200 lines
6.5 KiB
Python
200 lines
6.5 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Wed Sep 27 04:39:54 2023
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@author: astral
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"""
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import os
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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 random import random
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import itertools
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#from numba import jit, njit, prange
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# from plot import qtplot
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# from neuropercolation import Simulate4Layers
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eps_space = list(np.linspace(0.01,0.2,20))
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def new_folder(path):
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if not os.path.exists(path):
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os.makedirs(path)
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return path
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phase = np.vectorize(lambda x,y: (m.atan2(y,x)+m.pi)%(2*m.pi)-m.pi)
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diff = np.vectorize(lambda x,y: (y-x+m.pi)%(2*m.pi)-m.pi)
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H2 = lambda x: -x*m.log2(x)-(1-x)*m.log2(1-x)
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def neighbor(digit0, digit1, lenght):
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layer = int(lenght)
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dim = int(np.sqrt(layer))
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digit0, digit1 = np.array([digit0%dim, digit0//dim]), np.array([digit1%dim, digit1//dim])
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#print(digit0,digit1)
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coord_dif = list(map(abs,digit1 - digit0))
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layer_nbor = 0 in coord_dif and len(set([1,dim-1]).intersection(set(coord_dif))) != 0
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#print(coord_dif, set([1,dim-1]).intersection(set(coord_dif)))
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if layer_nbor:
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return True
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else:
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return False
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def kcomb(zp,zm):
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if zp+zm>5:
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val=None
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elif zp>2:
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val=1
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elif zm>2:
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val=0
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elif zp==zm:
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val=0.5
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elif zm==2:
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val=0.5**(3-zp)
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elif zp==2:
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val=1-0.5**(3-zm)
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elif zm==0 and zp==1:
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val=9/16
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elif zp==0 and zm==1:
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val=7/16
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else:
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raise NotImplementedError(zp,zm)
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return val
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#%%
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neighbourcomb = [[(i,j) for j in range(6)] for i in range(6)]
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probcombs = [[kcomb(*n) for n in row] for row in neighbourcomb]
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posscombs = {val for row in probcombs for val in row}
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probcombs1 = [kcomb(n,4-n) for n in range(5)]
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eta = lambda eps: 1-eps
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etastar = lambda eps,kp: kp*(1-eps)+(1-kp)*eps
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epsstar = lambda eps,kp: kp*eps+(1-kp)*(1-eps)
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KL = lambda eps,kp: eta(eps)*m.log2(eta(eps)/etastar(eps,kp)) + eps*m.log2(eps/epsstar(eps,kp)) if kp is not None else 0
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phi_mat = lambda eps: [[KL(eps,kcomb(i,j)) for j in range(6)] for i in range(6)]
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phi_vals = lambda eps,df=4: sorted({sum([KL(eps,kp) for kp in kps]) for kps in itertools.product(*[[1,0.5]]*df)})
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phi_sing = lambda eps: KL(eps,kcomb(1,0))
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phi_lims = lambda eps: [phi_sing(eps)+val for val in phi_vals(eps)]
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#%%
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path = new_folder('/cloud/Public/_data/neuropercolation/1lay/mips/')
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def phi(dim,statestr,partstr,eps):
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length = dim**2
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eta = 1-eps
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# statestr=statestr.translate(str.maketrans('','','.-='))
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state = np.array([int(q) for q in statestr])
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state = list(state.reshape((dim,dim)))
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state = [list([int(cell) for cell in row]) for row in state]
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part = np.array([int(p) for p in partstr])
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part = list(part.reshape((dim,dim)))
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part = [list([int(cell) for cell in row]) for row in part]
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inp = [[q+sum([state[(i+1)%dim][j],
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state[(i-1)%dim][j],
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state[i][(j+1)%dim],
