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  • how to use summation in matlab???

    - by lucky
    i have a randomly generated vector say A of length M say A=rand(M,1) and also i have function X(k)=sin(2*pi*k) how would i find Y(k) which is summation of A(l)*X(k-l) as l goes from 0 to M ... assume any value of k... but answer should be summation of all M+1 terms

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  • R: preventing unlist to drop NULL values

    - by nico
    I'm running into a strange problem. I have a vector of lists and I use unlist on them. Some of the elements in the vectors are NULL and unlist seems to be dropping them. How can I prevent this? Here's a simple (non) working example showing this unwanted feature of unlist a = c(list("p1"=2, "p2"=5), list("p1"=3, "p2"=4), list("p1"=NULL, "p2"=NULL), list("p1"=4, "p2"=5)) unlist(a) p1 p2 p1 p2 p1 p2 2 5 3 4 4 5

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  • Matlab code works with one version but not the other

    - by user1325655
    I have a code that works in Matlab version R2010a but shows errors in matlab R2008a. I am trying to implement a self organizing fuzzy neural network with extended kalman filter. I have the code running but it only works in matlab version R2010a. It doesn't work with other versions. Any help? Code attach function [ c, sigma , W_output ] = SOFNN( X, d, Kd ) %SOFNN Self-Organizing Fuzzy Neural Networks %Input Parameters % X(r,n) - rth traning data from nth observation % d(n) - the desired output of the network (must be a row vector) % Kd(r) - predefined distance threshold for the rth input %Output Parameters % c(IndexInputVariable,IndexNeuron) % sigma(IndexInputVariable,IndexNeuron) % W_output is a vector %Setting up Parameters for SOFNN SigmaZero=4; delta=0.12; threshold=0.1354; k_sigma=1.12; %For more accurate results uncomment the following %format long; %Implementation of a SOFNN model [size_R,size_N]=size(X); %size_R - the number of input variables c=[]; sigma=[]; W_output=[]; u=0; % the number of neurons in the structure Q=[]; O=[]; Psi=[]; for n=1:size_N x=X(:,n); if u==0 % No neuron in the structure? c=x; sigma=SigmaZero*ones(size_R,1); u=1; Psi=GetMePsi(X,c,sigma); [Q,O] = UpdateStructure(X,Psi,d); pT_n=GetMeGreatPsi(x,Psi(n,:))'; else [Q,O,pT_n] = UpdateStructureRecursively(X,Psi,Q,O,d,n); end; KeepSpinning=true; while KeepSpinning %Calculate the error and if-part criteria ae=abs(d(n)-pT_n*O); %approximation error [phi,~]=GetMePhi(x,c,sigma); [maxphi,maxindex]=max(phi); % maxindex refers to the neuron's index if ae>delta if maxphi<threshold %enlarge width [minsigma,minindex]=min(sigma(:,maxindex)); sigma(minindex,maxindex)=k_sigma*minsigma; Psi=GetMePsi(X,c,sigma); [Q,O] = UpdateStructure(X,Psi,d); pT_n=GetMeGreatPsi(x,Psi(n,:))'; else %Add a new neuron and update structure ctemp=[]; sigmatemp=[]; dist=0; for r=1:size_R dist=abs(x(r)-c(r,1)); distIndex=1; for j=2:u if abs(x(r)-c(r,j))<dist distIndex=j; dist=abs(x(r)-c(r,j)); end; end; if dist<=Kd(r) ctemp=[ctemp; c(r,distIndex)]; sigmatemp=[sigmatemp ; sigma(r,distIndex)]; else ctemp=[ctemp; x(r)]; sigmatemp=[sigmatemp ; dist]; end; end; c=[c ctemp]; sigma=[sigma sigmatemp]; Psi=GetMePsi(X,c,sigma); [Q,O] = UpdateStructure(X,Psi,d); KeepSpinning=false; u=u+1; end; else