[CLEAN] brouillons removed.

analysis/tfidf.py

-from node.models import Node, NodeType, Node_Resource,\
-        Project, Corpus, Document,\
-        Ngram, Node_Ngram, NodeNgramNgram, NodeNodeNgram,\
-        User, Language, ResourceType, Resource
-
-from math import log
-
-
-
-# - tfidf / corpus , type de corpus, tous corpus
-# - tfidf / échelle de temps
-# - tfidf / sources, auteurs etc.
-# => liste de listes
-
-
-
-def tfidf(corpus, document, ngram):
-    try:
-        x = Node_Ngram.objects.get(node=document, ngram=ngram).weight
-        y = Node_Ngram.objects.filter(node=document).count()
-        tf = x/y
-    
-        xx = Node.objects.filter(parent=corpus, type=NodeType.objects.get(name="Document")).count()
-        yy = Node_Ngram.objects.filter(ngram=ngram).count()
-        idf= log(xx/yy)
-        
-        result = tf * idf
-    except Exception as error:
-        print(error)
-        result = 0
-    return result
-
-
-
-def do_tfidf(corpus, reset=True):
-
-    with transaction.atomic():
-        if reset==True:
-            NodeNodeNgram.objects.filter(nodex=corpus).delete()
-        
-        if isinstance(corpus, Node) and corpus.type.name == "Corpus":
-            for document in Node.objects.filter(parent=corpus, type=NodeType.objects.get(name="Document")):
-                for node_ngram in Node_Ngram.objects.filter(node=document):
-                    try:
-                        nnn = NodeNodeNgram.objects.get(nodex=corpus, nodey=document, ngram=node_ngram.ngram)
-                    except:
-                        score = tfidf(corpus, document, node_ngram.ngram)
-                        nnn = NodeNodeNgram(nodex=corpus, nodey=node_ngram.node, ngram=node_ngram.ngram, score=score)
-                        nnn.save()
-        else:
-            print("Only implemented for corpus yet, whereas you put:", type(corpus))
-
-
-