def setUp(self):
mdl = smodel.Model()
S1 = smodel.Spec('S1', mdl)
ssys = smodel.Surfsys('ssys', mdl)
smodel.SReac('SR01', ssys, slhs=[S1], srhs=[S1], kcst=1)
if __name__ == "__main__":
mesh = meshio.importAbaqus('meshes/test.inp', 1e-7)[0]
else:
mesh = meshio.importAbaqus(
'tetODE_setPatchSReacK_bugfix_test/meshes/test.inp', 1e-7)[0]
comp1 = sgeom.TmComp('comp1', mesh, range(mesh.countTets()))
patch1 = sgeom.TmPatch('patch1', mesh, mesh.getSurfTris(), comp1)
patch1.addSurfsys('ssys')
rng = srng.create('mt19937', 512)
rng.initialize(1234)
self.sim = ssolver.TetODE(mdl, mesh, rng)
self.sim.setTolerances(1.0e-3, 1.0e-3)
def init_sim(model, mesh, seed, param):
# previous setup
# rng = srng.create('r123', 512)
# rng.initialize(seed)
# sim = ssolver.Tetexact(model, mesh, rng, True)
# Create the solver objects
if param['SSA_solver'] == 'TetODE':
sim = ssolver.TetODE(model,
mesh,
calcMembPot=sim_parameters['EF_solver'])
sim.setTolerances(1.0e-6, 1e-6)
elif param['SSA_solver'] == 'Tetexact':
rng = srng.create('mt19937', 512)
rng.initialize(seed)
sim = ssolver.Tetexact(model,
mesh,
rng,
calcMembPot=sim_parameters['EF_solver'])
sim.reset()
sim.setEfieldDT(param['EF_dt'])
else:
raise ValueError('SSA solver ' + param['SSA_solver'] + 'not available')
print('Running Rallpack1 test with ' + param['SSA_solver'])
# Correction factor for deviation between mesh and model cylinder:
area_cylinder = np.pi * param['diameter'] * param['length']
area_mesh_factor = sim.getPatchArea('memb') / area_cylinder
# Set initial conditions
memb = sgeom.castToTmPatch(mesh.getPatch('memb'))
for t in memb.tris:
sim.setTriCount(t, 'Leak', 1)
sim.setMembPotential('membrane', param['E_M'])
sim.setMembVolRes('membrane', param['R_A'])
sim.setMembCapac('membrane', param['C_M'] / area_mesh_factor)
v_zmin = mesh.getROIData('v_zmin')
I = param['Iinj'] / len(v_zmin)
for v in v_zmin:
sim.setVertIClamp(v, I)
return sim
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
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # SIMULATION # # # # # # # # # # # # # # # # # # # # # #
r = srng.create_mt19937(512)
r.initialize(7)
r_dummy = srng.create_mt19937(512)
r_dummy.initialize(7)
print "Creating Tet exact solver"
#Creating two solvers
sim_stoch = ssolver.Tetexact(mdl_stoch, mesh_stoch, r, True)
print "Creating Tet ODE solver"
sim_det = ssolver.TetODE(mdl_det, mesh_det, r_dummy)
sim_det.setTolerances(1.0e-3, 1.0e-3)
print "Resetting simulation objects.."
sim_stoch.reset()
print "Injecting molecules.."
sim_stoch.setTemp(TEMPERATURE + 273.15)
sim_stoch.setCompConc('cyto_stoch', 'Ca_stoch', Ca_iconc)
print "Calcium concentration in stochastic simulation is: ", sim_stoch.getCompConc(
'cyto_stoch', 'Ca_stoch')
print "No. of Ca molecules in stochastic simulation is: ", sim_stoch.getCompCount(
def test_unbdiff2D_ode():
"Surface Diffusion - Unbounded, point source (TetODE)"
m = gen_model()
g, patch_tris, patch_tris_n, ctri_idx, trirads, triareas = gen_geom()
sim = solvmod.TetODE(m, g)
sim.setTolerances(1.0e-7, 1.0e-7)
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_count = numpy.zeros((ntpnts, patch_tris_n))
sim.setTriCount(ctri_idx, 'X', NINJECT)
for i in range(ntpnts):
sim.run(tpnts[i])
for k in range(patch_tris_n):
res_count[i, k] = sim.getTriCount(patch_tris[k], 'X')
########################################################################
