Searching. Sorting. Lambdas - cs.ubbcluj.roarthur/FP2018/Lecture Notes/13.Searching.Sorting... ·...

Lecture 13

Lect. PhD.Arthur Molnar

Searching

The searchingproblem

Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Searching. Sorting. Lambdas

Lect. PhD. Arthur Molnar

Babes-Bolyai University

[email protected]

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Overview

1 SearchingThe searching problemSearching algorithmsBinary searchSearch in Python

2 SortingThe sorting problemSelection sortInsertion sortBubble SortQuick Sort

3 Lambda Expressions

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Feedback for the course

You can write feedback at academicinfo.ubbcluj.ro

It is both important as well as anonymous

Write both what you like (so we keep&improve it) andwhat you don’t

Best if you write about all activities (lecture,seminar andlaboratory)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Searching

Data are available in the internal memory, as a sequenceof records (k1, k2, ..., kn)

Search a record having a certain value for one of its fields,called the search key.

If the search is successful, we have the position of therecord in the given sequence.

We approach the search problem’s two possibilitiesseparately:

Searching with unordered keysSearching with ordered keys

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Searching - unordered keys

Problem specification

Data: a, n, (ki , i = 0, .., n − 1), where n ∈ N, n ≥ 0.

Results: p, where (0 ≤ p ≤ n − 1, a = kp) or p = −1, ifkey is not found.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


de f s ea r chSeq ( e l , l ) :’ ’ ’Search f o r an e l ement i n l i s te l − e l ementl − l i s t o f e l ement sReturn the p o s i t i o n o f the e lement , −1 i f not

found’ ’ ’poz = −1f o r i i n range (0 , l e n ( l ) ) :

i f e l == l [ i ] :poz = i

r e t u r n poz

Computational complexity is T (n) =n−1∑i=0

1 = n ∈ Θ(n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


de f s ea r chSeq ( e l , l ) :’ ’ ’Search f o r an e l ement i n l i s te l − e l ementl − l i s t o f e l ement sReturn the p o s i t i o n o f the e lement , −1 i f not

found’ ’ ’i = 0wh i l e i<l e n ( l ) and e l != l [ i ] :

i += 1i f i<l e n ( l ) :

r e t u r n ir e t u r n −1

What is the difference between this and the previous version?

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


Best case: the element is at the first position,T (n) ∈ Θ(1).

Worst case: the element is in the n-1 position,T (n) ∈ Θ(n).

Average case: if distributing the element uniformly, theloop can be executed 0, 1, .., n − 1 times, soT (n) = 1+2+..+n−1

n ∈ Θ(n).

Overabll complexity is O(n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Searching - ordered keys


Data: a, n, (ki , i = 0, .., n − 1), where n ∈ N, n ≥ 0, andk0 < k1 < ... < kn−1;

Results: p, where (p = 0 and a ≤ k0) or (p = n anda > kn−1) or (0 < p ≤ n − 1) and (kp−1 < a ≤ kp).

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


de f s ea r chSeq ( e l , l ) :’ ’ ’Search f o r an e l ement i n l i s te l − e l ementl − l i s t o f o r d e r ed e l ement sReturn the p o s i t i o n o f the f i r s t occu r r ence , o r

p o s i t i o n where e l ement can be i n s e r t e d’ ’ ’i f l e n ( l ) == 0 : r e t u r n 0poz = −1f o r i i n range (0 , l e n ( l ) ) :

i f e l<=l [ i ] :poz = i

i f poz == −1: r e t u r n l e n ( l )r e t u r n poz

Computational complexity is T (n) =n−1∑i=0

1 = n ∈ Θ(n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


de f s e a r c hSu c c e s o r ( e l , l ) :’ ’ ’Search f o r an e l ement i n l i s te l − e l ementl − l i s t o f o r d e r ed e l ement sReturn the p o s i t i o n o f the f i r s t occu r r ence , o r

p o s i t i o n where e l ement can be i n s e r t e d’ ’ ’i f l e n ( l )==0 or e l<=l [ 0 ] :

r e t u r n 0i f e l>=l [ −1 ] :

r e t u r n l e n ( l )i = 0wh i l e i<l e n ( l ) and e l> l [ i ] :

i += 1r e t u r n i

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions


Best case: the element is at the first position,T (n) ∈ Θ(1).

Worst case: the element is in the n-1 position,T (n) ∈ Θ(n).

Average case: if distributing the element uniformly, theloop can be executed 0, 1, .., n − 1 times, soT (n) = 1+2+..+n−1

n ∈ Θ(n).

Overabll complexity is O(n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Searching algorithms

Sequential search

Keys are successively examinedKeys may not be ordered

Binary search

Uses the divide and conquer techniqueKeys are ordered

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Recursive binary-search algorithm

de f b i n a r yS e a r c h ( key , data , l e f t , r i g h t ) :’ ’ ’Search f o r an e l ement i n an o rd e r ed l i s tkey − e l ement to s e a r c hl e f t , r i g h t − bounds o f the s e a r c hReturn i n s e r t i o n p o s i t i o n o f key tha t keeps l i s t

o r d e r ed’ ’ ’i f l e f t >= r i g h t − 1 :

r e t u r n r i g h tmidd l e = ( l e f t + r i g h t ) // 2i f key < data [ midd l e ] :

r e t u r n b i n a r yS e a r c h ( key , data , l e f t , m idd l e )e l s e :

r e t u r n b i n a r yS e a r c h ( key , data , middle , r i g h t)

p r i n t ( b i n a r yS e a r c h (2000 , data , 0 , l e n ( data ) ) )

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Recursive binary-search function

de f s e a r c h ( key , data ) :’ ’ ’Search f o r an e l ement i n an o rd e r ed l i s tkey − e l ement to s e a r c hdata − the l i s tReturn i n s e r t i o n p o s i t i o n o f key tha t keeps l i s t

o r d e r ed’ ’ ’i f l e n ( data ) == 0 or key < data [ 0 ] :

r e t u r n 0i f key > data [ −1 ] :

r e t u r n l e n ( data )r e t u r n b i n a r yS e a r c h ( key , data , 0 , l e n ( data ) )

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Binary-search recurrence

The recurrence: T(n) =

{1, n = 1

T (n2 ) + 1, n > 1

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Iterative binary-search function

de f b i n a r yS e a r c h ( key , data ) :’ ’ ’− s p e c i f i c a t i o n −’ ’ ’i f l e n ( data ) == 0 or key < data [ 0 ] :

r e t u r n 0i f key > data [ −1 ] :

r e t u r n l e n ( data )l e f t = 0r i g h t = l e n ( data )wh i l e r i g h t − l e f t > 1 :

midd l e = ( l e f t + r i g h t ) // 2i f key <= data [ midd l e ] :

r i g h t = midd lee l s e :

l e f t = midd ler e t u r n r i g h t

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Search problem runtime complexity

Algorithm Best case Average Worst case Overall

Sequential Θ(n) Θ(n) Θ(n) Θ(n)

Succesor Θ(1) Θ(n) Θ(n) O(n)

Binary-search Θ(1) Θ(log2 n) Θ(log2 n) O(log2 n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Demo

Collections and search

Examine the source code in ex34 search.py

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

The sorting problem

Sorting

Rearrange a data collection in such a way that the elements ofthe collection verify a given order.

Internal sort - data to be sorted are available in theinternal memory

External sort - data is available as a file (on externalmedia)

In-place sort - transforms the input data into the output,only using a small additional space. Its opposite is calledout-of-place.

Sorting stability - we say that sorting is stable when theoriginal order of multiple records having the same key ispreserved

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Demo

Stable sort example

Examine the source code in ex35 stableSort.py

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

The sorting problem

Elements of the data collection are called records

A record is formed by one or more components, calledfields

A key K is associated to each record, and is usually one ofthe fields.

