Python SciPy IndexError:边界长度与x0的长度不兼容 [英] Python SciPy IndexError: the length of bounds is not compatible with that of x0

问题描述

我是使用Python和scipy进行优化的新手.我遇到了错误

I'm new to optimizations using Python and scipy. I'm getting the error

IndexError: SLSQP Error: the length of bounds is not compatible with that of x0.

当尝试将bounds参数传递到scipy.optimize.minimize

x0 = np.array([[2,2,2,2,2,2,2,2,2,2,2],[2,2,2,2,2,2,2,2,2,2,2]])
bounds = ( [(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000)], [(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000),(0,12000)] )

x_max = optimize.minimize(f, x0.flatten(), method='SLSQP', bounds=bounds)

如何为这样的x0定义bounds?

推荐答案

请注意文档中给出的有关optimize.minimize的示例中的示例:

Notice in the example given in the docs for optimize.minimize:

>>> bnds = ((0, None), (0, None))
>>> res = minimize(fun, (2, 0), method='SLSQP', bounds=bnds,
...                constraints=cons)

bnds是一个元组序列. len(bnds)等于初始猜测的长度x0，在示例中为(2, 0).

that bnds is a sequence of tuples. len(bnds) equals the length of the initial guess, x0, which in the example is (2, 0).

在您的代码中，bounds是一个元组列表的元组.需要将其展平为一系列元组，例如

In your code bounds is a tuple of lists of tuples. It needs to be flattened to a sequence of tuples, such as

bnds = bounds[0]+bounds[1]

或更简单地

bnds = [(0, 12000)]*22
x_max = optimize.minimize(f, x0.flatten(), method='SLSQP', bounds=bnds)

还请注意，bnds是22个二元组的列表，与该列表一致 是x0.flatten()中的22个项目:

Notice also that bnds is a list of 22 two-tuples, which is consistent with there being 22 items in x0.flatten():

In [19]: x0.flatten()
Out[19]: array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])

In [20]: len(x0.flatten())
Out[20]: 22

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