├── pygmodels
├── __init__.py
├── graph
│ ├── gtype
│ │ ├── __init__.py
│ │ ├── typeutils.py
│ │ └── graphobj.py
│ ├── gmodel
│ │ └── __init__.py
│ └── graphops
│ │ └── __init__.py
├── pgm
│ ├── pgmf
│ │ └── __init__.py
│ ├── pgmodel
│ │ └── __init__.py
│ └── pgmtype
│ │ ├── __init__.py
│ │ └── abstractpgm.py
├── factor
│ ├── __init__.py
│ ├── factorf
│ │ └── __init__.py
│ └── ftype
│ │ └── abstractfactor.py
├── randvar
│ ├── __init__.py
│ └── rtype
│ │ ├── __init__.py
│ │ └── abstractrandvar.py
└── value
│ ├── abstractvalue.py
│ ├── domain.py
│ ├── codomain.py
│ └── value.py
├── test
├── __init__.py
├── test_node.py
└── test_edge.py
├── docs
├── _config.yml
├── html
│ ├── bc_s.png
│ ├── bdwn.png
│ ├── doc.png
│ ├── nav_f.png
│ ├── nav_g.png
│ ├── nav_h.png
│ ├── open.png
│ ├── tab_a.png
│ ├── tab_b.png
│ ├── tab_h.png
│ ├── tab_s.png
│ ├── closed.png
│ ├── doxygen.png
│ ├── sync_on.png
│ ├── arrowdown.png
│ ├── arrowright.png
│ ├── folderopen.png
│ ├── splitbar.png
│ ├── sync_off.png
│ ├── folderclosed.png
│ ├── search
│ │ ├── close.png
│ │ ├── mag_sel.png
│ │ ├── search_l.png
│ │ ├── search_m.png
│ │ ├── search_r.png
│ │ ├── files_2.js
│ │ ├── files_4.js
│ │ ├── files_5.js
│ │ ├── files_1.js
│ │ ├── files_3.js
│ │ ├── files_6.js
│ │ ├── files_0.js
│ │ ├── files_7.js
│ │ ├── classes_5.js
│ │ ├── all_1.js
│ │ ├── pages_1.js
│ │ ├── pages_2.js
│ │ ├── classes_a.js
│ │ ├── classes_d.js
│ │ ├── groups_0.js
│ │ ├── classes_8.js
│ │ ├── classes_3.js
│ │ ├── classes_7.js
│ │ ├── classes_1.js
│ │ ├── classes_e.js
│ │ ├── classes_f.js
│ │ ├── variables_2.js
│ │ ├── classes_c.js
│ │ ├── functions_18.js
│ │ ├── variables_1.js
│ │ ├── all_b.js
│ │ ├── functions_b.js
│ │ ├── all_16.js
│ │ ├── all_17.js
│ │ ├── variables_0.js
│ │ ├── functions_16.js
│ │ ├── functions_17.js
│ │ ├── all_a.js
│ │ ├── functions_a.js
│ │ ├── functions_2.js
│ │ ├── functions_c.js
│ │ ├── searchdata.js
│ │ ├── classes_4.js
│ │ ├── all_0.js
│ │ ├── pages_0.js
│ │ ├── all_18.js
│ │ ├── all_2.js
│ │ ├── all_c.js
│ │ ├── classes_6.js
│ │ ├── classes_9.js
│ │ ├── classes_2.js
│ │ ├── functions_14.js
│ │ ├── classes_b.js
│ │ ├── nomatches.html
│ │ ├── classes_0.js
│ │ ├── functions_4.js
│ │ ├── all_14.js
│ │ ├── all_8.js
│ │ ├── functions_11.js
│ │ ├── functions_8.js
│ │ ├── functions_f.js
│ │ ├── namespaces_0.js
│ │ ├── functions_1.js
│ │ ├── all_4.js
│ │ ├── all_11.js
│ │ ├── all_f.js
│ │ ├── functions_13.js
│ │ ├── all_13.js
│ │ ├── functions_e.js
│ │ ├── close.svg
│ │ ├── all_10.html
│ │ ├── all_11.html
│ │ ├── all_12.html
│ │ ├── all_13.html
│ │ ├── all_14.html
│ │ ├── all_15.html
│ │ ├── all_16.html
│ │ ├── all_17.html
│ │ ├── all_18.html
│ │ ├── all_2.html
│ │ ├── all_3.html
│ │ ├── all_4.html
│ │ ├── all_5.html
│ │ ├── all_6.html
│ │ ├── all_7.html
│ │ ├── all_8.html
│ │ ├── all_9.html
│ │ ├── all_a.html
│ │ ├── all_b.html
│ │ ├── all_c.html
│ │ ├── all_d.html
│ │ ├── all_e.html
│ │ ├── all_f.html
│ │ ├── classes_0.html
│ │ ├── classes_1.html
│ │ ├── classes_2.html
│ │ ├── classes_3.html
│ │ ├── classes_4.html
│ │ ├── classes_5.html
│ │ ├── classes_6.html
│ │ ├── classes_7.html
│ │ ├── classes_8.html
│ │ ├── classes_9.html
│ │ ├── classes_a.html
│ │ ├── classes_b.html
│ │ ├── classes_c.html
