How-To Tutorials

In this article by Karan Singh, author of the book, Learning Ceph, we will cover the following topics: Creating a sandbox environment with VirtualBox From zero to Ceph – deploying your first Ceph cluster Scaling up your Ceph cluster – monitor and OSD addition (For more resources related to this topic, see here.) Creating a sandbox environment with VirtualBox We can test deploy Ceph in a sandbox environment using Oracle VirtualBox virtual machines. This virtual setup can help us discover and perform experiments with Ceph storage clusters as if we are working in a real environment. Since Ceph is an open source software-defined storage deployed on top of commodity hardware in a production environment, we can imitate a fully functioning Ceph environment on virtual machines, instead of real-commodity hardware, for our testing purposes. Oracle VirtualBox is a free software available at http://www.virtualbox.org for Windows, Mac OS X, and Linux. We must fulfil system requirements for the VirtualBox software so that it can function properly during our testing. We assume that your host operating system is a Unix variant; for Microsoft windows, host machines use an absolute path to run the VBoxManage command, which is by default c:Program FilesOracleVirtualBoxVBoxManage.exe. The system requirement for VirtualBox depends upon the number and configuration of virtual machines running on top of it. Your VirtualBox host should require an x86-type processor (Intel or AMD), a few gigabytes of memory (to run three Ceph virtual machines), and a couple of gigabytes of hard drive space. To begin with, we must download VirtualBox from http://www.virtualbox.org/ and then follow the installation procedure once this has been downloaded. We will also need to download the CentOS 6.4 Server ISO image from http://vault.centos.org/6.4/isos/. To set up our sandbox environment, we will create a minimum of three virtual machines; you can create even more machines for your Ceph cluster based on the hardware configuration of your host machine. We will first create a single VM and install OS on it; after this, we will clone this VM twice. This will save us a lot of time and increase our productivity. Let's begin by performing the following steps to create the first virtual machine: The VirtualBox host machine used throughout in this demonstration is a Mac OS X which is a UNIX-type host. If you are performing these steps on a non-UNIX machine that is, on Windows-based host then keep in mind that virtualbox hostonly adapter name will be something like VirtualBox Host-Only Ethernet Adapter #<adapter number>. Please run these commands with the correct adapter names. On windows-based hosts, you can check VirtualBox networking options in Oracle VM VirtualBox Manager by navigating to File | VirtualBox Settings | Network | Host-only Networks. After the installation of the VirtualBox software, a network adapter is created that you can use, or you can create a new adapter with a custom IP:For UNIX-based VirtualBox hosts # VBoxManage hostonlyif remove vboxnet1 # VBoxManage hostonlyif create # VBoxManage hostonlyif ipconfig vboxnet1 --ip 192.168.57.1 --netmask 255.255.255.0 For Windows-based VirtualBox hosts # VBoxManage.exe hostonlyif remove "VirtualBox Host-Only Ethernet Adapter" # VBoxManage.exe hostonlyif create # VBoxManage hostonlyif ipconfig "VirtualBox Host-Only Ethernet Adapter" --ip 192.168.57.1 --netmask 255.255.255. VirtualBox comes with a GUI manager. If your host is running Linux OS, it should have the X-desktop environment (Gnome or KDE) installed. Open Oracle VM VirtualBox Manager and create a new virtual machine with the following specifications using GUI-based New Virtual Machine Wizard, or use the CLI commands mentioned at the end of every step: 1 CPU 1024 MB memory 10 GB X 4 hard disks (one drive for OS and three drives for Ceph OSD) 2 network adapters CentOS 6.4 ISO attached to VM The following is the step-by-step process to create virtual machines using CLI commands: Create your first virtual machine: # VBoxManage createvm --name ceph-node1 --ostype RedHat_64 --register # VBoxManage modifyvm ceph-node1 --memory 1024 --nic1 nat --nic2 hostonly --hostonlyadapter2 vboxnet1 For Windows VirtualBox hosts: # VBoxManage.exe modifyvm ceph-node1 --memory 1024 --nic1 nat --nic2 hostonly --hostonlyadapter2 "VirtualBox Host-Only Ethernet Adapter" Create CD-Drive and attach CentOS ISO image to first virtual machine: # VBoxManage storagectl ceph-node1 --name "IDE Controller" --add ide --controller PIIX4 --hostiocache on --bootable on # VBoxManage storageattach ceph-node1 --storagectl "IDE Controller" --type dvddrive --port 0 --device 0 --medium CentOS-6.4-x86_64-bin-DVD1.iso Make sure you execute the preceding command from the same directory where you have saved CentOS ISO image or you can specify the location where you saved it. Create SATA interface, OS hard drive and attach them to VM; make sure the VirtualBox host has enough free space for creating vm disks. If not, select the host drive which have free space: # VBoxManage storagectl ceph-node1 --name "SATA Controller" --add sata --controller IntelAHCI --hostiocache on --bootable on # VBoxManage createhd --filename OS-ceph-node1.vdi --size 10240 # VBoxManage storageattach ceph-node1 --storagectl "SATA Controller" --port 0 --device 0 --type hdd --medium OS-ceph-node1.vdi Create SATA interface, first ceph disk and attach them to VM: # VBoxManage createhd --filename ceph-node1-osd1.vdi --size 10240 # VBoxManage storageattach ceph-node1 --storagectl "SATA Controller" --port 1 --device 0 --type hdd --medium ceph-node1-osd1.vdi Create SATA interface, second ceph disk and attach them to VM: # VBoxManage createhd --filename ceph-node1-osd2.vdi --size 10240 # VBoxManage storageattach ceph-node1 --storagectl "SATA Controller" --port 2 --device 0 --type hdd --medium ceph-node1-osd2.vdi Create SATA interface, third ceph disk and attach them to VM: # VBoxManage createhd --filename ceph-node1-osd3.vdi --size 10240 # VBoxManage storageattach ceph-node1 --storagectl "SATA Controller" --port 3 --device 0 --type hdd --medium ceph-node1-osd3.vdi Now, at this point, we are ready to power on our ceph-node1 VM. You can do this by selecting the ceph-node1 VM from Oracle VM VirtualBox Manager, and then clicking on the Start button, or you can run the following command: # VBoxManage startvm ceph-node1 --type gui As soon as you start your VM, it should boot from the ISO image. After this, you should install CentOS on VM. If you are not already familiar with Linux OS installation, you can follow the documentation at https://access.redhat.com/site/documentation/en-US/Red_Hat_Enterprise_Linux/6/html/Installation_Guide/index.html. Once you have successfully installed the operating system, edit the network configuration of the machine: Edit /etc/sysconfig/network and change the hostname parameter HOSTNAME=ceph-node1 Edit the /etc/sysconfig/network-scripts/ifcfg-eth0 file and add: ONBOOT=yes BOOTPROTO=dhcp Edit the /etc/sysconfig/network-scripts/ifcfg-eth1 file and add:< ONBOOT=yes BOOTPROTO=static IPADDR=192.168.57.101 NETMASK=255.255.255.0 Edit the /etc/hosts file and add: 192.168.57.101 ceph-node1 192.168.57.102 ceph-node2 192.168.57.103 ceph-node3 Once the network settings have been configured, restart VM and log in via SSH from your host machine. Also, test the Internet connectivity on this machine, which is required to download Ceph packages: # ssh root@192.168.57.101 Once the network setup has been configured correctly, you should shut down your first VM so that we can make two clones of your first VM. If you do not shut down your first VM, the cloning operation might fail. Create clone of ceph-node1 as ceph-node2: # VBoxManage clonevm --name ceph-node2 ceph-node1 --register Create clone of ceph-node1 as ceph-node3: # VBoxManage clonevm --name ceph-node3 ceph-node1 --register After the cloning operation is complete, you can start all three VMs: # VBoxManage startvm ceph-node1 # VBoxManage startvm ceph-node2 # VBoxManage startvm ceph-node3 Set up VM ceph-node2 with the correct hostname and network configuration: Edit /etc/sysconfig/network and change the hostname parameter: HOSTNAME=ceph-node2 Edit the /etc/sysconfig/network-scripts/ifcfg-<first interface name> file and add: DEVICE=<correct device name of your first network interface, check ifconfig -a> ONBOOT=yes BOOTPROTO=dhcp HWADDR= <correct MAC address of your first network interface, check ifconfig -a > Edit the /etc/sysconfig/network-scripts/ifcfg-<second interface name> file and add: DEVICE=<correct device name of your second network interface, check ifconfig -a> ONBOOT=yes BOOTPROTO=static IPADDR=192.168.57.102 NETMASK=255.255.255.0 HWADDR= <correct MAC address of your second network interface, check ifconfig -a > Edit the /etc/hosts file and add: 192.168.57.101 ceph-node1 192.168.57.102 ceph-node2 192.168.57.103 ceph-node3 After performing these changes, you should restart your virtual machine to bring the new hostname into effect. The restart will also update your network configurations. Set up VM ceph-node3 with the correct hostname and network configuration: Edit /etc/sysconfig/network and change the hostname parameter:HOSTNAME=ceph-node3 Edit the /etc/sysconfig/network-scripts/ifcfg-<first interface name> file and add: DEVICE=<correct device name of your first network interface, check ifconfig -a> ONBOOT=yes BOOTPROTO=dhcp HWADDR= <correct MAC address of your first network interface, check ifconfig -a > Edit the /etc/sysconfig/network-scripts/ifcfg-<second interface name> file and add: DEVICE=<correct device name of your second network interface, check ifconfig -a> ONBOOT=yes BOOTPROTO=static IPADDR=192.168.57.103 NETMASK=255.255.255.0 HWADDR= <correct MAC address of your second network interface, check ifconfig -a > Edit the /etc/hosts file and add: 192.168.57.101 ceph-node1 192.168.57.102 ceph-node2 192.168.57.103 ceph-node3 After performing these changes, you should restart your virtual machine to bring a new hostname into effect; the restart will also update your network configurations. At this point, we prepare three virtual machines and make sure each VM communicates with each other. They should also have access to the Internet to install Ceph packages. From zero to Ceph – deploying your first Ceph cluster To deploy our first Ceph cluster, we will use the ceph-deploy tool to install and configure Ceph on all three virtual machines. The ceph-deploy tool is a part of the Ceph software-defined storage, which is used for easier deployment and management of your Ceph storage cluster. Since we created three virtual machines that run CentOS 6.4 and have connectivity with the Internet as well as private network connections, we will configure these machines as Ceph storage clusters as mentioned in the following diagram: Configure ceph-node1 for an SSH passwordless login to other nodes. Execute the following commands from ceph-node1: While configuring SSH, leave the paraphrase empty and proceed with the default settings: # ssh-keygen Copy the SSH key IDs to ceph-node2 and ceph-node3 by providing their root passwords. After this, you should be able to log in on these nodes without a password: # ssh-copy-id ceph-node2 Installing and configuring EPEL on all Ceph nodes: Install EPEL which is the repository for installing extra packages for your Linux system by executing the following command on all Ceph nodes: # rpm -ivh http://dl.fedoraproject.org/pub/epel/6/x86_64/epel-release-6-8.noarch.rpm Make sure the baserul parameter is enabled under the /etc/yum.repos.d/epel.repo file. The baseurl parameter defines the URL for extra Linux packages. Also make sure the mirrorlist parameter must be disabled (commented) under this file. Problems been observed during installation if the mirrorlist parameter is enabled under epel.repo file. Perform this step on all the three nodes. Install ceph-deploy on the ceph-node1 machine by executing the following command from ceph-node1: # yum install ceph-deploy Next, we will create a Ceph cluster using ceph-deploy by executing the following command from ceph-node1: # ceph-deploy new ceph-node1 ## Create a directory for ceph # mkdir /etc/ceph # cd /etc/ceph The new subcommand of ceph-deploy deploys a new cluster with ceph as the cluster name, which is by default; it generates a cluster configuration and keying files. List the present working directory; you will find the ceph.conf and ceph.mon.keyring files. In this testing, we will intentionally install the Emperor release (v0.72) of Ceph software, which is not the latest release. Later in this book, we will demonstrate the upgradation of Emperor to Firefly release of Ceph. To install Ceph software binaries on all the machines using ceph-deploy; execute the following command from ceph-node1:ceph-deploy install --release emperor ceph-node1 ceph-node2 ceph-node3 The ceph-deploy tool will first install all the dependencies followed by the Ceph Emperor binaries. Once the command completes successfully, check the Ceph version and Ceph health on all the nodes, as follows: # ceph –v Create your first monitor on ceph-node1: # ceph-deploy mon create-initial Once monitor creation is successful, check your cluster status. Your cluster will not be healthy at this stage: # ceph status Create an object storage device (OSD) on the ceph-node1 machine, and add it to the Ceph cluster executing the following steps: List the disks on VM: # ceph-deploy disk list ceph-node1 From the output, carefully identify the disks (other than OS-partition disks) on which we should create Ceph OSD. In our case, the disk names will ideally be sdb, sdc, and sdd. The disk zap subcommand will destroy the existing partition table and content from the disk. Before running the following command, make sure you use the correct disk device name. # ceph-deploy disk zap ceph-node1:sdb ceph-node1:sdc ceph-node1:sdd The osd create subcommand will first prepare the disk, that is, erase the disk with a filesystem, which is xfs by default. Then, it will activate the disk's first partition as data partition and second partition as journal: # ceph-deploy osd create ceph-node1:sdb ceph-node1:sdc ceph-node1:sdd Check the cluster status for new OSD entries: # ceph status At this stage, your cluster will not be healthy. We need to add a few more nodes to the Ceph cluster so that it can set up a distributed, replicated object storage, and hence become healthy. Scaling up your Ceph cluster – monitor and OSD addition Now we have a single-node Ceph cluster. We should scale it up to make it a distributed, reliable storage cluster. To scale up a cluster, we should add more monitor nodes and OSD. As per our plan, we will now configure ceph-node2 and ceph-node3 machines as monitor as well as OSD nodes. Adding the Ceph monitor A Ceph storage cluster requires at least one monitor to run. For high availability, a Ceph storage cluster relies on an odd number of monitors that's more than one, for example, 3 or 5, to form a quorum. It uses the Paxos algorithm to maintain quorum majority. Since we already have one monitor running on ceph-node1, let's create two more monitors for our Ceph cluster: The firewall rules should not block communication between Ceph monitor nodes. If they do, you need to adjust the firewall rules in order to let monitors form a quorum. Since this is our test setup, let's disable firewall on all three nodes. We will run these commands from the ceph-node1 machine, unless otherwise specified: # service iptables stop # chkconfig iptables off # ssh ceph-node2 service iptables stop # ssh ceph-node2 chkconfig iptables off # ssh ceph-node3 service iptables stop # ssh ceph-node3 chkconfig iptables off Deploy a monitor on ceph-node2 and ceph-node3: # ceph-deploy mon create ceph-node2 # ceph-deploy mon create ceph-node3 The deploy operation should be successful; you can then check your newly added monitors in the Ceph status: You might encounter warning messages related to clock skew on new monitor nodes. To resolve this, we need to set up Network Time Protocol (NTP) on new monitor nodes: # chkconfig ntpd on # ssh ceph-node2 chkconfig ntpd on # ssh ceph-node3 chkconfig ntpd on # ntpdate pool.ntp.org # ssh ceph-node2 ntpdate pool.ntp.org # ssh ceph-node3 ntpdate pool.ntp.org # /etc/init.d/ntpd start # ssh ceph-node2 /etc/init.d/ntpd start # ssh ceph-node3 /etc/init.d/ntpd start Adding the Ceph OSD At this point, we have a running Ceph cluster with three monitors OSDs. Now we will scale our cluster and add more OSDs. To accomplish this, we will run the following commands from the ceph-node1 machine, unless otherwise specified. We will follow the same method for OSD addition: # ceph-deploy disk list ceph-node2 ceph-node3 # ceph-deploy disk zap ceph-node2:sdb ceph-node2:sdc ceph-node2:sdd # ceph-deploy disk zap ceph-node3:sdb ceph-node3:sdc ceph-node3:sdd # ceph-deploy osd create ceph-node2:sdb ceph-node2:sdc ceph-node2:sdd # ceph-deploy osd create ceph-node3:sdb ceph-node3:sdc ceph-node3:sdd # ceph status Check the cluster status for a new OSD. At this stage, your cluster will be healthy with nine OSDs in and up: Summary The software-defined nature of Ceph provides a great deal of flexibility to its adopters. Unlike other proprietary storage systems, which are hardware dependent, Ceph can be easily deployed and tested on almost any computer system available today. Moreover, if getting physical machines is a challenge, you can use virtual machines to install Ceph, as mentioned in this article, but keep in mind that such a setup should only be used for testing purposes. In this article, we learned how to create a set of virtual machines using the VirtualBox software, followed by Ceph deployment as a three-node cluster using the ceph-deploy tool. We also added a couple of OSDs and monitor machines to our cluster in order to demonstrate its dynamic scalability. We recommend you deploy a Ceph cluster of your own using the instructions mentioned in this article. Resources for Article: Further resources on this subject: Linux Shell Scripting - various recipes to help you [article] GNU Octave: Data Analysis Examples [article] What is Kali Linux [article]

In this article by Bass Jobsen, author of the book Less Web Development Cookbook, you will learn: Giving your rules importance with the !important statement Using mixins with multiple parameters Using duplicate mixin names Building a switch leveraging argument matching Avoiding individual parameters to leverage the @arguments variable Using the @rest... variable to use mixins with a variable number of arguments Using mixins as functions Passing rulesets to mixins Using mixin guards (as an alternative for the if…else statements) Building loops leveraging mixin guards Applying guards to the CSS selectors Creating color contrasts with Less Changing the background color dynamically Aggregating values under a single property (For more resources related to this topic, see here.) Giving your rules importance with the !important statement The !important statement in CSS can be used to get some style rules always applied no matter where that rules appears in the CSS code. In Less, the !important statement can be applied with mixins and variable declarations too. Getting ready You can write the Less code for this recipe with your favorite editor. After that, you can use the command-line lessc compiler to compile the Less code. Finally, you can inspect the compiled CSS code to see where the !important statements appear. To see the real effect of the !important statements, you should compile the Less code client side, with the client-side compiler less.js and watch the effect in your web browser. How to do it… Create an important.less file that contains the code like the following snippet: .mixin() { color: red; font-size: 2em; } p { &.important {    .mixin() !important; } &.unimportant {    .mixin(); } } After compiling the preceding Less code with the command-line lessc compiler, you will find the following code output produced in the console: p.important { color: red !important; font-size: 2em !important; } p.unimportant { color: red; font-size: 2em; } You can, for instance, use the following snippet of the HTML code to see the effect of the !important statements in your browser: <p class="important"   style="color:green;font-size:4em;">important</p> <p class="unimportant"   style="color:green;font-size:4em;">unimportant</p> Your HTML document should also include the important.less and less.js files, as follows: <link rel="stylesheet/less" type="text/css"   href="important.less"> <script src="less.js" type="text/javascript"></script> Finally, the result will look like that shown in the following screenshot:  How it works… In Less, you can use the !important statement not only for properties, but also with mixins. When !important is set for a certain mixin, all properties of this mixin will be declared with the !important statement. You can easily see this effect when inspecting the properties of the p.important selector, both the color and size property got the !important statement after compiling the code. There's more… You should use the !important statements with care as the only way to overrule an !important statement is to use another !important statement. The !important statement overrules the normal CSS cascading, specificity rules, and even the inline styles. Any incorrect or