diff options
Diffstat (limited to 'scipy/weave/standard_array_spec.py')
| -rw-r--r-- | scipy/weave/standard_array_spec.py | 157 |
1 files changed, 157 insertions, 0 deletions
diff --git a/scipy/weave/standard_array_spec.py b/scipy/weave/standard_array_spec.py new file mode 100644 index 000000000..261aeb3a5 --- /dev/null +++ b/scipy/weave/standard_array_spec.py @@ -0,0 +1,157 @@ +from c_spec import common_base_converter +from c_spec import num_to_c_types +from scipy.base import * +from types import * +import os + + +num_typecode = {} +num_typecode['b'] = 'PyArray_SBYTE' +num_typecode['B'] = 'PyArray_UBYTE' +num_typecode['h'] = 'PyArray_SHORT' +num_typecode['H'] = 'PyArray_USHORT' +num_typecode['i'] = 'PyArray_INT' # PyArray_INT has troubles ?? What does this note mean ?? +num_typecode['I'] = 'PyArray_UINT' +num_typecode['l'] = 'PyArray_LONG' +num_typecode['f'] = 'PyArray_FLOAT' +num_typecode['d'] = 'PyArray_DOUBLE' +num_typecode['F'] = 'PyArray_CFLOAT' +num_typecode['D'] = 'PyArray_CDOUBLE' + +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. + // allow character and byte to match + // also allow int and long to match + int arr_type = arr_obj->descr->type_num; + if ( arr_type != numeric_type && + !(numeric_type == PyArray_CHAR && arr_type == PyArray_SBYTE) && + !(numeric_type == PyArray_SBYTE && arr_type == PyArray_CHAR) && + !(numeric_type == PyArray_INT && arr_type == PyArray_LONG) && + !(numeric_type == PyArray_LONG && arr_type == PyArray_INT)) + { + + char* type_names[20] = {"char","unsigned byte","byte", "short", "unsigned short", + "int", "unsigned int", "long", "float", "double", + "complex float","complex double", "object","ntype", + "unkown"}; + 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 ( arr_type != numeric_type && + !(numeric_type == PyArray_CHAR && arr_type == PyArray_SBYTE) && + !(numeric_type == PyArray_SBYTE && arr_type == PyArray_CHAR) && + !(numeric_type == PyArray_INT && arr_type == PyArray_LONG) && + !(numeric_type == PyArray_LONG && arr_type == PyArray_INT)) + { + char* type_names[20] = {"char","unsigned byte","byte", "short", + "unsigned short", "int", "unsigned int", + "long", "float", "double", + "complex float", "complex double", + "object","ntype","unkown"}; + 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("scipy"); +""" + +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 = [ArrayType] + self.headers = ['"scipy/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.dtypechar + + 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" + return res + + def declaration_code(self,templatize = 0,inline=0): + 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' \ + 'int* N%(name)s = %(array_name)s->dimensions;\n' \ + 'int* 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 % self.template_vars(inline=inline) + return code |