cf.List.apply_masking¶
-
List.apply_masking(*args, **kwargs)[source]¶ Apply masking as defined by the CF conventions.
Masking is applied according to any of the following criteria that are applicable:
where data elements are equal to the value of the
missing_valueproperty;where data elements are equal to the value of the
_FillValueproperty;where data elements are strictly less than the value of the
valid_minproperty;where data elements are strictly greater than the value of the
valid_maxproperty;where data elements are within the inclusive range specified by the two values of
valid_rangeproperty.
If any of the above properties have not been set the no masking is applied for that method.
Elements that are already masked remain so.
Note
If using the
apply_maskingmethod on a construct that has been read from a dataset with themask=Falseparameter to thereadfunction, then the mask defined in the dataset can only be recreated if themissing_value,_FillValue,valid_min,valid_max, andvalid_rangeproperties have not been updated.New in version (cfdm): 1.8.2
See also
- Parameters
- Returns
A new instance with masked values, or
Noneif the operation was in-place.
Examples
>>> print(v.data.array) [9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36], [0.023 0.036 0.045 0.062 0.046 0.073 0.006 0.066] [0.11 0.131 0.124 0.146 0.087 0.103 0.057 0.011] [0.029 0.059 0.039 0.07 0.058 0.072 0.009 0.017] [9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36, 9.96920997e+36]]) >>> masked_v = v.apply_masking() >>> print(masked_v.data.array) [[ -- -- -- -- -- -- -- --] [0.023 0.036 0.045 0.062 0.046 0.073 0.006 0.066] [0.11 0.131 0.124 0.146 0.087 0.103 0.057 0.011] [0.029 0.059 0.039 0.07 0.058 0.072 0.009 0.017] [ -- -- -- -- -- -- -- --]]