本文整理汇总了Python中openopt.NLP.f方法的典型用法代码示例。如果您正苦于以下问题：Python NLP.f方法的具体用法？Python NLP.f怎么用？Python NLP.f使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类openopt.NLP的用法示例。
在下文中一共展示了NLP.f方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: in
# 需要导入模块: from openopt import NLP [as 别名]
# 或者: from openopt.NLP import f [as 别名]
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])示例2: NLP
# 需要导入模块: from openopt import NLP [as 别名]
# 或者: from openopt.NLP import f [as 别名]
"""
p = NLP(x0=15, f=lambda x: x ** 2 - 0.4, df=lambda x: 2 * x, iprint=0, plot=1)
# after the problem is assigned, you could turn the parameters,
# along with some other that have been set as defaults:
p.x0 = 0.15
p.plot = 0
def f(x):
return x if x > 0 else x ** 2
p.f = f
# At last, you can modify any prob parameters in minimize/maximize/solve/manage functions:
r = p.minimize("ralg", x0=-1.5, iprint=-1, plot=1, color="r")
# or
# r = p.manage('ralg', start = False, iprint = 0, x0 = -1.5)
"""
Note that *any* kwarg passed to constructor will be assigned
e.g.
p = NLP(f, x0, myName='JohnSmith')
is equivalent to
p.myName='JohnSmith'
It can be very convenient for user-supplied callback functions
(see /examples/userCallback.py)