src/tests/helpers.c

   1 #include "tests/helpers.h"
   2
   3 //auxiliary to check vectors equality
   4 int checkEqualV(double* v1, double* v2, int n)
   5 {
   6     double epsilon = 1e-10; // arbitrary small value to make comparisons
   7     for (int i=0; i<n; i++)
   8     {
   9         if (fabs(v1[i] - v2[i]) >= epsilon)
  10             return S_FALSE;
  11     }
  12     return S_TRUE;
  13 }
  14
  15 // auxiliary to count distinct values in an integer array
  16 int countDistinctValues(int* v, int n)
  17 {
  18     int maxVal = v[0];
  19     for (int i=1; i<n; i++)
  20     {
  21         if (v[i] > maxVal)
  22             maxVal = v[i];
  23     }
  24     int* kountArray = (int*)calloc(maxVal+1,sizeof(int));
  25     int res = 0;
  26     for (int i=0; i<n; i++)
  27     {
  28         if (kountArray[v[i]] == 0)
  29         {
  30             res++;
  31             kountArray[v[i]] = 1; // mark this value as "seen"
  32         }
  33     }
  34     free(kountArray);
  35     return res;
  36 }
  37
  38 // helper to check clustering result
  39 int labelIsProcessed(int label, int* processedLabels, int countProcessedLabels)
  40 {
  41     for (int j=0; j<countProcessedLabels; j++)
  42     {
  43         if (processedLabels[j] == label)
  44             return S_TRUE;
  45     }
  46     return S_FALSE;
  47 }
  48
  49 // check both clusters purity and size (ideally they all contain n/clustCount points)
  50 int checkClustersProportions(int* clusters, int n, int clustCount, double tol)
  51 {
  52     // initialize array to keep track of clusters labels
  53     int* processedLabels = (int*)malloc(clustCount*sizeof(int));
  54     for (int j=0; j<clustCount; j++)
  55         processedLabels[j] = -1;
  56     int countProcessedLabels = 0, clustSize = n/clustCount;
  57
  58     int i=0;
  59     while (i<n)
  60     {
  61         // go to the next unprocessed label (if possible)
  62         while (i < n && labelIsProcessed(clusters[i], processedLabels, countProcessedLabels))
  63         {
  64             i++;
  65         }
  66         if (i >= n)
  67             break;
  68
  69         int label = clusters[i];
  70         processedLabels[countProcessedLabels++] = label;
  71
  72         // count elements in current cluster (represented by label)
  73         int countDataWithCurLabel = 0;
  74         for (int ii=0; ii<n; ii++)
  75         {
  76             if (clusters[ii] == label)
  77                 countDataWithCurLabel++;
  78         }
  79         // if cluster is too small or too big, test fails
  80         if ( fabs(countDataWithCurLabel - clustSize) / n > tol )
  81         {
  82             free(processedLabels);
  83             return S_FALSE;
  84         }
  85
  86         // now check counts per cluster (repartition);
  87         // the labels should not be spread between different (true) groups
  88         int maxCountLabelInClust = 0;
  89         for (int kounter=0; kounter<clustCount; kounter++)
  90         {
  91             int countLabelInClust = 0;
  92             for (int ii=kounter*clustSize; ii<(kounter+1)*clustSize; ii++)
  93             {
  94                 if (clusters[ii] == label)
  95                     countLabelInClust++;
  96             }
  97             if (countLabelInClust > maxCountLabelInClust)
  98                 maxCountLabelInClust = countLabelInClust;
  99         }
 100         // we must have max(repartition) / clustSize >= 1 - tol
 101         if ((double)maxCountLabelInClust / clustSize < 1.0 - tol)
 102         {
 103             free(processedLabels);
 104             return S_FALSE;
 105         }
 106     }
 107
 108     free(processedLabels);
 109     return S_TRUE;
 110 }