could not broadcast input array from shape(64,) into shape(6,))
时间: 2023-11-29 20:03:37 浏览: 37
这个错误通常是因为你正在尝试将形状不同的数组广播到一起。在 NumPy 中,当你尝试对形状不同的数组进行操作时,NumPy 会尝试将其广播到一个共同的形状,以便能够进行操作。
在这种情况下,你正在尝试将形状为 (64,) 的数组广播到形状为 (6,) 的数组中,这是不可能的。你需要确保你的数组形状相同或可以广播到相同的形状。你可以通过使用 reshape() 函数或者对数组进行切片等方法来改变数组的形状。
如果你仍然无法解决问题,请提供更多上下文或代码,以便更好地帮助你解决问题。
相关问题
could not broadcast input array from shape (12) into shape (16)
This error message indicates that you are trying to perform a broadcasting operation on two NumPy arrays that have incompatible shapes. Specifically, you are trying to broadcast an array with 12 elements into an array with 16 elements, which is not possible.
To fix this error, you need to ensure that the shapes of the arrays are compatible for broadcasting. One way to do this is to reshape the array with 12 elements to have the same shape as the array with 16 elements, or vice versa.
For example, if you have an array with shape (12,) and you want to broadcast it with an array with shape (4, 4), you can reshape the first array to have shape (4, 3) using the `reshape` method:
```python
import numpy as np
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
b = np.zeros((4, 4))
a_reshaped = a.reshape((4, 3))
result = a_reshaped + b
```
Alternatively, you could reshape the second array to have shape (12,) using the `flatten` method:
```python
import numpy as np
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
b = np.zeros((4, 4))
b_flat = b.flatten()
result = a + b_flat
```
Both of these approaches will ensure that the arrays have compatible shapes for broadcasting.
could not broadcast input array from shape (72,1) into shape (72,)
这个错误通常是由于数组的形状不匹配导致的。在 NumPy 中,(72,1) 的形状表示一个二维数组,而 (72,) 的形状表示一个一维数组。当你尝试广播不同形状的数组时,就会出现这个错误。
解决这个问题的方法之一是使用 `numpy.squeeze()` 函数来移除数组中的单维度,从而将形状从 (72,1) 转换为 (72,)。例如:
```
import numpy as np
a = np.ones((72, 1))
b = np.arange(72)
c = a + b # 报错:could not broadcast input array from shape (72,1) into shape (72,)
a = np.squeeze(a)
c = a + b # 正常运行
```
另一种方法是使用 `numpy.reshape()` 函数来显式地调整数组的形状。例如:
```
import numpy as np
a = np.ones((72, 1))
b = np.arange(72)
c = a.reshape(72) + b # 正常运行
```
这两种方法都可以解决这个问题,具体使用哪一种取决于你的实际情况。
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