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 = {} for i, solver in enumerate(solvers): p = NSP(obj, startPoint, maxIter = 17000, name = 'Rzhevsky2 (nVars: ' + str(n)+')', maxTime = 300, maxFunEvals=1e7, color = Colors[i]) p.fTol = 0.5e-12 p.maxTime = 100 #p.fEnough = -0.841408334595 p.fOpt = -0.841408334596 cb.TMP = 1000 cb.stat = {'dist':[], 'f':[], 'df':[]} r = p.solve(solver, iprint=10, ftol = 1e-15, xtol = 1e-12, show = solver == solvers[-1], plot = 0, callback = cb) R[solver] = hstack((asa(cb.stat['dist']), asa(cb.stat['f']), asa(cb.stat['df']))) ''' -------------------------------------------------- solver: gsubg problem: rjevsky2 (nVars: 10) type: NSP goal: minimum iter objFunVal 0 5.337e+03 10 -5.386e-01 20 -8.399e-01 30 -8.414e-01 40 -8.414e-01
R = {} for i, solver in enumerate(solvers): p = NSP( obj, startPoint, maxIter=1700, name="Rzhevsky5 (nVars: " + str(n) + ")", maxTime=300, maxFunEvals=1e7, color=Colors[i], ) p.fTol = 0.5e-10 cb.TMP = 1000 cb.stat = {"dist": [], "f": [], "df": []} p.fOpt = -34.408608965509742 p.maxTime = 30 r = p.solve(solver, iprint=1, xtol=1e-15, ftol=1e-15, gtol=1e-15, show=solver == solvers[-1], plot=0, callback=cb) R[solver] = hstack((asa(cb.stat["dist"]), asa(cb.stat["f"]), asa(cb.stat["df"]))) """ solver: gsubg problem: rjevsky5 (nVars: 50) type: NSP goal: minimum iter objFunVal 0 -2.241e+00 1 -3.056e+01 2 -3.387e+01 3 -3.427e+01 4 -3.434e+01 5 -3.436e+01 6 -3.439e+01 7 -3.439e+01 8 -3.439e+01
lines = [] R = {} for i, solver in enumerate(solvers): p = NSP(obj, startPoint, maxIter=1700, name='Rzhevsky5 (nVars: ' + str(n) + ')', maxTime=300, maxFunEvals=1e7, color=Colors[i]) p.fTol = 0.5e-10 cb.TMP = 1000 cb.stat = {'dist': [], 'f': [], 'df': []} p.fOpt = -34.408608965509742 p.maxTime = 30 r = p.solve(solver, iprint=1, xtol=1e-15, ftol=1e-15, gtol=1e-15, show=solver == solvers[-1], plot=0, callback=cb) R[solver] = hstack( (asa(cb.stat['dist']), asa(cb.stat['f']), asa(cb.stat['df']))) ''' solver: gsubg problem: rjevsky5 (nVars: 50) type: NSP goal: minimum iter objFunVal 0 -2.241e+00 1 -3.056e+01