Examples of Layer

_api.alienfactory.javamappy.Layer
Represents one of the layers in a {@link Map}. See {@link com.alienfactory.javamappy.viewer.LayerViewer} for details on rendering a Layer to the screen.
@author Steve Eynon
aima.core.learning.neural.Layer
Artificial Intelligence A Modern Approach (3rd Edition): page 729

Feed-forward networks are usually arranged in layers, such that each unit receives input only from units in the immediately preceding layer. @author Ravi Mohan @author Mike Stampone
chunmap.view.layer.Layer
@author chunquedong
cnslab.cnsnetwork.Layer
Data structure for storing a layer of neurons. @author Yi Dong @author David Wallace Croft
com.bbn.openmap.Layer
MPLE handling of the ProjectionListener interface. public void projectionChanged(com.bbn.openmap.event.ProjectionEvent pe) { Projection proj = setProjection(pe); if (proj != null) { // Use the projection to gather OMGraphics in the layer, // and prepare the layer so that in the paint() method, // the OMGraphics get rendered. // Call any methods that kick off work to build graphics // here... // You get the paint() methods called by calling // repaint(): repaint(); } fireStatusUpdate(LayerStatusEvent.FINISH_WORKING); } @see com.bbn.openmap.event.ProjectionListener @see com.bbn.openmap.event.ProjectionEvent @see com.bbn.openmap.PropertyConsumer
com.day.image.Layer
com.emitrom.lienzo.client.core.shape.Layer
Layer is an abstraction for the Canvas element.
- Layers are assigned z-indexes automatically.
- Every Layer contains a {@link SelectionLayer} to act as an off-set canvas.
- Layers may contain {@link IPrimitive} or {@link Group}.
com.ericsson.ssa.sip.Layer
A class that implements the Layer interface can be involved in the invocation chain in the container. Each class that implements the Layer interface has to be a singelton. @author ekrigro
com.extjs.gxt.ui.client.widget.Layer
An extended {@link El} object that supports a shadow and shim, constrain toviewport and automatic maintaining of shadow/shim positions.
com.gi.engine.carto.Layer
com.github.neuralnetworks.architecture.Layer
A layer of neurons. Each layer contains a set of connections that link it to other layers. In that sense every neural network is a graph. This is done for maximum versatility. It makes possible the representation of various architectures - committee of machines or parallel networks to be calculated on different GPU devices.
com.github.tjake.rbm.Layer
Represents a layer in nodes in a Neural network, supports some simple operations
com.google.gwt.layout.client.Layout.Layer
com.google.gwt.maeglin89273.game.mengine.layer.Layer
@author Maeglin Liao
com.greentea.relaxation.jnmf.model.Layer
Class Layer represents the layer of neurons. The feature of layer is that all neurons within it executing at the same time.
com.gwcworld.core.bean.Layer
com.prupe.mcpatcher.hd.FancyDial$Layer
com.prupe.mcpatcher.sky.SkyRenderer$Layer
com.sencha.gxt.core.client.dom.Layer
Wraps a XElement and provides support for shadows and shimming.
com.simplegeo.client.types.Layer
Class that a represents a Layer @author Pranil Kanderi
com.vividsolutions.jtstest.testbuilder.model.Layer
com.vividsolutions.jump.workbench.model.Layer
dwlab.shapes.layers.Layer
Layer is the group of sprites which have bounds. See also #directTo example.
gistoolkit.datasources.webservice.Layer
Represents an available layer in a web service.
gistoolkit.display.Layer
