This is documentation for an old release of NumPy (version 1.13). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

numpy.errstate

class numpy.errstate(**kwargs)

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.

Parameters:

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’}.

See also

seterr, geterr, seterrcall, geterrcall

Notes

The with statement was introduced in Python 2.5, and can only be used there by importing it: from __future__ import with_statement. In earlier Python versions the with statement is not available.

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

Examples

>>> from __future__ import with_statement  # use 'with' in Python 2.5
>>> 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.
...
__main__:2: RuntimeWarning: divide by zero encountered in divide
array([ NaN,  Inf,  Inf])

>>> np.sqrt(-1)
nan
>>> 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:

>>> np.geterr()
{'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
'under': 'ignore'}