LeetCode 2013: Detect Squares Solution
Master LeetCode problem 2013 (Detect Squares), a medium challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.
2013. Detect Squares
Problem Explanation
Explanation
To solve this problem, we can store the points in a data structure that allows for efficient retrieval of points based on their x and y coordinates. One way to achieve this is by using a hashmap of hashmaps, where the key of the outer hashmap represents the x-coordinate, and the inner hashmap stores the y-coordinate as the key and the frequency of that point as the value.
When adding a new point, we increment the frequency of that point in the hashmap. When counting the number of ways to form axis-aligned squares with a query point, we iterate through the points in the data structure and check for valid squares based on the given conditions.
The time complexity of adding a point is O(1), and the time complexity of counting is O(n), where n is the total number of points in the data structure.
Solution Code
class DetectSquares {
Map<Integer, Map<Integer, Integer>> points;
public DetectSquares() {
points = new HashMap<>();
}
public void add(int[] point) {
int x = point[0];
int y = point[1];
points.putIfAbsent(x, new HashMap<>());
points.get(x).put(y, points.get(x).getOrDefault(y, 0) + 1);
}
public int count(int[] point) {
int x = point[0];
int y = point[1];
int result = 0;
for (int px : points.keySet()) {
if (px == x) continue;
for (int py : points.get(px).keySet()) {
if (Math.abs(px - x) == Math.abs(py - y) && points.containsKey(x) && points.get(px).containsKey(y) && points.containsKey(px) && points.get(px).containsKey(py)) {
result += points.get(px).get(py) * points.get(x).get(y) * points.get(px).get(y);
}
}
}
return result;
}
}Try It Yourself
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