def setUp(self):
KCST = 10000.0
DCST = 0.08e-12
self.model = smodel.Model()
A = smodel.Spec('A', self.model)
B = smodel.Spec('B', self.model)
C = smodel.Spec('C', self.model)
D = smodel.Spec('D', self.model)
E = smodel.Spec('E', self.model)
F = smodel.Spec('F', self.model)
self.vsys1 = smodel.Volsys('vsys1', self.model)
self.vsys2 = smodel.Volsys('vsys2', self.model)
self.reac1 = smodel.Reac('reac1',
self.vsys1,
lhs=[A, B],
rhs=[C],
kcst=KCST)
self.reac2 = smodel.Reac('reac2',
self.vsys2,
lhs=[D, E],
rhs=[F],
kcst=KCST)
self.geom = sgeom.Geom()
self.comp1 = sgeom.Comp('comp1', self.geom, 1e-18)
self.comp1.addVolsys('vsys1')
self.comp2 = sgeom.Comp('comp2', self.geom, 1e-18)
self.comp2.addVolsys('vsys2')
if __name__ == "__main__":
self.mesh = meshio.importAbaqus('meshes/brick_40_4_4_1400tets.inp',
1e-6)[0]
else:
self.mesh = meshio.importAbaqus(
'multi_sys_test/meshes/brick_40_4_4_1400tets.inp', 1e-6)[0]
comp1_tets = []
comp2_tets = []
for t in range(self.mesh.ntets):
cord = self.mesh.getTetBarycenter(t)
if cord[0] < 0.0:
comp1_tets.append(t)
else:
comp2_tets.append(t)
self.tmcomp1 = sgeom.TmComp('comp1', self.mesh, comp1_tets)
self.tmcomp1.addVolsys('vsys1')
self.tmcomp2 = sgeom.TmComp('comp2', self.mesh, comp2_tets)
self.tmcomp2.addVolsys('vsys2')
self.rng = srng.create('r123', 512)
self.rng.initialize(1000)
def test_masteq():
mdl = smod.Model()
A = smod.Spec('A', mdl)
volsys = smod.Volsys('vsys', mdl)
# Production
R1 = smod.Reac('R1', volsys, lhs=[], rhs=[A], kcst=KCST_f)
R2 = smod.Reac('R2', volsys, lhs=[A], rhs=[], kcst=KCST_b)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 1000)
rng.initialize(int(time.time() % 4294967295))
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res = numpy.zeros([ntpnts])
sim.restore('./validation_cp/cp/masteq')
for t in range(0, ntpnts):
sim.run(tpnts[t])
res[t] = sim.getCompCount('comp1', 'A')
def fact(x):
return (1 if x == 0 else x * fact(x - 1))
# Do cumulative count, but not comparing them all.
# Don't get over 50 (I hope)
steps_n_res = numpy.zeros(50)
for r in res:
steps_n_res[int(r)] += 1
for s in range(50):
steps_n_res[s] = steps_n_res[s] / ntpnts
passed = True
max_err = 0.0
k1 = KCST_b
k2 = KCST_f * (6.022e23 * 1.0e-15)
# Compare 5 to 15
for m in range(5, 16):
analy = (1.0 / fact(m)) * math.pow((k2 / k1), m) * math.exp(-(k2 / k1))
assert (tol_funcs.tolerable(steps_n_res[m], analy, tolerance))
def setUp(self):
self.model = smodel.Model()
A = smodel.Spec("A", self.model)
B = smodel.Spec("B", self.model)
C = smodel.Spec("C", self.model)
D = smodel.Spec("D", self.model)
E = smodel.Spec("E", self.model)
self.vsys1 = smodel.Volsys('vsys1', self.model)
self.vsys2 = smodel.Volsys('vsys2', self.model)
self.ssys1 = smodel.Surfsys('ssys1', self.model)
self.reac1 = smodel.Reac('reac1', self.vsys1, lhs = [A], rhs = [A], kcst = 1e5)
self.reac2 = smodel.Reac('reac2', self.vsys2, lhs = [E], rhs = [E], kcst = 1e4)
self.sreac = smodel.SReac('sreac', self.ssys1, slhs = [B], srhs = [B], kcst = 1e3)
if __name__ == "__main__":
self.mesh = meshio.loadMesh('meshes/cyl_len10_diam1')[0]
else:
self.mesh = meshio.loadMesh('getROIArea_bugfix_test/meshes/cyl_len10_diam1')[0]
ntets = self.mesh.countTets()
comp1Tets, comp2Tets = [], []
comp1Tris, comp2Tris = set(), set()
for i in range(ntets):
if self.mesh.getTetBarycenter(i)[0] > 0:
comp1Tets.append(i)
comp1Tris |= set(self.mesh.getTetTriNeighb(i))
else:
comp2Tets.append(i)
comp2Tris |= set(self.mesh.getTetTriNeighb(i))
patch1Tris = list(comp1Tris & comp2Tris)
self.comp1 = sgeom.TmComp('comp1', self.mesh, comp1Tets)
self.comp2 = sgeom.TmComp('comp2', self.mesh, comp2Tets)
self.comp1.addVolsys('vsys1')
self.comp2.addVolsys('vsys2')
self.patch1 = sgeom.TmPatch('patch1', self.mesh, patch1Tris, self.comp1, self.comp2)
self.patch1.addSurfsys('ssys1')
self.ROI1 = self.mesh.addROI('ROI1', sgeom.ELEM_TET, comp1Tets)
self.ROI2 = self.mesh.addROI('ROI2', sgeom.ELEM_TET, comp2Tets)
self.ROI3 = self.mesh.addROI('ROI3', sgeom.ELEM_TRI, patch1Tris)
self.rng = srng.create('r123', 512)
self.rng.initialize(1000)
tet_hosts = gd.linearPartition(self.mesh, [steps.mpi.nhosts, 1, 1])
tri_hosts = gd.partitionTris(self.mesh, tet_hosts, patch1Tris)
self.solver = solv.TetOpSplit(self.model, self.mesh, self.rng, solv.EF_NONE, tet_hosts, tri_hosts)
def get_model():
mdl = smod.Model()
A = smod.Spec('A', mdl)
volsys = smod.Volsys('vsys',mdl)
R1 = smod.Reac('R1', volsys, lhs = [], rhs = [A])
R1.setKcst(1e-3)
return mdl
def test_forev():
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A], rhs=[B], kcst=KCST_f)
R2 = smod.Reac('R2', volsys, lhs=[B], rhs=[A], kcst=KCST_b)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 512)
rng.initialize(int(time.time() % 4294967295))
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_m = numpy.zeros([NITER, ntpnts, 2])
for i in range(0, NITER):
sim.restore('./validation_cp/cp/first_order_rev')
for t in range(0, ntpnts):
sim.run(tpnts[t])
res_m[i, t, 0] = sim.getCompConc('comp1', 'A') * 1e6
res_m[i, t, 1] = sim.getCompConc('comp1', 'B') * 1e6
mean_res = numpy.mean(res_m, 0)
Aeq = COUNT * (KCST_b /
KCST_f) / (1 +
(KCST_b / KCST_f)) / (VOL * 6.0221415e26) * 1e6
Beq = (COUNT / (VOL * 6.0221415e26)) * 1e6 - Aeq
max_err = 0.0
passed = True
for i in range(ntpnts):
if i < 7: continue
assert (tol_funcs.tolerable(mean_res[i, 0], Aeq, tolerance))
assert (tol_funcs.tolerable(mean_res[i, 1], Beq, tolerance))
def gen_model():
mdl = smodel.Model()
X = smodel.Spec('X', mdl)
A = smodel.Spec('A', mdl)
# Vol/surface systems
cytosolv = smodel.Volsys('cytosolv', mdl)
dif_X = smodel.Diff('diffX', cytosolv, X)
dif_X.setDcst(DCST)
reac_X = smodel.Reac('reacX', cytosolv, lhs=[A], rhs=[A, X])
return mdl
def cbsa2steps(cbsa_model):
import steps.geom as swm
import steps.model as smodel
import steps.rng as srng
import steps.solver as ssolver
mdl = smodel.Model()
vsys = smodel.Volsys('vsys', mdl)
mols = [smodel.Spec('M'+str(i), mdl) for i in range(1,cbsa_model.exp_n_molecules)]
reactions = []
for i in range(1,cbsa_model.exp_n_reactions):
reactants = list(np.where(cbsa_model.expS[:,i] < 0)[0])
reactants_sto = list(cbsa_model.expS[:,i][reactants]*-1)
modifiers = list(np.where(cbsa_model.expR[:,i] > 0)[0])
modifiers_sto = list(cbsa_model.expR[:,i][modifiers])
products = list(np.where(cbsa_model.expS[:,i] > 0)[0])
products_sto = list(cbsa_model.expS[:,i][products])
reactants += modifiers
reactants_sto += modifiers_sto
products += modifiers
products_sto += modifiers_sto
reactants_objs = [[mols[reactants[j]-1] for k in range(reactants_sto[j])] for j in range(len(reactants))]
reactants_objs = [item for sublist in reactants_objs for item in sublist]
products_objs = [[mols[products[j]-1] for k in range(products_sto[j])] for j in range(len(products))]
products_objs = [item for sublist in products_objs for item in sublist]
reactions.append(smodel.Reac("R"+str(i), vsys, lhs=reactants_objs, rhs=products_objs, kcst=cbsa_model.exp_k[i]))
wmgeom = swm.Geom()
comp = swm.Comp('comp', wmgeom)
comp.addVolsys('vsys')
comp.setVol(1.6667e-21)
r = srng.create('mt19937', 256)
r.initialize(int(timer()))
sim = ssolver.Wmdirect(mdl, wmgeom, r)
sim.reset()
for i in range(1,cbsa_model.exp_n_molecules):
sim.setCompConc('comp', 'M'+str(i), cbsa_model.exp_x0[i]*1e-6)
return sim
def gen_model():
mdl = smod.Model()
# The chemical species
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
C = smod.Spec('C', mdl)
D = smod.Spec('D', mdl)
E = smod.Spec('E', mdl)
F = smod.Spec('F', mdl)
G = smod.Spec('G', mdl)
H = smod.Spec('H', mdl)
I = smod.Spec('I', mdl)
J = smod.Spec('J', mdl)
volsys = smod.Volsys('vsys',mdl)
R1 = smod.Reac('R1', volsys, lhs = [A, B], rhs = [C], kcst = 1000.0e6)
R2 = smod.Reac('R2', volsys, lhs = [C], rhs = [A,B], kcst = 100)
R3 = smod.Reac('R3', volsys, lhs = [C, D], rhs = [E], kcst = 100e6)
R4 = smod.Reac('R4', volsys, lhs = [E], rhs = [C,D], kcst = 10)
R5 = smod.Reac('R5', volsys, lhs = [F, G], rhs = [H], kcst = 10e6)
R6 = smod.Reac('R6', volsys, lhs = [H], rhs = [F,G], kcst = 1)
R7 = smod.Reac('R7', volsys, lhs = [H, I], rhs = [J], kcst = 1e6)
R8 = smod.Reac('R8', volsys, lhs = [J], rhs = [H,I], kcst = 0.1*10)
# The diffusion rules
D1 = smod.Diff('D1', volsys, A, 100e-12)
D2 = smod.Diff('D2', volsys, B, 90e-12)
D3 = smod.Diff('D3', volsys, C, 80e-12)
D4 = smod.Diff('D4', volsys, D, 70e-12)
D5 = smod.Diff('D5', volsys, E, 60e-12)
D6 = smod.Diff('D6', volsys, F, 50e-12)
D7 = smod.Diff('D7', volsys, G, 40e-12)
D8 = smod.Diff('D8', volsys, H, 30e-12)
D9 = smod.Diff('D9', volsys, I, 20e-12)
D10 = smod.Diff('D10', volsys, J, 10e-12)
return mdl
def test_foirev():
mdl = smod.Model()
A = smod.Spec('A', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A], rhs=[], kcst=KCST)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 1000)
rng.initialize(int(time.time() % 4294967295))
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_m = np.zeros([NITER, ntpnts, 1])
res_std1 = np.zeros([ntpnts, 1])
res_std2 = np.zeros([ntpnts, 1])
for i in range(0, NITER):
sim.restore('./validation_cp/cp/first_order_irev')
for t in range(0, ntpnts):
sim.run(tpnts[t])
res_m[i, t, 0] = sim.getCompCount('comp1', 'A')
mean_res = np.mean(res_m, 0)
std_res = np.std(res_m, 0)
m_tol = 0
s_tol = 0
passed = True
for i in range(ntpnts):
if i == 0: continue
analy = N * np.exp(-KCST * tpnts[i])
std = np.power((N * (np.exp(-KCST * tpnts[i])) *
(1 - (np.exp(-KCST * tpnts[i])))), 0.5)
if not tol_funcs.tolerable(analy, mean_res[i], tolerance):
passed = False
assert (tol_funcs.tolerable(std, std_res[i], tolerance))
def setUp(self):
mdl = smodel.Model()
self.v1 = 1e-20
self.v2 = 2e-20
self.a1 = 3e-14
self.kreac = 200.0
self.ksreac = 100.0
S1 = smodel.Spec('S1', mdl)
S2 = smodel.Spec('S2', mdl)
S1S2 = smodel.Spec('S1S2', mdl)
vsys = smodel.Volsys('vsys', mdl)
ssys = smodel.Surfsys('ssys', mdl)
smodel.Reac('reac', vsys, lhs=[S1, S2], rhs=[S2, S2], kcst=self.kreac)
smodel.SReac('sreac', ssys, ilhs=[S1], slhs=[S2], srhs=[S1S2], kcst=self.ksreac)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom)
comp1.setVol(self.v1)
comp1.addVolsys('vsys')
comp2 = sgeom.Comp('comp2', geom)
comp2.setVol(self.v2)
comp1.addVolsys('vsys')
patch = sgeom.Patch('patch', geom, comp1, comp2)
patch.addSurfsys('ssys')
patch.setArea(self.a1)
self.mdl, self.geom, self.rng = mdl, geom, srng.create('mt19937',512)
self.rng.initialize(1234)
mdl = smodel.Model()
#mdl variable for discribing model.
