medopal medopal - 5 months ago 23
Java Question

Fastest algorithm to check if a number is pandigital?

Pandigital number is a number that contains the digits 1..number length.

For example 123, 4312 and 967412385.

I have solved many Project Euler problems, but the Pandigital problems always exceed the one minute rule.

This is my pandigital function:

private boolean isPandigital(int n){
Set<Character> set= new TreeSet<Character>();
String string = n+"";
for (char c:string.toCharArray()){
if (c=='0') return false;
set.add(c);
}
return set.size()==string.length();
}


Create your own function and test it with this method

int pans=0;
for (int i=123456789;i<=123987654;i++){
if (isPandigital(i)){
pans++;
}
}


Using this loop, you should get 720 pandigital numbers. My average time was 500 millisecond.

I'm using Java, but the question is open to any language.

UPDATE

@andras answer has the best time so far, but @Sani Huttunen answer inspired me to add a new algorithm, which gets almost the same time as @andras.

Answer

C#, 17ms, if you really want a check.

class Program
{
    static bool IsPandigital(int n)
    {
        int digits = 0; int count = 0; int tmp;

        for (; n > 0; n /= 10, ++count)
        {
            if ((tmp = digits) == (digits |= 1 << (n - ((n / 10) * 10) - 1)))
                return false;
        }

        return digits == (1 << count) - 1;
    }

    static void Main()
    {
        int pans = 0;
        Stopwatch sw = new Stopwatch();
        sw.Start();
        for (int i = 123456789; i <= 123987654; i++)
        {
            if (IsPandigital(i))
            {
                pans++;
            }
        }
        sw.Stop();
        Console.WriteLine("{0}pcs, {1}ms", pans, sw.ElapsedMilliseconds);
        Console.ReadKey();
    }
}

For a check that is consistent with the Wikipedia definition in base 10:

const int min = 1023456789;
const int expected = 1023;

static bool IsPandigital(int n)
{
    if (n >= min)
    {
        int digits = 0;

        for (; n > 0; n /= 10)
        {
            digits |= 1 << (n - ((n / 10) * 10));
        }

        return digits == expected;
    }
    return false;
}

To enumerate numbers in the range you have given, generating permutations would suffice.

The following is not an answer to your question in the strict sense, since it does not implement a check. It uses a generic permutation implementation not optimized for this special case - it still generates the required 720 permutations in 13ms (line breaks might be messed up):

static partial class Permutation
{
    /// <summary>
    /// Generates permutations.
    /// </summary>
    /// <typeparam name="T">Type of items to permute.</typeparam>
    /// <param name="items">Array of items. Will not be modified.</param>
    /// <param name="comparer">Optional comparer to use.
    /// If a <paramref name="comparer"/> is supplied, 
    /// permutations will be ordered according to the 
    /// <paramref name="comparer"/>
    /// </param>
    /// <returns>Permutations of input items.</returns>
    public static IEnumerable<IEnumerable<T>> Permute<T>(T[] items, IComparer<T> comparer)
    {
        int length = items.Length;
        IntPair[] transform = new IntPair[length];
        if (comparer == null)
        {
            //No comparer. Start with an identity transform.
            for (int i = 0; i < length; i++)
            {
                transform[i] = new IntPair(i, i);
            };
        }
        else
        {
            //Figure out where we are in the sequence of all permutations
            int[] initialorder = new int[length];
            for (int i = 0; i < length; i++)
            {
                initialorder[i] = i;
            }
            Array.Sort(initialorder, delegate(int x, int y)
            {
                return comparer.Compare(items[x], items[y]);
            });
            for (int i = 0; i < length; i++)
            {
                transform[i] = new IntPair(initialorder[i], i);
            }
            //Handle duplicates
            for (int i = 1; i < length; i++)
            {
                if (comparer.Compare(
                    items[transform[i - 1].Second], 
                    items[transform[i].Second]) == 0)
                {
                    transform[i].First = transform[i - 1].First;
                }
            }
        }

        yield return ApplyTransform(items, transform);

        while (true)
        {
            //Ref: E. W. Dijkstra, A Discipline of Programming, Prentice-Hall, 1997
            //Find the largest partition from the back that is in decreasing (non-icreasing) order
            int decreasingpart = length - 2;
            for (;decreasingpart >= 0 && 
                transform[decreasingpart].First >= transform[decreasingpart + 1].First;
                --decreasingpart) ;
            //The whole sequence is in decreasing order, finished
            if (decreasingpart < 0) yield break;
            //Find the smallest element in the decreasing partition that is 
            //greater than (or equal to) the item in front of the decreasing partition
            int greater = length - 1;
            for (;greater > decreasingpart && 
                transform[decreasingpart].First >= transform[greater].First; 
                greater--) ;
            //Swap the two
            Swap(ref transform[decreasingpart], ref transform[greater]);
            //Reverse the decreasing partition
            Array.Reverse(transform, decreasingpart + 1, length - decreasingpart - 1);
            yield return ApplyTransform(items, transform);
        }
    }

    #region Overloads

    public static IEnumerable<IEnumerable<T>> Permute<T>(T[] items)
    {
        return Permute(items, null);
    }

    public static IEnumerable<IEnumerable<T>> Permute<T>(IEnumerable<T> items, IComparer<T> comparer)
    {
        List<T> list = new List<T>(items);
        return Permute(list.ToArray(), comparer);
    }

    public static IEnumerable<IEnumerable<T>> Permute<T>(IEnumerable<T> items)
    {
        return Permute(items, null);
    }

    #endregion Overloads

    #region Utility

    public static IEnumerable<T> ApplyTransform<T>(
        T[] items, 
        IntPair[] transform)
    {
        for (int i = 0; i < transform.Length; i++)
        {
            yield return items[transform[i].Second];
        }
    }

    public static void Swap<T>(ref T x, ref T y)
    {
        T tmp = x;
        x = y;
        y = tmp;
    }

    public struct IntPair
    {
        public IntPair(int first, int second)
        {
            this.First = first;
            this.Second = second;
        }
        public int First;
        public int Second;
    }

    #endregion
}

class Program
{

    static void Main()
    {
        int pans = 0;
        int[] digits = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        Stopwatch sw = new Stopwatch();
        sw.Start();
        foreach (var p in Permutation.Permute(digits))
        {
            pans++;
            if (pans == 720) break;
        }
        sw.Stop();
        Console.WriteLine("{0}pcs, {1}ms", pans, sw.ElapsedMilliseconds);
        Console.ReadKey();
    }
}
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