# Lightweight Math Combinations Using C# — Visual Studio Magazine

The Data Science Lab

### Lightweight math combinations using C#

After discussing permutations earlier, Dr. James McCaffrey of Microsoft Research uses step-by-step examples and complete code walkthroughs to explore the combinations.

A zero-based mathematical combination (n, k) is a subset of k integers from 0 to n-1. For example, if n = 5 and k = 3 there are 10 combinations:

0 1 2 0 1 3 0 1 4 0 2 3 0 2 4 0 3 4 1 2 3 1 2 4 1 3 4 2 3 4

It is customary to list combinations in what is called lexicographical order. If each combination is interpreted as an ordinary integer, the combinations are listed from smallest (12) to largest (234).

The number of (n,k) combinations is n! / (k! * (nk)!) where n! is factorial(n) = n * (n-1) * (n-2) * . . 1. The function is often called Choose(). For example, Pick(5, 3) = 5! / (3! * (5-3)!) = 120 / (6 * 2) = 120 / 12 = 10.

The number of combinations becomes very, very large as n and k increase. For example, Choose(500, 100) =

204,169,423,593,847,671,561,387,240,724,193,094, 030,165,460,090,325,932,474,143,661,505,758,330, 944,415,515,994,945,349,100,113,181,687,417,345

which is significantly larger than the estimated number of atoms in the Universe.

To handle combinations using the C# language, it is necessary to use the BigInteger data type which can handle arbitrarily large values.

Mathematical combinations are related to mathematical permutations, but very different from them. A zero-based mathematical permutation of order n is a rearrangement of the integers from 0 to n-1. For example, a permutation of order n = 5 is (2, 0, 1, 4, 3).

A good way to see where this article is going is to take a look at the screenshot of a demo program in **Figure 1**. The demo shows how to create and display a (n,k) combination, calculate Choose(n,k) using the BigInteger type, display all (n,k) combinations using a Successor() function and directly calculate an element of specific combination.

This article assumes you have intermediate or better programming skills with the C# language, but does not assume you know anything about mathematical combinations. The complete demo code is shown in this article and is also available in the accompanying download. All normal error checking has been removed to keep the main ideas as clear as possible.

To create the demo program, I used Visual Studio 2022 (the free community edition) with .NET 6 (despite the new “dead” console model). However, the demo has no significant dependencies, so all relatively recent versions of VS and .NET can be used.

**Define and display a combination**

The easiest way to define a mathematical combination is to use an array of integers. The demo program implements a MakeComb() function like:

static int[] MakeComb(int n, int k) { int[] result = new int[k]; for (int i = 0; i < k; i++) result[i] = i; return result; }

The MakeComb() function can be called like this:

int n = 5; int k = 3; int[] c = MakeComb(n, k); Console.WriteLine("Initial Combination(n=5, k=3) is: "); ShowComb(c);

The ShowComb() function is defined as:

static void ShowComb(int[] comb) { int n = comb.Length; for (int i = 0; i < n; ++i) Console.Write(comb[i] + " "); Console.WriteLine(""); }

An alternative design is to define a dedicated Combination class, but in most scenarios using an array of integers is simple and efficient.

**Defining a Choose function**

The demo program uses the BigInteger type to define a Choose() function as shown in **List 1**. The function uses several mathematical tricks for efficiency. The first trick is based on the idea that Choose(n, k) = Choose(n, nk), for example, Choose(100, 97) has the same value as Choose(100, 3). This trick is useful because small values of k are easier to calculate.

The second tip is best explained with a concrete example. Computing Choose() using the base definition is inefficient because the n! and k! factorial terms can be very large. Another Choose() definition looks like this:

Choose(100, 3) = (100 * 99 * 98) / (3 * 2 * 1) = 50 * 33 * 98 = 161,700

In words, the denominator is k! (which using the first trick can be small) and the numerator is k terms in the form n * (n-1) * (n-2) * . . . which is much smaller than n!

**List 1:** A Choose() function

using System.Numerics; static BigInteger Choose(int n, int k) { // number combinations if (n < 0 || k < 0) throw new Exception("Negative argument in Choose()"); if (n < k) return 0; // special if (n == k) return 1; // short-circuit int delta, iMax; if (k < n - k) // ex: Choose(100,3) { delta = n - k; iMax = k; } else // ex: Choose(100,97) { delta = k; iMax = n - k; } BigInteger ans = delta + 1; for (int i = 2; i <= iMax; ++i) ans = (ans * (delta + i)) / i; return ans; }

The BigInteger type is defined in the System.Numerics namespace. The demo code defines Choose(n, k) as 0 when n

The demo program calls the Choose() function like this:

BigInteger numCombs = Choose(5,3); Console.WriteLine("Number of n=5, k=3 combs is: "); Console.WriteLine(numCombs); numCombs = Choose(100, 10); Console.WriteLine("Number ways choose 10 from 100: "); Console.WriteLine(numCombs.ToString("N0"));

Because the result of the Choose() function can be very large, it is often useful to use the “N0” formatting specification to place commas in the output.

