added ex27

exam/ex27/main.py

@@ -0,0 +1,101 @@
+import sys
+sys.path.append("../../")
+
+import numpy as np
+from collections import deque
+import matplotlib.pyplot as plt
+
+from util.io import readvalue
+
+def positive_int(s):
+	i = int(s)
+	if(not i > 0):
+		raise ValueError("{} <= 0".format(i))
+	return i
+def float_0_1(s):
+	i = float(s)
+	if(not i > 0):
+		raise ValueError("{} <= 0".format(i))
+	if(i > 1):
+		raise ValueError("{} > 1".format(i))
+	return i
+
+IS_TREE = 1
+TREE_IS_ON_FIRE = 2
+TREE_WILL_BE_ON_FIRE = 4
+
+def prepare_model(N, p):
+	model = np.zeros((N, N), dtype=np.int8)
+	model[np.random.uniform(size=(N,N)) < p] = IS_TREE
+	return model
+
+def index_plus(i, j, add_i, add_j, model):
+	new_i = i + add_i
+	new_j = j + add_j
+
+	if(new_i >= model.shape[0]):
+		new_i -= model.shape[0]
+	if(new_i < 0):
+		new_i += model.shape[0]
+	if(new_j >= model.shape[1]):
+		new_j -= model.shape[1]
+	if(new_j < 0):
+		new_j += model.shape[1]
+
+	return new_i, new_j
+	
+
+def do_tick(model):
+	for i in range(model.shape[0]):
+		for j in range(model.shape[1]):
+			if((not model[i][j] & IS_TREE) or model[i][j] & TREE_IS_ON_FIRE):
+				continue
+
+
+			if(
+				(model[index_plus(i, j, 1, 0, model)] & TREE_IS_ON_FIRE)
+				or (model[index_plus(i, j, 0, 1, model)] & TREE_IS_ON_FIRE)
+				or (model[index_plus(i, j, -1, 0, model)] & TREE_IS_ON_FIRE)
+				or (model[index_plus(i, j, 0, -1, model)] & TREE_IS_ON_FIRE)
+				):
+
+				model[i][j] |= TREE_WILL_BE_ON_FIRE
+			
+	model[(model & TREE_WILL_BE_ON_FIRE) != 0] |= TREE_IS_ON_FIRE
+	model[(model & TREE_WILL_BE_ON_FIRE) != 0] ^= TREE_WILL_BE_ON_FIRE
+
+def trees_on_fire(model):
+	unique, counts = np.unique((model & TREE_IS_ON_FIRE) != 0, return_counts=True)
+	if(True not in unique):
+		return 0
+	return counts[np.where(unique == True)[0]][0]
+	
+def set_initial_on_fire(model):
+	i = np.random.randint(0, model.shape[0])
+	j = np.random.randint(0, model.shape[1])
+	while True:
+		if(model[i][j] & IS_TREE):
+			model[i][j] |= TREE_IS_ON_FIRE
+			break
+		i = (i + 1) % model.shape[0]
+		j = (j + 1) % model.shape[1]
+
+
+N = readvalue("N > ", positive_int)
+p = readvalue("p > ", float_0_1)
+
+model = prepare_model(N, p)
+set_initial_on_fire(model)
+
+on_fire = deque()
+last_on_fire = 1
+while True:
+	do_tick(model)
+	now_on_fire = trees_on_fire(model)
+	on_fire.append(now_on_fire)
+	if(now_on_fire == last_on_fire):
+		break
+	last_on_fire = now_on_fire
+
+plt.plot(*zip(*enumerate(on_fire)))
+plt.show()