none.
Download these two files and store them in the same directory:
	Execute the script such that the figure appears on your screen. It looks a little weird with spikes; like 
	a random fence. We'll take care of that later. For now, I want you to discover the properties of the figure/axes 
	you can change with the property editor: in the figure window menu go to 'edit'->'axes properties' and/or 
	'figure properties'. Try to find a button that says 'More Properties'; change things and see what happens. 
	Take note of the respective names of the properties; they are similar to what you would use as parameters 	
	in get/set. Also try adding a title, and labels for x and y axis. There's nothing to turn in, just keep 
	in mind that basically every figure property you can change in the Figure Editor can be changed from the command 
	line/ your scripts.
     
	Now we're getting a little more serious; the display of the data as shown in the figure wrong, i.e. does not correspond to the 
	actual timeseries in the file! We've got to correct for this and make things look nicer. If you check line 5 in 
	fai_temp.m you will see that I plot temps over dates where dates is a vector 
	that holds the dates of temperature measurements in the format 'YYYYMMDD' (check FAI_temps.txt if you don't believe me). Matlab does not know 
	anything about the semantics of the dates vector for the x-axis and assumes dates contains
	integer values. This is where the weird spaces in your figure come from: we have big gaps
	from 1980-12-31 to 1981-01-01, i.e. 19801231...19810101, and 19811231 - 19820101, and so on. Matlab assumes those gaps 
	are values and plots a continuous x-axis which results in it reserving space on the x-axis. That's not wrong and also not too bad, but by default plot 
	connects all data points with a line. Now everybody thinks there's data where you have none. 
    
	This becomes clear when you replace line 5 in fai_temp.m with: plot(dates, temps, '.'). Understood? OK. Change it back!
    
	Let's fix this now! Matlab's internal representation of times is using serial date numbers. 
	Instead of using dates as given in the original file, let's do this:
    
dates from integer representation into strings using num2strdatenum, and the formatting
		string 'yyyymmdd'. Save this to a variable d_numsplot(dates, temps); replace dates with the serial 
		date numbers you just calculated. You should get a nice sinusoidal temperature series.You might notice that the tick labels are in strange places. Let's try having them every 5th year. There are many ways of doing this. For the most generic one we only need to know that the date format is 'yyyymmdd.' To get tick marks in the style '1985 - 1990 - 1995 ... ' without actuall knowing upper and lower bounds of the time series, we can do this (we treat the yyyymmdd dates as actual numbers here):
min on dates, to find minumum of the timeseries floor.max and ceil instead of min and floorset(gca, 'XTick', ticks) to set your tickmarks on the x-axis to 
		the dates you desired. (Well, it's really just me desiring that, I know)axis tightAlright. Now YOU know that your x-axis tick spacing is 5 years, but it's not really obvious in the figure as the datenumber labels haven't been converted to a reasonable string yet. We should change the tick labels!
set just like above, but this time change the property 'XTickLabel'
		to the result of calling datestr on the serial date number array ticks you 
		create above.datestr OR
		giving a freeform format similar to 'yyyy-mm-dd'. See datestr documentation for
		details. Play with different formats and find one you like.
	Great, now that we know what we're dealing with we can add title, x, and y labels. I recommend you to 
	use '\circF' as part of your ylabel argument to clarify that temperatures are in degrees Fahrenheit (we know that
	from experience - the numbers in the file certainly aren't degrees Celcius, they remain undocumented though).
    
title,xlabel,ylabel calls, set the 'FontSize' to 12title call, also set the 'FontWeight' to 'bold'If you want to get a better idea about how the temperature evolved over this long time, you could smooth it using a moving average approach over a period of 365 days:
smooth function which is part of the Curve Fitting Toolbox to temps and
		give the respective span to 365. d_numshold onlegend
	Your final figure should look similar to this:
	 
    
axes fai_spec.mplot command, add an axes call in which you set the position property to something 
		reasonable. Make the height of the axes not larger than 30% of the figure. I positioned my axes 10% from the left border, 65% from the bottom, 
		made it 89% wide and 30% high - the percentages are in relation to the figure dimensions.spectrogram(temps, 180, 90, 128, 1/(24*60*60), 'yaxis') . Briefly explain what the 
		parameters of this command mean (it's sometimes very useful to look at timeseries this way). 
    Here is a list that might be of help.
axesceildatenum: Convert a string into a serial date numberdatestr: Convert a serival date number into a formatted date stringfloormaxminset, get graphics' handle propertiesxlabel, ylabel, titlespectrogram: Have a spectrogram plottedsmooth: moving averageronni <at> gi <dot> alaska <dot> edu | Last modified: February 01 2013 21:41.