fix display

streamlit_app_LDA.py

@@ -21,8 +21,10 @@ num_topics = st.sidebar.slider("Number of Topics", min_value=2, max_value=20, va
 num_passes = st.sidebar.slider("Number of Passes", min_value=5, max_value=50, value=10)
 lda_document_is = st.radio("A 'Document' in the topic model will correspond to a:", ("self-state", "segment"))
 seed_value = st.sidebar.number_input("Random Seed", value=42)
-num_top_elements_to_show = st.sidebar.slider("# top element to show in a topic", min_value=2, max_value=15, value=5)
 
+st.sidebar.header("Display")
+num_top_elements_to_show = st.sidebar.slider("# top element to show in a topic", min_value=2, max_value=15, value=5)
+show_long_elements = st.checkbox("Show full element name")
 # ---------------------------
 # Load Data
 # ---------------------------
@@ -138,8 +140,11 @@ st.text(output_str)
 # Prepare and Display pyLDAvis Visualization
 # ---------------------------
 st.header("Interactive Topic Visualization")
-# vis_dict = {i: element_short_desc_map[v] for i, v in dictionary.items()}
-# vis_dictionary = corpora.dictionary.Dictionary([[new_token] for new_token in vis_dict.values()])
-vis_data = gensimvis.prepare(lda_model, corpus, dictionary)
+if not show_long_elements:
+    vis_dict = {i: element_short_desc_map[v] for i, v in dictionary.items()}
+    vis_dictionary = corpora.dictionary.Dictionary([[new_token] for new_token in vis_dict.values()])
+    vis_data = gensimvis.prepare(lda_model, corpus, vis_dictionary)
+else:
+    vis_data = gensimvis.prepare(lda_model, corpus, dictionary)
 html_string = pyLDAvis.prepared_data_to_html(vis_data)
-components.html(html_string, width=1300, height=800)
+components.html(html_string, width=2300, height=800, scrolling=True)