diff options
Diffstat (limited to 'weave/standard_array_spec.py')
| -rw-r--r-- | weave/standard_array_spec.py | 215 |
1 files changed, 137 insertions, 78 deletions
diff --git a/weave/standard_array_spec.py b/weave/standard_array_spec.py index 181b72f18..0509835a7 100644 --- a/weave/standard_array_spec.py +++ b/weave/standard_array_spec.py @@ -1,93 +1,152 @@ -from base_spec import base_converter -from scalar_spec import numeric_to_c_type_mapping +from c_spec import common_base_converter +from c_spec import num_to_c_types from Numeric import * from types import * import os -import standard_array_info -class array_converter(base_converter): - _build_information = [standard_array_info.array_info()] +num_typecode = {} +num_typecode['c'] = 'PyArray_CHAR' +num_typecode['1'] = 'PyArray_SBYTE' +num_typecode['b'] = 'PyArray_UBYTE' +num_typecode['s'] = 'PyArray_SHORT' +num_typecode['i'] = 'PyArray_INT' # PyArray_INT has troubles ?? What does this note mean ?? +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[13] = {"char","unsigned byte","byte", "short", "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); + } + } - def type_match(self,value): - return type(value) is ArrayType + 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[13] = {"char","unsigned byte","byte", "short", "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); + } + } +}; - def type_spec(self,name,value): - # factory - new_spec = array_converter() - new_spec.name = name - new_spec.numeric_type = value.typecode() - # dims not used, but here for compatibility with blitz_spec - new_spec.dims = len(shape(value)) - return new_spec +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 - def declaration_code(self,templatize = 0,inline=0): - if inline: - code = self.inline_decl_code() - else: - code = self.standard_decl_code() - return code +""" + +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); + } + } - def inline_decl_code(self): - type = numeric_to_c_type_mapping[self.numeric_type] - name = self.name - #dims = self.dims - var_name = self.retrieve_py_variable(inline=1) - templ = '// %(name)s array declaration\n' \ - 'py_%(name)s= %(var_name)s;\n' \ - 'PyArrayObject* %(name)s = convert_to_numpy(py_%(name)s,"%(name)s");\n' \ - 'conversion_numpy_check_type(%(name)s,py_type<%(type)s>::code,"%(name)s");\n' \ - 'int* _N%(name)s = %(name)s->dimensions;\n' \ - 'int* _S%(name)s = %(name)s->strides;\n' \ - 'int _D%(name)s = %(name)s->nd;\n' \ - '%(type)s* %(name)s_data = (%(type)s*) %(name)s->data;\n' - code = templ % locals() - return code + 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); + } + } +}; - def standard_decl_code(self): - type = numeric_to_c_type_mapping[self.numeric_type] - name = self.name - templ = '// %(name)s array declaration\n' \ - 'PyArrayObject* %(name)s = convert_to_numpy(py_%(name)s,"%(name)s");\n' \ - 'conversion_numpy_check_type(%(name)s,py_type<%(type)s>::code,"%(name)s");\n' \ - 'int* _N%(name)s = %(name)s->dimensions;\n' \ - 'int* _S%(name)s = %(name)s->strides;\n' \ - 'int _D%(name)s = %(name)s->nd;\n' \ - '%(type)s* %(name)s_data = (%(type)s*) %(name)s->data;\n' - code = templ % locals() - return code - #def c_function_declaration_code(self): - # """ - # This doesn't pass the size through. That info is gonna have to - # be redone in the c function. - # """ - # templ_dict = {} - # templ_dict['type'] = numeric_to_c_type_mapping[self.numeric_type] - # templ_dict['dims'] = self.dims - # templ_dict['name'] = self.name - # code = 'blitz::Array<%(type)s,%(dims)d> &%(name)s' % templ_dict - # return code - - def local_dict_code(self): - code = '// for now, array "%s" is not returned as arryas are edited' \ - ' in place (should this change?)\n' % (self.name) - return code +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 - def cleanup_code(self): - # could use Py_DECREF here I think and save NULL test. - code = "Py_XDECREF(py_%s);\n" % self.name - return code +""" - def __repr__(self): - msg = "(array:: name: %s, type: %s)" % \ - (self.name, self.numeric_type) - return msg +numeric_init_code = \ +""" +Py_Initialize(); +import_array(); +PyImport_ImportModule("Numeric"); +""" + +class array_converter(common_base_converter): - def __cmp__(self,other): - #only works for equal - return cmp(self.name,other.name) or \ - cmp(self.numeric_type,other.numeric_type) or \ - cmp(self.dims, other.dims) or \ - cmp(self.__class__, other.__class__) + def init_info(self): + common_base_converter.init_info(self) + self.type_name = 'numpy' + self.check_func = 'PyArray_Check' + self.c_type = 'PyArrayObject*' + self.to_c_return = '(PyArrayObject*) py_obj' + self.matching_types = [ArrayType] + self.headers = ['"Numeric/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.typecode() + + 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 def test(level=10): from scipy_base.testing import module_test |