Introduction to Programming: Lecture 6
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1 Introduction to Programming: Lecture 6 K Narayan Kumar Chennai Mathematical Institute 28 August 2012
2 Example: initial segments Write a Haskell function initsegs which returns the list of initial segments of a list. initsegs [1,2,3] = [[],[1],[1,2],[1,2,3]] initsegs [] = [[]]
3 Example: initial segments Write a Haskell function initsegs which returns the list of initial segments of a list. initsegs [1,2,3] = [[],[1],[1,2],[1,2,3]] initsegs [] = [[]] initsegs [] = [[]] initsegs (x:xs) = [] : map (x:) (initsegs xs)
4 Example: interleave interleave x l inserts x into all possible positions in the list l interleave 3 [] = [[3]] interleave 3 [2,3] = [[3,2,3],[2,3,3],[2,3,3]] interleave a "abcd" = ["aabcd","aabcd","abacd","abcad","abcda"]
5 Example: interleave interleave x l inserts x into all possible positions in the list l interleave 3 [] = [[3]] interleave 3 [2,3] = [[3,2,3],[2,3,3],[2,3,3]] interleave a "abcd" = ["aabcd","aabcd","abacd","abcad","abcda"] interleave x [] = [[x]] interleave x (y:ys) = (x:y:ys) : map (y:) (interleave x ys)
6 Example: Permutations Write down function that computes all the permutations of a given list.
7 Example: Permutations Write down function that computes all the permutations of a given list. Notice that this problem does not have a unique answer. We are happy with a listing of all the permutations in any order.
8 Example: Permutations Write down function that computes all the permutations of a given list. Notice that this problem does not have a unique answer. We are happy with a listing of all the permutations in any order. perm [1,2,3] = [[1,2,3],[2,1,3],[2,3,1], [1,3,2],[3,1,2],[3,2,1]]
9 Example: Permutations Write down function that computes all the permutations of a given list. Notice that this problem does not have a unique answer. We are happy with a listing of all the permutations in any order. perm [1,2,3] = [[1,2,3],[2,1,3],[2,3,1], [1,3,2],[3,1,2],[3,2,1]] perm [x] = [[x]] perm (x:xs) = concat (map (interleave x) (perm xs))
10 Example: Permutations Write down function that computes all the permutations of a given list. Notice that this problem does not have a unique answer. We are happy with a listing of all the permutations in any order. perm [1,2,3] = [[1,2,3],[2,1,3],[2,3,1], [1,3,2],[3,1,2],[3,2,1]] perm [x] = [[x]] perm (x:xs) = concat (map (interleave x) (perm xs)) The combination concat (map f l) appears so often that there is a function concatmap which does precisely this: concatmap f l = concat (map f l)
11 Example: Permutations Write down function that computes all the permutations of a given list. Notice that this problem does not have a unique answer. We are happy with a listing of all the permutations in any order. perm [1,2,3] = [[1,2,3],[2,1,3],[2,3,1], [1,3,2],[3,1,2],[3,2,1]] perm [x] = [[x]] perm (x:xs) = concat (map (interleave x) (perm xs)) The combination concat (map f l) appears so often that there is a function concatmap which does precisely this: concatmap f l = concat (map f l) Exercise: What is the type of concatmap
12 Example: Partitions Given a list l is a collection of nonempty lists l1, l2,..., lk such that l = l1 ++ l lk
13 Example: Partitions Given a list l is a collection of nonempty lists l1, l2,..., lk such that l = l1 ++ l lk part [1,2,3] = [[[1],[2],[3]],[[1,2],[3]], [[1],[2,3]],[[1,2,3]]]
14 Example: Partitions Given a list l is a collection of nonempty lists l1, l2,..., lk such that l = l1 ++ l lk part [1,2,3] = [[[1],[2],[3]],[[1,2],[3]], [[1],[2,3]],[[1,2,3]]] The type of part is part :: [a] -> [[[a]]]
15 Example: Partitions Given a list l is a collection of nonempty lists l1, l2,..., lk such that l = l1 ++ l lk part [1,2,3] = [[[1],[2],[3]],[[1,2],[3]], [[1],[2,3]],[[1,2,3]]] The type of part is part :: [a] -> [[[a]]] part [x] = [[[x]]] part (x:xs) = map ([x]:) (part xs) ++ map (f x) (part xs) where f x (y:ys) = (x:y):ys
16 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order.
