def test_polish(self):
solver = desolver.DESolver(error_func,
[(-100,100)]*3, 30, 200,
method = desolver.DE_RAND_1,
args=[self.xData,self.yData],
scale=0.8, crossover_prob=0.9,
goal_error=.01, polish=True, verbose=False,
use_pp = False, pp_modules=['numpy'])
assert(solver.best_error <= .01)
def test_seed(self):
solver = desolver.DESolver(error_func,
[(-100,100)]*3, 30, 200,
method = desolver.DE_LOCAL_TO_BEST_1,
args=[self.xData,self.yData],
seed = numpy.random.uniform(-1,1,size=(4,3)),
scale=0.5, crossover_prob=0.9,
goal_error=.01, polish=False, verbose=False,
use_pp = False, pp_modules=['numpy'])
assert(solver.best_error <= .01)
def test_pickle(self):
# run the example solver
solver = desolver.DESolver(error_func,
[(-100,100)]*3, 30, 200,
method = desolver.DE_RAND_1,
args=[self.xData,self.yData],
scale=0.8, crossover_prob=0.9,
goal_error=.01, polish=False, verbose=False,
use_pp = False, pp_modules=['numpy'])
# pickle and unpickle it
pstr = pickle.dumps(solver)
solver2 = pickle.loads(pstr)
xData = numpy.array([5.357, 9.861, 5.457, 5.936, 6.161, 6.731])
yData = numpy.array([0.376, 7.104, 0.489, 1.049, 1.327, 2.077])
# start timer
tStart = time.time()
# set up the solver
solver = desolver.DESolver(
dep_error_func,
[(-100, 100)] * 3,
30,
600,
#method = desolver.DE_BEST_1,
#method = desolver.DE_BEST_1_JITTER,
#method = desolver.DE_LOCAL_TO_BEST_1,
method=desolver.DE_RAND_1,
args=[xData, yData],
scale=[0.5, 1.0],
crossover_prob=0.9,
goal_error=.01,
polish=False,
verbose=True,
use_pp=True,
pp_modules=['global_fun'],
pp_depfuncs=[])
tElapsed = time.time() - tStart
print
print "Best generation:", solver.best_generation
print "Best individual:", solver.best_individual
print "Best error:", solver.best_error, \
": Elapsed time", tElapsed, \
'seconds for', solver.generation+1, 'generation(s)'
return numpy.prod(30.*numpy.sign(-x[include]-5.12))
testbed1 = [(lambda x:(x*x).sum(), [-5.12]*3, [5.12]*3, 1e-6,3,10,0.9,0.1), # NP changed from 5 to 10!
(lambda x:(x[0]**2-x[1])**2+(1.-x[0])**2,[-2.048]*2,[2.048]*2,1e-6,2,10,0.9,0.9),
(testbed1_3, [-5.12]*5, [5.12]*5, 1e-6,5,10,0.9,0.0)]
class Job:
def __init__(self,costfunction):
self.costfunction = costfunction
self.nfe = 0
def evaluateFitness(self,x):
self.nfe += 1
cost = self.costfunction(x)
return -cost
nrepeat = 20
for iproblem,(cost,minbounds,maxbounds,VTR,npar,NP,F,CR) in enumerate(testbed1):
job = Job(cost)
solver = desolver.DESolver(job,NP,10000,minbounds,maxbounds,
F=F,CR=CR,strictbounds=False,verbose=False,
reltol=0.,abstol=0.,minfitnesstoreach=-VTR)
print 'Problem %i' % iproblem
nfes = []
for ireplica in range(nrepeat):
job.nfe = 0
sol = solver.Solve()
nfe = job.nfe
print ' solution %i: %s, FV = %s, NFE=%i' % (ireplica,sol,-job.evaluateFitness(sol),nfe)
nfes.append(job.nfe)
print ' mean NFE = %i' % (float(sum(nfes))/len(nfes))