Can anybody let me know how I can compare two scans with different clusters in them. I have attached a picture showing both of the scans. I want to keep the clusters which are present in both the scans.
Assuming the two sets contain the same points ( possibly with some noise added), but one of the sets contains extra points.
It should then be fairly simple to check the distance from each point in set A to each point in set B. If there is any point within some radius can mark the point as part of both set A and B. This kind of search will probably benefit greatly from some kind of search structure, like a Kd-Tree, or some other optimization approach.
Without more details it is difficult to provide a more detailed suggestion.
Related
I am getting coordinates - lat/lon and I want to check if these coordinates are in the continental United States or not. Is there a easy way to do it in C#? I can convert the coordinates into MGRS or UTM.
Thanks!
Oh wow, they have it just for you:
http://econym.org.uk/gmap/states.xml
All the coords of the US states!
Build up a polygon and apply any polygon-contains-point algorithm.
The classic algorithm is ray-casting, and its even pretty simple. Let me know if you have any trouble with it.
Now, you have two options:
Use the data to build a polygon for each state, and check a point with each one of them. If none match, it is not in the US.
However, there is a problem with that approach - I don't know how the data was gathered, but its possible that there are very little gaps between states, or even slight overlaps. So if you only care if its generally in the US or not, I suggest the second approach:
Use the data to build a polygon for each state, and an algorithm to combine those polygons to one (like union). Save that polygon and use that as with the 1st approach.
I have two sets of points, A and B, and I'm trying to find the closest pair of points where one point is taken from each set. That is, if you were to use the points two draw to lines, I want the two points that allow me to draw the shortest line segment between the two lines.
Looking around, almost everything seems to deal with finding the closest points in 1 set. Although I did find one solution recommending voronoi tesselation to begin with, which seems a bit like overkill, I'm just looking for something a bit nicer than O(n^2).
If it helps, the two sets I'm comparing form lines, although they are not necessarily straight and I'm writing this in C#.
Thanks.
It should be possible to adapt the classical D&C algorithm (as described in the Wikipedia link), by processing all points together and tagging them with an extra bit.
The merging step needs to be modified to accept candidate left-right pairs with a member from every set only. This way, the recursive function will return the closest A-B pair. The O(N.Log(N)) behavior should be preserved.
If the "lines" you mention have a known equation so that point/line distances (or even line/line intersections) can be evaluated quickly, there could be faster solutions.
I wonder if there's any described algorithm that can convert isochrones into approximate area to show a range of some feature (in my problem this feature is a road network).
Example. I have something like on the image beneath:
It's a simple network (where I can arrive from the start point in X minutes or going Y kilometers). I have information of all the nodes and links. Now I need to create an isochrone map that show an approximate range where I can arrive.
Problems:
Convex hull - sucks because of too general approximation,
I can create buffors on roads - so I will get some polygon that shows range, but I will also have the holes by roads that connect into circles.
What I need to obtain is something like this:
I've found some potentially useful information HERE, but there are only some ideas how it could be done. If anyone has any concept, please, help me to solve my problem.
Interesting problem, to get better answers you might want to define exactly what will this area that shows the range (isochrone map) be used for? For example is it illustrative? If you define what kind of approximation you want it could help you solve the problem.
Now here are some ideas.
1) Find all the cycles in the graph (see link), then eliminate edges that are shared between two cycles. Finally take the convex hull of the remaining cycles, this together with all the roads, so that the outliers that do not form cycles are included, will give a good approximation for an isochrome map.
2) A simpler solution is to define a thickness around each point of every road, this thickness should be inversely proportional to how long it takes to arrive at that point from the starting point. I.e. the longer it takes to arrive at the point the less thick. You can then scale the thickness of all points until all wholes are filled, and then you will have an approximate isochrome map. One possible way of implementing this is to run an algorithm that takes all possible routes simultaneously from the starting point, branching off at every new intersection, while tracking how long it took to arrive at each point. During its execution, at every instant of time all previously discovered route should be thickened. At the end you can scale this thickness so as to fill all wholes.
Hopefully this will be of some help. Good luck.
I have solved the problem (it's not so fast and robust, but has to be enough for now).
I generated my possible routes using A* (A-Star) algorithm.
I used #Artur Gower's idea from point one to eliminate cycles and simplify my geometry.
Later I decided to generate 2 types of gemetries (1st - like on the image, 2nd - simple buffers):
1st one:
3. Then I have removed the rest of unnecessary points using Douglas-Peucker algorithm (very fast!).
4. In the end I used Concave Hull algorithm (aka Alpha-Shapes or Non-Convex Hull).
2nd one:
3. Apply a buffer to the existing geometry and take the exterior ring (JTS library made that really easier:)).
I have a CAD application, that allows user to draw lines and polygons and all that.
One thorny problem that I face is user drawing can be highly imprecise, for example, a user might want to draw two rectangles that are connected to each other. Hence there should be one line shared by two rectangles. However, it's easy for user to, instead of draw a line, draw two lines that are very close to each other, so close to each other that when look from the screen, you would be mistaken that they are the same line, except that they aren't when you zoom in a little bit.
