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A more technical way to describe this would be a random choice with discrete non-uniform probability distribution.
Suppose you have the following list of kissing sounds, and you want to pick one at random. But because kiss3.mp3 is a very special kissing sound, you want it to be chosen less often than the other kissing sounds. How do you go about this?
We will start from a list of possible options, and to each item we give a "weight" that says how likely it is to be chosen:
[('kiss1.mp3',3) , ('kiss2.mp3',3) , ('kiss3.mp3',1)]
The above list would mean that out of 7 times, on average, 3 times kiss1.mp3 should be chosen, 3 times kiss2.mp3 should be chosen and only one time kiss3.mp3 should be chosen.
This requires some python code.
python:
class NonUniformRandom(object):
def __init__(self, list_of_values_and_probabilities):
"""
expects a list of [ (value, probability), (value, probability),...]
"""
self.the_list = list_of_values_and_probabilities
self.the_sum = sum([ v[1] for v in list_of_values_and_probabilities])
def pick(self):
"""
return a random value taking into account the probabilities
"""
import random
r = random.uniform(0, self.the_sum)
s = 0.0
for k, w in self.the_list:
s += w
if r < s: return k
return kpython:
# initialize our random picker with the options and their likelyhood of being selected:
n = NonUniformRandom( [('kiss1.mp3', 3), ('kiss2.mp3',3), ('kiss3.mp3',1)] )
# Now generate a kissing demonstration with 14 kissing sounds
for i in range(14):
renpy.sound.queue(n.pick())