tpnt_compare = [50, 100, 150]
passed = True
max_err = 0.0
for t in tpnt_compare:
bin_n = 20
r_max = 0.0
for i in trirads:
if (i > r_max): r_max = i
r_min = 0.0
r_seg = (r_max - r_min) / bin_n
bin_mins = numpy.zeros(bin_n + 1)
r_tris_binned = numpy.zeros(bin_n)
bin_areas = numpy.zeros(bin_n)
r = r_min
for b in range(bin_n + 1):
bin_mins[b] = r
if (b != bin_n): r_tris_binned[b] = r + r_seg / 2.0
r += r_seg
bin_counts = [None] * bin_n
for i in range(bin_n):
bin_counts[i] = []
for i in range((res_count[t].size)):
i_r = trirads[i]
for b in range(bin_n):
if (i_r >= bin_mins[b] and i_r < bin_mins[b + 1]):
bin_counts[b].append(res_count[t][i])
bin_areas[b] += sim.getTriArea(int(patch_tris[i]))
break
bin_concs = numpy.zeros(bin_n)
for c in range(bin_n):
for d in range(bin_counts[c].__len__()):
bin_concs[c] += bin_counts[c][d]
bin_concs[c] /= (bin_areas[c] * 1.0e12)
for i in range(bin_n):
if (r_tris_binned[i] > 1.0 and r_tris_binned[i] < 5.0):
rad = r_tris_binned[i] * 1.0e-6
det_conc = 1.0e-12 * (
NINJECT / (4 * math.pi * DCST * tpnts[t])) * (math.exp(
(-1.0 * (rad * rad)) / (4 * DCST * tpnts[t])))
steps_conc = bin_concs[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
membrane = sgeom.Memb('membrane',
mesh, [memb],
opt_method=2,
search_percent=100.0)
# Set the single-channel conductance:
g_leak_sc = L_G_tot / len(memb_tris)
OC_L = smodel.OhmicCurr('OC_L',
ssys,
chanstate=Leak,
erev=leak_rev,
g=g_leak_sc)
# Create the solver objects
sim = ssolver.TetODE(mdl, mesh, calcMembPot=True)
sim.setTolerances(1.0e-6, 1e-6)
surfarea_mesh = sim.getPatchArea('memb')
surfarea_cyl = 1.0 * math.pi * 1000 * 1e-12
corr_fac_area = surfarea_mesh / surfarea_cyl
vol_cyl = math.pi * 0.5 * 0.5 * 1000 * 1e-18
vol_mesh = sim.getCompVol('cyto')
corr_fac_vol = vol_mesh / vol_cyl
RES_POT = zeros((SIM_NTPNTS, POT_N))
print "\nRunning simulation"
for t in memb_tris:
def test_unbdiff2D_linesource_ring_ode():
"Surface Diffusion - Unbounded, line source (TetODE)"
m = gen_model()
g, patch_tris, patch_tris_n, inject_tris, tridists, triareas = gen_geom()
sim = solvmod.TetODE(m, g, rng)
sim.setTolerances(1e-7, 1e-7)
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
res_count = np.zeros((ntpnts, patch_tris_n))
for t in inject_tris:
sim.setTriCount(t, 'X', float(NINJECT) / len(inject_tris))
for i in range(ntpnts):
sim.run(tpnts[i])
for k in range(patch_tris_n):
res_count[i, k] = sim.getTriCount(patch_tris[k], 'X')
tpnt_compare = [75, 100, 150]
passed = True
max_err = 0.0
for t in tpnt_compare:
bin_n = 50
r_min = 0
r_max = 0
for i in tridists:
if (i > r_max): r_max = i
if (i < r_min): r_min = i
r_seg = (r_max - r_min) / bin_n
bin_mins = np.zeros(bin_n + 1)
r_tris_binned = np.zeros(bin_n)
bin_areas = np.zeros(bin_n)
r = r_min
for b in range(bin_n + 1):
bin_mins[b] = r
if (b != bin_n): r_tris_binned[b] = r + r_seg / 2.0
r += r_seg
bin_counts = [None] * bin_n
for i in range(bin_n):
bin_counts[i] = []
for i in range((res_count[t].size)):
i_r = tridists[i]
for b in range(bin_n):
if (i_r >= bin_mins[b] and i_r < bin_mins[b + 1]):
bin_counts[b].append(res_count[t][i])
bin_areas[b] += sim.getTriArea(int(patch_tris[i]))
break
bin_concs = np.zeros(bin_n)
for c in range(bin_n):
for d in range(bin_counts[c].__len__()):
bin_concs[c] += bin_counts[c][d]
bin_concs[c] /= (bin_areas[c] * 1.0e12)
for i in range(bin_n):
