How-To Tutorials

In this article by Juampy Novillo Requena, author of Drush for Developers, Second Edition, we will learn that Drush site aliases offer a useful way to manage local environments without having to be within Drupal's root directory. (For more resources related to this topic, see here.) A site alias consists of an array of settings for Drush to access a Drupal project. They can be defined in different locations, using various file structures. You can find all of its variations at drush topic docs-aliases. In this article, we will use the following variations: We will define local site aliases at $HOME/.drush/aliases.drushrc.php, which are accessible anywhere for our command-line user. We will define a group of site aliases to manage the development and production environments of our sample Drupal project. These will be defined at sites/all/drush/example.aliases.drushrc.php. In the following example, we will use the site-alias command to generate a site alias definition for our sample Drupal project: $ cd /home/juampy/projects/example $ drush --uri=example.local site-alias --alias-name=example.local @self $aliases["example.local"] = array ( 'root' => '/home/juampy/projects/example', 'uri' => 'example.local', '#name' => 'self', ); The preceding command printed an array structure for the $aliases variable. You can see the root and uri options. There is also an internal property called #name that we can ignore. Now, we will place the preceding output at $HOME/.drush/aliases.drushrc.php so that we can invoke Drush commands to our local Drupal project from anywhere in the command-line interface: <?php   /** * @file * User-wide site alias definitions. * * Site aliases defined here are available everywhere for the current user. */   // Sample Drupal project. $aliases["example.local"] = array ( 'root' => '/home/juampy/projects/example', 'uri' => 'example.local', ); Here is how we use this site alias in a command. The following example is running the core-status command for our sample Drupal project: $ cd /home/juampy $ drush @example.local core-status Drupal version                 : 7.29-dev                               Site URI                       : example.local                               Database driver                 : mysql                               Database username               : root                                   Database name                   : drupal7x                               Database                       : Connected                               ... Drush alias files              : /home/juampy/.drush/aliases.drushrc.php Drupal root                     : /home/juampy/projects/example           Site path                       : sites/default                           File directory path             : sites/default/files                     Drush loaded our site alias file and used the root and uri options defined in it to find and bootstrap Drupal. The preceding command is equivalent to the following one: $ drush --root=/home/juampy/projects/example --uri=example.local core-status While $HOME/.drush/aliases.drushrc.php is a good place to define site aliases in your local environment, /etc/drush is a first class directory to place site aliases in servers. Let's discover now how we can connect to remote environments via Drush. Managing remote environments Site aliases that reference remote websites can be accessed by Drush through a password-less SSH connection (http://en.wikipedia.org/wiki/Secure_Shell). Before we start with these, let's make sure that we meet the requirements. Verifying requirements First, it is recommended to install the same version of Drush in all the servers that host your website. Drush will fail to run a command if it is not installed in the remote machine except for core-rsync, which runs rsync, a non-Drush command that is available in Unix-like systems. If you can already access the server that hosts your Drupal project through a public key, then skip to the next section. If not, you can either use the pushkey command from Drush extras (https://www.drupal.org/project/drush_extras), or continue reading to set it up manually. Accessing a remote server through a public key The first thing that we need to do is generate a public key for our command-line user in our local machine. Open the command-line interface and execute the following command. We will explain the output step by step: $ cd $HOME $ ssh-keygen Generating public/private rsa key pair. Enter file in which to save the key (/home/juampy/.ssh/id_rsa): By default, SSH keys are created at $HOME/.ssh/. It is fine to go ahead with the suggested path in the preceding prompt; so, let's hit Enter and continue: Created directory '/home/juampy/.ssh'. Enter passphrase (empty for no passphrase): ********* Enter same passphrase again: ********* If the .ssh directory does not exist for the current user, the ssh-keygen command will create it with the correct permissions. We are next prompted to enter a passphrase. It is highly recommended to set one as it makes our private key safer. Here is the rest of the output once we have entered a passphrase: Your identification has been saved in /home/juampy/.ssh/id_rsa. Your public key has been saved in /home/juampy/.ssh/id_rsa.pub. The key fingerprint is: 6g:bf:3j:a2:00:03:a6:00:e1:43:56:7a:a0:c7:e9:f3 juampy@juampy-box The key's randomart image is: +--[ RSA 2048]----+ |                 | |                 | |..               | |o..*             | |o + . . S        | | + * = . .       | | = O o . .     | |   *.o * . .     | |   .oE oo.     | +-----------------+ The result is a new hidden directory under our $HOME path named .ssh. This directory contains a private key file (id_rsa) and a public key file (id_rsa.pub). The former is to be kept secret by us, while the latter is the one we will copy into remote servers where we want to gain access. Now that we have a public key, we will announce it to the SSH agent so that it can be used without having to enter the passphrase every time: $ ssh-add ~/.ssh/id_rsa Identity added: /home/juampy/.ssh/id_rsa (/home/juampy/.ssh/id_rsa) Our key is ready to be used. Assuming that we know an SSH username and password to access the server that hosts the development environment of our website, we will now copy our public key into it. In the following command, replace exampledev and dev.example.com with the username and server's URL of your server: $ ssh-copy-id exampledev@dev.example.com exampledev@dev.example.com's password: Now try logging into the machine, with "ssh 'exampledev@dev.example.com'", and check in: ~/.ssh/authorized_keys to make sure we haven't added extra keys that you weren't Our public key has been copied to the server and now we do not need to enter a password to identify ourselves anymore when we log in to it. We could have logged on to the server ourselves and manually copied the key, but the benefit of using the ssh-copy-id command is that it takes care of setting the right permissions to the ~/.ssh/authorized_keys file. Let's test it by logging in to the server: $ ssh exampledev@dev.example.com Welcome! We are ready to set up remote site aliases and run commands using the credentials that we have just configured. We will do this in the next section. If you have any trouble setting up SSH authentication, you can find plenty of debugging tips at https://help.github.com/articles/generating-ssh-keys and http://git-scm.com/book/en/Git-on-the-Server-Generating-Your-SSH-Public-Key. Defining a group of remote site aliases for our project Before diving into the specifics of how to define a Drush site alias, let's assume the following scenario: you are part of a development team working on a project that has two environments, each one located in its own server: Development, which holds the bleeding edge version of the project's codebase. It can be reached at http://dev.example.com. Production, which holds the latest stable release and real data. It can be reached at http://www.example.com. Additionally, there might be a variable amount of local environments for each developer in their working machines; although, these do not need a site alias. Given the preceding scenario and assuming that we have SSH access to the development and production servers, we will create a group of site aliases that identify them. We will define this group at sites/all/drush/example.aliases.drushrc.php within our Drupal project: <?php /** * @file * * Site alias definitions for Example project. */   // Development environment. $aliases['dev'] = array( 'root' => '/var/www/exampledev/docroot', 'uri' => 'dev.example.com', 'remote-host' => 'dev.example.com', 'remote-user' => 'exampledev', );   // Production environment. $aliases['prod'] = array( 'root' => '/var/www/exampleprod/docroot', 'uri' => 'www.example.com', 'remote-host' => 'prod.example.com', 'remote-user' => 'exampleprod', ); The preceding file defines two arrays for the $aliases variable keyed by the environment name. Drush will find this group of site aliases when being invoked from the root of our Drupal project. There are many more settings available, which you can find by reading the contents of the drush topic docs-aliases command. These site aliases contain options known to us: root and uri refer to the remote root path and the hostname of the remote Drupal project. There are also two new settings: remote-host and remote-uri. The former defines the URL of the server hosting the website, while the latter is the user to authenticate Drush when connecting via SSH. Now that we have a group of Drush site aliases to work with, the following section will cover some examples using them. Using site aliases in commands Site aliases prepend a command name for Drush to bootstrap the site and then run the command there. Our site aliases are @example.dev and @example.prod. The word example comes from the filename example.aliases.drushrc.php, while dev and prod are the two keys that we added to the $aliases array. Let's see them in action with a few command examples: Check the status of the Development environment: $ cd /home/juampy/projects/example $ drush @example.dev status Drupal version                 : 7.26                           Site URI                       : http://dev.example.com         Database driver                : mysql                           Database username              : exampledev                     Drush temp directory           : /tmp                           ... Drush alias files              : /home/juampy/projects/example/sites/all/drush/example.aliases.drushrc.php     Drupal root                    : /var/www/exampledev/docroot ...                                           The preceding output shows the current status of our development environment. Drush sent the command via SSH to our development environment and rendered back the resulting output. Most Drush commands support site aliases. Let's see the next example. Log in to the development environment and copy all the files from the files directory located at the production environment: $ drush @example.dev site-ssh Welcome to example.dev server! $ cd `drush @example.dev drupal-directory` $ drush core-rsync @example.prod:%files @self:%files You will destroy data from /var/www/exampledev/docroot/sites/default/files and replace with data from exampleprod@prod.example.com:/var/www/exampleprod/docroot/sites/default/files/ Do you really want to continue? (y/n): y Note the use of @self in the preceding command, which is a special Drush site alias that represents the current Drupal project where we are located. We are using @self instead of @example.dev because we are already logged inside the development environment. Now, we will move on to the next example. Open a connection with the Development environment's database: $ drush @example.dev sql-cli Welcome to the MySQL monitor. Commands end with ; or g. mysql> select database(); +------------+ | database() | +------------+ | exampledev | +------------+ 1 row in set (0.02 sec) The preceding command will be identical to the following set of commands: drush @example.dev site-ssh cd /var/www/exampledev drush sql-cli However, Drush is so clever that it opens the connection for us. Isn't this neat? This is one of the commands I use most frequently. Let's finish by looking at our last example. Log in as the administrator user in production: $ drush @example.prod user-login http://www.example.com/user/reset/1/some-long-token/login Created new window in existing browser session. The preceding command creates a login URL and attempts to open your default browser with it. I love Drush! Summary In this article, we covered practical examples with site aliases. We started by defining a site alias for our local Drupal project, and then went on to write a group of site aliases to manage remote environments for a hypothetical Drupal project with a development and production site. Before using site aliases for our remote environments, we covered the basics of setting up SSH in order for Drush to connect to these servers and run commands there. Resources for Article: Further resources on this subject: Installing and Configuring Drupal [article] Installing and Configuring Drupal Commerce [article] 25 Useful Extensions for Drupal 7 Themers [article]

In this article by John Henry Krahenbuhl, author of the book, Learning Axure RP Interactive Prototypes, we will cover the following topics: Logo and links Global navigation Shopping cart Search (For more resources related to this topic, see here.) Logo and links To create our logo element, we will drag the Placeholder widget onto the Home page in the design area. We will then enable an OnClick interaction that will cause the Home page to open in the current window when the Placeholder widget is clicked. To create the logo element, perform the following steps: With the Home page opened in the design area, in the Widgets pane, click on the Placeholder widget. While holding down the mouse button, drag the Placeholder widget and place it at coordinates (10,20). With the Placeholder widget selected, type Logo. We will see Logo in the center of the Placeholder widget, like so: Next, we will name the Placeholder widget and add the OnClick interaction. With the Placeholder widget selected, perform the following steps: In the Widget Interactions and Notes pane, click in the Shape Name field and type CompanyLogo. In the Widget Interactions and Notes pane, click on the Interactions tab and then on Create Link…. In the Sitemap modal window, click on the Home page. You will see Case 1 added to the OnClick interaction, as follows: Axure has numerous point updates, and as a result, in the Widgets Interactions and Notes pane, your version may show Shape Name (or a similar label for the name field) instead of Shape Footnote and Name. We will now create three new links in our header using a Dynamic Panel and the Label widget. In the Widgets pane, click on the Dynamic Panel widget. While holding down the mouse button, drag the Dynamic Panel widget and place it at coordinates (570,10). With the Dynamic Panel widget selected, perform the following steps: In the Widget Interactions and Notes pane, click in the Dynamic Panel Name field and type HeaderLinksDP. In the toolbar, change the width w: to 300 and the height h: to 25. In the Widget Manager pane, we will see the following: In the Widget Manager pane, double-click on State1 to open it in the design area. With State1 selected, in the Widgets pane, click on the Label widget. While holding down the mouse button, drag the Label widget and place it at coordinates (80,4). With the Label widget selected, perform the following steps: Type Help. We will see Help displayed as text on the Label widget. In the Widget Interactions and Notes pane, click in the Shape Name field and type HelpLink. In the Widget Interactions and Notes pane, click on the Interactions tab and then click on Create Link…. In the Sitemap modal window, click on the Help page. Repeat step 7 twice to create two additional links using the following table for coordinates, text displayed, shape name of the label widgets, and create link: Coordinates Text displayed Shape name Create link... (140,4) Support SupportLink Support (220,4) Sign In SignInLink Sign In Slow double-click on State1 and rename it to Links. When renaming a dynamic panel state, if the state is currently selected (that is, highlighted in blue), you only need to slow click on the state name to rename the state. If the state is not currently selected, you will need to slow double-click on the state name to rename the state. We have now created the logo with three additional links. Our header should look like this: Next, we will add global navigation using the Classic Menu - Horizontal widget. Global navigation We will now add global navigation using the Classic Menu – Horizontal widget. Once we have added the Classic Menu – Horizontal widget, our header should look like this: Open the Home page in the design area. To create the global navigation element, perform the following steps: In the Widgets pane, click on the Classic Menu - Horizontal widget. While holding down the left mouse button, drag the Classic Menu - Horizontal widget and place it at coordinates (240,80). Right-click the first menu item labeled File, and in the flyout menu, click on Add Menu Item After. Your menu should look like this: Repeat step 2, adding one more menu item. You should now have a total of five menu items. Click on the first menu item to select it and type Women. With the menu item selected, perform the following steps: In the Widget Interactions and Notes pane, click in the Menu Item Name field and type HzMenuWomen. In the Widget Interactions and Notes pane, click on the Interactions tab and then click on Create Link…. In the Sitemap modal window, click on the Women page. Repeat step 5 to change the menu item displayed and menu item name for menu items 2–5 using the following table: Menu item displayed Menu item name Create link... Men HzMenuMen Men Kids HzMenuKids Kids Shoes HzMenuShoes Shoes Accessories HzMenuAccessories Accessories We have now created the global navigation with five menu items. Our header should now look like this: Next, we will add a shopping cart element using a Rectangle widget with a Text Field widget. Shopping cart We will now add a shopping cart element using a Rectangle widget and a special character for a shopping bag icon. Our shopping cart element will look like this: To create the Shopping Cart element, perform the following steps: From the Widgets pane, drag the Rectangle widget and place at coordinates (870,80). With the Rectangle widget selected, perform the following steps: Right-click on the Rectangle widget and click Edit Text. Type Shopping. In the toolbar, change the width w to 90 and the height h to 30. In the Widget Interactions and Notes pane, click in the Shape Name field and type ShoppingButton. In the Widget Properties and Style pane, with the Style tab selected, scroll to Alignment + Padding and change padding by changing the value of R to 15. From the Widgets pane, drag the Image widget and place at coordinates (937,85). With the Image widget selected, perform the following steps: In the toolbar, change the width w to 20 and the height h to 20. In the Widget Interactions and Notes pane, click in the Image Name field and type ShoppingBagIcon. Double-click the image and select the image you would like to use (that is, a shopping bag or shopping cart image). For our shopping bag icon, an image of a handbag emoji sized to 20 x 20 pixels was used. The handbag emoji as well as other useful emojis can be found at http://emojipedia.org. Next, we will add an expandable search text field element using a dynamic panel widget with two states. Search One popular design pattern is to use an expandable search text field. To accomplish this, we will use a Dynamic Panel widget labeled SearchDP with two states: Collapsed and Expanded. The Collapsed state is the default state and will contain a Text Field widget. The Text Field widget will respond to the OnMouseEnter interaction and will perform the following actions: Move the HeaderLinksDP (Dynamic Panel) in x: -80 pixels. Transitioning the Dynamic Panel to the Expanded state, using the slide left animation. Set focus on the Text Field widget labeled SearchTextFieldExpanded. To create the Search text field, Dynamic Panel, and States, perform the following steps: In the Widgets pane, click on the Dynamic Panel widget. While holding down the mouse button, drag the Dynamic Panel widget and place it at coordinates (790,10). With the Dynamic Panel widget selected, perform the following steps: Right-click on the Dynamic Panel widget and click on Order, then click on Send to Back. In the Widget Interactions and Notes pane, click in the Dynamic Panel Name field and type ExpandingSearchDP. In the toolbar, change the width w: to 170 and the height h: to 25. In the Widget Manager pane, double-click on State1 to open it in the design area. With State1 selected, perform the following steps: In the Widgets pane, click on the Rectangle widget. While holding down the mouse button, drag the Rectangle widget and place at coordinates (80,0). With the Rectangle widget selected, In the toolbar change the values of w to 90 and h to 24. In the Widget Interactions and Notes pane, click in the Text Field Name field and type SearchRectangleCollapsed. From the Widgets pane, drag the Image widget and place at coordinates (149,2). In the toolbar, change the width w to 20 and the height h to 20. In the Widget Interactions and Notes pane, click in the Image Name field and type SearchIcon. Double-click the image and select the image you would like to use (that is, a left-pointing, magnifying glass image). For our search icon, an image of a left-pointing, magnifying glass emoji sized to 20 x 20 pixels was used. This emoji as well as other useful emojis can be found at http://emojipedia.org. In the Widgets pane, click on the Text Field widget. While holding down the left mouse button, drag the Text Field widget and place at coordinates (80,0). With the text field widget selected, perform the following steps: In the Widget Interactions and Notes pane, click in the Text Field Name field and type SearchTextFieldCollapsed. In the toolbar, change the value of w to 65 and h to 24. Right-click on the Text Field widget and click on Hide Border. In the Widget Properties and Style pane, with the Style tab selected, scroll to Borders, Lines, + Fills. Click on the down arrow next to the paint bucket icon. In the drop-down menu, click on the box with the red diagonal line to indicate no fill. The fill drop-down menu with no fill selected looks like this: Right-click on State1 and click Duplicate State. Slow click on State1 and rename it to Collapsed. Slow double-click on State2 and rename it to Expanded. In the Widget Manager pane, double-click on Expanded to open it in the design area. With Expanded selected, perform the following steps: Click on the rectangle widget labeled SearchRectangleCollapsed to select it and perform the following steps: The SearchRectangleCollapsed widget is at coordinates (80,0) and is directly beneath the SearchTextFieldCollapsed widget at coordinates (80,0). Slow-double-click on the design area near coordinates (90,10) to select the SearchRectangleCollapsed widget. Once selected in the Widget Interactions and Notes pane, in the Shape Name field, you will see the name SearchRectangleCollapsed. In the Widget Interactions and Notes pane, click in the Shape Name field and rename the widget SearchRectangleExpanded. In the toolbar, change x to 0 and w to 170. Click on the text field widget labeled SearchTextFieldCollapsed at coordinates (80,0) to select it and perform the following steps: In the Widget Interactions and Notes pane, click in the Text Field Name field and rename the widget SearchTextFieldExpanded. In the toolbar, change x to 0 and w to 145. With the search text field dynamic panel created, we are now ready to define the interactions that will cause the search text field element to expand and collapse. To create this effect, perform the steps given in the following sections: In the Widget Manager pane, double-click on the Collapsed state to open it in the design area. In the design area, click on the text field widget named SearchTextFieldCollapsed at coordinates (80,0). With the text field widget selected in the Widget Interactions and Notes pane, click on the Interactions tab, then on More Events, and, finally, click on OnMouseEnter. A Case Editor dialog box will open. In the Case Editor dialog box, perform the steps given in the following section. Create the first action: Under Click to add actions, scroll to the Dynamic Panels drop-down menu and click on Set Panel State. Under Configure actions, click on the checkbox next to Set ExpandingSearchDP state. Change Select the State to Expanded. Change Animate In to slide left t: 250 ms. Create the second action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Move. Under Configure actions, click on the checkbox next to HeaderLinksDP. Change Move by x to -80. Create the third action: Under Click to add actions, scroll to the Miscellaneous drop-down menu and click on Wait. Under Configure actions, change Wait time: to 350 ms. Create the fourth action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Bring to Front/Back. Under Configure actions, click on the checkbox next to SearchTextFieldExpanded. Next to Order, click on the radio button next to Bring to Front. Create the fifth action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Focus. Under Configure actions, click on the checkbox next to SearchTextFieldExpanded. Click on OK. In the Widget Interactions and Notes pane, click on the Interactions tab and then click on Case 1. In the main menu, click on Edit and then click on Copy. In the design area, click on the rectangle widget named SearchRectangleCollapsed at coordinates (80,0) to select it. Recall that we must slow-double-click near coordinates (90,10) to select the SearchRectangleCollapsed since it is beneath the SearchTextFieldCollapsed widget. With the rectangle widget selected in the Widget Interactions and Notes pane, click on the Interactions tab, then click on More Events, and next to OnMouseEnter, click on the Paste button. The OnMouseEnter event with Case 1 will be shown as follows: In the Widget Manager pane, double-click on the Expanded state to open it in the design area. Click on the text field widget named SearchTextFieldExpanded near coordinates (0,0) to select it. With the text field widget selected in the Widget Interactions and Notes pane, click on the Interactions tab, then on More Events, and, finally, click on OnLostFocus. A Case Editor dialog box will open. In the Case Editor dialog box, perform the following steps: Create the condition. Click the Add Condition button. In the Condition Builder dialog box, in the outlined condition box perform the following steps: In the first dropdown, select cursor. In the second dropdown, select is not over. In the third dropdown, select area of widget. In the fourth text box dropdown, select SearchRectangle. Click OK. Create the first action: Under Click to add actions, scroll to the Dynamic Panels drop-down menu and click on Set Panel State. Under Configure actions, click on the checkbox next to Set ExpandingSearchDP state. Change Select the State to Collapsed. Change Animate In to slide right t: 200 ms. Create the second action: Under Click to add actions, scroll to the Miscellaneous drop-down menu and click on Wait. Under Configure actions, change Wait time: to 150 ms. Create the third action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Move. Under Configure actions, click on the checkbox next to HeaderLinksDP. Change Move by x: to 80. Create the fourth action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Set Text. Under Configure actions, click on the checkbox next to SearchTextFieldExpanded. Under Set text to, click on the first dropdown and select text on widget. Click on the second dropdown and select SearchTextFieldExpanded. Your case editor will look like this: Create the fifth action: Under Click to add actions, scroll to the Widgets drop-down menu and click on Bring to Front/Back. Under Configure actions, click on the checkbox next to HeaderLinksDP. Next to Order, click on the radio button next to Bring to Front. Click on OK. In the design area, click on the text field widget named SearchTextFieldExpanded to select it. Perform the following steps: Right-click on the SearchTextFieldExpanded widget and click on Assign Submit Button. In the Assign Submit Button dialog box, click on the checkbox next to SearchRectangleExpanded. Click on OK. In the design area, select the rectangle widget named SearchRectangleExpanded by slow-double-clicking near coordinates (10,10). With the Rectangle widget selected, go to the Widget Interactions and Notes pane, click on the Interactions tab, and click on Create Link…. In the Sitemap modal window, click on the Search page. We have now created an expandable search text field widget that retains the text typed into the widget when the dynamic panel changes states. With the design completed for our header, we need to convert these widgets into a header master that can be leveraged on each page of our design. To create a header master, open the Home page in the design area then navigate to Edit | Select All in the main menu. Right-click on any widget in the design area and click on Convert to Master. In the Convert to Master dialog box, type Header. For Drop Behavior, click on the radio button next to Lock to Master Location. Click on the Continue button. You will now see the header master appear in the Masters pane. With our header Master completed, next we will design an interactive carousel. Summary In this article, we focused on creating the home page. A home page should be intuitive; it should capture one's attention and encourage further engagement with the site. For the home page, we used the easily recognizable elements found on popular e-commerce sites. We created logo, links to navigate to different pages, and shopping cart. we also learned how to create an expanding search bar. Resources for Article: Further resources on this subject: Common design patterns and how to prototype them [Article] Axure RP 6 Prototyping Essentials: Advanced Interactions [Article] Viewing on Mobile Devices [Article]

In Part 1 of this series, we got everything in place for our Koa app using Jade and Mongel. In this post, we will cover Jade templates and how to use listing and viewing pages. Please note that this series requires that you use Node.js version 0.11+. Jade templates Rendering HTML is always an important part of any web application. Luckily, when using Node.js there are many great choices, and for this article we’ve chosen Jade. Keep in mind though that we will only touch on a tiny fraction of the Jade functionality. Let’s create our first Jade template. Create a file called create.jade and put in the following: create.jade doctype html html(lang='en') head title Create Page body h1 Create Page form(method='POST', action='/create') input(type='text', name='title', placeholder='Title') input(type='text', name='contents', placeholder='Contents') input(type='submit') For all the Jade questions you have that we won’t answer in this series, I refer you to the excellent official Jade website at http://jade-lang.com . If you add the following statement app.listen(3000); to the end of index.js, then you should be able to run the program from your terminal using the following command and by visiting http://localhost:3000 in your browser. $ node --harmony index.js The --harmony flag just tells the node program that we need support for generators in our program: Listing and viewing pages Now that we can create a page in our MongoDB database, it is time to actually list and view these pages. For this purpose we need to add another middleware to our index.js file after the first middleware: app.use(function* () { if (this.method != 'GET') { this.status = 405; this.body = 'Method Not Allowed'; return } … }); As you can probably already tell, this new middleware is very similar to the first one we added that handled the creation of pages. At first we make sure that the method of the request is GET, and if not, we respond appropriately and return the following: var params = this.path.split('/').slice(1); var id = params[0]; if (id.length == 0) { var pages = yield Page.find(); var html = jade.renderFile('list.jade', { pages: pages }); this.body = html; return } Then, we proceed to inspect the path attribute of the Koa context, looking for an ID that represents the page in the database. Remember how we redirected using the ID in the previous middleware. We inspect the path by splitting it into an array of strings separated by the forward slashes of a URL; this way the path /1234 becomes an array of ‘’ and ‘1234.’ Because the path starts with a forward slash, the first item in the array will always be the empty string, so we just discard that by default. Then we check the length of the ID parameter, and if it’s zero we know that there is in fact no ID in the path, and we should just look for the pages in the database and render our list.jade template with those pages made available to the template as the variable pages. Making data available in templates is also known as providing locals to the template. list.jade doctype html html(lang="en") head title Your Web Application body h1 Your Web Application ul - each page in pages li a(href='/#{page._id}')= page.title But if the length of id was not zero, we assume that it’s an id and we try to load that specific page from the database instead of all the pages, and we proceed to render our view.jade template with the: var page = yield Page.findById(id); var html = jade.renderFile('view.jade', page); this.body = html; view.jade doctype html html(lang="en") head title= title body h1= title p= contents That’s it You should now be able to run the app as previously described and create a page, list all of your pages, and view them. If you want to, you can continue and build a simple CMS system. Koa is very simple to use and doesn’t enforce a lot of functionality on you, allowing you to pick and choose between libraries that you need and want to use. There are many possibilities and that is one of Koa’s biggest strengths. Find even more Node.js content on our Node.js page. Featuring our latest titles and most popular tutorials, it's the perfect place to learn more about Node.js. About the author Christoffer Hallas is a software developer and entrepreneur from Copenhagen, Denmark. He is a computer polyglot and contributes to and maintains a number of open source projects. When not contemplating his next grand idea (which remains an idea), he enjoys music, sports, and design of all kinds. Christoffer can be found on GitHub as hallas and at Twitter as @hamderhallas.

