Update app.py

app.py

@@ -390,246 +390,245 @@ else:
     
 if currFile is None and len(st.session_state.results) > 0 and len(st.session_state.results[0]) > 0:
     st.write("Select a file to view from the sidebar")
-else:
-    try:
-        st.session_state.resetResult = False
-        currFileIndex = file_names.index(currFile)
-
-        if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
 
-            # Handle 
-            currSpeakerList, currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
-            speakerNames = currAnnotation.labels()
-    
-            # Update other categories
-            unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
-            categorySelections = st.session_state["categorySelect"][currFileIndex]
-            for i,category in enumerate(st.session_state.categories):
-                speakerSet = categorySelections[i]
-                st.sidebar.multiselect(category,
-                                        speakerSet+unusedSpeakers,
-                                        default=speakerSet,
-                                        key=f"multiselect_{category}",
-                                        on_change=updateCategoryOptions,
-                                        args=(currFileIndex,))
-                st.sidebar.button(f"Remove {category}",key=f"remove_{category}",on_click=removeCategory,args=(i,))
-
-    
-           
-            newCategory = st.sidebar.text_input('Add category', key='categoryInput',on_change=addCategory)   
-    
-            df4_dict = {}
-            nameList = st.session_state.categories
-            extraNames = []
-            valueList = [0 for i in range(len(nameList))]
-            extraValues = []
-    
-            for i,speakerSet in enumerate(categorySelections):
-                valueList[i] += su.sumTimes(currAnnotation.subset(speakerSet))
-            
-            for sp in unusedSpeakers:
-                extraNames.append(sp)
-                extraValues.append(su.sumTimes(currAnnotation.subset([sp])))
+    st.session_state.resetResult = False
+    currFileIndex = file_names.index(currFile)
+
+    if len(st.session_state.results) > currFileIndex and len(st.session_state.summaries) > currFileIndex and len(st.session_state.results[currFileIndex]) > 0:
+
+        # Handle 
+        currSpeakerList, currAnnotation, currTotalTime = st.session_state.results[currFileIndex]
+        speakerNames = currAnnotation.labels()
+
+        # Update other categories
+        unusedSpeakers = st.session_state.unusedSpeakers[currFileIndex]
+        categorySelections = st.session_state["categorySelect"][currFileIndex]
+        for i,category in enumerate(st.session_state.categories):
+            speakerSet = categorySelections[i]
+            st.sidebar.multiselect(category,
+                                    speakerSet+unusedSpeakers,
+                                    default=speakerSet,
+                                    key=f"multiselect_{category}",
+                                    on_change=updateCategoryOptions,
+                                    args=(currFileIndex,))
+            st.sidebar.button(f"Remove {category}",key=f"remove_{category}",on_click=removeCategory,args=(i,))
+
+
+       
+        newCategory = st.sidebar.text_input('Add category', key='categoryInput',on_change=addCategory)   
+
+        df4_dict = {}
+        nameList = st.session_state.categories
+        extraNames = []
+        valueList = [0 for i in range(len(nameList))]
+        extraValues = []
+
+        for i,speakerSet in enumerate(categorySelections):
+            valueList[i] += su.sumTimes(currAnnotation.subset(speakerSet))
+        
+        for sp in unusedSpeakers:
+            extraNames.append(sp)
+            extraValues.append(su.sumTimes(currAnnotation.subset([sp])))
 
