Algorithmic Thinking: Loops and Conditionals

Algorithmic Thinking:

Loops and Conditionals

Last Time

 A control flow structure: for loop

 range(n)

range(start, end)

range(start, end, step)

 Assignments that modify variables:

x = x + y

Iteration with for loops

def test1():

for i in range(1,6):

print("Woof")

>>> test1()

Woof

What determines how many

times “Woof” is printed is the

number of elements in the

range.

Any expression that gives 5

elements in the range would

give the same output.

For example,

range(5), range(0,5), …

Iteration with for loops

def test2():

for i in range(1,6):

print(i, end='-')

>>> test2()

1-2-3-4-5-

range(5) ?

range(0, 5) ?

range(1, 6) ?

range(1, 10, 2) ?

range(2, 10, 2) ?

range(10, 1, -1) ?

range(10, 2, -4) ?

Iteration with for loops

def test3():

for i in range(1,6):

print("Woof" * i)

>>> test3()

Woof

WoofWoof

WoofWoofWoof

WoofWoofWoofWoof

WoofWoofWoofWoofWoof

This expression creates a string

that concatenates i number

of “Woof”s.

This Lecture

 The notion of an algorithm

 Moving from algorithm to code

 Python control structures:

 While loops, conditionals

Algorithms

• An algorithm is “a precise rule (or set of rules)

specifying how to solve some problem.”

(thefreedictionary.com)

• The study of algorithms is one of the

foundations of computer science.

 New concept: algorithm

 New control structures

 While loops

 Conditionals

15110 Principles of Computing, Carnegie

Mellon University

8

image: AL-KHWARIZMI

historyoflinearalgebra.weebly.com

Mohammed al-Khowarizmi (äl-khōwärēz´mē)

Persian mathematician of the court of Mamun in Baghdad…

the word algorithm is said to have been derived from his name.

Much of the mathematical knowledge of medieval Europe was

derived from Latin translations of his works. (encyclopedia.com)

An algorithm is like a function

9

ALGORITHM

INPUT OUTPUT

F(x) = y

Input

• Input specification

• Recipes: ingredients, cooking utensils, …

• Knitting: size of garment, length of yarn, needles …

• Tax Code: wages, interest, tax withheld, …

• Input specification for computational algorithms:

• What kind of data is required?

• In what form will this data be received by the

algorithm?

10

Computation

• An algorithm requires clear and precisely stated

steps that express how to perform the

operations to yield the desired results.

• Algorithms assume a basic set of primitive

operations that are assumed to be understood

by the executor of the algorithm.

• Recipes: beat, stir, blend, bake, …

• Knitting: casting on, slip loop, draw yarn through, ...

• Tax code: deduct, look up, check box, …

• Computational: add, set, modulo, output, …

11

Output

• Output specification

• Recipes: number of servings, how to serve

• Knitting: final garment shape

• Tax Code: tax due or tax refund, where to pay

• Output specification for computational algorithms:

• What results are required?

• How should these results be reported?

• What happens if no results can be computed due to

an error in the input? What do we output to indicate

this?

12

Is this a “good” algorithm?

Input: slices of bread, jar of peanut butter, jar of jelly

1. Pick up some bread.

2. Put peanut butter on the bread.

3. Pick up some more bread.

4. Open the jar of jelly.

5. Spread the jelly on the bread.

6. Put the bread together to make your sandwich.

Output?

13

What makes a “good” algorithm?

• A good algorithm should produce the

correct outputs for any set of legal inputs.

• A good algorithm should execute efficiently

with the fewest number of steps as possible.

• A good algorithm should be designed in

such a way that others will be able to

understand it and modify it to specify

solutions to additional problems.

14

An epidemic (covered last week)

def compute_sick(numOfDays):

#computes total sick after n days

newly_sick = 1 #initially 1 sick person

total_sick = 1

for day in range(2, numOfDays + 1):

#each iteration represents one day

newly_sick = newly_sick * 2

total_sick = total_sick + newly_sick

return total_sick

15

Each newly infected person infects 2 people the next day.

The function returns the number of sick people after n days.

Variation on the Epidemic Example

Let us write a function that

 Inputs the size of the population

 Outputs the number of days left before all the population

dies out

How can we do that using iteration (loops)?

