kmeans.h

/*-------------------------------------------------------------------------
 *
 * kmeans.h
 *    Generic k-means implementation
 *
 * Copyright (c) 2016, Paul Ramsey <pramsey@cleverelephant.ca>
 *
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
 *
 * 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
 *
 * 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *------------------------------------------------------------------------*/

#ifndef KMEANS_H
#define KMEANS_H

#include <stdlib.h>
#include "php.h"

/*
 * When clustering lists with NULL elements, they will get this as
 * their cluster number. (All the other clusters will be non-negative)
 */
#define KMEANS_NULL_CLUSTER -1

/*
 * If the algorithm doesn't converge within this number of iterations,
 * it will return with a failure error code.
 */
#define KMEANS_MAX_ITERATIONS 1000

#define kmeans_malloc(size) emalloc(size)
#define kmeans_free(ptr) efree(ptr)

typedef void* Pointer;

typedef enum {
        KMEANS_OK,
        KMEANS_EXCEEDED_MAX_ITERATIONS,
        KMEANS_ERROR
} kmeans_result;

/*
 * Prototype for the distance calculating function
 */
typedef double (*kmeans_distance_method) (const Pointer a, const Pointer b);

/*
 * Prototype for the centroid calculating function
 * @param objs the list of all objects in the calculation
 * @param clusters the list of cluster numbers for each object
 * @param num_objs the number of objects/cluster numbers in the previous arrays
 * @param cluster the cluster number we are actually generating a centroid for here
 * @param centroid the object to write the centroid result into (already allocated)
 */
typedef void (*kmeans_centroid_method) (const Pointer *objs, const int *clusters, size_t num_objs, int cluster, Pointer centroid);

typedef struct kmeans_config
{
  /* Function returns the "distance" between any pair of objects */
  kmeans_distance_method distance_method;

  /* Function returns the "centroid" of a collection of objects */
  kmeans_centroid_method centroid_method;

  /*
   * An array of objects to be analyzed. User allocates this array
   * and is responsible for freeing it.
   * For objects that are not capable of participating in the distance
   * calculations, but for which you still want included in the process
   * (for examples, database nulls, or geometry empties) use a NULL
   * value in this list. All NULL values will be returned in the
   * KMEANS_NULL_CLUSTER.
   */
  Pointer *objs;

  /* Number of objects in the preceding array */
  uint32_t num_objs;

  /*
   * An array of initial centers for the algorithm
   * Can be randomly assigned, or using proportions,
   * unfortunately the algorithm is sensitive to starting
   * point, so using "better" set of starting points
   * might be wise. User allocates and is responsible for freeing
   */
  Pointer *centers;

  /* Number of means we are calculating, length of preceding array */
  unsigned int k;

  /*
   * Maximum number of times to iterate the algorithm, or 0 for
   * library default
   */
  unsigned int max_iterations;

  /* Iteration counter */
  unsigned int total_iterations;

  /* Array to fill in with cluster numbers. User allocates and frees. */
  int *clusters;

  int *clusters_sizes;
} kmeans_config;

/* This is where the magic happens. */
kmeans_result kmeans(kmeans_config *config);

#endif