In this article by Paul Gerrard and Radia M. Johnson, the authors of Mastering Scientific Computation with R, we'll discuss the fundamental ideas underlying structural equation modeling, which are often overlooked in other books discussing structural equation modeling (SEM) in R, and then delve into how SEM is done in R. We will then discuss two R packages, OpenMx and lavaan. We can directly apply our discussion of the linear algebra underlying SEM using OpenMx. Because of this, we will go over OpenMx first. We will then discuss lavaan, which is probably more user friendly because it sweeps the matrices and linear algebra representations under the rug so that they are invisible unless the user really goes looking for them. Both packages continue to be developed and there will always be some features better supported in one of these packages than in the other. (For more resources related to this topic, see here.) SEM model fitting and estimation methods To ultimately find a good solution, software has to use trial and error to come up with an implied covariance matrix that matches the observed covariance matrix as well as possible. The question is what does "as well as possible" mean? The answer to this is that the software must try to minimize some particular criterion, usually some sort of discrepancy function. Just what that criterion is depends on the estimation method used. The most commonly used estimation methods in SEM include: Ordinary least squares (OLS) also called unweighted least squares Generalized least squares (GLS) Maximum likelihood (ML) There are a number of other estimation methods as well, some of which can be done in R, but here we will stick with describing the most common ones. In general, OLS is the simplest and computationally cheapest estimation method. GLS is computationally more demanding, and ML is computationally more intensive. We will see why this is, as we discuss the details of these estimation methods. Any SEM estimation method seeks to estimate model parameters that recreate the observed covariance matrix as well as possible. To evaluate how closely an implied covariance matrix matches an observed covariance matrix, we need a discrepancy function. If we assume multivariate normality of the observed variables, the following function can be used to assess discrepancy: In the preceding figure, R is the observed covariance matrix, C is the implied covariance matrix, and V is a weight matrix. The tr function refers to the trace function, which sums the elements of the main diagonal. The choice of V varies based on the SEM estimation method: For OLS, V = I For GLS, V = R-1 In the case of an ML estimation, we seek to minimize one of a number of similar criteria to describe ML, as follows: In the preceding figure, n is the number of variables. There are a couple of points worth noting here. GLS estimation inverts the observed correlation matrix, something computationally demanding with large matrices, but something that must only be done once. Alternatively, ML requires inversion of the implied covariance matrix, which changes with each iteration. Thus, each iteration requires the computationally demanding step of matrix inversion. With modern fast computers, this difference may not be noticeable, but with large SEM models, this might start to be quite time-consuming. Assessing SEM model fit The final question in an SEM model is how well the model explains the data. This is answered with the use of SEM measures of fit. Most of these measures are based on a chi-squared distribution. The fit criteria for GLS and ML (as well as a number of other estimation procedures such as asymptotic distribution-free methods) multiplied by N-1 is approximately chi-square distributed. Here, the capital N represents the number of observations in the dataset, as opposed to lower case n, which gives the number of variables. We compute degrees of freedom as the difference between the number of estimated parameters and the number of known covariances (that is, the total number of values in one triangle of an observed covariance matrix). This gives way to the first test statistic for SEM models, a chi-squared significance level comparing our chi-square value to some minimum chi-square threshold to achieve statistical significance. As with conventional chi-square testing, a chi-square value that is higher than some minimal threshold will reject the null hypothesis. Most experimental science features such as rejection supports the hypothesis of the experiment. This is not the case in SEM, where the null hypothesis is that the model fits the data. Thus, a non-significant chi-square is an indicator of model fit, whereas a significant chi-square rejects model fit. A notable limitation of this is that a greater sample size, greater N, will increase the chi-square value and will therefore increase the power to reject model fit. Thus, using conventional chi-squared testing will tend to support models developed in small samples and reject models developed in large samples. The choice an interpretation of fit measures is a contentious one in SEM literature. However, as can be seen, chi-square has limitations. As such, other model fit criteria were developed that do not penalize models that fit in large samples (some may penalize models fit to small samples though). There are over a dozen indices, but the most common fit indices and interpretation information are as follows: Comparative fit index: In this index, a higher value is better. Conventionally, a value of greater than 0.9 was considered an indicator of good model fit, but some might argue that a value of at least 0.95 is needed. This is relatively sample size insensitive. Root mean square error of approximation: A value of under 0.08 (smaller is better) is often considered necessary to achieve model fit. However, this fit measure is quite sample size sensitive, penalizing small sample studies. Tucker-Lewis index (Non-normed fit index): This is interpreted in a similar manner as the comparative fit index. Also, this is not very sample size sensitive. Standardized root mean square residual: In this index, a lower value is better. A value of 0.06 or less is considered needed for model fit. Also, this may penalize small samples. In the next section, we will show you how to actually fit SEM models in R and how to evaluate fit using fit measures. Using OpenMx and matrix specification of an SEM We went through the basic principles of SEM and discussed the basic computational approach by which this can be achieved. SEM remains an active area of research (with an entire journal devoted to it, Structural Equation Modeling), so there are many additional peculiarities, but rather than delving into all of them, we will start by delving into actually fitting an SEM model in R. OpenMx is not in the CRAN repository, but it is easily obtainable from the OpenMx website, by typing the following in R: source('http://openmx.psyc.virginia.edu/getOpenMx.R')" Summarizing the OpenMx approach In this example, we will use OpenMx by specifying matrices as mentioned earlier. To fit an OpenMx model, we need to first specify the model and then tell the software to attempt to fit the model. Model specification involves four components: Specifying the model matrices; this has two parts: Declare starting values for the estimation Declaring which values can be estimated and which are fixed Telling OpenMx the algebraic relationship of the matrices that should produce an implied covariance matrix Giving an instruction for the model fitting criterion Providing a source of data The R commands that correspond to each of these steps are: mxMatrix mxAlgebra mxMLObjective mxData We will then pass the objects created with each of these commands to create an SEM model using mxModel. Explaining an entire example First, to make things simple, we will store the FALSE and TRUE logical values in single letter variables, which will be convenient when we have matrices full of TRUE and FALSE values as follows: F <- FALSE T <- TRUE Specifying the model matrices Specifying matrices is done with the mxMatrix function, which returns an MxMatrix object. (Note that the object starts with a capital "M" while the function starts with a lowercase "m.") Specifying an MxMatrix is much like specifying a regular R matrix, but MxMatrices has some additional components. The most notable difference is that there are actually two different matrices used to create an MxMatrix. The first is a matrix of starting values, and the second is a matrix that tells which starting values are free to be estimated and which are not. If a starting value is not freely estimable, then it is a fixed constant. Since the actual starting values that we choose do not really matter too much in this case, we will just pick one as a starting value for all parameters that we would like to be estimated. Let's take a look at the following example: mx.A <- mxMatrix( type = "Full", nrow=14, ncol=14, #Provide the Starting Values values = c(    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 ), #Tell R which values are free to be estimated    free = c(    F, F, F, F, F, F, F, F, F, F, F, F, F, F,    F, F, F, F, F, F, F, F, F, F, F, F, T, F,    F, F, F, F, F, F, F, F, F, F, F, F, T, F,    F, F, F, F, F, F, F, F, F, F, F, F, T, F,    F, F, F, F, F, F, F, F, F, F, F, F, F, F,    F, F, F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, F, F,    F, F, F, F, F, F, F, F, F, F, F, T, F, F,    F, F, F, F, F, F, F, F, F, F, F, T, F, F,    F, F, F, F, F, F, F, F, F, F, F, F, F, F,    F, F, F, F, F, F, F, F, F, F, F, T, F, F,    F, F, F, F, F, F, F, F, F, F, F, T, T, F ), byrow=TRUE,   #Provide a matrix name that will be used in model fitting name="A", ) We will now apply this same technique to the S matrix. Here, we will create two S matrices, S1 and S2. They differ simply in the starting values that they supply. We will later try to fit an SEM model using one matrix, and then the other to address problems with the first one. The difference is that S1 uses starting variances of 1 in the diagonal, and S2 uses starting variances of 5. Here, we will use the "symm" matrix type, which is a symmetric matrix. We could use the "full" matrix type, but by using "symm", we are saved from typing all of the symmetric values in the upper half of the matrix. Let's take a look at the following matrix: mx.S1 <- mxMatrix("Symm", nrow=14, ncol=14, values = c(    1,    0, 1,    0, 0, 1,    0, 1, 0, 1,    1, 0, 0, 0, 1,    0, 1, 0, 0, 0, 1,    0, 0, 1, 0, 0, 0, 1,    0, 0, 0, 1, 0, 1, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 ),      free = c(    T,    F, T,    F, F, T,    F, T, F, T,    T, F, F, F, T,    F, T, F, F, F, T,    F, F, T, F, F, F, T,    F, F, F, T, F, T, F, T,    F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, F, T ), byrow=TRUE, name="S" )   #The alternative, S2 matrix: mx.S2 <- mxMatrix("Symm", nrow=14, ncol=14, values = c(    5,    0, 5,    0, 0, 5,    0, 1, 0, 5,    1, 0, 0, 0, 5,    0, 1, 0, 0, 0, 5,    0, 0, 1, 0, 0, 0, 5,    0, 0, 0, 1, 0, 1, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5 ),         free = c(    T,    F, T,    F, F, T,    F, T, F, T,    T, F, F, F, T,    F, T, F, F, F, T,    F, F, T, F, F, F, T,    F, F, F, T, F, T, F, T,    F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, T,    F, F, F, F, F, F, F, F, F, F, F, F, F, T ), byrow=TRUE, name="S" ) mx.Filter <- mxMatrix("Full", nrow=11, ncol=14, values= c(        1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,      0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0    ),    free=FALSE,    name="Filter",    byrow = TRUE ) And finally, we will create our identity and filter matrices the same way, as follows: mx.I <- mxMatrix("Full", nrow=14, ncol=14,    values= c(        1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1    ),    free=FALSE,    byrow = TRUE,    name="I" ) Fitting the model Now, it is time to declare the model that we would like to fit using the mxModel command. This part includes steps 2 through step 4 mentioned earlier. Here, we will tell mxModel which matrices to use. We will then use the mxAlgegra command to tell R how the matrices should be combined to reproduce the implied covariance matrix. We will tell R to use ML estimation with the mxMLObjective command, and we will tell it to apply the estimation to a particular matrix algebra, which we named "C". This is simply the right-hand side of the McArdle McDonald equation. Finally, we will tell R where to get the data to use in model fitting using the following code: factorModel.1 <- mxModel("Political Democracy Model", #Model Matrices mx.A, mx.S1, mx.Filter, mx.I, #Model Fitting Instructions mxAlgebra(Filter %*% solve(I-A) %*% S %*% t(solve(I - A)) %*% t(Filter), name="C"),      mxMLObjective("C", dimnames = names(PoliticalDemocracy)),    #Data to fit mxData(cov(PoliticalDemocracy), type="cov", numObs=75) ) Now, let's tell R to fit the model and summarize the results using mxRun, as follows: summary(mxRun(factorModel.1)) Running Political Democracy Model Error in summary(mxRun(factorModel.1)) : error in evaluating the argument 'object' in selecting a method for function 'summary': Error: The job for model 'Political Democracy Model' exited abnormally with the error message: Expected covariance matrix is non-positive-definite. Uh oh! We got an error message telling us that the expected covariance matrix is not positive definite. Our observed covariance matrix is positive definite but the implied covariance matrix (at least at first) is not. This is an effect of the fact that if we multiply our starting value matrices together as specified by the McArdle McDonald equation, we get a starting implied covariance matrix. If we perform an eigenvalue decomposition of this starting implied covariance matrix, then we will find that the last eigenvalue is negative. This means a negative variance does not make much sense, and this is what "not positive definite" refers to. The good news is that this is simply our starting values, so we can fix this if we modify our starting values. In this case, we can choose values of five along the diagonal of the S matrix, and get a positive definite starting implied covariance matrix. We can rerun this using the mx.S2 matrix specified earlier and the software will proceed as follows: #Rerun with a positive definite matrix   factorModel.2 <- mxModel("Political Democracy Model", #Model Matrices mx.A, mx.S2, mx.Filter, mx.I, #Model Fitting Instructions mxAlgebra(Filter %*% solve(I-A) %*% S %*% t(solve(I - A)) %*% t(Filter), name="C"),    mxMLObjective("C", dimnames = names(PoliticalDemocracy)),    #Data to fit mxData(cov(PoliticalDemocracy), type="cov", numObs=75) )   summary(mxRun(factorModel.2)) This should provide a solution. As can be seen from the previous code, the parameters solved in the model are returned as matrix components. Just like we had to figure out how to go from paths to matrices, we now have to figure out how to go from matrices to paths (the reverse problem). In the following screenshot, we show just the first few free parameters: The preceding screenshot tells us that the parameter estimated in the position of the tenth row and twelfth column in the matrix A is 2.18. This corresponds to a path from the twelfth variable in the A matrix ind60, to the 10th variable in the matrix x2. Thus, the path coefficient from ind60 to x2 is 2.18. There are a few other pieces of information here. The first one tells us that the model has not converged but is "Mx status Green." This means that the model was still converging when it stopped running (that is, it did not converge), but an optimal solution was still found and therefore, the results are likely reliable. Model fit information is also provided suggesting a pretty good model fit with CFI of 0.99 and RMSEA of 0.032. This was a fair amount of work, and creating model matrices by hand from path diagrams can be quite tedious. For this reason, SEM fitting programs have generally adopted the ability to fit SEM by declaring paths rather than model matrices. OpenMx has the ability to allow declaration by paths, but applying model matrices has a few advantages. Principally, we get under the hood of SEM fitting. If we step back, we can see that OpenMx actually did very little for us that is specific to SEM. We told OpenMx how we wanted matrices multiplied together and which parameters of the matrix were free to be estimated. Instead of using the RAM specification, we could have passed the matrices of the LISREL or Bentler-Weeks models with the corresponding algebra methods to recreate an implied covariance matrix. This means that if we are trying to come up with our matrix specification, reproduce prior research, or apply a new SEM matrix specification method published in the literature, OpenMx gives us the power to do it. Also, for educators wishing to teach the underlying mathematical ideas of SEM, OpenMx is a very powerful tool. Fitting SEM models using lavaan If we were to describe OpenMx as the SEM equivalent of having a well-stocked pantry and full kitchen to create whatever you want, and you have the time and know how to do it, we might regard lavaan as a large freezer full of prepackaged microwavable dinners. It does not allow quite as much flexibility as OpenMx because it sweeps much of the work that we did by hand in OpenMx under the rug. Lavaan does use an internal matrix representation, but the user never has to see it. It is this sweeping under the rug that makes lavaan generally much easier to use. It is worth adding that the list of prepackaged features that are built into lavaan with minimal additional programming challenge many commercial SEM packages. The lavaan syntax The key to describing lavaan models is the model syntax, as follows: X =~ Y: Y is a manifestation of the latent variable X Y ~ X: Y is regressed on X Y ~~ X: The covariance between Y and X can be estimated Y ~ 1: This estimates the intercept for Y (implicitly requires mean structure) Y | a*t1 + b*t2: Y has two thresholds that is a and b Y ~ a * X: Y is regressed on X with coefficient a Y ~ start(a) * X: Y is regressed on X; the starting value used for estimation is a It may not be evident at first, but this model description language actually makes lavaan quite powerful. Wherever you have seen a or b in the previous examples, a variable or constant can be used in their place. The beauty of this is that multiple parameters can be constrained to be equal simply by assigning a single parameter name to them. Using lavaan, we can fit a factor analysis model to our physical functioning dataset with only a few lines of code: phys.func.data <- read.csv('phys_func.csv')[-1] names(phys.func.data) <- LETTERS[1:20] R has a built-in vector named LETTERS, which contains all of the capital letters of the English alphabet. The lower case vector letters contains the lowercase alphabet. We will then describe our model using the lavaan syntax. Here, we have a model of three latent variables, our factors, and each of them has manifest variables. Let's take a look at the following example: model.definition.1 <- ' #Factors    Cognitive =~ A + Q + R + S    Legs =~ B + C + D + H + I + J + M + N    Arms =~ E + F+ G + K +L + O + P + T    #Correlations Between Factors    Cognitive ~~ Legs    Cognitive ~~ Arms    Legs ~~ Arms ' We then tell lavaan to fit the model as follows: fit.phys.func <- cfa(model.definition.1, data=phys.func.data, ordered= c('A','B', 'C','D', 'E','F','G', 'H','I','J', 'K', 'L','M','N','O','P','Q','R', 'S', 'T')) In the previous code, we add an ordered = argument, which tells lavaan that some variables are ordinal in nature. In response, lavaan estimates polychoric correlations for these variables. Polychoric correlations assume that we binned a continuous variable into discrete categories, and attempts to explicitly model correlations assuming that there is some continuous underlying variable. Part of this requires finding thresholds (placed on an arbitrary scale) between each categorical response. (for example, threshold 1 falls between the response of 1 and 2, and so on). By telling lavaan to treat some variables as categorical, lavaan will also know to use a special estimation method. Lavaan will use diagonally weighted least squares, which does not assume normality and uses the diagonals of the polychoric correlation matrix for weights in the discrepancy function. With five response options, it is questionable as to whether polychoric correlations are truly needed. Some analysts might argue that with many response options, the data can be treated as continuous, but here we use this method to show off lavaan's capabilities. All SEM models in lavaan use the lavaan command. Here, we use the cfa command, which is one of a number of wrapper functions for the lavaan command. Others include sem and growth. These commands differ in the default options passed to the lavaan command. (For full details, see the package documentation.) Summarizing the data, we can see the loadings of each item on the factor as well as the factor intercorrelations. We can also see the thresholds between each category from the polychoric correlations as follows: summary(fit.phys.func) We can also assess things such as model fit using the fitMeasures command, which has most of the popularly used fit measures and even a few obscure ones. Here, we tell lavaan to simply extract three measures of model fit as follows: fitMeasures(fit.phys.func, c('rmsea', 'cfi', 'srmr')) Collectively, these measures suggest adequate model fit. It is worth noting here that the interpretation of fit measures largely comes from studies using maximum likelihood estimation, and there is some debate as to how well these generalize other fitting methods. The lavaan package also has the capability to use other estimators that treat the data as truly continuous in nature. For this, a particular dataset is far from multivariate normal distributed, so an estimator such as ML is appropriate to use. However, if we wanted to do so, the syntax would be as follows: fit.phys.func.ML <- cfa(model.definition.1, data=phys.func.data, estimator = 'ML') Comparing OpenMx to lavaan It can be seen that lavaan has a much simpler syntax that allows to rapidly model basic SEM models. However, we were a bit unfair to OpenMx because we used a path model specification for lavaan and a matrix specification for OpenMx. The truth is that OpenMx is still probably a bit wordier than lavaan, but let's apply a path model specification in each to do a fair head-to-head comparison. We will use the famous Holzinger-Swineford 1939 dataset here from the lavaan package to do our modeling, as follows: hs.dat <- HolzingerSwineford1939 We will create a new dataset with a shorter name so that we don't have to keep typing HozlingerSwineford1939. Explaining an example in lavaan We will learn to fit the Holzinger-Swineford model in this section. We will start by specifying the SEM model using the lavaan model syntax: hs.model.lavaan <- ' visual =~ x1 + x2 + x3 textual =~ x4 + x5 + x6 speed   =~ x7 + x8 + x9   visual ~~ textual visual ~~ speed textual ~~ speed '   fit.hs.lavaan <- cfa(hs.model.lavaan, data=hs.dat, std.lv = TRUE) summary(fit.hs.lavaan) Here, we add the std.lv argument to the fit function, which fixes the variance of the latent variables to 1. We do this instead of constraining the first factor loading on each variable to 1. Only the model coefficients are included for ease of viewing in this book. The result is shown in the following model: > summary(fit.hs.lavaan) …                      Estimate Std.err Z-value P(>|z|) Latent variables: visual =~    x1               0.900   0.081   11.127   0.000    x2               0.498   0.077   6.429   0.000    x3              0.656   0.074   8.817   0.000 textual =~    x4               0.990   0.057   17.474   0.000    x5               1.102   0.063   17.576   0.000    x6               0.917   0.054   17.082   0.000 speed =~    x7               0.619   0.070   8.903   0.000    x8               0.731   0.066   11.090   0.000    x9               0.670   0.065   10.305   0.000   Covariances: visual ~~    textual           0.459   0.064   7.189   0.000    speed             0.471   0.073   6.461   0.000 textual ~~    speed             0.283   0.069   4.117   0.000 Let's compare these results with a model fit in OpenMx using the same dataset and SEM model. Explaining an example in OpenMx The OpenMx syntax for path specification is substantially longer and more explicit. Let's take a look at the following model: hs.model.open.mx <- mxModel("Holzinger Swineford", type="RAM",      manifestVars = names(hs.dat)[7:15], latentVars = c('visual', 'textual', 'speed'),    # Create paths from latent to observed variables mxPath(        from = 'visual',        to = c('x1', 'x2', 'x3'),    free = c(TRUE, TRUE, TRUE),    values = 1          ), mxPath(        from = 'textual',        to = c('x4', 'x5', 'x6'),        free = c(TRUE, TRUE, TRUE),        values = 1      ), mxPath(    from = 'speed',    to = c('x7', 'x8', 'x9'),    free = c(TRUE, TRUE, TRUE),    values = 1      ), # Create covariances among latent variables mxPath(    from = 'visual',    to = 'textual',    arrows=2,    free=TRUE      ), mxPath(        from = 'visual',        to = 'speed',        arrows=2,        free=TRUE      ), mxPath(        from = 'textual',        to = 'speed',        arrows=2,        free=TRUE      ), #Create residual variance terms for the latent variables mxPath(    from= c('visual', 'textual', 'speed'),    arrows=2, #Here we are fixing the latent variances to 1 #These two lines are like st.lv = TRUE in lavaan    free=c(FALSE,FALSE,FALSE),    values=1 ), #Create residual variance terms mxPath( from= c('x1', 'x2', 'x3', 'x4', 'x5', 'x6', 'x7', 'x8', 'x9'),    arrows=2, ),    mxData(        observed=cov(hs.dat[,c(7:15)]),        type="cov",        numObs=301    ) )     fit.hs.open.mx <- mxRun(hs.model.open.mx) summary(fit.hs.open.mx) Here are the results of the OpenMx model fit, which look very similar to lavaan's. This gives a long output. For ease of viewing, only the most relevant parts of the output are included in the following model (the last column that R prints giving the standard error of estimates is also not shown here): > summary(fit.hs.open.mx) …   free parameters:                            name matrix     row     col Estimate Std.Error 1   Holzinger Swineford.A[1,10]     A     x1 visual 0.9011177 2   Holzinger Swineford.A[2,10]     A     x2 visual 0.4987688 3   Holzinger Swineford.A[3,10]     A     x3 visual 0.6572487 4   Holzinger Swineford.A[4,11]     A     x4 textual 0.9913408 5   Holzinger Swineford.A[5,11]     A     x5 textual 1.1034381 6   Holzinger Swineford.A[6,11]     A     x6 textual 0.9181265 7   Holzinger Swineford.A[7,12]     A     x7   speed 0.6205055 8   Holzinger Swineford.A[8,12]     A     x8 speed 0.7321655 9   Holzinger Swineford.A[9,12]     A     x9   speed 0.6710954 10   Holzinger Swineford.S[1,1]     S     x1     x1 0.5508846 11   Holzinger Swineford.S[2,2]     S     x2     x2 1.1376195 12   Holzinger Swineford.S[3,3]     S    x3     x3 0.8471385 13   Holzinger Swineford.S[4,4]     S     x4     x4 0.3724102 14   Holzinger Swineford.S[5,5]     S     x5     x5 0.4477426 15   Holzinger Swineford.S[6,6]     S     x6     x6 0.3573899 16   Holzinger Swineford.S[7,7]      S     x7     x7 0.8020562 17   Holzinger Swineford.S[8,8]     S     x8     x8 0.4893230 18   Holzinger Swineford.S[9,9]     S     x9     x9 0.5680182 19 Holzinger Swineford.S[10,11]     S visual textual 0.4585093 20 Holzinger Swineford.S[10,12]     S visual   speed 0.4705348 21 Holzinger Swineford.S[11,12]     S textual   speed 0.2829848 In summary, the results agree quite closely. For example, looking at the coefficient for the path going from the latent variable visual to the observed variable x1, lavaan gives an estimate of 0.900 while OpenMx computes a value of 0.901. Summary The lavaan package is user friendly, pretty powerful, and constantly adding new features. Alternatively, OpenMx has a steeper learning curve but tremendous flexibility in what it can do. Thus, lavaan is a bit like a large freezer full of prepackaged microwavable dinners, whereas OpenMx is like a well-stocked pantry with no prepared foods but a full kitchen that will let you prepare it if you have the time and the know-how. To run a quick analysis, it is tough to beat the simplicity of lavaan, especially given its wide range of capabilities. For large complex models, OpenMx may be a better choice. The methods covered here are useful to analyze statistical relationships when one has all of the data from events that have already occurred. Resources for Article: Further resources on this subject: Creating your first heat map in R [article] Going Viral [article] Introduction to S4 Classes [article]

