Merge branch 'DaleStudy:main' into main

Author: wogha95

find-median-from-data-stream/EGON.py

@@ -0,0 +1,67 @@
+from heapq import heappush, heappop
+from unittest import TestCase, main
+
+
+class MedianFinder:
+    """
+    Runtime: 137 ms (Beats 56.16%)
+    Time Complexity:
+        1) addNum
+            - 최악의 경우 heappush + (heappop + heappush) + (heappop + heapppush) 가 발생할 수 있으므로 O(5 * log n)
+            > O(5 * log n) ~= O(log n)
+        2) findMedian
+            > heap의 루트 값을 가지고 사칙연산만 하므로 O(1)
+
+    Memory: 39.94 MB (Beats 5.85%)
+    Space Complexity: O(n)
+        - max_heap은 최대 n // 2 개 혹은 n // 2 + 1개의 원소를 가지므로 O(n / 2 + 1), upper bound
+        - min_heap은 최대 n // 2개의 원소를 가지므로 O(n / 2)
+        > O(n / 2 + 1) + O(n / 2) ~= O(n) + O(n) ~= O(n)
+    """
+
+    def __init__(self):
+        self.max_heap = []
+        self.min_heap = []
+
+    def addNum(self, num):
+        heappush(self.max_heap, -num)
+        if self.min_heap and (-self.max_heap[0] > self.min_heap[0]):
+            heappush(self.min_heap, -heappop(self.max_heap))
+
+        if len(self.max_heap) > len(self.min_heap) + 1:
+            heappush(self.min_heap, -heappop(self.max_heap))
+        elif len(self.max_heap) < len(self.min_heap):
+            heappush(self.max_heap, -heappop(self.min_heap))
+
+    def findMedian(self):
+        if self.max_heap and self.min_heap:
+            if len(self.max_heap) == len(self.min_heap):
+                return ((-self.max_heap[0]) + self.min_heap[0]) / 2
+            else:
+                return -self.max_heap[0]
+        elif self.min_heap and not self.max_heap:
+            return self.min_heap[0]
+        elif not self.min_heap and self.max_heap:
+            return -self.max_heap[0]
+        else:
+            return 0.0
+
+
+class _LeetCodeTestCases(TestCase):
+
+    def test_1(self):
+        medianFinder = MedianFinder()
+        medianFinder.addNum(-1)
+        self.assertEqual(medianFinder.findMedian(), -1.0)
+        medianFinder.addNum(-2)
+        self.assertEqual(medianFinder.findMedian(), -1.5)
+        medianFinder.addNum(-3)
+        self.assertEqual(medianFinder.findMedian(), -2.0)
+        medianFinder.addNum(-4)
+        self.assertEqual(medianFinder.findMedian(), -2.5)
+        medianFinder.addNum(-5)
+        self.assertEqual(medianFinder.findMedian(), -3.0)
+
+
+if __name__ == '__main__':
+    main()

