/// <summary>
/// Performs Stage 1, 2, and 3 as described in class description.
/// </summary>
/// <param name="sequences">Input sequences</param>
/// <returns>Alignment results</returns>
private void DoAlignment(IList<ISequence> sequences)
{
Debug.Assert(this.alphabet != null);
Debug.Assert(sequences.Count > 0);
// Initializations
if (ConsensusResolver == null)
ConsensusResolver = new SimpleConsensusResolver(this.alphabet);
else
ConsensusResolver.SequenceAlphabet = this.alphabet;
// Get ProfileAligner ready
IProfileAligner profileAligner = null;
switch (ProfileAlignerName)
{
case (ProfileAlignerNames.NeedlemanWunschProfileAligner):
if (this.degreeOfParallelism == 1)
{
profileAligner = new NeedlemanWunschProfileAlignerSerial(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
else
{
profileAligner = new NeedlemanWunschProfileAlignerParallel(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
break;
case (ProfileAlignerNames.SmithWatermanProfileAligner):
if (this.degreeOfParallelism == 1)
{
profileAligner = new SmithWatermanProfileAlignerSerial(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
else
{
profileAligner = new SmithWatermanProfileAlignerParallel(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
break;
default:
throw new ArgumentException("Invalid profile aligner name");
}
this.AlignedSequences = new List<ISequence>(sequences.Count);
float currentScore = 0;
// STAGE 1
ReportLog("Stage 1");
// Generate DistanceMatrix
var kmerDistanceMatrixGenerator = new KmerDistanceMatrixGenerator(sequences, KmerLength, this.alphabet, DistanceFunctionName);
// Hierarchical clustering
IHierarchicalClustering hierarcicalClustering =
new HierarchicalClusteringParallel
(kmerDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
// Generate Guide Tree
var binaryGuideTree = new BinaryGuideTree(hierarcicalClustering);
// Progressive Alignment
IProgressiveAligner progressiveAlignerA = new ProgressiveAligner(profileAligner);
progressiveAlignerA.Align(sequences, binaryGuideTree);
currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerA.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreA)
{
this.AlignmentScoreA = currentScore;
this.AlignedSequencesA = progressiveAlignerA.AlignedSequences;
}
if (this.AlignmentScoreA > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreA;
this.AlignedSequences = this.AlignedSequencesA;
}
if (PAMSAMMultipleSequenceAligner.FasterVersion)
{
this.AlignedSequencesB = this.AlignedSequencesA;
this.AlignedSequencesC = this.AlignedSequencesA;
this.AlignmentScoreB = this.AlignmentScoreA;
this.AlignmentScoreC = this.AlignmentScoreA;
}
else
{
BinaryGuideTree binaryGuideTreeB = null;
IHierarchicalClustering hierarcicalClusteringB = null;
KimuraDistanceMatrixGenerator kimuraDistanceMatrixGenerator = new KimuraDistanceMatrixGenerator();
if (UseStageB)
{
// STAGE 2
ReportLog("Stage 2");
// Generate DistanceMatrix from Multiple Sequence Alignment
while (true)
{
kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequences);
// Hierarchical clustering
hierarcicalClusteringB = new HierarchicalClusteringParallel
(kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
// Generate Guide Tree
binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
BinaryGuideTree.CompareTwoTrees(binaryGuideTreeB, binaryGuideTree);
binaryGuideTree = binaryGuideTreeB;
// Progressive Alignment
IProgressiveAligner progressiveAlignerB = new ProgressiveAligner(profileAligner);
progressiveAlignerB.Align(sequences, binaryGuideTreeB);
currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerB.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreB)
{
this.AlignmentScoreB = currentScore;
this.AlignedSequencesB = progressiveAlignerB.AlignedSequences;
}
break;
}
if (this.AlignmentScoreB > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreB;
this.AlignedSequences = this.AlignedSequencesB;
}
}
else
{
binaryGuideTreeB = binaryGuideTree;
}
// STAGE 3
ReportLog("Stage 3");
// refinement
int maxRefineMentTime = 1;
if (sequences.Count == 2)
{
maxRefineMentTime = 0;
}
int refinementTime = 0;
this.AlignedSequencesC = new List<ISequence>(this.AlignedSequences.Count);
foreach (ISequence t in this.AlignedSequences)
{
this.AlignedSequencesC.Add(new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), t.ToArray())
{
ID = t.ID,
// Do not shallow copy dictionary
//Metadata = t.Metadata
});
}
while (refinementTime < maxRefineMentTime)
{
++refinementTime;
ReportLog("Refinement iter " + refinementTime);
bool needRefinement = false;
for (int edgeIndex = 0; edgeIndex < binaryGuideTreeB.NumberOfEdges; ++edgeIndex)
{
List<int>[] leafNodeIndices = binaryGuideTreeB.SeparateSequencesByCuttingTree(edgeIndex);
List<int>[] allIndelPositions = new List<int>[2];
IProfileAlignment[] separatedProfileAlignments = ProfileAlignment.ProfileExtraction(this.AlignedSequencesC, leafNodeIndices[0], leafNodeIndices[1], out allIndelPositions);
List<int>[] eStrings = new List<int>[2];
if (separatedProfileAlignments[0].NumberOfSequences < separatedProfileAlignments[1].NumberOfSequences)
{
profileAligner.Align(separatedProfileAlignments[0], separatedProfileAlignments[1]);
eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedA);
eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedB);
}
else
{
profileAligner.Align(separatedProfileAlignments[1], separatedProfileAlignments[0]);
eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedB);
eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedA);
}
for (int set = 0; set < 2; ++set)
{
Parallel.ForEach(leafNodeIndices[set], ParallelOption, i =>
{
//Sequence seq = new Sequence(_alphabet, "");
List<byte> seqBytes = new List<byte>();
int indexAllIndel = 0;
for (int j = 0; j < this.AlignedSequencesC[i].Count; ++j)
{
if (indexAllIndel < allIndelPositions[set].Count && j == allIndelPositions[set][indexAllIndel])
{
++indexAllIndel;
}
else
{
seqBytes.Add(this.AlignedSequencesC[i][j]);
}
}
this.AlignedSequencesC[i] = profileAligner.GenerateSequenceFromEString(eStrings[set], new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), seqBytes.ToArray()));
this.AlignedSequencesC[i].ID = this.AlignedSequencesC[i].ID;
// Do not shallow copy dictionary
//(_alignedSequencesC[i] as Sequence).Metadata = _alignedSequencesC[i].Metadata;
});
}
currentScore = MsaUtils.MultipleAlignmentScoreFunction(this.AlignedSequencesC, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreC)
{
this.AlignmentScoreC = currentScore;
needRefinement = true;
// recreate the tree
kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequencesC);
hierarcicalClusteringB = new HierarchicalClusteringParallel
(kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
break;
}
}
if (!needRefinement)
{
refinementTime = maxRefineMentTime;
break;
}
}
if (this.AlignmentScoreC > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreC;
this.AlignedSequences = this.AlignedSequencesC;
}
ReportLog("Stop Stage 3");
}
}
/// <summary>
/// Performs Stage 1, 2, and 3 as described in class description.
/// </summary>
/// <param name="sequences">Input sequences</param>
/// <returns>Alignment results</returns>
private void DoAlignment(IList <ISequence> sequences)
{
Debug.Assert(this.alphabet != null);
Debug.Assert(sequences.Count > 0);
// Initializations
if (ConsensusResolver == null)
{
ConsensusResolver = new SimpleConsensusResolver(this.alphabet);
}
else
{
ConsensusResolver.SequenceAlphabet = this.alphabet;
}
// Get ProfileAligner ready
IProfileAligner profileAligner = null;
switch (ProfileAlignerName)
{
case (ProfileAlignerNames.NeedlemanWunschProfileAligner):
if (this.degreeOfParallelism == 1)
{
profileAligner = new NeedlemanWunschProfileAlignerSerial(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
else
{
profileAligner = new NeedlemanWunschProfileAlignerParallel(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
break;
case (ProfileAlignerNames.SmithWatermanProfileAligner):
if (this.degreeOfParallelism == 1)
{
profileAligner = new SmithWatermanProfileAlignerSerial(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
else
{
profileAligner = new SmithWatermanProfileAlignerParallel(
SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
}
break;
default:
throw new ArgumentException("Invalid profile aligner name");
}
this.AlignedSequences = new List <ISequence>(sequences.Count);
float currentScore = 0;
// STAGE 1
ReportLog("Stage 1");
// Generate DistanceMatrix
var kmerDistanceMatrixGenerator = new KmerDistanceMatrixGenerator(sequences, KmerLength, this.alphabet, DistanceFunctionName);
// Hierarchical clustering
IHierarchicalClustering hierarcicalClustering =
new HierarchicalClusteringParallel
(kmerDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
// Generate Guide Tree
var binaryGuideTree = new BinaryGuideTree(hierarcicalClustering);
// Progressive Alignment
IProgressiveAligner progressiveAlignerA = new ProgressiveAligner(profileAligner);
progressiveAlignerA.Align(sequences, binaryGuideTree);
currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerA.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreA)
{
this.AlignmentScoreA = currentScore;
this.AlignedSequencesA = progressiveAlignerA.AlignedSequences;
}
if (this.AlignmentScoreA > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreA;
this.AlignedSequences = this.AlignedSequencesA;
}
if (PAMSAMMultipleSequenceAligner.FasterVersion)
{
this.AlignedSequencesB = this.AlignedSequencesA;
this.AlignedSequencesC = this.AlignedSequencesA;
this.AlignmentScoreB = this.AlignmentScoreA;
this.AlignmentScoreC = this.AlignmentScoreA;
}
else
{
BinaryGuideTree binaryGuideTreeB = null;
IHierarchicalClustering hierarcicalClusteringB = null;
KimuraDistanceMatrixGenerator kimuraDistanceMatrixGenerator = new KimuraDistanceMatrixGenerator();
if (UseStageB)
{
// STAGE 2
ReportLog("Stage 2");
// Generate DistanceMatrix from Multiple Sequence Alignment
while (true)
{
kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequences);
// Hierarchical clustering
hierarcicalClusteringB = new HierarchicalClusteringParallel
(kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
// Generate Guide Tree
binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
BinaryGuideTree.CompareTwoTrees(binaryGuideTreeB, binaryGuideTree);
binaryGuideTree = binaryGuideTreeB;
// Progressive Alignment
IProgressiveAligner progressiveAlignerB = new ProgressiveAligner(profileAligner);
progressiveAlignerB.Align(sequences, binaryGuideTreeB);
currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerB.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreB)
{
this.AlignmentScoreB = currentScore;
this.AlignedSequencesB = progressiveAlignerB.AlignedSequences;
}
break;
}
if (this.AlignmentScoreB > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreB;
this.AlignedSequences = this.AlignedSequencesB;
}
}
else
{
binaryGuideTreeB = binaryGuideTree;
}
// STAGE 3
ReportLog("Stage 3");
// refinement
int maxRefineMentTime = 1;
if (sequences.Count == 2)
{
maxRefineMentTime = 0;
}
int refinementTime = 0;
this.AlignedSequencesC = new List <ISequence>(this.AlignedSequences.Count);
foreach (ISequence t in this.AlignedSequences)
{
this.AlignedSequencesC.Add(new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), t.ToArray())
{
ID = t.ID,
// Do not shallow copy dictionary
//Metadata = t.Metadata
});
}
while (refinementTime < maxRefineMentTime)
{
++refinementTime;
ReportLog("Refinement iter " + refinementTime);
bool needRefinement = false;
for (int edgeIndex = 0; edgeIndex < binaryGuideTreeB.NumberOfEdges; ++edgeIndex)
{
List <int>[] leafNodeIndices = binaryGuideTreeB.SeparateSequencesByCuttingTree(edgeIndex);
List <int>[] allIndelPositions = new List <int> [2];
IProfileAlignment[] separatedProfileAlignments = ProfileAlignment.ProfileExtraction(this.AlignedSequencesC, leafNodeIndices[0], leafNodeIndices[1], out allIndelPositions);
List <int>[] eStrings = new List <int> [2];
if (separatedProfileAlignments[0].NumberOfSequences < separatedProfileAlignments[1].NumberOfSequences)
{
profileAligner.Align(separatedProfileAlignments[0], separatedProfileAlignments[1]);
eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedA);
eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedB);
}
else
{
profileAligner.Align(separatedProfileAlignments[1], separatedProfileAlignments[0]);
eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedB);
eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedA);
}
for (int set = 0; set < 2; ++set)
{
Parallel.ForEach(leafNodeIndices[set], ParallelOption, i =>
{
//Sequence seq = new Sequence(_alphabet, "");
List <byte> seqBytes = new List <byte>();
int indexAllIndel = 0;
for (int j = 0; j < this.AlignedSequencesC[i].Count; ++j)
{
if (indexAllIndel < allIndelPositions[set].Count && j == allIndelPositions[set][indexAllIndel])
{
++indexAllIndel;
}
else
{
seqBytes.Add(this.AlignedSequencesC[i][j]);
}
}
this.AlignedSequencesC[i] = profileAligner.GenerateSequenceFromEString(eStrings[set], new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), seqBytes.ToArray()));
this.AlignedSequencesC[i].ID = this.AlignedSequencesC[i].ID;
// Do not shallow copy dictionary
//(_alignedSequencesC[i] as Sequence).Metadata = _alignedSequencesC[i].Metadata;
});
}
currentScore = MsaUtils.MultipleAlignmentScoreFunction(this.AlignedSequencesC, SimilarityMatrix, GapOpenCost, GapExtensionCost);
if (currentScore > this.AlignmentScoreC)
{
this.AlignmentScoreC = currentScore;
needRefinement = true;
// recreate the tree
kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequencesC);
hierarcicalClusteringB = new HierarchicalClusteringParallel
(kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);
binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
break;
}
}
if (!needRefinement)
{
refinementTime = maxRefineMentTime;
break;
}
}
if (this.AlignmentScoreC > this.AlignmentScore)
{
this.AlignmentScore = this.AlignmentScoreC;
this.AlignedSequences = this.AlignedSequencesC;
}
ReportLog("Stop Stage 3");
}
}
/// <summary>
/// Creates binarytree using stage1 sequences and
/// cut the binary tree at an random edge to get two profiles.
/// Create NeedlemanWunschProfileAlignerSerial\Parallel instance
/// according to degree of parallelism
/// and using profile function score . Execute Align() method.
/// Validates the IProfileAlignment properties.
/// </summary>
/// <param name="nodeName">xml node name</param>
/// <param name="degreeOfParallelism">if 1 it is serial Profiler else parallel profiler</param>
/// <param name="edgeIndex">edge index to cut the tree</param>
/// <param name="profileFunction">profile function score name</param>
private void ValidateProfileAlignerAlignWithProfileFunctionScore(
string nodeName, int degreeOfParallelism, ProfileScoreFunctionNames profileFunction,
int edgeIndex)
{
Initialize(Constants.MuscleDnaSequenceNode, Constants.ExpectedScoreNode);
InitializeStage2Variables(Constants.MuscleDnaSequenceNode);
// Get Stage2 Binary Tree
List<ISequence> stage1AlignedSequences = GetStage1AlignedSequence();
IDistanceMatrix matrix = GetKimuraDistanceMatrix(stage1AlignedSequences);
IHierarchicalClustering hierarcicalClustering = GetHierarchicalClustering(matrix);
BinaryGuideTree binaryTree = GetBinaryTree(hierarcicalClustering);
// Cut Tree at an edge and get sequences.