In this article by John Horton, author of the book Learning Java by Building Android Games, we will learn how to set up our development environment by installing JDK and Android Studio. We will also learn how to create a new game activity and layout the same on a game screen UI. (For more resources related to this topic, see here.) Setting up our development environment The first thing we need to do is prepare our PC to develop for Android using Java. Fortunately, this is made quite simple for us. The next two tutorials have Windows-specific instructions and screenshots. However, it shouldn't be too difficult to vary the steps slightly to suit Mac or Linux. All we need to do is: Install a software package called the Java Development Kit (JDK), which allows us to develop in Java. Install Android Studio, a program designed to make Android development fast and easy. Android Studio uses the JDK and some other Android-specific tools that automatically get installed when we install Android Studio. Installing the JDK The first thing we need to do is get the latest version of the JDK. To complete this guide, perform the following steps: You need to be on the Java website, so visit http://www.oracle.com/technetwork/java/javase/downloads/index.html. Find the three buttons shown in the following screenshot and click on the one that says JDK (highlighted). They are on the right-hand side of the web page. Click on the DOWNLOAD button under the JDK option: You will be taken to a page that has multiple options to download the JDK. In the Product/File description column, you need to click on the option that matches your operating system. Windows, Mac, Linux and some other less common options are all listed. A common question here is, "do I have 32- or 64-bit windows?". To find out, right-click on your My Computer (This PC on Windows 8) icon, click on the Properties option, and look under the System heading in the System type entry, as shown in the following screenshot: Click on the somewhat hidden Accept License Agreement checkbox: Now click on the download option for your OS and system type as previously determined. Wait for the download to finish. In your Downloads folder, double-click on the file you just downloaded. The latest version at time of writing this for a 64-bit Windows PC was jdk-8u5-windows-x64. If you are using Mac/Linux or have a 32-bit OS, your filename will vary accordingly. In the first of several install dialogs, click on the Next button and you will see the next dialog box: Accept the defaults shown in the previous screenshot by clicking on Next. In the next dialog box, you can accept the default install location by clicking on Next. Next is the last dialog of the Java installer. Click on Close. The JDK is now installed. Next we will make sure that Android Studio is able to use the JDK. Right-click on your My Computer (This PC on Windows 8) icon and navigate to Properties | Advanced system settings | Environment variables | New (under System variables, not under User variables). Now you can see the New System Variable dialog, as shown in the following screenshot: Type JAVA_HOME for Variable name and enter C:Program FilesJavajdk1.8.0_05 for the Variable value field. If you installed the JDK somewhere else, then the file path you enter in the Variable value: field will need to point to wherever you put it. Your exact file path will likely have a different ending to match the latest version of Java at the time you downloaded it. Click on OK to save your new settings. Now click on OK again to clear the Advanced system settings dialog. Now we have the JDK installed on our PC. We are about half way towards starting to learn Java programming, but we need a friendly way to interact with the JDK and to help us make Android games in Java. Android Studio We learned that Android Studio is a tool that simplifies Android development and uses the JDK to allow us to write and build Java programs. There are other tools you can use instead of Android Studio. There are pros and cons in them all. For example, another extremely popular option is Eclipse. And as with so many things in programming, a strong argument can be made as to why you should use Eclipse instead of Android Studio. I use both, but what I hope you will love about Android Studio are the following elements: It is a very neat and, despite still being under development, a very refined and clean interface. It is much easier to get started compared to Eclipse because several Android tools that would otherwise need to be installed separately are already included in the package. Android Studio is being developed by Google, based on another product called IntelliJ IDEA. There is a chance it will be the standard way to develop Android in the not-too-distant future. If you want to use Eclipse, that's fine. However, some the keyboard shortcuts and user interface buttons will obviously be different. If you do not have Eclipse installed already and have no prior experience with Eclipse, then I even more strongly recommend you to go ahead with Android Studio. Installing Android Studio So without any delay, let's get Android Studio installed and then we can begin our first game project. To do this, let's visit https://developer.android.com/sdk/installing/studio.html. Click on the button labeled Download Android Studio to start the Android studio download. This will take you to another web page with a very similar-looking button to the one you just clicked on. Accept the license by checking in the checkbox, commence the download by clicking on the button labeled Download Android Studio for Windows, and wait for the download to complete. The exact text on the button will probably vary depending on the current latest version. In the folder in which you just downloaded Android Studio, right-click on the android-studio-bundle-135.12465-windows.exe file and click on Run as administrator. The end of your filename will vary depending upon the version of Android Studio and your operating system. When asked if you want to Allow the following program from an unknown publisher to make changes to your computer, click on Yes. On the next screen, click on Next. On the screen shown in the following screenshot, you can choose which users of your PC can use Android Studio. Choose whatever is right for you as all options will work, and then click on Next: In the next dialog, leave the default settings and then click on Next. Then on the Choose start menu folder dialog box, leave the defaults and click on Install. On the Installation complete dialog, click on Finish to run Android Studio for the first time. The next dialog is for users who have already used Android Studio, so assuming you are a first time user, select the I do not have a previous version of Android Studio or I do not want to import my settings checkbox, and then click on OK: That was the last piece of software we needed. Math game – asking a question Now that we have all that knowledge under our belts, we can use it to improve our math game. First, we will create a new Android activity to be the actual game screen as opposed to the start menu screen. We will then use the UI designer to lay out a simple game screen so that we can use our Java skills with variables, types, declaration, initialization, operators, and expressions to make our math game generate a question for the player. We can then link the start menu and game screens together with a push button. Creating the new game activity We will first need to create a new Java file for the game activity code and a related layout file to hold the game activity UI. Run Android Studio and select your Math Game Chapter 2 project. It might have been opened by default. Now we will create the new Android activity that will contain the actual game screen, which will run when the player taps the Play button on our main menu screen. To create a new activity, we now need another layout file and another Java file. Fortunately Android Studio will help us do this. To get started with creating all the files we need for a new activity, right-click on the src folder in the Project Explorer and then go to New | Activity. Now click on Blank Activity and then on Next. We now need to tell Android Studio a little bit about our new activity by entering information in the above dialog box. Change the Activity Name field to GameActivity. Notice how the Layout Name field is automatically changed for us to activity_game and the Title field is automatically changed to GameActivity. Click on Finish. Android Studio has created two files for us and has also registered our new activity in a manifest file, so we don't need to concern ourselves with it. If you look at the tabs at the top of the editor window, you will see that GameActivity.java has been opened up ready for us to edit, as shown in the following screenshot: Ensure that GameActivity.java is active in the editor window by clicking on the GameActivity.java tab shown previously. Here, we can see the code that is unnecessary. If we remove it, then it will make our working environment simpler and cleaner. We will simply use the code from MainActivity.java as a template for GameActivity.java. We can then make some minor changes. Click on the MainActivity.java tab in the editor window. Highlight all of the code in the editor window using Ctrl + A on the keyboard. Now copy all of the code in the editor window using the Ctrl + C on the keyboard. Now click on the GameActivity.java tab. Highlight all of the code in the editor window using Ctrl + A on the keyboard. Now paste the copied code and overwrite the currently highlighted code using Ctrl + V on the keyboard. Notice that there is an error in our code denoted by the red underlining as shown in the following screenshot. This is because we pasted the code referring to MainActivity in our file that is called GameActivity. Simply change the text MainActivity to GameActivity and the error will disappear. Take a moment to see if you can work out what other minor change is necessary, before I tell you. Remember that setContentView loads our UI design. Well what we need to do is change setContentView to load the new design (that we will build next) instead of the home screen design. Change setContentView(R.layout.activity_main); to setContentView(R.layout.activity_game);. Save your work and we are ready to move on. Note the Project Explorer where Android Studio puts the two new files it created for us. I have highlighted two folders in the next screenshot. In future, I will simply refer to them as our java code folder or layout files folder. You might wonder why we didn't simply copy and paste the MainActivity.java file to begin with and saved going through the process of creating a new activity? The reason is that Android Studio does things behind the scenes. Firstly, it makes the layout template for us. It also registers the new activity for use through a file we will see later, called AndroidManifest.xml. This is necessary for the new activity to be able to work in the first place. All things considered, the way we did it is probably the quickest. The code at this stage is exactly the same as the code for the home menu screen. We state the package name and import some useful classes provided by Android: package com.packtpub.mathgamechapter3a.mathgamechapter3a;   import android.app.Activity; import android.os.Bundle; We create a new activity, this time called GameActivity: public class GameActivity extends Activity { Then we override the onCreate method and use the setContentView method to set our UI design as the contents of the player's screen. Currently, however, this UI is empty: super.onCreate(savedInstanceState);setContentView(R.layout.activity_main); We can now think about the layout of our actual game screen. Laying out the game screen UI As we know, our math game will ask questions and offer the player some multiple choices to choose answers from. There are lots of extra features we could add, such as difficulty levels, high scores, and much more. But for now, let's just stick to asking a simple, predefined question and offering a choice of three predefined possible answers. Keeping the UI design to the bare minimum suggests a layout. Our target UI will look somewhat like this: The layout is hopefully self-explanatory, but let's ensure that we are really clear; when we come to building this layout in Android Studio, the section in the mock-up that displays 2 x 2 is the question and will be made up of three text views (both numbers, and the = sign is also a separate view). Finally, the three options for the answer are made up of Button layout elements. This time, as we are going to be controlling them using our Java code, there are a few extra things we need to do to them. So let's go through it step by step: Open the file that will hold our game UI in the editor window. Do this by double-clicking on activity_game.xml. This is located in our UI layout folder, which can be found in the project explorer. Delete the Hello World TextView, as it is not required. Find the Large Text element on the palette. It can be found under the Widgets section. Drag three elements onto the UI design area and arrange them near the top of the design as shown in the next screenshot. It does not have to be exact; just ensure that they are in a row and not overlapping, as shown in the following screenshot: Notice in the Component Tree window that each of the three TextViews has been assigned a name automatically by Android Studio. They are textView , textView2, and textView3: Android Studio refers to these element names as an id. This is an important concept that we will be making use of. So to confirm this, select any one of the textViews by clicking on its name (id), either in the component tree as shown in the preceding screenshot or directly on it in the UI designer shown previously. Now look at the Properties window and find the id property. You might need to scroll a little to do this: Notice that the value for the id property is textView. It is this id that we will use to interact with our UI from our Java code. So we want to change all the IDs of our TextViews to something useful and easy to remember. If you look back at our design, you will see that the UI element with the textView id is going to hold the number for the first part of our math question. So change the id to textPartA. Notice the lowercase t in text, the uppercase P in Part, and the uppercase A. You can use any combination of cases and you can actually name the IDs anything you like. But just as with naming conventions with Java variables, sticking to conventions here will make things less error-prone as our program gets more complicated. Now select textView2 and change id to textOperator. Select the element currently with id textView3 and change it to textPartB. This TextView will hold the later part of our question. Now add another Large Text from the palette. Place it after the row of the three TextViews that we have just been editing. This Large Text will simply hold our equals to sign and there is no plan to ever change it. So we don't need to interact with it in our Java code. We don't even need to concern ourselves with changing the ID or knowing what it is. If this situation changed, we could always come back at a later time and edit its ID. However, this new TextView currently displays Large Text and we want it to display an equals to sign. So in the Properties window, find the text property and enter the value =. We have changed the text property, and you might also like to change the text property for textPartA, textPartB, and textOperator. This is not absolutely essential because we will soon see how we can change it via our Java code; however, if we change the text property to something more appropriate, then our UI designer will look more like it will when the game runs on a real device. So change the text property of textPartA to 2, textPartB to 2, and textOperator to x. Your UI design and Component tree should now look like this: For the buttons to contain our multiple choice answers, drag three buttons in a row, below the = sign. Line them up neatly like our target design. Now, just as we did for the TextViews, find the id properties of each button, and from left to right, change the id properties to buttonChoice1, buttonChoice2, and buttonChoice3. Why not enter some arbitrary numbers for the text property of each button so that the designer more accurately reflects what our game will look like, just as we did for our other TextViews? Again, this is not absolutely essential as our Java code will control the button appearance. We are now actually ready to move on. But you probably agree that the UI elements look a little lost. It would look better if the buttons and text were bigger. All we need to do is adjust the textSize property for each TextView and for each Button. Then, we just need to find the textSize property for each element and enter a number with the sp syntax. If you want your design to look just like our target design from earlier, enter 70sp for each of the TextView textSize properties and 40sp for each of the Buttons textSize properties. When you run the game on your real device, you might want to come back and adjust the sizes up or down a bit. But we have a bit more to do before we can actually try out our game. Save the project and then we can move on. As before, we have built our UI. This time, however, we have given all the important parts of our UI a unique, useful, and easy to identify ID. As we will see we are now able to communicate with our UI through our Java code. Summary In this article, we learned how to set up our development environment by installing JDK and Android Studio. In addition to this, we also learned how to create a new game activity and layout the same on a game screen UI. Resources for Article: Further resources on this subject: Sound Recorder for Android [article] Reversing Android Applications [article] 3D Modeling [article]

In this article by Jordan Krause, author of the book Windows Server 2012 R2 Administrator Cookbook, we will see how Windows Server 2012 R2 by Microsoft brings a whole new way of looking at remote access. Companies have historically relied on third-party tools to connect remote users into the network, such as traditional and SSL VPN provided by appliances from large networking vendors. I'm here to tell you those days are gone. Those of us running Microsoft-centric shops can now rely on Microsoft technologies to connect our remote workforce. Better yet is that these technologies are included with the Server 2012 R2 operating system, and have functionality that is much improved over anything that a traditional VPN can provide. Regular VPN does still have a place in the remote access space, and the great news is that you can also provide it with Server 2012 R2. Our primary focus for this article will be DirectAccess (DA). DA is kind of like automatic VPN. There is nothing the user needs to do in order to be connected to work. Whenever they are on the Internet, they are also connected automatically to the corporate network. DirectAccess is an amazing way to have your Windows 7 and Windows 8 domain joined systems connected back to the network for data access and for management of those traveling machines. DirectAccess has actually been around since 2008, but the first version came with some steep infrastructure requirements and was not widely used. Server 2012 R2 brings a whole new set of advantages and makes implementation much easier than in the past. I still find many server and networking admins who have never heard of DirectAccess, so let's spend some time together exploring some of the common tasks associated with it. In this article, we will cover the following recipes: Configuring DirectAccess, VPN, or a combination of the two Pre-staging Group Policy Objects (GPOs) to be used by DirectAccess Enhancing the security of DirectAccess by requiring certificate authentication Building your Network Location Server (NLS) on its own system  (For more resources related to this topic, see here.) There are two "flavors" of remote access available in Windows Server 2012 R2. The most common way to implement the Remote Access role is to provide DirectAccess for your Windows 7 and Windows 8 domain joined client computers, and VPN for the rest. The DirectAccess machines are typically your company-owned corporate assets. One of the primary reasons that DirectAccess is usually only for company assets is that the client machines must be joined to your domain, because the DirectAccess configuration settings are brought down to the client through a GPO. I doubt you want home and personal computers joining your domain. VPN is therefore used for down level clients such as Windows XP, and for home and personal devices that want to access the network. Since this is a traditional VPN listener with all regular protocols available such as PPTP, L2TP, SSTP, it can even work to connect devices such as smartphones. There is a third function available within the Server 2012 R2 Remote Access role, called the Web Application Proxy ( WAP ). This function is not used for connecting remote computers fully into the network as DirectAccess and VPN are; rather, WAP is used for publishing internal web resources out to the internet. For example, if you are running Exchange and Lync Server inside your network and want to publish access to these web-based resources to the internet for external users to connect to, WAP would be a mechanism that could publish access to these resources. The term for publishing out to the internet like this is Reverse Proxy, and WAP can act as such. It can also behave as an ADFS Proxy. For further information on the WAP role, please visit: http://technet.microsoft.com/en-us/library/dn584107.aspx One of the most confusing parts about setting up DirectAccess is that there are many different ways to do it. Some are good ideas, while others are not. Before we get rolling with recipes, we are going to cover a series of questions and answers to help guide you toward a successful DA deployment. The first question that always presents itself when setting up DA is "How do I assign IP addresses to my DirectAccess server?". This is quite a loaded question, because the answer depends on how you plan to implement DA, which features you plan to utilize, and even upon how secure you believe your DirectAccess server to be. Let me ask you some questions, pose potential answers to those questions, and discuss the effects of making each decision. DirectAccess Planning Q&A Which client operating systems can connect using DirectAccess? Answer: Windows 7 Ultimate, Windows 7 Enterprise, and Windows 8.x Enterprise. You'll notice that the Professional SKU is missing from this list. That is correct, Windows 7 and Windows 8 Pro do not contain the DirectAccess connectivity components. Yes, this does mean that Surface Pro tablets cannot utilize DirectAccess out of the box. However, I have seen many companies now install Windows 8 Enterprise onto their Surface tablets, effectively turning them into "Surface Enterprises." This works fine and does indeed enable them to be DirectAccess clients. In fact, I am currently typing this text on a DirectAccess-connected Surface "Pro turned Enterprise" tablet. Do I need one or two NICs on my DirectAccess server? Answer: Technically, you could set it up either way. In practice however, it really is designed for dual-NIC implementation. Single NIC DirectAccess works okay sometimes to establish a proof-of-concept to test out the technology. But I have seen too many problems with single NIC implementation in the field to ever recommend it for production use. Stick with two network cards, one facing the internal network and one facing the Internet. Do my DirectAccess servers have to be joined to the domain? Answer: Yes. Does DirectAccess have site-to-site failover capabilities? Answer: Yes, though only Windows 8.x client computers can take advantage of it. This functionality is called Multi-Site DirectAccess. Multiple DA servers that are spread out geographically can be joined together in a multi-site array. Windows 8 client computers keep track of each individual entry point and are able to swing between them as needed or at user preference. Windows 7 clients do not have this capability and will always connect through their primary site. What are these things called 6to4, Teredo, and IP-HTTPS I have seen in the Microsoft documentation? Answer: 6to4, Teredo, and IP-HTTPS are all IPv6 transition tunneling protocols. All DirectAccess packets that are moving across the internet between DA client and DA server are IPv6 packets. If your internal network is IPv4, then when those packets reach the DirectAccess server they get turned down into IPv4 packets, by some special components called DNS64 and NAT64. While these functions handle the translation of packets from IPv6 into IPv4 when necessary inside the corporate network, the key point here is that all DirectAccess packets that are traveling over the Internet part of the connection are always IPv6. Since the majority of the Internet is still IPv4, this means that we must tunnel those IPv6 packets inside something to get them across the Internet. That is the job of 6to4, Teredo, and IP-HTTPS. 6to4 encapsulates IPv6 packets into IPv4 headers and shuttles them around the internet using protocol 41. Teredo similarly encapsulates IPv6 packets inside IPv4 headers, but then uses UDP port 3544 to transport them. IP-HTTPS encapsulates IPv6 inside IPv4 and then inside HTTP encrypted with TLS, essentially creating an HTTPS stream across the Internet. This, like any HTTPS traffic, utilizes TCP port 443. The DirectAccess traffic traveling inside either kind of tunnel is always encrypted, since DirectAccess itself is protected by IPsec. Do I want to enable my clients to connect using Teredo? Answer: Most of the time, the answer here is yes. Probably the biggest factor that weighs on this decision is whether or not you are still running Windows 7 clients. When Teredo is enabled in an environment, this gives the client computers an opportunity to connect using Teredo, rather than all clients connecting in over the IP-HTTPS protocol. IP-HTTPS is sort of the "catchall" for connections, but Teredo will be preferred by clients if it is available. For Windows 7 clients, Teredo is quite a bit faster than IP-HTTPS. So enabling Teredo on the server side means your Windows 7 clients (the ones connecting via Teredo) will have quicker response times, and the load on your DirectAccess server will be lessened. This is because Windows 7 clients who are connecting over IP-HTTPS are encrypting all of the traffic twice. This also means that the DA server is encrypting/decrypting everything that comes and goes twice. In Windows 8, there is an enhancement that brings IP-HTTPS performance almost on par with Teredo, and so environments that are fully cut over to Windows 8 will receive less benefit from the extra work that goes into making sure Teredo works. Can I place my DirectAccess server behind a NAT? Answer: Yes, though there is a downside. Teredo cannot work if the DirectAccess server is sitting behind a NAT. For Teredo to be available, the DA server must have an External NIC that has two consecutive public IP addresses. True public addresses. If you place your DA server behind any kind of NAT, Teredo will not be available and all clients will connect using the IP-HTTPS protocol. Again, if you are using Windows 7 clients, this will decrease their speed and increase the load on your DirectAccess server. How many IP addresses do I need on a standalone DirectAccess server? Answer: I am going to leave single NIC implementation out of this answer since I don't recommend it anyway. For scenarios where you are sitting the External NIC behind a NAT or, for any other reason, are limiting your DA to IP-HTTPS only, then we need one external address and one internal address. The external address can be a true public address or a private NATed DMZ address. Same with the internal; it could be a true internal IP or a DMZ IP. Make sure both NICs are not plugged into the same DMZ, however. For a better installation scenario that allows Teredo connections to be possible, you would need two consecutive public IP addresses on the External NIC and a single internal IP on the Internal NIC. This internal IP could be either true internal or DMZ. But the public IPs would really have to be public for Teredo to work. Do I need an internal PKI? Answer: Maybe. If you want to connect Windows 7 clients, then the answer is yes. If you are completely Windows 8, then technically you do not need internal PKI. But you really should use it anyway. Using an internal PKI, which can be a single, simple Windows CA server, increases the security of your DirectAccess infrastructure. You'll find out during this article just how easy it is to require certificates as part of the tunnel building authentication process. Configuring DirectAccess, VPN, or a combination of the two Now that we have some general ideas about how we want to implement our remote access technologies, where do we begin? Most services that you want to run on a Windows Server begin with a role installation, but the implementation of remote access begins before that. Let's walk through the process of taking a new server and turning it into a Microsoft Remote Access server. Getting ready All of our work will be accomplished on a new Windows Server 2012 R2. We are taking the two-NIC approach to networking, and so we have two NICs installed on this server. The Internal NIC is plugged into the corporate network and the External NIC is plugged into the Internet for the sake of simplicity. The External NIC could just as well be plugged into a DMZ. How to do it... Follow these steps to turn your new server into a Remote Access server: Assign IP addresses to your server. Remember, the most important part is making sure that the Default Gateway goes on the External NIC only. Join the new server to your domain. Install an SSL certificate onto your DirectAccess server that you plan to use for the IP-HTTPS listener. This is typically a certificate purchased from a public CA. If you're planning to use client certificates for authentication, make sure to pull down a copy of the certificate to your DirectAccess server. You want to make sure certificates are in place before you start with the configuration of DirectAccess. This way the wizards will be able to automatically pull in information about those certificates in the first run. If you don't, DA will set itself up to use self-signed certificates, which are a security no-no. Use Server Manager to install the Remote Access role. You should only do this after completing the steps listed earlier. If you plan to load balance multiple DirectAccess servers together at a later time, make sure to also install the feature called Network Load Balancing . After selecting your role and feature, you will be asked which Remote Access role services you want to install. For our purposes in getting the remote workforce connected back into the corporate network, we want to choose DirectAccess and VPN (RAS) .  Now that the role has been successfully installed, you will see a yellow exclamation mark notification near the top of Server Manager indicating that you have some Post-deployment Configuration that needs to be done. Do not click on Open the Getting Started Wizard ! Unfortunately, Server Manager leads you to believe that launching the Getting Started Wizard (GSW) is the logical next step. However, using the GSW as the mechanism for configuring your DirectAccess settings is kind of like roasting a marshmallow with a pair of tweezers. In order to ensure you have the full range of options available to you as you configure your remote access settings, and that you don't get burned later, make sure to launch the configuration this way: Click on the Tools menu from inside Server Manager and launch the Remote Access Management Console . In the left window pane, click on Configuration | DirectAccess and VPN . Click on the second link, the one that says Run the Remote Access Setup Wizard . Please note that once again the top option is to run that pesky Getting Started Wizard. Don't do it! I'll explain why in the How it works… section of this recipe. Now you have a choice that you will have to answer for yourself. Are you configuring only DirectAccess, only VPN, or a combination of the two? Simply click on the option that you want to deploy. Following your choice, you will see a series of steps (steps 1 through 4) that need to be accomplished. This series of mini-wizards will guide you through the remainder of the DirectAccess and VPN particulars. This recipe isn't large enough to cover every specific option included in those wizards, but at least you now know the correct way to bring a DirectAccess/VPN server into operation. How it works... The remote access technologies included in Server 2012 R2 have great functionality, but their initial configuration can be confusing. Following the procedure listed in this recipe will set you on the right path to be successful in your deployment, and prevent you from running into issues down the road. The reason that I absolutely recommend you stay away from using the "shortcut" deployment method provided by the Getting Started Wizard is twofold: GSW skips a lot of options as it sets up DirectAccess, so you don't really have any understanding of how it works after finishing. You may have DA up and running, but have no idea how it's authenticating or working under the hood. This holds so much potential for problems later, should anything suddenly stop working. GSW employs a number of bad security practices in order to save time and effort in the setup process. For example, using the GSW usually means that your DirectAccess server will be authenticating users without client certificates, which is not a best practice. Also, it will co-host something called the NLS website on itself, which is also not a best practice. Those who utilize the GSW to configure DirectAccess will find that their GPO, which contains the client connectivity settings, will be security-filtered to the Domain Computers group. Even though it also contains a WMI filter that is supposed to limit that policy application to mobile hardware such as laptops, this is a terribly scary thing to see inside GPO filtering settings. You probably don't want all of your laptops to immediately start getting DA connectivity settings, but that is exactly what the GSW does for you. Perhaps worst, the GSW will create and make use of self-signed SSL certificates to validate its web traffic, even the traffic coming in from the Internet! This is a terrible practice and is the number one reason that should convince you that clicking on the Getting Started Wizard is not in your best interests. Pre-staging Group Policy Objects (GPOs) to be used by DirectAccess One of the great things about DirectAccess is that all of the connectivity settings the client computers need in order to connect are contained within a Group Policy Object (GPO). This means that you can turn new client computers into DirectAccess-connected clients without ever touching that system. Once configured properly, all you need to do is add the new computer account to an Active Directory security group, and during the next automatic Group Policy refresh cycle (usually within 90 minutes), that new laptop will be connecting via DirectAccess whenever outside the corporate network. You can certainly choose not to pre-stage anything with the GPOs and DirectAccess will still work. When you get to the end of the DA configuration wizards, it will inform you that two new GPOs are about to be created inside Active Directory. One GPO is used to contain the DirectAccess server settings and the other GPO is used to contain the DirectAccess client settings. If you allow the wizard to handle the generation of these GPOs, it will create them, link them, filter them, and populate them with settings automatically. About half of the time I see folks do it this way and they are forever happy with letting the wizard manage those GPOs now and in the future. The other half of the time, it is desired that we maintain a little more personal control over the GPOs. If you are setting up a new DA environment but your credentials don't have permission to create GPOs, the wizard is not going to be able to create them either. In this case, you will need to work with someone on your Active Directory team to get them created. Another reason to manage the GPOs manually is to have better control over placement of these policies. When you let the DirectAccess wizard create the GPOs, it will link them to the top level of your domain. It also sets Security Filtering on those GPOs so they are not going to be applied to everything in your domain, but when you open up the Group Policy Management Console you will always see those DirectAccess policies listed right up there at the top level of the domain. Sometimes this is simply not desirable. So for this reason also, you may want to choose to create and manage the GPOs by hand, so that we can secure placement and links where we specifically want them to be located. The key factors here are to make sure your DirectAccess Server Settings GPO applies to only the DirectAccess server or servers in your environment. And that the DirectAccess Client Settings GPO applies to only the DA client computers that you plan to enable in your network. The best practice here is to specify this GPO to only apply to a specific Active Directory security group so that you have full control over which computer accounts are in that group. I have seen some folks do it based only on the OU links and include whole OUs in the filtering for the clients GPO (foregoing the use of an AD group at all), but doing it this way makes it quite a bit more difficult to add or remove machines from the access list in the future. Requiring certificates as part of your DirectAccess tunnel authentication process is a good idea in any environment. It makes the solution more secure, and enables advanced functionality. The primary driver for most companies to require these certificates is the enablement of Windows 7 clients to connect via DirectAccess, but I suggest that anyone using DirectAccess in any capacity make use of these certs. They are simple to deploy, easy to configure, and give you some extra peace of mind that only computers who have a certificate issued directly to them from your own internal CA server are going to be able to connect through your DirectAccess entry point. Getting ready While the DirectAccess wizards themselves are run from the DirectAccess server, our work with this recipe is not. The Group Policy settings that we will be configuring are all accomplished within Active Directory, and we will be doing the work from a Domain Controller in our environment. How to do it... To pre-stage Group Policy Objects (GPOs) for use with DirectAccess: On your Domain Controller, launch the Group Policy Management Console . Expand Forest | Domains | Your Domain Name . There should be a listing here called Group Policy Object . Right-click on that and choose New . Name your new GPO something like DirectAccess Server Settings. Click on the new DirectAccess Server Settings GPO and it should open up automatically to the Scope tab. We need to adjust the Security Filtering section so that this GPO only applies to our DirectAccess server. This is a critical step for each GPO to ensure the settings that are going to be placed here do not get applied to the wrong computers. Remove Authenticated Users that is prepopulated in that list. The list should now be empty. Click the Add… button and search for the computer account of your DirectAccess server. Mine is called RA-01. By default this window will only search user accounts, so you will need to adjust Object Types to include Computers before it will allow you to add your server into this filtering list. Your Security Filtering list should now look like this:  Now click on the Details tab of your GPO. Change the GPO Status to be User configuration settings disabled . We do this because our GPO is only going to contain computer-level settings, nothing at the user level. The last thing to do is link your GPO to an appropriate container. Since we have Security Filtering enabled, our GPO is only ever going to apply its settings to the RA-01 server; however, without creating a link, the GPO will not even attempt to apply itself to anything. My RA-01 server is sitting inside the OU called Remote Access Servers . So I will right-click on my Remote Access Servers OU and choose Link an Existing GPO… .  Choose the new DirectAccess Server Settings from the list of available GPOs and click on the OK button. This creates the link and puts the GPO into action. Since there are not yet any settings inside the GPO, it won't actually make any changes on the server. The DirectAccess configuration wizards take care of populating the GPO with the settings that are needed. Now we simply need to rinse and repeat all of these steps to create another GPO, something like DirectAccess Client Settings . You want to set up the client settings GPO in the same way. Make sure that it is filtering to only the Active Directory Security Group that you created to contain your DirectAccess client computers. And make sure to link it to an appropriate container that will include those computer accounts. So maybe your clients GPO will look something like this:  How it works... Creating GPOs in Active Directory is a simple enough task, but it is critical that you configure the Links and Security Filtering correctly. If you do not take care to ensure that these DirectAccess connection settings are only going to apply to the machines that actually need the settings, you could create a world of trouble by internal servers getting remote access connection settings and cause them issues with connection while inside the network. Enhancing the security of DirectAccess by requiring certificate authentication When a DirectAccess client computer builds its IPsec tunnels back to the corporate network, it has the ability to require a certificate as part of that authentication process. In earlier versions of DirectAccess, the one in Server 2008 R2 and the one provided by Unified Access Gateway ( UAG ), these certificates were required in order to make DirectAccess work. Setting up the certificates really isn't a big deal at all; as long as there is a CA server in your network you are already prepared to issue the certs needed at no cost. Unfortunately, though, there must have been enough complaints back to Microsoft in order for them to make these certificates "recommended" instead of "required" and they created a new mechanism in Windows 8 and Server 2012 called KerberosProxy that can be used to authenticate the tunnels instead. This allows the DirectAccess tunnels to build without the computer certificate, making that authentication process less secure. I'm here to strongly recommend that you still utilize certificates in your installs! They are not difficult to set up, and using them makes your tunnel authentication stronger. Further, many of you may not have a choice and will still be required to install these certificates. Only simple DirectAccess scenarios that are all Windows 8 on the client side can get away with the shortcut method of foregoing certs. Anybody who still wants to connect Windows 7 via DirectAccess will need to use certificates on all of their client computers, both Windows 7 and Windows 8. In addition to Windows 7 access, anyone who intends to use the advanced features of DirectAccess such as load balancing, multi-site, or two-factor authentication will also need to utilize these certificates. With any of these scenarios, certificates become a requirement again, not a recommendation. In my experience, almost everyone still has Windows 7 clients that would benefit from being DirectAccess connected, and it's always a good idea to make your DA environment redundant by having load balanced servers. This further emphasizes the point that you should just set up certificate authentication right out of the gate, whether or not you need it initially. You might decide to make a change later that would require certificates and it would be easier to have them installed from the get-go rather than trying to incorporate them later into a running DA environment. Getting ready In order to distribute certificates, you will need a CA server running in your network. Once certificates are distributed to the appropriate places, the rest of our work will be accomplished from our Server 2012 R2 DirectAccess server. How to do it... Follow these steps to make use of certificates as part of the DirectAccess tunnel authentication process: The first thing that you need to do is distribute certificates to your DirectAccess servers and all DirectAccess client computers. The easiest way to do this is by using the built-in Computer template provided by default in a Windows CA server. If you desire to build a custom certificate template for this purpose, you can certainly do so. I recommend that you duplicate the Computer template and build it from there. Whenever I create a custom template for use with DirectAccess, I try to make sure that it meets the following criterias: The Subject Name of the certificate should match the Common Name of the computer (which is also the FQDN of the computer). The Subject Alternative Name ( SAN ) of the certificate should match the DNS Name of the computer (which is also the FQDN of the computer). The certificate should serve the Intended Purposes of both Client Authentication and Server Authentication . You can issue the certificates manually using Microsoft Management Console (MMC). Otherwise, you can lessen your hands-on administrative duties by enabling Autoenrollment. Now that we have certificates distributed to our DirectAccess clients and servers, log in to your primary DirectAccess server and open up the Remote Access Management Console . Click on Configuration in the top-left corner. You should now see steps 1 through 4 listed. Click Edit… listed under Step 2 . Now you can either click Next twice or click on the word Authentication to jump directly to the authentication screen. Check the box that says Use computer certificates . Now we have to specify the Certification Authority server that issued our client certificates. If you used an intermediary CA to issue your certs, make sure to check the appropriate checkbox. Otherwise, most of the time, certificates are issued from a root CA and in this case you would simply click on the Browse… button and look for your CA in the list. This screen is sometimes confusing because people expect to have to choose the certificate itself from the list. This is not the case. What you are actually choosing from this list is the Certificate Authority server that issued the certificates. Make any other appropriate selections on the Authentication screen. For example, many times when we require client certificates for authentication, it is because we have Windows 7 computers that we want to connect via DirectAccess. If that is the case for you, select the checkbox for Enable Windows 7 client computers to connect via DirectAccess .  How it works... Requiring certificates as part of your DirectAccess tunnel authentication process is a good idea in any environment. It makes the solution more secure, and enables advanced functionality. The primary driver for most companies to require these certificates is the enablement of Windows 7 clients to connect via DirectAccess, but I suggest that anyone using DirectAccess in any capacity make use of these certs. They are simple to deploy, easy to configure, and give you some extra peace of mind that only computers who have a certificate issued directly to them from your own internal CA server are going to be able to connect through your DirectAccess entry point. Building your Network Location Server (NLS) on its own system If you zipped through the default settings when configuring DirectAccess, or worse used the Getting Started Wizard, chances are that your Network Location Server ( NLS ) is running right on the DirectAccess server itself. This is not the recommended method for using NLS, it really should be running on a separate web server. In fact, if you later want to do something more advanced such as setting up load balanced DirectAccess servers, you're going to have to move NLS off onto a different server anyway. So you might as well do it right the first time. NLS is a very simple requirement, yet a critical one. It is just a website, it doesn't matter what content the site has, and it only has to run inside your network. Nothing has to be externally available. In fact, nothing should be externally available, because you only want this site being accessed internally. This NLS website is a large part of the mechanism by which DirectAccess client computers figure out when they are inside the office and when they are outside. If they can see the NLS website, they know they are inside the network and will disable DirectAccess name resolution, effectively turning off DA. If they do not see the NLS website, they will assume they are outside the corporate network and enable DirectAccess name resolution. There are two gotchas with setting up an NLS website: The first is that it must be HTTPS, so it does need a valid SSL certificate. Since this website is only running inside the network and being accessed from domain-joined computers, this SSL certificate can easily be one that has been issued from your internal CA server. So no cost associated there. The second catch that I have encountered a number of times is that for some reason the default IIS splash screen page doesn't make for a very good NLS website. If you set up a standard IIS web server and use the default site as NLS, sometimes it works to validate the connections and sometimes it doesn't. Given that, I always set up a specific site that I create myself, just to be on the safe side. So let's work together to follow the exact process I always take when setting up NLS websites in a new DirectAccess environment. Getting ready Our NLS website will be hosted on an IIS server we have that runs Server 2012 R2. Most of the work will be accomplished from this web server, but we will also be creating a DNS record and will utilize a Domain Controller for that task. How to do it... Let's work together to set up our new Network Location Server website: First decide on an internal DNS name to use for this website and set it up in DNS of your domain. I am going to use nls.mydomain.local and am creating a regular Host (A) record that points nls.mydomain.local at the IP address of my web server. Now log in to that web server and let's create some simple content for this new website. Create a new folder called C:NLS. Inside your new folder, create a new Default.htm file. Edit this file and throw some simple text in there. I usually say something like This is the NLS website used by DirectAccess. Please do not delete or modify me!.  Remember, this needs to be an HTTPS website, so before we try setting up the actual website, we should acquire the SSL certificate that we need to use with this site. Since this certificate is coming from my internal CA server, I'm going to open up MMC on my web server to accomplish this task. Once MMC is opened, snap-in the Certificates module. Make sure to choose Computer account and then Local computer when it prompts you for which certificate store you want to open. Expand Certificates (Local Computer) | Personal | Certificates . Right-click on this Certificates folder and choose All Tasks | Request New Certificate… . Click Next twice and you should see your list of certificate templates that are available on your internal CA server. If you do not see one that looks appropriate for requesting a website certificate, you may need to check over the settings on your CA server to make sure the correct templates are configured for issuing. My template is called Custom Web Server . Since this is a web server certificate, there is some additional information that I need to provide in my request in order to successfully issue a certificate. So I go ahead and click on that link that says More information is required to enroll for this certificate. Click here to configure settings. .  Drop-down the Subject name | Type menu and choose the option Common name . Enter a common name for our website into the Value field, which in my case is nls.mydomain.local. Click the Add button and your CN should move over to the right side of the screen like this:  Click on OK then click on the Enroll button. You should now have an SSL certificate sitting in your certificates store that can be used to authenticate traffic moving to our nls.mydomain.local name. Open up Internet Information Services (IIS) Manager , and browse to the Sites folder. Go ahead and remove the default website that IIS automatically set up, so that we can create our own NLS website without any fear of conflict. Click on the Add Website… action. Populate the information as shown in the following screenshot. Make sure to choose your own IP address and SSL certificate from the lists, of course:  Click the OK button and you now have an NLS website running successfully in your network. You should be able to open up a browser on a client computer sitting inside the network and successfully browse to https://nls.mydomain.local. How it works... In this recipe, we configured a basic Network Location Server website for use with our DirectAccess environment. This site will do exactly what we need it to when our DA client computers try to validate whether they are inside or outside the corporate network. While this recipe meets our requirements for NLS, and in fact puts us into a good practice of installing DirectAccess with NLS being hosted on its own web server, there is yet another step you could take to make it even better. Currently this web server is a single point of failure for NLS. If this web server goes down or has a problem, we would have DirectAccess client computers inside the office who would think they are outside, and they would have some major name resolution problems until we sorted out the NLS problem. Given that, it is a great idea to make NLS redundant. You could cluster servers together, use Microsoft Network Load Balancing ( NLB ), or even use some kind of hardware load balancer if you have one available in your network. This way you could run the same NLS website on multiple web servers and know that your clients will still work properly in the event of a web server failure. Summary This article encourages you to use Windows Server 2012 R2 as the connectivity platform that brings your remote computers into the corporate network. We discussed DirectAccess and VPN in this article. We also saw how to configure DirectAccess and VPN, and how to secure DirectAccess using certificate authentication. Resources for Article: Further resources on this subject: Cross-premise Connectivity [article] Setting Up and Managing E-mails and Batch Processing [article] Upgrading from Previous Versions [article]