unnecessary use of the !important statements in your Less (or CCS) code will make your code messy and difficult to maintain. In most cases where you try to overrule a style rule, you should give preference to selectors with a higher specificity and not use the !important statements at all. With Less V2, you can also use the !important statement when declaring your variables. A declaration with the !important statement can look like the following code: @main-color: darkblue !important; Using mixins with multiple parameters In this section, you will learn how to use mixins with more than one parameter. Getting ready For this recipe, you will have to create a Less file, for instance, mixins.less. You can compile this mixins.less file with the command-line lessc compiler. How to do it… Create the mixins.less file and write down the following Less code into it: .mixin(@color; @background: black;) { background-color: @background; color: @color; } div { .mixin(red; white;); } Compile the mixins.less file by running the command shown in the console, as follows: lessc mixins.less Inspect the CSS code output on the console, and you will find that it looks like that shown, as follows: div { background-color: #ffffff; color: #ff0000; } How it works… In Less, parameters are either semicolon-separated or comma-separated. Using a semicolon as a separator will be preferred because the usage of the comma will be ambiguous. The comma separator is not used only to separate parameters, but is also used to define a csv list, which can be an argument itself. The mixin in this recipe accepts two arguments. The first parameter sets the @color variable, while the second parameter sets the @background variable and has a default value that has been set to black. In the argument list, the default values are defined by writing a colon behind the variable's name, followed by the value. Parameters with a default value are optional when calling the mixins. So the .color mixin in this recipe can also be called with the following line of code: .mixin(red); Because the second argument has a default value set to black, the .mixin(red); call also matches the .mixin(@color; @background:black){} mixin, as described in the Building a switch leveraging argument matching recipe. Only variables set as parameter of a mixin are set inside the scope of the mixin. You can see this when compiling the following Less code: .mixin(@color:blue){ color2: @color; } @color: red; div { color1: @color; .mixin; } The preceding Less code compiles into the following CSS code: div { color1: #ff0000; color2: #0000ff; } As you can see in the preceding example, setting @color inside the mixin to its default value does not influence the value of @color assigned in the main scope. So lazy loading is applied on only variables inside the same scope; nevertheless, you will have to note that variables assigned in a mixin will leak into the caller. The leaking of variables can be used to use mixins as functions, as described in the Using mixins as functions recipe. There's more… Consider the mixin definition in the following Less code: .mixin(@font-family: "Helvetica Neue", Helvetica, Arial,   sans-serif;) { font-family: @font-family; } The semicolon added at the end of the list prevents the fonts after the "Helvetica Neue" font name in the csv list from being read as arguments for this mixin. If the argument list contains any semicolon, the Less compiler will use semicolons as a separator. In the CSS3 specification, among others, the border and background shorthand properties accepts csv. Also, note that the Less compiler allows you to use the named parameters when calling mixins. This can be seen in the following Less code that uses the @color variable as a named parameter: .mixin(@width:50px; @color: yellow) { width: @width; color: @color; } span { .mixin(@color: green); } The preceding Less code will compile into the following CSS code: span { width: 50px; color: #008000; } Note that in the preceding code, #008000 is the hexadecimal representation for the green color. When using the named parameters, their order does not matter. Using duplicate mixin names When your Less code contains one or more mixins with the same name, the Less compiler compiles them all into the CSS code. If the mixin has parameters (see the Building a switch leveraging argument matching recipe) the number of parameters will also match. Getting ready Use your favorite text editor to create and edit the Less files used in this recipe. How to do it… Create a file called mixins.less that contains the following Less code: .mixin(){ height:50px; } .mixin(@color) { color: @color; }   .mixin(@width) { color: green; width: @width; }   .mixin(@color; @width) { color: @color; width: @width; }   .selector-1 { .mixin(red); } .selector-2 { .mixin(red; 500px); } Compile the Less code from step 1 by running the following command in the console: lessc mixins.less After running the command from the previous step, you will find the following Less code output on the console: .selector-1 { color: #ff0000; color: green; width: #ff0000; } .selector-2 { color: #ff0000; width: 500px; } How it works… The .selector-1 selector contains the .mixin(red); call. The .mixin(red); call does not match the .mixin(){}; mixin as the number of arguments does not match. On the other hand, both .mixin(@color){}; and .mixin(@width){}; match the color. For this reason, these mixins will compile into the CSS code. The .mixin(red; 500px); call inside the .selector-2 selector will match only the .mixin(@color; @width){}; mixin, so all other mixins with the same .mixin name will be ignored by the compiler when building the .selector-2 selector. The compiled CSS code for the .selector-1 selector also contains the width: #ff0000; property value as the .mixin(@width){}; mixin matches the call too. Setting the width property to a color value makes no sense in CSS as the Less compiler does not check for this kind of errors. In this recipe, you can also rewrite the .mixin(@width){}; mixin, as follows: .mixin(@width) when (ispixel(@width)){};. There's more… Maybe you have noted that the .selector-1 selector contains two color properties. The Less compiler does not remove duplicate properties unless the value also is the same. The CSS code sometimes should contain duplicate properties in order to provide a fallback for older browsers. Building a switch leveraging argument matching The Less mixin will compile into the final CSS code only when the number of arguments of the caller and the mixins match. This feature of Less can be used to build switches. Switches enable you to change the behavior of a mixin conditionally. In this recipe, you will create a mixin, or better yet, three mixins with the same name. Getting ready Use the command-line lessc compiler to evaluate the effect of this mixin. The compiler will output the final CSS to the console. You can use your favorite text editor to edit the Less code. This recipe makes use of browser-vendor prefixes, such as the -ms-transform prefix. CSS3 introduced vendor-specific rules, which offer you the possibility to write some additional CSS, applicable for only one browser. These rules allow browsers to implement proprietary CSS properties that would otherwise have no working standard (and might never actually become the standard). To find out which prefixes should be used for a certain property, you can consult the Can I use database (available at http://caniuse.com/). How to do it… Create a switch.less Less file, and write down the following Less code into it: @browserversion: ie9; .mixin(ie9; @degrees){ transform:rotate(@degrees); -ms-transform:rotate(@degrees); -webkit-transform:rotate(@degrees); } .mixin(ie10; @degrees){ transform:rotate(@degrees); -webkit-transform:rotate(@degrees); } .mixin(@_; @degrees){ transform:rotate(@degrees); } div { .mixin(@browserversion; 70deg); } Compile the Less code from step 1 by running the following command in the console: lessc switch.less Inspect the compiled CSS code that has been output to the console, and you will find that it looks like the following code: div { -ms-transform: rotate(70deg); -webkit-transform: rotate(70deg); transform: rotate(70deg); } Finally, run the following command and you will find that the compiled CSS wll indeed differ from that of step 2: lessc --modify-var="browserversion=ie10" switch.less Now the compiled CSS code will look like the following code snippet: div { -webkit-transform: rotate(70deg); transform: rotate(70deg); } How it works… The switch in this recipe is the @browserversion variable that can easily be changed just before compiling your code. Instead of changing your code, you can also set the --modify-var option of the compiler. Depending on the value of the @browserversion variable, the mixins that match will be compiled, and the other mixins will be ignored by the compiler. The .mixin(ie10; @degrees){} mixin matches the .mixin(@browserversion; 70deg); call only when the value of the @browserversion variable is equal to ie10. Note that the first ie10 argument of the mixin will be used only for matching (argument = ie10) and does not assign any value. You will note that the .mixin(@_; @degrees){} mixin will match each call no matter what the value of the @browserversion variable is. The .mixin(ie9,70deg); call also compiles the .mixin(@_; @degrees){} mixin. Although this should result in the transform: rotate(70deg); property output twice, you will find only one. Since the property got exactly the same value twice, the compiler outputs the property only once. There's more… Not only switches, but also mixin guards, as described in the Using mixin guards (as an alternative for the if…else statements) recipe, can be used to set some properties conditionally. Current versions of Less also support JavaScript evaluating; JavaScript code put between back quotes will be evaluated by the compiler, as can be seen in the following Less code example: @string: "example in lower case"; p { &:after { content: "`@{string}.toUpperCase()`"; } } The preceding code will be compiled into CSS, as follows: p:after { content: "EXAMPLE IN LOWER CASE"; } When using client-side compiling, JavaScript evaluating can also be used to get some information from the browser environment, such as the screen width (screen.width), but as mentioned already, you should not use client-side compiling for production environments. Because you can't be sure that future versions of Less still support JavaScript evaluating, and alternative compilers not written in JavaScript cannot evaluate the JavaScript code, you should always try to write your Less code without JavaScript. Avoiding individual parameters to leverage the @arguments variable In the Less code, the @arguments variable has a special meaning inside mixins. The @arguments variable contains all arguments passed to the mixin. In this recipe, you will use the @arguments variable together with the the CSS url() function to set a background image for a selector. Getting ready You can inspect the compiled CSS code in this recipe after compiling the Less code with the command-line lessc compiler. Alternatively, you can inspect the results in your browser using the client-side less.js compiler. When inspecting the result in your browser, you will also need an example image that can be used as a background image. Use your favorite text editor to create and edit the Less files used in this recipe. How to do it… Create a background.less file that contains the following Less code: .background(@color; @image; @repeat: no-repeat; @position:   top right;) { background: @arguments; }   div { .background(#000; url("./images/bg.png")); width:300px; height:300px; } Finally, inspect the compiled CSS code, and you will find that it will look like the following code snippet: div { background: #000000 url("./images/bg.png") no-repeat top     right; width: 300px; height: 300px; } How it works… The four parameters of the .background() mixin are assigned as a space-separated list to the @arguments variable. After that, the @arguments variable can be used to set the background property. Also, other CSS properties accept space-separated lists, for example, the margin and padding properties. Note that the @arguments variable does not contain only the parameters that have been set explicit by the caller, but also the parameters set by their default value. You can easily see this when inspecting the compiled CSS code of this recipe. The .background(#000; url("./images/bg.png")); caller doesn't set the @repeat or @position argument, but you will find their values in the compiled CSS code. Using the @rest... variable to use mixins with a variable number of arguments As you can also see in the Using mixins with multiple parameters and Using duplicate mixin names recipes, only matching mixins are compiled into the final CSS code. In some situations, you don't know the number of parameters or want to use mixins for some style rules no matter the number of parameters. In these situations, you can use the special ... syntax or the @rest... variable to create mixins that match independent of the number of parameters. Getting ready You will have to create a file called rest.less, and this file can be compiled with the command-line lessc compiler. You can edit the Less code with your favorite editor. How to do it… Create a file called rest.less that contains the following Less code: .mixin(@a...) { .set(@a) when (iscolor(@a)) {    color: @a; } .set(@a) when (length(@a) = 2) {    margin: @a; } .set(@a); } p{ .mixin(red); } p { .mixin(2px;4px); } Compile the rest.less file from step 1 using the following command in the console: lessc rest.less Inspect the CSS code output to the console that will look like the following code: p { color: #ff0000; } p { margin: 2px 4px; } How it works… The special ... syntax (three dots) can be used as an argument for a mixin. Mixins with the ... syntax in their argument list match any number of arguments. When you put a variable name starting with an @ in front of the ... syntax, all parameters are assigned to that variable. You will find a list of examples of mixins that use the special ... syntax as follows: .mixin(@a; ...){}: This mixin matches 1-N arguments .mixin(...){}: This mixin matches 0-N arguments; note that mixin() without any argument matches only 0 arguments .mixin(@a: 1; @rest...){}: This mixin matches 0-N arguments; note that the first argument is assigned to the @a variable, and all other arguments are assigned as a space-separated list to @rest Because the @rest... variable contains a space-separated list, you can use the Less built-in list function. Using mixins as functions People who are used to functional programming expect a mixin to change or return a value. In this recipe, you will learn to use mixins as a function that returns a value. In this recipe, the value of the width property inside the div.small and div.big selectors will be set to the length of the longest side of a right-angled triangle based on the length of the two shortest sides of this triangle using the Pythagoras theorem. Getting ready The best and easiest way to inspect the results of this recipe will be compiling the Less code with the command-line lessc compiler. You can edit the Less code with your favorite editor. How to do it… Create a file called pythagoras.less that contains the following Less code: .longestSide(@a,@b) { @length: sqrt(pow(@a,2) + pow(@b,2)); } div { &.small {    .longestSide(3,4);    width: @length; } &.big {    .longestSide(6,7);    width: @length; } } Compile the pythagoras.less file from step 1 using the following command in the console: lessc pyhagoras.less Inspect the CSS code output on the console after compilation and you will see that it looks like the following code snippet: div.small { width: 5; } div.big { width: 9.21954446; } How it works… Variables set inside a mixin become available inside the scope of the caller. This specific behavior of the Less compiler was used in this recipe to set the @length variable and to make it available in the scope of the div.small and div.big selectors and the caller. As you can see, you can use the mixin in this recipe more than once. With every call, a new scope is created and both selectors get their own value of @length. Also, note that variables set inside the mixin do not overwrite variables with the same name that are set in the caller itself. Take, for instance, the following code: .mixin() { @variable: 1; } .selector { @variable: 2; .mixin; property: @variable; } The preceding code will compile into the CSS code, as follows: .selector { property: 2; } There's more… Note that variables won't leak from the mixins to the caller in the following two situations: Inside the scope of the caller, a variable with the same name already has been defined (lazy loading will be applied) The variable has been previously defined by another mixin call (lazy loading will not be applied) Passing rulesets to mixins Since Version 1.7, Less allows you to pass complete rulesets as an argument for mixins. Rulesets, including the Less code, can be assigned to variables and passed into mixins, which also allow you to wrap blocks of the CSS code defined inside mixins. In this recipe, you will learn how to do this. Getting ready For this recipe, you will have to create a Less file called keyframes.less, for instance. You can compile this mixins.less file with the command-line lessc compiler. Finally, inspect the Less code output to the console. How to do it… Create the keyframes.less file, and write down the following Less code into it: // Keyframes .keyframe(@name; @roules) { @-webkit-keyframes @name {    @roules(); } @-o-keyframes @name {    @roules(); } @keyframes @name {    @roules(); } } .keyframe(progress-bar-stripes; { from { background-position: 40px 0; } to   { background-position: 0 0; } }); Compile the keyframes.less file by running the following command shown in the console: lessc keyframes.less Inspect the CSS code output on the console and you will find that it looks like the following code: @-webkit-keyframes progress-bar-stripes { from {    background-position: 40px 0; } to {    background-position: 0 0; } } @-o-keyframes progress-bar-stripes { from {    background-position: 40px 0; } to {    background-position: 0 0; } } @keyframes progress-bar-stripes { from {    background-position: 40px 0; } to {    background-position: 0 0; } } How it works… Rulesets wrapped between curly brackets are passed as an argument to the mixin. A mixin's arguments are assigned to a (local) variable. When you assign the ruleset to the @ruleset variable, you are enabled to call @ruleset(); to "mixin" the ruleset. Note that the passed rulesets can contain the Less code, such as built-in functions too. You can see this by compiling the following Less code: .mixin(@color; @rules) { @othercolor: green; @media (print) {    @rules(); } }   p { .mixin(red; {color: lighten(@othercolor,20%);     background-color:darken(@color,20%);}) } The preceding Less code will compile into the following CSS code: @media (print) { p {    color: #00e600;    background-color: #990000; } } A group of CSS properties, nested rulesets, or media declarations stored in a variable is called a detached ruleset. Less offers support for the detached rulesets since Version 1.7. There's more… As you could see in the last example in the previous section, rulesets passed as an argument can be wrapped in the @media declarations too. This enables you to create mixins that, for instance, wrap any passed ruleset into a @media declaration or class. Consider the example Less code shown here: .smallscreens-and-olderbrowsers(@rules) { .lt-ie9 & {    @rules(); } @media (min-width:768px) {    @rules(); } } nav { float: left; width: 20%; .smallscreens-and-olderbrowsers({    float: none;    width:100%; }); } The preceding Less code will compile into the CSS code, as follows: nav { float: left; width: 20%; } .lt-ie9 nav { float: none; width: 100%; } @media (min-width: 768px) { nav {    float: none;    width: 100%; } } The style rules wrapped in the .lt-ie9 class can, for instance, be used with Paul Irish's <html> conditional classes technique or Modernizr. Now you can call the .smallscreens-and-olderbrowsers(){} mixin anywhere in your code and pass any ruleset to it. All passed rulesets get wrapped in the .lt-ie9 class or the @media (min-width: 768px) declaration now. When your requirements change, you possibly have to change only these wrappers once. Using mixin guards (as an alternative for the if…else statements) Most programmers are used to and familiar with the if…else statements in their code. Less does not have these if…else statements. Less tries to follow the declarative nature of CSS when possible and for that reason uses guards for matching expressions. In Less, conditional execution has been implemented with guarded mixins. Guarded mixins use the same logical and comparison operators as the @media feature in CSS does. Getting ready You can compile the Less code in this recipe with the command-line lessc compiler. Also, check the compiler options; you can find them by running the lessc command in the console without any argument. In this recipe, you will have to use the –modify-var option. How to do it… Create a Less file named guards.less, which contains the following Less code: @color: white; .mixin(@color) when (luma(@color) >= 50%) { color: black; } .mixin(@color) when (luma(@color) < 50%) { color: white; }   p { .mixin(@color); } Compile the Less code in the guards.less using the command-line lessc compiler with the following command entered in the console: lessc guards.less Inspect the output written on the console, which will look like the following code: p { color: black; } Compile the Less code with different values set for the @color variable and see how to output change. You can use the command as follows: lessc --modify-var="color=green" guards.less The preceding command will produce the following CSS code: p {   color: white;   } Now, refer to the following command: lessc --modify-var="color=lightgreen" guards.less With the color set to light green, it will again produce the following CSS code: p {   color: black;   }   How it works… The use of guards to build an if…else construct can easily be compared with the switch expression, which can be found in the programming languages, such as PHP, C#, and pretty much any other object-oriented programming language. Guards are written with the when keyword followed by one or more conditions. When the condition(s) evaluates true, the code will be mixed in. Also note that the arguments should match, as described in the Building a switch leveraging argument matching recipe, before the mixin gets compiled. The syntax and logic of guards is the same as that of the CSS @media feature. A condition can contain the following comparison operators: >, >=, =, =<, and < Additionally, the keyword true is the only value that evaluates as true. Two or more conditionals can be combined with the and keyword, which is equivalent to the logical and operator or, on the other hand, with a comma as the logical or operator. The following code will show you an example of the combined conditionals: .mixin(@a; @color) when (@a<10) and (luma(@color) >= 50%) { } The following code contains the not keyword that can be used to negate conditions: .mixin(@a; @color) when not (luma(@color) >= 50%) { } There's more… Inside the guard conditions, (global) variables can also be compared. The following Less code example shows you how to use variables inside guards: @a: 10; .mixin() when (@a >= 10) {} The preceding code will also enable you to compile the different CSS versions with the same code base when using the modify-var option of the compiler. The effect of the guarded mixin described in the preceding code will be very similar with the mixins built in the Building a switch leveraging argument matching recipe. Note that in the preceding example, variables in the mixin's scope overwrite variables from the global scope, as can be seen when compiling the following code: @a: 10; .mixin(@a) when (@a < 10) {property: @a;} selector { .mixin(5); } The preceding Less code will compile into the following CSS code: selector { property: 5; } When you compare guarded mixins with the if…else constructs or switch expressions in other programming languages, you will also need a manner to create a conditional for the default situations. The built-in Less default() function can be used to create such a default conditional that is functionally equal to the else statement in the if…else constructs or the default statement in the switch expressions. The default() function returns true when no other mixins match (matching also takes the guards into account) and can be evaluated as the guard condition. Building loops leveraging mixin guards Mixin guards, as described besides others in the Using mixin guards (as an alternative for the if…else statements) recipe, can also be used to dynamically build a set of CSS classes. In this recipe, you will learn how to do this. Getting ready You can use your favorite editor to create the Less code in this recipe. How to do it… Create a shadesofblue.less Less file, and write down the following Less code into it: .shadesofblue(@number; @blue:100%) when (@number > 0) {   .shadesofblue(@number - 1, @blue - 10%);   @classname: e(%(".color-%a",@number)); @{classname} {    background-color: rgb(0, 0, @blue);    height:30px; } } .shadesofblue(10); You can, for instance, use the following snippet of the HTML code to see the effect of the compiled Less code from the preceding step: <div class="color-1"></div> <div class="color-2"></div> <div class="color-3"></div> <div class="color-4"></div> <div class="color-5"></div> <div class="color-6"></div> <div class="color-7"></div> <div class="color-8"></div> <div class="color-9"></div> <div class="color-10"></div> Your HTML document should also include the shadesofblue.less and less.js files, as follows: <link rel="stylesheet/less" type="text/css"   href="shadesofblue.less"> <script src="less.js" type="text/javascript"></script> Finally, the result will look like that shown in this screenshot: How it works… The CSS classes in this recipe are built with recursion. The recursion here has been done by the .shadesofblue(){} mixin calling itself with different parameters. The loop starts with the .shadesofblue(10); call. When the compiler reaches the .shadesofblue(@number - 1, @blue – 10%); line of code, it stops the current code and starts compiling the .shadesofblue(){} mixin again with @number decreased by one and @blue decreased by 10 percent. The process will be repeated till @number < 1. Finally, when the @number variable becomes equal to 0, the compiler tries to call the .shadesofblue(0,0); mixin, which does not match the when (@number > 0) guard. When no matching mixin is found, the compiler stops, compiles the rest of the code, and writes the first class into the CSS code, as follows: .color-1 { background-color: #00001a; height: 30px; } Then, the compiler starts again where it stopped before, at the .shadesofblue(2,20); call, and writes the next class into the CSS code, as follows: .color-2 { background-color: #000033; height: 30px; } The preceding code will be repeated until the tenth class. There's more… When inspecting the compiled CSS code, you will find that the height property has been repeated ten times, too. This kind of code repeating can be prevented using the :extend Less pseudo class. The following code will show you an example of the usage of the :extend Less pseudo class: .baseheight { height: 30px; } .mixin(@i: 2) when(@i > 0) { .mixin(@i - 1); .class@{i} {    width: 10*@i;    &:extend(.baseheight); } } .mixin(); Alternatively, in this situation, you can create a more generic selector, which sets the height property as follows: div[class^="color"-] { height: 30px; } Recursive loops are also useful when iterating over a list of values. Max Mikhailov, one of the members of the Less core team, wrote a wrapper mixin for recursive Less loops, which can be found at https://github.com/seven-phases-max. This wrapper contains the .for and .-each mixins that can be used to build loops. The following code will show you how to write a nested loop: @import "for"; #nested-loops { .for(3, 1); .-each(@i) {    .for(0, 2); .-each(@j) {      x: (10 * @i + @j);    } } } The preceding Less code will produce the following CSS code: #nested-loops { x: 30; x: 31; x: 32; x: 20; x: 21; x: 22; x: 10; x: 11; x: 12; } Finally, you can use a list of mixins as your data provider in some situations. The following Less code gives an example about using mixins to avoid recursion: .data() { .-("dark"; black); .-("light"; white); .-("accent"; pink); }   div { .data(); .-(@class-name; @color){    @class: e(@class-name);    &.@{class} {      color: @color;    } } } The preceding Less code will compile into the CSS code, as follows: div.dark { color: black; } div.light { color: white; }   div.accent { color: pink; } Applying guards to the CSS selectors Since Version 1.5 of Less, guards can be applied not only on mixins, but also on the CSS selectors. This recipe will show you how to apply guards on the CSS selectors directly to create conditional rulesets for these selectors. Getting ready The easiest way to inspect the effect of the guarded selector in this recipe will be using the command-line lessc compiler. How to do it… Create a Less file named darkbutton.less that contains the following code: @dark: true; button when (@dark){ background-color: black; color: white; } Compile the darkbutton.less file with the command-line lessc compiler by entering the following command into the console: lessc darkbutton.less Inspect the CSS code output on the console, which will look like the following code: button { background-color: black; color: white; } Now try the following command and you will find that the button selector is not compiled into the CSS code: lessc --modify-var="dark=false" darkbutton.less How it works… The guarded CSS selectors are ignored by the compiler and so not compiled into the CSS code when the guard evaluates false. Guards for the CSS selectors and mixins leverage the same comparison and logical operators. You can read in more detail how to create guards with these operators in Using mixin guards (as an alternative for the if…else statements) recipe. There's more… Note that the true keyword will be the only value that evaluates true. So the following command, which sets @dark equal to 1, will not generate the button selector as the guard evaluates false: lessc --modify-var="dark=1" darkbutton.less The following Less code will give you another example of applying a guard on a selector: @width: 700px; div when (@width >= 600px ){ border: 1px solid black; } The preceding code will output the following CSS code: div {   border: 1px solid black;   } On the other hand, nothing will be output when setting @width to a value smaller than 600 pixels. You can also rewrite the preceding code with the & feature referencing the selector, as follows: @width: 700px; div { & when (@width >= 600px ){    border: 1px solid black; } } Although the CSS code produced of the latest code does not differ from the first, it will enable you to add more properties without the need to repeat the selector. You can also add the code in a mixin, as follows: .conditional-border(@width: 700px) {    & when (@width >= 600px ){    border: 1px solid black; } width: @width; } Creating color contrasts with Less Color contrasts play an important role in the first impression of your website or web application. Color contrasts are also important for web accessibility. Using high contrasts between background and text will help the visually disabled, color blind, and even people with dyslexia to read your content more easily. The contrast() function returns a light (white by default) or dark (black by default) color depending on the input color. The contrast function can help you to write a dynamical Less code that always outputs the CSS styles that create enough contrast between the background and text colors. Setting your text color to white or black depending on the background color enables you to meet the highest accessibility guidelines for every color. A sample can be found at http://www.msfw.com/accessibility/tools/contrastratiocalculator.aspx, which shows you that either black or white always gives enough color contrast. When you use Less to create a set of buttons, for instance, you don't want some buttons with white text while others have black text. In this recipe, you solve this situation by adding a stroke to the button text (text shadow) when the contrast ratio between the button background and button text color is too low to meet your requirements. Getting ready You can inspect the results of this recipe in your browser using the client-side less.js compiler. You will have to create some HTML and Less code, and you can use your favorite editor to do this. You will have to create the following file structure: How to do it… Create a Less file named contraststrokes.less, and write down the following Less code into it: @safe: green; @danger: red; @warning: orange; @buttonTextColor: white; @ContrastRatio: 7; //AAA, small texts   .setcontrast(@backgroundcolor) when (luma(@backgroundcolor)   =< luma(@buttonTextColor)) and     (((luma(@buttonTextColor)+5)/     (luma(@backgroundcolor)+5)) < @ContrastRatio) { color:@buttonTextColor; text-shadow: 0 0 2px black; } .setcontrast(@backgroundcolor) when (luma(@backgroundcolor)   =< luma(@buttonTextColor)) and     (((luma(@buttonTextColor)+5)/     (luma(@backgroundcolor)+5)) >= @ContrastRatio) { color:@buttonTextColor; }   .setcontrast(@backgroundcolor) when (luma(@backgroundcolor)   >= luma(@buttonTextColor)) and     (((luma(@backgroundcolor)+5)/     (luma(@buttonTextColor)+5)) < @ContrastRatio) { color:@buttonTextColor; text-shadow: 0 0 2px white; } .setcontrast(@backgroundcolor) when (luma(@backgroundcolor)   >= luma(@buttonTextColor)) and     (((luma(@backgroundcolor)+5)/     (luma(@buttonTextColor)+5)) >= @ContrastRatio) { color:@buttonTextColor; }   button { padding:10px; border-radius:10px; color: @buttonTextColor; width:200px; }   .safe { .setcontrast(@safe); background-color: @safe; }   .danger { .setcontrast(@danger); background-color: @danger; }   .warning { .setcontrast(@warning); background-color: @warning; } Create an HTML file, and save this file as index.html. Write down the following HTML code into this index.html file: <!DOCTYPE html> <html> <head>    <meta charset="utf-8">    <title>High contrast buttons</title>    <link rel="stylesheet/less" type="text/css"       href="contraststrokes.less">    <script src="less.min.js"       type="text/javascript"></script> </head> <body>    <button style="background-color:green;">safe</button>    <button class="safe">safe</button><br>    <button style="background-color:red;">danger</button>    <button class="danger">danger</button><br>    <button style="background-color:orange;">     warning</button>    <button class="warning">warning</button> </body> </html> Now load the index.html file from step 2 in your browser. When all has gone well, you will see something like what's shown in the following screenshot: On the left-hand side of the preceding screenshot, you will see the original colored buttons, and on the right-hand side, you will find the high-contrast buttons. How it works… The main purpose of this recipe is to show you how to write dynamical code based on the color contrast ratio. Web Content Accessibility Guidelines (WCAG) 2.0 covers a wide range of recommendations to make web content more accessible. They have defined the following three conformance levels: Conformance Level A: In this level, all Level A success criteria are satisfied Conformance Level AA: In this level, all Level A and AA success criteria are satisfied Conformance Level AAA: In this level, all Level A, AA, and AAA success criteria are satisfied If you focus only on the color contrast aspect, you will find the following paragraphs in the WCAG 2.0 guidelines. 1.4.1 Use of Color: Color is not used as the only visual means of conveying information, indicating an action, prompting a response, or distinguishing a visual element. (Level A) 1.4.3 Contrast (Minimum): The visual presentation of text and images of text has a contrast ratio of at least 4.5:1 (Level AA) 1.4.6 Contrast (Enhanced): The visual presentation of text and images of text has a contrast ratio of at least 7:1 (Level AAA) The contrast ratio can be calculated with a formula that can be found at http://www.w3.org/TR/WCAG20/#contrast-ratiodef: (L1 + 0.05) / (L2 + 0.05) In the preceding formula, L1 is the relative luminance of the lighter of the colors, and L2 is the relative luminance of the darker of the colors. In Less, the relative luminance of a color can be found with the built-in luma() function. In the Less code of this recipe are the four guarded .setcontrast(){} mixins. The guard conditions, such as (luma(@backgroundcolor) =< luma(@buttonTextColor)) are used to find which of the @backgroundcolor and @buttonTextColor colors is the lighter one. Then the (((luma({the lighter color})+5)/(luma({the darker color})+5)) < @ContrastRatio) condition can, according to the preceding formula, be used to determine whether the contrast ratio between these colors meets the requirement (@ContrastRatio) or not. When the value of the calculated contrast ratio is lower than the value set by the @ContrastRatio, the text-shadow: 0 0 2px {color}; ruleset will be mixed in, where {color} will be white or black depending on the relative luminance of the color set by the @buttonTextColor variable. There's more… In this recipe, you added a stroke to the web text to improve the accessibility. First, you will have to bear in mind that improving the accessibility by adding a stroke to your text is not a proven method. Also, automatic testing of the accessibility (by calculating the color contrast ratios) cannot be done. Other options to solve this issue are to increase the font size or change the background color itself. You can read how to change the background color dynamically based on color contrast ratios in the Changing the background color dynamically recipe. When you read the exceptions of the 1.4.6 Contrast (Enhanced) paragraph of the WCAG 2.0 guidelines, you will find that large-scale text requires a color contrast ratio of 4.5 instead of 7.0 to meet the requirements of the AAA Level. Large-scaled text is defined as at least 18 point or 14 point bold or font size that would yield the equivalent size for Chinese, Japanese, and Korean (CJK) fonts. To try this, you could replace the text-shadow properties in the Less code of step 1 of this recipe with the font-size, 14pt, and font-weight, bold; declarations. After this, you can inspect the results in your browser again. Depending on, among others, the values you have chosen for the @buttonTextColor and @ContrastRatio variables, you will find something like the following screenshot: On the left-hand side of the preceding screenshot, you will see the original colored buttons, and on the right-hand side, you will find the high-contrast buttons. Note that when you set the @ContrastRatio variable to 7.0, the code does not check whether the larger font indeed meets the 4.5 contrast ratio requirement. Changing the background color dynamically When you define some basic colors to generate, for instance, a set of button elements, you can use the built-in contrast() function to set the font color. The built-in contrast() function provides the highest possible contrast, but does not guarantee that the contrast ratio is also high enough to meet your accessibility requirements. In this recipe, you will learn how to change your basic color automatically to meet the required contrast ratio. Getting ready You can inspect the results of this recipe in your browser using the client-side less.js compiler. Use your favorite editor to create the HTML and Less code in this recipe. You will have to create the following file structure: How to do it… Create a Less file named backgroundcolors.less, and write down the following Less code into it: @safe: green; @danger: red; @warning: orange; @ContrastRatio: 7.0; //AAA @precision: 1%; @buttonTextColor: black; @threshold: 43;   .setcontrastcolor(@startcolor) when (luma(@buttonTextColor)   < @threshold) { .contrastcolor(@startcolor) when (luma(@startcolor) < 100     ) and (((luma(@startcolor)+5)/     (luma(@buttonTextColor)+5)) < @ContrastRatio) {    .contrastcolor(lighten(@startcolor,@precision)); } .contrastcolor(@startcolor) when (@startcolor =     color("white")),(((luma(@startcolor)+5)/     (luma(@buttonTextColor)+5)) >= @ContrastRatio) {    @contrastcolor: @startcolor; } .contrastcolor(@startcolor); }   .setcontrastcolor(@startcolor) when (default()) { .contrastcolor(@startcolor) when (luma(@startcolor) < 100     ) and (((luma(@buttonTextColor)+5)/     (luma(@startcolor)+5)) < @ContrastRatio) {    .contrastcolor(darken(@startcolor,@precision)); } .contrastcolor(@startcolor) when (luma(@startcolor) = 100     ),(((luma(@buttonTextColor)+5)/(luma(@startcolor)+5))       >= @ContrastRatio) {    @contrastcolor: @startcolor; } .contrastcolor(@startcolor); }   button { padding:10px; border-radius:10px; color:@buttonTextColor; width:200px; }   .safe { .setcontrastcolor(@safe); background-color: @contrastcolor; }   .danger { .setcontrastcolor(@danger); background-color: @contrastcolor; }   .warning { .setcontrastcolor(@warning); background-color: @contrastcolor; } Create an HTML file and save this file as index.html. Write down the following HTML code into this index.html file: <!DOCTYPE html> <html> <head>    <meta charset="utf-8">    <title>High contrast buttons</title>      <link rel="stylesheet/less" type="text/css"       href="backgroundcolors.less">    <script src="less.min.js"       type="text/javascript"></script> </head> <body>    <button style="background-color:green;">safe</button>    <button class="safe">safe</button><br>    <button style="background-color:red;">danger</button>    <button class="danger">danger</button><br>    <button style="background-color:orange;">warning     </button>    <button class="warning">warning</button> </body> </html> Now load the index.html file from step 2 in your browser. When all has gone well, you will see something like the following screenshot: On the left-hand side of the preceding figure, you will see the original colored buttons, and on the right-hand side, you will find the high contrast buttons. How it works… The guarded .setcontrastcolor(){} mixins are used to determine the color set depending upon whether the @buttonTextColor variable is a dark color or not. When the color set by @buttonTextColor is a dark color, with a relative luminance below the threshold value set by the @threshold variable, the background colors should be made lighter. For light colors, the background colors should be made darker. Inside each .setcontrastcolor(){} mixin, a second set of mixins has been defined. These guarded .contrastcolor(){} mixins construct a recursive loop, as described in the Building loops leveraging mixin guards recipe. In each step of the recursion, the guards test whether the contrast ratio that is set by the @ContrastRatio variable has been reached or not. When the contrast ratio does not meet the requirements, the @startcolor variable will darken or lighten by the number of percent set by the @precision variable with the built-in darken() and lighten() functions. When the required contrast ratio has been reached or the color defining the @startcolor variable has become white or black, the modified color value of @startcolor will be assigned to the @contrastcolor variable. The guarded .contrastcolor(){} mixins are used as functions, as described in the Using mixins as functions recipe to assign the @contrastcolor variable that will be used to set the background-color property of the button selectors. There's more… A small value of the @precision variable will increase the number of recursions (possible) needed to find the required colors as there will be more and smaller steps needed. With the number of recursions also, the compilation time will increase. When you choose a bigger value for @precision, the contrast color found might differ from the start color more than needed to meet the contrast ratio requirement. When you choose, for instance, a dark button text color, which is not black, all or some base background colors will be set to white. The chances of finding the highest contrast for white increase for high values of the @ContrastRatio variable. The recursions will stop when white (or black) has been reached as you cannot make the white color lighter. When the recursion stops on reaching white or black, the colors set by the mixins in this recipe don't meet the required color contrast ratios. Aggregating values under a single property The merge feature of Less enables you to merge property values into a list under a single property. Each list can be either space-separated or comma-separated. The merge feature can be useful to define a property that accepts a list as a value. For instance, the background accepts a comma-separated list of backgrounds. Getting ready For this recipe, you will need a text editor and a Less compiler. How to do it… Create a file called defaultfonts.less that contains the following Less code: .default-fonts() { font-family+: Helvetica, Arial, sans-serif; } p { font-family+: "Helvetica Neue"; .default-fonts(); } Compile the defaultfonts.less file from step 1 using the following command in the console: lessc defaultfonts.less Inspect the CSS code output on the console after compilation and you will see that it looks like the following code: p { font-family: "Helvetica Neue", Helvetica, Arial, sans-   serif; } How it works… When the compiler finds the plus sign (+) before the assignment sign (:), it will merge the values into a CSV list and will not create a new property into the CSS code. There's more… Since Version 1.7 of Less, you can also merge the property's values separated by a space instead of a comma. For space-separated values, you should use the +_ sign instead of a + sign, as can be seen in the following code: .text-overflow(@text-overflow: ellipsis) { text-overflow+_ : @text-overflow; } p, .text-overflow { .text-overflow(); text-overflow+_ : ellipsis; } The preceding Less code will compile into the CSS code, as follows: p, .text-overflow { text-overlow: ellipsis ellipsis; } Note that the text-overflow property doesn't force an overflow to occur; you will have to explicitly set, for instance, the overflow property to hidden for the element. Summary This article walks you through the process of parameterized mixins and shows you how to use guards. A guard can be used with as if-else statements and make it possible to construct interactive loops in Less. Resources for Article: Further resources on this subject: Web Application Testing [article] LESS CSS Preprocessor [article] Bootstrap 3 and other applications [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.

This article written by Belén Cruz Zapata, the author of the book Android Studio Essentials, teaches us the uses of the AVD Manager tool. It introduces us to the Google Play services. (For more resources related to this topic, see here.) The Android Virtual Device Manager (AVD Manager) is an Android tool accessible from Android Studio to manage the Android virtual devices that will be executed in the Android emulator. To open the AVD Manager from Android Studio, navigate to the Tools | Android | AVD Manager menu option. You can also click on the shortcut from the toolbar. The AVD Manager displays the list of the existing virtual devices. Since we have not created any virtual device, initially the list will be empty. To create our first virtual device, click on the Create Virtual Device button to open the configuration dialog. The first step is to select the hardware configuration of the virtual device. The hardware definitions are listed on the left side of the window. Select one of them, like the Nexus 5, to examine its details on the right side as shown in the following screenshot. Hardware definitions can be classified into one of these categories: Phone, Tablet, Wear or TV. We can also configure our own hardware device definitions from the AVD Manager. We can create a new definition using the New Hardware Profile button. The Clone Device button creates a duplicate of an existing device. Click on the New Hardware Profile button to examine the existing configuration parameters. The most important parameters that define a device are: Device Name: Name of the device. Screensize: Screen size in inches. This value determines the size category of the device. Type a value of 4.0 and notice how the Size value (on the right side) is normal. Now type a value of 7.0 and the Size field changes its value to large. This parameter along with the screen resolution also determines the density category. Resolution: Screen resolution in pixels. This value determines the density category of the device. Having a screen size of 4.0 inches, type a value of 768 x 1280 and notice how the density value is 400 dpi. Change the screen size to 6.0 inches and the density value changes to hdpi. Now change the resolution to 480 x 800 and the density value is mdpi. RAM: RAM memory size of the device. Input: Indicate if the home, back, or menu buttons of the device are available via software or hardware. Supported device states: Check the allowed states. Cameras: Select if the device has a front camera or a back camera. Sensors: Sensors available in the device: accelerometer, gyroscope, GPS, and proximity sensor. Default Skin: Select additional hardware controls. Create a new device with a screen size of 4.7 inches, a resolution of 800 x 1280, a RAM value of 500 MiB, software buttons, and both portrait and landscape states enabled. Name it as My Device. Click on the Finish button. The hardware definition has been added to the list of configurations. Click on the Next button to continue the creation of a new virtual device. The next step is to select the virtual device system image and the target Android platform. Each platform has its architecture, so the system images that are installed on your system will be listed along with the rest of the images that can be downloaded (Show downloadable system images box checked). Download and select one of the images of the Lollipop release and click on the Next button. Finally, the last step is to verify the configuration of the virtual device. Enter the name of the Android Virtual Device in the AVD Name field. Give the virtual device a meaningful name to recognize it easily, such as AVD_nexus5_api21. Click on the Show Advanced Settings button. The settings that we can configure for the virtual device are the following: Emulation Options: The Store a snapshot for faster startup option saves the state of the emulator in order to load faster the next time. The Use Host GPU tries to accelerate the GPU hardware to run the emulator faster. Custom skin definition: Select if additional hardware controls are displayed in the emulator. Memory and Storage: Select the memory parameters of the virtual device. Let the default values, unless a warning message is shown; in this case, follow the instructions of the message. For example, select 1536M for the RAM memory and 64 for the VM Heap. The Internal Storage can also be configured. Select for example: 200 MiB. Select the size of the SD Card or select a file to behave as the SD card. Device: Select one of the available device configurations. These configurations are the ones we tested in the layout editor preview. Select the Nexus 5 device to load its parameters in the dialog. Target: Select the device Android platform. We have to create one virtual device with the minimum platform supported by our application and another virtual device with the target platform of our application. For this first virtual device, select the target platform, Android 4.4.2 - API Level 19. CPU/ABI: Select the device architecture. The value of this field is set when we select the target platform. Each platform has its architecture, so if we do not have it installed, the following message will be shown; No system images installed for this target. To solve this, open the SDK Manager and search for one of the architectures of the target platform, ARM EABI v7a System Image or Intel x86 Atom System Image. Keyboard: Select if a hardware keyboard is displayed in the emulator. Check it. Skin: Select if additional hardware controls are displayed in the emulator. You can select the Skin with dynamic hardware controls option. Front Camera: Select if the emulator has a front camera or a back camera. The camera can be emulated or can be real by the use of a webcam from the computer. Select None for both cameras. Keyboard: Select if a hardware keyboard is displayed in the emulator. Check it. Network: Select the speed of the simulated network and select the delay in processing data across the network. The new virtual device is now listed in the AVD Manager. Select the recently created virtual device to enable the remaining actions: Start: Run the virtual device. Edit: Edit the virtual device configuration. Duplicate: Creates a new device configuration displaying the last step of the creation process. You can change its configuration parameters and then verify the new device. Wipe Data: Removes the user files from the virtual device. Show on Disk: Opens the virtual device directory on your system. View Details: Open a dialog detailing the virtual device characteristics. Delete: Delete the virtual device. Click on the Start button. The emulator will be opened as shown in the following screenshot. Wait until it is completely loaded, and then you will be able to try it. In Android Studio, open the main layout with the graphical editor and click on the list of the devices. As the following screenshot shows, our custom device definition appears and we can select it to preview the layout: Navigation Editor The Navigation Editor is a tool to create and structure the layouts of the application using a graphical viewer. To open this tool navigate to the Tools | Android | Navigation Editor menu. The tool opens a file in XML format named main.nvg.xml. This file is stored in your project at /.navigation/app/raw/. Since there is only one layout and one activity in our project, the navigation editor only shows this main layout. If you select the layout, detailed information about it is displayed on the right panel of the editor. If you double-click on the layout, the XML layout file will be opened in a new tab. We can create a new activity by right-mouse clicking on the editor and selecting the New Activity option. We can also add transitions from the controls of a layout by shift clicking on a control and then dragging to the target activity. Open the main layout and create a new button with the label Open Activity: <Button        android_id="@+id/button_open"        android_layout_width="wrap_content"        android_layout_height="wrap_content"        android_layout_below="@+id/button_accept"        android_layout_centerHorizontal="true"        android_text="Open Activity" /> Open the Navigation Editor and add a second activity. Now the navigation editor displays both activities as the next screenshot shows. Now we can add the navigation between them. Shift-drag from the new button of the main activity to the second activity. A blue line and a pink circle have been added to represent the new navigation. Select the navigation relationship to see its details on the right panel as shown in the following screenshot. The right panel shows the source the activity, the destination activity and the gesture that triggers the navigation. Now open our main activity class and notice the new code that has been added to implement the recently created navigation. The onCreate method now contains the following code: findViewById(R.id.button_open).setOnClickListener( new View.OnClickListener() { @Override public void onClick(View v) { MainActivity.this.startActivity( new Intent(MainActivity.this, Activity2.class)); } }); This code sets the onClick method of the new button, from where the second activity is launched. Summary This article thought us about the Navigation Editor tool. It also showed how to integrate the Google Play services with a project in Android Studio. In this article, we got acquainted to the AVD Manager tool. Resources for Article: Further resources on this subject: Android Native Application API [article] Creating User Interfaces [article] Android 3.0 Application Development: Multimedia Management [article]

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 Aloysius Lim and William Tjhi, authors of the book R High Performance Programming, we will learn how to write and execute a parallel R code, where different parts of the code run simultaneously. So far, we have learned various ways to optimize the performance of R programs running serially, that is in a single process. This does not take full advantage of the computing power of modern CPUs with multiple cores. Parallel computing allows us to tap into all the computational resources available and to speed up the execution of R programs by many times. We will examine the different types of parallelism and how to implement them in R, and we will take a closer look at a few performance considerations when designing the parallel architecture of R programs. (For more resources related to this topic, see here.) Data parallelism versus task parallelism Many modern software applications are designed to run computations in parallel in order to take advantage of the multiple CPU cores available on almost any computer today. Many R programs can similarly be written in order to run in parallel. However, the extent of possible parallelism depends on the computing task involved. On one side of the scale are embarrassingly parallel tasks, where there are no dependencies between the parallel subtasks; such tasks can be made to run in parallel very easily. An example of this is, building an ensemble of decision trees in a random forest algorithm—randomized decision trees can be built independently from one another and in parallel across tens or hundreds of CPUs, and can be combined to form the random forest. On the other end of the scale are tasks that cannot be parallelized, as each step of the task depends on the results of the previous step. One such example is a depth-first search of a tree, where the subtree to search at each step depends on the path taken in previous steps. Most algorithms fall somewhere in between with some steps that must run serially and some that can run in parallel. With this in mind, careful thought must be given when designing a parallel code that works correctly and efficiently. Often an R program has some parts that have to be run serially and other parts that can run in parallel. Before making the effort to parallelize any of the R code, it is useful to have an estimate of the potential performance gains that can be achieved. Amdahl's law provides a way to estimate the best attainable performance gain when you convert a code from serial to parallel execution. It divides a computing task into its serial and potentially-parallel parts and states that the time needed to execute the task in parallel will be no less than this formula: T(n) = T(1)(P + (1-P)/n), where: T(n) is the time taken to execute the task using n parallel processes P is the proportion of the whole task that is strictly serial The theoretical best possible speed up of the parallel algorithm is thus: S(n) = T(1) / T(n) = 1 / (P + (1-P)/n) For example, given a task that takes 10 seconds to execute on one processor, where half of the task can be run in parallel, then the best possible time to run it on four processors is T(4) = 10(0.5 + (1-0.5)/4) = 6.25 seconds. The theoretical best possible speed up of the parallel algorithm with four processors is 1 / (0.5 + (1-0.5)/4) = 1.6x . The following figure shows you how the theoretical best possible execution time decreases as more CPU cores are added. Notice that the execution time reaches a limit that is just above five seconds. This corresponds to the half of the task that must be run serially, where parallelism does not help. Best possible execution time versus number of CPU cores In general, Amdahl's law means that the fastest execution time for any parallelized algorithm is limited by the time needed for the serial portions of the algorithm. Bear in mind that Amdahl's law provides only a theoretical estimate. It does not account for the overheads of parallel computing (such as starting and coordinating tasks) and assumes that the parallel portions of the algorithm are infinitely scalable. In practice, these factors might significantly limit the performance gains of parallelism, so use Amdahl's law only to get a rough estimate of the maximum speedup possible. There are two main classes of parallelism: data parallelism and task parallelism. Understanding these concepts helps to determine what types of tasks can be modified to run in parallel. In data parallelism, a dataset is divided into multiple partitions. Different partitions are distributed to multiple processors, and the same task is executed on each partition of data. Take for example, the task of finding the maximum value in a vector dataset, say one that has one billion numeric data points. A serial algorithm to do this would look like the following code, which iterates over every element of the data in sequence to search for the largest value. (This code is intentionally verbose to illustrate how the algorithm works; in practice, the max() function in R, though also serial in nature, is much faster.) serialmax <- function(data) {max = -Inffor (i in data) {if (i > max)max = i}return max} One way to parallelize this algorithm is to split the data into partitions. If we have a computer with eight CPU cores, we can split the data into eight partitions of 125 million numbers each. Here is the pseudocode for how to perform the same task in parallel: # Run this in parallel across 8 CPU corespart.results <- run.in.parallel(serialmax(data.part))# Compute global maxglobal.max <- serialmax(part.results) This pseudocode runs eight instances of serialmax()in parallel—one for each data partition—to find the local maximum value in each partition. Once all the partitions have been processed, the algorithm finds the global maximum value by finding the largest value among the local maxima. This parallel algorithm works because the global maximum of a dataset must be the largest of the local maxima from all the partitions. The following figure depicts data parallelism pictorially. The key behind data parallel algorithms is that each partition of data can be processed independently of the other partitions, and the results from all the partitions can be combined to compute the final results. This is similar to the mechanism of the MapReduce framework from Hadoop. Data parallelism allows algorithms to scale up easily as data volume increases—as more data is added to the dataset, more computing nodes can be added to a cluster to process new partitions of data. Data parallelism Other examples of computations and algorithms that can be run in a data parallel way include: Element-wise matrix operations such as addition and subtraction: The matrices can be partitioned and the operations are applied to each pair of partitions. Means: The sums and number of elements in each partition can be added to find the global sum and number of elements from which the mean can be computed. K-means clustering: After data partitioning, the K centroids are distributed to all the partitions. Finding the closest centroid is performed in parallel and independently across the partitions. The centroids are updated by first, calculating the sums and the counts of their respective members in parallel, and then consolidating them in a single process to get