numpy.seterr¶

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

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 : 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. old_settings : dict Dictionary containing the old settings.

seterrcall
Set a callback function for the ‘call’ mode.

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.

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(all='ignore')  # 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
```

numpy.geterrobj

numpy.geterr