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  • Worst Case number of rotations for BST to AVL algorithm?

    - by spacker_lechuck
    I have a basic algorithm below and I know that the worst case input BST is one that has degenerated to a linked list from inserts to only one side. How would I compute the worst case complexity in terms of number of rotations for this BST to AVL conversion algorithm? IF tree is right heavy { IF tree's right subtree is left heavy { Perform Double Left rotation } ELSE { Perform Single Left rotation } } ELSE IF tree is left heavy { IF tree's left subtree is right heavy { Perform Double Right rotation } ELSE { Perform Single Right rotation } }

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  • Scheduling algorithm optimized to execute during low usage periods.

    - by The Rook
    Lets say there is a Web Application serving mostly one country. Because of normal sleep habits website traffic follows a Sine wave, where 1 period lasts 24 hours and the lowest part of the wave is at about midnight. Is there a scheduling algorithm optimized to execute during low usage periods? I am thinking of this as a liquid that is "pored into" this sine wave to flatten out resource usage. A ideal algorithm would take the integral of this empty space. If the same tasks need to be run daily the amount of resources consumed by previous executions could be used to predict future usage by looking at the rate in which resource usage is increasing. By knowing the amount of resources required this algorithm could fill in this empty space while leaving as much buffer as possible on either side such that its interference was reduced as much as possible. It would also be possible to detect if there isn't enough resources before execution begins, this opens the door for a cloud to help out. Does anything like this exist? Or should I build it into an existing scheduler like quartz and make it open source?

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  • Algorithm to pick values from set to match target value?

    - by CSharperWithJava
    I have a fixed array of constant integer values about 300 items long (Set A). The goal of the algorithm is to pick two numbers (X and Y) from this array that fit several criteria based on input R. Formal requirement: Pick values X and Y from set A such that the expression X*Y/(X+Y) is as close as possible to R. That's all there is to it. I need a simple algorithm that will do that. Additional info: The Set A can be ordered or stored in any way, it will be hard coded eventually. Also, with a little bit of math, it can be shown that the best Y for a given X is the closest value in Set A to the expression X*R/(X-R). Also, X and Y will always be greater than R From this, I get a simple iterative algorithm that works ok: int minX = 100000000; int minY = 100000000; foreach X in A if(X<=R) continue; else Y=X*R/(X-R) Y=FindNearestIn(A, Y);//do search to find closest useable Y value in A if( X*Y/(X+Y) < minX*minY/(minX+minY) ) then minX = X; minY = Y; end end end I'm looking for a slightly more elegant approach than this brute force method. Suggestions?

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  • Linear Interpolation. How to implement this algorithm in C ? (Python version is given)

    - by psihodelia
    There exists one very good linear interpolation method. It performs linear interpolation requiring at most one multiply per output sample. I found its description in a third edition of Understanding DSP by Lyons. This method involves a special hold buffer. Given a number of samples to be inserted between any two input samples, it produces output points using linear interpolation. Here, I have rewritten this algorithm using Python: temp1, temp2 = 0, 0 iL = 1.0 / L for i in x: hold = [i-temp1] * L temp1 = i for j in hold: temp2 += j y.append(temp2 *iL) where x contains input samples, L is a number of points to be inserted, y will contain output samples. My question is how to implement such algorithm in ANSI C in a most effective way, e.g. is it possible to avoid the second loop? NOTE: presented Python code is just to understand how this algorithm works. UPDATE: here is an example how it works in Python: x=[] y=[] hold=[] num_points=20 points_inbetween = 2 temp1,temp2=0,0 for i in range(num_points): x.append( sin(i*2.0*pi * 0.1) ) L = points_inbetween iL = 1.0/L for i in x: hold = [i-temp1] * L temp1 = i for j in hold: temp2 += j y.append(temp2 * iL) Let's say x=[.... 10, 20, 30 ....]. Then, if L=1, it will produce [... 10, 15, 20, 25, 30 ...]

