private static void HandleMeshCollider(MeshCollider c, ref AlignmentData data)
{
// TODO: I don't think there's an efficient solution for those.
// The convex collider mesh doesn't seem accessible by script.
// We could access the original mesh, but that all is pretty inefficient.
// Best solution for now probably is to just restrict ourselves to the other colliders.
}
private void ExportAlignmentData(AlignmentData data,
DatasetInformation baselineDatasetInformation,
DatasetInformation alignDatasetInformation,
IEnumerable <UMCLight> baselineFeatures,
IEnumerable <UMCLight> aligneeFeatures)
{
var netValues = new List <double>();
var massValues = new List <double>();
var anchorPoints = data.Matches;
foreach (var match in anchorPoints)
{
netValues.Add(match.AnchorPointX.Net - match.AnchorPointY.Net);
massValues.Add(match.AnchorPointX.Mass - match.AnchorPointY.Mass);
}
var netHist =
MatchCountHistogramBuilder.CreateResidualHistogram(-.05, .05, .01, netValues);
var netHistogram = new Dictionary <double, int>();
Console.WriteLine();
for (var i = 0; i < netHist.Bins.Count; i++)
{
netHistogram.Add(netHist.Bins[i], Convert.ToInt32(netHist.Data[i]));
Console.WriteLine("{0}\t{1}", netHist.Bins[i], netHist.Data[i]);
}
}
/// <summary>
/// Arguments that hold alignment information when a dataset is aligned.
/// </summary>
public FeaturesAlignedEventArgs(DatasetInformation datasetInfo,
IEnumerable <UMCLight> baselineFeatures,
IEnumerable <UMCLight> aligneeFeatures,
AlignmentData alignmentData)
{
m_datasetInformation = datasetInfo;
BaselineFeatures = baselineFeatures;
AligneeFeatures = aligneeFeatures;
AlignmentData = alignmentData;
}
public new AlignmentData Align(MassTagDatabase database, IEnumerable <UMCLight> alignee, IProgress <ProgressData> progress = null)
{
var matches = base.Align(database, alignee);
var data = new AlignmentData {
Matches = matches
};
Matches = matches;
return(data);
}
public AlignmentViewModel(AlignmentData alignment)
{
this.WindowTitle = string.Format("{0} Alignment Data", alignment.AligneeDataset);
var plots = new AlignmentPlotCreator(alignment);
this.HeatmapImage = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.Heatmap));
this.NetScanImage = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.NetResidual));
this.MassHistogram = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.MassHistogram));
this.NetHistogram = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.NetHistogram));
this.MassMzImage = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.MassMzResidual));
this.MassScanImage = ImageConverter.ConvertImage(PlotImageUtility.CreateImage(plots.MassScanResidual));
}
public AlignmentPlotCreator(AlignmentData alignment)
{
var residuals = alignment.ResidualData;
Heatmap = HeatmapFactory.CreateAlignedHeatmap(alignment.HeatScores, alignment.BaselineIsAmtDB);
NetResidual = ScatterPlotFactory.CreateResidualPlot(residuals.Net, residuals.LinearCustomNet,
residuals.LinearNet, "NET Residuals", "Scans", "NET");
MassHistogram = HistogramFactory.CreateHistogram(alignment.MassErrorHistogram, "Mass Error", "Mass Error (ppm)");
NetHistogram = HistogramFactory.CreateHistogram(alignment.NetErrorHistogram, "NET Error", "NET Error");
MassMzResidual = ScatterPlotFactory.CreateResidualPlot(residuals.Mz, residuals.MzMassError,
residuals.MzMassErrorCorrected, "Mass Residuals", "m/z", "Mass Errors");
MassScanResidual = ScatterPlotFactory.CreateResidualPlot(residuals.Net, residuals.MzMassError,
residuals.MzMassErrorCorrected, "Mass Residuals", "Scan", "Mass Errors");
}
/// <summary>
/// Creates an empty layer.
