I've got a database of points (in this case, schools) and in my app, users search for the nearest ones to them. Under the hood, we're currently using ElasticSearch to filter by latlng (using Geo Distance, which gets the distance as the crow flies. For the majority of places, this works fine, but in some coastal areas, this will pick up places that are impossible to get to, in the example below, a radius of 20 miles will pick up schools in Weston-Super-Mare, in reality 55 miles:
I initially decided to use the Google Maps Distance Matrix API to filter my inital as the crow flies search, but there's a limit of 25 destinations per query, and as the requests will be dynamic and user-facing, it's not practical to parcel these requests up into small pieces and pop in a background job.
Is there any way to carry out these calculations while accounting for bodies of water on a database level? The schools are stored in a Postgres database, so I thoughts about using PostGIS and some kind of point in polygon query, but I have no idea where to start looking.
Any ideas are very much appreciated!
My first post here – hoping you can help me,
I want to design the intersection Traffic light simulation , I have data about number of vehicles every traffic light phase, and I already counting the length of the cycle lights on,
BUT I didn't know which algorithm can be used for modelling the traffic behavior
I am looking for an algorithm for such cases :
A. Number of vehicles data : (example)
North Path : 40 - 55 vehicles
South Path : 70 - 85 vehicles
East Path : 50 - 65 vehicles
West Path : 50 - 70 vehicles
I want to modelling the number of vehicles that appear in simulation on every path based on value of the random interval value
B. Direction of movement : (example)
North to South : 16 - 20 vehicles
North to West : 10 - 15 vehicles
North to East : 14 - 20 vehicles
and so on
Behaviors of every direction of vehicle movement use AI algorithm based on value of the random interval value
C. Behaviors :
The vehicle begins to slow down before stop if there is a vehicle in front of it or the red light is on
the vehicle will move to smaller queues than the queue in front of it
Have space between vehicles
using acceleration to the initial movement, and speed will be constant after that
If you're not sure where to start, you're probably going to need to start with some slightly simpler problems that you can combine together to get you to a final solution.
Perhaps the best place to start would be by trying to predict how many cars arrive at a light in one cycle? In such a case, you're going to need to know something about probability distributions and for low numbers that need to greater than or equal to 0, poisson distributions specifically.
If you're trying to predict which choice may be made by the driver of a car sitting at any given set of lights, based on measurements, the easiest approach may be to generate a discrete probability distribution (if drivers choices are uncorrelated) or Markov Chains (if they are correlated).
If you're trying to work out how single lights change colour (Green -> Amber, Amber -> Red, Red -> Green), you could model that as a State machine.
If you're trying to manage multiple sets of lights, particularly when those transitions can be driven by asynchronous events, your best bet is something like a discrete event simulation. If you're looking for a more formal description of the system as a whole you may need to move to Petri nets
If you care about the positions of the individual cars you may be able to model their positions (and transitions between positions) on a graph, where vertices are associated with a location. If you need to incorporate detailed information about geometry, dynamics, kinematics you are going to need detailed models of the cars and their interactions with the road surface (and potentially each other). This would be important if you wanted to model crashes within an intersections.
Just discovered this incredible library, but am a bit overwhelmed with all the options. Consider a visualization of players, let's say basketball players. We want to compare them across on a number of qualities, say passing, scoring, rebounding, etc.
On any given quality, we compare each players score relative to the other's. So if one player had 2 points while the other only had 1 point, the first player would get 66% and the other player 33%. If there scores were equal, they'd each get 50%.
The qualities, however, vary in importance. So now imagine each quality as a histogram bar. It's height will tell you how important that quality is relative to the other qualities, ie, relative to the other histogram bar. And each bar will be shaded half one color, half another color, showing you each player's relative score on that quality.
First Question: Could I create such a graph using D3? Could I make the histogram horizontal?
Is there a better way to visualize these two simultaneous comparisons?
Thanks!
EDIT:
I found this example which could work perfectly for my situations -- size of circles showing importance of quality, and division of circles into red/blue showing each player's score. But I can't figure out what kind of graph that is?
