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Module « numpy.matlib »

Fonction nansum - module numpy.matlib

Signature de la fonction nansum

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

Description

help(numpy.matlib.nansum)

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.
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.
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.
initial : scalar, optional
    Starting value for the sum. See `~numpy.ufunc.reduce` for details.

    .. versionadded:: 1.22.0
where : array_like of bool, optional
    Elements to include in the sum. See `~numpy.ufunc.reduce` for details.

    .. versionadded:: 1.22.0

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
--------
>>> import numpy as np
>>> 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.inf])
-inf
>>> from numpy.testing import suppress_warnings
>>> with np.errstate(invalid="ignore"):
...     np.nansum([1, np.nan, np.inf, -np.inf]) # both +/- infinity present
np.float64(nan)

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