Represents a layer of the rendered map.
gov.nasa.worldwind.layers.Layer
info.textgrid.lab.noteeditor.mei2013.Layer
3.org/2001/XMLSchema}anyType"> <choice maxOccurs="unbounded" minOccurs="0"> <group ref="{http://www.music-encoding.org/ns/mei}model.appLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.divLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.milestoneLike.music"/> <group ref="{http://www.music-encoding.org/ns/mei}model.annotLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.graphicprimitiveLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.editLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.transcriptionLike"/> <group ref="{http://www.music-encoding.org/ns/mei}model.layerPart"/> </choice> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.layer.anl.attributes"/> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.layer.vis.attributes"/> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.declaring.attributes"/> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.facsimile.attributes"/> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.layer.log.attributes"/> <attGroup ref="{http://www.music-encoding.org/ns/mei}att.common.attributes"/> </restriction> </complexContent> </complexType>
ini.trakem2.display.Layer
it.eng.spagobi.engines.geo.map.renderer.Layer
The Class Layer. @author Andrea Gioia (andrea.gioia@eng.it)
k8.wt.Layer
A Layer is an object used to get the available width and height at a defined depth.
org.apache.tuscany.sca.diagram.artifacts.Layer
Structure of a "Outermost layer" : not a SCA artifact
org.bouncycastle.pqc.crypto.rainbow.Layer
i.org/10.1007/11496137_12)
org.codemap.layers.Layer
org.eclipse.draw2d.Layer
org.eclipse.wb.draw2d.Layer
org.encog.neural.networks.layers.Layer
This interface defines all necessary methods for a neural network layer. @author jheaton
org.gdal.ogr.Layer
org.geomajas.layer.Layer
A layer which is is normally used as part of a map. @param < T> type of layer configuration info @author Joachim Van der Auwera @author Jan De Moerloose @since 1.6.0
org.geotools.data.ows.Layer
.org/geotools/branches/2.6.x/modules/extension/wms/src/main/java/org /geotools/data/ows/Layer.java $
org.geotools.geopkg.wps.GeoPackageProcessRequest.Layer
org.geotools.map.Layer
A Layer to be rendered.
Layers usually represent a single dataset; and arranged into a z-order by a Map for display. @source $URL$ @since 2.7 @version 8.0
org.gwtopenmaps.openlayers.client.layer.Layer
@author Erdem Gunay, Amr Alam - Refractions Research, Edwin Commandeur -Atlis EJS @author Nazzareno Sileno - CNR IMAA geoSDI Group - @email nazzareno.sileno@geosdi.org
org.jfree.ui.Layer
Used to indicate either the foreground or background layer. @author David Gilbert
org.joone.engine.Layer
org.jwildfire.create.tina.base.Layer
org.locationtech.udig.project.internal.Layer
Read/Write interface for layers @author Jesse @since 1.0.0 @model
org.neo4j.gis.spatial.Layer
Instances of Layer provide the ability for developers to add/remove and edit geometries associated with a single dataset (or layer). This includes support for several storage mechanisms, like in-node (geometries in properties) and sub-graph (geometries describe by the graph). A Layer can be associated with a dataset. In cases where the dataset contains only one layer, the layer itself is the dataset. See the class DefaultLayer for the standard implementation of that pattern.

org.neuroph.core.Layer

 Layer of neurons in a neural network. The Layer is basic neuron container (a collection of neurons), and it provides methods for manipulating neurons (add, remove, get, set, calculate, randomize).

@see Neuron @author Zoran Sevarac

org.newdawn.slick.tiled.Layer
A layer of tiles on the map @author kevin
org.openstreetmap.josm.gui.layer.Layer
A layer encapsulates the gui component of one dataset and its representation. Some layers may display data directly imported from OSM server. Other only display background images. Some can be edited, some not. Some are static and other changes dynamically (auto-updated). Layers can be visible or not. Most actions the user can do applies only on selected layers. The available actions depend on the selected layers too. All layers are managed by the MapView. They are displayed in a list to the right of the screen. @author imi
org.opentripplanner.api.parameter.Layer
org.qi4j.api.structure.Layer
The Layer represents a single layer in a Qi4j application.
org.timepedia.chronoscope.client.canvas.Layer
Layer is a core Chronoscope drawing abstraction
It is the key immediate-mode render API used for drawing shapes, corresponding very close to the Safari/WHATWG Javascript CANVAS. @author Ray Cromwell <ray@timepedia.org>
org.wicketstuff.openlayers.api.layer.Layer
@author Nino Martinez Wael (nino.martinez@jayway.dk)
org.xhtmlrenderer.layout.Layer
All positioned content as well as content with an overflow value other than visible creates a layer. Layers which define stacking contexts provide the entry for rendering the box tree to an output device. The main purpose of this class is to provide an implementation of Appendix E of the spec, but it also provides additional utility services including page management and mapping boxes to coordinates (for e.g. links). When rendering to a paged output device, the layer is also responsible for laying out absolute content (which is layed out after its containing block has completed layout).
org.zkoss.openlayers.layer.Layer
@author jumperchen
playn.core.Layer
stephencarmody.k8.wt.Layer
tv.floe.metronome.classification.neuralnetworks.core.Layer
zdenekdrahos.AI.NeuralNetwork.Layers.Layer

Examples of org.neuroph.core.Layer


    // set network type
    this.setNetworkType(NeuralNetworkType.MAXNET);


    // createLayer input layer in layer
    Layer inputLayer = LayerFactory.createLayer(neuronsCount,
        new NeuronProperties());
    this.addLayer(inputLayer);


    // createLayer properties for neurons in output layer
    NeuronProperties neuronProperties = new NeuronProperties();

View Full Code Here

Examples of org.neuroph.core.Layer

    double[] weights = flatNetwork.getWeights();


    int index = 0;


    for (int layerIndex = network.getLayers().size() - 1; layerIndex > 0; layerIndex--) {
      Layer layer = network.getLayers().get(layerIndex);


      for (Neuron neuron : layer.getNeurons()) {
        for (Connection connection : neuron.getInputConnections()) {
          if (index >= weights.length)
            throw new EncogEngineError("Weight size mismatch.");


          Weight weight = connection.getWeight();

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Examples of org.neuroph.core.Layer

   * @return True if unflattening was successful.
   */
  public static boolean unFlattenNeuralNetworkNetwork(NeuralNetwork network) {


    for (int layerIndex = network.getLayers().size() - 1; layerIndex > 0; layerIndex--) {
      Layer layer = network.getLayers().get(layerIndex);


      for (Neuron neuron : layer.getNeurons()) {
        for (Connection connection : neuron.getInputConnections()) {
          Weight weight = connection.getWeight();


          if (weight instanceof FlatWeight) {
            Weight weight2 = new Weight(weight.getValue());

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Examples of org.neuroph.core.Layer

    promoLayerIdx = 4,
    outputLayerIdx = 5;


  public RecommenderNetwork() {
        for(int i = 0; i < 6; i++)
            this.addLayer(new Layer());
    //this.createDemoNetwork();
  }

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Examples of org.neuroph.core.Layer

    neuronProperties.setProperty("transferFunction", TransferFunctionType.RAMP);
    // for sigmoid and tanh transfer functions
    neuronProperties.setProperty("transferFunction.slope", new Double(1)); 
    
    // create input layer    
    Layer inputLayer = LayerFactory.createLayer(productsCount,
        neuronProperties);
    this.addLayer(inputLayer);
    createProductLabels(inputLayer);


    
    // create product types layer    
    Layer typeLayer = LayerFactory.createLayer(typesCount,
        neuronProperties);
    createTypeLabels(typeLayer);
    this.addLayer(typeLayer);
    
    
    // create brands layer    
    Layer brandLayer = LayerFactory.createLayer(brandsCount,
        neuronProperties);
    createBrandLabels(brandLayer);
    this.addLayer(brandLayer);  
    
    
    // create price layer    
    Layer priceLayer = LayerFactory.createLayer(priceCount, neuronProperties);
    createPriceLabels(priceLayer);
    this.addLayer(priceLayer);  
    
    // create price layer    
    Layer promoLayer = LayerFactory.createLayer(promoCount, neuronProperties);
    createPromoLabels(promoLayer);
    this.addLayer(promoLayer);    
        
    // create output layer
    Layer outputLayer = LayerFactory.createLayer(productsCount,
        neuronProperties);
    this.addLayer(outputLayer);
    createProductLabels(outputLayer);
    
    createTypeConnections();

View Full Code Here

Examples of org.neuroph.core.Layer

    }


    // creates jets and sharks IAC example
    private void createNetwork() {
        // napraviti elegantni api za kreiranje vise layera NeuralNetwork.createLayers(6); // creates 6 empty layers
        this.addLayer(new Layer());  // Name
        this.addLayer(new Layer());  // Gang
        this.addLayer(new Layer());  // Age
        this.addLayer(new Layer());  // Education
        this.addLayer(new Layer());  // Marital Status
        this.addLayer(new Layer());  // Occupation
        
        this.addLayer(new Layer());  // Associations


        Layer layer = this.getLayerAt(0);
        
        IACNeuron neuron = new IACNeuron();
        neuron.setLabel("Art");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Rick");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Sam");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Ralph");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Lance");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);
        //----------------------------------------------


        layer = this.getLayerAt(1);


        neuron = new IACNeuron();
        neuron.setLabel("Jets");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Sharks");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);


        //----------------------------------------------


        layer = this.getLayerAt(2);


        neuron = new IACNeuron();
        neuron.setLabel("20's");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("30's");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("40's");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);
        
        //----------------------------------------------


        layer = this.getLayerAt(3);


        neuron = new IACNeuron();
        neuron.setLabel("J.H.");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("H.S.");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("College");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);


        //----------------------------------------------


        layer = this.getLayerAt(4);


        neuron = new IACNeuron();
        neuron.setLabel("Single");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Married");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Divorced");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);


        //----------------------------------------------


        layer = this.getLayerAt(5);


        neuron = new IACNeuron();
        neuron.setLabel("Pusher");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Burglar");
        layer.addNeuron(neuron);


        neuron = new IACNeuron();
        neuron.setLabel("Bookie");
        layer.addNeuron(neuron);


        ConnectionFactory.fullConnect(layer, -0.3);


        //----------------------------------------------


        layer = this.getLayerAt(6);


        neuron = new IACNeuron(); // Art     Jets  40's  J.H.  Single     Pusher
        layer.addNeuron(neuron);
        this.createConnection(neuron, this.getLayerAt(0).getNeuronAt(0), 0.1);  // art
        this.createConnection(neuron, this.getLayerAt(1).getNeuronAt(0), 0.1);  // jets
        this.createConnection(neuron, this.getLayerAt(2).getNeuronAt(2), 0.1);  // 40'a
        this.createConnection(neuron, this.getLayerAt(3).getNeuronAt(0), 0.1);  // J.H.
        this.createConnection(neuron, this.getLayerAt(4).getNeuronAt(0), 0.1);  // Single
        this.createConnection(neuron, this.getLayerAt(5).getNeuronAt(0), 0.1);  // Pusher


        this.createConnection(this.getLayerAt(0).getNeuronAt(0), neuron, 0.1);  // art
        this.createConnection(this.getLayerAt(1).getNeuronAt(0), neuron, 0.1);  // jets
        this.createConnection(this.getLayerAt(2).getNeuronAt(2), neuron, 0.1);  // 40'a
        this.createConnection(this.getLayerAt(3).getNeuronAt(0), neuron, 0.1);  // J.H.
        this.createConnection(this.getLayerAt(4).getNeuronAt(0), neuron, 0.1);  // Single
        this.createConnection(this.getLayerAt(5).getNeuronAt(0), neuron, 0.1);  // Pusher