The bubble chart is a force directed layout of nodes, I don't think there is a special name for the fact that the nodes show a relationship between two data points. Maybe if Mike sees this he can let you know since he is the one that built the example for the Times.
There are quite a few tricks to get this to work, you can check out the code at http://graphics8.nytimes.com/newsgraphics/2012/09/04/convention-speeches/ac823b240e99920e91945dbec49f35b268c09c38/index.js which has thankfully been left unminified.
School going kids wear a certain uniform on respective days within a week.
(e.g. for boys = White half pant, white shirt, tie of a certain color, belt ..)
(e.g. for girls = blue checked frock, navy blue pinafore, black shoes with navy blue socks and belt). They will have different variations to wear on different days.
What would be a good way to show such information in the user interface for boys / girls. Can you point me to any sites which depict such information very clearly.
Show the uniforms graphically through images of a boy and a girl wearing the correct uniform for the selected day of the week. If you want to go all out, you could have 360 degree views (spinnable by mouse/gesture) for the boy and girl.
How about this kind of table, replace smiley's with uniform images and Description of the uniform below that.
Photo and text. It's absolutely enough for parents. May be not enough for designer...
It seems to me to be over-complicated to have a "uniform" that changes on a daily basis, to the point that you require an app which informs people what to wear. But given the requirements, I'd simply show the list of items for each day.
If, for example, there are only a couple combinations, I'd give each combination a name and put the combination name on the calendar. Then I'd make the name itself a link to further information about it, including the detailed list of clothes and pictures of each item. Perhaps a picture of a model wearing the clothes but that might not be necessary.
If the uniform varies a lot, such that enumerating the combinations is impractical or impossible, I'd show the full list (with pictures) for each day.
Aside, is this an actual requirement for a real school? My high-school had a uniform and it wasn't nearly so complicated. There was just a list of allowable/required elements and it was distributed to the parents before the start of the school year. Most of the time the rules could be stated in a couple sentences, such as "From the start of the school year until October 1st, and from Easter until the end of the school year, the 'Summer Uniform' may be worn; the rest of the school year only the standard uniform is permissible. The standard uniform is ... for boys and ... for girls.' This certainly was straightforward enough that there was never any serious question, and if there was a problem the teachers would simply inform the students that they were "out of uniform".
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 5 years ago.
Improve this question
I'm working on a Civilization-like game and I'm looking for a good algorithm for generating Earth-like world maps. I've experimented with a few alternatives, but haven't hit on a real winner yet.
One option is to generate a heightmap using Perlin noise and add water at a level so that about 30% of the world is land. While Perlin noise (or similar fractal-based techniques) is frequently used for terrain and is reasonably realistic, it doesn't offer much in the way of control over the number, size and position of the resulting continents, which I'd like to have from a gameplay perspective.
A second option is to start with a randomly positioned one-tile seed (I'm working on a grid of tiles), determine the desired size for the continent and each turn add a tile that is horizontally or vertically adjacent to the existing continent until you've reached the desired size. Repeat for the other continents. This technique is part of the algorithm used in Civilization 4. The problem is that after placing the first few continents, it's possible to pick a starting location that's surrounded by other continents, and thus won't fit the new one. Also, it has a tendency to spawn continents too close together, resulting in something that looks more like a river than continents.
Does anyone happen to know a good algorithm for generating realistic continents on a grid-based map while keeping control over their number and relative sizes?
You could take a cue from nature and modify your second idea. Once you generate your continents (which are all about the same size), get them to randomly move and rotate and collide and deform each other and drift apart from each other. (Note: this may not be the easiest thing ever to implement.)
Edit: Here's another way of doing it, complete with an implementation — Polygonal Map Generation for Games.
