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  • How fast can you make linear search?

    - by Mark Probst
    I'm looking to optimize this linear search: static int linear (const int *arr, int n, int key) { int i = 0; while (i < n) { if (arr [i] >= key) break; ++i; } return i; } The array is sorted and the function is supposed to return the index of the first element that is greater or equal to the key. They array is not large (below 200 elements) and will be prepared once for a large number of searches. Array elements after the n-th can if necessary be initialized to something appropriate, if that speeds up the search. No, binary search is not allowed, only linear search.

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  • Linear Layout Issue at Runtime

    - by George
    Hi all, I am trying to build a layout dynamically which display some text and image for the most part, but has a series of buttons placed next to each other in the bottom. I have a linear layout that carries the text, another linear layout that carries the image. And yet another linear layout that carries the buttons that get created in a for loop. I have a main layout aligned vertical that adds the text, image and buttons layout, in that order. To finally generate something like this: Text .... Image ... Button1 Button2 Button3.... The problem is the number of buttons get decided at runtime, so if there are more than 4 buttons, the 5th button gets displayed really tiny. Also, when I tilt the phone, I get only the text and image showing, but no buttons coz the image covers the entire screen. Layoutting seems to be pretty complicated to me, any help is appreciated! Thanks George

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  • Interpolation of scattered data: What could I do?

    - by Simon
    Hi! I need your help. I'm working on a 3D chart in Java using Java 3D. It should be able to display a bunch of measured values. As measured, the data I get is scattered. This means I will have to interpolate the missing points in order to get my surface plotted nicely. I didn't study all that 3D-Geometry stuff yet and I don't know where to start. My idea is to triangulate the points to a surface and then, based on the triangulation, interpolate the missing points. (see this to have a rough idea of what I want to achieve) Does someone have experiences with the interpolation of scattered data? Is my approach the right one? If yes, what kind of data structures and algorithms will I need in order to triangulate my points cloud?

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  • -moz-linear-gradient with PNG baclground over top

    - by Alex
    So Firefox supports gradient Backgrounds. Also supports multiple Background images.. So why does this not work?? background:-moz-linear-gradient(top, #5989bd,#336296), url(Active-Arrow.png) right center no-repeat; Also tried: background-color:-moz-linear-gradient(top, #5989bd,#336296); background:url(Active-Arrow.png) right center no-repeat; Can this be done??

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  • System of linear equations in C++?

    - by Archagon
    I need to solve a system of linear equations in my program. Is there a simple linear algebra library for C++, preferably comprised of no more than a few headers? I've been looking for nearly an hour, and all the ones I found require messing around with Linux, compiling DLLs in MinGW, etc. etc. etc. (I'm using Visual Studio 2008.)

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  • OpenGL Colour Interpolation

    - by Will-of-fortune
    I'm currently working on an little project in C++ and OpenGL and am trying to implement a colour selection tool similar to that in photoshop, as below. However I am having trouble with interpolation of the large square. Working on my desktop computer with a 8800 GTS the result was similar but the blending wasn't as smooth. This is the code I am using: GLfloat swatch[] = { 0,0,0, 1,1,1, mR,mG,mB, 0,0,0 }; GLint swatchVert[] = { 400,700, 400,500, 600,500, 600,700 }; glVertexPointer(2, GL_INT, 0, swatchVert); glColorPointer(3, GL_FLOAT, 0, swatch); glDrawArrays(GL_QUADS, 0, 4); Moving onto my laptop with Intel Graphics HD 3000, this result was even worse with no change in code. I thought it was OpenGL splitting the quad into two triangles, so I tried rendering using triangles and interpolating the colour in the middle of the square myself but it still doesnt quite match the result I was hoping for. Any help would be appreciated. Thanks.

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  • Which linear programming package should I use for high numbers of constraints and "warm starts"

    - by davidsd
    I have a "continuous" linear programming problem that involves maximizing a linear function over a curved convex space. In typical LP problems, the convex space is a polytope, but in this case the convex space is piecewise curved -- that is, it has faces, edges, and vertices, but the edges aren't straight and the faces aren't flat. Instead of being specified by a finite number of linear inequalities, I have a continuously infinite number. I'm currently dealing with this by approximating the surface by a polytope, which means discretizing the continuously infinite constraints into a very large finite number of constraints. I'm also in the situation where I'd like to know how the answer changes under small perturbations to the underlying problem. Thus, I'd like to be able to supply an initial condition to the solver based on a nearby solution. I believe this capability is called a "warm start." Can someone help me distinguish between the various LP packages out there? I'm not so concerned with user-friendliness as speed (for large numbers of constraints), high-precision arithmetic, and warm starts. Thanks!

