import json, numpy as np
from active_noise_optimizer import kf_run, transition
out=[]
for tau in [0.2,1.,5.,20.]:
    b=[]; x=[]
    for seed in [10,11,12,13,14]:
        b.append(kf_run(seed,tau,.3,0.)[0]); x.append(kf_run(seed,tau,.3,.85)[0])
    out.append({'tau':tau,'baseline_mean':float(np.mean(b)),'baseline_std':float(np.std(b,ddof=1)), 'idea_mean':float(np.mean(x)), 'idea_std':float(np.std(x,ddof=1)), 'ratio':float(np.mean(x)/np.mean(b))})
# Exact crossing by bisection on rho-1.
lo,hi=1.,2.5
for _ in range(60):
    mid=(lo+hi)/2
    rho=max(abs(np.linalg.eigvals(transition(mid,1.,5.,.7))))
    if rho<1: lo=mid
    else: hi=mid
out.append({'stability_eta_crossing':(lo+hi)/2,'rho_at_crossing':float(max(abs(np.linalg.eigvals(transition((lo+hi)/2,1.,5.,.7)))) )})
open('repro_summary.json','w').write(json.dumps(out,indent=2))
print(json.dumps(out,indent=2))