17 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this
18 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this remove the first element to get a shorter list sort this shorter list insert the first element in the correct position in the sorted list
19 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this remove the first element to get a shorter list sort this shorter list insert the first element in the correct position in the sorted list sort [2,1,3,2,4]
20 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this remove the first element to get a shorter list sort this shorter list insert the first element in the correct position in the sorted list sort [2,1,3,2,4] insert 2 in sort [1,3,2,4]
21 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this remove the first element to get a shorter list sort this shorter list insert the first element in the correct position in the sorted list sort [2,1,3,2,4] insert 2 in sort [1,3,2,4] insert 2 in [1,2,3,4]
22 Sorting: Insertion sorting Given a list of integers rearrange it in ascending order. Here is one way to do this remove the first element to get a shorter list sort this shorter list insert the first element in the correct position in the sorted list sort [2,1,3,2,4] insert 2 in sort [1,3,2,4] insert 2 in [1,2,3,4] [1,2,2,3,4]
23 Insertion Sorting How to insert a number in the correct position in a sorted list?
24 Insertion Sorting How to insert a number in the correct position in a sorted list? insert 3 [1,2,2,4] = [1,2,2,3,4] insert 3 [] = [3]
25 Insertion Sorting How to insert a number in the correct position in a sorted list? insert 3 [1,2,2,4] = [1,2,2,3,4] insert 3 [] = [3] insert Int -> [Int] -> [Int] insert x [] = [x] insert x (y:ys) (x <= y) = x:y:ys otherwise = y : insert x ys
26 Insertion Sorting How to insert a number in the correct position in a sorted list? insert 3 [1,2,2,4] = [1,2,2,3,4] insert 3 [] = [3] insert Int -> [Int] -> [Int] insert x [] = [x] insert x (y:ys) (x <= y) = x:y:ys otherwise = y : insert x ys Note that insert is not polymorphic, in the sense that we have seen so far, as <= is not necessarily defined on all types.
27 Insertion Sorting Define isort :: [Int] -> [Int] using insert
28 Insertion Sorting Define isort :: [Int] -> [Int] using insert isort [] = [] isort (x:xs) = insert x (isort xs)
29 Insertion Sorting Define isort :: [Int] -> [Int] using insert isort [] = [] isort (x:xs) = insert x (isort xs) or more succinctly isort = foldr insert []
30 Sorting: Merge Sorting Here is another method to sort a list. Divide the list into two halves. Sort each recursively using this algorithm. Merge together the two sorted lists into a single sorted list.
31 Merging two sorted lists
32 Merging two sorted lists
33 Merging two sorted lists
34 Merging two sorted lists
35 Merging two sorted lists
36 Merging two sorted lists
37 Merging two sorted lists
38 Merging two sorted lists
39 Merging two sorted lists
40 Merging two sorted lists
41 Mergesort
42 Mergesort
43 Mergesort
44 Mergesort
45 Mergesort
46 Mergesort
47 Mergesort
48 Mergesort
49 Mergesort
50 Mergesort
51 Merging in Haskell merge to merge two sorted lists of integers.
52 Merging in Haskell merge to merge two sorted lists of integers. merge :: [Int] -> [Int] -> [Int] merge [] l = l merge l [] = l merge (x:xs) (y:ys) (x < y) = x : merge xs (y:ys) otherwise = y : merge (x:xs) ys
53 Merging in Haskell merge to merge two sorted lists of integers. merge :: [Int] -> [Int] -> [Int] merge [] l = l merge l [] = l merge (x:xs) (y:ys) (x < y) = x : merge xs (y:ys) otherwise = y : merge (x:xs) ys Once again, merge is not polymorphic, in the sense that we have seen so far, as it uses <.
54 Mergesort in Haskell Using merge to write down a mergesort
55 Mergesort in Haskell Using merge to write down a mergesort mergesort :: [Int] -> [Int] mergesort [] = [] mergesort [x] = [x] mergesort l = merge (mergesort fhalf) (mergesort shalf) where fhalf = take n l shalf = drop n l n = div (length l) 2
56 Mergesort in Haskell Using merge to write down a mergesort mergesort :: [Int] -> [Int] mergesort [] = [] mergesort [x] = [x] mergesort l = merge (mergesort fhalf) (mergesort shalf) where fhalf = take n l shalf = drop n l n = div (length l) 2
57 Sorting: Quicksort Suppose we can find the median (middle element in the sorted order) in a list
58 Sorting: Quicksort Suppose we can find the median (middle element in the sorted order) in a list Collect all values less than median and sort
59 Sorting: Quicksort Suppose we can find the median (middle element in the sorted order) in a list Collect all values less than median and sort Collect all values more than median and sort
60 Sorting: Quicksort Suppose we can find the median (middle element in the sorted order) in a list Collect all values less than median and sort Collect all values more than median and sort Combine these sorted sublists using ++ (No need to merge)
61 Sorting: Quicksort Suppose we can find the median (middle element in the sorted order) in a list Collect all values less than median and sort Collect all values more than median and sort Combine these sorted sublists using ++ (No need to merge) Median is not easy to find.
62 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice.
63 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice. Pick a pivot p from the list L
64 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice. Pick a pivot p from the list L Rearrange the list as L 1 pl 2 where
65 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice. Pick a pivot p from the list L Rearrange the list as L 1 pl 2 where L1 is the list of elements of L that are smaller than p and
66 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice. Pick a pivot p from the list L Rearrange the list as L 1 pl 2 where L1 is the list of elements of L that are smaller than p and L2 is the list of elements of L that are at least as big as p.
67 Quicksort A sorting algorithm proposed by C.A.R.Hoare. It is extensively used in practice. Pick a pivot p from the list L Rearrange the list as L 1 pl 2 where L1 is the list of elements of L that are smaller than p and L2 is the list of elements of L that are at least as big as p. Sort L 1 and L 2 recursively.
68 Quicksort
69 Quicksort
70 Quicksort
71 Quicksort
72 Quicksort
73 Quicksort
74 Quicksort... quicksort :: [Int] -> [Int] quicksort [] = [] quicksort (x:xs) = (quicksort lower) ++ [splitter] ++ (quicksort upper) where splitter = x lower = filter (<= x) xs upper = filter (> x) xs
75 Quicksort... quicksort :: [Int] -> [Int] quicksort [] = [] quicksort (x:xs) = (quicksort lower) ++ [splitter] ++ (quicksort upper) where splitter = x lower = filter (<= x) xs upper = filter (> x) xs In the worst case, lower or upper is empty
76 Quicksort... quicksort :: [Int] -> [Int] quicksort [] = [] quicksort (x:xs) = (quicksort lower) ++ [splitter] ++ (quicksort upper) where splitter = x lower = filter (<= x) xs upper = filter (> x) xs In the worst case, lower or upper is empty For our choice of splitter, worst case input is any sorted list
77 Measuring efficiency in Haskell Computation in Haskell is rewriting Using a definition to rewrite an expression = reduction step
78 Measuring efficiency in Haskell Computation in Haskell is rewriting Using a definition to rewrite an expression = reduction step Count number of reduction steps T(n) for input of size n
79 Measuring efficiency in Haskell Computation in Haskell is rewriting Using a definition to rewrite an expression = reduction step Count number of reduction steps T(n) for input of size n What is the complexity of ++? [] ++ y = y (x:xs) ++ y = x:(xs++y)
80 Measuring efficiency in Haskell Computation in Haskell is rewriting Using a definition to rewrite an expression = reduction step Count number of reduction steps T(n) for input of size n What is the complexity of ++? [] ++ y = y (x:xs) ++ y = x:(xs++y) [1,2,3] ++ [4,5,6] -> 1:([2,3] ++ [4,5,6]) -> 1:(2:([3] ++ [4,5,6])) -> 1:(2:(3:([] ++ [4,5,6]))) -> 1:(2:(3:([4,5,6])))
81 Measuring efficiency in Haskell Computation in Haskell is rewriting Using a definition to rewrite an expression = reduction step Count number of reduction steps T(n) for input of size n What is the complexity of ++? [] ++ y = y (x:xs) ++ y = x:(xs++y) [1,2,3] ++ [4,5,6] -> 1:([2,3] ++ [4,5,6]) -> 1:(2:([3] ++ [4,5,6])) -> 1:(2:(3:([] ++ [4,5,6]))) -> 1:(2:(3:([4,5,6]))) In l1 ++ l2 we use the second rule length l1 times and the first rule once It takes as many steps as length l1 + 1
82 Efficiency... We would like to define the complexity of a program to be a function from the size of the input to the number of steps.
