Remove unused recommenders when recommending and allow keeping topLists

via args

caliGraph.py

@@ -265,8 +265,18 @@ def removeRestOfSeries(G):
                 if adjNode['series_index'] > seriesState + 1.0001:
                     G.remove_node(adj)
 
+def removeUnusedRecommenders(G):
+    for n in list(G.nodes):
+        node = G.nodes[n]
+        if node['t'] == 'recommender':
+            for adj in G.adj[n]:
+                adjNode = G.nodes[adj]
+                if adjNode['t']=='book' and 'score' in adjNode:
+                    break
+            else: # No unrated recommendation
+                G.remove_node(n)
 
-def scoreOpinions(G, globMu, globStd, errorFac=0.7):
+def scoreOpinions(G, globMu, globStd, errorFac=0.5):
     for n in list(G.nodes):
         node = G.nodes[n]
         feedbacks = []
@@ -498,7 +508,7 @@ def genScores(G, books):
     return globMu, globStd
 
 
-def recommendNBooks(G, mu, std, n):
+def recommendNBooks(G, mu, std, n, removeTopListsB=True):
     removeRestOfSeries(G)
     removeBad(G, mu-std-1.5)
     removeKeepBest(G, int(n*2) + 5, maxDistForRead=1.5)
@@ -510,20 +520,23 @@ def recommendNBooks(G, mu, std, n):
     pruneTags(G, 4.25)
     pruneRecommenderCons(G, int(n/7)+1)
     pruneAuthorCons(G, int(n/15))
+    if removeTopListsB:
         removeTopLists(G)
     removeDangling(G, alsoBooks=True)
     removeKeepBest(G, n, maxDistForRead=0.75)
     removeEdge(G)
     removeDangling(G, alsoBooks=True)
+    removeUnusedRecommenders(G)
 
     scaleBooksByRating(G)
     scaleOpinionsByRating(G)
     addScoreToLabels(G)
 
-def fullGraph(G):
+def fullGraph(G, removeTopLists=True):
     removeEdge(G)
     removeHighSpanTags(G, 7)
     removeDangling(G, alsoBooks=False)
+    if removeTopLists:
         removeTopLists(G)
     pruneTags(G, 3)
     removeDangling(G, alsoBooks=True)
@@ -533,13 +546,14 @@ def fullGraph(G):
     addScoreToLabels(G)
 
 
-def readBooksAnalysis(G, minRating=0, showAllTags=True, removeUnconnected=False):
+def readBooksAnalysis(G, minRating=0, showAllTags=True, removeUnconnected=False, removeTopListsB=True):
     removeUnread(G)
     removeBad(G, minRating)
     if not showAllTags:
         removeEdge(G)
     removeHighSpanTags(G, 15)
     removeDangling(G, alsoBooks=removeUnconnected)
+    if removeTopListsB:
         removeTopLists(G)
     pruneTags(G, 8)
 
@@ -634,6 +648,7 @@ def cliInterface():
     parser.add_argument('--no-web', action="store_true")
     parser.add_argument('--no-list', action="store_true")
     parser.add_argument('--remove-edge', action="store_true")
+    parser.add_argument('--keep-top-lists', action="store_true")
     cmds = parser.add_subparsers(required=True, dest='cmd')
 
     p_rec = cmds.add_parser('recommend', description="TODO", aliases=['rec'])
@@ -663,13 +678,13 @@ def cliInterface():
         removeUnread(G)
 
     if args.cmd=="recommend":
-        recommendNBooks(G, mu, std, args.n)
+        recommendNBooks(G, mu, std, args.n, not args.keep_top_lists)
     elif args.cmd=="read":
-        readBooksAnalysis(G, args.min_rating, args.all_tags, args.only_connected)
+        readBooksAnalysis(G, args.min_rating, args.all_tags, args.only_connected, not args.keep_top_lists)
     elif args.cmd=="analyze":
         analyze(G, args.type, args.name, args.d)
     elif args.cmd=="full":
-        fullGraph(G)
+        fullGraph(G, not args.keep_top_lists)
     else:
         raise Exception("Bad")