find-median-from-data-stream/HC-kang.ts

@@ -0,0 +1,164 @@
+/**
+ * https://leetcode.com/problems/find-median-from-data-stream
+ * array with binary search
+ */
+class MedianFinder {
+  // S.C. O(n)
+  private nums: number[] = [];
+
+  // T.C. O(n)
+  addNum(num: number): void {
+    if (this.nums.length === 0) {
+      this.nums.push(num);
+      return;
+    } else {
+      this.putNumWithBinarySearch(num);
+    }
+  }
+
+  private putNumWithBinarySearch(num: number): void {
+    let left = 0;
+    let right = this.nums.length - 1;
+
+    while (left <= right) {
+      const mid = Math.floor((left + right) / 2);
+      if (this.nums[mid] === num) {
+        this.nums.splice(mid, 0, num);
+        return;
+      } else if (this.nums[mid] < num) {
+        left = mid + 1;
+      } else {
+        right = mid - 1;
+      }
+    }
+
+    // T.C. O(n)
+    this.nums.splice(left, 0, num);
+  }
+
+  // T.C. O(1)
+  findMedian(): number {
+    const len = this.nums.length;
+
+    if (len % 2 === 1) {
+      return this.nums[Math.floor(len / 2)];
+    } else {
+      return (this.nums[len / 2] + this.nums[len / 2 - 1]) / 2;
+    }
+  }
+}
+
+/**
+ * heap...
+ * TL;DR
+ */
+class MedianFinder {
+  // S.C. O(n)
+  private smallHalf: MaxHeap = new MaxHeap();
+  private largeHalf: MinHeap = new MinHeap();
+
+  // T.C. O(log n)
+  addNum(num: number): void {
+    this.smallHalf.push(num);
+    this.largeHalf.push(this.smallHalf.pop()!);
+
+    if (this.smallHalf.size() < this.largeHalf.size()) {
+      this.smallHalf.push(this.largeHalf.pop()!);
+    }
+  }
+
+  // T.C. O(1)
+  findMedian(): number {
+    if (this.smallHalf.size() === this.largeHalf.size()) {
+      return (this.smallHalf.peek()! + this.largeHalf.peek()!) / 2;
+    } else {
+      return this.smallHalf.peek()!;
+    }
+  }
+}
+
+class MinHeap {
+  protected heap: number[] = [];
+
+  push(val: number): void {
+    this.heap.push(val);
+    this.heapifyUp();
+  }
+
+  pop(): number | undefined {
+    if (this.heap.length === 0) return undefined;
+    if (this.heap.length === 1) return this.heap.pop();
+
+    const result = this.heap[0];
+    this.heap[0] = this.heap.pop()!;
+    this.heapifyDown();
+    return result;
+  }
+
+  peek(): number | undefined {
+    return this.heap[0];
+  }
+
+  size(): number {
+    return this.heap.length;
+  }
+
+  private heapifyUp(): void {
+    let index = this.heap.length - 1;
+    while (index > 0) {
+      const parentIndex = Math.floor((index - 1) / 2);
+      if (this.heap[parentIndex] <= this.heap[index]) break;
+
+      this.swap(parentIndex, index);
+      index = parentIndex;
+    }
+  }
+
+  private heapifyDown(): void {
+    let index = 0;
+    while (true) {
+      let smallest = index;
+      const leftChild = 2 * index + 1;
+      const rightChild = 2 * index + 2;
+
+      if (
+        leftChild < this.heap.length &&
+        this.heap[leftChild] < this.heap[smallest]
+      ) {
+        smallest = leftChild;
+      }
+
+      if (
+        rightChild < this.heap.length &&
+        this.heap[rightChild] < this.heap[smallest]
+      ) {
+        smallest = rightChild;
+      }
+
+      if (smallest === index) break;
+
+      this.swap(index, smallest);
+      index = smallest;
+    }
+  }
+
+  protected swap(i: number, j: number): void {
+    [this.heap[i], this.heap[j]] = [this.heap[j], this.heap[i]];
+  }
+}
+
+class MaxHeap extends MinHeap {
+  push(val: number): void {
+    super.push(-val);
+  }
+
+  pop(): number | undefined {
+    const val = super.pop();
+    return val === undefined ? undefined : -val;
+  }
+
+  peek(): number | undefined {
+    const val = super.peek();
+    return val === undefined ? undefined : -val;
+  }
+}

