i-rSrSSKJr SSKJr SSKJrJrJrJr SSK J r \(aSSK J r "SS5rg ) ExecutionSpans) annotations)datetime)overloadIterableIterator TYPE_CHECKING) ExecutionSpan)Figurec\rSrSrSrSSjrSSjr\SSj5r\SSj5rSSjrSSjr SS jr SS jr \ SS j5r \ SS j5r\ SS j5r\ SSj5rSSjrS S!SjjrS"S#SjjrSrg)$ra8A collection of timings for pub results. This class is a list-like containing :class:`~.ExecutionSpan`\s, where each execution span represents a time window of data collection, and contains a reference to exactly which of the data were collected during the window. .. code::python spans = sampler_job.result().metadata["execution"]["execution_spans"] for span in spans: print(span) It is possible for distinct time windows to overlap. This is not because a QPU was performing multiple executions at once, but is instead an artifact of certain classical processing that may happen concurrently with quantum execution. The guarantee being made is that the referenced data definitely occurred in the reported execution span, but not necessarily that the limits of the time window are as tight as possible. c$[U5UlgN)list_spans)selfspanss k/home/james-whalen/.local/lib/python3.13/site-packages/qiskit_ibm_runtime/execution_span/execution_spans.py__init__ExecutionSpans.__init__/s 5k c,[UR5$r)lenrrs r__len__ExecutionSpans.__len__2s4;;rcgrridxss r __getitem__ExecutionSpans.__getitem__5s7:rcgrrr s rr"r#8sHKrc^[U[5(aTRU$[U[5(a[ TRU5$[ U4SjU55$)Nc3B># UHnTRUv M g7frr).0idxrs r -ExecutionSpans.__getitem__..@s?$3dkk#.$s) isinstanceintrslicerr s` rr"r#;sQ dC ;;t$ $ dE " "!$++d"34 4?$???rc,[UR5$r)iterrrs r__iter__ExecutionSpans.__iter__BsDKK  rc4S[UR5S3$)NzExecutionSpans())reprrrs r__repr__ExecutionSpans.__repr__Es dkk!2 3155rcb[U[5=(a URUR:H$r)r,rr)rothers r__eq__ExecutionSpans.__eq__Hs!%0PT[[ELL5PPrcn[UVVs1sHoRHo"iM M snn5$s snnf)zMWhich pubs, by index, have dependence on one or more execution spans present.)sortedpub_idxs)rspanr)s rr>ExecutionSpans.pub_idxsKs+tEtt}}s}stEFFEs1 c&[SU55$)z0The start time of the entire collection, in UTC.c38# UHoRv M g7fr)startr(r?s rr*'ExecutionSpans.start..Ss/$$::$)minrs rrCExecutionSpans.startPs/$///rc&[SU55$)z/The stop time of the entire collection, in UTC.c38# UHoRv M g7fr)stoprDs rr*&ExecutionSpans.stop..Xs.99rF)maxrs rrKExecutionSpans.stopUs....rcPURUR- R5$)z2The total duration of this collection, in seconds.)rKrC total_secondsrs rdurationExecutionSpans.durationZs  DJJ&5577rc.^[U4SjU55$)zReturn a new set of spans where each one has been filtered to the specified pubs. See also :meth:~.ExecutionSpan.filter_by_pub`. Args: pub_idx: One or more pub indices to filter. c3D># UHoRT5v M g7fr) filter_by_pub)r(r?pub_idxs rr*/ExecutionSpans.filter_by_pub..gsKdd0099ds )r)rrVs `rrUExecutionSpans.filter_by_pub_sKdKKKrcbU(aUO [U5nURR5 U$)aReturn the same execution spans, sorted. Sorting is done by the :attr:`~.ExecutionSpan.start` timestamp of each execution span. Args: inplace: Whether to sort this instance in place, or return a copy. Returns: This instance if ``inplace``, a new instance otherwise, sorted. )rrsort)rinplaceobjs rrZExecutionSpans.sortis%d>$#7  rNcSSKJn U"XX1S9$)aDraw these execution spans. .. note:: To draw multiple sets of execution spans at once, for example coming from multiple jobs, consider calling :meth:`~qiskit_ibm_runtime.visualization.draw_execution_spans` directly. Args: name: The name of this set of spans. normalize_y: Whether to display the y-axis units as a percentage of work complete, rather than cumulative shots completed. line_width: The thickness of line segments. Returns: A plotly figure. )draw_execution_spans) normalize_y line_widthnames) visualizationr`)rnamerarbr`s rdrawExecutionSpans.drawxs( 9# j  rr')rzIterable[ExecutionSpan])returnr-)r!r-rhr )r!zslice | list[int]rh'ExecutionSpans')r!zint | slice | list[int]rhz ExecutionSpan | 'ExecutionSpans')rhzIterator[ExecutionSpan])rhstr)r9objectrhbool)rhz list[int])rhr)rhfloat)rVzint | Iterable[int]rhri)T)r[rlrhri)NF)rerjrarlrbr-rh PlotlyFigure)__name__ __module__ __qualname____firstlineno____doc__rrrr"r1r6r:propertyr>rCrKrQrUrZrf__static_attributes__rrrrrs(" :: KK@!6QGG00//88L  NO  -1 GJ   rN)rt __future__rrtypingrrrr execution_spanr plotly.graph_objectsr rorrrrr{s+">>);v v r