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  • Is there a substitute for blockproc in Matlab?

    - by SetchSen
    I've been using blockproc for processing images blockwise. Unfortunately, blockproc is part of the Image Processing Toolbox, which I don't have on my personal computer. Is there a combination of functions in base Matlab that can substitute for blockproc? My initial guess was to use im2col to transform each block into columns, and then arrayfun to process each column. Then I realized that im2col is also a part of the Image Processing Toolbox, so that doesn't solve my problem.

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  • MATLAB plot moving data points in seperate subplots simutaneously

    - by Nate B.
    I wish to visualize the movement of a data point throughout space across a period of time within MATLAB. However, the way I want my figure to display is such that only a single instant is plotted at any given time. That was easy, I simply created a for loop to update my 3D plot display for every set of coordinates (x,y,z) in my data. However, I wish to display 4 different viewing angles of this plot at all times. I am well aware of how to setup subplots within MATLAB, that is not the issue. My issue is getting all 4 of these subplots to execute simultaneously so that all 4 subplots are always displaying the same point in time. I would appreciate if anyone could suggest how to handle this issue. As requested, my code for a figure with a single plot is shown below: datan = DATA; %data in form of x,y,z,a,b,c by column for row# of time points tib=zeros(size(datan,1),12); tib(:,1:3) = datan(:,1:3); tib_ref=tib(1,1:3); for i=1:size(datan,1) tib(i,1:3)=tib(i,1:3)-tib_ref; end angle_to_dircos close all figure('Name','Directions (Individual Cycles)','NumberTitle','off') for cc=1:2 hold off for bb=1:10:size(tib,1); scatter3(tib(bb,1),tib(bb,2),tib(bb,3),'green','filled'); %z and y axes are flipped in polhemus system hold on p0 = [tib(bb,1),tib(bb,2),tib(bb,3)]; p1 = [tib(bb,1)+10*tib(bb,4),tib(bb,2)+10*tib(bb,5),tib(bb,3)+10*tib(bb,6)]; p2 = [tib(bb,1)+10*tib(bb,7),tib(bb,2)+10*tib(bb,8),tib(bb,3)+10*tib(bb,9)]; p3 = [-(tib(bb,1)+100*tib(bb,10)),-(tib(bb,2)+100*tib(bb,11)),-(tib(bb,3)+100*tib(bb,12))]; vectarrow(p0,p1,1,0,0) hold on vectarrow(p0,p2,0,1,0) hold on vectarrow(p0,p3,0,0,1) hold on az = 90; el = 0; view(az, el); xlim([-50,50]); ylim([-50,50]); zlim([-50,50]); xlabel('distance from center in X'); ylabel('distance from center in Y'); zlabel('distance from center in Z'); title('XYZ Scatter Plots of Tracker Position'); hold on plot3(0,0,0,'sk','markerfacecolor',[0,0,0]); p0 = [0,0,0]; p1 = [10,0,0]; p2 = [0,10,0]; p3 = [0,0,100]; vectarrow(p0,p1,1,0,0) hold on vectarrow(p0,p2,0,1,0) hold on vectarrow(p0,p3,1,0,1) drawnow; end end

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  • 3D plotting in Matlab

    - by Jill
    I'm using the subplot and then surf functions to generate images in 3D in Matlab. How do I get rid of the axes and axis' gridlines and change the color to all yellow or all green or something like that? Thanks.

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  • matlab get color

    - by iteratorr
    I am using matlab for cluster visualization. I want to somehow get the color of my current cluster center fill in the plot and draw line of same color to cluster members. How can I get the color?

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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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  • MATLAB : frequency distribution

    - by Arkapravo
    I have raw observations of 500 numeric values (ranging from 1 to 25000) in a text file, I wish to make a frequency distribution in MATLAB. I did try the histogram (hist), however I would prefer a frequency distribution curve than blocks and bars. Any help is appreciated !

