Matlab Cheat Sheet

Some nifty commands

clc Clear command window

clear Clear system memory

clear x Clear x from memory

commandwindow open/select commandwindow

whos lists data structures

whos x size, bytes, class and attributes of x

ans Last result

close all closes all ﬁgures

close(H) closes ﬁgure H

winopen(pwd) Open current folder

class(obj) returns objects class

save filename saves all variables to .mat ﬁle

save filename x,y saves x,y variables to .mat ﬁle

save -append filename x appends x to .mat ﬁle

load filename loads all variables from .mat ﬁle

ver Lists version and toolboxes

beep Makes the beep sound

doc function Help/documentation for function

docsearch string search documentation

web google.com opens webadress

inputdlg Input dialog box

methods(A) list class methods for A

Statistical commands

distrnd random numbers from dist

distpdf pdf from dist

distcdf cdf dist

distrnd random numbers from dist

hist(x) histogram of x

histfit(x) histogram and

*Standard distributions (dist): norm, t, f, gam, chi2, bino

*Standard functions: mean,median,var,cov(x,y),corr(x,y),

*quantile(x,p) is not textbook version.

(It uses interpolation for missing quantiles.

Keyboard shortcuts

edit filename Opens ﬁlename in editor

Alt Displays hotkeys

F1 Help/documentation for highlighted function

F5 Run code

F9 Run highlighted code

F10 Run code line

F11 Run code line, enter functions

Shift+F5 Leave debugger

F12 Insert break point

Ctrl+Page up/down Moves between tabs

Ctrl+shift Moves between components

Ctrl+C Interrupts code

Ctrl+D Open highlighted codes ﬁle

Ctrl+ R/T Comment/uncomment line

Ctrl+N New script

Ctrl+W Close script

Ctrl+shift+d Docks window

Ctrl+shift+u Undocks window

Ctrl+shift+m max window/restore size

Built in functions/constants

abs(x) absolute value

pi 3.1415...

inf ∞

eps ﬂoating point accuracy

1e6 10

sum(x) sums elements in x

cumsum(x) Cummulative sum

prod Product of array elements

cumprod(x) cummulative product

diff Diﬀerence of elements

round/ceil/fix/floor Standard functions..

*Standard functions: sqrt, log, exp, max, min, Bessel

*Factorial(x) is only precise for x < 21

Cell commands A cell can contain any variable type.

x=cell(a,b) a ×b cell array

x{n,m} access cell n,m

cell2mat(x) transforms cell to matrix

cellfun(’fname’,C) Applies fname to cells in C

cellfun

Strings and regular expressions

strcomp compare strings (case sensitive)

strcompi compare strings (not case sensitive)

strncomp as strcomp, but only n ﬁrst letters

strfind ﬁnd string within a string

, gives start position

regexp Search for regular expression

Logical operators

&& Short-Circuit AND.

& AND

|| Short-Circuit or

| or

~ not

== Equality comparison

~= not equal

isa(obj, ’class_name’) is object in class

*Other logical operators: <,>,>=,<=

*All above operators are elementwise

*Class indicators: isnan, isequal, ischar, isinf, isvector

, isempty, isscalar, iscolumn

*Short circuits only evaluate second criteria if

first criteria is passed, it is therefore faster.

And useful fpr avoiding errors occuring in second criteria

*non-SC are bugged and short circuit anyway

Variable generation

j:k row vector [j,j+1,...,k]

j:i:k row vector [j,j+i,...,k],

linspace(a,b,n) n points linearly spaced

and including a and b

NaN(a,b) a×b matrix of NaN values

ones(a,b) a×b matrix of 1 values

zeros(a,b) a×b matrix of 0 values

meshgrid(x,y) 2d grid of x and y vectors

[a,b]=deal(NaN(5,5)) declares a and b

global x gives x global scope

Tables

T=table(var1,var2,...,varN) Makes table*

T(rows,vars) get sub-table

T{rows,vars} get data from table

T.var or T.(varindex) all rows of var

T.var(rows) get values of var from rows

summary(T) summary of table

T.var3(T.var3>5)=5 changes some values

T.Properties.Varnames Variable names

T = array2table(A) ! make table from array

T = innerjoin(T1,T2) innerjoin

T = outerjoin(T1,T2) outerjoin !

