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
