Added Boxplots to the EXAMINE subcommand repertoire

[pspp-builds.git] / src / factor_stats.c

diff --git a/src/factor_stats.c b/src/factor_stats.c
index 16e1930d58188723db0ae4a7f64c3c9c9f083447..7c4cce000f928c63c7931469dab9396091d9d064 100644 (file)
--- a/src/factor_stats.c
+++ b/src/factor_stats.c
@@ -24,32 +24,34 @@ Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
 #include "hash.h"
 #include "algorithm.h"
 #include "alloc.h"
+#include "moments.h"
+#include "percentiles.h"
 
 #include <stdlib.h>
 #include <math.h>
 #include <float.h>
 #include <assert.h>
-
+#include <chart.h>
 
 
 void
-metrics_precalc(struct metrics *fs)
+metrics_precalc(struct metrics *m)
 {
-  assert (fs) ;
+  assert (m) ;
+
+  m->n_missing = 0;
+
+  m->min = DBL_MAX;
+  m->max = -DBL_MAX;
 
-  fs->n = 0;
-  fs->n_missing = 0;
-  fs->ssq = 0;
-  fs->sum = 0;
-  fs->min = DBL_MAX;
-  fs->max = -DBL_MAX;
 
-  fs->ordered_data = hsh_create(20,
+  m->moments = moments1_create(MOMENT_KURTOSIS);
+
+  m->ordered_data = hsh_create(20,
                                (hsh_compare_func *) compare_values,
                                (hsh_hash_func *) hash_value,
                                (hsh_free_func *) weighted_value_free,
                                (void *) 0);
-
 }
 
 
@@ -70,9 +72,9 @@ metrics_calc(struct metrics *fs, const union value *val,
     }
 
   x = val->f;
-  fs->n    += weight;
-  fs->ssq  += x * x * weight;
-  fs->sum  += x * weight;
+
+  moments1_add(fs->moments, x, weight);
+
 
   if ( x < fs->min) fs->min = x;
   if ( x > fs->max) fs->max = x;
@@ -116,87 +118,93 @@ metrics_calc(struct metrics *fs, const union value *val,
 void
 metrics_postcalc(struct metrics *m)
 {
-  double sample_var; 
   double cc = 0.0;
   double tc ;
   int k1, k2 ;
   int i;
   int j = 1;  
 
-  struct weighted_value **data;
 
+  moments1_calculate (m->moments, &m->n, &m->mean, &m->var, 
+                     &m->skewness, &m->kurtosis);
 
-  int n_data;
-  
-  m->mean = m->sum / m->n;
+  moments1_destroy (m->moments);
 
-  sample_var = ( m->ssq / m->n  - m->mean * m->mean );
 
-  m->var  = m->n * sample_var / ( m->n - 1) ;
   m->stddev = sqrt(m->var);
 
-
   /* FIXME: Check this is correct ???
      Shouldn't we use the sample variance ??? */
-  m->stderr = sqrt (m->var / m->n) ;
+  m->se_mean = sqrt (m->var / m->n) ;
 
-  data = (struct weighted_value **) hsh_data(m->ordered_data);
-  n_data = hsh_count(m->ordered_data);
 
-  if ( n_data == 0 ) 
-    {
-      m->trimmed_mean = m->mean;
-      return;
-    }
 
+  m->wvp = (struct weighted_value **) hsh_sort(m->ordered_data);
+  m->n_data = hsh_count(m->ordered_data);
 
-  m->wv = xmalloc(sizeof(struct weighted_value ) * n_data);
+  m->histogram = histogram_create(10, m->min, m->max);
 
-  for ( i = 0 ; i < n_data ; ++i )
-      m->wv[i] = *(data[i]);
-
-  sort (m->wv, n_data, sizeof (struct weighted_value) , 
-       (algo_compare_func *) compare_values, 0);
+  for ( i = 0 ; i < m->n_data ; ++i ) 
+    {
+      struct weighted_value **wv = (m->wvp) ;
+      gsl_histogram_accumulate(m->histogram, wv[i]->v.f, wv[i]->w);
+    }
 
-  
   /* Trimmed mean calculation */
+  if ( m->n_data <= 1 ) 
+    {
+      m->trimmed_mean = m->mean;
+      return;
+    }
 
   tc = m->n * 0.05 ;
   k1 = -1;
   k2 = -1;
 
