Spaces:
Sleeping
Sleeping
| from collections import defaultdict | |
| 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 | |
| st.set_page_config(page_title='Can you be truly random ?', layout = 'wide', page_icon = 'favicon.jpg', initial_sidebar_state = 'auto') | |
| # Custom CSS to styles | |
| st.markdown(""" | |
| <style> | |
| button { | |
| padding-top: 50px !important; | |
| padding-bottom: 50px !important; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| max_history = 10 | |
| def set_state(x): | |
| if x == 1: st.toast('The journey begins!', icon='😍') | |
| st.session_state.stage = x | |
| def reset_game(): | |
| set_state(0) | |
| if 'n_buttons' not in st.session_state: | |
| st.session_state.n_buttons = 2 | |
| st.session_state.history = [] | |
| st.session_state.preds = defaultdict(lambda: defaultdict(int)) | |
| st.session_state.pnl = [0] | |
| st.session_state.min = [0] | |
| st.session_state.max = [0] | |
| if 'stage' not in st.session_state: | |
| reset_game() | |
| st.title('Can your brain be random?') | |
| if st.session_state.stage == 0: | |
| st.button('Begin', on_click=set_state, args=[1],use_container_width=True) | |
| st.session_state.n_buttons = st.slider(label="How many buttons to play with?", min_value=2, max_value=5,value=2) | |
| 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.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!") | |
| # 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): | |
| 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:]) | |
| 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() | |
| weight = len(history)/(len(history)+i) * similarity | |
| scores[played] += weight | |
| denominator += weight | |
| if not denominator: | |
| return get_random_play() | |
| result = {str(i):scores[str(i)]/denominator for i in range(st.session_state.n_buttons)} | |
| return result | |
| 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): | |
| current_score = st.session_state.pnl[-1] | |
| current_score += -1 if user_win else (st.session_state.n_buttons-1) | |
| st.session_state.pnl.append(current_score) | |
| expected_change = (2**0.5) * ((st.session_state.n_buttons-1)/st.session_state.n_buttons) | |
| st.session_state.min.append(st.session_state.min[-1]-expected_change) | |
| st.session_state.max.append(st.session_state.max[-1]+expected_change) | |
| def user_select(i,choice): | |
| st.session_state.history.append(str(i)) | |
| if i == choice: | |
| st.toast("I win!", icon='🤪') | |
| update_pnl(user_win=False) | |
| else: | |
| st.toast('Well done!', icon='😍') | |
| update_pnl(user_win=True) | |
| # refresh_preds() | |
| def compute_perf(): | |
| data = np.array(st.session_state.pnl) | |
| if len(data) > 1: | |
| data = data[1:] - data[:-1] | |
| perf = data.mean() | |
| std = data.std() | |
| win = (data>0).mean() | |
| sharpe = perf / std | |
| return f'%age win={win:.2%} Sharpe={sharpe:.2f}' | |
| if st.session_state.stage == 1: | |
| pred = 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()} :-)') | |
| fig = px.line(st.session_state.pnl) | |
| fig.update_layout(showlegend=False) | |
| st.plotly_chart(fig, use_container_width=True) | |
| st.button('Start over', on_click=reset_game, args=[], | |
| use_container_width=True) |