-            
-            df4_dict = {
-                    "names": nameList+extraNames,
-                    "values": valueList+extraValues,
-                }
-            df4 = pd.DataFrame(data=df4_dict)
-            df4.name = "df4"
-            st.session_state.summaries[currFileIndex]["df4"] = df4
-            st.info(st.session_state.summaries)
-            df2 = st.session_state.summaries[currFileIndex]["df2"]
-            df3 = st.session_state.summaries[currFileIndex]["df3"]
-            df4 = st.session_state.summaries[currFileIndex]["df4"]
-            df5 = st.session_state.summaries[currFileIndex]["df5"]
-            speakers_dataFrame = st.session_state.summaries[currFileIndex]["speakers_dataFrame"]
-            currDF = speakers_dataFrame
-            speakers_times = st.session_state.summaries[currFileIndex]["speakers_times"]
-           
-            # generate plotting window
-            fig1 = go.Figure()
-            fig1.add_trace(go.Pie(values=df3["values"],labels=df3["names"]))
-            fig2 = go.Figure()
-            fig2.add_trace(go.Pie(values=df4["values"],labels=df4["names"]))
-            fig3_1 = px.sunburst(df5,
-                                branchvalues = 'total',
-                                names = "labels",
-                                ids = "ids",
-                                parents = "parents",
-                                values = "percentiles",
-                                custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
-                                color = 'labels',
-                                )
-            fig3_1.update_traces(
-                hovertemplate="<br>".join([
-                    '<b>%{customdata[0]}</b>',
-                    'Duration: %{customdata[1]}s',
-                    'Percentage of Total: %{customdata[2]:.2f}%',
-                    'Parent: %{customdata[3]}',
-                    'Percentage of Parent: %{customdata[4]:.2f}%'
-                ])
-            )
-            fig3 = px.treemap(df5,
-                            branchvalues = "total",
+        
+        df4_dict = {
+                "names": nameList+extraNames,
+                "values": valueList+extraValues,
+            }
+        df4 = pd.DataFrame(data=df4_dict)
+        df4.name = "df4"
+        st.session_state.summaries[currFileIndex]["df4"] = df4
+        st.info(st.session_state.summaries)
+        df2 = st.session_state.summaries[currFileIndex]["df2"]
+        df3 = st.session_state.summaries[currFileIndex]["df3"]
+        df4 = st.session_state.summaries[currFileIndex]["df4"]
+        df5 = st.session_state.summaries[currFileIndex]["df5"]
+        speakers_dataFrame = st.session_state.summaries[currFileIndex]["speakers_dataFrame"]
+        currDF = speakers_dataFrame
+        speakers_times = st.session_state.summaries[currFileIndex]["speakers_times"]
+       
+        # generate plotting window
+        fig1 = go.Figure()
+        fig1.add_trace(go.Pie(values=df3["values"],labels=df3["names"]))
+        fig2 = go.Figure()
+        fig2.add_trace(go.Pie(values=df4["values"],labels=df4["names"]))
+        fig3_1 = px.sunburst(df5,
+                            branchvalues = 'total',
                             names = "labels",
+                            ids = "ids",
                             parents = "parents",
-                            ids="ids",
                             values = "percentiles",
                             custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
-                            color='labels',
+                            color = 'labels',
                             )
-            fig3.update_traces(
-                hovertemplate="<br>".join([
-                    '<b>%{customdata[0]}</b>',
-                    'Duration: %{customdata[1]}s',
-                    'Percentage of Total: %{customdata[2]:.2f}%',
-                    'Parent: %{customdata[3]}',
-                    'Percentage of Parent: %{customdata[4]:.2f}%'
-                ])