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  • Why is a linked list implementation considered linear?

    - by VeeKay
    My apologies for asking such a simple question. Instead of posting such basic question in SO, I felt that this is more apt a question here. I tried finding an answer for this but none of them are logically appealing or convincing to my understanding. Typically, computer memory is always linear. So is the term non linear used for a data structure in a logical sense? If so, to logically achieve non linearity in a linear computer memory, we use pointers. Right? In that case, if pointers are virtual implementations for achieving non linearity, Why would a data structure like linked list be considered linear if in reality the nodes are never physically adjacent?

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  • Efficient Multiple Linear Regression in C# / .Net

    - by mrnye
    Does anyone know of an efficient way to do multiple linear regression in C#, where the number of simultaneous equations may be in the 1000's (with 3 or 4 different inputs). After reading this article on multiple linear regression I tried implementing it with a matrix equation: Matrix y = new Matrix( new double[,]{{745}, {895}, {442}, {440}, {1598}}); Matrix x = new Matrix( new double[,]{{1, 36, 66}, {1, 37, 68}, {1, 47, 64}, {1, 32, 53}, {1, 1, 101}}); Matrix b = (x.Transpose() * x).Inverse() * x.Transpose() * y; for (int i = 0; i < b.Rows; i++) { Trace.WriteLine("INFO: " + b[i, 0].ToDouble()); } However it does not scale well to the scale of 1000's of equations due to the matrix inversion operation. I can call the R language and use that, however I was hoping there would be a pure .Net solution which will scale to these large sets. Any suggestions? EDIT #1: I have settled using R for the time being. By using statconn (downloaded here) I have found it to be both fast & relatively easy to use this method. I.e. here is a small code snippet, it really isn't much code at all to use the R statconn library (note: this is not all the code!). _StatConn.EvaluateNoReturn(string.Format("output <- lm({0})", equation)); object intercept = _StatConn.Evaluate("coefficients(output)['(Intercept)']"); parameters[0] = (double)intercept; for (int i = 0; i < xColCount; i++) { object parameter = _StatConn.Evaluate(string.Format("coefficients(output)['x{0}']", i)); parameters[i + 1] = (double)parameter; }

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  • Haskell Linear Algebra Matrix Library for Arbitrary Element Types

    - by Johannes Weiß
    I'm looking for a Haskell linear algebra library that has the following features: Matrix multiplication Matrix addition Matrix transposition Rank calculation Matrix inversion is a plus and has the following properties: arbitrary element (scalar) types (in particular element types that are not Storable instances). My elements are an instance of Num, additionally the multiplicative inverse can be calculated. The elements mathematically form a finite field (??2256). That should be enough to implement the features mentioned above. arbitrary matrix sizes (I'll probably need something like 100x100, but the matrix sizes will depend on the user's input so it should not be limited by anything else but the memory or the computational power available) as fast as possible, but I'm aware that a library for arbitrary elements will probably not perform like a C/Fortran library that does the work (interfaced via FFI) because of the indirection of arbitrary (non Int, Double or similar) types. At least one pointer gets dereferenced when an element is touched (written in Haskell, this is not a real requirement for me, but since my elements are no Storable instances the library has to be written in Haskell) I already tried very hard and evaluated everything that looked promising (most of the libraries on Hackage directly state that they wont work for me). In particular I wrote test code using: hmatrix, assumes Storable elements Vec, but the documentation states: Low Dimension : Although the dimensionality is limited only by what GHC will handle, the library is meant for 2,3 and 4 dimensions. For general linear algebra, check out the excellent hmatrix library and blas bindings I looked into the code and the documentation of many more libraries but nothing seems to suit my needs :-(. Update Since there seems to be nothing, I started a project on GitHub which aims to develop such a library. The current state is very minimalistic, not optimized for speed at all and only the most basic functions have tests and therefore should work. But should you be interested in using or helping out developing it: Contact me (you'll find my mail address on my web site) or send pull requests.

