neuropercolation/evaluation/4Layer Phase to EI Survey.py
2023-12-14 19:49:44 +00:00

108 lines
3.8 KiB
Python

#!/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 numpy.linalg import norm
from datetime import datetime
from random import sample as choose
from plot import qtplot
eps_space = list(np.linspace(0.01,0.2,20))
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)
extremes = 50000
maxdt = 500
for dim in [9]:
for eps in eps_space[:1]:
path=f'/cloud/Public/_data/neuropercolation/4lay/cons=9-3dist_steps=1000100/dim=09/batch=0/'
try:
with open(path+f"eps={round(eps,3):.3f}_phase_diff.txt", 'r', encoding='utf-8') as f:
phase_diff = json.load(f)
except:
# None
# if True:
with open(path+f"eps={round(eps,3):.3f}_activation.txt", 'r', encoding='utf-8') as f:
activation = 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
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)
all_res = norm(resultant(phase_diff))
try:
with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'r', encoding='utf-8') as f:
ei = json.load(f)
except:
with open(path+f"eps={round(eps,3):.3f}_channels.txt", 'r', encoding='utf-8') as f:
channels = json.load(f)[100:]
ei = [np.sum(cha)*(1-H2(eps)) for cha in channels]
with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'w', encoding='utf-8') as f:
json.dump(ei, f, indent=1)
pha_divs = 32
pha_sort = [0]*pha_divs
pha_sort = [[pha for pha in list(enumerate(phase_diff))[:-maxdt] if i*m.pi/pha_divs <= abs(pha[1]) <= (i+1)*m.pi/pha_divs]
for i in range(pha_divs)]
dia_ei = [np.average([ei[i] for i, pha in pha_div]) for pha_div in pha_sort]
phase_dist = [len(pha)/len(phase[0][:-maxdt]) for pha in pha_sort]
qtplot(f'EI Distribution against phase diff for dim={dim}',
[[(div+.5)*m.pi/pha_divs for div in range(pha_divs)]],
[dia_ei],
[f'EI distribution against phase diff'],
x_tag = 'abs phase',
y_tag = 'average EI',
export=True,
path=path,
filename=f'Phase-EI eps={round(eps,3):.3f} dim={dim} pha_divs={pha_divs}.png',
close=True)
qtplot(f'Phasediff Distribution for dim={dim}',
[[(div+.5)*m.pi/pha_divs for div in range(pha_divs)]],
[phase_dist],
[f'Phase distribution'],
x_tag = 'abs phase',
y_tag = 'frequency',
export=True,
path=path,
filename=f'Phasediff dist eps={round(eps,3):.3f} dim={dim} pha_divs={pha_divs}.png',
close=True)
print(f'Done eps={eps:.3f} with dim={dim} at {datetime.now()}')
# qtplot(f'Resultant and EI evolution for dim={dim} with 4 layers',
# [[0]+eps_space]*2,
# [max(av_ei)*diff_res, av_ei],
# ['Resultant', 'avEI'],
# export=True,
# path=path,
# filename=f'Resultant and EI for dim={dim}.png',
# close=True)