Matlab/R Dictionary
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This document discusses MATLAB and R, focusing on their history, programming capabilities, and data analysis features. It compares the two programming languages in terms of syntax, data structures, and functionalities, highlighting their respective advantages in numerical programming and data visualization. The document also includes various coding examples for creating vectors, matrices, and working with data structures in both languages.
![The
basics:
vectors,
matrices
and
indexing
Task
Create
a
row
vector
v
=
[1
2
3
4]
v<-‐c(1,2,3,4)
Create
a
column
vector
v=[1;2;3;4]
or
v=[1
2
3
4]’
v<-‐c(1,2,3,4)
Note:
R
does
not
distinguish
between
row
and
column
vectors
Enter
a
matrix
A
A=[1
2
3;
4
5
6]
Enter
values
by
row:
A<-‐matrix(c(1,2,3,4,5,6),
nrow=2,
byrow=TRUE)
Enter
values
by
column:
A<-‐matrix(c(1,4,2,5,3,6),
nrow=2)
Access
third
element
of
vector
v
v(3)
v[3]
or
v[[3]]
Access
element
of
matrix
A
A(2,3)
A[2,3]
“Glue”
two
matrices
a1
and
a2,
A=[a1
a2]
A<-‐cbind(a1,a2)
same
number
of
rows,
side
by
side
“Stack”
two
matrices
a1
and
a2,
A=[a1;a2]
A<-‐rbind(a1,a2)
same
number
of
columns
Reshape*
matrix
A,
making
it
an
m
A=reshape(A,m,n)
dim(A)<-‐c(m,n)
x
n
matrix
with
elements
taken
columnwise
from
A](https://image.slidesharecdn.com/matlabrdictionary-12640449421672-phpapp02/85/Matlab-R-Dictionary-5-320.jpg)
![Working
with
data
structures
Task
Build
a
structure
v
of
length
n,
v=cell(1,n)
In
general,
cell v<-‐vector(’list’,n)
capable
of
containing
different
(m,n)
makes
an
m
×
n
cell
Then
you
can
do
e.g.:
array.
Then
you
can
do
e.g.:
v[[1]]<-‐12
data
types
in
different
elements.
v{1}=12
v[[2]]<-‐’hi
there’
MATLAB:
cell
array
v{2}=’hi
there’
v[[3]]<-‐matrix(runif(9),3)
R:
list
v{3}=rand(3)
Create
a
matrix-‐like
object
with
avals=2*ones(1,6);
v<-‐c(1,5,3,2,3,7)
different
named
columns.
yvals=6:-‐1:1;
v=[1
5
3
2
3
7];
d<-‐data.frame(cbind(a=2,
d=struct(’a’,
avals,
yy=6:1),
v)
MATLAB:
struct
array
’yy’,
yyvals,
’fac’,
v);
R:
data.frame](https://image.slidesharecdn.com/matlabrdictionary-12640449421672-phpapp02/85/Matlab-R-Dictionary-7-320.jpg)
![Condi,onals,
control
structures,
loops
Task
for
loops
over
values
in
vector
for
i=v
If
only
one
command:
command1
for
(i
in
v)
v
command2
command
end
If
multiple
commands:
for
(i
in
v)
{
command1
command2
}
If/else
statement
if
cond
if
(cond)
{
command1
command1
command2
command2
else
}
else
{
command3
command3
command4
command4
end
}
MATLAB
also
has
the
elseif
R
uses
chained
“else
if”
statement.
statements.
ifelse()
func,on
>
print(ifelse(c(T,F),
2,
3))
[1]
2
3](https://image.slidesharecdn.com/matlabrdictionary-12640449421672-phpapp02/85/Matlab-R-Dictionary-8-320.jpg)
![Func,ons
function
[a,
b]
=
minmax(z)
minmax
<-‐
function(c,
opt=12)
{
%
one
function
per
.m
file!
