Having this numpy array:
[[0 1 2]
[3 4 5]
[6 7 8]]
How do I duplicate for example row 1 so I get the below?:
[[0 1 2]
[3 4 5]
[3 4 5]
[6 7 8]]
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2 Answers
Approach #1
One approach with np.insert -
np.insert(a,2,a[1],axis=0)
For duplicating columns, use it along axis=1 -
np.insert(a,2,a[:,1],axis=1)
Put as functions to have generic number of duplications -
def dup_rows(a, indx, num_dups=1):
return np.insert(a,[indx+1]*num_dups,a[indx],axis=0)
def dup_cols(a, indx, num_dups=1):
return np.insert(a,[indx+1]*num_dups,a[:,[indx]],axis=1)
Sample run -
In [82]: a
Out[82]:
array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8]])
In [83]: np.insert(a,2,a[1],axis=0)
Out[83]:
array([[0, 1, 2],
[3, 4, 5],
[3, 4, 5],
[6, 7, 8]])
In [141]: np.insert(a,2,a[:,1],axis=1)
Out[141]:
array([[0, 1, 1, 2],
[3, 4, 4, 5],
[6, 7, 7, 8]])
Generic case runs -
In [255]: a
Out[255]:
array([[19, 65, 87, 46, 85],
[18, 45, 90, 26, 31],
[49, 35, 34, 62, 24],
[47, 85, 63, 91, 33],
[54, 37, 89, 79, 50],
[53, 54, 66, 59, 38]])
In [256]: dup_rows(a, indx=4, num_dups=3)
Out[256]:
array([[19, 65, 87, 46, 85],
[18, 45, 90, 26, 31],
[49, 35, 34, 62, 24],
[47, 85, 63, 91, 33],
[54, 37, 89, 79, 50],
[54, 37, 89, 79, 50],
[54, 37, 89, 79, 50],
[54, 37, 89, 79, 50],
[53, 54, 66, 59, 38]])
In [253]: dup_cols(a, indx=2, num_dups=2)
Out[253]:
array([[19, 65, 87, 87, 87, 46, 85],
[18, 45, 90, 90, 90, 26, 31],
[49, 35, 34, 34, 34, 62, 24],
[47, 85, 63, 63, 63, 91, 33],
[54, 37, 89, 89, 89, 79, 50],
[53, 54, 66, 66, 66, 59, 38]])
Approach #2
Another with np.repeat -
In [102]: reps = np.ones(a.shape[0],dtype=int)
In [103]: reps[1] = 2 # duplication factor
In [104]: np.repeat(a,reps,axis=0)
Out[104]:
array([[0, 1, 2],
[3, 4, 5],
[3, 4, 5],
[6, 7, 8]])
Comments
By oversampling the index?
>>> import numpy as np
>>> a = np.arange(9).reshape(3,3)
>>> a
array([[0, 1, 2],
[3, 4, 5],
[6, 7, 8]])
>>>
>>> a[[0,1,1,2]]
array([[0, 1, 2],
[3, 4, 5],
[3, 4, 5],
[6, 7, 8]])
