.

app.py

@@ -24,8 +24,9 @@ def req_4(data):
            plot_avid_readers(globals()[f"data_{data}"])
 
 
-def req_5(doc, vis, sort, data):
-    return also_like(globals()[f"data_{data}"], doc, vis, sort == "Ascending")
+def req_5_and_6(doc, vis, sort, data):
+    return also_like(globals()[f"data_{data}"], doc, vis, sort == "Ascending"), \
+           also_like_graph(globals()[f"data_{data}"], doc, vis, sort == "Ascending")
 
 
 with gr.Blocks(css="""
@@ -124,13 +125,13 @@ with gr.Blocks(css="""
             also_likes_df = gr.Dataframe(value=also_like(globals()[f"data_{selected_dataset_5.value}"], t5_doc_uuid.value, t5_visitor_uuid.value,
                                                          t5_sorting.value == 'Ascending'))
 
-        req_5_submit.click(fn=req_5, inputs=[t5_doc_uuid, t5_visitor_uuid, t5_sorting, selected_dataset_5], outputs=[also_likes_df])
-
     gr.Markdown("""
         ## Requirement 6: "Also likes" graph
         
         For the above “also like” functionality, this section generates a graph that displays the relationship between the input document and all documents that have been found as “also like” documents (and only these documents)
         """)
-    gr.Image('output.png')
+    also_likes_graph = gr.Image('output.png')
+
+    req_5_submit.click(fn=req_5_and_6, inputs=[t5_doc_uuid, t5_visitor_uuid, t5_sorting, selected_dataset_5], outputs=[also_likes_df, also_likes_graph])
 
 demo.launch()

cw2.py

@@ -127,6 +127,7 @@ def also_like_graph(data, doc_uuid, visitor_uuid, ascending):
         top_docs = also_like(data, doc_uuid, visitor_uuid, ascending, req_5=False)
         y = top_docs[1].value_counts()
         y = pd.DataFrame(y)
+        y.loc[len(y.index)] = [visitor_uuid, doc_uuid]
         print(y)
         dot = graphviz.Digraph()
         for index, row in top_docs.iterrows():
@@ -144,7 +145,7 @@ def also_like_graph(data, doc_uuid, visitor_uuid, ascending):
         graph.write_png('output.png')
         return 'output.png'
     except:
-        return "test.jpg"
+        return "output_test.jpg"
 
 
 # print(also_like(data_tiny, "100713205147-2ee05a98f1794324952eea5ca678c026", "b5d13a36dad1147b", False).groupby(1).count().nlargest(10, [0]))