Record arrays allow you to access fields as elements of an array using
arr.a and arr.b
numpy.recarray.trace () strong > is used to return the sum along the diagonal of an array.
numpy.recarray.trace (offset = 0, axis1 = 0, axis2 = 1, dtype = None, out = None)
offset: [int, optional] Offset of the diagonal from the main diagonal. Can be both positive and negative. Defaults to 0.
axis1: [int, optional] Axes to be used as the first and second axis of the 2-D sub-arrays from which the diagonals should be taken.
axis2: [int, optional] Axes to be used as the first and second axis of the 2-D sub-arrays from which the diagonals should be taken.
dtype : [optional] Determines the data-type of the returned array.
out: [ndarray, optional] A location into which the result is stored.
– & gt; If provided, it must have a shape that the inputs broadcast to.
– & gt; If not provided or None, a freshly-allocated array is returned.
Return: [ndarray] sum of a diagonal elements of the record array.
Code # 1:
# Python program explaining
# numpy.recarray.trace () method
# import numy as geek
numpy as geek
# create an input array with two different fields
int code >
, in_arr) code >
# convert it to an array of posts,
# using arr.view (np.recarray)
"Record array of float:"
"Record array of int:"
# using recarray.trace methods
# float array of records
rec_arr.a.trace ( )
"Output float traced array: "
# applying recarray.trace methods
# into an array of int records
" Output int traced array: "
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 float traced array: 10.0 Output int traced array: 6