Source code for qiskit_experiments.library.characterization.analysis.resonator_spectroscopy_analysis

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# (C) Copyright IBM 2021.
# This code is licensed under the Apache License, Version 2.0. You may
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"""Spectroscopy analysis class for resonators."""

from typing import List, Tuple
import numpy as np

import qiskit_experiments.curve_analysis as curve
from qiskit_experiments.framework import AnalysisResultData, ExperimentData
from qiskit_experiments.framework.matplotlib import get_non_gui_ax
from qiskit_experiments.data_processing.nodes import ProjectorType
from qiskit_experiments.database_service.device_component import Resonator

[docs] class ResonatorSpectroscopyAnalysis(curve.ResonanceAnalysis): """Class to analysis resonator spectroscopy.""" @classmethod def _default_options(cls): """Return default analysis options. Analysis Options: dimensionality_reduction (ProjectorType): Type of the data processor node that will reduce the two-dimensional data to one dimension. plot_iq_data (bool): Set True to generate IQ plot. """ options = super()._default_options() options.dimensionality_reduction = ProjectorType.ABS options.result_parameters = [ curve.ParameterRepr("freq", "res_freq0", "Hz"), curve.ParameterRepr("kappa", "kappa", "Hz"), ] options.plot_iq_data = True return options def _get_experiment_components(self, experiment_data: ExperimentData): """Return resonators as experiment components.""" return [Resonator(qubit) for qubit in experiment_data.metadata["physical_qubits"]] def _run_analysis( self, experiment_data: ExperimentData ) -> Tuple[List[AnalysisResultData], List["pyplot.Figure"]]: """Wrap the analysis to optionally plot the IQ data.""" analysis_results, figures = super()._run_analysis(experiment_data) if self.options.plot_iq_data: axis = get_non_gui_ax() figure = axis.get_figure() # TODO: Move plotting to a new IQPlotter class. figure.set_size_inches(*["figsize"]) iqs = [] for datum in if "memory" in datum: mem = np.array(datum["memory"]) # Average single-shot data. if len(mem.shape) == 3: for idx in range(mem.shape[1]): iqs.append(np.average(mem[:, idx, :], axis=0)) else: iqs.append(mem) if len(iqs) > 0: iqs = np.vstack(iqs) axis.scatter(iqs[:, 0], iqs[:, 1], color="b") axis.set_xlabel( "In phase [arb. units]",["axis_label_size"] ) axis.set_ylabel( "Quadrature [arb. units]",["axis_label_size"] ) axis.tick_params(["tick_label_size"]) axis.grid(True) figures.append(figure) return analysis_results, figures