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main.py
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main.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import mainAE
import mainSS
import mainR
import mainF
import mainN
from config import opt
run_data = 'NINO'
opt.data_list_index = 3
'''
ttttrain = False
if ttttrain:
# aepath = mainAE.main_run(opt, run_data)
opt.model_list_path[0] = 'checkpoints/AutoEncoder_NINO_0123162328.pth'
# sspath = mainSS.main_run(opt, run_data)
opt.model_list_path[1] = 'checkpoints/Recurrent_NINO_0206222418.pth'
rpath = mainR.main_run(opt, run_data)
opt.model_list_path[2] = rpath
fpath = mainF.main_run(opt, run_data)
opt.model_list_path[3] = fpath
opt._parse(printconfig = True)
if not ttttrain:
opt.train_test_pre = 0
opt.model_list_path = ['checkpoints/AutoEncoder_NINO_0123162228.pth', 'checkpoints/Recurrent_NINO_0206222215.pth', 'checkpoints/Recurrent_NINO_0208045318.pth', 'checkpoints/multiF_NINO_0208154733.pth']
# aepath = mainAE.main_run_pre(opt, run_data)
# sspath = mainSS.main_run_pre(opt, run_data)
rpath = mainR.main_run_pre(opt, run_data)
fpath = mainF.main_run_pre(opt, run_data)
'''
''' train
opt.recurrent_n = 2
opt.model_list_path[1] = 'checkpoints/Seq2Seq_NINO_0123193051.pth'
rnpath = mainN.main_run(opt, run_data)
print('rn path:', rnpath)
'''
''' train multi
recurrent_n_max = 3
recurrent_n_path = [None]*recurrent_n_max
opt.model_list_path[1] = 'checkpoints/Seq2Seq_NINO_0123193437.pth'
for i in range(recurrent_n_max):
opt.recurrent_n = i+2
rnpath = mainN.main_run(opt, run_data)
print('recurrent_n', opt.recurrent_n, 'path', rnpath)
recurrent_n_path[i] = rnpath
print(recurrent_n_path)
'''
''' test
opt.recurrent_n = 3
opt.model_list_path =[None, 'checkpoints/Seq2Seq_NINO_0123193230.pth', 'checkpoints/RecurrentN_NINO_0211195451.pth', None]
MSE, U = mainN.main_run_pre(opt, run_data)
print( MSE, U )
'''
#''' test multi
import matplotlib.pyplot as plt
import numpy as np, torch as t
import math
index = [['checkpoints/Seq2Seq_NINO_0123193051.pth',
'checkpoints/Recurrent_NINO_0123232400.pth',
'checkpoints/RecurrentN_NINO_0212055443.pth',
'checkpoints/RecurrentN_NINO_0212154529.pth',
'checkpoints/RecurrentN_NINO_0213024720.pth'], #index 0
['checkpoints/Seq2Seq_NINO_0123193230.pth',
'checkpoints/Recurrent_NINO_0123232459.pth',
'checkpoints/RecurrentN_NINO_0212055525.pth',
'checkpoints/RecurrentN_NINO_0212154546.pth',
'checkpoints/RecurrentN_NINO_0213024707.pth'], #index 1
['checkpoints/Seq2Seq_NINO_0123193337.pth',
'checkpoints/Recurrent_NINO_0123232535.pth',
'checkpoints/RecurrentN_NINO_0212055803.pth',
'checkpoints/RecurrentN_NINO_0212154908.pth',
'checkpoints/RecurrentN_NINO_0213024908.pth'], #index 2
['checkpoints/Seq2Seq_NINO_0123193437.pth',
'checkpoints/Recurrent_NINO_0123232604.pth',
'checkpoints/RecurrentN_NINO_0212055212.pth',
'checkpoints/RecurrentN_NINO_0212153659.pth',
'checkpoints/RecurrentN_NINO_0213023524.pth']] #index 3
MSEs, Us = np.zeros([4,5]), np.zeros([4,5])
for i in range(-4):
opt.data_list_index = i
for j in range(5):
opt.recurrent_n = j
opt.model_list_path =[None, index[i][0], None if j==0 else index[i][j], None]
MSE, U = mainN.main_run_pre(opt, run_data)
MSEs[i,j], Us[i,j] = MSE, U
