More optimizations

2024/src/aoc/days/day22.py

@@ -3,7 +3,7 @@
 import numpy
 from numpy.lib.stride_tricks import sliding_window_view
 
-from . import SeparateRunner
+from . import CombinedRunner
 
 
 def advance(secrets: numpy.array) -> numpy.array:
@@ -15,18 +15,9 @@ def advance(secrets: numpy.array) -> numpy.array:
     return new_secrets
 
 
-class DayRunner(SeparateRunner):
+class DayRunner(CombinedRunner):
     @classmethod
-    def part1(cls, input: str) -> int:
-        secrets = numpy.fromstring(input, dtype=int, sep="\n")
-
-        for _ in range(2000):
-            secrets = advance(secrets)
-
-        return secrets.sum()
-
-    @classmethod
-    def part2(cls, input: str) -> int:
+    def run_both(cls, input: str) -> tuple[int, int]:
         secrets = numpy.fromstring(input, dtype=int, sep="\n")
 
         progression = [secrets]
@@ -37,15 +28,14 @@ def part2(cls, input: str) -> int:
 
         field = numpy.stack(progression, axis=-1) % 10
         delta = field[:, 1:] - field[:, :-1]
+        windows = sliding_window_view(delta, 4, axis=1)
 
         per_signal = defaultdict(int)
 
-        for row_scores, row_deltas in zip(field, delta):
-            unique, positions = numpy.unique(
-                sliding_window_view(row_deltas, 4), return_index=True, axis=0
-            )
+        for row_scores, row_deltas in zip(field, windows):
+            unique, positions = numpy.unique(row_deltas, return_index=True, axis=0)
 
-            for key, index in zip(unique, positions):
-                per_signal[tuple(key)] += row_scores[index + 4]
+            for key, bananas in zip(unique, row_scores[positions + 4]):
+                per_signal[tuple(key)] += bananas
 
-        return max(per_signal.values())
+        return secrets.sum(), max(per_signal.values())