flex游戏引擎(PushButton)-简单移动飞机在背景上

HeroControllerComponent .as

//组件控制,包括键盘,移动

/*******************************************************************************
 * PushButton Engine
 * Copyright (C) 2009 PushButton Labs, LLC
 * For more information see http://www.pushbuttonengine.com
 *
 * This file is licensed under the terms of the MIT license, which is included
 * in the License.html file at the root directory of this SDK.
 ******************************************************************************/

package
{
 
 import com.pblabs.engine.PBE;
 import com.pblabs.engine.components.TickedComponent;
 import com.pblabs.engine.entity.PropertyReference;
 import com.pblabs.engine.core.InputKey; 
 
 import flash.geom.Point;
 
 // Make a ticked component so that it can update itself every frame with onTick()
 public class HeroControllerComponent extends TickedComponent
 {
  // Keep a property reference to our entity's position.
  public var positionReference:PropertyReference;
  
  // onTick() is called every frame
  public override function onTick(tickRate:Number):void
  {
       
   var position:Point = owner.getProperty(positionReference);
           
   // Look at our input keys to see which direction we should move. Left is -x, right is +x.
         
   if (PBE.isKeyDown(InputKey.RIGHT))
          
   {
             
    // Move our hero to the right
            
     position.x += 15;
           
   }
      
   if (PBE.isKeyDown(InputKey.LEFT))
         
   {
         
    // Move our hero to the left
           
     position.x -= 15;
        
   }
   if (PBE.isKeyDown(InputKey.UP))
    
   {
    
    // Move our hero to the right
    
    position.y -= 15;
    
   }
   
   if (PBE.isKeyDown(InputKey.DOWN))
    
   {
    
    // Move our hero to the left
    
    position.y += 15;
    
   }    
          
   // Finally, add some boundary limits so that we don't go off the edge of the screen.
   30.           
   if (position.x > 375)
         
   {
              
    // Set our position at the wall edge
              
     position.x = 375;               
          
   } 
         
   else if (position.x < -375)
         
   {
              
    // Set our position at the wall edge
              
     position.x = -375;
         
   }
   if (position.y > 260)
    
   {
    
    // Set our position at the wall edge
    
    position.y = 260;               
    
   } 
    
   else if (position.y < -260)
    
   {
    
    // Set our position at the wall edge
    
    position.y = -260;
    
   }    
        
   // Send our manipulated spatial variables back to the spatial manager
         
    owner.setProperty(positionReference, position);    
   
  }
 }
}

 

Lesson5Base.as

/*******************************************************************************
 * PushButton Engine
 * Copyright (C) 2009 PushButton Labs, LLC
 * For more information see http://www.pushbuttonengine.com
 *
 * This file is licensed under the terms of the MIT license, which is included
 * in the License.html file at the root directory of this SDK.
 ******************************************************************************/

package
{
    import com.pblabs.engine.PBE;
    import com.pblabs.engine.entity.*;
    import com.pblabs.rendering2D.*;
    import com.pblabs.rendering2D.ui.*;
   
    import flash.display.Sprite;
    import flash.geom.Point;
   
    [SWF(width="800", height="600", frameRate="60")]
    public class Lesson5Base extends Sprite
    {
        public function Lesson5Base()
        {
            // Start up PBE
            PBE.startup(this);
   new MyRes();
           
            // Set up a simple scene entity
            createScene();
           
            // Create a simple avatar entity
            createHero();
   createBackground();
   

        }
       
        private function createScene():void
        {
            var sceneView:SceneView = new SceneView();                        // Make the SceneView
            sceneView.width = 800;
            sceneView.height = 600;
           
            PBE.initializeScene(sceneView);                                   // This is just a helper function that will set up a basic scene for us
        }
     
  
  
        private function createHero():void
        {
            var hero:IEntity = allocateEntity();                              // Allocate an entity for our hero avatar
//创造位置及尺寸信息的组件            
   createSpatial( hero,
    
