/usr/share/pyshared/openopt/examples/nlp_5.py is in python-openopt 0.38+svn1589-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | from openopt import NLP
from numpy import cos, arange, ones, asarray, abs, zeros, sqrt, asscalar, inf
from string import rjust, ljust, expandtabs, center, lower
N = 100
M = 5
Power = 1.13
ff = lambda x: (abs(x-M) ** Power).sum()
x0 = cos(arange(N))
c = [lambda x: 2* x[0] **4-32, lambda x: x[1]**2+x[2]**2 - 8]
#c = lambda x: [2* x[0] **4-32, x[1]**2+x[2]**2 - 8000]
h1 = lambda x: 1e1*(x[-1]-1)**4
h2 = lambda x: (x[-2]-1.5)**4
h = (h1, h2)
lb = -6*ones(N)
ub = 6*ones(N)
lb[3] = 5.5
ub[4] = 4.5
gtol=1e-6
ftol = 1e-6
diffInt = 1e-8
contol = 1e-6
maxFunEvals = 1e6
maxTime = 10
Xlabel = 'time'
PLOT = 0
colors = ['b', 'k', 'y', 'g', 'r', 'm', 'c']
###############################################################
solvers = ['ralg', 'scipy_cobyla', 'lincher', 'scipy_slsqp', 'ipopt','algencan']
#solvers = ['ralg', 'ipopt']
#solvers = ['ralg', 'scipy_cobyla', 'lincher', 'scipy_slsqp', 'ipopt']
#solvers = ['ralg', 'ralg3']
solvers = ['ralg']
###############################################################
lines, results = [], {}
for j, solver in enumerate(solvers):
p = NLP(ff, x0, xlabel = Xlabel, c=c, h=h, lb = lb, ub = ub, gtol=gtol, diffInt = diffInt, ftol = ftol, maxIter = 1390, plot = PLOT, color = colors[j], iprint = 10, df_iter = 4, legend = solver, show=False, contol = contol, maxTime = maxTime, maxFunEvals = maxFunEvals, name='NLP_5')
if solver =='algencan':
p.gtol = 1e-2
elif solver == 'ralg':
pass
#p.debug = 1
p.debug = 1
r = p.solve(solver)
for fn in ('h','c'):
if not r.evals.has_key(fn): r.evals[fn]=0 # if no c or h are used in problem
results[solver] = (r.ff, p.getMaxResidual(r.xf), r.elapsed['solver_time'], r.elapsed['solver_cputime'], r.evals['f'], r.evals['c'], r.evals['h'])
if PLOT:
subplot(2,1,1)
F0 = asscalar(p.f(p.x0))
lines.append(plot([0, 1e-15], [F0, F0], color= colors[j]))
if PLOT:
for i in range(2):
subplot(2,1,i+1)
legend(lines, solvers)
subplots_adjust(bottom=0.2, hspace=0.3)
xl = ['Solver f_opt MaxConstr Time CPUTime fEvals cEvals hEvals']
for i in range(len(results)):
s=(ljust(lower(solvers[i]), 40-len(solvers[i]))+'%0.3f'% (results[solvers[i]][0]) + ' %0.1e' % (results[solvers[i]][1]) + (' %0.2f'% (results[solvers[i]][2])) + ' %0.2f '% (results[solvers[i]][3]) + str(results[solvers[i]][4]) + ' ' + rjust(str(results[solvers[i]][5]), 5) + ' '*8 +str(results[solvers[i]][6]))
xl.append(s)
xl = '\n'.join(xl)
subplot(2,1,1)
xlabel(Xlabel)
from pylab import *
subplot(2,1,2)
xlabel(xl)
show()
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