时间戳

首页 > 解决方案 > 将列表值列表分组到相等距离的 bin 中

python - 将列表值列表分组到相等距离的 bin 中

问题描述

在此之后，我设法将 1 个列表值分组到相等的距离箱中：

y = list(range(100))
def list_grouper(long_list, bins_number):
    bins = np.linspace(min(long_list), max(long_list), bins_number)
    bins_idx = np.digitize(long_list, bins)
    bins_idx = bins_idx -1 
    
    return bins_idx    
    
list_grouper(y, 20)

>>>array([ 0,  0,  0,  0,  0,  0,  1,  1,  1,  1,  1,  2,  2,  2,  2,  2,  3,
        3,  3,  3,  3,  4,  4,  4,  4,  4,  4,  5,  5,  5,  5,  5,  6,  6,
        6,  6,  6,  7,  7,  7,  7,  7,  8,  8,  8,  8,  8,  9,  9,  9,  9,
        9,  9, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12,
       13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 16,
       16, 16, 16, 16, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 19])

有没有办法在列表列表上做同样的事情？

list_of_lists = [list(range(20)), list(range(10, 40)), list(range(40, 60))]

这样在划分为相等距离（而不是每个列表的值分别）时，将考虑所有值（来自所有列表），但每个列表仍然是分开的？
例如

list_of_lists_output = [[0,0,0,0,1,1,1...], [5,5...], [8...]]

更新：
@Giacomo 方法几乎可以工作。如果列表具有相同数量的值，它会起作用。否则我会收到这两个错误：

list_of_lists = [list(range(20)), list(range(10, 40)), list(range(40, 60))]
list_of_lists = np.array(list_of_lists)
list_grouper2(list_of_lists, 5)

>>>ValueError: object too deep for desired array

或这个：

list_of_lists = [list(range(20)), list(range(10, 40))]
list_of_lists = np.array(list_of_lists)
list_grouper2(list_of_lists, 5)
>>>ValueError: operands could not be broadcast together with shapes (30,) (20,)

标签： pythonlist

解决方案

像这样的东西应该只适用于确定形状的数组

list_grouper(long_list, bins_number):

   temp = long_list.reshape(-1)
   bins = np.linspace(min(temp), max(temp), bins_number)
   bins_idx = np.digitize(long_list, bins)
   bins_idx = bins_idx -1 

   return bins_idx 

list_of_lists = np.array([list(range(20)), list(range(20,40))]) #shape (2,20)
one_lists = np.array([list(range(20))])

print("List of lists:")
print(list_grouper(list_of_lists, 20))

#List of lists:
#[[ 0  0  0  1  1  2  2  3  3  4  4  5  5  6  6  7  7  8  8  9]
#[ 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19]]

print("One list:")
print(list_grouper(one_lists, 20))

#One list:
#[[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]]

在处理可变大小数组时，一般的解决方案可能是

def list_grouper(long_list, bins_number):

   temp = np.concatenate(long_list, axis=0)
   bins = np.linspace(min(temp), max(temp), bins_number)

   toret = [np.digitize(i, bins) -1 for i in long_list]

   return toret  

list_of_lists = np.array([list(range(20)), list(range(20,60)), 
                              list(range(90,100))])
print(list_grouper(list_of_lists, 20))

#[array([0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3]), array([ 3,  4,  4,  4,  4,  4,  4,  5,  5,  5,  5,  5,  6,  6,  6,  6,  6,
#    7,  7,  7,  7,  7,  8,  8,  8,  8,  8,  9,  9,  9,  9,  9,  9, 10,
#   10, 10, 10, 10, 11, 11]), array([17, 17, 17, 17, 18, 18, 18, 18, 18, 19])]

希望最终能奏效！

推荐阅读