feat: introduce experements

Author: peplxx

experiments/base.py

@@ -0,0 +1,15 @@
+from abc import ABC, abstractmethod
+import streamlit as st
+
+class Experiment(ABC):
+    @abstractmethod
+    def run(self):
+        pass
+    
+    @abstractmethod
+    def get_description(self) -> str:
+        pass
+    
+    @property
+    def name(self) -> str:
+        return self.__class__.__name__.replace('Experiment', '')

experiments/coin_flip.py

@@ -0,0 +1,37 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from .base import Experiment
+import streamlit as st
+
+class CoinFlipExperiment(Experiment):
+    def run(self):
+        col1, col2, col3 = st.columns([1, 1, 1])
+        
+        with col1:
+            num_flips = st.slider("Number of flips", 1, 10000, 100)
+            flips = np.random.choice(['Heads', 'Tails'], size=num_flips)
+            unique, counts = np.unique(flips, return_counts=True)
+            probabilities = dict(zip(unique, counts/num_flips))
+            st.metric("Heads Probability", f"{probabilities.get('Heads', 0):.3f}")
+            st.metric("Tails Probability", f"{probabilities.get('Tails', 0):.3f}")
+            
+        with col2:
+            fig, ax = plt.subplots()
+            ax.bar(probabilities.keys(), probabilities.values())
+            ax.set_ylabel('Probability')
+            ax.set_title(f'Probability Distribution ({num_flips} flips)')
+            st.pyplot(fig)
+            
+        with col3:
+            st.write("Coin Flip Properties:")
+            st.write("""
+            - Each flip is independent
+            - Probability of heads = 0.5
+            - Probability of tails = 0.5
+            - Expected value = 0.5
+            - Variance = 0.25
+            """)
+            st.markdown("📚 **Learn More:** [Coin Flipping Probability](https://en.wikipedia.org/wiki/Coin_flipping#Physics)")
+    
+    def get_description(self) -> str:
+        return "Simulate coin flips and observe probability distribution"

experiments/manager.py

@@ -0,0 +1,22 @@
+from typing import Dict, Type
+from .base import Experiment
+from .coin_flip import CoinFlipExperiment
+import streamlit as st
+
+class ExperimentManager:
+    def __init__(self):
+        self.experiments: Dict[str, Type[Experiment]] = {
+            'Coin Flip': CoinFlipExperiment(),
+        }
+    
+    def get_experiment_names(self):
+        return list(self.experiments.keys())
+    
+    def run_experiment(self, name: str):
+        if name not in self.experiments:
+            raise ValueError(f"Unknown experiment: {name}")
+        
+        experiment = self.experiments[name]
+        st.header(name)
+        st.markdown(experiment.get_description())
+        experiment.run()

main.py

@@ -3,6 +3,8 @@
 from distributions.discrete import *
 from ui.sidebar import Sidebar
 import matplotlib.pyplot as plt
+import numpy as np
+from experiments.manager import ExperimentManager
 
 
 class ProbabilityExplorer:
@@ -49,6 +51,7 @@ def __init__(self):
             'Hypergeometric': HypergeometricDistribution(),
             'UniformDiscrete': UniformDiscreteDistribution(),
         }
+        self.experiment_manager = ExperimentManager()
 
 
     def run(self):
@@ -83,8 +86,14 @@ def run(self):
                 st.error("Error plotting distribution: " + str(e))
 
     def show_experiments_page(self):
-        pass
+        with st.sidebar:
+            experiment = st.selectbox(
+                "Choose an experiment:",
+                self.experiment_manager.get_experiment_names()
+            )
 
+        self.experiment_manager.run_experiment(experiment)
+
     def show_about_page(self):
         st.header("About project:")