Python code to create random events where the events have different probabilites specified by a frequence table.

event_gen.py

import random
""" Create random events where event probabilities are 
    set by a frequency list
    This shows two functional approaches, the second being more terse
    and then a object oriented approach"""

# functional approach using a closure
# setup: x = event_gen(freq_table)
# get sample:  x() -> sample index
def event_gen(freq_table):
    n = len(freq_table)
    cumulative_frequency = []
    total = 0.0
    for p in freq_table: # build cumlative frequencies
        total += p
        cumulative_frequency.append(total)

    def event_f():
        r = random.uniform(0, total) # between 0.0 and total
        for i in range(n):
            if cumulative_frequency[i] >= r: # find interval
                return i
    return event_f

        
# functional approach using a closure 
# and generators/list comprehensions
# setup: x = event_gen2(freq_table)
# get sample:  x() -> sample index
def event_gen2(freq_table):
    cumulative_frequency = [sum(freq_table[:i+1]) 
            for i in range(len(freq_table))] # terse but O(n squared)

    def event_i():
        r = random.uniform(0, cumulative_frequency[-1])
        return next((i for i, t 
                     in enumerate(cumulative_frequency) if t >= r))

    # return function that returns random sample index of event
    return event_i  
    
    
# Object Oriented approach
# setup: x = Event_gen(freq_table) # create object
# get sample: x() -> sample index
class EventGen(object):
    
    def __init__(self, freq_table):
        n = len(freq_table)
        self.cumulative_frequency = []
        total = 0.0
        for p in freq_table:
            total += p
            self.cumulative_frequency.append(total)
            
    def __call__(self): # allows us to 'call' object
        r = random.uniform(0, self.cumulative_frequency[-1])
        i = next((i for i, t in 
              enumerate(self.cumulative_frequency) if t >= r))
        return i
        
        
def test():
              # function/class      test label
    tests = ( (event_gen, 'event_gen functional case'),
              (event_gen2,'event_gen2 functional case'),
              (EventGen, 'EventGen OOP case'),
            )
              
    # simulate events for a game at sea
    freq_table = (20, 3, 1, 5, 2, 1)
    events = ('calm day', 'storm',  'alien', 
              'pirate', 'land', 'sea monster')
    n = 1000000 # run n samples
        
    for gen, label in tests: # run each case
        sample = gen(freq_table)  # get sampler function function
        
        hist = {e: 0 for e in events}  # histogram will be built
        
        for _ in range(n):
            hist[events[sample()]] += 1 # add 1 to historgram bucket
            
        total = sum(freq_table) 
        print(label)
        for event in hist.keys():
            print(f"{event:11s}  {hist[event]:6d} " 
                  f"{hist[event]*total/n:5.2f}")
        print()

if __name__ == '__main__':
    test()