private NearestNeighbourModel(NearestNeighbourModel original, Cloner cloner)
: base(original, cloner) {
kdTree = new alglib.nearestneighbor.kdtree();
kdTree.approxf = original.kdTree.approxf;
kdTree.boxmax = (double[])original.kdTree.boxmax.Clone();
kdTree.boxmin = (double[])original.kdTree.boxmin.Clone();
kdTree.buf = (double[])original.kdTree.buf.Clone();
kdTree.curboxmax = (double[])original.kdTree.curboxmax.Clone();
kdTree.curboxmin = (double[])original.kdTree.curboxmin.Clone();
kdTree.curdist = original.kdTree.curdist;
kdTree.debugcounter = original.kdTree.debugcounter;
kdTree.idx = (int[])original.kdTree.idx.Clone();
kdTree.kcur = original.kdTree.kcur;
kdTree.kneeded = original.kdTree.kneeded;
kdTree.n = original.kdTree.n;
kdTree.nodes = (int[])original.kdTree.nodes.Clone();
kdTree.normtype = original.kdTree.normtype;
kdTree.nx = original.kdTree.nx;
kdTree.ny = original.kdTree.ny;
kdTree.r = (double[])original.kdTree.r.Clone();
kdTree.rneeded = original.kdTree.rneeded;
kdTree.selfmatch = original.kdTree.selfmatch;
kdTree.splits = (double[])original.kdTree.splits.Clone();
kdTree.tags = (int[])original.kdTree.tags.Clone();
kdTree.x = (double[])original.kdTree.x.Clone();
kdTree.xy = (double[,])original.kdTree.xy.Clone();
k = original.k;
targetVariable = original.targetVariable;
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
if (original.classValues != null)
this.classValues = (double[])original.classValues.Clone();
}
private NearestNeighbourModel(NearestNeighbourModel original, Cloner cloner)
: base(original, cloner)
{
kdTree = new alglib.nearestneighbor.kdtree();
kdTree.approxf = original.kdTree.approxf;
kdTree.boxmax = (double[])original.kdTree.boxmax.Clone();
kdTree.boxmin = (double[])original.kdTree.boxmin.Clone();
kdTree.buf = (double[])original.kdTree.buf.Clone();
kdTree.curboxmax = (double[])original.kdTree.curboxmax.Clone();
kdTree.curboxmin = (double[])original.kdTree.curboxmin.Clone();
kdTree.curdist = original.kdTree.curdist;
kdTree.debugcounter = original.kdTree.debugcounter;
kdTree.idx = (int[])original.kdTree.idx.Clone();
kdTree.kcur = original.kdTree.kcur;
kdTree.kneeded = original.kdTree.kneeded;
kdTree.n = original.kdTree.n;
kdTree.nodes = (int[])original.kdTree.nodes.Clone();
kdTree.normtype = original.kdTree.normtype;
kdTree.nx = original.kdTree.nx;
kdTree.ny = original.kdTree.ny;
kdTree.r = (double[])original.kdTree.r.Clone();
kdTree.rneeded = original.kdTree.rneeded;
kdTree.selfmatch = original.kdTree.selfmatch;
kdTree.splits = (double[])original.kdTree.splits.Clone();
kdTree.tags = (int[])original.kdTree.tags.Clone();
kdTree.x = (double[])original.kdTree.x.Clone();
kdTree.xy = (double[, ])original.kdTree.xy.Clone();
k = original.k;
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
if (original.classValues != null)
{
this.classValues = (double[])original.classValues.Clone();
}
}
private NearestNeighbourModel(NearestNeighbourModel original, Cloner cloner)
: base(original, cloner)
{
kdTree = new alglib.nearestneighbor.kdtree();
kdTree.approxf = original.kdTree.approxf;
kdTree.boxmax = (double[])original.kdTree.boxmax.Clone();
kdTree.boxmin = (double[])original.kdTree.boxmin.Clone();
kdTree.buf = (double[])original.kdTree.buf.Clone();
kdTree.curboxmax = (double[])original.kdTree.curboxmax.Clone();
kdTree.curboxmin = (double[])original.kdTree.curboxmin.Clone();
kdTree.curdist = original.kdTree.curdist;
kdTree.debugcounter = original.kdTree.debugcounter;
kdTree.idx = (int[])original.kdTree.idx.Clone();
kdTree.kcur = original.kdTree.kcur;
kdTree.kneeded = original.kdTree.kneeded;
kdTree.n = original.kdTree.n;
kdTree.nodes = (int[])original.kdTree.nodes.Clone();
kdTree.normtype = original.kdTree.normtype;
kdTree.nx = original.kdTree.nx;
kdTree.ny = original.kdTree.ny;
kdTree.r = (double[])original.kdTree.r.Clone();
kdTree.rneeded = original.kdTree.rneeded;
kdTree.selfmatch = original.kdTree.selfmatch;
kdTree.splits = (double[])original.kdTree.splits.Clone();
kdTree.tags = (int[])original.kdTree.tags.Clone();
kdTree.x = (double[])original.kdTree.x.Clone();
kdTree.xy = (double[, ])original.kdTree.xy.Clone();
selfMatch = original.selfMatch;
k = original.k;
isCompatibilityLoaded = original.IsCompatibilityLoaded;
if (!IsCompatibilityLoaded)
{
weights = new double[original.weights.Length];
Array.Copy(original.weights, weights, weights.Length);
offsets = new double[original.offsets.Length];
Array.Copy(original.offsets, this.offsets, this.offsets.Length);
}
allowedInputVariables = (string[])original.allowedInputVariables.Clone();
if (original.classValues != null)
{
this.classValues = (double[])original.classValues.Clone();
}
}
