Generate line function data with noise

General Usage
1

I would like to assess one dimension reduction method on simulation data. Besides totally random data, I want to simulate a partial random dataset. Right now I can think of one method to generate such data

rand2 = collect(1:85)
for m in 1:20
v = []
for i in 1:85
    ai = i/m
    bi = rand(Float64)
    pi = i/85
    push!(v, ai+bi*pi)
end
rand2=hcat(rand2,v)
end
rand2 =rand2[:, (1:end) .!= 1]

Is there a better way to generate partially random data? Like data points follow line functions but there are noises. Thanks in advance!

2

List comprehensions provide this functionality quite nicely. You can easily generate a 2-dimensional matrix by specifying two dimensions to loop over (iterating over the ith row and jth column):

rand2 = [i*(1/j+rand()/85) for i=1:85, j=1:20]

This doesn’t work so well when one value in the matrix depends on the value of another, but that’s not the case here.