Question

这是我的Rosenbrock具体模型的代码。

from pyomo.environ import *
from pyomo.opt import SolverFactory
import numpy as np
import math
import statistics
import time

m = ConcreteModel()

m.x = Var()
m.y = Var()
m.z = Var()

def rosenbrock(model):
    return (1.0-m.x)2 + 100.0*(m.y - m.x2)2 + (1.0-m.y)2 + 100.0*(m.z - m.y2)2

m.obj = Objective(rule=rosenbrock, sense=minimize)

dist = 0.0
xval = yval = zval = error = times = []
for i in range(50):
    m.x = np.random.uniform(low=-5.0, high=5.0)
    m.y = np.random.uniform(low=-5.0, high=5.0)
    m.z = np.random.uniform(low=-5.0, high=5.0)
    solver = SolverFactory('ipopt')
    t1 = time.time()
    results = solver.solve(m, tee=True)

当通过tee = True时，solver.solve行将打印出精美的各种漂亮信息的显示。我想从打印中访问该信息，并仔细阅读了Pyomo和IPOPT文档，似乎无法理解如何访问打印到屏幕上的值。我还提供了打印输出的简短示例，我想保存每次运行的值，以便可以迭代和收集整个范围内的统计信息。

Number of nonzeros in equality constraint Jacobian...:        0
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:        5

Total number of variables............................:        3
                     variables with only lower bounds:        0
                variables with lower and upper bounds:        0
                     variables with only upper bounds:        0
Total number of equality constraints.................:        0
Total number of inequality constraints...............:        0
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:        0

****************

Number of objective function evaluations             = 45
Number of objective gradient evaluations             = 23
Number of equality constraint evaluations            = 0
Number of inequality constraint evaluations          = 0
Number of equality constraint Jacobian evaluations   = 0
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations             = 22
Total CPU secs in IPOPT (w/o function evaluations)   =      0.020
Total CPU secs in NLP function evaluations           =      0.000

我需要其中一些值，但是我在搜索文档时看不到任何可行的接口来访问它们，任何向导都知道该怎么做？谢谢。

Answer 1

请参阅此为Pyomo贡献的Ipopt求解器包装。从本质上讲，它是Ipopt输出日志的解析器，您应该能够对其进行概括/扩展以收集当前未收集的任何值。

https://github.com/Pyomo/pyomo/blob/master/pyomo/contrib/parmest/ipopt_solver_wrapper.py

从IPOPT Display Pyomo获得价值

1 个答案: