Clumps | Clumps Items and XP together to reduce lag

Given is an initial raster

I'm currently making an HTML5 game, and I'm trying to draw various things onto the canvas. My game is basically just where you move around in an infinite area, but I can't figure out how to optimize my code to draw bushes onto the screen. It works properly, but It lags a lot and I know there's ways to optimize it. Here's my current code:

I want to create subsets of raster stacks and write them as new stacks when the difference between the previous layer and the next layer is all NA following each clump of the raster layers. Without clumps, I would achieve this by following Robert's answer in this question ( as below in script). However, I want to run this by considering the clumps too. There may be 1 or 2 clumps in each layer. So starting from layer 1 in the example data stack below, I want to identify the clumps numbers and for each clump, create a subset of raster stacks until there are no-overlapping pixels between the previous and next layers (i.e., the difference between the two layers is all NA). So I want is; starting from layer 1, for each clump, retain all the layers that have at least 1 common pixel between the previous and next layer, write them as a 1 stack, and move to the next. In the sample r_stk, I want to retain layers 1:8 for clump 1 (top) assign them as 1 stack, run for clump 2 (bottom), and again retain layers 1:5 assign them as a new stack, and so on. Below are the sample data and code that would work fine following this answer if there would be no clumps.

I have a table with two columns name and age. I want to keep the names clumped together but order the clumps by the clump containing the youngest age.

I have data that consists of roughly 100,000 points on a 2-d graph. Each point has X and Y coordinates. I'm looking for an algorithm that will cluster these points based on density but I want to specify the number of clusters.

I originally tried K-Means since this would allow me to specify the number of clusters. However, my data naturally "clumps" into ridges. K-Means would inevitably bisect some of these ridges. DBSCAN seems like a better fit simply due to the shape of my data, but with DBSCAN I can't specify the number of clusters I'd like.

Essentially what I'm trying to find is an algorithm that will optimally cluster the graph into N groups based on density. Where N is supplied by me. At this point I don't care where it's implemented (R, Python, FORTRAN...).

Any direction you can provide would be much appreciated.

I would like to remove the pixels that form a large cluster and keep only the small cluster to analyse (means get pixels number and locations). First I apply a filter to color in white all pixels that has a value lower to 0.66. Then I use the function clump() in R. The model works but I cannot remove only the large cluster. I do not understand how clump function works.

Initial image:

Results image: plot_r is the image where the pixels with value < 0.66 are changed to 0. plot_rc is the results after clump() function. As observed I cannot remove only the large cluster of pixels (on top of the image plot_r). I changed the value (700 in the code) but not better, how to do?

Here the code:

I am building a web app in Go. I have had no issues in this project until I attempted trying link my index.html file to a javascript file called index.js using:

A clump in an array is defined as a series of 2 or more adjacent elements of the same value. For example:

Considering starting to use git for source control, so I've looked at it a little bit. But one big question I have is about how to see one's entire source repository with git.

You know how with a TFS source repository, you can just look at your "Source Control Explorer" in visual studio, and see the entire repository and drill down into all of the source code for your organization? And, secondarily, if you want to (with repositories that are not excessively large anyway) you can pull down the entire repository to your local dev machine if you want to.

How does one do that type of thing with git? As far as I can see, there is no equivalent. Am I just missing something? It seems like with git, that you can only pull down "clumps" of your codebase at a time to work on it...