Numpy recarray.repeat() function | Python

In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)], where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']. Record arrays allow the fields to be accessed as members of the array, using arr.a and arr.b.

numpy.recarray.repeat() function is used to repeat elements of record array.

Syntax : numpy.recarray.repeat(repeats, axis=None)



Parameters:
repeats : [int or array of ints] The number of repetitions for each element.
axis : [int or None] The axis along which to repeat values. If None, the array is flattened before repeating.

Return : [ndarray] Output array which has the same shape as record array, except along the given axis.

Code #1 :

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# Python program explaining
# numpy.recarray.repeat() method 
  
# importing numpy as geek
import numpy as geek
  
# creating input array with 2 different field 
in_arr = geek.array([[(5.0, 2), (3.0, -4), (6.0, 9)],
                     [(9.0, 1), (5.0, 4), (-12.0, -7)]],
                     dtype =[('a', float), ('b', int)])
  
print ("Input array : ", in_arr)
  
# convert it to a record array,
# using arr.view(np.recarray)
rec_arr = in_arr.view(geek.recarray)
print("Record array of float: ", rec_arr.a)
print("Record array of int: ", rec_arr.b)
  
# applying recarray.repeat methods
# to float record array along axis 1
out_arr = rec_arr.a.repeat(3, axis = 1)
print ("Output repeated float array along axis 1 : ", out_arr) 
  
# applying recarray.repeat methods
# to float record array along default axis 
out_arr = rec_arr.a.repeat(2)
print ("Output repeated float array along default axis : ", out_arr) 
  
# applying recarray.repeat methods
# to int record array along axis 0
out_arr = rec_arr.b.repeat(2, axis = 0)
print ("Output repeated int array along axis 0 : ", out_arr) 
  
# applying recarray.repeat methods
# to int record array along default
out_arr = rec_arr.b.repeat(2)
print ("Output repeated int array along default axis : ", out_arr)  

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Output:

Input array : [[( 5., 2) ( 3., -4) ( 6., 9)]
[( 9., 1) ( 5., 4) (-12., -7)]]
Record array of float: [[ 5. 3. 6.]
[ 9. 5. -12.]]
Record array of int: [[ 2 -4 9]
[ 1 4 -7]]

Output repeated float array along axis 1 : [[ 5. 5. 5. 3. 3. 3. 6. 6. 6.]
[ 9. 9. 9. 5. 5. 5. -12. -12. -12.]]
Output repeated float array along default axis : [ 5. 5. 3. 3. 6. 6. 9. 9. 5. 5. -12. -12.]
Output repeated int array along axis 0 : [[ 2 -4 9]
[ 2 -4 9]
[ 1 4 -7]
[ 1 4 -7]]
Output repeated int array along default axis : [ 2 2 -4 -4 9 9 1 1 4 4 -7 -7]

 

Code #2 :

We are applying numpy.recarray.repeat() to whole record array.

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# Python program explaining
# numpy.recarray.repeat() method 
  
# importing numpy as geek
import numpy as geek
  
# creating input array with 2 different field 
in_arr = geek.array([[(5.0, 2), (3.0, 4), (6.0, -7)],
                     [(9.0, 1), (6.0, 4), (-2.0, -7)]],
                     dtype =[('a', float), ('b', int)])
  
print ("Input record array : ", in_arr)
  
# convert it to a record array, 
# using arr.view(np.recarray)
rec_arr = in_arr.view(geek.recarray)
  
# applying recarray.repeat methods to  record array
out_arr = rec_arr.repeat(3)
  
print ("Output repeated record array : ", out_arr)

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Output:

Input record array : [[( 5., 2) ( 3., 4) ( 6., -7)]
[( 9., 1) ( 6., 4) (-2., -7)]]

Output repeated record array :
[( 5., 2) ( 5., 2) ( 5., 2) ( 3., 4) ( 3., 4) ( 3., 4) ( 6., -7)
( 6., -7) ( 6., -7) ( 9., 1) ( 9., 1) ( 9., 1) ( 6., 4) ( 6., 4)
( 6., 4) (-2., -7) (-2., -7) (-2., -7)]



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