ValueError:使用卷积时对象对于所需数组而言太深 [英] ValueError: object too deep for desired array while using convolution

问题描述

我正在尝试这样做:

h = [0.2,0.2,0.2,0.2,0.2]

Y = np.convolve(Y, h, "same")

Y看起来像这样:

执行此操作时出现此错误:

While doing this I get this error:

ValueError: object too deep for desired array

这是为什么?

我的猜测是因为convolve函数无法将Y视为一维数组.

My guess is because somehow the convolve function does not see Y as a 1D array.

推荐答案

屏幕截图中的Y数组不是一维数组，而是具有300行和1列的2D数组，如其shape所示(300, 1).

The Y array in your screenshot is not a 1D array, it's a 2D array with 300 rows and 1 column, as indicated by its shape being (300, 1).

要删除额外的维，可以将数组切片为Y[:, 0].要将n维数组通常转换为1D，可以使用np.reshape(a, a.size).

To remove the extra dimension, you can slice the array as Y[:, 0]. To generally convert an n-dimensional array to 1D, you can use np.reshape(a, a.size).

将2D数组转换为1D的另一个选项是numpy.ndarray模块的flatten()函数，不同之处在于它复制了数组.

Another option for converting a 2D array into 1D is flatten() function from numpy.ndarray module, with the difference that it makes a copy of the array.

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