scipp.DataArray
scipp.DataArray#
- class scipp.DataArray#
Named variable with associated coords, masks, and attributes.
- __init__(self, data: Variable, coords: Union[Mapping[str, Variable], Iterable[Tuple[str, Variable]]] = {}, masks: Union[Mapping[str, Variable], Iterable[Tuple[str, Variable]]] = {}, attrs: Union[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.
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.
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.
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.
nanmin
([dim])Minimum of elements in the input ignoring NaN's.
nansum
([dim])Sum of elements in the input ignoring NaN's.
plot
([aspect, cbar, crop, errorbars, grid, ...])Plot a Scipp object.
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.
squeeze
([dim])Remove dimensions of length 1.
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.
to_hdf5
(filename)Writes object out to file in hdf5 format.
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.
Attributes
Dict of attrs.
Returns helper
scipp.Bins
allowing bin-wise operations to be performed or None if not binned data.Dict of aligned coords.
Underlying data item.
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).
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.
- Seealso
Details in
scipp.all()
- Return type
- any(dim=None)#
Logical OR over input values.
- Seealso
Details in
scipp.any()
- Return type
- 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.
- bin(arg_dict=None, /, **kwargs)#
Create binned data by binning input along all dimensions given by edges.
- Seealso
Details in
scipp.bin()
- Return type
- 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
- ceil(*, out=None)#
Round up to the nearest integer of all values passed in x.
- Seealso
Details in
scipp.ceil()
- Return type
- 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 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).
- 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
- floor(*, out=None)#
Round down to the nearest integer of all values passed in x.
- Seealso
Details in
scipp.floor()
- Return type
- 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
- group(*args)#
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, /, **kwargs)#
Compute a histogram.
- Seealso
Details in
scipp.hist()
- Return type
- property masks#
Dict of masks.
- max(dim=None)#
Maximum of elements in the input.
- Seealso
Details in
scipp.max()
- Return type
- mean(dim=None)#
Arithmetic mean of elements in the input.
- Seealso
Details in
scipp.mean()
- Return type
- property meta#
Dict of coords and attrs.
- min(dim=None)#
Minimum of elements in the input.
- Seealso
Details in
scipp.min()
- Return type
- property name#
The name of the held data.
- nanhist(arg_dict=None, /, **kwargs)#
Compute a histogram, skipping NaN values.
- Seealso
Details in
scipp.nanhist()
- Return type
- nanmax(dim=None)#
Maximum of elements in the input ignoring NaN’s.
- Seealso
Details in
scipp.nanmax()
- Return type
- nanmean(dim=None)#
Arithmetic mean of elements in the input ignoring NaN’s.
- Seealso
Details in
scipp.nanmean()
- Return type
- nanmin(dim=None)#
Minimum of elements in the input ignoring NaN’s.
- Seealso
Details in
scipp.nanmin()
- Return type
- nansum(dim=None)#
Sum of elements in the input ignoring NaN’s.
- Seealso
Details in
scipp.nansum()
- Return type
- property ndim#
Number of dimensions of the data (read-only).
- plot(aspect='auto', cbar=True, crop=None, errorbars=True, grid=False, ignore_size=False, mask_color='black', norm='linear', scale=None, title=None, vmin=None, vmax=None, **kwargs)#
Plot a Scipp object.
- Parameters
obj (
Union
[Variable
,DataArray
,Dataset
,ndarray
,Dict
[str
,Union
[Variable
,DataArray
,Dataset
,ndarray
]]]) – The object to be plotted.aspect (
Literal
[‘auto’, ‘equal’], default:'auto'
) – Aspect ratio for the axes.cbar (
bool
, default:True
) – Show colorbar in 2d plots ifTrue
.crop (
Optional
[Dict
[str
,Dict
[str
,Variable
]]], default:None
) – Set the axis limits. Limits should be given as a dict with one entry per dimension to be cropped. Each entry should be a nested dict containing scalar values for'min'
and/or'max'
. Example:da.plot(crop={'time': {'min': 2 * sc.Unit('s'), 'max': 40 * sc.Unit('s')}})
errorbars (
bool
, default:True
) – Show errorbars in 1d plots ifTrue
.grid (
bool
, default:False
) – Show grid ifTrue
.ignore_size (
bool
, default:False
) – IfTrue
, skip the check that prevents the rendering of very large data objects.mask_color (
str
, default:'black'
) – Color of masks in 1d plots.norm (
Literal
[‘linear’, ‘log’], default:'linear'
) – Set to'log'
for a logarithmic y-axis (1d plots) or logarithmic colorscale (2d plots).scale (
Optional
[Dict
[str
,str
]], default:None
) – Change axis scaling betweenlog
andlinear
. For example, specifyscale={'tof': 'log'}
if you want log-scale for thetof
dimension.vmin (
Optional
[Variable
], default:None
) – Lower bound for data to be displayed (y-axis for 1d plots, colorscale for 2d plots).vmax (
Optional
[Variable
], default:None
) – Upper bound for data to be displayed (y-axis for 1d plots, colorscale for 2d plots).**kwargs – All other kwargs are directly forwarded to Matplotlib, the underlying plotting library. The underlying functions called are the following: - 1d data with a non bin-edge coordinate:
plot
- 1d data with a bin-edge coordinate:step
- 2d data:pcolormesh
- Returns
A figure.
- rebin(arg_dict=None, deprecated=None, /, **kwargs)#
Rebin a data array or dataset.
- Seealso
Details in
scipp.rebin()
- Return type
- 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.
- Seealso
Details in
scipp.round()
- Return type
- 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
- sum(dim=None)#
Sum of elements in the input.
- Seealso
Details in
scipp.sum()
- Return type
- 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.
- to_hdf5(filename)#
Writes object out to file in hdf5 format.
- 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.
- Seealso
Details in
scipp.transpose()
- Return type
- 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.
- 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.