Update app.py

app.py

@@ -171,9 +171,9 @@ def plot(y, label, timeframe='1h', ma=5, n_steps=None):
     plt.figure(figsize=(12,6))
     if ma:
         df_plot = pd.DataFrame({'date': label['timestamp'].values[-n_steps:], 'prediction':5*(y[-n_steps:]-0.5), 'real': label['close'].values[-n_steps:]})
-        plt.plot(df_plot['date'], df_plot['prediction'].rolling(window=ma).mean(), marker='o',  line_width=3, label='updown')
-        plt.plot(df_plot['date'], df_plot['real'].rolling(window=ma).mean(), marker='o',  line_width=3, label='real')
-        plt.plot(df_plot['date'], (df_plot['real']-df_plot['prediction']).rolling(window=ma).mean(), marker='o',  line_width=3, label='difference')
+        plt.plot(df_plot['date'], df_plot['prediction'].rolling(window=ma).mean(), marker='o',  label='updown')
+        plt.plot(df_plot['date'], df_plot['real'].rolling(window=ma).mean(), marker='o',   label='real')
+        plt.plot(df_plot['date'], (df_plot['real']-df_plot['prediction']).rolling(window=ma).mean(), marker='o', label='difference')
     else:
         plt.plot(label['timestamp'].values[-n_steps:], 5*(y[-n_steps:]-0.5), label='updown')
         plt.plot(label['timestamp'].values[-n_steps:], label['close'].values[-n_steps:], label='real')