解释xy = np.column_stack((x, con))
时间: 2024-05-19 22:11:11 浏览: 16
这行代码使用了NumPy库中的column_stack函数,将两个一维数组x和con按列堆叠成一个二维数组。其中x和con的长度必须相等。假设x为长度为n的一维数组,con为长度为m的一维数组,则np.column_stack((x, con))返回一个n行2列的二维数组,其中第一列为x,第二列为con。
举个例子,假设x=[1,2,3],con=[4,5,6],则np.column_stack((x, con))返回的二维数组为:
[[1, 4],
[2, 5],
[3, 6]]
相关问题
X = np.column_stack()
This code snippet is incomplete as no arguments have been passed to the `column_stack()` function.
`np.column_stack()` is a NumPy function that takes a sequence of 1-D arrays and stacks them as columns to make a single 2-D array.
For example, if we have two arrays `a = [1, 2, 3]` and `b = [4, 5, 6]`, we can stack them horizontally as columns using `column_stack()`:
```
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
X = np.column_stack((a, b)) # X is now [[1, 4], [2, 5], [3, 6]]
```
np.column_stack
This function is part of the NumPy library in Python. It takes a sequence of arrays as input and stacks them horizontally to make a single array. For example, if you have two 1-dimensional arrays `a` and `b`, `np.column_stack((a,b))` will create a 2-dimensional array with `a` and `b` as its columns.
Here is an example:
```
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = np.column_stack((a, b))
print(c)
```
This will output:
```
[[1 4]
[2 5]
[3 6]]
```
Here, `c` is a 2-dimensional array with `a` and `b` as its columns.
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