public class org.apache.commons.math.stat.clustering.EuclideanDoublePoint extends java.lang.Object implements org.apache.commons.math.stat.clustering.Clusterable, java.io.Serializable
{
private static final long serialVersionUID;
private final double[] point;
public void <init>(double[])
{
double[] v;
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v := @parameter: double[];
specialinvoke v.<java.lang.Object: void <init>()>();
v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point> = v;
return;
}
public org.apache.commons.math.stat.clustering.EuclideanDoublePoint centroidOf(java.util.Collection)
{
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v, v;
double[] v, v, v;
int v, v, v, v, v, v;
boolean v;
double v, v, v, v, v;
java.util.Iterator v;
java.util.Collection v;
java.lang.Object v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v := @parameter: java.util.Collection;
v = virtualinvoke v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] getPoint()>();
v = lengthof v;
v = newarray (double)[v];
v = interfaceinvoke v.<java.util.Collection: java.util.Iterator iterator()>();
label:
v = interfaceinvoke v.<java.util.Iterator: boolean hasNext()>();
if v == 0 goto label;
v = interfaceinvoke v.<java.util.Iterator: java.lang.Object next()>();
v = 0;
label:
v = lengthof v;
if v >= v goto label;
v = v[v];
v = virtualinvoke v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] getPoint()>();
v = v[v];
v = v + v;
v[v] = v;
v = v + 1;
goto label;
label:
v = 0;
label:
v = lengthof v;
if v >= v goto label;
v = v[v];
v = interfaceinvoke v.<java.util.Collection: int size()>();
v = v / v;
v[v] = v;
v = v + 1;
goto label;
label:
v = new org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
specialinvoke v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: void <init>(double[])>(v);
return v;
}
public double distanceFrom(org.apache.commons.math.stat.clustering.EuclideanDoublePoint)
{
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v, v;
double[] v, v;
double v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v := @parameter: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
v = virtualinvoke v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] getPoint()>();
v = staticinvoke <org.apache.commons.math.util.MathArrays: double distance(double[],double[])>(v, v);
return v;
}
public boolean equals(java.lang.Object)
{
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v;
double[] v, v;
java.lang.Object v;
boolean v, v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v := @parameter: java.lang.Object;
v = v instanceof org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
if v != 0 goto label;
return 0;
label:
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
v = staticinvoke <java.util.Arrays: boolean equals(double[],double[])>(v, v);
return v;
}
public double[] getPoint()
{
double[] v;
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
return v;
}
public int hashCode()
{
double[] v;
int v;
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
v = staticinvoke <java.util.Arrays: int hashCode(double[])>(v);
return v;
}
public java.lang.String toString()
{
double[] v;
java.lang.String v;
org.apache.commons.math.stat.clustering.EuclideanDoublePoint v;
v := @this: org.apache.commons.math.stat.clustering.EuclideanDoublePoint;
v = v.<org.apache.commons.math.stat.clustering.EuclideanDoublePoint: double[] point>;
v = staticinvoke <java.util.Arrays: java.lang.String toString(double[])>(v);
return v;
}
}