我正在使用 Gekko 对多个系统的多个问题进行基准测试,我想让我的代码返回函数调用、迭代和解决所需的时间。我知道求解器会自动打印所有这些数据,但是是否有可以返回的对象或属性以允许我的函数返回数值?
这是如何设置代码的示例。
def model(plot=False):
t = np.linspace(0, 1, 101)
m = GEKKO(remote=False); m.time=t
fe = m.Param(np.cos(2*np.pi*t)+3)
de = m.Var(fe[0])
e = m.CV(0); e.STATUS=1; e.SPHI=e.SPLO=0; e.WSPHI=1000; e.WSPLO=1
der = m.MV(0, lb=-1, ub=1); der.STATUS=1
m.Equations([de.dt() == der, e == fe-de])
m.options.IMODE=6; m.solve()
if plot:
import matplotlib.pyplot as plt
plt.plot(t, fe)
plt.plot(t, de)
plt.plot(t, der)
plt.show()
return m.fcalls
if __name__ == "__main__":
model(plot=True)
最佳答案
objective function , iterations , solve time , 和 solution status可在 Gekko 中使用:
m.options.OBJFCNVAL
m.options.ITERATIONS
m.options.SOLVETIME
m.options.APPSTATUS
你可以将这些作为列表返回,就像我对
summary
所做的那样.from gekko import GEKKO
import numpy as np
def model(plot=False):
t = np.linspace(0, 1, 101)
m = GEKKO(remote=False); m.time=t
fe = m.Param(np.cos(2*np.pi*t)+3)
de = m.Var(fe[0])
e = m.CV(0); e.STATUS=1; e.SPHI=e.SPLO=0; e.WSPHI=1000; e.WSPLO=1
der = m.MV(0, lb=-1, ub=1); der.STATUS=1
m.Equations([de.dt() == der, e == fe-de])
m.options.DIAGLEVEL=1
m.options.SOLVER=1
m.options.IMODE=6; m.solve()
if plot:
import matplotlib.pyplot as plt
plt.plot(t, fe)
plt.plot(t, de)
plt.plot(t, der)
plt.savefig('result.png')
return [m.options.OBJFCNVAL,\
m.options.ITERATIONS,\
m.options.SOLVETIME,\
m.options.APPSTATUS]
if __name__ == "__main__":
summary = model(plot=True)
print(summary)
如果你想要函数调用,它会稍微复杂一些,因为有不同类型的函数调用。有目标函数和约束的函数调用、一阶导数的函数调用和二阶导数的函数调用。您可以通过设置
m.options.DIAGLEVEL=1
获得所有子程序调用的完整报告以及每个子程序的个人和累计时间。或更高。这是此问题的求解器输出: Number of state variables: 1900
Number of total equations: - 1800
Number of slack variables: - 0
---------------------------------------
Degrees of freedom : 100
----------------------------------------------
Dynamic Control with APOPT Solver
----------------------------------------------
Iter Objective Convergence
0 9.81590E+01 1.00000E+00
1 7.62224E+01 4.00000E-10
2 7.62078E+01 1.10674E-02
3 7.62078E+01 1.00000E-10
4 7.62078E+01 8.32667E-17
5 7.62078E+01 8.32667E-17
Successful solution
---------------------------------------------------
Solver : APOPT (v1.0)
Solution time : 0.5382 sec
Objective : 76.20778997271815
Successful solution
---------------------------------------------------
一些求解器,如 IPOPT,没有从 API 中随时可用的迭代,因此它们总是报告为零。使用APOPT,汇总列表为
[76.207789973, 5, 0.5253, 1]
.时序和函数调用报告在求解器摘要之后。Timer # 1 0.70/ 1 = 0.70 Total system time
Timer # 2 0.54/ 1 = 0.54 Total solve time
Timer # 3 0.05/ 9 = 0.01 Objective Calc: apm_p
Timer # 4 0.00/ 5 = 0.00 Objective Grad: apm_g
