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# 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.
  Returns : | old_settings : dict Dictionary containing the old settings.

  See also

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

  `geterr`, `geterrcall`

  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.

  [R258] | 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(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

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