_name}
code = "%s%s" % (code, newcode)
except AttributeError:
pass
return code
|
