MATLAB Primer

Second Edition

By

Kermit Sigmon


Unauthorized Translation by Nam Sun Wang for

Computer Methods in Chemical Engineering


This Primer is based on a TeX/dvi/ps copy freely distributed via anonymous ftp from:

I ported it to the HTML format suitable for a web browser for the convenience of ENCH250 students -- a rather time-consuming task for me but a great time-saving on-line device for the students. The original author does not want significant modifications to be made to his MATLAB primer, but he does allow minor changes to adopt to the local system. Note that we have MATLAB v4 in the College of Engineering's PC labs and MATLAB v5 on the Unix, but this particular document describes MATLAB v3.5. The same primer for MATLAB v4 is in the postscript format; I have not yet had the time to convert it. Sorry, you have to purchase the upgrade to MATLAB v5.



0. Introduction

MATLAB is an interactive, matrix-based system for scientific and engineering calculations. You can solve complex numerical problems without actually writing a program. The name MATLAB is an abbreviation for MATrix LABoratory.

The purpose of this Primer is to help you begin to use MATLAB. They can best be used hands-on. You are encouraged to work at the computer as you read the Primer and freely experiment with examples.

You should liberally use the on-line help facility for more detailed information. After entering MATLAB as described in section 1, the command help will display a list of functions for which on-line help is available; the command help functionname will give information about a specific function. The command help eig, for example, will give information about the eigenvalue function eig. You can preview some of the features of MATLAB by entering the command demo.

The scope and power of MATLAB go far beyond these notes. Eventually you will want to consult the MATLAB User's Guide and Reference Guide. The documentation which accompanies the Student Edition of MATLAB is an excellent source. Copies of the complete User's Guide are often available for review at locations such as consulting desks, terminal rooms, computing labs, and the reserve desk of the library. Consult your instructor or your local computing center to learn where the User's Guides are located at your institution.

MATLAB is available for a number of environments: Sun/Apollo/VAXstation/HP workstations, VAX, MicroVAX, Gould, PC and AT compatibles, 80386 and 80486 computers, Apple Macintosh, and several parallel machines. There is a relatively inexpensive Student Edition available from Prentice Hall publishers. The information in these notes applies generally to all of these environments.

While the second edition of the Primer is based on version 3.5 of MATLAB, it is compatible with version 4.0 with the fundamental differences noted. An edition of the Primer based on version 4.0 is under development.

The plain TeX source (and a PostScript file primer35.ps) of this second edition of the MATLAB Primer is available via anonymous ftp from math.ufl.edu as the file primer35.tex in the directory pub/matlab. If ftp is unavailable to you, it can be obtained via listserv by sending an email message to listserv@math.ufl.edu which contains the single line send matlab/primer35.tex. It can also be obtained by sending a request to the author at sigmon@math.ufl.edu. The latest edition of the Primer will always be available as indicated above as the file primer.tex. A Spanish version is also available there.

MATLAB is licensed by The MathWorks, Inc., Cochituate Place, 24 Prime Park Way, Natick, MA 01760, (508)653-1415, Fax: (508)653-2997, Email: info@mathworks.com. Copyright (C) 1989, 1992 by Kermit Sigmon


1. Accessing MATLAB

On most systems, after logging in one can enter MATLAB with the system command matlab and exit MATLAB with the command exit or quit. On a PC, for example, if properly installed, one may enter MATLAB with the command:

        C>  matlab
and exit it with the command:
        >>  quit

On systems permitting multiple processes, such as a Unix system, you will find it convenient, for reasons discussed in section 14, to keep both MATLAB and your local editor active. If you are working on a workstation which runs processes in multiple windows, you will want to keep MATLAB active in one window and your local editor active in another. You should consult your instructor or your local computer center for details of the local installation.


2. Entering matrices

MATLAB works with essentially only one kind of object-a rectangular numerical matrix with possibly complex entries; all variables represent matrices. In some situations, 1-by-1 matrices are interpreted as scalars and matrices with only one row or one column are interpreted as vectors.

Matrices can be introduced into MATLAB in several different ways:

For example, either of the statements
        A = [1 2 3; 4 5 6; 7 8 9]
and
        A = [
        1  2  3
        4  5  6
        7  8  9 ]
creates the obvious 3-by-3 matrix and assigns it to a variable A. Try it. The elements within a row of a matrix may be separated by commas as well as a blank.

When listing a number in exponential form (e.g. 2.34e-9), blank spaces must be avoided. Listing entries of a large matrix is best done in an M-file, where errors can be easily edited away (see sections 12 and 14).

The built-in functions rand, magic, and hilb, for example, provide an easy way to create matrices with which to experiment. The command rand(n) will create an n x n matrix with randomly generated entries distributed uniformly between 0 and 1, while rand(m,n) will create an m x n one. magic(n) will create an integral n x n matrix which is a magic square (rows and columns have common sum); hilb(n) will create the n x n Hilbert matrix, the king of ill-conditioned matrices ( m and n denote, of course, positive integers). Matrices can also be generated with a for-loop (see section 6 below).

Individual matrix and vector entries can be referenced with indices inside parentheses in the usual manner. For example, A(2,3) denotes the entry in the second row, third column of matrix A and x(3) denotes the third coordinate of vector x. Try it. A matrix or a vector will only accept positive integers as indices.


