laboneq_applications.analysis.plotting_helpers

This module contains helper function for experiment analyses.

PlotRawDataOptions

Bases: TaskOptions

Options for the plot_raw_complex_data_1d task.

Attributes:

Name	Type	Description
use_cal_traces	bool	Whether to plot the calibration traces. Note that in the case of 2D data, the calibration traces are included in the 2D plot together with the main data. To achieve this, the 1D sweep points are extended by num_cal_traces * [sp_1d[-2] - sp_1d[-1]]. Default: True.
cal_states	str | tuple	The states to prepare in the calibration traces. Can be any string or tuple made from combining the characters 'g', 'e', 'f'. Default: same as transition
figure_size_raw_data	Sequence | None	The size of the figure.
save_figures	bool	Whether to save the figures. Default: True.
close_figures	bool	Whether to close the figures. Default: True.

cal_states: str | tuple = workflow.option_field('ge', description="The states to prepare in the calibration traces.Can be any string or tuple made from combining the characters 'g', 'e', 'f'.") class-attribute instance-attribute

close_figures: bool = workflow.option_field(True, description='Whether to close the figures.') class-attribute instance-attribute

figure_size_raw_data: Sequence | None = workflow.option_field(None, description='The size of the figure.') class-attribute instance-attribute

save_figures: bool = workflow.option_field(True, description='Whether to save the figures.') class-attribute instance-attribute

use_cal_traces: bool = workflow.option_field(True, description='Whether to include calibration traces in the experiment.') class-attribute instance-attribute

PlotSignalMagnitudeAndPhase2DOptions

Options for the plot_signal_magnitude_and_phase_2d task.

Attributes:

Name	Type	Description
figure_size_magnitude_phase	Sequence | None	The size of the figure.

figure_size_magnitude_phase: Sequence | None = workflow.option_field(None, description='The size of the figure.') class-attribute instance-attribute

plot_data_2d(x_values, y_values, z_values, label_x_values='', label_y_values='', label_z_values='', scaling_x_values=1.0, scaling_y_values=1.0, fit_x_values=None, fit_y_values=None, plot_title='', figure_name='2D_Data', save_figures=False, close_figures=True, figure=None, axis=None)

Create a 2D plot using pcolormesh.

Parameters:

Name	Type	Description	Default
x_values	ArrayLike	The 1D array to plot on the x-axis.	required
y_values	ArrayLike	The 1D array to plot on the y-axis.	required
z_values	ndarray	The 2D array to plot on the z-axis. The shape of z_values must be (len(y_values), len(x_values)).	required
label_x_values	str	The label that will appear on the x-axis. Default: ""	''
label_y_values	str	The label that will appear on the y-axis. Default: ""	''
label_z_values	str	The label that will appear on the colour bar of the z-axis. Default: ""	''
scaling_x_values	float	The scaling factor of the x-values. Default: 1.0.	1.0
scaling_y_values	float	The scaling factor of the y-values. Default: 1.0.	1.0
fit_x_values	ArrayLike | None	The 1D array with the fit points to plot on the x-axis. Default: None.	None
fit_y_values	ArrayLike | None	The 1D array with the fit points to plot on the y-axis. Default: None.	None
plot_title	str	The plot title. Default: ""	''
figure_name	str	The figure name. Default: "2D_Data".	'2D_Data'
save_figures	bool	Whether to save the figures. Default: False.	False
close_figures	bool	Whether to close the figures. Default: True.	True
figure	Figure	The matplotlib figure on which to plot. Default: None.	None
axis	Axes	The matplotlib axis on which to plot. Default: None.	None

Raises:

Type	Description
ValueError	If the x_values is not a 1D array.
ValueError	If the y_values is not a 1D array.
ValueError	If the z_values is not a 2D array.
ValueError	If the z_values does not have the shape (len(y_values), len(x_values)).

Returns:

Type	Description
tuple[Figure, Axes]	The matplotlib figure and axis.

plot_raw_complex_data_1d(qubits, result, sweep_points, xlabel, xscaling=1.0, options=None)

Creates plots of raw complex data acquired in integration mode.

Parameters:

Name	Type	Description	Default
qubits	QuantumElements	The qubits on which to run this task. May be either a single qubit or a list of qubits.	required
result	RunExperimentResults | Results	the result of the experiment. Can be either an instance of RunExperimentResults (returned by the run_experiment task), or an instance of Results (returned by session.run()).	required
sweep_points	QubitSweepPoints	The sweep points used in the experiment for each qubit. If qubits is a single qubit, sweep_points must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
xlabel	str	x-axis label	required
xscaling	float	value by which to scale the sweep_points	1.0
options	PlotRawDataOptions | None	The options for processing the raw data as an instance of [PlotRawDataOptions].	None

Returns:

Type	Description
dict[str, Figure]	dict with qubit UIDs as keys and the figures for each qubit as keys.

plot_raw_complex_data_2d(qubits, result, sweep_points_1d, sweep_points_2d, label_sweep_points_1d, label_sweep_points_2d, scaling_sweep_points_1d=1.0, scaling_sweep_points_2d=1.0, options=None)

Creates plots of two-dimensional raw complex data acquired in integration mode.