List<int>[] leafNodeIndices = binaryTree.SeparateSequencesByCuttingTree(edgeIndex);
// Extract profiles
List<int>[] removedPositions = null;
IProfileAlignment[] separatedProfileAlignments = ProfileAlignment.ProfileExtraction(
stage2ExpectedSequences, leafNodeIndices[0], leafNodeIndices[1], out removedPositions);
IProfileAligner aligner = null;
if (1 == degreeOfParallelism)
{
aligner = new NeedlemanWunschProfileAlignerSerial(similarityMatrix,
profileFunction, gapOpenPenalty, gapExtendPenalty, 2);
}
else
{
if (Environment.ProcessorCount >= degreeOfParallelism)
{
aligner = new NeedlemanWunschProfileAlignerParallel(similarityMatrix,
profileFunction, gapOpenPenalty,
gapExtendPenalty, 2);
}
else
{
ApplicationLog.WriteLine(String.Format(null,
@"PamsamBvtTest: NeedlemanWunschProfileAlignerParallel could not be instantiated
as number of processor is {0} and degree of parallelism {1}",
Environment.ProcessorCount.ToString((IFormatProvider) null),
degreeOfParallelism));
}
}
if (null != aligner)
{
IProfileAlignment profileAlignment = aligner.Align(separatedProfileAlignments[0],
separatedProfileAlignments[0]);
// Validate profile alignement
string expectedRowSize = utilityObj.xmlUtil.GetTextValue(nodeName, Constants.RowSize);
string expectedColSize = utilityObj.xmlUtil.GetTextValue(nodeName, Constants.ColumnSize);
Assert.IsTrue(
expectedColSize.Contains(profileAlignment.ProfilesMatrix.ColumnSize.ToString((IFormatProvider) null)));
Assert.IsTrue(
expectedRowSize.Contains(profileAlignment.ProfilesMatrix.RowSize.ToString((IFormatProvider) null)));
ApplicationLog.WriteLine(String.Format(null,
@"PamsamBvtTest: {0} Align() method validation completed successfully with
number of processor is {1} and degree of parallelism {2}",
profileAligner,
Environment.ProcessorCount.ToString((IFormatProvider) null),
degreeOfParallelism));
}
else
{
Assert.Fail("Profile Aligner is not instantiated");
}
}
/// <summary>
/// Creates binarytree using stage1 sequences and
/// cut the binary tree at an random edge to get two profiles.
/// Create NeedlemanWunschProfileAlignerSerial\Parallel instance
/// according to degree of parallelism
/// and execute AlignSimple\Align() method using two profiles.
/// Validate the IProfileAlignment properties.
/// </summary>
/// <param name="nodeName">xml node name</param>
/// <param name="moleculeType">Molecule Type</param>
/// <param name="degreeOfParallelism">if 1 it is serial Profiler else parallel profiler</param>
/// <param name="edgeIndex">edge index to cut the tree</param>
/// <param name="overloadType">Execute Align()\AlignSimple()</param>
private void ValidateProfileAlignerAlign(string nodeName, MoleculeType moleculeType,
int degreeOfParallelism, int edgeIndex, AlignType overloadType)
{
switch (moleculeType)
{
case MoleculeType.DNA:
Initialize(Constants.MuscleDnaSequenceNode, Constants.ExpectedScoreNode);
InitializeStage2Variables(Constants.MuscleDnaSequenceNode);
break;
case MoleculeType.RNA:
Initialize(Constants.MuscleRnaSequenceNode, Constants.ExpectedScoreNode);
InitializeStage2Variables(Constants.MuscleRnaSequenceNode);
break;
case MoleculeType.Protein:
Initialize(Constants.MuscleProteinSequenceNode, Constants.ExpectedScoreNode);
InitializeStage2Variables(Constants.MuscleProteinSequenceNode);
break;
}
// Get Stage2 Binary Tree
List<ISequence> stage1AlignedSequences = GetStage1AlignedSequence(moleculeType);
IDistanceMatrix matrix = GetKimuraDistanceMatrix(stage1AlignedSequences);
IHierarchicalClustering hierarcicalClustering = GetHierarchicalClustering(matrix);
BinaryGuideTree binaryTree = GetBinaryTree(hierarcicalClustering);
// Cut Tree at an edge and get sequences.