3. Matrix operations, array operations

The following matrix operations are available in MATLAB:

        +    addition
        -    subtraction
        *    multiplication
        ^    power
        '    transpose
        \    left division
        /    right division
These matrix operations apply, of course, to scalars (1-by-1 matrices) as well. If the sizes of the matrices are incompatible for the matrix operation, an error message will result, except in the case of scalar-matrix operations (for addition, subtraction, and division as well as for multiplication) in which case each entry of the matrix is operated on by the scalar.

The "matrix division" operations deserve special comment. If A is an invertible square matrix and b is a compatible column, resp. row, vector, then

        x=A \ b
is the solution of A*x=b and, resp.,
        x=b/A
is the solution of x*A=b . In left division, if A is square, then it is factored using Gaussian elimination and these factors are used to solve A*x=b. If A is not square, it is factored using Householder orthogonalization with column pivoting and the factors are used to solve the under- or over- determined system in the least squares sense. Right division is defined in terms of left division by
        b/A=(A' \ b')'
Array operations. The matrix operations of addition and subtraction already operate entry-wise but the other matrix operations given above do not-they are matrix operations. It is important to observe that these other operations,
        *  ,   ^  ,  \  , and /,
can be made to operate entry-wise by preceding them by a period. For example, either
        [1,2,3,4].*[1,2,3,4]
or
        [1,2,3,4].^2
will yield [1,4,9,16]. Try it. This is particularly useful when using Matlab graphics.


4. Statements, expressions, and variables; saving a session

MATLAB is an expression language; the expressions you type are interpreted and evaluated. MATLAB statements are usually of the form

        variable = expression,
or simply
        expression
Expressions are usually composed from operators, functions, and variable names. Evaluation of the expression produces a matrix, which is then displayed on the screen and assigned to the variable for future use. If the variable name and = sign are omitted, a variable ans (for answer) is automatically created to which the result is assigned.

A statement is normally terminated with the carriage return. However, a statement can be continued to the next line with three or more periods followed by a carriage return. On the other hand, several statements can be placed on a single line if separated by commas or semicolons.

If the last character of a statement is a semicolon, the printing is suppressed, but the assignment is carried out. This is essential in suppressing unwanted printing of intermediate results.

MATLAB is case-sensitive in the names of commands, functions, and variables. For example, solveUT is not the same as solveut.

The command who will list the variables currently in the workspace. A variable can be cleared from the workspace with the command clear variablename. The command clear alone will clear all nonpermanent variables.

The permanent variable eps (epsilon) gives the machine precision-about 10-16 on most machines. It is useful in determining tolerences for convergence of iterative processes.

A runaway display or computation can be stopped on most machines without leaving MATLAB with CTRL-C (CTRL-BREAK on a PC).

Saving a session. When one logs out or exits MATLAB all variables are lost. However, invoking the command save before exiting causes all variables to be written to a non-human-readable diskfile named matlab.mat. When one later reenters MATLAB, the command load will restore the workspace to its former state.


5. Matrix building functions

Convenient matrix building functions are

        eye(10)           identity matrix
        zeros(10)         matrix of zeros
        ones(10)          matrix of ones
        diag(A)           returns diagonal M.E. as vector
        triu(A)           upper triangular part of a matrix
        tril(A)           lower triangular part of a matrix
        rand(10)          randomly generated matrix
        hilb(5)           Hilbert matrix
        magic(5)          magic square
        toeplitz          see help toeplitz
For example, zeros(m,n) produces an m-by-n matrix of zeros and zeros(n) produces an n-by-n one; if A is a matrix, then zeros(A) produces a matrix of zeros of the same size as A .

If x is a vector, diag(x) is the diagonal matrix with x down the diagonal; if A is a square matrix, then diag(A) is a vector consisting of the diagonal of A . What is diag(diag(A))? Try it.

Matrices can be built from blocks. For example, if A is a 3-by-3 matrix, then

        B = [A, zeros(3,2); zeros(2,3), eye(2)]
will build a certain 5-by-5 matrix. Try it.


6. For, while, if - and relations

In their basic forms, these MATLAB flow control statements operate like those in most computer languages.

For. For example, for a given n, the statement

        x = []; for i = 1:n, x=[x,i^2 ], end
or
        x = [];
        for i = 1:n
            x = [x,i^2 ]
        end
will produce a certain n-vector and the statement
        x = []; for i = n:-1:1, x=[x,i^2 ], end
will produce the same vector in reverse order. Try them. Note that a matrix may be empty (such as x = []). The statements
        for i = 1:m
             for j = 1:n
                 H(i, j) = 1/(i+j-1);
             end
        end
        H
will produce and print to the screen the m-by-n hilbert matrix. The semicolon on the inner statement suppresses printing of unwanted intermediate results while the last H displays the final result.

While. The general form of a while loop is

        while   relation
          statements
        end
The statements will be repeatedly executed as long as the relation remains true. For example, for a given number a, the following will compute and display the smallest nonnegative integer n such that 2n >=a:
        n = 0;
        while  2^n < a
             n = n + 1;
        end
        n
If. The general form of a simple if statement is
        if relation
          statements
        end
The statements will be executed only if the relation is true. Multiple branching is also possible, as is illustrated by
         if n < 0
              parity = 0;
         elseif  rem(n,2) == 0
              parity = 2;
         else
              parity = 1;
         end
In two-way branching the elseif portion would, of course, be omitted.