the global means. Frequent itemset mining using the Partition algorithm: In the first pass, the frequent itemsets are mined from each partition of data to generate a global set of candidate itemsets; in the second pass, the supports of the candidate itemsets are summed from each partition to filter out the globally infrequent ones. The other main class of parallelism is task parallelism, where tasks are distributed to and executed on different processors in parallel. The tasks on each processor might be the same or different, and the data that they act on might also be the same or different. The key difference between task parallelism and data parallelism is that the data is not divided into partitions. An example of a task parallel algorithm performing the same task on the same data is the training of a random forest model. A random forest is a collection of decision trees built independently on the same data. During the training process for a particular tree, a random subset of the data is chosen as the training set, and the variables to consider at each branch of the tree are also selected randomly. Hence, even though the same data is used, the trees are different from one another. In order to train a random forest of say 100 decision trees, the workload could be distributed to a computing cluster with 100 processors, with each processor building one tree. All the processors perform the same task on the same data (or exact copies of the data), but the data is not partitioned. The parallel tasks can also be different. For example, computing a set of summary statistics on the same set of data can be done in a task parallel way. Each process can be assigned to compute a different statistic—the mean, standard deviation, percentiles, and so on. Pseudocode of a task parallel algorithm might look like this: # Run 4 tasks in parallel across 4 coresfor (task in tasks)run.in.parallel(task)# Collect the results of the 4 tasksresults <- collect.parallel.output()# Continue processing after all 4 tasks are complete Implementing data parallel algorithms Several R packages allow code to be executed in parallel. The parallel package that comes with R provides the foundation for most parallel computing capabilities in other packages. Let's see how it works with an example. This example involves finding documents that match a regular expression. Regular expression matching is a fairly computational expensive task, depending on the complexity of the regular expression. The corpus, or set of documents, for this example is a sample of the Reuters-21578 dataset for the topic corporate acquisitions (acq) from the tm package. Because this dataset contains only 50 documents, they are replicated 100,000 times to form a corpus of 5 million documents so that parallelizing the code will lead to meaningful savings in execution times. library(tm)data("acq")textdata <- rep(sapply(content(acq), content), 1e5) The task is to find documents that match the regular expression d+(,d+)? mln dlrs, which represents monetary amounts in millions of dollars. In this regular expression, d+ matches a string of one or more digits, and (,d+)? optionally matches a comma followed by one more digits. For example, the strings 12 mln dlrs, 1,234 mln dlrs and 123,456,789 mln dlrs will match the regular expression. First, we will measure the execution time to find these documents serially with grepl(): pattern <- "\d+(,\d+)? mln dlrs"system.time(res1 <- grepl(pattern, textdata))##   user  system elapsed ## 65.601   0.114  65.721 Next, we will modify the code to run in parallel and measure the execution time on a computer with four CPU cores: library(parallel)detectCores()## [1] 4cl <- makeCluster(detectCores())part <- clusterSplit(cl, seq_along(textdata))text.partitioned <- lapply(part, function(p) textdata[p])system.time(res2 <- unlist(    parSapply(cl, text.partitioned, grepl, pattern = pattern))) ##  user  system elapsed ## 3.708   8.007  50.806 stopCluster(cl) In this code, the detectCores() function reveals how many CPU cores are available on the machine, where this code is executed. Before running any parallel code, makeCluster() is called to create a local cluster of processing nodes with all four CPU cores. The corpus is then split into four partitions using the clusterSplit() function to determine the ideal split of the corpus such that each partition has roughly the same number of documents. The actual parallel execution of grepl() on each partition of the corpus is carried out by the parSapply() function. Each processing node in the cluster is given a copy of the partition of data that it is supposed to process along with the code to be executed and other variables that are needed to run the code (in this case, the pattern argument). When all four processing nodes have completed their tasks, the results are combined in a similar fashion to sapply(). Finally, the cluster is destroyed by calling stopCluster(). It is good practice to ensure that stopCluster() is always called in production code, even if an error occurs during execution. This can be done as follows: doSomethingInParallel <- function(...) {    cl <- makeCluster(...)    on.exit(stopCluster(cl))    # do something} In this example, running the task in parallel on four processors resulted in a 23 percent reduction in the execution time. This is not in proportion to the amount of compute resources used to perform the task; with four times as many CPU cores working on it, a perfectly parallelizable task might experience as much as a 75 percent runtime reduction. However, remember Amdahl's law—the speed of parallel code is limited by the serial parts, which includes the overheads of parallelization. In this case, calling makeCluster() with the default arguments creates a socket-based cluster. When such a cluster is created, additional copies of R are run as workers. The workers communicate with the master R process using network sockets, hence the name. The worker R processes are initialized with the relevant packages loaded, and data partitions are serialized and sent to each worker process. These overheads can be significant, especially in data parallel algorithms where large volumes of data needs to be transferred to the worker processes. Besides parSapply(), parallel also provides the parApply() and parLapply() functions; these functions are analogous to the standard sapply(), apply(), and lapply() functions, respectively. In addition, the parLapplyLB() and parSapplyLB() functions provide load balancing, which is useful when the execution of each parallel task takes variable amounts of time. Finally, parRapply() and parCapply() are parallel row and column apply() functions for matrices. On non-Windows systems, parallel supports another type of cluster that often incurs less overheads — forked clusters. In these clusters, new worker processes are forked from the parent R process with a copy of the data. However, the data is not actually copied in the memory unless it is modified by a child process. This means that, compared to socket-based clusters, initializing child processes is quicker and the memory usage is often lower. Another advantage of using forked clusters is that parallel provides a convenient and concise way to run tasks on them via the mclapply(), mcmapply(), and mcMap() functions. (These functions start with mc because they were originally a part of the multicore package) There is no need to explicitly create and destroy the cluster, as these functions do this automatically. We can simply call mclapply() and state the number of worker processes to fork via the mc.cores argument: system.time(res3 <- unlist(    mclapply(text.partitioned, grepl, pattern = pattern,             mc.cores = detectCores())))##    user  system elapsed ## 127.012   0.350  33.264 This shows a 49 percent reduction in execution time compared to the serial version, and 35 percent reduction compared to parallelizing using a socket-based cluster. For this example, forked clusters provide the best performance. Due to differences in system configuration, you might see very different results when you try the examples in your own environment. When you develop parallel code, it is important to test the code in an environment that is similar to the one that it will eventually run in. Implementing task parallel algorithms Let's now see how to implement a task parallel algorithm using both socket-based and forked clusters. We will look at how to run the same task and different tasks on workers in a cluster. Running the same task on workers in a cluster To demonstrate how to run the same task on a cluster, the task for this example is to generate 500 million Poisson random numbers. We will do this by using L'Ecuyer's combined multiple-recursive generator, which is the only random number generator in base R that supports multiple streams to generate random numbers in parallel. The random number generator is selected by calling the RNGkind() function. We cannot just use any random number generator in parallel because the randomness of the data depends on the algorithm used to generate random data and the seed value given to each parallel task. Most other algorithms were not designed to produce random numbers in multiple parallel streams, and might produce multiple highly correlated streams of numbers, or worse, multiple identical streams! First, we will measure the execution time of the serial algorithm: RNGkind("L'Ecuyer-CMRG")nsamples <- 5e8lambda <- 10system.time(random1 <- rpois(nsamples, lambda))##   user  system elapsed## 51.905   0.636  52.544 To generate the random numbers on a cluster, we will first distribute the task evenly among the workers. In the following code, the integer vector samples.per.process contains the number of random numbers that each worker needs to generate on a four-core CPU. The seq() function produces ncores+1 numbers evenly distributed between 0 and nsamples, with the first number being 0 and the next ncores numbers indicating the approximate cumulative number of samples across the worker processes. The round() function rounds off these numbers into integers and diff() computes the difference between them to give the number of random numbers that each worker process should generate. cores <- detectCores()cl <- makeCluster(ncores)samples.per.process <-    diff(round(seq(0, nsamples, length.out = ncores+1))) Before we can generate the random numbers on a cluster, each worker needs a different seed from which it can generate a stream of random numbers. The seeds need to be set on all the workers before running the task, to ensure that all the workers generate different random numbers. For a socket-based cluster, we can call clusterSetRNGStream() to set the seeds for the workers, then run the random number generation task on the cluster. When the task is completed, we call stopCluster() to shut down the cluster: clusterSetRNGStream(cl)system.time(random2 <- unlist(    parLapply(cl, samples.per.process, rpois,               lambda = lambda)))##  user  system elapsed ## 5.006   3.000  27.436stopCluster(cl) Using four parallel processes in a socket-based cluster reduces the execution time by 48 percent. The performance of this type of cluster for this example is better than that of the data parallel example because there is less data to copy to the worker processes—only an integer that indicates how many random numbers to generate. Next, we run the same task on a forked cluster (again, this is not supported on Windows). The mclapply() function can set the random number seeds for each worker for us, when the mc.set.seed argument is set to TRUE; we do not need to call clusterSetRNGStream(). Otherwise, the code is similar to that of the socket-based cluster: system.time(random3 <- unlist(    mclapply(samples.per.process, rpois,             lambda = lambda,             mc.set.seed = TRUE, mc.cores = ncores))) ##   user  system elapsed ## 76.283   7.272  25.052 On our test machine, the execution time of the forked cluster is slightly faster, but close to that of the socket-based cluster, indicating that the overheads for this task are similar for both types of clusters. Running different tasks on workers in a cluster So far, we have executed the same tasks on each parallel process. The parallel package also allows different tasks to be executed on different workers. For this example, the task is to generate not only Poisson random numbers, but also uniform, normal, and exponential random numbers. As before, we start by measuring the time to perform this task serially: RNGkind("L'Ecuyer-CMRG")nsamples <- 5e7pois.lambda <- 10system.time(random1 <- list(pois = rpois(nsamples,                                          pois.lambda),                            unif = runif(nsamples),                            norm = rnorm(nsamples),                            exp = rexp(nsamples)))##   user  system elapsed ## 14.180   0.384  14.570 In order to run different tasks on different workers on socket-based clusters, a list of function calls and their associated arguments must be passed to parLapply(). This is a bit cumbersome, but parallel unfortunately does not provide an easier interface to run different tasks on a socket-based cluster. In the following code, the function calls are represented as a list of lists, where the first element of each sublist is the name of the function that runs on a worker, and the second element contains the function arguments. The function do.call() is used to call the given function with the given arguments. cores <- detectCores()cl <- makeCluster(cores)calls <- list(pois = list("rpois", list(n = nsamples,                                        lambda = pois.lambda)),              unif = list("runif", list(n = nsamples)),              norm = list("rnorm", list(n = nsamples)),              exp = list("rexp", list(n = nsamples)))clusterSetRNGStream(cl)system.time(    random2 <- parLapply(cl, calls,                         function(call) {                             do.call(call[[1]], call[[2]])                         }))##  user  system elapsed ## 2.185   1.629  10.403stopCluster(cl) On forked clusters on non-Windows machines, the mcparallel() and mccollect() functions offer a more intuitive way to run different tasks on different workers. For each task, mcparallel() sends the given task to an available worker. Once all the workers have been assigned their tasks, mccollect() waits for the workers to complete their tasks and collects the results from all the workers. mc.reset.stream()system.time({    jobs <- list()    jobs[[1]] <- mcparallel(rpois(nsamples, pois.lambda),                            "pois", mc.set.seed = TRUE)    jobs[[2]] <- mcparallel(runif(nsamples),                            "unif", mc.set.seed = TRUE)    jobs[[3]] <- mcparallel(rnorm(nsamples),                            "norm", mc.set.seed = TRUE)    jobs[[4]] <- mcparallel(rexp(nsamples),                            "exp", mc.set.seed = TRUE)    random3 <- mccollect(jobs)})##   user  system elapsed ## 14.535   3.569   7.97 Notice that we also had to call mc.reset.stream() to set the seeds for random number generation in each worker. This was not necessary when we used mclapply(), which calls mc.reset.stream() for us. However, mcparallel() does not, so we need to call it ourselves. Summary In this article, we learned about two classes of parallelism: data parallelism and task parallelism. Data parallelism is good for tasks that can be performed in parallel on partitions of a dataset. The dataset to be processed is split into partitions and each partition is processed on a different worker processes. Task parallelism, on the other hand, divides a set of similar or different tasks to amongst the worker processes. In either case, Amdahl's law states that the maximum improvement in speed that can be achieved by parallelizing code is limited by the proportion of that code that can be parallelized. Resources for Article: Further resources on this subject: Using R for Statistics, Research, and Graphics [Article] Learning Data Analytics with R and Hadoop [Article] Aspects of Data Manipulation in R [Article]

In this article, written by Jayant Varma, the author of Xcode 6 Essentials, we shall look at Xcode closely as this is going to be the tool you would use quite a lot for all aspects of your app development for Apple devices. It is a good idea to know and be familiar with the interface, the sections, shortcut keys, and so on. (For more resources related to this topic, see here.) Starting Xcode Xcode, like many other Mac applications, is found in the Applications folder or the Launchpad. On starting Xcode, you will be greeted with the launch screen that offers some entry points for working with Xcode. Mostly, you will select Create a new Xcode project or Check out an existing project , if you have an existing project to continue work on. Xcode remembers what it was doing last, so if you had a project or file open, it will open up those windows again. Creating a new project After selecting the Create a new project option, we are guided via a wizard that helps us get started. Selecting the project type The first step is to select what type of project you want to create. At the moment, there are two distinct types of projects, mobile (iOS) or desktop (OS X) that you can create. Within each of those types, you can select the type of project you want. The screenshot displays a standard configuration for iOS application projects. The templates used when the selected type of project is created are self sufficient, that is, when the Run button is pressed, the app compiles and runs. It might do nothing, as this is a minimalistic template. On selecting the type of project, we can select the next step: Setting the project options This step allows selecting the options, namely setting the application name, the organization name, identifier, language, and devices to support. In the past, the language was always set to Objective-C, however with Xcode 6, there are two options: objective-C and Swift Setting the project properties On creation, the main screen is displayed. Here it offers the option to change other details related to the application such as the version number and build. It also allows you to configure the team ID and certificates used for signing the application to test on a mobile device or for distribution to the App Store. It also allows you to set the compatibility for earlier versions. The orientation and app icons, splash screens, and so on are also set from this screen. If you want to set these up later on in the project, it is fine, this can be accessed at any time and does not stop you from development. It needs to be set prior to deploying it on a device or creating an App Store ready application. Xcode overview Let us have a look at the Xcode interface to familiarize ourselves with the same as it would help improve productivity when building your application. The top section immediately following the traffic light (window chrome) displays a Play and Stop button. This allows the project to run and stop. The breadcrumb toolbar displays the project-specific settings with respect to the product and the target. With an iOS project, it could be a particular simulator for iPhone, iPad, and so on, or a physical device (number 5 in the following screenshot). Just under this are vertical areas that are the main content area with all the files, editors, UI, and so on. These can be displayed or hidden as required and can be stacked vertically or horizontally. The distinct areas in Xcode are as follows: Project navigation (number1) Editor and assistant editor (number 2 ) and (number 3 ) Utility/inspector (number 4 ) The toolbar (number 5 ) and (number 6 ) These sections can be switched on and off (shown or hidden) as required to make space for other sections or more screen space to work with: Sections in Xcode The project section The project navigation section has three sub sections, the topmost being the project toolbar that has eight icons. These can be seen as in the following screenshot. The next sub section contains the project files and all the assets required for this project. The bottom most section consists of recently edited files and filters: You can use the keyboard shortcuts to access these areas quickly with the CMD + 1...8 keys. The eight areas available under project navigation are key and for the beginner to Xcode, this could be a bit daunting. When you run the project, the current section might change and display another where you might wonder how to get back to the project (file) navigator. Getting familiar with these is always helpful and the easiest way to navigate between these is the CMD + 1..8 keys. Project navigator ( CMD + 1 ): This displays all of the files, folders, assets, frameworks, and so on that are part of this project. This is displayed as a hierarchical view and is the way that a majority of developers access their files, folders, and so on. Symbol navigator ( CMD + 2 ): This displays all of the classes, members, and methods that are available in them. This is the easiest way to navigate quickly to a method/function, attribute/property. Search navigator ( CMD + 3 ): This allows you to search the project for a particular match. This is quite useful to find and replace text. Issues navigator ( CMD + 4 ): This displays the warning and errors that occur while typing your code or on building and running it. This also displays the results of the static analyzer. Tests navigator ( CMD + 5 ); This displays the tests that you have present in your code either added by yourself or the default ones created with the project. Debug navigator ( CMD + 6 ): This displays the information about the application when you choose to run it. It has some amazing detailed information on CPU usage, memory usage, disk usage, threads, and so on. Breakpoint navigator ( CMD + 7 ): This displays all the breakpoints in your project from all files. This also allows you to create exception and symbolic breakpoints. Log navigator ( CMD + 8 ): This displays a log of all actions carried out, namely compiling, building, and running. This is more useful when used to determine the results of automated builds The editor and assistant editor sections The second area contains the editor and assistant editor sections. These display the code, the XIB (as appropriate), storyboard files, device previews, and so on. Each of the sub sections have a jump bar on the top that relates to files and allow for navigating back and forth in the files and display the location of the file in the workspace. To the right from this is a mini issues navigator that displays all warnings and errors. In the case of the assistant editors, it also displays two buttons: one to add a new assistant editor area and another to close it.   Source code editors While we are looking at the interface, it is worth noting that the Xcode code editor is a very advanced editor with a lot of features, which is now seen as standard with a lot of text editors. Some of the features that make working with Xcode easier are as follows: Code folding : This feature helps to hide code at points such as the function declaration, loops, matching brace brackets, and so on. When a function or portion of code is folded, it hides it from view, thereby allowing you to view other areas of the code that would not be visible unless you scrolled. Syntax highlighting : This is one of the most useful features as it helps you, the developer, to visually, at a glance, differentiate your source code from variables, constants, and strings. Xcode has syntax highlighting for a couple of languages as mentioned earlier. Context help : This is one of the best features whereby when you hover over a word in the source code with OPT pressed, it shows a dotted underline and the cursor changes to a question mark. When you click on a word with the dotted underline and the question mark cursor, it displays a popup with details about that word. It also highlights all instances of that word in the file. The popup details as much information as available. If it is a variable or a function that you have added to the code, then it will display the name of the file where it was declared. If it is a word that is contained in the Apple libraries, then it displays the description and other additional details. Context jump : This is another cool feature that allows jumping to the point of declaration of that word. This is achieved by clicking on a word while keeping the CMD button pressed. In many cases, this is mainly helpful to know how the function is declared and what parameters it expects. It can also be useful to get information on other enumerators and constants used with that function. The jump could be in the same file as where you are editing the code or it could be to the header files where they are declared. Edit all in scope : This is a cool feature where you can edit all of the instances of the word together rather than using search and replace. A case scenario is if you want to change the name of a variable and ensure that all instances you are using in the file are changed but not the ones that are text, then you can use this option to quickly change it. Catching mistakes with fix-it : This is another cool feature in Xcode that will save you a lot of time and hassle. As you type text, Xcode keeps analyzing the code and looking for errors. If you have declared a variable and not used it in your code, Xcode immediately draws attention to it suggesting that the variable is an unused variable. However, if it was supposed to be a pointer and you have declared it without *; Xcode immediately flags it as an error that the interface type cannot be statically allocated. It offers a fix-it solution of inserting * and the code has a greyed * character showing where it will be added. This helps the developer fix commonly overlooked issues such as missing semicolons, missing declarations, or misspelled variable names. Code completion : This is the bit that makes writing code so much easier, type in a few letters of the function name and Xcode pops up a list of functions, constants, methods, and so on that start with those letters and displays all of the required parameters (as applicable) including the return type. When selected, it adds the token placeholders that can be replaced with the actual parameter values. The results might vary from person to person depending on the settings and the speed of the system you run Xcode on. The assistant editor The assistant editor is mainly used to display the counterparts and related files to the file open in the primary editor (generally used when working with Objective-C where the .h or.m files are the related files). The assistant editors track the contents of the editor. Xcode is quite intelligent and knows the corresponding sections and counterparts. When you click on a file, it opens up in the editor. However, pressing the OPT + Shift while clicking on the file, you would be provided with an interactive dialog to select where to open the file. The options include the primary editor or the assistant editor. You can also add assistant editors as required.   Another way to open a file quickly is to use the Open Quickly option, which has a shortcut key of CMD + Shift + O . This displays a textbox that allows accessing a file from the project. The utility/inspector section The last section contains the inspector and library. This section changes based on the type of file selected in the current editor. The inspector has 6 tabs/sections and they are as follows: The file inspector ( CMD + OPT + 1 ): This displays the physical file information for the file selected. For code files, it is the text encoding, the targets that it belongs to, and the physical file path. While for the storyboard, it is the physical file path and allows setting attributes such as auto layout and size classes (new in Xcode 6). The quick help inspector ( CMD + OPT + 2 ): This displays information about the class or object selected. The identity inspector ( CMD + OPT + 3 ): This displays the class name, ID, and others that identify the object selected. The attributes inspector ( CMD + OPT + 4 ): This displays the attributes for the object selected as if it is the initial root view controller, does it extend under the top bars or not, if it has a navigation bar or not, and others. This also displays the user-defined attributes (a new feature with Xcode 6). The size inspector ( CMD + OPT + 5 ): This displays the size of the control selected and the associated constraints that help position it on the container. The connections inspector ( CMD + OPT + 6 ): This displays the connections created in the Interface Builder between the UI and the code. The lower half of this inspector contains four options that help you work efficiently, they are as follows: The file template library : This contains the options to create a new class, protocol. The options that are available when selecting the File | New option from the menu. The code snippets library : This is a wonderful but not widely used option. This can hold code snippets that can help you avoid writing repetitive blocks of code in your app. You can drag and drop the snippet to your code in the editor. This also offers features such as shortcuts, scopes, platforms, and languages. So you can have a shortcut such as appDidLoad (for example) that inserts the code to create and populate a button. This is achieved simply by setting the platform as appropriate to iOS or OS X. After creating a code snippet, as soon as you type the first few characters, the code snippet shows up in the list of autocomplete options; The object library : This is the toolbox that contains all of the controls that you need for creating your UI, be it a button, a label, a Table View, view, View Controller, or anything else. Adding a code snippet is as easy as dragging the selected code from the editor onto the snippet area. It is a little tricky because the moment you start dragging, it could break your selection highlight. You need to select the text, click (hold) and then drag it. The media library : This contains the list of all images and other media types that are available to this project/workspace. Summary In this article, you have seen a quick tour of Xcode, keeping the shortcuts and tips handy as they really do help get things done faster. The code snippets are a wonderful feature that allow for quickly setting up commonly used code with shortcut keywords. Resources for Article: Further resources on this subject: Introducing Xcode Tools for iPhone Development [article] Xcode 4 ios: Displaying Notification Messages [article] Linking OpenCV to an iOS project [article]

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 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 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 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 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 the authors, Fabrizio Volpe, Alessio Giombini, Lasse Nordvik Wedø, and António Vargas of the book, Lync Server Cookbook, we will cover the following recipes: Introducing Lync Online Administering with the Lync Admin Center Using Lync Online Remote PowerShell Using Lync Online cmdlets Introducing Lync in a hybrid scenario Planning and configuring a hybrid deployment Moving users to the cloud Moving users back on-premises Debugging Lync Online issues (For more resources related to this topic, see here.) Introducing Lync Online Lync Online is part of the Office 365 offer and provides online users with the same Instant Messaging (IM), presence, and conferencing features that we would expect from an on-premises deployment of Lync Server 2013. Enterprise Voice, however, is not available on Office 365 tenants (or at least, it is available only with limitations regarding both specific Office 365 plans and geographical locations). There is no doubt that forthcoming versions of Lync and Office 365 will add what is needed to also support all the Enterprise Voice features in the cloud. Right now, the best that we are able to achieve is to move workloads, homing a part of our Lync users (the ones with no telephony requirements) in Office 365, while the remaining Lync users are homed on-premises. These solutions might be interesting for several reasons, including the fact that we can avoid the costs of expanding our existing on-premises resources by moving a part of our Lync-enabled users to Office 365. The previously mentioned configuration, which involves different kinds of Lync tenants, is called a hybrid deployment of Lync, and we will see how to configure it and move our users from online to on-premises and vice versa. In this Article, every time we talk about Lync Online and Office 365, we will assume that we have already configured an Office tenant. Administering with the Lync Admin Center Lync Online provides the Lync Admin Center (LAC), a dedicated control panel, to manage Lync settings. To open it, access the Office 365 portal and select Service settings, Lync, and Manage settings in the Lync admin center, as shown in the following screenshot: LAC, if you compare it with the on-premises Lync Control Panel (or with the Lync Management Shell), offers few options. For example, it is not possible to create or delete users directly inside Lync. We will see some of the tasks we are able to perform in LAC, and then, we will move to the (more powerful) Remote PowerShell. There is an alternative path to open LAC. From the Office 365 portal, navigate to Users & Groups | Active Users. Select a user, after which you will see a Quick Steps area with an Edit Lync Properties link that will open the user-editable part of LAC. How to do it... LAC is divided into five areas: users, organization, dial-in conferencing, meeting invitation, and tools, as you can see in the following screenshot: The Users panel will show us the configuration of the Lync Online enabled users. It is possible to modify the settings with the Edit option (the small pencil icon on the right): I have tried to summarize all the available options (inside the general, external communications, and dial-in conferencing tabs) in the following screenshot: Some of the user's settings are worth a mention; in the General tab, we have the following:    The Record Conversations and meetings option enables the Start recording option in the Lync client    The Allow anonymous attendees to dial-out option controls whether the anonymous users that are dialing-in to a conference are required to call the conferencing service directly or are authorized for callback    The For compliance, turn off non-archived features option disables Lync features that are not recorded by In-Place Hold for Exchange When you place an Exchange 2013 mailbox on In-Place Hold or Litigation Hold, the Microsoft Lync 2013 content (instant messaging conversations and files shared in an online meeting) is archived in the mailbox. In the dial-in conferencing tab, we have the configuration required for dial-in conferencing. The provider's drop-down menu shows a list of third parties that are able to deliver this kind of feature. The Organization tab manages privacy for presence information, push services, and external access (the equivalent of the Lync federation on-premises). If you enable external access, we will have the option to turn on Skype federation, as we can see in the following screenshot: The Dial-In Conferencing option is dedicated to the configuration of the external providers. The Meeting Invitation option allows the user to customize the Lync Meeting invitation. The Tools options offer a collection of troubleshooting resources. See also For details about Exchange In-Place Hold, see the TechNet post In-Place Hold and Litigation Hold at http://technet.microsoft.com/en-us/library/ff637980(v=exchg.150).aspx. Using Lync Online Remote PowerShell The possibility to manage Lync using Remote PowerShell on a distant deployment has been available since Lync 2010. This feature has always required a direct connection from the management station to the Remote Lync, and a series of steps that is not always simple to set up. Lync Online supports Remote PowerShell using a dedicated (64-bit only) PowerShell module, the Lync Online Connector. It is used to manage online users, and it is interesting because there are many settings and automation options that are available only through PowerShell. Getting ready Lync Online Connector requires one of the following operating systems: Windows 7 (with Service Pack 1), Windows Server 2008 R2, Windows Server 2012, Windows Server 2012 R2, Windows 8, or Windows 8.1. At least PowerShell 3.0 is needed. To check it, we can use the $PSVersionTable variable. The result will be like the one in the following screenshot (taken on Windows 8.1, which uses PowerShell 4.0): How to do it... Download Windows PowerShell Module for Lync Online from the Microsoft site at http://www.microsoft.com/en-us/download/details.aspx?id=39366 and install it. It is useful to store our Office 365 credentials in an object (it is possible to launch the cmdlets at step 3 anyway, and we will be required with the Office 365 administrator credentials, but using this method, we will have to insert the authentication information again every time it is required). We can use the $credential = Get-Credential cmdlet in a PowerShell session. We will be prompted for our username and password for Lync Online, as shown in the following screenshot: To use the Online Connector, open a PowerShell session and use the New-CsOnlineSession cmdlet. One of the ways to start a remote PowerShell session is $session = New-CsOnlineSession -Credential $credential. Now, we need to import the session that we have created with Lync Online inside PowerShell, with the Import-PSSession $session cmdlet. A temporary Windows PowerShell module will be created, which contains all the Lync Online cmdlets. The name of the temporary module will be similar to the one we can see in the following screenshot: Now, we will have the cmdlets of the Lync Online module loaded in memory, in addition to any command that we already have available in PowerShell. How it works... The feature is based on a PowerShell module, the LyncOnlineConnector, shown in the following screenshot: It contains only two cmdlets, the Set-WinRMNetworkDelayMS and New-CsOnlineSession cmdlets. The latter will load the required cmdlets in memory. As we have seen in the previous steps, the Online Connector adds the Lync Online PowerShell cmdlets to the ones already available. This is something we will use when talking about hybrid deployments, where we will start from the Lync Management Shell and then import the module for Lync Online. It is a good habit to verify (and close) your previous remote sessions. This can be done by selecting a specific session (using Get-PSSession and then pointing to a specific session with the Remove-PSSession statement) or closing all the existing ones with the Get-PSSession | Remove-PSSession cmdlet. In the previous versions of the module, Microsoft Online Services Sign-In Assistant was required. This prerequisite was removed from the latest version. There's more... There are some checks that we are able to perform when using the PowerShell module for Lync Online. By launching the New-CsOnlineSession cmdlet with the –verbose switch, we will see all the messages related to the opening of the session. The result should be similar to the one shown in the following screenshot: Another verification comes from the Get-Command -Module tmp_gffrkflr.ufz command, where the module name (in this example, tmp_gffrkflr.ufz) is the temporary module we saw during the Import-PSSession step. The output of the command will show all the Lync Online cmdlets that we have loaded in memory. The Import-PSSession cmdlet imports all commands except the ones that have the same name of a cmdlet that already exists in the current PowerShell session. To overwrite the existing cmdlets, we can use the -AllowClobber parameter. See also During the introduction of this section, we also discussed the possibility to administer on-premises, remote Lync Server 2013 deployment with a remote PowerShell session. John Weber has written a great post about it in his blog Lync 2013 Remote Admin with PowerShell at http://tsoorad.blogspot.it/2013/10/lync-2013-remote-admin-with-powershell.html, which is helpful if you want to use the previously mentioned feature. Using Lync Online cmdlets In the previous recipe, we outlined the steps required to establish a remote PowerShell session with Lync Online. We have less than 50 cmdlets, as shown in the result of the Get-Command -Module command in the following screenshot: Some of them are specific for Lync Online, such as the following: Get-CsAudioConferencingProvider Get-CsOnlineUser Get-CsTenant Get-CsTenantFederationConfiguration Get-CsTenantHybridConfiguration Get-CsTenantLicensingConfiguration Get-CsTenantPublicProvider New-CsEdgeAllowAllKnownDomains New-CsEdgeAllowList New-CsEdgeDomainPattern Set-CsTenantFederationConfiguration Set-CsTenantHybridConfiguration Set-CsTenantPublicProvider Update-CsTenantMeetingUrl All the remaining cmdlets can be used either with Lync Online or with the on-premises version of Lync Server 2013. We will see the use of some of the previously mentioned cmdlets. How to do it... The Get-CsTenant cmdlet will list Lync Online tenants configured for use in our organization. The output of the command includes information such as the preferred language, registrar pool, domains, and assigned plan. The Get-CsTenantHybridConfiguration cmdlet gathers information about the hybrid configuration of Lync. Management of the federation capability for Lync Online (the feature that enables Instant Messaging and Presence information exchange with users of other domains) is based on the allowed domain and blocked domain lists, as we can see in the organization and external communications screen of LAC, shown in the following screenshot: There are similar ways to manage federation from the Lync Online PowerShell, but it required to put together different statements as follows:     We can use an accept all domains excluding the ones in the exceptions list approach. To do this, we have put the New-CsEdgeAllowAllKnownDomains cmdlet inside a variable. Then, we can use the Set-CsTenantFederationConfiguration cmdlet to allow all the domains (except the ones in the block list) for one of our domains on a tenant. We can use the example on TechNet (http://technet.microsoft.com/en-us/library/jj994088.aspx) and integrate it with Get-CsTenant.     