file prep for 2024 AOC
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23
2024/justfile
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2024/justfile
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#!/usr/bin/env -S just --justfile
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DAY := `date +%d`
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setup:
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python3 -m venv venv
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new:
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cp python/_sample.py python/day{{ DAY }}.py
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touch full/day{{ DAY }}.txt
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touch samples/day{{ DAY }}.txt
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full:
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/usr/bin/env python3 python/day{{ DAY }}.py
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sample:
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/usr/bin/env python3 python/day{{ DAY }}.py --sample
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wsample:
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watch /usr/bin/env python3 python/day{{ DAY }}.py --sample
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wfull:
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watch /usr/bin/env python3 python/day{{ DAY }}.py
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2024/python/_sample.py
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2024/python/_sample.py
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import matrix
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import shared
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import itertools
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import functools
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# @shared.profile
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def part1(rows):
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pass
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# @shared.profile
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def part2(rows):
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pass
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def main():
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rows = [row for row in shared.load_rows(15)]
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with shared.elapsed_timer() as elapsed:
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part1(rows)
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print("🕒", elapsed())
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rows = [row for row in shared.load_rows(1, True)]
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with shared.elapsed_timer() as elapsed:
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part2(rows)
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print("🕒", elapsed())
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if __name__ == "__main__":
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main()
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2024/python/anim.py
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2024/python/anim.py
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from matrix import get_size, pmx
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import imageio
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import matplotlib.pyplot as plt
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import numpy as np
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class Animate:
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def __init__(self, mx, day="CHANGEME"):
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self.mx = mx
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self.day = day
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_size = get_size(mx)
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self.height = _size[0]
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self.width = _size[1]
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self.f_count = -1
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def add_frame(self, frame):
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self.f_count += 1
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self.write_frame(frame)
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def write_frame(self, frame):
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current = np.zeros_like(self.mx)
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for y, row in enumerate(frame):
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for x, col in enumerate(row):
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current[y][x] = frame[y][x]
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fig, ax = plt.subplots()
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ax.imshow(current, cmap=plt.cm.gray)
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ax.axis("off")
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_figpath = f"gif-{self.day}/{self.f_count:05}.png"
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plt.savefig(_figpath)
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plt.close()
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def animate(self, frameskip=1):
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with imageio.get_writer(
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f"gif-{self.day}/day{self.day}.gif", mode="I"
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) as writer:
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names = [
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f"gif-{self.day}/{x:05}.png" for x in range(0, self.f_count, frameskip)
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]
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print(names)
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for filename in names:
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try:
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image = imageio.imread(filename)
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writer.append_data(image)
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except FileNotFoundError:
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pass
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472
2024/python/matrix.py
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472
2024/python/matrix.py
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from copy import deepcopy
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from collections import defaultdict
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import math
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from typing import List, Dict, Tuple
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split_word_to_chr_list = lambda y: [w for w in y]
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split_word_to_int_list = lambda y: [int(w) for w in y]
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split_line_to_int_list = lambda y: [int(w) for w in y.split(" ") if w]
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def split_x_out(l):
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return [x for _, x in l]
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def split_y_out(l):
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return [y for y, _ in l]
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class colors:
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# HEADER = '\033[95m'
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BLUE = "\033[94m"
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GREEN = "\033[92m"
