numpy.ma.choose() function - Python

numpy.ma.allclose() function - Python

Last Updated : 05 May, 2020

numpy.ma.allclose() function returns True if two arrays are element-wise equal within a tolerance. This function is equivalent to allclose except that masked values are treated as equal (default) or unequal, depending on the masked_equal argument.

Syntax : numpy.ma.allclose(a, b, masked_equal = True, rtol = 1e-05, atol = 1e-08) Parameters : a, b : [array_like] Input arrays to compare. masked_equal : [bool, optional] Whether masked values in a and b are considered equal (True) or not (False). They are considered equal by default. rtol : [float, optional] Relative tolerance. The relative difference is equal to rtol * b. Default is 1e-5. atol : [float, optional] Absolute tolerance. The absolute difference is equal to atol. Default is 1e-8. Return : [bool] Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned.

Code #1 :

Python3

# Python program explaining
# numpy.ma.allclose() function
 
# importing numpy as geek 
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma
  
a = geek.ma.array([1e10, 1e-8, 42.0], mask = [0, 0, 1])

b = geek.ma.array([1.00001e10, 1e-9, -42.0], mask = [0, 0, 1])

gfg = geek.ma.allclose(a, b)

print (gfg)

Output :

True

Code #2 :

Python3

# Python program explaining
# numpy.ma.allclose() function
 
# importing numpy as geek 
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma
  
a = geek.ma.array([1e10, 1e-8, 42.0], mask = [0, 0, 1])

b = geek.ma.array([1.00001e10, 1e-9, -42.0], mask = [0, 0, 1])

gfg = geek.ma.allclose(a, b, masked_equal = False)

print (gfg)

Output :

False

numpy.ma.choose() function - Python

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