if (r_tris_binned[i] > -10.0 and r_tris_binned[i] < 10.0):
dist = r_tris_binned[i] * 1e-6
det_conc = 1e-6 * (NINJECT / (4 * np.sqrt(
(np.pi * DCST * tpnts[t])))) * (np.exp(
(-1.0 * (dist * dist)) / (4 * DCST * tpnts[t])))
steps_conc = bin_concs[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
def test_rallpack3():
print("Rallpack 3 with TetODE")
#meshfile ='axon_cube_L1000um_D866m_600tets'
meshfile = 'axon_cube_L1000um_D866m_1135tets'
#meshfile = 'axon_cube_L1000um_D866nm_1978tets'
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Potassium conductance, Siemens/m^2
K_G = 360
# Sodium conductance, Siemens/m^2
Na_G = 1200
# Leak conductance, Siemens/m^2
L_G = 0.25
# Potassium reversal potential, V
K_rev = -77e-3
# Sodium reversal potential, V
Na_rev = 50e-3
# Leak reveral potential, V
leak_rev = -65.0e-3
# Potassium channel density
K_ro = 18.0e12
# Sodium channel density
Na_ro = 60.0e12
# Total leak conductance for ideal cylinder:
surfarea_cyl = 1.0 * np.pi * 1000 * 1e-12
L_G_tot = L_G * surfarea_cyl
# A table of potassium density factors at -65mV, found in getpops. n0, n1, n2, n3, n4
K_FACS = [0.216750577045, 0.40366011853, 0.281904943772, \
0.0874997924409, 0.0101845682113 ]
# A table of sodium density factors. m0h1, m1h1, m2h1, m3h1, m0h0, m1h0, m2h0, m3h0
NA_FACS = [0.343079175644, 0.0575250437508, 0.00321512825945, 5.98988373918e-05, \
0.506380603793, 0.0849062503811, 0.00474548939393, 8.84099403236e-05]
# Ohm.m
Ra = 1.0
# # # # # # # # # # # # # # # # SIMULATION CONTROLS # # # # # # # # # # # # # #
# The simulation dt (seconds); for TetODE this is equivalent to EField dt
SIM_DT = 5.0e-6
# Sim end time (seconds)
SIM_END = 0.1
# The number of sim 'time points'; * SIM_DT = sim end time
SIM_NTPNTS = int(SIM_END / SIM_DT) + 1
# The current injection in amps
Iinj = 0.1e-9
# # # # # # # # # # # # # DATA COLLECTION # # # # # # # # # # # # # # # # # #
# record potential at the two extremes along (z) axis
POT_POS = np.array([0.0, 1.0e-03])
POT_N = len(POT_POS)
# Length of the mesh, in m
LENGTH = 1000.0e-6
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
mdl = smodel.Model()
ssys = smodel.Surfsys('ssys', mdl)
# K channel
K = smodel.Chan('K', mdl)
K_n0 = smodel.ChanState('K_n0', mdl, K)
K_n1 = smodel.ChanState('K_n1', mdl, K)
K_n2 = smodel.ChanState('K_n2', mdl, K)
K_n3 = smodel.ChanState('K_n3', mdl, K)
K_n4 = smodel.ChanState('K_n4', mdl, K)
# Na channel
Na = smodel.Chan('Na', mdl)
Na_m0h1 = smodel.ChanState('Na_m0h1', mdl, Na)
Na_m1h1 = smodel.ChanState('Na_m1h1', mdl, Na)
Na_m2h1 = smodel.ChanState('Na_m2h1', mdl, Na)
Na_m3h1 = smodel.ChanState('Na_m3h1', mdl, Na)
Na_m0h0 = smodel.ChanState('Na_m0h0', mdl, Na)
Na_m1h0 = smodel.ChanState('Na_m1h0', mdl, Na)
Na_m2h0 = smodel.ChanState('Na_m2h0', mdl, Na)
Na_m3h0 = smodel.ChanState('Na_m3h0', mdl, Na)
# Leak
L = smodel.Chan('L', mdl)
Leak = smodel.ChanState('Leak', mdl, L)
# Gating kinetics
_a_m = lambda mV: ((((0.1 * (25 - (mV + 65.)) / (np.exp(
(25 - (mV + 65.)) / 10.) - 1)))))
_b_m = lambda mV: ((((4. * np.exp(-((mV + 65.) / 18.))))))
_a_h = lambda mV: ((((0.07 * np.exp((-(mV + 65.) / 20.))))))
_b_h = lambda mV: ((((1. / (np.exp((30 - (mV + 65.)) / 10.) + 1)))))
_a_n = lambda mV: ((((0.01 * (10 - (mV + 65.)) / (np.exp(
(10 - (mV + 65.)) / 10.) - 1)))))
_b_n = lambda mV: ((((0.125 * np.exp(-(mV + 65.) / 80.)))))
