R Graphics Cookbook Pdf

[Katina Piccirilli]

Mybook about data visualization in R is available! The book covers many of the same topics as the Graphs and Data Manipulation sections of this website, but it goes into more depth and covers a broader range of techniques. You can preview it at Google Books.

There are many ways of making graphs in R, each with its advantages and disadvantages. The focus here is on the ggplot2 package, which is based on the Grammar of Graphics (by Leland Wilkinson) to describe data graphics.

Graphics programmer spending most of my waking hours making pixels prettier and faster. This blog is my scratchpad for graphics techniques I try and experiment with. The opinions expressed herein are my own.

I was recently invited to review the new 3D Graphics Rendering Cookbook book by Sergey Kosarevsky and Viktor Latypov. The main focus of the book is the implementation of a large variety of graphics techniques using both modern OpenGL and Vulkan, an interesting approach that can show the parallels between the two graphics APIs and act as a steppingstone for less experienced programmers towards a better understanding of Vulkan.

Graphics programming involves more than loading and displaying a model on screen, and a lot of the programming time is spent on loading/converting assets, setting up UIs, multithreading the application, adding support for profiling. I appreciate the fact the authors devoted quite a bit of time on assembling and discussing a good collection of libraries and frameworks to handle all that and let the reader focus on the graphics techniques.

In general, I would recommend this book to people with some knowledge of graphics theory and techniques, wanting to get hands on with the actual implementation. The OpenGL path is lower friction and has a less steep learning curve and will help people will less experience in graphics programming, gradually transitioning to Vulkan during the second pass if they want to. People with more graphics programming experience can benefit from this book as well, especially those that have started learning Vulkan.

ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

ggplot2 is now over 10 years old and is used by hundreds of thousands of people to make millions of plots. That means, by-and-large, ggplot2 itself changes relatively little. When we do make changes, they will be generally to add new functions or arguments rather than changing the behaviour of existing functions, and if we do make changes to existing behaviour we will do them for compelling reasons.

If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages. Currently, there are three good places to start:

The Data Visualization and Communication chapters in R for Data Science. R for Data Science is designed to give you a comprehensive introduction to the tidyverse, and these two chapters will get you up to speed with the essentials of ggplot2 as quickly as possible.

There are many production-quality open source C++ libraries and frameworks out there. One of the traits of an experienced graphics developer is their comprehensive knowledge of available open source libraries that are suitable for getting the job done.

The GLFW library hides all the complexity of creating windows, graphics contexts, and surfaces, and getting input events from the operating system. In this recipe, we build a minimalistic application with GLFW and OpenGL to get some basic 3D graphics out onto the screen.

Now we are ready to use OpenGL to get some basic graphics out. Let's draw a colored triangle. To do that, we need a vertex shader and a fragment shader, which are both linked to a shader program, and a vertex array object (VAO). Follow these steps:

We use the GLSL built-in gl_VertexID input variable to index into the pos[] and col[] arrays to generate the vertex positions and colors programmatically. In this case, no user-defined inputs to the vertex shader are required.

The GLFW setup for macOS is quite similar to the Windows operating system. In the CMakeLists.txt file, you should add the following line to the list of used libraries: -framework OpenGL -framework Cocoa -framework CoreView -framework IOKit.

Every 3D graphics application needs some sort of math utility functions, such as basic linear algebra or computational geometry. This book uses the OpenGL Mathematics (GLM) header-only C++ mathematics library for graphics, which is based on the GLSL specification. The official documentation ( -truc.net) describes GLM as follows:

Let's augment the example from the previous recipe using a simple animation and a 3D cube. The model and projection matrices can be calculated inside the main loop based on the window aspect ratio, as follows:

The GL_DYNAMIC_STORAGE_BIT parameter tells the OpenGL implementation that the content of the data store might be updated after creation through calls to glBufferSubData(). The glBindBufferRange() function binds a range within a buffer object to an indexed buffer target. The buffer is bound to the indexed target of 0. This value should be used in the shader code to read data from the buffer.

