qblox_scheduler.analysis.readout_calibration_analysis

Module containing an analysis class for two-state readout calibration.

Classes

ReadoutCalibrationAnalysis

Find threshold and angle which discriminates qubit state.

Module Contents

class ReadoutCalibrationAnalysis(dataset: xarray.Dataset | None = None, tuid: quantify_core.data.types.TUID | str | None = None, label: str = '', settings_overwrite: dict | None = None, plot_figures: bool = True)

Bases: qblox_scheduler.analysis.base_analysis.BaseAnalysis

Find threshold and angle which discriminates qubit state.

Example

import os
import warnings

with warnings.catch_warnings():
    warnings.simplefilter("ignore")
    from qblox_scheduler.analysis.data_handling import OutputDirectoryManager as mng
from qblox_scheduler.analysis.readout_calibration_analysis import (
    ReadoutCalibrationAnalysis,
)

# load example data
test_data_dir = "../tests/test_data"
mng.set_datadir(test_data_dir)
ReadoutCalibrationAnalysis(tuid="20230509-152441-841-faef49").run().display_figs_mpl()

process_data() → None

Process the data so that the analysis can make assumptions on the format.

run_fitting() → None

Fit a state discriminator to the readout calibration data.

_get_points() → tuple

analyze_fit_results() → None

Check the fit success and populate .quantities_of_interest.

create_figures() → None

Generate figures of interest.

matplotlib figures and axes objects are added to the .figs_mpl and .axs_mpl dictionaries, respectively.