266 lines
12 KiB
Python
266 lines
12 KiB
Python
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#!/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:
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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/32
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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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dev_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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dev_in_ind = [i for i in dev_ind if last_sync(i)<last_orth(i)]
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dev_out_ind = [i for i in dev_ind if last_sync(i)>last_orth(i)]
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devm_in_ind = [i for i in dev_in_ind if phase_diff[i]<0]
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devp_in_ind = [i for i in dev_in_ind if phase_diff[i]>0]
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devm_out_ind = [i for i in dev_out_ind if phase_diff[i]<0]
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devp_out_ind = [i for i in dev_out_ind if phase_diff[i]>0]
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if extremes is None:
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extremes = len(dev_in_ind)//4000*1000
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print(len(dev_out_ind), len(dev_in_ind))
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#print(all_res, av_diff)
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bot_in_ind = dev_in_ind[ :extremes]
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top_in_ind = dev_in_ind[-extremes: ]
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bot_out_ind = dev_out_ind[ :extremes]
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top_out_ind = dev_out_ind[-extremes: ]
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bot_ind = bot_in_ind + bot_out_ind
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top_ind = top_in_ind + top_out_ind
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botm_in_ind = [i for i in bot_in_ind if phase_diff[i]<0]
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botp_in_ind = [i for i in bot_in_ind if phase_diff[i]>0]
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topm_in_ind = [i for i in top_in_ind if phase_diff[i]<0]
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topp_in_ind = [i for i in top_in_ind if phase_diff[i]>0]
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botm_out_ind = [i for i in bot_out_ind if phase_diff[i]<0]
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botp_out_ind = [i for i in bot_out_ind if phase_diff[i]>0]
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topm_out_ind = [i for i in top_out_ind if phase_diff[i]<0]
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topp_out_ind = [i for i in top_out_ind if phase_diff[i]>0]
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# bot_ei_pool = [ei for ei in enumerate(ei[:-maxdt]) if ei[1] <= bot_ei[1]]
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# top_ei_pool = [ei for ei in enumerate(ei[:-maxdt]) if ei[1] >= top_ei[1]]
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# bot_eis = choose(bot_ei_pool, extremes)
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# top_eis = choose(top_ei_pool, extremes)
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# bot_ind = [enum[0] for enum in bot_ei]
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# top_ind = [enum[0] for enum in top_ei]
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botm_in_res = []
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topm_in_res = []
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devm_in_res = []
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botp_in_res = []
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topp_in_res = []
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devp_in_res = []
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botm_out_res = []
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topm_out_res = []
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devm_out_res = []
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botp_out_res = []
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topp_out_res = []
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devp_out_res = []
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bot_ei = []
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top_ei = []
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dev_ei = []
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tot_res = []
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tot_ei = []
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for dt in range(maxdt):
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botm_in_res.append( resultant([phase_diff[i+dt] for i in botm_in_ind]) )
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topm_in_res.append( resultant([phase_diff[i+dt] for i in topm_in_ind]) )
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devm_in_res.append( resultant([phase_diff[i+dt] for i in devm_in_ind]) )
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botp_in_res.append( resultant([phase_diff[i+dt] for i in botp_in_ind]) )
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topp_in_res.append( resultant([phase_diff[i+dt] for i in topp_in_ind]) )
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devp_in_res.append( resultant([phase_diff[i+dt] for i in devp_in_ind]) )
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botm_out_res.append( resultant([phase_diff[i+dt] for i in botm_out_ind]) )
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topm_out_res.append( resultant([phase_diff[i+dt] for i in topm_out_ind]) )
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devm_out_res.append( resultant([phase_diff[i+dt] for i in devm_out_ind]) )
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botp_out_res.append( resultant([phase_diff[i+dt] for i in botp_out_ind]) )
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topp_out_res.append( resultant([phase_diff[i+dt] for i in topp_out_ind]) )
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devp_out_res.append( resultant([phase_diff[i+dt] for i in devp_out_ind]) )
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bot_ei.append( np.average([ei[i+dt] for i in bot_ind]) )
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top_ei.append( np.average([ei[i+dt] for i in top_ind]) )
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dev_ei.append( np.average([ei[i+dt] for i in dev_ind]) )
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tot_res.append( resultant(phase_diff[dt:dt-maxdt]) )
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tot_ei.append( np.average(ei[dt:dt-maxdt]) )
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if dt%100==99:
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print(f'Done dt={dt}')
