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, dim])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)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, *[, dims, shape, sizes])Fold a single dimension of a variable or data array into multiple dims.
group
(*args[, dim])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, dim])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, dim])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])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
Dict of attrs.
Returns helper
scipp.Bins
allowing bin-wise operations to be performed or None if not binned data.Dict of coords.
Underlying data item.
Dict of attrs.
Dict of coords and attrs.
The only dimension label for 1-dimensional data, raising an exception if the data is not 1-dimensional.
Dimension labels of the data (read-only).
Data type contained in the variable.
Dict of masks.
Dict of coords and attrs.
The name of the held data.
Number of dimensions of the data (read-only).
Shape of the data (read-only).
Number of elements in the data (read-only).
dict mapping dimension labels to dimension sizes (read-only).
Physical unit of the data.
The only value for 0-dimensional data, raising an exception if the data is not 0-dimensional.
Array of values of the data.
The only variance for 0-dimensional data, raising an exception if the data is not 0-dimensional.
Array of variances of the data.
- __getitem__(*args, **kwargs)#
Overloaded function.
__getitem__(self: scipp._scipp.core.DataArray, arg0: int) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: slice) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: scipp._scipp.core.Variable) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: tuple[str, scipp._scipp.core.Variable]) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: tuple[str, int]) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: tuple[str, slice]) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: ellipsis) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: list[int]) -> scipp._scipp.core.DataArray
__getitem__(self: scipp._scipp.core.DataArray, arg0: tuple[str, list[int]]) -> scipp._scipp.core.DataArray
- all(dim=None)#
Logical AND over input values.
- any(dim=None)#
Logical OR over input values.
- assign_attrs(attrs=None, /, **attrs_kwargs)#
Return new object with updated or inserted attrs.
- assign_coords(coords=None, /, **coords_kwargs)#
Return new object with updated or inserted coordinate.
- assign_masks(masks=None, /, **masks_kwargs)#
Return new object with updated or inserted 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: Coords#
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, /, *, dim=None, **kwargs)#
Create binned data by binning input along all dimensions given by edges.
- Seealso:
Details in
scipp.bin()
- Return type:
- property bins: Bins[_O] | None#
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.
- ceil(*, out=None)#
Round up to the nearest integer of all values passed in x.
- Seealso:
Details in
scipp.ceil()
- Return type:
VariableLike
- property coords#
Dict of 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.
deprecated_drop_attrs(self: scipp._scipp.core.DataArray, arg0: str) -> scipp._scipp.core.DataArray
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)#
Drop attrs. :rtype:
DataArray
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.
drop_coords(self: scipp._scipp.core.DataArray, arg0: str) -> scipp._scipp.core.DataArray
drop_coords(self: scipp._scipp.core.DataArray, arg0: list[str]) -> scipp._scipp.core.DataArray
- drop_masks(*args, **kwargs)#
Overloaded function.
drop_masks(self: scipp._scipp.core.DataArray, arg0: str) -> scipp._scipp.core.DataArray
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.
- floor(*, out=None)#
Round down to the nearest integer of all values passed in x.
- Seealso:
Details in
scipp.floor()
- Return type:
VariableLike
- fold(dim, *, dims=None, shape=None, sizes=None)#
Fold a single dimension of a variable or data array into multiple dims.
- group(*args, dim=None)#
Create binned data by grouping input by one or more coordinates.
- Seealso:
Details in
scipp.group()
- Return type:
- groupby(group, *, bins=None)#
Group dataset or data array based on values of specified labels.
- Seealso:
Details in
scipp.groupby()
- Return type:
- hist(arg_dict=None, /, *, dim=None, **kwargs)#
Compute a histogram.
- property masks#
Dict of masks.
- max(dim=None)#
Maximum of elements in the input.
- mean(dim=None)#
Arithmetic mean of elements in the input.
- median(dim=None)#
Compute the median of the input values.
- property meta: Coords#
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.
- property name#
The name of the held data.
- nanhist(arg_dict=None, /, *, dim=None, **kwargs)#
Compute a histogram, skipping NaN values.
- nanmax(dim=None)#
Maximum of elements in the input ignoring NaN’s.
- nanmean(dim=None)#
Arithmetic mean of elements in the input ignoring NaN’s.
- nanmedian(dim=None)#
Compute the median of the input values ignoring NaN’s.
- nanmin(dim=None)#
Minimum of elements in the input ignoring NaN’s.
- nanstd(dim=None, *, ddof)#
Compute the standard deviation of the input values ignoring NaN’s.
- nansum(dim=None)#
Sum of elements in the input ignoring NaN’s.
- nanvar(dim=None, *, ddof)#
Compute the variance of the input values ignoring NaN’s.
- 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.
- Return type:
- rebin(arg_dict=None, /, **kwargs)#
Rebin a data array or dataset.
- 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:
- 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.
- round(*, out=None)#
Round to the nearest integer of all values passed in x.
- 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.
- std(dim=None, *, ddof)#
Compute the standard deviation of the input values.
- sum(dim=None)#
Sum of elements in the input.
- 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. IfNone
, the unit is unchanged.dtype (
Optional
[Any
], default:None
) – Target dtype. IfNone
, the dtype is unchanged.copy (
bool
, default:True
) – IfFalse
, return the input object if possible. IfTrue
, 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.
- 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:
- transpose(dims=None)#
Transpose dimensions of the input.
- 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.
- 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.