Initial commit: AoC solutions 2023-2025

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

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

2024/8.py

@@ -0,0 +1,130 @@
+import numpy as np
+from base import AoCBase
+from typing import List
+
+
+class Day8(AoCBase):
+    def __init__(self):
+        super().__init__(8)  # Pass the day number to base class
+
+    def parse_input(self) -> List[str]:
+        """Override with specific parsing for this day."""
+        return self.raw_data.strip().split("\n")
+
+    def part1(self) -> int:
+        result = 0
+        np.set_printoptions(threshold=np.inf)
+        data = np.array([list(row) for row in self.data])
+        u = np.unique_values(data)
+        dict = {}
+        antennas = {}
+        for val in u:
+            if val == ".":
+                continue
+            indices = np.argwhere(data == val)
+            for idx in indices:
+                row, col = idx
+                antennas[(row, col)] = val
+                for i in range(0, len(indices)):
+                    idx_2 = indices[i]
+                    row, col = idx - idx_2  # -1 ,3
+                    row_2, col_2 = idx_2 - idx  # 1, -3
+                    if row == 0 and col == 0:
+                        continue
+                    a_r, a_c = idx + np.array([row, col])
+                    a2_r, a2_c = idx_2 + np.array([row_2, col_2])
+                    dict[(a_r, a_c)] = (a_r, a_c)
+                    dict[(a2_r, a2_c)] = (a2_r, a2_c)
+
+        shape = data.shape
+
+        for k in dict:
+            if k[0] >= 0 and k[1] >= 0 and k[0] < shape[0] and k[1] < shape[1]:
+                data[k[0], k[1]] = "#"
+                result += 1
+
+        s = np.array2string(data, 250)
+        v = replace_chars(s)
+        with open('output.txt', 'w') as f:
+            f.write(v)
+ 
+        return result
+
+    def part2(self) -> int:
+        result = 0
+        np.set_printoptions(threshold=np.inf)
+        data = np.array([list(row) for row in self.data])
+        u = np.unique_values(data)
+        dict = {}
+        antennas = {}
+        shape = data.shape
+        for val in u:
+            if val == ".":
+                continue
+            indices = np.argwhere(data == val)
+            for idx in indices:
+                row, col = idx
+                antennas[(row, col)] = val
+                for i in range(0, len(indices)):
+                    idx_2 = indices[i]
+                    row, col = idx - idx_2  # -1 ,3
+                    row_2, col_2 = idx_2 - idx  # 1, -3
+                    if row == 0 and col == 0:
+                        continue
+
+                    a_r, a_c = (0, 0)
+                    a2_r, a2_c = (0, 0)
+                    curr_idx = idx
+                    curr_idx_2 = idx_2
+                    while True:
+                        a_r, a_c = curr_idx + np.array([row, col])
+                        a2_r, a2_c = curr_idx_2 + np.array([row_2, col_2])
+                        dict[(a_r, a_c)] = (a_r, a_c)
+                        dict[(a2_r, a2_c)] = (a2_r, a2_c)
+                        print(a_r, a_c)
+                        print(a2_r, a2_c)
+                        curr_idx = np.array([a_r, a_c])
+                        curr_idx_2 = np.array([a2_r, a2_c])
+
+                        idx_ob = is_index_in_bounds(data, a_r, a_c)
+                        idx_ob_2 = is_index_in_bounds(data, a2_r, a2_c)
+                        if (not idx_ob) and (not (idx_ob_2)):
+                            break
+                        
+        for k in dict:
+            if k in antennas:
+                continue
+            if k[0] >= 0 and k[1] >= 0 and k[0] < shape[0] and k[1] < shape[1]:
+                data[k[0], k[1]] = "#"
+                result += 1
+
+        result += len(antennas)
+        s = np.array2string(data, 250)
+        v = replace_chars(s)
+        with open('output.txt', 'w') as f:
+            f.write(v)
+ 
+        return result
+    
+# Function to check if an index is within bounds
+def is_index_in_bounds(array, row, col):
+    num_rows, num_cols = array.shape
+    return 0 <= row < num_rows and 0 <= col < num_cols
+
+def replace_chars(input_string):
+    # Replace single quote
+    updated_string = input_string.replace("'", "")
+    # Replace open square bracket
+    updated_string = updated_string.replace("[", "")
+    # Replace close square bracket
+    updated_string = updated_string.replace("]", "")
+     # Remove spaces
+    updated_string = updated_string.replace(" ", "")
+    
+
+    return updated_string
+
+
+if __name__ == "__main__":
+    solution = Day8()
+    solution.solve()