#
functions
are
assigned
to
%
assign
to
formal
return
names
#
variables
a
=
min(z)
ret
<-‐
list(min
=
min(z),
b
=
max(z)
max
=
max(z))
end
ret
#
last
statement
is
#
return
value
}
%
if
minmax.m
in
path
#
if
minmax
was
created
in
current
[smallest,
largest]
=
…
#
environment
minmax([1
30
3])
x
<-‐
minmax(c(1,
30,
3))
smallest
<-‐
x$min](https://image.slidesharecdn.com/matlabrdictionary-12640449421672-phpapp02/85/Matlab-R-Dictionary-12-320.jpg)
Matlab/R Dictionary
- 1. MATLAB/R Dic,onary R meetup NYC January 7, 2010 Harlan Harris harlan@harris.name @HarlanH Marck Vaisman marck@vaisman.us @wahalulu MATLAB and the MATLAB logo are registered trademarks of The Mathworks.
- 2. About MATLAB What is MATLAB MATLAB History • Commercial numerical • Developed by Cleve Moler programming language, (Math/CS Prof at UNM) in the simula,on and visualiza,on 1970’s as a higher-‐level • One million users (engineers, numerical programming scien,sts, academics) language (vs. Fortran LINPACK) • MATrix LABoratory – • Adopted by engineers for specializes in matrix signal processing, control opera,ons modeling • Mathworks -‐ base & add-‐ons • Mul,purpose programming • Open-‐source Octave project language
- 3. Notes • Today’s focus: Compare MATLAB & R for data analysis, contrast as programming languages • MATLAB is Base plus many toolboxes – Base includes: descrip,ve stats, covariance and correla,on, linear and nonlinear regression – Sta,s,cs toolbox adds: dataset and category (like data.frames and factors) arrays, more visualiza,ons, distribu,ons, ANOVA, mul,variate regression, hypothesis tests
- 4. -‐> • Interac,ve programming: Scripts and Read-‐Evaluate-‐ Print Loop • Similar representa,ons of data – Both use vectors/arrays as the primary data structures • Matlab is based on 2-‐D matricies; R is based on 1-‐D vectors – Both prefer vectorized func,ons to for loops – Variables are declared dynamically • Can do most MATLAB func,onality in R; can do most R func,onality in MATLAB.
- 5. The basics: vectors, matrices and indexing Task Create a row vector v = [1 2 3 4] v<-‐c(1,2,3,4) Create a column vector v=[1;2;3;4] or v=[1 2 3 4]’ v<-‐c(1,2,3,4) Note: R does not distinguish between row and column vectors Enter a matrix A A=[1 2 3; 4 5 6] Enter values by row: A<-‐matrix(c(1,2,3,4,5,6), nrow=2, byrow=TRUE) Enter values by column: A<-‐matrix(c(1,4,2,5,3,6), nrow=2) Access third element of vector v v(3) v[3] or v[[3]] Access element of matrix A A(2,3) A[2,3] “Glue” two matrices a1 and a2, A=[a1 a2] A<-‐cbind(a1,a2) same number of rows, side by side “Stack” two matrices a1 and a2, A=[a1;a2] A<-‐rbind(a1,a2) same number of columns Reshape* matrix A, making it an m A=reshape(A,m,n) dim(A)<-‐c(m,n) x n matrix with elements taken columnwise from A
- 6. Operators Task Assignment = <-‐ or = Whole Matrix Opera,ons: Multiplication: A*B A %*% B Square the matrix: A^2 A %*% A Raise to power k: A^k A %*% A %*% A … Element-‐by-‐element A.*B A*B A./B A/B Opera,ons: A.^k A^k Compute A-‐1B AB A%*% solve(B) Sums Columns of matrix: sum(A) colSums(A) Rows of matrix: sum(A,2) rowSums(A) Logical operators (element-‐by-‐ a < b, a > b, a <= b, a >= b a < b, a > b, a <= b, a >= b a == b a == b element on vectors/matrices) a ~= b a != b AND: a && b AND: a && b (short-‐circuit) a & b (element-‐wise) OR: a || b OR: a || b a | b XOR: xor(a,b) XOR: xor(a,b) NOT: ~a NOT: !a
- 7. Working with data structures Task Build a structure v of length n, v=cell(1,n) In general, cell v<-‐vector(’list’,n) capable of containing different (m,n) makes an m × n cell Then you can do e.g.: array. Then you can do e.g.: v[[1]]<-‐12 data types in different elements. v{1}=12 v[[2]]<-‐’hi there’ MATLAB: cell array v{2}=’hi there’ v[[3]]<-‐matrix(runif(9),3) R: list v{3}=rand(3) Create a matrix-‐like object with avals=2*ones(1,6); v<-‐c(1,5,3,2,3,7) different named columns. yvals=6:-‐1:1; v=[1 5 3 2 3 7]; d<-‐data.frame(cbind(a=2, d=struct(’a’, avals, yy=6:1), v) MATLAB: struct array ’yy’, yyvals, ’fac’, v); R: data.frame
- 8. Condi,onals, control structures, loops Task for loops over values in vector for i=v If only one command: command1 for (i in v) v command2 command end If multiple commands: for (i in v) { command1 command2 } If/else statement if cond if (cond) { command1 command1 command2 command2 else } else { command3 command3 command4 command4 end } MATLAB also has the elseif R uses chained “else if” statement. statements. ifelse() func,on > print(ifelse(c(T,F), 2, 3)) [1] 2 3
- 9. Help! Task Get help on a func,on help fminsearch help(pmin) or ?pmin Search the help for a word lookfor inverse ??inverse Describe a variable class(a) class(a) str(a) Show variables in environment who ls() Underlying type of variable whos(‘a’) typeof(a)
- 10. Example: k-‐means clustering of Fisher Iris data Fisher Iris Dataset sepal_length,sepal_width,petal_length,petal_width,species 5.1,3.5,1.4,0.2,setosa 4.9,3.0,1.4,0.2,setosa 4.7,3.2,1.3,0.2,setosa 4.6,3.1,1.5,0.2,setosa …
- 11. Matlab and R as programming languages Scrip,ng, real-‐,me analysis Scrip,ng, real-‐,me analysis File-‐based environments Files unimportant Impera,ve programming style Func,onal programming style (impure) Sta,cally scoped Dynamically scoped Func,ons with mul,ple return values Func,ons with named arguments, lazy evalua,on Evolving OOP system Mul,ple compe,ng OOP systems Can be compiled Cannot be compiled Large library of func,ons Large library of func,ons Professional developed, cost money Varying quality and support Can embed (in) many other languages Can embed (in) many other languages
- 12. Func,ons function [a, b] = minmax(z) minmax <-‐ function(c, opt=12) { % one function per .m file! # functions are assigned to % assign to formal return names # variables a = min(z) ret <-‐ list(min = min(z), b = max(z) max = max(z)) end ret # last statement is # return value } % if minmax.m in path # if minmax was created in current [smallest, largest] = … # environment minmax([1 30 3]) x <-‐ minmax(c(1, 30, 3)) smallest <-‐ x$min
- 13. Object-‐Oriented Programming • Formerly: objects were • S3 classes: anributes + defined by a directory syntax tree, with one method – class(object) per file – plot.lm() • As of 2008: new • S4 classes: defini,ons + classdef syntax methods resembles other • R.oo, proto, etc… languages
- 14. Other notes • r.matlab package • Graphics – Matlab has much bener 3-‐d/interac,ve graphics support – R has ggplot2 and much bener sta,s,cal graphics
- 15. Addi,onal Resources • Will Dwinell, Data Mining in MATLAB • Computerworld ar,cle on Cleve Moler • Mathworks • Matlabcentral • Comparison of Data Analysis packages ( hnp://anyall.org/blog/2009/02/comparison-‐of-‐data-‐ analysis-‐packages-‐r-‐matlab-‐scipy-‐excel-‐sas-‐spss-‐ stata/) • R.matlab package • stackoverflow
- 16. References used for this talk • David Hiebeler MATLAB/R Reference document: hnp://www.math.umaine.edu/~hiebeler/comp/ matlabR.html • hnp://www.cyclismo.org/tutorial/R/index.html • hnp://www.stat.berkeley.edu/~spector/R.pdf • MATLAB documenta,on • hnp://www.r-‐cookbook.com/node/23
- 17. Thank You!