ValueError: object too deep for desired array while using convolution

Question

I\'m trying to do this:

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

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

Y looks like this:

Answer 1

np.convolve needs a flattened array as one of it's inputs, you can use numpy.ndarray.flatten() which is quite fast, find it here.

Answer 2

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).

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).

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.

Answer 3

You could try using scipy.ndimage.convolve it allows convolution of multidimensional images. here is the docs

Answer 4

np.convolve() takes one dimension array. You need to check the input and convert it into 1D.

You can use the np.ravel(), to convert the array to one dimension.