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  • Rot13 for numbers.

    - by dreeves
    EDIT: Now a Major Motion Blog Post at http://messymatters.com/sealedbids The idea of rot13 is to obscure text, for example to prevent spoilers. It's not meant to be cryptographically secure but to simply make sure that only people who are sure they want to read it will read it. I'd like to do something similar for numbers, for an application involving sealed bids. Roughly I want to send someone my number and trust them to pick their own number, uninfluenced by mine, but then they should be able to reveal mine (purely client-side) when they're ready. They should not require further input from me or any third party. (Added: Note the assumption that the recipient is being trusted not to cheat.) It's not as simple as rot13 because certain numbers, like 1 and 2, will recur often enough that you might remember that, say, 34.2 is really 1. Here's what I'm looking for specifically: A function seal() that maps a real number to a real number (or a string). It should not be deterministic -- seal(7) should not map to the same thing every time. But the corresponding function unseal() should be deterministic -- unseal(seal(x)) should equal x for all x. I don't want seal or unseal to call any webservices or even get the system time (because I don't want to assume synchronized clocks). (Added: It's fine to assume that all bids will be less than some maximum, known to everyone, say a million.) Sanity check: > seal(7) 482.2382 # some random-seeming number or string. > seal(7) 71.9217 # a completely different random-seeming number or string. > unseal(seal(7)) 7 # we always recover the original number by unsealing.

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  • correcting fisheye distortion programmatically

    - by Will
    I have some points that describe positions in a picture taken with a fisheye lens. I've found this description of how to generate a fisheye effect, but not how to reverse it. How do you calculate the radial distance from the centre to go from fisheye to rectilinear? My function stub looks like this: Point correct_fisheye(const Point& p,const Size& img) { // to polar const Point centre = {img.width/2,img.height/2}; const Point rel = {p.x-centre.x,p.y-centre.y}; const double theta = atan2(rel.y,rel.x); double R = sqrt((rel.x*rel.x)+(rel.y*rel.y)); // fisheye undistortion in here please //... change R ... // back to rectangular const Point ret = Point(centre.x+R*cos(theta),centre.y+R*sin(theta)); fprintf(stderr,"(%d,%d) in (%d,%d) = %f,%f = (%d,%d)\n",p.x,p.y,img.width,img.height,theta,R,ret.x,ret.y); return ret; } Alternatively, I could somehow convert the image from fisheye to rectilinear before finding the points, but I'm completely befuddled by the OpenCV documentation. Is there a straightforward way to do it in OpenCV, and does it perform well enough to do it to a live video feed?

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  • NSDecimalNumber subtraction

    - by happyCoding25
    Hello, I need to subtract 0.5 from number a and set the answer to number b. My code looks like it would work but I'm not sure what I'm doing wrong. The error I get Is on the subtraction line, the error says incompatible type for argument 1 of 'decimalNumberBySubtracting:'. Heres my header: (Note: I only showed the numbers because the header is large) NSDecimalNumber *a; NSDecimalNumber *b; Heres the rest: (Assume this is in an IBAction) b = [a decimalNumberBySubtracting:0.5]; If anyone knows how to properly subtract any help would be appreciated.

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  • How to generate a lower frequency version of a signal in Matlab?

    - by estourodepilha.com
    With a sine input, I tried to modify it's frequency cutting some lower frequencies in the spectrum, shifting the main frequency towards zero. As the signal is not fftshifted I tried to do that by eliminating some samples at the begin and at the end of the fft vector: interval = 1; samplingFrequency = 44100; signalFrequency = 440; sampleDuration = 1 / samplingFrequency; timespan = 1 : sampleDuration : (1 + interval); original = sin(2 * pi * signalFrequency * timespan); fourierTransform = fft(original); frequencyCut = 10; %% Hertz frequencyCut = floor(frequencyCut * (length(pattern) / samplingFrequency) / 4); %% Samples maxFrequency = length(fourierTransform) - (2 * frequencyCut); signal = ifft(fourierTransform(frequencyCut + 1:maxFrequency), 'symmetric'); But it didn't work as expected. I also tried to remove the center part of the spectrum, but it wielded a higher frequency sine wave too. How to make it right?

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  • How to perform spatial partitioning in n-dimensions?

