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Author: Partho Biswas

algoexpert.io/python/River_Sizes.py

@@ -1,6 +1,6 @@
 # https://www.algoexpert.io/questions/River%20Sizes
 
-
+# Approach 1: Using BFS
 # O(wh) time | O(wh) space
 def river_size(matrix):
     size = []  # It would contain all of our river sizes
@@ -47,3 +47,68 @@ def get_unvisited_neighbours(i, j, matrix, visited):
 
 
 
+# Approach 2: Using Disjoin Sets
+class DJS(object):
+    def __init__(self, numOfElements):
+        self.n = numOfElements
+        self.parents = [0 for _ in range(numOfElements)]
+        self.rank = [0 for _ in range(numOfElements)]
+        self.makeSet()
+
+    def makeSet(self):
+        for i in range(self.n):
+            self.parents[i] = i
+
+    def union(self, x, y):
+        parentX = self.find(x)
+        parentY = self.find(y)
+        if parentX == parentY:
+            return
+        if self.rank[parentX] > self.rank[parentY]:
+            self.parents[parentY] = parentX
+        elif self.rank[parentX] < self.rank[parentY]:
+            self.parents[parentX] = parentY
+        else:
+            self.parents[parentX] = parentY
+            self.rank[parentY] += 1
+
+    def find(self, x):
+        parentX = self.parents[x]
+        if x != parentX:
+            parentX = self.find(parentX)
+        return parentX
+
+
+from collections import defaultdict
+def riverSizes(matrix):
+    if not matrix:
+        return []
+    rowCount, colCount = len(matrix), len(matrix[0])
+    djs = DJS(rowCount * colCount)
+    for i in range(rowCount):
+        for j in range(colCount):
+            val = matrix[i][j]
+            if val == 0:
+                continue
+
+    if i + 1 < rowCount and matrix[i + 1][j] == 1:
+        djs.union(i * (colCount) + j, (i + 1) * (colCount) + j)
+
+    if i - 1 >= 0 and matrix[i - 1][j] == 1:
+        djs.union(i * (colCount) + j, (i - 1) * (colCount) + j)
+
+    if j + 1 < colCount and matrix[i][j + 1] == 1:
+        djs.union(i * (colCount) + j, (i) * (colCount) + j + 1)
+
+    if j - 1 >= 0 and matrix[i][j - 1] == 1:
+        djs.union(i * (colCount) + j, (i) * (colCount) + j - 1)
+
+    ilands = defaultdict(int)
+    for i in range(rowCount):
+        for j in range(colCount):
+            if matrix[i][j] == 1:
+                val = i * colCount + j
+                parent = djs.find(val)
+                ilands[parent] += 1
+
+    return ilands.values()