Re: R4ds Cheat Code Editor V1 08
Indira Rossetto
Software for editing the usrcheat.dat file, which is the cheat code database for NintendoDS R4. This software supports output in GBK character code, which prevents garbled characters in English/Chinese version R4 when Japanese is used for code names.
Starts from the v1.08 official version, the R4i supports Action Replay function, simultaneously supports the official Action Replay database and the user database. The R4i Action Replay Cheat uses for the creation and edition of user's database, either supports the user manual input or XML files import.
Open the cheat database users already have, if there are some cheat codes in the current database, the opened data will be added behind the cheat codes, to use this function will complete the merge of several databases.
"Game ID:" is composed by two parts, the first 4 letters are for the game "Game code", the last 8 hexadecimal numbers for the game crc code, used for the match of the cheat and the corresponding game.
"Cheat data:" use for input the cheat code, indicated with 16 hexadecimal numbers, every 8 numbers place a space, please certainly press "Update Code" button after input completed in order to add the data into the database, otherwise it will be lose.
Please be aware that if the current database already have some games, the opened database will be added behind these games, use this function will complete the Merge of several databases. (Recommended to remove the duplicated games).
Quarto provides a unified authoring framework for data science, combining your code, its results, and your prose. Quarto documents are fully reproducible and support dozens of output formats, like PDFs, Word files, presentations, and more.
Quarto is a command line interface tool, not an R package. This means that help is, by-and-large, not available through ?. Instead, as you work through this chapter, and use Quarto in the future, you should refer to the Quarto documentation.
Figure 28.1 shows a .qmd document in RStudio with notebook interface where code and output are interleaved. You can run each code chunk by clicking the Run icon (it looks like a play button at the top of the chunk), or by pressing Cmd/Ctrl + Shift + Enter. RStudio executes the code and displays the results inline with the code.
Create a new Quarto document using File > New File > Quarto Document. Read the instructions. Practice running the chunks individually. Then render the document by clicking the appropriate button and then by using the appropriate keyboard short cut. Verify that you can modify the code, re-run it, and see modified output.
Most importantly, while the visual editor displays your content with formatting, under the hood, it saves your content in plain Markdown and you can switch back and forth between the visual and source editors to view and edit your content using either tool.
Create a document in a Google doc or MS Word (or locate a document you have created previously) with some content in it such as headings, hyperlinks, formatted text, etc. Copy the contents of this document and paste it into a Quarto document in the visual editor. Then, switch over to the source editor and inspect the source code.
You can continue to run the code using the keyboard shortcut that by now (we hope!) you know and love: Cmd/Ctrl + Enter. However, chunks get a new keyboard shortcut: Cmd/Ctrl + Shift + Enter, which runs all the code in the chunk. Think of a chunk like a function. A chunk should be relatively self-contained, and focused around a single task.
Your chunk labels should be short but evocative and should not contain spaces. We recommend using dashes (-) to separate words (instead of underscores, _) and avoiding other special characters in chunk labels.
eval: false prevents code from being evaluated. (And obviously if the code is not run, no results will be generated). This is useful for displaying example code, or for disabling a large block of code without commenting each line.
Since Quarto is designed to be multi-lingual (works with R as well as other languages like Python, Julia, etc.), all of the knitr options are not available at the document execution level since some of them only work with knitr and not other engines Quarto uses for running code in other languages (e.g., Jupyter). You can, however, still set these as global options for your document under the knitr field, under opts_chunk. For example, when writing books and tutorials we set:
There is one other way to embed R code into a Quarto document: directly into the text, with: `r `. This can be very useful if you mention properties of your data in the text. For example, the example document used at the start of the chapter had:
To embed an image from an external file, you can use the Insert menu in the Visual Editor in RStudio and select Figure / Image. This will pop open a menu where you can browse to the image you want to insert as well as add alternative text or caption to it and adjust its size. In the visual editor you can also simply paste an image from your clipboard into your document and RStudio will place a copy of that image in your project folder.
The biggest challenge of graphics in Quarto is getting your figures the right size and shape. There are five main options that control figure sizing: fig-width, fig-height, fig-asp, out-width and out-height. Image sizing is challenging because there are two sizes (the size of the figure created by R and the size at which it is inserted in the output document), and multiple ways of specifying the size (i.e. height, width, and aspect ratio: pick two of three).
Figure sizing and scaling is an art and science and getting things right can require an iterative trial-and-error approach. You can learn more about figure sizing in the taking control of plot scaling blog post.
When mingling code and text, like in this book, you can set fig-show: hold so that plots are shown after the code. This has the pleasant side effect of forcing you to break up large blocks of code with their explanations.
Similar to figures, you can include two types of tables in a Quarto document. They can be markdown tables that you create directly in your Quarto document (using the Insert Table menu) or they can be tables generated as a result of a code chunk. In this section we will focus on the latter, tables generated via computation.
dependson should contain a character vector of every chunk that the cached chunk depends on. Knitr will update the results for the cached chunk whenever it detects that one of its dependencies have changed.
Troubleshooting Quarto documents can be challenging because you are no longer in an interactive R environment, and you will need to learn some new tricks. Additionally, the error could be due to issues with the Quarto document itself or due to the R code in the Quarto document.
One common error in documents with code chunks is duplicated chunk labels, which are especially pervasive if your workflow involves copying and pasting code chunks. To address this issue, all you need to do is to change one of your duplicated labels.
HTML documents typically have a number of external dependencies (e.g., images, CSS style sheets, JavaScript, etc.) and, by default, Quarto places these dependencies in a _files folder in the same directory as your .qmd file. If you publish the HTML file on a hosting platform (e.g., QuartoPub, ), the dependencies in this directory are published with your document and hence are available in the published report. However, if you want to email the report to a colleague, you might prefer to have a single, self-contained, HTML document that embeds all of its dependencies. You can do this by specifying the embed-resources option:
Quarto documents can include one or more parameters whose values can be set when you render the report. Parameters are useful when you want to re-render the same report with distinct values for various key inputs. For example, you might be producing sales reports per branch, exam results by student, or demographic summaries by country. To declare one or more parameters, use the params field.
Quarto can automatically generate citations and a bibliography in a number of styles. The most straightforward way of adding citations and bibliographies to a Quarto document is using the visual editor in RStudio.
If you add a citation using one of the first three methods, the visual editor will automatically create a bibliography.bib file for you and add the reference to it. It will also add a bibliography field to the document YAML. As you add more references, this file will get populated with their citations. You can also directly edit this file using many common bibliography formats including BibLaTeX, BibTeX, EndNote, Medline.
When Quarto renders your file, it will build and append a bibliography to the end of your document. The bibliography will contain each of the cited references from your bibliography file, but it will not contain a section heading. As a result it is common practice to end your file with a section header for the bibliography, such as # References or # Bibliography.
As with the bibliography field, your csl file should contain a path to the file. Here we assume that the csl file is in the same directory as the .qmd file. A good place to find CSL style files for common bibliography styles is -style-language/styles.
Quarto is also important because it so tightly integrates prose and code. This makes it a great analysis notebook because it lets you develop code and record your thoughts. An analysis notebook shares many of the same goals as a classic lab notebook in the physical sciences. It:
Supports rigorous thinking. You are more likely to come up with a strong analysis if you record your thoughts as you go, and continue to reflect on them. This also saves you time when you eventually write up your analysis to share with others.
You are going to create many, many, many analysis notebooks over the course of your career. How are you going to organize them so you can find them again in the future? We recommend storing them in individual projects, and coming up with a good naming scheme.
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