-            )
-            st.plotly_chart(fig1, use_container_width=True)
-            st.plotly_chart(fig2, use_container_width=True)
-            st.plotly_chart(fig3_1, use_container_width=True)
-            st.plotly_chart(fig3, use_container_width=True)
-
-    
-            fig_la = px.timeline(speakers_dataFrame, x_start="Start", x_end="Finish", y="Resource", color="Resource")
-            fig_la.update_yaxes(autorange="reversed") 
-            
-            hMax = int(currTotalTime//3600)
-            mMax = int(currTotalTime%3600//60)
-            sMax = int(currTotalTime%60)
-            msMax = int(currTotalTime*1000000%1000000)
-            timeMax = dt.time(hMax,mMax,sMax,msMax)
-                    
-            fig_la.update_layout(
-                xaxis_tickformatstops = [
-                    dict(dtickrange=[None, 1000], value="%H:%M:%S.%L"),
-                    dict(dtickrange=[1000, None], value="%H:%M:%S")
-                ],
-                xaxis=dict(
-                        range=[dt.datetime.combine(dt.date.today(), dt.time.min),dt.datetime.combine(dt.date.today(), timeMax)]
-                    ),
-                xaxis_title="Time",
-                yaxis_title="Speaker",
-                legend_title=None
-            )
+        fig3_1.update_traces(
+            hovertemplate="<br>".join([
+                '<b>%{customdata[0]}</b>',
+                'Duration: %{customdata[1]}s',
+                'Percentage of Total: %{customdata[2]:.2f}%',
+                'Parent: %{customdata[3]}',
+                'Percentage of Parent: %{customdata[4]:.2f}%'
+            ])
+        )
+        fig3 = px.treemap(df5,
+                        branchvalues = "total",
+                        names = "labels",
+                        parents = "parents",
+                        ids="ids",
+                        values = "percentiles",
+                        custom_data=['labels','valueStrings','percentiles','parentNames','parentPercentiles'],
+                        color='labels',
+                        )
+        fig3.update_traces(
+            hovertemplate="<br>".join([
+                '<b>%{customdata[0]}</b>',
+                'Duration: %{customdata[1]}s',
+                'Percentage of Total: %{customdata[2]:.2f}%',
+                'Parent: %{customdata[3]}',
+                'Percentage of Parent: %{customdata[4]:.2f}%'
+            ])
+        )
+        st.plotly_chart(fig1, use_container_width=True)
+        st.plotly_chart(fig2, use_container_width=True)
+        st.plotly_chart(fig3_1, use_container_width=True)
+        st.plotly_chart(fig3, use_container_width=True)
+
+
+        fig_la = px.timeline(speakers_dataFrame, x_start="Start", x_end="Finish", y="Resource", color="Resource")
+        fig_la.update_yaxes(autorange="reversed") 
+        
+        hMax = int(currTotalTime//3600)
+        mMax = int(currTotalTime%3600//60)
+        sMax = int(currTotalTime%60)
+        msMax = int(currTotalTime*1000000%1000000)
+        timeMax = dt.time(hMax,mMax,sMax,msMax)
+                
+        fig_la.update_layout(
+            xaxis_tickformatstops = [
+                dict(dtickrange=[None, 1000], value="%H:%M:%S.%L"),
+                dict(dtickrange=[1000, None], value="%H:%M:%S")
+            ],
+            xaxis=dict(
+                    range=[dt.datetime.combine(dt.date.today(), dt.time.min),dt.datetime.combine(dt.date.today(), timeMax)]
+                ),
+            xaxis_title="Time",
+            yaxis_title="Speaker",
+            legend_title=None
+        )
+        
+        st.plotly_chart(fig_la, use_container_width=True)
+        
+        fig2_la = px.bar(df2, x="values", y="names", color="names", orientation='h',
+                        custom_data=["names","values"])
+        fig2_la.update_xaxes(ticksuffix="%")
+        fig2_la.update_yaxes(autorange="reversed") 
+        fig2_la.update_layout(
+            xaxis_title="Percentage Time Spoken",
+            yaxis_title="Speaker",
+            legend_title=None
             
