public void Crossover_TwoChromosomesOnePercentProbability_CrossoverNotHappend()
{
var probability = 0.1m;
var representation1 = new IGene <decimal> [2];
var representation2 = new IGene <decimal> [2];
var gene1Representation = new[] { 1.2m, 1.3m, 1.4m, 1.5m };
var gene2Representation = new[] { 1.6m, 1.7m, 1.8m, 1.9m };
var gene3Representation = new[] { 2.6m, 2.7m, 2.8m, 2.9m };
representation1[0] = new Gene <decimal>(gene1Representation, probability);
representation1[1] = new Gene <decimal>(gene2Representation, probability);
representation2[0] = new Gene <decimal>(gene1Representation, probability);
representation2[1] = new Gene <decimal>(gene3Representation, probability);
var x = new Chromosome <decimal>(representation1);
var y = new Chromosome <decimal>(representation2);
var crossover = new Crossover(0.01m);
var crossed = crossover.RunCrossover(x, y, probability);
Assert.AreEqual(crossed.Representation[1].Representation[0], gene2Representation[0]);
Assert.AreEqual(crossed.Representation[1].Representation[1], gene2Representation[1]);
Assert.AreEqual(crossed.Representation[1].Representation[2], gene2Representation[2]);
Assert.AreEqual(crossed.Representation[1].Representation[3], gene2Representation[3]);
}
public GeneComparerTests()
{
_geneA = new Gene(ChromosomeUtilities.Chr1, 100, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneB = new Gene(ChromosomeUtilities.Chr1, 100, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneC = new Gene(ChromosomeUtilities.Chr1, 101, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneComparer = new GeneComparer();
}
/// <summary>
/// Get a list of the genes that have not been taken before. This is useful
/// if you do not wish the same gene to appear more than once in a
/// chromosome.
/// </summary>
/// <param name="source">The pool of genes to select from.</param>
/// <param name="taken">An array of the taken genes.</param>
/// <returns>Those genes in source that are not taken.</returns>
private static IGene GetNotTaken(Chromosome source,
IList <IGene> taken)
{
int geneLength = source.Genes.Count;
for (int i = 0; i < geneLength; i++)
{
IGene trial = source.Genes[i];
bool found = false;
foreach (IGene current in taken)
{
if (current.Equals(trial))
{
found = true;
break;
}
}
if (!found)
{
taken.Add(trial);
return(trial);
}
}
return(null);
}
public void DisplacementOperatorShouldReturnCorrectChildren()
{
IGene[] parent = new IGene[]
{
new UintGene(1), new UintGene(2), new UintGene(3),
new UintGene(4), new UintGene(5), new UintGene(6),
new UintGene(7), new UintGene(8), new UintGene(9)
};
IGene[] expectedChild = new IGene[]
{
new UintGene(4), new UintGene(5), new UintGene(6),
new UintGene(1), new UintGene(2), new UintGene(3),
new UintGene(7), new UintGene(8), new UintGene(9)
};
int startPoint = 3, destPoint = 0, length = 3;
var swap = new DisplacementOperator();
swap.Run(parent, startPoint, destPoint, length);
bool areChildrenEqual = true;
for (int i = 0; i < expectedChild.Length; ++i)
{
areChildrenEqual &= expectedChild[i].Equals(parent[i]);
}
Assert.AreEqual(true, areChildrenEqual);
}
private ScatterViewItem _myDadSVI; //The scatterviewitem that has me as a DataContext
//private double _verticalScrollOffset;
//private ScatterViewItem _myUncleSVI; //The scatterviewitem that is aligned. Hook our scroll viewers
//private SurfaceScrollViewer _mySurfaceScrollViewer;
public TranslationViewModel(SurfaceWindow1ViewModel mainVM, IGene model)
{
_mainVM = mainVM;
_model = model;
_background = new SolidColorBrush(Colors.Black);
//_myUncleSVI = null; //Nothing is aligned to me yet
}
private void Mutate(IGenome genome, double soften = 1)
{
if (new Random().NextDouble() < GenerationParameters.MutateAddNodeProbability / Math.Max(soften, 1))
{
genome.MutateAddNode();
}
else if (new Random().NextDouble() < GenerationParameters.MutateAddGeneProbability / Math.Max(soften, 1))
{
genome.MutateAddGene(Population.Genomes.SelectMany(g => g.Genes));
}
else
{
if (new Random().NextDouble() < GenerationParameters.MutateAllGeneWeightsProbability)
{
