GeneGenerator, C# - rextester

Language: Layout:

//GeneGenerator 1.0
//Copyright (C) 2013 nickolas360

/* 
 * How to use GeneGenerator:
 * 
 * First, you must define all genes you want to use.
 * 
 * The format is:
 * (Heterozygous Genotype)/Dominant Phenotype/Recessive Phenotype/Heterozygous Phenotype
 * The Heterozygous Phenotype is not necessary if it is the same as the Dominant Phenotype.
 * 
 * Only input the heterozygous genotype at the beginning! The program will assume that the
 * first letter is the dominant allele, and the second letter is the recessive one.
 * 
 * For example, to define a gene Tt, with TT and Tt being tall and tt being short, you would type:
 * Tt/Tall/Short
 * 
 * To define a gene with codominance BY, with BB being blue, YY being yellow, and BY being spotted, type:
 * BY/Blue/Yellow/Spotted
 * (You could switch the order of B and Y, as there is no "dominant" gene)
 * 
 * Example definitions for blood:
 * AO/A blood/O blood
 * BO/B blood/O blood
 * AB/A blood/B blood/AB blood
 * 
 * Example definitions for colorblindness (sex-linked):
 * Cc/Normal vision/Colorblind     <-- For female
 * CY/Normal vision/               <-- For male; include slash at the end (YY will never happen)
 * cY/Colorblind/                  <-- For male; include slash at the end (YY will never happen)
 */

/* 
 * Next, specify any parameters you would like.
 * 
 * Type "sortcount" to sort numbers of genotypes and phenotypes by how many of each kind
 * exist, rather than organizing from most dominant to most recessive.
 * 
 * Type "punnet" to generate a punnet square in addition to genotype and phenotype information.
 */

/* 
 * Next, type "start"
 * 
 * Input two genotype combinations.
 * These are just strings of genotypes.
 * For example, AaBbCc or TtBYrrMm.
 * 
 * The two genotype combinations must be the same number of genotypes.
 */

/* 
 * The information should be displayed.
 */

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Rextester
{
    public class Program
    {
        private static List<GenotypeInfo> definedGenotypes = new List<GenotypeInfo>();
        private static string[,] rawResults;
        private static Dictionary<string, Tuple<int, int>> resultsCount = new Dictionary<string, Tuple<int, int>>();
        private static Dictionary<string, Tuple<int, int>> resultsPhenotypeCount = new Dictionary<string, Tuple<int, int>>();
        private static List<KeyValuePair<string, Tuple<int, int>>> sortedResultsCount;
        private static List<KeyValuePair<string, Tuple<int, int>>> sortedResultsPhenotypeCount;
        private static bool sortByCount = false;
        private static bool punnetSquare = false;

public static void Main(string[] args)
        {
            //Get user input.
            string input = Console.ReadLine();
            //If input is "start", stop acceping gene definitions.
            while (input != "START" && input != "Start" && input != "start")
            {
                if (input == "SORTCOUNT" || input == "Sortcount" || input == "sortCount" || input == "sortcount")
                {
                    //If input is "sortcount", set the sortByCount flag.
                    sortByCount = true;
                }
                else if (input == "PUNNET" || input == "Punnet" || input == "punnet")
                {
                    //If input is "punnet", set the punnetSquare flag.
                    punnetSquare = true;
                }
                else
                {
                    //Otherwise, parse gene definition.
                    string heterozygousGenotype;
                    string dominantPhenotype;
                    string recessivePhenotype;
                    string heterozygousPhenotype;

//Get heterozygous genotype (already entered).
                    heterozygousGenotype = input.Substring(0, input.IndexOf('/'));
                    input = input.Substring(input.IndexOf('/') + 1);

//Get dominant phenotype.
                    dominantPhenotype = input.Substring(0, input.IndexOf('/'));
                    input = input.Substring(input.IndexOf('/') + 1);

//If there is only one more phenotype definition, gene is normal dominant-recessive.
                    //Otherwise, there is a incomplete/co-dominance phenotype.
                    if (input.IndexOf('/') == -1)
                    {
                        recessivePhenotype = input;
                        heterozygousPhenotype = dominantPhenotype;
                    }
                    else
                    {
                        recessivePhenotype = input.Substring(0, input.IndexOf('/'));
                        input = input.Substring(input.IndexOf('/') + 1);
                        heterozygousPhenotype = input;
                    }

//Generate dominant and recessive genotypes.
                    string dominantGenotype = heterozygousGenotype[0].ToString() + heterozygousGenotype[0].ToString();
                    string recessiveGenotype = heterozygousGenotype[1].ToString() + heterozygousGenotype[1].ToString();

