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MATLAB Post-Processing Techniques: Vectors, Graphics, and Analytical Solutions

This MATLAB guide covers post-processing techniques for vectors, matrices, graphics, and analytical solution comparisons. Learn how to manipulate vectors, create xy plots, work with matrices, reshape data, load files, use loops and conditions, generate BMP outputs, plot contours, and visualize data using quiver and streamline plots. Dive into advanced techniques like generating streamlines with custom starting points to analyze complex fluid dynamics simulations.

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MATLAB Post-Processing Techniques: Vectors, Graphics, and Analytical Solutions

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  1. Basic MATLAB

  2. Matlab • Post-processer • Graphics • Analytical solution comparisons

  3. Vectors >> a=[1 2 3 4] a = 1 2 3 4 >> a' ans = 1 2 3 4

  4. Autofilling and addressing Vectors > a=[1:0.2:3]' a = 1.0000 1.2000 1.4000 1.6000 1.8000 2.0000 2.2000 2.4000 2.6000 2.8000 3.0000 >> a(2:3) ans = 1.2000 1.4000

  5. xy Plots >> x=[1 3 6 8 10]; >> y=[0 2 1 3 1]; >> plot(x,y)

  6. Matrices >> b=[1 2 3 4;5 6 7 8] b = 1 2 3 4 5 6 7 8 >> b' ans = 1 5 2 6 3 7 4 8

  7. Matrices >> b=2.2*ones(4,4) b = 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000 2.2000

  8. Reshape >> a=[1:9] a = 1 2 3 4 5 6 7 8 9 >> bsquare=reshape(a,3,3) bsquare = 1 4 7 2 5 8 3 6 9 >>

  9. Load and if • a = load(‘filename’); (semicolon suppresses echo) • if(1) … else … end

  10. For • for i = 1:10 • … • end

  11. Grad [dhdx,dhdy]=gradient(h);

  12. BMP Output bsq=rand(100,100); %bmp1 output e(:,:,1)=1-bsq; %r e(:,:,2)=1-bsq; %g e(:,:,3)=ones(100,100); %b imwrite(e, 'junk.bmp','bmp'); image(imread('junk.bmp')) axis('equal')

  13. Contours • h=[…]; • contour(h) • [C,H]=contour(h) • Clabel(C,H)

  14. Contours (load data, prepare matrix) rho=load('rho_frame0012_subs00.dat') p_vector=rho/3 rows=100 columns=20 • • • • for j=1:columns j for i=1:rows p(i,j)=p_vector(j+(i-1)*columns); • • • • • • • • • • • %Get rid of '0 pressure' solids that dominate pressure field if p(i,j)==0 p(i,j)=NaN; end end end

  15. Contours • [C,H]=contour(p) • clabel(C,H) • axis equal

  16. Quiver (vector plots) >> scale=10; >> d=rand(100,4); >> quiver(d(:,1),d(:,2),d(:,3),d(:,4),scale)

  17. Quiver (and Quiver3) uv_vector=load('u_frame0012_subs00.dat') • rows=100 columns=20 for j=1:columns j for i=1:rows u(i,j)=uv_vector(j+(i-1)*20,1); v(i,j)=uv_vector(j+(i-1)*20,2); • • • • • • • end • • end hold on quiver(u,v) • •

  18. Streamline • [Stream]= stream2(u,v,5,100) • streamline(Stream)

  19. Streamlines • [Stream]= stream2(u,v,[1:20],100*ones(20,1)); • streamline(Stream) • (This is for streamlines starting at y = 100 from x = 1 to 20 along the x axis. Different geometries will require different starting points.)

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