Repeating each element of a numpy array 5 times

by 
In [1]: data = np.arange(-50,50,10)

To repeat each element 5 times use np.repeat:

In [3]: np.repeat(data, 5)
Out[3]: 
array([-50, -50, -50, -50, -50, -40, -40, -40, -40, -40, -30, -30, -30,
       -30, -30, -20, -20, -20, -20, -20, -10, -10, -10, -10, -10,   0,
         0,   0,   0,   0,  10,  10,  10,  10,  10,  20,  20,  20,  20,
        20,  30,  30,  30,  30,  30,  40,  40,  40,  40,  40])

To repeat the array 5 times use np.tile:

In [2]: np.tile(data, 5)
Out[2]: 
array([-50, -40, -30, -20, -10,   0,  10,  20,  30,  40, -50, -40, -30,
       -20, -10,   0,  10,  20,  30,  40, -50, -40, -30, -20, -10,   0,
        10,  20,  30,  40, -50, -40, -30, -20, -10,   0,  10,  20,  30,
        40, -50, -40, -30, -20, -10,   0,  10,  20,  30,  40])

Note, however, that sometimes you can take advantage of NumPy broadcasting instead of creating a larger array with repeated elements.

For example, if

z = np.array([1, 2])
v = np.array([[3], [4], [5]])

then to add these arrays to produce

 [[4 5]
  [5 6]
  [6 7]]

you do not need to use tile:

In [12]: np.tile(z, (3,1))
Out[12]: 
array([[1, 2],
       [1, 2],
       [1, 2]])

In [13]: np.tile(v, (1,2))
Out[13]: 
array([[3, 3],
       [4, 4],
       [5, 5]])

In [14]: np.tile(z, (3,1)) + np.tile(v, (1,2))
Out[14]: 
array([[4, 5],
       [5, 6],
       [6, 7]])

Instead, NumPy will broadcast the arrays for you:

In [15]: z + v
Out[15]: 
array([[4, 5],
       [5, 6],
       [6, 7]])

More Related Contents:

  1. Is there a NumPy function to return the first index of something in an array?
  2. Understanding NumPy’s einsum
  3. Intuition and idea behind reshaping 4D array to 2D array in NumPy
  4. Is there any numpy group by function?
  5. Computing the correlation coefficient between two multi-dimensional arrays
  6. Removing nan values from an array
  7. Why is numpy’s einsum faster than numpy’s built in functions?
  8. How to return 0 with divide by zero
  9. Reshape an array in NumPy
  10. Efficiently return the index of the first value satisfying condition in array
  11. How to save and load numpy.array() data properly?
  12. How do I access the ith column of a NumPy multidimensional array?
  13. Interweaving two numpy arrays
  14. python how to pad numpy array with zeros
  15. How can I check if one two-dimensional NumPy array contains a specific pattern of values inside it?
  16. Finding the consecutive zeros in a numpy array
  17. Numpy ValueError: setting an array element with a sequence. This message may appear without the existing of a sequence?
  18. Numpy: Fix array with rows of different lengths by filling the empty elements with zeros
  19. Numpy – add row to array
  20. How to split/partition a dataset into training and test datasets for, e.g., cross validation?
  21. Selecting Random Windows from Multidimensional Numpy Array Rows
  22. Find elements of array one nearest to elements of array two
  23. how to perform max/mean pooling on a 2d array using numpy
  24. How to find the index of a value in 2d array in Python?
  25. find and delete from more-dimensional numpy array
  26. Initialise numpy array of unknown length
  27. Creating same random number sequence in Python, NumPy and R
  28. Why does numpy.linalg.solve() offer more precise matrix inversions than numpy.linalg.inv()?
  29. load csv into 2D matrix with numpy for plotting
  30. Convert list of lists with different lengths to a numpy array [duplicate]

Leave a Comment