Numpy recarray.max () function | python



numpy.recarray.max() returns the maximum of an array of records or the maximum along the axis.

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

Parameters:
axis: [None or int or tuple of ints, optional] Axis or axes along which to operate. By default, flattened input is used.
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.

Return: [ndarray or scalar] Maximum of record array. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension arr.ndim – 1.

Code # 1:

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

 
# import numy as a geek

import numpy as geek

 
# create an input array with two different fields

in_arr = geek.array ([[( 5.0 , 2 ), ( 3.0 , - 4 ), ( 6.0 , 8 )],

[( 9.0 , 1 ), ( 5.0 , 4 ), ( - 12.0 , - 7 )]],

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 methods .max
# place an array of posts along the default axis
# i, e along the flattened array

out_arr1 = rec_arr.a. max ()

# Maximum smoothed array

print ( "Max of float record array, axis = None: " , out_arr1) 

  

 
# using recarray.max methods
# post array of records along axis 0
# i, e along the vertical

out_arr2 = rec_arr.a. max (axis = 0 )

# Maximum on axis 0

print ( "Max of float record array, axis = 0:" , out_arr2)

 

 
# using recarray.max methods
# place an array of records along axis 1
# i, e along the horizontal

out_arr3 = rec_arr.a. max (axis = 1 )

# Maximum by axis 0

print ( "Max of float record array, axis = 1: " , out_arr3)

  

 
# using recarray.max methods
# to an array of int records along the default axis
# i, e along the flattened array

out_arr4 = rec_arr.b. max ()

# Maximum smoothed array

print ( " Max of int record array, axis = None: " , out_arr4) 

  

  
# applying recarray.max methods
# into an array of int records along the 0 axis
# i, e along the vertical

out_arr5 = rec_arr.b. max (axis = 0 )

# Maximum on axis 0

print ( "Max of int record array, axis = 0:" , out_arr5)

 

  
# using recarray.max methods
# to an array of int records along axis 1
# i, e along the horizontal 

out_arr6 = rec_arr.b. max (axis = 1 )

# Maximum on axis 0

print ( "Max of int record array, axis = 1:" , out_arr6)

Output:

 Input array: [[(5., 2) (3., -4) (6., 8)] [(9., 1) (5., 4) (-12. , -7)]] Record array of float: [[5. 3. 6.] [9. 5. -12.]] Record array of int: [[2 -4 8] [1 4 -7]] Max of float record array, axis = None: 9.0 Max of float record array, axis = 0: [9. 5. 6.] Max of float record array, axis = 1: [6. 9.] Max of int record array, axis = None: 8 Max of int record array, axis = 0: [2 4 8] Max of int record array, axis = 1: [8 4]