We say that a collection of n records is:

Sorted in increasing order by the key K : if K (i) ≤ K (j) for0 ≤ i < j < nSorted in decreasing order: if K (i) ≥ K (j) for0 ≤ i < j < n

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Internal sorting


Data: n,K , where K = (k1, k2, ..., kn), ki ∈ R, i = 1, n

Results: K ′, where K ′ is a permutation of K , havingsorted elements: k ′1 ≤ k ′2 ≤ ... ≤ k ′n.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Sorting algorithms

A few algorithms that we will study:

Selection sort

Insertion sort

Bubble sort

Quick sort

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Selection Sort

Determine the element having the minimal key, and swapit with the first element.

Resume the procedure for the remaining elements, until allelements have been considered.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Selection sort algorithm

de f s e l e c t i o n S o r t ( data ) :f o r i i n range ( l e n ( data ) ) :

m in i ndex = i# Find sma l l e s t e l ement i n the r e s t o f the

l i s tf o r j i n range ( i +1, l e n ( data ) ) :

i f data [ j ] < data [ m in i ndex ] :m in i ndex = j

data [ i ] , data [ m in i ndex ] = data [ m in i ndex ] ,data [ i ]

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Selection sort - time complexity

The total number of comparisons isn−1∑i=1

n∑j=i+1

1 =n(n − 1)

2∈ Θ(n2)

Independent of the input data size, what are the best,average, worst-case computational complexities?

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Selection sort - space complexity

In-place algorithms. Algorithms that use a small(constant) quantity of additional memory.

Out-of-place or not-in-space algorithms. Algorithms thatuse a non-constant quantity of extra-space.

The additional memory required by selection sort is O(1).

Selection sort is an in-place sorting algorithm.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Direct selection sort

de f d i r e c t S e l e c t i o n S o r t ( data ) :f o r i i n range (0 , l e n ( data ) − 1) :

# S e l e c t the sm a l l e s t e l ementf o r j i n range ( i + 1 , l e n ( data ) ) :

i f data [ j ] < data [ i ] :data [ i ] , data [ j ] = data [ j ] , data [ i ]

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Direct selection sort

Overall time complexity:n−1∑i=1

n∑j=i+1

1 =n(n − 1)

2∈ Θ(n2)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Insertion Sort

Traverse the elements.

Insert the current element at the right position in thesubsequence of already sorted elements.

The sub-sequence containing the already processedelements is kept sorted, so that, at the end of thetraversal, the whole sequence is sorted.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Insertion Sort - Algorithm

de f i n s e r t S o r t ( data ) :f o r i i n range (1 , l e n ( data ) ) :

i nd e x = i − 1elem = data [ i ]# I n s e r t i n t o c o r r e c t p o s i t i o nwh i l e i ndex >= 0 and elem < data [ i ndex ] :

data [ i nd ex + 1 ] = data [ i nd ex ]i nd ex −= 1

data [ i ndex + 1 ] = elem

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Insertion Sort - time complexity

Maximum number of iterations (worst case) happens if theinitial array is sorted in a descending order:

T (n) =n∑

i=2

(i − 1) =n(n − 1)

2∈ Θ(n2)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Insertion Sort - time complexity

Minimum number of iterations (best case) happens if theinitial array is already sorted:

T (n) =n∑

i=2

1 = n − 1 ∈ Θ(n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Insertion Sort - Space complexity

Time complexity - The overall time complexity of insertionsort is O(n2).

Space complexity - The complexity of insertion sort is θ(1)

Insertion sort is an in-place sorting algorithm.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Bubble Sort

Compares pairs of consecutive elements that are swappedif not in the expected order.

