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])