feature: minimum cost to make array equal

binary_search/MinimumCostToMakeArrayEqual.py

@@ -0,0 +1,24 @@
+from typing import List
+
+
+# O(n * log(a)) time || O(1) space, a - range in nums
+def min_cost(self, nums: List[int], cost: List[int]) -> int:
+    if min(nums) == max(nums):
+        return 0
+
+    def f(x):
+        return sum(abs(a - x) * c for a, c in zip(nums, cost))
+
+    low, high = min(nums), max(nums)
+    res = f(low)
+    while low < high:
+        mid = low + (high - low) // 2
+        y1, y2 = f(mid), f(mid + 1)
+        res = min(y1, y2)
+
+        if y1 < y2:
+            high = mid
+        else:
+            low = mid + 1
+
+    return res

binary_search/test/test_min_cost.py

@@ -0,0 +1,15 @@
+import unittest
+
+from binary_search.MinimumCostToMakeArrayEqual import min_cost
+
+
+class MyTestCase(unittest.TestCase):
+    def test_min_cost(self):
+        self.assertEqual(8, min_cost(self, nums=[1, 3, 5, 2], cost=[2, 3, 1, 14]))
+
+    def test_min_cost_1(self):
+        self.assertEqual(0, min_cost(self, nums=[2, 2, 2, 2, 2], cost=[4, 2, 8, 1, 3]))
+
+
+if __name__ == '__main__':
+    unittest.main()