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YELLOW = "\033[93m"
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RED = "\033[91m"
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ENDC = "\033[0m"
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BLINK = "\033[5m"
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def apply_to_all(mx, func):
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for row_num, row in enumerate(mx):
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for col_num, val in enumerate(row):
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mx[row_num][col_num] = func(val)
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def rotate(m, right=True): # -90
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"""
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Takes a matrix, and rotates all of the values 90 degrees to the left
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"""
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x = list(zip(*m[::-1]))
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if right:
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return x
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return [list(reversed(y)) for y in x]
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def load_matrix_file(name, func=None):
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"""
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Open a file and split all space separated word lists to integers as a matrix
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"""
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with open(name, "r") as f:
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my_file = []
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for line in f:
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my_file.append(line.rstrip())
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if func:
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return [func(x) for x in my_file]
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return [split_word_to_int_list(x) for x in my_file]
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def number_starting_at(mx, x, y):
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current = ""
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try:
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d = mx[y][x]
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except IndexError:
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return None
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if not d.isdigit():
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return None
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current += d
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next = number_starting_at(mx, x + 1, y)
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if next is None:
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return current
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return current + next
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def find_in_matrix(mx, what, one=True):
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coords = []
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for row_num, row in enumerate(mx):
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for col_num, val in enumerate(row):
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if val == what:
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coord = (row_num, col_num)
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if one is True:
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return coord
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else:
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coords.append(coord)
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return coords
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def get_neighbors(matrix, x, y, _dict=False):
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neighbors = []
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# left
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try:
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if x - 1 >= 0:
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if _dict:
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neighbors.append({"x": x - 1, "y": y, "value": matrix[y][x - 1]})
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else:
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neighbors.append([(x - 1, y), matrix[y][x - 1]])
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except IndexError:
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pass
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# right
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try:
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if _dict:
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neighbors.append({"x": x + 1, "y": y, "value": matrix[y][x + 1]})
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else:
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neighbors.append([(x + 1, y), matrix[y][x + 1]])
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except IndexError:
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pass
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# up
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try:
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if y - 1 >= 0:
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if _dict:
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neighbors.append({"x": x, "y": y - 1, "value": matrix[y - 1][x]})
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else:
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neighbors.append([(x, y - 1), matrix[y - 1][x]])
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except IndexError:
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pass
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# down
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try:
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if _dict:
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neighbors.append({"x": x, "y": y + 1, "value": matrix[y + 1][x]})
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else:
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neighbors.append([(x, y + 1), matrix[y + 1][x]])
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except IndexError:
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pass
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return neighbors
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def valid_neighbors(matrix, x, y, criteria=None):
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if criteria is None:
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raise Exception("Please pass in a lambda for criteria")
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cur = matrix[y][x]
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neighbors = get_neighbors(matrix, x, y, _dict=True)
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valid = []
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for neighbor in neighbors:
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if criteria(cur, neighbor["value"]):
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valid.append(neighbor)
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return valid
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def sum_matrix(mtx):
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total = 0
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for row in mtx:
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total += sum(row)
