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choices is designed to make it easy to make it easy to
make things happen in a probabilistic manner. Its main
API is the Choice class.

When called, a Choice object will return one of its keys
according to the proability it has been assigned.

Here's an example:

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

Creating a Choice object
========================

There are three main ways for creating a Choice object:

- a dict of keys and probabilities
- a list of (key, probability) pairs
- a list of (key, sample_count) pairs

Each of those options is explained below.

A dict of keys and probabilities
--------------------------------

Perhaps the simplest way to create a Choice is to
provide the keys and associated probability wrapped
up as a dict:

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

A list of (key, probability) pairs
----------------------------------

As well as a dict assigning a probability to each key, you can
send in a list of (key,value) pairs as lists or tuples. This
allows for lots of flexibility, including non-hashable
types to be used. This means that you can provide objects such
as functions to be used as keys.

Let's say we wanted to create an NPC for a game and wanted
some scripted responses. Why not encode moods as functions
and then pass them togetheer as a Choice.

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

A list of (key, sample_count) pairs
-----------------------------------

You are not restricted to adding p to 1. If you only have samples,
and wish to calculate a probablilty distribution, you can provide
those too:

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


Usage
=====

Making decisions
----------------

To return a new value, simply call the Choice object.

    >>> where_to_go = Choice({"Paris": 0.4, "London": 0.4, "Copenhagen": 0.1, "Barcelona": 0.1 })
    >>> where_to_go()
    'Copenhagen'

Finding probabilities
---------------------

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

    >>> mood.distribution
    [('happy', 0.3), ('neutral', 0.6), ('sad', 0.1)]
    >>> where_to_go.distribution
    [('Paris': 0.4), ('London', 0.4), ('Copenhagen', 0.1), ('Barcelona', 0.1)]

Retrieving the probability of a particular key is supported:

    >>> birds['geese']
    0.0