find-median-from-data-stream/flynn.go

@@ -0,0 +1,67 @@
+/*
+풀이
+- 이진탐색을 이용합니다
+Big O
+- N: 현재 MedianFinder.nums의 크기
+- AddNum
+  - Time complexity: O(N)
+    - bisect -> O(logN)
+	- slices.Insert -> O(N)
+  - Space complexity: O(1)
+- FindMedian
+  - Time complexity: O(1)
+  - Space complexity: O(1)
+*/
+
+import "slices"
+
+type MedianFinder struct {
+	nums []int
+}
+
+func Constructor() MedianFinder {
+	mf := MedianFinder{}
+	mf.nums = make([]int, 0)
+	return mf
+}
+
+func (this *MedianFinder) AddNum(num int) {
+	n := len(this.nums)
+	if n == 0 {
+		this.nums = append(this.nums, num)
+	} else {
+		idx := bisectLeft(this.nums, num)
+		this.nums = slices.Insert(this.nums, idx, num)
+	}
+}
+
+func (this *MedianFinder) FindMedian() float64 {
+	n := len(this.nums)
+	if n%2 == 0 {
+		return (float64(this.nums[n/2-1]) + float64(this.nums[n/2])) / 2
+	} else {
+		return float64(this.nums[n/2])
+	}
+}
+
+// ----- Helper -----
+func bisectLeft(arr []int, x int) int {
+	lo := 0
+	hi := len(arr)
+	for lo < hi {
+		mid := lo + (hi-lo)/2
+		if arr[mid] < x {
+			lo = mid + 1
+		} else {
+			hi = mid
+		}
+	}
+	return lo
+}
+
+/**
+ * Your MedianFinder object will be instantiated and called as such:
+ * obj := Constructor();
+ * obj.AddNum(num);
+ * param_2 := obj.FindMedian();
+ */

house-robber/EGON.py

@@ -0,0 +1,42 @@
+from typing import List
+from unittest import TestCase, main
+
+
+class Solution:
+    def rob(self, nums: List[int]) -> int:
+        return self.solve_dp(nums)
+
+    """
+    Runtime: 0 ms (Beats 100.00%)
+    Time Complexity: O(n)
+        - nums 배열을 조회하며 dp 배열을 갱신하므로 O(n)
+            - 2항에 대한 max 연산을 사용하므로 * O(2)
+        > O(2 * n) ~= O(n)
+
+    Memory: 16.62 MB (Beats 24.05%)
+    Space Complexity: O(n)
+        > 길이가 n인 dp 배열을 사용하므로 O(n)
+    """
+
+    def solve_dp(self, nums: List[int]) -> int:
+        if len(nums) <= 2:
+            return max(nums)
+
+        dp = [0] * len(nums)
+        dp[0] = nums[0]
+        dp[1] = max(nums[0], nums[1])
+        for i in range(2, len(nums)):
+            dp[i] = max(dp[i - 1], dp[i - 2] + nums[i])
+
+        return dp[-1]
+
+
+class _LeetCodeTestCases(TestCase):
+    def test_1(self):
+        nums = [2,1,1,2]
+        output = 4
+        self.assertEqual(Solution().rob(nums), output)
+
+
+if __name__ == '__main__':
+    main()

house-robber/HC-kang.ts

@@ -0,0 +1,15 @@
+/**
+ * https://leetcode.com/problems/house-robber
+ * T.C. O(n)
+ * S.C. O(1)
+ */
+function rob(nums: number[]): number {
+  let prev = 0;
+  let curr = 0;
+  for (let i = 0; i < nums.length; i++) {
+    const temp = curr;
+    curr = Math.max(prev + nums[i], curr);
+    prev = temp;
+  }
+  return curr;
+}

house-robber/TonyKim9401.java

@@ -0,0 +1,21 @@
+// TC: O(n)
+// always need to check every case
+// SC: O(n)
+// the length of the result int list is same with the length of the given nums int list
+class Solution {
+    public int rob(int[] nums) {
+        int[] result = new int[nums.length];
+
+        if (nums.length < 2) return nums[0];
+        if (nums.length < 3) return Math.max(nums[0], nums[1]);
+
+        result[0] = nums[0];
+        result[1] = Math.max(nums[0], nums[1]);
+
+        for (int i = 2; i < nums.length; i++) {
+            result[i] = Math.max(result[i - 1], result[i - 2] + nums[i]);
+        }
+
+        return result[nums.length-1];
+    }
+}