/// </summary>
/// <param name="id">the order number in the FlexiVolume.</param>
/// <param name="brickid">the brick id.</param>
/// <param name="sheet">the sheet in the brick.</param>
/// <param name="side">the side (0 for base tracks, 1 for downstream, 2 for upstream).</param>
public Layer(int id, long brickid, int sheet, short side) : base()
{
m_BrickId = brickid;
m_SheetId = sheet;
m_Side = side;
m_Id = id;
m_DownstreamZ_Updated = false;
m_UpstreamZ_Updated = false;
AlignmentData al = new AlignmentData();
al.AffineMatrixXX = al.AffineMatrixYY = 1.0;
al.AffineMatrixXY = al.AffineMatrixYX = 0.0;
al.TranslationX = al.TranslationY = al.TranslationZ = 0.0;
al.DShrinkX = al.DShrinkY = 1.0;
al.SAlignDSlopeX = al.SAlignDSlopeY = 0.0;
SetAlignmentData(al);
Segments = new Segment[0];
}
private static void HandleCapsuleCollider(CapsuleCollider c, ref AlignmentData data)
{
/*
* var m = c.transform.localToWorldMatrix;
* switch(c.direction) {
* case 0: // aligned along x-axis
* list.Add(m.MultiplyVector(Vector3.right));
* list.Add(m.MultiplyVector(Vector3.left));
* break;
* case 1: // aligned along y-axis
* list.Add(m.MultiplyVector(Vector3.up));
* list.Add(m.MultiplyVector(Vector3.down));
* break;
* case 2: // aligned along z-axis
* list.Add(m.MultiplyVector(Vector3.forward));
* list.Add(m.MultiplyVector(Vector3.back));
* break;
* }*/
}
public static AlignmentData Scan(Vector3 pos, float radius, GameObject ignore = null)
{
var data = new AlignmentData();
foreach (var collider in Physics.OverlapSphere(pos, radius))
{
if (ignore != null && ignore.GetComponentsInChildren <Collider>().Contains(collider))
{
continue;
}
switch (collider)
{
case BoxCollider b:
HandleBoxCollider(b, ref data);
break;
case SphereCollider s:
HandleSphereCollider(s, ref data);
break;
case CapsuleCollider c:
HandleCapsuleCollider(c, ref data);
break;
case MeshCollider m:
HandleMeshCollider(m, ref data);
break;
}
}
/*
* Dictionary<Vector3, int> histogram = new Dictionary<Vector3, int>(new DirectionComparer());
* foreach(var dir in orientations) {
* if(histogram.TryGetValue(dir, out int count)) {
* histogram[dir] = count + 1;
* } else {
* histogram[dir] = 1;
* }
* }*/
return(data);
}
/// <summary>
/// Align a set of features to a set of baseline features.
/// </summary>
/// <param name="baseline">The baseline features to align to.</param>
/// <param name="alignee">The features to align.</param>
/// <param name="progress">The progress reporter for the alignment process.</param>
/// <returns>Information about the alignment.</returns>
public AlignmentData Align(IEnumerable <UMCLight> baseline, IEnumerable <UMCLight> alignee, IProgress <ProgressData> progress = null)
{
// Enumerate features to lists.
// Perform a deep copy of the LCMS features so that the original features are unaffected by the warp.
var aligneeFeatures = alignee.Select(feature => new UMCLight(feature)).ToList();
var baselineFeatures = baseline.ToList();
// Warp mass if NET_MASS_WARP, otherwise only warp NET.
var netMassWarp = this.options.AlignType == LcmsWarpAlignmentType.NET_MASS_WARP;
var alignmentData = netMassWarp ? this.WarpNetMass(aligneeFeatures, baselineFeatures)
: this.WarpNet(aligneeFeatures, baselineFeatures, true);
// TODO: Change this to return the new alignment data object.
var aData = new AlignmentData
{
AlignmentFunctions = new Dictionary <FeatureLight.SeparationTypes, LcmsWarpResults>()
};
return(aData);
}
private static void HandleBoxCollider(BoxCollider c, ref AlignmentData data)
{
var m = c.transform.localToWorldMatrix;
data.AddOrientation(m.MultiplyVector(Vector3.forward));
data.AddOrientation(m.MultiplyVector(Vector3.back));
data.AddOrientation(m.MultiplyVector(Vector3.up));
data.AddOrientation(m.MultiplyVector(Vector3.down));
data.AddOrientation(m.MultiplyVector(Vector3.right));
data.AddOrientation(m.MultiplyVector(Vector3.left));
var cornerA = m.MultiplyPoint(c.center + 0.5f * c.size);
var cornerB = m.MultiplyPoint(c.center - 0.5f * c.size);
data.AddLevelX(cornerA.x);
data.AddLevelX(cornerB.x);
data.AddLevelY(cornerA.y);
data.AddLevelY(cornerB.y);
data.AddLevelZ(cornerA.z);
data.AddLevelZ(cornerB.z);
}
private static void HandleSphereCollider(SphereCollider c, ref AlignmentData data)
{
}
/// <summary>
/// Aligns the dataset to the data stored in the alignment processor.
/// </summary>
/// <param name="alignmentProcessor">Aligner</param>
/// <param name="features">LC-MS Features to align to the baseline</param>
/// <param name="alignmentOptions">Options</param>
/// <param name="progress"></param>
/// <returns></returns>
private AlignmentData AlignFeatures(LcmsWarpAlignmentProcessor alignmentProcessor,
IEnumerable <UMCLight> features,
LcmsWarpAlignmentOptions alignmentOptions,
IProgress <ProgressData> progress = null)
{
var progData = new ProgressData(progress);
var localProgress = new Progress <ProgressData>(p => progData.Report(p.Percent, p.Status));
var alignmentData = new AlignmentData();
OnStatus("Starting alignment of features.");
// Set minMtdbnet and maxMtdbnet to 0
alignmentData.MinMTDBNET = 0;
alignmentData.MaxMTDBNET = 0;
var umcLights = features as List <UMCLight> ?? features.ToList();
progData.StepRange(5, "Starting alignment of features.");
var filteredFeatures = FilterFeaturesByAbundance(umcLights, alignmentOptions);
// Convert the features, and make a map, so that we can re-adjust the aligned values later.
var map = FeatureDataConverters.MapFeature(umcLights);
progData.StepRange(10, "Setting alignee features.");
// Set features
OnStatus("Setting alignee features.");
alignmentProcessor.SetAligneeDatasetFeatures(filteredFeatures);
progData.StepRange(90, "Performing alignment warping.");
// Find alignment
OnStatus("Performing alignment warping.");
alignmentProcessor.PerformAlignmentToMsFeatures(localProgress);
progData.StepRange(95);
// Extract alignment function
alignmentData.AlignmentFunction = alignmentProcessor.GetAlignmentFunction();
progData.StepRange(100);
// Extract the NET value for every scan
_scanToNETMap = alignmentProcessor.GetScanToNETMapping();
// Correct the features (updates NetAligned and MassMonoisotopicAligned)
OnStatus("Applying alignment function to all features.");
progData.Status = "Applying alignment function to all features.";
umcLights = alignmentProcessor.ApplyNetMassFunctionToAligneeDatasetFeatures(umcLights);
progData.Report(100);
// Find min/max scan for meta-data
var minScanBaseline = int.MaxValue;
var maxScanBaseline = int.MinValue;
foreach (var feature in umcLights)
{
maxScanBaseline = Math.Max(maxScanBaseline, feature.Scan);
minScanBaseline = Math.Min(minScanBaseline, feature.Scan);
}
// Update the scan and NET ranges
alignmentData.MinScanBaseline = minScanBaseline;
alignmentData.MaxScanBaseline = maxScanBaseline;
alignmentData.MinMTDBNET = (float)alignmentProcessor.MinReferenceNet;
alignmentData.MaxMTDBNET = (float)alignmentProcessor.MaxReferenceNet;
// Cache the matching features
alignmentData.FeatureMatches = alignmentProcessor.FeatureMatches;
// Pull out the heat maps...
