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# numpy.seterrcall

`numpy.``seterrcall`(func)

  Set the floating-point error callback function or log object.

  There are two ways to capture floating-point error messages. The first is to set the error-handler to ‘call’, using `seterr`. Then, set the function to call using this function.

  The second is to set the error-handler to ‘log’, using `seterr`. Floating-point errors then trigger a call to the ‘write’ method of the provided object.

  > Parameters: | func : callable f(err, flag) or object with write method Function to call upon floating-point errors (‘call’-mode) or object whose ‘write’ method is used to log such message (‘log’-mode). The call function takes two arguments. The first is a string describing the type of error (such as “divide by zero”, “overflow”, “underflow”, or “invalid value”), and the second is the status flag. The flag is a byte, whose four least-significant bits indicate the type of error, one of “divide”, “over”, “under”, “invalid”:
  >     [0 0 0 0 divide over under invalid]
  In other words, `flags = divide + 2*over + 4*under + 8*invalid`. If an object is provided, its write method should take one argument, a string.
  Returns: | h : callable, log instance or None The old error handler.

  See also

  `seterr`, `geterr`, `geterrcall`

  Examples

  Callback upon error:

      >>> def err_handler(type, flag):
      ...     print("Floating point error (%s), with flag %s" % (type, flag))
      ...

      >>> saved_handler = np.seterrcall(err_handler)
      >>> save_err = np.seterr(all='call')

      >>> np.array([1, 2, 3]) / 0.0
      Floating point error (divide by zero), with flag 1
      array([ Inf,  Inf,  Inf])

      >>> np.seterrcall(saved_handler)
      <function err_handler at 0x...>
      >>> np.seterr(**save_err)
      {'over': 'call', 'divide': 'call', 'invalid': 'call', 'under': 'call'}

  Log error message:

      >>> class Log(object):
      ...     def write(self, msg):
      ...         print("LOG: %s" % msg)
      ...

      >>> log = Log()
      >>> saved_handler = np.seterrcall(log)
      >>> save_err = np.seterr(all='log')

      >>> np.array([1, 2, 3]) / 0.0
      LOG: Warning: divide by zero encountered in divide

      array([ Inf,  Inf,  Inf])

      >>> np.seterrcall(saved_handler)
      <__main__.Log object at 0x...>
      >>> np.seterr(**save_err)
      {'over': 'log', 'divide': 'log', 'invalid': 'log', 'under': 'log'}