bloqade.analog.task.base.Report

← Module overview

classReport¶source

bloqade.analog.task.base.Report

Report is a helper class for organizing and analysing data

class Report(data, metas, geos, name='')

Public import paths

• from bloqade.analog.task.batch import Report
• from bloqade.analog.visualization.report_visualize import Report

Analyzing Results

When you’ve retrieved your results from either emulation or hardware you can generate a .report():

report = results.report()

For the examples below we analyze the results of a two atom program.

The report contains useful information such as:

The raw bitstrings measured per each execution of the program

>>> report.bitstrings()
[array([[1, 1],
        [1, 1],
        [1, 1],
        ...,
        [1, 1],
        [1, 1],

The number of times each unique bitstring occurred:

>>> report.counts()

[OrderedDict([('11', 892), ('10', 59), ('01', 49)])]

The Rydberg Density for each atom

>>> report.rydberg_densities()

                0      1
task_number
0            0.053  0.054

Parameters

Name	Type	Default	Description
data	—	required
metas	—	required
geos	—	required
name	—	''

Attributes

Name	Type	Default	Description
dataframe	pd.DataFrame	data
metas	List[Dict]	metas
geos	List[Geometry]	geos
name	str	name + ' ' + str(datetime.datetime.now())

methodlist_param¶source

bloqade.analog.task.base.Report.list_param

def list_param(field_name: str) -> List[Union[Number, None]]

List the parameters associate with the given variable field_name for each tasks.

Parameters

Name	Type	Description
field_name	str	variable name

Returns

List[Union[Number, None]]

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propertymarkdown¶source

bloqade.analog.task.base.Report.markdown

markdown: str

Get the markdown representation of the dataframe

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methodbitstrings¶source

bloqade.analog.task.base.Report.bitstrings

Signature

def bitstrings(filter_perfect_filling: bool = True, clusters: Union[tuple[int, int], List[tuple[int, int]]] = []) -> List[NDArray]

Get the bitstrings from the data.

Parameters

Name	Type	Default	Description
filter_perfect_filling	bool	True	whether return will only contain perfect filling shots. Defaults to True.
clusters	Union[tuple[int, int], List[tuple[int, int]]]	[]	(tuple[int, int], Sequence[Tuple[int, int]]): cluster index to filter shots from. If none are provided all clusters are used, defaults to [].

Returns

list of ndarraybitstrings: list corresponding to each task in the report. Each element is an ndarray of shape (nshots, nsites) where nshots is the number of shots for the task and nsites is the number of sites in the task. For example: ```python3 [array([[1, 1], [1, 1], [1, 1], ..., [1, 1], [1, 1], [1, 0]], dtype=int8)] ```

Note

Note that nshots may vary between tasks if filter_perfect_filling is set to True.

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methodcounts¶source

bloqade.analog.task.base.Report.counts

Signature

def counts(filter_perfect_filling: bool = True, clusters: Union[tuple[int, int], List[tuple[int, int]]] = []) -> List[OrderedDict[str, int]]

Get the counts of unique bit strings.

Parameters

Name	Type	Default	Description
filter_perfect_filling	bool	True	whether return will only contain perfect filling shots. Defaults to True.
clusters	Union[tuple[int, int], List[tuple[int, int]]]	[]	(tuple[int, int], Sequence[Tuple[int, int]]): cluster index to filter shots from. If none are provided all clusters are used, defaults to [].

Returns

list of OrderedDict[str, int]counts: list corresponding to each task in the report. Each element is an ndarray of shape (nshots, nsites) where nshots is the number of shots for the task and nsites is the number of sites in the task. For example: ```python [OrderedDict([('11', 892), ('10', 59), ('01', 49)])] ```

Note

Note that nshots may vary between tasks if filter_perfect_filling is set to True.

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methodrydberg_densities¶source

bloqade.analog.task.base.Report.rydberg_densities

Signature

def rydberg_densities(filter_perfect_filling: bool = True, clusters: Union[tuple[int, int], List[tuple[int, int]]] = []) -> Union[pd.Series, pd.DataFrame]

Get rydberg density for each task.

Parameters

Name	Type	Default	Description
filter_perfect_filling	bool	True	whether return will only contain perfect filling shots. Defaults to True.
clusters	Union[tuple[int, int], List[tuple[int, int]]]	[]	(tuple[int, int], Sequence[Tuple[int, int]]): cluster index to filter shots from. If none are provided all clusters are used, defaults to [].

Returns

Union[pd.Series, pd.DataFrame]rydberg_densities: per-site rydberg density for each task as a pandas DataFrame or Series. For example: ```python 0 1 task_number 0 0.053 0.054 ```

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methodshow¶source

bloqade.analog.task.base.Report.show

def show()

Interactive Visualization of the Report

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