# -*- coding: utf-8 -*- """ Created on Tue Aug 30 14:25:12 2022 @author: timofej """ import sys import os import json from plot import qtplot import math as m import numpy as np vect = np.vectorize @vect def log2(x): try: return m.log2(x) except ValueError: if x==0: return float(0) else: raise def new_folder(path): if not os.path.exists(path): os.makedirs(path) return path phase = np.vectorize(lambda x,y: (m.atan2(y,x)+m.pi)%(2*m.pi)-m.pi) diff = np.vectorize(lambda x,y: (y-x+m.pi)%(2*m.pi)-m.pi) H2 = lambda x: -x*m.log2(x)-(1-x)*m.log2(1-x) path = '/cloud/Public/_data/neuropercolation/4lay/cons=dimtimesdimby3_steps=100100/' suffix = '' chi = chr(967) vareps = chr(949) varphi = chr(981) vals = [[],[]] runsteps = 1000100 eps_space = np.linspace(0.005, 0.5, 100) eps_space = eps_space[1::2] dims = list(range(3,10))#+[16,49] mode='density' ma=[] s=[] k=[] mk=[] PHI=[] lastkurt=None for dim in dims: phis=[] con_gap = 3 cons = [(n,(2*n+m)%dim) for n in range(dim) for m in range(0,dim-2,con_gap)] dimpath = new_folder(path + f'dim={dim:02}_cons={len(cons)}/batch=0/') for epsilon in eps_space: try: with open(dimpath+f"eps={round(epsilon,3):.3f}_ei.txt", 'r', encoding='utf-8') as f: ei = np.array(json.load(f)[100:]) except: print('Calcing phi') with open(dimpath+f"eps={round(epsilon,3):.3f}_channels.txt", 'r', encoding='utf-8') as f: channels = np.array(json.load(f)[100:]) ei = channels*(1-H2(epsilon)) with open(dimpath+f"eps={round(epsilon,3):.3f}_ei.txt", 'r', encoding='utf-8') as f: json.dump(ei,f,indent=1) phi=np.average(ei) phis.append(phi) PHI.append(phis) #%% qtplot(f"Mean effect integration over noise level", [eps_space]*len(dims), PHI[::-1], [f'dim={dim:02d}x{dim:02d}' for dim in dims[::-1]], y_tag = f'effect integration {varphi}', export=True, path=dimpath+"", filename=f'eps={round(epsilon,3):.3f}_evolution.png', close=False) mode = 'density' #%%