//Create instances of GenotypeInfo and add them to the list.
                    definedGenotypes.Add(new GenotypeInfo(dominantGenotype, dominantPhenotype, 0));
                    definedGenotypes.Add(new GenotypeInfo(recessiveGenotype, recessivePhenotype, 2));
                    definedGenotypes.Add(new GenotypeInfo(heterozygousGenotype, heterozygousPhenotype, 1));
                }
                
                //Read user input again.
                input = Console.ReadLine();
            }

//Get results.
            GetResults();
            /*Console.ReadKey(true);*/
        }

public static void GetResults()
        {
            //Get genotype combinations.
            /*Console.WriteLine("Genotype combination 1:");*/
            string genotypeCollection1 = Console.ReadLine();
            /*Console.WriteLine("Genotype combination 2:");*/
            string genotypeCollection2 = Console.ReadLine();
            /*Console.Write("\n\n");*/

//Variables.
            int genotypeCount = genotypeCollection1.Length / 2;

string[] genotypes1 = new string[genotypeCount];
            string[] genotypes2 = new string[genotypeCount];
            
            char[] firstAlleles1 = new char[genotypeCount];
            char[] secondAlleles1 = new char[genotypeCount];
            char[] firstAlleles2 = new char[genotypeCount];
            char[] secondAlleles2 = new char[genotypeCount];

//Separate genotypes.
            for (int i = 0; i < genotypeCount; i++)
            {
                genotypes1[i] = genotypeCollection1.Substring(i * 2, 2);
                genotypes2[i] = genotypeCollection2.Substring(i * 2, 2);
            }

//Separate alleles.
            for (int i = 0; i < genotypeCount; i++)
            {
                firstAlleles1[i] = genotypes1[i][0];
                secondAlleles1[i] = genotypes1[i][1];
                firstAlleles2[i] = genotypes2[i][0];
                secondAlleles2[i] = genotypes2[i][1];
            }

//Get combinations.
            string[] combinationsTop = GetCombinations(new string[] { string.Empty }, firstAlleles1.Length - 1, firstAlleles1, secondAlleles1);
            string[] combinationsLeft = GetCombinations(new string[] { string.Empty }, firstAlleles2.Length - 1, firstAlleles2, secondAlleles2);

//If punnet square was requested, a raw results array is needed.
            if (punnetSquare) { rawResults = new string[combinationsTop.Length, combinationsLeft.Length]; }

//Loops for top row * left row (this multiplies like a punnet square)
            for (int i = 0; i < combinationsLeft.Length; i++)
            {
                for (int k = 0; k < combinationsTop.Length; k++)
                {
                    string singleCrossGenotypes = string.Empty;
                    string fullCrossGenotypes = string.Empty;
                    string singleCrossPhenotypes = string.Empty;
                    string fullCrossPhenotypes = string.Empty;
                    int rank = 0;

//Cross each gene and add it to the current full cross.
                    for (int m = 0; m < genotypeCount; m++)
                    {
                        //Cross one gene.
                        singleCrossGenotypes = combinationsTop[k][m].ToString() + combinationsLeft[i][m].ToString();

foreach (GenotypeInfo genotypeInfo in definedGenotypes)
                        {
                            //Locate the instance of GenotypeInfo the crossed genotype corresponds to.
                            if (genotypeInfo.GenotypeMatches(singleCrossGenotypes))
                            {
                                //Store values.
                                singleCrossGenotypes = genotypeInfo.Genotype;
                                singleCrossPhenotypes = genotypeInfo.Phenotype;

//Generate rank.
                                rank += (int)Math.Pow(3, genotypeCount - (m + 1)) * genotypeInfo.Dominance;
                            }
                        }

//Add single-gene crosses to the multi-gene ones (and format phenotype strings).
                        fullCrossGenotypes += singleCrossGenotypes;
                        fullCrossPhenotypes += fullCrossPhenotypes == string.Empty ? singleCrossPhenotypes : ", " + singleCrossPhenotypes;
                    }

//If punnet square was requested, add genotype combination to the raw results array.
                    if (punnetSquare) { rawResults[i, k] = fullCrossGenotypes; }

//If the generated geno/phenotype combination already exists, and one to the count.
                    //If not, create a new dictionary entry and set the count to one.
                    if (resultsCount.ContainsKey(fullCrossGenotypes))
                    {
                        resultsCount[fullCrossGenotypes] = Tuple.Create(
                            resultsCount[fullCrossGenotypes].Item1 + 1,
                            resultsCount[fullCrossGenotypes].Item2);
                    }
                    else
                    {
                        resultsCount.Add(fullCrossGenotypes, Tuple.Create(1, rank));
                    }

if (resultsPhenotypeCount.ContainsKey(fullCrossPhenotypes))
                    {
                        resultsPhenotypeCount[fullCrossPhenotypes] = Tuple.Create(
                            resultsPhenotypeCount[fullCrossPhenotypes].Item1 + 1,
                            resultsPhenotypeCount[fullCrossPhenotypes].Item2);
                    }
                    else
                    {
                        resultsPhenotypeCount.Add(fullCrossPhenotypes, Tuple.Create(1, rank));
                    }
                }
            }