    // with location of 0,0...
    
    new Point(0, 0),
    new Point(50,50)    
    
   );

           
            // Create an instance of our hero controller component
            var controller:HeroControllerComponent = new HeroControllerComponent();
            // Point the controller component to this entity's Spatial component for position information
            controller.positionReference = new PropertyReference("@Spatial.position");
           
            // Add the demo controller component to the Hero entity with the name "Controller"
            hero.addComponent( controller, "Controller" );
   
   
   
   // Create a simple render component to display our object
   var render:SpriteRenderer = new SpriteRenderer();
   // Tell the Render component to use one of the images embedded by our ResourceBundle
   render.fileName = "../assets/fanship.png";
   
   
   // Add the renderer to the scene.
   render.scene = PBE.scene;
   
   
   // Set our hero to render above the background.
   render.layerIndex = 10;

  
   //从空间组件中提取坐标信息
   // Point the render component to this entity's Spatial component for position information
   render.positionProperty = new PropertyReference("@Spatial.position");
   // Point the render component to this entity's Spatial component for size information
   render.sizeProperty = new PropertyReference("@Spatial.size");
   // Add our render component to the Hero entity with the name "Render"
   hero.addComponent( render, "Render" );
   
            hero.initialize("Hero");                                          // Register the entity with PBE under the name "Hero"        
        }
  private function createBackground():void
  {
    
   // Allocate an entity for our background sprite
    
   var bg:IEntity = PBE.allocateEntity();
     
   // Add our spatial component to the background entity ...
    
    createSpatial( bg,
     
     // with location of 0,0...
      
     new Point(0, 0)
 
    );

   // Create a simple render component to display our object
 
   // Just like the hero, this also uses a SpriteRenderComponent
  
   var render:SpriteRenderer = new SpriteRenderer();
 
   // Tell the Render component to use one of the images embedded by our ResourceLinker

    render.fileName = "../assets/bg.jpg";
 
   // Set our background to render below the hero.
 
    render.layerIndex = 1;

   // Add the renderer to the scene.
 
    render.scene = PBE.scene;
 
   // Point the render component to this entity's Spatial component for position information
  
    render.positionProperty = new PropertyReference("@Spatial.position");
 
   // Add our render component to the BG entity with the name "Render"
  
    bg.addComponent( render, "Render" );
 
   // Register the entity with PBE under the name "BG"
  
    bg.initialize("BG");         
             }
  
  private function createSpatial( ent:IEntity, pos:Point, size:Point = null ):void
  {
   //创建位置和尺寸信息组件,并加入到实体

   // Create our spatial component
   var spatial:SimpleSpatialComponent = new SimpleSpatialComponent();
   
   // Do a named lookup to register our background with the scene spatial database
   spatial.spatialManager = PBE.spatialManager;
   
   // Set our background position in space
   spatial.position = pos;
   
   if (size != null)
    spatial.size = size;
   
   ent.addComponent(spatial, "Spatial");
  }  
  
  
    }
}

 

//引用的资源定义,能把资源包括图片放入发布后的swf文件

 

// ActionScript file
/*******************************************************************************
 * PushButton Engine
 * Copyright (C) 2009 PushButton Labs, LLC
 * For more information see
http://www.pushbuttonengine.com
 *
 * This file is licensed under the terms of the MIT license, which is included
 * in the License.html file at the root directory of this SDK.
 ******************************************************************************/
//这个类非常重要,将完成图片资源打包进发布后的swf文件
package
{
 import com.pblabs.engine.resource.*;
 
 public class MyRes extends ResourceBundle
 {
  [Embed(source="../assets/bg.jpg")]
  //resBg这个名称不重要,但必须保证唯一,必须要申明
  public var resBg:Class;
  
  [Embed(source="../assets/fanship.png")]
  //resShip这个名称不重要,但必须保证唯一,必须要申明  
  public var resShip:Class;
 }
}

演示:http://www.deepfuturesoft.info/flexstudy/Lesson5Base.swf

 

