def save_object(self, obj, name):
"""
Save an object (*obj*) to the data_file using the Pickle protocol,
under the name *name* on the node /Objects.
"""
s = cPickle.dumps(obj, protocol=-1)
self.save_data(np.array(s, dtype='c'), "/Objects", name, force=True)
def save_object(self, obj, name):
"""
Save an object (*obj*) to the data_file using the Pickle protocol,
under the name *name* on the node /Objects.
"""
s = cPickle.dumps(obj, protocol=-1)
self.save_data(np.array(s, dtype='c'), "/Objects", name, force = True)
def write_hdf5(self, filename, dataset_name=None, info=None):
r"""Writes ImageArray to hdf5 file.
Parameters
----------
filename: string
The filename to create and write a dataset to
dataset_name: string
The name of the dataset to create in the file.
info: dictionary
A dictionary of supplementary info to write to append as attributes
to the dataset.
Examples
--------
>>> a = YTArray([1,2,3], 'cm')
>>> myinfo = {'field':'dinosaurs', 'type':'field_data'}
>>> a.write_hdf5('test_array_data.h5', dataset_name='dinosaurs',
... info=myinfo)
"""
import h5py
from yt.extern.six.moves import cPickle as pickle
if info is None:
info = {}
info["units"] = str(self.units)
info["unit_registry"] = np.void(pickle.dumps(self.units.registry.lut))
if dataset_name is None:
dataset_name = "array_data"
f = h5py.File(filename)
if dataset_name in f.keys():
d = f[dataset_name]
# Overwrite without deleting if we can get away with it.
if d.shape == self.shape and d.dtype == self.dtype:
d[:] = self
for k in d.attrs.keys():
del d.attrs[k]
else:
del f[dataset_name]
d = f.create_dataset(dataset_name, data=self)
else:
d = f.create_dataset(dataset_name, data=self)
for k, v in info.items():
d.attrs[k] = v
f.close()
def write_hdf5(self, filename, dataset_name=None, info=None):
r"""Writes ImageArray to hdf5 file.
Parameters
----------
filename: string
The filename to create and write a dataset to
dataset_name: string
The name of the dataset to create in the file.
info: dictionary
A dictionary of supplementary info to write to append as attributes
to the dataset.
Examples
--------
>>> a = YTArray([1,2,3], 'cm')
>>> myinfo = {'field':'dinosaurs', 'type':'field_data'}
>>> a.write_hdf5('test_array_data.h5', dataset_name='dinosaurs',
... info=myinfo)
"""
import h5py
from yt.extern.six.moves import cPickle as pickle
if info is None:
info = {}
info['units'] = str(self.units)
info['unit_registry'] = np.void(pickle.dumps(self.units.registry.lut))
if dataset_name is None:
dataset_name = 'array_data'
f = h5py.File(filename)
if dataset_name in f.keys():
d = f[dataset_name]
# Overwrite without deleting if we can get away with it.
if d.shape == self.shape and d.dtype == self.dtype:
d[:] = self
for k in d.attrs.keys():
del d.attrs[k]
else:
del f[dataset_name]
d = f.create_dataset(dataset_name, data=self)
else:
d = f.create_dataset(dataset_name, data=self)
for k, v in info.items():
d.attrs[k] = v
f.close()
def dump(self, result_storage):
if self.answer_name is None: return
# This is where we dump our result storage up to Amazon, if we are able
# to.
import pyrax
pyrax.set_credential_file(os.path.expanduser("~/.yt/rackspace"))
cf = pyrax.cloudfiles
c = cf.get_container("yt-answer-tests")
pb = get_pbar("Storing results ", len(result_storage))
for i, ds_name in enumerate(result_storage):
pb.update(i)
rs = cPickle.dumps(result_storage[ds_name])
object_name = "%s_%s" % (self.answer_name, ds_name)
if object_name in c.get_object_names():
obj = c.get_object(object_name)
c.delete_object(obj)
c.store_object(object_name, rs)
pb.finish()
def dump(self, result_storage):
if self.answer_name is None: return
# This is where we dump our result storage up to Amazon, if we are able
# to.
import pyrax
pyrax.set_credential_file(os.path.expanduser("~/.yt/rackspace"))
cf = pyrax.cloudfiles
c = cf.get_container("yt-answer-tests")
pb = get_pbar("Storing results ", len(result_storage))
for i, ds_name in enumerate(result_storage):
pb.update(i)
rs = cPickle.dumps(result_storage[ds_name])
object_name = "%s_%s" % (self.answer_name, ds_name)
if object_name in c.get_object_names():
obj = c.get_object(object_name)
c.delete_object(obj)
c.store_object(object_name, rs)
pb.finish()
