| import numpy as np | |
| from collections import Counter | |
| def main(): | |
| def most_common_2d(data): | |
| return [Counter(col).most_common()[0][0] for col in zip(*data)] | |
| def least_common_2d(data): | |
| return [Counter(col).most_common()[-1][0] for col in zip(*data)] | |
| def Counter_2d(data): | |
| return [Counter(col) for col in zip(*data)] | |
| def search(data, to_search="1"): | |
| if to_search == "1": | |
| most_common_index = 0 | |
| else: | |
| most_common_index = -1 | |
| previous_keep = data | |
| for i in range(len(data[0])): | |
| counts = Counter_2d(previous_keep) | |
| keep = [] | |
| for row in previous_keep: | |
| if (row[i] == counts[i].most_common()[most_common_index][0] and | |
| counts[i]["0"] != counts[i]["1"]): | |
| keep.append(row) | |
| elif counts[i]["0"] == counts[i]["1"]: | |
| if row[i] == to_search: | |
| keep.append(row) | |
| previous_keep = keep | |
| return int("".join(previous_keep[0]), 2) | |
| with open("/home/yassinealouini/Documents/code/advent_of_code/aoc/year_2021/data/3.txt") as f: | |
| tmp = f.read().rstrip().split("\n") | |
| data = [] | |
| for row in tmp: | |
| data.append([e for e in row]) | |
| gamma = int("".join(most_common_2d(data)), 2) | |
| epsilon = int("".join(least_common_2d(data)), 2) | |
| print("Solution to part I: ", gamma * epsilon) | |
| oxygen = search(data, "1") | |
| co2 = search(data, "0") | |
| print("Solution to part II: ", oxygen * co2) | |
| def streamlit_torch_3(data_input): | |
| """ Day 3 of AoC using PyTorch | |
| """ | |
| import torch | |
| import streamlit as st | |
| st.write("Solution to part I: ", 0) | |
| if __name__ == "__main__": | |
| main() |