def __setattr__(self, name: str, val: Any) -> None:
if name.startswith("!"):
super(GlobalAttributeManager, self).__setattr__(name[1:], val)
elif "/" in name:
raise KeyError("Attribute name cannot contain slash (/)")
else:
if self.f is not None:
if loompy.compare_loom_spec_version(self.f, "3.0.0") < 0 and "attrs" not in self.f["/"]:
normalized = loompy.normalize_attr_values(val, False)
self.f.attrs[name] = normalized
self.f.flush()
val = self.f.attrs[name]
# Read it back in to ensure it's synced and normalized
normalized = loompy.materialize_attr_values(val)
self.__dict__["storage"][name] = normalized
else:
normalized = loompy.normalize_attr_values(val, True)
if name in self.f["attrs"]:
del self.f["attrs"][name]
if not np.isscalar(normalized) and normalized.dtype == np.object_:
self.ds._file.create_dataset("attrs/" + name, data=normalized, dtype=h5py.special_dtype(vlen=str))
else:
self.f["attrs"][name] = normalized
self.f.flush()
val = self.f["attrs"][name][()]
# Read it back in to ensure it's synced and normalized
normalized = loompy.materialize_attr_values(val)
self.__dict__["storage"][name] = normalized
def __init__(self, f: h5py.File) -> None:
setattr(self, "!f", f)
storage: Dict[str, str] = {}
setattr(self, "!storage", storage)
if "attrs" not in self.f:
for key, val in f.attrs.items():
materialized = loompy.materialize_attr_values(val)
self.__dict__["storage"][key] = materialized
else:
for key, val in f["attrs"].items():
materialized = loompy.materialize_attr_values(val[()])
self.__dict__["storage"][key] = materialized
def __setattr__(self, name: str, val: np.ndarray) -> None:
"""
Set the value of a named attribute
Args:
name (str) Name of the attribute
val (np.ndarray) Value of the attribute
Remarks:
Length must match the corresponding matrix dimension
The values are automatically HMTL escaped and converted to ASCII for storage
"""
if name.startswith("!"):
super(AttributeManager, self).__setattr__(name[1:], val)
else:
if self.ds is not None:
values = loompy.normalize_attr_values(val)
a = ["/row_attrs/", "/col_attrs/"][self.axis]
if self.ds.shape[self.axis] != 0 and values.shape[0] != self.ds.shape[self.axis]:
raise ValueError(f"Attribute must have exactly {self.ds.shape[self.axis]} values but {len(values)} were given")
if self.ds._file[a].__contains__(name):
del self.ds._file[a + name]
self.ds._file[a + name] = values # TODO: for 2D arrays, use block compression along columns/rows
self.ds._file.flush()
self.__dict__["storage"][name] = loompy.materialize_attr_values(self.ds._file[a][name][:])
else:
self.__dict__["storage"][name] = val
def __setattr__(self, name: str, val: np.ndarray) -> None:
"""
Set the value of a named attribute
Args:
name (str) Name of the attribute
val (np.ndarray) Value of the attribute
Remarks:
Length must match the corresponding matrix dimension
The values are automatically HMTL escaped and converted to ASCII for storage
"""
if name.startswith("!"):
super(AttributeManager, self).__setattr__(name[1:], val)
elif "/" in name:
raise KeyError("Attribute name cannot contain slash (/)")
else:
if self.ds is not None:
values = loompy.normalize_attr_values(
val,
compare_loom_spec_version(self.ds._file, "3.0.0") >= 0)
a = ["/row_attrs/", "/col_attrs/"][self.axis]
if self.ds.shape[self.axis] != 0 and values.shape[
0] != self.ds.shape[self.axis]:
raise ValueError(
f"Attribute '{name}' must have exactly {self.ds.shape[self.axis]} values but {len(values)} were given"
)
if self.ds._file[a].__contains__(name):
del self.ds._file[a + name]
if isinstance(self.ds._file, h5py.File):
self.ds._file.create_dataset(
a + name,
data=values,
dtype=h5py.special_dtype(vlen=str)
if values.dtype == np.object_ else values.dtype,
maxshape=(values.shape[0], )
if len(values.shape) == 1 else (values.shape[0], None),
fletcher32=False,
compression="gzip",
shuffle=False,
compression_opts=2)
else:
self.ds._file.create_dataset(
a + name,
data=values.astype(np.string_)
if values.dtype == np.object_ else values)
self.ds._file[a + name].attrs["last_modified"] = timestamp()
self.ds._file[a].attrs["last_modified"] = timestamp()
self.ds._file.attrs["last_modified"] = timestamp()
if isinstance(self.ds._file, h5py.File):
self.ds._file.flush()
self.__dict__["storage"][
name] = loompy.materialize_attr_values(
self.ds._file[a][name][:])
else:
self.__dict__["storage"][name] = val
def __getattr__(self, name: str) -> np.ndarray:
try:
return self.__dict__["storage"][name]
except KeyError:
if self.f is not None:
if name in self.f.attrs:
val = self.f.attrs[name]
materialized = loompy.materialize_attr_values(val)
self.__dict__["storage"][name] = materialized
return materialized
raise AttributeError(
f"'{type(self)}' object has no attribute '{name}'")
def __setattr__(self, name: str, val: Any) -> None:
if name.startswith("!"):
super(FileAttributeManager, self).__setattr__(name[1:], val)
else:
if self.f is not None:
normalized = loompy.normalize_attr_values(val)
self.f.attrs[name] = normalized
self.f.flush()
val = self.f.attrs[name]
# Read it back in to ensure it's synced and normalized
normalized = loompy.materialize_attr_values(val)
self.__dict__["storage"][name] = normalized
def __getattr__(self, name: str) -> np.ndarray:
try:
return self.__dict__["storage"][name]
except KeyError:
if self.f is not None:
if loompy.compare_loom_spec_version(self.f, "3.0.0") < 0:
if name in self.f.attrs:
val = self.f.attrs[name]
else:
raise AttributeError(f"File has no global attribute '{name}'")
else:
if name in self.f["attrs"]:
val = self.f["attrs"][name]
else:
raise AttributeError(f"File has no global attribute '{name}'")
materialized = loompy.materialize_attr_values(val)
self.__dict__["storage"][name] = materialized
return materialized
def __getattr__(self, name: str) -> np.ndarray:
"""
Return the named attribute
Args:
name (str) Name of the attribute
Remarks:
The values will be loaded from file, and properly HTML unescaped
"""
try:
vals = self.__dict__["storage"][name]
if vals is None:
# Read values from the HDF5 file
a = ["/row_attrs/", "/col_attrs/"][self.axis]
vals = loompy.materialize_attr_values(self.ds._file[a][name][:])
self.__dict__["storage"][name] = vals
return vals
except KeyError:
raise AttributeError(f"'{type(self)}' object has no attribute '{name}'")
