Largest Rectangle In Histogram
To solve this coding challenge, it is essential to understand the underlying concepts and the steps required to find the area of the largest rectangle within a histogram. Below, I break down the approach and the steps involved with detailed explanations and pseudocode.
Explanation
The problem is to determine the area of the largest rectangle contained within a histogram represented by an array of integers where each element corresponds to the height of a bar and the width of each bar is 1.Problem Breakdown
- Histogram Representation :
- Each element of the array represents a bar's height.
- The width of each bar is uniformly 1.
- Goal :
- To find the maximum rectangular area which can be formed by one or more contiguous bars.
- A stack helps keep track of the indices of the bars in an increasing order of their heights.
- By maintaining this order, when a bar of lower height is encountered, it triggers the calculation of the potential largest rectangle formed with the heights stored in the stack.
- Initialize :
- A stack to keep track of bar indices.
-
A variable
max_area
- Append a Sentinel Value :
-
Append a
0
- Iterate Through Each Height :
- For each height in the histogram, if it is lower than the height of the bar represented by the index at the top of the stack, it implies a boundary for potential rectangles.
- Calculate Area :
- Pop the index from the stack, calculate the height of the rectangle using the popped index.
- Calculate the width based on the current index and the index of the remaining top stack element.
-
Update
max_area
max_area
- Return the Maximum Area :
- Finally, after processing all bars, return the maximum area calculated.
Approach
The problem can be efficiently solved using a monotonic stack . Here is why:Detailed Steps in Pseudocode
The core idea is to iterate through the histogram and utilize the stack to manage the heights and their indices, calculating the potential largest areas dynamically.Pseudocode
# Initialize an empty stack to store bar indices
stack = []
# Initialize max_area to keep track of the largest rectangle
max_area = 0
# Append 0 to heights to ensure the stack is emptied at the end
heights.append(0)
# Iterate over each bar in the histogram, including the appended 0 height
for current_index in range(length of heights):
# While stack is not empty and current height is less than height at stack's top index
while stack is not empty and heights[current_index] < heights[stack's top index]:
# Pop the top index from the stack, calculate height using this index
height_of_bar = heights[stack.pop()]
# Calculate width: If stack is empty, width is the current index, else width is difference between current index and new top index - 1
if stack is empty:
width = current_index
else:
width = current_index - stack's top index - 1
# Calculate area using height and width
area = height_of_bar * width
# Update max_area if current area is larger
max_area = max(max_area, area)
# Push the current index to the stack
stack.append(current_index)
# Return the max_area found
return max_area
This pseudocode provides a clear step-by-step method to find the largest rectangular area within the histogram. Each step is annotated to ensure that anyone reading can understand the purpose behind each operation. By using a stack to keep track of indices and dynamically calculating potential areas, we efficiently solve the problem with optimal time complexity.