Undirected Graphical Model

class pyAgrum.MarkovRandomField(*args)

MarkovRandomField represents a Markov random field.

MarkovRandomField(name=’’) -> MarkovRandomField
Parameters:
  • name (str) – the name of the Bayes Net

MarkovRandomField(source) -> MarkovRandomField
Parameters:
  • source (pyAgrum.MarkovRandomField) – the Markov random field to copy

add(*args)

Add a variable to the pyAgrum.MarkovRandomField.

Parameters:
  • variable (pyAgrum.DiscreteVariable) – the variable added

  • name (str) – the variable name

  • nbrmod (int) – the number of modalities for the new variable

  • id (int) – the variable forced id in the pyAgrum.MarkovRandomField

Returns:

the id of the new node

Return type:

int

Raises:
addFactor(*args)

Add a factor from a list or a set of id or str. If the argument is a set, the order is the order of the IDs of the variables

Parameters:

seq (sequence (list or set) of int or string) – The sequence (ordered or not) of node id or names

Return type:

Potential

addStructureListener(whenNodeAdded=None, whenNodeDeleted=None, whenEdgeAdded=None, whenedgeDeleted=None)

Add the listeners in parameters to the list of existing ones.

Parameters:
  • whenNodeAdded (lambda expression) – a function for when a node is added

  • whenNodeDeleted (lambda expression) – a function for when a node is removed

  • whenEdgeAdded (lambda expression) – a function for when an edge is added

  • whenEdgeDeleted (lambda expression) – a function for when an edge is removed

addVariables(listFastVariables, default_nbr_mod=2)

Add a list of variable in the form of ‘fast’ syntax.

Parameters:
  • listFastVariables (List[str]) – the list of variables in ‘fast’ syntax.

  • default_nbr_mod (int) – the number of modalities for the variable if not specified following fast syntax. Note that default_nbr_mod=1 is mandatory to create variables with only one modality (for utility for instance).

Returns:

the list of created ids.

Return type:

List[int]

adjacencyMatrix()

adjacency matrix from a graph/graphical models

Compute the adjacency matrix of a pyAgrum’s graph or graphical models (more generally an object that has nodes, children/parents or neighbours methods)

Returns:

adjacency matrix (as numpy.ndarray) with nodeId as key.

Return type:

numpy.ndarray

beginTopologyTransformation()
Return type:

None

changeVariableLabel(*args)

change the label of the variable associated to nodeId to the new value.

Parameters:
  • var (Union[int,str]) – a variable’s id (int) or name

  • old_label (str) – the old label

  • new_label (str) – the new label

Raises:

pyAgrum.NotFound – if id/name is not a variable or if old_label does not exist.

Return type:

None

changeVariableName(*args)

Changes a variable’s name in the pyAgrum.MarkovRandomField.

This will change the “pyAgrum.DiscreteVariable” names in the pyAgrum.MarkovRandomField.

Parameters:
  • car (Union[int,str]) – a variable’s id (int) or name

  • new_name (str) – the new name of the variable

Raises:
Return type:

None

clear()

Clear the whole MarkovRandomField

Return type:

None

completeInstantiation()

Give an instantiation over all the variables of the model

Returns:

a complete Instantiation for the model

Return type:

pyAgrum.Instantiation

connectedComponents()

connected components from a graph/graphical models

Compute the connected components of a pyAgrum’s graph or graphical models (more generally an object that has nodes, children/parents or neighbours methods)

The firstly visited node for each component is called a ‘root’ and is used as a key for the component. This root has been arbitrarily chosen during the algorithm.

Returns:

dict of connected components (as set of nodeIds (int)) with a nodeId (root) of each component as key.

Return type:

dict(int,Set[int])

dim()
Return type:

int

edges()
Return type:

object

empty()

Check if there are some variables in the model.

Returns:

True if there is no variable in the model.

Return type:

bool

endTopologyTransformation()

Terminates a sequence of insertions/deletions of arcs by adjusting all CPTs dimensions. End Multiple Change for all CPTs.

Return type:

pyAgrum.MarkovRandomField

erase(*args)

Remove a variable from the pyAgrum.MarkovRandomField.

Removes the corresponding variable from the pyAgrum.MarkovRandomField and from all of it’s children pyAgrum.Potential.

If no variable matches the given id, then nothing is done.

