Python numpy.geterrcall() Examples

The following are 30 code examples of numpy.geterrcall(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function .
Example #1
Source File: test_errstate.py    From pySINDy with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #2
Source File: test_errstate.py    From keras-lambda with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #3
Source File: test_errstate.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #4
Source File: test_errstate.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #5
Source File: test_errstate.py    From coffeegrindsize with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #6
Source File: test_errstate.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #7
Source File: test_errstate.py    From ImageFusion with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)
        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #8
Source File: test_errstate.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #9
Source File: test_errstate.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #10
Source File: test_errstate.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #11
Source File: test_errstate.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #12
Source File: test_errstate.py    From recruit with Apache License 2.0 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #13
Source File: test_errstate.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #14
Source File: test_errstate.py    From Computable with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)
        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #15
Source File: test_errstate.py    From vnpy_crypto with MIT License 5 votes vote down vote up
def test_errcall(self):
        def foo(*args):
            print(args)

        olderrcall = np.geterrcall()
        with np.errstate(call=foo):
            assert_(np.geterrcall() is foo, 'call is not foo')
            with np.errstate(call=None):
                assert_(np.geterrcall() is None, 'call is not None')
        assert_(np.geterrcall() is olderrcall, 'call is not olderrcall') 
Example #16
Source File: numeric.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #17
Source File: numeric.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #18
Source File: numeric.py    From coffeegrindsize with MIT License 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #19
Source File: numeric.py    From coffeegrindsize with MIT License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #20
Source File: numeric.py    From lambda-packs with MIT License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #21
Source File: numeric.py    From Carnets with BSD 3-Clause "New" or "Revised" License 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #22
Source File: numeric.py    From Carnets with BSD 3-Clause "New" or "Revised" License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #23
Source File: numeric.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #24
Source File: numeric.py    From Splunking-Crime with GNU Affero General Public License v3.0 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #25
Source File: numeric.py    From lambda-packs with MIT License 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #26
Source File: numeric.py    From twitter-stock-recommendation with MIT License 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #27
Source File: numeric.py    From twitter-stock-recommendation with MIT License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #28
Source File: numeric.py    From recruit with Apache License 2.0 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2] 
Example #29
Source File: numeric.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up
def geterr():
    """
    Get the current way of handling floating-point errors.

    Returns
    -------
    res : dict
        A dictionary with keys "divide", "over", "under", and "invalid",
        whose values are from the strings "ignore", "print", "log", "warn",
        "raise", and "call". The keys represent possible floating-point
        exceptions, and the values define how these exceptions are handled.

    See Also
    --------
    geterrcall, seterr, seterrcall

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

    Examples
    --------
    >>> np.geterr()
    {'over': 'warn', 'divide': 'warn', 'invalid': 'warn',
    'under': 'ignore'}
    >>> np.arange(3.) / np.arange(3.)
    array([ NaN,   1.,   1.])

    >>> oldsettings = np.seterr(all='warn', over='raise')
    >>> np.geterr()
    {'over': 'raise', 'divide': 'warn', 'invalid': 'warn', 'under': 'warn'}
    >>> np.arange(3.) / np.arange(3.)
    __main__:1: RuntimeWarning: invalid value encountered in divide
    array([ NaN,   1.,   1.])

    """
    maskvalue = umath.geterrobj()[1]
    mask = 7
    res = {}
    val = (maskvalue >> SHIFT_DIVIDEBYZERO) & mask
    res['divide'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_OVERFLOW) & mask
    res['over'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_UNDERFLOW) & mask
    res['under'] = _errdict_rev[val]
    val = (maskvalue >> SHIFT_INVALID) & mask
    res['invalid'] = _errdict_rev[val]
    return res 
Example #30
Source File: numeric.py    From Mastering-Elasticsearch-7.0 with MIT License 4 votes vote down vote up
def geterrcall():
    """
    Return the current callback function used on floating-point errors.

    When the error handling for a floating-point error (one of "divide",
    "over", "under", or "invalid") is set to 'call' or 'log', the function
    that is called or the log instance that is written to is returned by
    `geterrcall`. This function or log instance has been set with
    `seterrcall`.

    Returns
    -------
    errobj : callable, log instance or None
        The current error handler. If no handler was set through `seterrcall`,
        ``None`` is returned.

    See Also
    --------
    seterrcall, seterr, geterr

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

    Examples
    --------
    >>> np.geterrcall()  # we did not yet set a handler, returns None

    >>> oldsettings = np.seterr(all='call')
    >>> def err_handler(type, flag):
    ...     print("Floating point error (%s), with flag %s" % (type, flag))
    >>> oldhandler = np.seterrcall(err_handler)
    >>> np.array([1, 2, 3]) / 0.0
    Floating point error (divide by zero), with flag 1
    array([ Inf,  Inf,  Inf])

    >>> cur_handler = np.geterrcall()
    >>> cur_handler is err_handler
    True

    """
    return umath.geterrobj()[2]