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  • how to Compute the average probe length for success and failure - Linear probe (Hash Tables)

    - by fang_dejavu
    hi everyone, I'm doing an assignment for my Data Structures class. we were asked to to study linear probing with load factors of .1, .2 , .3, ...., and .9. The formula for testing is: The average probe length using linear probing is roughly Success-- ( 1 + 1/(1-L)**2)/2 or Failure-- (1+1(1-L))/2. we are required to find the theoretical using the formula above which I did(just plug the load factor in the formula), then we have to calculate the empirical (which I not quite sure how to do). here is the rest of the requirements **For each load factor, 10,000 randomly generated positive ints between 1 and 50000 (inclusive) will be inserted into a table of the "right" size, where "right" is strictly based upon the load factor you are testing. Repeats are allowed. Be sure that your formula for randomly generated ints is correct. There is a class called Random in java.util. USE it! After a table of the right (based upon L) size is loaded with 10,000 ints, do 100 searches of newly generated random ints from the range of 1 to 50000. Compute the average probe length for each of the two formulas and indicate the denominators used in each calculationSo, for example, each test for a .5 load would have a table of size approximately 20,000 (adjusted to be prime) and similarly each test for a .9 load would have a table of approximate size 10,000/.9 (again adjusted to be prime). The program should run displaying the various load factors tested, the average probe for each search (the two denominators used to compute the averages will add to 100), and the theoretical answers using the formula above. .** how do I calculate the empirical success?

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  • Simplest Algorithm for 2D Interpolation

    - by Gayan
    I have two shapes which are cross sections of a channel. I want to calculate the cross section of an intermediate point between the two defined points. What's the simplest algorithm to use in this situation? P.S. I came across several algorithms like natural neighbor and poisson which seemed complex. I'm looking for a simple solution which could be implemented quickly

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  • Algorithm for 2D Interpolation

    - by Gayan
    I have two shapes which are cross sections of a channel. I want to calculate the cross section of an intermediate point between the two defined points. What's the simplest algorithm to use in this situation? P.S. I came across several algorithms like natural neighbor and poisson which seemed complex. I'm looking for a simple solution which could be implemented quickly EDIT: I removed the word "Simplest" from the title since it might be misleading

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  • Double interpolation of regular expressions in Perl

    - by tomdee
    I have a Perl program that stores regular expressions in configuration files. They are in the form: regex = ^/d+$ Elsewhere, the regex gets parsed from the file and stored in a variable - $regex. I then use the variable when checking the regex, e.g. $lValid = ($valuetocheck =~ /$regex/); I want to be able to include perl variables in the config file, e.g. regex = ^\d+$stored_regex$ But I can't work out how to do it. When regular expressions are parsed by Perl they get interpreted twice. First the variables are expanded, and then the the regular expression itself is parsed. What I need is a three stage process: First interpolate $regex, then interpolate the variables it contains and then parse the resulting regular expression. Both the first two interpolations need to be "regular expression aware". e.g. they should know that the string contain $ as an anchor etc... Any ideas?

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  • OpenGL Color Interpolation across vertices

    - by gutsblow
    Right now, I have more than 25 vertices that form a model. I want to interpolate color linearly between the first and last vertex. The Problem is when I write the following code glColor3f(1.0,0.0,0.0); vertex3f(1.0,1.0,1.0); vertex3f(0.9,1.0,1.0); . .`<more vertices>; glColor3f(0.0,0.0,1.0); vertex3f(0.0,0.0,0.0); All the vertices except that last one are red. Now I am wondering if there is a way to interpolate color across these vertices without me having to manually interpolate color natively (like how opengl does it automatically) at each vertex since, I will be having a lot more number of colors at various vertices. Any help would be extremely appreciated. Thank you!

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  • how does linear probing handle this?

