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Ex_4_6.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue May 14 10:49:39 2024
+
+@author: delvigne
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+import random
+
+
+X = [0]
+Y = [0]
+t = [0]
+
+
+tend = 1000
+
+Beta_1 = 1
+alpha_1 = 0.2
+Beta_2 = 1
+alpha_2 = 0.2
+
+
+K = 1 #Affinity constant
+n = 9 #Hill coefficient
+
+
+while t[-1] < tend:
+
+    props = [(K**n / (K**n + Y[-1]**n)) * Beta_1, alpha_1 * X[-1], \
+    (K**n / (K**n + X[-1]**n)) * Beta_2, alpha_2 * Y[-1]]
+
+
+    prop_sum = sum(props)
+
+
+    tau = np.random.exponential(scale=1/prop_sum)
+
+    t.append(t[-1] + tau)
+
+
+    rand = random.uniform(0,1)
+
+
+    # G1 production event
+    if rand * prop_sum <= props[0]:
+            X.append(X[-1] + 1)
+            Y.append(Y[-1])
+
+    # G1 decay event
+    elif rand * prop_sum > props[0] and rand * prop_sum <= sum(props[:2]):
+            X.append(X[-1] - 1)
+            Y.append(Y[-1])
+
+    # G2 production event
+    elif rand * prop_sum > sum(props[:2]) and rand * prop_sum <= sum(props[:3]):
+            X.append(X[-1])
+            Y.append(Y[-1] + 1)
+
+    # G2 decay event
+    elif rand * prop_sum > sum(props[:3]) and rand * prop_sum <= sum(props[:4]):
+            X.append(X[-1])
+            Y.append(Y[-1] - 1)    
+
+
+
+
+f, (ax1, ax2) = plt.subplots(2, sharex=True, sharey=False)
+line1, = ax1.plot(t , X, color="b",label="X")
+line2, = ax2.plot(t , Y, color="r",label="Y")
+ax1.set_ylabel('X')
+ax2.set_ylabel('Y')
+
+ax2.set_xlabel('Time')
+plt.show()
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