def mpi_run():
problem = {
'yu_2d_only': {
'npop':
4000,
'ngen':
100,
'nobj':
10,
'nvar':
6,
'vran': [[0., 35.], [-35., 0], [-35., 0], [-35., 0], [0., 35.],
[-35., 0]],
'f':
yu_2d_only
},
}
def def_problem(v):
p = problem[v]
return p['f'], p['npop'], p['ngen'], p['nvar'], p['nobj'], p['vran']
eta_c, eta_m = 20, 20
f, npop, ngen, nvar, nobj, vran = def_problem('yu_2d_only')
#== create random parents
if rank == 0:
#pop = nsga2.nsga2init(npop, ngen, nvar, nobj, vran)
fid = h5py.File('./data/yu_2d_only.h5', 'r')
pop = copy.deepcopy(np.array(fid['0100']))
fid.close()
pop = mpi_controller(pop)
else:
mpi_worker(f, nvar, nobj)
#== evolve
for ng in range(ngen):
if rank == 0:
print('\n%4i-th generation' % (ng + 1))
print('started at {:%Y-%m-%d %H:%M:%S}'.format(
datetime.datetime.now()))
kd = nsga2.nsga2getChild(pop, nvar, nobj, vran, eta_c, eta_m)
#print 'got child'
kd = mpi_controller(kd)
#print 'cal child'
pop = nsga2.nsga2toursel(pop, kd, nvar)
#print 'select child'
#--- save results
fid = h5py.File('./data/nsls2_20161118.h5', 'a')
fid['%04i' % (ng + 1)] = pop
fid.close()
print('finished at {:%Y-%m-%d %H:%M:%S}'.format(
datetime.datetime.now()))
else:
mpi_worker(f, nvar, nobj)
MPI.Finalize()
def main():
problem = {
'yu_2d_only':
{
'npop': 8000,
'ngen': 100,
'nobj': 10,
'nvar': 6,
'vran': [[0.,35.],[-35.,0],[-35.,0],[-35.,0],[0.,35.],[-35.,0]],
'f': yu_2d_only
},
}
def def_problem(v):
p = problem[v]
return p['f'], p['npop'], p['ngen'], p['nvar'], p['nobj'], p['vran']
eta_c, eta_m = 20, 20
f, npop, ngen, nvar, nobj, vran = def_problem('yu_2d_only')
#== create random parents
if rank == 0:
if len(sys.argv) == 1:
pop = nsga2.nsga2init(npop, ngen, nvar, nobj, vran)
lastg = 0
#print lastg
# --- starting from previous result
else:
fid = h5py.File(sys.argv[1],'r')
lastg = fid.keys()[-1]
pop = np.array(fid[lastg])
fid.close()
lastg = int(lastg)
# ---
pop = mpi_controller(pop)
else:
mpi_worker(f,nvar,nobj)
lastg = None
lastg = comm.bcast(lastg, root=0)
#== evolve
for ng in xrange(lastg+1,ngen):
if rank == 0:
print('\n%4i-th generation ...'%ng)
kd = nsga2.nsga2getChild(pop, nvar, nobj, vran, eta_c, eta_m)
kd = mpi_controller(kd)
pop = nsga2.nsga2toursel(pop,kd,nvar)
#--- save results
fid = h5py.File(sys.argv[1],'a')
fid['%04i'%ng] = pop
fid.close()
print('finished at {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now()))
else:
mpi_worker(f,nvar,nobj)
MPI.Finalize()
def mpi_run():
problem = {
'yu_2d_only': {
'npop':
4000,
'ngen':
100,
'nobj':
10,
'nvar':
9,
#'vran': [[23.,27.],[-15.,-11.],[-16.,-12.],[-29.,-27.],[31.,35.],[-4.,0],[23.,27.],[-15.,-11.],[-16.,-12.]],
'vran': [[0., 35.], [-35., 0.], [-35., 0.], [-35., 0.], [0., 35.],
[-35., 0.], [-2., 2.], [-2., 2.], [-2., 2.]],
'f':
yu_2d_only
},
}
def def_problem(v):
p = problem[v]
return p['f'], p['npop'], p['ngen'], p['nvar'], p['nobj'], p['vran']
eta_c, eta_m = 20, 20
f, npop, ngen, nvar, nobj, vran = def_problem('yu_2d_only')
#== create random parents
if rank == 0:
pop = nsga2.nsga2init(npop, ngen, nvar, nobj, vran)
# --- starting from previous result
#fid = h5py.File('./data/anhe_20170203.h5','r')