#create a top-level container object for our model this top model
#container is required for all simulations in STEPS.
molX1bar = smodel.Spec('molX1bar', mdl)
molY1 = smodel.Spec('molY1', mdl)
#create 2 steps.model.Spec objects corresponding to 2 chamical
#spicies
vsys = smodel.Volsys('vsys', mdl)
#create a volume system
#volume systems art container objects that group a number of
#stoichimetric reaction rules.
c1reac_f = smodel.Reac('c1reac_f', vsys, lhs=[molX1bar], rhs=[molY1], kcst=0.2)
#create the reaction rules themselves
#what is cicst = 0.3e6?
import steps.geom as swm
#import the geometry module that contains the objects used to
#define the geometry, namely steps.geom.
wmgeom = swm.Geom()
#generate parent container object
comp = swm.Comp('comp', wmgeom)
comp.addVolsys('vsys')
comp.setVol(1.6667e-27)
#To this symple model, we only create one compartment and we
#store it in the variable called comp.
def setUp(self):
mdl = smodel.Model()
S1 = smodel.Spec('S1', mdl)
vsys = smodel.Volsys('vsys', mdl)
ssys = smodel.Surfsys('ssys', mdl)
smodel.Reac('R01', vsys, lhs=[S1], rhs=[S1], kcst=1)
smodel.SReac('SR01', ssys, slhs=[S1], srhs=[S1], kcst=1)
vrange = [-200.0e-3, 50e-3, 1e-3]
vrate = lambda v: 2.0
Chan1 = smodel.Chan('Chan1', mdl)
chanop = smodel.ChanState('chanop', mdl, Chan1)
chancl = smodel.ChanState('chancl', mdl, Chan1)
smodel.VDepSReac('VDSR01',
ssys,
slhs=[chancl],
srhs=[chanop],
k=vrate,
vrange=vrange)
smodel.VDepSReac('VDSR02',
ssys,
srhs=[chancl],
slhs=[chanop],
k=vrate,
vrange=vrange)
Chan1_Ohm_I = smodel.OhmicCurr('Chan1_Ohm_I',
ssys,
chanstate=chanop,
g=20e-12,
erev=-77e-3)
if __name__ == "__main__":
self.mesh = meshio.importAbaqus('meshes/test.inp', 1e-7)[0]
else:
self.mesh = meshio.importAbaqus(
'missing_solver_methods_test/meshes/test.inp', 1e-7)[0]
comp1 = sgeom.TmComp('comp1', self.mesh, range(self.mesh.countTets()))
comp1.addVolsys('vsys')
patch1 = sgeom.TmPatch('patch1', self.mesh, self.mesh.getSurfTris(),
comp1)
patch1.addSurfsys('ssys')
self.c1ROIInds = range(10)
self.p1ROIInds = range(5)
self.mesh.addROI('comp1ROI', sgeom.ELEM_TET, self.c1ROIInds)
self.mesh.addROI('patch1ROI', sgeom.ELEM_TRI, self.p1ROIInds)
membrane = sgeom.Memb('membrane', self.mesh, [patch1], opt_method=1)
rng = srng.create('mt19937', 512)
rng.initialize(1234)
self.sim = ssolver.Tetexact(mdl, self.mesh, rng, True)
self.sim.setEfieldDT(1e-4)
self.sim.reset()
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # STEPS - STochastic Engine for Pathway Simulation # Copyright (C) 2007-2011 Okinawa Institute of Science and Technology, Japan. # Copyright (C) 2003-2006 University of Antwerp, Belgium. # # See the file AUTHORS for details. # # This file is part of STEPS. # # STEPS 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 3 of the License, or # (at your option) any later version. # # STEPS 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, see <http://www.gnu.org/licenses/>. # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # import steps.model as smod import steps.geom as sgeom import steps.rng as srng import steps.solver as ssolv import math import time import steps.utilities.meshio as smeshio
INT = 1.1 # Sim endtime
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance = 1.0 / 100
########################################################################
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
C = smod.Spec('C', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A, B], rhs=[C], kcst=KCST)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 512)
import random
#rng.initialize(int(time.time()%4294967295))
import random
rng.initialize(int(random.random() * 1000))
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
Ob = smodel.Spec('Ob', mdl)
Oc = smodel.Spec('Oc', mdl)
Ia = smodel.Spec('Ia', mdl)
Ib = smodel.Spec('Ib', mdl)
A01 = smodel.Spec('A01', mdl)
Pa = smodel.Spec('Pa', mdl)
Pb = smodel.Spec('Pb', mdl)
Pc = smodel.Spec('Pc', mdl)
Sa = smodel.Spec('Sa', mdl)
Sb = smodel.Spec('Sb', mdl)
#create the volume system
vsys = smodel.Volsys('vsys', mdl)
#the forward reaction without the forward binding reaction
A11_to_Oa_f = smodel.Reac('A11_to_Oa_f', vsys, lhs = [A11], rhs = [Oa], kcst = 1800)
Oa_to_Ob_f = smodel.Reac('Oa_to_Ob_f', vsys, lhs = [Oa], rhs = [Ob], kcst = 133)
Oc_to_Ia_f = smodel.Reac('Oc_to_Ia_f', vsys, lhs = [Oc], rhs = [Ia], kcst = 630)
A01_to_Pa_f = smodel.Reac('A01_to_Pa_f', vsys, lhs = [A01], rhs = [Pa], kcst = 0.3)
Pa_to_Pb_f = smodel.Reac('Pa_to_Pb_f', vsys, lhs = [Pa], rhs = [Pb], kcst = 500)
Pc_to_Sa_f = smodel.Reac('Pc_to_Sa_f', vsys, lhs = [Pc], rhs = [Sa], kcst = 3000)
#the backward reaction without the backrward unbinding reaction
A11_to_Oa_b = smodel.Reac('A11_to_Oa_b', vsys, lhs = [Oa], rhs = [A11], kcst = 330)
Oa_to_Ob_b = smodel.Reac('Oa_to_Ob_b', vsys, lhs = [Ob], rhs = [Oa], kcst = 1500)
Oc_to_Ia_b = smodel.Reac('Oc_to_Ia_b', vsys, lhs = [Ia], rhs = [Oc], kcst = 400)
A01_to_Pa_b = smodel.Reac('A01_to_Pa_b', vsys, lhs = [Pa], rhs = [A01], kcst = 700)
Pa_to_Pb_b = smodel.Reac('Pa_to_Pb_b', vsys, lhs = [Pb], rhs = [Pa], kcst = 100)
Pc_to_Sa_b = smodel.Reac('Pc_to_Sa_b', vsys, lhs = [Sa], rhs = [Pc], kcst = 250)
#surface system
PumpD_f.setKcst(P_f_kcst)
PumpD_b = smodel.SReac('PumpD_b',
ssys_det,
slhs=[CaPump],
irhs=[Ca_det],
srhs=[Pump])
PumpD_b.setKcst(P_b_kcst)
PumpD_k = smodel.SReac('PumpD_k', ssys_det, slhs=[CaPump], srhs=[Pump])
PumpD_k.setKcst(P_k_kcst)
#iCBsf-fast
iCBsf1_f = smodel.Reac('iCBsf1_f',
vsys_det,
lhs=[Ca_det, iCBsf],
rhs=[iCBsCa],
kcst=iCBsf1_f_kcst)
iCBsf1_b = smodel.Reac('iCBsf1_b',
vsys_det,
lhs=[iCBsCa],
rhs=[Ca_det, iCBsf],
kcst=iCBsf1_b_kcst)
#iCBsCa
iCBsCa_f = smodel.Reac('iCBsCa_f',
vsys_det,
lhs=[Ca_det, iCBsCa],
rhs=[iCBCaCa],
kcst=iCBsCa_f_kcst)
iCBsCa_b = smodel.Reac('iCBsCa_b',
def getModel():
# Create model container
mdl = smod.Model()
# Create chemical species
ca = smod.Spec('ca', mdl)
ip3 = smod.Spec('ip3', mdl)
plc = smod.Spec('plc', mdl)
# Create calcium buffers
GCaMP6s = smod.Spec('GCaMP6s', mdl)
ca_GCaMP6s = smod.Spec('ca_GCaMP6s', mdl)
# Create IP3R states species
unb_IP3R = smod.Spec('unb_IP3R', mdl)
ip3_IP3R = smod.Spec('ip3_IP3R', mdl)
caa_IP3R = smod.Spec('caa_IP3R', mdl)
cai_IP3R = smod.Spec('cai_IP3R', mdl)
open_IP3R = smod.Spec('open_IP3R', mdl)
cai_ip3_IP3R = smod.Spec('cai_ip3_IP3R', mdl)
ca2_IP3R = smod.Spec('ca2_IP3R', mdl)
ca2_ip3_IP3R = smod.Spec('ca2_ip3_IP3R', mdl)
# ER surface sys
ssys = smod.Surfsys('ssys', mdl)
# plasma membrane surface
mb_surf = smod.Surfsys('mb_surf', mdl)
# Create volume system
# cytosol volume system
vsys = smod.Volsys('vsys', mdl)
# ER volume system
er_vsys = smod.Volsys('er_vsys', mdl)
##################################
##### DEFINE DIFFUSION RULES #####
##################################
# Diffusion constants
# Diffusion constant of Calcium (buffered)
DCST = 0.013e-9
# Diffusion constant of IP3
DIP3 = 0.280e-9
# Diffusion constant of GCaMP6s
DGCAMP = 0.050e-9
diff_freeca = smod.Diff('diff_freeca', vsys, ca, DCST)
