删除Python中的方括号
我有这样的想法:删除Python中的方括号,python,python-3.x,list,flatten,Python,Python 3.x,List,Flatten,我有这样的想法: [[[-0.015, -0.1533, 1. ]] [[-0.0069, 0.1421, 1. ]] ... [[ 0.1318, -0.4406, 1. ]] [[ 0.2059, -0.3854, 1. ]]] 但是,我想删除剩余的方括号,如下所示: [[-0.015 -0.1533 1. ] [-0.0069 0.1421 1. ] ... [ 0.1318 -0.4406 1.
[[[-0.015, -0.1533, 1. ]]
[[-0.0069, 0.1421, 1. ]]
...
[[ 0.1318, -0.4406, 1. ]]
[[ 0.2059, -0.3854, 1. ]]]
但是,我想删除剩余的方括号,如下所示:
[[-0.015 -0.1533 1. ]
[-0.0069 0.1421 1. ]
...
[ 0.1318 -0.4406 1. ]
[ 0.2059 -0.3854 1. ]]
我的代码是:
XY = []
for i in range(4000):
Xy_1 = [round(random.uniform(-0.5, 0.5), 4), round(random.uniform(-0.5, 0.5), 4), 1]
Xy_0 = [round(random.uniform(-0.5, 0.5), 4), round(random.uniform(-0.5, 0.5), 4), 0]
Xy.append(random.choices(population=(Xy_0, Xy_1), weights=(0.15, 0.85)))
Xy = np.asarray(Xy)
尝试扩展方法
Xy.extend(random.choices(population=(Xy_0, Xy_1), weights=(0.15, 0.85)))
您可以使用从阵列中删除1个dim
>>> np.squeeze(Xy)
array([[ 0.3609, 0.2378, 0. ],
[-0.2432, -0.2043, 1. ],
[ 0.3081, -0.2457, 1. ],
...,
[ 0.311 , 0.03 , 1. ],
[-0.0572, -0.317 , 1. ],
[ 0.3026, 0.1829, 1. ]])
或
使用
>Xy.整形(4000,3)
数组([[0.3609,0.2378,0.],
[-0.2432, -0.2043, 1. ],
[ 0.3081, -0.2457, 1. ],
...,
[ 0.311 , 0.03 , 1. ],
[-0.0572, -0.317 , 1. ],
[ 0.3026, 0.1829, 1. ]])
>>>
您可以使用这个随机选项(总体=(Xy_0,Xy_1),权重=(0.15,0.85))[0]
XY=[]
对于范围(4000)内的i:
Xy_1=[圆形(随机.均匀(-0.5,0.5),4),圆形(随机.均匀(-0.5,0.5),4),1]
Xy_0=[圆形(随机.均匀(-0.5,0.5),4),圆形(随机.均匀(-0.5,0.5),4),0]
#肾盂道:-)
追加(随机选择(总体=(Xy_0,Xy_1),权重=(0.15,0.85))[0])
Xy=np.asarray(Xy)
打印(Xy)
输出
[[0.3948 0.0915 1]
[ 0.4197 -0.344 1. ]
[-0.4541 0.3192 1. ]
[ 0.3285 0.0453 1. ]
[-0.0171 -0.3088 1. ]
[ 0.2958 -0.2757 1. ]
[-0.1303 0.1581 0. ]
[-0.4146 -0.4454 1. ]
[ 0.0247 0.325 1. ]
[-0.227 0.139 1. ]]
您可以尝试使用sum
删除1dim
a=[ [[-0.015, -0.1533, 1. ]],
[[-0.0069, 0.1421, 1. ]],
...
[[ 0.1318, -0.4406, 1. ]],
[[ 0.2059, -0.3854, 1. ]] ]
sum(a,[])
'''
[[-0.015, -0.1533, 1. ],
[-0.0069, 0.1421, 1. ],
...
[ 0.1318, -0.4406, 1. ],
[ 0.2059, -0.3854, 1. ]]
'''
看看挤压:这能回答你的问题吗?对于python列表,我们可以使用
sum
来减少1dim,即sum(嵌套的列表,[])
将减少1dim。有关numpy数组,请参阅@BramVanroy@Georgy在评论中链接的内容