Delete Runge_Kutta_solution.py

Runge_Kutta_solution.py

-import numpy as np
-import matplotlib.pyplot as plt
-
-plt.rcParams['font.size'] = 14
-plt.rcParams['font.family'] = 'Times New Roman'
-
-def dydt(t, Y, Kp, Km, X0, A0):
-    return Kp * (X0 - Y) * (A0 - Y) - Km * Y
-
-def runge_kutta(h, t_max, Kp, Km, X0, A0):
-    t_values = np.arange(0, t_max + h, h)
-    y_values = np.zeros(len(t_values))
-    y = 0 
-
-    for i in range(1, len(t_values)):
-        t = t_values[i-1]
-        k1 = h * dydt(t, y, Kp, Km, X0, A0)
-        k2 = h * dydt(t + 0.5*h, y + 0.5*k1, Kp, Km, X0, A0)
-        k3 = h * dydt(t + 0.5*h, y + 0.5*k2, Kp, Km, X0, A0)
-        k4 = h * dydt(t + h, y + k3, Kp, Km, X0, A0)
-
-        y += (k1 + 2*k2 + 2*k3 + k4) / 6
-        y_values[i] = y
-
-    return t_values, y_values
-
-
-#Set the parameters.
-#Association constant k+.
-Kp = @Kp
-#Dissociation constant k-.
-Km = @Km
-#Initial free binding sites X0 (receptors or antigens).
-X0 = @Xo
-#Initial AB concentration A0.
-A0 = @A0
-#Step width of Runge-Kutta algorythm. Can be set to 0.1 for rough estimation.
-h = @h0
-#Measuring time t_max.
-t_max = @t_max
-
-#Insert time points.
-t_data = @t_data #@t_data=np.array([t1,t2,t3,...])
-#Insert MFI data.
-y_data = @y_data #@y_data=np.array([y1,y2,y3,...])
-#Insert y standard deviation.
-stdev_data = @stdev_data #@stdev_data=np.array([stdev1,stdev2,stdev3,...])
-
-
-t_values, y_values = runge_kutta(h, t_max, Kp, Km, X0, A0)
-
-plt.plot(t_data, y_data, 'o', color='green', label='Label')
-
-
-#Plot the results.
-plt.plot(t_values, y_values, color='#8A2BE2', label='Runge-Kutta Solution')
-lower_bound = y_data - stdev_data
-upper_bound = y_data + stdev_data
-plt.fill_between(t_data, lower_bound, upper_bound, color='lightgreen', alpha=0.3, label='SD')
-plt.xlabel('Time in s')
-plt.ylabel('MFI')
-plt.legend(prop={'weight': 'bold'}, loc='lower right')
-plt.title('Title', fontweight='bold')
-
-#Plot limits.
-plt.xlim(-5, 3600)
-plt.ylim(0,150)
-
-ax = plt.gca() 
-ax.spines['top'].set_visible(False)
-ax.spines['right'].set_visible(False)
-
-
-#plt.savefig('Figure.png', bbox_inches='tight')
-
-plt.show()
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