pyriemann_qiskit.visualization.art.weights_spiral¶

pyriemann_qiskit.visualization.art.weights_spiral(axe, vqc, X, y, n_trainings=5)[source]¶

Artistic representation of vqc training.

Display a spiral. Each “branch” of the spiral corresponds to a parameter inside VQC. When the branch is “large” it means that the weight of the parameter varies a lot between different trainings.

Notes

Added in version 0.1.0.

Parameters:

axe (Axe) – Pointer to the matplotlib plot or subplot.
vqc (QuanticVQC) – The instance of VQC to evaluate.
X (ndarray, shape (n_samples, n_features)) – Input vector, where n_samples is the number of samples and n_features is the number of features.
y (ndarray, shape (n_samples,)) – Predicted target vector relative to X.
n_trainings (int (default: 5)) – Number of trainings to run, in order to evaluate the variability of the parameters’ weights.

Returns:

X (ndarray, shape (n_samples, n_features)) – Input vector, where n_samples is the number of samples and n_features is the number of features.
y (ndarray, shape (n_samples,)) – Predicted target vector relative to X.