Question

Note: This is part 2 of a 2 part question.

Part 1 here

I’m wanting to more about sorting algorithms and what better way to do than then to code! So I figure I need some data to work with.

My approach to creating some “standard” data will be as follows: create a set number of items, not sure how large to make it but I want to have fun and make my computer groan a little bit 😀

Once I have that list, I’ll push it into a text file and just read off that to run my algorithms against. I should have a total of 4 text files filled with the same data but just sorted differently to run my algorithms against (see below).

Correct me if I’m wrong but I believe I need 4 different types of scenarios to profile my algorithms.

• Randomly sorted data (for this I’m going to use the knuth shuffle)
• Reversed data (easy enough)
• Nearly sorted (not sure how to implement this)
• Few unique (once again not sure how to approach this)

This question is for generating a list with a few unique items of data.

Which approach is best to generate a dataset with a few unique items.

Answer 1

Answering my own question here. Don’t know if this is the best but it works.

    public static int[] FewUnique(int uniqueCount, int returnSize)
    {
        Random r = _random;
        int[] values = new int[uniqueCount];
        for (int i = 0; i < uniqueCount; i++)
        {
            values[i] = i;
        }

        int[] array = new int[returnSize];
        for (int i = 0; i < returnSize; i++)
        {
            array[i] = values[r.Next(0, values.Count())];
        }

        return array;
    }