I've created something similar to your first image in JavaScript. It's not super sophisticated but it works :
http://jsfiddle.net/AyexeM/zMZ9y/
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>Untitled Document</title>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.7.2/jquery.min.js"></script>
<style type="text/css">
#stage{
font-family: Courier New, monospace;
}
span{
display: none;
}
.tile{
float:left;
height:10px;
width:10px;
}
.water{
background-color: #55F;
}
.earth{
background-color: #273;
}
</style>
</head>
<body>
<div id="stage">
</div>
<script type="text/javascript">
var tileArray = new Array();
var probabilityModifier = 0;
var mapWidth=135;
var mapheight=65;
var tileSize=10;
var landMassAmount=2; // scale of 1 to 5
var landMassSize=3; // scale of 1 to 5
$('#stage').css('width',(mapWidth*tileSize)+'px');
for (var i = 0; i < mapWidth*mapheight; i++) {
var probability = 0;
var probabilityModifier = 0;
if (i<(mapWidth*2)||i%mapWidth<2||i%mapWidth>(mapWidth-3)||i>(mapWidth*mapheight)-((mapWidth*2)+1)){
// make the edges of the map water
probability=0;
}
else {
probability = 15 + landMassAmount;
if (i>(mapWidth*2)+2){
// Conform the tile upwards and to the left to its surroundings
var conformity =
(tileArray[i-mapWidth-1]==(tileArray[i-(mapWidth*2)-1]))+
(tileArray[i-mapWidth-1]==(tileArray[i-mapWidth]))+
(tileArray[i-mapWidth-1]==(tileArray[i-1]))+
(tileArray[i-mapWidth-1]==(tileArray[i-mapWidth-2]));
if (conformity<2)
{
tileArray[i-mapWidth-1]=!tileArray[i-mapWidth-1];
}
}
// get the probability of what type of tile this would be based on its surroundings
probabilityModifier = (tileArray[i-1]+tileArray[i-mapWidth]+tileArray[i-mapWidth+1])*(19+(landMassSize*1.4));
}
rndm=(Math.random()*101);
tileArray[i]=(rndm<(probability+probabilityModifier));
}
for (var i = 0; i < tileArray.length; i++) {
if (tileArray[i]){
$('#stage').append('<div class="tile earth '+i+'"> </div>');
}
else{
$('#stage').append('<div class="tile water '+i+'"> </div>');
}
}
</script>
</body>
</html>
I'd suggest you back up and
Think about what makes "good" continents.
Write an algorithm that can tell a good continental layout from a bad one.
Refine the algorithm so that you can quantify how good a good layout is.
Once you have that in place, you can start to implement an algorithm which should be shaped like this:
Generate crappy continents and then improve them.
For improvement you can try all sorts of standard optimization tricks, whether it's simulated annealing, genetic programming, or something completely ad hoc, like moving a randomly chosen edge square from whereever it is on the continent to the edge opposite the continent's center of mass. But the key is to be able to write a program that can tell good continents from bad ones. Start out with hand-drawn continents as well as your test continents, until you get something you like.
I wrote something similar to what you're after for an automated screensaver-style clone of Civilization 1. For the record I wrote this in VB.net but since you don't mention anything about language or platform in your question I'll keep it abstract.
The "map" specifies the number of continents, continent size variance (eg 1.0 would keep all continents with the same approximate land area, down to 0.1 would allow continents to exist with 1/10th the mass of the largest continent), maximum land area (as a percentage) to generate, and the central land bias. A "seed" is distributed randomly around the map for each continent, weighted towards the centre of the map as per the central bias (eg a low bias produces distributed continents more similar to Earth, where as a high central bias will resemble more of a Pangaea). Then for each iteration of growth, the "seeds" assign land tiles according to a distribution algorithm (more on that later) until a maximum land area has been reached.
