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.compress() function return selected slices of an array along given axis.
Syntax :
numpy.recarray.compress(condition, axis=None, out=None)Parameters:
condition : [1-D array of bool] Array that selects which entries to return.
axis : [int, optional] Axis along which to take slices.
out : Results will be placed in this array.Return : compressed_array, ndarray.
Code #1 :
# Python program explaining # numpy.recarray.compress() 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 int: ", rec_arr.b) # applying recarray.compress methods to float record array float_rec_arr = rec_arr.a print("Record array of float: ", float_rec_arr) out_arr = (rec_arr.a).compress([0, 1], axis = 0) print ("Output compressed array : ", out_arr) # applying recarray.compress methods to int record array int_rec_arr = rec_arr.b print("Record array of int: ", int_rec_arr) out_arr = int_rec_arr.compress([True, False], axis = 1) print ("Output compressed array : ", out_arr) |
Input array : [[(5.0, 2) (3.0, -4) (6.0, 9)] [(9.0, 1) (5.0, 4) (-12.0, -7)]] Record array of int: [[ 2 -4 9] [ 1 4 -7]] Record array of float: [[ 5. 3. 6.] [ 9. 5. -12.]] Output compressed array : [[ 9. 5. -12.]] Record array of int: [[ 2 -4 9] [ 1 4 -7]] Output compressed array : [[2] [1]]
Code #2 :
# Python program explaining # numpy.recarray.compress() 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 int: ", rec_arr.b) # applying recarray.compress methods to whole record array out_arr = rec_arr.compress([True, False], axis = 1) print ("Output compressed array : ", out_arr) |
Input array : [[(5.0, 2) (3.0, -4) (6.0, 9)] [(9.0, 1) (5.0, 4) (-12.0, -7)]] Record array of int: [[ 2 -4 9] [ 1 4 -7]] Output compressed array : [[(5.0, 2)] [(9.0, 1)]]