Relations. The relational operators in MATLAB are

         <      less than
         >      greater than
         <=     less than or equal
         >=     greater than or equal
         ==     equal
         ~=     not equal.
Note that "=" is used in an assignment statement while "==" is used in a relation. Relations may be connected or quantified by the logical operators
         &      and
         |      or
         ~      not.
When applied to scalars, a relation is actually the scalar 1 or 0 depending on whether the relation is true or false. Try 3 < 5, 3 > 5, 3 == 5, and 3 == 3. When applied to matrices of the same size, a relation is a matrix of 0's and 1's giving the value of the relation between corresponding entries. Try a = rand(5), b = triu(a), a == b.

A relation between matrices is interpreted by while and if to be true if each entry of the relation matrix is nonzero. Hence, if you wish to execute statement when matrices A and B are equal you could type

        if  A == B
            statement
        end
but if you wish to execute statement when A and B are not equal, you would type
        if any(any(A ~ B))
           statement
        end
or, more simply,
        if A == B else
           statement
        end
Note that the seemingly obvious
        if  A ~= B, statement, end
will not give what is intended since statement would execute only if each of the corresponding entries ofA and B differ. The functions any and all can be creatively used to reduce matrix relations to vectors or scalars. Two any's are required above since any is a vector operator (see
section 8).

The for statement permits any matrix to be used instead of 1:n. See the User's Guide for details of how this feature expands the power of the for statement.


7. Scalar functions

Certain MATLAB functions operate essentially on scalars, but operate element-wise when applied to a matrix. The most common such functions are

        sin    asin    exp                 abs       round
        cos    acos    log (natural log)   sqrt      floor
        tan    atan    rem (remainder)     sign      ceil


8. Vector functions

Other MATLAB functions operate essentially on a vector (row or column), but act on an m-by-n matrix (m>=2) in a column-by-column fashion to produce a row vector containing the results of their application to each column. Row-by-row action can be obtained by using the transpose; for example, mean(A')'. A few of these functions are

        max        sum       median     any
        min        prod      mean       all
        sort                 std
For example, the maximum entry in a matrix A is given by max(max(A)) rather than max(A). Try it.


9. Matrix functions

Much of MATLAB's power comes from its matrix functions. The most useful ones are

        eig         eigenvalues and eigenvectors
        chol        cholesky factorization
        svd         singular value decomposition
        inv         inverse
        lu          LU factorization
        qr          QR factorization
        hess        hessenberg form
        schur       schur decomposition
        rref        reduced row echelon form
        expm        matrix exponential
        sqrtm       matrix square root
        poly        characteristic polynomial
        det         determinant
        size        size
        norm        1-norm, 2-norm, F-norm, infinity-norm
        cond        condition number in the 2-norm
        rank        rank
MATLAB functions may have single or multiple output arguments. For example,
        y = eig(A)     or simply      eig(A)
produces a column vector containing the eigenvalues of A while
        [U,D] = eig(A)
produces a matrix U whose columns are the eigenvectors of A and a diagonal matrix D with the eigenvalues of A on its diagonal. Try it.


10. Command line editing and recall

The command line in MATLAB can be easily edited. The cursor can be positioned with the left/right arrows and the Backspace (or Delete) key used to delete the character to the left of the cursor. Other editing features are also available. On a PC try the Home, End, and Delete keys; on other systems see help cedit or type cedit.

A convenient feature is use of the up/down arrows to scroll through the stack of previous commands. One can, therefore, recall a previous command line, edit it, and execute the revised command line. For small routines, this is much more convenient that using an M-file which requires moving between MATLAB and the editor (see sections 12 and 14). For example, flopcounts (see section 15) for computing the inverse of matrices of various sizes could be compared by repeatedly recalling, editing, and executing

        a = rand(8); flops(0), inv(a); flops
If one wanted to compare plots of the functions y = sin mx and y = sin nx on the interval [0,2*pi] for various m and n, one might do the same for the command line:
        m=2; n=3; x=0:.01:2*pi; y=sin(m*x); z=cos(n*x); plot(x,y,x,z)


11. Submatrices and colon notation

Vectors and submatrices are often used in MATLAB to achieve fairly complex data manipulation effects. Colon notation" (which is used both to generate vectors and reference submatrices) and subscripting by vectors are keys to efficient manipulation of these objects. Creative use of these features permits one to minimize the use of loops (which slows MATLAB) and to make code simple and readable. Special effort should be made to become familiar with them.

The expression 1:5 (met earlier in for statements) is actually the row vector [1 2 3 4 5]. The numbers need not be integers nor the increment one. For example,

        0.2:0.2:1.2
gives [0.2, 0.4, 0.6, 0.8, 1.0, 1.2], and
        5:-1:1  gives   [5 4 3 2 1].
The following statements will, for example, generate a table of sines. Try it.
        x = [0.0:0.1:2.0]' ;
        y = sin(x);
        [x y]
Note that since sin operates entry-wise, it produces a vector y from the vector x.

