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Vectors actually describe two things: magnitude and direction. For instance, soldier Alpha can use the vector AB to figure out how far he has to travel (magnitude), but the vector also tells him in which direction to face (direction). Normally these two pieces of information are tied up together in a vector, but occasionally you only require one or the other. We have already seen how to calculate the magnitude, but we can also remove the magnitude information from the vector by dividing the components by the magnitude. This is called normalizing the vector, and produces a special kind of vector called a unit vector. Unit vectors always have a length of 1, and are often used to represent a heading. When we move into the third dimension, you will find them essential for everything from collision detection to lighting. Let s add a method to Vector2 that normalizes the vector and turns it into a unit vector (Listing 5-9). Listing 5-9. Testing the Unit Vector Method import math class Vector2(object): def __init__(self, x=0.0, y=0.0): self.x = x self.y = y def __str__(self): return "(%s, %s)"%(self.x, self.y) @classmethod def from_points(cls, P1, P2): return cls( P2[0] P1[0], P2[1] P1[1] ) def get_magnitude(self): return math.sqrt( self.x**2 + self.y**2 ) def normalize(self): magnitude = self.get_magnitude() self.x /= magnitude self.y /= magnitude

The Git source code control system is explained in greater detail in chapter 13, so this section just covers the mechanics of getting the Linux sources. When working with Git, you don t check out the sources, as with other source code control systems; you create a copy, or clone, of a repository. For the Linux kernel, you use the following command: $ git clone git://git.kernel.org/pub/scm/linux/kernel/git/stable/linux-2.6.31.y.git You ll likely use a different version of the kernel, so the 2.6.31 in this link will be the version of the kernel that you want to download. Your company may have a firewall that blocks the URL git://; if this is the case, replace git: with http:, and the data will be downloaded over port 80.

Note For help on troubleshooting Remote Access problems, take a look at the Troubleshooting Remote

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Building the kernel is frequently viewed as a difficult proposition. There s also the view that building the kernel is risky because the newly build kernel won t work properly even if it does compile. These assumptions are simply false. Building a kernel from source is easy, and the risks of the software not working are minimal the kernel is tested by thousands of software engineers on a daily basis. Because the project is complex, building the kernel requires a few steps not necessary for other project. The basic steps are as follows: 1.

A = (10.0, 20.0) B = (30.0, 35.0) AB = Vector2.from_points(A, B) print "Vector AB is", AB print "Magnitude of Vector AB is", AB.get_magnitude() AB.normalize() print "Vector AB normalized is", AB Executing this script produces the following output: Vector AB is (20.0, 15.0) Magnitude of Vector AB is 25.0 Vector AB normalized is (0.8, 0.6)

Configuration: During the configuration step, you set the parameters and options that control how the kernel is built. There are several different ways of configuring the kernel, but it doesn t matter which one you select because all of them perform the same underlying activities. Configuration is frequently aided by default configuration settings supplied with the kernel for most boards and processors; for many boards, you can use this default configuration as is to build a kernel that will boot on the board. Building the kernel: After it s configured, the kernel can be compiled and linked. This process works much like any other project using GNU Make as the build tool. The result of the kernel build is a binary that can be put on the board and booted as well as file suitable for debugging. Building the modules: The Linux kernel supports linking code into the image at runtime, similar to the way a program uses a shared library. Kernel modules support hardware components that may not be present when the kernel is started, so having the code in memory is a waste of resources. The code that can be linked into the kernel, in a process called loading, is called a module; these modules can be built separately from the kernel. Modules can be loaded and unloaded on demand.

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