shape mismatch: value array of shape (3,) could not be broadcast to indexing result of shape (15804,4)

This error occurs when you are trying to assign a value to an array using indexing, but the shape of the value array does not match the shape of the indexing result. In this case, the value array has a shape of (3,), which means it has three elements, but the indexing result has a shape of (15804,4), which means it has 15804 rows and 4 columns.

To fix this error, you need to make sure that the shape of the value array matches the shape of the indexing result. You can do this by reshaping the value array to match the indexing result, or by using different indexing techniques that result in a shape that matches the value array.

相关问题

ValueError: shape mismatch: value array of shape (3,) could not be broadcast to indexing result of shape (5732,4)

这个错误通常是由于尝试将一个形状不兼容的数组分配给另一个形状不同的数组引起的。在这种情况下，你正在尝试将形状为(3,)的值数组分配给形状为(5732, 4)的索引数组，因此出现了形状不匹配的错误。

要解决这个问题，你需要确保分配给索引数组的值具有与索引数组相同的形状。你可以通过调整值数组的形状或重新构造索引数组来解决这个问题。

如果你需要更具体的帮助，请提供更多上下文和代码，以便我更好地帮助你解决这个问题。

shape mismatch: value array of shape (6664,) could not be broadcast to indexing result of shape (6664,1)

This error occurs when there is a mismatch between the shape of the input array and the shape of the indexing result. In this case, the input array has a shape of (6664,), which means it has only one dimension with 6664 elements. However, the indexing result has a shape of (6664,1), which means it has two dimensions with 6664 rows and 1 column.

To fix this error, you need to reshape the input array to match the shape of the indexing result. You can do this by adding a new dimension to the input array using the numpy.newaxis attribute.

For example, if your input array is called arr, you can reshape it like this:

arr = arr[:, np.newaxis]

This will add a new dimension to the input array and reshape it to have a shape of (6664,1), which matches the shape of the indexing result.