numpy.geterr

numpy.geterr()[source]

Get the current way of handling floating-point errors.

Returns:

resdict

A dictionary with keys “divide”, “over”, “under”, and “invalid”, whose values are from the strings “ignore”, “print”, “log”, “warn”, “raise”, and “call”. The keys represent possible floating-point exceptions, and the values define how these exceptions are handled.

See also

geterrcall, seterr, seterrcall

Notes

For complete documentation of the types of floating-point exceptions and treatment options, see seterr.

Concurrency note: see Floating point error handling

Examples

Try it in your browser!

>>> import numpy as np
>>> np.geterr()
{'divide': 'warn', 'over': 'warn', 'under': 'ignore', 'invalid': 'warn'}
>>> np.arange(3.) / np.arange(3.)  
array([nan,  1.,  1.])
RuntimeWarning: invalid value encountered in divide

>>> oldsettings = np.seterr(all='warn', invalid='raise')
>>> np.geterr()
{'divide': 'warn', 'over': 'warn', 'under': 'warn', 'invalid': 'raise'}
>>> np.arange(3.) / np.arange(3.)
Traceback (most recent call last):
  ...
FloatingPointError: invalid value encountered in divide
>>> oldsettings = np.seterr(**oldsettings)  # restore original

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