negmas.outcomes Package

Defines basic concepts related to outcomes

Outcomes in this package are always assumed to be multi-issue outcomes where single-issue outcomes can be implemented as the special case with a single issue.

• Both Continuous and discrete issues are supported. All issue will have names. If none is given, a random name will be used. It is HIGHLY recommended to always name your issues.

• Outcomes are dictionaries with issue names as keys and issue values as values.

Examples

Different ways to create issues:

>>> issues = [make_issue((0.5, 2.0), 'price'), make_issue(['2018.10.'+ str(_) for _ in range(1, 4)], 'date')
...           , make_issue(20, 'count')]
>>> for _ in issues: print(_)
price: (0.5, 2.0)
date: ['2018.10.1', '2018.10.2', '2018.10.3']
count: (0, 19)

Outcome example compatible with the given set of issues:

>>> a = {'price': 1.2, 'date': '2018.10.04', 'count': 4}

Functions

check_one_and_only(outcome_space, issues, ...)	Ensures that one and only one of the three inputs is given (i.e. not None).
check_one_at_most(outcome_space, issues, ...)	Ensures that at most one of the three inputs is given (i.e. not None).
ensure_os(outcome_space, issues, outcomes)	Returns an outcome space from either an outcome-space, a list of issues, a list of outcomes, or the number of outcomes
os_or_none(outcome_space, issues, outcomes)	Returns an outcome space from either an outcome-space, a list of issues, a list of outcomes, or the number of outcomes
make_issue(values, *args[, optional])	A factory for creating issues based on values type as well as the base class of all issues
generate_issues(params[, counts, names])	Generates a set of issues with given parameters.
issues_from_genius(file_name[, ...])	Imports a the domain issues from a GENIUS XML file.
issues_from_geniusweb(file_name[, ...])	Imports a the domain issues from a GENIUS XML file.
issues_from_xml_str(xml_str[, safe_parsing, ...])	Exports a list/dict of issues from a GENIUS XML file.
issues_from_geniusweb_json_str(json_str[, ...])	Exports a list/dict of issues from a GeniusWeb json file.
issues_to_genius(issues, file_name)	Exports a the domain issues to a GENIUS XML file.
issues_to_xml_str(issues)	Converts the list of issues into a well-formed xml string.
issues_from_outcomes(outcomes[, ...])	Create a set of issues given some outcomes.
num_outcomes(issues)	Returns the total number of outcomes in a set of issues.
enumerate_issues(issues[, max_cardinality])	Enumerates the outcomes of a list of issues.
enumerate_discrete_issues(issues)	Enumerates all outcomes of this set of discrete issues if possible.
discretize_and_enumerate_issues(issues[, ...])	Enumerates the outcomes of a list of issues.
sample_issues(issues, n_outcomes[, ...])	Samples some outcomes from the outcome space defined by the list of issues.
sample_outcomes(issues[, n_outcomes, ...])	Discretizes the issue space and returns either a predefined number of outcomes or uniform samples.
combine_issues(issues[, name, ...])	Combines multiple issues into a single issue.
dict2outcome(d, issues)	Converts the outcome to a tuple no matter what was its type
outcome2dict(outcome, issues)	Converts the outcome to a dict no matter what was its type.
outcome_in_range(outcome, outcome_range, *)	Tests that the outcome is contained within the given range of outcomes.
outcome_is_complete(outcome, issues)	Tests that the outcome is valid and complete.
outcome_types_are_ok(outcome, issues)	Checks that the types of all issue values in the outcome are correct
outcome_is_valid(outcome, issues)	Test validity of an outcome given a set of issues.
generalized_minkowski_distance(a, b, ...[, ...])	Calculates the difference between two outcomes given an outcome-space (optionally with issue weights).
min_dist(test_outcome, outcomes, outcome_space)	Minimum distance between an outcome and a set of outcomes in an outcome-spaceself.
make_os([issues, outcomes, name])	A factory to create outcome-spaces from lists of Issue s or Outcome s.

Classes

Outcome	alias of tuple
PartialOutcomeTuple	alias of tuple
OutcomeSpace(*args, **kwargs)	The base protocol for all outcome spaces.
DiscreteOutcomeSpace(*args, **kwargs)	The base protocol for all outcome spaces with a finite number of items.
IndependentIssuesOS(*args, **kwargs)	An Outcome-Space that is constructed from a tuple of Issue objects.
IndependentDiscreteIssuesOS(*args, **kwargs)	An Outcome-Space that is constructed from a tuple of DiscreteIssue objects.
Issue(values[, name])	Base class of all issues in NegMAS
DiscreteIssue(values[, name])	An Issue with a discrete set of values.
CallableIssue(values[, name])	An Issue with a callable for generating values.
CategoricalIssue(values[, name])	An Issue type representing discrete values that have no ordering or difference defined.
OrdinalIssue(values[, name])	An Issue that have some defined ordering of outcomes but not necessarily a meaningful difference function between its values.
DiscreteOrdinalIssue(values[, name])	A DiscreteIssue that have some defined ordering of outcomes but not necessarily a meaningful difference function between its values.
RangeIssue(values[, name])	An issue representing a range of values (can be continuous or discrete)
CardinalIssue(values[, name])	An Issue for which differences between values are meaningful.
ContiguousIssue(values[, name])	A RangeIssue (also a DiscreteIssue) representing a contiguous range of integers.
ContinuousIssue(values[, name, n_levels])	A RangeIssue representing a continous range of real numbers with finite limits.
CountableInfiniteIssue(values, *args, **kwargs)	An issue that can have all integer values.
ContinuousInfiniteIssue(values[, name, n_levels])	An issue that can represent all real numbers
InfiniteIssue()	Indicates that the issue is infinite (i.e. one or more of its limits is infinity).
CartesianOutcomeSpace(issues[, name])	An outcome-space that is generated by the cartesian product of a tuple of Issue s.
DiscreteCartesianOutcomeSpace(issues[, name])	A discrete outcome-space that is generated by the cartesian product of a tuple of Issue s (i.e. with finite number of outcomes).

Class Inheritance Diagram