def problem():
mesh = dolfin.UnitCubeMesh(MPI.comm_world, 10, 10, 10)
cell = mesh.ufl_cell()
vec_element = dolfin.VectorElement("Lagrange", cell, 1)
# scl_element = dolfin.FiniteElement("Lagrange", cell, 1)
Q = dolfin.FunctionSpace(mesh, vec_element)
# Qs = dolfin.FunctionSpace(mesh, scl_element)
# Coefficients
v = dolfin.function.argument.TestFunction(Q) # Test function
du = dolfin.function.argument.TrialFunction(Q) # Incremental displacement
u = dolfin.Function(Q) # Displacement from previous iteration
B = dolfin.Constant((0.0, -0.5, 0.0), cell) # Body force per unit volume
T = dolfin.Constant((0.1, 0.0, 0.0),
cell) # Traction force on the boundary
# B, T = dolfin.Function(Q), dolfin.Function(Q)
# Kinematics
d = u.geometric_dimension()
F = ufl.Identity(d) + grad(u) # Deformation gradient
C = F.T * F # Right Cauchy-Green tensor
# Invariants of deformation tensors
Ic = tr(C)
J = det(F)
# Elasticity parameters
E, nu = 10.0, 0.3
mu = dolfin.Constant(E / (2 * (1 + nu)), cell)
lmbda = dolfin.Constant(E * nu / ((1 + nu) * (1 - 2 * nu)), cell)
# mu, lmbda = dolfin.Function(Qs), dolfin.Function(Qs)
# Stored strain energy density (compressible neo-Hookean model)
psi = (mu / 2) * (Ic - 3) - mu * ln(J) + (lmbda / 2) * (ln(J))**2
# Total potential energy
Pi = psi * dx - dot(B, u) * dx - dot(T, u) * ds
# Compute first variation of Pi (directional derivative about u in the direction of v)
F = ufl.derivative(Pi, u, v)
# Compute Jacobian of F
J = ufl.derivative(F, u, du)
return J, F
def freeEnergy(C, Cv):
J = sqrt(det(C))
I1 = tr(C)
Ce = C * inv(Cv)
Ie1 = tr(Ce)
Je = J / sqrt(det(Cv))
psiEq = (3**(1 - alph1) / (2.0 * alph1) * mu1 * (I1**alph1 - 3**alph1) +
3**(1 - alph2) / (2.0 * alph2) * mu2 * (I1**alph2 - 3**alph2) -
(mu1 + mu2) * ln(J) + mu_pr / 2 * (J - 1)**2)
psiNeq = (3**(1 - a1) / (2.0 * a1) * m1 * (Ie1**a1 - 3**a1) + 3**(1 - a2) /
(2.0 * a2) * m2 * (Ie1**a2 - 3**a2) - (m1 + m2) * ln(Je))
return psiEq + psiNeq
def bessk0(x):
"""
Modified Bessel function of the second kind.
Code taken from
[Flannery et al. 1992] B.P. Flannery,
W.H. Press, S.A. Teukolsky, W. Vetterling,
"Numerical recipes in C", Press Syndicate
of the University of Cambridge, New York
(1992).
"""
y1 = x * x / 4.0
expr1 = -ufl.ln(x / 2.0) * bessi0(x) + (
-0.57721566 + y1 * (0.42278420 + y1 *
(0.23069756 + y1 *
(0.3488590e-1 + y1 *
(0.262698e-2 + y1 *
(0.10750e-3 + y1 * 0.74e-5))))))
y2 = 2.0 / x
expr2 = (ufl.exp(-x) / ufl.sqrt(x) *
(1.25331414 + y2 * (-0.7832358e-1 + y2 *
(0.2189568e-1 + y2 *
(-0.1062446e-1 + y2 *
(0.587872e-2 + y2 *
(-0.251540e-2 + y2 * 0.53208e-3)))))))
return ufl.conditional(x > 2, expr2, expr1)
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert(len(s) == 7)
m, h, j, Cai, d, f, x1 = s
# Assign parameters
g_s = self._parameters["g_s"]
# Init return args
F_expressions = [ufl.zero()]*7
# Expressions for the Sodium current m gate component
alpha_m = (-47 - V)/(-1 + 0.0090952771017*ufl.exp(-0.1*V))
beta_m = 0.709552672749*ufl.exp(-0.056*V)
F_expressions[0] = -beta_m*m + (1 - m)*alpha_m
# Expressions for the Sodium current h gate component
alpha_h = 5.49796243871e-10*ufl.exp(-0.25*V)
beta_h = 1.7/(1 + 0.15802532089*ufl.exp(-0.082*V))
F_expressions[1] = (1 - h)*alpha_h - beta_h*h
# Expressions for the Sodium current j gate component
alpha_j = 1.86904730072e-10*ufl.exp(-0.25*V)/(1 +\
1.67882753e-07*ufl.exp(-0.2*V))
beta_j = 0.3/(1 + 0.0407622039784*ufl.exp(-0.1*V))
F_expressions[2] = (1 - j)*alpha_j - beta_j*j
# Expressions for the Slow inward current component
E_s = -82.3 - 13.0287*ufl.ln(0.001*Cai)
i_s = g_s*(-E_s + V)*d*f
F_expressions[3] = 7e-06 - 0.07*Cai - 0.01*i_s
# Expressions for the Slow inward current d gate component
alpha_d = 0.095*ufl.exp(1/20 - V/100)/(1 +\
1.43328813857*ufl.exp(-0.0719942404608*V))
beta_d = 0.07*ufl.exp(-44/59 - V/59)/(1 + ufl.exp(11/5 + V/20))
F_expressions[4] = -beta_d*d + (1 - d)*alpha_d
# Expressions for the Slow inward current f gate component
alpha_f = 0.012*ufl.exp(-28/125 - V/125)/(1 +\
66.5465065251*ufl.exp(0.149925037481*V))
beta_f = 0.0065*ufl.exp(-3/5 - V/50)/(1 + ufl.exp(-6 - V/5))
F_expressions[5] = (1 - f)*alpha_f - beta_f*f
# Expressions for the Time dependent outward current x1 gate component
alpha_x1 = 0.0311584109863*ufl.exp(0.0826446280992*V)/(1 +\
17.4117080633*ufl.exp(0.0571428571429*V))
beta_x1 = 0.000391646440562*ufl.exp(-0.0599880023995*V)/(1 +\
ufl.exp(-4/5 - V/25))
F_expressions[6] = (1 - x1)*alpha_x1 - beta_x1*x1
# Return results
return dolfin.as_vector(F_expressions)
def hyperelasticity_action_forms(mesh, vec_el):
cell = mesh.ufl_cell()
Q = dolfin.FunctionSpace(mesh, vec_el)
# Coefficients
v = dolfin.function.argument.TestFunction(Q) # Test function
du = dolfin.function.argument.TrialFunction(Q) # Incremental displacement
u = dolfin.Function(Q) # Displacement from previous iteration
u.vector().set(0.5)
B = dolfin.Constant((0.0, -0.5, 0.0), cell) # Body force per unit volume
T = dolfin.Constant((0.1, 0.0, 0.0), cell) # Traction force on the boundary
# Kinematics
d = u.geometric_dimension()
F = ufl.Identity(d) + grad(u) # Deformation gradient
C = F.T * F # Right Cauchy-Green tensor
# Invariants of deformation tensors
Ic = tr(C)
J = det(F)
# Elasticity parameters
E, nu = 10.0, 0.3
mu = dolfin.Constant(E / (2 * (1 + nu)), cell)
lmbda = dolfin.Constant(E * nu / ((1 + nu) * (1 - 2 * nu)), cell)
# Stored strain energy density (compressible neo-Hookean model)
psi = (mu / 2) * (Ic - 3) - mu * ln(J) + (lmbda / 2) * (ln(J)) ** 2
# Total potential energy
Pi = psi * dx - dot(B, u) * dx - dot(T, u) * ds
# Compute first variation of Pi (directional derivative about u in the direction of v)
F = ufl.derivative(Pi, u, v)
# Compute Jacobian of F
J = ufl.derivative(F, u, du)
w = dolfin.Function(Q)
w.vector().set(1.2)
L = ufl.action(J, w)
return None, L, None
def test_dolfin_expression_compilation_of_math_functions(dolfin):
# Define some PyDOLFIN coefficients
mesh = dolfin.UnitSquareMesh(3, 3)
# Using quadratic element deliberately for accuracy
V = dolfin.FunctionSpace(mesh, "CG", 2)
u = dolfin.Function(V)
u.interpolate(dolfin.Expression("x[0]*x[1]"))
w0 = u
# Define ufl expression with math functions
v = abs(ufl.cos(u))/2 + 0.02
uexpr = ufl.sin(u) + ufl.tan(v) + ufl.exp(u) + ufl.ln(v) + ufl.atan(v) + ufl.acos(v) + ufl.asin(v)
#print dolfin.assemble(uexpr**2*dolfin.dx, mesh=mesh) # 11.7846508409
# Define expected output from compilation
ucode = 'v_w0[0]'
vcode = '0.02 + fabs(cos(v_w0[0])) / 2'
funcs = 'asin(%(v)s) + (acos(%(v)s) + (atan(%(v)s) + (log(%(v)s) + (exp(%(u)s) + (sin(%(u)s) + tan(%(v)s))))))'
oneliner = funcs % {'u':ucode, 'v':vcode}
# Oneliner version (ignoring reuse):
expected_lines = ['double s[1];',
'Array<double> v_w0(1);',
'w0->eval(v_w0, x);',
's[0] = %s;' % oneliner,
'values[0] = s[0];']
#cppcode = format_dolfin_expression(classname="DebugExpression", shape=(), eval_body=expected_lines)
#print '-'*100
#print cppcode
#print '-'*100
#dolfin.plot(dolfin.Expression(cppcode=cppcode, mesh=mesh))
#dolfin.interactive()
# Split version (handles reuse of v, no other reuse):
expected_lines = ['double s[2];',
'Array<double> v_w0(1);',
'w0->eval(v_w0, x);',
's[0] = %s;' % (vcode,),
's[1] = %s;' % (funcs % {'u':ucode,'v':'s[0]'},),
'values[0] = s[1];']
