List of removeLayer() Examples

Examples of removeLayer()

com.bbn.openmap.layer.BufferedLayer.removeLayer()
Remove the layer from group.
com.github.neuralnetworks.architecture.NeuralNetworkImpl.removeLayer()
Remove layer from the network @param layer
com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()
de.yaams.extensions.basemap.tiled.core.Map.removeLayer()
Calls super method, and additionally fires a {@link MapChangedEvent}. @see MultilayerPlane#removeLayer(int)
org.geotools.map.MapContent.removeLayer()
Removes the given layer, if present, and publishes a {@linkplain MapLayerListEvent}. @param layer the layer to be removed @return {@code true} if the layer was removed
org.jfree.chart.plot.dial.DialPlot.removeLayer()
Removes the layer at the specified index and sends a {@link PlotChangeEvent} to all registered listeners. @param index the index.
tiled.core.Map.removeLayer()
Removes the layer at the specified index. Layers above this layer will move down to fill the gap. @param index the index of the layer to be removed @return the layer that was removed from the list

Examples of com.bbn.openmap.layer.BufferedLayer.removeLayer()

                if (DEBUG) {
                    debugmsg("Removing layer[" + i + "]= "
                            + layers[i].getName());
                }
                remove(layers[i]);
                bufLayer.removeLayer(layers[i]);
            }
        }


        if (!layerRemovalDelayed) {
            purgeAndNotifyRemovedLayers();

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Examples of com.github.neuralnetworks.architecture.NeuralNetworkImpl.removeLayer()

    @Test
    public void testRemoveLayer() {
  NeuralNetworkImpl mlp = NNFactory.mlp(new int[] {3, 4, 5}, true);
  assertEquals(5, mlp.getLayers().size(), 0);
  Layer currentOutput = mlp.getOutputLayer();
  mlp.removeLayer(mlp.getOutputLayer());
  assertEquals(3, mlp.getLayers().size(), 0);
  assertEquals(true, currentOutput != mlp.getOutputLayer());
    }


    @Test

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Examples of com.github.neuralnetworks.architecture.NeuralNetworkImpl.removeLayer()

    public void testRemoveLayer() {
  Environment.getInstance().setUseWeightsSharedMemory(true);
  NeuralNetworkImpl mlp = NNFactory.mlp(new int[] {3, 4, 5}, true);
  assertEquals(5, mlp.getLayers().size(), 0);
  Layer currentOutput = mlp.getOutputLayer();
  mlp.removeLayer(mlp.getOutputLayer());
  assertEquals(3, mlp.getLayers().size(), 0);
  assertEquals(true, currentOutput != mlp.getOutputLayer());
    }


    @Test

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Examples of com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()


  // training
  t.train();


  // the output layer is removed, thus making the hidden layer the new output
  ae.removeLayer(ae.getOutputLayer());


  // testing
  t.test();


  assertEquals(0, t.getOutputError().getTotalNetworkError(), 0);

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Examples of com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()

      Environment.getInstance().setExecutionMode(EXECUTION_MODE.SEQ);


      bae.train();


      // the output layer is needed only during the training phase...
      ae.removeLayer(ae.getOutputLayer());


      bae.test();


      // 2 of the iris classes are linearly not separable - an error of 1/3 illustrates that
      assertEquals(0, bae.getOutputError().getTotalNetworkError(), 1/3f);

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Examples of com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()

      bae.addEventListener(new LogTrainingListener(Thread.currentThread().getStackTrace()[1].getMethodName()));


      bae.train();


      // the output layer is needed only during the training phase...
      ae.removeLayer(ae.getOutputLayer());


      bae.test();


      // 2 of the iris classes are linearly not separable - an error of 1/3 illustrates that
      assertEquals(0, bae.getOutputError().getTotalNetworkError(), 2/3f);

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Examples of com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()

  Trainer<?> t = TrainerFactory.backPropagationAutoencoder(nn, trainInputProvider, testInputProvider,  new MultipleNeuronsOutputError(), new NNRandomInitializer(new MersenneTwisterRandomInitializer(-0.01f, 0.01f)), 0.01f, 0.5f, 0f, 0f, 0f);


  t.addEventListener(new LogTrainingListener(Thread.currentThread().getStackTrace()[1].getMethodName(), false, true));
  Environment.getInstance().setExecutionMode(EXECUTION_MODE.CPU);
  t.train();
  nn.removeLayer(nn.getOutputLayer());
  t.test();


  assertEquals(0, t.getOutputError().getTotalNetworkError(), 0.1);
    }

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Examples of com.github.neuralnetworks.architecture.types.Autoencoder.removeLayer()


  // training
  t.train();


  // the output layer is removed, thus making the hidden layer the new output
  ae.removeLayer(ae.getOutputLayer());


  // testing
  t.test();


  assertEquals(0, t.getOutputError().getTotalNetworkError(), 0);

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Examples of de.yaams.extensions.basemap.tiled.core.Map.removeLayer()

    Map map = editor.getCurrentMap();
    int layerIndex = editor.getCurrentLayerIndex();
    int totalLayers = map.getTotalLayers();


    if (layerIndex >= 0) {
      map.removeLayer(layerIndex);


      // If the topmost layer was selected, the layer index is invalid
      // after removing that layer. The right thing to do is to reset it
      // to the new topmost layer.
      if (layerIndex == totalLayers - 1) {

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Examples of org.geotools.map.MapContent.removeLayer()

                Layer selectedMapLayer = mapLayerTableViewer.getSelectedMapLayer();
                if (selectedMapLayer == null) {
                    return;
                }
                MapContent mapContext = pane.getMapContent();
                mapContext.removeLayer(selectedMapLayer);
                mapLayerTableViewer.selectionChanged(null);
            }
        });


        Button showLayersButton = new Button(buttonComposite, SWT.PUSH);

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