if maxphi<threshold %enlarge width [minsigma,minindex]=min(sigma(:,maxindex)); sigma(minindex,maxindex)=k_sigma*minsigma; Psi=GetMePsi(X,c,sigma); [Q,O] = UpdateStructure(X,Psi,d); pT_n=GetMeGreatPsi(x,Psi(n,:))'; else %Do nothing and exit the while KeepSpinning=false; end; end; end; end; W_output=O; end function [Q_next, O_next,pT_n] = UpdateStructureRecursively(X,Psi,Q,O,d,n) %O=O(t-1) O_next=O(t) p_n=GetMeGreatPsi(X(:,n),Psi(n,:)); pT_n=p_n'; ee=abs(d(n)-pT_n*O); %|e(t)| temp=1+pT_n*Q*p_n; ae=abs(ee/temp); if ee>=ae L=Q*p_n*(temp)^(-1); Q_next=(eye(length(Q))-L*pT_n)*Q; O_next=O + L*ee; else Q_next=eye(length(Q))*Q; O_next=O; end; end function [ Q , O ] = UpdateStructure(X,Psi,d) GreatPsiBig = GetMeGreatPsi(X,Psi); %M=u*(r+1) %n - the number of observations [M,~]=size(GreatPsiBig); %Others Ways of getting Q=[P^T(t)*P(t)]^-1 %************************************************************************** %opts.SYM = true; %Q = linsolve(GreatPsiBig*GreatPsiBig',eye(M),opts); % %Q = inv(GreatPsiBig*GreatPsiBig'); %Q = pinv(GreatPsiBig*GreatPsiBig'); %************************************************************************** Y=GreatPsiBig\eye(M); Q=GreatPsiBig'\Y; O=Q*GreatPsiBig*d'; end %This function works too with x % (X=X and Psi is a Matrix) - Gets you the whole GreatPsi % (X=x and Psi is the row related to x) - Gets you just the column related with the observation function [GreatPsi] = GetMeGreatPsi(X,Psi) %Psi - In a row you go through the neurons and in a column you go through number of %observations **** Psi(#obs,IndexNeuron) **** GreatPsi=[]; [N,U]=size(Psi); for n=1:N x=X(:,n); GreatPsiCol=[]; for u=1:U GreatPsiCol=[ GreatPsiCol ; Psi(n,u)*[1; x] ]; end; GreatPsi=[GreatPsi GreatPsiCol]; end; end function [phi, SumPhi]=GetMePhi(x,c,sigma) [r,u]=size(c); %u - the number of neurons in the structure %r - the number of input variables phi=[]; SumPhi=0; for j=1:u % moving through the neurons S=0; for i=1:r % moving through the input variables S = S + ((x(i) - c(i,j))^2) / (2*sigma(i,j)^2); end; phi = [phi exp(-S)]; SumPhi = SumPhi + phi(j); %phi(u)=exp(-S) end; end %This function works too with x, it will give you the row related to x function [Psi] = GetMePsi(X,c,sigma) [~,u]=size(c); [~,size_N]=size(X); %u - the number of neurons in the structure %size_N - the number of observations Psi=[]; for n=1:size_N [phi, SumPhi]=GetMePhi(X(:,n),c,sigma); PsiTemp=[]; for j=1:u %PsiTemp is a row vector ex: [1 2 3] PsiTemp(j)=phi(j)/SumPhi; end; Psi=[Psi; PsiTemp]; %Psi - In a row you go through the neurons and in a column you go through number of %observations **** Psi(#obs,IndexNeuron) **** end; end

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  • The internal implementation of R's dataset

    - by Yin Zhu
    I am trying to build a data processing program. Currently I use a double matrix to represent the data table, each row is an instance, each column represents a feature. I also have an extra vector as the target value for each instance, it is of double type for regression, it is of integer for classification. I want to make it more general. I am wondering how what kind of structure R uses to store a dataset, i.e. the internal implementation in R.

