BaseCurveAnalysis#

class BaseCurveAnalysis[source]#

Abstract superclass of curve analysis base classes.

Note that this class doesn’t define the _run_analysis() method, and no actual fitting protocol is implemented in this base class. However, this class defines several common methods that can be reused. A curve analysis subclass can construct proper fitting protocol by combining following methods, i.e. subroutines. See Curve Analysis workflow for how these subroutines are called.

Subclass must implement following methods.

_run_data_processing

This method performs data processing and returns the processed dataset. Input data is a list of dictionaries, where each entry represents an outcome of circuit sampling along with the metadata attached to it.

_format_data

This method consumes the processed dataset and outputs the formatted dataset. For example, this may include averaging Y values over the same X data points.

_run_curve_fit

This method performs the fitting with the predefined fit models and the formatted dataset. This is a core functionality of the _run_analysis() method that creates fit result objects from the formatted dataset.

Optionally, a subclass may override following methods. These methods have default implementations as described below.

_evaluate_quality

This method evaluates the quality of the fit based on the fit result. This returns “good” when reduced chi-squared is less than 3.0. Usually it returns string “good” or “bad” according to the evaluation. This criterion can be updated by subclass.

_run_curve_fit

This method performs the fitting with predefined fit models and the formatted dataset. This method internally calls _generate_fit_guesses() method. Note that this is a core functionality of the _run_analysis() method, that creates fit result object from the formatted dataset.

_create_analysis_results

This method creates analysis results for important fit parameters that might be defined by analysis options result_parameters.

_create_figures

This method creates figures by consuming the scatter table data. Figures are created when the analysis option plot is True.

_initialize

This method initializes analysis options against input experiment data. Usually this method is called before other methods are called.

Initialize the analysis object.

Attributes

drawer#: A short-cut for curve drawer instance, if set. None otherwise.

Deprecated since version 0.5: The method qiskit_experiments.curve_analysis.base_curve_analysis.BaseCurveAnalysis.drawer() is deprecated as of qiskit-experiments 0.5. It will be removed after 0.6. Use plotter from the new visualization module.

models#: Return fit models.

name#: Return name of this analysis.

options#: Return the analysis options for run() method.

parameters#: Return parameters estimated by this analysis.

plotter#: A short-cut to the curve plotter instance.

Methods

config()#

Return the config dataclass for this analysis

Return type:: AnalysisConfig

copy()#

Return a copy of the analysis

Return type:: BaseAnalysis

classmethod from_config(config)#

Initialize an analysis class from analysis config

Return type:: BaseAnalysis

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:

ExperimentData

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.

set_options(**fields)#

Set the analysis options for run() method.

Parameters:: fields – The fields to update the options