How to replicate array to specific length array

Question

I want replicate a small array to specific length array

Example:

var = [22,33,44,55] # ==> len(var) = 4
n = 13

The new array that I want would be:

var_new = [22,33,44,55,22,33,44,55,22,33,44,55,22]

This is my code:

import numpy as np
var = [22,33,44,55]
di = np.arange(13)
var_new = np.empty(13)
var_new[di] = var

I get error message:

DeprecationWarning: assignment will raise an error in the future, most likely because your index result shape does not match the value array shape. You can use arr.flat[index] = values to keep the old behaviour.

But I get my corresponding variable:

var_new
array([ 22.,  33.,  44.,  55.,  22.,  33.,  44.,  55.,  22.,  33.,  44.,
    55.,  22.])

So, how to solve the error? Is there an alternative?

_{See also Repeat list to max number of elements for general methods not specific to Numpy.}

_{See also Circular list iterator in Python for lazy iteration over such data.}

Asked By: delta27

||

Source

Answer 1

First of all, you don’t get an error, but a warning, that var_new[di] = var is deprecated if var_new[di] has dimensions that do not match var.

Second, the error message tells what to do: use

var_new[di].flat = var

and you do not get a warning any more and it is guaranteed to work.

Another, easy way to do this if numpy is not needed is to just use itertools:

>>> import itertools as it
>>> var = [22, 33, 44, 55]
>>> list(it.islice(it.cycle(var), 13))
[22, 33, 44, 55, 22, 33, 44, 55, 22, 33, 44, 55, 22]

Answered By: Antti Haapala — Слава Україні

Answer 2

There are better ways to replicate the array, for example you could simply use np.resize:

Return a new array with the specified shape.

If the new array is larger than the original array, then the new array is filled with repeated copies of a. […]

>>> import numpy as np
>>> var = [22,33,44,55]
>>> n = 13
>>> np.resize(var, n)
array([22, 33, 44, 55, 22, 33, 44, 55, 22, 33, 44, 55, 22])

Answered By: MSeifert

Answer 3

Copy the array (called lists in python) with [:] because they are mutable. The python short cut is then just to multiply the copy and add one more
element.

>>> var = [22, 33, 44, 55]
>>> n = 3
>>> newlist = var[:]*n + var[:1]

gives the 13 elements you want.

Answered By: Hillsie

Answer 4

var = [22,33,44,55]
n = 13

Repeating a list (or any other iterable) can be done without numpy, using itertools‘s cycle() and islice() functions

from itertools import cycle, islice
var_new = list(islice(cycle(var),0,n)

Answered By: Uri Goren

How to replicate array to specific length array

Question:

Answers: