qiskit.ignis.characterization.AmpCalFitter¶

class AmpCalFitter(backend_result, xdata, qubits, fit_p0, fit_bounds)[source]¶

Amplitude error fitter

See BaseFitter __init__

__init__(backend_result, xdata, qubits, fit_p0, fit_bounds)[source]¶: 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.
`guess_params`([qind])	Guess fit parameters for the amp cal
`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

Paramètres

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)[source]¶

Return the gate angle error

Paramètres: qind (int) – qubit index to return (-1 return all)
Renvoie: a list of errors
Type renvoyé: list

property backend_result¶

Return the execution results

Type renvoyé: Union[Result, List[Result]]

property description¶

Return the fitter’s purpose, e.g. “T1”

Type renvoyé: str

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

Fit the curve.

Compute self._params and self._params_err

Paramètres

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

Type renvoyé: Callable

guess_params(qind=0)[source]¶

Guess fit parameters for the amp cal

Paramètres: qind (int) – qubit index to guess fit parameters for
Renvoie: List of fit guess parameters [thetaerr, offset]
Type renvoyé: list

property measured_qubits¶

Return the indices of the qubits to be characterized

Type renvoyé: List[int]

property params¶

Return the fit function parameters that were calculated by curve_fit

Type renvoyé: List[float]

property params_err¶

Return the error of the fit function parameters

Type renvoyé: List[float]

plot(qind, series='0', ax=None, show_plot=False)[source]¶

Plot err data.

Paramètres

qind (int) – qubit index to plot
series (str) – the series to plot
ax (Axes) – plot axes
show_plot (bool) – call plt.show()

Renvoie

The axes object

Type renvoyé

Axes

Lève

ImportError – if matplotlib is not installed

property series¶

Return the list of series for the data

Type renvoyé: Optional[List[str]]

property xdata¶

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

Type renvoyé: 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.

Type renvoyé: List[Dict]