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Module « numpy »

Fonction seterrobj - module numpy

Signature de la fonction seterrobj

Description

seterrobj.__doc__

seterrobj(errobj)

    Set the object that defines floating-point error handling.

    The error object contains all information that defines the error handling
    behavior in NumPy. `seterrobj` is used internally by the other
    functions that set error handling behavior (`seterr`, `seterrcall`).

    Parameters
    ----------
    errobj : list
        The error object, a list containing three elements:
        [internal numpy buffer size, error mask, error callback function].

        The error mask is a single integer that holds the treatment information
        on all four floating point errors. The information for each error type
        is contained in three bits of the integer. If we print it in base 8, we
        can see what treatment is set for "invalid", "under", "over", and
        "divide" (in that order). The printed string can be interpreted with

        * 0 : 'ignore'
        * 1 : 'warn'
        * 2 : 'raise'
        * 3 : 'call'
        * 4 : 'print'
        * 5 : 'log'

    See Also
    --------
    geterrobj, seterr, geterr, seterrcall, geterrcall
    getbufsize, setbufsize

    Notes
    -----
    For complete documentation of the types of floating-point exceptions and
    treatment options, see `seterr`.

    Examples
    --------
    >>> old_errobj = np.geterrobj()  # first get the defaults
    >>> old_errobj
    [8192, 521, None]

    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    ...
    >>> new_errobj = [20000, 12, err_handler]
    >>> np.seterrobj(new_errobj)
    >>> np.base_repr(12, 8)  # int for divide=4 ('print') and over=1 ('warn')
    '14'
    >>> np.geterr()
    {'over': 'warn', 'divide': 'print', 'invalid': 'ignore', 'under': 'ignore'}
    >>> np.geterrcall() is err_handler
    True