If we prefer, we can use a block all domains but permit the ones in the allow list approach. It is required to define a domain name (pattern) for every domain to allow the New-CsEdgeDomainPattern cmdlet, and each one of them will be saved in a variable. Then, the New-CsEdgeAllowList cmdlet will create a list of allowed domains from the variables. Finally, the Set-CsTenantFederationConfiguration cmdlet will be used. The domain we will work on will be (again) cc3b6a4e-3b6b-4ad4-90be-6faa45d05642. The example on Technet (http://technet.microsoft.com/en-us/library/jj994023.aspx) will be used: $x = New-CsEdgeDomainPattern -Domain "contoso.com" $y = New-CsEdgeDomainPattern -Domain "fabrikam.com" $newAllowList = New-CsEdgeAllowList -AllowedDomain $x,$y Set-CsTenantFederationConfiguration -Tenant " cc3b6a4e-3b6b-4ad4-90be-6faa45d05642" -AllowedDomains $newAllowList The Get-CsOnlineUser cmdlet provides information about users enabled on Office 365. The result will show both users synced with Active Directory and users homed in the cloud. The command supports filters to limit the output; for example, the Get-CsOnlineUser -identity fab will gather information about the user that has alias = fab. This is an account synced from the on-premises Directory Services, so the value of the DirSyncEnabled parameter will be True. See also All the cmdlets of the Remote PowerShell for Lync Online are listed in the TechNet post Lync Online cmdlets at http://technet.microsoft.com/en-us/library/jj994021.aspx. This is the main source of details on the single statement. Introducing Lync in a hybrid scenario In a Lync hybrid deployment, we have the following: User accounts and related information homed in the on-premises Directory Services and replicated to Office 365. A part of our Lync users that consume on-premises resources and a part of them that use online (Office 365 / Lync Online) resources. The same (public) domain name used both online and on-premises (Lync-split DNS). Other Office 365 services and integration with other applications available to all our users, irrespective of where their Lync is provisioned. One way to define Lync hybrid configuration is by using an on-premises Lync deployment federated with an Office 365 / Lync Online tenant subscription. While it is not a perfect explanation, it gives us an idea of the scenario we are talking about. Not all the features of Lync Server 2013 (especially the ones related to Enterprise Voice) are available to Lync Online users. The previously mentioned motivations, along with others (due to company policies, compliance requirements, and so on), might recommend a hybrid deployment of Lync as the best available solution. What we have to clarify now is how to make those users on different deployments talk to each other, see each other's presence status, and so on. What we will see in this section is a high-level overview of the required steps. The Planning and configuring a hybrid deployment recipe will provide more details about the individual steps. The list of steps here is the one required to configure a hybrid deployment, starting from Lync on-premises. In the following sections, we will also see the opposite scenario (with our initial deployment in the cloud). How to do it... It is required to have an available Office 365 tenant configuration. Our subscription has to include Lync Online. We have to configure an Active Directory Federation Services (AD FS) server in our domain and make it available to the Internet using a public FQDN and an SSL certificate released from a third-party certification authority. Office 365 must be enabled to synchronize with our company's Directory Services, using Active Directory Sync. Our Office 365 tenant must be federated. The last step is to configure Lync for a hybrid deployment. There's more... One of the requirements for a hybrid distribution of Lync is an on-premises deployment of Lync Server 2013 or Lync Server 2010. For Lync Server 2010, it is required to have the latest available updates installed, both on the Front Ends and on the Edge servers. It is also required to have the Lync Server 2013 administrative tools installed on a separate server. More details about supported configuration are available on the TechNet post Planning for Lync Server 2013 hybrid deployments at http://technet.microsoft.com/en-us/library/jj205403.aspx. DNS SRV records for hybrid deployments, _sipfederationtls._tcp.<domain> and _sip._tls.<domain>, should point to the on-premises deployment. The lyncdiscover. <domain> record will point to the FQDN of the on-premises reverse proxy server. The _sip._tls. <domain> SRV record will resolve to the public IP of the Access Edge service of Lync on-premises. Depending on the kind of service we are using for Lync, Exchange, and SharePoint, only a part of the features related to the integration with the additional services might be available. For example, skills search is available only if we are using Lync and SharePoint on-premises. The following TechNet post Supported Lync Server 2013 hybrid configurations at http://technet.microsoft.com/en-us/library/jj945633.aspx offers a matrix of features / service deployment combinations. See also Interesting information about Lync Hybrid configuration is presented in sessions available on Channel9 and coming from the Lync Conference 2014 (Lync Online Hybrid Deep Dive at http://channel9.msdn.com/Events/Lync-Conference/Lync-Conference-2014/ONLI302) and from TechEd North America 2014 (Microsoft Lync Online Hybrid Deep Dive at http://channel9.msdn.com/Events/TechEd/NorthAmerica/2014/OFC-B341#fbid=). Planning and configuring a hybrid deployment The planning phase for a hybrid deployment starts from a simple consideration: do we have an on-premises deployment of Lync Server? If the previously mentioned scenario is true, do we want to move users to the cloud or vice versa? Although the first situation is by far the most common, we have to also consider the case in which we have our first deployment in the cloud. How to do it... This step is all that is required for the scenario that starts from Lync Online. We have to completely deploy our Lync on-premises. Establish a remote PowerShell session with Office 365. Use the shared SIP address cmdlet Set-CsTenantFederationConfiguration -SharedSipAddressSpace $True to enable Office 365 to use a Shared Session Initiation Protocol (SIP) address space with our on-premises deployment. To verify this, we can use the Get-CsTenantFederationConfiguration command. The SharedSipAddressSpace value should be set to True. All the following steps are for the scenario that starts from the on-premises Lync deployment. After we have subscribed with a tenant, the first step is to add the public domain we use for our Lync users to Office 365 (so that we can split it on the two deployments). To access the Office 365 portal, select Domains. The next step is Specify a domain name and confirm ownership. We will be required to type a domain name. If our domain is hosted on some specific providers (such as GoDaddy), the verification process can be automated, or we have to proceed manually. The process requires to add one DNS record (TXT or MX), like the ones shown in the following screenshot: If we need to check our Office 365 and on-premises deployments before continuing with the hybrid deployment, we can use the Setup Assistant for Office 365. The tool is available inside the Office 365 portal, but we have to launch it from a domain-joined computer (the login must be performed with the domain administrative credentials). In the Setup menu, we have a Quick Start and an Extend Your Setup option (we have to select the second one). The process can continue installing an app or without software installation, as shown in the following screenshot: The app (which makes the assessment of the existing deployment easier) is installed by selecting Next in the previous screen (it requires at least Windows 7 with Service Pack 1, .NET Framework 3.5, and PowerShell 2.0). Synchronization with the on-premises Active Directory is required. This last step federates Lync Server 2013 with Lync Online to allow communication between our users. The first cmdlet to use is Set-CSAccessEdgeConfiguration -AllowOutsideUsers 1 -AllowFederatedUsers 1 -UseDnsSrvRouting -EnablePartnerDiscovery 1. Note that the -EnablePartnerDiscovery parameter is required. Setting it to 1 enables automatic discovery of federated partner domains. It is possible to set it to 0. The second required cmdlet is New-CSHostingProvider -Identity LyncOnline -ProxyFqdn "sipfed.online.lync.com" -Enabled $true -EnabledSharedAddressSpace $true -HostsOCSUsers $true –VerificationLevel UseSourceVerification -IsLocal $false -AutodiscoverUrl https://webdir.online.lync.com/Autodiscover/AutodiscoverService.svc/root. The result of the commands is shown in the following screenshot: If Lync Online is already defined, we have to use the Set- CSHostingProvider cmdlet, or we can remove it (Remove-CsHostingProvider -Identity LyncOnline) and then create it using the previously mentioned cmdlet. There's more... In the Lync hybrid scenario, users created in the on-premises directory are replicated to the cloud, while users generated in the cloud will not be replicated on-premises. Lync Online users are managed using the Office 365 portal, while the users on-premises are managed using the usual tools (Lync Control Panel and Lync Management Shell). Moving users to the cloud By moving users from Lync on-premises to the cloud, we will lose some of the parameters. The operation requires the Lync administrative tools and the PowerShell module for Lync Online to be installed on the same computer. If we install the module for Lync Online before the administrative tools for Lync 2013 Server, the OCSCore.msi file overwrites the LyncOnlineConnector.ps1 file, and New-CsOnlineSession will require a -TargetServer parameter. In this situation, we have to reinstall the Lync Online module (see the following post on the Microsoft support site at http://support.microsoft.com/kb/2955287). Getting ready Remember that to move the user to Lync Online, they must be enabled for both Lync Server on-premises and Lync Online (so we have to assign the user a license for Lync Online by using the Office 365 portal). Users with no assigned licenses will show the error Move-CsUser : HostedMigration fault: Error=(507), Description=(User must has an assigned license to use Lync Online. For more details, refer to the Microsoft support site at http://support.microsoft.com/kb/2829501. How to do it... Open a new Lync Management Shell session and launch the remote session on Office 365 with the cmdlets' sequence we saw earlier. We have to add the –AllowClobber parameter so that the Lync Online module's cmdlets are able to overwrite the corresponding Lync Management Shell cmdlets: $credential = Get-Credential $session = New-CsOnlineSession -Credential $credential Import-PSSession $session -AllowClobber Open the Lync Admin Center (as we have seen in the dedicated section) by going to Service settings | Lync | Manage settings in the Lync Admin Center, and copy the first part of the URL, for example, https://admin0e.online.lync.com. Add the following string to the previous URL /HostedMigration/hostedmigrationservice.svc (in our example, the result will be https://admin0a.online.lync.com/HostedMigration/hostedmigrationservice.svc). The following cmdlet will move users from Lync on-premises to Lync Online. The required parameters are the identity of the Lync user and the URL that we prepared in step 2. The user identity is fabrizio.volpe@absoluteuc.biz: Move-CsUser -Identity fabrizio.volpe@absoluteuc.biz –Target sipfed.online.lync.com -Credential $creds -HostedMigrationOverrideUrl https://admin0e.online.lync.com/HostedMigration/hostedmigrationservice.sVc Usually, we are required to insert (again) the Office 365 administrative credentials, after which we will receive a warning about the fact that we are moving our user to a different version of the service, like the one in the following screenshot: See the There's more... section of this recipe for details about user information that is migrated to Lync Online. We are able to quickly verify whether the user has moved to Lync Online by using the Get-CsUser | fl DisplayName,HostingProvider,RegistrarPool,SipAddress command. On-premises HostingProvider is equal to SRV: and RegistrarPool is madhatter.wonderland.lab (the name of the internal Lync Front End). Lync Online values are HostingProvider : sipfed.online.lync.com, and leave RegistrarPool empty, as shown in the following screenshot (the user Fabrizio is homed on-premises, while the user Fabrizio volpe is homed on the cloud): There's more... If we plan to move more than one user, we have to add a selection and pipe it before the cmdlet we have already used, removing the –identity parameter. For example, to move all users from an Organizational Unit (OU), (for example, the LyncUsers in the Wonderland.Lab domain) to Lync Online, we can use Get-CsUser -OU "OU=LyncUsers,DC=wonderland,DC=lab"| Move-CsUser -Target sipfed.online.lync.com -Credential $creds -HostedMigrationOverrideUrl https://admin0e.online.lync.com/HostedMigration/hostedmigrationservice.sVc. We are also able to move users based on a parameter to match using the Get-CsUser –Filter cmdlet. As we mentioned earlier, not all the user information is migrated to Lync Online. Migration contact list, groups, and access control lists are migrated, while meetings, contents, and schedules are lost. We can use the Lync Meeting Update Tool to update the meeting links (which have changed when our user's home server has changed) and automatically send updated meeting invitations to participants. There is a 64-bit version (http://www.microsoft.com/en-us/download/details.aspx?id=41656) and a 32-bit version (http://www.microsoft.com/en-us/download/details.aspx?id=41657) of the previously mentioned tool. Moving users back on-premises It is possible to move back users that have been moved from the on-premises Lync deployment to the cloud, and it is also possible to move on-premises users that have been defined and enabled directly in Office 365. In the latter scenario, it is important to create the user also in the on-premises domain (Directory Service). How to do it… The Lync Online user must be created in the Active Directory (for example, I will define the BornOnCloud user that already exists in Office 365). The user must be enabled in the on-premises Lync deployment, for example, using the Lync Management Shell with the following cmdlet: Enable-CsUser -Identity "BornOnCloud" -SipAddress "SIP:BornOnCloud@absoluteuc.biz" -HostingProviderProxyFqdn "sipfed.online.lync.com" Sync the Directory Services. Now, we have to save our Office 365 administrative credentials in a $cred = Get-Credential variable and then move the user from Lync Online to the on-premises Front End using the Lync Management Shell (the -HostedMigrationOverrideURL parameter has the same value that we used in the previous section): Move-CsUser -Identity BornOnCloud@absoluteuc.biz -Target madhatter.wonderland.lab -Credential $cred -HostedMigrationOverrideURL https://admin0e.online.lync.com/HostedMigration/hostedmigrationservice.svc The Get-CsUser | fl DisplayName,HostingProvider,RegistrarPool,SipAddress cmdlet is used to verify whether the user has moved as expected. See also Guy Bachar has published an interesting post on his blog Moving Users back to Lync on-premises from Lync Online (http://guybachar.wordpress.com/2014/03/31/moving-users-back-to-lync-on-premises-from-lync-online/), where he shows how he solved some errors related to the user motion by modifying the HostedMigrationOverrideUrl parameter. Debugging Lync Online issues Getting ready When moving from an on-premises solution to a cloud tenant, the first aspect we have to accept is that we will not have the same level of control on the deployment we had before. The tools we will list are helpful in resolving issues related to Lync Online, but the level of understanding on an issue they give to a system administrator is not the same we have with tools such as Snooper or OCSLogger. Knowing this, the more users we will move to the cloud, the more we will have to use the online instruments. How to do it… The Set up Lync Online external communications site on Microsoft Support (http://support.microsoft.com/common/survey.aspx?scid=sw;en;3592&showpage=1) is a guided walk-through that helps in setting up communication between our Lync Online users and external domains. The tool provides guidelines to assist in the setup of Lync Online for small to enterprise businesses. As you can see in the following screenshot, every single task is well explained: The Remote Connectivity Analyzer (RCA) (https://testconnectivity.microsoft.com/) is an outstanding tool to troubleshoot both Lync on-premises and Lync Online. The web page includes tests to analyze common errors and misconfigurations related to Microsoft services such as Exchange, Lync, and Office 365. To test different scenarios, it is necessary to use various network protocols and ports. If we are working on a firewall-protected network, using the RCA, we are also able to test services that are not directly available to us. For Lync Online, there are some tests that are especially interesting; in the Office 365 tab, the Office 365 General Tests section includes the Office 365 Lync Domain Name Server (DNS) Connectivity Test and the Office 365 Single Sign-On Test, as shown in the following screenshot: The Single Sign-On test is really useful in a scenario. The test requires our domain username and password, both synced with the on-premises Directory Services. The steps include searching the FQDN of our AD FS server on an Internet DNS, verifying the certificate and connectivity, and then validating the token that contains the credentials. The Client tab offers to download the Microsoft Connectivity Analyzer Tool and the Microsoft Lync Connectivity Analyzer Tool, which we will see in the following two dedicated steps: The Microsoft Connectivity Analyzer Tool makes many of the tests we see in the RCA available on our desktop. The list of prerequisites is provided in the article Microsoft Connectivity Analyzer Tool (http://technet.microsoft.com/library/jj851141(v=exchg.80).aspx), and includes Windows Vista/Windows 2008 or later versions of the operating system, .NET Framework 4.5, and an Internet browser, such as Internet Explorer, Chrome, or Firefox. For the Lync tests, a 64-bit operating system is mandatory, and the UCMA runtime 4.0 is also required (it is part of Lync Server 2013 setup, and is also available for download at http://www.microsoft.com/en-us/download/details.aspx?id=34992). The tools propose ways to solve different issues, and then, they run the same tests available on the RCA site. We are able to save the results in an HTML file. The Microsoft Lync Connectivity Analyzer Tool is dedicated to troubleshooting the clients for mobile devices (the Lync Windows Store app and Lync apps). It tests all the required configurations, including autodiscover and webticket services. The 32-bit version is available at http://www.microsoft.com/en-us/download/details.aspx?id=36536, while the 64-bit version can be downloaded from http://www.microsoft.com/en-us/download/details.aspx?id=36535. .NET Framework 4.5 is required. The tool itself requires a few configuration parameters; we have to insert the user information that we usually add in the Lync app, and we have to use a couple of drop-down menus to describe the scenario we are testing (on-premises or Internet, and the kind of client we are going to test). The Show drop-down menu enables us to look not only at a summary of the test results but also at the detailed information. The detailed view includes all the information and requests sent and received during the test, with the FQDN included in the answer ticket from our services, and so on, as shown in the following screenshot: The Troubleshooting Lync Online sign-in post is a support page, available in two different versions (admins and users), and is a walk-through to help admins (or users) to troubleshoot login issues. The admin version is available at http://support.microsoft.com/common/survey.aspx?scid=sw;en;3695&showpage=1, while the user version is available at http://support.microsoft.com/common/survey.aspx?scid=sw;en;3719&showpage=1. Based on our answers to the different scenario questions, the site will propose to information or solution steps. The following screenshot is part of the resolution for the log-I issues of a company that has an enterprise subscription with a custom domain: The Office 365 portal includes some information to help us monitor our Lync subscription. In the Service Health menu, navigate to Service Health; we have a list of all the incidents and service issues of the past days. In the Reports menu, we have statistics about our Office 365 consumption, including Lync. In the following screenshot, we can see the previously mentioned pages: There's more... One interesting aspect of the Microsoft Lync Connectivity Analyzer Tool that we have seen is that it enables testing for on-premises or Office 365 accounts (both testing from inside our network and from the Internet). The previously mentioned capability makes it a great tool to troubleshoot the configuration for Lync on the mobile devices that we have deployed in our internal network. This setup is usually complex, including hair-pinning and split DNS, so the diagnostic is important to quickly find misconfigured services. See also The Troubleshooting Lync Sign-in Errors (Administrators) page on Office.com at http://office.microsoft.com/en-001/communicator-help/troubleshooting-lync-sign-in-errors-administrators-HA102759022.aspx contains a list of messages related to sign-in errors with a suggested solution or a link to additional external resources. Summary In this article, we have learned about managing Lync 2013 and Lync Online and using Lync Online Remote PowerShell and Lync Online cmdlets. Resources for Article: Further resources on this subject: Adding Dialogs [article] Innovation of Communication and Information Technologies [article] Choosing Lync 2013 Clients [article]

