这是我的 Rosenbrock 混凝土模型的代码。
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)
通过 tee=True 时的solver.solve 行打印出各种漂亮信息的漂亮显示。我想从打印输出中访问该信息，并浏览了 Pyomo 和 IPOPT 文档，但似乎无法理解如何访问打印到屏幕上的值。我还包含了一个简短的打印输出示例，我想保存每次运行的值，以便我可以迭代并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
****省略****
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，但我看不到通过搜索文档来访问它们的可行接口，任何向导都知道如何做到这一点？谢谢。