NGon | ASP.NET MVC variables in JS | Application Framework library

Passing the scene as an argument to the function seems to work, actually... it was not working when I was using mesh as the first call (giving a bunch of Warning: No strict ticks found and an ERROR: MethodError: no method matching _default(::Observable{Scene}, ::GLMakie.GLAbstraction.Style{:default}, ::Dict{Symbol,Any}))

However,

This problem occurs when the z-index value is lesser than the adjacent item. you can simply solve it by adding z-index:99 (or some other value) on the .col-sm-3:hover event.

Please see the code below:

The algorithm you want is a Voronoi Diagram. The essential description of the algorithm is such:

1. Generate a list of random points on a plane (or get the points as input from somewhere).
2. Create a geometric map of n-gons that represent all the space in the plane closest to each point.

The resulting graph will look something like this (stylized and colored):

The look and shape of the n-gons depend on the spacing of the points. You can play with different point distributions or generation methods to get a Voronoi Diagram with particular characteristics. You can also play with the n-gons themselves, for example you can treat the boundaries as fuzzy approximations, blending or leaving gaps between adjacent n-gons:

There are a ton of cool things you can do with a Voronoi Diagram, and pretty much every programming language has libraries that can compute one very quickly. For example, one of the interactive examples for Paper.js is a dynamically generated Voronoi Diagram where one of the points is the location of the cursor. Here's another example where someone uses Voronoi Diagrams as one of the steps for procedural terrain generation. Yet another example is a Voronoi Diagram using the locations of all the airports in the world, which you could use to find the closest airport to any location on the planet.

One such library in Javascript is d3-voronoi, though like I said, there are quite a few libraries out there, not to mention a gazillion tutorial articles on how to implement it yourself should you decide to go that route.

1. To sort each component, use lapply:

   sorted <- lapply(x, sort, decreasing = TRUE)

2. To convert the tables to dataframes, use as.data.frame. This gives you a list of dataframes, then changes the names:

   df <- lapply(sorted, as.data.frame) names(df) <- paste0("df_", names(sorted))

   If you also want these as separate variables (which is probably not a good idea), you could use

   for (n in names(df)) assign(n, df[[n]])

3. To get the head of each element of the list, use lapply again:

   lapply(df, head)

   This gives output starting out as

   $df_brand Var1 Freq 1 Nissin 381 2 Nongshim 98 3 Maruchan 76 4 Mama 71 5 Paldo 66 6 Myojo 63

   $df_style Var1 Freq 1 Pack 1531 2 Bowl 481 3 Cup 450 4 Tray 108 5 Box 6 6 2

try this

First I will say that using javascript will be longer than if you use some symbolic representation language like Latex. It is designed to do graphical representations with the minimum of fuss. The actual code base that makes it work is substantial but hidden for the general user.

As the content for the canvas is stored in the DOM it also a good idea to store as much information as you can in the DOM, the colors, fonts, etc can all be stored in an element`s dataset.

For this I have put the settings in the ordered list. It contains all the settings, but there is also a default set of settings in the rendering function. The elements dataset will overwrite the defaults, or you can not add any dataset properties and let it all use the defaults.

In the example below I have only put a minimum of vetting. People tend to put quotes around everything in the DOM as numbers can sometimes not work if represented as a string, I force all the numbers to the correct type. Though to be safe I should have checked to see if indeed they are valid numbers, the same for the other settings. I have just assumed that they will be correctly formatted.

All the work is done in a function, you pass it the query string needed to find the list and canvas. It then uses the list items to render to the canvas.

As the canvas size is not always known (it could be scaled via CSS) you need to have some way to specify size independent of pixels. For this I use a relative size. Thus the font size is as a fraction of the canvas size eg data-font-size = 16 means that the font will be 1/16th of the canvas height. The same for the line width, and the dash size is a multiple of the line width. eg data-line-dash = 4 means that the dashes are 4 times the length of the line width.

To use data set you add the property to the element in the HTML prefixed with the word data- then the property name/s separated by "-". In javascript you can not use "-" directly as part of a variable name (it's a subtract operator) so the property names are converted to camelcase (the same as CSS properties), and stored in the element's dataset property.

The compiler has no way of knowing what you're calling. I suggest making the names more descriptive like so:

You could use find_by to fetch the record for a specific name for both Food and Category models, and get their id values; for example: