How to replicate array to specific length array
numpy, python, python-3.x, replication
Solution
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])
Problem
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.