neuropercolation/evaluation/4Layer Activity.py

78 lines
1.7 KiB
Python
Raw Normal View History

2023-09-30 17:53:06 +00:00
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 30 14:25:12 2022
2023-12-14 19:49:44 +00:00
@author: timofej
2023-09-30 17:53:06 +00:00
"""
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
path = '/cloud/Public/_data/neuropercolation/4lay/cons=27-knight_steps=100100_causal/dim=09/batch=0/'
suffix = ''
chi = chr(967)
vareps = chr(949)
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=[]
lastkurt=None
for dim in dims[-1:]:
dimpath = new_folder(path + f'dim={dim:02}/')
for epsilon in eps_space[:]:
with open(path+f"eps={round(epsilon,3):.3f}_phase_diff.txt", 'r', encoding='utf-8') as f:
phase_diff = np.array(json.load(f)[:500])
with open(path+f"eps={round(epsilon,3):.3f}_ei.txt", 'r', encoding='utf-8') as f:
phase_diff = np.array(json.load(f)[:500])
qtplot(f"Phase relation time series for eps={round(epsilon,3):.3f}",
[list(range(500))]*2,
[phase_diff],
x_tag = 'time step',
y_tag = f'phase diffe´rence',
y_range = (-m.pi,m.pi),
export=True,
path=dimpath+"evolution/",
filename=f'eps={round(epsilon,3):.3f}_evolution.png',
close=False)
mode = 'density'
#%%