Removed show hack

[pazpar2-moved-to-github.git] / src / relevance.c

diff --git a/src/relevance.c b/src/relevance.c
index a63abaf..933ca20 100644 (file)
--- a/src/relevance.c
+++ b/src/relevance.c
@@ -1,5 +1,5 @@
 /* This file is part of Pazpar2.
-   Copyright (C) 2006-2010 Index Data
+   Copyright (C) 2006-2011 Index Data
 
 Pazpar2 is free software; you can redistribute it and/or modify it under
 the terms of the GNU General Public License as published by the Free
@@ -26,14 +26,14 @@ Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
 #include <stdlib.h>
 
 #include "relevance.h"
-#include "pazpar2.h"
+#include "session.h"
 
 struct relevance
 {
     int *doc_frequency_vec;
     int vec_len;
     struct word_entry *entries;
-    pp2_charset_t pct;
+    pp2_charset_token_t prt;
     NMEM nmem;
 };
 
@@ -68,7 +68,8 @@ int word_entry_match(struct word_entry *entries, const char *norm_str)
     return 0;
 }
 
-static struct word_entry *build_word_entries(pp2_charset_t pct, NMEM nmem,
+static struct word_entry *build_word_entries(pp2_charset_token_t prt,
+                                             NMEM nmem,
                                              const char **terms)
 {
     int termno = 1; /* >0 signals THERE is an entry */
@@ -77,14 +78,11 @@ static struct word_entry *build_word_entries(pp2_charset_t pct, NMEM nmem,
 
     for (; *p; p++)
     {
-        pp2_relevance_token_t prt = pp2_relevance_tokenize(pct, *p, 0);
         const char *norm_str;
 
-        while ((norm_str = pp2_relevance_token_next(prt)))
+        pp2_charset_token_first(prt, *p, 0);
+        while ((norm_str = pp2_charset_token_next(prt)))
             add_word_entry(nmem, &entries, norm_str, termno);
-
-        pp2_relevance_token_destroy(prt);
-
         termno++;
     }
     return entries;
@@ -93,15 +91,15 @@ static struct word_entry *build_word_entries(pp2_charset_t pct, NMEM nmem,
 void relevance_countwords(struct relevance *r, struct record_cluster *cluster,
                           const char *words, int multiplier, const char *name)
 {
-    pp2_relevance_token_t prt = pp2_relevance_tokenize(r->pct, words, 0);
     int *mult = cluster->term_frequency_vec_tmp;
     const char *norm_str;
     int i, length = 0;
 
+    pp2_charset_token_first(r->prt, words, 0);
     for (i = 1; i < r->vec_len; i++)
         mult[i] = 0;
 
-    while ((norm_str = pp2_relevance_token_next(prt)))
+    while ((norm_str = pp2_charset_token_next(r->prt)))
     {
         int res = word_entry_match(r->entries, norm_str);
         if (res)
@@ -120,11 +118,10 @@ void relevance_countwords(struct relevance *r, struct record_cluster *cluster,
     }
 
     cluster->term_frequency_vec[0] += length;
-    pp2_relevance_token_destroy(prt);
 }
 
-struct relevance *relevance_create(pp2_charset_t pct,
-                                   NMEM nmem, const char **terms)
+static struct relevance *relevance_create(pp2_charset_fact_t pft,
+                                          NMEM nmem, const char **terms)
 {
     struct relevance *res = nmem_malloc(nmem, sizeof(struct relevance));
     const char **p;
@@ -136,11 +133,61 @@ struct relevance *relevance_create(pp2_charset_t pct,
     res->doc_frequency_vec = nmem_malloc(nmem, res->vec_len * sizeof(int));
     memset(res->doc_frequency_vec, 0, res->vec_len * sizeof(int));
     res->nmem = nmem;
-    res->entries = build_word_entries(pct, nmem, terms);
-    res->pct = pct;
+    res->prt = pp2_charset_token_create(pft, "relevance");
+    res->entries = build_word_entries(res->prt, nmem, terms);
     return res;
 }
 
+// Recursively traverse query structure to extract terms.
+static void pull_terms(NMEM nmem, struct ccl_rpn_node *n,
+                       char **termlist, int *num, int max_terms)
+{
+    char **words;
+    int numwords;
+    int i;
+
+    switch (n->kind)
+    {
+    case CCL_RPN_AND:
+    case CCL_RPN_OR:
+    case CCL_RPN_NOT:
+    case CCL_RPN_PROX:
+        pull_terms(nmem, n->u.p[0], termlist, num, max_terms);
+        pull_terms(nmem, n->u.p[1], termlist, num, max_terms);
+        break;
+    case CCL_RPN_TERM:
+        nmem_strsplit(nmem, " ", n->u.t.term, &words, &numwords);
+        for (i = 0; i < numwords; i++)
+        {
+            if (*num < max_terms)
+                termlist[(*num)++] = words[i];
+        }
+        break;
+    default: // NOOP
+        break;
+    }
+}
+
+struct relevance *relevance_create_ccl(pp2_charset_fact_t pft,
+                                       NMEM nmem, struct ccl_rpn_node *query)
+{
+    char *termlist[512];
+    int num = 0;
+
+    pull_terms(nmem, query, termlist, &num, sizeof(termlist)/sizeof(*termlist));
+    termlist[num] = 0;
+    return relevance_create(pft, nmem, (const char **) termlist);
+}
+
+void relevance_destroy(struct relevance **rp)
+{
+    if (*rp)
+    {
+        pp2_charset_token_destroy((*rp)->prt);
+        *rp = 0;
+    }
+}
+
 void relevance_newrec(struct relevance *r, struct record_cluster *rec)
 {
     if (!rec->term_frequency_vec)
@@ -186,7 +233,7 @@ void relevance_prepare_read(struct relevance *rel, struct reclist *reclist)
     int i;
     float *idfvec = xmalloc(rel->vec_len * sizeof(float));
 
-    reclist_rewind(reclist);
+    reclist_enter(reclist);
     // Calculate document frequency vector for each term.
     for (i = 1; i < rel->vec_len; i++)
     {
@@ -230,9 +277,9 @@ void relevance_prepare_read(struct relevance *rel, struct reclist *reclist)
 #endif
             relevance += 100000 * (termfreq * idfvec[t] + 0.0000005);  
         }
-        rec->relevance = relevance;
+        rec->relevance_score = relevance;
     }
-    reclist_rewind(reclist);
+    reclist_leave(reclist);
     xfree(idfvec);
 }