UCSD computers:

Unix workstations: EBU1-3327, 3329, & 5702

PCs: EBU1-5702 & EBU2-239

Starting Matlab:

Unix:

> matlab

or

> matlab -nosplash -nojvm

PC: under the start menu, look for Matlab in the list of available applications.

Running a tutorial: The Mathworks has a good tutorial that will help you get started.

http://www.mathworks.com/academia/student_center/tutorials/launchpad.html

If you have used Matlab before, you might check out an alternative tutorial or help page to refresh your knowledge:

- This one accompanies Kamen and Heck's textbook,
*Fundamentals of Signals and Systems Using Matlab*
http://users.ece.gatech.edu/~bonnie/book/TUTORIAL/tutorial.html - University of Indiana Stat/Math Center: http://www.indiana.edu/~statmath/math/matlab/gettingstarted/index.html

load
sample_data.mat

load('sample_data.mat')

The .mat
extension indicates a Matlab binary file. These files can
contain multiple variables that have different dimensions. load('sample_data.mat')

From the UCSD PCs, you can access data for this class from the server ieng9. From the desktop, look for "class resources", and then me127s.pub.

You can use the command who to list the variables that you have in Matlab's work space. The command whos will also show you the size of each variable array.

Plotting:

line plots:

plot(time_bound/365,Fan_T)

xlabel('time (years)'); ylabel('temperature (degrees C)')

Alternatively, we could make the same plot from the ASCII data:

plot(DATA2(:,1)/365,DATA2(:,2))

Now what about plotting our big arrays. Plotting all the data as line plots clearly isn't very useful. Instead we'll want a way to represent the data in 3-dimensions---latitude, longitude, and a variable quantity.

contour plots: Contour plots show lines of constant property. They work well when quantities vary smoothly (but aren't so good if you want to plot discrete quantities.) The following commands produce a contour plot of temperature at 1 degree intervals, with longitude and latitude correctly identified, and contours labelled.

c=contour(lon_t,lat_t,T,18:30);

clabel(c)

xlabel('longitude'); ylabel('latitude');

title('40-year mean sea surface temperature in the tropical Pacific')

image plots: Shaded image plots color each grid point according to the value at that point, so they don't require smoothly varying data values. Matlab has two functions that handle this: image and imagesc. For many purposes, imagesc is more satisfactory, since it automatically scales the color scale to represent the full range of values in the data.

imagesc(lon_t,lat_t,T); axis xy; colorbar;

xlabel('longitude'); ylabel('latitude');

title('salinity in the tropical Pacific')

The Matlab image functions order arrays like mathematical matrices with coordinate (1,1) in the upper left corner. Data tend to start with the smallest latitude and longitude values, which should be mapped in the lower left corner. To make your Matlab image plot look correct, you can use axis xy, as above, or you can flip the matrix top-to-bottom: imagesc(lon_t,lat_t,flipud(T));

saving figures: Finally, Matlab gives you several ways to save figures. To save a plot that you want to edit more carefully, use the "Save" option under the Figure window "File" heading. This will give you a file with a .fig ending that will allow you to pick up where you left off editing a Matlab figure, but it won't give you a generic format that you can print out. Do not send me .fig files.

You can also use the "Save As" option under the "File" heading to save your work as a jpg, gif, tiff, postscript (ps), encapsulated postscript (eps), or a number of other formats which are convenient for posting to the web, including in other documents, or e-mailing to your professor.

If you want to save a file to print, you can use the print option to send it straight to the printer or to write it into a file as postscript.

Computing a histogram: Sometimes we want to plot a histogram of all the data values acquired in a particular region or at a particular point in time. For example, it might not make sense to plot heights of everyone in the classroom as a function of anything. (What would you use? arrival time? geographic coordinate in the classroom? age? shoe size?) Matlab makes histograms automatically. Let's define a set of random numbers x:

x=rand(20000,1);

hist(x)

If we don't like the number of bins that Matlab has used, we can
specify some formating details:hist(x)

hist(x,30)
uses 30 bins.

hist(x,0.05:.1:.95) uses bins centered at 0.05, 0.15, 0.25, ... 0.95.

hist(x,0.05:.1:.95) uses bins centered at 0.05, 0.15, 0.25, ... 0.95.

Computing means and standard deviations: Matlab has a number of built in functions to compute many basic statistical quantities. Here are a few:

- mean(A) computes the average of each column of the matrix A.
- mean(A'), computes the average of each row of the matrix A. Here we use the ' to tell Matlab to take the transpose of A. But watch out if A contains complex numbers. Following standard mathematical notation, the transpose of A has complex conjugates. Thus 1+2i in A becomes 1-2i in A'.
- mean(A,1) is the same as mean(A). The 1 says to compute the average over the first dimension in A.
- mean(A,2) is a lot like mean(A'), though it doesn't rotate the results, and it avoids problems with complex conjugates.
- std(A) or std(A,0,1) computes the standard deviation of each column of matrix A.
- std(A') or std(A,0,2) will provide
standard deviations for the rows of A.

- Sometimes missing data points are filled with not-a-number (or
NaN). The mean of a data set that contains a NaN is
NaN. The matlab function nanmean will ignore NaN values
when it computes the mean.

Automating a procedure: What if you want to repeat the same calculation with a series of different parameters? Here is one strategy:

run a for loop: loop through a series of variables, performing a calculation for each one.

for
i=3:8

array=reshape(A(:,i),nlat,nlon);

figure(i-2)

imagesc(array,lat,lon)

end

array=reshape(A(:,i),nlat,nlon);

figure(i-2)

imagesc(array,lat,lon)

end

Making an M-file: Programs that run in Matlab are identifiable because they end in .m. An M-file consists of a series of instructions that you want Matlab to execute. They can be set up as simple sets of instructions:

x=rand(10,1);

mean(x)

or as functions:mean(x)

function
z=test_function(x)

% This M-file, test_function.m, computes the column mean of input data x.

z=mean(x);

end

This one would be executed by typing test_function(x). Matlab programs don't need to be compiled, so they aren't always very efficient, but they can contain some fairly sophisticated programming concepts.

% This M-file, test_function.m, computes the column mean of input data x.

z=mean(x);

end

This one would be executed by typing test_function(x). Matlab programs don't need to be compiled, so they aren't always very efficient, but they can contain some fairly sophisticated programming concepts.

How do you create a Matlab .m file? New versions of Matlab have an option under "File" to let you open a new M-file to edit. In any version, you can also use a plain text editor to create your Matlab program.

Finding help: To find more details on any matlab function, you can always type help and the name of the function. Matlab's web site also offers extensive guidance: http://www.mathworks.com/support/product/product.html?product=ML