scipp.Variable

class scipp.Variable

Array of values with dimension labels and a unit, optionally including an array of variances.

__init__(self: scipp._scipp.core.Variable, *, dims: object, values: object = None, variances: object = None, unit: Union[str, scipp._scipp.core.Unit, None, scipp._scipp.core.DefaultUnit] = <automatically deduced unit>, dtype: object = None, aligned: bool = True) → None

Initialize a variable with values and/or variances.

At least one argument of values and variances must be used. if you want to preallocate memory to fill later, use scipp.empty().

Attention

This constructor is meant primarily for internal use. Use one of the Specialized creation functions instead. See in particular scipp.array() and scipp.scalar().

Parameters:

• dims – Dimension labels.

• values – Sequence of values for constructing an array variable.

• variances – Sequence of variances for constructing an array variable.

• unit – Physical unit, defaults to scipp.units.dimensionless.

• dtype – Type of the variable’s elements. Is deduced from other arguments in most cases. Defaults to sc.DType.float64 if no deduction is possible.

• aligned – Initial value for the alignment flag.

Methods

__init__(self, *, dims, values, variances, ...)	Initialize a variable with values and/or variances.
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, 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.
cumsum([dim, mode])	Return the cumulative sum along the specified dimension.
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.
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.
rename([dims_dict])	Rename dimension labels.
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.
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

aligned	Alignment flag for coordinates.
bins	Returns helper scipp.Bins allowing bin-wise operations to be performed or None if not binned data.
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.
fields	Provides access to fields of structured types such as vectors or matrices.
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.Variable, arg0: int) -> scipp._scipp.core.Variable

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

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

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

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

6. __getitem__(self: scipp._scipp.core.Variable, arg0: ellipsis) -> scipp._scipp.core.Variable

7. __getitem__(self: scipp._scipp.core.Variable, arg0: list[int]) -> scipp._scipp.core.Variable

8. __getitem__(self: scipp._scipp.core.Variable, arg0: tuple[str, list[int]]) -> scipp._scipp.core.Variable

property aligned

Alignment flag for coordinates.

Indicates whether a coordinate is aligned. Aligned coordinates must match between the operands of binary operations while unaligned coordinates are dropped on mismatch.

This flag is only meaningful when the variable is contained in a coords dict.

It cannot be set on a variable directly; instead, use sc.Coords.set_aligned().

For binned coordinates of a binned data array da, da.bins.coords[name].aligned should always be True. The alignment w.r.t. the events can be queried via da.bins.coords[name].bins.aligned and set via da.bins.coords.set_aligned(name, aligned).

all(dim=None)

Logical AND over input values.

Seealso:

Details in scipp.all()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

any(dim=None)

Logical OR over input values.

Seealso:

Details in scipp.any()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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

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]

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:

DataArray | DataGroup[Any]

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.

Seealso:

Details in scipp.broadcast()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

ceil(*, out=None)

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

Seealso:

Details in scipp.ceil()

Return type:

VariableLike

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

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.

cumsum(dim=None, mode='inclusive')

Return the cumulative sum along the specified dimension.

Seealso:

Details in scipp.cumsum()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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.

property fields: Any

Provides access to fields of structured types such as vectors or matrices.

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[Any])

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.

Seealso:

Details in scipp.fold()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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

Compute a histogram.

Seealso:

Details in scipp.hist()

Return type:

Variable | DataArray | Dataset | DataGroup[Any]

max(dim=None)

Maximum of elements in the input.

Seealso:

Details in scipp.max()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

mean(dim=None)

Arithmetic mean of elements in the input.

Seealso:

Details in scipp.mean()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

median(dim=None)

Compute the median of the input values.

Seealso:

Details in scipp.median()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

min(dim=None)

Minimum of elements in the input.

Seealso:

Details in scipp.min()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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

Compute a histogram, skipping NaN values.

Seealso:

Details in scipp.nanhist()

Return type:

Variable | DataArray | Dataset | DataGroup[Any]

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[Any])

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[Any])

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[Any])

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[Any])

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[Any])

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[Any])

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[Any])

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:

Any

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

Rename dimension labels.

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.

Dimensions 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:

Variable – A new variable with renamed dimensions which shares a buffer with the input.

See also

scipp.Variable.rename_dims

Equivalent for Variable but differs for DataArray and Dataset.

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(_T, Variable, DataArray, Dataset) – 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:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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[Any])

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[Any])

sum(dim=None)

Sum of elements in the input.

Seealso:

Details in scipp.sum()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

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

transpose(dims=None)

Transpose dimensions of the input.

Seealso:

Details in scipp.transpose()

Return type:

TypeVar(VariableLikeType, Variable, DataArray, Dataset, DataGroup[Any])

underlying_size(self: scipp._scipp.core.Variable) → 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[Any])

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.