[FIX] merge with samuel changes (use of nx.isolates for degree <=1)

analysis/functions.py

@@ -115,8 +115,9 @@ def do_distance(cooc_id):
     #edges_to_remove = [ e for e in G.edges_iter() if
 
     degree = G.degree()
-    nodes_to_remove = [n for n in degree if degree[n] <= 1]
-    G.remove_nodes_from(nodes_to_remove)
+    G.remove_nodes_from(nx.isolates(G))
+    #nodes_to_remove = [n for n in degree if degree[n] <= 1]
+    #G.remove_nodes_from(nodes_to_remove)
     partition = best_partition(G.to_undirected())
     print("Density of the graph:", nx.density(G))
     return(G,partition,ids,weight)
@@ -150,7 +151,8 @@ def get_cooc(request=None, corpus=None
                 G.node[node]['pk'] = ids[node]
                 G.node[node]['label']   = session.query(Ngram.terms).filter(Ngram.id==node).first()
                 G.node[node]['size']    = weight[ids[node]]
-                G.node[node]['group']   = partition[node]
+                G.node[node]['type']    = "NGrams"
+                G.node[node]['attributes'] = { "clust_default": partition[node]} # new format
                 # G.add_edge(node, "cluster " + str(partition[node]), weight=3)
             except Exception as error:
                 pass #PrintException()

gargantext_web/urls.py

@@ -78,6 +78,8 @@ urlpatterns = patterns('',
     url(r'^ngrams$', views.ngrams),  # to be removed
     url(r'^nodeinfo/(\d+)$', views.nodeinfo), # to be removed ?
     url(r'^tfidf/(\d+)/(\w+)$', views_optimized.tfidf),
+    url(r'^api/corpusintersection/(\w+)$', views_optimized.getCorpusIntersection),
+    url(r'^api/userportfolio/project/(\d+)/corpuses$', views_optimized.getUserPortfolio),
     
     url(r'^project/(\d+)/corpus/(\d+)/(\w+)/update$', views.update_nodes),
     # TODO rest to update corpus and information for progress bar

gargantext_web/views.py

@@ -566,33 +566,14 @@ def graph(request, project_id, corpus_id, generic=100, specific=100):
     project_type_id = cache.NodeType['Project'].id
     corpus_type_id = cache.NodeType['Corpus'].id
 
-    results = {}
-    projs = session.query(Node).filter(Node.user_id == user_id,Node.type_id==project_type_id).all()
-    for i in projs:
-        # print(i.id , i.name)
-        if i.id not in results: results[i.id] = {}
-        results[i.id]["proj_name"] = i.name
-        results[i.id]["corpuses"] = []
-        corpuses = session.query(Node).filter(Node.parent_id==i.id , Node.type_id==corpus_type_id).all()
-        for j in corpuses:
-            if int(j.id)!=int(corpus_id):
-                info = { "id":j.id , "name":j.name }
-                results[i.id]["corpuses"].append(info)
-                # print("\t",j.id , j.name)
-
-    # import pprint
-    # pprint.pprint(results)
-
-#    if specific != None and generic != None :
-
     graphurl = "corpus/"+str(corpus_id)+"/node_link.json"
+
     html = t.render(Context({\
             'debug': settings.DEBUG,
             'user'      : user,\
             'date'      : date,\
             'corpus'    : corpus,\
             'project'   : project,\
-            'corpusinfo'   : results,\
             'graphfile' : graphurl,\
             }))
 

gargantext_web/views_optimized.py

@@ -195,7 +195,7 @@ def tfidf(request, corpus_id, ngram_ids):
     """Takes IDs of corpus and ngram and returns list of relevent documents in json format
     according to TFIDF score (order is decreasing).
     """
-    limit=6
+    limit=5
     nodes_list = []
     # filter input
     ngram_ids = ngram_ids.split('a')
@@ -219,7 +219,7 @@ def tfidf(request, corpus_id, ngram_ids):
     # print("\tcorpus_id:",corpus_id)
     # convert query result to a list of dicts
     for node, score in nodes_query:
-        print("\t corpus:",corpus_id,"\t",node.name)
+        # print("\t corpus:",corpus_id,"\t",node.name)
         node_dict = {
             'id': node.id,
             'score': score,
@@ -229,6 +229,85 @@ def tfidf(request, corpus_id, ngram_ids):
                 node_dict[key] = node.hyperdata[key]
         nodes_list.append(node_dict)
 
