- instructions contains very simple Matlab instructions
- allfiles.tar contains all Matlab and image files currently in this directory. You should read the directions for downloading. It is a good idea to download this each time you use these files, since some of the programs here use other programs not listed here.
- In the recent versions of Matlab, you can rotate 3d graphs (and 2d graphs) by entering the command "rotate3d on" and then clicking and dragging on the graph. You can see how the axes will change, and when you let up on the mouse button, the graph moves to the new orientation. In Matlab 6, pull down the Tools menu on the graph window and select Move Camera. Then, when you click and drag on a graph, you see the graph itself rotate.

- Here are some basic directions for scanning things in Room 401 and the Scientific Computing Lab, plus information on image formats like GIF, JPG, PNG, BMP, and more.
- Here is a brief description of the types of images in Matlab
- Matlab has built-in demonstrations; run ipexindex
- trigimage.m displays an intensity plot of a trig field as an image, as a way of understanding the differences between matrices and images. Then it changes the colormaps.
- simpleRGBimage.m manually specifies intensities in an image
- simpleRGBimage2.m manually specifies intensities as uint8
- party.m reads a file, displays it and its red, green, and blue components
- trigfield2A.m turns an evolving trig field into a movie
- clown_treesBW.m loads, converts to grayscale (intensity image) and displays two Matlab images. It shows how to do simple modifications such as brightening, reverse video, superimposition, flipping, and blurring. It also makes a graph of the gray-scale intensity as a surface and contour graph. Page 1.
- thresh.m converts an image to black and white using threshholds
- edges.m illustrates Matlab edge detection methods

- isingminimum.m tries to minimize the Ising energy pixel by pixel
- isingminmac.m tries to minimize the Ising energy pixel by pixel; for the Macintosh.
- grapple1.m loads and displays grapple.gif, then performs median filtering. Output
- grapple2.m applies median filters until no further change occurs
- grapple3.m applies median filters with succesively larger windows
- party_gray.m reads a grayscale version of party_72.png and displays it. It is appropriate for Matlab on the Macintosh's at BGSU.

- iidfield1.m generates and graphs a matrix of iid variables. Output
- iidfield2.m generates, smooths, and graphs a matrix of iid variables. Out1Out2 Out3Out4 Out5
- trigfield1.m generates wave numbers and amplitudes and graphs a random field. Output
- trigfield2.m generates wave numbers and amplitudes which evolve over time
- trigfield3.m generates wave numbers with a preferred direction. Output
- trigfield4.m makes it easy to zoom in on part of a field. To use it, first set keep = 0, run trigfield4, then set keep = 1 and gridrange=[xmin xmax ymin ymax]. Then run trigfield4 again.
- trigfield5.m investigates the distribution of F(0). Output
- trigfield6.m investigates the joint distribution of F(0,0) and F(x,y). Output
- trigfield7.m allows you to explicitly choose wavenumbers. Output
- trigfield8.m generates field values at random locations. Output
- trigfield9.m computes the covariance associated with a given way of generating random wave numbers. Output
- trigfield10.m computes the covariogram for a given way of generating the norms of isotropic two-dimensional wave numbers. Output
- trigfield11.m displays a trig field using several different scales
- covariogram1.m uses data to produce a sample covariogram.
- covariogram2.m generates field values, computes a sample covariogram, and compares to the actual covariogram
- ou1.m simulates Ornstein-Uhlenbeck by inverting the covariance matrix
- kriging1.m generates field values at various locations, then predicts values at other locations using the known covariance
- kriging2.m generates field values at various locations, predicts values at other locations using the known covariance, and compares to Matlab's interpolation routine griddata
- cells.m generates Poisson patches of different colors
- bumps.m generates a field with bumps centered at Poisson points