scipp.Dataset

class scipp.Dataset

Dict of data arrays with aligned dimensions.

__init__(self, data: Union[Mapping[str, Union[Variable, DataArray]], Iterable[Tuple[str, Union[Variable, DataArray]]]] = {}, coords: Union[Mapping[str, Variable], Iterable[Tuple[str, Variable]]] = {}) → None

Dataset initializer.

Parameters

• data – Dictionary of name and data pairs.

• coords – Dictionary of name and coord pairs.

Methods

__init__(self[, data, coords])	Dataset initializer.
all([dim])	Logical AND over input values.
any([dim])	Logical OR over input values.
assign_coords([coords])	Return new object with updated or inserted coordinate.
clear(self)	Removes all data, preserving coordinates.
copy(self[, deep])	Return a (by default deep) copy.
drop_coords(*args, **kwargs)	Overloaded function.
get(key[, default])	Get the value associated with the provided key or the default value.
groupby(group, *[, bins])	Group dataset or data array based on values of specified labels.
hist([arg_dict])	Compute a histogram.
items(self)	view on self's items
keys(self)	view on self's keys
max([dim])	Maximum of elements in the input.
mean([dim])	Arithmetic mean of elements in the input.
min([dim])	Minimum of elements in the input.
nanmax([dim])	Maximum of elements in the input ignoring NaN's.
nanmean([dim])	Arithmetic mean of elements in the input ignoring NaN's.
nanmin([dim])	Minimum of elements in the input ignoring NaN's.
nansum([dim])	Sum of elements in the input ignoring NaN's.
plot(**kwargs)
pop(key[, default])	Remove and return an element.
rebin([arg_dict, deprecated])	Rebin a data array or dataset.
rename([dims_dict])	Rename the dimensions, coordinates and attributes of all the items.
rename_dims([dims_dict])	Rename dimensions.
save_hdf5(filename)	Write an object out to file in HDF5 format.
squeeze([dim])	Remove dimensions of length 1.
sum([dim])	Sum of elements in the input.
to_hdf5(filename)	Write an object out to file in HDF5 format.
transform_coords([targets, graph, ...])	Compute new coords based on transformations of input coords.
underlying_size(self)	Return the size of the object in bytes.
update(self[, other])	Update items from dict-like or iterable.
values(self)	view on self's values

Attributes

bins	Returns helper scipp.Bins allowing bin-wise operations to be performed or None if not binned data.
coords	Dict of coordinates.
dim	The only dimension label for 1-dimensional data, raising an exception if the data is not 1-dimensional.
dims	Dimension labels of the data (read-only).
meta	Dict of coordinates.
ndim	Number of dimensions of the data (read-only).
shape	Shape of the data (read-only).
sizes	dict mapping dimension labels to dimension sizes (read-only).

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: scipp._scipp.core.Dataset, arg0: str) -> scipp._scipp.core.DataArray

2. __getitem__(self: scipp._scipp.core.Dataset, arg0: int) -> scipp._scipp.core.Dataset

3. __getitem__(self: scipp._scipp.core.Dataset, arg0: slice) -> scipp._scipp.core.Dataset

4. __getitem__(self: scipp._scipp.core.Dataset, arg0: scipp._scipp.core.Variable) -> scipp._scipp.core.Dataset

5. __getitem__(self: scipp._scipp.core.Dataset, arg0: Tuple[str, scipp._scipp.core.Variable]) -> scipp._scipp.core.Dataset

6. __getitem__(self: scipp._scipp.core.Dataset, arg0: Tuple[str, int]) -> scipp._scipp.core.Dataset

7. __getitem__(self: scipp._scipp.core.Dataset, arg0: Tuple[str, slice]) -> scipp._scipp.core.Dataset

8. __getitem__(self: scipp._scipp.core.Dataset, arg0: ellipsis) -> scipp._scipp.core.Dataset

9. __getitem__(self: scipp._scipp.core.Dataset, arg0: List[int]) -> scipp._scipp.core.Dataset

10. __getitem__(self: scipp._scipp.core.Dataset, arg0: Tuple[str, List[int]]) -> scipp._scipp.core.Dataset

all(dim=None)

Logical AND over input values.

Seealso

Details in scipp.all()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

any(dim=None)

Logical OR over input values.

Seealso

Details in scipp.any()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

assign_coords(coords=None, /, **coords_kwargs)

Return new object with updated or inserted coordinate.

Parameters

• coords (Optional[Dict[str, Variable]], default: None) – New coordinates.

• coords_kwargs – Keyword arguments form of coords.

Returns

Union[DataArray, Dataset] – scipp.DataArray or scipp.Dataset with updated coordinates.

property bins

Returns helper scipp.Bins allowing bin-wise operations to be performed or None if not binned data.

clear(self: scipp._scipp.core.Dataset) → None

Removes all data, preserving coordinates.

property coords

Dict of coordinates.

copy(self: scipp._scipp.core.Dataset, deep: bool = True) → scipp._scipp.core.Dataset

Return a (by default deep) copy.

If deep=True (the default), a deep copy is made. Otherwise, a shallow copy is made, and the returned data (and meta data) values are new views of the data and meta data values of this object.

property dim

The only dimension label for 1-dimensional data, raising an exception if the data is not 1-dimensional.

property dims

Dimension labels of the data (read-only).

drop_coords(*args, **kwargs)

Overloaded function.