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  • Dynamically creating astar node map by triangular polygonal map

    - by jett
    My game's map format uses a bunch of triangles to make up the platforms and terrain in 2d. Right now I can set up a 2d array of nodes for the astar algorithm that basically is a bunch of rectangles across the maps x and y that can be set to "wall" if the a* algorithm should try to go around it. However I want a function in the map loader to create the node overlay if the nodes are not specified. I was thinking if more than n percent of the a* rectangle overlaid on map was filled by polygons I could mark that entry in the array as "wall". However I'm stuck on how to do this(or even start) where/when the triangles can be overlapping and also of variable size.

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  • Algorithm to optimize grouping

    - by Jeroen
    I would like to know if there's a known algorithm or best practice way to do the following: I have a collection with a subcollection, for example: R1 R2 R3 -- -- -- M M M N N L L A What i need is an algorithm to get the following result: R1, R2: M N L R2: A R3: M This is -not- what i want, it has more repeating values for R than the above: R1, R2, R3: M R1, R2: N L R2: A I need to group in way that i get the most optimized groups of R. The least amount of groups of R the better so i get the largest sub collections. Another example (with the most obvious result): R1 R2 R3 -- -- -- M M A V V B L L C Should result in: R1, R2: M V L R3: A B C I need to do this in LINQ/C#. Any solutions? Tips? Links?

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  • Collision detection of convex shapes on voxel terrain

    - by Dave
    I have some standard convex shapes (cubes, capsules) on a voxel terrain. It is very easy to detect single vertex collisions. However, it becomes computationally expensive when many vertices are involved. To clarify, currently my algorithm represents a cube as multiple vertices covering every face of the cube, not just the corners. This is because the cubes can be much bigger than the voxels, so multiple sample points (vertices) are required (the distance between sample points must be at least the width of a voxel). This very rapidly becomes intractable. It would be great if there were some standard algorithm(s) for collision detection between convex shapes and arbitrary voxel based terrain (like there is with OBB's and seperating axis theorem etc). Any help much appreciated.

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  • Is there an algorithm for a pool game?

    - by Dmitri
    Hello! I am looking for algorithm to calculate direction and speed of balls in a pool game. I am sure there has to be some type of open source code for this since pool games are some of the oldest computer games I can remember. I mean, when one ball hits another, I need a algorithm to calculate direction of both of them. It will depend of exact angle of where they hit each other and on speed. I want to practice Java coding, so I am looking for java code or package that has this type of code.

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  • Complex algorithm for complex problem

    - by Locaaaaa
    I got this question in an interview and I was not able to solve it. You have a circular road, with N number of gas stations. You know the ammount of gas that each station has. You know the ammount of gas you need to GO from one station to the next one. Your car starts with 0. The question is: Create an algorithm, to know from which gas station you must start driving. As an exercise to me, I would translate the algorithm to C#.

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  • 2D Grid Map Connectivity Check (avoiding stack overflow)

    - by SombreErmine
    I am trying to create a routine in C++ that will run before a more expensive A* algorithm that checks to see if two nodes on a 2D grid map are connected or not. What I need to know is a good way to accomplish this sequentially rather than recursively to avoid overflowing the stack. What I've Done Already I've implemented this with ease using a recursive algorithm; however, depending upon different situations it will generate a stack overflow. Upon researching this, I've come to the conclusion that it is overflowing the stack because of too many recursive function calls. I am sure that my recursion does not enter an infinite loop. I generate connected sets at the beginning of the level, and then I use those connected sets to determine connectivity on the fly later. Basically, the generating algorithm starts from left-to-right top-to-bottom. It skips wall nodes and marks them as visited. Whenever it reaches a walkable node, it recursively checks in all four cardinal directions for connected walkable nodes. Every node that gets checked is marked as visited so they aren't handled twice. After checking a node, it is added to either a walls set, a doors set, or one of multiple walkable nodes sets. Once it fills that area, it continues the original ltr ttb loop skipping already-visited nodes. I've also looked into flood-fill algorithms, but I can't make sense of the sequential algorithms and how to adapt them. Can anyone suggest a better way to accomplish this without causing a stack overflow? The only way I can think of is to do the left-to-right top-to-bottom loop generating connected sets on a row basis. Then check the previous row to see if any of the connected sets are connected and then join the sets that are. I haven't decided on the best data structures to use for that though. I also just thought about having the connected sets pre-generated outside the game, but I wouldn't know where to start with creating a tool for that. Any help is appreciated. Thanks!

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  • Algorithm to Solve Most of a Problem

    - by Mike G
    I need an Algorithm/Design Pattern that allows me to try to get the maximum number of rules followed. So I have a couple teams and I need to pair them with a referee and against each other into a round robin. There a rules on who can compete with who and who can judge who so I need to find the configuration that satisfies the most of these. Some rules are more important than others and are "worth more" when evaluating "what satisfies the most of them" There probably isn't a algorithm for this, but is there a design pattern that could help me maximize my chances of finding this configuration?

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  • Text comparison algorithm using java-diff-utils

    - by java_mouse
    One of the features in our project is to implement a comparison algorithm between two versions of text and provide a % change between the two versions. While I was researching, I came across google java-diff-utils project. Has anyone used this for comparing text using java-diff-utils ? Using this utility, I can get a list of "delta" which I assume I can use it for the % of difference between two versions of the text? Is this a correct way of doing this? If you have done any text comparison algorithm using Java, could you give me some pointers?

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  • How to implement an intelligent enemy in a shoot-em-up?

    - by bummzack
    Imagine a very simple shoot-em-up, something we all know: You're the player (green). Your movement is restricted to the X axis. Our enemy (or enemies) is at the top of the screen, his movement is also restricted to the X axis. The player fires bullets (yellow) at the enemy. I'd like to implement an A.I. for the enemy that should be really good at avoiding the players bullets. My first idea was to divide the screen into discrete sections and assign weights to them: There are two weights: The "bullet-weight" (grey) is the danger imposed by a bullet. The closer the bullet is to the enemy, the higher the "bullet-weight" (0..1, where 1 is highest danger). Lanes without a bullet have a weight of 0. The second weight is the "distance-weight" (lime-green). For every lane I add 0.2 movement cost (this value is kinda arbitrary now and could be tweaked). Then I simply add the weights (white) and go to the lane with the lowest weight (red). But this approach has an obvious flaw, because it can easily miss local minima as the optimal place to go would be simply between two incoming bullets (as denoted with the white arrow). So here's what I'm looking for: Should find a way through bullet-storm, even when there's no place that doesn't impose a threat of a bullet. Enemy can reliably dodge bullets by picking an optimal (or almost optimal) solution. Algorithm should be able to factor in bullet movement speed (as they might move with different velocities). Ways to tweak the algorithm so that different levels of difficulty can be applied (dumb to super-intelligent enemies). Algorithm should allow different goals, as the enemy doesn't only want to evade bullets, he should also be able to shoot the player. That means that positions where the enemy can fire at the player should be preferred when dodging bullets. So how would you tackle this? Contrary to other games of this genre, I'd like to have only a few, but very "skilled" enemies instead of masses of dumb enemies.

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  • Algorithm to calculate trajectories from vector field

    - by cheeesus
    I have a two-dimensional vector field, i.e., for each point (x, y) I have a vector (u, v), whereas u and v are functions of x and y. This vector field canonically defines a set of trajectories, i.e. a set of paths a particle would take if it follows along the vector field. In the following image, the vector field is depicted in red, and there are four trajectories which are partly visible, depicted in dark red: I need an algorithm which efficiently calculates some trajectories for a given vector field. The trajectories must satisfy some kind of minimum denseness in the plane (for every point in the plane we must have a 'nearby' trajectory), or some other condition to get a reasonable set of trajectories. I could not find anything useful on Google on this, and Stackexchange doesn't seem to handle the topic either. Before I start devising such an algorithm by myself: Are there any known algorithms for this problem? What is their name, for which keywords do I have to search?

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  • One dimensional cutting algorithm with minimum waste

    - by jm666
    Can anybody point me to some resources about "cutting algorithm"? The problem: have rods with length of L meters, e.g. 6 m need cut smaller pieces of different lengths, e.g. need: 4 x 1.2m 8 x 0,9m etc... (many other lengths and counts) How to determine the optimal cutting, what will produce the minimum wasted material? I'm capable write an perl program, but haven't any idea about the algorithm. (if here is already some CPAN module what can help, would be nice). Alternatively, if someone can point me to some "spreadsheet" solution, or to anything what helps. Ps: in addition, need care about the "cutting line width" too, whats means than from the 6m long rod is impossible to cut 6 x 1m, because the cutting itself takes "3mm" width, so it is possible cut only 5 x 1m and the last piece will be only 98.5 cm (1m minus 5 x 3mm cut-width) ;(.

