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Numpy recarray.repeat() function | Python

Last Updated : 27 Sep, 2019
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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 : Python3
# 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)  
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. Python3
# 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)
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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