from Markov import Markov city_weather = { 'New York': 'rainy', 'Chicago': 'snowy', 'Seattle': 'rainy', 'Boston': 'hailing', 'Miami': 'windy', 'Los Angeles': 'cloudy', 'San Francisco': 'windy' } city_weather_prediction = {} for city in city_weather: weather = Markov(day_zero_weather=city_weather[city]) weather.load_data(file_path='./weather.csv') prediction = weather._simulate_weather_for_day(7, trials=100) city_weather_prediction[city] = prediction for city in city_weather_prediction: print(city, ':', city_weather_prediction[city]) print('\nMost likely weather in seven days\n---------------------------------') for city in city_weather_prediction: weather_guess = max(city_weather_prediction[city], key=city_weather_prediction[city].get) print(city, ':', weather_guess)
#!/bin/usr/env python3 from Markov import Markov weather_today = Markov() weather_today.load_data() print(weather_today.get_prob('sunny', 'cloudy'))