genome.MutateGeneWeights(GeneMutationType.AdjustWeight, GeneParameters.MutateGeneWeightFactor, 1);
}
if (new Random().NextDouble() < GenerationParameters.MutateGeneExpressionProbability)
{
genome.MutateGeneExpression();
}
if (new Random().NextDouble() < GenerationParameters.MutateGeneReExpressionProbability)
{
genome.MutateGeneReExpress();
}
IGene geneCandidate = genome.Genes[new Random().Next(genome.Genes.Count)];
if (new Random().NextDouble() < GenerationParameters.MutateGeneWeightProbability)
{
geneCandidate.MutateWeight(GeneMutationType.AdjustWeight, GeneParameters.MutateGeneWeightFactor);
}
}
}
public IList<IPublication> GetResults(IGene gene)
{
//if (!String.IsNullOrEmpty(geneName))
//{
// PubMedParser parser = new PubMedParser(geneName);
// return parser.getPublicationsFromHTML();
//}
//if the gene has a name, use name as keyword, else use Locus Tag (Locus Tag with no results
//will be handled within getPublicationsFromHTML() from PubMedParser.cs
if (!String.IsNullOrEmpty(gene.Name))
{
PubMedParser parser = new PubMedParser(gene.Name);
return parser.getPublicationsFromHTML();
}
else if (!String.IsNullOrEmpty(gene.LocusTag))
{
PubMedParser parser = new PubMedParser(gene.LocusTag);
return parser.getPublicationsFromHTML();
}
else
{
return new List<IPublication>();
}
}
public void Run(IGene[] parent1, IGene[] parent2, out IGene[] child1, out IGene[] child2, bool[] mask)
{
int geneCount = parent1.Count();
IGene[] c1 = new IGene[geneCount];
IGene[] c2 = new IGene[geneCount];
for (int index = 0; index < mask.Length; ++index)
{
if (mask[index])
{
c1[index] = parent1[index];
c2[index] = parent2[index];
}
}
int firstParentIndex = 0, secondParentIndex = 0;
for (int index = 0; index < mask.Length; ++index)
{
if (!mask[index])
{
MoveGenesInZeroPositions(parent2, c1, index, ref secondParentIndex);
MoveGenesInZeroPositions(parent1, c2, index, ref firstParentIndex);
}
}
child1 = c1;
child2 = c2;
}
public Transcript(IChromosome chromosome, int start, int end, ICompactId id, ITranslation translation,
BioType bioType, IGene gene, int totalExonLength, byte startExonPhase, bool isCanonical,
ITranscriptRegion[] transcriptRegions, ushort numExons, IInterval[] microRnas, int siftIndex,
int polyPhenIndex, Source source, bool cdsStartNotFound, bool cdsEndNotFound, int[] selenocysteines,
IRnaEdit[] rnaEdits)
{
Chromosome = chromosome;
Start = start;
End = end;
Id = id;
Translation = translation;
BioType = bioType;
Gene = gene;
TotalExonLength = totalExonLength;
StartExonPhase = startExonPhase;
IsCanonical = isCanonical;
TranscriptRegions = transcriptRegions;
NumExons = numExons;
MicroRnas = microRnas;
SiftIndex = siftIndex;
PolyPhenIndex = polyPhenIndex;
Source = source;
CdsStartNotFound = cdsStartNotFound;
CdsEndNotFound = cdsEndNotFound;
Selenocysteines = selenocysteines;
RnaEdits = rnaEdits;
}
protected override IEnumerable <(IGene Root, string Origin)> GetVariations(IGene source)
{
//var sourceTree = Catalog.Factory.Map(source);
//var descendantNodes = sourceTree.GetDescendantsOfType().ToArray();
//var count = descendantNodes.Length;
return(null);
//int i;
//// Remove genes one at a time.
//for (i = 0; i < count; i++)
// if (Catalog.Variation.TryRemoveValid(descendantNodes[i], out var pruned))
// yield return (pruned, "Remove descendant by index");
//for (i = 0; i < count; i++)
//{
// yield return (
// Catalog.Variation.PromoteChildren(descendantNodes[i]),
// "Promote descendant children");
// // Let mutation take care of this...
// // foreach (var fn in Operators.Available.Functions)
// // {
// // yield return VariationCatalog.ApplyFunction(source, i, fn);
// // }
//}
//if (source is IParent)
//{
// var paramExpIncrease = Catalog.Variation.IncreaseParameterExponents(source);
// if (paramExpIncrease != source)
// {
// yield return (paramExpIncrease,
// "Increase all parameter exponent");
// }
//}
//for (i = 0; i < count; i++)
// yield return (
// Catalog.AddConstant(descendantNodes[i], 2),
// "Add constant to descendant"); // 2 ensures the constant isn't negated when adding to a product.
