[英]TypeError: x must be a python list of GEKKO parameters, variables, or expressions
[英]List handling in GEKKO python
我目前正在为一个大学项目研究蒸馏 flask 的 model,DAE 系统描述了物理问题,我正在尝试使用 GEKKO 解决它。
我在处理列表时遇到了问题:在这种情况下,我构建了一个 function 来输出混合的压缩因子,它需要 3 个 gekko 变量 T1,x,y (x,y 数组) zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1.value,x,y))
作为输入zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1.value,x,y))
m = GEKKO()
y = m.Array(m.Var,n,value=0.)
x = m.Array(m.Var,n,value=0.)
for i in range(n):
y[i].value = y0[i]
x[i].value = x0[i]
T1 = m.Var(value=3.31513478e+02, lb=300, ub=900)
如果我保留 3 个值,我会收到一些错误,例如:
File "F:\Codice_GEKKO\D86_GEKKO.py", line 113, in <module>
zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1.value,x,y))
File "F:\Codice_GEKKO\compressibilityfactor.py", line 48, in ZCALC
zv=np.max(np.roots([1,-1,(Av-Bv-Bv**2),-Av*Bv]))
File "<__array_function__ internals>", line 6, in roots
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\numpy\lib\polynomial.py", line 222, in roots
non_zero = NX.nonzero(NX.ravel(p))[0]
File "<__array_function__ internals>", line 6, in nonzero
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\numpy\core\fromnumeric.py", line 1908, in nonzero
return _wrapfunc(a, 'nonzero')
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\numpy\core\fromnumeric.py", line 67, in _wrapfunc
return _wrapit(obj, method, *args, **kwds)
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\numpy\core\fromnumeric.py", line 44, in _wrapit
result = getattr(asarray(obj), method)(*args, **kwds)
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\gekko\gk_operators.py", line 25, in __len__
return len(self.value)
File "C:\Users\verci\AppData\Local\Programs\Python\Python36\lib\site-packages\gekko\gk_operators.py", line 144, in __len__
return len(self.value)
TypeError: object of type 'int' has no len()```
Traceback (most recent call last):
File "F:\Codice_GEKKO\D86_GEKKO.py", line 113, in <module>
zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1,x,y))
File "F:\Codice_GEKKO\compressibilityfactor.py", line 27, in ZCALC
(1-np.sqrt(t/tc[ii])))**2
TypeError: loop of ufunc does not support argument 0 of type GK_Operators which has no callable sqrt method
第一个错误是由于 x 和 y 未列出,但它们是 GEKKO arrays 而第二个错误是由于 T1 不是浮点数(t=T1)
我发现通过使用 T1.value 我可以避免第二个错误,但我仍然有第一个错误
我已阅读 gekko 文档,但我无法找到从 GEKKO 数组中获取“标准”python 列表的方法
预先感谢您的帮助
有两种不同的方法来获得 zv 的值。
选项 1:初始化计算
第一种方法是使用浮点数来获得可用于参数初始化的单个计算。 第一种方法允许使用任何类型的函数,例如np.roots()
或np.sqrt()
。 function ZCALC()
返回一个浮点数。 即使使用 Gekko 变量作为输入,浮点数也可以通过T1.value
的标量变量或x[i].value
的数组变量访问。
def ZCALC(n,comps,R0,p,T1,x,y):
# using the initialized values
t = T1.value
i = 0 # select values from x,y arrays
x1 = x[i].value
y1 = y[i].value
print('t,x[0],y[0] initialized values')
print(t,x1,y1)
# include equations for compressibility factor
w = (1-np.sqrt(t/300))**2
z = np.max(np.roots([1,-1,x1**2,x1*y1]))
# original equations from question
#(1-np.sqrt(t/tc[ii])))**2
#zv=np.max(np.roots([1,-1,(Av-Bv-Bv**2),-Av*Bv]))
return z
zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1,x,y))
选项 2:隐式计算
如果压缩因子需要随着T1
和x,y
的变化而变化,则使用 Gekko 变量,以便使用该依赖项编译 model。 这些函数仅在问题初始化期间被调用。 Gekko 需要具有特定 Gekko 函数的方程来启用自动微分,从而为求解器提供梯度。
def ZCALC2(n,comps,R0,p,T1,x,y):
# using gekko variables
t = T1
i = 0
x1 = x[i] # use index to x array
y1 = y[i] # use index to y array
# use Gekko equations, not Numpy
w = (x1/y1)*(1-m.sqrt(t/300))**2
# set lower bound to get the maximum root
zv = m.Var(value=ZCALC(n,comps,R0,p,T1,x,y),lb=10)
# solve for roots of eq with gekko, not with np.roots
eq = 1-zv+x1**2*zv+x1*y1*zv**3
m.Equation(eq==0)
return zv
zv2 = ZCALC2(n,comps,R0,p,T1,x,y)
这是一个显示这两种方法的脚本:
import numpy as np
m=GEKKO(remote=False)
def ZCALC(n,comps,R0,p,T1,x,y):
# using the initialized values
t = T1.value
i = 0 # select values from x,y arrays
x1 = x[i].value
y1 = y[i].value
print('t,x[0],y[0] initialized values')
print(t,x1,y1)
# include equations for compressibility factor
w = (1-np.sqrt(t/300))**2
z = np.max(np.roots([1,-1,x1**2,x1*y1]))
# original equations from question
#(1-np.sqrt(t/tc[ii])))**2
#zv=np.max(np.roots([1,-1,(Av-Bv-Bv**2),-Av*Bv]))
return z
def ZCALC2(n,comps,R0,p,T1,x,y):
# using gekko variables
t = T1
i = 0
x1 = x[i] # use index to x array
y1 = y[i] # use index to y array
# use Gekko equations, not Numpy
w = (x1/y1)*(1-m.sqrt(t/300))**2
# set lower bound to get the maximum root
zv = m.Var(value=ZCALC(n,comps,R0,p,T1,x,y),lb=10)
# solve for roots of eq with gekko, not with np.roots
eq = 1-zv+x1**2*zv+x1*y1*zv**3
m.Equation(eq==0)
return zv
n = 3
y = m.Array(m.Var,n)
x = m.Array(m.Var,n)
x0 = [0.1,0.2,0.3]
y0 = [0.15,0.25,0.35]
for i in range(n):
y[i].value = y0[i]
x[i].value = x0[i]
T1 = m.Var(value=331, lb=300, ub=900)
comps = ['C2=','C3=','C2H8']; R0 = 8.314; p=10
# define Zv from initialized values (fixed parameter)
zv1 = m.Param(value=ZCALC(n,comps,R0,p,T1,x,y))
# define Zv from Gekko variables (updates with T1,x,y changes)
zv2 = ZCALC2(n,comps,R0,p,T1,x,y)
# initialized value of zv1 does not update with changes in T1,x,y
# initialized value of zv2 does update with changes in T1,x,y
print('initialized value of zv1, zv2')
print(zv1.value,zv2.value)
如果压缩因子相关性不能表示为 Gekko 方程,则尝试使用 1D 的cspline
或 2D 函数的bspline
来创建近似值。 如果可压缩性仅取决于 2 个变量T
和x
(将y
替换为x
的显式计算),则您可以使用bspline
function。
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