Kn0n1 = smodel.VDepSReac('Kn0n1',
ssys,
slhs=[K_n0],
srhs=[K_n1],
k=lambda V: 1.0e3 * 4. * _a_n(V * 1.0e3))
Kn1n2 = smodel.VDepSReac('Kn1n2',
ssys,
slhs=[K_n1],
srhs=[K_n2],
k=lambda V: 1.0e3 * 3. * _a_n(V * 1.0e3))
Kn2n3 = smodel.VDepSReac('Kn2n3',
ssys,
slhs=[K_n2],
srhs=[K_n3],
k=lambda V: 1.0e3 * 2. * _a_n(V * 1.0e3))
Kn3n4 = smodel.VDepSReac('Kn3n4',
ssys,
slhs=[K_n3],
srhs=[K_n4],
k=lambda V: 1.0e3 * 1. * _a_n(V * 1.0e3))
Kn4n3 = smodel.VDepSReac('Kn4n3',
ssys,
slhs=[K_n4],
srhs=[K_n3],
k=lambda V: 1.0e3 * 4. * _b_n(V * 1.0e3))
Kn3n2 = smodel.VDepSReac('Kn3n2',
ssys,
slhs=[K_n3],
srhs=[K_n2],
k=lambda V: 1.0e3 * 3. * _b_n(V * 1.0e3))
Kn2n1 = smodel.VDepSReac('Kn2n1',
ssys,
slhs=[K_n2],
srhs=[K_n1],
k=lambda V: 1.0e3 * 2. * _b_n(V * 1.0e3))
Kn1n0 = smodel.VDepSReac('Kn1n0',
ssys,
slhs=[K_n1],
srhs=[K_n0],
k=lambda V: 1.0e3 * 1. * _b_n(V * 1.0e3))
Na_m0h1_m1h1 = smodel.VDepSReac('Na_m0h1_m1h1',
ssys,
slhs=[Na_m0h1],
srhs=[Na_m1h1],
k=lambda V: 1.0e3 * 3. * _a_m(V * 1.0e3))
Na_m1h1_m2h1 = smodel.VDepSReac('Na_m1h1_m2h1',
ssys,
slhs=[Na_m1h1],
srhs=[Na_m2h1],
k=lambda V: 1.0e3 * 2. * _a_m(V * 1.0e3))
Na_m2h1_m3h1 = smodel.VDepSReac('Na_m2h1_m3h1',
ssys,
slhs=[Na_m2h1],
srhs=[Na_m3h1],
k=lambda V: 1.0e3 * 1. * _a_m(V * 1.0e3))
Na_m3h1_m2h1 = smodel.VDepSReac('Na_m3h1_m2h1',
ssys,
slhs=[Na_m3h1],
srhs=[Na_m2h1],
k=lambda V: 1.0e3 * 3. * _b_m(V * 1.0e3))
Na_m2h1_m1h1 = smodel.VDepSReac('Na_m2h1_m1h1',
ssys,
slhs=[Na_m2h1],
srhs=[Na_m1h1],
k=lambda V: 1.0e3 * 2. * _b_m(V * 1.0e3))
Na_m1h1_m0h1 = smodel.VDepSReac('Na_m1h1_m0h1',
ssys,
slhs=[Na_m1h1],
srhs=[Na_m0h1],
k=lambda V: 1.0e3 * 1. * _b_m(V * 1.0e3))
Na_m0h0_m1h0 = smodel.VDepSReac('Na_m0h0_m1h0',
ssys,
slhs=[Na_m0h0],
srhs=[Na_m1h0],
k=lambda V: 1.0e3 * 3. * _a_m(V * 1.0e3))
Na_m1h0_m2h0 = smodel.VDepSReac('Na_m1h0_m2h0',
ssys,
slhs=[Na_m1h0],
srhs=[Na_m2h0],
k=lambda V: 1.0e3 * 2. * _a_m(V * 1.0e3))
Na_m2h0_m3h0 = smodel.VDepSReac('Na_m2h0_m3h0',
ssys,
slhs=[Na_m2h0],
srhs=[Na_m3h0],
k=lambda V: 1.0e3 * 1. * _a_m(V * 1.0e3))
Na_m3h0_m2h0 = smodel.VDepSReac('Na_m3h0_m2h0',
ssys,
slhs=[Na_m3h0],
srhs=[Na_m2h0],
k=lambda V: 1.0e3 * 3. * _b_m(V * 1.0e3))
Na_m2h0_m1h0 = smodel.VDepSReac('Na_m2h0_m1h0',
ssys,
slhs=[Na_m2h0],
srhs=[Na_m1h0],
k=lambda V: 1.0e3 * 2. * _b_m(V * 1.0e3))
Na_m1h0_m0h0 = smodel.VDepSReac('Na_m1h0_m0h0',
ssys,
slhs=[Na_m1h0],
srhs=[Na_m0h0],
k=lambda V: 1.0e3 * 1. * _b_m(V * 1.0e3))
Na_m0h1_m0h0 = smodel.VDepSReac('Na_m0h1_m0h0',
ssys,
slhs=[Na_m0h1],
srhs=[Na_m0h0],
k=lambda V: 1.0e3 * _a_h(V * 1.0e3))
Na_m1h1_m1h0 = smodel.VDepSReac('Na_m1h1_m1h0',
ssys,
slhs=[Na_m1h1],
srhs=[Na_m1h0],
k=lambda V: 1.0e3 * _a_h(V * 1.0e3))
Na_m2h1_m2h0 = smodel.VDepSReac('Na_m2h1_m2h0',
ssys,
slhs=[Na_m2h1],
srhs=[Na_m2h0],
k=lambda V: 1.0e3 * _a_h(V * 1.0e3))
Na_m3h1_m3h0 = smodel.VDepSReac('Na_m3h1_m3h0',
ssys,
slhs=[Na_m3h1],
srhs=[Na_m3h0],
k=lambda V: 1.0e3 * _a_h(V * 1.0e3))
Na_m0h0_m0h1 = smodel.VDepSReac('Na_m0h0_m0h1',
ssys,
slhs=[Na_m0h0],
srhs=[Na_m0h1],
k=lambda V: 1.0e3 * _b_h(V * 1.0e3))
Na_m1h0_m1h1 = smodel.VDepSReac('Na_m1h0_m1h1',
ssys,
slhs=[Na_m1h0],
srhs=[Na_m1h1],
k=lambda V: 1.0e3 * _b_h(V * 1.0e3))
Na_m2h0_m2h1 = smodel.VDepSReac('Na_m2h0_m2h1',
ssys,
slhs=[Na_m2h0],
srhs=[Na_m2h1],
k=lambda V: 1.0e3 * _b_h(V * 1.0e3))
Na_m3h0_m3h1 = smodel.VDepSReac('Na_m3h0_m3h1',
ssys,
slhs=[Na_m3h0],
srhs=[Na_m3h1],
k=lambda V: 1.0e3 * _b_h(V * 1.0e3))
OC_K = smodel.OhmicCurr('OC_K',
ssys,
chanstate=K_n4,
erev=K_rev,
g=K_G / K_ro)
