SklearnIQDiscriminator¶

class SklearnIQDiscriminator(classifier, cal_results, qubit_mask, expected_states=None, standardize=False, schedules=None)[source]¶

Bases: qiskit.ignis.measurement.discriminator.iq_discriminators.IQDiscriminationFitter

A generic discriminant analysis discriminator for IQ data that takes an sklearn classifier as an argument.

Parameters

classifier (Classifier) – An sklearn classifier to train and do the discrimination. The classifier must have a fit method and a predict method
cal_results (Union[Result, List[Result]]) – calibration results, Result or list of Result used to fit the discriminator.
qubit_mask (List[int]) – determines which qubit’s level 1 data to use in the discrimination process.
expected_states (List[str]) – a list that should have the same length as schedules. All results in cal_results are used if schedules is None. expected_states must have the corresponding length.
standardize (bool) – if true the discriminator will standardize the xdata using the internal method _scale_data.
schedules (Union[List[str], List[Schedule]]) – The schedules or a subset of schedules in cal_results used to train the discriminator. The user may also pass the name of the schedules instead of the schedules. If schedules is None, then all the schedules in cal_results are used.

Methods

`add_data`	type result `Result`
`discriminate`	Applies the discriminator to x_data.
`fit`	Fits the discriminator using self._xdata and self._ydata.
`format_iq_data`	Takes IQ data obtained from get_memory(), applies the qubit mask and formats the data as a list of lists.
`get_xdata`	Retrieves feature data (xdata) for the discriminator.
`get_ydata`	Retrieves the expected states (ydata) for the discriminator.
`is_calibration`	Identify if a name corresponds to a calibration name identified by the regex pattern self._cal_pattern.
`plot`	Creates a plot of the data used to fit the discriminator.
`plot_xdata`	Add the relevant IQ data from the Qiskit Result, or list thereof, to the given axes as a scatter plot.

Attributes

expected_states¶: Returns the expected states used to train the discriminator.

fitted¶: True if the discriminator has been fitted to calibration data.

schedules¶: Returns the schedules with which the discriminator was fitted.