Results

Here are the final grades for the project. Note that the project gives a maximum 30 points out of the 100 points for the total grade. Note also that no matter the project grade, you still need to get at least 28/70 points (40%) in the final exam to pass the course.

Note that there were some errors in the project grades published last thursday. Hopefully, those errors are now fixed.

If you want to typeset the project with LaTeX, you may use the following template to get started. This include

• Neville and Divided Difference tables
• Interpolation tables
• Graphs
• Python and Matlab code

Download it here: LaTeX Template

For other help and introduction to LaTeX you may consult the LaTeX wikibook.

I describe here usage of polyfit and its close friend polyval.

To obtain an interpolating polynomial, you would go as follows:

p = polyfit([0.,2.,1.], [2.,1.,1.], 2)

Do not forget the third argument, which is the degree of the polynomial that you wish to interpolate with. You should always use the number of interpolation points minus one (here 2 = 3-1).

Now that you have the polynomial p, you may evaluate it at various points as follows

polyval(p, 10) # value of the polynomial at x = 10

This is especially useful if you want to plot a polynomial. You would go as follows:

xs = linspace(-1,3,500) # 500 points between -1 and 3
ys = polyval(p, xs) # the y values
plot(xs,ys)