Update app.py

app.py

@@ -127,7 +127,7 @@ def file(input_file, input_checks):
     else:
         return gr.update(value=output, visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)  # no next_button becomes available
 
-def freq(output_file, input_checks):
+def freq2(output_file, input_checks):
     #preds_dict = {"neutral": 10, "anger": 8, "fear": 2, "joy": 15, "love": 3, "sadness": 4}
     #bars = list(preds_dict.keys())
     #height = list(preds_dict.values())
@@ -150,6 +150,33 @@ def freq(output_file, input_checks):
     else:
         return gr.update(simple,x="Emotion categories",y="Frequencies",title="Emotion frequencies",tooltip=['Emotion category', 'Frequency'],y_lim=[20, 100], visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)  # no next_button becomes available
 
+def freq(output_file, input_checks):
+    simple = pd.DataFrame({
+    'Emotion category': ['neutral', 'anger', 'fear', 'joy', 'love', 'sadness'],
+    'Frequency': [10, 8, 2, 15, 3, 4]})
+
+    domain = ['neutral', 'anger', 'fear', 'joy', 'love', 'sadness']
+    range_ = ['#999999', '#b22222', '#663399', '#ffcc00', '#db7093', '#6495ed']
+    n = max(simple['Frequency'])
+
+    plot = alt.Chart(simple, title="Emotion frequencies").mark_bar().encode(
+    x=alt.X("Emotion category", sort=['neutral', 'anger', 'fear', 'joy', 'love', 'sadness']),
+    y=alt.Y("Frequency", axis=alt.Axis(grid=False), scale=alt.Scale(domain=[0, (n + 9) // 10 * 10])),
+    color=alt.Color("Emotion category", scale=alt.Scale(domain=domain, range=range_), legend=None),
+    tooltip=['Emotion category', 'Frequency']).properties(
+    width=300).configure_axis(
+    grid=False).interactive()
+
+    if "emotion distribution over time" in input_checks:
+        return gr.update(value=plot, visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)  # next_button_dist becomes available
+    elif "peaks" in input_checks:
+        return gr.update(value=plot, visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)  # next_button_peaks becomes available
+    elif "topics" in input_checks:
+        return gr.update(value=plot, visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)  # next_button_topics becomes available
+    else:
+        return gr.update(value=plot, visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)  # no next_button becomes available
+
+
 def dist(output_file, input_checks):
     dataframe = pd.DataFrame({'date_of_week': np.array([datetime.datetime(2021, 11, i+1) for i in range(7)]),'classes': [5, 6, 8, 2, 3, 7, 4]})
     # Plotting the time series of given dataframe
@@ -214,7 +241,7 @@ with gr.Blocks() as demo:
                 output_file = gr.File(label="Predictions", visible=False)
                 next_button_freq = gr.Button("Show emotion frequencies", visible=False)
                 
-                output_plot = gr.BarPlot(label="Emotion frequencies", visible=False).style(container=True)
+                output_plot = gr.Plot(show_label=False, visible=False).style(container=True)
                 next_button_dist = gr.Button("Show emotion distribution over time", visible=False)
                 
                 output_dist = gr.Plot(label="Emotion distribution over time", visible=False)