OnStatus("Retrieving alignment data.");
progData.Status = "Retrieving alignment data.";
alignmentData.HeatScores = alignmentProcessor.GetAlignmentHeatMap(alignmentOptions.StandardizeHeatScores);
// Mass and net error histograms!
alignmentData.MassErrorHistogram = alignmentProcessor.GetMassErrorHistogram(alignmentOptions.MassBinSize);
alignmentData.NetErrorHistogram = alignmentProcessor.GetNetErrorHistogram(alignmentOptions.NetBinSize);
alignmentData.DriftErrorHistogram = alignmentProcessor.GetDriftErrorHistogram(alignmentOptions.DriftTimeBinSize);
// Get the residual data from the warp.
alignmentData.ResidualData = alignmentProcessor.GetResidualData();
alignmentData.NETIntercept = alignmentProcessor.NetIntercept;
alignmentData.NETRsquared = alignmentProcessor.NetRsquared;
alignmentData.NETSlope = alignmentProcessor.NetSlope;
alignmentData.MassMean = alignmentProcessor.MassMu;
alignmentData.MassStandardDeviation = alignmentProcessor.MassStd;
alignmentData.NETMean = alignmentProcessor.NetMu;
alignmentData.NETStandardDeviation = alignmentProcessor.NetStd;
alignmentData.BaselineIsAmtDB = _options.AlignToMassTagDatabase;
return(alignmentData);
}
/// <summary>
/// Main Edlib method.
/// </summary>
/// <param name="originalQuery">String a</param>
/// <param name="originalTarget">String b</param>
/// <param name="config">Configuration</param>
/// <returns>Result of the alignment</returns>
public static AlignmentResult Align(string originalQuery, string originalTarget, AlignmentConfig config)
{
// NOTE: Is other mode useful? If so, why?
if (config.Mode == AlignmentMode.Hw || config.Mode == AlignmentMode.Shw)
{
throw new NotImplementedException();
}
AlignmentResult result = new AlignmentResult
{
Status = (int)AlignmentStatus.Ok,
EditDistance = -1,
EndLocations = null,
StartingLocations = null,
NumberOfLocations = 0,
Alignment = null,
AlignmentLength = 0,
AlphabetLength = 0,
};
// Transform sequences and recognize alphabet
byte[] query, target;
string alphabet = TransformSequences(originalQuery, originalTarget, out query, out target);
result.AlphabetLength = alphabet.Length;
// Initialization
int queryLength = originalQuery.Length;
int targetLength = originalTarget.Length;
int maxBlocks = CeilDivision(queryLength, WordSize);
int w = maxBlocks * WordSize - queryLength;
EqualityDefinition equalityDefinition = new EqualityDefinition(alphabet, config.AdditionalEqualities,
config.AdditionalEqualitiesLength);
ulong[] peq = BuildPeq(alphabet.Length, query, queryLength, ref equalityDefinition);
// Main Calculation
int positionNw = -1;
AlignmentData alignmentData = new AlignmentData();
bool dynamicK = false;
int k = config.K;
if (k < 0) // If valid k is not given, auto-adjust k until solution is found.
{
dynamicK = true;
k = WordSize; // Gives better results than smaller k.
}
do
{
MyersEditDistanceNw(peq, w, maxBlocks, queryLength, target, targetLength, k, false, -1,
ref result.EditDistance, ref positionNw, ref alignmentData);
k *= 2;
} while (dynamicK && result.EditDistance == -1);
// NOTE: Do we need this block code? We only care about editing distance
// Since we only care about the editing distance score, this is where we stop
if (result.EditDistance >= 0)
{
// If NW mode, set end location explicitly.
if (config.Mode == AlignmentMode.Nw)
{
result.EndLocations = new int[sizeof(int) * 1];
result.EndLocations[0] = targetLength - 1;
result.NumberOfLocations = 1;
}
// if (!(config.Task == AlignmentTask.TaskLocate || config.Task == AlignmentTask.TaskPath))
// {
// for (int i = 0; i < result.NumberOfLocations; i++) {
// result.StartingLocations[i] = 0;
// }
// }
}
return(result);
}
/// <summary>
/// Uses Myers' bit-vector algorithm to find edit distance for global(NW) alignment method.
