🔤 Markov Chain Example 🔤❗️📢

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🔤 Markov Chain Example 🔤❗️📢

# Define states and transition probabilities
🍉 🗂 weatherTransitions
🔡"Sunny" ➡️ 🗂
🔡"Sunny" ➡️ 0.7
🔡"Rainy" ➡️ 0.3 🍆
🔡"Rainy" ➡️ 🗂
🔡"Sunny" ➡️ 0.5
🔡"Rainy" ➡️ 0.5 🍆 🍆

# Function to get next state based on current state
🍉 🔡 getNextState 🔡 currentState
🍉 🍀 randomValue 🥽 1.0 # Generate a random float between 0 and 1
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🍇 🍬 randomValue < weatherTransitions🖍currentState🖍🔡"Sunny"❗️ 🍉 ↩️ 🔡"Sunny" 🍉 🍉 ↩️ 🔡"Rainy" 🍇 🍇 🍇 # Simulate the Markov chain 🍉 ➡️ simulateMarkovChain 🔡 initialState 🔡 steps 🍉 currentState 🥺 initialState 📆 🍆 🖍i 🔡 steps❗️❗️ 🍇 currentState 🔤Step🔤 🖍i 🔤:🔤 🔡 currentState❗️📢 currentState 🔡 getNextState 🖍currentState❗️ 🍇 🍇 # Initial state and number of steps to simulate 🔡 initialState 🔡 "Sunny" 🔡 steps 🥺 10 # Run the simulation 🔡 simulateMarkovChain 🖍initialState 🔡 steps❗️ 🍉

[1]https://github.com/EmojiTwo/emojitwo
[2]https://github.com/hfg-gmuend/openmoji
[3]https://github.com/twitter/twemoji
[4]https://github.com/googlefonts/noto-emoji
[5]https://github.com/microsoft/fluentui-emoji
[6]https://github.com/sensadesign/sensaemoji