
Problem Statement
In a problem environment, the task concerns transforming a given string of characters, each representing a colored block ('W' for white and 'B' for black), into a configuration where there are at least k
consecutive black blocks. This transformation allows changing a white block to a black block, referred as an operation. The goal is to determine the minimum number of such operations necessary to ensure at least one sequence of k
consecutive black blocks exists within the string.
Examples
Example 1
Input:
blocks = "WBBWWBBWBW", k = 7
Output:
3
Explanation:
One way to achieve 7 consecutive black blocks is to recolor the 0th, 3rd, and 4th blocks so that blocks = "BBBBBBBWBW". It can be shown that there is no way to achieve 7 consecutive black blocks in less than 3 operations. Therefore, we return 3.
Example 2
Input:
blocks = "WBWBBBW", k = 2
Output:
0
Explanation:
No changes need to be made, since 2 consecutive black blocks already exist. Therefore, we return 0.
Constraints
n == blocks.length
1 <= n <= 100
blocks[i]
is either'W'
or'B'
.1 <= k <= n
Approach and Intuition
To solve this problem, consider using a sliding window technique which efficiently counts the number of operations required without having to check every possible substring:
- Initialize a window of size
k
to inspect segments of theblocks
string. - Slide this window across
blocks
from the start to the end:- For each position of this window, calculate how many white blocks ('W') are present.
- Keep track of the minimum number of white blocks seen in any window position – this will translate to the minimum number of conversions required since each white block within a window needs to be converted to achieve
k
consecutive black blocks.
- The result is then the minimum number of 'W' characters that had to be counted in any window, as this would be the least number of operations required.
By focusing on the count of white blocks within each window, you avoid the necessity of explicitly modifying the string multiple times, leading to a more optimized solution. The method also ensures all regions of the string are assessed for the minimum operation count in a single pass, given the constraints. This approach is particularly effective for small to mid-sized strings as defined by the upper constraint (n <= 100
).
Solutions
- C++
- Java
- Python
class Solution {
public:
int minRecolorOperations(string blockLine, int width) {
int start = 0, whiteCount = 0, minRecolors = INT_MAX;
// Traverse with the end index
for (int end = 0; end < blockLine.size(); end++) {
// Count white blocks at the current end index
if (blockLine[end] == 'W') {
whiteCount++;
}
// When we have a window of size 'width'
if (end - start + 1 == width) {
// Compare and update the minimum recolor needed
minRecolors = min(minRecolors, whiteCount);
// Reduce white count when exceeding window size
if (blockLine[start] == 'W') whiteCount--;
// Slide the window
start++;
}
}
return minRecolors;
}
};
The provided C++ solution is designed to find the minimum number of recolor operations needed to transform a given segment of blocks into a segment consisting entirely of black blocks (denoted by 'B') in a string, where white blocks are denoted by 'W'. The goal is to have at least 'k' consecutive black blocks. The string representing the blocks and the desired length of consecutive black blocks, k
, are passed as inputs to the function.
Here’s how the solution works:
- Initiate a sliding window approach with two pointers,
start
andend
, to represent the current window of blocks being assessed. - Initialize
whiteCount
to track the number of white blocks in the current sliding window andminRecolors
to store the minimum recolor operations found. - Traverse the string using the
end
pointer. For each block at positionend
, if the block is white, increment thewhiteCount
. - Check if the size of the window between
start
andend
matches the desired widthk
. If it does:- Update
minRecolors
with the smaller value between the currentminRecolors
andwhiteCount
. - If the block at position
start
is white, decrementwhiteCount
(since the block will be excluded from the window in the next step). - Increment the
start
pointer to slide the window forward.
- Update
- The loop ends when
end
has moved past the last block in the string. - Finally, return
minRecolors
, which now holds the minimum number of recolors needed to achieve at leastk
consecutive black blocks within any segment of the input block string.
This approach efficiently minimizes the number of color changes required by dynamically adjusting the assessment window and counting only the necessary changes for each possible segment.
class Solution {
public int minRecolorsNeeded(String blockSequence, int k) {
int start = 0, whiteCount = 0, minRecolors = Integer.MAX_VALUE;
for (int end = 0; end < blockSequence.length(); end++) {
if (blockSequence.charAt(end) == 'W') {
whiteCount++;
}
if (end - start + 1 == k) {
minRecolors = Math.min(minRecolors, whiteCount);
if (blockSequence.charAt(start) == 'W') whiteCount--;
start++;
}
}
return minRecolors;
}
}
The given solution is a Java program designed to solve the problem of determining the minimum number of recolors needed to get exactly 'k' consecutive black blocks in a given string sequence of blocks colored either black ('B') or white ('W').
The program follows these steps:
Initialize three variables:
start
to mark the beginning of the sliding window,whiteCount
to keep track of the number of white blocks within the current window, andminRecolors
set to the maximum possible value (infinity in practical scenarios).Iterate over each character in the string with a variable
end
that represents the end of the sliding window.As the window slides (increment
end
), update thewhiteCount
if a white block ('W') is found.Check if the window size has reached 'k'. If it has:
- Update
minRecolors
to the minimum of its current value or thewhiteCount
. - If the block at the
start
position of the window is white, decrementwhiteCount
because the window is about to exclude that block in the next step. - Move the
start
forward by one position to slide the window.
- Update
Return
minRecolors
as the result which gives the minimum recolors needed.
The algorithm effectively uses a sliding window technique to examine each possible sequence of 'k' blocks in the string. By keeping a tally of white blocks within each window and updating the counters correctly with each slide, it minimizes the number of recalculations needed, resulting in an efficient solution.
class Solution:
def minRecolorings(self, blockLine: str, length: int) -> int:
start = 0
countWhite = 0
leastRecolors = float("inf")
for end in range(len(blockLine)):
if blockLine[end] == "W":
countWhite += 1
if end - start + 1 == length:
leastRecolors = min(leastRecolors, countWhite)
if blockLine[start] == "W":
countWhite -= 1
start += 1
return leastRecolors
The problem requires finding the minimum number of times you need to recolor white blocks to black in order to have k
consecutive black blocks in a given string representation of blocks. The solution is implemented in Python using a sliding window approach.
- Initialize
start
to zero, which marks the beginning of the sliding window. - Utilize
countWhite
to track the number of white blocks ('W'
) within the current window. - Use
leastRecolors
to keep track of the minimum recolors required, starting its value at infinity to ensure it will be updated during the process.
Follow the steps below to solve the problem:
- Iterate through each block in the
blockLine
string using a variableend
which marks the end of the sliding window. - Check if the current block is white (
'W'
) and incrementcountWhite
accordingly. - When the window size matches the desired length
k
:- Update
leastRecolors
with the minimum of its current value orcountWhite
. - If the block at the start of the window is white, decrement
countWhite
. - Move the start of the window forward by 1.
- Update
- The loop continues until every possible window of size
k
has been examined. - Return
leastRecolors
, which now contains the minimum number of recolors required to achieve at least one sequence ofk
consecutive black blocks.
This method efficiently uses a sliding window technique to check each possible sequence of k
blocks in the string, ensuring optimal performance by only requiring a single pass through the blockLine
. The conditionals within the loop handle the adjustment of the window and the count of white blocks efficiently.
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