153 lines
5.8 KiB
Python
153 lines
5.8 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Mon Aug 21 14:59:22 2023
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@author: astral
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"""
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import json
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import math as m
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import numpy as np
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from numpy.linalg import norm
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from datetime import datetime
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from random import sample as choose
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from plot import qtplot
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eps_space = list(np.linspace(0.01,0.2,20))
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def resultant(sample):
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phase_x = [m.cos(ind) for ind in sample]
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phase_y = [m.sin(ind) for ind in sample]
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return (np.average(phase_x), np.average(phase_y))
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def H2(x):
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return -x*m.log2(x)-(1-x)*m.log2(1-x)
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extremes = None
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maxdt = 300
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for dim in [9]:
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for eps in eps_space[:10]:
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path=f'/cloud/Public/_data/neuropercolation/4lay/cons=7-knight_steps=1000100/dim=07/batch=0/'
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try:
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with open(path+f"eps={round(eps,3):.3f}_phase_diff.txt", 'r', encoding='utf-8') as f:
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phase_diff = json.load(f)
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except:
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with open(path+f"eps={round(eps,3):.3f}_activation.txt", 'r', encoding='utf-8') as f:
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activation = json.load(f)[100:]
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osc = list(zip(*activation))
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phase = np.array([[np.arctan2(*act[::-1]) for act in osc[i]] for i in range(2)])
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phase_diff = (phase[1]-phase[0]+m.pi)%(2*m.pi)-m.pi
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with open(path+f"eps={round(eps,3):.3f}_phase_diff.txt", 'w', encoding='utf-8') as f:
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json.dump(list(phase_diff), f, indent=1)
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all_res = norm(resultant(phase_diff))
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av_diff = np.arccos(all_res)
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try:
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with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'r', encoding='utf-8') as f:
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ei = json.load(f)
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except:
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with open(path+f"eps={round(eps,3):.3f}_channels.txt", 'r', encoding='utf-8') as f:
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channels = json.load(f)[100:]
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ei = [np.sum(cha)*(1-H2(eps)) for cha in channels]
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with open(path+f"eps={round(eps,3):.3f}_ei.txt", 'w', encoding='utf-8') as f:
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json.dump(ei, f, indent=1)
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pha_center = av_diff
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pha_dev = m.pi
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orth_ind = sorted([i for i,val in enumerate(ei[:-maxdt]) if (pha_center-pha_dev)<=abs(phase_diff[i])<=(pha_center+pha_dev)], key = lambda i: ei[i])
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thres = 0.04*m.pi
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last_sync = lambda i: i if abs(phase_diff[i])<0.08*m.pi else last_sync(i-1)
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last_orth = lambda i: i if 0.42*m.pi<abs(phase_diff[i])<0.58*m.pi else last_orth(i-1)
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trav_out = [(i,pha) for i,pha in enumerate(phase_diff[:-maxdt]) if abs(pha)<thres and abs(phase_diff[i+1])>thres]
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diff00_ind = [last_sync(i) for i,pha in trav_out]
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diff00m_ind = [last_sync(i) for i,pha in trav_out if pha<0]
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diff00p_ind = [last_sync(i) for i,pha in trav_out if pha>0]
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trav_in = [(i,pha) for i,pha in enumerate(phase_diff[:-maxdt]) if m.pi/2-thres<abs(pha)<m.pi/2+thres and abs(phase_diff[i+1])<m.pi/2-thres]
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diff90_ind = [last_orth(i) for i,pha in trav_in]
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diff90m_ind = [last_orth(i) for i,pha in trav_in if pha<0]
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diff90p_ind = [last_orth(i) for i,pha in trav_in if pha>0]
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print(f'{len(diff00_ind)}/{len(trav_out)} synced states and {len(diff90_ind)}/{len(trav_in)} orthogonal states')
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#print(all_res, av_diff)
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in_ei = []
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out_ei = []
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inm_res = []
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inp_res = []
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outm_res = []
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outp_res = []
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for dt in range(maxdt):
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inm_res.append( resultant([phase_diff[i+dt] for i in diff90m_ind]) )
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outm_res.append( resultant([phase_diff[i+dt] for i in diff00m_ind]) )
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inp_res.append( resultant([phase_diff[i+dt] for i in diff90p_ind]) )
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outp_res.append( resultant([phase_diff[i+dt] for i in diff00p_ind]) )
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in_ei.append( np.average([ei[i+dt] for i in diff90_ind]) )
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out_ei.append( np.average([ei[i+dt] for i in diff00_ind]) )
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if dt%100==99:
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print(f'Done dt={dt}')
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im_res = list(zip(*inm_res))
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om_res = list(zip(*outm_res))
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ip_res = list(zip(*inp_res))
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op_res = list(zip(*outp_res))
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space = np.linspace(0,2*m.pi,101)
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av_ei = np.average(ei)
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qtplot(f'Transitions resultants for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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[im_res[0], om_res[0], ip_res[0], op_res[0], np.cos(space)],
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[im_res[1], om_res[1], ip_res[1], op_res[1], np.sin(space)],
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['Resultant ev inward -', 'Resultant ev outward -',
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'Resultant ev inward +', 'Resultant ev outward +',
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'Unit Circle'],
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x_tag = 'x',
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y_tag = 'y',
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lw=1,
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export=True,
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path=path,
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filename=f'Transitions resultant pm for eps={round(eps,3):.3f} dim={dim}.png',
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close=False)
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qtplot(f'Transitions ei for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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[np.array(range(maxdt))]*3,
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[in_ei, out_ei, [av_ei]*maxdt],
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['EI ev inward', 'EI ev outward', 'Average EI'],
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x_tag = 'dt',
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y_tag = 'average ei',
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export=True,
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path=path,
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filename=f'Transitions EI for eps={round(eps,3):.3f} dim={dim} .png',
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close=False)
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print(f'Done eps={eps:.3f} with dim={dim} at {datetime.now()}')
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# qtplot(f'Resultant and EI evolution for dim={dim} with 4 layers',
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# [[0]+eps_space]*2,
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# [max(av_ei)*diff_res, av_ei],
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# ['Resultant', 'avEI'],
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# export=True,
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# path=path,
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# filename=f'Resultant and EI for dim={dim}.png',
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# close=True)
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