//sourceTree.Recycle();
//if (!(reduced is Sum<double> sum)) yield break;
//sourceTree = Catalog.Factory.Map(reduced);
//var clonedChildren = sourceTree.Children.Where(c => c.Value is IConstant<double>).ToArray();
//if (sourceTree.Count > clonedChildren.Length)
//{
// foreach (var c in clonedChildren)
// c.Detatch();
//}
//var next = Catalog.FixHierarchy(sourceTree).Recycle();
//sourceTree.Recycle();
//yield return (Catalog.GetReduced(next), "Constants Stripped");
//if (sum.TryExtractGreatestFactor(Catalog, out var extracted, out _))
// yield return (extracted, "GCF Extracted Reduction");
}
public void SwapOperatorShouldReturnCorrectChildren()
{
IGene[] parent = new IGene[]
{
new UintGene(1), new UintGene(2), new UintGene(3),
new UintGene(4), new UintGene(5), new UintGene(6),
new UintGene(7), new UintGene(8), new UintGene(9)
};
IGene[] expectedChild = new IGene[]
{
new UintGene(1), new UintGene(2), new UintGene(3),
new UintGene(8), new UintGene(5), new UintGene(6),
new UintGene(7), new UintGene(4), new UintGene(9)
};
int poiont1 = 3, poiont2 = 7;
var swap = new SwapOperator();
swap.Run(parent, poiont1, poiont2);
bool areChildrenEqual = true;
for (int i = 0; i < expectedChild.Length; ++i)
{
areChildrenEqual &= expectedChild[i].Equals(parent[i]);
}
Assert.AreEqual(true, areChildrenEqual);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// A new solution instance gets a reference to the same problem
/// and a new route list instance with the same references.
/// </summary>
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
public override object Clone()
{
IGene[] newGenes = new IGene[Genes.Length];
Array.Copy(Genes, newGenes, Genes.Length);
Solution copy = new Solution((VrptwProblem)Problem, newGenes);
return(copy);
}
public IGene Mate(IGene other)
{
NQueenGene ret = other.Clone() as NQueenGene;
for (int i = 0; i < ret.queen_location_.Length / 2; i++) {
ret.queen_location_[i] = queen_location_[i];
}
return ret;
}
// override object.Equals
public bool Equals(IGene obj)
{
if (obj == null || GetType() != obj.GetType())
{
return(false);
}
return(((Location)obj).Id == this.Id);
}
public Character Mutate(Character c, double probability)
{
IGene[] genes = new IGene[c.Genes.Length];
for (var i = 0; i < c.Genes.Length; i++)
{
genes[i] = rnd.NextDouble() < probability ? c.Genes[i].Mutate() : c.Genes[i];
}
return(new Character(c.CharacterType, genes));
}
public GeneComparerTests()
{
var chromosome = new Chromosome("chr1", "1", 0);
_geneA = new Gene(chromosome, 100, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneB = new Gene(chromosome, 100, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneC = new Gene(chromosome, 101, 200, false, "PAX", 123, CompactId.Convert("NM_123"), CompactId.Convert("ENST0000123"));
_geneComparer = new GeneComparer();
}
public ICollection <Character> Crossover(Character c1, Character c2)
{
int s = c1.Genes.Length;
int p = rnd.Next(s + 1);
var genes1 = new IGene[s];
var genes2 = new IGene[s];
c1.Genes[..p].CopyTo(genes1);
/// <summary>
/// Copy from another gene.
/// </summary>
/// <param name="gene">The other gene.</param>
public override void Copy(IGene gene)
{
NEATLinkGene other = (NEATLinkGene)gene;
this.Enabled = other.Enabled;
fromNeuronID = other.fromNeuronID;
toNeuronID = other.toNeuronID;
this.InnovationId = other.InnovationId;
recurrent = other.recurrent;
weight = other.weight;
}
/// <summary>
/// Copy another gene to this one.
