def special_load(self, obj):
if 'data0' in self.__special__:
import tramway.tessellation.base as tessellation
if lazytype(obj) is tessellation.CellStats:
obj = lazyvalue(obj, deep=True)
try:
if obj._points is None:
raise AttributeError
except AttributeError:
obj._points = self.__special__['data0']
else:
import pandas
if lazytype(obj) is pandas.DataFrame:
obj = lazyvalue(obj, deep=True)
self.__special__['data0'] = obj
return obj
def load_rwa(path, verbose=None, lazy=False, force_load_spt_data=None):
"""
Load a .rwa file.
Note about laziness: the analysis tree uses an active handle to the opened file.
As a consequence, the file should be read only once.
It is safe to load, modify, save and then load again, but the first loaded data
should be terminated before loading the data again.
Arguments:
path (str): path to .rwa file
verbose (bool or int): verbosity level
lazy (bool): reads the file lazily
force_load_spt_data (bool): *new in 0.5*
compatibility flag for pre-0.5 code;
`None` currently defaults to `True`,
but will default to `False` in the future
Returns:
tramway.core.analyses.base.Analyses:
analysis tree;
if `lazy` is ``True``, return type is
:class:`tramway.core.analyses.lazy.Analyses` instead
"""
try:
hdf = RWAStore(path,
"r",
verbose=max(0,
int(verbose) - 2) if verbose else False)
# hdf._default_lazy = PermissivePeek
hdf.lazy = lazy
hdf.force_load_special = (True if force_load_spt_data is None else
force_load_spt_data)
try:
analyses = lazyvalue(hdf.peek("analyses"))
except (KeyboardInterrupt, SystemExit):
raise
except:
if verbose is not False:
print("cannot load file: {}".format(path))
raise
finally:
if not lazy:
hdf.close()
except EnvironmentError as e:
if hasattr(e, "errno") and e.errno == errno.ENOENT:
raise
elif e.args[1:]:
if verbose:
print(traceback.format_exc())
raise OSError("HDF5 libraries may not be installed")
else:
raise
return analyses
return coerce_labels(analyses)
def special_unload(self, obj):
# forced poke (calling lazyvalue) may not be necessary
if "data0" in self.__special__:
import tramway.tessellation.base as tessellation
if issubclass(lazytype(obj), tessellation.Partition):
obj = lazyvalue(obj, deep=True)
if obj.points is self.__special__["data0"]:
import copy
obj = copy.copy(obj)
obj._points = None
else:
import pandas
if issubclass(lazytype(obj), pandas.DataFrame):
obj = lazyvalue(obj, deep=True)
self.__special__["data0"] = obj
return obj
def load_rwa(path, verbose=None, lazy=False):
"""
Load a .rwa file.
Note about laziness: the analysis tree uses an active handle to the opened file.
As a consequence, the file should be read only once.
It is safe to load, modify, save and then load again, but the first loaded data
should be terminated before loading the data again.
Arguments:
path (str): path to .rwa file
verbose (bool or int): verbosity level
lazy (bool): reads the file lazily
Returns:
tramway.core.analyses.base.Analyses:
analysis tree;
if `lazy` is ``True``, return type is
:class:`tramway.core.analyses.lazy.Analyses` instead
"""
try:
hdf = RWAStore(path,
'r',
verbose=max(0,
int(verbose) - 2) if verbose else False)
#hdf._default_lazy = PermissivePeek
hdf.lazy = lazy
try:
analyses = lazyvalue(hdf.peek('analyses'))
except (KeyboardInterrupt, SystemExit):
raise
except:
if verbose is not False:
print('cannot load file: {}'.format(path))
raise
finally:
hdf.close()
except EnvironmentError as e:
if hasattr(e, 'errno') and e.errno == errno.ENOENT:
raise
elif e.args[1:]:
if verbose:
print(traceback.format_exc())
raise OSError('HDF5 libraries may not be installed')
else:
raise
return coerce_labels(analyses)
def special_load(self, obj, objname, lazy=None):
if objname != "_data":
return obj
if "data0" in self.__special__:
import tramway.tessellation.base as tessellation
if issubclass(lazytype(obj), tessellation.Partition):
obj = lazyvalue(obj, deep=True)
try:
if obj._points is None:
raise AttributeError
except AttributeError:
obj._points = lazyvalue(self.__special__["data0"],
deep=True)
else:
import pandas
if issubclass(lazytype(obj), pandas.DataFrame):
if self.force_load_special or not (self.lazy
if lazy is None else lazy):
obj = lazyvalue(obj, deep=True)
self.__special__["data0"] = obj
return obj
def get_base_grid(self, label, from_root=False):
label = 'tramway.roi.RoiHelper.basegrid:' + label
if from_root:
try:
artefact = self._extra_artefacts[label]
except KeyError:
artefact = None
if self.collections.rwa_file:
from rwa import HDF5Store, lazyvalue
f = HDF5Store(self.collections.rwa_file, 'r')
try:
artefact = lazyvalue(f.peek(label))
except KeyError:
pass
else:
self._extra_artefacts[label] = artefact
finally:
f.close()
else:
artefact = self.analyses[label].data
return artefact
def poke(self,
objname,
obj,
container=None,
visited=None,
_stack=None,
unload=None):
if unload is not None:
previous = self.unload
self.unload = unload
if visited is None:
visited = {}
if container is None:
container = self.store
try:
obj = obj.lazy_unwrap()
except AttributeError:
pass
obj = lazyvalue(obj,
deep=True) # in the case it was stored not unloaded
if self.unload and isinstance(obj, Lazy):
# set lazy attributes to None (unset them so that memory is freed)
#obj = copy(obj) # this causes a weird bug
for name in obj.__lazy__:
# `_lazy` should contain `name`;
# if it is not, the object definition has changed
if obj._lazy.get(name, True):
setattr(obj, obj.__fromlazy__(name), None)
obj = self.special_unload(obj)
HDF5Store.poke(self,
objname,
obj,
container,
visited=visited,
_stack=_stack)
if unload is not None:
self.unload = previous
