Here is draft two of my great circle arcs R animation. This time I focused on improving the smoothness of the lines and removing some buggy line behavior, keeping it on a flat map for now. As with DRAFT 1, the YouTube video is of significantly reduced quality, to the point that you will see zero improvement. It’s really not even worth watching there. A much higher quality source video is available here. It can be downloaded (~90 MB) and viewed locally using a standard video player such as VLC.
Here is the YouTube version if you must:
Recently I have shared examples of animations made using R which feature traversal of pathways, specifically grid cell borders and great circle arcs. Here I provide the basic code required to generate a path sequence from a path.
[Alpha] and [beta] versions of a simple R Shiny web application showing projected climate trends for various Alaska and western Canada communities is available. Since this probably sounds like the hundredth rendition of the same thing to regular blog readers, I’ll just mention that this offers some updated data, downscaled CRU 3.2 and CMIP5 global climate model outputs.
More fun with great circle arcs. Who doesn’t love a good great circles graphic? This time, however, it is an animation. Using R, not only have I animated path traversal along great circle arcs, but I’ve also projected them onto a three dimensional global surface. It was not without its challenges. And yes, the title indicates there will be more and better to come.
With the high number of thin, rapidly moving arcs, and color and transparency shifts from frame to frame, this video essentially also serves as a demonstration of ways in which a video can be significantly reduced in quality when re-encoded on upload to sites like YouTube and Vimeo for streaming purposes. A much higher quality source video is available here. It can be downloaded (~100 MB) and viewed locally using a standard video player such as VLC.
A simple app for mapping estimates of Alaska sea ice edge during different months, years, and decades is now formally available. I made this app in R about six months ago and shared an earlier version on Twitter. I have cleaned up the code a bit. Most notably, it now offers somewhat more adaptive color options for a variable number of factor levels.
All of my Shiny apps have been upgraded to Bootstrap 3 now that this is available in the Shiny package. The apps have also been relocated from their temporary home on RStudio’s Spark server to SNAP. Most people have been using and referencing the permanent SNAP urls, which redirected to Spark previously, but which are now pointing to SNAP again. Nevertheless, the Spark urls have propagated about the internet a bit. Please make sure to stick with
shiny.snap.uaf.edu/appName/ url format.
A convenient place to access all my publicly available apps is my leonawicz.github.io page. There are a couple apps there which you cannot run (
cmip3_cmip5, specifically) because they are only available from within the university domain. However, the vast majority of the apps are public, and for those few which are not I still include them in the page so that you may access the R code on Github. These still show a “Launch” button. I will tidy that up soon to remove any confusion.
The previous post on gridded data animation was fairly basic; very cool in its potential, but anticlimactic in isolation. Here I am ignoring the data altogether. Instead, I focus on simulating paths along the borders of the grid cells for a cool visual effect.