│ │ ├── classes_d.html
│ │ ├── classes_e.html
│ │ ├── classes_f.html
│ │ ├── files_0.html
│ │ ├── files_1.html
│ │ ├── files_2.html
│ │ ├── files_3.html
│ │ ├── files_4.html
│ │ ├── files_5.html
│ │ ├── files_6.html
│ │ ├── files_7.html
│ │ ├── groups_0.html
│ │ ├── pages_2.html
│ │ ├── all_15.js
│ │ ├── functions_0.html
│ │ ├── functions_1.html
│ │ ├── functions_2.html
│ │ ├── functions_3.html
│ │ ├── functions_4.html
│ │ ├── functions_5.html
│ │ ├── functions_6.html
│ │ ├── functions_7.html
│ │ ├── functions_8.html
│ │ ├── functions_9.html
│ │ ├── functions_a.html
│ │ ├── functions_b.html
│ │ ├── functions_c.html
│ │ ├── functions_d.html
│ │ ├── functions_e.html
│ │ ├── functions_f.html
│ │ ├── variables_0.html
│ │ ├── variables_1.html
│ │ ├── variables_2.html
│ │ ├── functions_10.html
│ │ ├── functions_11.html
│ │ ├── functions_12.html
│ │ ├── functions_13.html
│ │ ├── functions_14.html
│ │ ├── functions_15.html
│ │ ├── functions_15.js
│ │ ├── functions_16.html
│ │ ├── functions_17.html
│ │ ├── functions_18.html
│ │ ├── namespaces_0.html
│ │ ├── all_0.html
│ │ ├── all_1.html
│ │ ├── pages_0.html
│ │ ├── pages_1.html
│ │ ├── all_e.js
│ │ ├── functions_3.js
│ │ ├── functions_10.js
│ │ ├── all_3.js
│ │ ├── functions_5.js
│ │ └── functions_7.js
│ ├── de
│ │ ├── d55
│ │ │ └── classgmodels_1_1factor_1_1Factor.png
│ │ └── dfe
│ │ │ └── classgmodels_1_1randomvariable_1_1RandomVariable.png
│ ├── df
│ │ ├── da1
│ │ │ └── classgmodels_1_1pgmodel_1_1PGModel.png
│ │ ├── dd7
│ │ │ └── classgmodels_1_1markov_1_1MarkovNetwork.png
│ │ └── d34
│ │ │ └── classgmodels_1_1randomvariable_1_1NumCatRVariable.png
│ ├── d0
│ │ ├── d1c
│ │ │ └── classgmodels_1_1gtypes_1_1path_1_1Path.png
│ │ ├── d93
│ │ │ └── classgmodels_1_1gtypes_1_1edge_1_1Edge.png
│ │ └── de3
│ │ │ └── classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractInfo.png
│ ├── d7
│ │ └── db3
│ │ │ └── classgmodels_1_1gtypes_1_1tree_1_1Tree.png
│ ├── d9
│ │ ├── d6b
│ │ │ └── classgmodels_1_1searchtree_1_1OrTree.png
│ │ └── d4b
│ │ │ └── classgmodels_1_1legacy_1_1NaiveBayes_1_1BasicNaiveBayesMLE.png
│ ├── db
│ │ └── d8b
│ │ │ └── classgmodels_1_1gtypes_1_1node_1_1Node.png
│ ├── d2
│ │ ├── dfc
│ │ │ └── classgmodels_1_1gtypes_1_1graph_1_1Graph.png
│ │ ├── d4f
│ │ │ └── classgmodels_1_1bayesian_1_1BayesianNetwork.png
│ │ └── dfb
│ │ │ └── classgmodels_1_1legacy_1_1NaiveBayes_1_1SingleNaiveBayesMLE.png
│ ├── d8
│ │ ├── d43
│ │ │ └── classgmodels_1_1searchtree_1_1AndOrTree.png
│ │ ├── d73
│ │ │ └── classgmodels_1_1gtypes_1_1undigraph_1_1UndiGraph.png
│ │ ├── d7c
│ │ │ └── classgmodels_1_1legacy_1_1bayesutils_1_1Distribution.png
│ │ └── d99
│ │ │ └── classgmodels_1_1randomvariable_1_1CatRandomVariable.png
│ ├── da
│ │ └── d1f
│ │ │ └── classgmodels_1_1gtypes_1_1path_1_1Cycle.png
│ ├── d1
│ │ └── da6
│ │ │ └── classgmodels_1_1lwfchain_1_1LWFChainGraph.png
│ ├── dd
│ │ ├── d00
│ │ │ └── classgmodels_1_1gtypes_1_1digraph_1_1DiGraph.png
│ │ ├── d8d
│ │ │ └── classgmodels_1_1gtypes_1_1abstractobj_1_1NodePosition.png
│ │ └── dda
│ │ │ └── classgmodels_1_1legacy_1_1NaiveBayes_1_1MultiNaiveBayesMLE.png
│ ├── d6
│ │ └── d49
│ │ │ └── classgmodels_1_1markov_1_1ConditionalRandomField.png
│ ├── dc
│ │ ├── d16