    - by kevin42
    I'm trying to design an implementation of Vector Quantization as a c++ template class that can handle different types and dimensions of vectors (e.g. 16 dimension vectors of bytes, or 4d vectors of doubles, etc). I've been reading up on the algorithms, and I understand most of it: here and here I want to implement the Linde-Buzo-Gray (LBG) Algorithm, but I'm having difficulty figuring out the general algorithm for partitioning the clusters. I think I need to define a plane (hyperplane?) that splits the vectors in a cluster so there is an equal number on each side of the plane. [edit to add more info] This is an iterative process, but I think I start by finding the centroid of all the vectors, then use that centroid to define the splitting plane, get the centroid of each of the sides of the plane, continuing until I have the number of clusters needed for the VQ algorithm (iterating to optimize for less distortion along the way). The animation in the first link above shows it nicely. My questions are: What is an algorithm to find the plane once I have the centroid? How can I test a vector to see if it is on either side of that plane?

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  • how do I make a portable isnan/isinf function.

    - by monkeyking
    I've been using isinf,isnan functions on linux platforms which worked perfectly. But this didn't work on osx, so I decided to use std::isinf std::isnan which works on both linux and osx. But the intel compiler doesn't recognize it, and I guess its a bug in the intel compiler according to http://software.intel.com/en-us/forums/showthread.php?t=64188 So now I just want to avoid the hassle and define my own isinf,isnan implementation. Does anyone know how this could be done Thanks edit: I ended up doing this in my sourcecode for making isinf/isnan working #include <iostream> #include <cmath> #ifdef __INTEL_COMPILER #include <mathimf.h> #endif int isnan_local(double x) { #ifdef __INTEL_COMPILER return isnan(x); #else return std::isnan(x); #endif } int isinf_local(double x) { #ifdef __INTEL_COMPILER return isinf(x); #else return std::isinf(x); #endif } int myChk(double a){ std::cerr<<"val is: "<<a <<"\t"; if(isnan_local(a)) std::cerr<<"program says isnan"; if(isinf_local(a)) std::cerr<<"program says isinf"; std::cerr<<"\n"; return 0; } int main(){ double a = 0; myChk(a); myChk(log(a)); myChk(-log(a)); myChk(0/log(a)); myChk(log(a)/log(a)); return 0; }

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  • Is there a Java library with 3D spline functions?

    - by Liam
    In particular, I need a way to represent a curve/spline that passes through a set of known 3D points, and a way of finding other points on the curve/spline, by subdivision/interpolation. For example, if I have a set of points P0 to PN, I want to find 100 points between P0 and P1 that are on a spline that passes through P0 and P1. I see that Java3D's KBRotPosScaleSplinePathInterpolator performs such a calculation, but it is tied to that API's scenegraph model and I do not see how to return the values I need.

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  • Looking for a function that will split profits/loss equally between 2 business partners.

    - by Hamish Grubijan
    This is not homework, for I am not a student. This is for my general curiosity. I apologize if I am reinventing the wheel here.The function I seek can be defined as follows (language agnostic): int getPercentageOfA(double moneyA, double workA, double moneyB, double workB) { // Perhaps you may assume that workA == 0 // Compute result return result; } Suppose Alice and Bob want to do business together ... such as ... selling used books. Alice is only interested in investing money in it and nothing else. Bob might invest some money, but he might have no $ available to invest. He will, however, put in the effort in finding a seller, a buyer, and doing maintenance. There are no tools, education, health insurance costs, or other expenses to consider. Both Alice and Bob wish to split the profits "equally" (A different weight like 40/60 for advanced users). Both are entrepreneurs, so they deal with low ROI/wage, and high income alike. There is no fixed wage, minimum wage, fixed ROI, or minimum ROI. They try to find the best deal possible, assume risks and go for it. Now, let's stick with the 50/50 model. If Alice invests $100, Bob invests work, and they will end up with a profit (or loss) of $60, they will split it equally - either both get $30 for their efforts/investments, or Bob ends up owing $30 to Alice. A second possibility: Both Alice and Bob invest 100, then Bob does all the work, and they end up splitting $60 profit. It looks like Alice should get only $15, because $30 of that profit came from Bob's investment and Bob's effort, so Alice shall have none of it, and the other $30 is to be split 50/50. Both of the examples above are trivial even when A and B want to split it 35/65 or what have you. Now it gets more complicated: What if Alice invests $70, and Bob invests $30 + does all of the work. It appears simple: (70,30) = (30,30) + (40,0) ... but, if only we knew how to weigh the two parts relative to each other. Another complicated (I think) example: what if Alice and Bob invest $70 and $30 respectively, and also put in an equal amount of work? I have a few data points: When A and B put in the same amount of work and the same $ - 50/50. When A puts in 100% of the money, and B does 100% of the work - 50/50. When A does all of the work and puts in all of the money - 100 for A / 0 for B (and vice-versa). When A puts in 50% of the money, and B puts in 50% of the money as well as does all of the work - 25 for A, and 75 for B (and vice-versa). If I fix things such that always workA = 0%, workB = 100% of the total work, then getPercentageOfA becomes a function: height z given x and y. The question is - how do you extrapolate this function between these several points? What is this function? If you can cover the cases when workA does not have to be 0% of the total work, and when investment vs work is split as 85/15 or using some other model, then what would the new function be?

