Repository: numpy/numpy
File: numpy/_core/_ufunc_config.py (Python)

Code before:
        - warn: Print a :exc:`RuntimeWarning` (via the Python `warnings`
          module).
        - raise: Raise a :exc:`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, errstate, :ref:`fp_error_handling`


    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.

    .. [1] https://en.wikipedia.org/wiki/IEEE_754

    Examples
    --------
    >>> import numpy as np
    >>> orig_settings = np.seterr(all='ignore')  # seterr to known value
    >>> np.int16(32000) * np.int16(3)
    np.int16(30464)
    >>> np.seterr(over='raise')
    {'divide': 'ignore', 'over': 'ignore', 'under': 'ignore', 'invalid': 'ignore'}
    >>> old_settings = np.seterr(all='warn', over='raise')
    >>> np.int16(32000) * np.int16(3)

Review comment (suggestion):
Option 1: 

I can do everything like this in See Also:
 - advantage, it's juste a single link.
 - disadvantage, I can't say it's about concurrency, and can't choose the text (unless we fix docscrape to accept the `text <ref>` syntax.

Code after:
        - warn: Print a :exc:`RuntimeWarning` (via the Python `warnings`
          module).
        - raise: Raise a :exc:`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, errstate


    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.

    **Concurrency note:** see  :ref:`fp_error_handling`

    .. [1] https://en.wikipedia.org/wiki/IEEE_754

    Examples
    --------
    >>> import numpy as np
    >>> orig_settings = np.seterr(all='ignore')  # seterr to known value
    >>> np.int16(32000) * np.int16(3)
    np.int16(30464)
    >>> np.seterr(over='raise')
    {'divide': 'ignore', 'over': 'ignore', 'under': 'ignore', 'invalid': 'ignore'}