SlideShare a Scribd company logo
1 of 26
1
Functions
Rosen 6th ed., §2.3
2
Definition of Functions
• Given any sets A, B, a function f from (or
“mapping”) A to B (f:AB) is an
assignment of exactly one element f(x)B
to each element xA.
3
Graphical Representations
• Functions can be represented graphically in
several ways:
• •
A
B
a b
f
f
•
•
•
•
•
•
•
•
• x
y
Plot
Graph
Like Venn diagrams
A B
4
Definition of Functions (cont’d)
• Formally: given f:AB
“x is a function” : (x,y: x=y  f(x)  f(y)) or
“x is a function” : ( x,y: (x=y)  (f(x)  f(y))) or
“x is a function” : ( x,y: (x=y)  (f(x) = f(y))) or
“x is a function” : ( x,y: (x=y)  (f(x) = f(y))) or
“x is a function” : ( x,y: (f(x)  f(y))  (x  y))
5
Some Function Terminology
• If f:AB, and f(a)=b (where aA & bB),
then:
– A is the domain of f.
– B is the codomain of f.
– b is the image of a under f.
– a is a pre-image of b under f.
• In general, b may have more than one pre-image.
– The range RB of f is {b | a f(a)=b }.
6
Range vs. Codomain - Example
• Suppose that: “f is a function mapping
students in this class to the set of grades
{A,B,C,D,E}.”
• At this point, you know f’s codomain is:
__________, and its range is ________.
• Suppose the grades turn out all As and Bs.
• Then the range of f is _________, but its
codomain is __________________.
{A,B,C,D,E} unknown!
{A,B}
still {A,B,C,D,E}!
7
Function Addition/Multiplication
• We can add and multiply functions
f,g:RR:
– (f  g):RR, where (f  g)(x) = f(x)  g(x)
– (f × g):RR, where (f × g)(x) = f(x) × g(x)
8
Function Composition
• For functions g:AB and f:BC, there is a
special operator called compose (“○”).
– It composes (i.e., creates) a new function out of f,g by
applying f to the result of g.
(f○g):AC, where (f○g)(a) = f(g(a)).
– Note g(a)B, so f(g(a)) is defined and C.
– The range of g must be a subset of f’s domain!!
– Note that ○ (like Cartesian , but unlike +,,) is non-
commuting. (In general, f○g  g○f.)
9
Function Composition
10
Images of Sets under Functions
• Given f:AB, and SA,
• The image of S under f is simply the set of
all images (under f) of the elements of S.
f(S) : {f(s) | sS}
: {b |  sS: f(s)=b}.
• Note the range of f can be defined as simply
the image (under f) of f’s domain!
11
One-to-One Functions
• A function is one-to-one (1-1), or injective,
or an injection, iff every element of its
range has only one pre-image.
• Only one element of the domain is mapped
to any given one element of the range.
– Domain & range have same cardinality. What
about codomain?
12
One-to-One Functions (cont’d)
• Formally: given f:AB
“x is injective” : (x,y: xy  f(x)f(y)) or
“x is injective” : ( x,y: (xy)  (f(x)f(y))) or
“x is injective” : ( x,y: (xy)  (f(x)  f(y))) or
“x is injective” : ( x,y: (xy)  (f(x)  f(y))) or
“x is injective” : ( x,y: (f(x)=f(y))  (x =y))
13
One-to-One Illustration
• Graph representations of functions that are
(or not) one-to-one:
•
•
•
•
•
•
•
•
•
One-to-one
•
•
•
•
•
•
•
•
•
Not one-to-one
•
•
•
•
•
•
•
•
•
Not even a
function!
14
Sufficient Conditions for 1-1ness
• Definitions (for functions f over numbers):
– f is strictly (or monotonically) increasing iff
x>y  f(x)>f(y) for all x,y in domain;
– f is strictly (or monotonically) decreasing iff
x>y  f(x)<f(y) for all x,y in domain;
• If f is either strictly increasing or strictly
decreasing, then f is one-to-one.
– e.g. f(x)=x3
15
Onto (Surjective) Functions
• A function f:AB is onto or surjective or a
surjection iff its range is equal to its
codomain (bB, aA: f(a)=b).
• An onto function maps the set A onto (over,
covering) the entirety of the set B, not just
over a piece of it.
– e.g., for domain & codomain R, x3 is onto,
whereas x2 isn’t. (Why not?)
16
Illustration of Onto
• Some functions that are or are not onto their
codomains:
Onto
(but not 1-1)
•
•
•
•
•
•
•
•
•
Not Onto
(or 1-1)
•
•
•
•
•
•
•
•
•
Both 1-1
and onto
•
•
•
•
•
•
•
•
1-1 but
not onto
•
•
•
•
•
•
•
•
•
17
Bijections
• A function f is a one-to-one
correspondence, or a bijection, or
reversible, or invertible, iff it is both one-
to-one and onto.
18
Inverse of a Function
• For bijections f:AB, there exists an
inverse of f, written f 1:BA, which is the
unique function such that:
I
f
f 


