Automatisierung des cami aufrufs

cami/cami_suite.py

@@ -204,7 +204,7 @@ class cami():
             outputfile.write(f'gene\tpredicted_by\tcami_score\tindex_in_graph\tdegree_in_graph\n')
             all_vertices = cami_vertices.union(putative_vertices)
             for vertex in all_vertices:
-                outputfile.write(f'{name[vertex]}\t{codes2tools[vertex]}\t{cami_scores[vertex]}\t{str(vertex)}\tvertex.out_degree\n')
+                outputfile.write(f'{name[vertex]}\t{codes2tools[vertex]}\t{cami_scores[vertex]}\t{str(vertex)}\t{vertex.out_degree()}\n')
         print(f'saved all predictions by the used tools in: {self.output_dir}/all_predictions_{self.uid}.tsv')
 
         # save the predictions made by cami
@@ -228,7 +228,10 @@ class cami():
         # visualize with degradome
         if self.nof_tools < 7:
             print('Visualizing results using Degradome...')
-            url = degradome.send_request(self.result_gene_sets)
+            degradome_sets = {tool:self.result_gene_sets[tool] 
+                              for tool in self.result_gene_sets 
+                                if len(self.result_gene_sets[tool])>0}
+            url = degradome.send_request(degradome_sets)
             return url
            # TODO: save the venn diagram images in an outputfolder
            # TODO: Include seeds?

cami/degradome.py

@@ -18,7 +18,7 @@ def send_request(sets=dict()):
               'header': 'rawData'
              }
     print(f'Sending result sets to {url} to create Venn diagrams...')
-    r = requests.post(url, data=values, timeout=None)
+    r = requests.post(url, data=values, timeout=30)
     if r.ok:
         match = re.search(r'(<a href=\\")(http:\/\/degradome.*)(\\">)', r.text)
         if match: