numpy.seterr()

numpy.seterr(all=None, divide=None, over=None, under=None, invalid=None) [source]

Set how floating-point errors are handled.

Note that operations on integer scalar types (such as int16) are handled like floating point, and are affected by these settings.

Parameters:

Parameters:	all : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional Set treatment for all types of floating-point errors at once: ignore: Take no action when the exception occurs. warn: Print a `RuntimeWarning` (via the Python `warnings` module). raise: Raise a `FloatingPointError`. call: Call a function specified using the `seterrcall` function. print: Print a warning directly to `stdout`. log: Record error in a Log object specified by `seterrcall`. The default is not to change the current behavior. divide : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional Treatment for division by zero. over : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional Treatment for floating-point overflow. under : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional Treatment for floating-point underflow. invalid : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional Treatment for invalid floating-point operation.
Returns:	old_settings : dict Dictionary containing the old settings.

all : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional

Set treatment for all types of floating-point errors at once:

ignore: Take no action when the exception occurs.
warn: Print a RuntimeWarning (via the Python warnings module).
raise: Raise a FloatingPointError.
call: Call a function specified using the seterrcall function.
print: Print a warning directly to stdout.
log: Record error in a Log object specified by seterrcall.

The default is not to change the current behavior.

divide : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional

Treatment for division by zero.

over : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional

Treatment for floating-point overflow.

under : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional

Treatment for floating-point underflow.

invalid : {?ignore?, ?warn?, ?raise?, ?call?, ?print?, ?log?}, optional

Treatment for invalid floating-point operation.

Returns:

old_settings : dict

Dictionary containing the old settings.

Notes

The floating-point exceptions are defined in the IEEE 754 standard [1]:

Division by zero: infinite result obtained from finite numbers.
Overflow: result too large to be expressed.
Underflow: result so close to zero that some precision was lost.
Invalid operation: result is not an expressible number, typically indicates that a NaN was produced.

[R281]

http://en.wikipedia.org/wiki/IEEE_754

Examples

>>> old_settings = np.seterr(all='ignore')  #seterr to known value
>>> np.seterr(over='raise')
{'over': 'ignore', 'divide': 'ignore', 'invalid': 'ignore',
 'under': 'ignore'}
>>> np.seterr(**old_settings)  # reset to default
{'over': 'raise', 'divide': 'ignore', 'invalid': 'ignore', 'under': 'ignore'}

>>> np.int16(32000) * np.int16(3)
30464
>>> old_settings = np.seterr(all='warn', over='raise')
>>> np.int16(32000) * np.int16(3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
FloatingPointError: overflow encountered in short_scalars

>>> old_settings = np.seterr(all='print')
>>> np.geterr()
{'over': 'print', 'divide': 'print', 'invalid': 'print', 'under': 'print'}
>>> np.int16(32000) * np.int16(3)
Warning: overflow encountered in short_scalars
30464

Links:

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

doc_NumPy

2025-01-10 15:47:30

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