ess.reduce.nexus.types.NeXusData

class ess.reduce.nexus.types.NeXusData(x: SUPER)

Data array loaded from an NXevent_data or NXdata group.

This must be contained in an NXmonitor or NXdetector group.

__init__(self, data: Variable, coords: Mapping[str, Variable] | Iterable[tuple[str, Variable]] = {}, masks: 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.

• name – Name of the data array.

Methods

__init__(self, data[, coords, masks, name])	DataArray 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.
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.
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

bins	Returns helper scipp.Bins allowing bin-wise operations to be performed or None if not binned data.
coords	Dict of coords.
data	Underlying data item.
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.
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.