def yt_dataset(self, value):
if value == 0: return
if not hasattr(value, 'dataset_type'):
raise IOError('not a yt dataset?')
infile = '%s/%s' % (value.fullpath, value.basename)
self.skip_hash_check = False
if hasattr(self, 'hash'):
if isinstance(self.hash, np.bytes_):
self.hash = self.hash.decode('utf8')
hash = get_hash(infile)
if hash != self.hash:
raise IOError('hash mismatch!')
else:
self._ds = value
else:
self._ds = value
self.hash = get_hash(infile)
self._ds = value
self._ds_type = DatasetType(self._ds)
self._assign_simulation_attributes()
def yt_dataset(self, value):
if value is None:
return
if not hasattr(value, 'dataset_type'):
raise ValueError('not a yt dataset?')
hash = get_hash(os.path.join(value.fullpath, value.basename))
if hash != self.hash:
raise RuntimeError('hash mismatch!')
else:
self._ds = value
self._ds = value
self._ds_type = DatasetType(self._ds)
def yt_dataset(self, value):
if value is None:
return
if not hasattr(value, 'dataset_type'):
raise ValueError('not a yt dataset?')
#if 'skip_hash_check' in self._kwargs and self._kwargs['skip_hash_check']:
if (self.skip_hash_check) or (self.hash is None):
hash = self.hash
else:
hash = get_hash(os.path.join(value.fullpath, value.basename))
if hash != self.hash:
raise RuntimeError('hash mismatch!')
self._ds = value
self._ds_type = DatasetType(self._ds)
def yt_dataset(self, value):
if value is None:
return
if not hasattr(value, 'dataset_type'):
raise IOError('not a yt dataset?')
infile = '%s/%s' % (value.fullpath, value.basename)
hash = get_hash(infile)
if hash != self.hash:
raise IOError('hash mismatch!')
else:
self._ds = value
self._ds = value
self._ds_type = DatasetType(self._ds)