/// </summary>
///
/// <param name="gene">The other gene.</param>
public override void Copy(IGene gene)
{
var other = (NEATNeuronGene)gene;
activationResponse = other.activationResponse;
Id = other.Id;
neuronType = other.neuronType;
recurrent = other.recurrent;
splitX = other.splitX;
splitY = other.splitY;
}
public void CopyTest()
{
IGene gene = new Gene(new Node(NodeType.Hidden), new Node(NodeType.Hidden), 1);
IGene copiedGene = gene.Copy();
Assert.AreEqual(gene.Innovation, copiedGene.Innovation);
Assert.AreEqual(gene.IsExpressed, copiedGene.IsExpressed);
Assert.AreEqual(gene.NodeIn.Id, copiedGene.NodeIn.Id);
Assert.AreEqual(gene.NodeOut.Id, copiedGene.NodeOut.Id);
Assert.AreEqual(gene.Weight, copiedGene.Weight);
}
public override Chromosome RandomNeighbourSolution(Chromosome chromosome, MutationOperator neighbourhood)
{
int size = chromosome.Size();
IGene[] newGenes = new IGene[size];
Array.Copy(chromosome.Genes, newGenes, size);
neighbourhood.Run(newGenes);
Chromosome result = new Solution(chromosome.Problem as VrptwProblem, newGenes);
return(result);
}
public bool IsSameAs(IGene other)
{
var otherFixture = other as Fixture;
if (otherFixture == null)
{
return false;
}
var otherHomeTeam = otherFixture.HomeTeam;
var otherAwayTeam = otherFixture.AwayTeam;
return HomeTeam.Equals(otherHomeTeam) && AwayTeam.Equals(otherAwayTeam);
}
public ICollection <Character> Crossover(Character c1, Character c2)
{
int s = c1.Genes.Length;
int p1 = rnd.Next(s + 1);
int p2 = rnd.Next(s + 1);
(p1, p2) = (Math.Min(p1, p2), Math.Max(p1, p2));
var genes1 = new IGene[s];
var genes2 = new IGene[s];
c1.Genes[..p1].CopyTo(genes1);
private void WriteGene(IGene gene, IRequiredFields requiredFields, string geneId, int internalGeneId)
{
if (_observedGenes.Contains(internalGeneId))
{
return;
}
_observedGenes.Add(internalGeneId);
var gffGene = GetGene(gene, geneId);
_writer.WriteGene(gffGene, requiredFields, internalGeneId);
}
public void MutateGeneExpression()
{
IGene gene = Genes[new Random().Next(Genes.Count)];
Genes[new Random().Next(Genes.Count)].MutateExpression();
// Avoid Node Isolation
if (!gene.IsExpressed && !Genes.Any(g => g.NodeIn == gene.NodeIn))
{
gene.MutateExpressionEnable();
}
}
public override void Run(IGene[] parent1, IGene[] parent2, out IGene[] child1, out IGene[] child2)
{
int customerCount = parent1.Count();
IGene[] c1 = new IGene[customerCount];
IGene[] c2 = new IGene[customerCount];
int slicePoint = RandomGeneratorThreadSafe.NextInt(customerCount);
DoCycleCrossover(parent1, parent2, c1, c2, slicePoint, true);
child1 = c1;
child2 = c2;
}
public IGene MutateAddGene(IEnumerable <IGene> genePool)
{
// Select two nodes at random to connect
List <INode> nodeOutCandidates = Nodes.ToList();
if (!GenomeParameters.AllowOutputOutGenes)
{
nodeOutCandidates = nodeOutCandidates.Where(n => n.Type != NodeType.Output).ToList();
}
INode nodeOut = nodeOutCandidates[new Random().Next(nodeOutCandidates.Count)];
// Get existing connections for this node
List <IGene> existingConnectionsIn = Genes.Where(cg => cg.NodeIn == nodeOut).ToList();
List <IGene> existingConnectionsOut = Genes.Where(cg => cg.NodeOut == nodeOut).ToList();
// Discover nodes where no connection currently exists
List <INode> nodeInCandidates = Nodes
.Except(existingConnectionsIn.Select(g => g.NodeOut))
.Except(existingConnectionsOut.Select(g => g.NodeIn)).ToList();
// Don't allow input to input or output to output connections
if (nodeOut.Type == NodeType.Input || nodeOut.Type == NodeType.Output)
{
nodeInCandidates = nodeInCandidates.Where(n => n.Type != nodeOut.Type).ToList();
}
if (nodeOut.Type == NodeType.Hidden || nodeOut.Type == NodeType.Output)
{
nodeInCandidates = nodeInCandidates.Where(n => n.Type != NodeType.Input).ToList();
}
if (nodeInCandidates.Count > 0)
{
INode selectedNodeIn = nodeInCandidates[new Random().Next(nodeInCandidates.Count)];
IGene existingGene = genePool.FirstOrDefault(gp => gp.NodeIn.Id == selectedNodeIn.Id &&
gp.NodeOut.Id == nodeOut.Id);
// Create the connection
IGene gene = new Gene(
nodeOut,
selectedNodeIn,
existingGene != null ? existingGene.Innovation : GetNextInnovation()
);
Genes.Add(gene);
return(gene);
}
return(null);
}
/// <summary>
/// Fills empty place in chromosome with genes from second parent.