The colon notation can be used to access submatrices of a matrix. For example,

A(1:4,3) is the column vector consisting of the first four entries of the third column of A.
A colon by itself denotes an entire row or column:
A(:,3) is the third column of A , and A(1:4,:) is the first four rows.
Arbitrary integral vectors can be used as subscripts:
A(:,[2 4]) contains as columns, columns 2 and 4 of A .
Such subscripting can be used on both sides of an assignment statement:
A(:,[2 4 5]) = B(:,1:3) replaces columns 2,4,5 of A with the first three columns of B. Note that the entire altered matrix A is printed and assigned. Try it.
Columns 2 and 4 of A can be multiplied on the right by the 2-by-2 matrix [1 2;3 4]:
A(:,[2,4]) = A(:,[2,4])*[1 2;3 4]
Once again, the entire altered matrix is printed and assigned.

If x is an n-vector, what is the effect of the statement x = x(n:-1:1)? Try it.

To appreciate the usefulness of these features, compare these MATLAB statements with a Pascal, FORTRAN, or C routine to effect the same.


12. M-files

MATLAB can execute a sequence of statements stored on diskfiles. Such files are called M-files" because they must have the file type of .m" as the last part of their filename. Much of your work with MATLAB will be in creating and refining M-files.

There are two types of M-files: script files and function files.

Script files. A script file consists of a sequence of normal MATLAB statements. If the file has the filename, say, rotate.m, then the MATLAB command rotate will cause the statements in the file to be executed. Variables in a script file are global and will change the value of variables of the same name in the environment of the current MATLAB session.

Script files are often used to enter data into a large matrix; in such a file, entry errors can be easily edited out. If, for example, one enters in a diskfile data.m

        A = [
        1 2 3 4
        5 6 7 8
        ];
then the MATLAB statement data will cause the assignment given in data.m to be carried out.

An M-file can reference other M-files, including referencing itself recursively.

Function files. Function files provide extensibility to MATLAB. You can create new functions specific to your problem which will then have the same status as other MATLAB functions. Variables in a function file are by default local. However, version 4.0 permits a variable to be declared global.

We first illustrate with a simple example of a function file.

        function  a = randint(m,n)
        %RANDINT  Randomly generated integral matrix.
        %         randint(m,n) returns an m-by-n such matrix with entries
        %         between 0 and 9.
        a = floor(10*rand(m,n));
A more general version of this function is the following:
        function  a = randint(m,n,a,b)
        %RANDINT  Randomly generated integral matrix.
        %         randint(m,n) returns an m-by-n such matrix with entries
        %         between 0 and 9.
        %         rand(m,n,a,b) return entries between integers  a  and  b .
        if nargin < 3, a = 0; b = 9; end
        a = floor((b-a+1)*rand(m,n)) + a;
This should be placed in a diskfile with filename randint.m (corresponding to the function name). The first line declares the function name, input arguments, and output arguments; without this line the file would be a script file. Then a MATLAB statement z = randint(4,5), for example, will cause the numbers 4 and 5 to be passed to the variables a and b in the function file with the output result being passed out to the variable z. Since variables in a function file are local, their names are independent of those in the current MATLAB environment.

Note that use of nargin ("number of input arguments") permits one to set a default value of an omitted input variable-such as a and b in the example.

A function may also have multiple output arguments. For example:

        function  [mean, stdev] = stat(x)
        % STAT  Mean and standard deviation
        %      For a vector x, stat(x) returns the
        %      mean and standard deviation of  x.
        %      For a matrix x, stat(x) returns two row vectors containing,
        %      respectively, the mean and standard deviation of each column.
        [m  n] = size(x);
        if m == 1
              m = n;     % handle case of a row vector
        end
        mean = sum(x)/m;
        stdev = sqrt(sum(x.^ 2)/m - mean.^2);
Once this is placed in a diskfile stat.m, a MATLAB command [xm, xd] = stat(x), for example, will assign the mean and standard deviation of the entries in the vector x to m and xd, respectively. Single assignments can also be made with a function having multiple output arguments. For example, xm = stat(x) (no brackets needed around xm) will assign the mean of x to xm.

The % symbol indicates that the rest of the line is a comment; MATLAB will ignore the rest of the line. However, the first few comment lines, which document the M-file, are available to the on-line help facility and will be displayed if, for example, help stat is entered. Such documentation should always be included in a function file.

This function illustrates some of the MATLAB features that can be used to produce efficient code. Note, for example, that x.^2 is the matrix of squares of the entries of x, that sum is a vector function (section 8), that sqrt is a scalar function (section 7), and that the division in sum(x)/m is a matrix-scalar operation.

The following function, which gives the greatest common divisor of two integers via the Euclidean algorithm, illustrates the use of an error message (see the next section).

        function  a = gcd(a,b)
        % GCD  Greatest common divisor
        %      gcd(a,b) is the greatest common divisor of
        %      the integers a and b, not both zero.
        a = round(abs(a));  b = round(abs(b));
        if  a == 0 & b == 0
            error('The gcd is not defined when both numbers are zero')
        else
            while b  ~= 0
                r = rem(a,b);
                a = b;  b = r;
            end
        end
Some more advanced features are illustrated by the following function. As noted earlier, some of the input arguments of a function-such as tol in the example, may be made optional through use of nargin ("number of input arguments"). The variable nargout can be similarly used. Note that the fact that a relation is a number (1 when true; 0 when false) is used and that, when while or if evaluates a relation, "nonzero" means "true" and 0 means "false". Finally, the MATLAB function feval permits one to have as an input variable a string naming another function.
        function  [b, steps] = bisect(fun, x, tol)
        %BISECT Zero of a function of one variable via the bisection method.
        %         bisect(fun,x) returns a zero of the function.  fun is a string
        %         containing the name of a real-valued function of a single
        %         real variable; ordinarily functions are defined in M-files.
        %         x  is a starting guess.  The value returned is near a point
        %         where  fun  changes sign.  For example,
        %         bisect('sin',3) is pi.  Note the quotes around sin.
        %
        %         An optional third input argument sets a tolerence for the
        %         relative accuracy of the result.  The default is eps.
        %         An optional second output argument gives a matrix containing a
        %         trace of the steps; the rows are of form  [c f(c)].

        % Initialization
        if nargin < 3, tol = eps; end
        trace = (nargout == 2);
        if x  ~= 0, dx = x/20; else, dx = 1/20; end
        a = x - dx;  fa = feval(fun,a);
        b = x + dx;  fb = feval(fun,b);

        % Find change of sign.
        while (fa > 0) == (fb > 0)
             dx = 2.0*dx;
             a = x - dx;  fa = feval(fun,a);
             if (fa > 0) ~= (fb > 0), break, end
             b = x + dx;  fb = feval(fun,b);
        end
        if trace, steps = [a fa; b fb]; end

        % Main loop
        while  abs(b - a) > 2.0*tol*max(abs(b),1.0)
             c = a + 0.5*(b - a);  fc = feval(fun,c);
             if trace, steps = [steps; [c fc]]; end
             if (fb > 0) == (fc > 0)
                  b = c;  fb = fc;
               else
                 a = c;  fa = fc;
             end
        end
Some of MATLAB's functions are built-in while others are distributed as M-files. The actual listing of any M-file-MATLAB's or your own-can be viewed with the MATLAB command type functionname. Try entering type eig, type vander, and type rank.


13. Text strings, error messages, input

Text strings are entered into MATLAB surrounded by single quotes. For example,

        s = 'This is a test'
assigns the given text string to the variable s.

Text strings can be displayed with the function disp. For example:

        disp('this message is hereby displayed')
Error messages are best displayed with the function error
        error('Sorry, the matrix must be symmetric')
since when placed in an M-File, it causes execution to exit the M-file.

In an M-file the user can be prompted to interactively enter input data with the function input. When, for example, the statement

        iter = input('Enter the number of iterations:  ')
is encountered, the prompt message is displayed and execution pauses while the user keys in the input data. Upon pressing the return key, the data is assigned to the variable iter and execution resumes.


14. Managing M-files

While using MATLAB one frequently wishes to create or edit an M-file and then return to MATLAB. One wishes to keep MATLAB active while editing a file since otherwise all variables would be lost upon exiting.

This can be easily done using the !-feature. If, while in MATLAB, you precede it with an !, any system command-such as those for editing, printing, or copying a file-can be executed without exiting MATLAB. If, for example, the system command ed accesses your editor, the MATLAB command

        >> !ed rotate.m
will let you edit the file named rotate.m using your local editor. Upon leaving the editor, you will be returned to MATLAB just where you left it.

As noted in section 1, on systems permitting multiple processes, such as one running Unix, it may be preferable to keep both MATLAB and your local editor active, keeping one process suspended while working in the other. If these processes can be run in multiple windows, as on a workstation, you will want to keep MATLAB active in one window and your editor active in another.

You may consult your instructor or your local computing center for details of the local installation.

Version 4.0 has many debbugging tools. See help dbtype and references given there.

When in MATLAB, the command dir will list the contents of the current directory while the command what will list only the M-files in the directory. The MATLAB commands delete and type can be used to delete a diskfile and print a file to the screen, respectively, and chdir can be used to change the working directory. While these commands may duplicate system commands, they avoid the use of an !.

M-files must be accessible to MATLAB. On most mainframe or workstation network installations, personal M-files which are stored in a subdirectory of one's home directory named matlab will be accessible to MATLAB from any directory in which one is working. See the discussion of MATLABPATH in the User's Guide for further information.


15. Comparing efficiency of algorithms: flops and etime

Two measures of the efficiency of an algorithm are the number of floating point operations (flops) performed and the elapsed time.

The MATLAB function flops keeps a running total of the flops performed. The command flops(0) (not flops = 0!) will reset flops to 0. Hence, entering flops(0) immediately before executing an algorithm and flops immediately after gives the flop count for the algorithm.

The MATLAB function clock gives the current time accurate to a hundreth of a second (see help clock). Given two such times t1 and t2, etime(t2,t1) gives the elapsed time from t1 to t2. One can, for example, measure the time required to solve a given linear system Ax=b using Gaussian elimination as follows:

        t = clock; x = A \ b; time = etime(clock,t)
You may wish to compare this time-and flop count-with that for solving the system using x = inv(A)*b;. Try it. Version 4.0 has the more convenient tic and toc.

It should be noted that, on timesharing machines, etime may not be a reliable measure of the efficiency of an algorithm since the rate of execution depends on how busy the computer is at the time.


16. Output format

While all computations in MATLAB are performed in double precision, the format of the displayed output can be controlled by the following commands.

        format short     fixed point with 4 decimal places (the default)
        format long      fixed point with 14 decimal places
        format short e   scientific notation with 4 decimal places
        format long e    scientific notation with 15 decimal places
Once invoked, the chosen format remains in effect until changed.

The command format compact will suppress most blank lines allowing more information to be placed on the screen or page. It is independent of the other format commands.


17. Hardcopy

Hardcopy is most easily obtained with the diary command. The command

        diary {\it filename}
causes what appears subsequently on the screen (except graphics) to be written to the named diskfile (if the filename is omitted it will be written to a default file named diary) until one gives the command diary off; the command diary on will cause writing to the file to resume, etc. When finished, you can edit the file as desired and print it out on the local system. The !-feature (see
section 14) will permit you to edit and print the file without leaving MATLAB.


18. Graphics

MATLAB can produce both planar plots and 3-D mesh surface plots. To preview some of these capabilities in version 3.5, enter the command plotdemo.

Planar plots. The plot command creates linear x-y plots; if x and y are vectors of the same length, the command plot(x,y) opens a graphics window and draws an x-y plot of the elements of x versus the elements of y. You can, for example, draw the graph of the sine function over the interval -4 to 4 with the following commands:

        x = -4:.01:4;  y = sin(x);  plot(x,y)
Try it. The vector x is a partition of the domain with meshsize 0.01 while y is a vector giving the values of sine at the nodes of this partition (recall that sin operates entrywise).

When in the graphics screen, pressing any key will return you to the command screen while the command shg (show graph) will then return you to the current graphics screen. If your machine supports multiple windows with a separate graphics window, you will want to keep the graphics window exposed-but moved to the side-and the command window active.

As a second example, you can draw the graph of y=e-x^2 over the interval -1.5 to 1.5 as follows:

        x = -1.5:.01:1.5;  y = exp(-x.^2);  plot(x,y)
Note that one must precede the power-to sign by a period to ensure that it operates entrywise (see
section 3).

Plots of parametrically defined curves can also be made. Try, for example,

        t=0:.001:2*pi; x=cos(3*t); y=sin(2*t); plot(x,y)
The command grid will place grid lines on the current graph.

The graphs can be given titles, axes labeled, and text placed within the graph with the following commands which take a string as an argument.

        title         graph title
        xlabel        x-axis label
        ylabel        y-axis label
        gtext         interactively-positioned text
        text          position text at specified coordinates
For example, the command
        title('Best Least Squares Fit')
gives a graph a title. The command gtext('The Spot') allows a mouse or the arrow keys to position a crosshair on the graph, at which the text will be placed when any key is pressed.

By default, the axes are auto-scaled. This can be overridden by the command axis. If c=[xmin,xmax,ymin,ymax] is a 4-element vector, then axis(c) sets the axis scaling to the precribed limits. By itself, axis freezes the current scaling for subsequent graphs; entering axis again returns to auto-scaling. The command axis('square') ensures that the same scale is used on both axes. In version 4.0, axis has been significantly changed; see help axis.

Two ways to make multiple plots on a single graph are illustrated by

        x=0:.01:2*pi;y1=sin(x);y2=sin(2*x);
        y3=sin(4*x);plot(x,y1,x,y2,x,y3)
and by forming a matrix Y containing the functional values as columns
        x=0:.01:2*pi; Y=[sin(x)', sin(2*x)', sin(4*x)']; plot(x,Y)
Another way is with hold. The command hold freezes the current graphics screen so that subsequent plots are superimposed on it. Entering hold again releases the "hold." The commands hold on and hold off are also available in version 4.0.

One can override the default linetypes and pointtypes. For example,

        x=0:.01:2*pi; y1=sin(x); y2=sin(2*x); y3=sin(4*x);
        plot(x,y1,'--',x,y2,':',x,y3,'+')
renders a dashed line and dotted line for the first two graphs while for the third the symbol is placed at each node. The line- and mark-types are
Linetypes: solid (-), dashed (-). dotted (:), dashdot (-.)

Marktypes: point (.), plus (), star (*), circle (o), x-mark (x)

See help plot for line and mark colors.

The command subplot can be used to partition the screen so that up to four plots can be viewed simultaneously. See help subplot.

Graphics hardcopy A hardcopy of the graphics screen can be most easily obtained with the MATLAB command print. It will send a high-resolution copy of the current graphics screen to the printer, placing the graph on the top half of the page.

In version 4.0 the meta and gpp commands described below have been absorbed into the print command. See help print.

Producing unified hard copy of several plots requires more effort. The Matlab command meta filename stores the current graphics screen in a file named filename.met (a "metafile") in the current directory. Subsequent meta (no filename) commands append a new current graphics screen to the previously named metafile. This metafile-which may now contain several plots-may be processed later with the graphics post-processor (GPP) program to produce high-resolution hardcopy, two plots per page.

The program GPP (graphics post-processor) is a system command, not a MATLAB command. However, in practice it is usually involked from within MATLAB using the "!" feature (see section 14). It acts on a device-independent metafile to produce an output file appropriate for many different hardcopy devices.

The selection of the specific hardcopy device is made with the option key "/d". For example, the system commands

        gpp  filename  /dps
        gpp  filename  /djet
will produce files filename.ps and filename.jet suitable for printing on, respectively, PostScript and HP LaserJet printers. They can be printed using the usual printing command for the local system-for example, lpr filename.ps on a Unix system. Entering the system command gpp with no arguments gives a list of all supported hardcopy devices. On a PC, most of this can be automated by appropriately editing the file gpp.bat distributed with MATLAB. (Obsolent in MATLAB Version v4.0 and above.)

3-D mesh plots. Three dimensional mesh surface plots are drawn with the function mesh. The command mesh(z) creates a three-dimensional perspective plot of the elements of the matrix z. The mesh surface is defined by the z-coordinates of points above a rectangular grid in the x-y plane. Try mesh(eye(10)).

To draw the graph of a function z=f(x,y) over a rectangle, one first defines vectors xx and yy which give partitions of the sides of the rectangle. With the function meshdom (mesh domain; called meshgrid in version 4.0) one then creates a matrix x, each row of which equals xx and whose column length is the length of yy, and similarly a matrix y, each column of which equals yy, as follows:

        [x,y] = meshdom(xx,yy);
One then computes a matrix z, obtained by evaluating f entrywise over the matrices x and y, to which mesh can be applied.

You can, for example, draw the graph of z=e-x^2-y^2 over the square [-2,2] x [-2,2] as follows (try it):

        xx = -2:.1:2;
        yy = xx;
        [x,y] = meshdom(xx,yy);
        z = exp(-x.^2 - y.$^2);
        mesh(z)
One could, of course, replace the first three lines of the preceding with
        [x,y] = meshdom(-2:.1:2, -2:.1:2);
You are referred to the User's Guide for further details regarding mesh.

In version 4.0, the 3-D graphics capabilities of MATLAB have been considerably expanded. Consult the on-line help for plot3, mesh, and surf.


19. Reference

There are many MATLAB features which cannot be included in these introductory notes. Listed below are some of the MATLAB functions and operators available, grouped by subject area (Source: MATLAB User's Guide, version 3.5). Use the on-line help facility or consult the User's Guide for more detailed information on the functions.

There are many functions beyond these. There exist, in particular, several "toolboxes" of functions for specific areas; included among such are signal processing, control systems, robust-control, system identification, optimization, splines, chemometrics, mu-analysis and synthesis, state-space identification, and neural networks. (The toolboxes, which are optional, may not be installed on your system.) These can be explored via the command help.

General

   help        help facility
   demo        run demonstrations
   who         list variables in memory
   what        list M-files on disk
   size        row and column dimensions
   length      vector length
   clear       clear workspace
   computer    type of computer
   ^C          local abort
   exit        exit MATLAB
   quit        same as exit


Matrix/Array Operators

   Matrix Operators               Array Operators
   ---------------------------------------------------
   +    addition                  +    addition
   -    subtraction               -    subtraction
   *    multiplication            .*   multiplication
   /    right division            ./   right division
   \    left division             .\   left division
   ^    power                     .^   power
   '    conjugate transpose       .'   transpose


Relational and Logical Operators

   <           less than
   <=          less than or equal
   >           greater than
   >=          greater than or equal
   ==          equal
   ~=          not equal
   &           and
   |           or
   ~           not


Special Characters

   =           assignment statement
   [           used to form vectors and matrices
   ]           see [
   (           arithmetic expression precedence
   )           see (
   .           decimal point
   ...         continue statement to next line
   ,           separate subscripts and function arguments
   ;           end rows, suppress printing
   %           comments
   :           subscripting, vector generation
   !           execute operating system command


Special Values

   ans         answer when expression not assigned
   eps         floating point precision
   pi          pi
   i, j        sqrt(-1)
   inf         infinity
   NaN         Not-a-Number
   clock       wall clock
   date        date
   flops       floating point operation count
   nargin      number of function input arguments
   nargout     number of function output arguments


Disk Files

   chdir       change current directory
   delete      delete file
   diary       diary of the session
   dir         directory of files on disk
   load        load variables from file
   save        save variables to file
   type        list function or file
   what        show M-files on disk
   fprintf     write to a file
   pack        compact memory via save


Special Matrices

   compan      companion
   diag        diagonal
   eye         identity
   gallery     esoteric
   hadamard    Hadamard
   hankel      Hankel
   hilb        Hilbert
   invhilb     inverse Hilbert
   linspace    linearly spaced vectors
   logspace    logarithmically spaced vectors
   magic       magic square
   meshdom     domain for mesh points
   ones        constant
   pascal      Pascal
   rand        random elements
   toeplitz    Toeplitz
   vander      Vandermonde
   zeros       zero


Matrix Manipulation

   rot90       rotation
   fliplr      flip matrix left-to-right
   flipud      flip matrix up-to-down
   diag        diagonal matrices
   tril        lower triangular part
   triu        upper triangular part
   reshape     reshape
   .'          transpose
   :           convert matrix to single column; A(:)


Relational and Logical Functions

   any         logical conditions
   all         logical conditions
   find        find array indices of logical values
   isnan       detect NaNs
   finite      detect infinities
   isempty     detect empty matrices
   isstr       detect string variables
   strcmp      compare string variables


Control Flow

   if          conditionally execute statements
   elseif      used with if
   else        used with if
   end         terminate bif, for, while
   for         repeat statements a number of times
   while       do while
   break       break out of for and while loops
   return      return from functions
   pause       pause until key pressed


Programming and M-files

   input       get numbers from keyboard
   keyboard    call keyboard as M-file
   error       display error message
   function    define function
   eval        interpret text in variables
   feval       evaluate function given by string
   echo        enable command echoing
   exist       check if variables exist
   casesen     set case sensitivity
   global      define global variables
   startup     startup M-file
   getenv      get environment string
   menu        select item from menu
   etime       elapsed time


