## Very Brief Matlab Tutorial

```>> xv=(1:2:7)'		% create a column vector of x coordinates

xv =

1
3
5
7

>> yv=[1 2 3 7]'	% column vector of y coordinates

yv =

1
2
3
7

>> format compact	% to eliminate blank lines in output
>> A=[xv.^0 xv.^1 xv.^2] % cool! raise xv to powers and form matrix!
A =
1     1     1
1     3     9
1     5    25
1     7    49
>> flops(0)		% reset floating point operation (flop) counter

>> A\yv			% find least squares solution to A*c=yv, where
% A is 4x3, c is 3x1, yv is 4x1,
% (in this case fitting quadratic
% function to the four points in xv and yv vectors)
ans =
1.5125		% coeffs of quadratic function
-0.5500
0.1875
>> flops		% how many flops were used to solve?
ans =
200

>> plot(xv,yv)		% plot a curve

>> size(A)		% several ways to print the size of a matrix
ans =
4     3
>> sprintf('A matrix is %g by %g', size(A,1), size(A,2))
ans =
A matrix is 4 by 3
>> disp(sprintf('A matrix is %g by %g', size(A,1), size(A,2)))
A matrix is 4 by 3

>> [1 1e-8]
ans =
1.0000    0.0000	% note that 1e-8 is printed as 0
>> format short g
>> [ 1 1e-8]
ans =
1        1e-08	% but with "format short g", it's not

>> gausscost(10);	% call a user-defined function

% below is an example of a function definition
% note: semicolons on the end of a statement suppress printing

function cost = gausscost(n)
% return cost of Matlab's Gaussian elimination routine on n x n system

A = rand(n,n);	% create n x n random matrix
b = rand(n,1);	% create n x 1 random vector
flops(0);	% reset flop counter