The comparison process ends when all pairs of consecutiveelements are in the expected order.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Bubble Sort - Algorithm

de f bubb l eSo r t ( data ) :done = Fa l s ewh i l e not done :

done = Truef o r i i n range (0 , l e n ( data ) − 1) :

i f data [ i ] > data [ i +1] :data [ i ] , data [ i +1] = data [ i +1] , data

[ i ]done = Fa l s e

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Bubble Sort - Complexity

Best-case running time complexity order is θ(n)

Worst-case running time complexity order is θ(n2)

Average running-time complexity order is θ(n2)

Space complexity, additional memory required is θ(1)

Bubble sort is an in-place sorting algorithm.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort

Based on the divide and conquer technique

1 Divide: partition array into 2 sub-arrays such thatelements in the lower part ≤ elements in the higher part.

Partitioning

Re-arrange the elements so that the element called pivotoccupies the final position in the sub-sequence. If i is thatposition: kj ≤ ki ≤ kl , for Left ≤ j < i < l ≤ Right

2 Conquer: recursively sort the 2 sub-arrays.

3 Combine: trivial since sorting is done in place.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - partitioning algorithm

de f p a r t i t i o n ( data , l e f t , r i g h t ) :p i v o t = data [ l e f t ]i = l e f tj = r i g h twh i l e i != j :

# Find an e lement sma l l e r than the p i v o twh i l e data [ j ] >= p i v o t and i < j :

j −= 1data [ i ] = data [ j ]# Find an e lement l a r g e r than the p i v o twh i l e data [ i ] <= p i v o t and i < j :

i += 1data [ j ] = data [ i ]

# Place the p i v o t i n p o s i t i o ndata [ i ] = p i v o tr e t u r n i

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - algorithm

de f qu i c kSo r t ( data , l e f t , r i g h t ) :# P a r t i t i o n the l i s tpos = p a r t i t i o n ( data , l e f t , r i g h t )# Order l e f t s i d ei f l e f t < pos − 1 :

qu i c kSo r t ( data , l e f t , pos − 1)# Order r i g h t s i d ei f pos + 1 < r i g h t :

q u i c kSo r t ( data , pos + 1 , r i g h t )

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - time complexity

The run time of quick-sort depends on the distribution ofsplits

The partitioning function requires linear time

Best case, the partitioning function splits the arrayevenly: T (n) = 2T (n2 ) + Θ(n),T (n) ∈ Θ(n log2 n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - best partitioning

We partition n elements log2 n times, soT (n) ∈ Θ(n log2 n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - worst partitioning

In the worst case, function Partition splits the array suchthat one side of the partition has only one element:T (n) = T (1) + T (n − 1) + Θ(n) = T (n − 1) + Θ(n) =n∑

k=1

Θ(k) ∈ Θ(n2)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Quick Sort - Worst case

Worst case partitioning appears when the input array issorted or reverse sorted, so n elements are partitioned ntimes, T (n) ∈ Θ(n2)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Sorting runtime complexity

Algorithm Worst case Average

Selection sort Θ(n2) Θ(n2)

Insertion sort Θ(n2) Θ(n2)

Bubble sort Θ(n2) Θ(n2)

Quick sort Θ(n2) Θ(n log2 n)

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Demo

Sorting

Examine the source code in ex36 sort.py

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Lambda expressions

Lambda expressions

Small anonymous functions, that you define and use in thesame place.

Syntactically restricted to a single expression.

Can reference variables from the containing scope (justlike nested functions).

They are syntactic sugar for a function definition.

Lecture 13


Searching


Searchingalgorithms

Binary search

Search in Python

Sorting

The sortingproblem

Selection sort

Insertion sort

Bubble Sort

Quick Sort

LambdaExpressions

Demo

Lambda Expressions

Examine the source code in ex36 lambdas.py

Searching. Sorting. Lambdas - cs.ubbcluj.roarthur/FP2018/Lecture Notes/13.Searching.Sorting... ·...

Documents

Transcript of Searching. Sorting. Lambdas - cs.ubbcluj.roarthur/FP2018/Lecture Notes/13.Searching.Sorting... ·...