iq_readout.classifiers.TwoStateClassifier

class TwoStateClassifier(params)

Template for creating two-state classifiers.

The elements to be rewritten for each specific classifier are:

• _pdf_func_..., which specify the PDFs

• _param_names, which specify the parameter names of the PDFs

• statistics, which computes the relevant statistics

• fit, which performs the fit

NB: if the classifier does not use max-likelihood classification, then predict needs to the overwritten.

__init__(params)

Loads params to this TwoStateClassifier.

Parameters:

paramsdict

The structure of the dictionary must be

{
    0: {"param1": float, ...},
    1: {"param1": float, ...}
}

Methods

fit(shots_0, shots_1, **kargs)	Runs fit to the given data.
from_yaml(filename)	Load the TwoStateClassifier from YAML file.
pdf_0(z)	Returns \(p(z|0)\).
pdf_1(z)	Returns \(p(z|1)\).
predict(z[, p_0])	Classifies the given data to 0 or 1 using maximum-likelihood classification, which is defined by
to_yaml(filename)	Stores parameters in a YAML file.

Attributes

params	Returns the parameters required to set up the classifier.
statistics	Returns dictionary with general statistical data: