How to make a function that picks according to a changing distribution, without passing over and over?

This is not a question about MatLab, but it is a question about how to achieve something that would be easy in object-oriented programming when you're using a less sophisticated language.

I'm a mathematician who is writing some MatLab code to test an algorithm in linear algebra (I won't burden you with the details). The beginning of the program is to generate a random 500 by 50 matrix of floats (call it A). In the course of running my program, I will want to pick random rows of A, not uniformly at random, but rather according to a distribution where the likelihood of row i being picked is different, depending on the specific matrix that has been generated.

I want to write a function called "pickRandomRow" that I can call over and over when I need it. It will use the same probability distribution on the rows throughout each individual run of the program, but that distribution will change between runs of the program (because the random matrix will be different).

If I were using a more object-oriented language than MatLab, I would make a class called "rowPicker" which could be initialized with the information about the specific random matrix I'm using on this run. But here, I'm not sure how to make a function in MatLab that can know the information it needs to know about the random matrix A once and for all, without passing A to the function over and over (expensively), when it's not changing.

Possible options

• Make pickRandomRow a script instead of a function, so it can see the workspace. Then I wouldn't be able to give pickRandomRow any arguments, but so far I don't see why I'd need to.
• Start messing areound with classes in MatLab.