a = np.array格式怎么相减
时间: 2023-11-23 09:17:20 浏览: 54
To subtract two NumPy arrays element-wise, you can simply use the subtraction operator `-` between the two arrays. Here's an example:
```python
import numpy as np
a = np.array([1, 2, 3])
b = np.array([2, 4, 6])
c = b - a
print(c)
```
Output:
```
[1 2 3]
```
In this example, we define two NumPy arrays `a` and `b` with the same length. Then, we subtract `a` from `b` using the `-` operator and store the result in a new NumPy array `c`. The resulting array `c` contains the element-wise difference between `b` and `a`, which is `[1, 2, 3]`.
Note that the two arrays `a` and `b` must have the same shape (i.e., the same number of elements) in order to be subtracted element-wise.
相关问题
24. 从二维数组a = np.array([[3,3,3],[4,4,4],[5,5,5]])中的每行减去一维数组b= np.array([1,2,3])中相应的值。
可以使用numpy库中的广播(broadcasting)机制来实现:
```python
import numpy as np
a = np.array([[3,3,3],[4,4,4],[5,5,5]])
b = np.array([1,2,3])
result = a - b.reshape(-1, 1)
print(result)
```
输出结果为:
```
[[2 2 2]
[2 2 2]
[2 2 2]]
```
其中,b.reshape(-1, 1)的作用是将一维数组b转化为列向量(3行1列),从而实现广播机制。将b与a进行相减时,b将被广播为3行3列的矩阵,然后再进行相减。
[x, y] = np.array([x, y]) - np.array([a, b])
这行代码的作用是将二维向量 `[x, y]` 减去另一个二维向量 `[a, b]`,得到的结果是一个新的二维向量。具体来说,它对应了以下的计算公式:
```
[x-a, y-b]
```
其中 `np.array([x, y])` 和 `np.array([a, b])` 分别表示二维向量 `[x, y]` 和 `[a, b]`,`-` 表示向量减法,即对应元素相减,最终得到一个新的二维向量 `[x-a, y-b]`。这个操作在计算机图形学、机器学习等领域中经常被用到。