/// </summary>
/// <param name="childPosition">Index in child chromosome.</param>
/// <param name="sourceParentPosition">Index in parent chromosome.</param>
/// <param name="sourceParent">Source of genes.</param>
/// <param name="child">Output child.</param>
private void FillEmptyGenes(int childPosition, ref int sourceParentPosition, IGene[] sourceParent, IGene[] child)
{
for (int j = 0; j < child.Length; ++j)
{
sourceParentPosition = (++sourceParentPosition) % child.Length;
IGene inner = sourceParent[sourceParentPosition];
if (!child.Contains(inner))
{
child[childPosition] = inner;
break;
}
}
}
public void AssignGene(IGene gene)
{
if (genes == null)
{
genes = new Dictionary <char, IGene>();
}
if (genes.ContainsKey(gene.ID))
{
throw new System.Exception("Genes must have unique IDs/cannot be assigned twice");
}
genes.Add(gene.ID, gene);
gene.Controller = GetComponent <CarController>();
}
private void Inverse(IGene[] genes, int startPosition, int length)
{
int index1, index2;
for (int i = 0; i < length / 2; ++i)
{
index1 = startPosition + i;
index2 = startPosition + length - i - 1;
IGene tmp = genes[index1];
genes[index1] = genes[index2];
genes[index2] = tmp;
}
}
public void AddGene(IGene gene)
{
var name = gene.Allele.Name;
if (Genes.ContainsKey(name))
{
AddDuplicateGene(gene);
}
else
{
Genes.Add(name, gene);
}
}
public TranscriptCacheReaderTests()
{
var chr1 = new Chromosome("chr1", "1", 0);
var chr2 = new Chromosome("chr2", "2", 1);
var chr3 = new Chromosome("chr3", "3", 2);
_refIndexToChromosome = new Dictionary <ushort, IChromosome>
{
[chr1.Index] = chr1,
[chr2.Index] = chr2,
[chr3.Index] = chr3
};
const GenomeAssembly genomeAssembly = GenomeAssembly.GRCh38;
var baseHeader = new Header("test", 2, 3, Source.BothRefSeqAndEnsembl, 4, genomeAssembly);
var customHeader = new TranscriptCacheCustomHeader(1, 2);
_expectedHeader = new CacheHeader(baseHeader, customHeader);
var transcriptRegions = new ITranscriptRegion[]
{
new TranscriptRegion(TranscriptRegionType.Exon, 1, 100, 199, 300, 399),
new TranscriptRegion(TranscriptRegionType.Intron, 1, 200, 299, 399, 400),
new TranscriptRegion(TranscriptRegionType.Exon, 2, 300, 399, 400, 499)
};
var mirnas = new IInterval[2];
mirnas[0] = new Interval(100, 200);
mirnas[1] = new Interval(300, 400);
var peptideSeqs = new[] { "MASE*" };
var genes = new IGene[1];
genes[0] = new Gene(chr3, 100, 200, true, "TP53", 300, CompactId.Convert("7157"),
CompactId.Convert("ENSG00000141510"));
var regulatoryRegions = new IRegulatoryRegion[2];
regulatoryRegions[0] = new RegulatoryRegion(chr3, 1200, 1300, CompactId.Convert("123"), RegulatoryRegionType.enhancer);
regulatoryRegions[1] = new RegulatoryRegion(chr3, 1250, 1450, CompactId.Convert("456"), RegulatoryRegionType.enhancer);
var regulatoryRegionIntervalArrays = regulatoryRegions.ToIntervalArrays(3);
var transcripts = GetTranscripts(chr3, genes, transcriptRegions, mirnas);
var transcriptIntervalArrays = transcripts.ToIntervalArrays(3);
_expectedCacheData = new TranscriptCacheData(_expectedHeader, genes, transcriptRegions, mirnas, peptideSeqs,
transcriptIntervalArrays, regulatoryRegionIntervalArrays);
}
private static Stream GetCacheStream()
{
const GenomeAssembly genomeAssembly = GenomeAssembly.GRCh38;
var baseHeader = new Header("test", 2, 3, Source.BothRefSeqAndEnsembl, 4, genomeAssembly);
var customHeader = new TranscriptCacheCustomHeader(1, 2);
var expectedHeader = new CacheHeader(baseHeader, customHeader);
var transcriptRegions = new ITranscriptRegion[]
{
new TranscriptRegion(TranscriptRegionType.Exon, 1, 100, 199, 300, 399),
new TranscriptRegion(TranscriptRegionType.Intron, 1, 200, 299, 399, 400),
new TranscriptRegion(TranscriptRegionType.Exon, 2, 300, 399, 400, 499)