-            st.plotly_chart(fig_la, use_container_width=True)
+        )
+        fig2_la.update_traces(
+            hovertemplate="<br>".join([
+                '<b>%{customdata[0]}</b>',
+                'Percentage of Time: %{customdata[1]:.2f}%'
+            ])
+        )
+        st.plotly_chart(fig2_la, use_container_width=True)
+
+except ValueError:
+    pass
+
+if len(st.session_state.results) > 0:
+    with st.spinner(text='Processing summary results...'):
+        fileNames = st.session_state.file_names
+        results = []
+        indices = []
+        for i, resultTuple in enumerate(st.session_state.results):
+            if len(resultTuple) == 2:
+                fileNames.append(resultTuple[0])
+                results.append(resultTuple[1])
+                indices.append(i)
+        st.info(f'filenames : {fileNames}')
+        st.info(f'indices : {indices}')
+        st.info(f'results : {results}')
+        if len(indices) > 1:
             
-            fig2_la = px.bar(df2, x="values", y="names", color="names", orientation='h',
-                            custom_data=["names","values"])
-            fig2_la.update_xaxes(ticksuffix="%")
-            fig2_la.update_yaxes(autorange="reversed") 
-            fig2_la.update_layout(
-                xaxis_title="Percentage Time Spoken",
-                yaxis_title="Speaker",
-                legend_title=None
-                
-            )
-            fig2_la.update_traces(
-                hovertemplate="<br>".join([
-                    '<b>%{customdata[0]}</b>',
-                    'Percentage of Time: %{customdata[1]:.2f}%'
-                ])
-            )
-            st.plotly_chart(fig2_la, use_container_width=True)
-
-    except ValueError:
-        pass
-    
-    if len(st.session_state.results) > 0:
-        with st.spinner(text='Processing summary results...'):
-            fileNames = st.session_state.file_names
-            results = []
-            indices = []
-            for i, resultTuple in enumerate(st.session_state.results):
-                if len(resultTuple) == 2:
-                    fileNames.append(resultTuple[0])
-                    results.append(resultTuple[1])
-                    indices.append(i)
-            st.info(f'filenames : {fileNames}')
-            st.info(f'indices : {indices}')
-            st.info(f'results : {results}')
-            if len(indices) > 1:
-                
-                df6_dict = {
-                    "files":fileNames,
-                }
-                allCategories = copy.deepcopy(st.session_state.categories)
-                for i in indices:
-                    currSpeakerList, currAnnotation, currTotalTime = st.session_state.results[i]
-                    categorySelections = st.session_state["categorySelect"][i]
-                    catSummary,extraCats = su.calcCategories(currAnnotation,categorySelections)
-                    st.session_state.summaries[i]["categories"] = (catSummary,extraCats)
-                    for extra in extraCats:
-                        df6_dict[extra] = []
-                        if extra not in allCategories:
-                            allCategories.append(extra)
+            df6_dict = {
+                "files":fileNames,
+            }
+            allCategories = copy.deepcopy(st.session_state.categories)
+            for i in indices:
+                currSpeakerList, currAnnotation, currTotalTime = st.session_state.results[i]
+                categorySelections = st.session_state["categorySelect"][i]
+                catSummary,extraCats = su.calcCategories(currAnnotation,categorySelections)
+                st.session_state.summaries[i]["categories"] = (catSummary,extraCats)
+                for extra in extraCats:
+                    df6_dict[extra] = []
+                    if extra not in allCategories:
+                        allCategories.append(extra)
 
-            
-                for category in st.session_state.categories:
-                    df6_dict[category] = []
-                for i in indices:
-                    summary, extras = st.session_state.summaries[i]["categories"]
-                    theseCategories = st.session_state.categories + extras
-                    for j, timeSlots in enumerate(summary):
-                        df6_dict[theseCategories[j]].append(sum([t.duration for _,t in timeSlots])/st.session_state.results[i][2])
-                    for category in allCategories:
-                        if category not in theseCategories:
-                            df6_dict[category].append(0)
-                df6 = pd.DataFrame(df6_dict)
-                summFig = px.bar(df6, x="files", y=allCategories)
-                st.plotly_chart(summFig, use_container_width=True)
+        
+            for category in st.session_state.categories:
+                df6_dict[category] = []
+            for i in indices:
+                summary, extras = st.session_state.summaries[i]["categories"]
+                theseCategories = st.session_state.categories + extras
+                for j, timeSlots in enumerate(summary):
+                    df6_dict[theseCategories[j]].append(sum([t.duration for _,t in timeSlots])/st.session_state.results[i][2])
+                for category in allCategories:
+                    if category not in theseCategories:
+                        df6_dict[category].append(0)
+            df6 = pd.DataFrame(df6_dict)
+            summFig = px.bar(df6, x="files", y=allCategories)
+            st.plotly_chart(summFig, use_container_width=True)
 