/// </summary>
/// <param name="peq"></param>
/// <param name="w"></param>
/// <param name="maxBlocks"></param>
/// <param name="queryLength"></param>
/// <param name="target"></param>
/// <param name="targetLength"></param>
/// <param name="k"></param>
/// <param name="findAlignment"></param>
/// <param name="targetStopPosition"></param>
/// <param name="bestScore"></param>
/// <param name="position"></param>
/// <param name="alignmentData"></param>
/// <returns>Status code.</returns>
private static int MyersEditDistanceNw(ulong[] peq, int w, int maxBlocks, int queryLength, byte[] target,
int targetLength, int k, bool findAlignment, int targetStopPosition, ref int bestScore,
ref int position, ref AlignmentData alignmentData)
{
if (targetStopPosition > -1 && findAlignment)
{
return((int)AlignmentStatus.Error);
}
// Each STRONG_REDUCE_NUM column is reduced in more expensive way.
const int strongReduceNum = 2048;
if (k < Math.Abs(targetLength - queryLength))
{
bestScore = position = -1;
return((int)AlignmentStatus.Ok);
}
k = Math.Min(k, Math.Max(queryLength, targetLength));
int firstBlock = 0;
int lastBlock = Math.Min(maxBlocks,
CeilDivision(Math.Min(k, (k + queryLength - targetLength) / 2) + 1,
WordSize)) - 1;
Block[] bl; // Current block
Block[] blocks = new Block[maxBlocks];
for (int i = 0; i < maxBlocks; i++)
{
blocks[i] = new Block();
}
// Initialize p, m, and score
bl = blocks;
for (int b = 0; b <= lastBlock; b++)
{
bl[b].Score = (b + 1) * WordSize;
bl[b].P = UInt64.MaxValue;
bl[b].M = 0;
}
if (findAlignment)
{
alignmentData = new AlignmentData(maxBlocks, targetLength);
}
else if (targetStopPosition > -1)
{
alignmentData = new AlignmentData(maxBlocks, 1);
}
for (int c = 0; c < targetLength; c++)
{
ulong[] peqC = peq;
// Get offset for the character peq
// peq + *targetChar * maxBlocks
int startPeqC = target[c] * maxBlocks;
// Calculate column
int hout = 1;
// Get first block offset
for (int b = firstBlock; b <= lastBlock; b++)
{
ulong pout, mout;
hout = CalculateBlock(bl[b].P, bl[b].M, peqC[startPeqC + b], hout, out pout, out mout);
bl[b].P = pout;
bl[b].M = mout;
bl[b].Score += hout;
}
k = Math.Min(k,
bl[lastBlock].Score +
Math.Max(targetLength - c - 1, queryLength - ((1 + lastBlock) * WordSize - 1) - 1) +
(lastBlock == maxBlocks - 1 ? w : 0));
// Adjust number of blocks using Ukkonen algorithm
if (lastBlock + 1 < maxBlocks &&
!
( //score[lastBlock] >= k + Constants.WORDSIZE || // NOTICE: this condition could be satisfied if above block also!
((lastBlock + 1) * WordSize - 1
> k - bl[lastBlock].Score + 2 * WordSize - 2 - targetLength + c +
queryLength)))
{
lastBlock++;
bl[lastBlock].P = UInt64.MaxValue;
bl[lastBlock].M = 0;
ulong pout, mout;
int newHout = CalculateBlock(bl[lastBlock].P,
bl[lastBlock].M, peqC[startPeqC + lastBlock], hout, out pout, out mout);
bl[lastBlock].Score =
bl[lastBlock - 1].Score - hout + WordSize + newHout;
bl[lastBlock].P = pout;
bl[lastBlock].M = mout;
hout = newHout;
}
// While block is out of band, move one block up.
