numpy.ma.allclose(a, b, masked_equal=True, rtol=1e-05, atol=1e-08)
[source]
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.
Parameters: |
a, b : array_like Input arrays to compare. masked_equal : bool, optional Whether masked values in rtol : float, optional Relative tolerance. The relative difference is equal to atol : float, optional Absolute tolerance. The absolute difference is equal to |
---|---|
Returns: |
y : bool Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned. |
If the following equation is element-wise True, then allclose
returns True:
absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))
Return True if all elements of a
and b
are equal subject to given tolerances.
>>> a = ma.array([1e10, 1e-7, 42.0], mask=[0, 0, 1]) >>> a masked_array(data = [10000000000.0 1e-07 --], mask = [False False True], fill_value = 1e+20) >>> b = ma.array([1e10, 1e-8, -42.0], mask=[0, 0, 1]) >>> ma.allclose(a, b) False
>>> a = ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1]) >>> b = ma.array([1.00001e10, 1e-9, -42.0], mask=[0, 0, 1]) >>> ma.allclose(a, b) True >>> ma.allclose(a, b, masked_equal=False) False
Masked values are not compared directly.
>>> a = ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1]) >>> b = ma.array([1.00001e10, 1e-9, 42.0], mask=[0, 0, 1]) >>> ma.allclose(a, b) True >>> ma.allclose(a, b, masked_equal=False) False
© 2008–2017 NumPy Developers
Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.allclose.html