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  • Abstracting the adding of click events to elements selected by class using jQuery

    - by baroquedub
    I'm slowly getting up to speed with jQuery and am starting to want to abstract my code. I'm running into problems trying to define click events at page load. In the code below, I'm trying to run through each div with the 'block' class and add events to some of its child elements by selecting them by class: <script language="javascript" type="text/javascript"> $(document).ready(function (){ $('HTML').addClass('JS'); // if JS enabled, hide answers $(".block").each(function() { problem = $(this).children('.problem'); button = $(this).children('.showButton'); problem.data('currentState', 'off'); button.click(function() { if ((problem.data('currentState')) == 'off'){ button.children('.btn').html('Hide'); problem.data('currentState', 'on'); problem.fadeIn('slow'); } else if ((problem.data('currentState')) == 'on'){ button.children('.btn').html('Solve'); problem.data('currentState', 'off'); problem.fadeOut('fast'); } return false; }); }); }); </script> <style media="all" type="text/css"> .JS div.problem{display:none;} </style> <div class="block"> <div class="showButton"> <a href="#" title="Show solution" class="btn">Solve</a> </div> <div class="problem"> <p>Answer 1</p> </div> </div> <div class="block"> <div class="showButton"> <a href="#" title="Show solution" class="btn">Solve</a> </div> <div class="problem"> <p>Answer 2</p> </div> </div> Unfortunately using this, only the last of the divs' button actually works. The event is not 'localised' (if that's the right word for it?) i.e. the event is only applied to the last $(".block") in the each method. So I have to laboriously add ids for each element and define my click events one by one. Surely there's a better way! Can anyone tell me what I'm doing wrong? And how I can get rid of the need for those IDs (I want this to work on dynamically generated pages where I might not know how many 'blocks' there are...) <script language="javascript" type="text/javascript"> $(document).ready(function (){ $('HTML').addClass('JS'); // if JS enabled, hide answers // Preferred version DOESN'T' WORK // So have to add ids to each element and laboriously set-up each one in turn... $('#problem1').data('currentState', 'off'); $('#showButton1').click(function() { if (($('#problem1').data('currentState')) == 'off'){ $('#showButton1 > a').html('Hide'); $('#problem1').data('currentState', 'on'); $('#problem1').fadeIn('slow'); } else if (($('#problem1').data('currentState')) == 'on'){ $('#showButton1 > a').html('Solve'); $('#problem1').data('currentState', 'off'); $('#problem1').fadeOut('fast'); } return false; }); $('#problem2').data('currentState', 'off'); $('#showButton2').click(function() { if (($('#problem2').data('currentState')) == 'off'){ $('#showButton2 > a').html('Hide'); $('#problem2').data('currentState', 'on'); $('#problem2').fadeIn('slow'); } else if (($('#problem2').data('currentState')) == 'on'){ $('#showButton2 > a').html('Solve'); $('#problem2').data('currentState', 'off'); $('#problem2').fadeOut('fast'); } return false; }); }); </script> <style media="all" type="text/css"> .JS div.problem{display:none;} </style> <div class="block"> <div class="showButton" id="showButton1"> <a href="#" title="Show solution" class="btn">Solve</a> </div> <div class="problem" id="problem1"> <p>Answer 1</p> </div> </div> <div class="block"> <div class="showButton" id="showButton2"> <a href="#" title="Show solution" class="btn">Solve</a> </div> <div class="problem" id="problem2"> <p>Answer 2</p> </div> </div>

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  • Two collections and a for loop. (Urgent help needed) Checking an object variable against an inputted