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  • Draw Lines Over a Circle

    - by VOX
    There's a line A-B and C at the center between A and B. It forms a circle as in the figure. If we assume A-B line as a diameter of the circle and then C is it's center. My problem is I have no idea how to draw another three lines (in blue) each 45 degree away from AC or AB. No, this is not a homework, it's part of my complex geometry in a rendering. http://www.freeimagehosting.net/image.php?befcd84d8c.png

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  • Finding coordinates of a point between two points?

    - by Nicros
    Doing some 3D stuff in wpf- want to use a simpler test to see if everything is working (before moving to curves). The basic question is given two points x1,y1,z1 and x2,y2,z2 I have calculated the distance between the points. But how to find the coordinates of another point (x3,y3,z3) that lies on that line at some distance? I.e. if my line is 100 long between -50,0,0 and 50,0,0 what are the coordinates of the point at 100 * 0.1 along the line? I think this is a simple formula but I haven't found it yet....

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  • How to solve such system with given parts of it? (maple)

    - by Kabumbus
    So I had a system #for given koefs k:=3; n:=3; #let us solve system: koefSolution:= solve({ sum(a[i], i = 0 .. k) = 0, sum(a[i], i = 0 .. k)-(sum(b[i], i = 0 .. k)) = 0, sum(i^n*a[i], i = 0 .. k)-(sum(i^(n-1)*b[i], i = 0 .. k)) = 0 }); So I have a vector like koefSolution := { a[0] = 7*a[2]+26*a[3]-b[1]-4*b[2]-9*b[3], a[1] = -8*a[2]-27*a[3]+b[1]+4*b[2]+9*b[3], a[2] = a[2], a[3] = a[3], b[0] = -b[1]-b[2]-b[3], b[1] = b[1], b[2] = b[2], b[3] = b[3]} I have a[0] so I try solve({koefSolution, a[0] = 1}); why it does not solve my system for given a[0]? ( main point here is to fill koefSolution with given a[] and b[] and optimize.)

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  • solving origin of a vectors

    - by Mike
    I have two endpoints (xa,ya) and (xb,yb) of two vectors, respectively a and b, originating from a same point (xo, yo). Also, I know that |a|=|b|+s, where s is a constant. I tried to compute the origin (xo, yo) but seem to fail at some point. How to solve this?

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  • Runge-Kutta Method with adaptive step

    - by infoholic_anonymous
    I am implementing Runge-Kutta method with adaptive step in matlab. I get different results as compared to matlab's own ode45 and my own implementation of Runge-Kutta method with fixed step. What am I doing wrong in my code? Is it possible? function [ result ] = rk4_modh( f, int, init, h, h_min ) % % f - function handle % int - interval - pair (x_min, x_max) % init - initial conditions - pair (y1(0),y2(0)) % h_min - lower limit for h (step length) % h - initial step length % x - independent variable ( for example time ) % y - dependent variable - vertical vector - in our case ( y1, y2 ) function [ k1, k2, k3, k4, ka, y ] = iteration( f, h, x, y ) % core functionality performed within loop k1 = h * f(x,y); k2 = h * f(x+h/2, y+k1/2); k3 = h * f(x+h/2, y+k2/2); k4 = h * f(x+h, y+k3); ka = (k1 + 2*k2 + 2*k3 + k4)/6; y = y + ka; end % constants % relative error eW = 1e-10; % absolute error eB = 1e-10; s = 0.9; b = 5; % initialization i = 1; x = int(1); y = init; while true hy = y; hx = x; %algorithm [ k1, k2, k3, k4, ka, y ] = iteration( f, h, x, y ); % error estimation for j=1:2 [ hk1, hk2, hk3, hk4, hka, hy ] = iteration( f, h/2, hx, hy ); hx = hx + h/2; end err(:,i) = abs(hy - y); % step adjustment e = abs( hy ) * eW + eB; a = min( e ./ err(:,i) )^(0.2); mul = a * s; if mul >= 1 % step length admitted keepH(i) = h; k(:,:,i) = [ k1, k2, k3, k4, ka ]; previous(i,:) = [ x+h, y' ]; %' i = i + 1; if floor( x + h + eB ) == int(2) break; else h = min( [mul*h, b*h, int(2)-x] ); x = x + keepH(i-1); end else % step length requires further adjustments h = mul * h; if ( h < h_min ) error('Computation with given precision impossible'); end end end result = struct( 'val', previous, 'k', k, 'err', err, 'h', keepH ); end The function in question is: function [ res ] = fun( x, y ) % res(1) = y(2) + y(1) * ( 0.9 - y(1)^2 - y(2)^2 ); res(2) = -y(1) + y(2) * ( 0.9 - y(1)^2 - y(2)^2 ); res = res'; %' end The call is: res = rk4( @fun, [0,20], [0.001; 0.001], 0.008 ); The resulting plot for x1 : The result of ode45( @fun, [0, 20], [0.001, 0.001] ) is:

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  • Bracketing algorithm when root finding. Single root in "quadratic" function

    - by Ander Biguri
    I am trying to implement a root finding algorithm. I am using the hybrid Newton-Raphson algorithm found in numerical recipes that works pretty nicely. But I have a problem in bracketing the root. While implementing the root finding algorithm I realised that in several cases my functions have 1 real root and all the other imaginary (several of them, usually 6 or 9). The only root I am interested is in the real one so the problem is not there. The thing is that the function approaches the root like a cubic function, touching with the point the y=0 axis... Newton-Rapson method needs some brackets of different sign and all the bracketing methods I found don't work for this specific case. What can I do? It is pretty important to find that root in my program... EDIT: more problems: sometimes due to reaaaaaally small numerical errors, say a variation of 1e-6 in some value the "cubic" function does NOT have that real root, it is just imaginary with a neglectable imaginary part... (checked with matlab) EDIT 2: Much more information about the problem. Ok, I need root finding algorithm. Info I have: The root I need to find is between [0-1] , if there are more roots outside that part I am not interested in them. The root is real, there may be imaginary roots, but I don't want them. Probably all the rest of the roots will be imaginary The root may be double in that point, but I think that actually doesn't mater in numerical analysis problems I need to use the root finding algorithm several times during the overall calculations, but the function will always be a polynomial In one of the particular cases of the root finding, my polynomial will be similar to a quadratic function that touches Y=0 with the point. Example of a real case: The coefficient may not be 100% precise and that really slight imprecision may make the function not to touch the Y=0 axis. I cannot solve for this specific case because in other cases it may be that the polynomial is pretty normal and doesn't make any "strange" thing. The method I am actually using is NewtonRaphson hybrid, where if the derivative is really small it makes a bisection instead of NewRaph (found in numerical recipes). Matlab's answer to the function on the image: roots: 0.853553390593276 + 0.353553390593278i 0.853553390593276 - 0.353553390593278i 0.146446609406726 + 0.353553390593273i 0.146446609406726 - 0.353553390593273i 0.499999999999996 + 0.000000040142134i 0.499999999999996 - 0.000000040142134i The function is a real example I prepared where I know that the answer I want is 0.5 Note: I still haven't check completely some of the answers I you people have give me (Thank you!), I am just trying to give al the information I already have to complete the question.

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  • Using bitwise operators on > 32 bit integers

    - by dqhendricks
    I am using bitwise operations in order to represent many access control flags within one integer. ADMIN_ACCESS = 1; EDIT_ACCOUNT_ACCESS = 2; EDIT_ORDER_ACCESS = 4; var myAccess = 3; // ie: ( ADMIN_ACCESS | EDIT_ACCOUNT_ACCESS ) if ( myAccess & EDIT_ACCOUNT_ACCESS ) { // check for correct access // allow for editing of account } Most of this is occurring on the PHP side of my project. There is one piece however where Javascript is used to join several access flags using | when saving someone's access level. This works fine to a point. I have found that once an integer (flag) gets too large ( 32bit), it no longer works correctly with bitwise operators in Javascript. For instance: alert( 4294967296 | 1 ); // equals 1, but should equal 4294967297 I am trying to find a workaround for this so that I do not have to limit my number of access control flags to 32. Each access control flag is two times the previous control flag so that each control flag will not interfere with other control flags. dec(4) = bin(100) dec(8) = bin(1000) dec(16) = bin(10000) I have noticed that when adding two of these flags together with a simple +, it seems to come out with the same answer as a bitwise or operation, but am having trouble wrapping my head around whether this is a simple substitution, or if there might be problems with doing this. Can anyone comment on the validity of this workaround? Example: (4294967296 | 262144 | 524288) == (4294967296 + 262144 + 524288)

