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I have a matrix with these dimensions (150,2) and I want to duplicate each row N times. I show what I mean with an example.

Input:

a = [[2, 3], [5, 6], [7, 9]]

suppose N= 3, I want this output:

[[2 3]
 [2 3]
 [2 3]
 [5 6]
 [5 6]
 [5 6]
 [7 9]
 [7 9]
 [7 9]]

Thank you.

Use np.repeat with parameter axis=0 as:

a = np.array([[2, 3],[5, 6],[7, 9]])

print(a)
[[2 3]
 [5 6]
 [7 9]]

r_a = np.repeat(a, repeats=3, axis=0)

print(r_a)
[[2 3]
 [2 3]
 [2 3]
 [5 6]
 [5 6]
 [5 6]
 [7 9]
 [7 9]
 [7 9]]

To create an empty multidimensional array in NumPy (e.g. a 2D array m*n to store your matrix), in case you don't know m how many rows you will append and don't care about the computational cost Stephen Simmons mentioned (namely re-buildinging the array at each append), you can squeeze to 0 the dimension to which you want to append to: X = np.empty(shape=[0, n]).

This way you can use for example (here m = 5 which we assume we didn't know when creating the empty matrix, and n = 2):

import numpy as np

 n = 2
 X = np.empty(shape=[0, n])

 for i in range(5):
 for j in range(2):
 X = np.append(X, [[i, j]], axis=0)

 print X

 which will give you:

 [[ 0. 0.]
 [ 0. 1.]
 [ 1. 0.]
 [ 1. 1.]
 [ 2. 0.]
 [ 2. 1.]
 [ 3. 0.]
 [ 3. 1.]
 [ 4. 0.]
 [ 4. 1.]]