could not broadcast input array from shape (50,9) into shape (9,)
时间: 2024-06-07 09:07:48 浏览: 20
这个错误通常发生在你试图将一个形状为 (50, 9) 的数组广播(broadcast)到一个形状为 (9,) 的数组时。广播是一种 NumPy 中的机制,用于在某些情况下自动将形状不同的数组进行转换,以使它们具有相同的形状,从而可以进行运算。但是,在某些情况下,由于不同数组的形状不兼容,广播操作会失败,就会出现这个错误。
当你遇到这个错误时,首先需要检查你的代码中涉及到的所有数组的形状是否正确。如果你确认数组的形状是正确的,那么可能是因为你正在进行某些操作,而这些操作要求数组具有相同的形状。在这种情况下,你可以尝试使用 NumPy 中的一些函数(如 reshape、transpose、tile 等)来调整数组的形状,以使其与其他数组兼容。如果你无法解决问题,请提供更多的代码和具体的错误信息以便我更好地帮助你。
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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