 In this article by Alex Kasko, Stanislav Kobyl yanskiy, and Alexey Mironchenko, authors of the book OpenJDK Cookbook, we will cover the following topics: Building the IcedTea browser plugin on Linux Using the IcedTea Java WebStart implementation on Linux Preparing the IcedTea Java WebStart implementation for Mac OS X Preparing the IcedTea Java WebStart implementation for Windows Introduction For a long time, for end users, the Java applets technology was the face of the whole Java world. For a lot of non-developers, the word Java itself is a synonym for the Java browser plugin that allows running Java applets inside web browsers. The Java WebStart technology is similar to the Java browser plugin but runs remotely on loaded Java applications as separate applications outside of web browsers. The OpenJDK open source project does not contain the implementations for the browser plugin nor for the WebStart technologies. The Oracle Java distribution, otherwise matching closely to OpenJDK codebases, provided its own closed source implementation for these technologies. The IcedTea-Web project contains free and open source implementations of the browser plugin and WebStart technologies. The IcedTea-Web browser plugin supports only GNU/Linux operating systems and the WebStart implementation is cross-platform. While the IcedTea implementation of WebStart is well-tested and production-ready, it has numerous incompatibilities with the Oracle WebStart implementation. These differences can be seen as corner cases; some of them are: Different behavior when parsing not well-formed JNLP descriptor files: The Oracle implementation is generally more lenient for malformed descriptors. Differences in JAR (re)downloading and caching behavior: The Oracle implementation uses caching more aggressively. Differences in sound support: This is due to differences in sound support between Oracle Java and IcedTea on Linux. Linux historically has multiple different sound providers (ALSA, PulseAudio, and so on) and IcedTea has more wide support for different providers, which can lead to sound misconfiguration. The IcedTea-Web browser plugin (as it is built on WebStart) has these incompatibilities too. On top of them, it can have more incompatibilities in relation to browser integration. User interface forms and general browser-related operations such as access from/to JavaScript code should work fine with both implementations. But historically, the browser plugin was widely used for security-critical applications like online bank clients. Such applications usually require security facilities from browsers, such as access to certificate stores or hardware crypto-devices that can differ from browser to browser, depending on the OS (for example, supports only Windows), browser version, Java version, and so on. Because of that, many real-world applications can have problems running the IcedTea-Web browser plugin on Linux. Both WebStart and the browser plugin are built on the idea of downloading (possibly untrusted) code from remote locations, and proper privilege checking and sandboxed execution of that code is a notoriously complex task. Usually reported security issues in the Oracle browser plugin (most widely known are issues during the year 2012) are also fixed separately in IcedTea-Web. Building the IcedTea browser plugin on Linux The IcedTea-Web project is not inherently cross-platform; it is developed on Linux and for Linux, and so it can be built quite easily on popular Linux distributions. The two main parts of it (stored in corresponding directories in the source code repository) are netx and plugin. NetX is a pure Java implementation of the WebStart technology. We will look at it more thoroughly in the following recipes of this article. Plugin is an implementation of the browser plugin using the NPAPI plugin architecture that is supported by multiple browsers. Plugin is written partly in Java and partly in native code (C++), and it officially supports only Linux-based operating systems. There exists an opinion about NPAPI that this architecture is dated, overcomplicated, and insecure, and that modern web browsers have enough built-in capabilities to not require external plugins. And browsers have gradually reduced support for NPAPI. Despite that, at the time of writing this book, the IcedTea-Web browser plugin worked on all major Linux browsers (Firefox and derivatives, Chromium and derivatives, and Konqueror). We will build the IcedTea-Web browser plugin from sources using Ubuntu 12.04 LTS amd64. Getting ready For this recipe, we will need a clean Ubuntu 12.04 running with the Firefox web browser installed. How to do it... The following procedure will help you to build the IcedTea-Web browser plugin: Install prepackaged binaries of OpenJDK 7: sudo apt-get install openjdk-7-jdk Install the GCC toolchain and build dependencies: sudo apt-get build-dep openjdk-7 Install the specific dependency for the browser plugin: sudo apt-get install firefox-dev Download and decompress the IcedTea-Web source code tarball: wget http://icedtea.wildebeest.org/download/source/icedtea-web-1.4.2.tar.gz tar xzvf icedtea-web-1.4.2.tar.gz Run the configure script to set up the build environment: ./configure Run the build process: make Install the newly built plugin into the /usr/local directory: sudo make install Configure the Firefox web browser to use the newly built plugin library: mkdir ~/.mozilla/plugins cd ~/.mozilla/plugins ln -s /usr/local/IcedTeaPlugin.so libjavaplugin.so Check whether the IcedTea-Web plugin has appeared under Tools | Add-ons | Plugins. Open the http://java.com/en/download/installed.jsp web page to verify that the browser plugin works. How it works... The IcedTea browser plugin requires the IcedTea Java implementation to be compiled successfully. The prepackaged OpenJDK 7 binaries in Ubuntu 12.04 are based on IcedTea, so we installed them first. The plugin uses the GNU Autconf build system that is common between free software tools. The xulrunner-dev package is required to access the NPAPI headers. The built plugin may be installed into Firefox for the current user only without requiring administrator privileges. For that, we created a symbolic link to our plugin in the place where Firefox expects to find the libjavaplugin.so plugin library. There's more... The plugin can also be installed into other browsers with NPAPI support, but installation instructions can be different for different browsers and different Linux distributions. As the NPAPI architecture does not depend on the operating system, in theory, a plugin can be built for non-Linux operating systems. But currently, no such ports are planned. Using the IcedTea Java WebStart implementation on Linux On the Java platform, the JVM needs to perform the class load process for each class it wants to use. This process is opaque for the JVM and actual bytecode for loaded classes may come from one of many sources. For example, this method allows the Java Applet classes to be loaded from a remote server to the Java process inside the web browser. Remote class loading also may be used to run remotely loaded Java applications in standalone mode without integration with the web browser. This technique is called Java WebStart and was developed under Java Specification Request (JSR) number 56. To run the Java application remotely, WebStart requires an application descriptor file that should be written using the Java Network Launching Protocol (JNLP) syntax. This file is used to define the remote server to load the application form along with some metainformation. The WebStart application may be launched from the web page by clicking on the JNLP link, or without the web browser using the JNLP file obtained beforehand. In either case, running the application is completely separate from the web browser, but uses a sandboxed security model similar to Java Applets. The OpenJDK project does not contain the WebStart implementation; the Oracle Java distribution provides its own closed-source WebStart implementation. The open source WebStart implementation exists as part of the IcedTea-Web project. It was initially based on the NETwork eXecute (NetX) project. Contrary to the Applet technology, WebStart does not require any web browser integration. This allowed developers to implement the NetX module using pure Java without native code. For integration with Linux-based operating systems, IcedTea-Web implements the javaws command as shell script that launches the netx.jar file with proper arguments. In this recipe, we will build the NetX module from the official IcedTea-Web source tarball. Getting ready For this recipe, we will need a clean Ubuntu 12.04 running with the Firefox web browser installed. How to do it... The following procedure will help you to build a NetX module: Install prepackaged binaries of OpenJDK 7: sudo apt-get install openjdk-7-jdk Install the GCC toolchain and build dependencies: sudo apt-get build-dep openjdk-7 Download and decompress the IcedTea-Web source code tarball: wget http://icedtea.wildebeest.org/download/source/icedtea-web-1.4.2.tar.gz tar xzvf icedtea-web-1.4.2.tar.gz Run the configure script to set up a build environment excluding the browser plugin from the build: ./configure –disable-plugin Run the build process: make Install the newly-built plugin into the /usr/local directory: sudo make install Run the WebStart application example from the Java tutorial: javaws http://docs.oracle.com/javase/tutorialJWS/samples/ deployment/dynamictree_webstartJWSProject/dynamictree_webstart.jnlp How it works... The javaws shell script is installed into the /usr/local/* directory. When launched with a path or a link to the JNLP file, javaws launches the netx.jar file, adding it to the boot classpath (for security reasons) and providing the JNLP link as an argument. Preparing the IcedTea Java WebStart implementation for Mac OS X The NetX WebStart implementation from the IcedTea-Web project is written in pure Java, so it can also be used on Mac OS X. IcedTea-Web provides the javaws launcher implementation only for Linux-based operating systems. In this recipe, we will create a simple implementation of the WebStart launcher script for Mac OS X. Getting ready For this recipe, we will need Mac OS X Lion with Java 7 (the prebuilt OpenJDK or Oracle one) installed. We will also need the netx.jar module from the IcedTea-Web project, which can be built using instructions from the previous recipe. How to do it... The following procedure will help you to run WebStart applications on Mac OS X: Download the JNLP descriptor example from the Java tutorials at http://docs.oracle.com/javase/tutorialJWS/samples/deployment/dynamictree_webstartJWSProject/dynamictree_webstart.jnlp. Test that this application can be run from the terminal using netx.jar: java -Xbootclasspath/a:netx.jar net.sourceforge.jnlp.runtime.Boot dynamictree_webstart.jnlp Create the wslauncher.sh bash script with the following contents: #!/bin/bash if [ "x$JAVA_HOME" = "x" ] ; then JAVA="$( which java 2>/dev/null )" else JAVA="$JAVA_HOME"/bin/java fi if [ "x$JAVA" = "x" ] ; then echo "Java executable not found" exit 1 fi if [ "x$1" = "x" ] ; then echo "Please provide JNLP file as first argument" exit 1 fi $JAVA -Xbootclasspath/a:netx.jar net.sourceforge.jnlp.runtime.Boot $1 Mark the launcher script as executable: chmod 755 wslauncher.sh Run the application using the launcher script: ./wslauncher.sh dynamictree_webstart.jnlp How it works... The next.jar file contains a Java application that can read JNLP files and download and run classes described in JNLP. But for security reasons, next.jar cannot be launched directly as an application (using the java -jar netx.jar syntax). Instead, netx.jar is added to the privileged boot classpath and is run specifying the main class directly. This allows us to download applications in sandbox mode. The wslauncher.sh script tries to find the Java executable file using the PATH and JAVA_HOME environment variables and then launches specified JNLP through netx.jar. There's more... The wslauncher.sh script provides a basic solution to run WebStart applications from the terminal. To integrate netx.jar into your operating system environment properly (to be able to launch WebStart apps using JNLP links from the web browser), a native launcher or custom platform scripting solution may be used. Such solutions lay down the scope of this book. Preparing the IcedTea Java WebStart implementation for Windows The NetX WebStart implementation from the IcedTea-Web project is written in pure Java, so it can also be used on Windows; we also used it on Linux and Mac OS X in previous recipes in this article. In this recipe, we will create a simple implementation of the WebStart launcher script for Windows. Getting ready For this recipe, we will need a version of Windows running with Java 7 (the prebuilt OpenJDK or Oracle one) installed. We will also need the netx.jar module from the IcedTea-Web project, which can be built using instructions from the previous recipe in this article. How to do it... The following procedure will help you to run WebStart applications on Windows: Download the JNLP descriptor example from the Java tutorials at http://docs.oracle.com/javase/tutorialJWS/samples/deployment/dynamictree_webstartJWSProject/dynamictree_webstart.jnlp. Test that this application can be run from the terminal using netx.jar: java -Xbootclasspath/a:netx.jar net.sourceforge.jnlp.runtime.Boot dynamictree_webstart.jnlp Create the wslauncher.sh bash script with the following contents: #!/bin/bash if [ "x$JAVA_HOME" = "x" ] ; then JAVA="$( which java 2>/dev/null )" else JAVA="$JAVA_HOME"/bin/java fi if [ "x$JAVA" = "x" ] ; then echo "Java executable not found" exit 1 fi if [ "x$1" = "x" ] ; then echo "Please provide JNLP file as first argument" exit 1 fi $JAVA -Xbootclasspath/a:netx.jar net.sourceforge.jnlp.runtime.Boot $1 Mark the launcher script as executable: chmod 755 wslauncher.sh Run the application using the launcher script: ./wslauncher.sh dynamictree_webstart.jnlp How it works... The netx.jar module must be added to the boot classpath as it cannot be run directly because of security reasons. The wslauncher.bat script tries to find the Java executable using the JAVA_HOME environment variable and then launches specified JNLP through netx.jar. There's more... The wslauncher.bat script may be registered as a default application to run the JNLP files. This will allow you to run WebStart applications from the web browser. But the current script will show the batch window for a short period of time before launching the application. It also does not support looking for Java executables in the Windows Registry. A more advanced script without those problems may be written using Visual Basic script (or any other native scripting solution) or as a native executable launcher. Such solutions lay down the scope of this book. Summary In this article we covered the configuration and installation of WebStart and browser plugin components, which are the biggest parts of the Iced Tea project.