# Define expected evaluation values: [(x,value), (x,value), ...]
import math
x, y = 0.6, 0.7
u = x*y
v = abs(math.cos(u))/2 + 0.02
v0 = .52
expected0 = math.tan(v0) + 1 + math.log(v0) + math.atan(v0) + math.acos(v0) + math.asin(v0)
expected = math.sin(u) + math.tan(v) + math.exp(u) + math.log(v) + math.atan(v) + math.acos(v) + math.asin(v)
expected_values = [((0.0, 0.0), (expected0,)),
((x, y), (expected,)),
]
# Execute all tests
check_dolfin_expression_compilation(uexpr, expected_lines, expected_values, members={'w0':w0})
def ogden_vol(self, params, C):
kappa = params['kappa']
psi_vol = (kappa / 4.) * (self.IIIc - 2. * ln(sqrt(self.IIIc)) - 1.)
S = 2. * diff(psi_vol, C)
return S
def test_assign_to_mfs_sub(cg1, vcg1):
W = cg1*vcg1
w = Function(W)
u = Function(cg1)
v = Function(vcg1)
u.assign(4)
v.assign(10)
w.sub(0).assign(u)
assert np.allclose(w.sub(0).dat.data_ro, 4)
assert np.allclose(w.sub(1).dat.data_ro, 0)
w.sub(1).assign(v)
assert np.allclose(w.sub(0).dat.data_ro, 4)
assert np.allclose(w.sub(1).dat.data_ro, 10)
Q = vcg1*cg1
q = Function(Q)
q.assign(11)
w.sub(1).assign(q.sub(0))
assert np.allclose(w.sub(1).dat.data_ro, 11)
assert np.allclose(w.sub(0).dat.data_ro, 4)
with pytest.raises(ValueError):
w.sub(1).assign(q.sub(1))
with pytest.raises(ValueError):
w.sub(1).assign(w.sub(0))
with pytest.raises(ValueError):
w.sub(1).assign(u)
with pytest.raises(ValueError):
w.sub(0).assign(v)
w.sub(0).assign(ufl.ln(q.sub(1)))
assert np.allclose(w.sub(0).dat.data_ro, ufl.ln(11))
with pytest.raises(ValueError):
w.assign(q.sub(1))
def test_assign_to_mfs_sub(cg1, vcg1):
W = cg1 * vcg1
w = Function(W)
u = Function(cg1)
v = Function(vcg1)
u.assign(4)
v.assign(10)
w.sub(0).assign(u)
assert np.allclose(w.sub(0).dat.data_ro, 4)
assert np.allclose(w.sub(1).dat.data_ro, 0)
w.sub(1).assign(v)
assert np.allclose(w.sub(0).dat.data_ro, 4)
assert np.allclose(w.sub(1).dat.data_ro, 10)
Q = vcg1 * cg1
q = Function(Q)
q.assign(11)
w.sub(1).assign(q.sub(0))
assert np.allclose(w.sub(1).dat.data_ro, 11)
assert np.allclose(w.sub(0).dat.data_ro, 4)
with pytest.raises(ValueError):
w.sub(1).assign(q.sub(1))
with pytest.raises(ValueError):
w.sub(1).assign(w.sub(0))
with pytest.raises(ValueError):
w.sub(1).assign(u)
with pytest.raises(ValueError):
w.sub(0).assign(v)
w.sub(0).assign(ufl.ln(q.sub(1)))
assert np.allclose(w.sub(0).dat.data_ro, ufl.ln(11))
with pytest.raises(ValueError):
w.assign(q.sub(1))
def test_latex_formatting_of_cmath():
x = ufl.SpatialCoordinate(ufl.triangle)[0]
assert expr2latex(ufl.exp(x)) == r"e^{x_0}"
assert expr2latex(ufl.ln(x)) == r"\ln(x_0)"
assert expr2latex(ufl.sqrt(x)) == r"\sqrt{x_0}"
assert expr2latex(abs(x)) == r"\|x_0\|"
assert expr2latex(ufl.sin(x)) == r"\sin(x_0)"
assert expr2latex(ufl.cos(x)) == r"\cos(x_0)"
assert expr2latex(ufl.tan(x)) == r"\tan(x_0)"
assert expr2latex(ufl.asin(x)) == r"\arcsin(x_0)"
assert expr2latex(ufl.acos(x)) == r"\arccos(x_0)"
assert expr2latex(ufl.atan(x)) == r"\arctan(x_0)"
def test_complex_algebra(self):
z1 = ComplexValue(1j)
z2 = ComplexValue(1+1j)
# Remember that ufl.algebra functions return ComplexValues, but ufl.mathfunctions return complex Python scalar
# Any operations with a ComplexValue and a complex Python scalar promote to ComplexValue
assert z1*z2 == ComplexValue(-1+1j)
assert z2/z1 == ComplexValue(1-1j)
assert pow(z2, z1) == ComplexValue((1+1j)**1j)
assert sqrt(z2) * as_ufl(1) == ComplexValue(cmath.sqrt(1+1j))
assert ((sin(z2) + cosh(z2) - atan(z2)) * z1) == ComplexValue((cmath.sin(1+1j) + cmath.cosh(1+1j) - cmath.atan(1+1j))*1j)
assert (abs(z2) - ln(z2))/exp(z1) == ComplexValue((abs(1+1j) - cmath.log(1+1j))/cmath.exp(1j))
def test_cpp_formatting_of_cmath():
x, y = ufl.SpatialCoordinate(ufl.triangle)
# Test cmath functions
assert expr2cpp(ufl.exp(x)) == "exp(x[0])"
assert expr2cpp(ufl.ln(x)) == "log(x[0])"
assert expr2cpp(ufl.sqrt(x)) == "sqrt(x[0])"
assert expr2cpp(abs(x)) == "fabs(x[0])"
assert expr2cpp(ufl.sin(x)) == "sin(x[0])"
assert expr2cpp(ufl.cos(x)) == "cos(x[0])"
assert expr2cpp(ufl.tan(x)) == "tan(x[0])"
assert expr2cpp(ufl.asin(x)) == "asin(x[0])"
assert expr2cpp(ufl.acos(x)) == "acos(x[0])"
assert expr2cpp(ufl.atan(x)) == "atan(x[0])"
def _I(self, v, s, time):
"""
Original gotran transmembrane current dV/dt
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert(len(s) == 7)
m, h, j, Cai, d, f, x1 = s
# Assign parameters
E_Na = self._parameters["E_Na"]
g_Na = self._parameters["g_Na"]
g_Nac = self._parameters["g_Nac"]
g_s = self._parameters["g_s"]
IstimAmplitude = self._parameters["IstimAmplitude"]
IstimPulseDuration = self._parameters["IstimPulseDuration"]
IstimStart = self._parameters["IstimStart"]
C = self._parameters["C"]
# Init return args
current = [ufl.zero()]*1
# Expressions for the Sodium current component
i_Na = (g_Nac + g_Na*(m*m*m)*h*j)*(-E_Na + V)
# Expressions for the Slow inward current component
E_s = -82.3 - 13.0287*ufl.ln(0.001*Cai)
i_s = g_s*(-E_s + V)*d*f
# Expressions for the Time dependent outward current component
i_x1 = 0.00197277571153*(-1 +\
21.7584023962*ufl.exp(0.04*V))*ufl.exp(-0.04*V)*x1
# Expressions for the Time independent outward current component
i_K1 = 0.0035*(-4 +\
119.85640019*ufl.exp(0.04*V))/(8.33113748769*ufl.exp(0.04*V) +\
69.4078518388*ufl.exp(0.08*V)) + 0.0035*(4.6 + 0.2*V)/(1 -\
0.398519041085*ufl.exp(-0.04*V))
# Expressions for the Stimulus protocol component
Istim = ufl.conditional(ufl.And(ufl.ge(time, IstimStart),\
ufl.le(time, IstimPulseDuration + IstimStart)), IstimAmplitude,\
0)
# Expressions for the Membrane component
current[0] = (-i_K1 + Istim - i_Na - i_x1 - i_s)/C
# Return results
return current[0]
def V(self, Us):
"""Calculate potential due to this group
Required argument:
Us: an iterable producing the concentrations of the ligands in the
group. These may be numbers, but in the most important applcation
they are UFL expressions.