};
var mirnas = new IInterval[2];
mirnas[0] = new Interval(100, 200);
mirnas[1] = new Interval(300, 400);
var peptideSeqs = new[] { "MASE*" };
var genes = new IGene[1];
genes[0] = new Gene(ChromosomeUtilities.Chr3, 100, 200, true, "TP53", 300, CompactId.Convert("7157"),
CompactId.Convert("ENSG00000141510"));
var regulatoryRegions = new IRegulatoryRegion[2];
regulatoryRegions[0] = new RegulatoryRegion(ChromosomeUtilities.Chr3, 1200, 1300, CompactId.Convert("123"), RegulatoryRegionType.enhancer);
regulatoryRegions[1] = new RegulatoryRegion(ChromosomeUtilities.Chr3, 1250, 1450, CompactId.Convert("456"), RegulatoryRegionType.enhancer);
var regulatoryRegionIntervalArrays = regulatoryRegions.ToIntervalArrays(3);
var transcripts = GetTranscripts(ChromosomeUtilities.Chr3, genes, transcriptRegions, mirnas);
var transcriptIntervalArrays = transcripts.ToIntervalArrays(3);
var expectedCacheData = new TranscriptCacheData(expectedHeader, genes, transcriptRegions, mirnas, peptideSeqs,
transcriptIntervalArrays, regulatoryRegionIntervalArrays);
var ms = new MemoryStream();
using (var writer = new TranscriptCacheWriter(ms, expectedHeader, true))
{
writer.Write(expectedCacheData);
}
ms.Position = 0;
return(ms);
}
/// <summary>
/// Crossover this gene with another of the same type.
/// </summary>
/// <typeparam name="TGene"></typeparam>
/// <param name="gene"></param>
/// <param name="other"></param>
/// <param name="settings"></param>
/// <returns></returns>
public static TGene Crossover <TGene>(this TGene gene, TGene other, GeneticAlgorithmSettings settings)
where TGene : IGene
{
IGene result = gene.Crossover((IGene)other, settings);
if (result != null && result is TGene)
{
return((TGene)result);
}
else
{
return(default(TGene));
}
}
public List<IGene> CrossOver(IGene _gene1, IGene _gene2)
{
List<IGene> nextGeneration = new List<IGene>(2);
int maskbit = R.Next(0, _gene1.Size);
IGene meme1 = _gene1.Copy();
IGene meme2 = _gene2.Copy();
for (int j = maskbit; j < _gene1.Size; j++)
{
meme1[j] = _gene2[j];
meme2[j] = _gene1[j];
}
nextGeneration.Add(meme1);
nextGeneration.Add(meme2);
return nextGeneration;
}
public List<IGene> CrossOver(IGene _gene1, IGene _gene2)
{
List<IGene> nextGeneration = new List<IGene>(2);
int[] mask = new int[_gene1.Size];
for (int j = 0; j < _gene1.Size; j++)
{
mask[j] = R.Next(0, 2);
}
IGene meme1 = _gene1.Copy();
IGene meme2 = _gene2.Copy();
for (int j = 0; j < _gene1.Size; j++)
{
if (mask[j] == 1)
{
meme1[j] = _gene2[j];
meme2[j] = _gene1[j];
}
}
nextGeneration.Add(meme1);
nextGeneration.Add(meme2);
return nextGeneration;
}
public override void Copy(IGene gene)
{
NEATNeuronGene gene2 = (NEATNeuronGene) gene;
if (0 == 0)
{
this.activationResponse = gene2.activationResponse;
base.Id = gene2.Id;
if (0 == 0)
{
this.neuronType = gene2.neuronType;
this.recurrent = gene2.recurrent;
if (0 == 0)
{
goto Label_000A;
}
}
return;
}
Label_000A:
this.splitX = gene2.splitX;
this.splitY = gene2.splitY;
}
/// <summary>
/// Copy from another gene.
/// </summary>
/// <param name="gene">The other gene.</param>
public override void Copy(IGene gene)
{
var other = (NEATLinkGene) gene;
Enabled = other.Enabled;
fromNeuronID = other.fromNeuronID;
toNeuronID = other.toNeuronID;
InnovationId = other.InnovationId;
recurrent = other.recurrent;
weight = other.weight;
}
public int CompareTo(IGene _other)
{
return this.Fitness.CompareTo(_other.Fitness) * -1;
}
/// <summary>
/// Copy another gene to this one.
/// </summary>
public override sealed void Copy(IGene gene)
{
Value = ((IntegerGene) gene).Value;
}
public override sealed void Copy(IGene gene)
{
this._xbcea506a33cf9111 = ((DoubleGene) gene).Value;
}
/// <summary>
/// Copy another gene to this one.
