Numpy recarray.compress() function | Python

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 :

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# 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) 

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Output:

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 :

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# 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) 

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Output:

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)]]


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