"""
if len(Us) != self.nligands:
raise KSDGException('wrong number of ligands %d, should be %d' %
(len(Us), self.nligands))
if self.nligands == 0:
return (0.0)
sU = sum(l.weight * U for l, U in zip(self.ligands, Us))
return (-self.beta * ufl.ln(self.alpha + sU))
def strain_energy(i1, i2, i3):
"""Strain energy function
i1, i2, i3: principal invariants of the Cauchy-Green tensor
"""
# Determinant of configuration gradient F
J = ufl.sqrt(i3) # noqa: F841
#
# Classical St. Venant-Kirchhoff
# Ψ = la / 8 * (i1 - 3)**2 + mu / 4 * ((i1 - 3)**2 + 4 * (i1 - 3) - 2 * (i2 - 3))
# Modified St. Venant-Kirchhoff
# Ψ = la / 2 * (ufl.ln(J))**2 + mu / 4 * ((i1 - 3)**2 + 4 * (i1 - 3) - 2 * (i2 - 3))
# Compressible neo-Hooke
Ψ = mu / 2 * (i1 - 3 - 2 * ufl.ln(J)) + la / 2 * (J - 1)**2
# Compressible Mooney-Rivlin (beta = 0)
# Ψ = mu / 4 * (i1 - 3) + mu / 4 * (i2 - 3) - mu * ufl.ln(J) + la / 2 * (J - 1)**2
#
return Ψ
def Vfunc(U):
return -params['beta'] * ufl.ln(U + params['alpha'])
def test_diff_then_integrate():
# Define 1D geometry
n = 21
mesh = UnitIntervalMesh(MPI.comm_world, n)
# Shift and scale mesh
x0, x1 = 1.5, 3.14
mesh.coordinates()[:] *= (x1 - x0)
mesh.coordinates()[:] += x0
x = SpatialCoordinate(mesh)[0]
xs = 0.1 + 0.8 * x / x1 # scaled to be within [0.1,0.9]
# Define list of expressions to test, and configure
# accuracies these expressions are known to pass with.
# The reason some functions are less accurately integrated is
# likely that the default choice of quadrature rule is not perfect
F_list = []
def reg(exprs, acc=10):
for expr in exprs:
F_list.append((expr, acc))
# FIXME: 0*dx and 1*dx fails in the ufl-ffc-jit framework somewhere
# reg([Constant(0.0, cell=cell)])
# reg([Constant(1.0, cell=cell)])
monomial_list = [x**q for q in range(2, 6)]
reg(monomial_list)
reg([2.3 * p + 4.5 * q for p in monomial_list for q in monomial_list])
reg([x**x])
reg([x**(x**2)], 8)
reg([x**(x**3)], 6)
reg([x**(x**4)], 2)
# Special functions:
reg([atan(xs)], 8)
reg([sin(x), cos(x), exp(x)], 5)
reg([ln(xs), pow(x, 2.7), pow(2.7, x)], 3)
reg([asin(xs), acos(xs)], 1)
reg([tan(xs)], 7)
try:
import scipy
except ImportError:
scipy = None
if hasattr(math, 'erf') or scipy is not None:
reg([erf(xs)])
else:
print(
"Warning: skipping test of erf, old python version and no scipy.")
# if 0:
# print("Warning: skipping tests of bessel functions, doesn't build on all platforms.")
# elif scipy is None:
# print("Warning: skipping tests of bessel functions, missing scipy.")
# else:
# for nu in (0, 1, 2):
# # Many of these are possibly more accurately integrated,
# # but 4 covers all and is sufficient for this test
# reg([bessel_J(nu, xs), bessel_Y(nu, xs), bessel_I(nu, xs), bessel_K(nu, xs)], 4)
# To handle tensor algebra, make an x dependent input tensor
# xx and square all expressions
def reg2(exprs, acc=10):
for expr in exprs:
F_list.append((inner(expr, expr), acc))
xx = as_matrix([[2 * x**2, 3 * x**3], [11 * x**5, 7 * x**4]])
x3v = as_vector([3 * x**2, 5 * x**3, 7 * x**4])
cc = as_matrix([[2, 3], [4, 5]])
reg2([xx])
reg2([x3v])
reg2([cross(3 * x3v, as_vector([-x3v[1], x3v[0], x3v[2]]))])
reg2([xx.T])
reg2([tr(xx)])
reg2([det(xx)])
reg2([dot(xx, 0.1 * xx)])
reg2([outer(xx, xx.T)])
reg2([dev(xx)])
reg2([sym(xx)])
reg2([skew(xx)])
reg2([elem_mult(7 * xx, cc)])
reg2([elem_div(7 * xx, xx + cc)])
reg2([elem_pow(1e-3 * xx, 1e-3 * cc)])
reg2([elem_pow(1e-3 * cc, 1e-3 * xx)])
reg2([elem_op(lambda z: sin(z) + 2, 0.03 * xx)], 2) # pretty inaccurate...
# FIXME: Add tests for all UFL operators:
# These cause discontinuities and may be harder to test in the
# above fashion:
# 'inv', 'cofac',
# 'eq', 'ne', 'le', 'ge', 'lt', 'gt', 'And', 'Or', 'Not',
# 'conditional', 'sign',
# 'jump', 'avg',
# 'LiftingFunction', 'LiftingOperator',
# FIXME: Test other derivatives: (but algorithms for operator
# derivatives are the same!):
# 'variable', 'diff',
# 'Dx', 'grad', 'div', 'curl', 'rot', 'Dn', 'exterior_derivative',
# Run through all operators defined above and compare integrals
debug = 0
for F, acc in F_list:
# Apply UFL differentiation
f = diff(F, SpatialCoordinate(mesh))[..., 0]
if debug:
print(F)
print(x)
print(f)
# Apply integration with DOLFIN
# (also passes through form compilation and jit)
M = f * dx
f_integral = assemble_scalar(M) # noqa
f_integral = MPI.sum(mesh.mpi_comm(), f_integral)
# Compute integral of f manually from anti-derivative F
# (passes through PyDOLFIN interface and uses UFL evaluation)
F_diff = F((x1, )) - F((x0, ))
