Day 10 solution

2018/day-10/python/main.py

@@ -0,0 +1,98 @@
+import re
+import os
+import sys
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+from collections import namedtuple
+
+
+# Constants
+
+RE_PATTERN = r"position=<\s*(\-*\d+),\s*(\-*\d+)> velocity=<([-*\s?]\d+), ([-?\s?]\d+)>"
+PATH = os.path.join(sys.path[0], '..', 'input')
+
+getX = lambda p : p.pos[0]
+getY = lambda p : p.pos[1]
+
+# MovingPoint (pos, velocity) class
+
+class MovingPoint(object):
+    def __init__(self, input):
+        match = re.search(RE_PATTERN, input)
+        self.pos = [int(match.group(1)), int(match.group(2))]
+        self.vel = [int(match.group(3)), int(match.group(4))]
+
+    def calculate(self, t):
+        return Point(self.pos[0] + (self.vel[0] * t), self.pos[1] + (self.vel[1] * t))
+
+    def simulate(self, t=1):
+        self.pos[0] += self.vel[0] * t
+        self.pos[1] += self.vel[1] * t
+
+    def __repr__(self):
+        return f"<MovingPoint pos({self.pos[0]}, {self.pos[1]}) vel({self.vel[0]}, {self.vel[1]})"
+
+class Matrix(object):
+    def __init__(self, input):
+        self.points = []
+        for line in input.readlines():
+            self.points.append(MovingPoint(line))
+        input.close()
+    
+    def simulate(self, t=1):
+        for point in self.points:
+            point.simulate(t)
+
+    @property
+    def minX(self):
+        return min(self.points, key=lambda p : p.pos[0]).pos[0]
+    
+    @property
+    def maxX(self):
+        return max(self.points, key=lambda p : p.pos[0]).pos[0]
+    
+    @property
+    def minY(self):
+        return min(self.points, key=lambda p : p.pos[1]).pos[1]
+
+    @property
+    def maxY(self):
+        return max(self.points, key=lambda p : p.pos[1]).pos[1]
+
+    @property
+    def Xs(self):
+        return [p.pos[0] for p in self.points]
+
+    @property
+    def Ys(self):
+        return [p.pos[1] for p in self.points]
+
+import copy
+
+print('Building Matrix')
+original = Matrix(open(PATH, 'r'))
+matrix = copy.deepcopy(original)
+difs = []
+print('Matrix built, copy made.')
+
+# Simulate all likely points in time of message
+print('Simulating')
+for i in range(11000):
+    difX = abs(matrix.maxX - matrix.minX)
+    difY = abs(matrix.maxY - matrix.minY)
+    difs.append(difX + difY)
+    matrix.simulate(1)
+print('Simulated')
+
+# Point in time where all points are closest
+best = min(list(enumerate(difs)), key=lambda x:x[1])
+print(f'Found best point {best[0]} seconds in the future.')
+
+print('Resimulating')
+original.simulate(best[0])
+print('Building Scatter Plot')
+plt.scatter(original.Xs, original.Ys)
+plt.gca().invert_yaxis()
+plt.show()