solvers = ['ralg', 'amsg2p']
solvers = ['gsubg']
Colors = ['r', 'k','b']
xOpt = 1.0/n
def cb(p):
tmp = ceil(log10(norm(xOpt - p.xk)))
if tmp < cb.TMP:
# print 'distance:', tmp, 'itn:', p.iter, 'n_func:', p.nEvals['f'], 'n_grad:', -p.nEvals['df']
cb.TMP = tmp
cb.stat['dist'].append(tmp)
cb.stat['f'].append(p.nEvals['f'])
cb.stat['df'].append(-p.nEvals['df'])
return False
asa = lambda x:asarray(x).reshape(-1, 1)
R = {}
lines = []
for i, solver in enumerate(solvers):
p = NSP(obj, startPoint, maxIter = 4700, name = 'Rzhevsky3 (nVars: ' + str(n)+')', maxTime = 30000, maxFunEvals=1e7, color = Colors[i])
#p.maxIter = 10#; p.useSparse = False
p.fEnough = 1.0e-5
p.fOpt = 1.0e-5
p.fTol = 0.5e-5
cb.TMP = 1000
cb.stat = {'dist':[], 'f':[], 'df':[]}
r = p.manage(solver, iprint=1, xtol = 1e-10, ftol = 1e-10, show = solver == solvers[-1], plot = 0, callback = cb)
R[solver] = hstack((asa(cb.stat['dist']), asa(cb.stat['f']), asa(cb.stat['df'])))
from numpy import arange
from numpy.linalg import norm
from openopt import NSP, oosolver
from FuncDesigner import *
N = 100000
x = oovar('x')
startPoint = {x: 1 + 1.0 / arange(1, N+1)}
S = 1e4 ** (1.0/arange(1, N+1))
arr = sin(arange(N))
f = sum((x-arr)**2 * S) / 1e4
solvers = [oosolver('ralg')]
solvers = [oosolver('gsubg', dual=True, zhurb = 50)]
#solvers = [oosolver('gsubg', zhurb = 20, dual=False)]
#solvers = ['ipopt']
#solvers = ['slmvm2']
#solvers = ['mma']
for solver in solvers:
p = NSP(f, startPoint, maxIter = 10000, maxTime = 15000, maxFunEvals=1e7)
p.fEnough = 1.5e-1
p.fTol = 5.0e-1
#p.constraints = (y > 5)(tol=1e-4) #x>1e-1 #[2*y<sin(arange(N))]
#r = p.solve(solver, iprint=10, xtol = 1e-36, ftol = 1e-16, show = solver == solvers[-1])
r = p.manage(solver, iprint=1, xtol = 1e-8, ftol = 1e-7, show = solver == solvers[-1])