# Compare results. Using custom relative delta instead
# of decimal digits here because some numbers are >> 1.
delta = min(abs(f_integral), abs(F_diff)) * 10**-acc
assert f_integral - F_diff <= delta
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert(len(s) == 16)
Xr1, Xr2, Xs, m, h, j, d, f, fCa, s, r, g, Ca_i, Ca_SR, Na_i, K_i = s
# Assign parameters
P_kna = self._parameters["P_kna"]
g_K1 = self._parameters["g_K1"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_Na = self._parameters["g_Na"]
g_bna = self._parameters["g_bna"]
g_CaL = self._parameters["g_CaL"]
g_bca = self._parameters["g_bca"]
g_to = self._parameters["g_to"]
K_mNa = self._parameters["K_mNa"]
K_mk = self._parameters["K_mk"]
P_NaK = self._parameters["P_NaK"]
K_NaCa = self._parameters["K_NaCa"]
K_sat = self._parameters["K_sat"]
Km_Ca = self._parameters["Km_Ca"]
Km_Nai = self._parameters["Km_Nai"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
K_pCa = self._parameters["K_pCa"]
g_pCa = self._parameters["g_pCa"]
g_pK = self._parameters["g_pK"]
Buf_c = self._parameters["Buf_c"]
Buf_sr = self._parameters["Buf_sr"]
Ca_o = self._parameters["Ca_o"]
K_buf_c = self._parameters["K_buf_c"]
K_buf_sr = self._parameters["K_buf_sr"]
K_up = self._parameters["K_up"]
V_leak = self._parameters["V_leak"]
V_sr = self._parameters["V_sr"]
Vmax_up = self._parameters["Vmax_up"]
a_rel = self._parameters["a_rel"]
b_rel = self._parameters["b_rel"]
c_rel = self._parameters["c_rel"]
tau_g = self._parameters["tau_g"]
Na_o = self._parameters["Na_o"]
Cm = self._parameters["Cm"]
F = self._parameters["F"]
R = self._parameters["R"]
T = self._parameters["T"]
V_c = self._parameters["V_c"]
stim_amplitude = self._parameters["stim_amplitude"]
stim_duration = self._parameters["stim_duration"]
stim_period = self._parameters["stim_period"]
stim_start = self._parameters["stim_start"]
K_o = self._parameters["K_o"]
# Init return args
F_expressions = [ufl.zero()]*16
# Expressions for the Reversal potentials component
E_Na = R*T*ufl.ln(Na_o/Na_i)/F
E_K = R*T*ufl.ln(K_o/K_i)/F
E_Ks = R*T*ufl.ln((K_o + Na_o*P_kna)/(P_kna*Na_i + K_i))/F
E_Ca = 0.5*R*T*ufl.ln(Ca_o/Ca_i)/F
# Expressions for the Inward rectifier potassium current component
alpha_K1 = 0.1/(1.0 + 6.14421235332821e-06*ufl.exp(0.06*V - 0.06*E_K))
beta_K1 = (0.36787944117144233*ufl.exp(0.1*V - 0.1*E_K) +\
3.0606040200802673*ufl.exp(0.0002*V - 0.0002*E_K))/(1.0 +\
ufl.exp(0.5*E_K - 0.5*V))
xK1_inf = alpha_K1/(alpha_K1 + beta_K1)
i_K1 = 0.4303314829119352*g_K1*ufl.sqrt(K_o)*(-E_K + V)*xK1_inf
# Expressions for the Rapid time dependent potassium current component
i_Kr = 0.4303314829119352*g_Kr*ufl.sqrt(K_o)*(-E_K + V)*Xr1*Xr2
# Expressions for the Xr1 gate component
xr1_inf = 1.0/(1.0 +\
0.02437284407327961*ufl.exp(-0.14285714285714285*V))
alpha_xr1 = 450.0/(1.0 + 0.011108996538242306*ufl.exp(-0.1*V))
beta_xr1 = 6.0/(1.0 +\
13.581324522578193*ufl.exp(0.08695652173913043*V))
tau_xr1 = 1.0*alpha_xr1*beta_xr1
F_expressions[0] = (-Xr1 + xr1_inf)/tau_xr1
# Expressions for the Xr2 gate component
xr2_inf = 1.0/(1.0 + 39.12128399815321*ufl.exp(0.041666666666666664*V))
alpha_xr2 = 3.0/(1.0 + 0.049787068367863944*ufl.exp(-0.05*V))
beta_xr2 = 1.12/(1.0 + 0.049787068367863944*ufl.exp(0.05*V))
tau_xr2 = 1.0*alpha_xr2*beta_xr2
F_expressions[1] = (-Xr2 + xr2_inf)/tau_xr2
# Expressions for the Slow time dependent potassium current component
i_Ks = g_Ks*ufl.elem_pow(Xs, 2.0)*(-E_Ks + V)
# Expressions for the Xs gate component
xs_inf = 1.0/(1.0 + 0.6996725373751304*ufl.exp(-0.07142857142857142*V))
alpha_xs = 1100.0/ufl.sqrt(1.0 +\
0.18887560283756186*ufl.exp(-0.16666666666666666*V))
beta_xs = 1.0/(1.0 + 0.049787068367863944*ufl.exp(0.05*V))
tau_xs = 1.0*alpha_xs*beta_xs
F_expressions[2] = (-Xs + xs_inf)/tau_xs
# Expressions for the Fast sodium current component
i_Na = g_Na*ufl.elem_pow(m, 3.0)*(-E_Na + V)*h*j
# Expressions for the m gate component
m_inf = 1.0*ufl.elem_pow(1.0 +\
0.0018422115811651339*ufl.exp(-0.1107419712070875*V), -2.0)
alpha_m = 1.0/(1.0 + 6.14421235332821e-06*ufl.exp(-0.2*V))
beta_m = 0.1/(1.0 + 1096.6331584284585*ufl.exp(0.2*V)) + 0.1/(1.0 +\
0.7788007830714049*ufl.exp(0.005*V))
tau_m = 1.0*alpha_m*beta_m
F_expressions[3] = (-m + m_inf)/tau_m
# Expressions for the h gate component
h_inf = 1.0*ufl.elem_pow(1.0 +\
15212.593285654404*ufl.exp(0.13458950201884254*V), -2.0)
alpha_h = ufl.conditional(ufl.lt(V, -40.0),\
4.4312679295805147e-07*ufl.exp(-0.14705882352941177*V), 0)
beta_h = ufl.conditional(ufl.lt(V, -40.0), 310000.0*ufl.exp(0.3485*V)\
+ 2.7*ufl.exp(0.079*V), 0.77/(0.13 +\
0.049758141083938695*ufl.exp(-0.0900900900900901*V)))
tau_h = 1.0/(alpha_h + beta_h)
F_expressions[4] = (-h + h_inf)/tau_h
# Expressions for the j gate component
j_inf = 1.0*ufl.elem_pow(1.0 +\
15212.593285654404*ufl.exp(0.13458950201884254*V), -2.0)
alpha_j = ufl.conditional(ufl.lt(V, -40.0), 1.0*(37.78 +\
V)*(-25428.0*ufl.exp(0.2444*V) -\
6.948e-06*ufl.exp(-0.04391*V))/(1.0 +\
50262745825.95399*ufl.exp(0.311*V)), 0)
beta_j = ufl.conditional(ufl.lt(V, -40.0),\
0.02424*ufl.exp(-0.01052*V)/(1.0 +\
0.003960868339904256*ufl.exp(-0.1378*V)),\
0.6*ufl.exp(0.057*V)/(1.0 +\
0.040762203978366204*ufl.exp(-0.1*V)))
tau_j = 1.0/(alpha_j + beta_j)
F_expressions[5] = (-j + j_inf)/tau_j
# Expressions for the Sodium background current component
i_b_Na = g_bna*(-E_Na + V)
# Expressions for the L_type Ca current component
i_CaL = 4.0*g_CaL*ufl.elem_pow(F, 2.0)*(-0.341*Ca_o +\
Ca_i*ufl.exp(2.0*F*V/(R*T)))*V*d*f*fCa/(R*T*(-1.0 +\
ufl.exp(2.0*F*V/(R*T))))
# Expressions for the d gate component
d_inf = 1.0/(1.0 + 0.513417119032592*ufl.exp(-0.13333333333333333*V))