Rows and vars indicate rows and variables.

tables are great for large datasets, because they

use less memory and allow faster operations.

*rowfun is great for tables, much faster than eg. looping

matrix and vector operations/functions

x=[1, 2, 3] 1x3 (Row) vector

x=[1; 2; 3] 3x1 (Column) vector

x=[1, 2; 3, 4] 2x2 matrix

x(2)=4 change index value nr 2

x(:) All elements of x (same as x)

x(j:end) j’th to last element of x

x(2:5) 2nd to 5th element of x

x(j,:) all j row elements

x(:,j) all j column elements

diag(x) diagonal elements of x

x.*y Element by element multiplication

x./y Element by element division

x+y Element by element addition

x-y Element by element subtraction

A^n normal/Matrix power of A

A.^n Elementwise power of A

A’ Transpose

inv(A) Inverse of matrix

size(x) Rows and Columns

eye(n) Identity matrix

sort(A) sorts vector from smallest to largest

eig(A) Eigenvalues and eigenvectors

numel(A) number of array elements

x(x>5)=0 change elemnts >5 to 0

x(x>5) list elements >5

find(A>5) Indices of elements >5

find(isnan(A)) Indices of NaN elements

[A,B] concatenates horizontally

[A;B] concatenates vertically

For functions on matrices, see bsxfun,arrayfun or repmat

*if arrayfun/bsxfun is passed a gpuArray, it runs on GPU.

*Standard operations: rank,rref,kron,chol

*Inverse of matrix inv(A) should almost never be used, use RREF

through \ instead: inv(A)b = A\b.

Plotting commands

fig1 = plot(x,y) 2d line plot, handle set to ﬁg1

set(fig1, ’LineWidth’, 2) change line width

set(fig1, ’LineStyle’, ’-’) dot markers (see *)

set(fig1, ’Marker’, ’.’) marker type (see *)

set(fig1, ’color’, ’red’) line color (see *)

set(fig1, ’MarkerSize’, 10) marker size (see *)

set(fig1, ’FontSize’, 14) fonts to size 14

figure new ﬁgure window

figure(j) graphics object j

get(j) returns information

graphics object j

gcf(j) get current ﬁgure handle

subplot(a,b,c) Used for multiple

ﬁgures in single plot

xlabel(’\mu line’,’FontSize’,14) names x/y/z axis

ylim([a b]) Sets y/x axis limits

for plot to a-b

title(’name’,’fontsize’,22) names plot

grid on/off; Adds grid to plot

legend(’x’,’y’,’Location’,’Best’) adds legends

hold on retains current ﬁgure

when adding new stuﬀ

hold off restores to default

(no hold on)

set(h,’WindowStyle’,’Docked’); Docked window

style for plots

datetick(’x’,yy) time series axis

plotyy(x1,y1,x2,y2) plot on two y axis

refreshdata refresh data in graph

if speciﬁed source

drawnow do all in event queue

* Some markers: ’, +, *, x, o, square

* Some colors: red, blue, green, yellow, black

* color shortcuts: r, b, g, y, k

* Some line styles: -, --, :, -.

* shortcut combination example: plot(x,y,’b--o’)

Output commands

format short Displays 4 digits after 0

format long Displays 15 digits after 0

disp(x) Displays the string x

num2str(x) Converts the number in x to string

num2str([’nA is = ’ OFTEN USED!

num2str(a)]) !

