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Advent_of_code/src/Year_2019/P8.py

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Python

# --- Day 8: Space Image Format ---
# The Elves' spirits are lifted when they realize you have an opportunity to
# reboot one of their Mars rovers, and so they are curious if you would spend a
# brief sojourn on Mars. You land your ship near the rover.
# When you reach the rover, you discover that it's already in the process of
# rebooting! It's just waiting for someone to enter a BIOS password. The Elf
# responsible for the rover takes a picture of the password (your puzzle input)
# and sends it to you via the Digital Sending Network.
# Unfortunately, images sent via the Digital Sending Network aren't encoded
# with any normal encoding; instead, they're encoded in a special Space Image
# Format. None of the Elves seem to remember why this is the case. They send
# you the instructions to decode it.
# Images are sent as a series of digits that each represent the color of a
# single pixel. The digits fill each row of the image left-to-right, then move
# downward to the next row, filling rows top-to-bottom until every pixel of the
# image is filled.
# Each image actually consists of a series of identically-sized layers that are
# filled in this way. So, the first digit corresponds to the top-left pixel of
# the first layer, the second digit corresponds to the pixel to the right of
# that on the same layer, and so on until the last digit, which corresponds to
# the bottom-right pixel of the last layer.
# For example, given an image 3 pixels wide and 2 pixels tall, the image data
# 123456789012 corresponds to the following image layers:
# Layer 1: 123
# 456
# Layer 2: 789
# 012
# The image you received is 25 pixels wide and 6 pixels tall.
# To make sure the image wasn't corrupted during transmission, the Elves would
# like you to find the layer that contains the fewest 0 digits. On that layer,
# what is the number of 1 digits multiplied by the number of 2 digits?
from collections import Counter
with open("files/P8.txt") as f:
digits = [
int(digit) for line in f.read().strip().split() for digit in line
]
def part_1() -> None:
picture_size = 25 * 6
layers = []
for i in range(0, len(digits), picture_size):
layer = Counter(digits[i : i + picture_size])
layers.append(layer)
fewest_zeros = min(layer[0] for layer in layers)
for layer in layers:
if layer[0] == fewest_zeros:
print(f"The result is {layer[1] * layer[2]}")
# --- Part Two ---
# Now you're ready to decode the image. The image is rendered by stacking the
# layers and aligning the pixels with the same positions in each layer. The
# digits indicate the color of the corresponding pixel: 0 is black, 1 is white,
# and 2 is transparent.
# The layers are rendered with the first layer in front and the last layer in
# back. So, if a given position has a transparent pixel in the first and second
# layers, a black pixel in the third layer, and a white pixel in the fourth
# layer, the final image would have a black pixel at that position.
# For example, given an image 2 pixels wide and 2 pixels tall, the image data
# 0222112222120000 corresponds to the following image layers:
# Layer 1: 02
# 22
# Layer 2: 11
# 22
# Layer 3: 22
# 12
# Layer 4: 00
# 00
# Then, the full image can be found by determining the top visible pixel in
# each position:
# The top-left pixel is black because the top layer is 0.
# The top-right pixel is white because the top layer is 2 (transparent),
# but the second layer is 1.
# The bottom-left pixel is white because the top two layers are 2, but the
# third layer is 1.
# The bottom-right pixel is black because the only visible pixel in that
# position is 0 (from layer 4).
# So, the final image looks like this:
# 01
# 10
# What message is produced after decoding your image?
def part_2() -> None:
picture_size = 25 * 6
layers = []
for i in range(0, len(digits), picture_size):
layer = digits[i : i + picture_size]
layers.append(layer)
full_image = []
for pixel in range(picture_size):
for layer in layers:
if layer[pixel] == 2:
continue
full_image.append(layer[pixel])
# only grab the first non-transparent pixel
break
for idx, pixel in enumerate(full_image):
# only black (0) and white (1) pixels are in the full image
if pixel == 0:
print(" ", end="")
elif pixel == 1:
print("X", end="")
# wrap around image's width (25 pixels)
if (idx + 1) % 25 == 0:
print()
if __name__ == "__main__":
part_1()
part_2()