Delete NUMBA_FUNCTIONS.PY

◯ᴥᗱᗴᗝИNᗱᗴᙁ⚭ⵙ⚭ᙁᗱᗴИNᗝᗱᗴᴥ◯/2.90/SCRIPTS/ADDONS/TISSUE-MASTER/NUMBA_FUNCTIONS.PY

@@ -1,54 +0,0 @@
-# ##### 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
-    print("Tissue: Numba module loaded succesfully")
-    @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
-
-    @jit
-    def numba_lerp2(v00, v10, v01, v11, vx, vy):
-        co0 = v00 + (v10 - v00) * vx
-        co1 = v01 + (v11 - v01) * vx
-        co2 = co0 + (co1 - co0) * vy
-        return co2
-except:
-    print("Tissue: Numba not installed")
-    pass