    - by Weadadada Awda
    • the hash function: h(x) = | 2x + 5 | mod M • a bucket array of capacity N • a set of objects with keys: 12, 44, 13, 88, 23, 94, 11, 39, 20, 16, 5 (to input from left to right) 4.a [5 pts] Write the hash table where M=N=11 and collisions are handled using linear probing. So I got up to here x x x x x 44 88 12 23 13 94 but the next variable should go after the 94 now, (the 11) but does it start from the beggining or what? thx

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  • implementation of interp1 function of MATLAB in J2ME

    - by Jeeka
    Hi, i am looking to implement the interp1, 1-D data interpolation (table lookup), function available in MATLAB in J2ME or JAVA. here is the link http://www.mathworks.com/access/helpdesk/help/techdoc/ref/interp1.html Is there any library available in J2ME or JAVA which has already implemented the same function ? If not can anybody help me in implementing interp1 function in J2ME or JAVA ?

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  • Linear Regression and Java Dates

    - by Smithers
    I am trying to find the linear trend line for a set of data. The set contains pairs of dates (x values) and scores (y values). I am using a version of this code as the basis of my algorithm. The results I am getting are off by a few orders of magnitude. I assume that there is some problem with round off error or overflow because I am using Date's getTime method which gives you a huge number of milliseconds. Does anyone have a suggestion on how to minimize the errors and compute the correct results?

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  • Solving linear system over integers with numpy

    - by A. R. S.
    I'm trying to solve an overdetermined linear system of equations with numpy. Currently, I'm doing something like this (as a simple example): a = np.array([[1,0], [0,1], [-1,1]]) b = np.array([1,1,0]) print np.linalg.lstsq(a,b)[0] [ 1. 1.] This works, but uses floats. Is there any way to solve the system over integers only? I've tried something along the lines of print map(int, np.linalg.lstsq(a,b)[0]) [0, 1] in order to convert the solution to an array of ints, expecting [1, 1], but clearly I'm missing something. Could anyone point me in the right direction?

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  • average case running time of linear search algorithm

    - by Brahadeesh
    Hi all. I am trying to derive the average case running time for deterministic linear search algorithm. The algorithm searches an element x in an unsorted array A in the order A[1], A[2], A[3]...A[n]. It stops when it finds the element x or proceeds until it reaches the end of the array. I searched on wikipedia and the answer given was (n+1)/(k+1) where k is the number of times x is present in the array. I approached in another way and am getting a different answer. Can anyone please give me the correct proof and also let me know whats wrong with my method? E(T)= 1*P(1) + 2*P(2) + 3*P(3) ....+ n*P(n) where P(i) is the probability that the algorithm runs for 'i' time (i.e. compares 'i' elements). P(i)= (n-i)C(k-1) * (n-k)! / n! Here, (n-i)C(k-1) is (n-i) Choose (k-1). As the algorithm has reached the ith step, the rest of k-1 x's must be in the last n-i elements. Hence (n-i)C(k-i). (n-k)! is the total number of ways of arranging the rest non x numbers, and n! is the total number of ways of arranging the n elements in the array. I am not getting (n+1)/(k+1) on simplifying.

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  • linear combinations in python/numpy

    - by nmaxwell
    greetings, I'm not sure if this is a dumb question or not. Lets say I have 3 numpy arrays, A1,A2,A3, and 3 floats, c1,c2,c3 and I'd like to evaluate B = A1*c1+ A2*c2+ A3*c3 will numpy compute this as for example, E1 = A1*c1 E2 = A2*c2 E3 = A3*c3 D1 = E1+E2 B = D1+E3 or is it more clever than that? In c++ I had a neat way to abstract this kind of operation. I defined series of general 'LC' template functions, LC for linear combination like: template<class T,class D> void LC( T & R, T & L0,D C0, T & L1,D C1, T & L2,D C2) { R = L0*C0 +L1*C1 +L2*C2; } and then specialized this for various types, so for instance, for an array the code looked like for (int i=0; i<L0.length; i++) R.array[i] = L0.array[i]*C0 + L1.array[i]*C1 + L2.array[i]*C2; thus avoiding having to create new intermediate arrays. This may look messy but it worked really well. I could do something similar in python, but I'm not sure if its nescesary. Thanks in advance for any insight. -nick

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  • Triangulation & Direct linear transform

