As we in general, try to solve the problem first; we start with a brute force, simple, algorithm: design it below # 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 . Inputs: - changes: the list holding the changes in prices; the value whose index is k represents the change between day and day 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 ; day 1: it became day 2: it became 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 (0,0,0)

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
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As we in general, try to solve the problem first; we start with a brute force, simple, algorithm: design it below
# 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 (0,0,0)
# Try vour alaorithm
Transcribed Image Text:As we in general, try to solve the problem first; we start with a brute force, simple, algorithm: design it below # 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 (0,0,0) # Try vour alaorithm
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])
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