old_C_code/stage1/src/Classification/getClass.c

   1 #include "Algorithm/get_dissimilarities.h"
   2 #include "TimeSeries/deserialize.h"
   3 #include <math.h>
   4 #include "Algorithm/compute_coefficients.h"
   5 #include <string.h>
   6 #include "Util/utils.h"
   7
   8 uint32_t* get_class(PowerCurve* data, uint32_t nbSeries, PowerCurve* medoids,
   9     uint32_t nbClusters, uint32_t nbValues, uint32_t p_for_dissims, double* DISTOR)
  10 {
  11     // nbReducedCoordinates = smallest power of 2 which is above nbValues
  12     uint32_t nbReducedCoordinates = (uint32_t)ceil(log2(nbValues));
  13
  14     // Preprocessing to reduce dimension of both data and medoids
  15     float* reducedCoordinates_data = (float*) malloc(nbSeries * nbReducedCoordinates * sizeof(float));
  16     compute_coefficients(data, nbSeries, nbValues,
  17         reducedCoordinates_data, 0, nbReducedCoordinates);
  18     float* reducedCoordinates_medoids = (float*) malloc(nbClusters * nbReducedCoordinates * sizeof(float));
  19     compute_coefficients(medoids, nbClusters, nbValues,
  20         reducedCoordinates_medoids, 0, nbReducedCoordinates);
  21
  22     float* dissimilarities = get_dissimilarities_inter(reducedCoordinates_data, nbSeries,
  23         reducedCoordinates_medoids, nbClusters, nbReducedCoordinates, p_for_dissims);
  24     free(reducedCoordinates_data);
  25     free(reducedCoordinates_medoids);
  26
  27     // 3] Finally, assign each row to the least dissimilar center
  28     uint32_t* result = (uint32_t*) malloc(nbSeries*sizeof(uint32_t));
  29     for (uint32_t i=0; i<nbSeries; i++)
  30     {
  31         uint32_t minIndex = 0;
  32         float minDissim = dissimilarities[i*nbClusters + 0];
  33         for (uint32_t j=1; j<nbClusters; j++)
  34         {
  35             if (dissimilarities[i*nbClusters + j] < minDissim)
  36             {
  37                 minDissim = dissimilarities[i*nbClusters + j];
  38                 minIndex = j;
  39             }
  40         }
  41         result[i] = minIndex + 1;
  42         (*DISTOR) += minDissim;
  43     }
  44     free(dissimilarities);
  45     return result;
  46 }