Matlab Exam 1

Front 1

Index

Back 1

An index is used together with the variable name of the array to access each value.

The value stored in the n-th element is accessed by Scores(n).

Front 2

disp(ygrhufjdc)

Back 2

display that (x,y) shite. For indexing maxrices disp(Buetto(6,9)

Front 3

transpose

Back 3

In linear algebra, there is an operation called the transpose which converts a row vector
into a column vector and vice versa.
MATLAB has a built-in function named transpose that perform this operation.
Thus transpose(Scores) gives exactly the same vector as ScoresC.

Front 4

length

Back 4

The number of elements in a given row or column array can be obtained using the
MATLAB built-in function length. For example
len = length(ScoresR)
produces the result
len = 4
Thus we know that the length of the vector ScoresR is 4 (it has 4 elements)

Front 5

swapping two elements of a matrix using indices

Back 5

temp = SCORES(1,3); % copy of score of 1st student
SCORES(1,3) = SCORES(2,3); % replace it with the 2nd student’s
SCORES(2,3) = temp; % replace 2nd student’s score with temp
Note that the use of a temporary variable is needed in order to make the switch!

Front 6

size

Back 6

One can find the size of an array using the built-in function size.

Dim = size(SCORES)

The statement [ numRows numCols ] = size(SCORES)
gives numRows = 4 and numCols = 3. The size function has an optional second argument that can be used to return either
the number of rows or columns. For example,
nRows = size(SCORES,1)
gives the number of rows (the first index), and
nCols = size(SCORES,2)
gives the number of columns (the second index).

Front 7

the apostrophe

Back 7

The apostrophe can also be used to take the transpose of an array if its elements are all
real quantities.
Assuming that to be the case, then transpose(SCORES) gives exactly the same array
as SCORES’.

Front 8

sum

Back 8

TotalExams = sum(SCORES,1); columns

TotalStudents = sum(SCORES,2); rows

Front 9

function for average

Back 9

The built-in function mean can be used in the same way, to compute the mean (or the
arithmetic average) of a given array.

can be used in same 1,2 specification as sum for a matrix

Front 10

creates an m by n array whose elements are all zeros.

Back 10

zeros(m,n)

Front 11

creates an array the same size as SCORES with elements all set to zeros.

Back 11

zeros(size(Scores))

Front 12

creates an m by n array whose elements are all ones.

Back 12

ones(m,n)

Front 13

creates an array the same size as SCORES with elements all set to ones

Back 13

ones(size(Scores))

Front 14

create an n deminsion identity matrix

Back 14

eye(n)

Front 15

efficient way to generate a large, patterned vector

Back 15

Colon operator.

Given three numbers intendedFirst, increment, and intendedEnd, the statement
Vec = intendedFirst : increment : intendedEnd


The last element of Vec has a value closest to or equal to intendedEnd but does not
go beyond it.

Front 16

linspace

Back 16

The linspace function has three arguments firstElement, lastElement and
numberPoints, and creates a row vector whose first and last elements are given by
firstElement and lastElement respectively (unless numberPoints is less than 2)

Front 17

accessing elements of an Array

Back 17

Array = ARR

One can retrieve any element by specifying the indices. For example its element at
position
2, 3; theElement = ARR(2,3)

One can retrieve multiple elements from a given array using vector indices. For example,
Mtx1 = ARR([ 2 5 ],3)

gives us 2,3 and 5,3 of ARR

Mtx2 = ARR(2,2:4)

The vector indices need not be in ascending or descending order, for example:
Mtx3 = ARR(4,[ 5 1 3 ])

Both the first and the second indices can be vectors:
MTX5 = ARR([5 2],2:4)

Notation: end gives the highest value that a given index can take. For example,
Mtx7 = ARR(3,2:end)

You can even do this
MTX8 = ARR(3:end,2:end)

Front 18

adding element to an array

Back 18

An element can be appended to an array.
The size of the array will be expanded just enough to accommodate the extra element.
The elements whose values are not specified are set to zero.

