Maximum Value of K Coins From Piles

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class Solution:
    def maxValueOfCoins(self, piles: List[List[int]], k: int) -> int:
        @functools.lru_cache(None)
        def dp(i, m):
            if m == 0 or i == len(piles):
                return 0
            result = dp(i + 1, m)
            current = 0
            pile_length = len(piles[i])
            loop_range = min(pile_length, m)
            for j in range(loop_range):
                current += piles[i][j]
                dp_value = dp(i + 1, m - j - 1)
                total_value = current + dp_value
                result = max(result, total_value)
            return result

        return dp(0, k)

10 Prerequisite LeetCode Problems

“Maximum Value of K Coins From Piles” involves pplying sorting and greedy algorithm strategies. Here are 10 problems to build up to it:

“Maximum Product of Three Numbers” (LeetCode Problem #628): This problem requires sorting and simple understanding of product maximization.
“Assign Cookies” (LeetCode Problem #455): This problem involves greedy algorithms where you try to maximize the number of satisfied children, which is somewhat similar to maximizing the number of coins.
“Best Time to Buy and Sell Stock II” (LeetCode Problem #122): This problem is a good introduction to greedy algorithms, as it requires you to think about when to buy and sell stocks to maximize profit.
“Largest Number At Least Twice of Others” (LeetCode Problem #747): This problem requires finding the maximum element and comparing it with others, which is a basic operation in many greedy algorithms.
“Sell Diminishing-Valued Colored Balls” (LeetCode Problem #1648): This problem is about selling balls to maximize profit, which is a more complex version of the greedy algorithm.
“Array Partition I” (LeetCode Problem #561): This problem requires pairing and summing elements from a sorted array to maximize the total sum, which requires similar thought processes as the original problem.
“Last Stone Weight” (LeetCode Problem #1046): This problem is about repeatedly choosing the two largest stones (or piles), which involves a similar process to the one needed for the original problem.
“Maximum Subarray” (LeetCode Problem #53): This problem involves finding a contiguous subarray with the largest sum, which can provide useful practice with maximizing operations.
“Minimum Cost to Move Chips to The Same Position” (LeetCode Problem #1217): This problem is about moving items (or coins) to minimize cost, which requires similar greedy strategies as the original problem.
“Candy” (LeetCode Problem #135): This problem is about distributing items (or coins) based on certain rules, which requires an understanding of greedy algorithms and sorting.

Problem Classification

Problem Statement: There are n piles of coins on a table. Each pile consists of a positive number of coins of assorted denominations.

In one move, you can choose any coin on top of any pile, remove it, and add it to your wallet.

Given a list piles, where piles[i] is a list of integers denoting the composition of the ith pile from top to bottom, and a positive integer k, return the maximum total value of coins you can have in your wallet if you choose exactly k coins optimally.

Example 1:

Input: piles = [[1,100,3],[7,8,9]], k = 2 Output: 101 Explanation: The above diagram shows the different ways we can choose k coins. The maximum total we can obtain is 101. Example 2:

Input: piles = [[100],[100],[100],[100],[100],[100],[1,1,1,1,1,1,700]], k = 7 Output: 706 Explanation: The maximum total can be obtained if we choose all coins from the last pile.

Constraints:

n == piles.length 1 <= n <= 1000 1 <= piles[i][j] <= 105 1 <= k <= sum(piles[i].length) <= 2000

Analyze the provided problem statement. Categorize it based on its domain, ignoring ‘How’ it might be solved. Identify and list out the ‘What’ components. Based on these, further classify the problem. Explain your categorizations.

Visual Model of the Problem

How to visualize the problem statement for this problem?

Problem Restatement

Could you start by paraphrasing the problem statement in your own words? Try to distill the problem into its essential elements and make sure to clarify the requirements and constraints. This exercise should aid in understanding the problem better and aligning our thought process before jumping into solving it.

Abstract Representation of the Problem

Could you help me formulate an abstract representation of this problem?

Alternatively, if you’re working on a specific problem, you might ask something like:

Given this problem, how can we describe it in an abstract way that emphasizes the structure and key elements, without the specific real-world details?

Terminology

Are there any specialized terms, jargon, or technical concepts that are crucial to understanding this problem or solution? Could you define them and explain their role within the context of this problem?

Problem Simplification and Explanation

Could you please break down this problem into simpler terms? What are the key concepts involved and how do they interact? Can you also provide a metaphor or analogy to help me understand the problem better?

