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Fonction nansum - module numpy

Signature de la fonction nansum

def nansum(a, axis=None, dtype=None, out=None, keepdims=<no value>) 

Description

nansum.__doc__

    Return the sum of array elements over a given axis treating Not a
    Numbers (NaNs) as zero.

    In NumPy versions <= 1.9.0 Nan is returned for slices that are all-NaN or
    empty. In later versions zero is returned.

    Parameters
    ----------
    a : array_like
        Array containing numbers whose sum is desired. If `a` is not an
        array, a conversion is attempted.
    axis : {int, tuple of int, None}, optional
        Axis or axes along which the sum is computed. The default is to compute the
        sum of the flattened array.
    dtype : data-type, optional
        The type of the returned array and of the accumulator in which the
        elements are summed.  By default, the dtype of `a` is used.  An
        exception is when `a` has an integer type with less precision than
        the platform (u)intp. In that case, the default will be either
        (u)int32 or (u)int64 depending on whether the platform is 32 or 64
        bits. For inexact inputs, dtype must be inexact.

        .. versionadded:: 1.8.0
    out : ndarray, optional
        Alternate output array in which to place the result.  The default
        is ``None``. If provided, it must have the same shape as the
        expected output, but the type will be cast if necessary.  See
        :ref:`ufuncs-output-type` for more details. The casting of NaN to integer
        can yield unexpected results.

        .. versionadded:: 1.8.0
    keepdims : bool, optional
        If this is set to True, the axes which are reduced are left
        in the result as dimensions with size one. With this option,
        the result will broadcast correctly against the original `a`.


        If the value is anything but the default, then
        `keepdims` will be passed through to the `mean` or `sum` methods
        of sub-classes of `ndarray`.  If the sub-classes methods
        does not implement `keepdims` any exceptions will be raised.

        .. versionadded:: 1.8.0

    Returns
    -------
    nansum : ndarray.
        A new array holding the result is returned unless `out` is
        specified, in which it is returned. The result has the same
        size as `a`, and the same shape as `a` if `axis` is not None
        or `a` is a 1-d array.

    See Also
    --------
    numpy.sum : Sum across array propagating NaNs.
    isnan : Show which elements are NaN.
    isfinite: Show which elements are not NaN or +/-inf.

    Notes
    -----
    If both positive and negative infinity are present, the sum will be Not
    A Number (NaN).

    Examples
    --------
    >>> np.nansum(1)
    1
    >>> np.nansum([1])
    1
    >>> np.nansum([1, np.nan])
    1.0
    >>> a = np.array([[1, 1], [1, np.nan]])
    >>> np.nansum(a)
    3.0
    >>> np.nansum(a, axis=0)
    array([2.,  1.])
    >>> np.nansum([1, np.nan, np.inf])
    inf
    >>> np.nansum([1, np.nan, np.NINF])
    -inf
    >>> from numpy.testing import suppress_warnings
    >>> with suppress_warnings() as sup:
    ...     sup.filter(RuntimeWarning)
    ...     np.nansum([1, np.nan, np.inf, -np.inf]) # both +/- infinity present
    nan