Note
This is the documentation for the current state of the development branch of Qiskit Experiments. The documentation or APIs here can change prior to being released.
MultiStateDiscriminationAnalysis¶
- class MultiStateDiscriminationAnalysis[source]¶
This class fits a multi-state discriminator to the data.
The class will report the configuration of the discriminator in the analysis result as well as the fidelity of the discrimination reported as
\[F = 1 - \frac{1}{d}\sum{i\neq j}P(i|j)\]Here, \(d\) is the number of levels that were discriminated while \(P(i|j)\) is the probability of measuring outcome \(i\) given that state \(j\) was prepared.
Note
This class requires that scikit-learn is installed.
Analysis options
These are the keyword arguments of the
run()
method.- Options
Defined in the class
MultiStateDiscriminationAnalysis
:plot (bool)
Default value:True
SetTrue
to create figure for fit result.plotter (BasePlotter)
Default value: Instance ofIQPlotter
A plotter instance to visualize the analysis result.ax (AxesSubplot)
Default value:None
Optional. A matplotlib axis object in which to draw.discriminator (BaseDiscriminator)
Default value: Instance ofSkQDA
The sklearn discriminator to classify the data. The default is a quadratic discriminant analysis.
Defined in the class
BaseAnalysis
:figure_names (str or List[str])
Default value:None
Identifier of figures that appear in the experiment data to sort figures by name.
Initialization
Initialize the analysis object.
Attributes
- plotter¶
A short-cut to the IQ plotter instance.
Methods
- config()¶
Return the config dataclass for this analysis
- Return type:
- copy()¶
Return a copy of the analysis
- Return type:
- classmethod from_config(config)¶
Initialize an analysis class from analysis config
- Return type:
- run(experiment_data, replace_results=False, **options)¶
Run analysis and update ExperimentData with analysis result.
- Parameters:
experiment_data (ExperimentData) – the experiment data to analyze.
replace_results (bool) – If True clear any existing analysis results, figures, and artifacts in the experiment data and replace with new results. See note for additional information.
options – additional analysis options. See class documentation for supported options.
- Returns:
An experiment data object containing analysis results, figures, and artifacts.
- Raises:
QiskitError – If experiment_data container is not valid for analysis.
- Return type:
Note
Updating Results
If analysis is run with
replace_results=True
then any analysis results, figures, and artifacts in the experiment data will be cleared and replaced with the new analysis results. Saving this experiment data will replace any previously saved data in a database service using the same experiment ID.If analysis is run with
replace_results=False
and the experiment data being analyzed has already been saved to a database service, or already contains analysis results or figures, a copy with a unique experiment ID will be returned containing only the new analysis results and figures. This data can then be saved as its own experiment to a database service.