Initial commit: AoC solutions 2023-2025

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2023/11.py

@@ -0,0 +1,51 @@
+import numpy as np
+
+def main():
+    with open("11-input.txt", "r") as file:
+        arr = []
+        for line in file.readlines():
+            char_array = []
+            for char in line.strip():
+                char_array.append(char)
+            arr.append(char_array)
+        matrix = np.array(arr)
+        dot_columns = np.all(matrix == ".", axis=0)
+        dot_rows = np.all(matrix == ".", axis=1)
+        coordinates = np.array(np.nonzero(matrix == '#'))
+        distance = []
+        for i in range(0, coordinates.shape[1]):
+            row = coordinates[0, i]
+            col = coordinates[1, i]
+            for ii in range(i + 1, coordinates.shape[1]):
+                next_row = coordinates[0, ii]
+                next_col = coordinates[1, ii]
+                empty_rows_passed = get_rows_passed(dot_rows[min(row, next_row):max(row,next_row)])
+                empty_cols_passed = get_cols_passed(dot_columns[min(col, next_col):max(next_col, col)])
+                d = (abs(next_row  - row) + (abs(next_col - col))) + (empty_cols_passed * 999_999) + (empty_rows_passed * 999_999)
+                item = i, ii, d
+                if distance.count(item) == 0:
+                    distance.append(item)
+        print(distance)
+        print(len(distance))
+        s = 0
+        for d in distance:
+           s += d[2] 
+
+        print(s)
+
+def get_rows_passed(rows: []):
+    passed = 0
+    for r in rows:
+        if r:
+            passed += 1
+    return passed
+
+def get_cols_passed(rows: []):
+    passed = 0
+    for r in rows:
+        if r:
+            passed += 1
+    return passed
+
+if __name__ == "__main__":
+    main()