// NOTE: Condition used here is more loose than the one from the article, since I simplified the max() part of it.
// I could consider adding that max part, for optimal performance.
while (lastBlock >= firstBlock &&
(bl[lastBlock].Score >= k + WordSize ||
((lastBlock + 1) * WordSize - 1 >
// TODO: Does not work if do not put +1! Why???
k - bl[lastBlock].Score + 2 * WordSize - 2 - targetLength + c +
queryLength + 1)))
{
lastBlock--;
}
// While outside of band, advance block
while (firstBlock <= lastBlock &&
(bl[firstBlock].Score >= k + WordSize ||
((firstBlock + 1) * WordSize - 1 <
bl[firstBlock].Score - k - targetLength + queryLength + c)))
{
firstBlock++;
}
if (c % strongReduceNum == 0)
{
while (lastBlock >= firstBlock)
{
int[] scores = GetBlockCellValues(bl[lastBlock]);
int numCells = lastBlock == maxBlocks - 1 ? WordSize - w : WordSize;
int r = lastBlock * WordSize + numCells - 1;
bool reduce = true;
for (int i = WordSize - numCells; i < WordSize; i++)
{
// TODO: Does not work if do not put +1! Why???
if (scores[i] <= k && r <= k - scores[i] - targetLength + c + queryLength + 1)
{
reduce = false;
break;
}
r--;
}
if (!reduce)
{
break;
}
lastBlock--;
}
while (firstBlock <= lastBlock)
{
int[] scores = GetBlockCellValues(bl[firstBlock]);
int numCells = firstBlock == maxBlocks - 1 ? WordSize - w : WordSize;
int r = firstBlock * WordSize + numCells - 1;
bool reduce = true;
for (int i = WordSize - numCells; i < WordSize; i++)
{
if (scores[i] <= k && r >= scores[i] - k - targetLength + c + queryLength)
{
reduce = false;
break;
}
r--;
}
if (!reduce)
{
break;
}
firstBlock++;
}
}
if (lastBlock < firstBlock)
{
bestScore = position = -1;
return((int)AlignmentStatus.Ok);
}
if (findAlignment && c < targetLength)
{
for (int b = firstBlock; b <= lastBlock; b++)
{
alignmentData.Ps[maxBlocks * c + b] = bl[b].P;
alignmentData.Ms[maxBlocks * c + b] = bl[b].M;
alignmentData.Scores[maxBlocks * c + b] = bl[b].Score;
alignmentData.FirstBlocks[c] = firstBlock;
alignmentData.LastBlocks[c] = lastBlock;
}
}
if (c == targetStopPosition)
{
for (int b = firstBlock; b <= lastBlock; b++)
{
alignmentData.Ps[b] = blocks[b].P;
alignmentData.Ms[b] = blocks[b].M;
alignmentData.Scores[b] = blocks[b].Score;
alignmentData.FirstBlocks[0] = firstBlock;
alignmentData.LastBlocks[0] = lastBlock;
}
bestScore = -1;
position = targetStopPosition;
return((int)AlignmentStatus.Ok);
}
}
if (lastBlock == maxBlocks - 1)
{
int bs = GetBlockCellValues(bl[lastBlock])[w];
if (bs <= k)
{
bestScore = bs;
position = targetLength - 1;
return((int)AlignmentStatus.Ok);
}
}
bestScore = position = -1;
return((int)AlignmentStatus.Ok);
}
public Quaternion TryMatchOrientation(AlignmentData other)
{
return(AlignmentEstimator.GetRotation(Orientations, other.Orientations));
}
/// <summary>
/// Sets the alignment data for this layer, also recomputing the inverse matrix.
/// </summary>
/// <param name="a">the new alignment data to be used.</param>
public void SetAlignment(AlignmentData a)
{
SetAlignmentData(a);
}
void Update()
{
radius = transform.localScale.Average();
data = AlignmentQuery.Scan(transform.position, radius);
}