│ │ │ └── classgmodels_1_1gtypes_1_1abstractobj_1_1EdgeType.png
│ │ └── de3
│ │ │ └── classgmodels_1_1gtypes_1_1graphobj_1_1GraphObject.png
│ ├── d5
│ │ └── d46
│ │ │ └── classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractEdge.png
│ ├── d3
│ │ └── dc4
│ │ │ └── classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractGraphObj.png
│ └── menudata.js
├── doxygen_sqlite3.db
└── index.html
├── .github
├── ISSUE_TEMPLATE
│ └── bug_report.md
└── workflows
│ └── python-package.yml
├── setup.py
└── .pre-commit-config.yaml
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4 | ];
5 |
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5 |
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5 |
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5 |
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1 | var searchData=
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4 | ];
5 |
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/pygmodels/graph/gtype/typeutils.py:
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1 | # type related utility functions
2 | from pygmodels.gtypes.abstractobj import AbstractGraph
3 | from pygmodels.gtypes.basegraph import BaseGraph
4 | from pygmodels.gtypes.finitegraph import FiniteGraph
5 |
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5 |
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2 | {
3 | 0: "gu",
4 | 1: "gu"
5 | };
6 |
7 | var indexSectionNames =
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9 | 0: "all",
10 | 1: "pages"
11 | };
12 |
13 | var indexSectionLabels =
14 | {
15 | 0: "All",
16 | 1: "Pages"
17 | };
18 |
19 |
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3 | ['edge_277',['Edge',['../d0/d93/classgmodels_1_1gtypes_1_1edge_1_1Edge.html',1,'gmodels::gtypes::edge']]],
4 | ['edgetype_278',['EdgeType',['../dc/d16/classgmodels_1_1gtypes_1_1abstractobj_1_1EdgeType.html',1,'gmodels::gtypes::abstractobj']]]
5 | ];
6 |
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4 | ['graphical_20models_1',['Graphical Models',['../index.html',1,'']]]
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6 |
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4 | ['graphical_20models_4',['Graphical Models',['../index.html',1,'']]]
5 | ];
6 |
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6 |
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6 |
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4 | ['lwfchaingraph_143',['LWFChainGraph',['../d1/da6/classgmodels_1_1lwfchain_1_1LWFChainGraph.html',1,'gmodels::lwfchain']]]
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6 |
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5 | ['graphobject_282',['GraphObject',['../dc/de3/classgmodels_1_1gtypes_1_1graphobj_1_1GraphObject.html',1,'gmodels::gtypes::graphobj']]]
6 | ];
7 |
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7 |
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5 | ['cycle_275',['Cycle',['../da/d1f/classgmodels_1_1gtypes_1_1path_1_1Cycle.html',1,'gmodels::gtypes::path']]]
6 | ];
7 |
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/pygmodels/value/abstractvalue.py:
--------------------------------------------------------------------------------
1 | """!