1. drop_coords(self: scipp._scipp.core.Dataset, arg0: str) -> scipp._scipp.core.Dataset

2. drop_coords(self: scipp._scipp.core.Dataset, arg0: List[str]) -> scipp._scipp.core.Dataset

get(key, default=None)

Get the value associated with the provided key or the default value.

groupby(group, *, bins=None)

Group dataset or data array based on values of specified labels.

Seealso

Details in scipp.groupby()

Return type

Union[GroupByDataArray, GroupByDataset]

hist(arg_dict=None, /, **kwargs)

Compute a histogram.

Seealso

Details in scipp.hist()

items(self: scipp._scipp.core.Dataset) → scipp._scipp.core.Dataset_items_view

view on self’s items

keys(self: scipp._scipp.core.Dataset) → scipp._scipp.core.Dataset_keys_view

view on self’s keys

max(dim=None)

Maximum of elements in the input.

Seealso

Details in scipp.max()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

mean(dim=None)

Arithmetic mean of elements in the input.

Seealso

Details in scipp.mean()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

property meta

Dict of coordinates.

min(dim=None)

Minimum of elements in the input.

Seealso

Details in scipp.min()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

nanmax(dim=None)

Maximum of elements in the input ignoring NaN’s.

Seealso

Details in scipp.nanmax()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

nanmean(dim=None)

Arithmetic mean of elements in the input ignoring NaN’s.

Seealso

Details in scipp.nanmean()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

nanmin(dim=None)

Minimum of elements in the input ignoring NaN’s.

Seealso

Details in scipp.nanmin()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

nansum(dim=None)

Sum of elements in the input ignoring NaN’s.

Seealso

Details in scipp.nansum()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

property ndim

Number of dimensions of the data (read-only).

pop(key, default=NotSpecified)

Remove and return an element.

If key is not found, default is returned if given, otherwise KeyError is raised.

rebin(arg_dict=None, deprecated=None, /, **kwargs)

Rebin a data array or dataset.

Seealso

Details in scipp.rebin()

rename(dims_dict=None, /, **names)

Rename the dimensions, coordinates and attributes of all the items.

The renaming can be defined:

• using a dict mapping the old to new names, e.g. rename({'x': 'a', 'y': 'b'})

• using keyword arguments, e.g. rename(x='a', y='b')

In both cases, x is renamed to a and y to b.

Names not specified in either input are unchanged.

Parameters

• dims_dict (Optional[Dict[str, str]], default: None) – Dictionary mapping old to new names.

• names (str) – Mapping of old to new names as keyword arguments.

Returns

Dataset – A new dataset with renamed dimensions, coordinates, and attributes. Buffers are shared with the input.

See also

scipp.Dataset.rename_dims

Only rename dimensions, not coordinates and attributes.

rename_dims(dims_dict=None, /, **names)

Rename dimensions.

The renaming can be defined:

• using a dict mapping the old to new names, e.g. rename_dims({'x': 'a', 'y': 'b'})

• using keyword arguments, e.g. rename_dims(x='a', y='b')

In both cases, x is renamed to a and y to b.

Dimensions not specified in either input are unchanged.

This function only renames dimensions. See the rename method to also rename coordinates and attributes.

Parameters

• dims_dict (Optional[Dict[str, str]], default: None) – Dictionary mapping old to new names.

• names (str) – Mapping of old to new names as keyword arguments.

Returns

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup) – A new object with renamed dimensions.

save_hdf5(filename)

Write an object out to file in HDF5 format.

Return type

None

property shape

Shape of the data (read-only).

property sizes

dict mapping dimension labels to dimension sizes (read-only).

squeeze(dim=None)

Remove dimensions of length 1.

Seealso

Details in scipp.squeeze()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

sum(dim=None)

Sum of elements in the input.

Seealso

Details in scipp.sum()

Return type

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup)

to_hdf5(filename)

Write an object out to file in HDF5 format.

Deprecated since version 23.03.0: Use scipp.io.hdf5.save_hdf5() instead. Will be removed in version 23.09.0.

Return type

None

transform_coords(targets=None, /, graph=None, *, rename_dims=True, keep_aliases=True, keep_intermediate=True, keep_inputs=True, quiet=False, **kwargs)

Compute new coords based on transformations of input coords.

Seealso

Details in scipp.transform_coords()

Return type

Union[DataArray, Dataset]

underlying_size(self: scipp._scipp.core.Dataset) → int

Return the size of the object in bytes.

The size includes the object itself and all arrays contained in it. But arrays may be counted multiple times if components share buffers, e.g. multiple coordinates referencing the same memory. Conversely, the size may be underestimated. Especially, but not only, with dtype=PyObject.

This function includes all memory of the underlying buffers. Use __sizeof__ to get the size of the current slice only.

update(self: scipp._scipp.core.Dataset, other: object = None, /, **kwargs) → None

Update items from dict-like or iterable.

If other has a .keys() method, then update does: for k in other.keys(): self[k] = other[k].

If other is given but does not have a .keys() method, then update does: for k, v in other: self[k] = v.

In either case, this is followed by: for k in kwargs: self[k] = kwargs[k].

See also

dict.update

values(self: scipp._scipp.core.Dataset) → scipp._scipp.core.Dataset_values_view

view on self’s values