-            
-                voiceNames = ["No Voice","One Voice","Multi Voice"]
-                df7_dict = {
-                    "files":fileNames,
-                }
-                for category in voiceNames:
-                    df7_dict[category] = []
-                for resultID,summary in enumerate(st.session_state.summaries):
-                    partialDf = summary["df5"]
-                    for i in range(len(voiceNames)):
-                        df7_dict[voiceNames[i]].append(partialDf["percentiles"][i])
-                df7 = pd.DataFrame(df7_dict)
-                sorted_df7 = df7.sort_values(by=['One Voice', 'Multi Voice'])
-                summFig2 = px.bar(sorted_df7, x="files", y=["One Voice","Multi Voice","No Voice",])
-                st.plotly_chart(summFig2, use_container_width=True)
-                sorted_df7_3 = df7.sort_values(by=['Multi Voice','One Voice'])
-                summFig3 = px.bar(sorted_df7_3, x="files", y=["One Voice","Multi Voice","No Voice",])
-                st.plotly_chart(summFig3, use_container_width=True)
-                sorted_df7_4 = df7.sort_values(by=['No Voice', 'Multi Voice'],ascending=False)
-                summFig4 = px.bar(sorted_df7_4, x="files", y=["One Voice","Multi Voice","No Voice",])
-                st.plotly_chart(summFig4, use_container_width=True)
-    
-    
-    
-    old = '''userid = st.text_input("user id:", "Guest")
-    colorPref = st.text_input("Favorite color?", "None")
-    radio = st.radio('Pick one:', ['Left','Right'])
-    selection = st.selectbox('Select', [1,2,3])
-    if st.button("Upload Files to Dataset"):
-        save_data({"color":colorPref,"direction":radio,"number":selection},
-                 file_paths,
-                 userid)
-        st.success('I think it worked!')
-    '''
-    @st.cache_data
-    def convert_df(df):
-       return df.to_csv(index=False).encode('utf-8')
-    
-    
-    if currDF is not None:
-        csv = convert_df(currDF)
         
-        st.download_button(
-           "Press to Download analysis data",
-           csv,
-           "file.csv",
-           "text/csv",
-           key='download-csv'
-        )
+            voiceNames = ["No Voice","One Voice","Multi Voice"]
+            df7_dict = {
+                "files":fileNames,
+            }
+            for category in voiceNames:
+                df7_dict[category] = []
+            for resultID,summary in enumerate(st.session_state.summaries):
+                partialDf = summary["df5"]
+                for i in range(len(voiceNames)):
+                    df7_dict[voiceNames[i]].append(partialDf["percentiles"][i])
+            df7 = pd.DataFrame(df7_dict)
+            sorted_df7 = df7.sort_values(by=['One Voice', 'Multi Voice'])
+            summFig2 = px.bar(sorted_df7, x="files", y=["One Voice","Multi Voice","No Voice",])
+            st.plotly_chart(summFig2, use_container_width=True)
+            sorted_df7_3 = df7.sort_values(by=['Multi Voice','One Voice'])
+            summFig3 = px.bar(sorted_df7_3, x="files", y=["One Voice","Multi Voice","No Voice",])
+            st.plotly_chart(summFig3, use_container_width=True)
+            sorted_df7_4 = df7.sort_values(by=['No Voice', 'Multi Voice'],ascending=False)
+            summFig4 = px.bar(sorted_df7_4, x="files", y=["One Voice","Multi Voice","No Voice",])
+            st.plotly_chart(summFig4, use_container_width=True)
+
+
+
+old = '''userid = st.text_input("user id:", "Guest")
+colorPref = st.text_input("Favorite color?", "None")
+radio = st.radio('Pick one:', ['Left','Right'])
+selection = st.selectbox('Select', [1,2,3])
+if st.button("Upload Files to Dataset"):
+    save_data({"color":colorPref,"direction":radio,"number":selection},
+             file_paths,
+             userid)
+    st.success('I think it worked!')
+'''
+@st.cache_data
+def convert_df(df):
+   return df.to_csv(index=False).encode('utf-8')
+
+
+if currDF is not None:
+    csv = convert_df(currDF)
+    
+    st.download_button(
+       "Press to Download analysis data",
+       csv,
+       "file.csv",
+       "text/csv",
+       key='download-csv'
+    )