iq_readout.two_state_classifiers.MaxFidLinearClassifier

class MaxFidLinearClassifier(params)

Read gmlda.md and TwoStateLinearClassifier documentation

__init__(params)

Loads params to this TwoStateLinearClassifier.

Parameters:

params

The structure of the dictionary must be

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

Methods

fit(shots_0, shots_1[, n_bins])	Fits the given data to extract the best parameters for classification.
from_yaml(filename)	Load the TwoStateClassifier from YAML file.
pdf_0(z)	Returns \(p(z|0)\).
pdf_0_projected(z_proj)	Returns \(p_{proj}(z_{proj}|0)\).
pdf_1(z)	Returns \(p(z|1)\).
pdf_1_projected(z_proj)	Returns \(p_{proj}(z_{proj}|1)\).
predict(z[, p_0])	Classifies the given data to 0 or 1 using a threshold: - 0 if z_proj <= threshold - 1 otherwise
project(z)	Returns the projection of the given IQ data to the mu_0 - mu_1 axis
to_yaml(filename)	Stores parameters in a YAML file.

Attributes

params	Returns the parameters required to set up the classifier.
params_proj	Returns the parameters for the projected PDFs, computed from params.
statistics	Returns dictionary with general statistical data: