#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Aug 21 14:59:22 2023 @author: timofej """ import json import math as m import numpy as np from datetime import datetime from plot import qtplot eps_space = list(np.linspace(0.005,0.5,100)) eps_space= eps_space[1::2] def resultant(sample): phase_x = [m.cos(ind) for ind in sample] phase_y = [m.sin(ind) for ind in sample] return (np.average(phase_x), np.average(phase_y)) def H2(x): return -x*m.log2(x)-(1-x)*m.log2(1-x) dims=list(range(3,10)) R=[] EI=[] for dim in dims: cons = [(n,(2*n+m)%dim) for n in range(dim) for m in range(0,dim-2,3)] path=f'/cloud/Public/_data/neuropercolation/4lay/cons=dimtimesdimby3_steps=100100/dim={dim:02d}_cons={len(cons)}/batch=0/' diff_res = [1] av_ei = [0] for eps in eps_space: try: with open(path+f"eps={round(eps,3):.3f}_phase_diff.txt", 'r', encoding='utf-8') as f: phase_diff = json.load(f)[100:] with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'r', encoding='utf-8') as f: ei = json.load(f)[100:] except: with open(path+f"eps={round(eps,3):.3f}_activation.txt", 'r', encoding='utf-8') as f: activation = json.load(f)[100:] with open(path+f"eps={round(eps,3):.3f}_channels.txt", 'r', encoding='utf-8') as f: channels = json.load(f)[100:] osc = list(zip(*activation)) phase = np.array([[np.arctan2(*act[::-1]) for act in osc[i]] for i in range(2)]) phase_diff = (phase[1]-phase[0]+m.pi)%(2*m.pi)-m.pi ei = [np.sum(cha)*(1-H2(eps)) for cha in channels] res = np.linalg.norm(resultant(phase_diff)) diff_res.append(res) av_ei.append(np.average(ei)) with open(path+f"eps={round(eps,3):.3f}_phase_diff.txt", 'w', encoding='utf-8') as f: json.dump(list(phase_diff), f, indent=1) with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'w', encoding='utf-8') as f: json.dump(ei, f, indent=1) print(f'Done eps={eps:.3f} with dim={dim} at {datetime.now()}') R.append(diff_res) EI.append(av_ei) #%% savepath=f'/cloud/Public/_data/neuropercolation/4lay/cons=dimtimesdimby3_steps=100100/plots/' qtplot(f'Total resultant of phase-difference', [[0]+eps_space]*len(dims), R[::-1], [f'{dim}x{dim}' for dim in dims[::-1]], y_tag = 'concentration', export=False, path=savepath, filename=f'Resultant_ev.png', close=False) qtplot(f'Average Effect Integrated Information', [[0]+eps_space]*len(dims), EI[::-1], [f'{dim}x{dim}' for dim in dims[::-1]], y_tag='integrated information', export=False, path=savepath, filename=f'EI_ev.png', close=False)