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Minor dtype optimisation

This commit is contained in:
Luke Hubmayer-Werner 2021-12-21 13:42:01 +10:30
parent a84fdc6207
commit 7cd1acb39a
1 changed files with 8 additions and 4 deletions
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12
2021/day20.py
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@ -1,4 +1,7 @@
import numpy as np
from sys import argv
filename = argv[1] if len(argv)>1 else 'day20input'
def unfold(func, arg, n):
for _ in range(n):
@ -7,15 +10,16 @@ def unfold(func, arg, n):
mapping = {'#':1, '.':0}
with open('day20input', 'r') as file:
with open(filename, 'r') as file:
rawinput = file.read().strip()
cipher_str, _, input_str = rawinput.partition('\n\n')
cipher = np.array([mapping[c] for c in cipher_str])
input_arr = np.array([[mapping[c] for c in string] for string in input_str.split('\n')])
cipher = np.array([mapping[c] for c in cipher_str], dtype=np.int8)
input_arr = np.array([[mapping[c] for c in string] for string in input_str.split('\n')], dtype=np.int8)
roll_offsets = [(x,y) for y in [1,0,-1] for x in [1,0,-1]] # Note roll is opposite direction to our sampling i.e. (1,1) means (0,0) is old (-1,-1)
def sample(array):
lookup_values = sum([2**(8-n)*np.roll(array, offset, (1,0)) for n,offset in enumerate(roll_offsets)]) # Note axis 1 is x axis 0 is y.
#lookup_values = sum([2**(8-n)*np.roll(array, offset, (1,0)) for n,offset in enumerate(roll_offsets)]) # Note axis 1 is x axis 0 is y.
lookup_values = np.sum([2**(8-n)*np.roll(array, offset, (1,0)) for n,offset in enumerate(roll_offsets)], 0, dtype=np.int16) # Note axis 1 is x axis 0 is y.
return cipher[lookup_values]
def visualize(array):