308 lines
7.6 KiB
Python
308 lines
7.6 KiB
Python
import matrix
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import math
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import sys
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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 typing import Optional, List, Tuple
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from dataclasses import dataclass
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from collections import defaultdict
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def cityblock(y1,x1, y2,x2):
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return abs(y2-y1) + abs(x2-x1)
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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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limit: Tuple[int,int] = (0,0)
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_d: int = None
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_edges: List[Tuple[int,int]]= None
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_border: List[Tuple[int,int]]= None
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def __str__(self):
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return (f"Sensor(sX={self.sX}, sY={self.sY}, bX={self.bX},"
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f"bY={self.bY}, d={self._d}, edges={len(self._edges)}, borders={len(self._borders)})")
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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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if self._d is None:
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self._d = cityblock(self.sY,self.sX, self.bY, self.bX)
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return self._d
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def distance_to(self, bY, bX):
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return cityblock(self.sY,self.sX, bY, bX)
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def on_line(self, y):
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midpoint = (y,self.s[1])
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d = self.distance_to(*midpoint)
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if d > self.distance:
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return []
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need = self.distance - d
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start = (y, midpoint[1] - need)
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end = (y, midpoint[1] + need)
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return list(range(start[1],end[1]+1))
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def in_range(self, bY,bX):
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d = cityblock(self.sY,self.sX, bY, bX)
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if self.d < d:
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return False
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return True
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def in_diamond(self):
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sX,sY = self.sX, self.sY
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up_lim = sY - self.distance
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dn_lim = sY + self.distance
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le_lim = sX - self.distance
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ri_lim = sX + self.distance
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u = (up_lim, sX)
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d = (dn_lim, sX)
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l = (sY, le_lim)
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r = (sY, ri_lim)
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infliction = 1
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height = -1
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for idx, x in enumerate(range(l[1],r[1]+1)):
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height += infliction
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if (sY, x) == self.s:
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infliction = -1
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for y in range(sY-height, sY+height+1):
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yield (y,x)
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def edges(self):
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if self._edges:
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return self._edges
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sX,sY = self.sX, self.sY
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up_lim = sY - self.distance
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dn_lim = sY + self.distance
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le_lim = sX - self.distance
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ri_lim = sX + self.distance
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u = (up_lim, sX)
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d = (dn_lim, sX)
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l = (sY, le_lim)
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r = (sY, ri_lim)
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infliction = 1
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height = -1
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edges = set()
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# to left -1 and right + 1
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for idx, x in enumerate(range(l[1],r[1]+1)):
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height += infliction
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if (sY, x) == self.s:
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infliction = -1
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edges.add((sY-height,x))
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edges.add((sY+height,x))
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self._edges = edges
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return self._edges
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def border(self):
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if self._border:
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return self._border
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sX,sY = self.sX, self.sY
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up_lim = sY - self.distance
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dn_lim = sY + self.distance
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le_lim = sX - self.distance
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ri_lim = sX + self.distance
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u = (up_lim, sX)
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d = (dn_lim, sX)
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l = (sY, le_lim)
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r = (sY, ri_lim)
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infliction = 1
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height = -1
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border = set()
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# to left -1 and right + 1
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for idx, x in enumerate(range(l[1]-1,r[1]+2)):
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height += infliction
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if (sY, x) == self.s:
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infliction = -1
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border.add((sY-height,x))
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border.add((sY+height,x))
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self._border = border
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return self._border
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def part1(rows, sample=False):
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sensors = []
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sensor_points = []
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beacon_points = []
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ineligible_points = set()
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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,limit=(0,0)))
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minX, maxX = min(xSet),max(xSet)
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minY, maxY = min(ySet),max(ySet)
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limLo = min(minX,minY)
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limHi = max(maxX,maxY)
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for sensor in sensors:
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sensor.limit = (limLo,limHi)
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sensor_points.append(sensor.s)
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beacon_points.append(sensor.b)
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if sample:
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for yx in sensor.in_diamond():
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ineligible_points.add(yx)
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CHECK_ROW = 2000000
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if sample:
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CHECK_ROW = 10
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ineligible = set()
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for s in sensors:
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coll = s.on_line(CHECK_ROW)
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ineligible.update(coll)
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count_ignoring_current_beacons = 0
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for i in ineligible:
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if (CHECK_ROW, i) not in beacon_points:
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count_ignoring_current_beacons += 1
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print(count_ignoring_current_beacons, "with removing beacons, final answer")
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if not sample:
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return
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mx = matrix.matrix_of_size(maxX+1, maxY+1)
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for yx in ineligible_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "#"
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for yx in beacon_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "B"
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for yx in sensor_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "S"
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print(matrix.ppmx(mx, pad=False,space=True))
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tuning = lambda y,x: y + (4000000 * x)
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def part2(rows, sample=False):
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sensors = []
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sensor_points = []
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beacon_points = []
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ineligible_points = set()
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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.edges()
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_ = sensor.border()
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sensor_points.append(sensor.s)
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beacon_points.append(sensor.b)
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if sample:
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for yx in sensor.in_diamond():
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ineligible_points.add(yx)
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L = 4000000
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if sample:
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L = 20
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borders = defaultdict(int)
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for s in sensors:
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for yx in s.border():
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y,x = yx
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if y > 0 and y <= L and x > 0 and x <= L:
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borders[yx] += 1
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TARGET = None
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for (eY,eX) in borders.keys():
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#print("checking:",(eY,ex))
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away_from = []
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for idx, s in enumerate(sensors):
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d = s.distance_to(eY,eX)
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if d > s.distance:
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away_from.append(s.s)
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if len(away_from) == len(sensors):
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TARGET = (eY,eX)
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print(TARGET, tuning(eY,eX))
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break
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if not sample:
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return
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# """ PRINT OUTPUT """
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mx = matrix.matrix_of_size(maxX+1, maxY+1)
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for yx in ineligible_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "#"
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for yx in beacon_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "B"
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for yx in sensor_points:
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y,x = yx
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if y >= 0 and x >= 0:
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if y <= maxY and x <= maxX:
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mx[y][x] = "S"
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mx[TARGET[0]][TARGET[1]] = "!"
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matrix.highlight(mx, blink_green=[TARGET,])
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def main():
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sample = False
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if sys.argv[-1] == "--sample":
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sample = True
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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, sample)
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print("🕒", elapsed())
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with shared.elapsed_timer() as elapsed:
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part2(rows, sample)
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print("🕒", elapsed())
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if __name__ == "__main__":
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main()
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