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(); } }