cf.CellMeasure.apply_masking¶
-
CellMeasure.
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_value
property;where data elements are equal to the value of the
_FillValue
property;where data elements are strictly less than the value of the
valid_min
property;where data elements are strictly greater than the value of the
valid_max
property;where data elements are within the inclusive range specified by the two values of
valid_range
property.
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_masking
method on a construct that has been read from a dataset with themask=False
parameter to theread
function, then the mask defined in the dataset can only be recreated if themissing_value
,_FillValue
,valid_min
,valid_max
, andvalid_range
properties have not been updated.New in version (cfdm): 1.8.2
See also
- Parameters
- Returns
A new instance with masked values, or
None
if 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] [ -- -- -- -- -- -- -- --]]