Parameters:

var (Union[int,str,pyAgrum.DiscreteVariable]) – a variable’s id (int) or name of variable or a reference of this variable to remove.

Return type:

None

eraseFactor(*args)
Return type:

None

exists(*args)

Check if a node with this name or id exists

Parameters:

norid (str|int) – name or id of the searched node

Returns:

True if there is a node with such a name or id

Return type:

bool

existsEdge(*args)
Return type:

bool

factor(*args)

Returns the factor of a set of variables (if existing).

Parameters:

vars (Union[Set[int],Set[str]]) – A set of ids or names of variable the pyAgrum.MarkovRandomField.

Returns:

The factor of the set of nodes.

Return type:

pyAgrum.Potential

Raises:

pyAgrum.NotFound – If no variable’s id matches varId.

factors()
Return type:

List[Set[int]]

family(*args)
Return type:

List[int]

static fastPrototype(*args)
Create a Markov random field with a modified dot-like syntax which specifies:
  • the structure a-b-c;b-d-e;. The substring a-b-c indicates a factor with the scope (a,b,c).

  • the type of the variables with different syntax (cf documentation).

Examples

>>> import pyAgrum as gum
>>> bn=pyAgrum.MarkovRandomField.fastPrototype('A--B[1,3]-C{yes|No}--D[2,4]--E[1,2.5,3.9]',6)
Parameters:
  • dotlike (str) – the string containing the specification

  • domainSize (int or str) – the default domain size or the default domain for variables

Returns:

the resulting Markov random field

Return type:

pyAgrum.MarkovRandomField

static fromBN(bn)
Parameters:

bn (BayesNet)

Return type:

MarkovRandomField

generateFactor(vars)

Randomly generate factor parameters for a given factor in a given structure.

Parameters:
  • node (Union[int,str]) – a variable’s id (int) or name

  • vars (List[int])

Return type:

None

generateFactors()

Randomly generates factors parameters for a given structure.

Return type:

None

graph()
Return type:

UndiGraph

hasSameStructure(other)
idFromName(name)
Parameters:

name (str)

Return type:

int

ids(names)

List of ids for a list of names of variables in the model

Parameters:
  • lov (List[str]) – List of variable names

  • names (List[str])

Returns:

The ids for the list of names of the graph variables

Return type:

List[int]

isIndependent(*args)

check if nodes X and nodes Y are independent given nodes Z

Parameters:
  • X (str|intList[str|int]) – a list of of nodeIds or names

  • Y (str|intList[str|int]) – a list of of nodeIds or names

  • Z (str|intList[str|int]) – a list of of nodeIds or names

Raises:

InvalidArgument – if X and Y share variables

Returns:

True if X and Y are independent given Z in the model

Return type:

bool

loadUAI(*args)

Load an UAI file.

Parameters:
  • name (str) – the name’s file

  • l (list) – list of functions to execute

Raises:
Return type:

str

log10DomainSize()

returns the log10 of the domain size of the model defined as the product of the domain sizes of the variables in the model.

Returns:

the log10 domain size.

Return type:

float

maxNonOneParam()
Return type:

float

maxParam()
Return type:

float

maxVarDomainSize()
Return type:

int

minNonZeroParam()
Return type:

float

minParam()
Return type:

float

minimalCondSet(*args)
Return type:

object

names()

Set of names of variables in the model

Returns:

The names of the graph variables

Return type:

Set[str]

neighbours(norid)
Parameters:

norid (object)

Return type:

object

nodeId(var)
Parameters:

var (DiscreteVariable)

Return type:

int

nodes()
Return type:

object

nodeset(names)

Set of ids for a list of names of variables in the model

Parameters:
  • lov (List[str]) – List of variable names

  • names (List[str])

Returns:

The set of ids for the list of names of the graph variables

Return type:

Set[int]

properties()
Return type:

List[str]

saveUAI(name)

Save the MarkovRandomField in an UAI file.

Parameters:

name (str) – the file’s name

Return type:

None

size()
Return type:

int

sizeEdges()
Return type:

int

smallestFactorFromNode(node)
Parameters:

node (int)

Return type:

List[int]

property thisown

The membership flag

toDot()
Return type:

str

toDotAsFactorGraph()
Return type:

str

variable(*args)
Return type:

DiscreteVariable

variableFromName(name)
Parameters:

name (str)

Return type:

DiscreteVariable

variableNodeMap()