Lecture 5b: Starting Matlab

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1 Lecture 5b: Starting Matlab James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University August 7, 2013

2 Outline 1 Resources 2 Starting Matlab 3 Homework # 16 Homework # 17 4 A Sample Matlab Session

3 Abstract This lecture is going to help you get started with Matlab ( see )

4 Resources In the text, Section 2.4 is the first discussion about how to use Matlab in the text.

5 Starting Matlab Create a directory for this class. On a CCIT Computer: On Your Laptop: Set up a directory on your public U drive called M111 or something you like better. or use a flash drive. Create a directory on your hard drive if you are on a laptop. or use a flash drive.

6 Starting Matlab Starting Matlab: On a CCIT Computer: With Student Edition: Go to a computer lab of your choice. Go to All Programs in Windows. Scroll down to choose CES Scroll to choose MatLab2011a or whatever Matlab shows up. CCIT installs newer versions from time to time so the version of Matlab you see here might be different. I ll just call this Matlab for convenience. Click on MatLab and it starts up. Once Matlab is installed, just start it up.

7 Starting Matlab You ll see something like this.

8 Starting Matlab Now that Matlab is up and running: Let s assume your choice of directory is neanderthal. Go to a directory which is for this class s programs and files. In MatLab typing pwd shows your current directory Changing directory: On a CCIT Computer: In Matlab, type % change to y o u r p u b l i c d i r e c t o r y cd U: \ % change to y o u r d i r e c t o r y f o r t h i s c l a s s. cd n e a n d e r t h a l On Your Laptop: Just cd to your directory wherever it is.

9 Let s start with Riemann sums in Matlab. As you have seen, doing these by hand is tedious. Let s look at how we might do them using MatLab. Here is a typical MatLab session to do this. Let s calculate the Riemann sum for the function f (x) = x 2 on the interval [1, 3] using the partition P = {1, 1.5, 2.1, 2.8, 3.0} and evaluation set E = {1.2, 1.7, 2.5, 2.9}. First, set up our function. MatLab allows us to define a function inside the MatLab environment as follows >> f x ) ( x. ˆ 2 ) ; This defines the function f (x) = x 2. If we had wanted to define g(x) = 2x 2 + 3, we would have used >> g x ) ( 2 x. ˆ 2 + 3) ;

10 In MatLab, variables with columns are what in mathematics are called vectors. Consider this example. We want the variable X to have 3 rows and 1 columns. To do that, we insert a ; between the numbers so each number starts a new row. Note there is no semicolon at the end of the line below so Matlab displays what X is after we type the command. % >> X = [ 1 ; 2 ; 3 ] X = Adding the ; turns off the display. >> X = [ 1 ; 2 ; 3 ] ;

11 Variables that are only one row and multiple columns are also possible. These are also vectors but oriented differently. Consider this example. We want the variable Y to have 1 rows and 4 columns. To do that, we insert a, between the numbers so each number starts a new column. We leave off the ; so that Y is displayed. % >> Y = [ 1, 2, 6, 8] Y = Adding the ; turns off the display. >> Y = [ 1, 2, 6, 8];

12 Now let Z be another column vector the same size as X. >> Z = [ 4 ; 2 ; 6 ] ; The MatLab notation X.*Z means to multiple component wise: 1 4 (1)(4) = (2)( 2) = (3)(6) 18 So in MatLab, we have >> X. Z ans =

13 To square X, we would write X.^2 to square each component creating a new vector with each entry squared. >> X. ˆ 2 ans = The way we set up the function f (x.^2); makes use of this. The variable X may or may not be a vector. So we write x.^2 so that if x is a vector, multiplication is done component wise and if not, it is just the squaring of a number. So for our function, to find f for all the values in X, we just type >> f (X) ans = 1 4 9

14 Now let s setup the partition with the command >> P = [ 1 ; 1. 5 ; 2. 1 ; 2. 8 ; 3. 0 ] P = The command diff in MatLab is applied to a vector to create the differences we have called the x i s. >> dx = d i f f (P) dx =

