Segmenting SpatialPolygons

Both SpatialPolygons and SpatialPolygons consist of list of Polygons. Each of these Polygons in turn consist of vertices, i.e., the points where the edges of the polygon meet. When you transform a SpatialPolygons(DataFrame) to a different projection (e.g., from long-lat coordinates to UTM) with the spTransform-function, actually only the vertices are transformed (and not the lines connecting them). This means that also in the new projection straight lines are drawn between the vertices, whereas in reality they should be curved (due to the quasi-spherical shape of our world). For most shapes this isn't much of an issue. But when your shape covers a large area, you could run into serious problems.

This problem can be solved by adding more vertices to the polygons. In other words, add new vertices by interpolating between the existing vertices. If you do this before re-projecting, the new projection will be a lot more accurate. I tried to find an existing package in R that would do this, but I could not find any (please leave a comment if you did find an alternative). Therefore, I've written a small function to take care of this myself, which I will demonstrate in this post.

The source code of this function and the accompanying example is given below. This code is also used to produced the graphical illustration below. Note how the red line crosses the islands Northeast of Scotland in the original projection. Compare this with the new projection of the red lines with and without segmentation. Also note that the red lines in the new projection are straight when we don't apply segmentation, and they are curved (as they are supposed to be) when we do apply segmentation.

The segmentation is achieved relatively simple by looping all the lists of Polygons with the lapply function and then looping each line segment with the apply function (see R script below). The new vertices are derived via linear interpolation using the approx function. You could go for something more fancy like spline interpolation, but linear will do just fine in this example. As I've implemented all this in the function named ‘SPSegmentation’, you can simply call it on any SpatialPolygons or SpatialPolygonsDataFrame object you would like. With some modifications, you could also use this function of SpatialLines and SpatialLinesDataFrame objects.

In case you want to achieve the opposite (i.e., reduce the number of vertices in a SpatialPolygons(DataFrame)), you can use the gSimplify function from the rgeos package. This uses a Ramer–Douglas–Peucker algorithm to simplify the shape, which could save you some computing time, but your shape will also become less detailed as a result.

ProTrackR: chiptunes in R (part three)

It has been a while but I've made some small progress on the ProTrackR package. Many bugs are fixed and some functionality is added. This is making tracking in R more and more easy and fun. As if developing a package for handling ProTracker modules isn't the nerdiest thing ever, I found a way to top it off. What if I combine the ProTrackR package with a Shiny interface? Well, you'll get a basic online tracker.

For more information you can also read parts one and two on ProTrackR.

Fixing a function

Sometimes R functions are not always doing exactly what you want. In that case you could try to look up the source code for that function paste it into your code and make your modifications there. But sometimes it takes only a small tweak and you want to keep your code as clean as possible. For me this was the case for the vuong test in the pscl package. This function only prints the output, but does not return it. This can easily be fixed by converting the function into text with the ‘deparse’ function. Then the ‘print’ statement can be replaced by a ‘return’ statement by using ‘gsub’. Now the modified text can be turned into a function again by calling ‘eval’ and ‘parse’. With this hack the new function will return the output I need. The code below shows you all described in this post. Go ahead and mutate functions just like that...