static Data.mask_fpe(*arg)[source]

Masking of floating-point errors in the results of arithmetic operations.

Deprecated at version 3.14.0. It is currently not possible to control how floating-point errors are handled, due to the use of dask for handling all array manipulations. This may change in the future (see for more details).

If masking is allowed then only floating-point errors which would otherwise be raised as FloatingPointError exceptions are masked. Whether FloatingPointError exceptions may be raised is determined by cf.Data.seterr.

If called without an argument then the current behaviour is returned.

Note that if the raising of FloatingPointError exceptions has been suppressed then invalid values in the results of arithmetic operations may be subsequently converted to masked values with the mask_invalid method.

arg: bool, optional

The new behaviour. True means that FloatingPointError exceptions are suppressed and replaced with masked values. False means that FloatingPointError exceptions are raised. The default is not to change the current behaviour.


The behaviour prior to the change, or the current behaviour if no new value was specified.


>>> d = cf.Data([0., 1])
>>> e = cf.Data([1., 2])
>>> old = cf.Data.mask_fpe(False)
>>> old = cf.Data.seterr('raise')
>>> e/d
FloatingPointError: divide by zero encountered in divide
>>> e**123456
FloatingPointError: overflow encountered in power
>>> old = cf.Data.mask_fpe(True)
>>> old = cf.Data.seterr('raise')
>>> e/d
<CF Data: [--, 2.0] >
>>> e**123456
<CF Data: [1.0, --] >
>>> old = cf.Data.mask_fpe(True)
>>> old = cf.Data.seterr('ignore')
>>> e/d
<CF Data: [inf, 2.0] >
>>> e**123456
<CF Data: [1.0, inf] >