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return total
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M_UL, M_U, M_UR = (-1, -1), (0, -1), (1, -1)
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M_L, M_R = (-1, 0), (1, 0)
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M_DL, M_D, M_DR = (-1, 1), (0, 1), (1, 1)
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M_NW, M_N, M_NE = (-1, -1), (0, -1), (1, -1)
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M_W, M_E = (-1, 0), (1, 0)
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M_SW, M_S, M_SE = (-1, 1), (0, 1), (1, 1)
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CARDINALS = {
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M_NW: "NW",
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M_N: "N",
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M_NE: "NE",
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M_W: "W",
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M_E: "E",
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M_SW: "SW",
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M_S: "S",
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M_SE: "SE",
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}
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def get_neighbor_coords(matrix, c, r, diagonals=True):
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height = len(matrix)
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width = len(matrix[0])
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if diagonals:
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coords = (M_UL, M_U, M_UR, M_L, M_R, M_DL, M_D, M_DR)
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else:
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coords = (M_U, M_L, M_R, M_D)
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neighbors = []
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for _c, _r in coords:
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try:
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value = matrix[r + _r][c + _c] # Try to get a value error
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if r + _r >= 0 and c + _c >= 0:
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neighbors.append(
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[{"c": c + _c, "r": r + _r}, value]
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) # woo, no error, this coord is valid
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except IndexError:
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pass # okay we out of bounds boizzzz
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return neighbors
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def get_neighbors_cardinal(matrix, c, r, diagonals=True):
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height = len(matrix)
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width = len(matrix[0])
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coords = [M_N, M_W, M_E, M_S]
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if diagonals:
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coords.extend([M_NW, M_NE, M_SW, M_SE])
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neighbors = {}
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for coord in coords:
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_c, _r = coord
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try:
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value = matrix[r + _r][c + _c] # Try to get a value error
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if r + _r >= 0 and c + _c >= 0:
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neighbors[CARDINALS[coord]] = {"c": c + _c, "r": r + _r, "value":value} # woo, no error, this coord is valid
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except IndexError:
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pass # okay we out of bounds boizzzz
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return neighbors
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def line_of_sight_coords(
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matrix, row, col, distance=None
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) -> Dict[str, List[Tuple[int, int]]]:
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"""
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Takes a matrix, a row, and a column
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calculates the coordinates to the edge for all four cardinal directions
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returns a dict with a list of tuple coordes TRAVELING AWAY from the
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requested coordinate
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"""
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height, width = get_size(matrix)
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col_ids = list(range(0, height))
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row_ids = list(range(0, width))
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if distance:
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up_ids, down_ids = (
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list(reversed(col_ids[:col])),
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col_ids[col + 1 : col + distance + 1],
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)
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left_ids, right_ids = (
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list(reversed(row_ids[:row])),
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row_ids[row + 1 : row + distance + 1],
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)
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else:
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up_ids, down_ids = list(reversed(col_ids[:col])), col_ids[col + 1 :]
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left_ids, right_ids = list(reversed(row_ids[:row])), row_ids[row + 1 :]
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left = [(r, col) for r in left_ids]
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right = [(r, col) for r in right_ids]
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up = [(row, c) for c in up_ids]
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down = [(row, c) for c in down_ids]
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return {
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"U": up,
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"L": left,
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"D": down,
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"R": right,
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}
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def line_of_sight(mx, row, col, distance=None):
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"""
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renders a line of sight coord calculation, into the values
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"""
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coords = line_of_sight_coords(mx, row, col, distance)
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los = defaultdict(list)
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for k, ids in coords.items():
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for _row, _col in ids:
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los[k].append(mx[_row][_col])
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return los
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def coords_between_points(point1, point2):
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y1, x1 = point1
