neuropercolation/evaluation/plots/bootstrap_plot.py

from plot import qtplot
import json
import math as ma
import numpy as np

path='/cloud/Public/_data/neuropercolation/4lay/cons=dimtimesdimby3_steps=100100/dim=09_cons=27/batch=0/'
eps_sp=np.linspace(0.01,0.2,20)
eps_ep=eps_sp

extremes=10000
strength=100000

savepath=path+f'extremes={extremes}_bootstrength={strength}/'

dt=250
boots=[]
for eps in eps_ep:
    eps=round(eps,3)
    with open(savepath+f'eps={eps:.3f}_dt={dt}_simpbootstrap.txt','r') as f:
        
        confs=list(zip(*json.load(f)))[1]
        ps=[1-conf for conf in confs]
        boots.append(ps)
        

    lower=[0.001]*len(ps)
    higher=[0.999]*len(ps)

   
    qtplot(f"Bootstrapping p-value for noise level {eps}",[range(dt+1)]*3,[lower,higher,ps],[f'right-sided p-value','p=0.999 limit','p=0.001 limit'],colors=['w','r','g'],y_tag='p-value',y_log=False)