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  • Power Law distribution for a given exponent in C# using MathNet

    - by Eric Tobias
    Hello! I am currently working on a project where I need to generate multiple values (floats or doubles preferably) that follow a power law distribution with a given exponent! I was advised to use the MathNet.Iridium library to help me. The problem I have is that the documentation is not as explicit as it should be if there is any! I see multiple distributions that fit the general idea of the power law distribution but I cannot pinpoint a good distribution to use with a certain exponent as a parameter. Does anybody have more experience in that matter and could give me some hints or advice?

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  • Calculating bounding box a certain distance away from a lat/long coordinate in Java

    - by Bryce Thomas
    Given a coordinate (lat, long), I am trying to calculate a square bounding box that is a given distance (e.g. 50km) away from the coordinate. So as input I have lat, long and distance and as output I would like two coordinates; one being the south-west (bottom-left) corner and one being the north-east (top-right) corner. I have seen a couple of answers on here that try to address this question in Python, but I am looking for a Java implementation in particular. Just to be clear, I intend on using the algorithm on Earth only and so I don't need to accommodate a variable radius. It doesn't have to be hugely accurate (+/-20% is fine) and it'll only be used to calculate bounding boxes over small distances (no more than 150km). So I'm happy to sacrifice some accuracy for an efficient algorithm. Any help is much appreciated. Edit: I should have been clearer, I really am after a square, not a circle. I understand that the distance between the center of a square and various points along the square's perimeter is not a constant value like it is with a circle. I guess what I mean is a square where if you draw a line from the center to any one of the four points on the perimeter that results in a line perpendicular to a side of the perimeter, then those 4 lines have the same length.

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  • Histogram matching - image processing - c/c++

    - by Raj
    Hello I have two histograms. int Hist1[10] = {1,4,3,5,2,5,4,6,3,2}; int Hist1[10] = {1,4,3,15,12,15,4,6,3,2}; Hist1's distribution is of type multi-modal; Hist2's distribution is of type uni-modal with single prominent peak. My questions are Is there any way that i could determine the type of distribution programmatically? How to quantify whether these two histograms are similar/dissimilar? Thanks

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  • What statistics can be maintained for a set of numerical data without iterating?