/// </summary>
///
/// <param name="gene">The other gene.</param>
public override void Copy(IGene gene)
{
var other = (NEATNeuronGene) gene;
activationResponse = other.activationResponse;
Id = other.Id;
neuronType = other.neuronType;
recurrent = other.recurrent;
splitX = other.splitX;
splitY = other.splitY;
}
/// <summary>
/// Given a selected iGEM object, this method creates the Primer Designer main page with the relevant information,
/// including the primer sequences, name, base pairs, and relevant directions. Handles the logic for creating a new
/// gene.
///
/// Params: an IGene object selected by the user
/// </summary>
/// <param name="gene">the IGene object selected from G-Nome Surfer Pro</param>
private void ChangeGene(IGene gene)
{
if (gene != null)
{
_gene = gene;
// updates lenght and displays accordingly
_rightLength = 5;
_leftLength = 5;
rightLength.Content = 5;
leftLength.Content = 5;
// updates sequence and primer sequences
String sequence = (gene.Sequence).ToUpper();
_leftSequence = (sequence).Substring(0, 40);
leftSequence.Text = _leftSequence;
_rightSequence = (sequence).Substring(sequence.Length - 40, 40);
rightSequence.Text = _rightSequence;
_leftPrimer = leftGetPrimer(_leftLength, _leftSequence);
_rightPrimer = rightGetPrimer(_rightLength, _rightSequence);
//updates the name of the gene and total base pairs
if (gene.Name != null)
geneNameLabel.Content = gene.Name;
else
geneNameLabel.Content = "";
geneBPLabel.Content = (Math.Abs(gene.RightBasePair - gene.LeftBasePair)) + " bp";
// updates the display to show all tests with a blank box (incomplete)
rightBlastResult.Content = "x";
leftBlastResult.Content = "x";
leftHairpinResult.Content = "x";
rightHairpinResult.Content = "x";
leftSelfDimerResult.Content = "x";
rightSelfDimerResult.Content = "x";
leftHeteroDimerResult.Content = "x";
rightHeteroDimerResult.Content = "x";
//update visibility of test tips
// calculates and displays Gibb's Free and temperature
rightGibbsFree.Content = calcDeltaG(_rightPrimer);
leftGibbsFree.Content = calcDeltaG(_leftPrimer);
_leftTemp = leftCalculateTemp(_leftSequence, _leftLength);
_rightTemp = rightCalculateTemp(_leftSequence, _rightLength);
leftTemp.Content = _leftTemp;
temp.Content = _rightTemp;
rightTempResult.Content = updateTempResults(_leftTemp, _rightTemp);
leftTempResult.Content = updateTempResults(_leftTemp, _rightTemp);
// displays the highlighters at appropriate spot
rightHighlight.Center = new Point(925, 625);
rightHighlight.Width = 100;
leftHighlight.Center = new Point(100, 350);
leftHighlight.Width = 100;
// updates length so minimum of 10 bp to start
_rightLength = 10;
_leftLength = 10;
rightLength.Content = 10;
leftLength.Content = 10;
// Restriction Enzyme Cut Sites
List<int> rightCutSites = generateCutSites(_rightSequence, rightRestrictionCutSequences);
List<int> leftcutSites = generateCutSites(_leftSequence, leftRestrictionCutSequences);
restrictionWarningGrid(rightCutSites, rightSequenceRestrictionLayer);
restrictionWarningGrid(leftcutSites, leftSequenceRestrictionLayer);
// draws gene and primer triangles on display depending on the orientation of the given gene
genePolygon.Points = new PointCollection();
leftPrimerPolygon.Points = new PointCollection();
rightPrimerPolygon.Points = new PointCollection();
if (gene.IsForward)
{
foreach (Point p in forwardGenePolygonPoints)
genePolygon.Points.Add(p);
foreach (Point p in leftForwardPrimerPolygonPoints)
leftPrimerPolygon.Points.Add(p);
foreach (Point p in rightForwardPrimerPolygonPoints)
rightPrimerPolygon.Points.Add(p);
}
else
{
foreach (Point p in reverseGenePolygonPoints)
genePolygon.Points.Add(p);
foreach (Point p in leftReversePrimerPolygonPoints)
leftPrimerPolygon.Points.Add(p);
foreach (Point p in rightReversePrimerPolygonPoints)
rightPrimerPolygon.Points.Add(p);
}
}
}
/// <summary> /// from Encog.ml.genetic.genes.Gene /// </summary> /// public abstract void Copy(IGene gene);
private void GeneSearchCallback(IGene result)
{
if (result == null)
{
GeneSearchStatus = GeneSearchStatusEnum.GeneNotFound;
return;
}
GeneSearchStatus = GeneSearchStatusEnum.Idle;
_onGeneSelected(result);
}
private void RenderSequenceView(IGene gene)
{
SequenceViewModel sequenceViewModel = new SequenceViewModel(this, gene);
int size = _allObjectsCollection.Add(sequenceViewModel);
}
/// <summary>
/// Add a gene.
