ModelPackage (magpie API)

java.lang.Object
- magpie.user.server.ModelPackage

public class ModelPackage
extends java.lang.Object

Holds information about a model.

Field Summary

Fields
Modifier and Type	Field and Description
`java.lang.String`	`Author` Author of this model
`protected Dataset`	`Dataset` Dataset used to generate attributes
`java.lang.String`	`Description` Short description of this model
`protected java.lang.Integer`	`MaxNumEntries` Maximum mumber of entries to run, overrules ServerLauncher.MaxNumEntries
`protected BaseModel`	`Model` Model to be evaluated
`java.lang.String`	`ModelCitation` Citation for this model
`java.lang.String`	`Notes` Long form description of model
`protected java.util.concurrent.atomic.AtomicLong`	`NumberEvaluated` Number of entries evaluated
`protected java.util.concurrent.atomic.AtomicLong`	`NumberRuns` How many times this model has been run
`java.lang.String`	`Property` Name of property being modeled.
`protected java.util.concurrent.atomic.AtomicLong`	`RunTime` How long this model has been run for, in milliseconds
`java.lang.String`	`TrainingSet` Training set description
`protected java.lang.String`	`Units` Units for property

Constructor Summary

Constructors
Constructor and Description

ModelPackage(Dataset data, BaseModel model)
Initialize model package

Constructors
Constructor and Description
`ModelPackage(Dataset data, BaseModel model)` Initialize model package

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`datasetMatches(Dataset toCheckAgainst)` Check whether the dataset type is the same as a provided type.
`Dataset`	`getDatasetCopy()` Get a copy of the dataset
`int`	`getMaxNumEntries()` Get the maximum number of entries this model is allowed to run.
`long`	`getNumberEntriesEvaluated()`
`long`	`getNumberRuns()`
`java.lang.String[]`	`getPossibleClasses()` Get the names of classes for a classification model
`long`	`getRunTime()`
`java.lang.String`	`getUnits()` Get the units for the model (regression), or the possible classes (classification)
`boolean`	`isClassifer()` Get whether model is a classification model
`boolean`	`modelSupports(Dataset toCheckAgainst)` Check whether dataset is a superclass of a certain class.
`void`	`runModel(Dataset data)` Run the model stored in this package.
`void`	`setUnits(java.lang.String units)`
`org.json.JSONObject`	`toJSON()` Render the model information as a JSON file
`void`	`writeDataset(java.io.OutputStream output)` Write the dataset out via serialization
`void`	`writeModel(java.io.OutputStream output)` Write the model out via serialization

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

- Field Detail
  - Dataset
```
protected final Dataset Dataset
```
    Dataset used to generate attributes
  - Model
```
protected final BaseModel Model
```
    Model to be evaluated
  - Property
```
public java.lang.String Property
```
    Name of property being modeled. HTML format suggested
  - TrainingSet
```
public java.lang.String TrainingSet
```
    Training set description
  - Author
```
public java.lang.String Author
```
    Author of this model
  - ModelCitation
```
public java.lang.String ModelCitation
```
    Citation for this model
  - Description
```
public java.lang.String Description
```
    Short description of this model
  - Notes
```
public java.lang.String Notes
```
    Long form description of model
  - Units
```
protected java.lang.String Units
```
    Units for property
  - NumberRuns
```
protected java.util.concurrent.atomic.AtomicLong NumberRuns
```
    How many times this model has been run
  - NumberEvaluated
```
protected java.util.concurrent.atomic.AtomicLong NumberEvaluated
```
    Number of entries evaluated
  - RunTime
```
protected java.util.concurrent.atomic.AtomicLong RunTime
```
    How long this model has been run for, in milliseconds
  - MaxNumEntries
```
protected java.lang.Integer MaxNumEntries
```
    Maximum mumber of entries to run, overrules ServerLauncher.MaxNumEntries
- Constructor Detail
  - ModelPackage
```
public ModelPackage(Dataset data,
                    BaseModel model)
```
    Initialize model package
    
    Parameters:
    
    data - Dataset used to generate attributes
    
    model - Model to be evaluated
- Method Detail
  - getNumberRuns
```
public long getNumberRuns()
```
    Returns:
    
    Number of times model has been run
  - getNumberEntriesEvaluated
```
public long getNumberEntriesEvaluated()
```
    Returns:
    
    Number of entries that were evaluated
  - getRunTime
```
public long getRunTime()
```
    Returns:
    
    Milliseconds Magpie has spent evalauting this model
  - isClassifer
```
public boolean isClassifer()
```
    Get whether model is a classification model
    
    Returns:
  - getUnits
```
public java.lang.String getUnits()
```
    Get the units for the model (regression), or the possible classes (classification)
    
    Returns:
    
    Model units or classes
  - setUnits
```
public void setUnits(java.lang.String units)
```
  - getPossibleClasses
```
public java.lang.String[] getPossibleClasses()
```
    Get the names of classes for a classification model
    
    Returns:
    
    Possible classes
  - getMaxNumEntries
```
public int getMaxNumEntries()
```
    Get the maximum number of entries this model is allowed to run.
    
    Returns:
    
    Maximum for this model, if defined, or the global maximum
  - runModel
```
public void runModel(Dataset data)
              throws java.lang.Exception
```
    Run the model stored in this package.
    Synchronized because some ML algorithms (e.g., ANNs in Weka) do not handle concurrent execution
    
    Parameters:
    
    data - Dataset to be run, attributes will also be computed
    
    Throws:
    
    java.lang.Exception
  - getDatasetCopy
```
public Dataset getDatasetCopy()
```
    Get a copy of the dataset
    
    Returns:
    
    Clone of dataset
  - writeDataset
```
public void writeDataset(java.io.OutputStream output)
                  throws java.io.IOException
```
    Write the dataset out via serialization
    
    Parameters:
    
    output - Output stream
    
    Throws:
    
    java.io.IOException
  - writeModel
```
public void writeModel(java.io.OutputStream output)
                throws java.io.IOException
```
    Write the model out via serialization
    
    Parameters:
    
    output - Output stream
    
    Throws:
    
    java.io.IOException
  - modelSupports
```
public boolean modelSupports(Dataset toCheckAgainst)
```
    Check whether dataset is a superclass of a certain class.
    
    You can use this to check whether the model supports data of a certain type. For example, a CrystalStructureDataset is a subclass of CompositionDataset so entries supported the CrystalStructureDataset are also valid entires for a CompositionDataset
    
    Parameters:
    
    toCheckAgainst - Dataset type to check against
    
    Returns:
    
    Whether this model is compatible with data stored in that object
  - datasetMatches
```
public boolean datasetMatches(Dataset toCheckAgainst)
```
    Check whether the dataset type is the same as a provided type.
    
    Parameters:
    
    toCheckAgainst - Dataset type to check against
    
    Returns:
    
    Whether the type of dataset are the same
  - toJSON
```
public org.json.JSONObject toJSON()
```
    Render the model information as a JSON file
    
    Returns:
    
    JSON object holding various data about the model

Class ModelPackage

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

Dataset

Model

Property

TrainingSet

Author

ModelCitation

Description

Notes

Units

NumberRuns

NumberEvaluated

RunTime

MaxNumEntries

Constructor Detail

ModelPackage

Method Detail

getNumberRuns

getNumberEntriesEvaluated

getRunTime

isClassifer

getUnits

setUnits

getPossibleClasses

getMaxNumEntries

runModel

getDatasetCopy

writeDataset

writeModel

modelSupports

datasetMatches

toJSON