Update app.py

app.py

@@ -6,6 +6,7 @@ import pandas as pd
 from tqdm import tqdm
 
 import matplotlib.pyplot as plt
+import datetime
 
 from transformers import AutoTokenizer, AutoConfig, AutoModel, AutoModelForSequenceClassification
 
@@ -110,45 +111,6 @@ def inference_sentence(text):
     output = "This sentence will be processed:\n" + text
     return output
 
-"""
-def inference_dataset1(input_file):
-    output = "output.txt"
-    f = open(output, 'w')
-    f.write("The predictions come here.")
-    f.close()
-    return gr.update(value=output, visible=True), gr.update(visible=True)
-
-def inference_dataset2(input_file, input_checks):
-    if "emotion frequencies" in input_checks:
-        preds_dict = {"neutral": 10, "anger": 15, "fear": 2, "joy": 30, "love": 5, "sadness": 8}
-        bars = list(preds_dict.keys())
-        height = list(preds_dict.values())
-        x_pos = np.arange(len(bars))
-        plt.bar(x_pos, height, color=['lightgrey', 'firebrick', 'rebeccapurple', 'orange', 'palevioletred', 'cornflowerblue'])
-        plt.xticks(x_pos, bars)
-        return gr.update(value=plt, visible=True)
-    else:
-        return None
-
-def inference_dataset3(input_file, input_checks):
-    if "emotion distribution over time" in input_checks:
-        return gr.update(value="This option was selected.", visible=True)
-    else:
-        return gr.update(value="This option was not selected.")
-
-def inference_dataset4(input_file, input_checks):
-    if "peaks" in input_checks:
-        return gr.update(value="This option was selected.", visible=True)
-    else:
-        return gr.update(value="This option was not selected.")
-
-def inference_dataset5(input_file, input_checks):
-    if "topics" in input_checks:
-        return gr.update(value="This option was selected.", visible=True)
-    else:
-        return gr.update(value="This option was not selected.")
-"""
-
 def file(input_file, input_checks):
     output = "output.txt"
     f = open(output, 'w')
@@ -182,6 +144,27 @@ def freq(output_file, input_checks):
     else:
         return gr.update(value=plt, visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)  # next_button_freq 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
+    plt.plot(dataframe.date_of_week, dataframe.classes)
+    
+    # Giving title to the chart using plt.title
+    plt.title('Emotions over time')
+    
+    # rotating the x-axis tick labels at 30degree
+    # towards right
+    plt.xticks(rotation=30, ha='right')
+    
+    # Providing x and y label to the chart
+    plt.xlabel('Date')
+    plt.ylabel('Number of emotions')
+    if "peaks" in input_checks:
+        return gr.update(value=plt, visible=True), gr.update(visible=True), gr.update(visible=False)  # next_button_peaks becomes available
+    elif "topics" in input_checks:
+        return gr.update(value=plt, visible=True), gr.update(visible=False), gr.update(visible=True)  # next_button_peaks becomes available
+    else:
+        return gr.update(value=plt, visible=True), gr.update(visible=False), gr.update(visible=False)  # next_button_freq becomes available
 
 with gr.Blocks() as demo:
     with gr.Tab("Sentence"):
@@ -212,39 +195,23 @@ with gr.Blocks() as demo:
                 send_btn = gr.Button("Send")
             with gr.Column():
                 output_file = gr.File(label="Predictions", visible=False)
-                next_button_freq = gr.Button("Next_button freq", visible=False)
+                next_button_freq = gr.Button("Show emotion frequencies", visible=False)
                 
                 output_plot = gr.Plot(label="Emotion frequencies", visible=False)
-                next_button_dist = gr.Button("Next_button dist", visible=False)
+                next_button_dist = gr.Button("Show emotion distribution over time", visible=False)
                 
-                output_dist = gr.Textbox(label="Emotion distribution over time", visible=False)
-                next_button_peaks = gr.Button("Next_button peaks", visible=False)
+                output_dist = gr.Plot(label="Emotion distribution over time", visible=False)
+                next_button_peaks = gr.Button("Show peaks", visible=False)
                 
                 output_peaks = gr.Textbox(label="Peaks", visible=False)
-                next_button_topics = gr.Button("Next_button topics", visible=False)
+                next_button_topics = gr.Button("Show topics", visible=False)
                 
                 output_topics = gr.Textbox(label="Topics", visible=False)
         
-        #send_btn.click(fn=inference_dataset1, inputs=input_file, outputs=[output_file,next_button_freq]) # next_button_freq becomes visible
         send_btn.click(fn=file, inputs=[input_file,input_checks], outputs=[output_file,next_button_freq,next_button_dist,next_button_peaks,next_button_topics])
         next_button_freq.click(fn=freq, inputs=[output_file,input_checks], outputs=[output_plot,next_button_dist,next_button_peaks,next_button_topics])
+        next_button_dist.click(fn=dist, inputs=[output_file,input_checks], outputs=[output_plot,next_button_peaks,next_button_topics])
 
-        """"
-        if "emotion frequencies" in input_checks:
-            next_button_freq.click(fn=freq_freq, inputs=[output_file,input_checks], outputs=[output_plot,next_button_dist]) # next_button_dist becomes visible
-        else:
-            if "emotion distribution over time" in input_checks:
-                next_button_freq.click(fn=freq_dist, inputs=[output_file,input_checks], outputs=[output_dist,next_peaks]) # nex_button_peaks becomes visible
-            else:
-                if "peaks" in input_checks:
-                    next_button_freq.click(fn=freq_peaks, inputs=[output_file,input_checks], outputs=[output_,next_peaks]) # nex_button_peaks becomes visible
-        """
-
-
-        #output_file.change(fn=inference_dataset2, inputs=[input_file,input_checks], outputs=output_plot).then(fn=inference_dataset3, inputs=[input_file,input_checks], outputs=output_dist)
-        #output_plot.change(fn=inference_dataset3, inputs=[input_file,input_checks], outputs=output_dist)
-        #output_dist.change(fn=inference_dataset4, inputs=[input_file,input_checks], outputs=output_peaks)
-        #output_peaks.change(fn=inference_dataset5, inputs=[input_file,input_checks], outputs=output_topics)
         
 demo.launch()