本文整理汇总了Python中openopt.NLP.ub[4]方法的典型用法代码示例。如果您正苦于以下问题：Python NLP.ub[4]方法的具体用法？Python NLP.ub[4]怎么用？Python NLP.ub[4]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.ub[4]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: h2
# 需要导入模块: from openopt import NLP [as 别名]
# 或者: from openopt.NLP import ub[4] [as 别名]
r[1,1] = 2 * x[1]
r[1,2] = 2 * x[2]
return r
p.dc = dc
h1 = lambda x: 1e1*(x[-1]-1)**4
h2 = lambda x: (x[-2]-1.5)**4
p.h = lambda x: (h1(x), h2(x))
def dh(x):
r = zeros((2, p.n))
r[0,-1] = 1e1*4*(x[-1]-1)**3
r[1,-2] = 4*(x[-2]-1.5)**3
return r
p.dh = dh
p.lb = -6*ones(N)
p.ub = 6*ones(N)
p.lb[3] = 5.5
p.ub[4] = 4.5
#r = p.solve('ipopt', showLS=0, xtol=1e-7, maxIter = 1504)
#solver = 'ipopt'
solver = 'ralg'
#solver = 'scipy_slsqp'
#solver = 'algencan'
r = p.solve(solver, maxIter = 1504, plot=1)
#!! fmin_cobyla can't use user-supplied gradient
#r = p.solve('scipy_cobyla')
示例2: min
# 需要导入模块: from openopt import NLP [as 别名]
# 或者: from openopt.NLP import ub[4] [as 别名]
# (x0-1)^4 + (x2-1)^4 + ... +(x49-1)^4 -> min (N=nVars=50)
f = lambda x : ((x-1)**4).sum()
x0 = cos(arange(N))
p = NLP(f, x0, maxIter = 1e3, maxFunEvals = 1e5)
# f(x) gradient (optional):
p.df = lambda x: 4*(x-1)**3
# lb<= x <= ub:
# x4 <= -2.5
# 3.5 <= x5 <= 4.5
# all other: lb = -5, ub = +15
p.lb = -5*ones(N)
p.ub = 15*ones(N)
p.ub[4] = -2.5
p.lb[5], p.ub[5] = 3.5, 4.5
# Ax <= b
# x0+...+xN>= 1.1*N
# x9 + x19 <= 1.5
# x10+x11 >= 1.6
p.A = zeros((3, N))
p.A[0, 9] = 1
p.A[0, 19] = 1
p.A[1, 10:12] = -1
p.A[2] = -ones(N)
p.b = [1.5, -1.6, -1.1*N]
# you can use any types of A, Aeq, b, beq: