svdval_decay()

svdval_decay(singular_values, threshold: float = 1e-08, plot: bool = True, right: int = None, ax: Axes = None, **kwargs)

Count the number of normalized singular values that are greater than a specified threshold.

Parameters:

singular_values(n,) ndarray

Singular values of a snapshot matrix, e.g., scipy.linalg.svdvals(states).

thresholdfloat or list[float]

Cutoff value(s) for the singular values.

plotbool

If True, plot the singular values and the cutoff value(s) against the singular value index.

rightint or None

Maximum singular value index to plot (plt.xlim(right=right)).

axmatplotlib.Axes or None

Axes to plot the results on if plot=True. If not given, a new single-axes figure is created.

kwargsdict

Options to pass to matplotlib.pyplot.semilogy().

Returns:

ranksint or list[int]

Number of singular values greater than the cutoff value(s).