OC_Na = smodel.OhmicCurr('OC_Na',
ssys,
chanstate=Na_m3h0,
erev=Na_rev,
g=Na_G / Na_ro)
# Mesh geometry
mesh = meshio.loadMesh('validation_efield/meshes/' + meshfile)[0]
cyto = sgeom.TmComp('cyto', mesh, range(mesh.ntets))
# The tetrahedrons from which to record potential
POT_TET = np.zeros(POT_N, dtype='uint')
i = 0
for p in POT_POS:
# Assuming axiz aligned with z-axis
POT_TET[i] = mesh.findTetByPoint([0.0, 0.0, POT_POS[i]])
i = i + 1
# Find the tets connected to the bottom face
# First find all the tets with ONE face on a boundary
boundtets = []
#store the 0to3 index of the surface triangle for each of these boundary tets
bt_srftriidx = []
for i in range(mesh.ntets):
tettemp = mesh.getTetTetNeighb(i)
if (tettemp[0] == -1 or tettemp[1] == -1 or tettemp[2] == -1
or tettemp[3] == -1):
boundtets.append(i)
templist = []
if (tettemp[0] == -1):
templist.append(0)
if (tettemp[1] == -1):
templist.append(1)
if (tettemp[2] == -1):
templist.append(2)
if (tettemp[3] == -1):
templist.append(3)
bt_srftriidx.append(templist)
assert (boundtets.__len__() == bt_srftriidx.__len__())
# Find the tets on the z=0 and z=1000um boundaries, and the triangles
minztets = []
minztris = []
maxztris = []
minzverts = set([])
boundminz = mesh.getBoundMin()[2] + LENGTH / mesh.ntets
boundmaxz = mesh.getBoundMax()[2] - LENGTH / mesh.ntets
for i in range(boundtets.__len__()):
# get the boundary triangle
for btriidx in bt_srftriidx[i]:
zminboundtri = True
tribidx = mesh.getTetTriNeighb(boundtets[i])[btriidx]
tritemp = mesh.getTri(tribidx)
trizs = [0.0, 0.0, 0.0]
trizs[0] = mesh.getVertex(tritemp[0])[2]
trizs[1] = mesh.getVertex(tritemp[1])[2]
trizs[2] = mesh.getVertex(tritemp[2])[2]
for j in range(3):
if (trizs[j] > boundminz): zminboundtri = False
if (zminboundtri):
minztets.append(boundtets[i])
minztris.append(tribidx)
minzverts.add(tritemp[0])
minzverts.add(tritemp[1])
minzverts.add(tritemp[2])
continue
zmaxboundtri = True
for j in range(3):
if (trizs[j] < boundmaxz): zmaxboundtri = False
if (zmaxboundtri):
maxztris.append(tribidx)
n_minztris = len(minztris)
assert (n_minztris > 0)
minzverts = list(minzverts)
n_minzverts = len(minzverts)
assert (n_minzverts > 0)
memb_tris = list(mesh.getSurfTris())
# Doing this now, so will inject into first little z section
for t in minztris:
memb_tris.remove(t)
for t in maxztris:
memb_tris.remove(t)
# Create the membrane with the tris removed at faces
memb = sgeom.TmPatch('memb', mesh, memb_tris, cyto)
memb.addSurfsys('ssys')
membrane = sgeom.Memb('membrane',
mesh, [memb],
opt_method=2,
search_percent=100.0)
# Set the single-channel conductance:
g_leak_sc = L_G_tot / len(memb_tris)
OC_L = smodel.OhmicCurr('OC_L',
ssys,
chanstate=Leak,
erev=leak_rev,
g=g_leak_sc)
# Create the solver objects
sim = ssolver.TetODE(mdl, mesh, calcMembPot=True)
sim.setTolerances(1.0e-6, 1e-6)
surfarea_mesh = sim.getPatchArea('memb')
surfarea_cyl = 1.0 * np.pi * 1000 * 1e-12
corr_fac_area = surfarea_mesh / surfarea_cyl
vol_cyl = np.pi * 0.5 * 0.5 * 1000 * 1e-18
vol_mesh = sim.getCompVol('cyto')
corr_fac_vol = vol_mesh / vol_cyl
RES_POT = np.zeros((SIM_NTPNTS, POT_N))
for t in memb_tris:
sim.setTriCount(t, 'Leak', 1)
sim.setPatchCount('memb', 'Na_m0h1', (Na_ro * surfarea_cyl * NA_FACS[0]))
sim.setPatchCount('memb', 'Na_m1h1', (Na_ro * surfarea_cyl * NA_FACS[1]))
sim.setPatchCount('memb', 'Na_m2h1', (Na_ro * surfarea_cyl * NA_FACS[2]))
sim.setPatchCount('memb', 'Na_m3h1', (Na_ro * surfarea_cyl * NA_FACS[3]))