alpha_d = 0.25 + 1.4/(1.0 +\
0.0677244716592409*ufl.exp(-0.07692307692307693*V))
beta_d = 1.4/(1.0 + 2.718281828459045*ufl.exp(0.2*V))
gamma_d = 1.0/(1.0 + 12.182493960703473*ufl.exp(-0.05*V))
tau_d = 1.0*alpha_d*beta_d + gamma_d
F_expressions[6] = (-d + d_inf)/tau_d
# Expressions for the f gate component
f_inf = 1.0/(1.0 + 17.411708063327644*ufl.exp(0.14285714285714285*V))
tau_f = 80.0 + 165.0/(1.0 + 12.182493960703473*ufl.exp(-0.1*V)) +\
1125.0*ufl.exp(-0.004166666666666667*ufl.elem_pow(27.0 + V, 2.0))
F_expressions[7] = (-f + f_inf)/tau_f
# Expressions for the FCa gate component
alpha_fCa = 1.0/(1.0 + 8.03402376701711e+27*ufl.elem_pow(Ca_i, 8.0))
beta_fCa = 0.1/(1.0 + 0.006737946999085467*ufl.exp(10000.0*Ca_i))
gama_fCa = 0.2/(1.0 + 0.391605626676799*ufl.exp(1250.0*Ca_i))
fCa_inf = 0.15753424657534246 + 0.684931506849315*alpha_fCa +\
0.684931506849315*beta_fCa + 0.684931506849315*gama_fCa
tau_fCa = 2.0
d_fCa = (-fCa + fCa_inf)/tau_fCa
F_expressions[8] = ufl.conditional(ufl.And(ufl.gt(V, -60.0),\
ufl.gt(fCa_inf, fCa)), 0, d_fCa)
# Expressions for the Calcium background current component
i_b_Ca = g_bca*(-E_Ca + V)
# Expressions for the Transient outward current component
i_to = g_to*(-E_K + V)*r*s
# Expressions for the s gate component
s_inf = 1.0/(1.0 + 54.598150033144236*ufl.exp(0.2*V))
tau_s = 3.0 + 5.0/(1.0 + 0.01831563888873418*ufl.exp(0.2*V)) +\
85.0*ufl.exp(-0.003125*ufl.elem_pow(45.0 + V, 2.0))
F_expressions[9] = (-s + s_inf)/tau_s
# Expressions for the r gate component
r_inf = 1.0/(1.0 + 28.031624894526125*ufl.exp(-0.16666666666666666*V))
tau_r = 0.8 + 9.5*ufl.exp(-0.0005555555555555556*ufl.elem_pow(40.0 +\
V, 2.0))
F_expressions[10] = (-r + r_inf)/tau_r
# Expressions for the Sodium potassium pump current component
i_NaK = K_o*P_NaK*Na_i/((K_mNa + Na_i)*(K_mk + K_o)*(1.0 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the Sodium calcium exchanger current component
i_NaCa = K_NaCa*(Ca_o*ufl.elem_pow(Na_i,\
3.0)*ufl.exp(F*gamma*V/(R*T)) - alpha*ufl.elem_pow(Na_o,\
3.0)*Ca_i*ufl.exp(F*(-1.0 + gamma)*V/(R*T)))/((1.0 +\
K_sat*ufl.exp(F*(-1.0 + gamma)*V/(R*T)))*(Ca_o +\
Km_Ca)*(ufl.elem_pow(Km_Nai, 3.0) + ufl.elem_pow(Na_o, 3.0)))
# Expressions for the Calcium pump current component
i_p_Ca = g_pCa*Ca_i/(K_pCa + Ca_i)
# Expressions for the Potassium pump current component
i_p_K = g_pK*(-E_K + V)/(1.0 +\
65.40521574193832*ufl.exp(-0.16722408026755853*V))
# Expressions for the Calcium dynamics component
i_rel = (c_rel + a_rel*ufl.elem_pow(Ca_SR, 2.0)/(ufl.elem_pow(b_rel,\
2.0) + ufl.elem_pow(Ca_SR, 2.0)))*d*g
i_up = Vmax_up/(1.0 + ufl.elem_pow(K_up, 2.0)*ufl.elem_pow(Ca_i, -2.0))
i_leak = V_leak*(-Ca_i + Ca_SR)
g_inf = ufl.conditional(ufl.lt(Ca_i, 0.00035), 1.0/(1.0 +\
5.439910241481018e+20*ufl.elem_pow(Ca_i, 6.0)), 1.0/(1.0 +\
1.9720198874049195e+55*ufl.elem_pow(Ca_i, 16.0)))
d_g = (-g + g_inf)/tau_g
F_expressions[11] = ufl.conditional(ufl.And(ufl.gt(V, -60.0),\
ufl.gt(g_inf, g)), 0, d_g)
Ca_i_bufc = 1.0/(1.0 + Buf_c*K_buf_c*ufl.elem_pow(K_buf_c + Ca_i,\
-2.0))
Ca_sr_bufsr = 1.0/(1.0 + Buf_sr*K_buf_sr*ufl.elem_pow(K_buf_sr +\
Ca_SR, -2.0))
F_expressions[12] = (-i_up - 0.5*Cm*(1.0*i_CaL + 1.0*i_b_Ca +\
1.0*i_p_Ca - 2.0*i_NaCa)/(F*V_c) + i_leak + i_rel)*Ca_i_bufc
F_expressions[13] = V_c*(-i_leak - i_rel + i_up)*Ca_sr_bufsr/V_sr
# Expressions for the Sodium dynamics component
F_expressions[14] = 1.0*Cm*(-1.0*i_Na - 1.0*i_b_Na - 3.0*i_NaCa -\
3.0*i_NaK)/(F*V_c)
# Expressions for the Membrane component
i_Stim = ufl.conditional(ufl.And(ufl.ge(time -\
stim_period*ufl.floor(time/stim_period), stim_start), ufl.le(time\
- stim_period*ufl.floor(time/stim_period), stim_duration +\
stim_start)), -stim_amplitude, 0)
# Expressions for the Potassium dynamics component
F_expressions[15] = 1.0*Cm*(2.0*i_NaK - 1.0*i_K1 - 1.0*i_Kr -\
1.0*i_Ks - 1.0*i_Stim - 1.0*i_p_K - 1.0*i_to)/(F*V_c)
# Return results
return dolfin.as_vector(F_expressions)
chi = 0.2
po = Gdry/lamo
muo = Rg*T*(math.log(Omega*cod/(1+Omega*cod))+1/(1+Omega*cod)+ chi/pow((1+Omega*cod),2)) \
+Omega*po
mus = muo
mutop = -10000
# Kinematics
I = Identity(3)
F = I + grad(u)
J = det(F)
# Constitutive equations
S = (Gdry/lamo)*F-p*cofac(F)
mu = Rg*T*(ufl.ln(Omega*Jo*c/(1+Omega*Jo*c)) + 1./(1.+Omega*Jo*c)+ \
chi/pow((1.+Omega*Jo*c),2))+Omega*p
h = g(c)*grad(c)+(-c*D/(Rg*T))*Omega*grad(p)
dmudp = Omega
dmu = mu-mus
# Boundary conditions
def left_boundary(x, on_boundary): # x = 0
return on_boundary and abs(x[0]) < DOLFIN_EPS
def back_boundary(x, on_boundary): # y = 0
return on_boundary and abs(x[1]) < DOLFIN_EPS
def test_div_grad_then_integrate_over_cells_and_boundary():
# Define 2D geometry
n = 10
mesh = RectangleMesh(Point(0.0, 0.0), Point(2.0, 3.0), 2 * n, 3 * n)
x, y = SpatialCoordinate(mesh)
xs = 0.1 + 0.8 * x / 2 # scaled to be within [0.1,0.9]
# ys = 0.1 + 0.8 * y / 3 # scaled to be within [0.1,0.9]
n = FacetNormal(mesh)
# Define list of expressions to test, and configure accuracies
# these expressions are known to pass with. The reason some
# functions are less accurately integrated is likely that the
# default choice of quadrature rule is not perfect
F_list = []
def reg(exprs, acc=10):
for expr in exprs:
F_list.append((expr, acc))
# FIXME: 0*dx and 1*dx fails in the ufl-ffc-jit framework somewhere
# reg([Constant(0.0, cell=cell)])
# reg([Constant(1.0, cell=cell)])
monomial_list = [x**q for q in range(2, 6)]
reg(monomial_list)
reg([2.3 * p + 4.5 * q for p in monomial_list for q in monomial_list])
reg([xs**xs])
reg(
[xs**(xs**2)], 8
) # Note: Accuracies here are from 1D case, not checked against 2D results.
