X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Ffactor_stats.c;h=e090517bddc494e2a60279664d4ad53d96b26062;hb=933b760efccdfa26f14254f1fae002ea3b0a1495;hp=fe259ff4e790d31f91b4ce7c4a7f3906836e93a5;hpb=d2f8593a1f1d39a3264682af0da898a3d67b68cf;p=pspp

diff --git a/src/factor_stats.c b/src/factor_stats.c
index fe259ff4e7..e090517bdd 100644
--- a/src/factor_stats.c
+++ b/src/factor_stats.c
@@ -15,77 +15,321 @@ General Public License for more details.
 
 You should have received a copy of the GNU General Public License
 along with this program; if not, write to the Free Software
-Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
-02111-1307, USA. */
+Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
+02110-1301, USA. */
 
+#include <config.h>
 #include "factor_stats.h"
-#include "config.h"
 #include "val.h"
+#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)
 {
-  fs->n = 0;
-  fs->ssq = 0;
-  fs->sum = 0;
-  fs->min = DBL_MAX;
-  fs->max = -DBL_MAX;
+  assert (m) ;
+
+  m->n_missing = 0;
+
+  m->min = DBL_MAX;
+  m->max = -DBL_MAX;
+
+  m->histogram = 0;
+
+  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);
 }
 
+
+/* Include val in the calculation for the metrics.
+   If val is null, then treat it as MISSING
+*/
 void
-metrics_calc(struct metrics *fs, double x, double weight)
+metrics_calc(struct metrics *fs, const union value *val, 
+	     double weight, int case_no)
 {
-  fs->n    += weight;
-  fs->ssq  += x * x * weight;
-  fs->sum  += x * weight;
+  struct weighted_value **wv;
+  double x;
+  
+  if ( ! val ) 
+    {
+      fs->n_missing += weight;
+      return ;
+    }
+
+  x = val->f;
+
+  moments1_add(fs->moments, x, weight);
+
 
   if ( x < fs->min) fs->min = x;
   if ( x > fs->max) fs->max = x;
 
+
+  wv = (struct weighted_value **) hsh_probe (fs->ordered_data,(void *) val );
+
+  if ( *wv  ) 
+    {
+      /* If this value has already been seen, then simply 
+	 increase its weight  and push a new case number */
+
+      struct case_node *cn;
+
+      assert( (*wv)->v.f == val->f );
+      (*wv)->w += weight;      
+
+      cn = xmalloc( sizeof (struct case_node) ) ;
+      cn->next = (*wv)->case_nos ;
+      cn->num = case_no;
+
+      (*wv)->case_nos = cn;
+    }
+  else
+    {
+      struct case_node *cn;
+
+      *wv = weighted_value_create();
+      (*wv)->v = *val;
+      (*wv)->w = weight;
+      
+      cn = xmalloc( sizeof (struct case_node) ) ;
+      cn->next=0;
+      cn->num = case_no;
+      (*wv)->case_nos  = cn;
+
+    }
+
 }
 
 void
-metrics_postcalc(struct metrics *fs)
+metrics_postcalc(struct metrics *m)
 {
-  double sample_var; 
-  fs->mean = fs->sum / fs->n;
+  double cc = 0.0;
+  double tc ;
+  int k1, k2 ;
+  int i;
+  int j = 1;  
 
-  sample_var = ( fs->ssq / fs->n  - fs->mean * fs->mean );
+  moments1_calculate (m->moments, &m->n, &m->mean, &m->var, 
+		      &m->skewness, &m->kurtosis);
 
-  fs->var  = fs->n * sample_var / ( fs->n - 1) ;
-  fs->stddev = sqrt(fs->var);
+  moments1_destroy (m->moments);
 