print(MSEs,Us)
#
#MSEs = np.array([[1.19935327, 0.44766346, 1.14411952, 1.17249683, 1.13329989],
# [0.7814886 , 0.28622022, 0.53806496 ,0.58601214, 1.75423543],
# [0.36341466, 0.15255875, 0.21720217, 0.23372307, 0.22571262],
# [0.20302946, 0.06328554 ,0.64642089 ,0.84699274, 0.74393498]])
MSEs = np.array([[1.1994, 0.4343, 0.3712, 0.3478, 0.3395],
[0.7851, 0.3309, 0.3297, 0.3104, 0.2641],
[0.3634, 0.1933, 0.1797, 0.1683, 0.1503],
[0.203, 0.113, 0.1098, 0.1006, 0.1064]])
plt.figure()
for i in range(4):
plt.plot([0, 1,2,3,4],MSEs[i,:])
plt.legend(['ENSO 1-2','ENSO 3','ENSO 3-4','ENSO 4'])
plt.grid()
gamma = np.array([9, 0.007332864, 0.00135719,
8, 0.00875126 ,0.001554874,
7, 0.006605908 ,0.001126431,
6, 0.005543081 ,0.001536232,
5, 0.007102284 ,0.004847112,
4, 0.005554814, 0.001784069,
3, 0.005522578, 0.001364947,
2, 0.001986593, 0.000956078,
1, 0.004345652, 0.001784546,
0.5, 0.000893087, 0.003177977,
0.2, 0.003450265, 0.004654602,
0.1, 0.002527938, 0.004027253,
0.067, 0.008045462, 0.001564802,
0.05, 0.014167879, 0.003121907,
0.04, 0.005019571, 0.002034204,
0.033, 0.002786551, 0.002992637])
gamma = gamma.reshape((-1,3))
plt.figure()
for i in range(2):
plt.plot(gamma[:,i+1])
plt.legend(['RPR','HFP'])
plt.grid()
plt.figure()
x = ['0.9','0.8','0.7','0.6','0.5','0.4','0.3','0.2','0.1','0.05','0.02','0.01','0.0067','0.005']
xx = ['1/9','1/8','1/7','1/6','1/5','1/4','1/3','1/2','1','2','5','10','15','20','25','30']
plt.plot(xx[:-2],gamma[:-2,1])
plt.legend(['RPR'])
plt.grid()
plt.figure()
plt.subplot(121)
line = ['-o','-d','-s','-x']
for i in range(4):
plt.plot(['0', '1','2','3','4'],MSEs[i,:], line[i])
plt.legend(['ENSO 1-2','ENSO 3','ENSO 3-4','ENSO 4'])
plt.grid()
plt.xlabel('The recurrent number: M.')
plt.subplot(222)
xx = ['1/9','1/8','1/7','1/6',r'$\frac{1}{5}$',r'$\frac{1}{4}$',r'$\frac{1}{3}$',r'$\frac{1}{2}$','1','2','5','10','15','20','25','30']
#plt.plot(xx[4:-2],gamma[4:-2,1], color = 'g')
xx_none = [' ',' ',' ',' ',' ', ' ',' ',' ',' ',' ']
plt.plot(xx_none,gamma[4:-2,1], color = 'g')
plt.legend(['RPR'])
plt.grid()
plt.subplots_adjust(wspace=0.25, hspace=0)
plt.subplot(224)
xx = ['1/9','1/8','1/7','1/6',r'$\frac{1}{5}$',r'$\frac{1}{4}$',r'$\frac{1}{3}$',r'$\frac{1}{2}$','1','2','5','10','15','20','25','30']
plt.plot(xx[4:-2],gamma[4:-2,2], color = 'orangered')
plt.ylim([0.0001,0.014])
plt.legend(['HFP'])
plt.grid()
plt.xlabel('The ratio of $\gamma$ to $1-\gamma$.')
#plt.tight_layout()
import time
plt.savefig('savedfig\A_'+str(time.time())+'.svg')
#'''
fig = plt.figure()
plt.subplot(121)
#ax_l = fig.add_subplot(121)
line = ['-o','-d','-s','-x']
for i in range(4):
plt.plot(['0', '1','2','3','4'],MSEs[i,:], line[i])
plt.legend(['ENSO 1-2','ENSO 3','ENSO 3-4','ENSO 4'])
plt.xlabel('M')
plt.grid()
f, axarr = plt.subplots(2, sharex=True, sharey=True)
f.suptitle('the balance factor')
axarr[0].plot(xx[4:-2],gamma[4:-2,1], color = 'g')
axarr[0].grid()
axarr[0].legend(['RPR'])
axarr[1].plot(xx[4:-2],gamma[4:-2,2], color = 'orangered')
axarr[1].grid()
axarr[1].legend(['HFP'])
plt.xlabel('the ratio of $\gamma$ to $1-\gamma$')
# é—´è·è°ƒæ•´ä¸ºï¼
f.subplots_adjust(hspace=0)
# è®¾ç½®å…¨éƒ¨æ ‡ç¾åœ¨å¤–éƒ?for ax in axarr:
ax.label_outer()