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class AstypeContext(object):
def __init__(self, dset, dtype):
self._dset = dset
self._dtype = numpy.dtype(dtype)
def __enter__(self):
self._dset._local.astype = self._dtype
def __exit__(self, *args):
self._dset._local.astype = None
class Dataset(HLObject):
"""
Represents an HDF5 dataset
"""
def astype(self, dtype):
""" Get a context manager allowing you to perform reads to a
different destination type, e.g.:
>>> with dataset.astype('f8'):
... double_precision = dataset[0:100:2]
"""
pass
#return AstypeContext(self, dtype)
@property
# and contributor agreement.
"""
Implements high-level access to committed datatypes in the file. """
from __future__ import absolute_import
import posixpath as pp
#from ..h5t import TypeID
from .base import HLObject
from .objectid import TypeID
from .h5type import createDataType
class Datatype(HLObject):
"""
Represents an HDF5 named datatype stored in a file.
To store a datatype, simply assign it to a name in a group:
>>> MyGroup["name"] = numpy.dtype("f")
>>> named_type = MyGroup["name"]
>>> assert named_type.dtype == numpy.dtype("f") """
@property
def dtype(self):
"""Numpy dtype equivalent for this datatype"""
return self._dtype
def __init__(self, bind):
import os.path as op
import numpy
import collections
from .base import HLObject, MutableMappingHDF5, guess_dtype
from .objectid import TypeID, GroupID, DatasetID
from . import dataset
from .dataset import Dataset
from . import table
from .table import Table
from .datatype import Datatype
from . import h5type
class Group(HLObject, MutableMappingHDF5):
""" Represents an HDF5 group.
"""
def __init__(self, bind, **kwargs):
#print "group init, bind:", bind
""" Create a new Group object by binding to a low-level GroupID.
"""
if not isinstance(bind, GroupID):
raise ValueError("%s is not a GroupID" % bind)
HLObject.__init__(self, bind, **kwargs)
self._req_prefix = "/groups/" + self.id.uuid
self._link_db = {} # cache for links