numpy.ma.allclose#
- 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 themasked_equal
argument.- Parameters:
- a, barray_like
Input arrays to compare.
- masked_equalbool, optional
Whether masked values in a and b are considered equal (True) or not (False). They are considered equal by default.
- rtolfloat, optional
Relative tolerance. The relative difference is equal to
rtol * b
. Default is 1e-5.- atolfloat, optional
Absolute tolerance. The absolute difference is equal to atol. Default is 1e-8.
- Returns:
- ybool
Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned.
See also
all
,any
numpy.allclose
the non-masked
allclose
.
Notes
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.
Examples
>>> a = np.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 = np.ma.array([1e10, 1e-8, -42.0], mask=[0, 0, 1]) >>> np.ma.allclose(a, b) False
>>> a = np.ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1]) >>> b = np.ma.array([1.00001e10, 1e-9, -42.0], mask=[0, 0, 1]) >>> np.ma.allclose(a, b) True >>> np.ma.allclose(a, b, masked_equal=False) False
Masked values are not compared directly.
>>> a = np.ma.array([1e10, 1e-8, 42.0], mask=[0, 0, 1]) >>> b = np.ma.array([1.00001e10, 1e-9, 42.0], mask=[0, 0, 1]) >>> np.ma.allclose(a, b) True >>> np.ma.allclose(a, b, masked_equal=False) False