1
19
Inverse of a function (cont’d)
20
The Identity Function
• For any domain A, the identity function
I:AA (variously written, IA, 1, 1A) is the
unique function such that aA: I(a)=a.
• Some identity functions you’ve seen:
– ing with T, ing with F, ing with , ing
with U.
• Note that the identity function is both one-
to-one and onto (bijective).
21
• The identity function:
Identity Function Illustrations
•
•
•
•
•
•
•
•
•
Domain and range x
y
22
Graphs of Functions
• We can represent a function f:AB as a set
of ordered pairs {(a,f(a)) | aA}.
• Note that a, there is only one pair (a, f(a)).
• For functions over numbers, we can
represent an ordered pair (x,y) as a point on
a plane. A function is then drawn as a curve
(set of points) with only one y for each x.
23
Graphs of Functions
24
A Couple of Key Functions
• In discrete math, we frequently use the
following functions over real numbers:
– x (“floor of x”) is the largest integer  x.
– x (“ceiling of x”) is the smallest integer  x.
25
Visualizing Floor & Ceiling
• Real numbers “fall to their floor” or “rise to
their ceiling.”
• Note that if xZ,
x   x &
x   x
• Note that if xZ,
x = x = x.
0
1
1
2
3
2
3
.
.
.
.
.
.
. . .
1.6
1.6=2
1.4= 2
1.4
1.4= 1
1.6=1
3
3=3= 3
26
Plots with floor/ceiling: Example
• Plot of graph of function f(x) = x/3:
x
f(x)
Set of points (x, f(x))
+3
2
+2
3

More Related Content

Similar to Functions.ppt

Similar to Functions.ppt (20)

functions.pdf
functions.pdffunctions.pdf
functions.pdf
 
01. Functions-Theory & Solved Examples Module-4.pdf
01. Functions-Theory & Solved Examples Module-4.pdf01. Functions-Theory & Solved Examples Module-4.pdf
01. Functions-Theory & Solved Examples Module-4.pdf
 
Functions
FunctionsFunctions
Functions
 
Math for 800 09 functions
Math for 800   09 functionsMath for 800   09 functions
Math for 800 09 functions
 
Pre-Cal 40S March 3, 2009
Pre-Cal 40S March 3, 2009Pre-Cal 40S March 3, 2009
Pre-Cal 40S March 3, 2009
 
Functions.pptx
Functions.pptxFunctions.pptx
Functions.pptx
 
Chpt 2-functions-seqs v.5
Chpt 2-functions-seqs v.5Chpt 2-functions-seqs v.5
Chpt 2-functions-seqs v.5
 
Functions 1 - Math Academy - JC H2 maths A levels
Functions 1 - Math Academy - JC H2 maths A levelsFunctions 1 - Math Academy - JC H2 maths A levels
Functions 1 - Math Academy - JC H2 maths A levels
 
Functions and graphs
Functions and graphsFunctions and graphs
Functions and graphs
 
Calculus- Basics
Calculus- BasicsCalculus- Basics
Calculus- Basics
 
Inverse Functions
Inverse FunctionsInverse Functions
Inverse Functions
 
First Partial Review
First Partial ReviewFirst Partial Review
First Partial Review
 
Graph a function
Graph a functionGraph a function
Graph a function
 
Per4 function2
Per4 function2Per4 function2
Per4 function2
 
Functions
FunctionsFunctions
Functions
 
Quadratic functions
Quadratic functionsQuadratic functions
Quadratic functions
 
L2 graphs piecewise, absolute,and greatest integer
L2 graphs  piecewise, absolute,and greatest integerL2 graphs  piecewise, absolute,and greatest integer
L2 graphs piecewise, absolute,and greatest integer
 
Funções 4
Funções 4Funções 4
Funções 4
 
9-Functions.pptx
9-Functions.pptx9-Functions.pptx
9-Functions.pptx
 
CMSC 56 | Lecture 9: Functions Representations
CMSC 56 | Lecture 9: Functions RepresentationsCMSC 56 | Lecture 9: Functions Representations
CMSC 56 | Lecture 9: Functions Representations
 

Recently uploaded

Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxAshokKarra1
 
ACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfSpandanaRallapalli
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersSabitha Banu
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfTechSoup
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designMIPLM
 
ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4MiaBumagat1
 
What is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPWhat is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPCeline George
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptxmary850239
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxDr.Ibrahim Hassaan
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYKayeClaireEstoconing
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 
Science 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxScience 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxMaryGraceBautista27
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Celine George
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)lakshayb543
 

Recently uploaded (20)

Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptx
 
ACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdf
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginners
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-design
 
ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4ANG SEKTOR NG agrikultura.pptx QUARTER 4
ANG SEKTOR NG agrikultura.pptx QUARTER 4
 
What is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPWhat is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERP
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptx
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for Beginners
 
Science 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxScience 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptx
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
 

