scipp.DataArray

class scipp.DataArray

Named variable with associated coords, masks, and attributes.

__init__(self, data: Variable, coords: Mapping[str, Variable] | Iterable[Tuple[str, Variable]] = {}, masks: Mapping[str, Variable] | Iterable[Tuple[str, Variable]] = {}, attrs: Mapping[str, Variable] | Iterable[Tuple[str, Variable]] = {}, name: str = '') → None

DataArray initializer.

Parameters:

• data – Data and optionally variances.

• coords – Coordinates referenced by dimension.

• masks – Masks referenced by name.

• attrs – Attributes referenced by dimension.

• name – Name of the data array.

Methods

__init__(self, data[, coords, masks, attrs, ...])	DataArray initializer.
all([dim])	Logical AND over input values.
any([dim])	Logical OR over input values.
assign_attrs([attrs])	Return new object with updated or inserted attrs.
assign_coords([coords])	Return new object with updated or inserted coordinate.
assign_masks([masks])	Return new object with updated or inserted masks.
astype(self, type, *[, copy])	Converts a Variable or DataArray to a different dtype.
bin([arg_dict])	Create binned data by binning input along all dimensions given by edges.
broadcast([dims, shape, sizes])	Broadcast a Variable or a DataArray.
ceil(*[, out])	Round up to the nearest integer of all values passed in x.
copy(self[, deep])	Return a (by default deep) copy.
deprecated_drop_attrs(*args, **kwargs)	Overloaded function.
drop_attrs(*args, **kwargs)	Drop attrs.
drop_coords(*args, **kwargs)	Overloaded function.
drop_masks(*args, **kwargs)	Overloaded function.
flatten([dims, to])	Flatten multiple dimensions into a single dimension.
floor(*[, out])	Round down to the nearest integer of all values passed in x.
fold(dim[, sizes, dims, shape])	Fold a single dimension of a variable or data array into multiple dims.
group(*args)	Create binned data by grouping input by one or more coordinates.
groupby(group, *[, bins])	Group dataset or data array based on values of specified labels.
hist([arg_dict])	Compute a histogram.
max([dim])	Maximum of elements in the input.
mean([dim])	Arithmetic mean of elements in the input.
median([dim])	Compute the median of the input values.
min([dim])	Minimum of elements in the input.
nanhist([arg_dict])	Compute a histogram, skipping NaN values.
nanmax([dim])	Maximum of elements in the input ignoring NaN's.
nanmean([dim])	Arithmetic mean of elements in the input ignoring NaN's.
nanmedian([dim])	Compute the median of the input values ignoring NaN's.
nanmin([dim])	Minimum of elements in the input ignoring NaN's.
nanstd([dim])	Compute the standard deviation of the input values ignoring NaN's.
nansum([dim])	Sum of elements in the input ignoring NaN's.
nanvar([dim])	Compute the variance of the input values ignoring NaN's.
plot(**kwargs)	Wrapper function to plot data.
rebin([arg_dict, deprecated])	Rebin a data array or dataset.
rename([dims_dict])	Rename the dimensions, coordinates, and attributes.
rename_dims([dims_dict])	Rename dimensions.
round(*[, out])	Round to the nearest integer of all values passed in x.
save_hdf5(filename)	Write an object out to file in HDF5 format.
squeeze([dim])	Remove dimensions of length 1.
std([dim])	Compute the standard deviation of the input values.
sum([dim])	Sum of elements in the input.
to(*[, unit, dtype, copy])	Converts a Variable or DataArray to a different dtype and/or a different unit.
transform_coords([targets, graph, ...])	Compute new coords based on transformations of input coords.
transpose([dims])	Transpose dimensions of the input.
underlying_size(self)	Return the size of the object in bytes.
var([dim])	Compute the variance of the input values.

Attributes

attrs	Dict of attrs.
bins	Returns helper scipp.Bins allowing bin-wise operations to be performed or None if not binned data.
coords	Dict of aligned coords.
data	Underlying data item.
deprecated_attrs	Dict of attrs.
deprecated_meta	Dict of coords and attrs.
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).
dtype	Data type contained in the variable.
masks	Dict of masks.
meta	Dict of coords and attrs.
name	The name of the held data.
ndim	Number of dimensions of the data (read-only).
shape	Shape of the data (read-only).
size	Number of elements in the data (read-only).
sizes	dict mapping dimension labels to dimension sizes (read-only).
unit	Physical unit of the data.
value	The only value for 0-dimensional data, raising an exception if the data is not 0-dimensional.
values	Array of values of the data.
variance	The only variance for 0-dimensional data, raising an exception if the data is not 0-dimensional.
variances	Array of variances of the data.

__getitem__(*args, **kwargs)

Overloaded function.

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

2. __getitem__(self: scipp._scipp.core.DataArray, arg0: slice) -> scipp._scipp.core.DataArray

3. __getitem__(self: scipp._scipp.core.DataArray, arg0: scipp._scipp.core.Variable) -> scipp._scipp.core.DataArray

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

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

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

7. __getitem__(self: scipp._scipp.core.DataArray, arg0: ellipsis) -> scipp._scipp.core.DataArray

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

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

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_attrs(attrs=None, /, **attrs_kwargs)

Return new object with updated or inserted attrs.

Parameters:

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

• attrs_kwargs – Keyword arguments form of attrs.

Returns:

DataArray – scipp.DataArray with updated attributes.

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.

assign_masks(masks=None, /, **masks_kwargs)

Return new object with updated or inserted masks.

Parameters:

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

• masks_kwargs – Keyword arguments form of masks.

Returns:

DataArray – scipp.DataArray with updated masks.

astype(self: scipp._scipp.core.DataArray, type: object, *, copy: bool = True) → scipp._scipp.core.DataArray

Converts a Variable or DataArray to a different dtype.

If the dtype is unchanged and copy is False, the object is returned without making a deep copy.

Parameters:

• type – Target dtype.

• copy – If False, return the input object if possible. If True, the function always returns a new object.

Raises:

If the data cannot be converted to the requested dtype.

Returns:

New variable or data array with specified dtype.

Return type:

Union[scipp.Variable, scipp.DataArray]

property attrs

Dict of attrs.

Deprecated since version 23.9.0: Use coords with unset alignment flag instead, or store attributes in higher-level data structures.

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

Create binned data by binning input along all dimensions given by edges.

Seealso:

Details in scipp.bin()

property bins

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

broadcast(dims=None, shape=None, sizes=None)

Broadcast a Variable or a DataArray.

Seealso:

Details in scipp.broadcast()

Return type:

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

ceil(*, out=None)

Round up to the nearest integer of all values passed in x.

Seealso:

Details in scipp.ceil()

Return type:

Union[Variable, DataArray, Dataset, DataGroup]

property coords

Dict of aligned coords.

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

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 data

Underlying data item.

property deprecated_attrs

Dict of attrs.

deprecated_drop_attrs(*args, **kwargs)

Overloaded function.

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

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

property deprecated_meta

Dict of coords and attrs.

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_attrs(*args, **kwargs)

Drop attrs.

Deprecated since version 23.9.0: Use coords with unset alignment flag instead, or store attributes in higher-level data structures.

drop_coords(*args, **kwargs)

Overloaded function.

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

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

drop_masks(*args, **kwargs)

Overloaded function.

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

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

property dtype

Data type contained in the variable.

flatten(dims=None, to=None)

Flatten multiple dimensions into a single dimension.

Seealso:

Details in scipp.flatten()

Return type:

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

floor(*, out=None)

Round down to the nearest integer of all values passed in x.

Seealso:

Details in scipp.floor()

Return type:

Union[Variable, DataArray, Dataset, DataGroup]

fold(dim, sizes=None, dims=None, shape=None)

Fold a single dimension of a variable or data array into multiple dims.

Seealso:

Details in scipp.fold()

Return type:

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

group(*args: str | Variable)

Create binned data by grouping input by one or more coordinates.

Seealso:

Details in scipp.group()

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()

property masks

Dict of masks.

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)

median(dim=None)

Compute the median of the input values.

Seealso:

Details in scipp.median()

Return type:

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

property meta

Dict of coords and attrs.

Deprecated since version 23.9.0: Use coords with unset alignment flag instead, or store attributes in higher-level data structures.

min(dim=None)

Minimum of elements in the input.

Seealso:

Details in scipp.min()

Return type:

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

property name

The name of the held data.

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

Compute a histogram, skipping NaN values.

Seealso:

Details in scipp.nanhist()

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)

nanmedian(dim=None)

Compute the median of the input values ignoring NaN’s.

Seealso:

Details in scipp.nanmedian()

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)

nanstd(dim=None, *, ddof)

Compute the standard deviation of the input values ignoring NaN’s.

Seealso:

Details in scipp.nanstd()

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)

nanvar(dim=None, *, ddof)

Compute the variance of the input values ignoring NaN’s.

Seealso:

Details in scipp.nanvar()

Return type:

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

property ndim

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

plot(**kwargs)

Wrapper function to plot data. See https://scipp.github.io/plopp/ for details.

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.

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:

DataArray – A new data array with renamed dimensions, coordinates, and attributes. Buffers are shared with the input.

See also

scipp.DataArray.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.

round(*, out=None)

Round to the nearest integer of all values passed in x.

Seealso:

Details in scipp.round()

Return type:

Union[Variable, DataArray, Dataset, DataGroup]

save_hdf5(filename)

Write an object out to file in HDF5 format.

Return type:

None

property shape

Shape of the data (read-only).

property size

Number of elements in 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)

std(dim=None, *, ddof)

Compute the standard deviation of the input values.

Seealso:

Details in scipp.std()

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(*, unit=None, dtype=None, copy=True)

Converts a Variable or DataArray to a different dtype and/or a different unit.

If the dtype and unit are both unchanged and copy is False, the object is returned without making a deep copy.

This method will choose whether to do the dtype or units translation first, by using the following rules in order:

• If either the input or output dtype is float64, the unit translation will be done on the float64 type

• If either the input or output dtype is float32, the unit translation will be done on the float32 type

• If both the input and output dtypes are integer types, the unit translation will be done on the larger type

• In other cases, the dtype is converted first and then the unit translation is done

Parameters:

• unit (Union[Unit, str, None], default: None) – Target unit. If None, the unit is unchanged.

• dtype (Optional[Any], default: None) – Target dtype. If None, the dtype is unchanged.

• copy (bool, default: True) – If False, return the input object if possible. If True, the function always returns a new object.

Returns:

Same as input – New object with specified dtype and unit.

Raises:

• scipp.DTypeError – If the input cannot be converted to the given dtype.

• scipp.UnitError – If the input cannot be converted to the given unit.

See also

scipp.to_unit, scipp.DataArray.astype, scipp.Variable.astype

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]

transpose(dims=None)

Transpose dimensions of the input.

Seealso:

Details in scipp.transpose()

Return type:

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

underlying_size(self: scipp._scipp.core.DataArray) → 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.

property unit

Physical unit of the data.

property value

The only value for 0-dimensional data, raising an exception if the data is not 0-dimensional.

property values

Array of values of the data.

var(dim=None, *, ddof)

Compute the variance of the input values.

Seealso:

Details in scipp.var()

Return type:

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

property variance

The only variance for 0-dimensional data, raising an exception if the data is not 0-dimensional.

property variances

Array of variances of the data.