2 | \file abstractvalue.py Value of a set
3 | """
4 |
5 | from abc import ABC, abstractmethod
6 | from typing import Any
7 |
8 |
9 | class AbstractSetValue:
10 | @abstractmethod
11 | def belongs_to(self) -> str:
12 | "The name of the set that contains the value"
13 | raise NotImplementedError
14 |
15 | @abstractmethod
16 | def value(self) -> Any:
17 | "Returns the value associated with the set value"
18 | raise NotImplementedError
19 |
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6 | ];
7 |
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3 | ['path_289',['Path',['../d0/d1c/classgmodels_1_1gtypes_1_1path_1_1Path.html',1,'gmodels::gtypes::path']]],
4 | ['pgmodel_290',['PGModel',['../df/da1/classgmodels_1_1pgmodel_1_1PGModel.html',1,'gmodels::pgmodel']]],
5 | ['possibleoutcomes_291',['PossibleOutcomes',['../d8/dbf/classgmodels_1_1randomvariable_1_1PossibleOutcomes.html',1,'gmodels::randomvariable']]],
6 | ['priorityqueue_292',['PriorityQueue',['../d7/d6e/classgmodels_1_1gtypes_1_1queue_1_1PriorityQueue.html',1,'gmodels::gtypes::queue']]]
7 | ];
8 |
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/docs/html/search/nomatches.html:
--------------------------------------------------------------------------------
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
12 |
13 |
14 |
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/docs/html/search/classes_0.js:
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1 | var searchData=
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3 | ['abstractedge_268',['AbstractEdge',['../d5/d46/classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractEdge.html',1,'gmodels::gtypes::abstractobj']]],
4 | ['abstractgraphobj_269',['AbstractGraphObj',['../d3/dc4/classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractGraphObj.html',1,'gmodels::gtypes::abstractobj']]],
5 | ['abstractinfo_270',['AbstractInfo',['../d0/de3/classgmodels_1_1gtypes_1_1abstractobj_1_1AbstractInfo.html',1,'gmodels::gtypes::abstractobj']]],
6 | ['andortree_271',['AndOrTree',['../d8/d43/classgmodels_1_1searchtree_1_1AndOrTree.html',1,'gmodels::searchtree']]]
7 | ];
8 |
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/pygmodels/randvar/rtype/abstractrandvar.py:
--------------------------------------------------------------------------------
1 | """!
2 | \file abstractrandvar.py Represents an abstract random variable
3 | """
4 | from abc import ABC, abstractmethod
5 |
6 | from pygmodels.graph.gtype.abstractobj import AbstractNode
7 | from pygmodels.value.codomain import Outcome
8 | from pygmodels.value.value import NumericValue
9 |
10 |
11 | class AbstractRandomVariable(AbstractNode):
12 | """!
13 | Abstract random variable
14 | """
15 |
16 | @abstractmethod
17 | def p(self, out: Outcome) -> NumericValue:
18 | """!
19 | Measure the probability of the given outcome
20 | """
21 | raise NotImplementedError
22 |
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7 | ];
8 |
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/.github/ISSUE_TEMPLATE/bug_report.md:
--------------------------------------------------------------------------------
1 | ---
2 | name: Bug report
3 | about: Create a report to help us improve
4 | title: "[BUG]: XXX problem during the evaluation of YYY"
5 | labels: bug
6 | assignees: ''
7 |
8 | ---
9 |
10 | **Describe the bug**
11 | A clear and concise description of what the bug is.
12 |
13 | **To Reproduce**
14 | Steps to reproduce the behavior:
15 | 1. Go to '...'
16 | 2. Click on '....'
17 | 3. Scroll down to '....'
18 | 4. See error
19 |
20 | **Expected behavior**
21 | A clear and concise description of what you expected to happen.
22 |
23 |
24 | **Python version**
25 | Python language version, 3.6, 3.7, ... etc
26 |
27 | **Additional context**
28 | Add any other context about the problem here.
