public class BayesianNetworkDiffSMParameterSet extends SequenceScoringParameterSet
BayesianNetworkDiffSM
. This
class fulfills the requirements of a SequenceScoringParameterSet
and
can be used to create a new BayesianNetworkDiffSM
.ParameterSet.ParameterList
alphabet, length
errorMessage, parameters, parent
Constructor and Description |
---|
BayesianNetworkDiffSMParameterSet()
Creates a new
BayesianNetworkDiffSMParameterSet with
empty parameter values. |
BayesianNetworkDiffSMParameterSet(AlphabetContainer alphabet,
int length,
double ess,
boolean plugInParameters,
Measure structureMeasure)
Creates a new
BayesianNetworkDiffSMParameterSet with
pre-defined parameter values. |
BayesianNetworkDiffSMParameterSet(StringBuffer representation)
Creates a new
BayesianNetworkDiffSMParameterSet from its
XML representation as defined by the Storable
interface. |
Modifier and Type | Method and Description |
---|---|
double |
getEss()
Returns the equivalent samples size (ess) defined in this set of
parameters.
|
String |
getInstanceComment()
Returns a comment (a textual description) of the class that can be
constructed using this
ParameterSet . |
String |
getInstanceName()
Returns the name of an instance of the class that can be constructed
using this
ParameterSet . |
Measure |
getMeasure()
Returns the structure
Measure defined by this set of parameters. |
boolean |
getPlugInParameters()
Returns true if plug-in parameters shall be used when creating a
BayesianNetworkDiffSM from this set of parameters. |
clone, equals, fromXML, getAlphabetContainer, getLength, getNumberOfParameters, getParameterAt, hasDefaultOrIsSet, reset, toXML
getInstance, getInstanceClass
fromGalaxy, getAllParameterNames, getComment, getComment, getErrorMessage, getIndex, getName, getName, getParameterForName, getParent, initParameterList, initParameterList, isAtomic, isComparable, parametersLoaded, setParent, toGalaxy
public BayesianNetworkDiffSMParameterSet(AlphabetContainer alphabet, int length, double ess, boolean plugInParameters, Measure structureMeasure) throws Exception
BayesianNetworkDiffSMParameterSet
with
pre-defined parameter values.alphabet
- the alphabet of the scoring function boxed in an
AlphabetContainer
, e.g
new AlphabetContainer(new DNAAlphabet())
length
- the length of the scoring function, i.e. the length of the
sequences this scoring function can handleess
- the equivalent sample sizeplugInParameters
- indicates if plug-in parameters, i.e. generative (MAP)
parameters, shall be used upon initializationstructureMeasure
- the Measure
used for the structure, e.g.
InhomogeneousMarkov
Exception
- if the alphabet or the length are not in the expected range
of valuespublic BayesianNetworkDiffSMParameterSet() throws Exception
BayesianNetworkDiffSMParameterSet
with
empty parameter values.Exception
- if the parameter for the structure measures could not be createdpublic BayesianNetworkDiffSMParameterSet(StringBuffer representation) throws NonParsableException
BayesianNetworkDiffSMParameterSet
from its
XML representation as defined by the Storable
interface.representation
- the XML code as StringBuffer
NonParsableException
- is thrown if the XML representation could not be parsedpublic double getEss()
public boolean getPlugInParameters()
BayesianNetworkDiffSM
from this set of parameters.public Measure getMeasure() throws ParameterSetParser.NotInstantiableException
Measure
defined by this set of parameters.Measure
ParameterSetParser.NotInstantiableException
- if the Measure
could not be created from its own
InstanceParameterSet
public String getInstanceComment()
InstanceParameterSet
ParameterSet
.getInstanceComment
in class InstanceParameterSet
public String getInstanceName()
InstanceParameterSet
ParameterSet
.getInstanceName
in class InstanceParameterSet