mat2str(x) Converts the matrix in x to string

int2str(x) Converts the integer in x to string

sprintf(x) formated data to a string

System commands

addpath(string) adds path to workspace

genpath(string) gets strings for subfolders

pwd Current directory

mkdir Makes new directory

tempdir Temporary directory

inmem Functions in memory

exit Close matlab

dir list folder content

ver lists toolboxes

Nonlinear nummerical methods

quad(fun,a,b) simpson integration of @fun

from a to b

fminsearch(fun,x0) minimum of unconstrained

multivariable function

using derivative-free method

fmincon minimum of constrained function

Example: Constrained log-likelihood maximization, note the -

Parms_est = fmincon(@(Parms) -flogL(Parms,x1,x2,x3,y)

,InitialGuess,[],[],[],[],LwrBound,UprBound,[]);

Debbuging etc.

keyboard Pauses exceution

return resumes exceution

tic starts timer

toc stops timer

profile on starts proﬁler

profile viewer Lets you see proﬁler output

try/catch Great for ﬁnding where

errors occur

dbstop if error stops at ﬁrst

error inside try/catch block

dbclear clears breakpoints

dbcont resume execution

lasterr Last error message

lastwarn Last warning message

break Terminates executiion of for/while loop

waitbar Waiting bar

Data import/export

xlsread/xlswrite Spreadsheets (.xls,.xlsm)

readtable/writetable Spreadsheets (.xls,.xlsm)

dlmread/dlmwrite text ﬁles (txt,csv)

load/save -ascii text ﬁles (txt,csv)

load/save matlab ﬁles (.m)

imread/imwrite Image ﬁles

Programming commands

return Return to invoking function

exist(x) checks if x exists

G=gpuArray(x) Convert varibles to GPU array

function [y1,...,yN] = myfun(x1,...,xM)

Anonymous functions not stored in main programme

myfun = @(x1,x2) x1+x2;

or even using

myfun2 = @myfun(x) myfun(x3,2)

Conditionals and loops

for i=1:n

procedure Iterates over procedure

end incrementing i from 1 to n by 1

while(criteria)

procedure Iterates over procedure

end as long as criteria is true(1)

if(criteria 1) if criteria 1 is true do procedure 1

procedure1

elseif(criteria 2) ,else if criteria 2 is true do procedure 2

procedure2

else , else do procedure 3

procedure3

end

switch switch_expression if case n holds,

case 1 run procedure n. If none holds

procedure 1 run procedure 3

case 2 (if speciﬁed)

procedure 2

otherwise

procedure 3

end

General comments

• Monte-Carlo:

If sample sizes are increasing generate largest

size ﬁrst in a vector and use increasingly larger portions for

calculations. Saves time+memory.

• Trick: Program that (1) takes a long time to run and (2)

doesnt use all of the CPU/memory ? - split it into more

programs and run using diﬀerent workers (instances).

• Matlab is a column vector based language, load memory

columnwise ﬁrst always. For faster code also prealocate

memory for variables, Matlab requires contiguous memory

usage!. Matlab uses copy-on-write, so passing pointers

(adresses) to a function will not speed it up. Change

variable class to potentially save memory (Ram) using:

int8, int16, int32, int64, double, char, logical, single

• You can turn the standard (mostly) Just-In-Time

compilation oﬀ using: feature accel oﬀ. You can use

compiled (c,c++,fortran) functions using MEX functions.

• Avoid global variables, they user-error prone and compilers

cant optimize them well.

• Functions deﬁned in a .m ﬁle is only available there.

Preface function names with initials to avoid clashes, eg.

MrP function1.

• Graphic cards(GPU)’s have many (small) cores. If (1)

program is computationally intensive (not spending much

time transfering data) and (2) massively parallel, so

computations can be independent. Consider using the GPU!

• Using multiple cores (parallel computing) is often easy to

implement, just use parfor instead of for loops.

• Warnings: empty matrices are NOT overwritten ([] + 1 = []).

Rows/columns are added without warning if you write in a

nonexistent row/column. Good practise: Use 3i rather than

3*i for imaginary number calculations, because i might have

been overwritten by earlier. 1/0 returns inf, not NaN. Dont

use == for comparing doubles, they are ﬂoating point

precision for example: 0.01 == (1 − 0.99) = 0.

 2015 Thor Nielsen ([email protected])

http://www.econ.ku.dk/pajhede/