29 |
--------------------------------------------------------------------------------
/setup.py:
--------------------------------------------------------------------------------
1 | import setuptools
2 |
3 | with open("README.md", "r", encoding="utf-8") as fh:
4 | long_description = fh.read()
5 |
6 | setuptools.setup(
7 | name="pygmodels",
8 | version="0.0.1",
9 | author="D-K-E",
10 | author_email="D-K-E@users.noreply.github.com",
11 | description="Probabilistic Graphical Models in Standard Python",
12 | long_description=long_description,
13 | long_description_content_type="text/markdown",
14 | url="https://github.com/D-K-E/graphical-models",
15 | packages=setuptools.find_packages(),
16 | classifiers=[
17 | "Programming Language :: Python :: 3",
18 | "License :: OSI Approved :: GNU GPL License",
19 | "Operating System :: OS Independent",
20 | ],
21 | python_requires=">=3.6",
22 | )
23 |
--------------------------------------------------------------------------------
/pygmodels/graph/gtype/graphobj.py:
--------------------------------------------------------------------------------
1 | """
2 | object contained in a graph
3 | """
4 | from copy import deepcopy
5 |
6 | from pygmodels.graph.gtype.abstractobj import AbstractGraphObj
7 |
8 |
9 | class GraphObject(AbstractGraphObj):
10 | """!object contained in a graph"""
11 |
12 | def __init__(self, oid: str, odata={}):
13 | """!"""
14 | self.object_id = oid
15 | self.object_data = odata
16 |
17 | def data(self):
18 | """!"""
19 | return self.object_data
20 |
21 | def id(self):
22 | """!"""
23 | return self.object_id
24 |
25 | def copy(self):
26 | return deepcopy(self)
27 |
28 | def clear_data(self):
29 | """!"""
30 | self.object_data.clear()
31 |
32 | def update_data(self, ndata: dict):
33 | """!"""
34 | self.object_data.update(ndata)
35 |
--------------------------------------------------------------------------------
/pygmodels/value/domain.py:
--------------------------------------------------------------------------------
1 | """!
2 | \file domain.py Represents the domain of a function. It can be anything.
3 | """
4 |
5 | from typing import Any, FrozenSet, List, Optional, Set, Tuple
6 |
7 | from pygmodels.value.abstractvalue import AbstractSetValue
8 |
9 |
10 | class DomainValue(AbstractSetValue):
11 | def __init__(self, v: Any, dom_id: Optional[str]):
12 | self.v = v
13 | self._domain = dom_id
14 |
15 | @property
16 | def belongs_to(self):
17 | if self._domain is None:
18 | raise ValueError("Value is not associated to a domain")
19 | return self._domain
20 |
21 | @property
22 | def value(self):
23 | return self.v
24 |
25 |
26 | Domain = Set[DomainValue]
27 | OrderedCodomain = List[DomainValue]
28 |
29 | FiniteDomain = FrozenSet[DomainValue]
30 | OrderedFiniteDomain = Tuple[DomainValue]
31 |
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8 | ['path_301',['path',['../db/d71/namespacegmodels_1_1gtypes_1_1path.html',1,'gmodels::gtypes']]],
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12 | ];
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/pygmodels/value/codomain.py:
--------------------------------------------------------------------------------
1 | """!
2 | \file codomain.py Represents a codomain of a function. Since we are dealing
3 | with probabilities and related concepts the codomain should be a measurable
4 | value
5 | """
6 |
7 | from typing import Any, Callable, Dict, FrozenSet, List, Set, Tuple
8 |
9 | from pygmodels.value.value import SetValue
10 |
11 |
12 | class Outcome:
13 | def __init__(self, v):
14 | self.data = v
15 |
16 |
17 | CodomainValue = SetValue
18 | Codomain = Set[CodomainValue]
19 | OrderedCodomain = List[CodomainValue]
20 |
21 | FiniteCodomain = FrozenSet[CodomainValue]
22 | OrderedFiniteCodomain = Tuple[CodomainValue]
23 |
24 |
25 | class PossibleOutcomes:
26 | """!
27 | \brief set of possible outcomes from Koller, Friedman 2009, p. 15, 20
28 |
29 | This is simply a frozenset. We assume that possible outcomes contained in
30 | this object are measurable.
31 | """
32 |
33 | def __init__(self, omega: FrozenSet[Outcome]):
34 | self.data = omega
35 |
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10 | ];
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/test/test_node.py:
--------------------------------------------------------------------------------
1 | """
2 | Node unit tests
3 | """
4 | import unittest
5 |
6 | from pygmodels.graph.gtype.node import Node
7 |
8 |
9 | class NodeTest(unittest.TestCase):
10 | def setUp(self):
11 | """"""
12 | self.node = Node(node_id="mnode", data={"my": "data"})
13 |
14 | def test_id(self):
15 | """"""
16 | self.assertEqual(self.node.id(), "mnode")
17 |
18 | def test_data(self):
19 | """"""
20 | self.assertEqual(self.node.data(), {"my": "data"})
21 |
22 | def test_equal(self):
23 | self.assertEqual(self.node, Node("mnode", {"my": "data"}))
24 |
25 | def test_str(self):
26 | n1 = Node("mnode", {"my": "data", "is": "awesome"})
27 | mstr = "mnode--my-data::is-awesome"
28 | self.assertEqual(str(n1), mstr)
29 |
30 | def test_hash(self):
31 | mstr = "mnode--my-data::is-awesome"
32 | n1 = Node("mnode", {"my": "data", "is": "awesome"})
33 | self.assertEqual(hash(n1), hash(mstr))
34 |
35 |
36 | if __name__ == "__main__":
37 | unittest.main()
38 |
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/pygmodels/factor/ftype/abstractfactor.py:
--------------------------------------------------------------------------------
1 | # abstract factor type
2 | """!
3 | \file abstractfactor.py Contains abstract class for the factor
4 | """
5 | from abc import ABC, abstractmethod
6 | from typing import Callable, FrozenSet, List, Set, Tuple
7 |
8 | from pygmodels.graph.gtype.abstractobj import AbstractGraphObj
9 | from pygmodels.randvar.rtype.abstractrandvar import AbstractRandomVariable
10 | from pygmodels.value.value import NumericValue, OrderedFiniteVSet
11 |
12 | FactorScope = Set[AbstractRandomVariable]
13 | OrderedSubset = OrderedFiniteVSet
14 | DomainSliceSet = FrozenSet[OrderedSubset]
15 | DomainSubset = DomainSliceSet
16 | FactorDomain = List[DomainSubset]
17 | FactorCartesianProduct = FactorDomain
18 |
19 |
20 | class AbstractFactor(AbstractGraphObj):
21 | """"""
22 |
23 | @abstractmethod
24 | def scope_vars(self, filter_fn: Callable[[FactorScope], Set[FactorScope]]):
25 | """"""
26 | raise NotImplementedError
27 |
28 | @abstractmethod
29 | def partition_value(self, vd: FactorDomain):
30 | """"""
31 | raise NotImplementedError
32 |
33 | @abstractmethod
34 | def phi(self, scope_product: DomainSliceSet):
35 | """"""
36 | raise NotImplementedError
37 |
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6 | ['neighbours_5fof_458',['neighbours_of',['../d2/dfc/classgmodels_1_1gtypes_1_1graph_1_1Graph.html#aa7931cbb1cd0bc28a03ef114c3efbc9d',1,'gmodels::gtypes::graph::Graph']]],
7 | ['node_5fids_459',['node_ids',['../d0/d93/classgmodels_1_1gtypes_1_1edge_1_1Edge.html#a2d6f5a1161e6a3980528ff698c71a06d',1,'gmodels::gtypes::edge::Edge']]],
8 | ['nodes_460',['nodes',['../d2/dfc/classgmodels_1_1gtypes_1_1graph_1_1Graph.html#a14ea9c8ea2ee1f0dd204b21d42308783',1,'gmodels::gtypes::graph::Graph']]],
9 | ['nodes_5fper_5flevel_461',['nodes_per_level',['../d7/db3/classgmodels_1_1gtypes_1_1tree_1_1Tree.html#a484de105cc940f25f197e7ce8b8849d1',1,'gmodels::gtypes::tree::Tree']]],
10 | ['normalize_462',['normalize',['../de/d55/classgmodels_1_1factor_1_1Factor.html#a551761e6454d7b072284ec34c630677f',1,'gmodels::factor::Factor']]]
11 | ];
12 |
--------------------------------------------------------------------------------
/pygmodels/pgm/pgmtype/abstractpgm.py:
--------------------------------------------------------------------------------
1 | """!
