Conditional Numpy slicing and append to another array

Question

I have two numpy arrays in Python.

vec_1 = np.array([2.3, 1.4, 7.3, 1.8, 0, 0, 0])
vec_2 = np.array([29, 7, 5.8, 2.4, 6.7, 5, 8])

I am wanting a slice from vec_1 where the slice would be all 0's (except the last one) plus the preceding (Non 0) value so that the slice from vec_1 would be:

slice = ([1.8,0,0])

The slice would replace the last x elements of vec_2 so that it would look like so:

vec_2 = ([29, 7, 5.8, 2.4, 1.8, 0, 0])

vec_2's last 3 elements in this example are replaced by the slice from vec_1. Lastly, how could this be made dynamic so that slice lengths are determined in step 1 and then replace the last x elements in vec_2. When a 0 is observed in vec_1, it will be 0 from that point to the end of the array.

DDaly · Accepted Answer · 2021-03-05 23:11:07Z

1

import numpy as np

vec_1 = np.array([2.3, 1.4, 7.3, 1.8, 0, 0, 0])
vec_2 = np.array([29, 7, 5.8, 2.4, 6.7, 5, 8])

##Take the lowest value where 0 appears in vec_1 and subtract 1. :-1 to remove the last 0
vec_1_slice = vec_1[np.where(vec_1 == 0)[0][0] - 1:-1]

##Remove the last however many digits are in vec_1_slice then add vec_1_slice
vec_2 = np.append(vec_2[:-len(vec_1_slice)], vec_1_slice)

Output

vec_2
Out[237]: array([29. ,  7. ,  5.8,  2.4,  1.8,  0. ,  0. ])

answered Mar 5, 2021 at 23:11

DDaly

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1 Comment

brodo80 Over a year ago

Tested this solution and works well. Thank You!

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