diff_ip3 = smod.Diff('diff_ip3', vsys, ip3, DIP3)
diff_GCaMP6s = smod.Diff('diff_GCaMP6s', vsys, GCaMP6s, DGCAMP)
diff_ca_GCaMP6s = smod.Diff('diff_ca_GCaMP6s', vsys, ca_GCaMP6s, DGCAMP)
##################################
######## DEFINE REACTIONS ########
##################################
#### Calcium in and out and Buffering Reactions ####
# Ca -> null
ca_deg = smod.Reac('ca_deg', vsys, lhs=[ca])
# Ca leak
ca_leak = smod.Reac('ca_leak', vsys, rhs=[ca])
# Calcium binding to GCaMP6s molecules
GCaMP6s_bind_ca_f = smod.Reac('GCaMP6s_bind_ca_f', vsys, \
lhs=[ca, GCaMP6s], rhs=[ca_GCaMP6s])
GCaMP6s_bind_ca_b = smod.Reac('GCaMP6s_bind_ca_b', vsys, \
lhs=[ca_GCaMP6s], rhs=[GCaMP6s, ca])
#### IP3 Influx and Buffering Reactions ######
# IP3 leak
ip3_leak = smod.Reac('ip3_leak', vsys, rhs=[ip3])
# IP3 degradation
ip3_deg = smod.Reac('ip3_deg', vsys, lhs=[ip3])
# ca activating plc_delta-dependent IP3 synthesis
plc_ip3_synthesis = smod.SReac('plc_ip3_synthesis', mb_surf, \
slhs=[plc], ilhs= [ca], srhs=[plc], irhs= [ca, ip3])
##### IP3R kinetics #####
# surface/volume reaction ca from cytosol binds activating IP3R site on unbound IP3R
unb_IP3R_bind_caa_f = smod.SReac('unb_IP3R_bind_caa_f', ssys,\
ilhs=[ca], slhs=[unb_IP3R], srhs=[caa_IP3R])
unb_IP3R_bind_caa_b = smod.SReac('unb_IP3R_bind_caa_b', ssys, \
slhs=[caa_IP3R], srhs=[unb_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds inactivating IP3R site on unbound IP3R
unb_IP3R_bind_cai_f = smod.SReac('unb_IP3R_bind_cai_f', ssys, \
ilhs=[ca], slhs=[unb_IP3R], srhs=[cai_IP3R])
unb_IP3R_bind_cai_b = smod.SReac('unb_IP3R_bind_cai_b', ssys, \
slhs=[cai_IP3R], srhs=[unb_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds activating IP3R site on caa_IP3R
caa_IP3R_bind_ca_f = smod.SReac('caa_IP3R_bind_ca_f', ssys, \
ilhs=[ca], slhs=[caa_IP3R], srhs=[ca2_IP3R])
caa_IP3R_bind_ca_b = smod.SReac('caa_IP3R_bind_ca_b', ssys, \
slhs=[ca2_IP3R], srhs=[caa_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds activating IP3R site on ip3_IP3R
ip3_IP3R_bind_caa_f = smod.SReac('ip3_IP3R_bind_caa_f', ssys, \
ilhs=[ca], slhs=[ip3_IP3R], srhs=[open_IP3R])
ip3_IP3R_bind_caa_b = smod.SReac('ip3_IP3R_bind_caa_b', ssys, \
slhs=[open_IP3R], srhs=[ip3_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds inactivating IP3R site on ip3_IP3R
ip3_IP3R_bind_cai_f = smod.SReac('ip3_IP3R_bind_cai_f', ssys, \
ilhs=[ca], slhs=[ip3_IP3R], srhs=[cai_ip3_IP3R])
ip3_IP3R_bind_cai_b = smod.SReac('ip3_IP3R_bind_cai_b', ssys, \
slhs=[cai_ip3_IP3R], srhs=[ip3_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds activating IP3R site on cai_IP3R
cai_IP3R_bind_ca_f = smod.SReac('cai_IP3R_bind_ca_f', ssys, \
ilhs=[ca], slhs=[cai_IP3R], srhs=[ca2_IP3R])
cai_IP3R_bind_ca_b = smod.SReac('cai_IP3R_bind_ca_b', ssys, \
slhs=[ca2_IP3R], srhs=[cai_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds inactivating IP3R site on open_IP3R
open_IP3R_bind_ca_f = smod.SReac('open_IP3R_bind_ca_f', ssys, \
ilhs=[ca], slhs=[open_IP3R], srhs=[ca2_ip3_IP3R])
open_IP3R_bind_ca_b = smod.SReac('open_IP3R_bind_ca_b', ssys, \
slhs=[ca2_ip3_IP3R], srhs=[open_IP3R], irhs=[ca])
# surface/volume reaction ca from cytosol binds activating IP3R site on cai_ip3_IP3R
cai_ip3_IP3R_bind_ca_f = smod.SReac('cai_ip3_IP3R_bind_ca_f', ssys, \
ilhs=[ca], slhs=[cai_ip3_IP3R], srhs=[ca2_ip3_IP3R])
cai_ip3_IP3R_bind_ca_b = smod.SReac('cai_ip3_IP3R_bind_ca_b', ssys, \
slhs=[ca2_ip3_IP3R], srhs=[cai_ip3_IP3R], irhs=[ca])
# surface/volume reaction ip3 from cytosol binds unb_IP3R
unb_IP3R_bind_ip3_f = smod.SReac('unb_IP3R_bind_ip3_f', ssys, \
ilhs=[ip3], slhs=[unb_IP3R], srhs=[ip3_IP3R])
unb_IP3R_bind_ip3_b = smod.SReac('unb_IP3R_bind_ip3_b', ssys, \
slhs=[ip3_IP3R], srhs=[unb_IP3R], irhs=[ip3])
# surface/volume reaction ip3 from cytosol binds caa_IP3R
caa_IP3R_bind_ip3_f = smod.SReac('caa_IP3R_bind_ip3_f', ssys, \
ilhs=[ip3], slhs=[caa_IP3R], srhs=[open_IP3R])
caa_IP3R_bind_ip3_b = smod.SReac('caa_IP3R_bind_ip3_b', ssys, \
slhs=[open_IP3R], srhs=[caa_IP3R], irhs=[ip3])
# surface/volume reaction ip3 from cytosol binds cai_IP3R
cai_IP3R_bind_ip3_f = smod.SReac('cai_IP3R_bind_ip3_f', ssys, \
ilhs=[ip3], slhs=[cai_IP3R], srhs=[cai_ip3_IP3R])
cai_IP3R_bind_ip3_b = smod.SReac('cai_IP3R_bind_ip3_b', ssys, \
slhs=[cai_ip3_IP3R], srhs=[cai_IP3R], irhs=[ip3])
# surface/volume reaction ip3 from cytosol binds ca2_IP3R
ca2_IP3R_bind_ip3_f = smod.SReac('ca2_IP3R_bind_ip3_f', ssys, \
ilhs=[ip3], slhs=[ca2_IP3R], srhs=[ca2_ip3_IP3R])
ca2_IP3R_bind_ip3_b = smod.SReac('ca2_IP3R_bind_ip3_b', ssys, \
slhs=[ca2_ip3_IP3R], srhs=[ca2_IP3R], irhs=[ip3])
##### Ca ions passing through open IP3R channel to cytosol #####
Ca_IP3R_flux = smod.SReac('R_Ca_channel_f', ssys, \
slhs=[open_IP3R], irhs=[ca], srhs=[open_IP3R])
##################################
#### REACTION CONSTANT VALUES ####
##################################
##### Calcium Influx and Buffering Reactions #####
# GCaMP6s mediated calcium buffering
GCaMP6s_bind_ca_f.setKcst(7.78e6)
GCaMP6s_bind_ca_b.setKcst(1.12)
############# VALUES FOR GCAMP6f #################
#### GCaMP6s_bind_ca_f.setKcst(1.05e7) ####
#### GCaMP6s_bind_ca_b.setKcst(3.93) ####
##################################################
# Ca -> null
ca_deg.setKcst(30)
# Ca leak
ca_leak.setKcst(15e-8)
##### IP3 Influx and Buffering Reactions #####
# IP3 leak does not exist in this model. IP3 synthesis only occurs through PLC activity
# IP3 -> null
ip3_deg.setKcst(1.2e-4)
# ca activating plc_delta-dependent IP3 synthesis
plc_ip3_synthesis.setKcst(1)
#### IP3R kinetics #####
caa_f = 1.2e6
cai_f = 1.6e4
ip3_f = 4.1e7
caa_b = 5e1
cai_b = 1e2
ip3_b = 4e2
unb_IP3R_bind_caa_f.setKcst(caa_f)
unb_IP3R_bind_caa_b.setKcst(caa_b)
unb_IP3R_bind_cai_f.setKcst(cai_f)
unb_IP3R_bind_cai_b.setKcst(cai_b)
caa_IP3R_bind_ca_f.setKcst(cai_f)
caa_IP3R_bind_ca_b.setKcst(cai_b)
ip3_IP3R_bind_caa_f.setKcst(caa_f)
ip3_IP3R_bind_caa_b.setKcst(caa_b)
ip3_IP3R_bind_cai_f.setKcst(cai_f)
ip3_IP3R_bind_cai_b.setKcst(cai_b)
cai_IP3R_bind_ca_f.setKcst(caa_f)
cai_IP3R_bind_ca_b.setKcst(caa_b)
open_IP3R_bind_ca_f.setKcst(cai_f)
open_IP3R_bind_ca_b.setKcst(cai_b)
unb_IP3R_bind_ip3_f.setKcst(ip3_f)
unb_IP3R_bind_ip3_b.setKcst(ip3_b)
caa_IP3R_bind_ip3_f.setKcst(ip3_f)
caa_IP3R_bind_ip3_b.setKcst(ip3_b)
cai_IP3R_bind_ip3_f.setKcst(ip3_f)
cai_IP3R_bind_ip3_b.setKcst(ip3_b)
cai_ip3_IP3R_bind_ca_f.setKcst(caa_f)
cai_ip3_IP3R_bind_ca_b.setKcst(caa_b)
ca2_IP3R_bind_ip3_f.setKcst(ip3_f)
ca2_IP3R_bind_ip3_b.setKcst(ip3_b)
# Ca ions passing through open IP3R channel
Ca_IP3R_flux.setKcst(6e3)
return mdl
NITER = 100000 # The number of iterations
DT = 0.1 # Sampling time-step
INT = 1.1 # Sim endtime
# Tolerance for the comparison:
# In test runs, with good code, < 1% will fail with a 1.5% tolerance
tolerance = 2.0 / 100
########################################################################
mdl = smod.Model()
A = smod.Spec('A', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A], rhs=[], kcst=KCST)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 1000)
rng.initialize(int(time.time() % 4294967295))
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_m = numpy.zeros([NITER, ntpnts, 1])
def test_kis_ode():
"Reaction-diffusion - Degradation-diffusion (TetODE)"
NITER = 1 # The number of iterations
DT = 0.01 # Sampling time-step
INT = 0.11 # Sim endtime
DCSTA = 400 * 1e-12
DCSTB = DCSTA
RCST = 100000.0e6
NA0 = 10000 # Initial number of A molecules
NB0 = NA0 # Initial number of B molecules
SAMPLE = 5000
# create the array of tet indices to be found at random
tetidxs = np.zeros(SAMPLE, dtype='int')
# further create the array of tet barycentre distance to centre
tetrads = np.zeros(SAMPLE)
#Small expected error
tolerance = 1.5 / 100
########################################################################
rng = srng.create('r123', 512)
rng.initialize(1000) # The max unsigned long
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A, B], rhs=[])
R1.setKcst(RCST)
D_a = smod.Diff('D_a', volsys, A)
D_a.setDcst(DCSTA)
D_b = smod.Diff('D_b', volsys, B)
D_b.setDcst(DCSTB)
mesh = meshio.loadMesh('validation_rd/meshes/brick_40_4_4_STEPS')[0]
ntets = mesh.countTets()
VOLA = mesh.getMeshVolume() / 2.0
VOLB = VOLA
comp1 = sgeom.TmComp('comp1', mesh, range(ntets))
comp1.addVolsys('vsys')
# Now fill the array holding the tet indices to sample at random
assert (SAMPLE <= ntets)
numfilled = 0
while (numfilled < SAMPLE):
if (ntets != SAMPLE):
max = mesh.getBoundMax()
min = mesh.getBoundMin()
rnx = rng.getUnfII()
rny = rng.getUnfII()
rnz = rng.getUnfII()
xpnt = min[0] + (max[0] - min[0]) * rnx
ypnt = min[1] + (max[1] - min[1]) * rny
zpnt = min[2] + (max[2] - min[2]) * rnz
idx = mesh.findTetByPoint([xpnt, ypnt, zpnt])
if (idx == -1): continue
if (idx not in tetidxs):
tetidxs[numfilled] = idx
numfilled += 1
else:
tetidxs[numfilled] = numfilled
numfilled += 1
tetidxs.sort()
# Now find the distance of the centre of the tets to the Z lower face
for i in range(SAMPLE):
baryc = mesh.getTetBarycenter(int(tetidxs[i]))
r = baryc[0]
tetrads[i] = r * 1e6
Atets = []
Btets = []
for t in range(ntets):
baryx = mesh.getTetBarycenter(t)[0]
if (baryx < 0.0):
Atets.append(t)
continue
if (baryx >= 0.0):
Btets.append(t)
continue
assert (False)
sim = ssolv.TetODE(mdl, mesh, rng)
sim.setTolerances(1.0e-3, 1.0e-3)
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
resA = np.zeros((NITER, ntpnts, SAMPLE))
resB = np.zeros((NITER, ntpnts, SAMPLE))
for i in range(0, NITER):
sim.setCompCount('comp1', 'A', 2 * NA0)
sim.setCompCount('comp1', 'B', 2 * NB0)
for t in Btets:
sim.setTetCount(t, 'A', 0)
for t in Atets:
sim.setTetCount(t, 'B', 0)
for t in range(0, ntpnts):
sim.run(tpnts[t])
for k in range(SAMPLE):
resA[i, t, k] = sim.getTetCount(int(tetidxs[k]), 'A')
resB[i, t, k] = sim.getTetCount(int(tetidxs[k]), 'B')
itermeansA = np.mean(resA, axis=0)
itermeansB = np.mean(resB, axis=0)
def getdetc(t, x):
N = 1000 # The number to represent infinity in the exponential calculation
L = 20e-6
concA = 0.0
for n in range(N):
concA += ((1.0 / (2 * n + 1)) * np.exp(
(-(DCSTA / (20.0e-6)) * np.power(
(2 * n + 1), 2) * np.power(np.pi, 2) * t) / (4 * L)) *
np.sin(((2 * n + 1) * np.pi * x) / (2 * L)))
concA *= ((4 * NA0 / np.pi) / (VOLA * 6.022e26)) * 1.0e6
return concA
tpnt_compare = [5, 10]
for tidx in tpnt_compare:
NBINS = 50
radmax = 0.0
radmin = 10.0
for r in tetrads:
if (r > radmax): radmax = r
if (r < radmin): radmin = r
rsec = (radmax - radmin) / NBINS
binmins = np.zeros(NBINS + 1)
tetradsbinned = np.zeros(NBINS)
r = radmin
bin_vols = np.zeros(NBINS)
for b in range(NBINS + 1):
binmins[b] = r
if (b != NBINS): tetradsbinned[b] = r + rsec / 2.0
r += rsec
bin_countsA = [None] * NBINS
bin_countsB = [None] * NBINS
for i in range(NBINS):
bin_countsA[i] = []
bin_countsB[i] = []
filled = 0
for i in range(itermeansA[tidx].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_countsA[b].append(itermeansA[tidx][i])
bin_vols[b] += sim.getTetVol(int(tetidxs[i]))
filled += 1.0
break
filled = 0
for i in range(itermeansB[tidx].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_countsB[b].append(itermeansB[tidx][i])
filled += 1.0
break
bin_concsA = np.zeros(NBINS)
bin_concsB = np.zeros(NBINS)
for c in range(NBINS):
for d in range(bin_countsA[c].__len__()):
bin_concsA[c] += bin_countsA[c][d]
for d in range(bin_countsB[c].__len__()):
bin_concsB[c] += bin_countsB[c][d]
bin_concsA[c] /= (bin_vols[c])
bin_concsA[c] *= (1.0e-3 / 6.022e23) * 1.0e6
bin_concsB[c] /= (bin_vols[c])
bin_concsB[c] *= (1.0e-3 / 6.022e23) * 1.0e6
for i in range(NBINS):
rad = abs(tetradsbinned[i]) * 1.0e-6
if (tetradsbinned[i] < -5):
# compare A
det_conc = getdetc(tpnts[tidx], rad)
steps_conc = bin_concsA[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
if (tetradsbinned[i] > 5):
# compare B
det_conc = getdetc(tpnts[tidx], rad)
steps_conc = bin_concsB[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
def model(tissue):
""" initialises model using tissue array """
mdl = smodel.Model()
unique_p = []
for cell in tissue:
[unique_p.append(p) for p in cell.prtcl_names if p not in unique_p]
NP = []
NPi = []
NPR = []
# Create particles and corresponding species
for p in unique_p:
# Free NPs
NP.append(smodel.Spec('N{}'.format(p), mdl))
# internalised NPs
NPi.append(smodel.Spec('N{}i'.format(p), mdl))
# complexes state: NPs bound to a cell receptor
# NPR.append(smodel.Spec('N{}R'.format(p), mdl))
# receptor state: 'naive' state (no bound NPs)
R = smodel.Spec('R', mdl)
NPR = smodel.Spec('NPR', mdl)
d = {}
rxn_ = {}
dfsn_ = {}
# Lpop where cell and particle properties are connected to reactions
for n, cell in enumerate(tissue):
for p_idx, p in enumerate(unique_p):
tag = str(n) + p
prtcl = getattr(cell, p)
d["surfsys{}".format(tag)] = smodel.Surfsys(
"surfsys{}".format(tag), mdl)
d["volsys{}".format(tag)] = smodel.Volsys("volsys{}".format(tag),
mdl)
k_diff = prtcl['D'] / (float(cell.S) * float(cell.S))
dfsn_["frwd_{}".format(tag)] = smodel.SReac(
"frwd_{}".format(tag),
d["surfsys{}".format(tag)],
ilhs=[NP[p_idx]],
orhs=[NP[p_idx]],
kcst=k_diff)
dfsn_["bkwd_{}".format(tag)] = smodel.SReac(
"bkwd_{}".format(tag),
d["surfsys{}".format(tag)],
olhs=[NP[p_idx]],
irhs=[NP[p_idx]],
kcst=k_diff)
# binding reactions:
if 'k_a' in prtcl:
k_bind = prtcl['k_a']
k_unbind = prtcl['k_d']
k_intern = prtcl['k_i']
rxn_["bind_{}".format(tag)] = smodel.Reac(
"bind_{}".format(tag),
d["volsys{}".format(tag)],
lhs=[NP[p_idx], R],
rhs=[NPR],
kcst=k_bind)
rxn_["unbind_{}".format(tag)] = smodel.Reac(
"unbind_{}".format(tag),
d["volsys{}".format(tag)],
lhs=[NPR],
rhs=[NP[p_idx], R],
kcst=k_unbind)
rxn_["intern_{}".format(tag)] = smodel.Reac(
"intern_{}".format(tag),
d["volsys{}".format(tag)],
lhs=[NPR],
rhs=[NPi[p_idx], R],
kcst=k_intern)
# Diffusion
dfsn1 = smodel.Diff('dfsn1',
d["volsys{}".format(tag)],
NP[p_idx],
dcst=k_diff)
dfsn2 = smodel.Diff('dfsn2',
d["volsys{}".format(tag)],
NPR,
dcst=k_diff)
dfsn3 = smodel.Diff('dfsn3',
d["volsys{}".format(tag)],
R,
dcst=k_diff)
dfsn4 = smodel.Diff('dfsn4',
d["volsys{}".format(tag)],