Keep track of the number of sick people.

But do we know how many times we should loop?

Recall the Epidemic Example

17

def days_left(population):

#computes the number of days until extinction

days = 1

newly_sick = 1

total_sick = 1

while total_sick < population:

#each iteration represents one day

newly_sick = newly_sick * 2

total_sick = total_sick + newly_sick

days = days + 1

print(days, " days for the population to die off")

return days

while loop

Format:

while condition:

loop body

18

one or more instructions

to be repeated

condition

loop body

false

true

After the loop condition becomes false

during the loop body, the loop body

still runs to completion (before its check

before the next turn) and exit the loop

and go on with the next step.

def days_left(population):

#computes the number of days until extinction

days = 1

newly_sick = 1

total_sick = 1

while total_sick < population:

#each iteration represents one day

newly_sick = newly_sick * 2

total_sick = total_sick + newly_sick

days = days + 1

print(days, " days for the population to die off")

return days

Recall the Epidemic Example

19

Loop condition

Should be

changing so

that loop will

end at a point

While Loop Examples

What is the output?

i = 1

while i < 6:

print(i, end=' ')

i = i + 1

print('\n After :', i)

How about this?

i = 0

while i < 5:

i = i + 1

print(i , end=' ')

print('\n After :', i)

20

What is the value of i when we exit the loop?

‘\n’ means new line

While Loop Examples

i = 1

while i < 6:

print(i, end=' ')

i = i + 1

print('\n', 'After :',i)

print('-------------');

i = 0

while i < 5:

i = i + 1

print(i , end=' ')

print('\n After :', i)

21

>>>

1 2 3 4 5

After : 6

-------------

1 2 3 4 5

After : 5

>>>

While vs. For Loops

# Prints first 10 positive integers

i = 1

while i < 11:

print(i)

i = i + 1

# Prints first 10 positive integers

for i in range(1,11):

print(i)

22

When to use for or while loops

 If you know in advance how many times you want to run

a loop use a for loop.

 When you don’t know the number of repetition needed,

use a while loop.

A Simple Algorithm

Input numerical score between 0 and 100 and

Output “Pass” or “Fail”

Algorithm:

1. If score >= 60

a. Set grade to “Pass”

b. Print “Pass”

2. Otherwise,

a. Set grade to “Fail”

b. Print “Fail”

3. Print “See you in class”

4. Return grade

Exactly one of the steps 1 or 2

is executed, but step 3 and

step 4 are always executed.

Coding the Grader in Python

Algorithm:

1. If score >= 60

a. Set grade to “Pass”

b. Print “ Pass”

2. Otherwise,

a. Set grade to “Fail”

b. Print “Fai”

3. Print “See you in class ”

4. Return grade

def grader(score):

if score >= 60:

grade = "Pass"

print("!!!Pass")

else:

grade = "Fail"

print("!!!Fail")

print("See you in class")

return grade

Control Flow

26

false

score >= 60

true

set grade to “Pass”

print “Pass”

set grade to “Fail”

print “ Fail”

print(“See you in class”)

return grade

FLOW CHART: if statement

Format:

if condition :

statement_list

27

statements

false

condition

true

FLOW CHART: if/else statement

Format:

if condition :

statement_list1

else:

statement_list2

28

statement_list1

false

condition

true

statement_list2

Grader for Letter Grades

29

score >= 90

set grade to “A”

print “you got an A”

score >= 80

score >= 70

set grade to “B”

print “you got a B”

set grade to “C”

print “you got a C”

set grade to “D or lower”

print “your grade is less than C”

true

false

Nested if statements

30

def grader2(score):

if score >= 90:

grade = "A"

print("You got an A")

else: # score less than 90

if score >= 80:

grade = "B"

print("You got a B")

else: # score less than 80

if score >= 70:

grade = "C"

print("You got a C")

else: #score less than 70

grade = "D or lower"

print("Your grade is less than C")

return grade

Equivalently

31

def grader3(score):

if score >= 90:

grade = "A"

print("You got an A")

elif score >= 80:

grade = "B"

print("You got a B")

elif score >= 70:

grade = "C"

print("You got a C")

else:

grade = "D or lower"

print("Your grade is less than C")

return grade

Flow chart:

if/elif/else statement

Format:

if condition1:

statement_list1

elif condition2 :

statement_list2

else:

statement_list3

32

statement_list1

false

condition1

true

statement_list3

condition2

statement_list2

true

false

Example: Finding the maximum

How do we find the maximum in a sequence of integers

shown to us one at a time?