Functions.ppt

  • 2. 2 Definition of Functions • Given any sets A, B, a function f from (or “mapping”) A to B (f:AB) is an assignment of exactly one element f(x)B to each element xA.
  • 3. 3 Graphical Representations • Functions can be represented graphically in several ways: • • A B a b f f • • • • • • • • • x y Plot Graph Like Venn diagrams A B
  • 4. 4 Definition of Functions (cont’d) • Formally: given f:AB “x is a function” : (x,y: x=y  f(x)  f(y)) or “x is a function” : ( x,y: (x=y)  (f(x)  f(y))) or “x is a function” : ( x,y: (x=y)  (f(x) = f(y))) or “x is a function” : ( x,y: (x=y)  (f(x) = f(y))) or “x is a function” : ( x,y: (f(x)  f(y))  (x  y))
  • 5. 5 Some Function Terminology • If f:AB, and f(a)=b (where aA & bB), then: – A is the domain of f. – B is the codomain of f. – b is the image of a under f. – a is a pre-image of b under f. • In general, b may have more than one pre-image. – The range RB of f is {b | a f(a)=b }.
  • 6. 6 Range vs. Codomain - Example • Suppose that: “f is a function mapping students in this class to the set of grades {A,B,C,D,E}.” • At this point, you know f’s codomain is: __________, and its range is ________. • Suppose the grades turn out all As and Bs. • Then the range of f is _________, but its codomain is __________________. {A,B,C,D,E} unknown! {A,B} still {A,B,C,D,E}!
  • 7. 7 Function Addition/Multiplication • We can add and multiply functions f,g:RR: – (f  g):RR, where (f  g)(x) = f(x)  g(x) – (f × g):RR, where (f × g)(x) = f(x) × g(x)
  • 8. 8 Function Composition • For functions g:AB and f:BC, there is a special operator called compose (“○”). – It composes (i.e., creates) a new function out of f,g by applying f to the result of g. (f○g):AC, where (f○g)(a) = f(g(a)). – Note g(a)B, so f(g(a)) is defined and C. – The range of g must be a subset of f’s domain!! – Note that ○ (like Cartesian , but unlike +,,) is non- commuting. (In general, f○g  g○f.)
  • 10. 10 Images of Sets under Functions • Given f:AB, and SA, • The image of S under f is simply the set of all images (under f) of the elements of S. f(S) : {f(s) | sS} : {b |  sS: f(s)=b}. • Note the range of f can be defined as simply the image (under f) of f’s domain!
  • 11. 11 One-to-One Functions • A function is one-to-one (1-1), or injective, or an injection, iff every element of its range has only one pre-image. • Only one element of the domain is mapped to any given one element of the range. – Domain & range have same cardinality. What about codomain?
  • 12. 12 One-to-One Functions (cont’d) • Formally: given f:AB “x is injective” : (x,y: xy  f(x)f(y)) or “x is injective” : ( x,y: (xy)  (f(x)f(y))) or “x is injective” : ( x,y: (xy)  (f(x)  f(y))) or “x is injective” : ( x,y: (xy)  (f(x)  f(y))) or “x is injective” : ( x,y: (f(x)=f(y))  (x =y))
  • 13. 13 One-to-One Illustration • Graph representations of functions that are (or not) one-to-one: • • • • • • • • • One-to-one • • • • • • • • • Not one-to-one • • • • • • • • • Not even a function!
  • 14. 14 Sufficient Conditions for 1-1ness • Definitions (for functions f over numbers): – f is strictly (or monotonically) increasing iff x>y  f(x)>f(y) for all x,y in domain; – f is strictly (or monotonically) decreasing iff x>y  f(x)<f(y) for all x,y in domain; • If f is either strictly increasing or strictly decreasing, then f is one-to-one. – e.g. f(x)=x3
  • 15. 15 Onto (Surjective) Functions • A function f:AB is onto or surjective or a surjection iff its range is equal to its codomain (bB, aA: f(a)=b). • An onto function maps the set A onto (over, covering) the entirety of the set B, not just over a piece of it. – e.g., for domain & codomain R, x3 is onto, whereas x2 isn’t. (Why not?)
  • 16. 16 Illustration of Onto • Some functions that are or are not onto their codomains: Onto (but not 1-1) • • • • • • • • • Not Onto (or 1-1) • • • • • • • • • Both 1-1 and onto • • • • • • • • 1-1 but not onto • • • • • • • • •
  • 17. 17 Bijections • A function f is a one-to-one correspondence, or a bijection, or reversible, or invertible, iff it is both one- to-one and onto.
  • 18. 18 Inverse of a Function • For bijections f:AB, there exists an inverse of f, written f 1:BA, which is the unique function such that: I f f    1
  • 19. 19 Inverse of a function (cont’d)
  • 20. 20 The Identity Function • For any domain A, the identity function I:AA (variously written, IA, 1, 1A) is the unique function such that aA: I(a)=a. • Some identity functions you’ve seen: – ing with T, ing with F, ing with , ing with U. • Note that the identity function is both one- to-one and onto (bijective).
  • 21. 21 • The identity function: Identity Function Illustrations • • • • • • • • • Domain and range x y
  • 22. 22 Graphs of Functions • We can represent a function f:AB as a set of ordered pairs {(a,f(a)) | aA}. • Note that a, there is only one pair (a, f(a)). • For functions over numbers, we can represent an ordered pair (x,y) as a point on a plane. A function is then drawn as a curve (set of points) with only one y for each x.
  • 24. 24 A Couple of Key Functions • In discrete math, we frequently use the following functions over real numbers: – x (“floor of x”) is the largest integer  x. – x (“ceiling of x”) is the smallest integer  x.
  • 25. 25 Visualizing Floor & Ceiling • Real numbers “fall to their floor” or “rise to their ceiling.” • Note that if xZ, x   x & x   x • Note that if xZ, x = x = x. 0 1 1 2 3 2 3 . . . . . . . . . 1.6 1.6=2 1.4= 2 1.4 1.4= 1 1.6=1 3 3=3= 3
  • 26. 26 Plots with floor/ceiling: Example • Plot of graph of function f(x) = x/3: x f(x) Set of points (x, f(x)) +3 2 +2 3