优化解决时返回函数调用和其他信息
returning function calls and other info when optimization solves
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 return 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，但是是否有一个对象或属性可以 returned 以允许我的函数 return 数值？
这里是代码设置的示例。
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)
objective function, iterations, solve time, and solution status 在 Gekko 中可用：
m.options.OBJFCNVALm.options.ITERATIONSm.options.SOLVETIMEm.options.APPSTATUS
您可以 return 这些作为列表，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)
如果要函数调用，就稍微复杂一点，因为函数调用的类型不同。有 objective 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。通过设置 m.options.DIAGLEVEL=1 或更高，您可以获得所有子程序调用以及每个子程序的个人和累积时间的完整报告。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 API 中可用的迭代，因此它们总是报告为零。使用 APOPT，摘要列表为 [76.207789973, 5, 0.5253, 1]。时间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 objective 函数请求、一阶导数请求和约束评估请求。
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 return 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，但是是否有一个对象或属性可以 returned 以允许我的函数 return 数值？
这里是代码设置的示例。
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)
objective function, iterations, solve time, and solution status 在 Gekko 中可用：
m.options.OBJFCNVALm.options.ITERATIONSm.options.SOLVETIMEm.options.APPSTATUS
您可以 return 这些作为列表，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)
如果要函数调用，就稍微复杂一点，因为函数调用的类型不同。有 objective 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。通过设置 m.options.DIAGLEVEL=1 或更高，您可以获得所有子程序调用以及每个子程序的个人和累积时间的完整报告。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 API 中可用的迭代，因此它们总是报告为零。使用 APOPT，摘要列表为 [76.207789973, 5, 0.5253, 1]。时间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 objective 函数请求、一阶导数请求和约束评估请求。