15 Next, we set up the evaluation set E. >> E = [ 1. 2 ; 1. 7 ; 2. 5 ; 2. 9 ] E = Find f (E); a new vector with the values f (s i ) s. Use f (E). dx to create the new vector with components f (s i ) x i. >> g = f ( E). dx g =

16 Finally, we add all these components together to get the Riemann sum. In MatLab, we add up the entries of a vector g with the command sum(g). >> RS = sum ( g ) RS = Without the comments, the MatLab session is not too long. >> f x ) ( x. ˆ 2 ) ; >> P = [ 1 ; 1. 5 ; 2. 1 ; 2. 8 ; 3. 0 ] ; >> dx = d i f f (P) ; >> E = [ 1. 2 ; 1. 7 ; 2. 5 ; 2. 9 ] ; >> g = f ( E). dx ; >> RS = sum ( g ) ;

17 Let s learn how to graph a function f. To graph f we need to set up a variable which tells us how many data points to use in the plot. This variable is different from our partition variable. The linspace command sets up a variable y to be a vector with 21 points in it. The first point is 1 and the last point is 3 and the interval [1, 3] is divided into 20 equal size pieces. So this command creates y values spaced.1 apart: {y 1 = 1, y 2 = 1.1, y 3 = 1.2,..., y 20 = 2.9, y 21 = 3.0}. We use the pairs (y i, f (y i )) to make a plot by connecting the dots determined by the pairs using lines. And here is the plot in Matlab >> y = l i n s p a c e ( 1, 3, 2 1 ) ; >> p l o t ( y, f ( y ) ) ;

18 We can add stuff to this bare bones plot. >> x l a b e l ( x a x i s ) ; >> y l a b e l ( y a x i s ) ; >> l e g e n d ( x ˆ 2, l o c a t i o n, best ) ; >> t i t l e ( P l o t o f f ( x ) = x ˆ2 on [ 1, 3 ] ) ; xlabel sets the name printed under the horizontal axis. ylabel sets the name printed next to the vertical axis. legend sets a blurb printed inside the graph explaining the plot. Great when you plot multiple things on the same graph. title sets the title of the graph.

19 The graph pops up in a separate window as you can see. Using the file menu, select save as and scroll through the choices to save the graph as a.png file a Portable Network Graphics file. You ll need to give the file a name. I chose graph1.png.

20 To graph a rectangle, we graph 4 lines. The MatLab command >> p l o t ( [ x1 x2 ] ], [ y1 y2 ] ) plots a line from the pair (x1, y1) to (x2, y2). To plot rectangle, do this. >> h o l d on % s e t a x i s so we can s e e r e c t a n g l e >> a x i s ( [ P( 1 ) 1 P( 2 )+1 0 f ( E ( 1 ) ) +1]) % p l o t top, LHS, RHS and bottom o f r e c t a n g l e >> p l o t ( [ P( 1 ) P( 2 ) ], [ f ( E ( 1 ) ) f ( E ( 1 ) ) ] ) ; >> p l o t ( [ P( 1 ) P( 1 ) ], [ 0 f ( E ( 1 ) ) ] ) ; >> p l o t ( [ P( 2 ) P( 2 ) ], [ 0 f ( E ( 1 ) ) ] ) ; >> p l o t ( [ P( 1 ) P( 2 ) ], [ 0 0 ] ) ; >> h o l d o f f

21 This generates the rectangle. To show the Riemann sum approximation as rectangles, we use a for loop in MatLab >> f o r i = 1 : 4.. do s t u f f f o r each c h o i c e o f i end

22 To put this all together, we have to force Matlab to plot repeatedly without erasing the previous plot. We use hold on and hold off to do this. We start with hold on and then all plots are kept until the hold off is used. We still think f is always positive so the bottom is 0 and the top is the f (E(I )) value. h o l d on % s e t h o l d to on f o r i = 1 : 4 % graph r e c t a n g l e s bottom = 0 ; top = f (E( i ) ) ; p l o t ( [ P( i ) P( i +1) ], [ f ( E ( i ) ) f ( E( i ) ) ] ) ; p l o t ( [ P( i ) P( i ) ], [ bottom top ] ) ; p l o t ( [ E( i ) E ( i ) ], [ bottom top ], r ) ; p l o t ( [ P( i +1) P( i +1) ], [ bottom top ] ) ; p l o t ( [ P( i ) P( i +1) ], [ 0 0 ] ) ; end h o l d o f f % s e t h o l d o f f

