BinnedDataSet¶

class minkit.BinnedDataSet(edges, gaps, pars, values)[source]¶

Bases: minkit.pdfs.dataset.DataObject

A binned data set.

Parameters

edges (darray) – edges of the bins.
gaps (numpy.ndarray) – gaps between edges belonging to different parameters.
data_pars (Registry(Parameter)) – data parameters.
values (darray) – values of the data for each center.

Attributes Summary

`aop`	Object to do operations on arrays.
`backend`	Backend interface.
`bounds`	Bounds of each data parameter.
`data_pars`	Data parameters associated to this sample.
`edges`	Edges of the histogram.
`edges_indices`	Indices to access the edges.
`gaps`	Gaps among the different edges.
`ndim`	Number of dimensions.
`sample_type`
`values`	Values of the data set.

Methods Summary

`from_ndarray`(edges, data_par, values[, backend])	Build the class from the array of edges and values.
`to_backend`(backend)	Initialize this class in a different backend.

Attributes Documentation

aop¶

Object to do operations on arrays.

Type: ArrayOperations

backend¶

Backend interface.

Type: Backend

bounds¶

Bounds of each data parameter.

Type: numpy.ndarray

data_pars¶

Data parameters associated to this sample.

Type: Registry(Parameter)

edges¶

Edges of the histogram.

Type: darray

edges_indices¶

Indices to access the edges.

Type: numpy.ndarray

gaps¶

Gaps among the different edges.

Type: numpy.ndarray

ndim¶

Number of dimensions.

Type: int

sample_type = 'binned'¶

values¶

Values of the data set.

Type: darray

Methods Documentation

classmethod from_ndarray(edges, data_par, values, backend=None)[source]¶

Build the class from the array of edges and values.

Parameters

edges (numpy.ndarray) – edges of the bins.
data_par (Parameter) – data parameter.
values (numpy.ndarray) – values at each bin.

Returns

Binned data set.

Return type

to_backend(backend)[source]¶

Initialize this class in a different backend.

Parameters: backend (Backend) – new backend.
Returns: This class in the new backend.