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In python 3 Simple Iterative As we in general, try to solve the problem

In python 3 Simple Iterative As we in general, try to solve the problem

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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In python 3

Simple Iterative

As we in general, try to solve the problem first; we start with a brute force, simple, algorithm: design it below

 

Divide and Conquer Now, we would try to use a divide and conquer paradigm. Hint: try the three steps, and design multiple versions to master these steps # write your implementation here def maxProfit(changes): This is just an interface for <maxProfitDivide> it returns the indices of (i,j) indicating the day to buy and sell respectively to have the maximum profit in a list of prices per day in <changes>. Inputs: - changes: the list holding the changes in prices; the value whose index is k represents the change between day <k> and day <k+1> <changes> has at least a single change [two days] Output: - i: the index of the change before which we buy - j: the index of the change after which we sell maxProfit: the value of the maximum profit return (0,0,0) maxProfit([13,7,-30,15,10,-5,12,7,-11,6])
Transcribed Image Text:Divide and Conquer Now, we would try to use a divide and conquer paradigm. Hint: try the three steps, and design multiple versions to master these steps # write your implementation here def maxProfit(changes): This is just an interface for <maxProfitDivide> it returns the indices of (i,j) indicating the day to buy and sell respectively to have the maximum profit in a list of prices per day in <changes>. Inputs: - changes: the list holding the changes in prices; the value whose index is k represents the change between day <k> and day <k+1> <changes> has at least a single change [two days] Output: - i: the index of the change before which we buy - j: the index of the change after which we sell maxProfit: the value of the maximum profit return (0,0,0) maxProfit([13,7,-30,15,10,-5,12,7,-11,6])
# write your implementation here def maxProfitBrute(changes): it returns the indices of (i,j) indicating the day to buy and sell respectively to have the maximum profit in a list of prices per day in <changes>. Inputs: - changes: the list holding the changes in prices; the value whose index is k represents the change between day <k> and day <k+1> <changes> has at least a single change [two days] Output: - i: the index of the change before which we buy j: the index of the change after which we sell - maxProfit: the value of the maximum profit Example: changes = [1,2] - that means the price started with <x>; - day 1: it became <X+1> - day 2: it became <X+3> In that case: (i,j) = (0,1) as we should buy at the first day, and sell after the third day # return the values return (0,0,e) # Try your algorithm maxProfitBrute([13,7,-30,15,10, -5,12,7, -11,6])
Transcribed Image Text:# write your implementation here def maxProfitBrute(changes): it returns the indices of (i,j) indicating the day to buy and sell respectively to have the maximum profit in a list of prices per day in <changes>. Inputs: - changes: the list holding the changes in prices; the value whose index is k represents the change between day <k> and day <k+1> <changes> has at least a single change [two days] Output: - i: the index of the change before which we buy j: the index of the change after which we sell - maxProfit: the value of the maximum profit Example: changes = [1,2] - that means the price started with <x>; - day 1: it became <X+1> - day 2: it became <X+3> In that case: (i,j) = (0,1) as we should buy at the first day, and sell after the third day # return the values return (0,0,e) # Try your algorithm maxProfitBrute([13,7,-30,15,10, -5,12,7, -11,6])
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