        neuron = new IACNeuron(); // Rick  Sharks  30's  H.S.  Divorced   Burglar
        layer.addNeuron(neuron);
        this.createConnection(neuron, this.getLayerAt(0).getNeuronAt(1), 0.1);  // Rick
        this.createConnection(neuron, this.getLayerAt(1).getNeuronAt(1), 0.1);  // Sharks
        this.createConnection(neuron, this.getLayerAt(2).getNeuronAt(1), 0.1);  // 30'a
        this.createConnection(neuron, this.getLayerAt(3).getNeuronAt(1), 0.1);  // H.S.
        this.createConnection(neuron, this.getLayerAt(4).getNeuronAt(2), 0.1);  // Divorced
        this.createConnection(neuron, this.getLayerAt(5).getNeuronAt(1), 0.1);  // Burglar


        this.createConnection(this.getLayerAt(0).getNeuronAt(1), neuron, 0.1);  // Rick
        this.createConnection(this.getLayerAt(1).getNeuronAt(1), neuron, 0.1);  // Sharks
        this.createConnection(this.getLayerAt(2).getNeuronAt(1), neuron, 0.1);  // 30'a
        this.createConnection(this.getLayerAt(3).getNeuronAt(1), neuron, 0.1);  // H.S.
        this.createConnection(this.getLayerAt(4).getNeuronAt(2), neuron, 0.1);  // Divorced
        this.createConnection(this.getLayerAt(5).getNeuronAt(1), neuron, 0.1);  // Burglar


        neuron = new IACNeuron(); // Sam     Jets  20's  College  Single     Bookie
        layer.addNeuron(neuron);
        this.createConnection(neuron, this.getLayerAt(0).getNeuronAt(2), 0.1);  // Sam
        this.createConnection(neuron, this.getLayerAt(1).getNeuronAt(0), 0.1);  // Jets
        this.createConnection(neuron, this.getLayerAt(2).getNeuronAt(0), 0.1);  // 20's
        this.createConnection(neuron, this.getLayerAt(3).getNeuronAt(2), 0.1);  // College
        this.createConnection(neuron, this.getLayerAt(4).getNeuronAt(0), 0.1);  // Single
        this.createConnection(neuron, this.getLayerAt(5).getNeuronAt(2), 0.1);  // Bookie


        this.createConnection(this.getLayerAt(0).getNeuronAt(2), neuron, 0.1);  // Sam
        this.createConnection(this.getLayerAt(1).getNeuronAt(0), neuron, 0.1);  // Jets
        this.createConnection(this.getLayerAt(2).getNeuronAt(0), neuron, 0.1);  // 20's
        this.createConnection(this.getLayerAt(3).getNeuronAt(2), neuron, 0.1);  // College
        this.createConnection(this.getLayerAt(4).getNeuronAt(0), neuron, 0.1);  // Single
        this.createConnection(this.getLayerAt(5).getNeuronAt(2), neuron, 0.1);  // Bookie


        neuron = new IACNeuron(); // Ralph  Jets  30's  J.H.  Single     Pusher
        layer.addNeuron(neuron);
        this.createConnection(neuron, this.getLayerAt(0).getNeuronAt(3), 0.1);  // Ralph
        this.createConnection(neuron, this.getLayerAt(1).getNeuronAt(0), 0.1);  // Jets
        this.createConnection(neuron, this.getLayerAt(2).getNeuronAt(1), 0.1);  // 30's
        this.createConnection(neuron, this.getLayerAt(3).getNeuronAt(0), 0.1);  // J.H.
        this.createConnection(neuron, this.getLayerAt(4).getNeuronAt(0), 0.1);  // Single
        this.createConnection(neuron, this.getLayerAt(5).getNeuronAt(0), 0.1);  // Pusher


        this.createConnection(this.getLayerAt(0).getNeuronAt(3), neuron, 0.1);  // Ralph
        this.createConnection(this.getLayerAt(1).getNeuronAt(0), neuron, 0.1);  // Jets
        this.createConnection(this.getLayerAt(2).getNeuronAt(1), neuron, 0.1);  // 30's
        this.createConnection(this.getLayerAt(3).getNeuronAt(0), neuron, 0.1);  // J.H.
        this.createConnection(this.getLayerAt(4).getNeuronAt(0), neuron, 0.1);  // Single
        this.createConnection(this.getLayerAt(5).getNeuronAt(0), neuron, 0.1);  // Pusher