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  • MATLAB query about for loop, reading in data and plotting

    - by mp7
    Hi there, I am a complete novice at using matlab and am trying to work out if there is a way of optimising my code. Essentially I have data from model outputs and I need to plot them using matlab. In addition I have reference data (with 95% confidence intervals) which I plot on the same graph to get a visual idea on how close the model outputs and reference data is. In terms of the model outputs I have several thousand files (number sequentially) which I open in a loop and plot. The problem/question I have is whether I can preprocess the data and then plot later - to save time. The issue I seem to be having when I try this is that I have a legend which either does not appear or is inaccurate. My code (apolgies if it not elegant): fn= xlsread(['tbobserved' '.xls']); time= fn(:,1); totalreference=fn(:,4); totalreferencelowerci=fn(:,6); totalreferenceupperci=fn(:,7); figure plot(time,totalrefrence,'-', time, totalreferencelowerci,'--', time, totalreferenceupperci,'--'); xlabel('Year'); ylabel('Reference incidence per 100,000 population'); title ('Total'); clickableLegend('Observed reference data', 'Totalreferencelowerci', 'Totalreferenceupperci','Location','BestOutside'); xlim([1910 1970]); hold on start_sim=10000; end_sim=10005; h = zeros (1,1000); for i=start_sim:end_sim %is there any way of doing this earlier to save time? a=int2str(i); incidenceFile =strcat('result_', 'Sim', '_', a, 'I_byCal_total.xls'); est_tot=importdata(incidenceFile, '\t', 1); cal_tot=est_tot.data; magnitude=1; t1=cal_tot(:,1)+1750; totalmodel=cal_tot(:,3)+cal_tot(:,5); h(a)=plot(t1,totalmodel); xlim([1910 1970]); ylim([0 500]); hold all clickableLegend(h(a),a,'Location','BestOutside') end Essentially I was hoping to have a way of reading in the data and then plot later - ie. optimise the code. I hope you might be able to help. Thanks. mp

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  • Working with a figure file in Matlab

    - by 49er
    I've got a .fig file showing the intensities of 2d data. How do I obtain the values when I load it in Matlab? Is it even possible? When I try playing with the children properties I am able to obtain only the size of my x and y vectors, not the values themselves which I don't know how to extract.

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  • MATLAB clear current figure

    - by rlbond
    I want to clear MATLAB's global CurrentFigure property, because I need a plot that I make to not be overwritten if a careless user uses plot without opening a new figure. I tried set(0, 'CurrentFigure', []); But it doesn't seem to work. Is this impossible?

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  • compilation of image stitching code in matlab

    - by chee
    i am facing lots of problems while running code for image stitching given at this link http://se.cs.ait.ac.th/cvwiki/matlab:tutorial:image_stitching_from_high-view_images_using_homography may i get help regarding this type of problems here. EDIT: Image stitching code fails with the following message: ??? Undefined function or variable 'x2'. Error in ==compute_direct_homography at 26 amplified_x2=x2.*repmat([diagonal_ratio(x1,x2) diagonal_ratio(x1,x2) 1]',1,size(x2,2)); %assumption 1degree of lat and long =110,000 meters refer wiki Error in == project at 3 compute_direct_homography;

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  • Matlab regex if statement

    - by Dan
    I want to have matlab take user input but accept both cases of a letter. For example I have: function nothing = checkGC(gcfile) if exist(gcfile) reply = input('file exists, would you like to overwrite? [Y/N]: ', 's'); if (reply == [Yy]) display('You have chosen to overwrite!') else $ Do nothing end end The if statement obviously doesn't work, but basically I want to accept a lowercase or uppcase Y. Whats the best way to do this?

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  • Evaluating and graphing functions in Matlab

    - by thiol3
    New to programming, I am trying to graph the following Gaussian function in Matlab (should graph in 3 dimensions) but am making some mistakes somewhere. What is wrong? sigma = 1 for i = 1:20 for j = 1:20 z(i,j) = (1/(2*pi*sigma^2))*exp(-(i^2+j^2)/(2*sigma^2)); end end surf(z)

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  • Funny plots in MATLAB

    - by Arkapravo
    I recently learned the ezplot function in MATLAB. Recently I typed in ezplot('x^y - y^x', [-100 100 -100 100]); and this is what I got; Can anyone please tell me whatever is happening ? for lower scaling of x and y ( [ -10 10 -10 10]) there are more patterns in the 2nd 3rd and 4th quadrants. I was not very sure of the shape of curve, but I did not expect this !

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