This article by Vinith Menon, the author of Microsoft Hyper-V PowerShell Automation, delves into the basics of Hyper-V, right from installing Hyper-V to resizing virtual hard disks. The Hyper-V PowerShell module includes several significant features that extend its use, improve its usability, and allow you to control and manage your Hyper-V environment with more granular control. Various organizations have moved on from Hyper-V (V2) to Hyper-V (V3). In Hyper-V (V2), the Hyper-V management shell was not built-in and the PowerShell module had to be manually installed. In Hyper-V (V3), Microsoft has provided an exhaustive set of cmdlets that can be used to manage and automate all configuration activities of the Hyper-V environment. The cmdlets are executed across the network using Windows Remote Management. In this article, we will cover: The basics of setting up a Hyper-V environment using PowerShell The fundamental concepts of Hyper-V management with the Hyper-V management shell The updated features in Hyper-V (For more resources related to this topic, see here.) Here is a list of all the new features introduced in Hyper-V in Windows Server 2012 R2. We will be going in depth through the important changes that have come into the Hyper-V PowerShell module with the following features and functions: Shared virtual hard disk Resizing the live virtual hard disk Installing and configuring your Hyper-V environment Installing and configuring Hyper-V using PowerShell Before you proceed with the installation and configuration of Hyper-V, there are some prerequisites that need to be taken care of: The user account that is used to install the Hyper-V role should have administrative privileges on the computer There should be enough RAM on the server to run newly created virtual machines Once the prerequisites have been taken care of, let's start with installing the Hyper-V role: Open a PowerShell prompt in Run as Administrator mode: Type the following into the PowerShell prompt to install the Hyper-V role along with the management tools; once the installation is complete, the Hyper-V Server will reboot and the Hyper-V role will be successfully installed: Install-WindowsFeature –Name Hyper-V -IncludeManagementTools - Restart Once the server boots up, verify the installation of Hyper-V using the Get-WindowsFeature cmdlet: Get-WindowsFeature -Name hyper* You will be able to see that the Hyper-V role, Hyper-V PowerShell management shell, and the GUI management tools are successfully installed:   Fundamental concepts of Hyper-V management with the Hyper-V management shell In this section, we will look at some of the fundamental concepts of Hyper-V management with the Hyper-V management shell. Once you get the Hyper-V role installed as per the steps illustrated in the previous section, a PowerShell module to manage your Hyper-V environment will also get installed. Now, perform the following steps: Open a PowerShell prompt in the Run as Administrator mode. PowerShell uses cmdlets that are built using a verb-noun naming system (for more details, refer to Learning Windows PowerShell Names at http://technet.microsoft.com/en-us/library/dd315315.aspx). Type the following command into the PowerShell prompt to get a list of all the cmdlets in the Hyper-V PowerShell module: Get-Command -Module Hyper-V Hyper-V in Windows Server 2012 R2 ships with about 178 cmdlets. These cmdlets allow a Hyper-V administrator to handle very simple, basic tasks to advanced ones such as setting up a Hyper-V replica for virtual machine disaster recovery. To get the count of all the available Hyper-V cmdlets, you can type the following command in PowerShell: Get-Command -Module Hyper-V | Measure-Object The Hyper-V PowerShell cmdlets follow a very simple approach and are very user friendly. The cmdlet name itself indirectly communicates with the Hyper-V administrator about its functionality. The following screenshot shows the output of the Get command: For example, in the following screenshot, the Remove-VMSwitch cmdlet itself says that it's used to delete a previously created virtual machine switch: If the administrator is still not sure about the task that can be performed by the cmdlet, he or she can get help with detailed examples using the Get-Help cmdlet. To get help on the cmdlet type, type the cmdlet name in the prescribed format. To make sure that the latest version of help files are installed on the server, run the Update-Help cmdlet before executing the following cmdlet: Get-Help <Hyper-V cmdlet> -Full The following screenshot is an example of the Get-Help cmdlet: Shared virtual hard disks This new and improved feature in Windows Server 2012 R2 allows an administrator to share a virtual hard disk file (the .vhdx file format) between multiple virtual machines. These .vhdx files can be used as shared storage for a failover cluster created between virtual machines (also known as guest clustering). A shared virtual hard disk allows you to create data disks and witness disks using .vhdx files with some advantages: Shared disks are ideal for SQL database files and file servers Shared disks can be run on generation 1 and generation 2 virtual machines This new feature allows you to save on storage costs and use the .vhdx files for guest clustering, enabling easier deployment rather than using virtual Fibre Channel or Internet Small Computer System Interface (iSCSI), which are complicated and require storage configuration changes such as zoning and Logic Unit Number (LUN) masking. In Windows Server 2012 R2, virtual iSCSI disks (both shared and unshared virtual hard disk files) show up as virtual SAS disks when you add an iSCSI hard disk to a virtual machine. Shared virtual hard disks (.vhdx) files can be placed on Cluster Shared Volumes (CSV) or a Scale-Out File Server cluster Let's look at the ways you can automate and manage your shared .vhdx guest clustering configuration using PowerShell. In the following example, we will demonstrate how you can create a two-node file server cluster using the shared VHDX feature. After that, let's set up a testing environment within which we can start learning these new features. The steps are as follows: We will start by creating two virtual machines each with 50 GB OS drives, which contains a sysprep image of Windows Server 2012 R2. Each virtual machine will have 4 GB RAM and four virtual CPUs. D:vhdbase_1.vhdx and D:vhdbase_2.vhdx are already existing VHDX files with sysprepped image of Windows Server 2012 R2. The following code is used to create two virtual machines: New-VM –Name "Fileserver_VM1" –MemoryStartupBytes 4GB – NewVHDPath d:vhdbase_1.vhdx -NewVHDSizeBytes 50GB New-VM –Name "Fileserver_VM2" –MemoryStartupBytes 4GB –NewVHDPath d:vhdbase_2.vhdx -NewVHDSizeBytes 50GB Next, we will install the file server role and configure a failover cluster on both the virtual machines using PowerShell. You need to enable PowerShell remoting on both the file servers and also have them joined to a domain. The following is the code: Install-WindowsFeature -computername Fileserver_VM1 File- Services, FS-FileServer, Failover-Clustering   Install-WindowsFeature -computername Fileserver_VM1 RSAT- Clustering –IncludeAllSubFeature   Install-WindowsFeature -computername Fileserver_VM2 File- Services, FS-FileServer, Failover-Clustering   Install-WindowsFeature -computername Fileserver_VM2 RSAT- Clustering -IncludeAllSubFeature Once we have the virtual machines created and the file server and failover clustering features installed, we will create the failover cluster as per Microsoft's best practices using the following set of cmdlets: New-Cluster -Name Cluster1 -Node FileServer_VM1,   FileServer_VM2 -StaticAddress 10.0.0.59 -NoStorage – Verbose You will need to choose a name and IP address that fits your organization. Next, we will create two vhdx files named sharedvhdx_data.vhdx (which will be used as a data disk) and sharedvhdx_quorum.vhdx (which will be used as the quorum or the witness disk). To do this, the following commands need to be run on the Hyper-V cluster: New-VHD -Path   c:ClusterStorageVolume1sharedvhdx_data.VHDX -Fixed - SizeBytes 10GB   New-VHD -Path   c:ClusterStorageVolume1sharedvhdx_quorum.VHDX -Fixed - SizeBytes 1GB Once we have created these virtual hard disk files, we will add them as shared .vhdx files. We will attach these newly created VHDX files to the Fileserver_VM1 and Fileserver_VM2 virtual machines and specify the parameter-shared VHDX files for guest clustering: Add-VMHardDiskDrive –VMName Fileserver_VM1 -Path   c:ClusterStorageVolume1sharedvhdx_data.VHDX – ShareVirtualDisk   Add-VMHardDiskDrive –VMName Fileserver_VM2 -Path   c:ClusterStorageVolume1sharedvhdx_data.VHDX – ShareVirtualDisk Finally, we will be making the disks available online and adding them to the failover cluster using the following command: Get-ClusterAvailableDisk | Add-ClusterDisk Once we have executed the preceding set of steps, we will have a highly available file server infrastructure using shared VHD files. Live virtual hard disk resizing With Windows Server 2012 R2, a newly added feature in Hyper-V allows the administrators to expand or shrink the size of a virtual hard disk attached to the SCSI controller while the virtual machines are still running. Hyper-V administrators can now perform maintenance operations on a live VHD and avoid any downtime by not temporarily shutting down the virtual machine for these maintenance activities. Prior to Windows Server 2012 R2, to resize a VHD attached to the virtual machine, it had to be turned off leading to costly downtime. Using the GUI controls, the VHD resize can be done by using only the Edit Virtual Hard Disk wizard. Also, note that the VHDs that were previously expanded can be shrunk. The Windows PowerShell way of doing a VHD resize is by using the Resize-VirtualDisk cmdlet. Let's look at the ways you can automate a VHD resize using PowerShell. In the next example, we will demonstrate how you can expand and shrink a virtual hard disk connected to a VM's SCSI controller. We will continue using the virtual machine that we created for our previous example. We have a pre-created VHD of 50 GB that is connected to the virtual machine's SCSI controller. Expanding the virtual hard disk Let's resize the aforementioned virtual hard disk to 57 GB using the Resize-Virtualdisk cmdlet: Resize-VirtualDisk -Name "scsidisk" -Size (57GB) Next, if we open the VM settings and perform an inspect disk operation, we'll be able to see that the VHDX file size has become 57 GB: Also, one can verify this when he or she logs into the VM, opens disk management, and extends the unused partition. You can see that the disk size has increased to 57 GB: Resizing the virtual hard disk Let's resize the earlier mentioned VHD to 57 GB using the Resize-Virtualdisk cmdlet: For this exercise, the primary requirement is to shrink the disk partition by logging in to the VM using disk management, as you can see in the following screenshot; we're shrinking the VHDX file by 7 GB: Next, click on Shrink. Once you complete this step, you will see that the unallocated space is 7 GB. You can also execute this step using the Resize-Partition Powershell cmdlet: Get-Partition -DiskNumber 1 | Resize-Partition -Size 50GB The following screenshot shows the partition: Next, we will resize/shrink the VHD to 50 GB: Resize-VirtualDisk -Name "scsidisk" -Size (50GB) Once the previous steps have been executed successfully, run a re-scan disk using disk management and you will see that the disk size is 50 GB: Summary In this article, we went through the basics of setting up a Hyper-V environment using PowerShell. We also explored the fundamental concepts of Hyper-V management with Hyper-V management shell. Resources for Article: Further resources on this subject: Hyper-V building blocks for creating your Microsoft virtualization platform [article] The importance of Hyper-V Security [article] Network Access Control Lists [article]

In article by Alberto Paro, the author of ElasticSearch Cookbook Second Edition, we will cover about the following recipes: (For more resources related to this topic, see here.) Installing additional script plugins Managing scripts Sorting data using scripts Computing return fields with scripting Filtering a search via scripting Introduction ElasticSearch has a powerful way of extending its capabilities with custom scripts, which can be written in several programming languages. The most common ones are Groovy, MVEL, JavaScript, and Python. In this article, we will see how it's possible to create custom scoring algorithms, special processed return fields, custom sorting, and complex update operations on records. The scripting concept of ElasticSearch can be seen as an advanced stored procedures system in the NoSQL world; so, for an advanced usage of ElasticSearch, it is very important to master it. Installing additional script plugins ElasticSearch provides native scripting (a Java code compiled in JAR) and Groovy, but a lot of interesting languages are also available, such as JavaScript and Python. In older ElasticSearch releases, prior to version 1.4, the official scripting language was MVEL, but due to the fact that it was not well-maintained by MVEL developers, in addition to the impossibility to sandbox it and prevent security issues, MVEL was replaced with Groovy. Groovy scripting is now provided by default in ElasticSearch. The other scripting languages can be installed as plugins. Getting ready You will need a working ElasticSearch cluster. How to do it... In order to install JavaScript language support for ElasticSearch (1.3.x), perform the following steps: From the command line, simply enter the following command: bin/plugin --install elasticsearch/elasticsearch-lang-javascript/2.3.0 This will print the following result: -> Installing elasticsearch/elasticsearch-lang-javascript/2.3.0... Trying http://download.elasticsearch.org/elasticsearch/elasticsearch-lang-javascript/ elasticsearch-lang-javascript-2.3.0.zip... Downloading ....DONE Installed lang-javascript If the installation is successful, the output will end with Installed; otherwise, an error is returned. To install Python language support for ElasticSearch, just enter the following command: bin/plugin -install elasticsearch/elasticsearch-lang-python/2.3.0 The version number depends on the ElasticSearch version. Take a look at the plugin's web page to choose the correct version. How it works... Language plugins allow you to extend the number of supported languages to be used in scripting. During the ElasticSearch startup, an internal ElasticSearch service called PluginService loads all the installed language plugins. In order to install or upgrade a plugin, you need to restart the node. The ElasticSearch community provides common scripting languages (a list of the supported scripting languages is available on the ElasticSearch site plugin page at http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/modules-plugins.html), and others are available in GitHub repositories (a simple search on GitHub allows you to find them). The following are the most commonly used languages for scripting: Groovy (http://groovy.codehaus.org/): This language is embedded in ElasticSearch by default. It is a simple language that provides scripting functionalities. This is one of the fastest available language extensions. Groovy is a dynamic, object-oriented programming language with features similar to those of Python, Ruby, Perl, and Smalltalk. It also provides support to write a functional code. JavaScript (https://github.com/elasticsearch/elasticsearch-lang-javascript): This is available as an external plugin. The JavaScript implementation is based on Java Rhino (https://developer.mozilla.org/en-US/docs/Rhino) and is really fast. Python (https://github.com/elasticsearch/elasticsearch-lang-python): This is available as an external plugin, based on Jython (http://jython.org). It allows Python to be used as a script engine. Considering several benchmark results, it's slower than other languages. There's more... Groovy is preferred if the script is not too complex; otherwise, a native plugin provides a better environment to implement complex logic and data management. The performance of every language is different; the fastest one is the native Java. In the case of dynamic scripting languages, Groovy is faster, as compared to JavaScript and Python. In order to access document properties in Groovy scripts, the same approach will work as in other scripting languages: doc.score: This stores the document's score. doc['field_name'].value: This extracts the value of the field_name field from the document. If the value is an array or if you want to extract the value as an array, you can use doc['field_name'].values. doc['field_name'].empty: This returns true if the field_name field has no value in the document. doc['field_name'].multivalue: This returns true if the field_name field contains multiple values. If the field contains a geopoint value, additional methods are available, as follows: doc['field_name'].lat: This returns the latitude of a geopoint. If you need the value as an array, you can use the doc['field_name'].lats method. doc['field_name'].lon: This returns the longitude of a geopoint. If you need the value as an array, you can use the doc['field_name'].lons method. doc['field_name'].distance(lat,lon): This returns the plane distance, in miles, from a latitude/longitude point. If you need to calculate the distance in kilometers, you should use the doc['field_name'].distanceInKm(lat,lon) method. doc['field_name'].arcDistance(lat,lon): This returns the arc distance, in miles, from a latitude/longitude point. If you need to calculate the distance in kilometers, you should use the doc['field_name'].arcDistanceInKm(lat,lon) method. doc['field_name'].geohashDistance(geohash): This returns the distance, in miles, from a geohash value. If you need to calculate the same distance in kilometers, you should use doc['field_name'] and the geohashDistanceInKm(lat,lon) method. By using these helper methods, it is possible to create advanced scripts in order to boost a document by a distance that can be very handy in developing geolocalized centered applications. Managing scripts Depending on your scripting usage, there are several ways to customize ElasticSearch to use your script extensions. In this recipe, we will see how to provide scripts to ElasticSearch via files, indexes, or inline. Getting ready You will need a working ElasticSearch cluster populated with the populate script (chapter_06/populate_aggregations.sh), available at https://github.com/aparo/ elasticsearch-cookbook-second-edition. How to do it... To manage scripting, perform the following steps: Dynamic scripting is disabled by default for security reasons; we need to activate it in order to use dynamic scripting languages such as JavaScript or Python. To do this, we need to turn off the disable flag (script.disable_dynamic: false) in the ElasticSearch configuration file (config/elasticseach.yml) and restart the cluster. To increase security, ElasticSearch does not allow you to specify scripts for non-sandbox languages. Scripts can be placed in the scripts directory inside the configuration directory. To provide a script in a file, we'll put a my_script.groovy script in the config/scripts location with the following code content: doc["price"].value * factor If the dynamic script is enabled (as done in the first step), ElasticSearch allows you to store the scripts in a special index, .scripts. To put my_script in the index, execute the following command in the command terminal: curl -XPOST localhost:9200/_scripts/groovy/my_script -d '{ "script":"doc["price"].value * factor" }' The script can be used by simply referencing it in the script_id field; use the following command: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "match_all": {} }, "sort": {    "_script" : {      "script_id" : "my_script",      "lang" : "groovy",      "type" : "number",      "ignore_unmapped" : true,      "params" : {        "factor" : 1.1      },      "order" : "asc"    } } }' How it works... ElasticSearch allows you to load your script in different ways; each one of these methods has their pros and cons. The most secure way to load or import scripts is to provide them as files in the config/scripts directory. This directory is continuously scanned for new files (by default, every 60 seconds). The scripting language is automatically detected by the file extension, and the script name depends on the filename. If the file is put in subdirectories, the directory path becomes part of the filename; for example, if it is config/scripts/mysub1/mysub2/my_script.groovy, the script name will be mysub1_mysub2_my_script. If the script is provided via a filesystem, it can be referenced in the code via the "script": "script_name" parameter. Scripts can also be available in the special .script index. These are the REST end points: To retrieve a script, use the following code: GET http://<server>/_scripts/<language>/<id"> To store a script use the following code: PUT http://<server>/_scripts/<language>/<id> To delete a script use the following code: DELETE http://<server>/_scripts/<language>/<id> The indexed script can be referenced in the code via the "script_id": "id_of_the_script" parameter. The recipes that follow will use inline scripting because it's easier to use it during the development and testing phases. Generally, a good practice is to develop using the inline dynamic scripting in a request, because it's faster to prototype. Once the script is ready and no changes are needed, it can be stored in the index since it is simpler to call and manage. In production, a best practice is to disable dynamic scripting and store the script on the disk (generally, dumping the indexed script to disk). See also The scripting page on the ElasticSearch website at http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/modules-scripting.html Sorting data using script ElasticSearch provides scripting support for the sorting functionality. In real world applications, there is often a need to modify the default sort by the match score using an algorithm that depends on the context and some external variables. Some common scenarios are given as follows: Sorting places near a point Sorting by most-read articles Sorting items by custom user logic Sorting items by revenue Getting ready You will need a working ElasticSearch cluster and an index populated with the script, which is available at https://github.com/aparo/ elasticsearch-cookbook-second-edition. How to do it... In order to sort using scripting, perform the following steps: If you want to order your documents by the price field multiplied by a factor parameter (that is, sales tax), the search will be as shown in the following code: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "match_all": {} }, "sort": {    "_script" : {      "script" : "doc["price"].value * factor",      "lang" : "groovy",      "type" : "number",      "ignore_unmapped" : true,    "params" : {        "factor" : 1.1      },            "order" : "asc"        }    } }' In this case, we have used a match_all query and a sort script. If everything is correct, the result returned by ElasticSearch should be as shown in the following code: { "took" : 7, "timed_out" : false, "_shards" : {    "total" : 5,    "successful" : 5,    "failed" : 0 }, "hits" : {    "total" : 1000,    "max_score" : null,    "hits" : [ {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "161",      "_score" : null, "_source" : … truncated …,      "sort" : [ 0.0278578661440021 ]    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "634",      "_score" : null, "_source" : … truncated …,     "sort" : [ 0.08131364254827411 ]    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "465",      "_score" : null, "_source" : … truncated …,      "sort" : [ 0.1094966959069832 ]    } ] } } How it works... The sort scripting allows you to define several parameters, as follows: order (default "asc") ("asc" or "desc"): This determines whether the order must be ascending or descending. script: This contains the code to be executed. type: This defines the type to convert the value. params (optional, a JSON object): This defines the parameters that need to be passed. lang (by default, groovy): This defines the scripting language to be used. ignore_unmapped (optional): This ignores unmapped fields in a sort. This flag allows you to avoid errors due to missing fields in shards. Extending the sort with scripting allows the use of a broader approach to score your hits. ElasticSearch scripting permits the use of every code that you want. You can create custom complex algorithms to score your documents. There's more... Groovy provides a lot of built-in functions (mainly taken from Java's Math class) that can be used in scripts, as shown in the following table: Function Description time() The current time in milliseconds sin(a) Returns the trigonometric sine of an angle cos(a) Returns the trigonometric cosine of an angle tan(a) Returns the trigonometric tangent of an angle asin(a) Returns the arc sine of a value acos(a) Returns the arc cosine of a value atan(a) Returns the arc tangent of a value toRadians(angdeg) Converts an angle measured in degrees to an approximately equivalent angle measured in radians toDegrees(angrad) Converts an angle measured in radians to an approximately equivalent angle measured in degrees exp(a) Returns Euler's number raised to the power of a value log(a) Returns the natural logarithm (base e) of a value log10(a) Returns the base 10 logarithm of a value sqrt(a) Returns the correctly rounded positive square root of a value cbrt(a) Returns the cube root of a double value IEEEremainder(f1, f2) Computes the remainder operation on two arguments, as prescribed by the IEEE 754 standard ceil(a) Returns the smallest (closest to negative infinity) value that is greater than or equal to the argument and is equal to a mathematical integer floor(a) Returns the largest (closest to positive infinity) value that is less than or equal to the argument and is equal to a mathematical integer rint(a) Returns the value that is closest in value to the argument and is equal to a mathematical integer atan2(y, x) Returns the angle theta from the conversion of rectangular coordinates (x,y_) to polar coordinates (r,_theta) pow(a, b) Returns the value of the first argument raised to the power of the second argument round(a) Returns the closest integer to the argument random() Returns a random double value abs(a) Returns the absolute value of a value max(a, b) Returns the greater of the two values min(a, b) Returns the smaller of the two values ulp(d) Returns the size of the unit in the last place of the argument signum(d) Returns the signum function of the argument sinh(x) Returns the hyperbolic sine of a value cosh(x) Returns the hyperbolic cosine of a value tanh(x) Returns the hyperbolic tangent of a value hypot(x,y) Returns sqrt(x^2+y^2) without an intermediate overflow or underflow acos(a) Returns the arc cosine of a value atan(a) Returns the arc tangent of a value If you want to retrieve records in a random order, you can use a script with a random method, as shown in the following code: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "match_all": {} }, "sort": {    "_script" : {      "script" : "Math.random()",      "lang" : "groovy",      "type" : "number",      "params" : {}    } } }' In this example, for every hit, the new sort value is computed by executing the Math.random() scripting function. See also The official ElasticSearch documentation at http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/modules-scripting.html Computing return fields with scripting ElasticSearch allows you to define complex expressions that can be used to return a new calculated field value. These special fields are called script_fields, and they can be expressed with a script in every available ElasticSearch scripting language. Getting ready You will need a working ElasticSearch cluster and an index populated with the script (chapter_06/populate_aggregations.sh), which is available at https://github.com/aparo/ elasticsearch-cookbook-second-edition. How to do it... In order to compute return fields with scripting, perform the following steps: Return the following script fields: "my_calc_field": This concatenates the text of the "name" and "description" fields "my_calc_field2": This multiplies the "price" value by the "discount" parameter From the command line, execute the following code: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/ _search?&pretty=true&size=3' -d '{ "query": {    "match_all": {} }, "script_fields" : {    "my_calc_field" : {      "script" : "doc["name"].value + " -- " + doc["description"].value"    },    "my_calc_field2" : {      "script" : "doc["price"].value * discount",      "params" : {       "discount" : 0.8      }    } } }' If everything works all right, this is how the result returned by ElasticSearch should be: { "took" : 4, "timed_out" : false, "_shards" : {    "total" : 5,    "successful" : 5,    "failed" : 0 }, "hits" : {    "total" : 1000,    "max_score" : 1.0,    "hits" : [ {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "4",      "_score" : 1.0,      "fields" : {        "my_calc_field" : "entropic -- accusantium",        "my_calc_field2" : 5.480038242170081      }    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "9",      "_score" : 1.0,      "fields" : {        "my_calc_field" : "frankie -- accusantium",        "my_calc_field2" : 34.79852410178313      }    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "11",      "_score" : 1.0,      "fields" : {        "my_calc_field" : "johansson -- accusamus",        "my_calc_field2" : 11.824173084636591      }    } ] } } How it works... The scripting fields are similar to executing an SQL function on a field during a select operation. In ElasticSearch, after a search phase is executed and the hits to be returned are calculated, if some fields (standard or script) are defined, they are calculated and returned. The script field, which can be defined with all the supported languages, is processed by passing a value to the source of the document and, if some other parameters are defined in the script (in the discount factor example), they are passed to the script function. The script function is a code snippet; it can contain everything that the language allows you to write, but it must be evaluated to a value (or a list of values). See also The Installing additional script plugins recipe in this article to install additional languages for scripting The Sorting using script recipe to have a reference of the extra built-in functions in Groovy scripts Filtering a search via scripting ElasticSearch scripting allows you to extend the traditional filter with custom scripts. Using scripting to create a custom filter is a convenient way to write scripting rules that are not provided by Lucene or ElasticSearch, and to implement business logic that is not available in the query DSL. Getting ready You will need a working ElasticSearch cluster and an index populated with the (chapter_06/populate_aggregations.sh) script, which is available at https://github.com/aparo/ elasticsearch-cookbook-second-edition. How to do it... In order to filter a search using a script, perform the following steps: Write a search with a filter that filters out a document with the value of age less than the parameter value: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "filtered": {      "filter": {        "script": {          "script": "doc["age"].value > param1",          "params" : {            "param1" : 80          }        }      },      "query": {        "match_all": {}      }    } } }' In this example, all the documents in which the value of age is greater than param1 are qualified to be returned. If everything works correctly, the result returned by ElasticSearch should be as shown here: { "took" : 30, "timed_out" : false, "_shards" : {    "total" : 5,    "successful" : 5,    "failed" : 0 }, "hits" : {    "total" : 237,    "max_score" : 1.0,    "hits" : [ {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "9",      "_score" : 1.0, "_source" :{ … "age": 83, … }    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "23",      "_score" : 1.0, "_source" : { … "age": 87, … }    }, {      "_index" : "test-index",      "_type" : "test-type",      "_id" : "47",      "_score" : 1.0, "_source" : {…. "age": 98, …}    } ] } } How it works... The script filter is a language script that returns a Boolean value (true/false). For every hit, the script is evaluated, and if it returns true, the hit passes the filter. This type of scripting can only be used as Lucene filters, not as queries, because it doesn't affect the search (the exceptions are constant_score and custom_filters_score). These are the scripting fields: script: This contains the code to be executed params: These are optional parameters to be passed to the script lang (defaults to groovy): This defines the language of the script The script code can be any code in your preferred and supported scripting language that returns a Boolean value. There's more... Other languages are used in the same way as Groovy. For the current example, I have chosen a standard comparison that works in several languages. To execute the same script using the JavaScript language, use the following code: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "filtered": {      "filter": {        "script": {          "script": "doc["age"].value > param1",          "lang":"javascript",          "params" : {            "param1" : 80          }        }      },      "query": {        "match_all": {}      }    } } }' For Python, use the following code: curl -XGET 'http://127.0.0.1:9200/test-index/test-type/_search?&pretty=true&size=3' -d '{ "query": {    "filtered": {      "filter": {        "script": {          "script": "doc["age"].value > param1",          "lang":"python",          "params" : {            "param1" : 80          }        }      },      "query": {        "match_all": {}      }    } } }' See also The Installing additional script plugins recipe in this article to install additional languages for scripting The Sorting data using script recipe in this article to get a reference of the extra built-in functions in Groovy scripts Summary In this article you have learnt the ways you can use scripting to extend the ElasticSearch functional capabilities using different programming languages. Resources for Article: Further resources on this subject: Indexing the Data [Article] Low-Level Index Control [Article] Designing Puppet Architectures [Article]