Scores(6,9)= 75 % all else in new rs and cs will be 0s %%use () not []

Front 19

making 1 big matrix from 2 little guys, row.wise

Back 19

*must have same #rows

Given an n by m array A and an n by k array
B, since they both have the same number
of rows, they can be concatenated side by side to obtain an
n by m + k array as follows
ABH = [ A B ]

Front 20

Making 1 big matrix from 2 little guys, column.wise

Back 20

*must have same number of columns

given A (n,k) and C(r,k);

ACV = [ A; C ]

Front 21

replicate a given array a certain number of
times to produce larger array.

Back 21

repmat;

Specifically given an array A, repmat(A,m,n) is an array obtained by replicating A m
times vertically and n times horizontally

Front 22

deleting rows and columns from an array

Back 22

Rows and columns can be deleted from an array by assigning them to an empty array.
The remaining rows and columns are repackaged so that the original array will have a
reduced size.

Front 23

how do i delete partial rows or partial columns of a jawn?

Back 23

you dont.

deleting a partial row or a partial column from a 2D array is illegal.

I can do this with 1Xn vectors doe

Front 24

Entering Data from the Keyboard at runtime

Back 24

For numerical input, R = input(’How many apples’)

Front 25

elementwise addition or subtraction

Back 25

+

-

Front 26

elementwise multiplication, division, exponetiation

Back 26

.*

./

.^

for two matrices, they must be same size

Front 27

Log) equal t0

Back 27

==

Front 28

log) not equal to

Back 28

~=

Front 29

log) strictly greater

Back 29

>

Front 30

log) greater than or equal to

Back 30

>=

Front 31

log) strictly less than

Back 31

<

Front 32

log) less than or equal to

Back 32

<=

this one looks like a dick.

Front 33

Binary logic operator

And

Back 33

&

Front 34

Binary logic operator AND with short circuit evaluation for scalers

Back 34

&&

Front 35

Binary logic operator inclusive OR

Back 35

|

Front 36

Binary logic operator inclusive OR with short circuit evaluation for scalers

Back 36

||

Front 37

Binary logic operator, exclusive OR

Back 37

xor

Front 38

what is the short circuit evaluation

Back 38

Note that in evaluating r1 and r3, the fact that b1 is false already implies
that r1 and r3 must be false.
There is really no need to see if b2 is true or not.

Front 39

find

Back 39

Given a vector of logical values, the built-in function find finds elements
whose values are true.
The function returns a vector (having the same row/column orientation as
the logical vector) of positions of the elements within the array whose
values are true.

Front 40

create a vector containing all true elements of a logical stipulation

Back 40

use vector indexing

Vec is some bullsh8t

Fd= find(Vec > something else)

Vec(Fd) = all elements of origional Vec that are > something else

Front 41

logical indexing

Back 41

Rd= rand(1,5)

Log=( Rd > .5 )

RdLog= Rd(Log)

Results in vector of values of Rd that satisfy Log without bullsh8t 0s;

Front 42

any

Back 42

The function any operates on a logical vector and returns true if any of
the elements in the vector is true, and returns false if all the elements
are false.

Front 43

all

Back 43

The function all operates on a logical vector and returns true if all the
elements in the vector are true, and returns false if at least one of the
elements is false.

Front 44

generate random numbers over interval [a,b]

Back 44

v = a + (b − a)u

where u is a random number (or vec/array of them) normal rand

Front 45

randn

Back 45

In MATLAB the function randn generates normally distributed random points
r with a mean of 0 and a standard deviation of
1. Normally distributed random numbers with any mean µ and standard deviation σ are
obtained by multiplying r by σ and shifting them by µ: σr + µ. The usage of the randn function is basically the same as the function rand. The biggest difference is it uses different generators since the distribution is different for
the uniformly distributed and the normally distributed random numbers.

Front 46

discrete random variable

Back 46

A (mathematical) variable is a discrete variable if it can only take on a countable number
of discrete values (there is a fixed nonzero distance between any two consecutive
values).
If it takes on those discrete values at random, then it is called a discrete random variable

Front 47

discrete variable

Back 47

If a variable can take on any value between two specified values, it is called a continuous variable; otherwise, it is called a discrete variable.

Some examples will clarify the difference between discrete and continuous variables.

* Suppose we flip a coin and count the number of heads. The number of heads could be any integer value between 0 and plus infinity. However, it could not be any number between 0 and plus infinity. We could not, for example, get 2.5 heads. Therefore, the number of heads must be a discrete variable.