ValueError: non-broadcastable output operand with shape (110,1) doesn't match the broadcast shape (110,4)

这个错误通常会在使用numpy的广播机制时出现。它表示输出操作数的形状不可广播到给定的形状。

例如，如果你在一个形状为(110,1)的数组上执行乘法，它将无法广播到形状为(110,4)的数组。这是因为这两个形状无法对齐。

解决办法通常是将两个数组形状对齐，或者重构数组以使其可以广播。你可以使用numpy的reshape函数或者transpose函数来实现这一点。

如果你需要更具体的解决方案，请提供更多的上下文和代码。

相关问题

ValueError: non-broadcastable output operand with shape (1640,1) doesn't match the broadcast shape (1640,4)

This error occurs when you are trying to perform a mathematical operation that cannot be broadcasted to the output shape. In this case, the output operand has shape (1640,1) but the broadcast shape is (1640,4).

To fix this error, you can reshape the output operand to match the broadcast shape using the numpy.reshape() function. For example:

import numpy as np

# create a matrix with shape (1640, 4)
a = np.ones((1640, 4))

# create an output operand with shape (1640, 1)
b = np.ones((1640, 1))

# reshape the output operand to match the broadcast shape
b = b.reshape(1640, 4)

# perform the mathematical operation
c = a + b

In this example, we reshape the output operand `b` to have shape (1640, 4) using the `reshape()` function. Now, we can perform the mathematical operation without getting the ValueError.

ValueError: non-broadcastable output operand with shape (45,1) doesn't match the broadcast shape (45,5)

This error occurs when you are trying to perform an operation that requires two arrays to have the same shape, but they do not. Specifically, the error message is telling you that you are trying to assign the result of an operation to an array with shape (45,1), but the operation result has shape (45,5), which cannot be broadcast to match the shape of the output array.

To fix this error, you need to make sure that the arrays you are working with have compatible shapes. One possible solution is to reshape the output array to match the shape of the operation result. For example:

import numpy as np

a = np.random.rand(45, 5)
b = np.random.rand(45, 1)

c = a * b.reshape(45, 1)

In this example, we reshape the array `b` to have shape (45, 1) so that it can be broadcast with `a`. The result of the multiplication is an array with shape (45, 5), but we can reshape it to have shape (45, 1) by taking the sum of each row:

d = c.sum(axis=1, keepdims=True)

Now `d` has shape (45, 1) and can be assigned to an array with the same shape.