# inferi.probability¶

Contains probability concept classes.

class inferi.probability.EventSpace[source]

An abstract class for objects which are a container of simple events.

Any class inheriting from this class should ensure its instances have a _simple_events property which is a set of Simple Event objects.

simple_events

The set of simple events in this space.

Return type: set
outcomes(p=False)[source]

The set of outcomes that the event space’s simple events can produce.

Parameters: p (bool) – if True, the results will be returned as a dict with probabilities associated. set or dict
class inferi.probability.Event(*events, name='E')[source]

Base class: EventSpace

An occurance that is made up of multiple simple events.

Events are containers both of their simple events, and the outcomes of those simple events.

Parameters: *events – The Event objects within this set. name (str) – The name of the event (default is ‘E’). TypeError – if non-events are given. TypeError – if the name is not a string.
sample_space

The sample space that the event is part of.

Return type: SampleSpace
name

Returns the name of the Event.

Return type: str
complement

Returns the complement of the event - the event that this event does not happen.

Return type: Event
probability(given=None, fraction=False)[source]

Returns the probability of the event happening.

Parameters: given (Event) – an optional pre-condition to consider. fraction (bool) – If True, the result will be returned as a Fraction. TypeError – if the given event is not an Event float
mutually_exclusive_with(event)[source]

Looks at some other event and checks if this event is mutually exclusive with the other event. That is, whether it is impossible for them both to happen in a given statistical experiment.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
independent_of(event)[source]

Checks to see if this event is independent of some other event - that is, whether its probability is unaffacted by the occurence of the other event.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
dependent_on(event)[source]

Checks to see if this event is dependent of some other event - that is, whether its probability is affacted by the occurence of the other event.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
outcomes(p=False)

The set of outcomes that the event space’s simple events can produce.

Parameters: p (bool) – if True, the results will be returned as a dict with probabilities associated. set or dict
simple_events

The set of simple events in this space.

Return type: set
class inferi.probability.SimpleEvent(outcome, probability, space)[source]

Base class: py:class:.Event

A simple event - a single outcome of a statistical experiment.

Parameters: outcome – The result of this event occuring. probability (float) – The probability of this event occuring. TypeError – if probability isn’t numeric. ValueError – if probability is not between 0 and 1.
outcome

The result of this event occuring.

complement

Returns the complement of the event - the event that this event does not happen.

Return type: Event
dependent_on(event)

Checks to see if this event is dependent of some other event - that is, whether its probability is affacted by the occurence of the other event.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
independent_of(event)

Checks to see if this event is independent of some other event - that is, whether its probability is unaffacted by the occurence of the other event.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
mutually_exclusive_with(event)

Looks at some other event and checks if this event is mutually exclusive with the other event. That is, whether it is impossible for them both to happen in a given statistical experiment.

Parameters: event (Event) – the other event to check with. TypeError – if a non-Event is given. bool
name

Returns the name of the Event.

Return type: str
outcomes(p=False)

The set of outcomes that the event space’s simple events can produce.

Parameters: p (bool) – if True, the results will be returned as a dict with probabilities associated. set or dict
probability(given=None, fraction=False)

Returns the probability of the event happening.

Parameters: given (Event) – an optional pre-condition to consider. fraction (bool) – If True, the result will be returned as a Fraction. TypeError – if the given event is not an Event float
sample_space

The sample space that the event is part of.

Return type: SampleSpace
simple_events

The set of simple events in this space.

Return type: set
class inferi.probability.SampleSpace(*outcomes, p=None)[source]

Base class: EventSpace

The set of all possible things that can result from a statistical experiment.

Parameters: *outcomes – All the possible outcomes. p (dict) – The probabilities for the supplied outcomes. If not given, these will be weighted equally. ValueError – if you supply probabilities that don’t add up to 1.
event(*outcomes, name=None)[source]

If a single outcome is given, this function will return the SimpleEvent corresponding to that outcome.

If multiple outcomes are given, the function will return the Event corresponding to one of those outcomes occuring.

If a callable is provided, the function will return the Event of all the simple events that return True when the callable is applied to their outcome.

Parameters: *outcomes – The outcome(s) to look for. name (str) – The name to apply if a Event is returned. SimpleEvent or Event
chances_of(*outcomes)[source]

Returns the probability of the given outcome or outcomes occuring in a single statistical experiment.

If multiple outcomes are given, the function will return the Event corresponding to one of those outcomes occuring.

If a callable is provided, the function will return the Event of all the simple events that return True when the callable is applied to their outcome.

Parameters: *outcomes – The outcome(s) to look for. float
experiment()[source]

Generate an outcome.

outcomes(p=False)

The set of outcomes that the event space’s simple events can produce.

Parameters: p (bool) – if True, the results will be returned as a dict with probabilities associated. set or dict
simple_events

The set of simple events in this space.

Return type: set