//Sort arrays by rank (AABBCC...aabbcc, and equivalent phenotypes).
            sortedResultsCount = resultsCount.ToList();
            sortedResultsCount.Sort((firstPair, nextPair) =>
            {
                return firstPair.Value.Item2.CompareTo(nextPair.Value.Item2);
            });

sortedResultsPhenotypeCount = resultsPhenotypeCount.ToList();
            sortedResultsPhenotypeCount.Sort((firstPair, nextPair) =>
            {
                return firstPair.Value.Item2.CompareTo(nextPair.Value.Item2);
            });

//Sort by the number of instances of each geno/phenotype, if requested.
            if (sortByCount)
            {
                sortedResultsCount.Sort((firstPair, nextPair) =>
                {
                    return firstPair.Value.Item1.CompareTo(nextPair.Value.Item1);
                });

sortedResultsPhenotypeCount.Sort((firstPair, nextPair) =>
                {
                    return firstPair.Value.Item1.CompareTo(nextPair.Value.Item1);
                });
            }

//Display information to the user.
            DisplayInformation(genotypeCount, combinationsTop, combinationsLeft);
        }

public static string[] GetCombinations(string[] currentArray, int allelePosition, char[] firstAlleles, char[] secondAlleles)
        {
            if (allelePosition >= 0)
            {
                //Double the current array, and to half, and one allele, and to the other half, add the other.
                string[] newCombinations = new string[currentArray.Length * 2];

for (int i = 0; i < currentArray.Length; i++)
                {
                    newCombinations[i] = firstAlleles[allelePosition] + currentArray[i];
                    newCombinations[i + currentArray.Length] = secondAlleles[allelePosition] + currentArray[i];
                }

//Move the allele position along one and run the function again.
                return GetCombinations(newCombinations, allelePosition - 1, firstAlleles, secondAlleles);
            }
            else
            {
                //If the end of the alleles has been reached, return the array.
                return currentArray;
            }
        }

public static void DisplayInformation(int numberOfGenotypes, string[] top, string[] left)
        {
            //If requested, display a punnet square.
            if (punnetSquare)
            {
                Console.Write(new string(' ', numberOfGenotypes + 1));
                foreach (string alleleCombination in top)
                {
                    Console.Write(alleleCombination + new string(' ', numberOfGenotypes + 1));
                }

for (int i = 0; i < left.Length; i++)
                {
                    Console.Write("\n" + left[i] + ' ');
                    for (int k = 0; k < top.Length; k++)
                    {
                        Console.Write(rawResults[i, k] + ' ');
                    }
                }

Console.Write("\n\n");
            }
            
            //Write out how many of each geno/phenotype combination there are.
            foreach (KeyValuePair<string, Tuple<int, int>> genotypePair in sortedResultsCount)
            {
                Console.WriteLine("-- {0} instance{1} of genotype {2}.", genotypePair.Value.Item1, genotypePair.Value.Item1 > 1 ? "s" : " ", genotypePair.Key);
            }

Console.Write("\n");

foreach (KeyValuePair<string, Tuple<int, int>> phenotypePair in sortedResultsPhenotypeCount)
            {
                Console.WriteLine("-- {0} instance{1} of phenotype {2}.", phenotypePair.Value.Item1, phenotypePair.Value.Item1 > 1 ? "s" : " ", phenotypePair.Key);
            }
        }
    }
    
    public class GenotypeInfo
    {
        public string Genotype { get; set; }
        public string Phenotype { get; set; }
        public int Dominance { get; set; }

public GenotypeInfo(string genotype, string phenotype, int dominance)
        {
            Genotype = genotype;
            Phenotype = phenotype;
            Dominance = dominance;
        }

public bool GenotypeMatches(string genotype)
        {
            if (genotype == Genotype)
            {
                return true;
            }
            else if (genotype[1].ToString() + genotype[0].ToString() == Genotype)
            {
                return true;
            }
            else
            {
                return false;
            }
        }
    }
}

Show compiler warnings [ - ] Show input
Compilation time: 0.14 sec, absolute running time: 0.12 sec, cpu time: 0.06 sec, average memory usage: 22 Mb, average nr of threads: 6