My application would require user to properly draw the lines ( or my preprocessing must be able to do auto correction), or else my internal algorithm (let's call it The Algorithm) would not be able to process the inputs correctly.
What is the best strategy to combat this kind of problem? I am thinking about rounding the point coordinates to a certain degree of precision, but although I can't exactly pinpoint the problem of this approach, but I feel that this is not the correct way of doing things, that this will introduce a new set of problem.
Edit: For the sake of argument the snapping isn't an available option. For the matter, all sorts of "input-side" guidance are not available. The correction must be done via preprocessing on my code, when the drawing is finished, but just before I submit it to my algorithm.
Crazy restriction, you say. But a user can construct their input either in my application, or they can construct their input in other CAD software and then submit to my engine to do the calculation. I can't control how they input in other CAD software.
Edit 2:I can let user to specify the "cluster radius" to occur, but the important point is, I would need to make sure that my preprocessing algorithm is consistent and won't really introduce a new set of problem.
Any idea?
One problem I see is that your clustering/snapping algorithm would have to decide on its own which point to move onto which other point.
During live input snapping is simple: the first point stays put, the second point is snapped onto the first. If in offline mode you get a bunch of points that you know should be snapped together, you have no idea where the resulting point should lie. Calculate the average, possibly resulting in a completely new point? Choose the most central point out of all the candidates? Pick one at random? Try to align your point with some other points on the x/y/z-axis?
If your program allows any user interaction at all, you could detect point clusters that might be candidates for merging, and present the user with different merge target points to choose from.
Otherwise, you could make this kind of behaviour configurable: take a merge radius ("if two or more poins are within n units of one another...") and a merging algorithm ("... merge them into the most central of the points given") as parameters and read them from a config file.
Snapping points. User should be able to snap to end points (and many more) then, when you detect a snap, just change the point user clicked to snap point point. Check AutoCAD, functions line End, Middle and so on.
EDIT: If you want offline snapping then you just need to check every pair of points if they are near each other. The problem is that this in NP-problem so it will take a lot of time as you can't really get under O(n^2) time complexity. This algorithm you need should be under "clustering".
EDIT2: I think you shouldn't consider that input data is bad. But if you reallllllly want to do this, simples way is to take each point, check if there are other points in users defined radius, if yes find whole group that should merge into one point, find avg of coordinates of points and point all of them to that specific point. But remember - most designers KNOW what are snap points for and if they don't use them they have valid idea for that.
Your basic problem seems to me (I hope I understood correctly) to determine if two lines are the "same" line.
Out of my own experience your feeling is correct, rounding the coordinates in the input might prove not to be a good idea.
Maybe you should leave the coordinates in the input as they are but implement your function let's name it IsSameLine That you use in "The Algorithm" (who among others determines if two rectangles are connected if i understood your description correctly).
IsSameLine could transform the endpoints of the input lines from source coordinates to screen coordinates considering a certain (possibly configurable) screen resolution and check if they are the same in screen coordinates.
I.e. let's say you have an input file with the following extent (lowerleft) (upperRight) ((10,10), (24,53)). The question would be how far apart would be points (11,15) and (11.1, 15.1) if drawn at "zoom to extents" level on a 1600x1200 pixels screen. So you can determine a transform from source coordinates to "screen coordinates". You use then this transformation in IsSameLine as described above.
I'm not sure however this would be actually a good solution for you.
Another (maybe better?) possibility is to implement IsSameLine to return true if the points of the two lines are at maximum epsilon distance apart. The epsilon could have a default value computed based on the extent of the input vector data and probably it would be a good idea to give the user the possibility to give another value for it.
I found an interesting pairs matching game at http://xepthu.uhm.vn. The rule is simple, you have to find and connect two identical pokemon but the path between them is not blocked and the direction can't not be changed 3 times. Let's see an example:
I've think alot about the algorithm to check if the path between any 2 selected pokemon is valid but because I'm a newbie so I can't find any solution. Can you suggest me one in C#?
This is basically a path finding problem from graph theory. The fields in the grid are the nodes, and all adjacent fields are connected by an edge.
Path finding is a well-known problem, and there are many algorithms that solve this. Since your graph is quite small, the best solution here is probably just a brute force algorithm. A popular path finding algorithm is Dijkstra's algorithm.
Brute force: Start at some pokemon and explore all possible ways to see if one leads to an identical pokemon. You can stop exploring a way if the way is blocked or has more than 2 turns.
You'll need some "pointer" pointing to a field in the grid. The pointer can move left, right, up or down, provided that the field in that direction is not blocked. Move the pointer to an adjacent field. Remember where you came from and how many turns you made. Repeat this until you've reached your destination. Backtrack if the number of turns reaches 3. Make sure you don't run in circles.
Take a look at planar graphs. You will have to introduce a second condition: no more than four nodes may be traversed (start node - first direction change - second direction change - end node).