Skip to main content

Making choices from a probability distribution

Project description

The PDist is designed to make it easy to make it easy to make things happen in a probablistic manner. Provide keys with an associated probability attached, and then call the resulting object when you need a new value.

>>> mood = PDist({'happy': 0.3, 'neutral': 0.6, 'sad': 0.1})
>>> mood()
>>> mood()

You can retrieve the distribution of how those values are applied by accessing the PDist.distribution attribute:

>>> mood.distribution
[('happy', 0.3), ('neutral', 0.6), ('sad', 0.1)]

As well as providing a dict to assign probabilities, you can send in a list of lists/tuples. This allows for for non-hashable types to be used. This means that you provide objects such as functions to be used as keys:

>>> def grumpy(news):
...    return ':/'
>>> def happy(news):
...    return ':)'
>>> react = PDist([(grumpy, 0.7), (happy, 0.3)])
>>> reaction = react()
>>> reaction("We're getting married!")

You are not restricted to adding your input variables up to 1. For example, if you only have a tally chart, and wish to calculate a probability distribution from that sample, you can provide that too:

>>> spotted = {'geese': 0, 'ducks': 12, 'sparrows': 4, 'other': 39}
>>> bird_pdist = PDist(spotted)
>>> bird_pdist.distribution
[('geese', 0.0), ('sparrows', 0.07272727272727272), ('ducks', 0.21818181818181817), ('other', 0.7090909090909091)]

Retrieving the probability of a particular key is supported. However, the search strategy is very inefficient and probably shouldn’t be used outside of the interactive Python shell.

>>> bird_pdist['geese']

Project details

Release history Release notifications

This version


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for choices, version 0.1
Filename, size File type Python version Upload date Hashes
Filename, size choices-0.1.tar.gz (2.5 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page