Text and Strings

   abs         convert string to ASCII values
   eval        evaluate text macro
   num2str     convert number to string
   int2str     convert integer to string
   setstr      set flag indicating matrix is a string
   sprintf     convert number to string
   isstr       detect string variables
   strcomp     compare string variables
   hex2num     convert hex string to number


Command Window

   clc         clear command screen
   home        move cursor home
   format      set output display format
   disp        display matrix or text
   fprintf     print formatted number
   echo        enable command echoing


Graph Paper

   plot        linear X-Y plot
   loglog      loglog X-Y plot
   semilogx    semi-log X-Y plot
   semilogy    semi-log X-Y plot
   polar       polar plot
   mesh        3-dimensional mesh surface
   contour     contour plot
   meshdom     domain for mesh plots
   bar         bar charts
   stairs      stairstep graph
   errorbar    add error bars


Graph Annotation

   title       plot title
   xlabel      x-axis label
   ylabel      y-axis label
   grid        draw grid lines
   text        arbitrarily position text
   gtext       mouse-positioned text
   ginput      graphics input


Graph Window Control

   axis        manual axis scaling
   hold        hold plot on screen
   shg         show graph window
   clg         clear graph window
   subplot     split graph window


Graph Window Hardcopy

   print       send graph to printer
   prtsc       screen dump
   meta        graphics metafile


Elementary Math Functions

   abs         absolute value or complex magnitude
   angle       phase angle
   sqrt        square root
   real        real part
   imag        imaginary part
   conj        complex conjugate
   round       round to nearest integer
   fix         round toward zero
   floor       round toward -infinity
   ceil        round toward infinity
   sign        signum function
   rem         remainder
   exp         exponential base e
   log         natural logarithm
   log10       log base 10


Trigonometric Functions

   sin         sine
   cos         cosine
   tan         tangent
   asin        arcsine
   acos        arccosine
   atan        arctangent
   atan2       four quadrant arctangent
   sinh        hyperbolic sine
   cosh        hyperbolic cosine
   tanh        hyperbolic tangent
   asinh       hyperbolic arcsine
   acosh       hyperbolic arccosine
   atanh       hyperbolic arctangent


Special Functions

   bessel      bessel function
   gamma       gamma function
   rat         rational approximation
   erf         error function
   inverf      inverse error function
   ellipk      complete elliptic integral of first kind
   ellipj      Jacobian elliptic integral


Decompositions and Factorizations

   balance     balanced form
   backsub     backsubstitution
   cdf2rdf     convert complex-diagonal to real-diagonal
   chol        Cholesky factorization
   eig         eigenvalues and eigenvectors
   hess        Hessenberg form
   inv         inverse
   lu          factors from Gaussian elimination
   nnls        nonnegative least squares
   null        null space
   orth        orthogonalization
   pinv        pseudoinverse
   qr          orthogonal-triangular decomposition
   qz          QZ algorithm
   rref        reduced row echelon form
   schur       Schur decomposition
   svd         singular value decomposition


Matrix Conditioning

   cond        condition number in 2-norm
   norm        1-norm,2-norm,F-norm, infinity-norm
   rank        rank
   rcond       condition estimate (reciprocal)


Elementary Matrix Functions

   expm        matrix exponential
   logm        matrix logarithm
   sqrtm       matrix square root
   funm        arbitrary matrix function
   poly        characteristic polynomial
   det         determinant
   trace       trace
   kron        Kronecker tensor product


Polynomials

   poly        characteristic polynomial
   roots       polynomial roots---companion matrix method
   roots1      polynomial roots---Laguerre's method
   polyval     polynomial evaluation
   polyvalm    matrix polynomial evaluation
   conv        multiplication
   deconv      division
   residue     partial-fraction expansion
   polyfit     polynomial curve fitting


Column-wise Data Analysis

   max         maximum value
   min         minimum value
   mean        mean value
   median      median value
   std         standard deviation
   sort        sorting
   sum         sum of elements
   prod        product of elements
   cumsum      cumulative sum of elements
   cumprod     cumulative product of elements
   diff        approximate derivatives
   hist        histograms
   corrcoef    correlation coefficients
   cov         covariance matrix
   cplxpair    reorder into complex pairs


Signal Processing

   abs         complex magnitude
   angle       phase angle
   conv        convolution
   corrcoef    correlation coefficients
   cov         covariance
   deconv      deconvolution
   fft         radix-2 fast Fourier transform
   fft2        two-dimensional FFT
   ifft        inverse fast Fourier transform
   ifft2       inverse 2-D FFT
   fftshift    FFT rearrangement

Numerical Integration

   quad        numerical function integration
   quad8       numerical function integration


Differential Equation Solution

   ode23       2nd/3rd order Runge-Kutta method
   ode45       4th/5th order Runge-Kutta-Fehlberg method


Nonlinear Equations and Optimization

   fmin        minimum of a function of one variable
   fmins       minimum of a multivariable function
   fsolve      solution of a system of nonlinear equations
               (zeros of a multivariable function)
   fzero       zero of a function of one variable


Interpolation

   spline      cubic spline
   table1      1-D table look-up
   table2      2-D table look-up


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Computer Methods in Chemical Engineering -- MATLAB Primer
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