Constraints

Given the problem statement and the constraints provided, identify specific characteristics or conditions that can be exploited to our advantage in finding an efficient solution. Look for patterns or specific numerical ranges that could be useful in manipulating or interpreting the data.

What are the key insights from analyzing the constraints?

Case Analysis

Could you please provide additional examples or test cases that cover a wider range of the input space, including edge and boundary conditions? In doing so, could you also analyze each example to highlight different aspects of the problem, key constraints and potential pitfalls, as well as the reasoning behind the expected output for each case? This should help in generating key insights about the problem and ensuring the solution is robust and handles all possible scenarios.

Identification of Applicable Theoretical Concepts

Can you identify any mathematical or algorithmic concepts or properties that can be applied to simplify the problem or make it more manageable? Think about the nature of the operations or manipulations required by the problem statement. Are there existing theories, metrics, or methodologies in mathematics, computer science, or related fields that can be applied to calculate, measure, or perform these operations more effectively or efficiently?

Problem Breakdown and Solution Methodology

Given the problem statement, can you explain in detail how you would approach solving it? Please break down the process into smaller steps, illustrating how each step contributes to the overall solution. If applicable, consider using metaphors, analogies, or visual representations to make your explanation more intuitive. After explaining the process, can you also discuss how specific operations or changes in the problem’s parameters would affect the solution? Lastly, demonstrate the workings of your approach using one or more example cases.

Inference of Problem-Solving Approach from the Problem Statement

How did you infer from the problem statement that this problem can be solved using ?

Could you please provide a stepwise refinement of our approach to solving this problem?
How can we take the high-level solution approach and distill it into more granular, actionable steps?
Could you identify any parts of the problem that can be solved independently?
Are there any repeatable patterns within our solution?

Solution Approach and Analysis

Thought Process

Explain the thought process by thinking step by step to solve this problem from the problem statement and code the final solution. Write code in Python3. What are the cues in the problem statement? What direction does it suggest in the approach to the problem? Generate insights about the problem statement.

From Brute Force to Optimal Solution

Could you please begin by illustrating a brute force solution for this problem? After detailing and discussing the inefficiencies of the brute force approach, could you then guide us through the process of optimizing this solution? Please explain each step towards optimization, discussing the reasoning behind each decision made, and how it improves upon the previous solution. Also, could you show how these optimizations impact the time and space complexity of our solution?

Coding Constructs

Consider the following piece of complex software code.

What are the high-level problem-solving strategies or techniques being used by this code?
If you had to explain the purpose of this code to a non-programmer, what would you say?
Can you identify the logical elements or constructs used in this code, independent of any programming language?
Could you describe the algorithmic approach used by this code in plain English?
What are the key steps or operations this code is performing on the input data, and why?
Can you identify the algorithmic patterns or strategies used by this code, irrespective of the specific programming language syntax?

Language Agnostic Coding Drills

Your mission is to deconstruct this code into the smallest possible learning units, each corresponding to a separate coding concept. Consider these concepts as unique coding drills that can be individually implemented and later assembled into the final solution.

Dissect the code and identify each distinct concept it contains. Remember, this process should be language-agnostic and generally applicable to most modern programming languages.
Once you’ve identified these coding concepts or drills, list them out in order of increasing difficulty. Provide a brief description of each concept and why it is classified at its particular difficulty level.
Next, describe the problem-solving approach that would lead from the problem statement to the final solution. Think about how each of these coding drills contributes to the overall solution. Elucidate the step-by-step process involved in using these drills to solve the problem. Please refrain from writing any actual code; we’re focusing on understanding the process and strategy.

Targeted Drills in Python

Now that you’ve identified and ordered the coding concepts from a complex software code in the previous exercise, let’s focus on creating Python-based coding drills for each of those concepts.

Begin by writing a separate piece of Python code that encapsulates each identified concept. These individual drills should illustrate how to implement each concept in Python. Please ensure that these are suitable even for those with a basic understanding of Python.
In addition to the general concepts, identify and write coding drills for any problem-specific concepts that might be needed to create a solution. Describe why these drills are essential for our problem.
Once all drills have been coded, describe how these pieces can be integrated together in the right order to solve the initial problem. Each drill should contribute to building up to the final solution.

Remember, the goal is to not only to write these drills but also to ensure that they can be cohesively assembled into one comprehensive solution.