[英]Meaning of 'minimization_failures' when using scipy.optimize.basinhopping?
I am trying to use scipy.optimize.basinhopping
with a function b_log(x)
at point x=10
. 我正在尝试在点
x=10
scipy.optimize.basinhopping
与函数b_log(x)
一起使用。 I do not understand the meaning of "minimization_failures" below. 我不明白下面“ minimization_failures”的含义。 Can anyone explain?
谁能解释?
In [144]: scipy.optimize.basinhopping(b_log,10)
Out[144]:
nfev: 6969
minimization_failures: 101
fun: 420
x: array([10])
message: ['requested number of basinhopping iterations completed successfully']
njev: 1919
nit: 100
From the original source : 从原始来源 :
# do a local minimization
minres = self.minimizer(x_after_step)
x_after_quench = minres.x
energy_after_quench = minres.fun
if not minres.success:
self.res.minimization_failures += 1
if self.disp:
print("warning: basinhopping: local minimization failure")
So, minimization_failures
means exactly what its name says: The number of times a minimization could not be done during the monte-carlo-step. 因此,
minimization_failures
含义恰如其名:在蒙特卡洛步骤中无法进行最小化的次数。
Edit: Have a look at this for some explanation of the method. 编辑:看看这个方法的一些解释。 I think u may need to provide the additional arguments to the function (eg T and minimizer_kwargs).
我认为您可能需要为函数提供其他参数(例如T和minimumr_kwargs)。
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