sim.setPatchCount('memb', 'Na_m0h0', (Na_ro * surfarea_cyl * NA_FACS[4]))
sim.setPatchCount('memb', 'Na_m1h0', (Na_ro * surfarea_cyl * NA_FACS[5]))
sim.setPatchCount('memb', 'Na_m2h0', (Na_ro * surfarea_cyl * NA_FACS[6]))
sim.setPatchCount('memb', 'Na_m3h0', (Na_ro * surfarea_cyl * NA_FACS[7]))
sim.setPatchCount('memb', 'K_n0', (K_ro * surfarea_cyl * K_FACS[0]))
sim.setPatchCount('memb', 'K_n1', (K_ro * surfarea_cyl * K_FACS[1]))
sim.setPatchCount('memb', 'K_n2', (K_ro * surfarea_cyl * K_FACS[2]))
sim.setPatchCount('memb', 'K_n3', (K_ro * surfarea_cyl * K_FACS[3]))
sim.setPatchCount('memb', 'K_n4', (K_ro * surfarea_cyl * K_FACS[4]))
sim.setMembPotential('membrane', -65e-3)
sim.setMembVolRes('membrane', Ra * corr_fac_vol)
sim.setMembCapac('membrane', 0.01 / corr_fac_area)
for v in minzverts:
sim.setVertIClamp(v, Iinj / n_minzverts)
for l in range(SIM_NTPNTS):
sim.run(SIM_DT * l)
for p in range(POT_N):
RES_POT[l, p] = sim.getTetV(int(POT_TET[p])) * 1.0e3
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Benchmark
# At 0um- the end of the mesh
ifile_benchmark_x0 = open(
'validation_efield/data/rallpack3_benchmark/rallpack3_0_0.001dt_1000seg',
'r')
# At 1000um- the end of the mesh
ifile_benchmark_x1000 = open(
'validation_efield/data/rallpack3_benchmark/rallpack3_1000_0.001dt_1000seg',
'r')
tpnt_benchmark = []
v_benchmark_x0 = []
v_benchmark_x1000 = []
lines_benchmark_x0 = ifile_benchmark_x0.readlines()[2:]
# Read in mv and ms
for line_benchmark_x0 in lines_benchmark_x0:
nums = line_benchmark_x0.split()
tpnt_benchmark.append(float(nums[0]))
v_benchmark_x0.append(float(nums[1]))
lines_benchmark_x1000 = ifile_benchmark_x1000.readlines()[2:]
for line_benchmark_x1000 in lines_benchmark_x1000:
nums = line_benchmark_x1000.split()
v_benchmark_x1000.append(float(nums[1]))
# Get rid of the last point which seems to be missing from STEPS
v_benchmark_x0 = v_benchmark_x0[:-1]
tpnt_benchmark = tpnt_benchmark[:-1]
v_benchmark_x1000 = v_benchmark_x1000[:-1]
rms0 = stats(v_benchmark_x0, RES_POT[:, 0])
assert (rms0 < 0.15)
rms1000 = stats(v_benchmark_x1000, RES_POT[:, 1])
assert (rms1000 < 1.1)
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 test_bounddiff_ode():
"Diffusion - Bounded (TetODE)"
m = gen_model()
g, area, a = gen_geom()
# And fetch the total number of tets to make the data structures
ntets = g.countTets()
sim = solvmod.TetODE(m, g)
sim.setTolerances(1e-3, 1e-3)
tpnts = numpy.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
# Create the big old data structure: iterations x time points x concentrations
res = numpy.zeros((NITER, ntpnts, SAMPLE))
# Find the tets connected to the bottom face
# First find all the tets with ONE face on a boundary
boundtets = []
#store the 0to3 index of the surface triangle for each of these boundary tets
bt_srftriidx = []
for i in range(ntets):
tettemp = g.getTetTetNeighb(i)
if (tettemp[0] == -1 or tettemp[1] == -1 or tettemp[2] == -1
or tettemp[3] == -1):
boundtets.append(i)
templist = []
if (tettemp[0] == -1):
templist.append(0)
if (tettemp[1] == -1):
templist.append(1)
if (tettemp[2] == -1):
templist.append(2)
if (tettemp[3] == -1):
templist.append(3)
bt_srftriidx.append(templist)
assert (boundtets.__len__() == bt_srftriidx.__len__())
minztets = []
boundminz = g.getBoundMin()[2] + 0.01e-06
num2s = 0
for i in range(boundtets.__len__()):
# get the boundary triangle
if (bt_srftriidx[i].__len__() == 2): num2s += 1
for btriidx in bt_srftriidx[i]:
zminboundtri = True
tribidx = g.getTetTriNeighb(boundtets[i])[btriidx]
