numpy.ma.masked_values — NumPy v2.6.dev0 Manual

ma.masked_values(x, value, rtol=1e-05, atol=1e-08, copy=True, shrink=True)

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Mask using floating point equality.

Return a MaskedArray, masked where the data in array x are approximately equal to value, determined using

isclose

. The default tolerances for

masked_values

are the same as those for

isclose

.

For integer types, exact equality is used, in the same way as

masked_equal

.

The fill_value is set to value and the mask is set to nomask if possible.

Parameters:xarray_likeArray to mask.

valuefloatMasking value.

rtol, atolfloat, optionalTolerance parameters passed on to

isclose

copybool, optionalWhether to return a copy of x.

shrinkbool, optionalWhether to collapse a mask full of False to nomask.

Returns:resultMaskedArrayThe result of masking x where approximately equal to value.

Examples

>>> importnumpyasnp>>> importnumpy.maasma>>> x=np.array([1,1.1,2,1.1,3])>>> ma.masked_values(x,1.1)masked_array(data=[1.0, --, 2.0, --, 3.0], mask=[False, True, False, True, False], fill_value=1.1)Note that mask is set to nomask if possible.

>>> ma.masked_values(x,2.1)masked_array(data=[1. , 1.1, 2. , 1.1, 3. ], mask=False, fill_value=2.1)Unlike

masked_equal

,

masked_values

can perform approximate equalities.

>>> ma.masked_values(x,2.1,atol=1e-1)masked_array(data=[1.0, 1.1, --, 1.1, 3.0], mask=[False, False, True, False, False], fill_value=2.1)