plots

app.py

@@ -198,14 +198,31 @@ from vega_datasets import data
 iris = data.iris()
 
 
-def scatter_plot_fn(request: gr.Request):
+def scatter_plot_fn_energy(request: gr.Request):
+    
     token = request.request.session.get('token')
     if token:
         sp = spotipy.Spotify(token)
         results = sp.current_user()
         print(results)
+    df = get_features(sp)
     return gr.ScatterPlot(
-        value=iris,
+        value=df,
+        x="danceability",
+        y="energy"
+    )
+
+def scatter_plot_fn_liveness(request: gr.Request):
+    token = request.request.session.get('token')
+    if token:
+        sp = spotipy.Spotify(token)
+        results = sp.current_user()
+        print(results)
+    df = get_features(sp)
+    return gr.ScatterPlot(
+        value=df,
+        x="acousticness",
+        y="liveness"
     )
 
 def heatmap_plot_fn(request: gr.Request):
@@ -213,7 +230,7 @@ def heatmap_plot_fn(request: gr.Request):
     if token:
         sp = spotipy.Spotify(token)
         data = heatmap.build_heatmap(heatmap.fetch_recent_songs(sp))
-        fig, _ = heatmap.plot(data)
+        fig, ax = heatmap.plot(data)
         return fig
 
 
@@ -236,9 +253,9 @@ def get_features(spotify):
         'valence',
         'tempo',
     ]
-    features_means = df[names].mean()
+    
     # print (features_means.to_json())
-    return features_means
+    return df
 
 
 ##########
@@ -258,14 +275,13 @@ with gr.Blocks() as demo:
         with gr.Column():
             with gr.Row():
                 with gr.Column():
-                    hm_plot = gr.Plot().style(container=True)
-                with gr.Column():
-                    plot = gr.ScatterPlot(show_label=False).style(container=True)
-            with gr.Row():
-                with gr.Column():
-                    plot = gr.ScatterPlot(show_label=False).style(container=True)
+                    energy_plot = gr.ScatterPlot(show_label=False).style(container=True)
                 with gr.Column():
-                    plot = gr.ScatterPlot(show_label=False).style(container=True)
+                    liveness_plot = gr.ScatterPlot(show_label=False).style(container=True)
+    with gr.Row():
+        gr.Markdown(" ### We have recommendations for you!")
+    with gr.Row():
+        heatmap_plot = gr.Plot()
     with gr.Row():
         gr.Markdown(" ### We have recommendations for you!")
     with gr.Row():
@@ -275,9 +291,10 @@ with gr.Blocks() as demo:
             label="Reccomended Songs",
             value=[["something", "something", "something"], ["something", "something", "something"]]  # TODO: replace with actual reccomendations once get_started() is implemeted.
         )
-    #demo.load(fn=scatter_plot_fn, outputs=plot)
-    demo.load(fn=heatmap_plot_fn, output=hm_plot)
-    demo.load(fn=get_spider_plot, outputs=spider_plot)
+    
+    demo.load(fn=heatmap_plot_fn, outputs = heatmap_plot)
+    demo.load(fn=scatter_plot_fn_energy, outputs = energy_plot)
+    demo.load(fn=scatter_plot_fn_liveness, outputs = liveness_plot)
 
 
 gradio_app = gr.mount_gradio_app(app, demo, "/gradio")