The land distribution algorithm can be as precise as you want but I found more interesting results applying various genetic algorithms and rolling the dice. Conway's "Game of Life" is a really easy one to start out with. You'll need to add SOME globally aware logic to avoid things like continents growing into each other but for the most part things take care of themselves. The problem I found with more fractal-based approaches (which was my first inclination) was the results either looked too patterned, or lead to too many scenarios requiring hacky-feeling workaround rules to get a result which still didn't feel dynamic enough. Depending on the algorithm you use, you may want to apply a "blurring" pass over the result to eliminate things like abundant single-square ocean tiles and checkered coastlines. In the event something like a continent being spawned surrounded by several others and having nowhere left to grow, relocate the seed to a new point on the map and continue the growth passes. Yes, it can mean you sometimes end up with more continents than planned, but if it's really something you firmly don't want then another way to help avoid it is bias the growth algorithms so they favour growth in the direction with least proximity to other seeds. At worst (in my opinion anyway), you can flag a series as invalid when a seed has nowhere left to grow and generate a new map. Just make sure you set a maximum number of attempts so if anything unrealistic is specified (like fitting 50 even-weighted continents on a 10x10 board) it doesn't spend forever trying to find a valid solution.
I can't vouch for how Civ etc do it, and of course doesn't cover things like climate, land age etc but by playing around with the seed growth algorithm you can get pretty interesting results that resemble continents, archipelagos etc. You can use the same approach to produce 'organic' looking rivers, mountain ranges etc too.
Just thinking off the cuff here:
Pick some starting points, and assign each a randomly drawn (hoped for) size. You can can maintain a separate size draw for planned continents and planned islands if you want.
Loop over the land elements, and where they are not yet at the planned size add one square. But the fun part is weighing the chance that each neighboring element will be the one. Some suggested thing that might factor in:
Distance to the nearest "other" land. Further is better generates wide oceanic spaces. Nearer is better makes narrow channels. You have to decide if you're going to let bits merge as well.
Distance from the seed. Nearer is better means compact land masses, farther is better means long strung out bits
Number of existing land squares adjacent. Weighting in favor of many adjacent squares gives you smooth coast, preferring few gives you lots of inlets and peninsulas.
Presence of "resources" squares nearby? Depends on the game rules, when you generate resource square, and if you want to make it easy.
Will you allow bits to approach or join with the poles?
??? don't know what else
Continue until all land masses have reached the planned size or can't grow anymore for some reason.
Notice that diddling the parameter to these weighting factors allows you to tune the kind of world generated , which is a feature I liked about some of the Civs.
This way you'll need to do terrain generation on each bit separately.
You could try a diamond square algorithm or perlin noise to generate something like a height map. Then, assign ranges values to what shows up on the map. If your "height" goes from 0 to 100, then make 0 - 20 water, 20 - 30 beach, 30 - 80 grass, 80 - 100 mountains. I think notch did something similar to this in minicraft, but I'm not an expert, I'm just in a diamond square mindset after finally getting it working.
I think you can use "dynamic programming" style approach here.
Solve small problems first and combine
solutions smartly to solve bigger
problem.
A1= [elliptical rectangular random ... ]// list of continents with area A1 approx.
A2= [elliptical rectangular random ... ]// list of continents with area A2 approx.
A3= [elliptical rectangular random ... ]// list of continents with area A3 approx.
...
An= [elliptical rectangular random ... ]// list of continents with area An approx.
// note that elliptical is approximately elliptical in shape and same for the other shapes.
Choose one/more randomly from each of the lists (An).
Now you have control over number and area of continents.
You can use genetic algorithm for positioning them
as you see "fit" ;)
It will be very good to take a look at some "Graph Layout Algorithms"
Force Based Algorithms
Genetic Algorithm for Graph Layout
You can modify these to suit your purpose.
I had an idea for map creation similar to the tectonic plates answer. It went something like this:
sweep through the grid squares giving each square a "land" square if rnd <= 0.292 (the actual percentage of dry land on planet earth).
Migrate each land chunk one square toward its nearest larger neighbour. If neighbours are equidistant, go toward the larger chunk. If chunks are equal size, choose one randomly.
if two land squares touch, group them into a chunk, moving all squares as one from now on.
repeat from step 2. Stop when all chunks are connected.