-
-  for ( i = 0 ; i < n_data ; ++i ) 
+  for ( i = 0 ; i < m->n_data ; ++i ) 
     {
-      cc += m->wv[i].w;
-      m->wv[i].cc = cc;
+      cc += m->wvp[i]->w;
+      m->wvp[i]->cc = cc;
 
-      m->wv[i].rank = j + (m->wv[i].w - 1) / 2.0 ;
+      m->wvp[i]->rank = j + (m->wvp[i]->w - 1) / 2.0 ;
       
-      j += m->wv[i].w;
+      j += m->wvp[i]->w;
       
       if ( cc < tc ) 
        k1 = i;
-
     }
 
-  k2 = n_data;
-  for ( i = n_data -1  ; i >= 0; --i ) 
+  
+
+  k2 = m->n_data;
+  for ( i = m->n_data -1  ; i >= 0; --i ) 
     {
-      if ( tc > m->n - m->wv[i].cc) 
+      if ( tc > m->n - m->wvp[i]->cc) 
        k2 = i;
     }
 
 
+  /* Calculate the percentiles */
+  ptiles(m->ptile_hash, m->wvp, m->n_data, m->n, m->ptile_alg);
+
+  tukey_hinges(m->wvp, m->n_data, m->n, m->hinge);
+
+  /* Special case here */
+  if ( k1 + 1 == k2 ) 
+    {
+      m->trimmed_mean = m->wvp[k2]->v.f;
+      return;
+    }
+
   m->trimmed_mean = 0;
   for ( i = k1 + 2 ; i <= k2 - 1 ; ++i ) 
     {
-      m->trimmed_mean += m->wv[i].v.f * m->wv[i].w;
+      m->trimmed_mean += m->wvp[i]->v.f * m->wvp[i]->w;
     }
 
 
-  m->trimmed_mean += (m->n - m->wv[k2 - 1].cc - tc) * m->wv[k2].v.f ;
-  m->trimmed_mean += (m->wv[k1 + 1].cc - tc) * m->wv[k1 + 1].v.f ;
+  m->trimmed_mean += (m->n - m->wvp[k2 - 1]->cc - tc) * m->wvp[k2]->v.f ;
+  m->trimmed_mean += (m->wvp[k1 + 1]->cc - tc) * m->wvp[k1 + 1]->v.f ;
   m->trimmed_mean /= 0.9 * m->n ;
 
 }
@@ -255,19 +263,18 @@ create_factor_statistics (int n, union value *id0, union value *id1)
 void
 factor_statistics_free(struct factor_statistics *f)
 {
+  hsh_destroy(f->m->ordered_data);
+  gsl_histogram_free(f->m->histogram);
   free(f->m) ; 
-
   free(f);
 }
 
 
 
 
-
-
 int 
 factor_statistics_compare(const struct factor_statistics *f0,
-                         const struct factor_statistics *f1, void *aux)
+                         const struct factor_statistics *f1, int width)
 {
 
   int cmp0;
@@ -275,7 +282,7 @@ factor_statistics_compare(const struct factor_statistics *f0,
   assert(f0);
   assert(f1);
 
-  cmp0 = compare_values(&f0->id[0], &f1->id[0], aux);
+  cmp0 = compare_values(&f0->id[0], &f1->id[0], width);
 
   if ( cmp0 != 0 ) 
     return cmp0;
@@ -287,20 +294,20 @@ factor_statistics_compare(const struct factor_statistics *f0,
   if ( ( f0->id[1].f != SYSMIS )  && (f1->id[1].f == SYSMIS) ) 
     return -1;
 
-  return compare_values(&f0->id[1], &f1->id[1], aux);
+  return compare_values(&f0->id[1], &f1->id[1], width);
   
 }
 
 unsigned int 
-factor_statistics_hash(const struct factor_statistics *f, void *aux)
+factor_statistics_hash(const struct factor_statistics *f, int width)
 {
   
   unsigned int h;
 
-  h = hash_value(&f->id[0], aux);
+  h = hash_value(&f->id[0], width);
   
   if ( f->id[1].f != SYSMIS )
-    h += hash_value(&f->id[1], aux);
+    h += hash_value(&f->id[1], width);
 
 
   return h;