23 We don t know if f can be negative. So the rectangles might need to point down. We do that by setting the bottom and top of the rectangles using an if test. bottom = 0 ; top = f (E( i ) ) ; i f f (E( i ) ) < 0 top = 0 ; bottom = f ( E ( i ) ) ; end

24 All together, we have h o l d on % s e t h o l d to on [ s i z e P,m] = s i z e (P) ; f o r i = 1 : s i z e P 1 % graph a l l t h e r e c t a n g l e s bottom = 0 ; top = f ( E ( i ) ) ; i f f ( E ( i ) ) < 0 top = 0 ; bottom = f ( E ( i ) ) ; end p l o t ( [ P( i ) P( i +1) ], [ f (E( i ) ) f (E( i ) ) ] ) ; p l o t ( [ P( i ) P( i ) ], [ bottom top ] ) ; p l o t ( [ E ( i ) E ( i ) ], [ bottom top ], r ) ; p l o t ( [ P( i +1) P( i +1) ], [ bottom top ] ) ; p l o t ( [ P( i ) P( i +1) ], [ 0 0 ] ) ; end y = l i n s p a c e (P( 1 ),P( s i z e P ), 101) ; % o v e r l a y t h e f u n c t i o n graph p l o t ( y, f ( y ) ) ; x l a b e l ( x a x i s ) ; y l a b e l ( y a x i s ) ; t i t l e ( Riemann Sum o v e r l a y e d on the f u n c t i o n graph ) ; h o l d o f f ;

25 To save typing, let s learn to use a Matlab function. In Matlab s file menu, choose create a new Matlab function which gives f u n c t i o n [ v a l u e 1, v a l u e 2,... ] = MyFunction ( arg1, arg2,... ) % s t u f f i n h e r e end [value1, value2,...] are returned values the function calculates that we want to save. (arg1, arg2,...) are things the function needs to do the calculations. They are called the arguments to the function. MyFunction is the name of the function. This function must be stored in the file MyFunction.m.

26 Our function returns the Riemann sum, RS, and use the arguments: our function f, the partition P and the Evaluation set E. Since only one value returned [RS] can be RS. f u n c t i o n RS = RiemannSum ( f, P, E) % comments a l w a y b e g i n w i t h a % matlab l i n e s h e r e end The name for the function RiemannSum must be used as the file name: i.e. we must use RiemannSum.m as the file name.

27 Here is a complete Riemann sum graphing function! f u n c t i o n RS = RiemannSum ( f, P, E) % f i n d Riemann sum dx = d i f f (P) ; RS = sum ( f ( E ). dx ) ; [ s i z e P,m] = s i z e (P) ; %g e t s i z e o f P a r t i t i o n c l f ; % c l e a r t h e o l d graph h o l d on % s e t h o l d to on f o r i = 1 : s i z e (P) 1 % graph a l l t h e r e c t a n g l e s bottom = 0 ; top = f ( E ( i ) ) ; i f f ( E ( i ) ) < 0 top = 0 ; bottom = f ( E ( i ) ) ; end p l o t ( [ P( i ) P( i +1) ], [ f (E( i ) ) f (E( i ) ) ] ) ; p l o t ( [ P( i ) P( i ) ], [ bottom top ] ) ; p l o t ( [ E ( i ) E ( i ) ], [ bottom top ], r ) ; p l o t ( [ P( i +1) P( i +1) ], [ bottom top ] ) ; p l o t ( [ P( i ) P( i +1) ], [ 0 0 ] ) ; end y = l i n s p a c e (P( 1 ),P( s i z e P ), 101) ; % o v e r l a y t h e f u n c t i o n graph p l o t ( y, f ( y ) ) ; x l a b e l ( x a x i s ) ; y l a b e l ( y a x i s ) ; t i t l e ( Riemann Sum o v e r l a y e d on the f u n c t i o n graph ) ; h o l d o f f ; end

28 A typical use is then >> f x ) s i n ( 3 x ) ; >> P = [ 1 ; 1. 5 ; 2. 1 ; 2. 8 ; 3. 0 ] ; >> E = [ 1. 2 ; 1. 7 ; 2. 5 ; 2. 9 ] ; >> RS = RiemannSum ( f, P, E ) ; This generates a pop up figure which we can save to a file.

