numpy.ma.average(a, axis=None, weights=None, returned=False)
[source]
Return the weighted average of array over the given axis.
Parameters: |
a : array_like Data to be averaged. Masked entries are not taken into account in the computation. axis : int, optional Axis along which to average weights : array_like, optional The importance that each element has in the computation of the average. The weights array can either be 1-D (in which case its length must be the size of returned : bool, optional Flag indicating whether a tuple |
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Returns: |
average, [sum_of_weights] : (tuple of) scalar or MaskedArray The average along the specified axis. When returned is |
>>> a = np.ma.array([1., 2., 3., 4.], mask=[False, False, True, True]) >>> np.ma.average(a, weights=[3, 1, 0, 0]) 1.25
>>> x = np.ma.arange(6.).reshape(3, 2) >>> print(x) [[ 0. 1.] [ 2. 3.] [ 4. 5.]] >>> avg, sumweights = np.ma.average(x, axis=0, weights=[1, 2, 3], ... returned=True) >>> print(avg) [2.66666666667 3.66666666667]
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.average.html