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.swapaxes()
function return a view of the array with axis1 and axis2 interchanged.
Syntax :
numpy.recarray.swapaxes(axis1, axis2)
Parameters:
axis1 : [int] First axis.
axis2 : [int] Second axis.Return : [ndarray] Resultant array.
Code #1 :
# Python program explaining # numpy.recarray.swapaxes() 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.swapaxes methods # to float record array taking axis1 = 0 and axis2 = 1 out_arr = rec_arr.a.swapaxes( 0 , 1 ) print ( "Output float array : " , out_arr) # applying recarray.swapaxes methods # to int record array taking axis1 = 1 and axis2 = 0 out_arr = rec_arr.b.swapaxes( 1 , 0 ) print ( "Output int array : " , 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 float array : [[ 5. 9.] [ 3. 5.] [ 6. -12.]] Output int array : [[ 2 1] [-4 4] [ 9 -7]]
Code #2 :
We are applying numpy.recarray.swapaxes()
to whole record array.
# Python program explaining # numpy.recarray.swapaxes() 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 array : " , in_arr) # convert it to a record array, # using arr.view(np.recarray) rec_arr = in_arr.view(geek.recarray) # applying recarray.swapaxes methods to # record array taking axis1 = 0 and axis2 = 1 out_arr = rec_arr.swapaxes( 1 , 0 ) print ( "Output record array : " , out_arr) |
Input array : [[( 5., 2) ( 3., 4) ( 6., -7)] [( 9., 1) ( 6., 4) (-2., -7)]] Output record array : [[( 5., 2) ( 9., 1)] [( 3., 4) ( 6., 4)] [( 6., -7) (-2., -7)]]