mean

Arguments

x

Vector, matrix, or hypermatrix of real or complex numbers. Sparse matrices accepted.

orientation

direction = index of the dimension along which the mean is computed. "r" is equivalent to 1. "c" is equivalent to 2. "m" is equivalent to find(size(x)>1,1).

y

dense scalar if orientation is not used or if x is a scalar. Otherwise, array such that size(y,orientation) is 1 (sparse-encoded if x is so).

Description

y = mean(x) returns the mean of all entries. If at least one entry is NaN, NaN is returned. This scalar result is always dense-encoded.

y = mean(x,1) or y=mean(x,"r") computes the means accross rows. y is a row if x is a matrix.

y = mean(x,2) or y=mean(x,"c") computes the means accross columns. y is a column if x is a matrix.

y = mean(x, n) with 3 ≤ n ≤ ndims(x) computes the means along the n^th dimension of x.

y = mean(x,'m') is the mean along the first non singleton dimension of x (for compatibility with Matlab).

mean([]) and mean(sparse([])) return NaN. For any orientation not "m", mean([], orientation) returns [], and mean(sparse([]), orientation) returns sparse([]).

mean() can be overloaded.

Examples

With a matrix:

A = [0,1,1,0,1;1,0,0,1,1;0,0,1,0,0;0,0,1,0,0]
mean(A)
mean(A, 'r')
mean(A, 'c')

--> A = [0,1,1,0,1;1,0,0,1,1;0,0,1,0,0;0,0,1,0,0]
 A  =
   0.   1.   1.   0.   1.
   1.   0.   0.   1.   1.
   0.   0.   1.   0.   0.
   0.   0.   1.   0.   0.

--> mean(A)
 ans  =
   0.4

--> mean(A, 'r')
 ans  =
   0.25   0.25   0.75   0.25   0.5

--> mean(A, 'c')
 ans  =
   0.6
   0.6
   0.2
   0.2

With an hypermatrix:

A = [1,0,0,1,0,0,1,1,1,1,1,1,0,1,0,1,1,0,1,1,1,1,1,0,1,0,1,0,1,1,1,0,1,0,0,1,0,1,1,0];
A = matrix(A, [4,5,2])
mean(A)
mean(A, 'r')
mean(A, 'c')
mean(A, 3)

A = matrix(1:12, [1,1,2,3,2]);
// in this case mean(A,'m') is equivalent to mean(A,3), the first non singleton dimension of A
mean(A, 'm')

--> A = matrix(A, [4,5,2])
 A  =
(:,:,1)
   1.   0.   1.   0.   1.
   0.   0.   1.   1.   0.
   0.   1.   1.   0.   1.
   1.   1.   1.   1.   1.

(:,:,2)
   1.   1.   1.   1.   0.
   1.   0.   1.   0.   1.
   1.   1.   1.   0.   1.
   0.   0.   0.   1.   0.

--> mean(A)
 ans  =
   0.625

--> mean(A, 'r')
 ans  =
(:,:,1)
   0.5   0.5   1.   0.5   0.75

(:,:,2)
   0.75   0.5   0.75   0.5   0.5

--> mean(A, 'c')
 ans  =
(:,:,1)
   0.6
   0.4
   0.6
   1.

(:,:,2)
   0.8
   0.6
   0.8
   0.2

--> mean(A, 3)
 ans  =
   1.    0.5   1.    0.5   0.5
   0.5   0.    1.    0.5   0.5
   0.5   1.    1.    0.    1.
   0.5   0.5   0.5   1.    0.5

See also

• sum — sum of array elements
• median — median (row median, column median,...) of vector/matrix/array entries
• stdev — standard deviation (row or column-wise) of vector/matrix entries

History