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 :
# 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) |
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.
# 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) |
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)]
