from Markov import Markov weather_today = Markov() weather_today.load_data(file_path='./weather.csv') # Demonstrate that your Markov class works by printing the probability that a windy day follows a cloudy day. print(weather_today.get_prob('cloudy', 'windy')) # This line should print 0.08 # An example use of the Markov class: print(weather_today.get_prob('sunny', 'cloudy')) # This line should print 0.3
#!/bin/usr/env python3 from Markov import Markov weather_today = Markov() weather_today.load_data() print(weather_today.get_prob('sunny', 'cloudy'))
from Markov import Markov import numpy as np weather_today = Markov() weather_today.load_data(file_path='./weather.csv') print(weather_today.get_prob('cloudy', 'windy'))