● Preparing data sets ● CTD Data from Tomales Bay ● Clean up ● Binning ● Combined Temperature-Depth plots ● T-S scatter plots ● Multiple plots on a single figure ● What haven't you learned in this class? Outline

Preparing Data ● Data needs to be prepped for loading into matlab. – Comment out all extraneous (usually non-number) material that matlab can't use. – Make sure there are no empty elements – fill with missing data. – Use a consistent symbol or marker for problem data ● If you are using excel, I suggest looking into the Matlab Excel Toolbox, particularly for time series data. – Lets you pull and push data from excel to matlab – Converts times and dates to matlab format for you – You will still need to have relatively clean and organized data

Example: CTD data from Tomales Bay ● CTD stands for conductivity, temperature, depth. ● Measures temperature and salinity (as well as other things) as a function of depth underwater. ● Lowered into water from a boat on a rope down to a certain depth and then raised. ● Take a look at a data file in z:\Pkg\WFCB\class5\data\tomales to see format. ● I have modified the files somewhat so they can easily be loaded. ● Meanings of each column are specified in the header of the files.

Basic plot ● A standard and interesting plot from a CTD is temperature (along the x-axis) vs. depth (along the y- axis) ● Exercise: Do this plot for the data file 13Oct2005_2108.cnv ● Hint: You will probably want to reverse the direction of the depth so that deeper is at the bottom. ● Correct plot is on next slide.

Depth / Temperature plot (1) Calibration (2) Downcast (3) Upcast (4) Surface Stratification (5) At surface

Cleaning up data ● Typically, only downcast is used as it is generally more accurate and has quicker response time. ● Also, need to remove calibration data near surface. ● Manufacturer has lots of GOOD programs to do this, but basic stuff can be done in matlab. ● Exercise: Remove upcast data and data within 0.5 meters of surface. Put code in a script so that you can later do it for all data files. Finally replot. ● Hint: Use the maximum depth to define split between down and up. ● Exercise 2: Make a function that would do this data cleanup for an arbitrary data matrix.

Binning data ● The next step is to bin data into depth bins. ● Again, manufacturer has programs for this. ● Exercise: Bin data so by the average value over every 0.5 meters starting at 0.5 meters depth. Then replot. ● Hint: Make a list of bin starting and ending points and then step through the list and compute average values. ● Hint: You will need to check to see if a bin actually has data. If not, then use NaN. continue might be useful for doing this. ● Exercise 2: Make a function that would do the binning for an arbitrary data matrix.

Loading in all the data ● So now that we know how to process one dataset, how about all of them. ● Files are numbered: “06” is at Tomales mouth, “08” is 2 km from mouth,..., “15” is 18 km from mouth. ● Exercise: Load and process all of the data files. As there are only ten, you could do each one separately. Or, you could use a more advanced approach and load them all using iteration. ● Hint: If doing each separately, cut & paste in a script. ● Hint: If using iteration, you might use a cell array to store filenames. ● Hint: Use a 3-D array to store all the results.

Combined Temperature-Depth Plots ● Exercise: Plot all the Temp-Depth curves on a single figure with a different color for each curve. Add a legend. ● Hint: This can be done with a single plot command if you pull out the appropriate data. The squeeze command might be useful. Or, you can use a for loop. ● Hint: You might want to use the jet command to get nice color. ● Exercise: Do the same thing for Salinity-Depth and Fluorescence-Depth. Do you see any patterns?

T-S Scatter Plot ● Exercise: Using very similar techniques to the previous exercises, you can make a scatter plot of temperature vs. salinity. ● Hint: Use a 'linestyle' of '.'

Multiple axes on a single figure ● You can use the subplot command to put more than one set of plots on a single figure window. An example is: » clf » subplot( 1, 2, 1 ) » plot( 1:10 ) » subplot( 1, 2, 2 ) » plot( (1:10).^2 ) ● Exercise: Can you use this model to place the T-Depth figures on the left and the S-Depth figures on the right.

What haven't you learned? ● I just want to point out a few things I haven't really taught in this class that might be of interest: – Strings and cell arrays: These are quite important for dealing with text information – Structures in more depth – Debugging: Really important. There are some notes in class 4 related to this. – 3D Graphics – Exporting Figures to files – Graphical User Interfaces (GUI): You can make interactive graphs. Look at guidetemplate for an example. – Object-oriented Programming: Often useful for modeling.