In this article by Paul Goodey, author of the book Salesforce CRM – The Definitive Admin Handbook - Third Edition, we will look at the administration of Salesforce Mobile solutions that can significantly improve productivity and user satisfaction and help them access data and application functionality out of the office. (For more resources related to this topic, see here.) In the past, mobile devices that were capable of accessing software applications were very expensive. Often, these devices were regarded as a nice to have accessory by management and were seen as a company perk by field-based teams. Today, mobile devices are far more prevalent within the business environment, and organizations are increasingly realizing the benefits of using mobile phones and devices to access business applications. Salesforce has taken the lead in recognizing how mobiles have become the new standard for being connected in people's personal and professional lives. It has also highlighted how increasingly, the users of their apps are living lives connected to the Internet, but rather than sitting at a desk in the office, they are in between meetings, on the road, in planes, in trains, in cabs, or even in the queue for lunch. As a result, Salesforce has developed innovative mobile solutions that help you and your users embrace this mobile-first world in Salesforce CRM. Accessing Salesforce Mobile products Salesforce offers two varieties of mobile solutions, namely mobile browser apps and downloadable apps. Mobile browser apps, as the name suggests, are accessed using a web browser that is available on a mobile device. Downloadable apps are accessed by first downloading the client software from, say, the Apple App Store or Google Play and then installing it onto the mobile device. Mobile browser apps and downloadable apps offer various features and benefits and, as we'll see, are available for various Salesforce mobile products and device combinations. Most mobile devices these days have some degree of web browser capability, which can be used to access Salesforce CRM; however, some Salesforce mobile products are optimized for use with certain devices. By accessing a Salesforce mobile browser app, your users do not require anything to be installed. Supported mobile browsers for Salesforce are generally available on Android, Apple, BlackBerry, and Microsoft Windows 8.1 devices. Downloadable apps, on the other hand, will require the app to be first downloaded from the App Store for Apple® devices or from Google Play™ for Android™ devices and then installed on the mobile device. Salesforce mobile products' overview Salesforce has provided certain mobile products as downloadable apps only, while others have been provided as both downloadable and mobile browser-based. The following list outlines the various mobile app products, features, and capabilities used to access Salesforce CRM on mobile devices: SalesforceA Salesforce Touch Salesforce1 Salesforce Classic Salesforce Touch is no longer available and is mentioned here for completeness as this product has been recently incorporated into the Salesforce1 product. SalesforceA SalesforceA is a downloadable system administration app that allows you to manage your organization's users and view certain information for your Salesforce organization from your mobile device. Salesforce A is intended to be used by system administrators, as it is restricted to users with the Manage Users permission. The SalesforceA app provides the facilities to carry out user tasks, such as deactivating or freezing users, resetting passwords, unlocking users, editing user details, calling and emailing users, and assigning permission sets. These user task buttons are displayed as action icons, as shown in the following screenshot: These icons are presented in the action bar at the bottom of the mobile device screen, as shown in the following screenshot: In addition to the user tasks, you can view the system status and also switch between your user accounts in multiple organizations. This allows you to access different organizations and communities without having to log out and log back in to each user account. By staying logged in to multiple accounts in different organizations, you will save time by easily switching to the particular organization user account that you need to access. SalesforceA supported devices At the time of writing, the following devices are supported by Salesforce for use with the SalesforceA downloadable app: Android phones Apple iPhone Apple iPod Touch SalesforceA can be installed from Google Play™ for Android™ phones and the Apple® App Store for Apple devices. Salesforce Touch Salesforce Touch is the name of an earlier Salesforce mobile product and is no longer available. With the Spring 2014 release, Salesforce Touch was incorporated into the Salesforce1 app. Hence, both the Salesforce Touch mobile browser and Salesforce Touch downloadable apps are no longer available; however, the functionality that they once offered is available in Salesforce1, which is covered in this article. Salesforce1 Salesforce1 is Salesforce's next-generation mobile CRM platform that has been designed for Salesforce's customers, developers, and ISVs (independent software vendors) to connect mobile apps, browser apps, and third-party app services. Salesforce1 has been developed for a mobile-first environment and demonstrates how Salesforce's focus as a platform provider aims to connect enterprises with systems that can be programmed through APIs, along with mobile apps and services that can be utilized by marketing, sales, and customer service. There are two ways to use Salesforce1: either using a mobile browser app that users can access by logging into Salesforce from a supported mobile browser or downloadable apps that users can install from the App Store or Google Play. Either way, Salesforce1 allows users to access and update Salesforce data from an interface that has been optimized to navigate and work on their touchscreen mobile devices. Using Salesforce1, records can be viewed, edited, and created. Users can manage their activities, view their dashboards, and use Chatter. Salesforce1 also supports many standard objects and list views, all custom objects, plus the integration of other mobile apps and many of your organization's Salesforce customizations, including Visualforce tabs and pages. Salesforce1 supported devices At the time of writing this, the following devices are supported by Salesforce for the Salesforce1 mobile browser app: Android phones Apple iPad Apple iPhone BlackBerry Z10 Windows 8.1 phones (Beta support) Also, at the time of writing this, Salesforce specifies the following devices as being supported for the Salesforce1 downloadable app: Android phones Apple iPad Apple iPhone Salesforce1 data availability Your organization edition, the user's license type, along with the user's profile and any permission sets, determines the data that is available to the user within Salesforce1. Generally, users have the same visibility of objects, record types, fields, and page layouts that they have while accessing the full Salesforce browser app. However, at the time of writing this, not all data is available in the current release of the Salesforce1 app. In Winter 2015, these key objects are fully accessible from the Salesforce1 navigation menu: Accounts; Campaigns; Cases; Contacts; Contracts; Leads; Opportunities; Tasks; and Users. Dashboards and Events, however, are restricted to being viewable from only the Salesforce1 navigation menu. Custom objects are fully accessible if they have a tab that the user can access. For new users who are yet to build a history of recent objects, they initially see a set of default objects in the Recent section in the Salesforce1 navigation menu. The majority of standard and custom fields, and most of the related lists for the supported objects, are available on these records; however, at the time of writing this, the following exceptions exist: Rich text area field support varies (detailed shortly) Links on formula fields are not supported State and country picklist fields are not supported Related lists in Salesforce1 are restricted (detailed shortly) Rich text area field support varies Support for rich text area fields varies by the version of Salesforce1 and the type of device. For Android's downloadable apps, you can view and edit rich text area fields. However, for Android's mobile browser apps, you can only view rich text area fields; editing is not supported currently. For iOS's downloadable apps, you can view but not edit rich text area fields. However, for iOS's mobile browser apps, you can view and also edit rich text area fields. Finally, for both BlackBerry and Windows 8.1 mobile browser apps, you can neither view nor edit rich text area fields. Related lists in Salesforce1 Related lists in Salesforce1 are restricted and display the first four fields that are defined on the page layout for that object. The number of fields shown cannot be increased. If Chatter is enabled, users can also access feeds, people, groups, and Salesforce Files. When users are working with records in the full Salesforce app, it can take up to 15 days for this data to appear in the Recent section; thus, to make records appear under the Recent section sooner, ask users to pin them from their search results in the full Salesforce site. Salesforce1 administration You can manage your organization's access to Salesforce1 apps; there are two areas of administration: the mobile browser app that users can access by logging in to Salesforce from a supported mobile browser and the downloadable app that users can install from the App Store or Google Play. The upcoming sections describe the ways to control user access to each of these mobile apps. Salesforce1 mobile browser app access You can control whether users can access the Salesforce1 mobile browser app when they log into Salesforce from a mobile browser. To select or deselect this feature, navigate to Setup | Mobile Administration | Salesforce1 | Settings, as shown in the following screenshot: By selecting the Enable the Salesforce1 mobile browser app checkbox, all users are activated to access Salesforce1 from their mobile browsers. Deselecting this option turns off the mobile browser app, which means that users will automatically access the full Salesforce site from their mobile browser. By default, the mobile browser app is turned on in all Salesforce organizations. Salesforce1 desktop browser access Selecting the Enable the Salesforce1 mobile browser app checkbox, as described in the previous section, permits users who are activated to access Salesforce1 from their desktop browsers. Users can navigate to the Salesforce1 app within their desktop browser by appending “/one/one.app” to the end of the Salesforce URL. As an example, for the following Salesforce URL accessed from the server na10, you would enter the https://na10.salesforce.com/one/one.app desktop browser URL. Salesforce1 downloadable app access The Salesforce1 app is distributed as a managed package, and within Salesforce, it is implemented as a connected app. You might already see the Salesforce1 connected app in your list of installed apps as it might have been automatically installed in your organization. The list of included apps can change with each Salesforce release but, to simplify administration, each package is asynchronously installed in Salesforce organizations whenever any user in that organization first accesses Salesforce1. However, to manually install or reinstall the Salesforce1 package for connected apps, you can install it from the AppExchange. To view the details for the Salesforce1 app in the connected app settings, navigate to Setup | Manage Apps | Connected Apps. The apps that connect to your Salesforce organization are then listed as shown in the following screenshot: Salesforce1 notifications Notifications allow all users in your organization to receive mobile notifications in Salesforce1, for example, whenever they are mentioned in Chatter or whenever they receive approval requests. To activate mobile notifications, navigate to Setup | Mobile Administration | Notifications | Settings, as shown in the following screenshot: The settings for notifications can be set as follows: Enable in-app notifications: Set this option to keep users notified about relevant Salesforce activity while they are using Salesforce1. Enable push notifications: Set this option to keep users notified of relevant Salesforce activity when they are not using the Salesforce1 downloadable app. Include full content in push notifications: Keep this checkbox unchecked if you do not want users to receive full content in push notifications. This can prevent users from receiving potentially sensitive data that might be in comments, for example. If you set this option, a pop-up dialog appears, displaying terms and conditions where you must click on OK or Cancel. Salesforce1 branding This option allows you to customize the appearance of the Salesforce1 app so that it complies with any company branding requirements that might be in place. Salesforce1 branding is supported in downloadable apps' Version 5.2 or higher and also in the mobile browser app. To specify Salesforce1 branding, navigate to Setup | Mobile Administration | Salesforce1 | Branding, as shown in the following screenshot: Salesforce1 compact layouts In Salesforce1, compact layouts are used to display the key fields on a record and are specifically designed to view records on touchscreen mobile devices. As space is limited on mobile devices and quick recognition of records is important, the first four fields that you assign to a compact layout are displayed. If a mobile user does not have the required access to one of the first four fields that have been assigned to a compact layout, the next field, if more than four fields have been set on the layout, is used. If you are yet to create custom compact layouts, the records will be displayed using a read-only, predefined system default compact layout, and after you have created a custom compact layout, you can then set it as the primary compact layout for that object. As with the full Salesforce CRM site, if you have record types associated with an object, you can alter the primary compact layout assignment and assign specific compact layouts to different record types. You can also clone a compact layout from its detail page. The upcoming field types cannot be included on compact layouts: text area, long text area, rich text area, and multiselect picklists. Salesforce1 offline access In Salesforce1, the mechanism to handle offline access is determined by users' most recently used records. These records are cached for offline access; at the time of writing this, they are read-only. The cached data is encrypted and secured through persistent storage by Salesforce1's downloadable apps. Offline access is available in Salesforce1's downloadable apps Version 6.0 and higher and was first released in Summer 2014. Offline access is enabled by default when Salesforce1's downloadable app is installed. To manage these settings, navigate to Setup | Mobile Administration | Offline. Now, check or uncheck Enable Offline Sync for Salesforce1, as shown in the following screenshot: When offline access is enabled, data based on the objects is downloaded to each user's mobile device and presented in the Recent section of the Salesforce1 navigation menu and on the user's most recently viewed records. The data is encrypted and stored in a secure, persistent cache on the mobile device. Setting up Salesforce1 with the Salesforce1 Wizard The Salesforce1 Wizard simplifies the setting up of the Salesforce1 mobile app. The wizard offers a visual tour of the key setup steps and is useful if you are new to Salesforce1 or need to quickly set up the core Salesforce1 settings. The Salesforce1 Wizard guides you through the setting up of the following Salesforce1 configuration steps: Choose which items appear in the navigation menu Configure global actions Create a contact custom compact layout Optionally, invite users to start using the Salesforce1 app To access the Salesforce1 Wizard, navigate to Setup | Salesforce1 Setup. Now, click on Launch Quick Start Wizard within the Salesforce1 Setup page, as shown in the following screenshot: Upon clicking on the Let's Get Started section link (shown in the following screenshot), you will be presented with the Salesforce1 Setup visual tour, as shown in the next section. The Quick Start Wizard The Quick Start Wizard guides you through the minimum configuration steps required to set up Salesforce1. By clicking on the Launch Quick Start Wizard button, the process to complete the essential setup tasks for Salesforce1 is initiated and provides a step-by-step wizard guide. The five steps are: Customize the Navigation Menu: This step results in the setup of the navigation menu for all users in your organization. To reorder items, drag them up and down. To remove items, drag them to the Available Items list, as shown in the following screenshot: Arrange Global Actions: Global actions provide users with quick access to Salesforce functions and in this step, you will choose and arrange the Salesforce1 global actions, as shown in the following screenshot: Actions might might have a different appearance, depending upon your version of Salesforce1. Create a Custom Compact Layout for Contacts: Compact layouts are used to show the key fields on a record in the highlights area at the top of the record detail. In this step, you are able to create a custom compact layout for contacts to set, for example, a contact's name, e-mail, and phone number, as shown in the following screenshot: However, after you have completed the Quick Start Wizard, you can create compact layouts for other objects as required. Review: In this step, you are given the chance to preview the changes to verify the results of the changes, as shown in the following screenshot: The review step screen gives you a live preview that uses your current access as the logged-in user. Send Invitations: This is the final step of the Quick Start Wizard, which will provide you with a basic setup of Salesforce1 and allow you to get feedback on what you have implemented. In this step, you can invite your users to start using the Salesforce1 app, as shown in the following screenshot: This step can be skipped and you can always send invitations later from the Salesforce1 setup page. You can also implement additional options to customize the app, such as incorporating your own branding. Differences between Salesforce1 and the full Salesforce CRM browser app In the Winter 2015 release and at the time of writing this, Salesforce1 does not have all of the features of the full Salesforce CRM site; moreover, in some areas, it includes functionality that is not available in, or is different from, the complete Salesforce site. As an example, on the full Salesforce CRM site, compact layouts determine which fields appear in the Chatter feed item and which appear after a user creates a record via a publisher action. However, compact layouts in Salesforce1 are used to display the key fields on a record. For details about the features that differ between the full Salesforce CRM site and Salesforce1, refer to Salesforce1 Limits and Differences from the Full Salesforce Site within the Salesforce Help menu sections. Summary In this article, we looked at ways in which mobile has become the new normal way to stay connected in both our personal and professional lives. Salesforce has recognized this well; we are all spending time being connected to the cloud and using business applications. However, instead of sitting at a desk, users are often on the go. To try and help their customers become successful businesses of this mobile-first world, Salesforce has produced mobile solutions that can help user get things done regardless of where they are and what they are doing. We looked at SalesforceA, which is an admin specific app that can help you manage users and monitor the status of Salesforce while on the move. We discussed Salesforce Touch, which is being replaced with Salesforce1, and we also spoke about the features and benefits of Salesforce1, which is available as a downloadable app and a browser app. Resources for Article: Further resources on this subject: Customization in Microsoft Dynamics CRM [Article] Getting Started with Microsoft Dynamics CRM 2013 Marketing [Article] Diagnostic leveraging of the Accelerated POC with the CRM Online service [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.