【立创EDA-PCB设计基础】6.布线铺铜实战及细节详解 本文进行布线铺铜实战及详解布线铺铜的细节 阅读详情

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Download.2. addpath(genpath('DeepLearnToolbox'));Example: Deep Belief Network---------------------```matlabfunction test_example_DBNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit RBM and visualize its weightsrand('state',0)dbn.sizes = [100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);figure; visualize(dbn.rbm{1}.W'); % Visualize the RBM weights%% ex2 train a 100-100 hidden unit DBN and use its weights to initialize a NNrand('state',0)%train dbndbn.sizes = [100 100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);%unfold dbn to nnnn = dbnunfoldtonn(dbn, 10);nn.activation_function = 'sigm';%train nnopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.10, 'Too big error');```Example: Stacked Auto-Encoders---------------------```matlabfunction test_example_SAEload mnist_uint8;train_x = double(train_x)/255;test_x = double(test_x)/255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN% Setup and train a stacked denoising autoencoder (SDAE)rand('state',0)sae = saesetup([784 100]);sae.ae{1}.activation_function = 'sigm';sae.ae{1}.learningRate = 1;sae.ae{1}.inputZeroMaskedFraction = 0.5;opts.numepochs = 1;opts.batchsize = 100;sae = saetrain(sae, train_x, opts);visualize(sae.ae{1}.W{1}(:,2:end)')% Use the SDAE to initialize a FFNNnn = nnsetup([784 100 10]);nn.activation_function = 'sigm';nn.learningRate = 1;nn.W{1} = sae.ae{1}.W{1};% Train the FFNNopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.16, 'Too big error');```Example: Convolutional Neural Nets---------------------```matlabfunction test_example_CNNload mnist_uint8;train_x = double(reshape(train_x',28,28,60000))/255;test_x = double(reshape(test_x',28,28,10000))/255;train_y = double(train_y');test_y = double(test_y');%% ex1 Train a 6c-2s-12c-2s Convolutional neural network %will run 1 epoch in about 200 second and get around 11% error. %With 100 epochs you'll get around 1.2% errorrand('state',0)cnn.layers = { struct('type', 'i') %input layer struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %sub sampling layer struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %subsampling layer};cnn = cnnsetup(cnn, train_x, train_y);opts.alpha = 1;opts.batchsize = 50;opts.numepochs = 1;cnn = cnntrain(cnn, train_x, train_y, opts);[er, bad] = cnntest(cnn, test_x, test_y);%plot mean squared errorfigure; plot(cnn.rL);assert(er<0.12, 'Too big error');```Example: Neural Networks---------------------```matlabfunction test_example_NNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);% normalize[train_x, mu, sigma] = zscore(train_x);test_x = normalize(test_x, mu, sigma);%% ex1 vanilla neural netrand('state',0)nn = nnsetup([784 100 10]);opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samples[nn, L] = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.08, 'Too big error');%% ex2 neural net with L2 weight decayrand('state',0)nn = nnsetup([784 100 10]);nn.weightPenaltyL2 = 1e-4; % L2 weight decayopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex3 neural net with dropoutrand('state',0)nn = nnsetup([784 100 10]);nn.dropoutFraction = 0.5; % Dropout fraction opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex4 neural net with sigmoid activation functionrand('state',0)nn = nnsetup([784 100 10]);nn.activation_function = 'sigm'; % Sigmoid activation functionnn.learningRate = 1; % Sigm require a lower learning rateopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex5 plotting functionalityrand('state',0)nn = nnsetup([784 20 10]);opts.numepochs = 5; % Number of full sweeps through datann.output = 'softmax'; % use softmax outputopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex6 neural net with sigmoid activation and plotting of validation and training error% split training data into training and validation datavx = train_x(1:10000,:);tx = train_x(10001:end,:);vy = train_y(1:10000,:);ty = train_y(10001:end,:);rand('state',0)nn = nnsetup([784 20 10]); 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