In this article by Atmajitsinh Gohil, author of the book R Data Visualization Cookbook, we will cover the following topics: A simple bar plot A simple line plot Line plot to tell an effective story Merging histograms Making an interactive bubble plot (For more resources related to this topic, see here.) The main motivation behind this article is to introduce the basics of plotting in R and an element of interactivity via the googleVis package. The basic plots are important as many packages developed in R use basic plot arguments and hence understanding them creates a good foundation for new R users. We will start by exploring the scatter plots in R, which are the most basic plots for exploratory data analysis, and then delve into interactive plots. Every section will start with an introduction to basic R plots and we will build interactive plots thereafter. We will utilize the power of R analytics and implement them using the googleVis package to introduce the element of interactivity. The googleVis package is developed by Google and it uses the Google Chart API to create interactive plots. There are a range of plots available with the googleVis package and this provides us with an advantage to plot the same data on various plots and select the one that delivers an effective message. The package undergoes regular updates and releases, and new charts are implemented with every release. The readers should note that there are other alternatives available to create interactive plots in R, but it is not possible to explore all of them and hence I have selected googleVis to display interactive elements in a chart. I have selected these purely based on my experience with interactivity in plots. The other good interactive package is offered by GGobi. A simple bar plot A bar plot can often be confused with histograms. Histograms are used to study the distribution of data whereas bar plots are used to study categorical data. Both the plots may look similar to the naked eye but the main difference is that the width of a bar plot is not of significance, whereas in histograms the width of the bars signifies the frequency of data. In this recipe, I have made use of the infant mortality rate in India. The data is made available by the Government of India. The main objective is to study the basics of a bar plot in R as shown in the following screenshot: How to do it… We start the recipe by importing our data in R using the read.csv() function. R will search for the data under the current directory, and hence we use the setwd() function to set our working directory: setwd("D:/book/scatter_Area/chapter2") data = read.csv("infant.csv", header = TRUE) Once we import the data, we would like to process the data by ordering it. We order the data using the order() function in R. We would like R to order the column Total2011 in a decreasing order: data = data[order(data$Total2011, decreasing = TRUE),] We use the ifelse() function to create a new column. We would utilize this new column to add different colors to bars in our plot. We could also write a loop in R to do this task but we will keep this for later. The ifelse() function is quick and easy. We instruct R to assign yes if values in the column Total2011 are more than 12.2 and no otherwise. The 12.2 value is not randomly chosen but is the average infant mortality rate of India: new = ifelse(data$Total2011>12.2,"yes","no") Next, we would like to join the vector of yes and no to our original dataset. In R, we can join columns using the cbind() function. Rows can be combined using rbind(): data = cbind(data,new) When we initially plot the bar plot, we observe that we need more space at the bottom of the plot. We adjust the margins of a plot in R by passing the mar() argument within the par() function. The mar() function uses four arguments: bottom, left, top, and right spacing: par(mar = c(10,5,5,5)) Next, we generate a bar plot in R using the barplot() function. The abline() function is used to add a horizontal line on the bar plot: barplot(data$Total2011, las = 2, names.arg= data$India,width =0.80, border = NA,ylim=c(0,20), col = "#e34a33", main = "InfantMortality Rate of India in 2011")abline(h = 12.2, lwd =2, col = "white", lty =2) How it works… The order() function uses permutation to rearrange (decreasing or increasing) the rows based on the variable. We would like to plot the bars from highest to lowest, and hence we require to arrange the data. The ifelse() function is used to generate a new column. We would use this column under the There's more… section of this recipe. The first argument under the ifelse() function is the logical test to be performed. The second argument is the value to be assigned if the test is true, and the third argument is the value to be assigned if the logical test fails. The first argument in the barplot() function defines the height of the bars and horiz = TRUE (not used in our code) instructs R to plot the bars horizontally. The default setting in R will plot the bars vertically. The names.arg argument is used to label the bars. We also specify border = NA to remove the borders and las = 2 is specified to apply the direction to our labels. Try replacing the las values with 1,2,3, or 4 and observe how the orientation of our labels change.. The first argument in the abline() function assigns the position where the line is drawn, that is, vertical or horizontal. The lwd, lty, and col arguments are used to define the width, line type, and color of the line. There's more… While plotting a bar plot, it's a good practice to order the data in ascending or descending order. An unordered bar plot does not convey the right message and the plot is hard to read when there are more bars involved. When we observe a plot, we are interested to get the most information out, and ordering the data is the first step toward achieving this objective. We have not specified how we can use the ifelse() and cbind() functions in the plot. If we would like to color the plot with different colors to let the readers know which states have high infant mortality above the country level, we can do this by pasting col = (data$new) in place of col = "#e34a33". See also New York Times has a very interesting implementation of an interactive bar chart and can be accessed at http://www.nytimes.com/interactive/2007/09/28/business/20070930_SAFETY_GRAPHIC.html A simple line plot Line plots are simply lines connecting all the x and y dots. They are very easy to interpret and are widely used to display an upward or downward trend in data. In this recipe, we will use the googleVis package and create an interactive R line plot. We will learn how we can emphasize on certain variables in our data. The following line plot shows fertility rate: Getting ready We will use the googleVis package to generate a line plot. How to do it… In order to construct a line chart, we will install and load the googleVis package in R. We would also import the fertility data using the read.csv() function: install.packages("googleVis") library(googleVis) frt = read.csv("fertility.csv", header = TRUE, sep =",") The fertility data is downloaded from the OECD website. We can construct our line object using the gvisLineChart() function: gvisLineChart(frt, xvar = "Year","yvar=c("Australia","Austria","Belgium","Canada","Chile","OECD34"), options = list( width = 1100, height= 500, backgroundColor = " "#FFFF99",title ="Fertility Rate in OECD countries" , vAxis = "{title : 'Total Fertility " Rate',gridlines:{color:'#DEDECE',count : 4}, ticks : "   [0,1,2,3,4]}", series = "{0:{color:'black', visibleInLegend :false},        1:{color:'BDBD9D', visibleInLegend :false},        2:{color:'BDBD9D', visibleInLegend :false},            3:{color:'BDBD9D', visibleInLegend :false},           4:{color:'BDBD9D', visibleInLegend :false},          34:{color:'3333FF', visibleInLegend :true}}")) We can construct the visualization using the plot() function in R: plot(line) How it works… The first three arguments of the gvisLineChart() function are the data and the name of the columns to be plotted on the x-axis and y-axis. The options argument lists the chart API options to add and modify elements of a chart. For the purpose of this recipe, we will use part of the dataset. Hence, while we assign the series to be plotted under yvar = c(), we will specify the column names that we would like to be plotted in our chart. Note that the series starts at 0, and hence Australia, which is the first column, is in fact series 0 and not 1. For the purpose of this exercise, let's assume that we would like to demonstrate the mean fertility rate among all OECD economies to our audience. We can achieve this using series {} under option = list(). The series argument will allow us to specify or customize a specific series in our dataset. Under the gvisLineChart() function, we instruct the Google Chart API to color OECD series (series 34) and Australia (series 0) with a different color and also make the legend visible only for OECD and not the entire series. It would be best to display all the legends but we use this to show the flexibility that comes with the Google Chart API. Finally, we can use the plot() function to plot the chart in a browser. The following screenshot displays a part of the data. The dim() function gives us a general idea about the dimensions of the fertility data: New York Times Visualization often combines line plots with bar chart and pie charts. Readers should try constructing such visualization. We can use the gvisMerge() function to merge plots. The function allows merging of just two plots and hence the readers would have to use multiple gvisMerge() functions to create a very similar visualization. The same can also be constructed in R but we will lose the interactive element. See also The OECD website provides economic data related to OECD member countries. The data can be freely downloaded from the website http://www.oecd.org/statistics/. New York Times Visualization combines bar charts and line charts and can be accessed at http://www.nytimes.com/imagepages/2009/10/16/business/20091017_CHARTS_GRAPHIC.html. Line plot to tell an effective story In the previous recipe, we learned how to plot a very basic line plot and use some of the options. In this recipe, we will go a step further and make use of specific visual cues such as color and line width for easy interpretation. Line charts are a great tool to visualize time series data. The fertility data is discrete but connecting points over time provides our audience with a direction. The visualization shows the amazing progress countries such as Mexico and Turkey have achieved in reducing their fertility rate. OECD defines fertility rate as Refers to the number of children that would be born per woman, assuming no female mortality at child-bearing ages and the age-specific fertility rates of a specified country and reference period. Line plots have been widely used by New York Times to create very interesting infographics. This recipe is inspired by one of the New York Times visualizations. It is very important to understand that many of the infographics created by professionals are created using D3.js or Processing. We will not go into the detail of the same but it is good to know the working of these softwares and how they can be used to create visualizations. Getting ready We would need to install and load the googleVis package to construct a line chart. How to do it… To generate an interactive plot, we will load the fertility data in R using the read.csv() function. To generate a line chart that plots the entire dataset, we will use the gvisLineChart() function: line = gvisLineChart(frt, xvar = "Year", yvar=c("Australia",""Austria","Belgium","Canada","Chile","Czech.Republic", "Denmark","Estonia","Finland","France","Germany","Greece","Hungary"", "Iceland","Ireland","Israel","Italy","Japan","Korea","Luxembourg",""Mexico", "Netherlands","New.Zealand","Norway","Poland","Portugal","Slovakia"","Slovenia", "Spain","Sweden","Switzerland","Turkey","United.Kingdom","United."States","OECD34"), options = list( width = 1200, backgroundColor = "#ADAD85",title " ="Fertility Rate in OECD countries" , vAxis = "{gridlines:{color:'#DEDECE',count : 3}, ticks : " [0,1,2,3,4]}", series = "{0:{color:'BDBD9D', visibleInLegend :false}, 20:{color:'009933', visibleInLegend :true}, 31:{color:'996600', visibleInLegend :true}, 34:{color:'3333FF', visibleInLegend :true}}")) To display our visualization in a new browser, we use the generic R plot() function: plot(line) How it works… The arguments passed in the gvisLineChart() function, are exactly the same as discussed under the simple line plot with some minor changes. We would like to plot the entire data for this exercise, and hence we have to state all the column names in yvar =c(). Also, we would like to color all the series with the same color but highlight Mexico, Turkey, and OECD average. We have achieved this in the previous code using series {}, and further specify and customize colors and legend visibility for specific countries. In this particular plot, we have made use of the same color for all the economies but have highlighted Mexico and Turkey to signify the development and growth that took place in the 5-year period. It would also be effective if our audience could compare the OECD average with Mexico and Turkey. This provides the audience with a benchmark they can compare with. If we plot all the legends, it may make the plot too crowded and 34 legends may not make a very attractive plot. We could avoid this by only making specific legends visible. See also D3 is a great tool to develop interactive visualization and this can be accessed at http://d3js.org/. Processing is an open source software developed by MIT and can be downloaded from https://processing.org/. A good resource to pick colors and use them in our plots is the following link: http://www.w3schools.com/tags/ref_colorpicker.asp. I have used New York Times infographics as an inspiration for this plot. You can find a collection of visualization put out by New York Times in 2011 by going to this link, http://www.smallmeans.com/new-york-times-infographics/. Merging histograms Histograms help in studying the underlying distribution. It is more useful when we are trying to compare more than one histogram on the same plot; this provides us with greater insight into the skewness and the overall distribution. In this recipe, we will study how to plot a histogram using the googleVis package and how we merge more than one histogram on the same page. We will only merge two plots but we can merge more plots and try to adjust the width of each plot. This makes it easier to compare all the plots on the same page. The following plot shows two merged histograms: How to do it… In order to generate a histogram, we will install the googleVis package as well as load the same in R: install.packages("googleVis") library(googleVis) We have downloaded the prices of two different stocks and have calculated their daily returns over the entire period. We can load the data in R using the read.csv() function. Our main aim in this recipe is to plot two different histograms and plot them side by side in a browser. Hence, we require to divide our data in three different data frames. For the purpose of this recipe, we will plot the aapl and msft data frames: stk = read.csv("stock_cor.csv", header = TRUE, sep = ",") aapl = data.frame(stk$AAPL) msft = data.frame(stk$MSFT) googl = data.frame(stk$GOOGL) To generate the histograms, we implement the gvisHistogram() function: al = gvisHistogram(aapl, options = list(histogram = "{bucketSize " :1}",legend = "none",title ='Distribution of AAPL Returns', "   width = 500,hAxis = "{showTextEvery: 5,title: "     'Returns'}",vAxis = "{gridlines : {count:4}, title : "       'Frequency'}")) mft = gvisHistogram(msft, options = list(histogram = "{bucketSize " :1}",legend = "none",title ='Distribution of MSFT Returns', "   width = 500,hAxis = "{showTextEvery: 5,title: 'Returns'}","     vAxis = "{gridlines : {count:4}, title : 'Frequency'}")) We combine the two gvis objects in one browser using the gvisMerge() function: mrg = gvisMerge(al,mft, horizontal = TRUE) plot(mrg) How it works… The data.frame() function is used to construct a data frame in R. We require this step as we do not want to plot all the three histograms on the same plot. Note the use of the $ notation in the data.frame() function. The first argument in the gvisHistogram() function is our data stored as a data frame. We can display individual histograms using the plot(al) and plot(mft) functions. But in this recipe, we will plot the final output. We observe that most of the attributes of a histogram function are the same as discussed in previous recipes. The histogram functionality will use an algorithm to create buckets, but we can control this using the bucketSize as histogram = "{bucketSize :1}". Try using different bucket sizes and observe how the buckets in the histograms change. More options related to histograms can also be found in the following link under the Controlling Buckets section: https://developers.google.com/chart/interactive/docs/gallery/histogram#Buckets We have utilized showTextEvery, which is also very specific to histograms. This option allows us to specify how many horizontal axis labels we would like to show. We have used 5 to make the histogram more compact. Our main objective is to observe the distribution and the plot serves our purpose. Finally, we will implement plot() to plot the chart in our favorite browser. We do the same steps to plot the return distribution of Microsoft (MSFT). Now, we would like to place both the plots side by side and view the differences in the distribution. We will use the gvisMerge() function to generate histograms side by side. In our recipe, we have two plots for AAPL and MSFT. The default setting plots each chart vertically but we can specify horizontal = true to plot charts horizontally. Making an interactive bubble plot My first encounter with a bubble plot was while watching a TED video of Hans Roslling. The video led me to search for creating bubble plots in R; a very good introduction to this is available on the Flowing Data website. The advantage of a bubble plot is that it allows us to visualize a third variable, which in our case would be the size of the bubble. In this recipe, I have made use of the googleVis package to plot a bubble plot but you can also implement this in R. The advantage of the Google Chart API is the interactivity and the ease with which they can be attached to a web page. Also note that we could also use squares instead of circles, but this is not implemented in the Google Chart API yet. In order to implement a bubble plot, I have downloaded the crime dataset by state. The details regarding the link and definition of crime data are available in the crime.txt file and are shown in the following screenshot: How to do it… As with all the plots in this article, we will install and load the googleVis Package. We will also import our data file in R using the read.csv() function: crm = read.csv("crimeusa.csv", header = TRUE, sep =",") We can construct our bubble chart using the gvisBubbleChart() function in R: bub1 = gvisBubbleChart(crm,idvar = "States",xvar= "Robbery", yvar="Burglary", sizevar ="Population", colorvar = "Year",options = list(legend = "none",width = 900, height = 600,title=" Crime per State in 2012", sizeAxis ="{maxSize : 40, minSize:0.5}",vAxis = "{title : 'Burglary'}",hAxis= "{title :'Robbery'}"))bub2 = gvisBubbleChart(crm,idvar = "States",xvar= "Robbery", yvar="Burglary",sizevar ="Population",options = list(legend = "none",width = 900, height = 600,title=" Crime per State in 2012", sizeAxis ="{maxSize : 40, minSize:0.5}",vAxis = "{title : 'Burglary'}",hAxis= "{title :'Robbery'}"))ata How it works… The gvisBubbleChart() function uses six attributes to create a bubble chart, which are as follows: data: This is the data defined as a data frame, in our example, crm idvar: This is the vector that is used to assign IDs to the bubbles, in our example, states xvar: This is the column in the data to plot on the x-axis, in our example, Robbery yvar: This is the column in the data to plot on the y-axis, in our example, Burglary sizevar: This is the column used to define the size of the bubble colorvar: This is the column used to define the color We can define the minimum and maximum sizes of each bubble using minSize and maxSize, respectively, under options(). Note that we have used gvisMerge to portray the differences among the bubble plots. In the plot on the right, we have not made use of colorvar and hence all the bubbles are of the same size. There's more… The Google Chart API makes it easier for us to plot a bubble, but the same can be achieved using the R basic plot function. We can make use of the symbols to create a plot. The symbols need not be a bubble; it can be a square as well. By this time, you should have watched Hans' TED lecture and would be wondering how you could create a motion chart with bubbles floating around. The Google Charts API has the ability to create motion charts and the readers can definitely use the googleVis reference manual to learn about this. See also TED video by Hans Rosling can be accessed at http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen The Flowing Data website generates bubble charts using the basic R plot function and can be accessed at http://flowingdata.com/2010/11/23/how-to-make-bubble-charts/ Animated Bubble Chart by New York Times can be accessed at http://2010games.nytimes.com/medals/map.html Summary This article introduces some of the basic R plots, such as line and bar charts. It also discusses the basic elements of interactive plots using the googleVis package in R. This article is a great resource for understanding the basic R plotting techniques. Resources for Article: Further resources on this subject: Using R for Statistics, Research, and Graphics [article] Data visualization [article] Visualization as a Tool to Understand Data [article]

In this article by David R. Heffelfinger, the author of Java EE 7 Development with NetBeans 8, we will introduce Contexts and Dependency Injection (CDI) and other aspects of it. CDI can be used to simplify integrating the different layers of a Java EE application. For example, CDI allows us to use a session bean as a managed bean, so that we can take advantage of the EJB features, such as transactions, directly in our managed beans. In this article, we will cover the following topics: Introduction to CDI Qualifiers Stereotypes Interceptor binding types Custom scopes (For more resources related to this topic, see here.) Introduction to CDI JavaServer Faces (JSF) web applications employing CDI are very similar to JSF applications without CDI; the main difference is that instead of using JSF managed beans for our model and controllers, we use CDI named beans. What makes CDI applications easier to develop and maintain are the excellent dependency injection capabilities of the CDI API. Just as with other JSF applications, CDI applications use facelets as their view technology. The following example illustrates a typical markup for a JSF page using CDI: <?xml version='1.0' encoding='UTF-8' ?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"    "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html      >    <h:head>        <title>Create New Customer</title>    </h:head>    <h:body>        <h:form>            <h3>Create New Customer</h3>            <h:panelGrid columns="3">                <h:outputLabel for="firstName" value="First Name"/>                <h:inputText id="firstName" value="#{customer.firstName}"/>                <h:message for="firstName"/>                  <h:outputLabel for="middleName" value="Middle Name"/>                <h:inputText id="middleName"                  value="#{customer.middleName}"/>                <h:message for="middleName"/>                  <h:outputLabel for="lastName" value="Last Name"/>                <h:inputText id="lastName" value="#{customer.lastName}"/>                <h:message for="lastName"/>                  <h:outputLabel for="email" value="Email Address"/>                <h:inputText id="email" value="#{customer.email}"/>                <h:message for="email"/>                <h:panelGroup/>                <h:commandButton value="Submit"                  action="#{customerController.navigateToConfirmation}"/>            </h:panelGrid>        </h:form>    </h:body> </html> As we can see, the preceding markup doesn't look any different from the markup used for a JSF application that does not use CDI. The page renders as follows (shown after entering some data): In our page markup, we have JSF components that use Unified Expression Language expressions to bind themselves to CDI named bean properties and methods. Let's take a look at the customer bean first: package com.ensode.cdiintro.model;   import java.io.Serializable; import javax.enterprise.context.RequestScoped; import javax.inject.Named;   @Named @RequestScoped public class Customer implements Serializable {      private String firstName;    private String middleName;    private String lastName;    private String email;      public Customer() {    }      public String getFirstName() {        return firstName;    }      public void setFirstName(String firstName) {        this.firstName = firstName;    }      public String getMiddleName() {        return middleName;    }      public void setMiddleName(String middleName) {        this.middleName = middleName;    }      public String getLastName() {        return lastName;    }      public void setLastName(String lastName) {        this.lastName = lastName;    }      public String getEmail() {        return email;    }      public void setEmail(String email) {        this.email = email;    } } The @Named annotation marks this class as a CDI named bean. By default, the bean's name will be the class name with its first character switched to lowercase (in our example, the name of the bean is "customer", since the class name is Customer). We can override this behavior if we wish by passing the desired name to the value attribute of the @Named annotation, as follows: @Named(value="customerBean") A CDI named bean's methods and properties are accessible via facelets, just like regular JSF managed beans. Just like JSF managed beans, CDI named beans can have one of several scopes as listed in the following table. The preceding named bean has a scope of request, as denoted by the @RequestScoped annotation. Scope Annotation Description Request @RequestScoped Request scoped beans are shared through the duration of a single request. A single request could refer to an HTTP request, an invocation to a method in an EJB, a web service invocation, or sending a JMS message to a message-driven bean. Session @SessionScoped Session scoped beans are shared across all requests in an HTTP session. Each user of an application gets their own instance of a session scoped bean. Application @ApplicationScoped Application scoped beans live through the whole application lifetime. Beans in this scope are shared across user sessions. Conversation @ConversationScoped The conversation scope can span multiple requests, and is typically shorter than the session scope. Dependent @Dependent Dependent scoped beans are not shared. Any time a dependent scoped bean is injected, a new instance is created. As we can see, CDI has equivalent scopes to all JSF scopes. Additionally, CDI adds two additional scopes. The first CDI-specific scope is the conversation scope, which allows us to have a scope that spans across multiple requests, but is shorter than the session scope. The second CDI-specific scope is the dependent scope, which is a pseudo scope. A CDI bean in the dependent scope is a dependent object of another object; beans in this scope are instantiated when the object they belong to is instantiated and they are destroyed when the object they belong to is destroyed. Our application has two CDI named beans. We already discussed the customer bean. The other CDI named bean in our application is the controller bean: package com.ensode.cdiintro.controller;   import com.ensode.cdiintro.model.Customer; import javax.enterprise.context.RequestScoped; import javax.inject.Inject; import javax.inject.Named;   @Named @RequestScoped public class CustomerController {      @Inject    private Customer customer;      public Customer getCustomer() {        return customer;    }      public void setCustomer(Customer customer) {        this.customer = customer;    }      public String navigateToConfirmation() {        //In a real application we would        //Save customer data to the database here.          return "confirmation";    } } In the preceding class, an instance of the Customer class is injected at runtime; this is accomplished via the @Inject annotation. This annotation allows us to easily use dependency injection in CDI applications. Since the Customer class is annotated with the @RequestScoped annotation, a new instance of Customer will be injected for every request. The navigateToConfirmation() method in the preceding class is invoked when the user clicks on the Submit button on the page. The navigateToConfirmation() method works just like an equivalent method in a JSF managed bean would, that is, it returns a string and the application navigates to an appropriate page based on the value of that string. Like with JSF, by default, the target page's name with an .xhtml extension is the return value of this method. For example, if no exceptions are thrown in the navigateToConfirmation() method, the user is directed to a page named confirmation.xhtml: <?xml version='1.0' encoding='UTF-8' ?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html      >    <h:head>        <title>Success</title>    </h:head>    <h:body>        New Customer created successfully.        <h:panelGrid columns="2" border="1" cellspacing="0">            <h:outputLabel for="firstName" value="First Name"/>            <h:outputText id="firstName" value="#{customer.firstName}"/>              <h:outputLabel for="middleName" value="Middle Name"/>            <h:outputText id="middleName"              value="#{customer.middleName}"/>              <h:outputLabel for="lastName" value="Last Name"/>            <h:outputText id="lastName" value="#{customer.lastName}"/>              <h:outputLabel for="email" value="Email Address"/>            <h:outputText id="email" value="#{customer.email}"/>          </h:panelGrid>    </h:body> </html> Again, there is nothing special we need to do to access the named beans properties from the preceding markup. It works just as if the bean was a JSF managed bean. The preceding page renders as follows: As we can see, CDI applications work just like JSF applications. However, CDI applications have several advantages over JSF, for example (as we mentioned previously) CDI beans have additional scopes not found in JSF. Additionally, using CDI allows us to decouple our Java code from the JSF API. Also, as we mentioned previously, CDI allows us to use session beans as named beans. Qualifiers In some instances, the type of bean we wish to inject into our code may be an interface or a Java superclass, but we may be interested in injecting a subclass or a class implementing the interface. For cases like this, CDI provides qualifiers we can use to indicate the specific type we wish to inject into our code. A CDI qualifier is an annotation that must be decorated with the @Qualifier annotation. This annotation can then be used to decorate the specific subclass or interface. In this section, we will develop a Premium qualifier for our customer bean; premium customers could get perks that are not available to regular customers, for example, discounts. Creating a CDI qualifier with NetBeans is very easy; all we need to do is go to File | New File, select the Contexts and Dependency Injection category, and select the Qualifier Type file type. In the next step in the wizard, we need to enter a name and a package for our qualifier. After these two simple steps, NetBeans generates the code for our qualifier: package com.ensode.cdiintro.qualifier;   import static java.lang.annotation.ElementType.TYPE; import static java.lang.annotation.ElementType.FIELD; import static java.lang.annotation.ElementType.PARAMETER; import static java.lang.annotation.ElementType.METHOD; import static java.lang.annotation.RetentionPolicy.RUNTIME; import java.lang.annotation.Retention; import java.lang.annotation.Target; import javax.inject.Qualifier;   @Qualifier @Retention(RUNTIME) @Target({METHOD, FIELD, PARAMETER, TYPE}) public @interface Premium { } Qualifiers are standard Java annotations. Typically, they have retention of runtime and can target methods, fields, parameters, or types. The only difference between a qualifier and a standard annotation is that qualifiers are decorated with the @Qualifier annotation. Once we have our qualifier in place, we need to use it to decorate the specific subclass or interface implementation, as shown in the following code: package com.ensode.cdiintro.model;   import com.ensode.cdiintro.qualifier.Premium; import javax.enterprise.context.RequestScoped; import javax.inject.Named;   @Named @RequestScoped @Premium public class PremiumCustomer extends Customer {      private Integer discountCode;      public Integer getDiscountCode() {        return discountCode;    }      public void setDiscountCode(Integer discountCode) {        this.discountCode = discountCode;    } } Once we have decorated the specific instance we need to qualify, we can use our qualifiers in the client code to specify the exact type of dependency we need: package com.ensode.cdiintro.controller;   import com.ensode.cdiintro.model.Customer; import com.ensode.cdiintro.model.PremiumCustomer; import com.ensode.cdiintro.qualifier.Premium;   import java.util.logging.Level; import java.util.logging.Logger; import javax.enterprise.context.RequestScoped; import javax.inject.Inject; import javax.inject.Named;   @Named @RequestScoped public class PremiumCustomerController {      private static final Logger logger = Logger.getLogger(            PremiumCustomerController.class.getName());    @Inject    @Premium    private Customer customer;      public String saveCustomer() {          PremiumCustomer premiumCustomer =          (PremiumCustomer) customer;          logger.log(Level.INFO, "Saving the following information n"                + "{0} {1}, discount code = {2}",                new Object[]{premiumCustomer.getFirstName(),                    premiumCustomer.getLastName(),                    premiumCustomer.getDiscountCode()});          //If this was a real application, we would have code to save        //customer data to the database here.          return "premium_customer_confirmation";    } } Since we used our @Premium qualifier to decorate the customer field, an instance of the PremiumCustomer class is injected into that field. This is because this class is also decorated with the @Premium qualifier. As far as our JSF pages go, we simply access our named bean as usual using its name, as shown in the following code; <?xml version='1.0' encoding='UTF-8' ?> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html      >    <h:head>        <title>Create New Premium Customer</title>    </h:head>    <h:body>        <h:form>            <h3>Create New Premium Customer</h3>            <h:panelGrid columns="3">                <h:outputLabel for="firstName" value="First Name"/>                 <h:inputText id="firstName"                    value="#{premiumCustomer.firstName}"/>                <h:message for="firstName"/>                  <h:outputLabel for="middleName" value="Middle Name"/>                <h:inputText id="middleName"                     value="#{premiumCustomer.middleName}"/>                <h:message for="middleName"/>                  <h:outputLabel for="lastName" value="Last Name"/>                <h:inputText id="lastName"                    value="#{premiumCustomer.lastName}"/>                <h:message for="lastName"/>                  <h:outputLabel for="email" value="Email Address"/>                <h:inputText id="email"                    value="#{premiumCustomer.email}"/>                <h:message for="email"/>                  <h:outputLabel for="discountCode" value="Discount Code"/>                <h:inputText id="discountCode"                    value="#{premiumCustomer.discountCode}"/>                <h:message for="discountCode"/>                   <h:panelGroup/>                <h:commandButton value="Submit"                      action="#{premiumCustomerController.saveCustomer}"/>            </h:panelGrid>        </h:form>    </h:body> </html> In this example, we are using the default name for our bean, which is the class name with the first letter switched to lowercase. Now, we are ready to test our application: After submitting the page, we can see the confirmation page. Stereotypes A CDI stereotype allows us to create new annotations that bundle up several CDI annotations. For example, if we need to create several CDI named beans with a scope of session, we would have to use two annotations in each of these beans, namely @Named and @SessionScoped. Instead of having to add two annotations to each of our beans, we could create a stereotype and annotate our beans with it. To create a CDI stereotype in NetBeans, we simply need to create a new file by selecting the Contexts and Dependency Injection category and the Stereotype file type. Then, we need to enter a name and package for our new stereotype. At this point, NetBeans generates the following code: package com.ensode.cdiintro.stereotype;   import static java.lang.annotation.ElementType.TYPE; import static java.lang.annotation.ElementType.FIELD; import static java.lang.annotation.ElementType.METHOD; import static java.lang.annotation.RetentionPolicy.RUNTIME; import java.lang.annotation.Retention; import java.lang.annotation.Target; import javax.enterprise.inject.Stereotype;   @Stereotype @Retention(RUNTIME) @Target({METHOD, FIELD, TYPE}) public @interface NamedSessionScoped { } Now, we simply need to add the CDI annotations that we want the classes annotated with our stereotype to use. In our case, we want them to be named beans and have a scope of session; therefore, we add the @Named and @SessionScoped annotations as shown in the following code: package com.ensode.cdiintro.stereotype;   import static java.lang.annotation.ElementType.TYPE; import static java.lang.annotation.ElementType.FIELD; import static java.lang.annotation.ElementType.METHOD; import static java.lang.annotation.RetentionPolicy.RUNTIME; import java.lang.annotation.Retention; import java.lang.annotation.Target; import javax.enterprise.context.SessionScoped; import javax.enterprise.inject.Stereotype; import javax.inject.Named;   @Named @SessionScoped @Stereotype @Retention(RUNTIME) @Target({METHOD, FIELD, TYPE}) public @interface NamedSessionScoped { } Now we can use our stereotype in our own code: package com.ensode.cdiintro.beans;   import com.ensode.cdiintro.stereotype.NamedSessionScoped; import java.io.Serializable;   @NamedSessionScoped public class StereotypeClient implements Serializable {      private String property1;    private String property2;      public String getProperty1() {        return property1;    }      public void setProperty1(String property1) {        this.property1 = property1;    }      public String getProperty2() {        return property2;    }      public void setProperty2(String property2) {        this.property2 = property2;    } } We annotated the StereotypeClient class with our NamedSessionScoped stereotype, which is equivalent to using the @Named and @SessionScoped annotations. Interceptor binding types One of the advantages of EJBs is that they allow us to easily perform aspect-oriented programming (AOP) via interceptors. CDI allows us to write interceptor binding types; this lets us bind interceptors to beans and the beans do not have to depend on the interceptor directly. Interceptor binding types are annotations that are themselves annotated with @InterceptorBinding. Creating an interceptor binding type in NetBeans involves creating a new file, selecting the Contexts and Dependency Injection category, and selecting the Interceptor Binding Type file type. Then, we need to enter a class name and select or enter a package for our new interceptor binding type. At this point, NetBeans generates the code for our interceptor binding type: package com.ensode.cdiintro.interceptorbinding;   import static java.lang.annotation.ElementType.TYPE; import static java.lang.annotation.ElementType.METHOD; import static java.lang.annotation.RetentionPolicy.RUNTIME; import java.lang.annotation.Inherited; import java.lang.annotation.Retention; import java.lang.annotation.Target; import javax.interceptor.InterceptorBinding;   @Inherited @InterceptorBinding @Retention(RUNTIME) @Target({METHOD, TYPE}) public @interface LoggingInterceptorBinding { } The generated code is fully functional; we don't need to add anything to it. In order to use our interceptor binding type, we need to write an interceptor and annotate it with our interceptor binding type, as shown in the following code: package com.ensode.cdiintro.interceptor;   import com.ensode.cdiintro.interceptorbinding.LoggingInterceptorBinding; import java.io.Serializable; import java.util.logging.Level; import java.util.logging.Logger; import javax.interceptor.AroundInvoke; import javax.interceptor.Interceptor; import javax.interceptor.InvocationContext;   @LoggingInterceptorBinding @Interceptor public class LoggingInterceptor implements Serializable{      private static final Logger logger = Logger.getLogger(            LoggingInterceptor.class.getName());      @AroundInvoke    public Object logMethodCall(InvocationContext invocationContext)            throws Exception {          logger.log(Level.INFO, new StringBuilder("entering ").append(                invocationContext.getMethod().getName()).append(                " method").toString());          Object retVal = invocationContext.proceed();          logger.log(Level.INFO, new StringBuilder("leaving ").append(                invocationContext.getMethod().getName()).append(                " method").toString());          return retVal;    } } As we can see, other than being annotated with our interceptor binding type, the preceding class is a standard interceptor similar to the ones we use with EJB session beans. In order for our interceptor binding type to work properly, we need to add a CDI configuration file (beans.xml) to our project. Then, we need to register our interceptor in beans.xml as follows: <?xml version="1.0" encoding="UTF-8"?> <beans               xsi_schemaLocation="http://>    <interceptors>          <class>        com.ensode.cdiintro.interceptor.LoggingInterceptor      </class>    </interceptors> </beans> To register our interceptor, we need to set bean-discovery-mode to all in the generated beans.xml and add the <interceptor> tag in beans.xml, with one or more nested <class> tags containing the fully qualified names of our interceptors. The final step before we can use our interceptor binding type is to annotate the class to be intercepted with our interceptor binding type: package com.ensode.cdiintro.controller;   import com.ensode.cdiintro.interceptorbinding.LoggingInterceptorBinding; import com.ensode.cdiintro.model.Customer; import com.ensode.cdiintro.model.PremiumCustomer; import com.ensode.cdiintro.qualifier.Premium; import java.util.logging.Level; import java.util.logging.Logger; import javax.enterprise.context.RequestScoped; import javax.inject.Inject; import javax.inject.Named;   @LoggingInterceptorBinding @Named @RequestScoped public class PremiumCustomerController {      private static final Logger logger = Logger.getLogger(            PremiumCustomerController.class.getName());    @Inject    @Premium    private Customer customer;      public String saveCustomer() {          PremiumCustomer premiumCustomer = (PremiumCustomer) customer;          logger.log(Level.INFO, "Saving the following information n"                + "{0} {1}, discount code = {2}",                new Object[]{premiumCustomer.getFirstName(),                    premiumCustomer.getLastName(),                    premiumCustomer.getDiscountCode()});          //If this was a real application, we would have code to save        //customer data to the database here.          return "premium_customer_confirmation";    } } Now, we are ready to use our interceptor. After executing the preceding code and examining the GlassFish log, we can see our interceptor binding type in action. The lines entering saveCustomer method and leaving saveCustomer method were added to the log by our interceptor, which was indirectly invoked by our interceptor binding type. Custom scopes In addition to providing several prebuilt scopes, CDI allows us to define our own custom scopes. This functionality is primarily meant for developers building frameworks on top of CDI, not for application developers. Nevertheless, NetBeans provides a wizard for us to create our own CDI custom scopes. To create a new CDI custom scope, we need to go to File | New File, select the Contexts and Dependency Injection category, and select the Scope Type file type. Then, we need to enter a package and a name for our custom scope. After clicking on Finish, our new custom scope is created, as shown in the following code: package com.ensode.cdiintro.scopes;   import static java.lang.annotation.ElementType.TYPE; import static java.lang.annotation.ElementType.FIELD; import static java.lang.annotation.ElementType.METHOD; import static java.lang.annotation.RetentionPolicy.RUNTIME; import java.lang.annotation.Inherited; import java.lang.annotation.Retention; import java.lang.annotation.Target; import javax.inject.Scope;   @Inherited @Scope // or @javax.enterprise.context.NormalScope @Retention(RUNTIME) @Target({METHOD, FIELD, TYPE}) public @interface CustomScope { } To actually use our scope in our CDI applications, we would need to create a custom context which, as mentioned previously, is primarily a concern for framework developers and not for Java EE application developers. Therefore, it is beyond the scope of this article. Interested readers can refer to JBoss Weld CDI for Java Platform, Ken Finnigan, Packt Publishing. (JBoss Weld is a popular CDI implementation and it is included with GlassFish.) Summary In this article, we covered NetBeans support for CDI, a new Java EE API introduced in Java EE 6. We provided an introduction to CDI and explained additional functionality that the CDI API provides over standard JSF. We also covered how to disambiguate CDI injected beans via CDI Qualifiers. Additionally, we covered how to group together CDI annotations via CDI stereotypes. We also, we saw how CDI can help us with AOP via interceptor binding types. Finally, we covered how NetBeans can help us create custom CDI scopes. Resources for Article: Further resources on this subject: Java EE 7 Performance Tuning and Optimization [article] Java EE 7 Developer Handbook [article] Java EE 7 with GlassFish 4 Application Server [article]

