101 lines
2.1 KiB
Python
101 lines
2.1 KiB
Python
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import matrix
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import math
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from pprint import pprint
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import shared
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from scanf import scanf
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from dataclasses import dataclass
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from scipy.spatial.distance import cityblock
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def manhattan(a, b):
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return abs(b[0] - a[0]) + abs(b[1] - a[1])
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@dataclass
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class Sensor:
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sX: int
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sY: int
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bX: int
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bY: int
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@property
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def s(self):
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return (self.sY, self.sX)
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@property
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def b(self):
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return (self.bY, self.bX)
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@property
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def distance(self):
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a,b = zip(self.s, self.b)
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return cityblock(a, b)
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def distance_to(self, y,x):
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a,b = zip(self.s, (y,x))
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return cityblock(a, b)
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#@shared.profile
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def part1(rows):
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CHECK_ROW = 10
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CHECK_ROW = 2000000
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sensors = []
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sensor_points = []
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beacon_points = []
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xSet = set()
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ySet = set()
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for row in rows:
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x,y,bx,by = scanf("Sensor at x=%d, y=%d: closest beacon is at x=%d, y=%d", row)
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xSet.add(x)
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xSet.add(bx)
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ySet.add(y)
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ySet.add(by)
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sensors.append(Sensor(sX=x,sY=y,bX=bx,bY=by))
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minX, maxX = min(xSet),max(xSet)
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minY, maxY = min(ySet),max(ySet)
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for sensor in sensors:
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sensor_points.append(sensor.s)
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beacon_points.append(sensor.b)
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ineligible = set()
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for x in range(minX,maxX):
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point = (CHECK_ROW, x)
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if x % 10000 == 0:
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print(point)
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if point in beacon_points:
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continue
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if point in sensor_points:
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continue
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for s in sensors:
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d = s.distance_to(*point)
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if d <= s.distance:
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ineligible.add(point)
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pprint(ineligible)
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print(len(ineligible))
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# mx[sensor.sY][sensor.sX] = "S"
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# mx[sensor.bY][sensor.bX] = "B"
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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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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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