numpy.MaskedArray.average() function is used to return the weighted average of array over the given axis.
Syntax :
numpy.ma.average(arr, axis=None, weights=None, returned=False)Parameters:
arr :[ array_like] Input masked array whose data to be averaged. Masked entries are not taken into account in the computation.
axis :[ int, optional] Axis along which to average arr. If None, averaging is done over the flattened array.
weights : [array_like, optional] The importance that each element has in the computation of the average. If weights=None, then all data in arr are assumed to have a weight equal to one. If weights is complex, the imaginary parts are ignored.
returned :[ bool, optional] It indicates whether a tuple (result, sum of weights) should be returned as output (True), or just the result (False). Default is False.Return : [ 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.
Code #1 :
# Python program explaining # numpy.MaskedArray.average() method     # importing numpy as geek  # and numpy.ma module as ma import numpy as geek import numpy.ma as ma     # creating input array  in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]]) print ("Input array : ", in_arr)     # Now we are creating a masked array. # by making entry as invalid.  mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr)     # applying MaskedArray.average    # methods to masked array out_arr = ma.average(mask_arr) print ("normal average of masked array : ", out_arr) |
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] normal average of masked array : 0.75
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Code #2 :
# Python program explaining # numpy.MaskedArray.average() method     # importing numpy as geek  # and numpy.ma module as ma import numpy as geek import numpy.ma as ma     # creating input array  in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]]) print ("Input array : ", in_arr)     # Now we are creating a masked array. # by making entry as invalid.  mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr)     # applying MaskedArray.average    # methods to masked array out_arr = ma.average(mask_arr, weights =[[0, 1], [ 0, 2], [ 3, 1]]) print ("weighted average of masked array : ", out_arr) |
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] weighted average of masked array : 1.7142857142857142
