我们从Python开源项目中，提取了以下42个代码示例，用于说明如何使用__builtin__.float()。
def _set_array_types(): ibytes = [1, 2, 4, 8, 16, 32, 64] fbytes = [2, 4, 8, 10, 12, 16, 32, 64] for bytes in ibytes: bits = 8*bytes _add_array_type('int', bits) _add_array_type('uint', bits) for bytes in fbytes: bits = 8*bytes _add_array_type('float', bits) _add_array_type('complex', 2*bits) _gi = dtype('p') if _gi.type not in sctypes['int']: indx = 0 sz = _gi.itemsize _lst = sctypes['int'] while (indx < len(_lst) and sz >= _lst[indx](0).itemsize): indx += 1 sctypes['int'].insert(indx, _gi.type) sctypes['uint'].insert(indx, dtype('P').type)
def issubclass_(arg1, arg2): """ Determine if a class is a subclass of a second class. `issubclass_` is equivalent to the Python built-in ``issubclass``, except that it returns False instead of raising a TypeError if one of the arguments is not a class. Parameters ---------- arg1 : class Input class. True is returned if `arg1` is a subclass of `arg2`. arg2 : class or tuple of classes. Input class. If a tuple of classes, True is returned if `arg1` is a subclass of any of the tuple elements. Returns ------- out : bool Whether `arg1` is a subclass of `arg2` or not. See Also -------- issubsctype, issubdtype, issctype Examples -------- >>> np.issubclass_(np.int32, np.int) True >>> np.issubclass_(np.int32, np.float) False """ try: return issubclass(arg1, arg2) except TypeError: return False
def issubsctype(arg1, arg2): """ Determine if the first argument is a subclass of the second argument. Parameters ---------- arg1, arg2 : dtype or dtype specifier Data-types. Returns ------- out : bool The result. See Also -------- issctype, issubdtype,obj2sctype Examples -------- >>> np.issubsctype('S8', str) True >>> np.issubsctype(np.array([1]), np.int) True >>> np.issubsctype(np.array([1]), np.float) False """ return issubclass(obj2sctype(arg1), obj2sctype(arg2))
def flatten_dtype(ndtype, flatten_base=False): """ Unpack a structured data-type by collapsing nested fields and/or fields with a shape. Note that the field names are lost. Parameters ---------- ndtype : dtype The datatype to collapse flatten_base : {False, True}, optional Whether to transform a field with a shape into several fields or not. Examples -------- >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float), ... ('block', int, (2, 3))]) >>> np.lib._iotools.flatten_dtype(dt) [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32')] >>> np.lib._iotools.flatten_dtype(dt, flatten_base=True) [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32'), dtype('int32'), dtype('int32'), dtype('int32'), dtype('int32'), dtype('int32')] """ names = ndtype.names if names is None: if flatten_base: return [ndtype.base] * int(np.prod(ndtype.shape)) return [ndtype.base] else: types = [] for field in names: info = ndtype.fields[field] flat_dt = flatten_dtype(info[0], flatten_base) types.extend(flat_dt) return types
def __init__(self, fnct, arg=None, fnct_inv=None, fnct_inv_arg=None, type='float', fnct_search=None, obj=None, method=False, store=False, multi=False, **args): _column.__init__(self, **args) self._obj = obj self._method = method self._fnct = fnct self._fnct_inv = fnct_inv self._arg = arg self._multi = multi if 'relation' in args: self._obj = args['relation'] if 'digits' in args: self.digits = args['digits'] else: self.digits = (16,2) self._fnct_inv_arg = fnct_inv_arg if not fnct_inv: self.readonly = 1 self._type = type self._fnct_search = fnct_search self.store = store if store: if self._type != 'many2one': # m2o fields need to return tuples with name_get, not just foreign keys self._classic_read = True self._classic_write = True if type=='binary': self._symbol_get=lambda x:x and str(x) if type == 'float': self._symbol_c = float._symbol_c self._symbol_f = float._symbol_f self._symbol_set = float._symbol_set
def _set_up_aliases(): type_pairs = [('complex_', 'cdouble'), ('int0', 'intp'), ('uint0', 'uintp'), ('single', 'float'), ('csingle', 'cfloat'), ('singlecomplex', 'cfloat'), ('float_', 'double'), ('intc', 'int'), ('uintc', 'uint'), ('int_', 'long'), ('uint', 'ulong'), ('cfloat', 'cdouble'), ('longfloat', 'longdouble'), ('clongfloat', 'clongdouble'), ('longcomplex', 'clongdouble'), ('bool_', 'bool'), ('unicode_', 'unicode'), ('object_', 'object')] if sys.version_info[0] >= 3: type_pairs.extend([('bytes_', 'string'), ('str_', 'unicode'), ('string_', 'string')]) else: type_pairs.extend([('str_', 'string'), ('string_', 'string'), ('bytes_', 'string')]) for alias, t in type_pairs: allTypes[alias] = allTypes[t] sctypeDict[alias] = sctypeDict[t] # Remove aliases overriding python types and modules to_remove = ['ulong', 'object', 'unicode', 'int', 'long', 'float', 'complex', 'bool', 'string', 'datetime', 'timedelta'] if sys.version_info[0] >= 3: # Py3K to_remove.append('bytes') to_remove.append('str') to_remove.remove('unicode') to_remove.remove('long') for t in to_remove: try: del allTypes[t] del sctypeDict[t] except KeyError: pass
def sctype2char(sctype): """ Return the string representation of a scalar dtype. Parameters ---------- sctype : scalar dtype or object If a scalar dtype, the corresponding string character is returned. If an object, `sctype2char` tries to infer its scalar type and then return the corresponding string character. Returns ------- typechar : str The string character corresponding to the scalar type. Raises ------ ValueError If `sctype` is an object for which the type can not be inferred. See Also -------- obj2sctype, issctype, issubsctype, mintypecode Examples -------- >>> for sctype in [np.int32, np.float, np.complex, np.string_, np.ndarray]: ... print(np.sctype2char(sctype)) l d D S O >>> x = np.array([1., 2-1.j]) >>> np.sctype2char(x) 'D' >>> np.sctype2char(list) 'O' """ sctype = obj2sctype(sctype) if sctype is None: raise ValueError("unrecognized type") return _sctype2char_dict[sctype] # Create dictionary of casting functions that wrap sequences # indexed by type or type character
def sctype2char(sctype): """ Return the string representation of a scalar dtype. Parameters ---------- sctype : scalar dtype or object If a scalar dtype, the corresponding string character is returned. If an object, `sctype2char` tries to infer its scalar type and then return the corresponding string character. Returns ------- typechar : str The string character corresponding to the scalar type. Raises ------ ValueError If `sctype` is an object for which the type can not be inferred. See Also -------- obj2sctype, issctype, issubsctype, mintypecode Examples -------- >>> for sctype in [np.int32, np.float, np.complex, np.string_, np.ndarray]: ... print np.sctype2char(sctype) l d D S O >>> x = np.array([1., 2-1.j]) >>> np.sctype2char(x) 'D' >>> np.sctype2char(list) 'O' """ sctype = obj2sctype(sctype) if sctype is None: raise ValueError("unrecognized type") return _sctype2char_dict[sctype] # Create dictionary of casting functions that wrap sequences # indexed by type or type character
