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# ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
import numpy as np
try:
from numba import jit
@jit
def numba_reaction_diffusion(n_verts, n_edges, edge_verts, a, b, diff_a, diff_b, f, k, dt, time_steps):
arr = np.arange(n_edges)*2
id0 = edge_verts[arr] # first vertex indices for each edge
id1 = edge_verts[arr+1] # second vertex indices for each edge
for i in range(time_steps):
lap_a = np.zeros(n_verts)
lap_b = np.zeros(n_verts)
lap_a0 = a[id1] - a[id0] # laplacian increment for first vertex of each edge
lap_b0 = b[id1] - b[id0] # laplacian increment for first vertex of each edge
for i, j, la0, lb0 in zip(id0,id1,lap_a0,lap_b0):
lap_a[i] += la0
lap_b[i] += lb0
lap_a[j] -= la0
lap_b[j] -= lb0
ab2 = a*b**2
#a += eval("(diff_a*lap_a - ab2 + f*(1-a))*dt")
#b += eval("(diff_b*lap_b + ab2 - (k+f)*b)*dt")
a += (diff_a*lap_a - ab2 + f*(1-a))*dt
b += (diff_b*lap_b + ab2 - (k+f)*b)*dt
return a, b
except:
pass
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