As you might have noticed in the preceding code, the glBindBufferRange() function takes an offset into the buffer as one of its input parameters. That means we can make the buffer twice as large and store two different copies of PerFrameData in it. One with isWireframe set to true and another one set to false. Then, we can update the entire buffer with just one call to glNamedBufferSubData(), instead of updating the buffer twice, and use the offset parameter of glBindBufferRange() to feed the correct instance of PerFrameData into the shader. This is the correct and most attractive approach, too.

The reason we decided not to use it in this recipe is that the OpenGL implementation might impose alignment restrictions on the value of offset. For example, many implementations require offset to be a multiple of 256. Then, the actual required alignment can be queued as follows:

The alignment requirement would make the simple and straightforward code of this recipe more complicated and difficult to follow without providing any meaningful performance improvements. In more complicated real-world use cases, particularly as the number of different values in the buffer goes up, this approach becomes more useful.

Almost every graphics application requires texture images to be loaded from files in some image file formats. Let's take a look at the STB image loader and discuss how we can use it to support popular formats, such as .jpeg, .png, and a floating point format .hdr for high dynamic range texture data.

STB supports the loading of high-dynamic-range images in Radiance .HDR file format. Use the stbi_loadf() function to load files as floating-point images. This will preserve the full dynamic range of the image and will be useful to load high-dynamic-range light probes for physically-based lighting in the Chapter 6, Physically Based Rendering Using the glTF2 Shading Model.

Graphical applications require some sort of UI. The interactive UI can be used to debug real-time applications and create powerful productivity and visualization tools. Dear ImGui is a fast, portable, API-agnostic immediate-mode GUI library for C++ developed by Omar Cornut ( ):

The ImGui library provides numerous comprehensive examples that explain how to make a GUI renderer for different APIs, including a 700-line code example using OpenGL 3 and GLFW (imgui/examples/imgui_impl_opengl3.cpp). In this recipe, we will demonstrate how to make a minimalistic ImGui renderer in 200 lines of code using OpenGL 4.6. This is not feature-complete, but it can serve as a good starting point for those who want to integrate ImGui into their own modern graphical applications.

The IM_OFFSETOF() macro is a part of ImGui, too. It is used to calculate the offset of member fields inside the ImDrawVert structure. The macro definition itself is quite verbose and platform-dependent. Please refer to imgui/imgui.h for implementation details.

These were the necessary steps to set up vertex arrays, buffers, and shaders for UI rendering. There are still some initialization steps that need to be done for ImGui itself before we can render anything. Follow these steps:

Now we are ready to proceed with the OpenGL state setup for rendering. All ImGui graphics should be rendered with blending and the scissor test turned on and the depth test and backface culling disabled. Here is the code snippet to set this state:

Once we exit the main loop, we should destroy the ImGui context with ImGui::DestroyContext(). OpenGL object deletion is similar to some of the previous recipes and will be omitted here for the sake of brevity.

The preceding code will render the UI. To enable user interaction, we need to pass user input events from GLWF to ImGui. Let's demonstrate how to deal with the mouse input to make our minimalistic UI interactive:

Now we can run our demo application. The application for this recipe renders a Dear ImGui demo window. If everything has been done correctly, the resulting output should look similar to the following screenshot. It is possible to interact with the UI using a mouse:

Our minimalistic implementation skipped some features that were needed to handle all ImGui rendering possibilities. For example, we did not implement user-defined rendering callbacks or the handling of flipped clipping rectangles. Please refer to imgui/examples/imgui_impl_opengl3.cpp for more details.

Another important part is to pass all of the necessary GLFW events into ImGui, including numerous keyboard events, cursor shapes, scrolling, and more. The complete reference implementation can be found in imgui/examples/imgui_impl_glfw.cpp.

Profiling enables developers to get vital measurement data and feedback in order to optimize the performance of their applications. EasyProfiler is a lightweight cross-platform profiler library for C++, which can be used to profile multithreaded graphical applications ( _profiler).

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