SwitchingFCalongAtask/runOptimization.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 23 10:12:45 2021

@author: Oscar Portoles
"""

import pygmo as po
import numpy as np
# import optimProbs as udp
import optimizationProcesses as udp
import sys
import time
import copy

def main():
    velocity    = sys.argv[1] 	# velocty [m/s] given as input paramter in terminal
    nStage      = 4
    nTask       = 100		# nTask x nGenera = optimization iterations, 
    nGenera     = 20
    sizePop     = 50  		# number of individuals on each island 
    fitPercentil= 99.5
    probMigra   = 0.1 		# probability of a migration happening in a task "nTask"
    zHist       = None
    zSim        = []
    simLog      = []
    edgePulse   = []
        
    pathsave    = './dataSave/'
    namefile    = 'stgSequence_Lopt_allPu1000_wE_P040_optIni_v' + str(velocity) + '_fixG0p15L0p6_Stg' 
     
    # algorithms: 
    algos = [po.algorithm(po.de1220(gen=nGenera,allowed_variants=[1,3,6,8],variant_adptv=1)), # jDE (Brest et al.) [rand-to-best/1/exp, rand-to-best/1/bin, rand-to-current/2/bin, rand-to-current/2/exp]                 
              po.algorithm(po.de1220(gen=nGenera,allowed_variants=[15,16],variant_adptv=1)), # jDE (Brest et al.) rand-to-current/2/bin
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[15,16],variant_adptv=2)), # iDE (Elsayed  et al.) rand-to-current/2/bin
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[1,3,6,8],variant_adptv=2)), # iDE (Elsayed et al.) best/1/bin, rand/1/bin, rand-to-current/2/bin, 
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[2,7],variant_adptv=1)),
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[15,16],variant_adptv=1)), # jDE (Brest et al.) rand-to-current/2/bin
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[15,16],variant_adptv=2)), # iDE (Elsayed  et al.) rand-to-current/2/bin
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[1,3,6,8],variant_adptv=1)),
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[1,3,6,8],variant_adptv=2)), 
                po.algorithm(po.de1220(gen=nGenera,allowed_variants=[2,7],variant_adptv=1)),             
                ]
    nIsla = len(algos)
    # My island
    myUDI = po.mp_island(use_pool=True)
    myUDI.resize_pool(nIsla)  
    # PUT the righ file name to read the bumps topologies!
    for iXstage in range(nStage):
        # problem
        prob   = po.problem(udp.Opt_allROIpulse_Wenecor(stageIx=iXstage,vel=velocity,zh=zHist))  
        # empty archi
        archi = po.archipelago()
        # fill up archipiealago with islands
        for algo_ in algos:
            archi.push_back(po.island(algo=algo_, prob=prob, size=sizePop, udi=myUDI))
        print('All islands set for Stage ', iXstage+1)
        start  = time.time()
        # set migration topology
        archi.set_topology( po.topology(po.ring(n=nIsla, w=probMigra)) )
        # Evolve (optimize)
        archi.evolve(n=nTask)
        print(archi.status)
        # wait for archi to end
        archi.wait_check()
        print('Stage: ', iXstage+1, ', best ftiness: ',[np.round(fIsla[0],3) for fIsla in archi.get_champions_f()] , 
              ', Duration: ', np.round( (time.time() - start)/3600, 4))
        # logs from UDP and migration
        logsUDP  = []
        for isla_ in archi:
            logsUDP.append( isla_.get_population().problem.extract(type(udp.Opt_allROIpulse_Wenecor())).get_mylogs() )    

        log_mig = archi.get_migration_log()
        logsUDP = np.asarray(logsUDP)
        # Find and re-run the best solution to pass the end as initial conditions
        udpH = udp.FindAndKeepBestSolution(stageIx=iXstage,vel=velocity,zh=zHist)
        udpH.getBestWeightedModel(logsUDP, fitPercentil)
        zHist = udpH.runBestModel()
        zi = np.imag(zHist)
             
        # keep simulated data
        zSim.append( udpH.z[:,udpH.maxDlay+1:,:] )
        simLog.append( udpH.log)
        edgePulse.append( udpH.edgePulse )
        # save results of current stage
        outfile  = pathsave + namefile + str(iXstage+1) + '.npz'
        np.savez(outfile,logsUDP=logsUDP, nGen=nGenera, sizeP=sizePop, pMig=probMigra,
                 log_mig=log_mig,nIsla=nIsla, allow_pickle=True)
        print('Done with ', namefile)

    zSim    = np.hstack(zSim)
    simLog  = np.asarray(simLog)
    outfile  = pathsave + namefile + 'trialZ.npz'
    np.savez(outfile,sim_z=zSim, sim_log=simLog,edgePulse=edgePulse)
    return zSim

if __name__ == "__main__":
    __spec__ = "ModuleSpec(name='builtins', loader=<class '_frozen_importlib.BuiltinImporter'>)"
    z = main()