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y2, x2 = point2
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coords = []
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x = 0
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y = 0
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if x2 < x1:
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y = point1[0]
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for _x in range(x2, x1 + 1):
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coords.append((y, _x))
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elif x1 < x2:
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y = point1[0]
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for _x in range(x1, x2 + 1):
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coords.append((y, _x))
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elif y2 < y1:
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x = point1[1]
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for _y in range(y2, y1 + 1):
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coords.append((_y, x))
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elif y1 < y2:
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x = point1[1]
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for _y in range(y1, y2 + 1):
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coords.append((_y, x))
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return coords
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def get_size(matrix):
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height = len(matrix)
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width = len(matrix[0])
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return height, width
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def row_col_from_int(matrix, x):
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h, w = get_size(matrix)
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col = x % w
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row = x // h
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return row, col
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def matrix_of_size(width, height, default=0):
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return [[default] * width for x in range(height)]
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def set_matrix_dict(m):
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for x in range(len(m)):
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for y in range(len(m[x])):
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m[x][y] = {}
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return m
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def pmx(*matrices, pad=True, space=True):
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"""
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print a matrix of integers, zero turns to `.` for clarity
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"""
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if len(matrices) > 1:
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matrices = list(zip(*matrices))
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for row in matrices:
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r = []
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for col in row:
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r.append("".join([f"{int(x)or '.'}".rjust(3) for x in col]))
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print(" ".join(r))
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else:
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for row in matrices:
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for c in row:
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if pad:
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f = lambda x: f"{int(x)or '.'}".rjust(2)
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if space:
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f = lambda x: f"{int(x)or '.'}".rjust(3)
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else:
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f = lambda x: f"{int(x)or '.'}"
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if space:
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f = lambda x: f"{int(x)or '.'} "
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print("".join([f(x) for x in c]))
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def ppmx(*matrices, pad=True, space=True, zero="."):
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"""
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print a matrix of anything, Falsy values turns to `.` for clarity
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"""
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out = []
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if len(matrices) > 1:
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matrices = list(zip(*matrices))
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for row in matrices:
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r = []
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for col in row:
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r.append("".join([f"{x or zero}".rjust(3) for x in col]))
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out.append(" ".join(r))
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else:
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for row in matrices:
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for c in row:
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if pad:
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f = lambda x: f"{x or zero}".rjust(2)
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if space:
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f = lambda x: f"{x or zero}".rjust(3)
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else:
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f = lambda x: f"{x or zero}"
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if space:
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f = lambda x: f"{x or zero} "
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out.append("".join([f(x) for x in c]))
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return "\n".join(out)
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def view_matrix(matrix, y1, x1, y2, x2):
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lines = ppmx(matrix, pad=0, space=0).split("\n")
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for line in lines[y1 : y2 + 1]:
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print(line[x1:x2])
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def highlight(matrix, red=[], green=[], blue=[], blink_green=[]):
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"""
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print a matrix of anything, Falsy values turns to `.` for clarity
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"""
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mx = deepcopy(matrix)
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for y, x in red:
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if (y, x) in blue or (y, x) in green or (y, x) in blink_green:
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continue
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new = f"{colors.RED}{mx[y][x]}{colors.ENDC}"
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mx[y][x] = new
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for y, x in green:
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if (y, x) in blue or (y, x) in blink_green:
