daily

Author: TurtleSmoke

problems/problem_1052/solution_1.py

@@ -0,0 +1,42 @@
+from typing import List
+
+import pytest
+
+
+class Solution:
+    def maxSatisfied(self, customers: List[int], grumpy: List[int], minutes: int) -> int:
+        tmp = sum(grumpy[i] * customers[i] for i in range(minutes))
+        non_satisfied = tmp
+        satisfied = 0
+
+        for i in range(len(customers) - minutes):
+            satisfied += customers[i] * (grumpy[i] ^ 1)
+            tmp += -grumpy[i] * customers[i] + grumpy[i + minutes] * customers[i + minutes]
+            non_satisfied = max(non_satisfied, tmp)
+
+        for i in range(len(customers) - minutes, len(customers)):
+            satisfied += customers[i] * (grumpy[i] ^ 1)
+
+        return satisfied + non_satisfied
+
+
+tests = [
+    (
+        ([1, 0, 1, 2, 1, 1, 7, 5], [0, 1, 0, 1, 0, 1, 0, 1], 3),
+        16,
+    ),
+    (
+        ([1], [0], 1),
+        1,
+    ),
+]
+
+
+@pytest.mark.timeout(2)
+@pytest.mark.parametrize(
+    "inputs, expected",
+    tests,
+)
+def test_validator(inputs, expected):
+    output = Solution().maxSatisfied(*inputs)
+    assert output == expected

problems/problem_1052/solution_2.py

@@ -0,0 +1,29 @@
+from typing import List
+import numpy as np
+import pytest
+
+
+class Solution:
+    def maxSatisfied(self, c: List[int], g: List[int], m: int) -> int:
+        c = np.array(c)
+        g = np.array(g)
+        return int((c * (g ^ 1)).sum() + np.convolve(c * g, np.ones(m), mode="valid").max())
+
+
+tests = [
+    (
+        ([1, 0, 1, 2, 1, 1, 7, 5], [0, 1, 0, 1, 0, 1, 0, 1], 3),
+        16,
+    ),
+    (
+        ([1], [0], 1),
+        1,
+    ),
+]
+
+
+@pytest.mark.timeout(2)
+@pytest.mark.parametrize("inputs, expected", tests)
+def test_validator(inputs, expected):
+    output = Solution().maxSatisfied(*inputs)
+    assert output == expected