In this article by Jos Dirksen author of the book Three.js Cookbook, we will learn how Three.js offers a large number of different materials and supports many different types of textures. These textures provide a great way to create interesting effects and graphics. In this article, we'll show you recipes that allow you to get the most out of these components provided by Three.js. (For more resources related to this topic, see here.) Using HTML canvas as a texture Most often when you use textures, you use static images. With Three.js, however, it is also possible to create interactive textures. In this recipe, we will show you how you can use an HTML5 canvas element as an input for your texture. Any change to this canvas is automatically reflected after you inform Three.js about this change in the texture used on the geometry. Getting ready For this recipe, we need an HTML5 canvas element that can be displayed as a texture. We can create one ourselves and add some output, but for this recipe, we've chosen something else. We will use a simple JavaScript library, which outputs a clock to a canvas element. The resulting mesh will look like this (see the 04.03-use-html-canvas-as-texture.html example): The JavaScript used to render the clock was based on the code from this site: http://saturnboy.com/2013/10/html5-canvas-clock/. To include the code that renders the clock in our page, we need to add the following to the head element: <script src="../libs/clock.js"></script> How to do it... To use a canvas as a texture, we need to perform a couple of steps: The first thing we need to do is create the canvas element: var canvas = document.createElement('canvas'); canvas.width=512; canvas.height=512; Here, we create an HTML canvas element programmatically and define a fixed width. Now that we've got a canvas, we need to render the clock that we use as the input for this recipe on it. The library is very easy to use; all you have to do is pass in the canvas element we just created: clock(canvas); At this point, we've got a canvas that renders and updates an image of a clock. What we need to do now is create a geometry and a material and use this canvas element as a texture for this material: var cubeGeometry = new THREE.BoxGeometry(10, 10, 10); var cubeMaterial = new THREE.MeshLambertMaterial(); cubeMaterial.map = new THREE.Texture(canvas); var cube = new THREE.Mesh(cubeGeometry, cubeMaterial); To create a texture from a canvas element, all we need to do is create a new instance of THREE.Texture and pass in the canvas element we created in step 1. We assign this texture to the cubeMaterial.map property, and that's it. If you run the recipe at this step, you might see the clock rendered on the sides of the cubes. However, the clock won't update itself. We need to tell Three.js that the canvas element has been changed. We do this by adding the following to the rendering loop: cubeMaterial.map.needsUpdate = true; This informs Three.js that our canvas texture has changed and needs to be updated the next time the scene is rendered. With these four simple steps, you can easily create interactive textures and use everything you can create on a canvas element as a texture in Three.js. How it works... How this works is actually pretty simple. Three.js uses WebGL to render scenes and apply textures. WebGL has native support for using HTML canvas element as textures, so Three.js just passes on the provided canvas element to WebGL and it is processed as any other texture. Making part of an object transparent You can create a lot of interesting visualizations using the various materials available with Three.js. In this recipe, we'll look at how you can use the materials available with Three.js to make part of an object transparent. This will allow you to create complex-looking geometries with relative ease. Getting ready Before we dive into the required steps in Three.js, we first need to have the texture that we will use to make an object partially transparent. For this recipe, we will use the following texture, which was created in Photoshop: You don't have to use Photoshop; the only thing you need to keep in mind is that you use an image with a transparent background. Using this texture, in this recipe, we'll show you how you can create the following (04.08-make-part-of-object-transparent.html): As you can see in the preceeding, only part of the sphere is visible, and you can look through the sphere to see the back at the other side of the sphere. How to do it... Let's look at the steps you need to take to accomplish this: The first thing we do is create the geometry. For this recipe, we use THREE.SphereGeometry: var sphereGeometry = new THREE.SphereGeometry(6, 20, 20); Just like all the other recipes, you can use whatever geometry you want. In the second step, we create the material: var mat = new THREE.MeshPhongMaterial(); mat.map = new THREE.ImageUtils.loadTexture( "../assets/textures/partial-transparency.png"); mat.transparent = true; mat.side = THREE.DoubleSide; mat.depthWrite = false; mat.color = new THREE.Color(0xff0000); As you can see in this fragment, we create THREE.MeshPhongMaterial and load the texture we saw in the Getting ready section of this recipe. To render this correctly, we also need to set the side property to THREE.DoubleSide so that the inside of the sphere is also rendered, and we need to set the depthWrite property to false. This will tell WebGL that we still want to test our vertices against the WebGL depth buffer, but we don't write to it. Often, you need to set this to false when working with more complex transparent objects or particles. Finally, add the sphere to the scene: var sphere = new THREE.Mesh(sphereGeometry, mat); scene.add(sphere); With these simple steps, you can create really interesting effects by just experimenting with textures and geometries. There's more With Three.js, it is possible to repeat textures (refer to the Setup repeating textures recipe). You can use this to create interesting-looking objects such as this: The code required to set a texture to repeat is the following: var mat = new THREE.MeshPhongMaterial(); mat.map = new THREE.ImageUtils.loadTexture( "../assets/textures/partial-transparency.png"); mat.transparent = true; mat.map.wrapS = mat.map.wrapT = THREE.RepeatWrapping; mat.map.repeat.set( 4, 4 ); mat.depthWrite = false; mat.color = new THREE.Color(0x00ff00); By changing the mat.map.repeat.set values, you define how often the texture is repeated. Using a cubemap to create reflective materials With the approach Three.js uses to render scenes in real time, it is difficult and very computationally intensive to create reflective materials. Three.js, however, provides a way you can cheat and approximate reflectivity. For this, Three.js uses cubemaps. In this recipe, we'll explain how to create cubemaps and use them to create reflective materials. Getting ready A cubemap is a set of six images that can be mapped to the inside of a cube. They can be created from a panorama picture and look something like this: In Three.js, we map such a map on the inside of a cube or sphere and use that information to calculate reflections. The following screenshot (example 04.10-use-reflections.html) shows what this looks like when rendered in Three.js: As you can see in the preceeding screenshot, the objects in the center of the scene reflect the environment they are in. This is something often called a skybox. To get ready, the first thing we need to do is get a cubemap. If you search on the Internet, you can find some ready-to-use cubemaps, but it is also very easy to create one yourself. For this, go to http://gonchar.me/panorama/. On this page, you can upload a panoramic picture and it will be converted to a set of pictures you can use as a cubemap. For this, perform the following steps: First, get a 360 degrees panoramic picture. Once you have one, upload it to the http://gonchar.me/panorama/ website by clicking on the large OPEN button:  Once uploaded, the tool will convert the panorama picture to a cubemap as shown in the following screenshot:  When the conversion is done, you can download the various cube map sites. The recipe in this book uses the naming convention provided by Cube map sides option, so download them. You'll end up with six images with names such as right.png, left.png, top.png, bottom.png, front.png, and back.png. Once you've got the sides of the cubemap, you're ready to perform the steps in the recipe. How to do it... To use the cubemap we created in the previous section and create reflecting material,we need to perform a fair number of steps, but it isn't that complex: The first thing you need to do is create an array from the cubemap images you downloaded: var urls = [ '../assets/cubemap/flowers/right.png', '../assets/cubemap/flowers/left.png', '../assets/cubemap/flowers/top.png', '../assets/cubemap/flowers/bottom.png', '../assets/cubemap/flowers/front.png', '../assets/cubemap/flowers/back.png' ]; With this array, we can create a cubemap texture like this: var cubemap = THREE.ImageUtils.loadTextureCube(urls); cubemap.format = THREE.RGBFormat; From this cubemap, we can use THREE.BoxGeometry and a custom THREE.ShaderMaterial object to create a skybox (the environment surrounding our meshes): var shader = THREE.ShaderLib[ "cube" ]; shader.uniforms[ "tCube" ].value = cubemap; var material = new THREE.ShaderMaterial( { fragmentShader: shader.fragmentShader, vertexShader: shader.vertexShader, uniforms: shader.uniforms, depthWrite: false, side: THREE.DoubleSide }); // create the skybox var skybox = new THREE.Mesh( new THREE.BoxGeometry( 10000, 10000, 10000 ), material ); scene.add(skybox); Three.js provides a custom shader (a piece of WebGL code) that we can use for this. As you can see in the code snippet, to use this WebGL code, we need to define a THREE.ShaderMaterial object. With this material, we create a giant THREE.BoxGeometry object that we add to scene. Now that we've created the skybox, we can define the reflecting objects: var sphereGeometry = new THREE.SphereGeometry(4,15,15); var envMaterial = new THREE.MeshBasicMaterial( {envMap:cubemap}); var sphere = new THREE.Mesh(sphereGeometry, envMaterial); As you can see, we also pass in the cubemap we created as a property (envmap) to the material. This informs Three.js that this object is positioned inside a skybox, defined by the images that make up cubemap. The last step is to add the object to the scene, and that's it: scene.add(sphere); In the example in the beginning of this recipe, you saw three geometries. You can use this approach with all different types of geometries. Three.js will determine how to render the reflective area. How it works... Three.js itself doesn't really do that much to render the cubemap object. It relies on a standard functionality provided by WebGL. In WebGL, there is a construct called samplerCube. With samplerCube, you can sample, based on a specific direction, which color matches the cubemap object. Three.js uses this to determine the color value for each part of the geometry. The result is that on each mesh, you can see a reflection of the surrounding cubemap using the WebGL textureCube function. In Three.js, this results in the following call (taken from the WebGL shader in GLSL): vec4 cubeColor = textureCube( tCube, vec3( -vReflect.x, vReflect.yz ) ); A more in-depth explanation on how this works can be found at http://codeflow.org/entries/2011/apr/18/advanced-webgl-part-3-irradiance-environment-map/#cubemap-lookup. There's more... In this recipe, we created the cubemap object by providing six separate images. There is, however, an alternative way to create the cubemap object. If you've got a 360 degrees panoramic image, you can use the following code to directly create a cubemap object from that image: var texture = THREE.ImageUtils.loadTexture( 360-degrees.png', new THREE.UVMapping()); Normally when you create a cubemap object, you use the code shown in this recipe to map it to a skybox. This usually gives the best results but requires some extra code. You can also use THREE.SphereGeometry to create a skybox like this: var mesh = new THREE.Mesh( new THREE.SphereGeometry( 500, 60, 40 ), new THREE.MeshBasicMaterial( { map: texture })); mesh.scale.x = -1; This applies the texture to a sphere and with mesh.scale, turns this sphere inside out. Besides reflection, you can also use a cubemap object for refraction (think about light bending through water drops or glass objects): All you have to do to make a refractive material is load the cubemap object like this: var cubemap = THREE.ImageUtils.loadTextureCube(urls, new THREE.CubeRefractionMapping()); And define the material in the following way: var envMaterial = new THREE.MeshBasicMaterial({envMap:cubemap}); envMaterial.refractionRatio = 0.95; Summary In this article, we learned about the different textures and materials supported by Three.js Resources for Article:  Further resources on this subject: Creating the maze and animating the cube [article] Working with the Basic Components That Make Up a Three.js Scene [article] Mesh animation [article]

