From 282a0cc48efc65eef8de70177fac1fe0a46a2a9d Mon Sep 17 00:00:00 2001
From: Bachir Lachguel <bachirgiga@gmail.com>
Date: Sun, 27 Dec 2020 18:34:45 +0100
Subject: [PATCH] Implement nagel-schreckenberg

---
 main.py | 42 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 41 insertions(+), 1 deletion(-)

diff --git a/main.py b/main.py
index 5af2d5a..4b63571 100644
--- a/main.py
+++ b/main.py
@@ -1,2 +1,42 @@
+from random import uniform, shuffle
+import matplotlib.pyplot as plt
 import numpy as np
-import scipy as sp
+ 
+L = 500 # number of cells in row
+num_iters = 500 # number of iterations
+density = 0.48 # how many positives
+vmax = 2
+p = 0.2
+
+cars_num = int(density * L)
+initial = [0] * cars_num + [-1] * (L - cars_num)
+shuffle(initial)
+
+iterations = [initial]
+
+for i in range(num_iters):
+	prev,curr = iterations[-1],[-1] * L
+
+	for x in range(L):
+		if prev[x] > -1:
+			vi = prev[x]
+			d = 1
+			while prev[(x + d) % L] < 0:
+				d += 1
+
+			vtemp = min(vi+1, d - 1, vmax) # increse speed up to max speed, but don't move further than next car
+			v = max(vtemp - 1, 0) if uniform(0,1) < p else vtemp # with probability p hit the brakes, otherwise sustain velocity
+			curr[(x + v) % L] = v # perform the move
+			#print(x,v)
+
+	iterations.append(curr)
+
+
+a = np.zeros(shape=(num_iters,L))
+for i in range(L):
+	for j in range(num_iters):
+		a[j,i] = 1 if iterations[j][i] > -1 else 0
+ 
+# showing image
+plt.imshow(a, cmap="Greys", interpolation="nearest")
+plt.show() 
-- 
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