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
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
Return the analysis options for
run()
method.A short-cut to the IQ plotter instance.
Methods
Return the config dataclass for this analysis
Return a copy of the analysis
Initialize an analysis class from analysis config
MultiStateDiscriminationAnalysis.run
(...[, ...])Run analysis and update ExperimentData with analysis result.
Set the analysis options for
run()
method.