In this article by Alan Thorn author of the book Mastering Unity Scripting will cover the following topics: Events Event management (For more resources related to this topic, see here.) The Update events for MonoBehaviour objects seem to offer a convenient place for executing code that should perform regularly over time, spanning multiple frames, and possibly multiple scenes. When creating sustained behaviors over time, such as artificial intelligence for enemies or continuous motion, it may seem that there are almost no alternatives to filling an Update function with many if and switch statements, branching your code in different directions depending on what your objects need to do at the current time. But, when the Update events are seen this way, as a default place to implement prolonged behaviors, it can lead to severe performance problems for larger and more complex games. On deeper analysis, it's not difficult to see why this would be the case. Typically, games are full of so many behaviors, and there are so many things happening at once in any one scene that implementing them all through the Update functions is simply unfeasible. Consider the enemy characters alone, they need to know when the player enters and leaves their line of sight, when their health is low, when their ammo has expired, when they're standing on harmful terrain, when they're taking damage, when they're moving or not, and lots more. On thinking initially about this range of behaviors, it seems that all of them require constant and continuous attention because enemies should always know, instantly, when changes in these properties occur as a result of the player input. That is, perhaps, the main reason why the Update function seems to be the most suitable place in these situations but there are better alternatives, namely, event-driven programming. By seeing your game and your application in terms of events, you can make considerable savings in performance. This article then considers the issue of events and how to manage them game wide. Events Game worlds are fully deterministic systems; in Unity, the scene represents a shared 3D Cartesian space and timeline inside which finite GameObjects exist. Things only happen within this space when the game logic and code permits them to. For example, objects can only move when there is code somewhere that tells them to do so, and under specific conditions, such as when the player presses specific buttons on the keyboard. Notice from the example that behaviors are not simply random but are interconnected; objects move only when keyboard events occur. There is an important connection established between the actions, where one action entails another. These connections or linkages are referred to as events; each unique connection being a single event. Events are not active but passive; they represent moments of opportunity but not action in themselves, such as a key press, a mouse click, an object entering a collider volume, the player being attacked, and so on. These are examples of events and none of them say what the program should actually do, but only the kind of scenario that just happened. Event-driven programming starts with the recognition of events as a general concept and comes to see almost every circumstance in a game as an instantiation of an event; that is, as an event situated in time, not just an event concept but as a specific event that happens at a specific time. Understanding game events like these is helpful because all actions in a game can then be seen as direct responses to events as and when they happen. Specifically, events are connected to responses; an event happens and triggers a response. Further, the response can go on to become an event that triggers further responses and so on. In other words, the game world is a complete, integrated system of events and responses. Once the world is seen this way, the question then arises as to how it can help us improve performance over simply relying on the Update functions to move behaviors forward on every frame. And the method is simply by finding ways to reduce the frequency of events. Now, stated in this way, it may sound a crude strategy, but it's important. To illustrate, let's consider the example of an enemy character firing a weapon at the player during combat. Throughout the gameplay, the enemy will need to keep track of many properties. Firstly, their health, because when it runs low the enemy should seek out medical kits and aids to restore their health again. Secondly, their ammo, because when it runs low the enemy should seek to collect more and also the enemy will need to make reasoned judgments about when to fire at the player, such as only when they have a clear line of sight. Now, by simply thinking about this scenario, we've already identified some connections between actions that might be identified as events. But before taking this consideration further, let's see how we might implement this behavior using an Update function, as shown in the following code sample 4-1. Then, we'll look at how events can help us improve on that implementation: // Update is called once per frame void Update () {    //Check enemy health    //Are we dead?    if(Health <= 0)    {          //Then perform die behaviour          Die();          return;    }    //Check for health low    if(health <= 20)    {        //Health is low, so find first-aid          RunAndFindHealthRestore();          return;    }    //Check ammo    //Have we run out of ammo?    if(Ammo <= 0)    {          //Then find more          SearchMore();          return;    }    //Health and ammo are fine. Can we see player? If so, shoot    if(HaveLineOfSight)    {            FireAtPlayer();    } } The preceding code sample 4-1 shows a heavy Update function filled with lots of condition checking and responses. In essence, the Update function attempts to merge event handling and response behaviors into one and the results in an unnecessarily expensive process. If we think about the event connections between these different processes (the health and ammo check), we see how the code could be refactored more neatly. For example, ammo only changes on two occasions: when a weapon is fired or when new ammo is collected. Similarly, health only changes on two occasions: when an enemy is successfully attacked by the player or when an enemy collects a first-aid kit. In the first case, there is a reduction, and in the latter case, an increase. Since these are the only times when the properties change (the events), these are the only points where their values need to be validated. See the following code sample 4-2 for a refactored enemy, which includes C# properties and a much reduced Update function: using UnityEngine; using System.Collections; public class EnemyObject : MonoBehaviour {    //-------------------------------------------------------    //C# accessors for private variables    public int Health    {          get{return _health;}          set          {                //Clamp health between 0-100                _health = Mathf.Clamp(value, 0, 100);               //Check if dead                if(_health <= 0)                {                      OnDead();                      return;                }                //Check health and raise event if required                if(_health <= 20)               {                      OnHealthLow();                      return;                }          }    }    //-------------------------------------------------------    public int Ammo    {          get{return _ammo;}          set          {              //Clamp ammo between 0-50              _ammo = Mathf.Clamp(value,0,50);                //Check if ammo empty                if(_ammo <= 0)                {                      //Call expired event                      OnAmmoExpired();                      return;                }          }    }    //-------------------------------------------------------    //Internal variables for health and ammo    private int _health = 100;    private int _ammo = 50;    //-------------------------------------------------------    // Update is called once per frame    void Update ()    {    }    //-------------------------------------------------------    //This event is called when health is low    void OnHealthLow()    {          //Handle event response here    }    //-------------------------------------------------------    //This event is called when enemy is dead    void OnDead()    {        //Handle event response here    }    //-------------------------------------------------------    //Ammo run out event    void OnAmmoExpired()    {        //Handle event response here    }    //------------------------------------------------------- } The enemy class in the code sample 4-2 has been refactored to an event-driven design, where properties such as Ammo and Health are validated not inside the Update function but on assignment. From here, events are raised wherever appropriate based on the newly assigned values. By adopting an event-driven design, we introduce performance optimization and cleanness into our code; we reduce the excess baggage and value checks as found with the Update function in the code sample 4-1, and instead we only allow value-specific events to drive our code, knowing they'll be invoked only at the relevant times. Event management Event-driven programming can make our lives a lot easier. But no sooner than we accept events into the design do we come across a string of new problems that require a thoroughgoing resolution. Specifically, we saw in the code sample 4-2 how C# properties for health and ammo are used to validate and detect for relevant changes and then to raise events (such as OnDead) where appropriate. This works fine in principle, at least when the enemy must be notified about events that happen to itself. However, what if an enemy needed to know about the death of another enemy or needed to know when a specified number of other enemies had been killed? Now, of course, thinking about this specific case, we could go back to the enemy class in the code sample 4-2 and amend it to call an OnDead event not just for the current instance but for all other enemies using functions such as SendMessage. But this doesn't really solve our problem in the general sense. In fact, let's state the ideal case straight away; we want every object to optionally listen for every type of event and to be notified about them as and when they happen, just as easily as if the event had happened to them. So the question that we face now is about how to code an optimized system to allow easy event management like this. In short, we need an EventManager class that allows objects to listen to specific events. This system relies on three central concepts, as follows: Event Listener: A listener refers to any object that wants to be notified about an event when it happens, even its own events. In practice, almost every object will be a listener for at least one event. An enemy, for example, may want notifications about low health and low ammo among others. In this case, it's a listener for at least two separate events. Thus, whenever an object expects to be told when an event happens, it becomes a listener. Event Poster: In contrast to listeners, when an object detects that an event has occurred, it must announce or post a public notification about it that allows all other listeners to be notified. In the code sample 4-2, the enemy class detects the Ammo and Health events using properties and then calls the internal events, if required. But to be a true poster in this sense, we require that the object must raise events at a global level. Event Manager: Finally, there's an overarching singleton Event Manager object that persists across levels and is globally accessible. This object effectively links listeners to posters. It accepts notifications of events sent by posters and then immediately dispatches the notifications to all appropriate listeners in the form of events. Starting event management with interfaces The first or original entity in the event handling system is the listener—the thing that should be notified about specific events as and when they happen. Potentially, a listener could be any kind of object or any kind of class; it simply expects to be notified about specific events. In short, the listener will need to register itself with the Event Manager as a listener for one or more specific events. Then, when the event actually occurs, the listener should be notified directly by a function call. So, technically, the listener raises a type-specificity issue for the Event Manager about how the manager should invoke an event on the listener if the listener could potentially be an object of any type. Of course, this issue can be worked around, as we've seen, using either SendMessage or BroadcastMessage. Indeed, there are event handling systems freely available online, such as NotificationCenter that rely on these functions. However, we'll avoid them using interfaces and use polymorphism instead, as both SendMessage and BroadcastMessage rely heavily on reflection. Specifically, we'll create an interface from which all listener objects derive. More information on the freely available NotificationCenter (C# version) is available from the Unity wiki at http://wiki.unity3d.com/index.php?title=CSharpNotificationCenter. In C#, an interface is like a hollow abstract base class. Like a class, an interface brings together a collection of methods and functions into a single template-like unit. But, unlike a class, an interface only allows you to define function prototypes such as the name, return type, and arguments for a function. It doesn't let you define a function body. The reason being that an interface simply defines the total set of functions that a derived class will have. The derived class may implement the functions however necessary, and the interface simply exists so that other objects can invoke the functions via polymorphism without knowing the specific type of each derived class. This makes interfaces a suitable candidate to create a Listener object. By defining a Listener interface from which all objects will be derived, every object has the ability to be a listener for events. The following code sample 4-3 demonstrates a sample Listener interface: 01 using UnityEngine; 02 using System.Collections; 03 //----------------------------------------------------------- 04 //Enum defining all possible game events 05 //More events should be added to the list 06 public enum EVENT_TYPE {GAME_INIT, 07                                GAME_END, 08                                 AMMO_EMPTY, 09                                 HEALTH_CHANGE, 10                                 DEAD}; 11 //----------------------------------------------------------- 12 //Listener interface to be implemented on Listener classes 13 public interface IListener 14 { 15 //Notification function invoked when events happen 16 void OnEvent(EVENT_TYPE Event_Type, Component Sender,    Object Param = null); 17 } 18 //----------------------------------------------------------- The following are the comments for the code sample 4-3: Lines 06-10: This enumeration should define a complete list of all possible game events that could be raised. The sample code lists only five game events: GAME_INIT, GAME_END, AMMO_EMPTY, HEALTH_CHANGE, and DEAD. Your game will presumably have many more. You don't actually need to use enumerations for encoding events; you could just use integers. But I've used enumerations to improve event readability in code. Lines 13-17: The Listener interface is defined as IListener using the C# interfaces. It supports just one event, namely OnEvent. This function will be inherited by all derived classes and will be invoked by the manager whenever an event occurs for which the listener is registered. Notice that OnEvent is simply a function prototype; it has no body. More information on C# interfaces can be found at http://msdn.microsoft.com/en-us/library/ms173156.aspx. Using the IListener interface, we now have the ability to make a listener from any object using only class inheritance; that is, any object can now declare itself as a listener and potentially receive events. For example, a new MonoBehaviour component can be turned into a listener with the following code sample 4-4. This code uses multiple inheritance, that is, it inherits from two classes. More information on multiple inheritance can be found at http://www.dotnetfunda.com/articles/show/1185/multiple-inheritance-in-csharp: using UnityEngine; using System.Collections; public class MyCustomListener : MonoBehaviour, IListener {    // Use this for initialization    void Start () {}    // Update is called once per frame    void Update () {}    //---------------------------------------    //Implement OnEvent function to receive Events    public void OnEvent(EVENT_TYPE Event_Type, Component Sender, Object Param = null)    {    }    //--------------------------------------- } Creating an EventManager Any object can now be turned into a listener, as we've seen. But still the listeners must register themselves with a manager object of some kind. Thus, it is the duty of the manager to call the events on the listeners when the events actually happen. Let's now turn to the manager itself and its implementation details. The manager class will be called EventManager, as shown in the following code sample 4-5. This class, being a persistent singleton object, should be attached to an empty GameObject in the scene where it will be directly accessible to every other object through a static instance property. More on this class and its usage is considered in the subsequent comments: 001 using UnityEngine; 002 using System.Collections; 003 using System.Collections.Generic; 004 //----------------------------------- 005 //Singleton EventManager to send events to listeners 006 //Works with IListener implementations 007 public class EventManager : MonoBehaviour 008 { 009     #region C# properties 010 //----------------------------------- 011     //Public access to instance 012     public static EventManager Instance 013       { 014             get{return instance;} 015            set{} 016       } 017   #endregion 018 019   #region variables 020       // Notifications Manager instance (singleton design pattern) 021   private static EventManager instance = null; 022 023     //Array of listeners (all objects registered for events) 024     private Dictionary<EVENT_TYPE, List<IListener>> Listeners          = new Dictionary<EVENT_TYPE, List<IListener>>(); 025     #endregion 026 //----------------------------------------------------------- 027     #region methods 028     //Called at start-up to initialize 029     void Awake() 030     { 031             //If no instance exists, then assign this instance 032             if(instance == null) 033           { 034                   instance = this; 035                   DontDestroyOnLoad(gameObject); 036           } 037             else 038                   DestroyImmediate(this); 039     } 040//----------------------------------------------------------- 041     /// <summary> 042     /// Function to add listener to array of listeners 043     /// </summary> 044     /// <param name="Event_Type">Event to Listen for</param> 045     /// <param name="Listener">Object to listen for event</param> 046     public void AddListener(EVENT_TYPE Event_Type, IListener        Listener) 047    { 048           //List of listeners for this event 049           List<IListener> ListenList = null; 050 051           // Check existing event type key. If exists, add to list 052           if(Listeners.TryGetValue(Event_Type,                out ListenList)) 053           { 054                   //List exists, so add new item 055                   ListenList.Add(Listener); 056                   return; 057           } 058 059           //Otherwise create new list as dictionary key 060           ListenList = new List<IListener>(); 061           ListenList.Add(Listener); 062           Listeners.Add(Event_Type, ListenList); 063     } 064 //----------------------------------------------------------- 065       /// <summary> 066       /// Function to post event to listeners 067       /// </summary> 068       /// <param name="Event_Type">Event to invoke</param> 069       /// <param name="Sender">Object invoking event</param> 070       /// <param name="Param">Optional argument</param> 071       public void PostNotification(EVENT_TYPE Event_Type,          Component Sender, Object Param = null) 072       { 073           //Notify all listeners of an event 074 075           //List of listeners for this event only 076           List<IListener> ListenList = null; 077 078           //If no event exists, then exit 079           if(!Listeners.TryGetValue(Event_Type,                out ListenList)) 080                   return; 081 082             //Entry exists. Now notify appropriate listeners 083             for(int i=0; i<ListenList.Count; i++) 084             { 085                   if(!ListenList[i].Equals(null)) 086                   ListenList[i].OnEvent(Event_Type, Sender, Param); 087             } 088     } 089 //----------------------------------------------------------- 090     //Remove event from dictionary, including all listeners 091     public void RemoveEvent(EVENT_TYPE Event_Type) 092     { 093           //Remove entry from dictionary 094           Listeners.Remove(Event_Type); 095     } 096 //----------------------------------------------------------- 097       //Remove all redundant entries from the Dictionary 098     public void RemoveRedundancies() 099     { 100             //Create new dictionary 101             Dictionary<EVENT_TYPE, List<IListener>>                TmpListeners = new Dictionary                <EVENT_TYPE, List<IListener>>(); 102 103             //Cycle through all dictionary entries 104             foreach(KeyValuePair<EVENT_TYPE, List<IListener>>                Item in Listeners) 105             { 106                   //Cycle all listeners, remove null objects 107                   for(int i = Item.Value.Count-1; i>=0; i--) 108                   { 109                         //If null, then remove item 110                         if(Item.Value[i].Equals(null)) 111                                 Item.Value.RemoveAt(i); 112                   } 113 114           //If items remain in list, then add to tmp dictionary 115                   if(Item.Value.Count > 0) 116                         TmpListeners.Add (Item.Key,                              Item.Value); 117             } 118 119             //Replace listeners object with new dictionary 120             Listeners = TmpListeners; 121     } 122 //----------------------------------------------------------- 123       //Called on scene change. Clean up dictionary 124       void OnLevelWasLoaded() 125       { 126           RemoveRedundancies(); 127       } 128 //----------------------------------------------------------- 129     #endregion 130 } More information on the OnLevelWasLoaded event can be found at http://docs.unity3d.com/ScriptReference/MonoBehaviour.OnLevelWasLoaded.html. The following are the comments for the code sample 4-5: Line 003: Notice the addition of the System.Collections.Generic namespace giving us access to additional mono classes, including the Dictionary class. This class will be used throughout the EventManager class. In short, the Dictionary class is a special kind of 2D array that allows us to store a database of values based on key-value pairing. More information on the Dictionary class can be found at http://msdn.microsoft.com/en-us/library/xfhwa508%28v=vs.110%29.aspx. Line 007: The EventManager class is derived from MonoBehaviour and should be attached to an empty GameObject in the scene where it will exist as a persistent singleton. Line 024: A private member variable Listeners is declared using a Dictionary class. This structure maintains a hash-table array of key-value pairs, which can be looked up and searched like a database. The key-value pairing for the EventManager class takes the form of EVENT_TYPE and List<Component>. In short, this means that a list of event types can be stored (such as HEALTH_CHANGE), and for each type there could be none, one, or more components that are listening and which should be notified when the event occurs. In effect, the Listeners member is the primary data structure on which the EventManager relies to maintain who is listening for what. Lines 029-039: The Awake function is responsible for the singleton functionality, that is, to make the EventManager class into a singleton object that persists across scenes. Lines 046-063: The AddListener method of EventManager should be called by a Listener object once for each event for which it should listen. The method accepts two arguments: the event to listen for (Event_Type) and a reference to the listener object itself (derived from IListener), which should be notified if and when the event happens. The AddListener function is responsible for accessing the Listeners dictionary and generating a new key-value pair to store the connection between the event and the listener. Lines 071-088: The PostNotification function can be called by any object, whether a listener or not, whenever an event is detected. When called, the EventManager cycles all matching entries in the dictionary, searching for all listeners connected to the current event, and notifies them by invoking the OnEvent method through the IListener interface. Lines 098-127: The final methods for the EventManager class are responsible for maintaining data integrity of the Listeners structure when a scene change occurs and the EventManager class persists. Although the EventManager class persists across scenes, the listener objects themselves in the Listeners variable may not do so. They may get destroyed on scene changes. If so, scene changes will invalidate some listeners, leaving the EventManager with invalid entries. Thus, the RemoveRedundancies method is called to find and eliminate all invalid entries. The OnLevelWasLoaded event is invoked automatically by Unity whenever a scene change occurs. More information on the OnLevelWasLoaded event can be found online at: http://docs.unity3d.com/ScriptReference/MonoBehaviour.OnLevelWasLoaded.html. #region and #endregion The two preprocessor directives #region and #endregion (in combination with the code folding feature) can be highly useful for improving the readability of your code and also for improving the speed with which you can navigate the source file. They add organization and structure to your source code without affecting its validity or execution. Effectively, #region marks the top of a code block and #endregion marks the end. Once a region is marked, it becomes foldable, that is, it becomes collapsible using the MonoDevelop code editor, provided the code folding feature is enabled. Collapsing a region of code is useful for hiding it from view, which allows you to concentrate on reading other areas relevant to your needs, as shown in the following screenshot: Enabling code folding in MonoDevelop To enable code folding in MonoDevelop, select Options in Tools from the application menu. This displays the Options window. From here, choose the General tab in the Text Editor option and click on Enable code folding as well as Fold #regions by default. Using EventManager Now, let's see how to put the EventManager class to work in a practical context from the perspective of listeners and posters in a single scene. First, to listen for an event (any event) a listener must register itself with the EventManager singleton instance. Typically, this will happen once and at the earliest opportunity, such as the Start function. Do not use the Awake function; this is reserved for an object's internal initialization as opposed to the functionality that reaches out beyond the current object to the states and setup of others. See the following code sample 4-6 and notice that it relies on the Instance static property to retrieve a reference to the active EventManager singleton: //Called at start-up void Start() { //Add myself as listener for health change events EventManager.Instance.AddListener(EVENT_TYPE.HEALTH_CHANGE, this); } Having registered listeners for one or more events, objects can then post notifications to EventManager as events are detected, as shown in the following code sample 4-7: public int Health { get{return _health;} set {    //Clamp health between 0-100    _health = Mathf.Clamp(value, 0, 100);    //Post notification - health has been changed   EventManager.Instance. PostNotification(EVENT_TYPE.HEALTH_CHANGE, this, _health); } } Finally, after a notification is posted for an event, all the associated listeners are updated automatically through EventManager. Specifically, EventManager will call the OnEvent function of each listener, giving listeners the opportunity to parse event data and respond where needed, as shown in the following code sample 4-7: //Called when events happen public void OnEvent(EVENT_TYPE Event_Type, Component Sender, object Param = null) { //Detect event type switch(Event_Type) {    case EVENT_TYPE.HEALTH_CHANGE:          OnHealthChange(Sender, (int)Param);    break; } } Summary This article focused on the manifold benefits available for your applications by adopting an event-driven framework consistently through the EventManager class. In implementing such a manager, we were able to rely on either interfaces or delegates, and either method is powerful and extensible. Specifically, we saw how it's easy to add more and more functionality into an Update function but how doing this can lead to severe performance issues. Better is to analyze the connections between your functionality to refactor it into an event-driven framework. Essentially, events are the raw material of event-driven systems. They represent a necessary connection between one action (the cause) and another (the response). To manage events, we created the EventManager class—an integrated class or system that links posters to listeners. It receives notifications from posters about events as and when they happen and then immediately dispatches a function call to all listeners for the event. Resources for Article: Further resources on this subject: Customizing skin with GUISkin [Article] 2D Twin-stick Shooter [Article] Components in Unity [Article]

In this article by Christopher Ilacqua, Henric Cronström, and James Richardson, authors of the book Learning Qlik® Sense, we will look at the evolving requirements that compel organizations to readdress how they deliver business intelligence and support data-driven decision-making. This is important as it supplies some of the reasons as to why Qlik® Sense is relevant and important to their success. The purpose of covering these factors is so that you can consider and plan for them in your organization. Among other things, in this article, we will cover the following topics: The ongoing data explosion The rise of in-memory processing Barrierless BI through Human-Computer Interaction The consumerization of BI and the rise of self-service The use of information as an asset The changing role of IT (For more resources related to this topic, see here.) Evolving market factors Technologies are developed and evolved in response to the needs of the environment they are created and used within. The most successful new technologies anticipate upcoming changes in order to help people take advantage of altered circumstances or reimagine how things are done. Any market is defined by both the suppliers—in this case, Qlik®—and the buyers, that is, the people who want to get more use and value from their information. Buyers' wants and needs are driven by a variety of macro and micro factors, and these are always in flux in some markets more than others. This is obviously and apparently the case in the world of data, BI, and analytics, which has been changing at a great pace due to a number of factors discussed further in the rest of this article. Qlik Sense has been designed to be the means through which organizations and the people that are a part of them thrive in a changed environment. Big, big, and even bigger data A key factor is that there's simply much more data in many forms to analyze than before. We're in the middle of an ongoing, accelerating data boom. According to Science Daily, 90 percent of the world's data was generated over the past two years. The fact is that with technologies such as Hadoop and NoSQL databases, we now have unprecedented access to cost-effective data storage. With vast amounts of data now storable and available for analysis, people need a way to sort the signal from the noise. People from a wider variety of roles—not all of them BI users or business analysts—are demanding better, greater access to data, regardless of where it comes from. Qlik Sense's fundamental design centers on bringing varied data together for exploration in an easy and powerful way. The slow spinning down of the disk At the same time, we are seeing a shift in how computation occurs and potentially, how information is managed. Fundamentals of the computing architectures that we've used for decades, the spinning disk and moving read head, are becoming outmoded. This means storing and accessing data has been around since Edison invented the cylinder phonograph in 1877. It's about time this changed. This technology has served us very well; it was elegant and reliable, but it has limitations. Speed limitations primarily. Fundamentals that we take for granted today in BI, such as relational and multidimensional storage models, were built around these limitations. So were our IT skills, whether we realized it at the time. With the use of in-memory processing and 64-bit addressable memory spaces, these limitations are gone! This means a complete change in how we think about analysis. Processing data in memory means we can do analysis that was impractical or impossible before with the old approach. With in-memory computing, analysis that would've taken days before, now takes just seconds (or much less). However, why does it matter? Because it allows us to use the time more effectively; after all, time is the most finite resource of all. In-memory computing enables us to ask more questions, test more scenarios, do more experiments, debunk more hypotheses, explore more data, and run more simulations in the short window available to us. For IT, it means no longer trying to second-guess what users will do months or years in advance and trying to premodel it in order to achieve acceptable response times. People hate watching the hourglass spin. Qlik Sense's predecessor QlikView® was built on the exploitation of in-memory processing; Qlik Sense has it at its core too. Ubiquitous computing and the Internet of Things You may know that more than a billion people use Facebook, but did you know that the majority of those people do so from a mobile device? The growth in the number of devices connected to the Internet is absolutely astonishing. According to Cisco's Zettabyte Era report, Internet traffic from wireless devices will exceed traffic from wired devices in 2014. If we were writing this article even as recently as a year ago, we'd probably be talking about mobile BI as a separate thing from desktop or laptop delivered analytics. The fact of the matter is that we've quickly gone beyond that. For many people now, the most common way to use technology is on a mobile device, and they expect the kind of experience they've become used to on their iOS or Android device to be mirrored in complex software, such as the technology they use for visual discovery and analytics. From its inception, Qlik Sense has had mobile usage in the center of its design ethos. It's the first data discovery software to be built for mobiles, and that's evident in how it uses HTML5 to automatically render output for the device being used, whatever it is. Plug in a laptop running Qlik Sense to a 70-inch OLED TV and the visual output is resized and re-expressed to optimize the new form factor. So mobile is the new normal. This may be astonishing but it's just the beginning. Mobile technology isn't just a medium to deliver information to people, but an acceleration of data production for analysis too. By 2020, pretty much everyone and an increasing number of things will be connected to the Internet. There are 7 billion people on the planet today. Intel predicts that by 2020, more than 31 billion devices will be connected to the Internet. So, that's not just devices used by people directly to consume or share information. More and more things will be put online and communicate their state: cars, fridges, lampposts, shoes, rubbish bins, pets, plants, heating systems—you name it. These devices will generate a huge amount of data from sensors that monitor all kinds of measurable attributes: temperature, velocity, direction, orientation, and time. This means an increasing opportunity to understand a huge gamut of data, but without the right technology and approaches it will be complex to analyze what is going on. Old methods of analysis won't work, as they don't move quickly enough. The variety and volume of information that can be analyzed will explode at an exponential rate. The rise of this type of big data makes us redefine how we build, deliver, and even promote analytics. It is an opportunity for those organizations that can exploit it through analysis; this can sort the signals from the noise and make sense of the patterns in the data. Qlik Sense is designed as just such a signal booster; it takes how users can zoom and pan through information too large for them to easily understand the product. Unbound Human-Computer Interaction We touched on the boundary between the computing power and the humans using it in the previous section. Increasingly, we're removing barriers between humans and technology. Take the rise of touch devices. Users don't want to just view data presented to them in a static form. Instead, they want to "feel" the data and interact with it. The same is increasingly true of BI. The adoption of BI tools has been too low because the technology has been hard to use. Adoption has been low because in the past BI tools often required people to conform to the tool's way of working, rather than reflecting the user's way of thinking. The aspiration for Qlik Sense (when part of the QlikView.Next project) was that the software should be both "gorgeous and genius". The genius part obviously refers to the built-in intelligence, the smarts, the software will have. The gorgeous part is misunderstood or at least oversimplified. Yes, it means cosmetically attractive (which is important) but much more importantly, it means enjoyable to use and experience. In other words, Qlik Sense should never be jarring to users but seamless, perhaps almost transparent to them, inducing a state of mental flow that encourages thinking about the question being considered rather than the tool used to answer it. The aim was to be of most value to people. Qlik Sense will empower users to explore their data and uncover hidden insights, naturally. Evolving customer requirements It is not only the external market drivers that impact how we use information. Our organizations and the people that work within them are also changing in their attitude towards technology, how they express ideas through data, and how increasingly they make use of data as a competitive weapon. Consumerization of BI and the rise of self-service The consumerization of any technology space is all about how enterprises are affected by, and can take advantage of, new technologies and models that originate and develop in the consumer marker, rather than in the enterprise IT sector. The reality is that individuals react quicker than enterprises to changes in technology. As such, consumerization cannot be stopped, nor is it something to be adopted. It can be embraced. While it's not viable to build a BI strategy around consumerization alone, its impact must be considered. Consumerization makes itself felt in three areas: Technology: Most investment in innovation occurs in the consumer space first, with enterprise vendors incorporating consumer-derived features after the fact. (Think about how vendors added the browser as a UI for business software applications.) Economics: Consumer offerings are often less expensive or free (to try) with a low barrier of entry. This drives prices down, including enterprise sectors, and alters selection behavior. People: Demographics, which is the flow of Millennial Generation into the workplace, and the blurring of home/work boundaries and roles, which may be seen from a traditional IT perspective as rogue users, with demands to BYOPC or device. In line with consumerization, BI users want to be able to pick up and just use the technology to create and share engaging solutions; they don't want to read the manual. This places a high degree of importance on the Human-Computer Interaction (HCI) aspects of a BI product (refer to the preceding list) and governed access to information and deployment design. Add mobility to this and you get a brand new sourcing and adoption dynamic in BI, one that Qlik engendered, and Qlik Sense is designed to take advantage of. Think about how Qlik Sense Desktop was made available as a freemium offer. Information as an asset and differentiator As times change, so do differentiators. For example, car manufacturers in the 1980s differentiated themselves based on reliability, making sure their cars started every single time. Today, we expect that our cars will start; reliability is now a commodity. The same is true for ERP systems. Originally, companies implemented ERPs to improve reliability, but in today's post-ERP world, companies are shifting to differentiating their businesses based on information. This means our focus changes from apps to analytics. And analytics apps, like those delivered by Qlik Sense, help companies access the data they need to set themselves apart from the competition. However, to get maximum return from information, the analysis must be delivered fast enough, and in sync with the operational tempo people need. Things are speeding up all the time. For example, take the fashion industry. Large mainstream fashion retailers used to work two seasons per year. Those that stuck to that were destroyed by fast fashion retailers. The same is true for old style, system-of-record BI tools; they just can't cope with today's demands for speed and agility. The rise of information activism A new, tech-savvy generation is entering the workforce, and their expectations are different than those of past generations. The Beloit College Mindset List for the entering class of 2017 gives the perspective of students entering college this year, how they see the world, and the reality they've known all their lives. For this year's freshman class, Java has never been just a cup of coffee and a tablet is no longer something you take in the morning. This new generation of workers grew up with the Internet and is less likely to be passive with data. They bring their own devices everywhere they go, and expect it to be easy to mash-up data, communicate, and collaborate with their peers. The evolution and elevation of the role of IT We've all read about how the role of IT is changing, and the question CIOs today must ask themselves is: "How do we drive innovation?". IT must transform from being gatekeepers (doers) to storekeepers (enablers), providing business users with self-service tools they need to be successful. However, to achieve this transformation, they need to stock helpful tools and provide consumable information products or apps. Qlik Sense is a key part of the armory that IT needs to provide to be successful in this transformation. Summary In this article, we looked at the factors that provide the wider context for the use of Qlik Sense. The factors covered arise out of both increasing technical capability and demands to compete in a globalized, information-centric world, where out-analyzing your competitors is a key success factor. Resources for Article: Further resources on this subject: Securing QlikView Documents [article] Conozca QlikView [article] Introducing QlikView elements [article]

In this article by Marco Schwartz and Oliver Manickum authors of the book Programming Arduino with LabVIEW, we will see how to design an interfave using LabVIEW. (For more resources related to this topic, see here.) At this stage, we know that we have our two sensors working and that they were interfaced correctly with the LabVIEW interface. However, we can do better; for now, we simply have a text display of the measurements, which is not elegant to read. Also, the light-level measurement goes from 0 to 5, which doesn't mean anything for somebody who will look at the interface for the first time. Therefore, we will modify the interface slightly. We will add a temperature gauge to display the data coming from the temperature sensor, and we will modify the output of the reading from the photocell to display the measurement from 0 (no light) to 100 percent (maximum brightness). We first need to place the different display elements. To do this, perform the following steps: Start with Front Panel. You can use a temperature gauge for the temperature and a simple slider indicator for Light Level. You will find both in the Indicators submenu of LabVIEW. After that, simply place them on the right-hand side of the interface and delete the other indicators we used earlier. Also, name the new indicators accordingly so that we can know to which element we have to connect them later. Then, it is time to go back to Block Diagram to connect the new elements we just added in Front Panel. For the temperature element, it is easy: you can simply connect the temperature gauge to the TMP36 output pin. For the light level, we will make slightly more complicated changes. We will divide the measured value beside the Analog Read element by 5, thus obtaining an output value between 0 and 1. Then, we will multiply this value by 100, to end up with a value going from 0 to 100 percent of the ambient light level. To do so perform the following steps: The first step is to place two elements corresponding to the two mathematical operations we want to do: a divide operator and a multiply operator. You can find both of them in the Functions panel of LabVIEW. Simply place them close to the Analog Read element in your program. After that, right-click on one of the inputs of each operator element, and go to Create | Constant to create a constant input for each block. Add a value of 5 for the division block, and add a value of 100 for the multiply block. Finally, connect the output of the Analog Read element to the input of the division block, the output of this block to the input of the multiply block, and the output of the multiply block to the input of the Light Level indicator. You can now go back to Front Panel to see the new interface in action. You can run the program again by clicking on the little arrow on the toolbar. You should immediately see that Temperature is now indicated by the gauge on the right and Light Level is immediately changing on the slider, depending on how you cover the sensor with your hand. Summary In this article, we connected a temperature sensor and a light-level sensor to Arduino and built a simple LabVIEW program to read data from these sensors. Then, we built a nice graphical interface to visualize the data coming from these sensors. There are many ways you can build other projects based on what you learned in this article. You can, for example, connect higher temperatures and/or more light-level sensors to the Arduino board and display these measurements in the interface. You can also connect other kinds of sensors that are supported by LabVIEW, for example, other analog sensors. For example, you can add a barometric pressure sensor or a humidity sensor to the project to build an even more complete weather-measurement station. One other interesting extension of this article will be to use the storage and plotting capabilities of LabVIEW to dynamically plot the history of the measured data inside the LabVIEW interface. Resources for Article: Further resources on this subject: The Arduino Mobile Robot [article] Using the Leap Motion Controller with Arduino [article] Avoiding Obstacles Using Sensors [article]