numpy.ma.average — NumPy v1.11 Manual (original) (raw)

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 the average is computed. The default is to compute the average of the flattened array. 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 a along the given axis) or of the same shape as a. If weights=None, then all data in a are assumed to have a weight equal to one. If weights is complex, the imaginary parts are ignored. returned : bool, optional Flag indicating whether a tuple (result, sum of weights)should be returned as output (True), or just the result (False). Default is False.
Returns:	average, [sum_of_weights] : (tuple of) scalar or MaskedArray The average along the specified axis. When returned is True, return a tuple with the average as the first element and the sum of the weights as the second element. The return type is np.float64_if a is of integer type and floats smaller than float64, or the input data-type, otherwise. If returned, sum_of_weights* is always_float64*.

Parameters:

a : array_like Data to be averaged. Masked entries are not taken into account in the computation. axis : int, optional Axis along which the average is computed. The default is to compute the average of the flattened array. 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 a along the given axis) or of the same shape as a. If weights=None, then all data in a are assumed to have a weight equal to one. If weights is complex, the imaginary parts are ignored. returned : bool, optional Flag indicating whether a tuple (result, sum of weights)should be returned as output (True), or just the result (False). Default is False.

Returns:

average, [sum_of_weights] : (tuple of) scalar or MaskedArray The average along the specified axis. When returned is True, return a tuple with the average as the first element and the sum of the weights as the second element. The return type is np.float64_if a is of integer type and floats smaller than float64, or the input data-type, otherwise. If returned, sum_of_weights is always_float64.

Examples

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]