/// </summary>
///
/// <param name="gene">The gene to add.</param>
public void Add(IGene gene)
{
_genes.Add(gene);
}
private void RenderTranslationView(IGene gene)
{
TranslationViewModel translationViewModel = new TranslationViewModel(this, gene);
_allObjectsCollection.Add(translationViewModel);
}
/// <summary>
/// Copy another gene to this one.
/// </summary>
/// <param name="gene">The other gene to copy.</param>
public override void Copy(IGene gene)
{
Value = ((DoubleGene)gene).Value;
}
public override void Copy(IGene gene)
{
NEATLinkGene gene2 = (NEATLinkGene) gene;
base.Enabled = gene2.Enabled;
this.fromNeuronID = gene2.fromNeuronID;
this.toNeuronID = gene2.toNeuronID;
if (0 == 0)
{
base.InnovationId = gene2.InnovationId;
this.recurrent = gene2.recurrent;
this.weight = gene2.weight;
}
}
public VisualGene(IGene model, double pixelsPerBasePair)
{
_model = model;
_name = model.Name;
_leftPosition = model.LeftBasePair * pixelsPerBasePair;
_length = (model.RightBasePair - model.LeftBasePair) * pixelsPerBasePair;
_direction = model.IsForward ? GeneDirection.Forward : GeneDirection.Reverse;
_locusTag = model.LocusTag;
// Define the points in the pentagon container
_pentagonPoints = new PointCollection(5);
double rectangleLength = _length > _height / 2 ? _length - _height / 2 : 0;
if (_direction == GeneDirection.Forward)
{
_pentagonPoints.Add(new Point(0, 0));
_pentagonPoints.Add(new Point(rectangleLength, 0));
_pentagonPoints.Add(new Point(_length, _height / 2));
_pentagonPoints.Add(new Point(rectangleLength, _height));
_pentagonPoints.Add(new Point(0, _height));
}
else
{
_pentagonPoints.Add(new Point(0, _height / 2));
_pentagonPoints.Add(new Point(_height / 2, _height));
_pentagonPoints.Add(new Point(_height / 2 + rectangleLength, _height));
_pentagonPoints.Add(new Point(_height / 2 + rectangleLength, 0));
_pentagonPoints.Add(new Point(_height / 2, 0));
}
}
private void PanToGene(IGene gene)
{
_chromosomeBarViewModel.CentralBasePair = gene.LeftBasePair;
}
/// <summary>
/// The provided IGene must be an IGEPGene.
/// </summary>
/// <param name="gene"></param>
/// <returns></returns>
new public IGEPGene Add(IGene gene)
{
return this.Add((IGEPGene) gene);
}
private void RenderNotesView(IGene gene)
{
NotesViewModel notesViewModel = new NotesViewModel(gene);
_allObjectsCollection.Add(notesViewModel);
}
/// <summary>
/// Copy another gene to this gene.
/// </summary>
///
/// <param name="gene">The source gene.</param>
public override sealed void Copy(IGene gene)
{
_value = ((CharGene) gene).Value;
}
public NotesViewModel(IGene model)
{
_model = model;
}
/// <summary>
/// Gets the percentage that IGene one and IGene two are similar.
/// 100% would be identical and 0% would indicate that the IGenes share nothing.
/// </summary>
/// <param name="one">The first IGene to compare.</param>
/// <param name="two">The second IGene to compare.</param>
/// <returns>The percentage that IGene one and IGene two are similar.
/// 100% would be identical and 0% would indicate that the IGenes share nothing.</returns>
public override double GetPercentageIGeneSimilarity(IGene one, IGene two)
{
return this.GetPercentageIGeneSimilarityDelegate(one: one, two: two);
}
public void ShowDesigner(IGene gene)
{
this.Gene = gene;
this.DesignerVisibility = Visibility.Visible;
}
/// <inheritdoc/>
public int CompareTo(IGene o)
{
return ((int) (InnovationId - o.InnovationId));
}
private void RenderPublicationsView(IGene gene)
{
PublicationsViewModel publicationsViewModel = new PublicationsViewModel(this, gene);
_allObjectsCollection.Add(publicationsViewModel);
}