List<int>[] leafNodeIndices = binaryTree.SeparateSequencesByCuttingTree(edgeIndex);
// Extract profiles
List<int>[] removedPositions = null;
IProfileAlignment[] separatedProfileAlignments = ProfileAlignment.ProfileExtraction(
stage2ExpectedSequences, leafNodeIndices[0], leafNodeIndices[1], out removedPositions);
// Align it
IProfileAlignment alignedProfile = null;
if (1 == degreeOfParallelism)
{
var nwprofileAligner = new
NeedlemanWunschProfileAlignerSerial(similarityMatrix,
ProfileScoreFunctionNames.InnerProductFast,
gapOpenPenalty, gapExtendPenalty, 2);
switch (overloadType)
{
case AlignType.AlignSimpleAllParams:
alignedProfile = nwprofileAligner.AlignSimple(similarityMatrix,
gapOpenPenalty, separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
case AlignType.AlignSimpleOnlyProfiles:
alignedProfile = nwprofileAligner.AlignSimple(separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
case AlignType.AlignAllParams:
alignedProfile = nwprofileAligner.Align(similarityMatrix, gapOpenPenalty,
gapExtendPenalty, separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
}
}
else
{
if (Environment.ProcessorCount >= degreeOfParallelism)
{
var nwprofileAlignerParallel = new
NeedlemanWunschProfileAlignerParallel(
similarityMatrix,
ProfileScoreFunctionNames.InnerProductFast,
gapOpenPenalty,
gapExtendPenalty, 2);
alignedProfile = nwprofileAlignerParallel.AlignSimple(
separatedProfileAlignments[0],
separatedProfileAlignments[1]);
switch (overloadType)
{
case AlignType.AlignSimpleAllParams:
alignedProfile = nwprofileAlignerParallel.AlignSimple(similarityMatrix,
gapOpenPenalty,
separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
case AlignType.AlignSimpleOnlyProfiles:
alignedProfile = nwprofileAlignerParallel.AlignSimple(
separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
case AlignType.AlignAllParams:
alignedProfile = nwprofileAlignerParallel.Align(
similarityMatrix, gapOpenPenalty,
gapExtendPenalty, separatedProfileAlignments[0],
separatedProfileAlignments[1]);
break;
}
}
else
{
ApplicationLog.WriteLine(
String.Format(null,
@"PamsamP1Test: NeedlemanWunschProfileAlignerParallel could not be instantiated
as number of processor is {0} and degree of parallelism {1}",
Environment.ProcessorCount.ToString((IFormatProvider) null),
degreeOfParallelism));
}
}
if (null != alignedProfile)
{
// Validate profile alignement
string expectedRowSize = utilityObj.xmlUtil.GetTextValue(nodeName, Constants.RowSize);
string expectedColSize = utilityObj.xmlUtil.GetTextValue(nodeName, Constants.ColumnSize);
Assert.AreEqual(expectedColSize,
alignedProfile.ProfilesMatrix.ColumnSize.ToString((IFormatProvider) null));
Assert.AreEqual(expectedRowSize, alignedProfile.ProfilesMatrix.RowSize.ToString((IFormatProvider) null));
ApplicationLog.WriteLine(
String.Format(null, @"PamsamP1Test: {0} {1} method validation completed successfully with
number of processor is {2} and degree of parallelism {3} for molecule type {4}",
profileAligner,
overloadType,
Environment.ProcessorCount.ToString((IFormatProvider) null),
degreeOfParallelism,
moleculeType));
}
else
{
Assert.Fail("Profile Aligner is not instantiated");
}
}