本文整理汇总了Python中openopt.NLP.df_iter方法的典型用法代码示例。如果您正苦于以下问题：Python NLP.df_iter方法的具体用法？Python NLP.df_iter怎么用？Python NLP.df_iter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.df_iter方法的1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: help
# 需要导入模块: from openopt import NLP [as 别名]
# 或者: from openopt.NLP import df_iter [as 别名]
# see also: help(NLP) -> maxTime, maxCPUTime, ftol and xtol
# that are connected to / used in lincher and some other solvers
# optional: check of user-supplied derivatives
p.checkdf()
p.checkdc()
p.checkdh()
# last but not least:
# please don't forget,
# Python indexing starts from ZERO!!
p.plot = 0
p.iprint = 0
p.df_iter = 4
p.maxTime = 4000
p.debug=1
#r = p.solve('algencan')
r = p.solve('ralg')
#r = p.solve('lincher')
"""
typical output:
OpenOpt checks user-supplied gradient df (size: (50,))
according to:
prob.diffInt = 1e-07
prob.check.maxViolation = 1e-05
max(abs(df_user - df_numerical)) = 2.50111104094e-06
(is registered in df number 41)