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## de.jstacs.models.discrete.inhomogeneous
Class InhomogeneousDGM

    java.lang.Object
      de.jstacs.models.AbstractModel
          de.jstacs.models.discrete.DiscreteGraphicalModel
              de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM

All Implemented Interfaces:
  InstantiableFromParameterSet, Model, Storable, Cloneable

Direct Known Subclasses:
  DAGModel

    public abstract class InhomogeneousDGM

extends DiscreteGraphicalModel

This class is the main class for all inhomogeneous discrete graphical models (IDGM).

Author:
  Jens Keilwagen
See Also:
  `IDGMParameterSet`

Field Summary
`protected static OutputStream` | `DEFAULT_STREAM` The default OutputStream
`protected SafeOutputStream` | `sostream` This stream is used for comments, ... while the training, ... .

Fields inherited from class de.jstacs.models.discrete.DiscreteGraphicalModel
`params, trained`

Fields inherited from class de.jstacs.models.AbstractModel
`alphabets, length`

Constructor Summary
`InhomogeneousDGM(IDGMParameterSet params)` The default constructor.
`InhomogeneousDGM(StringBuffer representation)` This is the constructor for `Storable`.

Method Summary
`protected void` | `check(Sequence sequence, int startpos, int endpos)` Checks some conditions on a sequence.
`InhomogeneousDGM` | `clone()` Follows the conventions of `Object`'s clone-method.
`abstract String` | `getStructure()` Returns a string representation of the graph.
`protected void` | `set(DGMParameterSet parameter, boolean trained)` Sets the parameters as internal parameters and does some essential computations.
`void` | `setOutputStream(OutputStream stream)` Sets the output stream for the model.

Methods inherited from class de.jstacs.models.discrete.DiscreteGraphicalModel
`fromXML, getCurrentParameterSet, getDescription, getESS, getFurtherModelInfos, getXMLTag, isTrained, setFurtherModelInfos, toString, toXML`

Methods inherited from class de.jstacs.models.AbstractModel
`emitSample, getAlphabetContainer, getCharacteristics, getLength, getLogProbFor, getLogProbFor, getLogProbFor, getLogProbFor, getLogProbFor, getMaximalMarkovOrder, getPriorTerm, getProbFor, getProbFor, set, setNewAlphabetContainerInstance, train`

Methods inherited from class java.lang.Object
`equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Methods inherited from interface de.jstacs.models.Model
`getInstanceName, getLogPriorTerm, getNumericalCharacteristics, getProbFor, train`

Field Detail

### sostream

    protected SafeOutputStream sostream

  This stream is used for comments, ... while the training, ... .

### DEFAULT_STREAM

    protected static final OutputStream DEFAULT_STREAM

  The default OutputStream

Constructor Detail

### InhomogeneousDGM

    public InhomogeneousDGM(IDGMParameterSet params)
                     throws CloneNotSupportedException,
                            IllegalArgumentException,
                            NonParsableException

  The default constructor.

  Parameters:
    `params` - the parameter set
  Throws:
    `CloneNotSupportedException` - if the parameter set could not be cloned
    `IllegalArgumentException` - if the parameter set is not instantiated
    `NonParsableException` - if the parameter set is not parsable

### InhomogeneousDGM

    public InhomogeneousDGM(StringBuffer representation)
                     throws NonParsableException

  This is the constructor for `Storable`.

  Parameters:
    `representation` - the xml representation
  Throws:
    `NonParsableException` - if the representation could not be parsed.

Method Detail

### clone

    public InhomogeneousDGM clone()
                           throws CloneNotSupportedException

  Description copied from class: `AbstractModel`
  Follows the conventions of `Object`'s clone-method.

  Specified by:
    `clone` in interface `Model`
  Overrides:
    `clone` in class `DiscreteGraphicalModel`
  Returns:
    an object, that is a copy of the current `AbstractModel` (the member-`AlphabetContainer` isn't deeply cloned since it is assumed to be immutable). The type of the returned object is defined by the class `X` directly inherited from `AbstractModel`. Hence `X`'s clone-method should work as:
    1. `Object o = (X)super.clone();` 2. all additional member variables of `o` defined by `X` that are not of simple data-types like int, double, ... , have to be deeply copied 3. `return o`
  Throws:
    `CloneNotSupportedException`

### getStructure

    public abstract String getStructure()
                                 throws NotTrainedException

  Returns a string representation of the graph.

  Returns:
    a string representation of the graph
  Throws:
    `NotTrainedException` - if the structure is not set, this can only be the case if the model is not trained

### setOutputStream

    public void setOutputStream(OutputStream stream)

  Sets the output stream for the model. This stream will sometimes be used to write some information about the training/progress/...

  Parameters:
    `stream` - the output stream

### check

    protected void check(Sequence sequence,
                         int startpos,
                         int endpos)
                  throws NotTrainedException,
                         IllegalArgumentException

  Description copied from class: `DiscreteGraphicalModel`
  Checks some conditions on a sequence.

  Overrides:
    `check` in class `DiscreteGraphicalModel`
  Parameters:
    `sequence` - the sequence
    `startpos` - the startposition
    `endpos` - the endposition
  Throws:
    `NotTrainedException` - if the model is not trained
    `IllegalArgumentException` - if some constraints are not fulfilled

### set

    protected void set(DGMParameterSet parameter,
                       boolean trained)
                throws CloneNotSupportedException,
                       NonParsableException

  Description copied from class: `DiscreteGraphicalModel`
  Sets the parameters as internal parameters and does some essential computations. Used in fromParameterSet-methods.

  Overrides:
    `set` in class `DiscreteGraphicalModel`
  Parameters:
    `parameter` - the new ParameterSet
    `trained` - the indicator for the model
  Throws:
    `CloneNotSupportedException` - if the parmeterSet could not be cloned
    `NonParsableException` - if the parameters of the model could not be parsed

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