 
+  m->stddev = sqrt(m->var);
+
   /* FIXME: Check this is correct ???
      Shouldn't we use the sample variance ??? */
-  fs->stderr = sqrt (fs->var / fs->n) ;
+  m->se_mean = sqrt (m->var / m->n) ;
+
+
+
+  m->wvp = (struct weighted_value **) hsh_sort(m->ordered_data);
+  m->n_data = hsh_count(m->ordered_data);
+
+  /* Trimmed mean calculation */
+  if ( m->n_data <= 1 ) 
+    {
+      m->trimmed_mean = m->mean;
+      return;
+    }
+
+  m->histogram = histogram_create(10, m->min, m->max);
+
+  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);
+    }
+
+  tc = m->n * 0.05 ;
+  k1 = -1;
+  k2 = -1;
+
+  for ( i = 0 ; i < m->n_data ; ++i ) 
+    {
+      cc += m->wvp[i]->w;
+      m->wvp[i]->cc = cc;
+
+      m->wvp[i]->rank = j + (m->wvp[i]->w - 1) / 2.0 ;
+      
+      j += m->wvp[i]->w;
+      
+      if ( cc < tc ) 
+	k1 = i;
+    }
+
+  
+
+  k2 = m->n_data;
+  for ( i = m->n_data -1  ; i >= 0; --i ) 
+    {
+      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->wvp[i]->v.f * m->wvp[i]->w;
+    }
+
+
+  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 ;
+
+
+}
 
+
+struct weighted_value *
+weighted_value_create(void)
+{
+  struct weighted_value *wv;
+  wv = xmalloc (sizeof (struct weighted_value ));
+
+  wv->cc = 0;
+  wv->case_nos = 0;
+
+  return wv;
 }
 
+void 
+weighted_value_free(struct weighted_value *wv)
+{
+  struct case_node *cn ;
+
+  if ( !wv ) 
+    return ;
+
+  cn = wv->case_nos;
+
+  while(cn)
+    {
+      struct case_node *next = cn->next;
+      
+      free(cn);
+      cn = next;
+    }
+
+  free(wv);
+
+}
+
+
+
+
+
+/* Create a factor statistics object with for N dependent vars
+   and ID as the value of the independent variable */
+struct factor_statistics * 
+create_factor_statistics (int n, union value *id0, union value *id1)
+{
+  struct factor_statistics *f;
+
+  f =  xmalloc( sizeof  ( struct factor_statistics ));
+
+  f->id[0] = *id0;
+  f->id[1] = *id1;
+  f->m = xmalloc( sizeof ( struct metrics ) * n ) ;
+  memset (f->m, 0, sizeof(struct metrics) * n);
+  f->n_var = n;
+
+  return f;
+}
 
-/* Functions for hashes */
 
 void 
-free_factor_stats(struct factor_statistics *f, int width UNUSED)
+metrics_destroy(struct metrics *m)
 {
-  free (f);
+  hsh_destroy(m->ordered_data);
+  hsh_destroy(m->ptile_hash);
+  if ( m-> histogram ) 
+    gsl_histogram_free(m->histogram);
 }
 
-int
-compare_indep_values(const struct factor_statistics *f1, 
-		     const struct factor_statistics *f2, 
-		     int width)
+void
+factor_statistics_free(struct factor_statistics *f)
 {
-  return compare_values(f1->id, f2->id, width);
+
+  int i; 
+  for ( i = 0 ; i < f->n_var; ++i ) 
+       metrics_destroy(&f->m[i]);
+  free(f->m) ; 
+  free(f);
 }
 
 
-unsigned 
-hash_indep_value(const struct factor_statistics *f, int width)
+
+
+int 
+factor_statistics_compare(const struct factor_statistics *f0,
+	                  const struct factor_statistics *f1, int width)
+{
+
+  int cmp0;
+
+  assert(f0);
+  assert(f1);
+
+  cmp0 = compare_values(&f0->id[0], &f1->id[0], width);
+
+  if ( cmp0 != 0 ) 
+    return cmp0;
+
+
+  if ( ( f0->id[1].f == SYSMIS )  && (f1->id[1].f != SYSMIS) ) 
+    return 1;
+
+  if ( ( f0->id[1].f != SYSMIS )  && (f1->id[1].f == SYSMIS) ) 
+    return -1;
+
+  return compare_values(&f0->id[1], &f1->id[1], width);
+  
+}
+
+unsigned int 
+factor_statistics_hash(const struct factor_statistics *f, int width)
 {
-  return hash_value(f->id, width);
+  
+  unsigned int h;
+
+  h = hash_value(&f->id[0], width);
+  
+  if ( f->id[1].f != SYSMIS )
+    h += hash_value(&f->id[1], width);
+
+
+  return h;
+
 }
+