        neuron = new IACNeuron(); // Lance  Jets  20's  J.H.  Married    Burglar
        layer.addNeuron(neuron);
        this.createConnection(neuron, this.getLayerAt(0).getNeuronAt(4), 0.1);  // Lance
        this.createConnection(neuron, this.getLayerAt(1).getNeuronAt(0), 0.1);  // Jets
        this.createConnection(neuron, this.getLayerAt(2).getNeuronAt(0), 0.1);  // 20's
        this.createConnection(neuron, this.getLayerAt(3).getNeuronAt(0), 0.1);  // J.H.
        this.createConnection(neuron, this.getLayerAt(4).getNeuronAt(1), 0.1);  // Married

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Examples of org.neuroph.core.Layer

   * Sets default input and output neurons for network (first layer as input,
   * last as output)
   */
  public static void setDefaultIO(NeuralNetwork nnet) {
                ArrayList<Neuron> inputNeurons = new ArrayList<Neuron>();
                Layer firstLayer = (Layer) nnet.getLayers().get(0);
                for (Neuron neuron : firstLayer.getNeurons() ) {
                    if (!(neuron instanceof BiasNeuron)) {  // dont set input to bias neurons
                        inputNeurons.add(neuron);
                    }
                }

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Examples of org.neuroph.core.Layer

    // init neuron settings for input layer
    NeuronProperties inputNeuronProperties = new NeuronProperties();
       inputNeuronProperties.setProperty("transferFunction", TransferFunctionType.LINEAR);


    // create input layer
    Layer inputLayer = LayerFactory.createLayer(inputNeuronsCount, inputNeuronProperties);
    this.addLayer(inputLayer);


    NeuronProperties outputNeuronProperties = new NeuronProperties();
    outputNeuronProperties.setProperty("neuronType", ThresholdNeuron.class);
    outputNeuronProperties.setProperty("thresh", new Double(Math.abs(Math.random())));
    outputNeuronProperties.setProperty("transferFunction", transferFunctionType);
    // for sigmoid and tanh transfer functions set slope propery
    outputNeuronProperties.setProperty("transferFunction.slope", new Double(1));


    // createLayer output layer
    Layer outputLayer = LayerFactory.createLayer(outputNeuronsCount, outputNeuronProperties);
    this.addLayer(outputLayer);


    // create full conectivity between input and output layer
    ConnectionFactory.fullConnect(inputLayer, outputLayer);

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Examples of org.newdawn.slick.tiled.Layer

  @Override
  public void render(int x, int y, int sx, int sy, int width, int height,
      boolean lineByLine) {
    for (int ty = 0; ty < height; ty++) {
      for (int i = 0; i < layers.size(); i++) {
        Layer layer = (Layer) layers.get(i);
        if (!m_isCurrent) {
          layer.render(x, y, sx, sy, width, ty, lineByLine,
              tileWidth, tileHeight);
        } else if (!layer.name.equalsIgnoreCase("WalkBehind")) {
          layer.render(x, y, sx, sy, width, ty, lineByLine,
              tileWidth, tileHeight);
        }
      }
    }
  }

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Examples of org.openstreetmap.josm.gui.layer.Layer

            }
        } else if (klass.isAssignableFrom(GpxLayer.class)) {
            if (!Main.isDisplayingMapView())
                return null;
            boolean merge = Main.pref.getBoolean("download.gps.mergeWithLocal", false);
            Layer active = Main.map.mapView.getActiveLayer();
            if (active instanceof GpxLayer && (merge || ((GpxLayer) active).data.fromServer))
                return ((GpxLayer) active).data.getDataSourceBounds();
            for (GpxLayer l : Main.map.mapView.getLayersOfType(GpxLayer.class)) {
                if (merge || l.data.fromServer)
                    return l.data.getDataSourceBounds();

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