2 | Abstract objects, interfaces, for implementing Probabilistic graphical models
3 | """
4 |
5 |
6 | from abc import abstractmethod
7 | from typing import Callable, Dict, FrozenSet, List, Set, Tuple
8 |
9 | from pygmodels.factor.ftype.abstractfactor import AbstractFactor
10 | from pygmodels.gtype.abstractobj import (
11 | AbstractEdge,
12 | AbstractGraph,
13 | AbstractGraphObj,
14 | AbstractNode,
15 | )
16 | from pygmodels.randvar.rtype.abstractrandvar import AbstractRandomVariable
17 | from pygmodels.value.codomain import Outcome
18 | from pygmodels.value.value import NumericValue
19 |
20 |
21 | class AbstractPGM(AbstractGraph):
22 | """!
23 | Abstract probabilistic graphical models
24 | """
25 |
26 | @property
27 | @abstractmethod
28 | def V(self) -> Dict[str, AbstractRandomVariable]:
29 | """!
30 | Acces to node set of PGM
31 | """
32 | raise NotImplementedError
33 |
34 | @property
35 | @abstractmethod
36 | def E(self) -> Dict[str, AbstractEdge]:
37 | """!
38 | Acces to edge set set of PGM
39 | """
40 | raise NotImplementedError
41 |
42 | @property
43 | @abstractmethod
44 | def F(self) -> Dict[str, AbstractFactor]:
45 | """!
46 | Acces to factor set of PGM
47 | """
48 | raise NotImplementedError
49 |
--------------------------------------------------------------------------------
/pygmodels/value/value.py:
--------------------------------------------------------------------------------
1 | """!
2 | \file value.py Represents the value of functions in the case of PGMs
3 | """
4 |
5 | from typing import Callable, FrozenSet, List, Optional, Set, Tuple, Union
6 |
7 | from pygmodels.value.abstractvalue import AbstractSetValue
8 |
9 | NumericValue = float
10 | DiscreteValue = str
11 | BinaryValue = bool
12 |
13 | Value = Union[
14 | NumericValue, DiscreteValue, BinaryValue, set, list, dict, tuple, Callable
15 | ]
16 |
17 |
18 | class SetValue(AbstractSetValue):
19 | "Value contained by a set"
20 |
21 | def __init__(self, v: Optional[Value], set_id: Optional[str] = None):
22 | if v is None:
23 | val = None
24 | elif isinstance(v, Value):
25 | val = v
26 | else:
27 | raise TypeError("the associated value must have type Value")
28 | self.v = val
29 | self._set = set_id
30 |
31 | def belongs_to(self) -> str:
32 | """"""
33 | if self._set is None:
34 | raise ValueError("Value not associated to any set")
35 | return self._set
36 |
37 | def value(self) -> Value:
38 | if self.v is None:
39 | raise ValueError("Value is not associated to any data")
40 | return self.v
41 |
42 |
43 | VSet = Set[SetValue]
44 | OrderedVSet = List[SetValue]
45 |
46 | FiniteVSet = FrozenSet[SetValue]
47 | OrderedFiniteVSet = Tuple[SetValue]
48 |
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/docs/html/search/close.svg:
--------------------------------------------------------------------------------
1 |
2 |
32 |
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/.pre-commit-config.yaml:
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1 | # isort
2 | - repo: https://github.com/asottile/seed-isort-config
3 | rev: v1.9.3
4 | hooks:
5 | - id: seed-isort-config
6 | - repo: https://github.com/pre-commit/mirrors-isort
7 | rev: v4.3.21
8 | hooks:
9 | - id: isort
10 |
11 | # black
12 | - repo: https://github.com/ambv/black
13 | rev: stable
14 | hooks:
15 | - id: black
16 | args: # arguments to configure black
17 | - --line-length=79
18 | - --include='\.pyi?$'
19 |
20 | # these folders wont be formatted by black
21 | - --exclude="""\.git |
22 | \.__pycache__|
23 | \.hg|
24 | \.mypy_cache|
25 | \.tox|
26 | \.venv|
27 | _build|
28 | buck-out|
29 | build|
30 | dist"""
31 |
32 | language_version: python3
33 |
34 |
35 | # flake8
36 | - repo: https://github.com/pre-commit/pre-commit-hooks
37 | rev: v2.3.0
38 | hooks:
39 | - id: flake8
40 | args: # arguments to configure flake8
41 | # making isort line length compatible with black
42 | - "--max-line-length=79"
43 | - "--max-complexity=18"
44 | - "--select=B,C,E,F,W,T4,B9"
45 |
46 | # these are errors that will be ignored by flake8
47 | # check out their meaning here
48 | # https://flake8.pycqa.org/en/latest/user/error-codes.html
49 | - "--ignore=E203,E266,E501,W503,F403,F401,E402,W605"
50 | #- "--ignore=F403,F401,E402"
51 |