This is similar to how gravity works in a 3D space. It's pretty complicated. A simpler algorithm for your needs would work as follows:
Drop in n starter land squares at random x,y positions and acceptable distances from each other. These are seeds for your continents. (Use the Pythagorean theorem to ensure the seeds have a minimum distance between themselves and all others.)
spawn a land square from an existing land square in a random direction, if that direction is an ocean square.
repeat step 2. Stop when land squares fill 30% of total map size.
if continents are close enough to each other, drop in land bridges as desired to simulate a Panama type effect.
Drop in smaller, random islands as desired for a more natural look.
for each extra "island" square you add, cut out inland seas and lake squares from the continents using the same algorithm in reverse. This will maintain the land percentage at the desired amount.
Let me know how this works out. I've never tried it myself.
PS. I see this is similar to what you tried. Except it sets up all the seeds at once, before beginning, so the continents will be far enough apart and will stop when the map is sufficiently filled.
I haven't actually tried this but it was inspired by David Johnstone's answer regarding tectonic plates. I tried implementing it myself in my old Civ project and when it came to handling collisions I had another idea. Instead of generating tiles directly, each continent consists of nodes. Distribute mass to each node then generate a series of "blob" continents using a 2D metaball approach. Tectonics and continental drift would be ridiculously easy to "fake" simply by moving the nodes around. Depending on how complex you want to go, you could even apply things like currents to handle the node movement and generate mountain ranges that correspond to plate boundaries overlapping. Probably wouldn't add that much to the gameplay side of things, but it could make for an interesting map generation from a purely academic perspective :)
A good explanation of metaballs if you haven't worked with them before:
http://www.gamedev.net/page/resources/_//feature/fprogramming/exploring-metaballs-and-isosurfaces-in-2d-r2556
Here's what I'm thinking, since I'm about to implement something like this that I have for a game in development. :
The world divided into regions. depending on the size of the world, it will determine how many regions. For this example, we'll assume a medium sized world, with 6 regions. Each grid zone breaks into 9 grid zones. those grid zones break into 9 grids each. (this is not for character movement, but merely for map creation) The Grids are for biomes, grid zones are for over arching land features, (continent vs ocean) and the regions are for overall climate. The grids break down into tiles.
Randomly generated, the regions get assigned logical climate sets. Grid zones get randomly assigned to, for instance; ocean or land. Grids get assigned biomes randomly with modifiers based on their grid zones and climate, these being forest, desert, plains, glacial, swamp or volcanic. Once all those basics are assigned, it's time to blend them together, using a random percentage based function that fills in tile sets. For example; if you have a forest biome, next to a desert biome, you have an algorithm that decreases the likely hood that a tile will be "foresty" and increases that it will be "deserty." So, about half way between them, you'll see a sort of blended affect combining the two biomes to off a somewhat smooth transition between them. Transition from one grid zone to the next would probably take a little more work to insure logic landmass formations.Like, for example, a biome from one grid zone that touches the biome from another, instead of having a simple switching percentage based on proximity. For example, there are 50 tiles from the center of the biome to the edge of the biome, meaning, there are 50 from the edge it touches to the center of the next biome. That would logically leave a 100% change from one biome to the next. So as the tiles get nearer to the border of the two biomes, the percentage narrows out to around 60% or so. It'd, I think, be unwise to give too much probability of crossing biomes far from the border, but you'll want the border to be somewhat blended. For the grid zones, the percentage change will be much more pronounced. Instead of the % going down to around 60%, it'd only drop down to around 80%. And a secondary check would then have to be performed to ensure that there's not a random water tile in the middle of a land biome next to the ocean without some logic to it. So, either, connect that water tile to the ocean mass to make a channel to explain the water tile, or remove it altogether. Land in a water based biome is easier to explain using rock outcrops and such.
Oh, kinda dumb, sorry.
I'd place fractal terrain according to some layout that you know "works" (e.g. 2x2 grid, diamond, etc, with some jitter) but with a Gaussian distribution damping peaks down towards the edges of the continent centers. Place the water level lower so that is mostly land until you get near the edges.