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Brusselator_reflektiv_Rand_fluktuationen_multirender_try.py
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Brusselator_reflektiv_Rand_fluktuationen_multirender_try.py
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import numpy as np
import matplotlib.pyplot as plt
import time
import random
from scipy.ndimage.interpolation import rotate
import ray
ray.init()
'''Definition der Laufvariablen'''
t_tot = 500
dt = 0.01
l = 750
t = np.arange(0, t_tot+0.01, dt)
n = len(t)
'''Nebenbedingungsmatrix erstellen'''
A = np.empty(shape=(l, l), dtype=float)
B = np.empty(shape=(l, l), dtype=float)
start_A = 0.5
stop_A = 3.0
start_B = 2.0
stop_B = 9.0
A_in = np.arange(start_A, stop_A, (stop_A-start_A)/(l))
B_in = np.arange(start_B, stop_B, (stop_B-start_B)/(l))
#A[:,:] = A_in[0:l]
#B[:,:] = B_in[0:l]
#B = rotate(B,angle=90)
A[:, :] = 1
B[:, :] = 3
'''Arrays fuer die beiden Konzentrationen: (Zeit, y-Laenge, x-Laenge)'''
Cx = np.empty(shape=(l, l), dtype=float)
Cy = np.empty(shape=(l, l), dtype=float)
'''Verschobene Konzentrationsarrays fuer die Diffusion'''
Cx_oben = np.empty(shape=(l, l), dtype=float)
Cx_unten = np.empty(shape=(l, l), dtype=float)
Cx_links = np.empty(shape=(l, l), dtype=float)
Cx_rechts = np.empty(shape=(l, l), dtype=float)
Cy_oben = np.empty(shape=(l, l), dtype=float)
Cy_unten = np.empty(shape=(l, l), dtype=float)
Cy_links = np.empty(shape=(l, l), dtype=float)
Cy_rechts = np.empty(shape=(l, l), dtype=float)
Cx_diff_gesamt = np.empty(shape=(l, l), dtype=float)
Cy_diff_gesamt = np.empty(shape=(l, l), dtype=float)
k1 = 1.0
k2 = 1.0
k3 = 1.0
k4 = 1.0
'''Diffusionskoeffizientenmatrix erstellen'''
Dx = np.empty(shape=(l, l), dtype=float)
Dy = np.empty(shape=(l, l), dtype=float)
start_Dx = 1.0
stop_Dx = 3.0
start_Dy = 3.0
stop_Dy = 9.00
Dx_in = np.arange(start_Dx, stop_Dx, (stop_Dx-start_Dx)/l)
Dy_in = np.arange(start_Dy, stop_Dy, (stop_Dy-start_Dy)/l)
#Dx[:,:] = Dx_in
#Dy[:,:] = Dy_in
#Dy = rotate(Dy,angle=90)
Dx[:,:] = 2
Dy[:,:] = 0.2
betrachtungsintervall = 10
'''Einlesen der Startkonzentrationen (optionale wenn benötigt)'''
Cx[:, :] = A
Cy[:, :] = B/A
h = 0
plt.ion()
@ray.remote
def draw_figure(i,h, print, n):
plt.clf()
plt.imshow(print[:, :], cmap='RdBu', interpolation="lanczos") # , cmap='hot', interpolation="nearest", cmap='hsv', interpolation="lanczos" bilinear
plt.axis('off')
plt.clim(0.2, 3.5)
plt.title("t=" + str(np.round((dt * i), decimals=1)) + ", Iteration " + str(i),fontsize=8)
plt.tight_layout()
plt.savefig("render/image_" + str(h) + ".png", dpi=350)
start = time.time()
print("Start der Berechnung...")
for i in range(1, n):
if i % int(random.random() * 100 + 1) == 0 and i < 1000:
f1 = random.random()
f2 = random.random()
x1 = int(random.random() * l)
y1 = int(random.random() * l)
x2 = int(random.random() * l)
y2 = int(random.random() * l)
Cx[x1, y1] += f1
Cy[x1, y1] -= f1
Cx[x2, y2] += f2
Cy[x2, y2] -= f2
Cx_oben[:, :] = np.roll(Cx[:, :], -1, axis=0)
Cx_oben[-1, :] = Cx[-1, :]
Cx_unten[:, :] = np.roll(Cx[:, :], 1, axis=0)
Cx_unten[0, :] = Cx[0, :]
Cx_links[:, :] = np.roll(Cx[:, :], -1, axis=1)
Cx_links[:, -1] = Cx[:, -1]
Cx_rechts[:, :] = np.roll(Cx[:, :], 1, axis=1)
Cx_rechts[:, 0] = Cx[:, 0]
Cy_oben[:, :] = np.roll(Cy[:, :], -1, axis=0)
Cy_oben[-1, :] = Cy[-1, :]
Cy_unten[:, :] = np.roll(Cy[:, :], 1, axis=0)
Cy_unten[0, :] = Cy[0, :]
Cy_links[:, :] = np.roll(Cy[:, :], -1, axis=1)
Cy_links[:, -1] = Cy[:, -1]
Cy_rechts[:, :] = np.roll(Cy[:, :], 1, axis=1)
Cy_rechts[:, 0] = Cy[:, 0]
'''Cx_oben[:, :] = np.roll(Cx[:, :], -1, axis=0)
Cx_unten[:, :] = np.roll(Cx[:, :], 1, axis=0)
Cx_links[:, :] = np.roll(Cx[:, :], -1, axis=1)
Cx_rechts[:, :] = np.roll(Cx[:, :], 1, axis=1)
Cy_oben[:, :] = np.roll(Cy[:, :], -1, axis=0)
Cy_unten[:, :] = np.roll(Cy[:, :], 1, axis=0)
Cy_links[:, :] = np.roll(Cy[:, :], -1, axis=1)
Cy_rechts[:, :] = np.roll(Cy[:, :], 1, axis=1)'''
Cx_diff_gesamt[:, :] = Dx[:,:] * (- 4 * Cx[:, :] + Cx_oben[:, :] + Cx_unten[:, :] + Cx_links[:, :] + Cx_rechts[:, :])
Cy_diff_gesamt[:, :] = Dy[:,:] * (- 4 * Cy[:, :] + Cy_oben[:, :] + Cy_unten[:, :] + Cy_links[:, :] + Cy_rechts[:, :])
X = (k1 * A[:, :] - k2 * B[:, :] * Cx[:, :] + k3 * Cy[:, :] * Cx[:, :] ** 2 - k4 * Cx[:, :])*dt + Cx[:, :] + Cx_diff_gesamt[:, :] * dt
Y = (k2 * B[:, :] * Cx[:, :] - k3 * Cy[:, :] * Cx[:, :] ** 2)*dt + Cy[:, :] + Cy_diff_gesamt[:, :] * dt
Cx[:, :] = X
Cy[:, :] = Y
end = time.time()
if i % ((t_tot/dt)/1000) == 0:
end = time.time()
print("Iteration " + str(i) + " " + str(np.round((i/n)*100, decimals=1)) + "% erledigt (" + str(np.round(i / (end - start), decimals=1)) + " I/s, " + str(np.round(i / (end - start)/betrachtungsintervall, decimals=1)) + " f/s) Restdauer: " + str(np.round((((t_tot/dt)-i)/(i / (end - start)))/60, decimals=1)) + " min")
if i == 1:
draw_figure.remote(i, h, Cx[:,:], n)
h += 1
if i % betrachtungsintervall == 0:
draw_figure.remote(i, h, Cx[:,:], n)
h += 1
print("Warte auf Imagerender...")
plt.pause(600000)