How to Copy/Repeat an Array N Times into a New Array

Create an array with same element repeated multiple times

You can do it like this:

function fillArray(value, len) {
  if (len == 0) return [];
  var a = [value];
  while (a.length * 2 <= len) a = a.concat(a);
  if (a.length < len) a = a.concat(a.slice(0, len - a.length));
  return a;
}

It doubles the array in each iteration, so it can create a really large array with few iterations.

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Note: You can also improve your function a lot by using push instead of concat, as concat will create a new array each iteration. Like this (shown just as an example of how you can work with arrays):

function fillArray(value, len) {
  var arr = [];
  for (var i = 0; i < len; i++) {
    arr.push(value);
  }
  return arr;
}

How to 'repeat' an array n times

You could do this:

var repeated = [].concat(... new Array(100).fill([1, 2, 3]));

That creates an array of a given length (100 here) and fills it with the array to be repeated ([1, 2, 3]). That array is then spread as the argument list to [].concat().

Oh wait just

var repeated = new Array(100).fill([1, 2, 3]).flat();

would be a little shorter.

repeating a numpy array N times

This is what you want:

x=np.concatenate([my_input_array, my_input_array, my_input_array])
for i in x:
    print(i)

Output:

-1.02295637
-0.60583836
-0.42240581
-0.78376377
-0.85821456
-1.02295637
-0.60583836
-0.42240581
-0.78376377
-0.85821456
-1.02295637
-0.60583836
-0.42240581
-0.78376377
-0.85821456

Repeat a 2D NumPy array N times

By my tests, np.repeat is a little faster than np.tile:

X = np.repeat(arr[None,:], 3, axis=0)

Alternatively, use np.concatenate:

X = np.concatenate([[arr]] * 3, axis=0)

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arr = np.arange(10000 * 1000).reshape(10000, 1000)

%timeit np.repeat(arr[None,:], 3, axis=0)
%timeit np.tile(arr, (3, 1, 1))
%timeit np.concatenate([[arr]] * 3, axis=0)
# Read-only, array cannot be modified.
%timeit np.broadcast_to(arr, (3, *arr.shape))
# Creating copy of the above.
%timeit np.broadcast_to(arr, (3, *arr.shape)).copy()

170 ms ± 3.82 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
187 ms ± 3.12 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
243 ms ± 3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
10.9 µs ± 218 ns per loop (mean ± std. dev. of 7 runs, 100000 loops 
189 ms ± 2.45 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)each) 

np.array_equals(np.repeat(arr[None,:], 3, axis=0), 
                np.tile(arr, (3, 1, 1))
True

Creating a list repeated n times using an existing variable which is mutable

You can just use .copy():

import numpy as np


R = np.array([[2,3,0], [6,78,8],[1,2,3]])
U = [R.copy() for _ in range(3)]

U[1][2,2] = 0

print(U)

Gives:

[array([[ 2,  3,  0],
       [ 6, 78,  8],
       [ 1,  2,  3]]),
 array([[ 2,  3,  0],
       [ 6, 78,  8],
       [ 1,  2,  0]]),
 array([[ 2,  3,  0],
       [ 6, 78,  8],
       [ 1,  2,  3]])]

Repeat ndarray n times

Use np.tile

>>> a = np.array([True, True, False])
>>> np.tile(a, 3)
... array([ True,  True, False,  True,  True, False,  True,  True, False])

Python: How to fill an array with x repeated n times?

This can be done using a simple one-liner using np.concatenate:

data = np.concatenate([np.repeat(i, j) for i, j in zip(x, n)])

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