reg([xs**(xs**3)], 6)
reg([xs**(xs**4)], 2)
# Special functions:
reg([atan(xs)], 8)
reg([sin(x), cos(x), exp(x)], 5)
reg([ln(xs), pow(x, 2.7), pow(2.7, x)], 3)
reg([asin(xs), acos(xs)], 1)
reg([tan(xs)], 7)
# To handle tensor algebra, make an x dependent input tensor
# xx and square all expressions
def reg2(exprs, acc=10):
for expr in exprs:
F_list.append((inner(expr, expr), acc))
xx = as_matrix([[2 * x**2, 3 * x**3], [11 * x**5, 7 * x**4]])
xxs = as_matrix([[2 * xs**2, 3 * xs**3], [11 * xs**5, 7 * xs**4]])
x3v = as_vector([3 * x**2, 5 * x**3, 7 * x**4])
cc = as_matrix([[2, 3], [4, 5]])
reg2(
[xx]
) # TODO: Make unit test for UFL from this, results in listtensor with free indices
reg2([x3v])
reg2([cross(3 * x3v, as_vector([-x3v[1], x3v[0], x3v[2]]))])
reg2([xx.T])
reg2([tr(xx)])
reg2([det(xx)])
reg2([dot(xx, 0.1 * xx)])
reg2([outer(xx, xx.T)])
reg2([dev(xx)])
reg2([sym(xx)])
reg2([skew(xx)])
reg2([elem_mult(7 * xx, cc)])
reg2([elem_div(7 * xx, xx + cc)])
reg2([elem_pow(1e-3 * xxs, 1e-3 * cc)])
reg2([elem_pow(1e-3 * cc, 1e-3 * xx)])
reg2([elem_op(lambda z: sin(z) + 2, 0.03 * xx)], 2) # pretty inaccurate...
# FIXME: Add tests for all UFL operators:
# These cause discontinuities and may be harder to test in the
# above fashion:
# 'inv', 'cofac',
# 'eq', 'ne', 'le', 'ge', 'lt', 'gt', 'And', 'Or', 'Not',
# 'conditional', 'sign',
# 'jump', 'avg',
# 'LiftingFunction', 'LiftingOperator',
# FIXME: Test other derivatives: (but algorithms for operator
# derivatives are the same!):
# 'variable', 'diff',
# 'Dx', 'grad', 'div', 'curl', 'rot', 'Dn', 'exterior_derivative',
# Run through all operators defined above and compare integrals
debug = 0
if debug:
F_list = F_list[1:]
for F, acc in F_list:
if debug:
print('\n', "F:", str(F))
# Integrate over domain and its boundary
int_dx = assemble(div(grad(F)) * dx(mesh)) # noqa
int_ds = assemble(dot(grad(F), n) * ds(mesh)) # noqa
if debug:
print(int_dx, int_ds)
# Compare results. Using custom relative delta instead of
# decimal digits here because some numbers are >> 1.
delta = min(abs(int_dx), abs(int_ds)) * 10**-acc
assert int_dx - int_ds <= delta
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert (len(s) == 18)
Xr1, Xr2, Xs, m, h, j, d, f, f2, fCass, s, r, Ca_SR, Ca_i, Ca_ss,\
R_prime, Na_i, K_i = s
# Assign parameters
P_kna = self._parameters["P_kna"]
g_K1 = self._parameters["g_K1"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_Na = self._parameters["g_Na"]
g_bna = self._parameters["g_bna"]
g_CaL = self._parameters["g_CaL"]
g_bca = self._parameters["g_bca"]
g_to = self._parameters["g_to"]
K_mNa = self._parameters["K_mNa"]
K_mk = self._parameters["K_mk"]
P_NaK = self._parameters["P_NaK"]
K_NaCa = self._parameters["K_NaCa"]
K_sat = self._parameters["K_sat"]
Km_Ca = self._parameters["Km_Ca"]
Km_Nai = self._parameters["Km_Nai"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
K_pCa = self._parameters["K_pCa"]
g_pCa = self._parameters["g_pCa"]
g_pK = self._parameters["g_pK"]
Buf_c = self._parameters["Buf_c"]
Buf_sr = self._parameters["Buf_sr"]
Buf_ss = self._parameters["Buf_ss"]
Ca_o = self._parameters["Ca_o"]
EC = self._parameters["EC"]
K_buf_c = self._parameters["K_buf_c"]
K_buf_sr = self._parameters["K_buf_sr"]
K_buf_ss = self._parameters["K_buf_ss"]
K_up = self._parameters["K_up"]
V_leak = self._parameters["V_leak"]
V_rel = self._parameters["V_rel"]
V_sr = self._parameters["V_sr"]
V_ss = self._parameters["V_ss"]
V_xfer = self._parameters["V_xfer"]
Vmax_up = self._parameters["Vmax_up"]
k1_prime = self._parameters["k1_prime"]
k2_prime = self._parameters["k2_prime"]
k3 = self._parameters["k3"]
k4 = self._parameters["k4"]
max_sr = self._parameters["max_sr"]
min_sr = self._parameters["min_sr"]
Na_o = self._parameters["Na_o"]
Cm = self._parameters["Cm"]
F = self._parameters["F"]
R = self._parameters["R"]
T = self._parameters["T"]
V_c = self._parameters["V_c"]
K_o = self._parameters["K_o"]
# Init return args
F_expressions = [ufl.zero()] * 18
# Expressions for the Reversal potentials component
E_Na = R * T * ufl.ln(Na_o / Na_i) / F
E_K = R * T * ufl.ln(K_o / K_i) / F
E_Ks = R * T * ufl.ln((Na_o * P_kna + K_o) / (K_i + P_kna * Na_i)) / F
E_Ca = 0.5 * R * T * ufl.ln(Ca_o / Ca_i) / F
# Expressions for the Inward rectifier potassium current component
alpha_K1 = 0.1 / (1 +
6.14421235333e-06 * ufl.exp(-0.06 * E_K + 0.06 * V))
beta_K1 = (3.06060402008*ufl.exp(0.0002*V - 0.0002*E_K) +\
0.367879441171*ufl.exp(0.1*V - 0.1*E_K))/(1 + ufl.exp(0.5*E_K -\
0.5*V))
xK1_inf = alpha_K1 / (alpha_K1 + beta_K1)
i_K1 = 0.430331482912 * g_K1 * ufl.sqrt(K_o) * (-E_K + V) * xK1_inf
# Expressions for the Rapid time dependent potassium current component
i_Kr = 0.430331482912 * g_Kr * ufl.sqrt(K_o) * (-E_K + V) * Xr1 * Xr2
# Expressions for the Xr1 gate component
xr1_inf = 1.0 / (1 + ufl.exp(-26 / 7 - V / 7))
alpha_xr1 = 450 / (1 + ufl.exp(-9 / 2 - V / 10))
beta_xr1 = 6 / (1 + 13.5813245226 * ufl.exp(0.0869565217391 * V))
tau_xr1 = alpha_xr1 * beta_xr1
F_expressions[0] = (xr1_inf - Xr1) / tau_xr1
# Expressions for the Xr2 gate component
xr2_inf = 1.0 / (1 + ufl.exp(11 / 3 + V / 24))
alpha_xr2 = 3 / (1 + ufl.exp(-3 - V / 20))
beta_xr2 = 1.12 / (1 + ufl.exp(-3 + V / 20))
tau_xr2 = alpha_xr2 * beta_xr2
F_expressions[1] = (xr2_inf - Xr2) / tau_xr2
# Expressions for the Slow time dependent potassium current component
i_Ks = g_Ks * (Xs * Xs) * (-E_Ks + V)
# Expressions for the Xs gate component
xs_inf = 1.0 / (1 + ufl.exp(-5 / 14 - V / 14))
