python - scipy.optimize.lsq_linear 边界错误

Question

我正在尝试计算以下公式:

http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.lsq_linear.html#scipy.optimize.lsq_linear

我有以下代码，但它不会接受 6 个单独变量的边界，它只会接受一个元组，这使得所有变量的边界都相同。

## cut benchmark out of data
benchmark_ser = data_df.ix[:,0]
##  get out the stocks data
stocks_df = data_df.ix[:,1:]

## create/get bounds
bds = (0,.2) # <- i want to change this line 
             #    to something that will provide 
             #    a bound for each variable like 
             #    [(0,.1),(0,.2),(0,.5),(0,.6)]

wgt_arr = sp.optimize.lsq_linear(stocks_df, benchmark_ser, bds)

我目前收到以下错误:

ValueError: 'bounds' must contain 2 elements.

谢谢

Answer 1

来自docs (强调我的):

bounds : 2-tuple of array_like, optional

Lower and upper bounds on independent variables. Defaults to no bounds. Each array must have shape (n,) or be a scalar, in the latter case a bound will be the same for all variables. Use np.inf with an appropriate sign to disable bounds on all or some variables.

因此，与其给它一个 (lower_bound, upper_bound) 元组列表，您需要一个包含两个类数组对象的元组:(1) 所有下限和 (2) 所有上限

尝试改变

bds = [(0,.1),(0,.2),(0,.5),(0,.6)]

到

bds = ([0., 0., 0., 0.], [.1, .2, .5, .6])