qiskit.ignis.characterization.AngleCalCXFitter

class AngleCalCXFitter(backend_result, xdata, qubits, fit_p0, fit_bounds)

Amplitude error fitter

See BaseFitter __init__

__init__(backend_result, xdata, qubits, fit_p0, fit_bounds)

See BaseFitter __init__

Methods

__init__(backend_result, xdata, qubits, …)	See BaseFitter __init__
add_data(results[, recalc, refit])	Add new execution results to previous execution results
angle_err([qind])	Return the gate angle error
fit_data([qid, p0, bounds, series])	Fit the curve.
plot(qind[, series, ax, show_plot])	Plot err data.

Attributes

backend_result	Return the execution results
description	Return the fitter’s purpose, e.g.
fit_fun	Return the function used in the fit, e.g.
measured_qubits	Return the indices of the qubits to be characterized
params	Return the fit function parameters that were calculated by curve_fit
params_err	Return the error of the fit function parameters
series	Return the list of series for the data
xdata	Return the data points on the x-axis, the independenet parameter which is fit against
ydata	Return the data points on the y-axis

add_data(results, recalc=True, refit=True)

Add new execution results to previous execution results

Parameters

• results (Union[Result, List[Result]]) – new execution results

• recalc (bool) – whether tp recalculate the data

• refit (bool) – whether to refit the data

angle_err(qind=- 1)

Return the gate angle error

Parameters

qind (int) – qubit index to return (-1 return all)

Returns

a list of errors

Return type

list

property backend_result

Return the execution results

Return type

Union[Result, List[Result]]

property description

Return the fitter’s purpose, e.g. ‘T1’

Return type

str

fit_data(qid=- 1, p0=None, bounds=None, series=None)

Fit the curve.

Compute self._params and self._params_err

Parameters

• qid (int) – qubit for fitting. If -1 fit for all the qubits

• p0 (Optional[List[float]]) – initial guess, equivalent to p0 in scipy.optimize

• bounds (Optional[Tuple[List[float], List[float]]]) – bounds, equivalent to bounds in scipy.optimize

• series (Optional[str]) – series to fit (if None fit all)

property fit_fun

Return the function used in the fit, e.g. BaseFitter._exp_fit_fun

Return type

Callable

property measured_qubits

Return the indices of the qubits to be characterized

Return type

List[int]

property params

Return the fit function parameters that were calculated by curve_fit

Return type

List[float]

property params_err

Return the error of the fit function parameters

Return type

List[float]

plot(qind, series='0', ax=None, show_plot=False)

Plot err data.

Parameters

• qind (int) – qubit index to plot

• series (str) – the series to plot

• ax (Axes) – plot axes

• show_plot (bool) – call plt.show()

Returns

The axes object

Return type

Axes

Raises

ImportError – if matplotlib is not installed

property series

Return the list of series for the data

Return type

Optional[List[str]]

property xdata

Return the data points on the x-axis, the independenet parameter which is fit against

Return type

Union[List[float], array]

property ydata

Return the data points on the y-axis

The data points are returning in the form of a list of dictionaries:

• ydata[i][‘mean’] is a list, where item

  no. j is the probability of success of qubit i for a circuit that lasts xdata[j].

• ydata[i][‘std’] is a list, where ydata[‘std’][j] is the

  standard deviation of the success of qubit i.

Return type

List[Dict]