    - by Elliott
    Hi there, I'm relatively new to java, I'm certain the error is trivial. But can't for the life of me spot it. I have an end of term exam on monday and currently trying to get to grips with past papers! Anyway heregoes, in another method (ALGO_1) I search over elements of and check the value H_NAME equals a value entered in the main. When I attempt to run the code I get a null pointer exception, also upon trying to print (with System.out.println etc) the H_NAME value after each for loop in the snippet I also get a null statement returned to me. I am fairly certain that the collection is simply not storing the data gathered up by the Scanner. But then again when I check the collection size with size() it is about the right size. Either way I'm pretty lost and would appreciate the help. Main questions I guess to ask are: from the readBackground method is the data.add in the wrong place? is the snippet simply structured wrongly? oh and another point when I use System.out.println to check the Background object values name, starttime, increment etc they print out fine. Thanks in advance.(PS im guessing the formatting is terrible, apologies.) snippet of code: for(Hydro hd: hydros){ System.out.println(hd.H_NAME); for(Background back : backgs){ System.out.println(back.H_NAME); if(back.H_NAME.equals(hydroName)){ //get error here public static Collection<Background> readBackground(String url) throws IOException { URL u = new URL(url); InputStream is = u.openStream(); InputStreamReader isr = new InputStreamReader(is); BufferedReader b = new BufferedReader(isr); String line =""; Vector<Background> data = new Vector<Background>(); while((line = b.readLine())!= null){ Scanner s = new Scanner(line); String name = s.next(); double starttime = Double.parseDouble(s.next()); double increment = Double.parseDouble(s.next()); double sum = 0; double p = 0; double nterms = 0; while((s.hasNextDouble())){ p = Double.parseDouble(s.next()); nterms++; sum += p; } double pbmean = sum/nterms; Background SAMP = new Background(name, starttime, increment, pbmean); data.add(SAMP); } return data; } Edit/Delete Message

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  • How to do an alphnumeric sort in R

    - by cbare
    Is there an alphanumeric sort for R? Say I had a character vector like so: > seq.names <- c('abc21', 'abc2', 'abc1', 'abc01', 'abc4', 'abc201', '1b', '1a') I'd like to sort it aphanumerically, so I get back this: c('1a', '1b', 'abc1', 'abc01', 'abc2', 'abc4', 'abc21', 'abc201') Does this exist somewhere, or should I start coding? Thanks, -chris

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  • How would you program Pascal's triangle in R?

    - by Peter Flom
    I am reading, on my own (not for HW) about programming, and one exercise involved programming Pascal's triangle in R. My first idea was to make a list and then append things to it, but that didn't work too well. Then I thought of starting with a vector, and making a list out of that, at the end. Then I thought of making a matrix, and making a list out of that at the end. Not sure which way to even approach this. Any hints? thanks

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  • Idiomatic scheme and generic programming, why only on numbers ?

    - by Skeptic
    Hi, In Scheme, procedures like +, -, *, / works on different types of numbers, but we don't much see any other generic procedures. For example, length works only on list so that vector-length and string-length are needed. I guess it comes from the fact that the language doesn't really offer any mechanism for defining generic procedure (except cond of course) like "type classes" in Haskell or a standardized object system. Is there an idiomatic scheme way to handle generic procedures that I'm not aware of ?

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  • Help with code optimization

    - by Ockonal
    Hello, I've written a little particle system for my 2d-application. Here is raining code: // HPP ----------------------------------- struct Data { float x, y, x_speed, y_speed; int timeout; Data(); }; std::vector<Data> mData; bool mFirstTime; void processDrops(float windPower, int i); // CPP ----------------------------------- Data::Data() : x(rand()%ScreenResolutionX), y(0) , x_speed(0), y_speed(0), timeout(rand()%130) { } void Rain::processDrops(float windPower, int i) { int posX = rand() % mWindowWidth; mData[i].x = posX; mData[i].x_speed = WindPower*0.1; // WindPower is float mData[i].y_speed = Gravity*0.1; // Gravity is 9.8 * 19.2 // If that is first time, process drops randomly with window height if (mFirstTime) { mData[i].timeout = 0; mData[i].y = rand() % mWindowHeight; } else { mData[i].timeout = rand() % 130; mData[i].y = 0; } } void update(float windPower, float elapsed) { // If this is first time - create array with new Data structure objects if (mFirstTime) { for (int i=0; i < mMaxObjects; ++i) { mData.push_back(Data()); processDrops(windPower, i); } mFirstTime = false; } for (int i=0; i < mMaxObjects; i++) { // Sleep until uptime > 0 (To make drops fall with randomly timeout) if (mData[i].timeout > 0) { mData[i].timeout--; } else { // Find new x/y positions mData[i].x += mData[i].x_speed * elapsed; mData[i].y += mData[i].y_speed * elapsed; // Find new speeds mData[i].x_speed += windPower * elapsed; mData[i].y_speed += Gravity * elapsed; // Drawing here ... // If drop has been falled out of the screen if (mData[i].y > mWindowHeight) processDrops(windPower, i); } } } So the main idea is: I have some structure which consist of drop position, speed. I have a function for processing drops at some index in the vector-array. Now if that's first time of running I'm making array with max size and process it in cycle. But this code works slower that all another I have. Please, help me to optimize it. I tried to replace all int with uint16_t but I think it doesn't matter.

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  • Standard library function in R for finding the mode?

    - by Nick
    In statistical language R, mean() and median() are standard functions which do what you'd expect. mode() tells you the internal storage mode of the R object, not the value that occurs the most in its argument. But surely there is a standard library function that implements mode for a vector (or list).

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  • C++ STL containers

    - by cambr
    Different STL containers like vector, stack, set, queue, etc support different access methods on them. If you are coding for example in Notepad++ or vim, you have to continuously refer to the documentation to see what all methods are available, atleast I have to. Is there some good way of remembering which container supports which methods??

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  • Memory Allocation by STL C++ Objects

    - by Vaibhav
    I am using malloc_stats() function to display the amount of "system bytes" and "in use" bytes used by the process. I wanted to know if the in use bytes also include the memory used by STL C++ Objects like map, vector, sets? If yes, is it safe to assume that this is only amount of memory that will be used by the process?

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  • Create lags with a for-loop in R

    - by cptn
    I've got a data.frame with stock data of several companies (here it's only two). I want 10 additional columns in my stock data.frame df with lagged dates (from -5 days to +5 days) for both companies in my event data.frame. I'm using a for loop which is probably not the best solution, but it works partially. DATE <- c("01.01.2000","02.01.2000","03.01.2000","06.01.2000","07.01.2000","09.01.2000","10.01.2000","01.01.2000","02.01.2000","04.01.2000","06.01.2000","07.01.2000","09.01.2000","10.01.2000") RET <- c(-2.0,1.1,3,1.4,-0.2, 0.6, 0.1, -0.21, -1.2, 0.9, 0.3, -0.1,0.3,-0.12) COMP <- c("A","A","A","A","A","A","A","B","B","B","B","B","B","B") df <- data.frame(DATE, RET, COMP, stringsAsFactors=F) df # DATE RET COMP # 1 01.01.2000 -2.00 A # 2 02.01.2000 1.10 A # 3 03.01.2000 3.00 A # 4 06.01.2000 1.40 A # 5 07.01.2000 -0.20 A # 6 09.01.2000 0.60 A # 7 10.01.2000 0.10 A # 8 01.01.2000 -0.21 B # 9 02.01.2000 -1.20 B # 10 04.01.2000 0.90 B # 11 06.01.2000 0.30 B # 12 07.01.2000 -0.10 B # 13 09.01.2000 0.30 B # 14 10.01.2000 -0.12 B this loop works fine comp <- as.vector(unique(df$COMP)) mylist <- vector('list', length(comp)) # create lags in DATE for(i in 1:length(comp)) { print(i) comp_i <- comp[i] df_k <- df[df$COMP %in% comp_i, ] # all trading days of one firm df_k <- transform(df_k, DATEm1 = c(NA, head(DATE, -1)), DATEm2 = c(NA, NA, head(DATE, -2)), DATEm3 = c(NA, NA, NA, head(DATE, -3)), DATEm4 = c(NA, NA, NA, NA,head(DATE, -4)), DATEm5 = c(NA, NA, NA, NA, NA, head(DATE, -5)), DATEp1 = c(DATE[-1], NA)) #DATEp2 = c(DATE[-2], NA, NA), #DATEp3 = c(DATE[-3], NA, NA, NA), #DATEp4 = c(DATE[-4], NA, NA, NA, NA), #DATEp5 = c(DATE[-5], NA, NA, NA, NA, NA)) mylist[[i]] = df_k } df1 <- do.call(rbind, mylist) But if I add the lines with DATEp2, DATEp3, DATEp4, DATEp5. the code doesn't work. Can anybody tell me what I'm doing wrong here? Here the code with all the lagged dates. # create lags in DATE for(i in 1:length(comp)) { print(i) comp_i <- comp[i] df_k <- df[df$COMP %in% comp_i, ] # all trading days of one firm df_k <- transform(df_k, DATEm1 = c(NA, head(DATE, -1)), DATEm2 = c(NA, NA, head(DATE, -2)), DATEm3 = c(NA, NA, NA, head(DATE, -3)), DATEm4 = c(NA, NA, NA, NA,head(DATE, -4)), DATEm5 = c(NA, NA, NA, NA, NA, head(DATE, -5)), DATEp1 = c(DATE[-1], NA), DATEp2 = c(DATE[-2], NA, NA), DATEp3 = c(DATE[-3], NA, NA, NA), DATEp4 = c(DATE[-4], NA, NA, NA, NA), DATEp5 = c(DATE[-5], NA, NA, NA, NA, NA)) mylist[[i]] = df_k } df1 <- do.call(rbind, mylist)