alpha_xs = 1400 / ufl.sqrt(1 + ufl.exp(5 / 6 - V / 6))
beta_xs = 1.0 / (1 + ufl.exp(-7 / 3 + V / 15))
tau_xs = 80 + alpha_xs * beta_xs
F_expressions[2] = (xs_inf - Xs) / tau_xs
# Expressions for the Fast sodium current component
i_Na = g_Na * (m * m * m) * (-E_Na + V) * h * j
# Expressions for the m gate component
m_inf = 1.0/((1 + 0.00184221158117*ufl.exp(-0.110741971207*V))*(1 +\
0.00184221158117*ufl.exp(-0.110741971207*V)))
alpha_m = 1.0 / (1 + ufl.exp(-12 - V / 5))
beta_m = 0.1 / (1 + ufl.exp(-1 / 4 + V / 200)) + 0.1 / (
1 + ufl.exp(7 + V / 5))
tau_m = alpha_m * beta_m
F_expressions[3] = (-m + m_inf) / tau_m
# Expressions for the h gate component
h_inf = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V)))
alpha_h = ufl.conditional(ufl.lt(V, -40),\
4.43126792958e-07*ufl.exp(-0.147058823529*V), 0)
beta_h = ufl.conditional(ufl.lt(V, -40), 2.7*ufl.exp(0.079*V) +\
310000*ufl.exp(0.3485*V), 0.77/(0.13 +\
0.0497581410839*ufl.exp(-0.0900900900901*V)))
tau_h = 1.0 / (alpha_h + beta_h)
F_expressions[4] = (-h + h_inf) / tau_h
# Expressions for the j gate component
j_inf = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V)))
alpha_j = ufl.conditional(ufl.lt(V, -40), (37.78 +\
V)*(-25428*ufl.exp(0.2444*V) - 6.948e-06*ufl.exp(-0.04391*V))/(1 +\
50262745826.0*ufl.exp(0.311*V)), 0)
beta_j = ufl.conditional(ufl.lt(V, -40),\
0.02424*ufl.exp(-0.01052*V)/(1 +\
0.0039608683399*ufl.exp(-0.1378*V)), 0.6*ufl.exp(0.057*V)/(1 +\
0.0407622039784*ufl.exp(-0.1*V)))
tau_j = 1.0 / (alpha_j + beta_j)
F_expressions[5] = (-j + j_inf) / tau_j
# Expressions for the Sodium background current component
i_b_Na = g_bna * (-E_Na + V)
# Expressions for the L_type Ca current component
i_CaL = 4*g_CaL*(F*F)*(-15 + V)*(0.25*Ca_ss*ufl.exp(F*(-30 +\
2*V)/(R*T)) - Ca_o)*d*f*f2*fCass/(R*T*(-1 + ufl.exp(F*(-30 +\
2*V)/(R*T))))
# Expressions for the d gate component
d_inf = 1.0 / (1 + 0.344153786865 * ufl.exp(-0.133333333333 * V))
alpha_d = 0.25 + 1.4 / (1 + ufl.exp(-35 / 13 - V / 13))
beta_d = 1.4 / (1 + ufl.exp(1 + V / 5))
gamma_d = 1.0 / (1 + ufl.exp(5 / 2 - V / 20))
tau_d = alpha_d * beta_d + gamma_d
F_expressions[6] = (-d + d_inf) / tau_d
# Expressions for the f gate component
f_inf = 1.0 / (1 + ufl.exp(20 / 7 + V / 7))
tau_f = 20 + 1102.5*ufl.exp(-((27 + V)*(27 + V))/225) + 180/(1 +\
ufl.exp(3 + V/10)) + 200/(1 + ufl.exp(13/10 - V/10))
F_expressions[7] = (f_inf - f) / tau_f
# Expressions for the F2 gate component
f2_inf = 0.33 + 0.67 / (1 + ufl.exp(5 + V / 7))
tau_f2 = 80/(1 + ufl.exp(3 + V/10)) + 562*ufl.exp(-((27 + V)*(27 +\
V))/240) + 31/(1 + ufl.exp(5/2 - V/10))
F_expressions[8] = (-f2 + f2_inf) / tau_f2
# Expressions for the FCass gate component
fCass_inf = 0.4 + 0.6 / (1 + 400.0 * (Ca_ss * Ca_ss))
tau_fCass = 2 + 80 / (1 + 400.0 * (Ca_ss * Ca_ss))
F_expressions[9] = (fCass_inf - fCass) / tau_fCass
# Expressions for the Calcium background current component
i_b_Ca = g_bca * (-E_Ca + V)
# Expressions for the Transient outward current component
i_to = g_to * (-E_K + V) * r * s
# Expressions for the s gate component
s_inf = 1.0 / (1 + ufl.exp(4 + V / 5))
tau_s = 3 + 5/(1 + ufl.exp(-4 + V/5)) + 85*ufl.exp(-((45 + V)*(45 +\
V))/320)
F_expressions[10] = (s_inf - s) / tau_s
# Expressions for the r gate component
r_inf = 1.0 / (1 + ufl.exp(10 / 3 - V / 6))
tau_r = 0.8 + 9.5 * ufl.exp(-((40 + V) * (40 + V)) / 1800)
F_expressions[11] = (r_inf - r) / tau_r
# Expressions for the Sodium potassium pump current component
i_NaK = K_o*P_NaK*Na_i/((K_mNa + Na_i)*(K_mk + K_o)*(1 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the Sodium calcium exchanger current component
i_NaCa = K_NaCa*(-alpha*(Na_o*Na_o*Na_o)*Ca_i*ufl.exp(F*(-1 +\
gamma)*V/(R*T)) +\
Ca_o*(Na_i*Na_i*Na_i)*ufl.exp(F*gamma*V/(R*T)))/((1 +\
K_sat*ufl.exp(F*(-1 + gamma)*V/(R*T)))*(Km_Ca +\
Ca_o)*((Na_o*Na_o*Na_o) + (Km_Nai*Km_Nai*Km_Nai)))
# Expressions for the Calcium pump current component
i_p_Ca = g_pCa * Ca_i / (Ca_i + K_pCa)
# Expressions for the Potassium pump current component
i_p_K = g_pK * (-E_K +
V) / (1 + 65.4052157419 * ufl.exp(-0.167224080268 * V))
# Expressions for the Calcium dynamics component
i_up = Vmax_up / (1 + (K_up * K_up) / (Ca_i * Ca_i))
i_leak = V_leak * (Ca_SR - Ca_i)
i_xfer = V_xfer * (Ca_ss - Ca_i)
kcasr = max_sr - (-min_sr + max_sr) / (1 + (EC * EC) / (Ca_SR * Ca_SR))
Ca_i_bufc = 1.0 / (1 + Buf_c * K_buf_c / ((Ca_i + K_buf_c) *
(Ca_i + K_buf_c)))
Ca_sr_bufsr = 1.0/(1 + Buf_sr*K_buf_sr/((Ca_SR + K_buf_sr)*(Ca_SR +\
K_buf_sr)))
Ca_ss_bufss = 1.0/(1 + Buf_ss*K_buf_ss/((Ca_ss + K_buf_ss)*(Ca_ss +\
K_buf_ss)))
F_expressions[13] = (i_xfer - Cm*(i_b_Ca + i_p_Ca -\
2*i_NaCa)/(2*F*V_c) + V_sr*(-i_up + i_leak)/V_c)*Ca_i_bufc
k1 = k1_prime / kcasr
k2 = k2_prime * kcasr
O = (Ca_ss * Ca_ss) * R_prime * k1 / ((Ca_ss * Ca_ss) * k1 + k3)
F_expressions[15] = -Ca_ss * R_prime * k2 + k4 * (1 - R_prime)
i_rel = V_rel * (Ca_SR - Ca_ss) * O
F_expressions[12] = (i_up - i_leak - i_rel) * Ca_sr_bufsr
F_expressions[14] = (-Cm*i_CaL/(2*F*V_ss) - V_c*i_xfer/V_ss +\
V_sr*i_rel/V_ss)*Ca_ss_bufss
# Expressions for the Sodium dynamics component
F_expressions[16] = Cm * (-i_b_Na - i_Na - 3 * i_NaCa -
3 * i_NaK) / (F * V_c)
# Expressions for the Membrane component
i_Stim = 0
# Expressions for the Potassium dynamics component
F_expressions[17] = Cm*(2*i_NaK - i_Ks - i_Stim - i_Kr - i_to - i_p_K\
- i_K1)/(F*V_c)
# Return results
return as_vector(F_expressions)