    - by Dan Tao
    Update Just for future reference, I'm going to list all of the statistics that I'm aware of that can be maintained in a rolling collection, recalculated as an O(1) operation on every addition/removal (this is really how I should've worded the question from the beginning): Obvious Count Sum Mean Max* Min* Median** Less Obvious Variance Standard Deviation Skewness Kurtosis Mode*** Weighted Average Weighted Moving Average**** OK, so to put it more accurately: these are not "all" of the statistics I'm aware of. They're just the ones that I can remember off the top of my head right now. *Can be recalculated in O(1) for additions only, or for additions and removals if the collection is sorted (but in this case, insertion is not O(1)). Removals potentially incur an O(n) recalculation for non-sorted collections. **Recalculated in O(1) for a sorted, indexed collection only. ***Requires a fairly complex data structure to recalculate in O(1). ****This can certainly be achieved in O(1) for additions and removals when the weights are assigned in a linearly descending fashion. In other scenarios, I'm not sure. Original Question Say I maintain a collection of numerical data -- let's say, just a bunch of numbers. For this data, there are loads of calculated values that might be of interest; one example would be the sum. To get the sum of all this data, I could... Option 1: Iterate through the collection, adding all the values: double sum = 0.0; for (int i = 0; i < values.Count; i++) sum += values[i]; Option 2: Maintain the sum, eliminating the need to ever iterate over the collection just to find the sum: void Add(double value) { values.Add(value); sum += value; } void Remove(double value) { values.Remove(value); sum -= value; } EDIT: To put this question in more relatable terms, let's compare the two options above to a (sort of) real-world situation: Suppose I start listing numbers out loud and ask you to keep them in your head. I start by saying, "11, 16, 13, 12." If you've just been remembering the numbers themselves and nothing more, and then I say, "What's the sum?", you'd have to think to yourself, "OK, what's 11 + 16 + 13 + 12?" before responding, "52." If, on the other hand, you had been keeping track of the sum yourself while I was listing the numbers (i.e., when I said, "11" you thought "11", when I said "16", you thought, "27," and so on), you could answer "52" right away. Then if I say, "OK, now forget the number 16," if you've been keeping track of the sum inside your head you can simply take 16 away from 52 and know that the new sum is 36, rather than taking 16 off the list and them summing up 11 + 13 + 12. So my question is, what other calculations, other than the obvious ones like sum and average, are like this? SECOND EDIT: As an arbitrary example of a statistic that (I'm almost certain) does require iteration -- and therefore cannot be maintained as simply as a sum or average -- consider if I asked you, "how many numbers in this collection are divisible by the min?" Let's say the numbers are 5, 15, 19, 20, 21, 25, and 30. The min of this set is 5, which divides into 5, 15, 20, 25, and 30 (but not 19 or 21), so the answer is 5. Now if I remove 5 from the collection and ask the same question, the answer is now 2, since only 15 and 30 are divisible by the new min of 15; but, as far as I can tell, you cannot know this without going through the collection again. So I think this gets to the heart of my question: if we can divide kinds of statistics into these categories, those that are maintainable (my own term, maybe there's a more official one somewhere) versus those that require iteration to compute any time a collection is changed, what are all the maintainable ones? What I am asking about is not strictly the same as an online algorithm (though I sincerely thank those of you who introduced me to that concept). An online algorithm can begin its work without having even seen all of the input data; the maintainable statistics I am seeking will certainly have seen all the data, they just don't need to reiterate through it over and over again whenever it changes.

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  • Examples of monoids/semigroups in programming

    - by jkff
    It is well-known that monoids are stunningly ubiquitous in programing. They are so ubiquitous and so useful that I, as a 'hobby project', am working on a system that is completely based on their properties (distributed data aggregation). To make the system useful I need useful monoids :) I already know of these: Numeric or matrix sum Numeric or matrix product Minimum or maximum under a total order with a top or bottom element (more generally, join or meet in a bounded lattice, or even more generally, product or coproduct in a category) Set union Map union where conflicting values are joined using a monoid Intersection of subsets of a finite set (or just set intersection if we speak about semigroups) Intersection of maps with a bounded key domain (same here) Merge of sorted sequences, perhaps with joining key-equal values in a different monoid/semigroup Bounded merge of sorted lists (same as above, but we take the top N of the result) Cartesian product of two monoids or semigroups List concatenation Endomorphism composition. Now, let us define a quasi-property of an operation as a property that holds up to an equivalence relation. For example, list concatenation is quasi-commutative if we consider lists of equal length or with identical contents up to permutation to be equivalent. Here are some quasi-monoids and quasi-commutative monoids and semigroups: Any (a+b = a or b, if we consider all elements of the carrier set to be equivalent) Any satisfying predicate (a+b = the one of a and b that is non-null and satisfies some predicate P, if none does then null; if we consider all elements satisfying P equivalent) Bounded mixture of random samples (xs+ys = a random sample of size N from the concatenation of xs and ys; if we consider any two samples with the same distribution as the whole dataset to be equivalent) Bounded mixture of weighted random samples Which others do exist?

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  • efficiently determining if a polynomial has a root in the interval [0,T]

    - by user168715
    I have polynomials of nontrivial degree (4+) and need to robustly and efficiently determine whether or not they have a root in the interval [0,T]. The precise location or number of roots don't concern me, I just need to know if there is at least one. Right now I'm using interval arithmetic as a quick check to see if I can prove that no roots can exist. If I can't, I'm using Jenkins-Traub to solve for all of the polynomial roots. This is obviously inefficient since it's checking for all real roots and finding their exact positions, information I don't end up needing. Is there a standard algorithm I should be using? If not, are there any other efficient checks I could do before doing a full Jenkins-Traub solve for all roots? For example, one optimization I could do is to check if my polynomial f(t) has the same sign at 0 and T. If not, there is obviously a root in the interval. If so, I can solve for the roots of f'(t) and evaluate f at all roots of f' in the interval [0,T]. f(t) has no root in that interval if and only if all of these evaluations have the same sign as f(0) and f(T). This reduces the degree of the polynomial I have to root-find by one. Not a huge optimization, but perhaps better than nothing.

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