For example I have the following array:
[0, 0, 0, 1, 0, 0, 0]
what I want is
[0, 0, 1, 1, 1, 0, 0]
If the 1 is at the at the end, for example [1, 0, 0, 0]
it should add only on one side [1, 1, 0, 0]
How do I add a 1 on either side while keeping the array the same length? I have looked at the numpy pad function, but that didn't seem like the right approach.
CodePudding user response:
You can use np.pad
to create two shifted copies of the array: one shifted 1 time toward the left (e.g. 0 1 0
-> 1 0 0
) and one shifted 1 time toward the right (e.g. 0 1 0
-> 0 0 1
).
Then you can add all three arrays together:
0 1 0
1 0 0
0 0 1
-------
1 1 1
Code:
output = a np.pad(a, (1,0))[:-1] np.pad(a, (0,1))[1:]
# (1, 0) says to pad 1 time at the start of the array and 0 times at the end
# (0, 1) says to pad 0 times at the start of the array and 1 time at the end
Output:
# Original array
>>> a = np.array([1, 0, 0, 0, 1, 0, 0, 0])
>>> a
array([1, 0, 0, 0, 1, 0, 0, 0])
# New array
>>> output = a np.pad(a, (1,0))[:-1] np.pad(a, (0,1))[1:]
>>> output
array([1, 1, 0, 1, 1, 1, 0, 0])
CodePudding user response:
One way using numpy.convolve
with mode == "same"
:
np.convolve([0, 0, 0, 1, 0, 0, 0], [1,1,1], "same")
Output:
array([0, 0, 1, 1, 1, 0, 0])
With other examples:
np.convolve([1,0,0,0], [1,1,1], "same")
# array([1, 1, 0, 0])
np.convolve([0,0,0,1], [1,1,1], "same")
# array([0, 0, 1, 1])
np.convolve([1,0,0,0,1,0,0,0], [1,1,1], "same")
# array([1, 1, 0, 1, 1, 1, 0, 0])