treer | commandline tool to generate directory structure tree | File Utils library

Apparently by converting Minus Integer to Date help the trick, in this case (-2910983) from the year 1970 is -6000, therefore a sequence of 1 Year will help and then finally converted to Date

First raster::projectRaster does not "set" the projection but, rather reprojects the raster given a transformation and resampling. Given the computational requirements of this it is much faster to reproject the point data using sp::spTransform. Once your data is in the same projection space, you can use raster::extract to extract the raster values. Values out side the raster or in nodata (NA) areas will be assigned NA values. You can drop these observations using a simple NA index with which.

It looks like your data may have a constant value outside of the permafrost. Once you identify what this value is (eg., 0) you can remove these points as well. Here is a worked example. First we add packages and create some example data that is similar to yours.

The problem isn't with v@polygons[c(1:3,6)] but rather in the attempt to apply @Polygons[[1]]@coords directly to the resulting list. instead, you could use lapply() on v@polygons[c(1:3,6)] like this:

How can it do that? I thought it would just be 1 core!

The fact that you see all your cores being used doesn't mean your code execution is parallel. We can see from the implementation it's sequential, but we don't know which CPU our single thread will get scheduled on by the OS on each cycle.

When you execute a method inside a thread, the OS decides how many CPU time slices it will get and when, according to a priority queue it manages.

To see that your algorithm may run on different cores we can ask the OS on which logical core it's currently executing our thread. I've prepared a small implementation for Windows, which has a native WinAPI method called GetCurrentProcessorNumber() which returns the processor number we're executing on. We'll use JNA for the example:

build.sbt: