# numpy.ma.allclose() function – Python

`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
```

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