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Module « numpy.matlib »

Fonction nancumsum - module numpy.matlib

Signature de la fonction nancumsum

def nancumsum(a, axis=None, dtype=None, out=None) 

Description

help(numpy.matlib.nancumsum)

Return the cumulative sum of array elements over a given axis treating Not a
Numbers (NaNs) as zero.  The cumulative sum does not change when NaNs are
encountered and leading NaNs are replaced by zeros.

Zeros are returned for slices that are all-NaN or empty.

Parameters
----------
a : array_like
    Input array.
axis : int, optional
    Axis along which the cumulative sum is computed. The default
    (None) is to compute the cumsum over the flattened array.
dtype : dtype, optional
    Type of the returned array and of the accumulator in which the
    elements are summed.  If `dtype` is not specified, it defaults
    to the dtype of `a`, unless `a` has an integer dtype with a
    precision less than that of the default platform integer.  In
    that case, the default platform integer is used.
out : ndarray, optional
    Alternative output array in which to place the result. It must
    have the same shape and buffer length as the expected output
    but the type will be cast if necessary. See :ref:`ufuncs-output-type` for
    more details.

Returns
-------
nancumsum : 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.cumsum : Cumulative sum across array propagating NaNs.
isnan : Show which elements are NaN.

Examples
--------
>>> import numpy as np
>>> np.nancumsum(1)
array([1])
>>> np.nancumsum([1])
array([1])
>>> np.nancumsum([1, np.nan])
array([1.,  1.])
>>> a = np.array([[1, 2], [3, np.nan]])
>>> np.nancumsum(a)
array([1.,  3.,  6.,  6.])
>>> np.nancumsum(a, axis=0)
array([[1.,  2.],
       [4.,  2.]])
>>> np.nancumsum(a, axis=1)
array([[1.,  3.],
       [3.,  3.]])

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