Python 如何调用numpy数组中的元素？
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How to call an element in a numpy array?
提问by kame
This is a really simple question, but I didnt find the answer. How to call an element in an numpy array?
这是一个非常简单的问题，但我没有找到答案。如何调用numpy数组中的元素？
import numpy as np
arr = np.array([[1,2,3,4,5],[6,7,8,9,10]])
print arr(0,0)
The code above doesn't work.
上面的代码不起作用。
采纳答案by carl
Just use square brackets instead:
只需使用方括号：
print arr[1,1]
回答by alvas
TL;DR:
特尔；博士：
Using slicing:
使用切片：
>>> import numpy as np
>>>
>>> arr = np.array([[1,2,3,4,5],[6,7,8,9,10]])
>>>
>>> arr[0,0]
1
>>> arr[1,1]
7
>>> arr[1,0]
6
>>> arr[1,-1]
10
>>> arr[1,-2]
9
In Long:
在长：
Hopefully this helps in your understanding:
希望这有助于您的理解：
>>> import numpy as np
>>> np.array([ [1,2,3], [4,5,6] ])
array([[1, 2, 3],
[4, 5, 6]])
>>> x = np.array([ [1,2,3], [4,5,6] ])
>>> x[1][2] # 2nd row, 3rd column
6
>>> x[1,2] # Similarly
6
But to appreciate why slicingis useful, in more dimensions:
但是要了解为什么切片是有用的，在更多方面：
>>> np.array([ [[1,2,3], [4,5,6]], [[7,8,9],[10,11,12]] ])
array([[[ 1, 2, 3],
[ 4, 5, 6]],
[[ 7, 8, 9],
[10, 11, 12]]])
>>> x = np.array([ [[1,2,3], [4,5,6]], [[7,8,9],[10,11,12]] ])
>>> x[1][0][2] # 2nd matrix, 1st row, 3rd column
9
>>> x[1,0,2] # Similarly
9
>>> x[1][0:2][2] # 2nd matrix, 1st row, 3rd column
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
IndexError: index 2 is out of bounds for axis 0 with size 2
>>> x[1, 0:2, 2] # 2nd matrix, 1st and 2nd row, 3rd column
array([ 9, 12])
>>> x[1, 0:2, 1:3] # 2nd matrix, 1st and 2nd row, 2nd and 3rd column
array([[ 8, 9],
[11, 12]])
回答by imflash217
If you are using numpyand your array is an np.arrayof np.arrayelements like:
如果使用的是numpy和你的阵列是np.array的np.array相同的元素：
A = np.array([np.array([10,11,12,13]), np.array([15,16,17,18]), np.array([19,110,111,112])])
A = np.array([np.array([10,11,12,13]), np.array([15,16,17,18]), np.array([19,110,111,112])])
and you want to access the inner elements (like 10,11,12 13,14.......) then use:
并且您想访问内部元素（如10,11,12 13,14.......）然后使用：
A[0][0]instead of A[0,0]
A[0][0]代替 A[0,0]
For example:
例如：
>>> import numpy as np
>>>A = np.array([np.array([10,11,12,13]), np.array([15,16,17,18]), np.array([19,110,111,112])])
>>> A[0][0]
>>> 10
>>> A[0,0]
>>> Throws ERROR
(P.S.: Might be useful when using numpy.array_split())
（PS：使用时可能有用numpy.array_split()）
回答by u10405951
Also, you could try to use ndarray.item(), for example, arr.item((0, 0))(rowid+colid to index) or arr.item(0)(flatten index), its doc https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.item.html
此外，您可以尝试使用ndarray.item()例如arr.item((0, 0))(rowid+colid to index) 或arr.item(0)(flatten index)，其文档https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.item。 html