NPi[p_idx],
dcst=k_diff)
return mdl
########################################################################
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys',mdl)
diffA = smod.Diff('diffA', volsys, A)
diffA.setDcst(DCST_A)
diffB = smod.Diff('diffB', volsys, B)
diffB.setDcst(DCST_B)
# Production
R1 = smod.Reac('R1', volsys, lhs = [A, B], rhs = [B], kcst = KCST_f)
R2 = smod.Reac('R2', volsys, lhs = [], rhs = [A], kcst = KCST_b)
geom = meshio.loadMesh('./validation_rd/meshes/'+filename)[0]
comp1 = sgeom.TmComp('comp1', geom, range(geom.ntets))
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 512)
rng.initialize(int(time.time()%4294967295))
sim = ssolv.Tetexact(mdl, geom, rng)
sim.reset()
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
kcst=k3_pmca)
PMCA_leak = smodel.SReac('PMCA_leak',
surfsys0,
slhs=[PMCA_P0],
srhs=[PMCA_P0],
irhs=[Ca],
kcst=kl_pmca)
# ////////////////////////////////////////////////////////////////////////////////////////////////////////
PV = smodel.Spec('PV', model)
PV_Ca = smodel.Spec('PV_Ca', model)
PV_2Ca = smodel.Spec('PV_2Ca', model)
kreac_f_PV_Ca = smodel.Reac('kreac_f_PV_Ca',
vsys0,
lhs=[PV, Ca],
rhs=[PV_Ca],
kcst=107e6)
kreac_b_PV_Ca = smodel.Reac('kreac_b_PV_Ca',
vsys0,
lhs=[PV_Ca],
rhs=[PV, Ca],
kcst=0.95)
kreac_f_PV_2Ca = smodel.Reac('kreac_f_PV_2Ca',
vsys0,
lhs=[PV_Ca, Ca],
rhs=[PV_2Ca],
kcst=107e6)
kreac_b_PV_2Ca = smodel.Reac('kreac_b_PV_2Ca',
vsys0,
tetrads = numpy.zeros(SAMPLE)
########################################################################
rng = srng.create('mt19937', 512)
rng.initialize(int(time.time()%4294967295)) # The max unsigned long
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys',mdl)
R1 = smod.Reac('R1', volsys, lhs = [A,B], rhs = [])
R1.setKcst(RCST)
D_a = smod.Diff('D_a', volsys, A)
D_a.setDcst(DCSTA)
D_b = smod.Diff('D_b', volsys, B)
D_b.setDcst(DCSTB)
mesh = meshio.loadMesh('./validation_rd/meshes/brick_40_4_4_1686tets')[0]
VOLA = mesh.getMeshVolume()/2.0
VOLB = VOLA
ntets = mesh.countTets()
def test_kisilevich():
"Reaction-diffusion - Degradation-diffusion (Parallel TetOpSplit)"
NITER = 50 # The number of iterations
DT = 0.1 # Sampling time-step
INT = 0.3 # Sim endtime
DCSTA = 400 * 1e-12
DCSTB = DCSTA
RCST = 100000.0e6
#NA0 = 100000 # 1000000 # Initial number of A molecules
NA0 = 1000
NB0 = NA0 # Initial number of B molecules
SAMPLE = 1686
# <1% fail with a tolerance of 7.5%
tolerance = 7.5 / 100
# create the array of tet indices to be found at random
tetidxs = numpy.zeros(SAMPLE, dtype='int')
# further create the array of tet barycentre distance to centre
tetrads = numpy.zeros(SAMPLE)
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys', mdl)
R1 = smod.Reac('R1', volsys, lhs=[A, B], rhs=[])
R1.setKcst(RCST)
D_a = smod.Diff('D_a', volsys, A)
D_a.setDcst(DCSTA)
D_b = smod.Diff('D_b', volsys, B)
D_b.setDcst(DCSTB)
mesh = meshio.loadMesh('validation_rd_mpi/meshes/brick_40_4_4_1686tets')[0]
VOLA = mesh.getMeshVolume() / 2.0
VOLB = VOLA
ntets = mesh.countTets()
acomptets = []
bcomptets = []
max = mesh.getBoundMax()
min = mesh.getBoundMax()
midz = 0.0
compatris = set()
compbtris = set()
for t in range(ntets):
barycz = mesh.getTetBarycenter(t)[0]
tris = mesh.getTetTriNeighb(t)
if barycz < midz:
acomptets.append(t)
compatris.add(tris[0])
compatris.add(tris[1])
compatris.add(tris[2])
compatris.add(tris[3])
else:
bcomptets.append(t)
compbtris.add(tris[0])
compbtris.add(tris[1])
compbtris.add(tris[2])
compbtris.add(tris[3])
dbset = compatris.intersection(compbtris)
dbtris = list(dbset)
compa = sgeom.TmComp('compa', mesh, acomptets)
compb = sgeom.TmComp('compb', mesh, bcomptets)
compa.addVolsys('vsys')
compb.addVolsys('vsys')
diffb = sgeom.DiffBoundary('diffb', mesh, dbtris)
# Now fill the array holding the tet indices to sample at random
assert (SAMPLE <= ntets)
numfilled = 0
while (numfilled < SAMPLE):
tetidxs[numfilled] = numfilled
numfilled += 1
# Now find the distance of the centre of the tets to the Z lower face
for i in range(SAMPLE):
baryc = mesh.getTetBarycenter(int(tetidxs[i]))
r = baryc[0]
tetrads[i] = r * 1.0e6
Atets = acomptets
Btets = bcomptets
rng = srng.create('r123', 512)
rng.initialize(1000)
tet_hosts = gd.binTetsByAxis(mesh, steps.mpi.nhosts)
sim = solvmod.TetOpSplit(mdl, mesh, rng, False, tet_hosts)
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
resA = numpy.zeros((NITER, ntpnts, SAMPLE))
resB = numpy.zeros((NITER, ntpnts, SAMPLE))
for i in range(0, NITER):
sim.reset()
sim.setDiffBoundaryDiffusionActive('diffb', 'A', True)
sim.setDiffBoundaryDiffusionActive('diffb', 'B', True)
sim.setCompCount('compa', 'A', NA0)
sim.setCompCount('compb', 'B', NB0)
for t in range(0, ntpnts):
sim.run(tpnts[t])
for k in range(SAMPLE):
resA[i, t, k] = sim.getTetCount(int(tetidxs[k]), 'A')
resB[i, t, k] = sim.getTetCount(int(tetidxs[k]), 'B')
itermeansA = numpy.mean(resA, axis=0)
itermeansB = numpy.mean(resB, axis=0)
def getdetc(t, x):
N = 1000 # The number to represent infinity in the exponential calculation
L = 20e-6
concA = 0.0
for n in range(N):
concA += ((1.0 / (2 * n + 1)) * math.exp(
(-(DCSTA / (20.0e-6)) * math.pow(
(2 * n + 1), 2) * math.pow(math.pi, 2) * t) / (4 * L)) *
math.sin(((2 * n + 1) * math.pi * x) / (2 * L)))
concA *= ((4 * NA0 / math.pi) / (VOLA * 6.022e26)) * 1.0e6
return concA
tpnt_compare = [1, 2]
passed = True
max_err = 0.0
for tidx in tpnt_compare:
NBINS = 10
radmax = 0.0
radmin = 10.0
for r in tetrads:
if (r > radmax): radmax = r
if (r < radmin): radmin = r
rsec = (radmax - radmin) / NBINS
binmins = numpy.zeros(NBINS + 1)
tetradsbinned = numpy.zeros(NBINS)
r = radmin
bin_vols = numpy.zeros(NBINS)
for b in range(NBINS + 1):
binmins[b] = r
if (b != NBINS): tetradsbinned[b] = r + rsec / 2.0
r += rsec
bin_countsA = [None] * NBINS
bin_countsB = [None] * NBINS
for i in range(NBINS):
bin_countsA[i] = []
bin_countsB[i] = []
filled = 0
for i in range(itermeansA[tidx].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_countsA[b].append(itermeansA[tidx][i])
bin_vols[b] += sim.getTetVol(int(tetidxs[i]))
filled += 1.0
break
filled = 0
for i in range(itermeansB[tidx].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_countsB[b].append(itermeansB[tidx][i])
filled += 1.0
break
bin_concsA = numpy.zeros(NBINS)
bin_concsB = numpy.zeros(NBINS)
for c in range(NBINS):
for d in range(bin_countsA[c].__len__()):
bin_concsA[c] += bin_countsA[c][d]
for d in range(bin_countsB[c].__len__()):
bin_concsB[c] += bin_countsB[c][d]
bin_concsA[c] /= (bin_vols[c])
bin_concsA[c] *= (1.0e-3 / 6.022e23) * 1.0e6
bin_concsB[c] /= (bin_vols[c])
bin_concsB[c] *= (1.0e-3 / 6.022e23) * 1.0e6
for i in range(NBINS):
rad = abs(tetradsbinned[i]) * 1.0e-6
if (tetradsbinned[i] < -5):
# compare A
det_conc = getdetc(tpnts[tidx], rad)
steps_conc = bin_concsA[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
if (tetradsbinned[i] > 5):
# compare B
det_conc = getdetc(tpnts[tidx], rad)
steps_conc = bin_concsB[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
def run_sim():