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continue
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new = f"{colors.GREEN}{mx[y][x]}{colors.ENDC}"
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mx[y][x] = new
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for y, x in blue:
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if (y, x) in blink_green:
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continue
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new = f"{colors.BLUE}{mx[y][x]}{colors.ENDC}"
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mx[y][x] = new
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for y, x in blink_green:
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new = f"{colors.BLINK}{colors.GREEN}{mx[y][x]}{colors.ENDC}"
|
||||
mx[y][x] = new
|
||||
print(ppmx(mx, pad=False, space=True, zero="0"))
|
||||
|
||||
|
||||
def draw_shape_at(mx, row, col, shape=None, value=1):
|
||||
if shape is None:
|
||||
raise Exception("Please provide a list of coordinate offsets from Y,X to draw")
|
||||
for y, x in shape:
|
||||
mx[row + y][col + x] = value
|
||||
|
||||
|
||||
def collision_at(mx, row, col, shape=None):
|
||||
if shape is None:
|
||||
raise Exception("Please provide a list of coordinate offsets from Y,X to draw")
|
||||
for y, x in shape:
|
||||
if mx[row + y][col + x] != 0:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def out_of_bounds(mx, row, col, shape=None):
|
||||
if shape is None:
|
||||
raise Exception("Please provide a list of coordinate offsets from Y,X to draw")
|
||||
height, width = get_size(mx)
|
||||
for y, x in shape:
|
||||
if row + y > height - 1:
|
||||
return True
|
||||
if col + x >= width:
|
||||
return True
|
||||
if col + x < 0:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def spiral_generator(width, height):
|
||||
k = 0
|
||||
l = 0
|
||||
m = height
|
||||
n = width
|
||||
|
||||
""" k - starting row index
|
||||
m - ending row index
|
||||
l - starting column index
|
||||
n - ending column index
|
||||
i - iterator """
|
||||
|
||||
while k < m and l < n:
|
||||
# Print the first row from
|
||||
# the remaining rows
|
||||
for i in range(l, n):
|
||||
yield (i, k)
|
||||
# print(a[k][i], end=" ")
|
||||
|
||||
k += 1
|
||||
|
||||
# Print the last column from
|
||||
# the remaining columns
|
||||
for i in range(k, m):
|
||||
yield (n - 1, i)
|
||||
# print(a[i][n - 1], end=" ")
|
||||
|
||||
n -= 1
|
||||
|
||||
# Print the last row from
|
||||
# the remaining rows
|
||||
if k < m:
|
||||
for i in range(n - 1, (l - 1), -1):
|
||||
# print(a[m - 1][i], end=" ")
|
||||
yield (i, m - 1)
|
||||
|
||||
m -= 1
|
||||
|
||||
# Print the first column from
|
||||
# the remaining columns
|
||||
if l < n:
|
||||
for i in range(m - 1, k - 1, -1):
|
||||
# print(a[i][l], end=" ")
|
||||
yield (l, i)
|
||||
|
||||
l += 1
|
||||
173
2024/python/shared.py
Normal file
173
2024/python/shared.py
Normal file
@ -0,0 +1,173 @@
|
||||
from contextlib import contextmanager
|
||||
from timeit import default_timer
|
||||
from pathlib import Path
|
||||
import cProfile
|
||||
import functools
|
||||
import pstats
|
||||
from itertools import groupby
|
||||
|
||||
def all_equal(iterable):
|
||||
g = groupby(iterable)
|
||||
return next(g, True) and not next(g, False)
|
||||
|
||||
|
||||
def profile(func):
|
||||
@functools.wraps(func)
|
||||
def inner(*args, **kwargs):
|
||||
profiler = cProfile.Profile()
|
||||
profiler.enable()
|
||||
try:
|
||||
retval = func(*args, **kwargs)
|
||||
finally:
|
||||
profiler.disable()
|
||||
with open("profile.out", "w") as profile_file:
|
||||
stats = pstats.Stats(profiler, stream=profile_file)
|
||||
stats.print_stats()
|
||||
return retval
|
||||
|
||||
return inner
|
||||
|
||||
def spl(y):
|
||||
return [int(w) for w in y]
|
||||
|
||||
def minmax(l):
|
||||
return min(l), max(l)
|
||||
|
||||
|
||||
def load_rows(day, part2=False):
|
||||
return [row for row in load(day, part2)]
|
||||
|
||||
|
||||
def load(day, part2=False):
|
||||
if part2:
|
||||
path = Path(get_fname(day) + ".part2")
|
||||
try:
|
||||
return path.read_text().rstrip().split("\n")
|
||||
except FileNotFoundError:
|
||||
# No part 2 file, use first file
|
||||
pass
|
||||
path = Path(get_fname(day))
|
||||
return path.read_text().rstrip().split("\n")
|
||||
|
||||
|
||||
def get_fname(day: int) -> str:
|
||||
import sys
|
||||
|
||||
if sys.argv[-1] == "--sample":
|
||||
return f"samples/day{day:02}.txt"
|
||||
else:
|
||||
return f"full/day{day:02}.txt"
|
||||
|
||||
|
||||
#############
|
||||
def load_char_matrix(f):
|
||||
my_file = []
|
||||
for line in f:
|
||||
my_file.append(line.rstrip())
|
||||
return [list(x) for x in my_file]
|
||||
|
||||
|
||||
def load_file_char_matrix(name):
|
||||
with open(name, "r") as f:
|
||||
return load_char_matrix(f)
|
||||
|
||||
|
||||
def load_int_matrix(f):
|
||||
my_file = []
|
||||
for line in f:
|
||||
my_file.append(line.rstrip())
|
||||
return [list(map(int, x)) for x in my_file]
|
||||
|
||||
|
||||
def load_file_int_matrix(name):
|
||||
with open(name, "r") as f:
|
||||
return load_int_matrix(f)
|
||||
|
||||
|
||||
def load_word_matrix(f):
|
||||
my_file = []
|
||||
for line in f:
|
||||
my_file.append(line.rstrip())
|
||||
return [x.split(" ") for x in my_file]
|
||||
|
||||
|
||||
def load_file_word_matrix(name):
|
||||
with open(name, "r") as f:
|
||||
return load_word_matrix(f)
|
||||
|
||||
|
||||
#############
|
||||
|
||||
|
||||
def rotate(WHAT, times=1):
|
||||
what = WHAT
|
||||
for x in range(times):
|
||||
what = list(zip(*what[::-1]))
|
||||
return what
|
||||
|
||||
|
||||
@contextmanager
|
||||
def elapsed_timer():
|
||||
start = default_timer()
|
||||
elapser = lambda: default_timer() - start
|
||||
yield lambda: elapser()
|
||||
end = default_timer()
|
||||
elapser = lambda: end - start
|
||||
|
||||
|
||||
def render_cubes(maxX, maxY, maxZ, my_cubes):
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
|
||||
|
||||
def cuboid_data(o, size=(1, 1, 1)):
|
||||
X = [
|
||||
[[0, 1, 0], [0, 0, 0], [1, 0, 0], [1, 1, 0]],
|
||||
[[0, 0, 0], [0, 0, 1], [1, 0, 1], [1, 0, 0]],
|
||||
[[1, 0, 1], [1, 0, 0], [1, 1, 0], [1, 1, 1]],
|
||||
[[0, 0, 1], [0, 0, 0], [0, 1, 0], [0, 1, 1]],
|
||||
[[0, 1, 0], [0, 1, 1], [1, 1, 1], [1, 1, 0]],
|
||||
[[0, 1, 1], [0, 0, 1], [1, 0, 1], [1, 1, 1]],
|
||||
]
|
||||
X = np.array(X).astype(float)
|
||||
for i in range(3):
|
||||
X[:, :, i] *= size[i]
|
||||
X += np.array(o)
|
||||
return X
|
||||
|
||||
def plotCubeAt(positions, sizes=None, colors=None, **kwargs):
|
||||
if not isinstance(colors, (list, np.ndarray)):
|
||||
colors = ["C0"] * len(positions)
|
||||
if not isinstance(sizes, (list, np.ndarray)):
|
||||
sizes = [(1, 1, 1)] * len(positions)
|
||||
g = []
|
||||
for p, s, c in zip(positions, sizes, colors):
|
||||
g.append(cuboid_data(p, size=s))
|
||||
return Poly3DCollection(
|
||||
np.concatenate(g), facecolors=np.repeat(colors, 6, axis=0), **kwargs
|
||||
)
|
||||
|
||||
N1 = maxX
|
||||
N2 = maxY
|
||||
N3 = maxZ
|
||||
ma = np.random.choice([0, 1], size=(N1, N2, N3), p=[0.99, 0.01])
|
||||
x, y, z = np.indices((N1, N2, N3)) - 0.5
|
||||
# positions = np.c_[x[ma==1],y[ma==1],z[ma==1]]
|
||||
positions = np.c_[my_cubes]
|
||||
colors = np.random.rand(len(positions), 3)
|
||||
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(projection="3d")
|
||||
ax.set_aspect("equal")
|
||||
|
||||
pc = plotCubeAt(positions, colors=colors, edgecolor="k")
|
||||
ax.add_collection3d(pc)
|
||||
|
||||
ax.set_xlim([0, maxX])
|
||||
ax.set_ylim([0, maxY])
|
||||
ax.set_zlim([0, maxZ])
|
||||
# plotMatrix(ax, ma)
|
||||
# ax.voxels(ma, edgecolor="k")
|
||||
|
||||
plt.show()
|
||||
Loading…
Reference in New Issue
Block a user