tritemp = g.getTri(tribidx)
trizs = [0.0, 0.0, 0.0]
trizs[0] = g.getVertex(tritemp[0])[2]
trizs[1] = g.getVertex(tritemp[1])[2]
trizs[2] = g.getVertex(tritemp[2])[2]
for j in range(3):
if (trizs[j] > boundminz): zminboundtri = False
if (zminboundtri): minztets.append(boundtets[i])
nztets = minztets.__len__()
volztets = 0.0
for z in minztets:
volztets += g.getTetVol(z)
conc = NITER * 6.022e23 * 1.0e-3 / volztets
for j in range(NITER):
tetcount = int((1.0 * NINJECT) / nztets)
totset = 0
for k in minztets:
sim.setTetCount(k, 'X', tetcount)
totset += tetcount
for i in range(ntpnts):
sim.run(tpnts[i])
for k in range(SAMPLE):
res[j, i, k] = sim.getTetCount(int(tetidxs[k]), 'X')
itermeans = numpy.mean(res, axis=0)
########################################################################
D = DCST
pi = math.pi
nmax = 1000
N = NINJECT
N = int((1.0 * NINJECT) / nztets) * nztets
def getprob(x, t):
if (x > a):
print('x out of bounds')
return
p = 0.0
for n in range(nmax):
if (n == 0): A = math.sqrt(1.0 / a)
else: A = math.sqrt(2.0 / a)
p += math.exp(-D * math.pow(
(n * pi / a), 2) * t) * A * math.cos(n * pi * x / a) * A * a
return p * N / a
tpnt_compare = [6, 8, 10]
passed = True
max_err = 0.0
for t in tpnt_compare:
NBINS = 5
radmax = 0.0
radmin = 11.0
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_counts = [None] * NBINS
for i in range(NBINS):
bin_counts[i] = []
filled = 0
for i in range(itermeans[t].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_counts[b].append(itermeans[t][i])
bin_vols[b] += sim.getTetVol(int(tetidxs[i]))
filled += 1.0
break
bin_concs = numpy.zeros(NBINS)
for c in range(NBINS):
for d in range(bin_counts[c].__len__()):
bin_concs[c] += bin_counts[c][d]
bin_concs[c] /= (bin_vols[c])
bin_concs[c] *= (1.0e-3 / 6.022e23) * 1.0e6
for i in range(NBINS):
if (tetradsbinned[i] > 2 and tetradsbinned[i] < 8):
rad = tetradsbinned[i] * 1.0e-6
det_conc = (getprob(rad, tpnts[t]) / area) * (1.0 / 6.022e20)
steps_conc = bin_concs[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
def test_constsourcediff_reac_ode():
"Reaction-diffusion - Constant source from reaction (TetODE)"
m = gen_model()
g = gen_geom()
real_vol = g.getMeshVolume()
#Effective area
area = real_vol / 10e-6
# And fetch the total number of tets to make the data structures
ntets = g.countTets()
sim = solvmod.TetODE(m, g)
sim.setTolerances(1e-3, 1e-3)
tpnts = np.arange(0.0, INT, DT)
ntpnts = tpnts.shape[0]
#Create the data structure: time points x concentrations
res = np.zeros((ntpnts, SAMPLE))
# Find the tets connected to the bottom face
# First find all the tets with ONE face on a boundary
boundtets = []
#store the 0to3 index of the surface triangle for each of these boundary tets
bt_srftriidx = []
for i in range(ntets):
tettemp = g.getTetTetNeighb(i)
if (tettemp[0] == -1 or tettemp[1] == -1 or tettemp[2] == -1
or tettemp[3] == -1):
boundtets.append(i)
templist = []
if (tettemp[0] == -1):
templist.append(0)
if (tettemp[1] == -1):
templist.append(1)
if (tettemp[2] == -1):
templist.append(2)
if (tettemp[3] == -1):
templist.append(3)
bt_srftriidx.append(templist)
assert (boundtets.__len__() == bt_srftriidx.__len__())
minztets = []
maxztets = []
boundminz = g.getBoundMin()[2] + 0.01e-06
boundmaxz = g.getBoundMax()[2] - 0.01e-06
minztris = []
maxztris = []
num2s = 0
for i in range(boundtets.__len__()):
# get the boundary triangle
if (bt_srftriidx[i].__len__() == 2): num2s += 1
for btriidx in bt_srftriidx[i]:
zminboundtri = True
