Skip to main contentIBM Quantum Documentation

SliceSpan

class SliceSpan(start, stop, data_slices)

GitHub

Bases: ExecutionSpan

An ExecutionSpan for data stored in a sliceable format.

This type of execution span references pub result data by assuming that it is a sliceable portion of the (row major) flattened data. Therefore, for each pub dependent on this span, the constructor accepts a single slice object, along with the corresponding shape of the data to be sliced.

Parameters

  • start (datetime) – The start time of the span, in UTC.
  • stop (datetime) – The stop time of the span, in UTC.
  • data_slices (dict[int, tuple[ShapeType, slice]]) – A map from pub indices to pairs (shape_tuple, slice).

Attributes

duration

The duration of this span, in seconds.

pub_idxs

size

start

The start time of the span, in UTC.

stop

The stop time of the span, in UTC.


Methods

contains_pub

contains_pub(pub_idx)

GitHub

Return whether the pub with the given index has data with dependence on this span.

Parameters

pub_idx (int | Iterable[int]) – One or more pub indices from the original primitive call.

Returns

Whether there is dependence on this span.

Return type

bool

filter_by_pub

filter_by_pub(pub_idx)

GitHub

Return a new span whose slices are filtered to the provided pub indices.

For example, if this span contains slice information for pubs with indices 1, 3, 4 and [1, 4] is provided, then the span returned by this method will contain slice information for only those two indices, but be identical otherwise.

Parameters

pub_idx (int | Iterable[int]) – One or more pub indices from the original primitive call.

Returns

A new filtered span.

Return type

SliceSpan

mask

mask(pub_idx)

GitHub

Return an array-valued mask specifying which parts of a pub result depend on this span.

Parameters

pub_idx (int) – The index of the pub to return a mask for.

Returns

An array with the same shape as the pub data.

Return type

ndarray[Any, dtype[bool]]

Was this page helpful?
Report a bug or request content on GitHub.