Universality (noiseless CS)

import pandas as pd
from matplotlib import rcParams
rcParams['axes.unicode_minus'] = False
from tramp.experiments import qplot

Model

We consider for the sensing matrix \(F\) a random features matrix \(F = \tfrac{1}{\sqrt{N}}f(WX)\) where \(f\) = abs, relu, sgn or tanh. See data/cs_universality.py for the corresponding script.

rename = {
    "alpha": r"$\alpha$", "prior_rho": r"$\rho$",
    "source=": "", "n_iter": "iterations"
}
univ = pd.read_csv("data/cs_universality.csv")
qplot(
    univ.query("source=='SE'"),
    x="alpha", y="v", linestyle="f", column="prior_rho",
    rename=rename, usetex=True, font_size=16
)