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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
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 */
/**
 *
 * This package provides classes to implement Binary Space Partition trees.
 *
 * 

* {@link org.apache.commons.math3.geometry.partitioning.BSPTree BSP trees} * are an efficient way to represent parts of space and in particular * polytopes (line segments in 1D, polygons in 2D and polyhedrons in 3D) * and to operate on them. The main principle is to recursively subdivide * the space using simple hyperplanes (points in 1D, lines in 2D, planes * in 3D). *

* *

* We start with a tree composed of a single node without any cut * hyperplane: it represents the complete space, which is a convex * part. If we add a cut hyperplane to this node, this represents a * partition with the hyperplane at the node level and two half spaces at * each side of the cut hyperplane. These half-spaces are represented by * two child nodes without any cut hyperplanes associated, the plus child * which represents the half space on the plus side of the cut hyperplane * and the minus child on the other side. Continuing the subdivisions, we * end up with a tree having internal nodes that are associated with a * cut hyperplane and leaf nodes without any hyperplane which correspond * to convex parts. *

* *

* When BSP trees are used to represent polytopes, the convex parts are * known to be completely inside or outside the polytope as long as there * is no facet in the part (which is obviously the case if the cut * hyperplanes have been chosen as the underlying hyperplanes of the * facets (this is called an autopartition) and if the subdivision * process has been continued until all facets have been processed. It is * important to note that the polytope is not defined by a * single part, but by several convex ones. This is the property that * allows BSP-trees to represent non-convex polytopes despites all parts * are convex. The {@link * org.apache.commons.math3.geometry.partitioning.Region Region} class is * devoted to this representation, it is build on top of the {@link * org.apache.commons.math3.geometry.partitioning.BSPTree BSPTree} class using * boolean objects as the leaf nodes attributes to represent the * inside/outside property of each leaf part, and also adds various * methods dealing with boundaries (i.e. the separation between the * inside and the outside parts). *

* *

* Rather than simply associating the internal nodes with an hyperplane, * we consider sub-hyperplanes which correspond to the part of * the hyperplane that is inside the convex part defined by all the * parent nodes (this implies that the sub-hyperplane at root node is in * fact a complete hyperplane, because there is no parent to bound * it). Since the parts are convex, the sub-hyperplanes are convex, in * 3D the convex parts are convex polyhedrons, and the sub-hyperplanes * are convex polygons that cut these polyhedrons in two * sub-polyhedrons. Using this definition, a BSP tree completely * partitions the space. Each point either belongs to one of the * sub-hyperplanes in an internal node or belongs to one of the leaf * convex parts. *

* *

* In order to determine where a point is, it is sufficient to check its * position with respect to the root cut hyperplane, to select the * corresponding child tree and to repeat the procedure recursively, * until either the point appears to be exactly on one of the hyperplanes * in the middle of the tree or to be in one of the leaf parts. For * this operation, it is sufficient to consider the complete hyperplanes, * there is no need to check the points with the boundary of the * sub-hyperplanes, because this check has in fact already been realized * by the recursive descent in the tree. This is very easy to do and very * efficient, especially if the tree is well balanced (the cost is * O(log(n)) where n is the number of facets) * or if the first tree levels close to the root discriminate large parts * of the total space. *

* *

* One of the main sources for the development of this package was Bruce * Naylor, John Amanatides and William Thibault paper Merging * BSP Trees Yields Polyhedral Set Operations Proc. Siggraph '90, * Computer Graphics 24(4), August 1990, pp 115-124, published by the * Association for Computing Machinery (ACM). The same paper can also be * found here. *

* *

* Note that the interfaces defined in this package are not intended to * be implemented by Apache Commons Math users, they are only intended to be * implemented within the library itself. New methods may be added even for * minor versions, which breaks compatibility for external implementations. *

* */ package org.apache.commons.math3.geometry.partitioning;




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