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 :
# 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 :
# 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