# Set up and run the simulations once, before the tests
# analyze the results.
##################### First order irreversible #########################
global KCST_foi, N_foi, tolerance_foi
KCST_foi = 5 # The reaction constant
N_foi = 50 # Can set count or conc
NITER_foi = 1 # The number of iterations
# Tolerance for the comparison:
tolerance_foi = 1.0e-4 / 100
####################### First order reversible #########################
global KCST_f_for, KCST_b_for, COUNT_for, tolerance_for
KCST_f_for = 20.0 # The reaction constant
KCST_b_for = 5.0
COUNT_for = 100000 # Can set count or conc
NITER_for = 1 # The number of iterations
tolerance_for = 1.0e-4 / 100
####################### Second order irreversible A2 ###################
global KCST_soA2, CONCA_soA2, tolerance_soA2
KCST_soA2 = 10.0e6 # The reaction constant
CONCA_soA2 = 10.0e-6
NITER_soA2 = 1 # The number of iterations
tolerance_soA2 = 1.0e-4 / 100
####################### Second order irreversible AA ###################
global KCST_soAA, CONCA_soAA, CONCB_soAA, tolerance_soAA
KCST_soAA = 5.0e6 # The reaction constant
CONCA_soAA = 20.0e-6
CONCB_soAA = CONCA_soAA
NITER_soAA = 1 # The number of iterations
tolerance_soAA = 1.0e-4 / 100
####################### Second order irreversible AB ###################
global KCST_soAB, CONCA_soAB, CONCB_soAB, tolerance_soAB
KCST_soAB = 5.0e6 # The reaction constant
CONCA_soAB = 1.0e-6
n_soAB = 2
CONCB_soAB = CONCA_soAB / n_soAB
NITER_soAB = 1 # The number of iterations
tolerance_soAB = 1.0e-4 / 100
####################### Third order irreversible A3 ###################
global KCST_toA3, CONCA_toA3, tolerance_toA3
KCST_toA3 = 1.0e12 # The reaction constant
CONCA_toA3 = 10.0e-6
NITER_toA3 = 1 # The number of iterations
tolerance_toA3 = 1.0e-4 / 100
####################### Third order irreversible A2B ###################
global KCST_toA2B, CONCA_toA2B, CONCB_toA2B, tolerance_toA2B
KCST_toA2B = 0.1e12 # The reaction constant
CONCA_toA2B = 30.0e-6
CONCB_toA2B = 20.0e-6
NITER_toA2B = 1 # The number of iterations
tolerance_toA2B = 1.0e-4 / 100
####################### Second order irreversible 2D ###################
global COUNTA_so2d, COUNTB_so2d, CCST_so2d, tolerance_so2d
COUNTA_so2d = 100.0
n_so2d = 2.0
COUNTB_so2d = COUNTA_so2d / n_so2d
KCST_so2d = 10.0e10 # The reaction constant
AREA_so2d = 10.0e-12
NITER_so2d = 1 # The number of iterations
tolerance_so2d = 1.0e-4 / 100
############################ Common parameters ########################
global VOL
DT = 0.1 # Sampling time-step
INT = 1.1 # Sim endtime
NITER_max = 1
########################################################################
mdl = smod.Model()
volsys = smod.Volsys('vsys', mdl)
surfsys = smod.Surfsys('ssys', mdl)
# First order irreversible
A_foi = smod.Spec('A_foi', mdl)
A_foi_diff = smod.Diff('A_foi_diff', volsys, A_foi, 0.01e-12)
R1_foi = smod.Reac('R1_foi', volsys, lhs=[A_foi], rhs=[], kcst=KCST_foi)
# First order reversible
A_for = smod.Spec('A_for', mdl)
B_for = smod.Spec('B_for', mdl)
A_for_diff = smod.Diff('A_for_diff', volsys, A_for, 0.01e-12)
B_for_diff = smod.Diff('B_for_diff', volsys, B_for, 0.01e-12)
R1_for = smod.Reac('R1_for',
volsys,
lhs=[A_for],
rhs=[B_for],
kcst=KCST_f_for)
R2_for = smod.Reac('R2_for',
volsys,
lhs=[B_for],
rhs=[A_for],
kcst=KCST_b_for)
# Second order irreversible A2
A_soA2 = smod.Spec('A_soA2', mdl)
C_soA2 = smod.Spec('C_soA2', mdl)
A_soA2_diff = smod.Diff('A_soA2_diff', volsys, A_soA2, 1e-12)
R1_soA2 = smod.Reac('R1_soA2',
volsys,
lhs=[A_soA2, A_soA2],
rhs=[C_soA2],
kcst=KCST_soA2)
# Second order irreversible AA
A_soAA = smod.Spec('A_soAA', mdl)
B_soAA = smod.Spec('B_soAA', mdl)
C_soAA = smod.Spec('C_soAA', mdl)
A_soAA_diff = smod.Diff('A_soAA_diff', volsys, A_soAA, 0.2e-12)
B_soAA_diff = smod.Diff('B_soAA_diff', volsys, B_soAA, 0.2e-12)
R1_soAA = smod.Reac('R1_soAA',
volsys,
lhs=[A_soAA, B_soAA],
rhs=[C_soAA],
kcst=KCST_soAA)
# Second order irreversible AB
A_soAB = smod.Spec('A_soAB', mdl)
B_soAB = smod.Spec('B_soAB', mdl)
C_soAB = smod.Spec('C_soAB', mdl)
A_soAB_diff = smod.Diff('A_soAB_diff', volsys, A_soAB, 0.1e-12)
B_soAB_diff = smod.Diff('B_soAB_diff', volsys, B_soAB, 0.1e-12)
R1_soAB = smod.Reac('R1_soAB',
volsys,
lhs=[A_soAB, B_soAB],
rhs=[C_soAB],
kcst=KCST_soAB)
# Third order irreversible A3
A_toA3 = smod.Spec('A_toA3', mdl)
C_toA3 = smod.Spec('C_toA3', mdl)
A_soA3_diff = smod.Diff('A_soA3_diff', volsys, A_toA3, 0.2e-12)
R1_toA3 = smod.Reac('R1_toA3',
volsys,
lhs=[A_toA3, A_toA3, A_toA3],
rhs=[C_toA3],
kcst=KCST_toA3)
# Third order irreversible A2B
A_toA2B = smod.Spec('A_toA2B', mdl)
B_toA2B = smod.Spec('B_toA2B', mdl)
C_toA2B = smod.Spec('C_toA2B', mdl)
A_soA2B_diff = smod.Diff('A_soA2B_diff', volsys, A_toA2B, 0.1e-12)
B_soA2B_diff = smod.Diff('B_soA2B_diff', volsys, B_toA2B, 0.1e-12)
R1_toA3 = smod.Reac('R1_toA2B',
volsys,
lhs=[A_toA2B, A_toA2B, B_toA2B],
rhs=[C_toA2B],
kcst=KCST_toA2B)
# Second order irreversible 2D
A_so2d = smod.Spec('A_so2d', mdl)
B_so2d = smod.Spec('B_so2d', mdl)
C_so2d = smod.Spec('C_so2d', mdl)
A_so2d_diff = smod.Diff('A_so2d_diff', surfsys, A_so2d, 1.0e-12)
B_so2d_diff = smod.Diff('B_so2d_diff', surfsys, B_so2d, 1.0e-12)
SR1_so2d = smod.SReac('SR1_so2d',
surfsys,
slhs=[A_so2d, B_so2d],
srhs=[C_so2d],
kcst=KCST_so2d)
mesh = smeshio.importAbaqus('validation_rd/meshes/sphere_rad1_37tets.inp',
1e-6)[0]
VOL = mesh.getMeshVolume()
comp1 = sgeom.TmComp('comp1', mesh, range(mesh.ntets))
comp1.addVolsys('vsys')
patch1 = sgeom.TmPatch('patch1', mesh, mesh.getSurfTris(), comp1)
patch1.addSurfsys('ssys')
CCST_so2d = KCST_so2d / (6.02214179e23 * patch1.getArea())
rng = srng.create('r123', 512)
rng.initialize(1000)
sim = ssolv.TetODE(mdl, mesh, rng)
sim.setTolerances(1e-9, 1e-7)
global tpnts, ntpnts
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_m_foi = numpy.zeros([NITER_foi, ntpnts, 1])
res_m_for = numpy.zeros([NITER_for, ntpnts, 2])
res_m_soA2 = numpy.zeros([NITER_soA2, ntpnts, 2])
res_m_soAA = numpy.zeros([NITER_soAA, ntpnts, 3])
res_m_soAB = numpy.zeros([NITER_soAB, ntpnts, 3])
res_m_toA3 = numpy.zeros([NITER_toA3, ntpnts, 2])
res_m_toA2B = numpy.zeros([NITER_toA2B, ntpnts, 3])
res_m_so2d = numpy.zeros([NITER_so2d, ntpnts, 3])
for i in range(0, NITER_max):
if i < NITER_foi:
sim.setCompCount('comp1', 'A_foi', N_foi)
if i < NITER_for:
sim.setCompCount('comp1', 'A_for', COUNT_for)
sim.setCompCount('comp1', 'B_for', 0.0)
if i < NITER_soA2:
sim.setCompConc('comp1', 'A_soA2', CONCA_soA2)
if i < NITER_soAA:
sim.setCompConc('comp1', 'A_soAA', CONCA_soAA)
sim.setCompConc('comp1', 'B_soAA', CONCB_soAA)
if i < NITER_soAB:
sim.setCompConc('comp1', 'A_soAB', CONCA_soAB)
sim.setCompConc('comp1', 'B_soAB', CONCB_soAB)
if i < NITER_toA3:
sim.setCompConc('comp1', 'A_toA3', CONCA_toA3)
if i < NITER_toA2B:
sim.setCompConc('comp1', 'A_toA2B', CONCA_toA2B)
sim.setCompConc('comp1', 'B_toA2B', CONCB_toA2B)
if i < NITER_so2d:
sim.setPatchCount('patch1', 'A_so2d', COUNTA_so2d)
sim.setPatchCount('patch1', 'B_so2d', COUNTB_so2d)
for t in range(0, ntpnts):
sim.run(tpnts[t])
if i < NITER_foi:
res_m_foi[i, t, 0] = sim.getCompCount('comp1', 'A_foi')
if i < NITER_for:
res_m_for[i, t, 0] = sim.getCompConc('comp1', 'A_for') * 1e6
res_m_for[i, t, 1] = sim.getCompConc('comp1', 'B_for') * 1e6
if i < NITER_soA2:
res_m_soA2[i, t, 0] = sim.getCompConc('comp1', 'A_soA2')