**Definition of a successor function**

Defining a function that returns the successor combination of a given combination is a well-known problem. The demo program defines a Successor() function in **List 2**.

**List 2:** The Combination Successor() function

static int[] Successor(int[] comb, int n, int k) { if (IsLast(comb, n, k) == true) return null; int[] result = new int[k]; // make copy for (int i = 0; i < k; ++i) result[i] = comb[i]; int idx = k - 1; while (idx > 0 && result[idx] == n - k + idx) --idx; ++result[idx]; for (int j = idx; j < k - 1; ++j) result[j + 1] = result[j] + 1; return result; }

Suppose n = 10 and k = 6 and a current combination is (0, 2, 3, 4, 8, 9). The successor combination is (0, 2, 3, 5, 6, 7).

The Successor() function first finds the leftmost index (idx) of the value to increment. In this example idx = [3]. The value at [3] is 4 and it is incremented giving an intermediate result of (0, 2, 3, 5, 8, 9). Then the algorithm sequentially increments the tail values to the right of idx giving the final successor result of (0, 2, 3, 5, 6, 7).

With a Successor() function in hand, it is possible to iterate through all the combinations with code like:

int[] c = MakeComb(5, 3); // [0,1,2] Console.WriteLine("All n=5, k=3 combinations: "); while (c != null) { ShowComb(c); c = Successor(c, n, k); }

The Successor() demo function returns null if the current combination is the last combination. For example, for n = 8 and k = 3, the last combination in lexicographical order is (5, 6, 7). The demo program defines an IsLast() function as:

static bool IsLast(int[] comb, int n, int k) { // is comb(8,3) like [5,6,7] ? if (comb[0] == n - k) return true; else return false; }

The last combination (n, k) will have the form (nk), (n-k+1), . . (n-1). Due to the lexicographical order, it is enough to check the first value of the combination to see if it is nk because this condition is only true for the last combination.

**The lexicographic combination element meme directly**

Suppose you want a specific combination item. For example, all the combinations 10 n = 5, k = 3 are:

[0] 0 1 2 [1] 0 1 3 [2] 0 1 4 [3] 0 2 3 [4] 0 2 4 [5] 0 3 4 [6] 1 2 3 [7] 1 2 4 [8] 1 3 4 [9] 2 3 4

You want a function named Element that accepts an index, m, and returns the specified combination, for example, for n = 5 and k = 3, Element(m=5) returns (0, 3, 4).

Because there are only Choose(5, 3) = 10 possible combinations, you can start with the initial combination (0, 1, 2) then call the Successor() function in a for loop with five iterations and finish to the desired combination combination.

But this simple approach only works for very small values of n and k. Surprisingly enough, it is possible to write a function that directly returns a specified combination. The demo program defines an Element() function in **List 3**.

**List 3:** Direct calculation of the same combination element

static int[] Element(BigInteger m, int n, int k) { // compute element [m] using the combinadic BigInteger maxM = Choose(n, k) - 1; if (m > maxM) throw new Exception("m value is too large in Element"); int[] ans = new int[k]; int a = n; int b = k; BigInteger x = maxM - m; // x is the "dual" of m for (int i = 0; i < k; ++i) { ans[i] = LargestV(a, b, x); // see helper below x = x - Choose(ans[i], b); a = ans[i]; b = b - 1; } for (int i = 0; i < k; ++i) ans[i] = (n - 1) - ans[i]; return ans; } static int LargestV(int a, int b, BigInteger x) { int v = a - 1; while (Choose(v, b) > x) --v; return v; }

The Element() function calls a LargestV() helper function. The Element() function can be called like this:

int n = 100; int k = 10; BigInteger m = BigInteger.Parse("9999999999"); int[] c = Element(m, n, k); Console.WriteLine("Combination [" + m + "] " + " of C(n=100,k=10): "); ShowComb(c);

The algorithm of the Element() function is beautiful but quite complicated. The algorithm is based on expressing an integer as a “combinadic”, which is a linear combination of the values of the Choose() function. You can find a detailed explanation of the algorithm in my blog post.

**Wrap**

The examples in this article use zero-based combinations. This is convenient because in many practical uses of combinations, combination values correspond to array indices. In a pure mathematical context, one-based combinations are more common.

An idea closely related to mathematical combinations goes by the rather strange name “Stirling numbers of the second kind”, usually written in the form S(n, k). The function returns the number of ways to partition n elements into k subsets. For example, suppose n = 4 and k = 2, then S(4, 2) = 7. If the n elements are (0, 1, 2, 3) then the 7 partitions are: (0 | 123), (1 |023), (2|013), (3|012), (01|23), (02|13) and (03|12). It is possible to implement the function S(n, k) using the ideas presented in this article.

About the Author

Dr. James McCaffrey works for Microsoft Research in Redmond, Washington. He has worked on several Microsoft products including Azure and Bing. Jacques can be reached at [email protected].

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