29

30 To see graphically how the Riemann sums converge to the Riemann integral, let s write a new function: Riemann sums using uniform partitions and midpoint evaluation sets. f u n c t i o n RS = RiemannUniformSum ( f, a, b, n ) % s e t up a u n i f o r m p a r t i t i o n w i t h n+1 p o i n t s d e l t a x = ( b a ) /n ; P = [ a : d e l t a x : b ] ; % makes a row v e c t o r f o r i =1:n s t a r t = a+( i 1) d e l t a x ; s t o p = a+i d e l t a x ; E( i ) = 0. 5 ( s t a r t+s t o p ) ; end % send i n transpose of P and E so we use column v e c t o r s % b e c a u s e o r i g i n a l RiemannSum f u n c t i o n u s e s columns RS = RiemannSum ( f, P, E ) ; end We can then generate a sequence of Riemann sums for different values of n.

31 A typical session: >> f x ) s i n ( 3 x ) ; >> RS = RiemannUniformSum ( f, 1,4,10) >> RS = RiemannUniformSum ( f, 1,4,20) >> RS = RiemannUniformSum ( f, 1,4,40) >> RS = RiemannUniformSum ( f, 1,4,80)

32 Riemann sum with a uniform partition P 10 of [ 1, 4] for n = 10. The function is sin(3x) and the Riemann sum is

33 Riemann sum with a uniform partition P 20 of [ 1, 4] for n = 20. The function is sin(3x) and the Riemann sum is

34 Riemann sum with a uniform partition P 40 of [ 1, 4] for n = 40. The function is sin(3x) and the Riemann sum is

35 Riemann sum with a uniform partition P 80 of [ 1, 4] for n = 80. The function is sin(3x) and the Riemann sum is The actual value is 4 quite close! 1 sin(3x)dx = The n = 80 case is

36 The experiment we just did should help you understand better what we mean by the Riemann Integral. What we have shown is lim S(f, P n, E n ) = n for the particular sequence of uniform partitions P n with the particular choice of the evaluation sets E n being the midpoints of each of the subintervals determined by the partition. Note the P n = 5/n in each case. Of course, the Riemann integral existing means we get this value no matter what sequence of partitions we choose with associated evaluation sets as long as the norm of the partitions goes to 0.

37 Homework # 16 HW #16 Directions: For the given function f, partition P and evaluation set E, do the following: use Matlab to find S(f, P, E) for the partition P and evaluation set E. 1 Create a new word document called HW16.doc; don t use docx please. 2 Do the document in single space. 3 Do matlab fragments in bold font. 4 The document starts with your name, MTHSC 111, Summer Session I, 2012, HW 16 and the date. Then 1 State Problem 1. insert into your doc the matlab commands you use to solve the problem. Do this in bold. before each line of matlab add explanatory comments so I can check to see you know what you re doing. 2 State Problem 2. same stuff

38 Homework # 16 Something like this: Jim Peterson MTHSC 111 Summer Session I, 2012 HW 16 May 26, 2012 Problem 1: Let f (t) = sin(5t) on the interval [1, 3] with P = {1, 1.5, 2.0, 2.5, 3.0} and E = {1.2, 1.8, 2.3, 2.8}. % add e x p l a n a t i o n h e r e >> f x ) s i n (5 x ) ; % add e x p l a n a t i o n h e r e >> P = [ 1 ; 1. 5 ; 2. 0 ; 2. 5 ; 3. 0 ] ; % add e x p l a n a t i o n h e r e >> E = [ 1. 2 ; 1. 8 ; 2. 3 ; 2. 8 ] ; % add e x p l a n a t i o n h e r e >> dx = d i f f (P) ; % add e x p l a n a t i o n h e r e >> g = f ( E ). dx ; % add e x p l a n a t i o n h e r e >> RS = sum ( g ) RS =

