Numpy recarray.all () function | python

Arrays | NumPy | Python Methods and Functions

In general, arrays can have data types that contain fields similar to columns in a spreadsheet. An example is [(a, int), (b, float)] , where each entry in the array is a pair (int, float). Typically, these attributes are accessed using dictionary searches such as arr [& # 39; a & # 39;] and arr [& # 39; b & # 39;]
Arrays of records allow you to access fields as elements of an array using arr.a and arr.b numpy.recarray.all () returns True if all elements of the array of records are True.

Syntax: numpy.recarray.all (axis = None, out = None, keepdims = False)

Parameters:
axis: [None or int or tuple of ints, optional] Axis or axes along which a logical AND reduction is performed.
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.
keepdims: [bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
If the default value is passed, then keepdims will not be passed through to all method of sub-classes of ndarray, however any non-default value will be ... If the sub-classes sum method does not implement keepdims any exceptions will be raised.

Returns: [ndarray, bool] It returns True if all elements evaluate to True.

Code # 1:

# Python program explaining
# numpy.recarray.all () method

 
# import numy as geek

import numpy as geek

 
# create an input array with two different fields

in_arr = geek.array ([( 5.0 , 2 ), ( 3.0 , 4 )],

dtype = [( `a` , float ), ( `b` , int )])

print ( "Input array:" , in_arr)

 
# convert it to an array of posts 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)

 
# using recarray.all methods to place an array of records

out_arr = geek.recarray. all (rec_arr.a)

print ( "Output array:" , out_arr) 

  
# applying recarray.all methods to the array int records

out_arr = geek.recarray. all (rec_arr.b)

print ( "Output array:" , out_arr) 

Exit:

 Input array: [(5.0, 2) (3.0, 4)] Record array of float: [5. 3.] Record array of int: [2 4] Output array: True Output array: True 

Code # 2:

If we apply numpy.recarray.all () to the entire array of records, this will give the Type error because array is flexible or mixed.

# Python program explaining
# numpy.recarray.all () method

  
# import numy like a geek

import numpy as geek

 
# create an input array with two different fields

in_arr = geek.array ([( 5.0 , 2 ), ( 3.0 , 4 )],

dtype = [( `a` , float ) , ( `b` , int )])

print ( "Input array:" , in_arr) 

 
# convert it to an array of posts using arr.view (np.recarray)

rec_arr = in_arr.view (geek.recarray)

print ( "Record array" , rec_arr)

 
# application recarray.all methods to write an array

out_arr = geek.recarray. all (rec_arr)

print ( " Output array: "  , out_arr) 

Exit:

 TypeError: cannot perform reduce with flexible type 




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