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state[i][(j-1)%dim]
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]) for j,q in enumerate(row)] for i,row in enumerate(state)]
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beps = [[int(inp[i][j]>2)*eta+int(inp[i][j]<3)*eps for j,q in enumerate(row)] for i,row in enumerate(state)]
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zplus = [[q+sum([state[(i+1)%dim][j]*(part[i][j]==part[(i+1)%dim][j]),
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state[(i-1)%dim][j]*(part[i][j]==part[(i-1)%dim][j]),
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state[i][(j+1)%dim]*(part[i][j]==part[i][(j+1)%dim]),
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state[i][(j-1)%dim]*(part[i][j]==part[i][(j-1)%dim])
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]) for j,q in enumerate(row)] for i,row in enumerate(state)]
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zminus = [[(1-q)+sum([(1-state[(i+1)%dim][j])*(part[i][j]==part[(i+1)%dim][j]),
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(1-state[(i-1)%dim][j])*(part[i][j]==part[(i-1)%dim][j]),
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(1-state[i][(j+1)%dim])*(part[i][j]==part[i][(j+1)%dim]),
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(1-state[i][(j-1)%dim])*(part[i][j]==part[i][(j-1)%dim])
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]) for j,q in enumerate(row)] for i,row in enumerate(state)]
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kplus = [[kcomb(zplus[i][j],zminus[i][j]) for j,q in enumerate(row)] for i,row in enumerate(state)]
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pi = [[eps*(1-kplus[i][j]) + eta*kplus[i][j] for j,q in enumerate(row)] for i,row in enumerate(state)]
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crossent = [[-beps[i][j]*m.log2(pi[i][j])-(1-beps[i][j])*m.log2(1-pi[i][j]) for j,q in enumerate(row)] for i,row in enumerate(state)]
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return np.sum(crossent) - length*H2(eps)
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def MIP(dim,statestr,eps):
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lophi=np.inf
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mip = []
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# statestr=statestr.translate(str.maketrans('','','.-='))
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for parti in range(1,2**(dim**2-1)):
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partstr = bin(parti)[2:].zfill(dim**2)
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curphi = phi(dim,statestr,partstr,eps)
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if curphi<lophi:
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lophi=curphi
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mip = [partstr]
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elif curphi==lophi:
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mip.append(partstr)
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print(f'Done with {dim},{eps} = {mip},{lophi}')
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return mip,lophi
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def calc_mips(dim,eps,save=True):
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mips = [[] for i in range(5)]
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statestr='0'*dim**2
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lims = phi_lims(eps)
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# statestr=statestr.translate(str.maketrans('','','.-='))
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for parti in range(1,2**(dim**2-1)):
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partstr = bin(parti)[2:].zfill(dim**2)
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curphi = phi(dim,statestr,partstr,eps)
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for cha,mip in enumerate(mips):
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if curphi<lims[cha]:
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mip.append(parti)
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print(f'Part {partstr} in mips[{cha}] with phi={curphi}')
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mipath = new_folder(path+f'dim={dim:02d}/')
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for cha,mip in enumerate(mips):
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with open(mipath+f"eps={round(eps,3):.3f}_mipis_{cha}.txt", 'w', encoding='utf-8') as f:
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json.dump(mip, f, indent=1) if save else None
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return mips
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def smartMIP(dim,statestr,eps):
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lophi=np.inf
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mip = []
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phi_lims = phi_vals(eps)
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for parti in range(0,dim**2):
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partstr = bin(2**parti)[2:].zfill(dim**2)
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curphi = phi(dim,statestr,partstr,eps)
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if curphi<lophi:
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lophi=curphi
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mip = [partstr]
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elif curphi==lophi:
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mip.append(partstr)
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mipath = new_folder(path+f'dim={dim:02d}/')
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with open(mipath+f"eps={round(eps,3):.3f}_mips.txt", 'r', encoding='utf-8') as f:
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mips=json.load(f)
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for parti in range(1,2**(dim**2-1)):
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partstr = bin(parti)[2:].zfill(dim**2)
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if mips[parti-1]<curphi:
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curphi = phi(dim,statestr,partstr,eps)
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if curphi<lophi:
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lophi=curphi
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mip = [partstr]
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elif curphi==lophi:
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mip.append(partstr)
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return mip,lophi
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