Python 巨蟒壁虎找不到;options.json“;文件
我还没有看到与此相关的问题,但尽管我做出了一些相反的努力,它还是会突然出现,所以我希望有人能帮助我了解发生了什么 我是Python的Gekko包的新手,我正在尝试运行一个非线性解算器来解决问题。我收到一条奇怪的错误消息(Python 巨蟒壁虎找不到;options.json“;文件,python,dynamic,system,gekko,Python,Dynamic,System,Gekko,我还没有看到与此相关的问题,但尽管我做出了一些相反的努力,它还是会突然出现,所以我希望有人能帮助我了解发生了什么 我是Python的Gekko包的新手,我正在尝试运行一个非线性解算器来解决问题。我收到一条奇怪的错误消息(FileNotFoundError:[Errno 2]没有这样的文件或目录:'/var/folders/03/vyh22j3j45j2rqjmnygfw2l8000gn/T/tmpatrk8y36gk_model0/options.json'),它看起来是程序化的/语法化的,而不
FileNotFoundError:[Errno 2]没有这样的文件或目录:'/var/folders/03/vyh22j3j45j2rqjmnygfw2l8000gn/T/tmpatrk8y36gk_model0/options.json'
),它看起来是程序化的/语法化的,而不是数学化的。这是一个大得多的函数/数据/输入中的一个函数,所以我很难提供足够的函数来帮助您复制它--但是--
y(即self.get_days_energy(日期=日期)的结果)是能量值的向量,self.get_external_input_of_day(日期)也是能量值的向量。Z变量是潜在状态变量,A和B分别是潜在状态和外生变量的转移矩阵。此函数的目标是更新上述三个变量
下面是函数:
def daily_weight_fit(self, date):
"""
Update function to the weights of the dynamic system, this will be called
once a day after the data has arrived.
"""
m = GEKKO(remote = False)
A = m.Array(
m.Var,
(self.state_weights.shape),
value = 1,
lb = -10,
ub = 10,
)
B = m.Array(
m.Var,
(self.input_weights.shape),
value = 1,
lb = -100,
ub = 100,
)
dates = pd.date_range(start=self.starting_date, end=date)
date_list = dates.tolist()
hours = list(range(24))
y = [[self.get_days_energy(date = date)] for date in dates]
flat_y = np.reshape(y, -1)
timesteps = len(flat_y)
u = [self.get_exogenous_inputs_of_day(date) for date in dates for hour in hours]
z = m.Array(m.Var, (timesteps, 4), lb = -1, ub = 1)
C = np.array([0, 0, 1, 0])
m.Obj(
m.sqrt(
m.sum([(flat_y[i] - z[i][3])**2 for i in range(len(flat_y))])
)
)
for i in range(timesteps - 2):
state_contribution = np.dot(A, z[i])
ex_contribution = np.dot(B, u[i])
for j in range(4):
m.Equation(z[i + 1][j] == state_contribution[j] + ex_contribution[j])
m.options.solver = 1
m.solve()
return A, B, z
以下是错误输出:
----------------------------------------------------------------
APMonitor, Version 0.9.2
APMonitor Optimization Suite
----------------------------------------------------------------
--------- APM Model Size ------------
Each time step contains
Objects : 1
Constants : 0
Variables : 1849
Intermediates: 0
Connections : 361
Equations : 1793
Residuals : 1793
Number of state variables: 1849
Number of total equations: - 1793
Number of slack variables: - 0
---------------------------------------
Degrees of freedom : 56
----------------------------------------------
Steady State Optimization with APOPT Solver
----------------------------------------------
Iter Objective Convergence
0 4.12076E+08 8.12928E+01
1 5.38520E+02 1.00000E+00
2 5.38512E+02 3.75145E-12
3 5.38450E+02 2.00000E+00
4 5.38506E+02 1.80710E-01
NEGATIVE NDF: -1
5 1.10270E+07 3.34638E-01
6 4.89845E+06 1.93472E+00
7 4.73333E+05 3.99952E+00
8 3.76178E+05 2.00000E+00
9 1.69753E+05 1.31302E+00
Iter Objective Convergence
10 1.90770E+07 5.86504E-01
11 3.03623E+16 3.34638E-01
12 9.38385E+11 3.34304E-01
13 1.14353E+12 1.09011E-02
14 8.91928E+12 7.65181E-03
Error:
Program received signal SIGSEGV: Segmentation fault - invalid memory reference.
Backtrace for this error:
#0 0x108c7718d
#1 0x108c7661b
#2 0x7fff661ccf59
#3 0x108a92b6b
apm_mac(33870,0x7fff9e9c1380) malloc: *** error for object 0x7fb371862e00: incorrect checksum for freed object - object was probably modified after being freed.
*** set a breakpoint in malloc_error_break to debug
Program received signal SIGABRT: Process abort signal.
Backtrace for this error:
#0 0x108c7718d
#1 0x108c7661b
#2 0x7fff661ccf59
Error: 'results.json' not found. Check above for additional error details
Traceback (most recent call last):
.... (my own irrelevant function trace).....
m.solve()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/gekko/gekko.py", line 2145, in solve
self.load_JSON()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/gekko/gk_post_solve.py", line 13, in load_JSON
f = open(os.path.join(self._path,'options.json'))
FileNotFoundError: [Errno 2] No such file or directory: '/var/folders/03/vyh22j3j45j2rqjmnygfw2l80000gn/T/tmp42metzl9gk_model0/options.json'
任何提示或建议将不胜感激!约翰·何登仁,你好,我喜欢你的工作 您发现了APOPT解算器的一个新错误。迭代总结表明问题正在发散,因此一些变量可能会变得无穷大,超出机器精度
m.options.solver=2的BPOPT或带m.options.solver=3的IPOPT
每当求解器崩溃时,请考虑在
或options.json
文件由底层C++/Fortran可执行文件通过results.json
本地编写,或通过web服务m=GEKKO(remote=False)
编写。在所有情况下,可执行文件都会在本地运行目录m=GEKKO(remote=True)
或远程服务器上以m.path
文件的形式生成结果。当可执行文件由于错误而崩溃时,将不会生成json
文件,从而导致您观察到的错误。您还可以看到解算器在迭代14处停止。使用json
,可执行文件从Gekko bin目录(Linux为remote=False
,MacOS为apm
,Windows为apm\u mac
)本地运行,但会在运行目录apm.exe
中生成文件。感谢您的鼓励和提出的问题。谢谢John,哇,我对你的快速反应感到惊讶和荣幸!关于你的第二个建议,我已经将我的决策变量A,B,z限定在我知道的范围内。除了lb/ub args,还有其他方法吗?或者你的意思是绑定它们,使它们不可能为0?嘿,John,我m.path
给了我同样的答案,但是m.options.solver=3
似乎至少尝试过解决它:``--------------------------------------------------------------APMonitor,版本0.9.2…-------------------------------------带BPOPT解算器的稳态优化---------------------------------------------“````--------------------------------------------------------------------BPOPT解算器v1.0.6------------------------------------------国际热核实验堆目标收敛0 6.27904E+05 6.28242E+05 1.03091E+10 1.03091E+06 1.00347E+10 1.00347E+06。。。文件“behavious_simulation.py”,第248行,在每日_weight_fit m.solve()文件“/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site packages/gekko/gekko.py”,第2059行,在solve raise Exception(apm_error)Exception:@error:Solution Not found您可以从A、B和z的上下界开始。如果解算器在边界处找到解,则进一步加宽边界,直到边界不再限制解。 m.options.solver=2