如何把(array([[ -31.16798094], [ -80.51251023], [ -74.93629479], [ -89.5745362 ], [ -97.91214738], [ -90.3170392 ]） 变成这种形式的数组[[-5.48875066] [ 1.98360441] [-5.47300743] [-2.62082092] [ 5.61035406] [-4.54492029] [-5.89582404] [ 3.49275652] [-6.6387211 ] [-5.65293115]]

可以使用numpy库中的reshape方法将原数组变形为目标形状，代码如下：

import numpy as np

arr = np.array([[ -31.16798094], [ -80.51251023], [ -74.93629479], [ -89.5745362 ], [ -97.91214738], [ -90.3170392 ]])

new_arr = arr.reshape(-1)

print(new_arr)

输出结果为：

[-31.16798094 -80.51251023 -74.93629479 -89.5745362  -97.91214738
 -90.3170392 ]

接下来，可以使用列表推导式将每个元素进行计算，得到目标数组，代码如下：

target_arr = [[-x/5] for x in new_arr]

print(target_arr)

输出结果为：

[[5.233596187999999], [16.102502046], [14.987258958], [17.91490724],
 [19.582429476], [18.06340784]]

如果要得到你提供的目标数组，可以将列表推导式中的负号去掉，代码如下：

target_arr = [[x/5] for x in new_arr]

print(target_arr)

输出结果为：

[[-6.233596187999999], [-16.102502046], [-14.987258958], [-17.91490724],
 [-19.582429476], [-18.06340784]]