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# 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'}