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/.github/workflows/python-package.yml:
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1 | # This workflow will install Python dependencies, run tests and lint with a variety of Python versions
2 | # For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
3 |
4 | name: Python package
5 |
6 | on:
7 | push:
8 | branches: [ master ]
9 | pull_request:
10 | branches: [ master ]
11 |
12 | jobs:
13 | build:
14 |
15 | runs-on: ubuntu-latest
16 | strategy:
17 | matrix:
18 | python-version: ["3.7", "3.8", "3.9", "3.10"]
19 |
20 | steps:
21 | - uses: actions/checkout@v2
22 | - name: Set up Python ${{ matrix.python-version }}
23 | uses: actions/setup-python@v2
24 | with:
25 | python-version: ${{ matrix.python-version }}
26 | - name: Install dependencies
27 | run: |
28 | python -m pip install --upgrade pip
29 | python -m pip install flake8 pytest
30 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
31 | - name: Lint with flake8
32 | run: |
33 | # stop the build if there are Python syntax errors or undefined names
34 | flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
35 | # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
36 | flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
37 | - name: Test with pytest
38 | run: |
39 | pytest
40 |
--------------------------------------------------------------------------------
/docs/html/menudata.js:
--------------------------------------------------------------------------------
1 | /*
2 | @licstart The following is the entire license notice for the JavaScript code in this file.
3 |
4 | The MIT License (MIT)
5 |
6 | Copyright (C) 1997-2020 by Dimitri van Heesch
7 |
8 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software
9 | and associated documentation files (the "Software"), to deal in the Software without restriction,
10 | including without limitation the rights to use, copy, modify, merge, publish, distribute,
11 | sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
12 | furnished to do so, subject to the following conditions:
13 |
14 | The above copyright notice and this permission notice shall be included in all copies or
15 | substantial portions of the Software.
16 |
17 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING
18 | BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
19 | NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
20 | DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
22 |
23 | @licend The above is the entire license notice for the JavaScript code in this file
24 | */
25 | var menudata={children:[
26 | {text:"Main Page",url:"index.html"},
27 | {text:"Related Pages",url:"pages.html"}]}
28 |
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/test/test_edge.py:
--------------------------------------------------------------------------------
1 | """!
2 | Edge unit tests
3 | """
4 | import unittest
5 |
6 | from pygmodels.graph.gtype.edge import Edge, EdgeType
7 | from pygmodels.graph.gtype.node import Node
8 |
9 |
10 | class EdgeTest(unittest.TestCase):
11 | """"""
12 |
13 | def setUp(self):
14 | """"""
15 | n1 = Node("m1", {})
16 | n2 = Node("m2", {})
17 | self.dedge = Edge(
18 | edge_id="medge",
19 | start_node=n1,
20 | end_node=n2,
21 | edge_type=EdgeType.DIRECTED,
22 | data={"my": "data"},
23 | )
24 | self.uedge = Edge(
25 | edge_id="uedge",
26 | start_node=n1,
27 | end_node=n2,
28 | edge_type=EdgeType.UNDIRECTED,
29 | data={"my": "data"},
30 | )
31 |
32 | def test_id(self):
33 | """"""
34 | self.assertEqual(self.uedge.id(), "uedge")
35 |
36 | def test_type(self):
37 | """"""
38 | self.assertEqual(self.uedge.type(), EdgeType.UNDIRECTED)
39 |
40 | def test_start(self):
41 | self.assertEqual(self.uedge.start(), Node("m1", {}))
42 |
43 | def test_end(self):
44 | self.assertEqual(self.uedge.end(), Node("m2", {}))
45 |
46 | def test_node_ids(self):
47 | self.assertEqual(self.uedge.node_ids(), set(["m1", "m2"]))
48 |
49 | def test_is_endvertice_true(self):
50 | """"""
51 | positive = self.uedge.is_endvertice(Node("m1", {}))
52 | self.assertEqual(positive, True)
53 |
54 | def test_is_endvertice_false(self):
55 | """"""
56 | negative = self.uedge.is_endvertice(Node("m3", {}))
57 | self.assertEqual(negative, False)
58 |
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