-    # print("= = = = = = = = \n")
-    data = json.dumps(nodes_list)
-    return JsonHttpResponse(data)
+    return JsonHttpResponse(nodes_list)
+
+
+def getCorpusIntersection(request , corpuses_ids):
+
+    FinalDict = False
+    if request.method == 'POST' and "nodeids" in request.POST and len(request.POST["nodeids"])>0:
+        import ast
+        node_ids = [int(i) for i in (ast.literal_eval( request.POST["nodeids"] )) ]
+        # Here are the visible nodes of the initial semantic map.
+
+        corpuses_ids = corpuses_ids.split('a')
+        corpuses_ids = [int(i) for i in corpuses_ids] # corpus[1] will be the corpus to compare
+        cooc_type_id = cache.NodeType['Cooccurrence'].id
+        
+        cooc_ids  = session.query(Node.id).filter(Node.user_id == request.user.id , Node.parent_id==corpuses_ids[1] , Node.type_id == cooc_type_id ).first()
+        if len(cooc_ids)==0:
+            return JsonHttpResponse(FinalDict)
+         # If corpus[1] has a coocurrence.id then lets continue
+
+        Cooc_Avg = {}
+        import networkx as nx
+        G = nx.Graph() # I use an undirected graph, because direction doesnt matter here, coocs should be a triangular matrix, so...
+        ngrams_data1 = session.query(NodeNgramNgram).filter( NodeNgramNgram.node_id==cooc_ids[0], NodeNgramNgram.ngramx_id.in_( node_ids )).all()
+        for ngram in ngrams_data1: # are there visible nodes in the X-axis of corpus to compare ?
+            G.add_edge(  ngram.ngramx_id ,  ngram.ngramy_id , weight=ngram.score)
+
+        ngrams_data2 = session.query(NodeNgramNgram).filter( NodeNgramNgram.node_id==cooc_ids[0], NodeNgramNgram.ngramy_id.in_( node_ids )).all()
+        for ngram in ngrams_data2: # are there visible nodes in the Y-axis of corpus to compare ?
+            if not G.has_edge(ngram.ngramx_id,ngram.ngramy_id):
+                G.add_edge(  ngram.ngramx_id ,  ngram.ngramy_id , weight=ngram.score)
+
+        for e in G.edges_iter():
+            n1 = e[0]
+            n2 = e[1]
+            # print( G[n1][n2]["weight"] , "\t", n1,",",n2 )
+            if n1 not in Cooc_Avg:
+                Cooc_Avg[n1]=0
+            if n2 not in Cooc_Avg:
+                Cooc_Avg[n2]=0
+            Cooc_Avg[n1]+=G[n1][n2]["weight"] 
+            Cooc_Avg[n2]+=G[n1][n2]["weight"] 
+        FinalDict = {}
+        for node in node_ids:
+            if node in Cooc_Avg:
+                FinalDict[node] = Cooc_Avg[node]/G.degree(node)
+        # Getting AVG-COOC of each ngram that exists in the cooc-matrix of the compared-corpus. 
+
+    return JsonHttpResponse(FinalDict)
+
+
+def getUserPortfolio(request , project_id):
+    user = request.user
+    user_id         = cache.User[request.user.username].id
+    project_type_id = cache.NodeType['Project'].id
+    corpus_type_id = cache.NodeType['Corpus'].id
+
+    results = {}
+    projs = session.query(Node).filter(Node.user_id == user_id,Node.type_id==project_type_id ).all()
+    for i in projs:
+        # print (i.id,i.name)
+        if i.id not in results: 
+            results[i.id] = {}
+        results[i.id]["proj_name"] = i.name
+        results[i.id]["corpuses"] = []
+        corpuses = session.query(Node).filter(Node.parent_id==i.id , Node.type_id==corpus_type_id).all()
+        for j in corpuses:
+            doc_count = session.query(func.count(Node.id)).filter(Node.parent_id==j.id).all()[0][0]
+            if doc_count >= 10:
+                # print(session.query(Node).filter(Node.id==j.id).first())
+                info = { 
+                    "id":j.id , 
+                    "name":j.name ,
+                    "c":doc_count
+                }
+                results[i.id]["corpuses"].append(info)
+                # print("\t\t",j.id , j.name , doc_count)
+
+        if len(results[i.id]["corpuses"])==0:
+            del results[i.id]
+
+    return JsonHttpResponse( results )

parsing/FileParsers/EuropressFileParser.py

@@ -5,6 +5,7 @@ from lxml.html import html5parser
 from datetime import datetime, date
 from django.utils import timezone
 import dateutil.parser
+import dateparser
 
 from .FileParser import FileParser
 from ..NgramsExtractors import *
@@ -140,7 +141,10 @@ class EuropressFileParser(FileParser):
 
                         if format_europresse == 50.2:
                             # TODO here check the split if needed: 'Brest Ville, mercredi 26 novembre 2014'
+                            try:# # 2015-oct-08 exception added
                                 text = text.split(', ')[1] 
+                            except:
+                                pass
 
                         format_date_fr = re.compile('\d*\s*\w+\s+\d{4}', re.UNICODE)
                         format_date_fr_v2 = re.compile('\s*\w+\s+\d+\s+\w+\s+\d{4}', re.UNICODE)
@@ -166,12 +170,15 @@ class EuropressFileParser(FileParser):
 
                         if test_date_fr is not None or test_date_fr_v2 is not None:
                             self.localeEncoding = "fr_FR"
-                            locale.setlocale(locale.LC_ALL, localeEncoding)
+                            locale.setlocale(locale.LC_ALL, "fr_FR.utf-8")
                             if encoding != "utf-8":
                                 text = text.replace('י', 'é')
                                 text = text.replace('ű', 'û')
                                 text = text.replace(' aot ', ' août ')
 
+                            try:
+                                hyperdata['publication_date'] = dateparser.parse(text, languages=['fr'])
+                            except:
                                 try :
                                     hyperdata['publication_date'] = datetime.strptime(text, '%d %B %Y')
                                 except :
@@ -278,10 +285,10 @@ class EuropressFileParser(FileParser):
                     else:
                         hyperdata['doi'] = "not found"
 
-                    try:
-                        hyperdata['length_words'] = len(hyperdata['abstract'].split(' '))
-                    except:
-                        PrintException()
+                    # try:
+                    #     hyperdata['length_words'] = len(hyperdata['abstract'].split(' '))
+                    # except:
+                    #     PrintException()
 
                     hyperdata['length_letters'] = len(hyperdata['abstract'])