DragFitter¶
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class
DragFitter(backend_result, xdata, qubits, fit_p0, fit_bounds=None)[source]¶ Bases:
qiskit.ignis.characterization.fitters.IQFitterDrag Experiment fitter
See IQFitter __init__
fit_p0 is [a, x0, c] where the fit is a*(x-x0)^2+c
Methods
Add new execution results to previous execution results
Return the drag amplitude from the fit
Fit the curve.
Guess parameters for the drag fit
Plot the data and fit
Attributes
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backend_result¶ Return the execution results
- Return type
Union[Result,List[Result]]
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description¶ Return the fitter’s purpose, e.g. ‘T1’
- Return type
str
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fit_fun¶ Return the function used in the fit, e.g. BaseFitter._exp_fit_fun
- Return type
Callable
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measured_qubits¶ Return the indices of the qubits to be characterized
- Return type
List[int]
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params¶ Return the fit function parameters that were calculated by curve_fit
- Return type
List[float]
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params_err¶ Return the error of the fit function parameters
- Return type
List[float]
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series¶ Return the list of series for the data
- Return type
Optional[List[str]]
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xdata¶ Return the data points on the x-axis, the independenet parameter which is fit against
- Return type
Union[List[float],array]
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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]
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