fun_2d_outer()

Applies a function to the outer dimension of two-dimensional data

Syntax
y = fun_2d_outer(data, fun)

Argument

Name	Description	Range	Type	Required
data	two-dimensional data	(-∞, ∞)	integer, real, complex	yes
fun	name of function (usually mean, max, or min) that will be applied to the outer dimension of the data		string	yes

Examples

y = fun_2d_outer(data, min)

Defined in

$HPEESOF_DIR/expressions/ael/statistcal_fun.ael

See Also

max_outer(), mean_outer(), min_outer()

Notes/Equations

Used in max_outer(), mean_outer(), min_outer() functions.
Functions such as mean, max, and min operate on the inner dimension of two-dimensional data. The function fun_2d_outer enables these functions to be applied to the outer dimension. As an example, assume that a Monte Carlo simulation of an amplifier was run, with 151 random sets of parameter values, and that for each set the S-parameters were simulated over 26 different frequency points. S21 becomes a [151 Monte Carlo iteration X 26 frequency] matrix, with the inner dimension being frequency, and the outer dimension being Monte Carlo index. Now, assume that it is desired to know the mean value of the S-parameters at each frequency. Inserting an equation mean(S21) computes the mean value of S21 at each Monte Carlo iteration. If S21 is simulated from 1 to 26 GHz, it computes the mean value over this frequency range, which usually is not very useful. The function fun_2d_outer allows the mean to be computed over each element in the outer dimension.