У меня есть список m (вставленный в конце), состоящий из numpy массивов. Форма:
>> np.shape(m)
(23, 2)
После достижения 2-й вложенной глубины число массивов в списке списка изменяется между 1 или 2, например,
здесь есть один массив:
>> m[2][1]
[array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]
или два из них здесь:
>> m[2][0]
[array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 163, 164, 165, 166, 167, 168, 169,
180]),
array([150, 197, 217, 218, 220])]
Что бы я хотел сделать:
Если бы я oop превысил i, j и k следующим образом:
>>> for i in range(np.shape(m)[0]): # outer loop, from i=0 to i=22
for j in range(np.shape(m)[1]): # 1st nested loop, from j=0 to j=1
for k in range(np.shape(m[i][j])[0]): # 2nd nested loop, from k=0 to k=1, or just k=0
print ("i = ", i, "j = ", j, "k = ", k, "components = " ,m[i][j][k])
i = 0 j = 0 k = 0 components = [ 1 14 15 16 39 40 50 51 76 77 78 79 80 81 119 120 136 143
144 145 162 176 177 178 199 200 201 202 203 204 205 215]
### Are all of m[0][0][0] components seen further on in the m array?
i = 0 j = 1 k = 0 components = [ 1 14 15 16 39 40 50 51 76 77 78 79 80 81 119 120 136 143
162 176 177 178 215]
### Are all of m[0][1][0] components seen further on in the m array?
Как только мы достигли l oop сверх k, у нас есть уникальный список компонентов.
Я хотел бы получить i, j и k, где этот список компонентов повторяется далее в списке m.
Например, компоненты i=1, j=1, k=1 снова отображаются в i=2, j=0, k=0
>>> m[1][1][1]
array([150, 197, 217, 218, 220])
>>> m[2][0][0]
array([150, 197, 217, 218, 220])
И сохраните эту информацию в списке: t = [[1, 1, 1], [2, 0, 0]]
Что мне удалось сделать до сих пор:
Как только я достиг самый глубокий внутренний l oop сверх k, я думаю сделать это:
for i in range(np.shape(m)[0]): # outer loop, from i=0 to i=22
for j in range(np.shape(m)[1]): # 1st nested loop, from j=0 to j=1
for k in range(np.shape(m[i][j])[0]): # 2nd nested loop, from k=0 to k=1, or just k=0
print ("i = ", i, "j = ", j, "k = ", k, "components = " ,m[i][j][k])
list_search = m[i][j][k]
print ('list_search = ', list_search)
if np.all(list_search == m[i][j][k]):
print ("match: i = ", i, "; j= ", j, "; k = ", k)
if np.all(list_search == m[i][j][k]):
print ("match: i = ", i, "; j= ", j, "; k = ", k)
if np.all(list_search == m[i][j][k]):
print ("match: i = ", i, "; j= ", j, "; k = ", k)
Расположение этих операторов if np.all, кажется, не правильно, так как это приводит к нескольким совпадениям там, где они должны не быть Мне трудно понять, что не так.
m = [([np.array([ 1, 14, 15, 16, 39, 40, 50, 51, 76, 77, 78, 79, 80,
81, 119, 120, 136, 143, 144, 145, 162, 176, 177, 178, 199, 200,
201, 202, 203, 204, 205, 215])],
[np.array([ 1, 14, 15, 16, 39, 40, 50, 51, 76, 77, 78, 79, 80,
81, 119, 120, 136, 143, 162, 176, 177, 178, 215]),
np.array([144, 145, 199, 200, 201, 202, 203, 204, 205])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 163, 164, 165, 166, 167, 168, 169,
180]),
np.array([150, 197, 217, 218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 163, 164, 165, 166, 167, 168, 169,
180]),
np.array([150, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([132, 133, 163, 164, 165, 166, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])]),
([np.array([132, 133, 163, 164, 165, 166, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([132, 133, 163, 164, 165, 166, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])]),
([np.array([132, 133, 163, 164, 165, 166, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]),
([np.array([129, 130, 154, 155, 156, 157, 158, 159, 160]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([129, 130, 154, 155, 156, 157, 158, 159, 160]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]),
([np.array([129, 130, 154, 155, 156, 157, 158, 159, 160]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([129, 130, 154, 155, 156, 157, 158, 159, 160]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])]),
([np.array([129, 130, 154, 155, 156, 157, 158, 159, 160]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 132, 133, 149, 150, 163, 164, 165, 166, 167, 168,
169, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([129, 130, 132, 154, 155, 156, 157, 158, 159, 160, 163, 164, 166]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([ 6, 7, 35, 60, 61, 62, 63, 115, 133, 149, 150, 165, 167,
168, 169, 180, 197, 217, 218, 220])]),
([np.array([ 6, 7, 35, 60, 61, 62, 63, 115, 133, 149, 150, 165, 167,
168, 169, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 8, 22, 23, 25, 36, 43, 64, 65, 92, 93, 94, 95, 98,
99, 116, 123, 137, 161, 216]),
np.array([144, 145, 199, 200, 201, 202, 203, 204, 205])],
[np.array([ 8, 22, 23, 25, 36, 43, 64, 65, 92, 93, 94, 95, 98,
99, 116, 123, 137, 144, 145, 161, 199, 200, 201, 202, 203, 204,
205, 216])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([133, 165, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])]),
([np.array([133, 165, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 8, 22, 23, 25, 36, 43, 64, 65, 92, 93, 94, 95, 98,
99, 116, 123, 137, 144, 145, 161, 199, 200, 201, 202, 203, 204,
205, 216])],
[np.array([ 8, 22, 23, 25, 36, 43, 64, 65, 92, 93, 94, 95, 98,
99, 116, 123, 137, 161, 216]),
np.array([144, 145, 199, 200, 201, 202, 203, 204, 205])]),
([np.array([129, 130, 132, 154, 155, 156, 157, 158, 159, 160, 163, 164, 166]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])]),
([np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 129, 130, 132, 133, 149, 150, 154, 155, 156, 157,
158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 180, 197, 217,
218, 220])],
[np.array([129, 130, 132, 133, 154, 155, 156, 157, 158, 159, 160, 163, 164,
165, 166, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])]),
([np.array([129, 130, 132, 133, 154, 155, 156, 157, 158, 159, 160, 163, 164,
165, 166, 167, 168, 169])],
[np.array([129, 130, 132, 154, 155, 156, 157, 158, 159, 160, 163, 164, 166]),
np.array([133, 165, 167, 168, 169])]),
([np.array([133, 165, 167, 168, 169]),
np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 149, 150, 180, 197, 217, 218, 220])],
[np.array([ 6, 7, 9, 24, 35, 44, 60, 61, 62, 63, 66, 67, 96,
97, 115, 124, 133, 149, 150, 165, 167, 168, 169, 180, 197, 217,
218, 220])])]