numpy.errstate()

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.

Parameters:

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?}.

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?}.

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'}

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.errstate.html

doc_NumPy

2025-01-10 15:47:30

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