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  • Create a fast algorithm for a "weighted" median

    - by Hameer Abbasi
    Suppose we have a set S with k elements of 2-dimensional vectors, (x, n). What would be the most efficient algorithm to calculate the median of the weighted set? By "weighted set", I mean that the number x has a weight n. Here is an example (inefficient due to sorting) algorithm, where Sx is the x-part, and Sn is the n-part. Assume that all co-ordinate pairs are already arranged in Sx, with the respective changes also being done in Sn, and the sum of n is sumN: sum <= 0; i<= 0 while(sum < sumN) sum <= sum + Sn(i) ++i if(sum > sumN/2) return Sx(i) else return (Sx(i)*Sn(i) + Sx(i+1)*Sn(i+1))/(Sn(i) + Sn(i+1)) EDIT: Would this hold in two or more dimensions, if we were to calculate the median first in one dimension, then in another, with n being the sum along that dimension in the second pass?

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  • How do I optimize searching for the nearest point?

    - by Rootosaurus
    For a little project of mine I'm trying to implement a space colonization algorithm in order to grow trees. The current implementation of this algorithm works fine. But I have to optimize the whole thing in order to make it generate faster. I work with 1 to 300K of random attraction points to generate one tree, and it takes a lot of time to compute and compare distances between attraction points and tree node in order to keep only the closest treenode for an attraction point. So I was wondering if some solutions exist (I know they must exist) in order to avoid the time loss looping on each tree node for each attraction point to find the closest... and so on until the tree is finished.

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  • Automated tests for differencing algorithm

    - by Matthew Rodatus
    We are designing a differencing algorithm (based on Longest Common Subsequence) that compares a source text and a modified copy to extract the new content (i.e. content that is only in the modified copy). I'm currently compiling a library of test case data. We need to be able to run automated tests that verify the test cases, but we don't want to verify strict accuracy. Given the heuristic nature of our algorithm, we need our test pass/failures to be fuzzy. We want to specify a threshold of overlap between the desired result and the actual result (i.e. the content that is extracted). I have a few sketches in my mind as to how to solve this, but has anyone done this before? Does anyone have guidance or ideas about how to do this effectively?

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  • Low CPU/Memory/Memory-bandwith Pathfinding (maybe like in Warcraft 1)

    - by Valmond
    Dijkstra and A* are all nice and popular but what kind of algorithm was used in Warcraft 1 for pathfinding? I remember that the enemy could get trapped in bowl-like caverns which means there were (most probably) no full-path calculations from "start to end". If I recall correctly, the algorithm could be something like this: A) Move towards enemy until success or hitting a wall B) If blocked by a wall, follow the wall until you can move towards the enemy without being blocked and then do A) But I'd like to know, if someone knows :-) [edit] As explained to Byte56, I'm searching for a low cpu/mem/mem-bandwidth algo and wanted to know if Warcraft had some special secrets to deliver (never seen that kind of pathfinding elsewhere), I hope that that is more concordant with the stackexchange rules.

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  • Algorithm to simplify building/structural meshes

    - by morpheus
    I am looking for an algorithm to simplify the meshes of buildings or similar structures. EDIT: I had made a comment that Hoppe's algorithm tends to make meshes more and more spherical with simplification. But, I am not sure about it, so am deleting the comment. Buildings in contrast should tend to become more and more rectangular with increasing simplification. The D3DX extensions for D3D in version 9.0 (d3dx9.lib) used to have classes to do progressive mesh simplification. See: http://doc.51windows.net/Directx9_SDK/?url=/directx9_sdk/graphics/reference/d3dx/functions/mesh/d3dxgeneratepmesh.htm http://msdn.microsoft.com/en-us/library/windows/desktop/bb281243(v=vs.85).aspx

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