Comparison of Bayesian networks

To compare Bayesian network, one can compare the structure of the BNs (see pyagrum.lib.bn_vs_vb.GraphicalBNComparator). However BNs can also be compared as probability distributions.

class pyagrum.ExactBNdistance(*args)

Class representing exacte computation of divergence and distance between BNs

ExactBNdistance(P,Q) -> ExactBNdistance : Parameters: : - P (pyagrum.BayesNet) a Bayesian network - Q (pyagrum.BayesNet) another Bayesian network to compare with the first one

ExactBNdistance(ebnd) -> ExactBNdistance : Parameters: : - ebnd (pyagrum.ExactBNdistance) the exact BNdistance to copy

• Raises: pyagrum.OperationNotAllowed – If the 2BNs have not the same domain size of compatible node sets

compute()

• Returns: a dictionnary containing the different values after the computation.
• Return type: Dict[str,float]

class pyagrum.GibbsBNdistance(*args)

Class representing a Gibbs-Approximated computation of divergence and distance between BNs

GibbsBNdistance(P,Q) -> GibbsBNdistance : Parameters: : - P (pyagrum.BayesNet) – a Bayesian network - Q (pyagrum.BayesNet) – another Bayesian network to compare with the first one

GibbsBNdistance(gbnd) -> GibbsBNdistance : Parameters: : - gbnd (pyagrum.GibbsBNdistance) – the Gibbs BNdistance to copy

• Raises: pyagrum.OperationNotAllowed – If the 2BNs have not the same domain size of compatible node sets

burnIn()

• Returns: size of burn in on number of iteration
• Return type: int

compute()

• Returns: a dictionnary containing the different values after the computation.
• Return type: Dict[str,float]

continueApproximationScheme(error)

Continue the approximation scheme.

• Parameters: error (float)
• Return type: bool

currentTime()

• Returns: get the current running time in second (float)
• Return type: float

disableEpsilon()

Disable epsilon as a stopping criterion.

• Return type: None

disableMaxIter()

Disable max iterations as a stopping criterion.

• Return type: None

disableMaxTime()

Disable max time as a stopping criterion.

• Return type: None

disableMinEpsilonRate()

Disable a min epsilon rate as a stopping criterion.

• Return type: None

enableEpsilon()

Enable epsilon as a stopping criterion.

• Return type: None

enableMaxIter()

Enable max iterations as a stopping criterion.

• Return type: None

enableMaxTime()

Enable max time as a stopping criterion.

• Return type: None

enableMinEpsilonRate()

Enable a min epsilon rate as a stopping criterion.

• Return type: None

epsilon()

• Returns: the value of epsilon
• Return type: float

history()

• Returns: the scheme history
• Return type: tuple
• Raises: pyagrum.OperationNotAllowed – If the scheme did not performed or if verbosity is set to false

initApproximationScheme()

Initiate the approximation scheme.

• Return type: None

isDrawnAtRandom()

• Returns: True if variables are drawn at random
• Return type: bool

isEnabledEpsilon()

• Returns: True if epsilon is used as a stopping criterion.
• Return type: bool

isEnabledMaxIter()

• Returns: True if max iterations is used as a stopping criterion
• Return type: bool

isEnabledMaxTime()

• Returns: True if max time is used as a stopping criterion
• Return type: bool

isEnabledMinEpsilonRate()

• Returns: True if epsilon rate is used as a stopping criterion
• Return type: bool

maxIter()

• Returns: the criterion on number of iterations
• Return type: int

maxTime()

• Returns: the timeout(in seconds)
• Return type: float

messageApproximationScheme()

• Returns: the approximation scheme message
• Return type: str

minEpsilonRate()

• Returns: the value of the minimal epsilon rate
• Return type: float

nbrDrawnVar()

• Returns: the number of variable drawn at each iteration
• Return type: int

nbrIterations()

• Returns: the number of iterations
• Return type: int

periodSize()

• Returns: the number of samples between 2 stopping
• Return type: int
• Raises: pyagrum.OutOfBounds – If p<1

remainingBurnIn()

• Returns: the number of remaining burn in
• Return type: int

setBurnIn(b)

• Parameters: b (int) – size of burn in on number of iteration
• Return type: None

setDrawnAtRandom(_atRandom)

• Parameters: _atRandom (bool) – indicates if variables should be drawn at random
• Return type: None

setEpsilon(eps)

• Parameters: eps (float) – the epsilon we want to use
• Raises: pyagrum.OutOfBounds – If eps<0
• Return type: None

setMaxIter(max)

• Parameters: max (int) – the maximum number of iteration
• Raises: pyagrum.OutOfBounds – If max <= 1
• Return type: None

setMaxTime(timeout)

• Parameters:
  • tiemout (float) – stopping criterion on timeout (in seconds)
  • timeout (float)
• Raises: pyagrum.OutOfBounds – If timeout<=0.0
• Return type: None

setMinEpsilonRate(rate)

• Parameters: rate (float) – the minimal epsilon rate
• Return type: None

setNbrDrawnVar(_nbr)

• Parameters: _nbr (int) – the number of variables to be drawn at each iteration
• Return type: None

setPeriodSize(p)

• Parameters: p (int) – number of samples between 2 stopping
• Raises: pyagrum.OutOfBounds – If p<1
• Return type: None

setVerbosity(v)

• Parameters: v (bool) – verbosity
• Return type: None

startOfPeriod()

• Returns: True if it is a start of a period
• Return type: bool

stateApproximationScheme()

• Returns: the state of the approximation scheme
• Return type: int

stopApproximationScheme()

Stop the approximation scheme.

• Return type: None

updateApproximationScheme(incr=1)

Update the approximation scheme.

• Parameters: incr (int)
• Return type: None

verbosity()

• Returns: True if the verbosity is enabled
• Return type: bool