tribidx = g.getTetTriNeighb(boundtets[i])[btriidx]
tritemp = g.getTri(tribidx)
trizs = [0.0, 0.0, 0.0]
trizs[0] = g.getVertex(tritemp[0])[2]
trizs[1] = g.getVertex(tritemp[1])[2]
trizs[2] = g.getVertex(tritemp[2])[2]
for j in range(3):
if (trizs[j] > boundminz): zminboundtri = False
if (zminboundtri):
minztets.append(boundtets[i])
minztris.append(zminboundtri)
continue
zmaxboundtri = True
for j in range(3):
if (trizs[j] < boundmaxz): zmaxboundtri = False
if (zmaxboundtri):
maxztets.append(boundtets[i])
maxztris.append(zmaxboundtri)
nminztets = minztets.__len__()
nmaxztets = maxztets.__len__()
totset = 0
for k in minztets:
sim.setTetReacK(k, 'reacX', FLUX / nminztets)
sim.setTetCount(k, 'A', 1)
totset += sim.getTetCount(k, 'X')
for l in maxztets:
sim.setTetReacK(l, 'reacX', FLUX / nmaxztets)
sim.setTetCount(l, 'A', 1)
totset += sim.getTetCount(l, 'X')
for i in range(ntpnts):
sim.run(tpnts[i])
for k in range(SAMPLE):
res[i, k] = sim.getTetCount(int(tetidxs[k]), 'X') * 1.0e6
########################################################################
L = 5.0e-6
a = 10e-6
D = DCST
pi = np.pi
J = FLUX / area
tpnt_compare = [12, 24]
for t in tpnt_compare:
NBINS = 50
radmax = 0.0
radmin = 0.0
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_counts = [None] * NBINS
for i in range(NBINS):
bin_counts[i] = []
filled = 0
for i in range(res[t].size):
irad = tetrads[i]
for b in range(NBINS):
if (irad >= binmins[b] and irad < binmins[b + 1]):
bin_counts[b].append(res[t][i])
bin_vols[b] += sim.getTetVol(int(tetidxs[i]))
filled += 1.0
break
bin_concs = np.zeros(NBINS)
for c in range(NBINS):
for d in range(bin_counts[c].__len__()):
bin_concs[c] += bin_counts[c][d]
bin_concs[c] /= (bin_vols[c])
bin_concs[c] *= (1.0e-3 / 6.022e23)
for i in range(NBINS):
if (tetradsbinned[i] > -5 and tetradsbinned[i] < -3) \
or (tetradsbinned[i] > 3 and tetradsbinned[i] < -5):
rad = tetradsbinned[i] * 1.0e-6
nsum = 0.0
nmax = 100
for n in range(1, nmax):
nsum+= (np.power(-1., n)/np.power(n, 2))*np.exp(-D*(np.power(((n*pi)/L), 2)*\
tpnts[t]))*np.cos((n*pi*rad)/L)
det_conc = (1.0 / 6.022e20) * ((J * L) / D) * (
((D * tpnts[t]) / np.power(L, 2)) +
((3 * np.power(rad, 2) - np.power(L, 2)) /
(6 * np.power(L, 2))) - (2 / np.power(pi, 2)) * nsum)
steps_conc = bin_concs[i]
assert tol_funcs.tolerable(det_conc, steps_conc, tolerance)
# Create the membrane across which the potential will be solved
membrane = sgeom.Memb('membrane', mesh, [patch], opt_method = 1)
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Create the random number generator
r = srng.create('mt19937',512)
r.initialize(int(time.time()%10000))
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# # # # # # # # # # # # # # # # # SIMULATION # # # # # # # # # # # # # # # # # #
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Create solver object
sim = ssolver.TetODE(mdl, mesh, r, True)
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Inject channels
surfarea = sim.getPatchArea('patch')
sim.setPatchCount('patch', 'Na_m0h0', Na_ro*surfarea*Na_facs[0])
sim.setPatchCount('patch', 'Na_m1h0', Na_ro*surfarea*Na_facs[1])
sim.setPatchCount('patch', 'Na_m2h0', Na_ro*surfarea*Na_facs[2])
sim.setPatchCount('patch', 'Na_m3h0', Na_ro*surfarea*Na_facs[3])
sim.setPatchCount('patch', 'Na_m0h1', Na_ro*surfarea*Na_facs[4])
sim.setPatchCount('patch', 'Na_m1h1', Na_ro*surfarea*Na_facs[5])
sim.setPatchCount('patch', 'Na_m2h1', Na_ro*surfarea*Na_facs[6])
sim.setPatchCount('patch', 'Na_m3h1', Na_ro*surfarea*Na_facs[7])