Numpy recarray.min () function | python

numpy.recarray.min() returns the minimum of the array of records or the minimum along the axis.

Syntax: numpy.recarray.min (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] Minimum 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.min () 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.min methods
# place an array of h Along the default axis
# i, e along the flattened array

out_arr1 = rec_arr.a. min ()

# Minimum smoothed array

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

 

 
# using recarray.min methods
# place an array of posts along axis 0
# i, e along the vertical

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

# Minimum along axis 0

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

 

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

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

# Minimum along axis 0

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

 

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

out_arr4 = rec_arr.b. min ()

# Minimum smoothed array

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

 

 
# apply recarray.min methods
# into an array of int records along the 0 axis
# i, e along verticals

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

# Minimum along axis 0

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

 

 
# applying recarray.min methods
# into an array of int records along axis 1
# i, e along the horizontal

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

# Minimum along axis 0

print ( "Min 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]] Min of float record array, axis = None: -12.0 Min of float record array, axis = 0: [5. 3. -12.] Min of float record array, axis = 1: [3. -12.] Min of int record array, axis = None: 1 Min of int record array, axis = 0: [1 4 7] Min of int record array, axis = 1: [2 1] 




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