Now logs

lib/tasks/tag_clustering.rake

@@ -51,7 +51,7 @@ namespace :tag do
       end
     end
 
-    $pad = 0.05
+    $PAD = 0.05
 
     # max flow lg distance to consider tag close
     $MAX_DIST = 4
@@ -168,22 +168,28 @@ namespace :tag do
 
     # normalize, min will always be 0
     tags.each do |t|
-      # increase max by $pad so its rank isn't 0
-      t[:rank] = 1 - (t[:rank]/(max*(1+$pad)))
+      # increase max by $PAD so its rank isn't 0
+      t[:rank] = 1 - (t[:rank]/(max*(1+$PAD)))
     end
 
     return tags
   end
 
   def find_relevant_results(tagId, tags)
+    puts "\nStarted Calculating relevant results for tag of Id #{tagId}\n"
+
     los_ranked = {}
+
+    puts "\nGetting tags from the same cluster, only close ones, MAX_DIST = #{$MAX_DIST}\n"
+    puts "Normalization with padding = #{$PAD}\n"
     close_tags = ranked_close_tags(tagId, tags)
 
-    p "==============="
+    puts "============\n"
     p "close_tags"
     close_tags.each {|ct| p Tag.find(ct[:id]).name+" | "+ct[:id].to_s+" | "+ct[:rank].to_s+" | "+tags[ct[:id]][:rank].to_s}
-    p "==============="
+    puts "============\n"
 
+    puts "\nStarted Ranking LOs...\n"
     # ranks each LO
     # freq = cluster_frequency(close_tags)
     LearningObject.all.each do |lo|
@@ -192,6 +198,7 @@ namespace :tag do
       # los_ranked[lo.id] = relevance_raw_rank(lo, close_tags)
     end
 
+    puts "\nSorting LOs...\n"
     # sorts by its ranking
     los_ranked = los_ranked.sort_by { |id, rank| rank }
     # get highest ranks