Added tasks 3101, 3102

Author: javadev

src/main/kotlin/g3101_3200/s3101_count_alternating_subarrays/Solution.kt

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+package g3101_3200.s3101_count_alternating_subarrays
+
+// #Medium #Array #Math #2024_04_23_Time_499_ms_(97.78%)_Space_70.3_MB_(80.00%)
+
+class Solution {
+    fun countAlternatingSubarrays(nums: IntArray): Long {
+        var count: Long = 0
+        var length: Long
+        var start = 0
+        var end = 1
+        while (end < nums.size) {
+            if (nums[end] != nums[end - 1]) {
+                end++
+            } else {
+                length = end - start.toLong()
+                count += (length * (length + 1)) / 2
+                start = end
+                end++
+            }
+        }
+        length = end - start.toLong()
+        count += (length * (length + 1)) / 2
+        return count
+    }
+}

src/main/kotlin/g3101_3200/s3101_count_alternating_subarrays/readme.md

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+3101\. Count Alternating Subarrays
+
+Medium
+
+You are given a binary array `nums`.
+
+We call a subarray **alternating** if **no** two **adjacent** elements in the subarray have the **same** value.
+
+Return _the number of alternating subarrays in_ `nums`.
+
+**Example 1:**
+
+**Input:** nums = [0,1,1,1]
+
+**Output:** 5
+
+**Explanation:**
+
+The following subarrays are alternating: `[0]`, `[1]`, `[1]`, `[1]`, and `[0,1]`.
+
+**Example 2:**
+
+**Input:** nums = [1,0,1,0]
+
+**Output:** 10
+
+**Explanation:**
+
+Every subarray of the array is alternating. There are 10 possible subarrays that we can choose.
+
+**Constraints:**
+
+*   <code>1 <= nums.length <= 10<sup>5</sup></code>
+*   `nums[i]` is either `0` or `1`.

src/main/kotlin/g3101_3200/s3102_minimize_manhattan_distances/Solution.kt

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+package g3101_3200.s3102_minimize_manhattan_distances
+
+// #Hard #Array #Math #2024_04_23_Time_701_ms_(95.83%)_Space_100.4_MB_(75.00%)
+
+import kotlin.math.abs
+import kotlin.math.max
+import kotlin.math.min
+
+class Solution {
+    private fun manhattan(points: Array<IntArray>, i: Int, j: Int): Int {
+        return (
+            abs(points[i][0] - points[j][0]) + abs(
+                points[i][1] - points[j][1]
+            )
+            )
+    }
+
+    private fun maxManhattanDistance(points: Array<IntArray>, remove: Int): IntArray {
+        val n = points.size
+        var maxSum = Int.MIN_VALUE
+        var minSum = Int.MAX_VALUE
+        var maxDiff = Int.MIN_VALUE
+        var minDiff = Int.MAX_VALUE
+        var maxSumIndex = -1
+        var minSumIndex = -1
+        var maxDiffIndex = -1
+        var minDiffIndex = -1
+        for (i in 0 until n) {
+            if (i != remove) {
+                val sum = points[i][0] + points[i][1]
+                val diff = points[i][0] - points[i][1]
+                if (sum > maxSum) {
+                    maxSumIndex = i
+                    maxSum = sum
+                }
+                if (sum < minSum) {
+                    minSumIndex = i
+                    minSum = sum
+                }
+                if (diff > maxDiff) {
+                    maxDiffIndex = i
+                    maxDiff = diff
+                }
+                if (diff < minDiff) {
+                    minDiffIndex = i
+                    minDiff = diff
+                }
+            }
+        }
+        return if (max(maxSum - minSum, maxDiff - minDiff) == maxSum - minSum
+        ) intArrayOf(maxSumIndex, minSumIndex)
+        else intArrayOf(maxDiffIndex, minDiffIndex)
+    }
+
+    fun minimumDistance(points: Array<IntArray>): Int {
+        val m = maxManhattanDistance(points, -1)
+        val m1 = maxManhattanDistance(points, m[0])
+        val m2 = maxManhattanDistance(points, m[1])
+        return min(
+            manhattan(points, m1[0], m1[1]),
+            manhattan(points, m2[0], m2[1])
+        )
+    }
+}

