Octave - Numerical Derivatives in Octave 1.) 2.) 3.) Create an m-file called exercise3_first name_last name.m Create the variable delx = "; 100 Create the matrix x = (0: delx: 8π)

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Chapter2: Second-order Linear Odes
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Octave - Numerical Derivatives in Octave
1.)
2.)
3.)
4.)
5.)
6.)
7.)
8.)
9.)
10.)
11.)
Create an m-file called exercise3_first name_last name.m
Create the variable delx = "; 100
Create the matrix x = (0: delx: 8n)
Create a second matrix called y = cos(2x);
You're going to create a numerical approximation to the derivative of y
(2x). Create the matrix dy by giving the function diff your matrix y.
Your last step is to create the matrix dydx by dividing dy by delx.
Graph x vs. y in red dots.
Graph the derivative in black dots. To graph it, you'll have to use x (2: end).
That's because diff returns a matrix with one less element. So, you can't use x, it
has one too many values.
Calculate the true derivative by hand and graph it in green dots.
Add a legend, title, x label, and y label. You don't need units in the labels.
Answer the following question using the disp () function. As Ax gets smaller,
should the approximation get better or worse? Justify your answer.
Transcribed Image Text:Octave - Numerical Derivatives in Octave 1.) 2.) 3.) 4.) 5.) 6.) 7.) 8.) 9.) 10.) 11.) Create an m-file called exercise3_first name_last name.m Create the variable delx = "; 100 Create the matrix x = (0: delx: 8n) Create a second matrix called y = cos(2x); You're going to create a numerical approximation to the derivative of y (2x). Create the matrix dy by giving the function diff your matrix y. Your last step is to create the matrix dydx by dividing dy by delx. Graph x vs. y in red dots. Graph the derivative in black dots. To graph it, you'll have to use x (2: end). That's because diff returns a matrix with one less element. So, you can't use x, it has one too many values. Calculate the true derivative by hand and graph it in green dots. Add a legend, title, x label, and y label. You don't need units in the labels. Answer the following question using the disp () function. As Ax gets smaller, should the approximation get better or worse? Justify your answer.
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