How to replace values in Numpy Ndarrays based on a sequence

Question

I have a numpy multidimensional array with sequences of zeros and ones. I want to replace the zero for any sequence 101. For example:

a = np.array([[0,0,1,0,1],[1,0,1,1,1], [1,1,1,1,1], [1,1,1,0,1]])

should become:

a = np.array([[0,0,1,1,1],[1,1,1,1,1], [1,1,1,1,1], [1,1,1,1,1]])

Divakar · Accepted Answer · 2019-02-18 20:18:29Z

2

We can use 2D convolution -

from scipy.signal import convolve2d

k = np.array([[1,0,1]]) # kernel for convolution
a[(convolve2d(a,k,'same')==2) & (a==0)] = 1

answered Feb 18, 2019 at 20:18

Divakar

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Phenomenon Over a year ago

Thanks. Using 2D convolution works for this case. Is there a way to solve this if the case changes? For example, replacing a sequence of [1,0.5, 0.5,1] with [1 0 0 1] anywhere in the ndarray.

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