class numpy.errstate(**kwargs)[source]

Context manager for floating-point error handling.

Using an instance of errstate as a context manager allows statements in that context to execute with a known error handling behavior. Upon entering the context the error handling is set with seterr and seterrcall, and upon exiting it is reset to what it was before.

Changed in version 1.17.0: errstate is also usable as a function decorator, saving a level of indentation if an entire function is wrapped. See contextlib.ContextDecorator for more information.

kwargs : {divide, over, under, invalid}

Keyword arguments. The valid keywords are the possible floating-point exceptions. Each keyword should have a string value that defines the treatment for the particular error. Possible values are {‘ignore’, ‘warn’, ‘raise’, ‘call’, ‘print’, ‘log’}.


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


>>> from collections import OrderedDict
>>> olderr = np.seterr(all='ignore')  # Set error handling to known state.
>>> np.arange(3) / 0.
array([nan, inf, inf])
>>> with np.errstate(divide='warn'):
...     np.arange(3) / 0.
array([nan, inf, inf])
>>> np.sqrt(-1)
>>> with np.errstate(invalid='raise'):
...     np.sqrt(-1)
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
FloatingPointError: invalid value encountered in sqrt

Outside the context the error handling behavior has not changed:

>>> OrderedDict(sorted(np.geterr().items()))
OrderedDict([('divide', 'ignore'), ('invalid', 'ignore'), ('over', 'ignore'), ('under', 'ignore')])


__call__(self, func) Call self as a function.

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