#pop = copy.deepcopy(np.array(fid['0030']))
#fid.close()
# ---
pop = mpi_controller(pop)
else:
mpi_worker(f, nvar, nobj)
#== evolve
for ng in xrange(0, ngen):
if rank == 0:
print('\n%4i-th generation ...' % ng)
kd = nsga2.nsga2getChild(pop, nvar, nobj, vran, eta_c, eta_m)
kd = mpi_controller(kd)
pop = nsga2.nsga2toursel(pop, kd, nvar)
#--- save results
fid = h5py.File('data/anhe_20170204.h5', 'a')
fid['%04i' % ng] = pop
fid.close()
print('finished at {:%Y-%m-%d %H:%M:%S}'.format(
datetime.datetime.now()))
else:
mpi_worker(f, nvar, nobj)
MPI.Finalize()
def mpi_run():
problem = {
'yu_2d':
{
'npop': 4000,
'ngen': 100,
'nobj': 34,
'nvar': 6,
'vran': [[0.,35.],[-35.,0],[-35.,0],[-35.,0],[0.,35.],[-35.,0]],
'f': yu_2d
},
'yu_2d_only':
{
'npop': 4000,
'ngen': 100,
'nobj': 8,
'nvar': 6,
'vran': [[0.,35.],[-35.,0],[-35.,0],[-35.,0],[0.,35.],[-35.,0]],
'f': yu_2d_only
},
}
def def_problem(v):
p = problem[v]
return p['f'], p['npop'], p['ngen'], p['nvar'], p['nobj'], p['vran']
eta_c, eta_m = 20, 20
f, npop, ngen, nvar, nobj, vran = def_problem('yu_2d_only')
#== create random parents
if rank == 0:
pop = nsga2.nsga2init(npop, ngen, nvar, nobj, vran)
#pop = np.loadtxt('./data/yu_2d_only_0037.txt')
pop = mpi_controller(pop)
else:
mpi_worker(f,nvar,nobj)
#== evolve
for ng in range(ngen):
if rank == 0:
print('\n%4i-th generation ...'%(ng+1))
kd = nsga2.nsga2getChild(pop, nvar, nobj, vran, eta_c, eta_m)
kd = mpi_controller(kd)
pop = nsga2.nsga2toursel(pop,kd,nvar)
#--- save results
'''
fname = './data/yu_2d_only_new_'+string.zfill(ng+1,4)+'.txt'
fid = open(fname,'w')
m,n = pop.shape
for i1 in range(m):
fid.write((n*'%15.6e'+'\n')%tuple(pop[i1]))
fid.close()
'''
fid = h5py.File('data/yu_2d_only_triangler.h5','a')
fid['%04i'%(ng+1)] = pop
fid.close()
else:
mpi_worker(f,nvar,nobj)
MPI.Finalize()
def mpi_run():
rank = MPI.COMM_WORLD.Get_rank()
name = MPI.Get_processor_name()
size = MPI.COMM_WORLD.Get_size()
problem = {
'yu_2d_only': {
'npop': 500,
'ngen': 100,
'nobj': 10,
'nvar': 5,
'vran': [[0, 1000], [-1000, 0], [0, 1000], [-1000, 0], [0, 1000]],
'f': yu_2d_only
},
}
def def_problem(v):
p = problem[v]
return p['f'], p['npop'], p['ngen'], p['nvar'], p['nobj'], p['vran']
eta_c, eta_m = 20, 20
f, npop, ngen, nvar, nobj, vran = def_problem('yu_2d_only')
#== create random parents
if rank == 0:
#pop = nsga2.nsga2init(npop, ngen, nvar, nobj, vran)
fid = h5py.File('./data/sls_20161128_8.h5', 'r')
last = fid.keys()[-1]
pop = copy.deepcopy(np.array(fid[last]))
fid.close()
pop = master(pop)
else:
slave(f, nvar, nobj)
#== evolve
for ng in range(ngen):
if rank == 0:
print('\n%4i-th generation' % (ng + 1))
print('started at {:%Y-%m-%d %H:%M:%S}'.format(
datetime.datetime.now()))
kd = nsga2.nsga2getChild(pop, nvar, nobj, vran, eta_c, eta_m)
print 'got child'
kd = master(kd)
print 'cal child'
pop = nsga2.nsga2toursel(pop, kd, nvar)
print 'select child'
#--- save results
fid = h5py.File('./data/sls_20161128_9.h5', 'a')
fid['%04i' % (ng + 1)] = pop
fid.close()
print('finished at {:%Y-%m-%d %H:%M:%S}'.format(
datetime.datetime.now()))
else:
slave(f, nvar, nobj)
MPI.Finalize()