Sparse scree plot from Sparse PCA

[hamster-on-wheels]

For each combination of n_components and alpha, I run the following for 6 times.
After that I plot eigen_values as a scree plot.

B, A, eigen_values, obj = ristretto.pca.compute_rspca(
    X, n_components=n_components, n_subspace=3, alpha=alpha, robust=robust)

For a small alpha and robust=True, the scree plot looks normal.
The horizontal axis is the component index, the vertical axis is the median eigenvalue over the 6 runs.
The color of the line corresponds to n_components.

However, for robust=False or higher values of alpha, I get a different kind of scree plot:

While nearly all of the plots shows the 3rd and higher components all have an eigenvalue close to 0, I don't quite believe the system only has 2 components.

Why do I get the 2nd kind of scree plot?