Update app.py

app.py

@@ -1,15 +1,17 @@
 from collections import defaultdict
 
-
+import seaborn as sns
 import streamlit as st
 import streamlit.components.v1 as components
 import plotly.graph_objects as go
 import plotly.express as px
 import numpy as np
+import pandas as pd
 
 
 st.set_page_config(page_title='Can you be truly random ?', layout = 'wide', page_icon = 'favicon.jpg', initial_sidebar_state = 'auto')
 
+cm = sns.light_palette("green", as_cmap=True)
 
 
 # Custom CSS to styles
@@ -23,7 +25,7 @@ st.markdown("""
 """, unsafe_allow_html=True)
 
 
-max_history = 10
+
 
 def set_state(x):
     if x == 1: st.toast('The journey begins!', icon='😍')
@@ -39,6 +41,7 @@ def reset_game():
     st.session_state.pnl = [0]
     st.session_state.min = [0]
     st.session_state.max = [0]
+    st.session_state.max_history = 10
 
 if 'stage' not in st.session_state:
     reset_game()
@@ -52,73 +55,43 @@ if st.session_state.stage == 0:
     
     st.markdown(f'You will be presented with {st.session_state.n_buttons} buttons to randomly choose from')
     
-    st.markdown("At each round, I will try to predict which button you click :-)")
+    
+    st.session_state.max_history = st.slider(label="How much memory can I use?", min_value=2, max_value=20,value=10)
+    st.markdown(f"At each round, I will try to predict which button you click")
+    st.markdown(f"I will examine {st.session_state.max_history}-long sequences you played in the past")
+    st.markdown('This will help me make a guess')
     st.markdown(f"If I get it right, I earn {st.session_state.n_buttons-1} point(s), otherwise you earn 1 point")
-    st.markdown(f"Play as long as you want and try to beat me!")
+    st.markdown(f'This is a fair game, as you have {(1-1/st.session_state.n_buttons):.0%} chances of winning')
+    st.subheader(f"Play as long as you want and try to beat me!")
     
         
     
-
-# def get_prev_seqs(history):
-#     # st.write(history)
-    
-#     seqs = []
-#     for h in range(max_history+1):
-#         if len(history) >= h:
-#             previous_seq = ''.join(history[-h:]) if h > 0 else ""
-#             # st.write(previous_seq)
-#             seqs.append(previous_seq) # from small to largest
-#     return seqs
-    
-# def refresh_preds():
-#     played = st.session_state.history[-1]
-#     seqs = get_prev_seqs(st.session_state.history[:-1])
-#     for seq in seqs:
-#         # st.write(f'"{seq}"',played)
-#         st.session_state.preds[seq][played] += 1
-
-def make_pred(max_history=max_history,alpha=0.5):
+def make_pred(max_history=st.session_state.max_history,alpha=0.5):
     history = st.session_state.history
     
     denominator = 0
     scores = {str(i):0 for i in range(st.session_state.n_buttons)}
     recent = np.array(history[-max_history:])
+    data = []
     for i in range(1,len(history)):
         past = np.array(history[-i-max_history:-i])
         
         played = history[-i]
         decay = np.exp(-alpha*np.linspace(1,0,len(past)))
-        similarity = ((past == recent[-len(past):])*decay).sum() / decay.sum()
+        same = past == recent[-len(past):]
+        similarity = (same*decay).sum() / decay.sum()
         weight = len(history)/(len(history)+i) * similarity
         scores[played] += weight
         denominator += weight
+        if similarity > 0.5:
+            data.append([played,similarity,weight,i] + [None]* (max_history-len(past)) +list(same))
     if not denominator:
-        return get_random_play()
+        return get_random_play(),data
     result = {str(i):scores[str(i)]/denominator for i in range(st.session_state.n_buttons)}
-    return result
+    return result, data
     
 def get_random_play():
     return {str(i):1/st.session_state.n_buttons for i in range(st.session_state.n_buttons)}
-
-# def make_pred():
-#     seqs = get_prev_seqs(st.session_state.history)
-#     # st.write('seqs',seqs)
-#     scores = defaultdict(float)
-#     denominator = 0
-#     for i,seq in enumerate(seqs):
-#         weight = (i+1)**2
-#         preds = st.session_state.preds[seq]
-#         total = sum(preds.values())
-        
-#         if total:
-#             for played,value in preds.items():
-#                 scores[played] += weight*value/total
-#             denominator += weight
-#     if denominator:
-#         scores = {played:value/denominator for played,value in scores.items()}
-#         return scores
-#     else:
-#         return get_random_play()
         
 
 def update_pnl(user_win):
@@ -148,22 +121,45 @@ def compute_perf():
         std = data.std()
         win = (data>0).mean()
         sharpe = perf / std
-        return f'%age win={win:.2%} Sharpe={sharpe:.2f}'
-    
+        return win,sharpe
+    else:
+        return 0,0
+
+
+
 
 if st.session_state.stage == 1:
-    pred = make_pred()
+    pred,data = make_pred()
+    
     choice = max(pred,key=pred.get)
     
     cols = st.columns(st.session_state.n_buttons)
     for i,col in enumerate(cols):
         col.button(str(i),on_click=user_select, args=[str(i),choice],
         use_container_width=True)
-
-    st.subheader(f'My earnings so far... {compute_perf()} :-)')
+        
+    col1,col2 = st.columns(st.session_state.n_buttons)
+    
+    win,sharpe = compute_perf()
+    if sharpe > 0.1: 
+        emoticon = "🚀"
+    elif sharpe < 0:
+        emoticon = "📉"
+    else:
+        emoticon = "🧠"
+    text = f'%age win={win:.0%} Sharpe={sharpe:.3f} {emoticon}'
+    col1.subheader('My earnings so far...')
+    col1.write(text)
     fig = px.line(st.session_state.pnl)
     fig.update_layout(showlegend=False)
-    st.plotly_chart(fig, use_container_width=True)
+    fig.update_layout(xaxis={'visible': True, 'showticklabels': False})
+    col1.plotly_chart(fig, use_container_width=True)
+    
+    cols = ['you_played','similarity','weight','how_long_ago'] +  [f'same_{i}' for i in range(st.session_state.max_history)]
+    data = pd.DataFrame(data,columns=cols).set_index('how_long_ago').sort_values('weight',ascending=False)[:10]
+    col2.subheader(f'In the past, you played')
+    col2.dataframe(data.style.background_gradient(cmap=cm), use_container_width=True)
+    col2.subheader(f'I play {choice}, p={pred[choice]:.0%}')
     
     st.button('Start over', on_click=reset_game, args=[],
         use_container_width=True)