could not broadcast input array from shape (31,71) into shape (31,)
时间: 2024-05-26 20:12:22 浏览: 21
这个错误信息通常是由于在广播操作中形状不一致引起的。在 Numpy 中,广播操作需要所有参与计算的数组形状一致,或是在某一维度上的形状为 1 。你可以检查你的代码,在进行广播操作时是否有数组形状不一致的情况出现,或是某个数组的某个维度大小不为1。如果有,你可以使用 reshape 函数调整形状,或是使用 expand_dims 函数来添加维度,以满足广播的要求。
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 (2) into shape (1,35)
This error message indicates that there is a mismatch between the dimensions of two arrays that you are trying to merge or broadcast together. Specifically, you are trying to broadcast an array with shape (2) onto an array with shape (1, 35), which is not possible.
To resolve this error, you will need to reshape or resize one or both of the arrays so that they have compatible shapes. One approach might be to reshape the (2) array to have shape (1, 2) using the np.reshape() function, and then broadcast it onto the (1, 35) array.
For example:
```
import numpy as np
a = np.array([1, 2])
b = np.zeros((1, 35))
a_reshaped = np.reshape(a, (1, 2))
b[:a_reshaped.shape[0], :a_reshaped.shape[1]] += a_reshaped
print(b)
```
This code reshapes the (2) array to have shape (1, 2), and then adds it to the (1, 35) array using array indexing. The resulting output should be a (1, 35) array with the first two elements set to the values of the (2) array.
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