Installing the v2png Program from Vega (Node.js Module) on Windows

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The export_png() function in the R ggvis package requires us to have the program vg2png installed, from the node.js module vega. While installing vega using npm on Windows may seem straightforward, it appears that there are some additional steps required to ensure that vg2png is correctly installed and recognized by the ggvis package.

In this article, we will walk through the process of installing vega and its dependency, canvas, on a Windows system. We will also explore potential issues with vg2png installation and provide guidance on resolving common errors when using export_png() in R ggvis.

Installing Node.js and npm

Before we begin installing vega, it is essential to have Node.js and npm installed on your system. npm (Node Package Manager) is the package manager for node.js, which allows us to easily install and manage dependencies for our projects.

To download and install Node.js and npm on Windows, follow these steps:

1. Visit the official Node.js website (www.nodejs.org) and click on the “Download” button.
2. Select the correct version of Node.js that suits your system architecture (32-bit or 64-bit).
3. Follow the installation instructions to install Node.js and npm.

Installing Vega using npm

Once you have installed Node.js and npm, you can proceed with installing vega using npm:

npm install -g trifacta/vega

This command installs the trifacta/vega package globally on your system. The -g flag indicates that we want to install the package as a global module.

Verifying Vega Installation

After installing vega, verify its presence by checking the npm documentation for vega:

npm --version

If you have installed vega correctly, this command should output the current version of vega.

Next, let’s check if vg2png is also present in the vega installation directory:

ls -l $(npm config get prefix)/node_modules/vega/bin/

This command lists the files and directories within the vega installation directory.

Understanding the Output

The output will show the presence of vg2svg and vg2png, which are the two main executables provided by vega. These executables can be used for generating SVG and PNG images, respectively.

However, upon closer inspection of the command output, we notice that the actual path to vg2png is different from what npm has suggested:

C:\Users\username\AppData\Roaming\npm\node_modules\vega\bin\vg2svg
C:\Users\username\AppData\Roaming\npm\node_modules\vega\bin\vg2png

The corrected path to vg2png is actually located within the node_modules/vega/bin directory.

Resolving Common Issues with v2png Installation

While installing vega and its dependency, canvas, on Windows may seem straightforward, there are some potential issues that you might encounter:

• Missing executables: Make sure to verify the presence of vg2svg and vg2png in the node_modules/vega/bin directory.
• Incorrect npm configuration: Ensure that your npm configuration is set correctly. You can check your npm configuration by running npm --version.

If you have installed vega correctly, but are still encountering issues with vg2png, try re-running the following commands to verify its installation:

ls -l $(npm config get prefix)/node_modules/vega/bin/vg2png

This command lists the files and directories within the vega installation directory.

If you still encounter issues, you can attempt to reinstall vega using the following command:

npm uninstall -g trifacta/vega
npm install -g trifacta/vega

Using v2png with R ggvis

Once you have verified that vg2png is correctly installed, you can proceed with using it in your R ggvis code. Here’s an example of how to use export_png() with the vg2png executable:

library(ggvis)

mtcars %>%
  ggvis(x = ~wt) %>%
  export_png(file = "plot.png")

In this example, we create a ggvis object from the mtcars dataset and then use the export_png() function to generate an image file named “plot.png” using the vg2png executable.

Conclusion

Installing vega and its dependency, canvas, on Windows may seem straightforward, but there are some potential issues that you might encounter. By following this guide, you should be able to successfully install vega and use it with your R ggvis code to generate high-quality images using the vg2png executable.

Keep in mind that the actual path to vg2png is different from what npm has suggested. Always verify its presence within the node_modules/vega/bin directory.

Last modified on 2023-07-23