83 Efficiency... We would like to define the complexity of a program to be a function from the size of the input to the number of steps. T(n) = n for ++ where n is the length of the left argument.
84 Efficiency... We would like to define the complexity of a program to be a function from the size of the input to the number of steps. T(n) = n for ++ where n is the length of the left argument. The function ++ takes the same number of steps on inputs of the same length.
85 Efficiency... We would like to define the complexity of a program to be a function from the size of the input to the number of steps. T(n) = n for ++ where n is the length of the left argument. The function ++ takes the same number of steps on inputs of the same length. This need not always be the case.
86 Efficiency... elem :: Int -> [Int] -> Bool elem i [] = False elem i (x:xs) (i==x) = True otherwise = elem i xs The number of steps taken depends on the input (not just its length)
87 Efficiency... elem :: Int -> [Int] -> Bool elem i [] = False elem i (x:xs) (i==x) = True otherwise = elem i xs The number of steps taken depends on the input (not just its length) elem 3 [3,7,8,9] -> True
88 Efficiency... elem :: Int -> [Int] -> Bool elem i [] = False elem i (x:xs) (i==x) = True otherwise = elem i xs The number of steps taken depends on the input (not just its length) elem 3 [3,7,8,9] -> True elem 3 [4,7,8,9] -> elem 3 [7,8,9] -> elem 3 [8,9] -> elem 3 [9] -> elem 3 [] -> False
89 Efficiency... elem :: Int -> [Int] -> Bool elem i [] = False elem i (x:xs) (i==x) = True otherwise = elem i xs The number of steps taken depends on the input (not just its length) elem 3 [3,7,8,9] -> True elem 3 [4,7,8,9] -> elem 3 [7,8,9] -> elem 3 [8,9] -> elem 3 [9] -> elem 3 [] -> False What do we take the value of T(n) to be?
90 Efficiency... We can take the complexity T(n) on inputs of length n to be
91 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity
92 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity
93 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity The average among all inputs of length n. Average-case complexity
94 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity The average among all inputs of length n. Average-case complexity Best-case complexity is useless. For eg. it suggests that elem returns the answer in one step on any inputs of any length n.
95 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity The average among all inputs of length n. Average-case complexity Best-case complexity is useless. For eg. it suggests that elem returns the answer in one step on any inputs of any length n. Worst-case is pessimistic. But it assures us that on any input of length n the program does NOT take more than T(n) steps.
96 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity The average among all inputs of length n. Average-case complexity Best-case complexity is useless. For eg. it suggests that elem returns the answer in one step on any inputs of any length n. Worst-case is pessimistic. But it assures us that on any input of length n the program does NOT take more than T(n) steps. Average-case is perhaps a more accurate description. But is usually very difficult to calculate.
97 Efficiency... We can take the complexity T(n) on inputs of length n to be The maximum among all inputs of length n. Worst-case complexity The minimum among all inputs of length n. Best-case complexity The average among all inputs of length n. Average-case complexity Best-case complexity is useless. For eg. it suggests that elem returns the answer in one step on any inputs of any length n. Worst-case is pessimistic. But it assures us that on any input of length n the program does NOT take more than T(n) steps. Average-case is perhaps a more accurate description. But is usually very difficult to calculate. For the purposes of this course, we stick to worst-case analysis.
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