src/main/kotlin/g3101_3200/s3102_minimize_manhattan_distances/readme.md

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+3102\. Minimize Manhattan Distances
+
+Hard
+
+You are given a array `points` representing integer coordinates of some points on a 2D plane, where <code>points[i] = [x<sub>i</sub>, y<sub>i</sub>]</code>.
+
+The distance between two points is defined as their Manhattan distance.
+
+Return _the **minimum** possible value for **maximum** distance between any two points by removing exactly one point_.
+
+**Example 1:**
+
+**Input:** points = [[3,10],[5,15],[10,2],[4,4]]
+
+**Output:** 12
+
+**Explanation:**
+
+The maximum distance after removing each point is the following:
+
+*   After removing the 0<sup>th</sup> point the maximum distance is between points (5, 15) and (10, 2), which is `|5 - 10| + |15 - 2| = 18`.
+*   After removing the 1<sup>st</sup> point the maximum distance is between points (3, 10) and (10, 2), which is `|3 - 10| + |10 - 2| = 15`.
+*   After removing the 2<sup>nd</sup> point the maximum distance is between points (5, 15) and (4, 4), which is `|5 - 4| + |15 - 4| = 12`.
+*   After removing the 3<sup>rd</sup> point the maximum distance is between points (5, 15) and (10, 2), which is `|5 - 10| + |15 - 2| = 18`.
+
+12 is the minimum possible maximum distance between any two points after removing exactly one point.
+
+**Example 2:**
+
+**Input:** points = [[1,1],[1,1],[1,1]]
+
+**Output:** 0
+
+**Explanation:**
+
+Removing any of the points results in the maximum distance between any two points of 0.
+
+**Constraints:**
+
+*   <code>3 <= points.length <= 10<sup>5</sup></code>
+*   `points[i].length == 2`
+*   <code>1 <= points[i][0], points[i][1] <= 10<sup>8</sup></code>

src/test/kotlin/g3101_3200/s3101_count_alternating_subarrays/SolutionTest.kt

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+package g3101_3200.s3101_count_alternating_subarrays
+
+import org.hamcrest.CoreMatchers.equalTo
+import org.hamcrest.MatcherAssert.assertThat
+import org.junit.jupiter.api.Test
+
+internal class SolutionTest {
+    @Test
+    fun countAlternatingSubarrays() {
+        assertThat(Solution().countAlternatingSubarrays(intArrayOf(0, 1, 1, 1)), equalTo(5L))
+    }
+
+    @Test
+    fun countAlternatingSubarrays2() {
+        assertThat(
+            Solution().countAlternatingSubarrays(intArrayOf(1, 0, 1, 0)),
+            equalTo(10L)
+        )
+    }
+}

src/test/kotlin/g3101_3200/s3102_minimize_manhattan_distances/SolutionTest.kt

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+package g3101_3200.s3102_minimize_manhattan_distances
+
+import com_github_leetcode.CommonUtils
+import org.hamcrest.CoreMatchers.equalTo
+import org.hamcrest.MatcherAssert.assertThat
+import org.junit.jupiter.api.Test
+
+internal class SolutionTest {
+    @Test
+    fun minimumDistance() {
+        assertThat(
+            Solution()
+                .minimumDistance(
+                    CommonUtils.convertLeetCodeIrregularLengths2DArrayInputIntoJavaArray(
+                        "[3,10],[5,15],[10,2],[4,4]"
+                    )
+                ),
+            equalTo(12)
+        )
+    }
+
+    @Test
+    fun minimumDistance2() {
+        assertThat(
+            Solution()
+                .minimumDistance(
+                    CommonUtils.convertLeetCodeIrregularLengths2DArrayInputIntoJavaArray(
+                        "[1,1],[1,1],[1,1]"
+                    )
+                ),
+            equalTo(0)
+        )
+    }
+}