neuropercolation/evaluation/4laysign.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 10 07:07:28 2023

@author: astral
"""

import sys as _sys
from sign import sampling as _samp
from sign import plotting as _plot
from sign import full_stats as _stats
import numpy as _np
import json
from plot import qtplot

import gc as _gc

_dim = 9
_epsilons = _np.linspace(0.005,0.20,40)
_noeffects = list(range(1,41,5))
try:
    _exeps = int(_sys.argv[1])
    _epses=_epsilons[_exeps-1:_exeps]
    _nf = int(_sys.argv[2])
    _nfs = _noeffects[_nf-1:_nf]
except:
    _epses=_epsilons
    _nfs = list(range(1,41,5))
_samplemethod = 'allpos_ei'
_ext = 5000
_dt=40

path='/cloud/Public/_data/neuropercolation/4lay/cons=27-knight_steps=1000100/dim=09/batch=0/'
plotpath = path + _samplemethod + f'_samples={_ext}/'
savepath = path + _samplemethod + f'_samples={_ext}/dt={_dt}/'

meanlist = []
stdlist = []
integrallist = []
cohendlist = []
norm_p_list = []
ttest_p_list = []
sign_p_list = []


resultant_i = []
resultant_c = []
for _eps in _epses[11:21]:
    res_evol_i = []
    res_evol_c = []
    for nf in _nfs:
        #_samp(_dim,_eps,_samplemethod,_ext,_dt,noeff=nf)
        resultant_i = []
        resultant_c = []
        for t in range(1,_dt):
            res_i, res_c = _stats(_dim,_eps,_samplemethod,_ext,t,noeff=nf,ret='phases')
            resultant_i.append(res_i)
            resultant_c.append(res_c)
        
        res_evol_i.append(resultant_i)
        res_evol_c.append(resultant_c)
    #     mean,std,integral,cohend,norm_p,ttest_p,sign_p = _stats(_dim,_eps,_samplemethod,_ext,1)
        
    #     meanlist.append(mean)
    #     stdlist.append(std)
    #     integrallist.append(integral)
    #     cohendlist.append(-cohend)
    #     norm_p_list.append(norm_p)
    #     ttest_p_list.append(ttest_p)
    #     sign_p_list.append(sign_p)
        
        
    with open(savepath+f"phasediff_means.txt", 'w', encoding='utf-8') as f:
        json.dump(meanlist, f, indent=1)
    with open(savepath+f"phasediff_stds.txt", 'w', encoding='utf-8') as f:
        json.dump(stdlist, f, indent=1)
    with open(savepath+f"phasediff_integrals.txt", 'w', encoding='utf-8') as f:
        json.dump(integrallist, f, indent=1)
    with open(savepath+f"phasediff_cohends.txt", 'w', encoding='utf-8') as f:
        json.dump(cohendlist, f, indent=1)
    with open(savepath+f"phasediff_norm_ps.txt", 'w', encoding='utf-8') as f:
        json.dump(norm_p_list, f, indent=1)
    with open(savepath+f"phasediff_ttest_ps.txt", 'w', encoding='utf-8') as f:
        json.dump(ttest_p_list, f, indent=1)
    with open(savepath+f"phasediff_sign_ps.txt", 'w', encoding='utf-8') as f:
        json.dump(sign_p_list, f, indent=1)
    
# stdlowlist = [meanlist[eps] - stdlist[eps] for eps in range(len(meanlist))]
# stdhighlist = [meanlist[eps] + stdlist[eps] for eps in range(len(meanlist))]

# norm_conf = [1-p for p in norm_p_list]
# ttest_conf = [1-p for p in ttest_p_list]
# sign_conf = [1-p for p in sign_p_list]
    res_tot_i = _np.average(res_evol_i,axis=0)
    res_evol_c.append(res_tot_i)
    qtplot(f'Resultant reduction disconnect eps={_eps} dim={_dim} with 4 layers',
            [list(range(_dt-1))]*(len(_nfs)+1),
            res_evol_c,
            [f'{nf} disconnected steps' for nf in _nfs]+['connected steps'],
            x_tag = 'dt',
            y_tag = 'resultant',
            export=True,
            path=plotpath,
            filename=f'Resultant reduction disconnect eps={_eps} dim={_dim} extremes={_ext}.png',
            close=True)
    
qtplot(f'Mean causal phase reduction for dt={_dt} dim={_dim} with 4 layers',
        [_epsilons]*3,
        [stdlowlist, stdhighlist, meanlist],
        ['Low standard deviation',
          'High standard deviation',
          'Mean'],
        colors=['r','r','g'],
        x_tag = f'noise level {chr(949)}',
        y_tag = 'abs phase reduction',
        export=True,
        path=savepath,
        filename=f'Mean phase reduction dim={_dim} extremes={_ext}.png',
        close=True)
# qtplot(f'Phase reduction probability for dt={_dt} dim={_dim} with 4 layers',
#         [_epsilons],
#         [integrallist],
#         ['probability of phase reduction'],
#         x_tag = f'noise level {chr(949)}',
#         y_tag = 'abs phase reduction',
#         export=True,
#         path=savepath,
#         filename=f'Probability of phase reduction dim={_dim} extremes={_ext}.png',
#         close=True)
# qtplot(f'Effect size phase reduction for dt={_dt} dim={_dim} with 4 layers',
#         [_epsilons],
#         [cohendlist],
#         ["Absolute Cohen's d (negative)"],
#         x_tag = f'noise level {chr(949)}',
#         y_tag = 'effect size',
#         x_range = (0,0.2),
#         # y_range = (0.05,1),
#         y_log = True,
#         export=True,
#         path=savepath,
#         filename=f'Effect size phase reduction dim={_dim} extremes={_ext}.png',
#         close=False)
# qtplot(f'Test p-values for dt={_dt} dim={_dim} with 4 layers',
#         [_epsilons]*5,
#         [[0.001 for eps in _epsilons],[0.0001 for eps in _epsilons],
#           norm_p_list,ttest_p_list,sign_p_list],
#         ['0.001 limit','0.0001 limit',
#           'p-value for normality', 'p-value for mean difference', 'p-value for median'],
#         x_tag = f'noise level {chr(949)}',
#         y_tag = 'p-value',
#         y_range = (0,0.01),
#         lw=2,
#         export=True,
#         path=savepath,
#         filename=f'P-values phase reduction dim={_dim} extremes={_ext}.png',
#         close=True)
# qtplot(f'Test confidences for dt={_dt} dim={_dim} with 4 layers',
#         [_epsilons]*5,
#         [[0.999 for eps in _epsilons],[0.9999 for eps in _epsilons],
#           norm_conf,ttest_conf,sign_conf],
#         ['0.999 limit', '0.999 limit',
#           'confidence for normality', 'confidence for mean difference', 'confidence for median'],
#         x_tag = f'noise level {chr(949)}',
#         y_tag = 'confidence´',
#         y_range = (0.99,1),
#         lw=2,
#         export=True,
#         path=savepath,
#         filename=f'Confidences phase reduction dim={_dim} extremes={_ext}.png',
#         close=True)