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  • Copying from istream never stops

    - by the_drow
    This bit of code runs infinitely: copy(istream_iterator<char>(cin), istream_iterator<char>(), back_inserter(buff)); The behavior I was expecting is that it will stop when I press enter. However it doesn't. buff is a vector of chars.

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  • Refactor the following two C++ methods to move out duplicate code

    - by ossandcad
    I have the following two methods that (as you can see) are similar in most of its statements except for one (see below for details) unsigned int CSWX::getLineParameters(const SURFACE & surface, vector<double> & params) { VARIANT varParams; surface->getPlaneParams(varParams); // this is the line of code that is different SafeDoubleArray sdParams(varParams); for( int i = 0 ; i < sdParams.getSize() ; ++i ) { params.push_back(sdParams[i]); } if( params.size() > 0 ) return 0; return 1; } unsigned int CSWX::getPlaneParameters(const CURVE & curve, vector<double> & params) { VARIANT varParams; curve->get_LineParams(varParams); // this is the line of code that is different SafeDoubleArray sdParams(varParams); for( int i = 0 ; i < sdParams.getSize() ; ++i ) { params.push_back(sdParams[i]); } if( params.size() > 0 ) return 0; return 1; } Is there any technique that I can use to move the common lines of code of the two methods out to a separate method, that could be called from the two variations - OR - possibly combine the two methods to a single method? The following are the restrictions: The classes SURFACE and CURVE are from 3rd party libraries and hence unmodifiable. (If it helps they are both derived from IDispatch) There are even more similar classes (e.g. FACE) that could fit into this "template" (not C++ template, just the flow of lines of code) I know the following could (possibly?) be implemented as solutions but am really hoping there is a better solution: I could add a 3rd parameter to the 2 methods - e.g. an enum - that identifies the 1st parameter (e.g. enum::input_type_surface, enum::input_type_curve) I could pass in an IDispatch and try dynamic_cast< and test which cast is NON_NULL and do an if-else to call the right method (e.g. getPlaneParams() vs. get_LineParams()) The following is not a restriction but would be a requirement because of my teammates resistance: Not implement a new class that inherits from SURFACE/CURVE etc. (They would much prefer to solve it using the enum solution I stated above)

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