39 Homework # 16 Actual HW # 16 1 Let f (t) = t on the interval [1, 3] with P = {1, 1.5, 2.0, 2.5, 3.0} and E = {1.2, 1.8, 2.3, 2.8}. 2 Let f (t) = sin(4t) on the interval [ 2, 3] with P = { 2, 1.6,.1, } and E = { 1.8, 1.3,.5, 1.1, 1.7, 2.6}. 3 Let f (t) = 3t 2 2t 7 on the interval [1, 2] with P = {1, 1.2, 1.5, 1.8, 2.0} and E = {1.1, 1.3, 1.7, 1.9}

40 Homework # 17 HW # 17 Directions: For the given function f, interval [a, b] and choice of n, you ll calculate the corresponding uniform partition Riemann sum using the functions RiemannSum in file RiemannSum.m and RiemannUniformSum in file RiemannUniformSum.m. Create a new file in Matlab Type the code for RiemannSum into this file. Save this file as RiemannSum.m in your directory. Create a new file in Matlab Type the code for RiemannUniformSum into this file. Save this file as RiemannUniformSum.m in your directory. If you are using the CCIT networked Matlab, you have to get Matlab to recognize the new files. So do this: >> cd.. >> cd n e a n d e r t h a l % use y o u r d i r e c t o r y s name h e r e If you are using your own Matlab you don t have to do this.

41 Homework # 17 HW # 17 Directions Continued: 1 Create a new word document called HW17.doc in single space with matlab fragments in bold font. 2 The document starts with your name, MTHSC 111, Summer Session I, 2012, HW 17 and the date. Then 1 State Problem 1. insert into your doc the matlab to solve the problem in bold. before each line of matlab add explanatory comments. For each value of n, do a save as and save the figure with a filename like HW17[ ].png where [ ] is where you put the number of the graph. Something like HW17a.png, HW17b.png etc. Insert this picture into the doc resizing as needed to make it look good. Explain in the doc what the picture shows. 2 State Problem 2. same stuff

42 Homework # 17 Something like this: Jim Peterson MTHSC 111 Summer Session I, 2012 HW 17 May 26, 2012 Problem 1: Let f (t) = sin(5t) on the interval [1, 3] with n = 10, 20, 40 and 60. % add e x p l a n a t i o n h e r e >> f x ) s i n (5 x ) ; % add e x p l a n a t i o n h e r e >> RS = RiemannUniformSum ( f, 1, 3, 1 0 ) % add e x p l a n a t i o n h e r e and i n s e r t graph >> RS = RiemannUniformSum ( f, 1, 3, 2 0 ) % add e x p l a n a t i o n h e r e and i n s e r t graph >> RS = RiemannUniformSum ( f, 1, 3, 4 0 ) % add e x p l a n a t i o n h e r e and i n s e r t graph >> RS = RiemannUniformSum ( f, 1, 3, 6 0 ) % add e x p l a n a t i o n h e r e and i n s e r t graph Then compare the Riemann sum for n = 60 with the true value of the Riemann integral and comment on how they compare.

43 Homework # 17 Actual HW # 17 1 Let f (t) = t 2 2t + 3 on the interval [ 2, 3] with n = 8, 16, 32 and 48. Compare the Riemann sum you get for n = 48 with the true value of the Riemann integral and comment on how they compare. 2 Let f (t) = sin(2t) on the interval [ 1, 5] with n = 10, 40, 60 and 80. Compare the Riemann sum you get for n = 80 with the true value of the Riemann integral and comment on how they compare. 3 Let f (t) = t 2 + 8t + 5 on the interval [ 2, 3] with n = 4, 12, 30 and 50. Compare the Riemann sum you get for n = 50 with the true value of the Riemann integral and comment on how they compare.

44 A Sample Matlab Session Start Matlab

45 A Sample Matlab Session Simple Riemann sums

46 A Sample Matlab Session Uniform Riemann sum with n = 10.

47 A Sample Matlab Session Plot that pops up for n = 10.

48 A Sample Matlab Session Uniform Riemann sum with n = 30.

49 A Sample Matlab Session Plot that pops up for n = 10.

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