我有一个5维矩阵。
我希望能够提取满足条件的某个（2d）切片的每一行中第一个值的索引，然后使用这些索引来提取另一个切片中相应索引的值。
以下是我的例子：
In [3]: g = np.arange(48400).reshape(20,11,11,2,10)
我正在使用的两个切片是：
In [4]: sliceA = g[0,:,:,0,0]
In [5]: sliceA
Out[5]:
array([[ 0, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200],
[ 220, 240, 260, 280, 300, 320, 340, 360, 380, 400, 420],
[ 440, 460, 480, 500, 520, 540, 560, 580, 600, 620, 640],
[ 660, 680, 700, 720, 740, 760, 780, 800, 820, 840, 860],
[ 880, 900, 920, 940, 960, 980, 1000, 1020, 1040, 1060, 1080],
[1100, 1120, 1140, 1160, 1180, 1200, 1220, 1240, 1260, 1280, 1300],
[1320, 1340, 1360, 1380, 1400, 1420, 1440, 1460, 1480, 1500, 1520],
[1540, 1560, 1580, 1600, 1620, 1640, 1660, 1680, 1700, 1720, 1740],
[1760, 1780, 1800, 1820, 1840, 1860, 1880, 1900, 1920, 1940, 1960],
[1980, 2000, 2020, 2040, 2060, 2080, 2100, 2120, 2140, 2160, 2180],
[2200, 2220, 2240, 2260, 2280, 2300, 2320, 2340, 2360, 2380, 2400]])
和我单独制作的一个，然后加入（为了说明目的）：
In [6]: sliceB = np.array([[ 3, 12, 21, 31, 41, 51, 69, 77, 83, 91, 100],
...: [ 6, 12, 23, 33, 43, 51, 69, 77, 83, 91, 100],
...: [ 8, 12, 27, 37, 47, 51, 69, 77, 83, 91, 100],
...: [ 4, 12, 28, 38, 48, 51, 69, 77, 83, 91, 100],
...: [ 7, 12, 29, 39, 49, 51, 69, 77, 83, 91, 100],
...: [ 9, 12, 22, 32, 42, 51, 69, 77, 83, 91, 100],
...: [ 6, 12, 21, 31, 41, 51, 69, 77, 83, 91, 100],
...: [ 8, 12, 25, 35, 45, 51, 69, 77, 83, 91, 100],
...: [ 5, 12, 26, 36, 46, 51, 69, 77, 83, 91, 100],
...: [ 7, 12, 22, 32, 42, 51, 69, 77, 83, 91, 100],
...: [ 3, 12, 24, 34, 44, 51, 69, 77, 83, 91, 100]])
In [11]: g[0,:,:,0,1] = sliceB
In [12]: g[0,:,:,0,1]
Out[12]:
array([[ 3, 12, 21, 31, 41, 51, 69, 77, 83, 91, 100],
[ 6, 12, 23, 33, 43, 51, 69, 77, 83, 91, 100],
[ 8, 12, 27, 37, 47, 51, 69, 77, 83, 91, 100],
[ 4, 12, 28, 38, 48, 51, 69, 77, 83, 91, 100],
[ 7, 12, 29, 39, 49, 51, 69, 77, 83, 91, 100],
[ 9, 12, 22, 32, 42, 51, 69, 77, 83, 91, 100],
[ 6, 12, 21, 31, 41, 51, 69, 77, 83, 91, 100],
[ 8, 12, 25, 35, 45, 51, 69, 77, 83, 91, 100],
[ 5, 12, 26, 36, 46, 51, 69, 77, 83, 91, 100],
[ 7, 12, 22, 32, 42, 51, 69, 77, 83, 91, 100],
[ 3, 12, 24, 34, 44, 51, 69, 77, 83, 91, 100]])
现在，我想在sliceB的每一行中创建满足条件（例如＆gt; = 35）的第一个元素的索引数组，即这些值：
array([[ 3, 12, 21, 31, *41*, 51, 69, 77, 83, 91, 100],
[ 6, 12, 23, 33, *43*, 51, 69, 77, 83, 91, 100],
[ 8, 12, 27, *37*, 47, 51, 69, 77, 83, 91, 100],
[ 4, 12, 28, *38*, 48, 51, 69, 77, 83, 91, 100],
[ 7, 12, 29, *39*, 49, 51, 69, 77, 83, 91, 100],
[ 9, 12, 22, 32, *42*, 51, 69, 77, 83, 91, 100],
[ 6, 12, 21, 31, *41*, 51, 69, 77, 83, 91, 100],
[ 8, 12, 25, *35*, 45, 51, 69, 77, 83, 91, 100],
[ 5, 12, 26, *36*, 46, 51, 69, 77, 83, 91, 100],
[ 7, 12, 22, 32, *42*, 51, 69, 77, 83, 91, 100],
[ 3, 12, 24, 34, *44*, 51, 69, 77, 83, 91, 100]])
然后使用它在sliceA中创建一个带有相应索引的值数组，即：
array([[ 0, 20, 40, 60, *80*, 100, 120, 140, 160, 180, 200],
[ 220, 240, 260, 280, *300*, 320, 340, 360, 380, 400, 420],
[ 440, 460, 480, *500*, 520, 540, 560, 580, 600, 620, 640],
[ 660, 680, 700, *720*, 740, 760, 780, 800, 820, 840, 860],
[ 880, 900, 920, *940*, 960, 980, 1000, 1020, 1040, 1060, 1080],
[1100, 1120, 1140, 1160, *1180*, 1200, 1220, 1240, 1260, 1280, 1300],
[1320, 1340, 1360, 1380, *1400*, 1420, 1440, 1460, 1480, 1500, 1520],
[1540, 1560, 1580, *1600*, 1620, 1640, 1660, 1680, 1700, 1720, 1740],
[1760, 1780, 1800, *1820*, 1840, 1860, 1880, 1900, 1920, 1940, 1960],
[1980, 2000, 2020, 2040, *2060*, 2080, 2100, 2120, 2140, 2160, 2180],
[2200, 2220, 2240, 2260, *2280*, 2300, 2320, 2340, 2360, 2380, 2400]])
我使用以下功能尝试了几个小时： np.amax，np.argmax，np.where，x [x> 34] .min（）
但似乎无法找到缺失的链接或组合。
为了提高速度，我想在没有循环的情况下这样做。
答案 0 :(得分：3)
我现在无法测试它，但它应该非常简单：
idx = np.argmax(sliceB >= 35, axis=1) # index of first occurrence of condition
sliceA[np.arange(sliceA.shape[0]), idx]
答案 1 :(得分：2)
这样的事情应该有效：
#First sort sliceA
tmp = np.argsort(sliceA,axis=1)
#Mask all indices that you dont want with values larger then any in the array
tmp[ sliceB<=34 ] = tmp.shape[-1]*2
#Find the minimum positions
min_pos = tmp.argmin(axis=1)
#Finally take the slice
print sliceA[np.arange(sliceA.shape[0]),min_pos]
[ 80 300 500 720 940 1180 1400 1600 1820 2060 2280]