    - by srand
    Following Hartley/Zisserman's Multiview Geometery, Algorithm 12: The optimal triangulation method (p318), I got the corresponding image points xhat1 and xhat2 (step 10). In step 11, one needs to compute the 3D point Xhat. One such method is Direct Linear Transform (DLT), mentioned in 12.2 (p312) and 4.1 (p88). The homogenous method (DLT), p312-313, states that it finds a solution as the unit singular vector corresponding to the smallest singular value of A, thus, A = [xhat1(1) * P1(3,:)' - P1(1,:)' ; xhat1(2) * P1(3,:)' - P1(2,:)' ; xhat2(1) * P2(3,:)' - P2(1,:)' ; xhat2(2) * P2(3,:)' - P2(2,:)' ]; [Ua Ea Va] = svd(A); Xhat = Va(:,end); plot3(Xhat(1),Xhat(2),Xhat(3), 'r.'); However, A is a 16x1 matrix, resulting in a Va that is 1x1. What am I doing wrong (and a fix) in getting the 3D point? For what its worth sample data: xhat1 = 1.0e+009 * 4.9973 -0.2024 0.0027 xhat2 = 1.0e+011 * 2.0729 2.6624 0.0098 P1 = 699.6674 0 392.1170 0 0 701.6136 304.0275 0 0 0 1.0000 0 P2 = 1.0e+003 * -0.7845 0.0508 -0.1592 1.8619 -0.1379 0.7338 0.1649 0.6825 -0.0006 0.0001 0.0008 0.0010 A = <- my computation 1.0e+011 * -0.0000 0 0.0500 0 0 -0.0000 -0.0020 0 -1.3369 0.2563 1.5634 2.0729 -1.7170 0.3292 2.0079 2.6624

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  • Java - Using Linear Coordinates to Check Against AI [closed]

    - by Oliver Jones
    I'm working on some artificial intelligence, and I want my AI not to run into given coordinates as these are references of a wall/boundary. To begin with, every time my AI hits a wall, it makes a reference to that position (x,y). When it hits the same wall three times, it uses linear check points to 'imagine' there is a wall going through these coordinates. I want to now prevent my AI from going into that wall again. To detect if my coordinates make a straight line, i use: private boolean collinear(double x1, double y1, double x2, double y2, double x3, double y3) { return (y1 - y2) * (x1 - x3) == (y1 - y3) * (x1 - x2); } This returns true is the given points are linear to one another. So my problems are: How do I determine whether my robot is approaching the wall from its current trajectory? Instead of Java 'imagining' theres a line from 1, to 3. But to 'imagine' a line all the way through these linear coordinantes, until infinity (or close). I have a feeling this is going to require some confusing trigonometry? (REPOST: http://stackoverflow.com/questions/13542592/java-using-linear-coordinates-to-check-against-ai)

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  • Recommended library for linear programming in .Net?

    - by tbone
    Can anyone recommend a library - free, or commercial but affordable ( There are some listed here: http://en.wikipedia.org/wiki/Linear_programming#Solvers_and_scripting_.28programming.29_languages I am just starting out with LP and hope someone can recommend something. I am trying to basically minimize pricing for cell phone subscription services.

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  • Efficient algorithm to generate all solutions of a linear diophantine equation with ai=1

    - by Ben
    I am trying to generate all the solutions for the following equations for a given H. With H=4 : 1) ALL solutions for x_1 + x_2 + x_3 + x_4 =4 2) ALL solutions for x_1 + x_2 + x_3 = 4 3) ALL solutions for x_1 + x_2 = 4 4) ALL solutions for x_1 =4 For my problem, there are always 4 equations to solve (independently from the others). There are a total of 2^(H-1) solutions. For the previous one, here are the solutions : 1) 1 1 1 1 2) 1 1 2 and 1 2 1 and 2 1 1 3) 1 3 and 3 1 and 2 2 4) 4 Here is an R algorithm which solve the problem. library(gtools) H<-4 solutions<-NULL for(i in seq(H)) { res<-permutations(H-i+1,i,repeats.allowed=T) resum<-apply(res,1,sum) id<-which(resum==H) print(paste("solutions with ",i," variables",sep="")) print(res[id,]) } However, this algorithm makes more calculations than needed. I am sure it is possible to go faster. By that, I mean not generating the permutations for which the sums is H Any idea of a better algorithm for a given H ?

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