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bm_in_res = list(zip(*botm_in_res))
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tm_in_res = list(zip(*topm_in_res))
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dm_in_res = list(zip(*devm_in_res))
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bp_in_res = list(zip(*botp_in_res))
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tp_in_res = list(zip(*topp_in_res))
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dp_in_res = list(zip(*devp_in_res))
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bm_out_res = list(zip(*botm_out_res))
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tm_out_res = list(zip(*topm_out_res))
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dm_out_res = list(zip(*devm_out_res))
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bp_out_res = list(zip(*botp_out_res))
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tp_out_res = list(zip(*topp_out_res))
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dp_out_res = list(zip(*devp_out_res))
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t_res = list(zip(*tot_res))
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space = np.linspace(0,2*m.pi,101)
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qtplot(f'Diachronic resultant +/- for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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[bm_in_res[0], tm_in_res[0], dm_in_res[0], bp_in_res[0], tp_in_res[0], dp_in_res[0],
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bm_out_res[0], tm_out_res[0], dm_out_res[0], bp_out_res[0], tp_out_res[0], dp_out_res[0],
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t_res[0], np.cos(space)],
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[bm_in_res[1], tm_in_res[1], dm_in_res[1], bp_in_res[1], tp_in_res[1], dp_in_res[1],
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bm_out_res[1], tm_out_res[1], dm_out_res[1], bp_out_res[1], tp_out_res[1], dp_out_res[1],
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t_res[1], np.sin(space)],
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['Resultant ev in of bottom {extremes} ei -', 'Resultant ev in of top {extremes} ei -',
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'Resultant ev in of phase filtered ei -',
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'Resultant ev in of bottom {extremes} ei +', 'Resultant ev in of top {extremes} ei +',
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'Resultant ev in of phase filtered ei +',
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'Resultant ev out of bottom {extremes} ei -', 'Resultant ev out of top {extremes} ei -',
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'Resultant ev out of phase filtered ei -',
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'Resultant ev out of bottom {extremes} ei +', 'Resultant ev out of top {extremes} ei +',
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'Resultant ev out of phase filtered ei +',
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'Average Resultant', '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'Diachronic Resultant filtered pm inout eps={round(eps,3):.3f} dim={dim} extremes={extremes} roll{pha_dev:.3f}.png',
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close=True)
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qtplot(f'Diachronic resultant +/- for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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[bm_in_res[0], tm_in_res[0], dm_in_res[0], bp_in_res[0], tp_in_res[0], dp_in_res[0],
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t_res[0], np.cos(space)],
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[bm_in_res[1], tm_in_res[1], dm_in_res[1], bp_in_res[1], tp_in_res[1], dp_in_res[1],
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t_res[1], np.sin(space)],
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['Resultant ev in of bottom {extremes} ei -', 'Resultant ev in of top {extremes} ei -',
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'Resultant ev in of phase filtered ei -',
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'Resultant ev in of bottom {extremes} ei +', 'Resultant ev in of top {extremes} ei +',
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'Resultant ev in of phase filtered ei +',
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'Average Resultant', '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'Evolution of Resultant filtered pm in eps={round(eps,3):.3f} dim={dim} extremes={extremes} roll{pha_dev:.3f}.png',
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close=True)
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qtplot(f'Diachronic resultant +/- for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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[bm_out_res[0], tm_out_res[0], dm_out_res[0], bp_out_res[0], tp_out_res[0], dp_out_res[0],
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t_res[0], np.cos(space)],
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[bm_out_res[1], tm_out_res[1], dm_out_res[1], bp_out_res[1], tp_out_res[1], dp_out_res[1],
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t_res[1], np.sin(space)],
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['Resultant ev out of bottom {extremes} ei -', 'Resultant ev out of top {extremes} ei -',
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'Resultant ev out of phase filtered ei -',
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'Resultant ev out of bottom {extremes} ei +', 'Resultant ev out of top {extremes} ei +',
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'Resultant ev out of phase filtered ei +',
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'Average Resultant', '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'Evolution of Resultant filtered pm out eps={round(eps,3):.3f} dim={dim} extremes={extremes} roll{pha_dev:.3f}.png',
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close=True)
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# qtplot(f'Diachronic ei +/- for eps={round(eps,3):.3f} with dim={dim} with 4 layers',
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# [np.array(range(maxdt))]*4,
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# [bot_ei, top_ei, dev_ei, tot_ei],
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# ['EI ev of bottom {extremes} ei', 'EI ev of top {extremes} ei',
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# 'EI ev of phase filtered ei', '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'Diachronic EI filtered eps={round(eps,3):.3f} dim={dim} extremes={extremes} roll{pha_dev:.3f}.png',
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# close=True)
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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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