if i < NITER_soAA:
res_m_soAA[i, t, 0] = sim.getCompConc('comp1', 'A_soAA')
res_m_soAA[i, t, 1] = sim.getCompConc('comp1', 'B_soAA')
if i < NITER_soAB:
res_m_soAB[i, t, 0] = sim.getCompConc('comp1', 'A_soAB')
res_m_soAB[i, t, 1] = sim.getCompConc('comp1', 'B_soAB')
if i < NITER_toA3:
res_m_toA3[i, t, 0] = sim.getCompConc('comp1', 'A_toA3')
if i < NITER_toA2B:
res_m_toA2B[i, t, 0] = sim.getCompConc('comp1', 'A_toA2B')
res_m_toA2B[i, t, 1] = sim.getCompConc('comp1', 'B_toA2B')
res_m_toA2B[i, t, 2] = sim.getCompConc('comp1', 'C_toA2B')
if i < NITER_so2d:
res_m_so2d[i, t, 0] = sim.getPatchCount('patch1', 'A_so2d')
res_m_so2d[i, t, 1] = sim.getPatchCount('patch1', 'B_so2d')
global mean_res_foi
mean_res_foi = numpy.mean(res_m_foi, 0)
global mean_res_for
mean_res_for = numpy.mean(res_m_for, 0)
global mean_res_soA2
mean_res_soA2 = numpy.mean(res_m_soA2, 0)
global mean_res_soAA
mean_res_soAA = numpy.mean(res_m_soAA, 0)
global mean_res_soAB
mean_res_soAB = numpy.mean(res_m_soAB, 0)
global mean_res_toA3
mean_res_toA3 = numpy.mean(res_m_toA3, 0)
global mean_res_toA2B
mean_res_toA2B = numpy.mean(res_m_toA2B, 0)
global mean_res_so2d
mean_res_so2d = numpy.mean(res_m_so2d, 0)
global ran_sim
ran_sim = True
def gen_model(x, flux):
####
####
print "Create sim"
mdl = smod.Model()
# Defining chemical compartments
vsys = smod.Volsys('vsys_Cyt', mdl)
ssys = smod.Surfsys('ssys', mdl)
##
## Cytosolic molecule species
##
CYT_MOL_NUM = len(x.CYT_MOL_NAME)
CYT_MOL = []
for i in range(CYT_MOL_NUM):
print i, x.CYT_MOL_NAME[i]
ns = globals()
ns[x.CYT_MOL_NAME[i]] = smod.Spec(x.CYT_MOL_NAME[i], mdl)
# CYT_MOL.append( smod.Spec(CYT_MOL_NAME[i], mdl) )
##
## Surface molecule species
##
SUR_MOL_NUM = len(x.SUR_MOL_NAME)
SUR_MOL = []
for i in range(SUR_MOL_NUM):
print i, x.SUR_MOL_NAME[i]
ns = globals()
ns[x.SUR_MOL_NAME[i]] = smod.Spec(x.SUR_MOL_NAME[i], mdl)
##
## Cytosolic molecule reactions
##
smod.Reac('on_CB', vsys, lhs=[Ca, CB], rhs=[CBCa], kcst=x.kon_CB)
smod.Reac('of_CB', vsys, lhs=[CBCa], rhs=[Ca, CB], kcst=x.kof_CB)
smod.Reac('on_TN1', vsys, lhs=[Ca, N0C0], rhs=[N1C0], kcst=2 * x.kon_TN)
smod.Reac('of_TN1', vsys, lhs=[N1C0], rhs=[Ca, N0C0], kcst=x.kof_TN)
smod.Reac('on_RN1', vsys, lhs=[Ca, N1C0], rhs=[N2C0], kcst=x.kon_RN)
smod.Reac('of_RN1', vsys, lhs=[N2C0], rhs=[Ca, N1C0], kcst=2 * x.kof_RN)
smod.Reac('on_TN2', vsys, lhs=[Ca, N0C1], rhs=[N1C1], kcst=2 * x.kon_TN)
smod.Reac('of_TN2', vsys, lhs=[N1C1], rhs=[Ca, N0C1], kcst=x.kof_TN)
smod.Reac('on_RN2', vsys, lhs=[Ca, N1C1], rhs=[N2C1], kcst=x.kon_RN)
smod.Reac('of_RN2', vsys, lhs=[N2C1], rhs=[Ca, N1C1], kcst=2 * x.kof_RN)
smod.Reac('on_TN3', vsys, lhs=[Ca, N0C2], rhs=[N1C2], kcst=2 * x.kon_TN)
smod.Reac('of_TN3', vsys, lhs=[N1C2], rhs=[Ca, N0C2], kcst=x.kof_TN)
smod.Reac('on_RN3', vsys, lhs=[Ca, N1C2], rhs=[N2C2], kcst=x.kon_RN)
smod.Reac('of_RN3', vsys, lhs=[N2C2], rhs=[Ca, N1C2], kcst=2 * x.kof_RN)
smod.Reac('on_TC1', vsys, lhs=[Ca, N0C0], rhs=[N0C1], kcst=2 * x.kon_TC)
smod.Reac('of_TC1', vsys, lhs=[N0C1], rhs=[Ca, N0C0], kcst=x.kof_TC)
smod.Reac('on_RC1', vsys, lhs=[Ca, N0C1], rhs=[N0C2], kcst=x.kon_RC)
smod.Reac('of_RC1', vsys, lhs=[N0C2], rhs=[Ca, N0C1], kcst=2 * x.kof_RC)
smod.Reac('on_TC2', vsys, lhs=[Ca, N1C0], rhs=[N1C1], kcst=2 * x.kon_TC)
smod.Reac('of_TC2', vsys, lhs=[N1C1], rhs=[Ca, N1C0], kcst=x.kof_TC)
smod.Reac('on_RC2', vsys, lhs=[Ca, N1C1], rhs=[N1C2], kcst=x.kon_RC)
smod.Reac('of_RC2', vsys, lhs=[N1C2], rhs=[Ca, N1C1], kcst=2 * x.kof_RC)
smod.Reac('on_TC3', vsys, lhs=[Ca, N2C0], rhs=[N2C1], kcst=2 * x.kon_TC)
smod.Reac('of_TC3', vsys, lhs=[N2C1], rhs=[Ca, N2C0], kcst=x.kof_TC)
smod.Reac('on_RC3', vsys, lhs=[Ca, N2C1], rhs=[N2C2], kcst=x.kon_RC)
smod.Reac('of_RC3', vsys, lhs=[N2C2], rhs=[Ca, N2C1], kcst=2 * x.kof_RC)
##
## Ca pump and VGCC
##
smod.SReac('PA_To_PA_Ca',
ssys,
slhs=[PA],
ilhs=[Ca],
srhs=[PA_Ca],
kcst=150 * 1e6)
smod.SReac('PA_Ca_To_PA', ssys, slhs=[PA_Ca], srhs=[PA], kcst=12)
smod.SReac('Leak_To_Leak_Ca',
ssys,
slhs=[Leak],
srhs=[Leak],
irhs=[Ca],
kcst=0.015)
smod.SReac('NR_Glu_To_NR', ssys, slhs=[NR_Glu], srhs=[NR], kcst=50)
smod.SReac('NR_Glu_To_NR_O', ssys, slhs=[NR_Glu], srhs=[NR_O], kcst=200)
smod.SReac('NR_O_To_NR_Glu', ssys, slhs=[NR_O], srhs=[NR_Glu], kcst=50)
smod.SReac('NR_O_To_NR_O_Ca',
ssys,
slhs=[NR_O],
srhs=[NR_O],
irhs=[Ca],
kcst=flux)
##
## Species on left hand side: Surface (slhs), Outer comp (olhs), Inner comp (ilhs)
## Species on right hand side: Surface (srhs), Outer comp (orhs), Inner comp (irhs)
##
# Diffusion rules
smod.Diff('D_Ca', vsys, Ca, x.DCa)
smod.Diff('D_N0C0', vsys, N0C0, x.DCaM)
smod.Diff('D_N0C1', vsys, N0C1, x.DCaM)
smod.Diff('D_N0C2', vsys, N0C2, x.DCaM)
smod.Diff('D_N1C0', vsys, N1C0, x.DCaM)
smod.Diff('D_N1C1', vsys, N1C1, x.DCaM)
smod.Diff('D_N1C2', vsys, N1C2, x.DCaM)
smod.Diff('D_N2C0', vsys, N2C0, x.DCaM)
smod.Diff('D_N2C1', vsys, N2C1, x.DCaM)
smod.Diff('D_N2C2', vsys, N2C2, x.DCaM)
smod.Diff('D_CB', vsys, CB, x.DCB)
smod.Diff('D_CBCa', vsys, CBCa, x.DCB)
return mdl
def test_masteq():
"Reaction - Production and degradation (Wmdirect)"
########################################################################
KCST_f = 100 / (6.022e23 * 1.0e-15) # The reaction constant, production
KCST_b = 10 # The reaction constant, degradation
VOL = 1.0e-18
DT = 0.1 # Sampling time-step
INT = 200000.1 # Sim endtime
# Tolerance for the comparison:
# In tests with good code <1% fail with tolerance of 1.5%
tolerance = 1.5 / 100
########################################################################
mdl = smod.Model()
A = smod.Spec('A', mdl)
volsys = smod.Volsys('vsys', mdl)
# Production
R1 = smod.Reac('R1', volsys, lhs=[], rhs=[A], kcst=KCST_f)
R2 = smod.Reac('R2', volsys, lhs=[A], rhs=[], kcst=KCST_b)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
rng = srng.create('r123', 1000)
rng.initialize(1000)
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res = numpy.zeros([ntpnts])
sim.reset()
sim.setCompCount('comp1', 'A', 0)
for t in range(0, ntpnts):
sim.run(tpnts[t])
res[t] = sim.getCompCount('comp1', 'A')
def fact(x):
return (1 if x == 0 else x * fact(x - 1))
# Do cumulative count, but not comparing them all.
# Don't get over 50 (I hope)
steps_n_res = numpy.zeros(50)
for r in res:
steps_n_res[int(r)] += 1
for s in range(50):
steps_n_res[s] = steps_n_res[s] / ntpnts
passed = True
max_err = 0.0
k1 = KCST_b
k2 = KCST_f * (6.022e23 * 1.0e-15)
# Compare 5 to 15
for m in range(5, 16):
analy = (1.0 / fact(m)) * math.pow((k2 / k1), m) * math.exp(-(k2 / k1))
assert tol_funcs.tolerable(steps_n_res[m], analy, tolerance)
import steps.rng as srng
import steps.solver as ssolver
##############################
# Model Setup
##############################
mdl = smodel.Model()
molA = smodel.Spec('molA', mdl)
molB = smodel.Spec('molB', mdl)
molC = smodel.Spec('molC', mdl)
vsys = smodel.Volsys('vsys', mdl)
kreac_f = smodel.Reac('kreac_f', vsys, lhs=[molA,molB], rhs=[molC], kcst=0.3e6)
kreac_b = smodel.Reac('kreac_b', vsys, lhs=[molC], rhs=[molA,molB])
kreac_b.kcst = 0.7
##############################
# Geom Setup
##############################
wmgeom = swm.Geom()
comp = swm.Comp('comp', wmgeom)
comp.addVolsys('vsys')
comp.setVol(1.6667e-21)
##############################
# RNG Setup
##############################
def run_sim():