Parameters:

Name	Type	Description	Default
qubits	QuantumElements	The qubits on which to run this task. May be either a single qubit or a list of qubits.	required
result	RunExperimentResults | Results	the result of the experiment. Can be either an instance of RunExperimentResults (returned by the run_experiment task), or an instance of Results (returned by session.run()).	required
sweep_points_1d	QubitSweepPoints	The sweep points corresponding to the innermost sweep. If qubits is a single qubit, sweep_points_1d must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
sweep_points_2d	QubitSweepPoints	The sweep points corresponding to the outermost sweep. If qubits is a single qubit, sweep_points_2d must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
label_sweep_points_1d	str	The label that will appear on the axis of the 1D sweep points. Passed to the label_x_values parameter of plot_data_2d.	required
label_sweep_points_2d	str	The label that will appear on the axis of the 2D sweep points. Passed to the label_y_values parameter of plot_data_2d.	required
scaling_sweep_points_1d	float	The scaling factor of the 1D sweep points. Passed to the scaling_x_values parameter of plot_data_2d. Default: 1.0.	1.0
scaling_sweep_points_2d	float	The scaling factor of the 2D sweep points. Passed to the scaling_y_values parameter of plot_data_2d. Default: 1.0.	1.0
options	PlotRawDataOptions | None	The options for this task as an instance of [PlotRawDataOptions]. See the docstring of this class for more details.	None

Returns:

Type	Description
dict[str, Figure]	dict with qubit UIDs as keys and the figures for each qubit as keys.

plot_signal_magnitude_and_phase_2d(qubits, result, sweep_points_1d, sweep_points_2d, label_sweep_points_1d, label_sweep_points_2d, scaling_sweep_points_1d=1.0, scaling_sweep_points_2d=1.0, options=None)

Create the qubit-spectroscopy plots.

Parameters:

Name	Type	Description	Default
qubits	QuantumElements	The qubits on which to run this task. May be either a single qubit or a list of qubits.	required
result	RunExperimentResults | Results	the result of the experiment. Can be either an instance of RunExperimentResults (returned by the run_experiment task), or an instance of Results (returned by session.run()).	required
sweep_points_1d	QubitSweepPoints	The sweep points corresponding to the innermost sweep. If qubits is a single qubit, sweep_points_1d must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
sweep_points_2d	QubitSweepPoints	The sweep points corresponding to the outermost sweep. If qubits is a single qubit, sweep_points_2d must be a list of numbers or an array. Otherwise, it must be a list of lists of numbers or arrays.	required
label_sweep_points_1d	str	The label that will appear on the axis of the 1D sweep points. Passed to the label_x_values parameter of plot_data_2d.	required
label_sweep_points_2d	str	The label that will appear on the axis of the 2D sweep points. Passed to the label_y_values parameter of plot_data_2d.	required
scaling_sweep_points_1d	float	The scaling factor of the 1D sweep points. Passed to the scaling_x_values parameter of plot_data_2d. Default: 1.0.	1.0
scaling_sweep_points_2d	float	The scaling factor of the 2D sweep points. Passed to the scaling_y_values parameter of plot_data_2d. Default: 1.0.	1.0
options	PlotSignalMagnitudeAndPhase2DOptions | None	The options for this task as an instance of [PlotSignalMagnitudeAndPhase2DOptions]. See the docstring of this class for more details.	None

Returns:

Type	Description
dict[str, Figure]	dict with qubit UIDs as keys and the figures for each qubit as values.

sorted_mesh(x_values, y_values, z_values)

Prepare the x, y, z arrays to be plotted with matplotlib pcolormesh.

Ensures that the z values are sorted according to the values in x_values and y_values and creates np.meshgrid from x_values and y_values.

Parameters:

Name	Type	Description	Default
x_values	ArrayLike	array of the values to be plotted on the x-axis: typically the real-time sweep points.	required
y_values	ArrayLike	array of the values to be plotted on the y-axis: typically the near-time sweep points.	required
z_values	ArrayLike	array of the values to be plotted on the z-axis: typically the data.	required

Returns:

Type	Description
tuple[ArrayLike, ArrayLike, ArrayLike]	the x, y, and z values to be passed directly to pcolormesh.

timestamped_title(title, dt=None)

Return a plot title with a timestamp in the local timezone.

Parameters:

Name	Type	Description	Default
title	str	The title of the plot without a timestamp.	required
dt	datetime | None	The time to use to create the timestamp. If None, the workflow start time is used. If there is no active workflow, the current time is used.	None

Note

The timestamp is generated using the function local_timestamp and thus has the same format as the timestamps used by the FolderStore in the logbook folders it creates.

Returns:

Type	Description
str	The title with a timestamp, formatted as "TIMESTAMP - TITLE".