Timer # 5 0.02/ 9 = 0.00 Constraint Calc: apm_c
Timer # 6 0.00/ 0 = 0.00 Sparsity: apm_s
Timer # 7 0.00/ 0 = 0.00 1st Deriv #1: apm_a1
Timer # 8 0.00/ 5 = 0.00 1st Deriv #2: apm_a2
Timer # 9 0.02/ 200 = 0.00 Custom Init: apm_custom_init
Timer # 10 0.00/ 200 = 0.00 Mode: apm_node_res::case 0
Timer # 11 0.00/ 600 = 0.00 Mode: apm_node_res::case 1
Timer # 12 0.00/ 200 = 0.00 Mode: apm_node_res::case 2
Timer # 13 0.00/ 400 = 0.00 Mode: apm_node_res::case 3
Timer # 14 0.00/ 4800 = 0.00 Mode: apm_node_res::case 4
Timer # 15 0.00/ 2000 = 0.00 Mode: apm_node_res::case 5
Timer # 16 0.00/ 0 = 0.00 Mode: apm_node_res::case 6
Timer # 17 0.00/ 5 = 0.00 Base 1st Deriv: apm_jacobian
Timer # 18 0.02/ 5 = 0.00 Base 1st Deriv: apm_condensed_jacobian
Timer # 19 0.00/ 1 = 0.00 Non-zeros: apm_nnz
Timer # 20 0.00/ 0 = 0.00 Count: Division by zero
Timer # 21 0.00/ 0 = 0.00 Count: Argument of LOG10 negative
Timer # 22 0.00/ 0 = 0.00 Count: Argument of LOG negative
Timer # 23 0.00/ 0 = 0.00 Count: Argument of SQRT negative
Timer # 24 0.00/ 0 = 0.00 Count: Argument of ASIN illegal
Timer # 25 0.00/ 0 = 0.00 Count: Argument of ACOS illegal
Timer # 26 0.00/ 1 = 0.00 Extract sparsity: apm_sparsity
Timer # 27 0.00/ 17 = 0.00 Variable ordering: apm_var_order
Timer # 28 0.00/ 1 = 0.00 Condensed sparsity
Timer # 29 0.00/ 0 = 0.00 Hessian Non-zeros
Timer # 30 0.00/ 3 = 0.00 Differentials
Timer # 31 0.00/ 0 = 0.00 Hessian Calculation
Timer # 32 0.00/ 0 = 0.00 Extract Hessian
Timer # 33 0.00/ 1 = 0.00 Base 1st Deriv: apm_jac_order
Timer # 34 0.06/ 1 = 0.06 Solver Setup
Timer # 35 0.40/ 1 = 0.40 Solver Solution
Timer # 36 0.00/ 23 = 0.00 Number of Variables
Timer # 37 0.00/ 12 = 0.00 Number of Equations
Timer # 38 0.05/ 17 = 0.00 File Read/Write
Timer # 39 0.00/ 1 = 0.00 Dynamic Init A
Timer # 40 0.02/ 1 = 0.02 Dynamic Init B
Timer # 41 0.02/ 1 = 0.02 Dynamic Init C
Timer # 42 0.00/ 1 = 0.00 Init: Read APM File
Timer # 43 0.00/ 1 = 0.00 Init: Parse Constants
Timer # 44 0.00/ 1 = 0.00 Init: Model Sizing
Timer # 45 0.00/ 1 = 0.00 Init: Allocate Memory
Timer # 46 0.00/ 1 = 0.00 Init: Parse Model
Timer # 47 0.00/ 1 = 0.00 Init: Check for Duplicates
Timer # 48 0.00/ 1 = 0.00 Init: Compile Equations
Timer # 49 0.00/ 1 = 0.00 Init: Check Uninitialized
Timer # 50 0.00/ 205 = 0.00 Evaluate Expression Once
Timer # 51 0.00/ 0 = 0.00 Sensitivity Analysis: LU Factorization
Timer # 52 0.00/ 0 = 0.00 Sensitivity Analysis: Gauss Elimination
Timer # 53 0.00/ 0 = 0.00 Sensitivity Analysis: Total Time
计时器 3、4 和 5 可能与您的问题最相关。它们是目标函数请求、一阶导数请求和约束评估请求。
关于python - 优化求解时返回函数调用和其他信息,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/62160528/