33

175 203 109 158 138 246 146 265 152 222 307 299

What’s the maximum?

Example: Finding the maximum

How do we find the maximum in a sequence of integers

shown to us one at a time?

34

What’s the maximum?

158 175 203 109 138 246

146 265 152 222 307 299

This slide is added just for the lecture notes in PDF.

Same with the previous slide which animates the list of numbers

Example: Finding the maximum

Input: a non-empty li st of integers.

1. Set max_so_far to the first number in list.

2. For each number n in list:

a. If n is greater than max_so_far,

then set max_so_far to n.

Output: max_so_far as the maximum of the list.

35

Loop

Until Now

 Notion of an algorithm:

 Kinds of instructions needed to express algorithms

 What makes an algorithm a good one

 Instructions for specifying control flow (for loop, while

loop, if/then/else)

 Flow charts to express control flow in a language-

independent way

 Coding these control flow structures in Python

36

Representing Lists in Python

We will use a list to represent a collection of

data values.

scores = [78, 93, 80, 68, 100, 94, 85]

colors = [‘red’, ‘green’, ‘blue’]

mixed = [‘purple’, 100, 90.5]

A list is an ordered sequence of values and

may contain values of any data type.

In Python lists may be heterogeneous

(may contain items of different data types).

37

Some List Operations

 Indexing (think of subscripts in a sequence)

 Length (number of items contained in the list)

 Slicing

 Membership check

 Concatenation

 …

38

Some List Operations

>>> names = [ "Al", "Jane", "Jill", "Mark" ]

>>> len(names)

4

>>> Al in names

Error ... name 'Al' is not defined

>>> "Al" in names

True

>>> names + names

['Al', 'Jane', 'Jill', 'Mark', 'Al', 'Jane', 'Jill', 'Mark']

39

Accessing List Elements

"Al" "Jane" "Jill" "Mark"

0

1

2

3

indices

list elements

>>> names[0]

'Al‘

>>> names[4]

Traceback (most recent call last):

File "<pyshell#8>", line 1, in <module>

names[4]

IndexError: list index out of range

>>> names[3]

'Mark‘

>>> names[len(names)-1]

'Mark'

names

Slicing Lists

0

1

2

3

indices

list elements

>>> names[1:3]

['Jane', 'Jill']

>>> names[0:4:2]

[‘Al', 'Jill']

slice

incremental slice

"Al" "Jane" "Jill" "Mark"

names

Start

End

Step

Slicing Lists

0 1 2 3

indices

list elements

names, names[0:4], names[0,4,1]

They all refer to ['Al', 'Jane', 'Jill‘, ‘Mark']

>>> names[1:3] ['Jane', 'Jill']

>>> names[1:4] ['Jane', 'Jill‘, ‘Mark']

>>> names[0:4:2] [‘Al', 'Jill']

>>> names[:3] ['Al', 'Jane', 'Jill‘]

>>> names[:2] ['Al', 'Jane']

>>> names[2:] ['Jill', 'Mark']

"Al" "Jane" "Jill" "Mark"

names

43

source: docs.python.org

Modifying Lists

>>> names = ['Al', 'Jane', 'Jill', 'Mark']

>>> names[1] = "Kate"

>>> names

['Al', 'Kate', 'Jill', 'Mark']

>>> names[1:3] = [ "Me", "You" ]

>>> names

['Al', 'Me', 'You', 'Mark']

>>> names[1:3] = [ "AA", "BB", "CC", "DD" ]

['Al', 'AA', 'BB', 'CC', 'DD', 'Mark']

The list grew in length, we could make it shrink as well.

44

>>> a = [1, 2, 3]

>>> a[0:0] = [-2, -1, 0]

>>> a

[-2, -1, 0, 1, 2, 3]

>>> a = [1, 2, 3]

>>> a[0:1] = [-2, -1, 0]

>>> a

[-2, -1, 0, 2, 3]

45

source: docs.python.org

Tomorrow

 We will continue Lists and algorithms