distances | R package with tools for distance metrics

I have a P array which represents 6 forces (weights):

I have two tables: one has a list of weather stations near major cities and the distance to the city, and the other has weather averages for each weather station. I want to do a join such as showing weather data from the station closest to San Francisco.

Example table distances:

I have a large DataFrame of distances that I want to classify.

• pyspark 2.1.0

I have two dataframes with the following structures:

dataframe 1:

I want to create a coloured map using an equation, like sound propagation. Basically i want to put the source in the middle of the map (or anywhere) and proyect how the intensity dicrease in relation with the distance from the source.

I have n points in a 3D space. I want to stochastically sample a subset of points with all nearest-neighbor distances larger than r. The size of the subset m is unknown, but I want the sampled points to be as dense as possible, i.e. maximize m.

There are similar questions, but they are all about generating points, rather than sampling from given points.
Generate random points in 3D space with minimum nearest-neighbor distance

Generate 3-d random points with minimum distance between each of them?

Say I have 300 random 3D points,

I would like to voxelise a .stl file and write it into an np.array. The resolution of the voxels should be adjustable. Here is my code for this:

So what I want in theory is pretty simple. I want create something where you:

1. have 2 lines that the user draws
2. have code that take the first line and take the 2 points from it
3. take the other lines 2 points
4. takes the first point from the first line and compares it to the 2 points from (let's call it) line 2
5. does the same for the 2nd point of line 1
6. and draws line connecting the points the first point of line 1 to the closest point of line 2, then drawing the 2nd point of line one to the last one (of line 2).

Sounds a bit complicated, but probably because I'm bad a explaining things.

The code I have for this is here I also just want to add that the function "draw_line()" just takes the inputs of "start_pos", and "end_pos" so it doesn't matter what order the inputs are put in. Also "y2, y1" is the starting point or, 1st, and z is the 2nd.

How can I efficiently calculate distances between (almost) consecutive rows of a large-ish (~4m rows) of a data.table? I've outlined my current approach, but it is very slow. My actual data has up to a few hundred columns. I need to calculate lags and leads for future use, so I create these and use them to calculate distances.