# Set up and run the simulations once, before the tests
# analyze the results.
##################### First order irreversible #########################
global KCST_foi, N_foi, tolerance_foi
KCST_foi = 5 # The reaction constant
N_foi = 50 # Can set count or conc
NITER_foi = 100000 # The number of iterations
# Tolerance for the comparison:
# In test runs, with good code, < 1% will fail with a 1.5% tolerance
tolerance_foi = 2.0 / 100
####################### First order reversible #########################
global KCST_f_for, KCST_b_for, COUNT_for, tolerance_for
KCST_f_for = 10.0 # The reaction constant
KCST_b_for = 2.0
COUNT_for = 100000 # Can set count or conc
NITER_for = 10 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance_for = 1.0 / 100
####################### Second order irreversible A2 ###################
global KCST_soA2, CONCA_soA2, tolerance_soA2
KCST_soA2 = 10.0e6 # The reaction constant
CONCA_soA2 = 10.0e-6
NITER_soA2 = 1000 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 2%
tolerance_soA2 = 1.0 / 100
####################### Second order irreversible AA ###################
global KCST_soAA, CONCA_soAA, CONCB_soAA, tolerance_soAA
KCST_soAA = 50.0e6 # The reaction constant
CONCA_soAA = 20.0e-6
CONCB_soAA = CONCA_soAA
NITER_soAA = 1000 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance_soAA = 1.0 / 100
####################### Second order irreversible AB ###################
global KCST_soAB, CONCA_soAB, CONCB_soAB, tolerance_soAB
KCST_soAB = 5.0e6 # The reaction constant
CONCA_soAB = 1.0e-6
n_soAB = 2
CONCB_soAB = CONCA_soAB / n_soAB
NITER_soAB = 1000 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance_soAB = 1.0 / 100
####################### Third order irreversible A3 ###################
global KCST_toA3, CONCA_toA3, tolerance_toA3
KCST_toA3 = 1.0e12 # The reaction constant
CONCA_toA3 = 100.0e-6
NITER_toA3 = 1000 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance_toA3 = 1.0 / 100
####################### Third order irreversible A2B ###################
global KCST_toA2B, CONCA_toA2B, CONCB_toA2B, tolerance_toA2B
KCST_toA2B = 0.1e12 # The reaction constant
CONCA_toA2B = 30.0e-6
CONCB_toA2B = 20.0e-6
NITER_toA2B = 1000 # The number of iterations
# In test runs, with good code, <0.1% will fail with a tolerance of 1%
tolerance_toA2B = 1.0 / 100
####################### Second order irreversible 2D ###################
global COUNTA_so2d, COUNTB_so2d, CCST_so2d, tolerance_so2d
COUNTA_so2d = 100.0
n_so2d = 2.0
COUNTB_so2d = COUNTA_so2d / n_so2d
KCST_so2d = 10.0e10 # The reaction constant
AREA_so2d = 10.0e-12
CCST_so2d = KCST_so2d / (6.02214179e23 * AREA_so2d)
NITER_so2d = 1000 # The number of iterations
# In tests fewer than 0.1% fail with tolerance of 2%
tolerance_so2d = 2.0 / 100
############################ Common parameters ########################
global VOL
DT = 0.1 # Sampling time-step
INT = 1.1 # Sim endtime
VOL = 9.0e-18
NITER_max = 100000
########################################################################
mdl = smod.Model()
volsys = smod.Volsys('vsys', mdl)
surfsys = smod.Surfsys('ssys', mdl)
# First order irreversible
A_foi = smod.Spec('A_foi', mdl)
R1_foi = smod.Reac('R1_foi', volsys, lhs=[A_foi], rhs=[], kcst=KCST_foi)
# First order reversible
A_for = smod.Spec('A_for', mdl)
B_for = smod.Spec('B_for', mdl)
R1_for = smod.Reac('R1_for',
volsys,
lhs=[A_for],
rhs=[B_for],
kcst=KCST_f_for)
R2_for = smod.Reac('R2_for',
volsys,
lhs=[B_for],
rhs=[A_for],
kcst=KCST_b_for)
# Second order irreversible A2
A_soA2 = smod.Spec('A_soA2', mdl)
C_soA2 = smod.Spec('C_soA2', mdl)
R1_soA2 = smod.Reac('R1_soA2',
volsys,
lhs=[A_soA2, A_soA2],
rhs=[C_soA2],
kcst=KCST_soA2)
# Second order irreversible AA
A_soAA = smod.Spec('A_soAA', mdl)
B_soAA = smod.Spec('B_soAA', mdl)
C_soAA = smod.Spec('C_soAA', mdl)
R1_soAA = smod.Reac('R1_soAA',
volsys,
lhs=[A_soAA, B_soAA],
rhs=[C_soAA],
kcst=KCST_soAA)
# Second order irreversible AB
A_soAB = smod.Spec('A_soAB', mdl)
B_soAB = smod.Spec('B_soAB', mdl)
C_soAB = smod.Spec('C_soAB', mdl)
R1_soAB = smod.Reac('R1_soAB',
volsys,
lhs=[A_soAB, B_soAB],
rhs=[C_soAB],
kcst=KCST_soAB)
# Third order irreversible A3
A_toA3 = smod.Spec('A_toA3', mdl)
C_toA3 = smod.Spec('C_toA3', mdl)
R1_toA3 = smod.Reac('R1_toA3',
volsys,
lhs=[A_toA3, A_toA3, A_toA3],
rhs=[C_toA3],
kcst=KCST_toA3)
# Third order irreversible A2B
A_toA2B = smod.Spec('A_toA2B', mdl)
B_toA2B = smod.Spec('B_toA2B', mdl)
C_toA2B = smod.Spec('C_toA2B', mdl)
R1_toA3 = smod.Reac('R1_toA2B',
volsys,
lhs=[A_toA2B, A_toA2B, B_toA2B],
rhs=[C_toA2B],
kcst=KCST_toA2B)
# Second order irreversible 2D
A_so2d = smod.Spec('A_so2d', mdl)
B_so2d = smod.Spec('B_so2d', mdl)
C_so2d = smod.Spec('C_so2d', mdl)
SR1_so2d = smod.SReac('SR1_so2d',
surfsys,
slhs=[A_so2d, B_so2d],
srhs=[C_so2d],
kcst=KCST_so2d)
geom = sgeom.Geom()
comp1 = sgeom.Comp('comp1', geom, VOL)
comp1.addVolsys('vsys')
patch1 = sgeom.Patch('patch1', geom, comp1, area=AREA_so2d)
patch1.addSurfsys('ssys')
rng = srng.create('r123', 512)
rng.initialize(1000)
sim = ssolv.Wmdirect(mdl, geom, rng)
sim.reset()
global tpnts, ntpnts
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_m_foi = numpy.zeros([NITER_foi, ntpnts, 1])
res_std1_foi = numpy.zeros([ntpnts, 1])
res_std2_foi = numpy.zeros([ntpnts, 1])
res_m_for = numpy.zeros([NITER_for, ntpnts, 2])
res_m_soA2 = numpy.zeros([NITER_soA2, ntpnts, 2])
res_m_soAA = numpy.zeros([NITER_soAA, ntpnts, 3])
res_m_soAB = numpy.zeros([NITER_soAB, ntpnts, 3])
res_m_toA3 = numpy.zeros([NITER_toA3, ntpnts, 2])
res_m_toA2B = numpy.zeros([NITER_toA2B, ntpnts, 3])
res_m_so2d = numpy.zeros([NITER_so2d, ntpnts, 3])
for i in range(0, NITER_max):
sim.reset()
if i < NITER_foi:
sim.setCompCount('comp1', 'A_foi', N_foi)
if i < NITER_for:
sim.setCompCount('comp1', 'A_for', COUNT_for)
sim.setCompCount('comp1', 'B_for', 0.0)
if i < NITER_soA2:
sim.setCompConc('comp1', 'A_soA2', CONCA_soA2)
if i < NITER_soAA:
sim.setCompConc('comp1', 'A_soAA', CONCA_soAA)
sim.setCompConc('comp1', 'B_soAA', CONCB_soAA)
if i < NITER_soAB:
sim.setCompConc('comp1', 'A_soAB', CONCA_soAB)
sim.setCompConc('comp1', 'B_soAB', CONCB_soAB)
if i < NITER_toA3:
sim.setCompConc('comp1', 'A_toA3', CONCA_toA3)
if i < NITER_toA2B:
sim.setCompConc('comp1', 'A_toA2B', CONCA_toA2B)
sim.setCompConc('comp1', 'B_toA2B', CONCB_toA2B)
if i < NITER_so2d:
sim.setPatchCount('patch1', 'A_so2d', COUNTA_so2d)
sim.setPatchCount('patch1', 'B_so2d', COUNTB_so2d)
for t in range(0, ntpnts):
sim.run(tpnts[t])
if i < NITER_foi:
res_m_foi[i, t, 0] = sim.getCompCount('comp1', 'A_foi')
if i < NITER_for:
res_m_for[i, t, 0] = sim.getCompConc('comp1', 'A_for') * 1e6
res_m_for[i, t, 1] = sim.getCompConc('comp1', 'B_for') * 1e6
if i < NITER_soA2:
res_m_soA2[i, t, 0] = sim.getCompConc('comp1', 'A_soA2')
if i < NITER_soAA:
res_m_soAA[i, t, 0] = sim.getCompConc('comp1', 'A_soAA')
res_m_soAA[i, t, 1] = sim.getCompConc('comp1', 'B_soAA')
if i < NITER_soAB:
res_m_soAB[i, t, 0] = sim.getCompConc('comp1', 'A_soAB')
res_m_soAB[i, t, 1] = sim.getCompConc('comp1', 'B_soAB')
if i < NITER_toA3:
res_m_toA3[i, t, 0] = sim.getCompConc('comp1', 'A_toA3')
if i < NITER_toA2B:
res_m_toA2B[i, t, 0] = sim.getCompConc('comp1', 'A_toA2B')
res_m_toA2B[i, t, 1] = sim.getCompConc('comp1', 'B_toA2B')
res_m_toA2B[i, t, 2] = sim.getCompConc('comp1', 'C_toA2B')
if i < NITER_so2d:
res_m_so2d[i, t, 0] = sim.getPatchCount('patch1', 'A_so2d')
res_m_so2d[i, t, 1] = sim.getPatchCount('patch1', 'B_so2d')
global mean_res_foi, std_res_foi
mean_res_foi = numpy.mean(res_m_foi, 0)
std_res_foi = numpy.std(res_m_foi, 0)
global mean_res_for
mean_res_for = numpy.mean(res_m_for, 0)
global mean_res_soA2
mean_res_soA2 = numpy.mean(res_m_soA2, 0)
global mean_res_soAA
mean_res_soAA = numpy.mean(res_m_soAA, 0)
global mean_res_soAB
mean_res_soAB = numpy.mean(res_m_soAB, 0)
global mean_res_toA3
mean_res_toA3 = numpy.mean(res_m_toA3, 0)
global mean_res_toA2B
mean_res_toA2B = numpy.mean(res_m_toA2B, 0)
global mean_res_so2d
mean_res_so2d = numpy.mean(res_m_so2d, 0)
global ran_sim
ran_sim = True
def test_masteqdiff():
SCALE = 1.0
KCST_f = 100e6 * SCALE # The reaction constant, degradation
KCST_b = (20.0e-10 * SCALE) # The reaction constant, production
DCST_A = 20e-12
DCST_B = 20e-12
B0 = 1 # The number of B moleucles
DT = 0.1 # Sampling time-step
INT = 50000.1 # Sim endtime
filename = 'cube_1_1_1_73tets.inp'
# A tolerance of 7.5% will fail <1% of the time
tolerance = 7.5 / 100
########################################################################
mdl = smod.Model()
A = smod.Spec('A', mdl)
B = smod.Spec('B', mdl)
volsys = smod.Volsys('vsys', mdl)
diffA = smod.Diff('diffA', volsys, A)
diffA.setDcst(DCST_A)
diffB = smod.Diff('diffB', volsys, B)
diffB.setDcst(DCST_B)
# Production
R1 = smod.Reac('R1', volsys, lhs=[A, B], rhs=[B], kcst=KCST_f)
R2 = smod.Reac('R2', volsys, lhs=[], rhs=[A], kcst=KCST_b)
geom = meshio.loadMesh('./validation_rd/meshes/' + filename)[0]
comp1 = sgeom.TmComp('comp1', geom, range(geom.ntets))
comp1.addVolsys('vsys')
rng = srng.create('mt19937', 512)
rng.initialize(int(time.time() % 4294967295))
sim = ssolv.Tetexact(mdl, geom, rng)
sim.reset()
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res = np.zeros([ntpnts])
res_std1 = np.zeros([ntpnts])
res_std2 = np.zeros([ntpnts])
sim.restore('./validation_cp/cp/masteq_diff')
b_time = time.time()
for t in range(0, ntpnts):
sim.run(tpnts[t])
res[t] = sim.getCompCount('comp1', 'A')
def fact(x):
return (1 if x == 0 else x * fact(x - 1))
# Do cumulative count, but not comparing them all.
# Don't get over 50 (I hope)
steps_n_res = np.zeros(50)
for r in res:
steps_n_res[int(r)] += 1
for s in range(50):
steps_n_res[s] = steps_n_res[s] / ntpnts
passed = True
max_err = 0.0
k1 = KCST_f / 6.022e23
k2 = KCST_b * 6.022e23
v = comp1.getVol() * 1.0e3 # litres
for m in range(5, 11):
analy = (1.0 / fact(m)) * np.power(
(k2 * v * v) / (B0 * k1), m) * np.exp(-((k2 * v * v) / (k1 * B0)))
assert (tol_funcs.tolerable(steps_n_res[m], analy, tolerance))