# Before defining the energy density and thus the total potential # energy, it only remains to specify constants for the elasticity # parameters:: # Elasticity parameters E = 10.0 nu = 0.3 mu = E/(2*(1 + nu)) lmbda = E*nu/((1 + nu)*(1 - 2*nu)) # Both the first variation of the potential energy, and the Jacobian of # the variation, can be automatically computed by a call to # ``derivative``:: # Stored strain energy density (compressible neo-Hookean model) psi = (mu/2)*(Ic - 3) - mu*ln(J) + (lmbda/2)*(ln(J))**2 # Total potential energy Pi = psi*dx # - inner(B, u)*dx - inner(T, u)*ds # First variation of Pi (directional derivative about u in the direction of v) F_form = derivative(Pi, u, v) # Compute Jacobian of F J_form = derivative(F_form, u, du) # Compute Cauchy stress sigma = (1/J)*diff(psi, F)*F.T forms = [F_form, J_form] elements = [(element)]
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert(len(s) == 16)
Xr1, Xr2, Xs, m, h, j, d, f, fCa, s, r, Ca_SR, Ca_i, g, Na_i, K_i = s
# Assign parameters
P_kna = self._parameters["P_kna"]
g_K1 = self._parameters["g_K1"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_Na = self._parameters["g_Na"]
g_bna = self._parameters["g_bna"]
g_CaL = self._parameters["g_CaL"]
g_bca = self._parameters["g_bca"]
g_to = self._parameters["g_to"]
K_mNa = self._parameters["K_mNa"]
K_mk = self._parameters["K_mk"]
P_NaK = self._parameters["P_NaK"]
K_NaCa = self._parameters["K_NaCa"]
K_sat = self._parameters["K_sat"]
Km_Ca = self._parameters["Km_Ca"]
Km_Nai = self._parameters["Km_Nai"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
K_pCa = self._parameters["K_pCa"]
g_pCa = self._parameters["g_pCa"]
g_pK = self._parameters["g_pK"]
Buf_c = self._parameters["Buf_c"]
Buf_sr = self._parameters["Buf_sr"]
Ca_o = self._parameters["Ca_o"]
K_buf_c = self._parameters["K_buf_c"]
K_buf_sr = self._parameters["K_buf_sr"]
K_up = self._parameters["K_up"]
V_leak = self._parameters["V_leak"]
V_sr = self._parameters["V_sr"]
Vmax_up = self._parameters["Vmax_up"]
a_rel = self._parameters["a_rel"]
b_rel = self._parameters["b_rel"]
c_rel = self._parameters["c_rel"]
tau_g = self._parameters["tau_g"]
Na_o = self._parameters["Na_o"]
Cm = self._parameters["Cm"]
F = self._parameters["F"]
R = self._parameters["R"]
T = self._parameters["T"]
V_c = self._parameters["V_c"]
stim_amplitude = self._parameters["stim_amplitude"]
stim_duration = self._parameters["stim_duration"]
stim_start = self._parameters["stim_start"]
K_o = self._parameters["K_o"]
# Init return args
F_expressions = [ufl.zero()]*16
# Expressions for the Reversal potentials component
E_Na = R*T*ufl.ln(Na_o/Na_i)/F
E_K = R*T*ufl.ln(K_o/K_i)/F
E_Ks = R*T*ufl.ln((Na_o*P_kna + K_o)/(K_i + P_kna*Na_i))/F
E_Ca = 0.5*R*T*ufl.ln(Ca_o/Ca_i)/F
# Expressions for the Inward rectifier potassium current component
alpha_K1 = 0.1/(1 + 6.14421235333e-06*ufl.exp(-0.06*E_K + 0.06*V))
beta_K1 = (3.06060402008*ufl.exp(0.0002*V - 0.0002*E_K) +\
0.367879441171*ufl.exp(0.1*V - 0.1*E_K))/(1 + ufl.exp(0.5*E_K -\
0.5*V))
xK1_inf = alpha_K1/(alpha_K1 + beta_K1)
i_K1 = 0.430331482912*g_K1*ufl.sqrt(K_o)*(-E_K + V)*xK1_inf
# Expressions for the Rapid time dependent potassium current component
i_Kr = 0.430331482912*g_Kr*ufl.sqrt(K_o)*(-E_K + V)*Xr1*Xr2
# Expressions for the Xr1 gate component
xr1_inf = 1.0/(1 + ufl.exp(-26/7 - V/7))
alpha_xr1 = 450/(1 + ufl.exp(-9/2 - V/10))
beta_xr1 = 6/(1 + 13.5813245226*ufl.exp(0.0869565217391*V))
tau_xr1 = alpha_xr1*beta_xr1
F_expressions[0] = (xr1_inf - Xr1)/tau_xr1
# Expressions for the Xr2 gate component
xr2_inf = 1.0/(1 + ufl.exp(11/3 + V/24))
alpha_xr2 = 3/(1 + ufl.exp(-3 - V/20))
beta_xr2 = 1.12/(1 + ufl.exp(-3 + V/20))
tau_xr2 = alpha_xr2*beta_xr2
F_expressions[1] = (xr2_inf - Xr2)/tau_xr2
# Expressions for the Slow time dependent potassium current component
i_Ks = g_Ks*(Xs*Xs)*(-E_Ks + V)
# Expressions for the Xs gate component
xs_inf = 1.0/(1 + ufl.exp(-5/14 - V/14))
alpha_xs = 1100/ufl.sqrt(1 + ufl.exp(-5/3 - V/6))
beta_xs = 1.0/(1 + ufl.exp(-3 + V/20))
tau_xs = alpha_xs*beta_xs
F_expressions[2] = (xs_inf - Xs)/tau_xs
# Expressions for the Fast sodium current component
i_Na = g_Na*(m*m*m)*(-E_Na + V)*h*j
# Expressions for the m gate component
m_inf = 1.0/((1 + 0.00184221158117*ufl.exp(-0.110741971207*V))*(1 +\
0.00184221158117*ufl.exp(-0.110741971207*V)))
alpha_m = 1.0/(1 + ufl.exp(-12 - V/5))
beta_m = 0.1/(1 + ufl.exp(-1/4 + V/200)) + 0.1/(1 + ufl.exp(7 + V/5))
tau_m = alpha_m*beta_m
F_expressions[3] = (-m + m_inf)/tau_m
# Expressions for the h gate component
h_inf = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V)))
alpha_h = 4.43126792958e-07*ufl.exp(-0.147058823529*V)/(1 +\
2.35385266837e+17*ufl.exp(1.0*V))
beta_h = (2.7*ufl.exp(0.079*V) + 310000*ufl.exp(0.3485*V))/(1 +\
2.35385266837e+17*ufl.exp(1.0*V)) + 0.77*(1 - 1/(1 +\
2.35385266837e+17*ufl.exp(1.0*V)))/(0.13 +\
0.0497581410839*ufl.exp(-0.0900900900901*V))
tau_h = 1.0/(alpha_h + beta_h)
F_expressions[4] = (-h + h_inf)/tau_h
# Expressions for the j gate component
j_inf = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V)))
alpha_j = (37.78 + V)*(-25428*ufl.exp(0.2444*V) -\
6.948e-06*ufl.exp(-0.04391*V))/((1 +\
2.35385266837e+17*ufl.exp(1.0*V))*(1 +\
50262745826.0*ufl.exp(0.311*V)))
beta_j = 0.6*(1 - 1/(1 +\
2.35385266837e+17*ufl.exp(1.0*V)))*ufl.exp(0.057*V)/(1 +\
0.0407622039784*ufl.exp(-0.1*V)) +\
0.02424*ufl.exp(-0.01052*V)/((1 +\
2.35385266837e+17*ufl.exp(1.0*V))*(1 +\
0.0039608683399*ufl.exp(-0.1378*V)))
tau_j = 1.0/(alpha_j + beta_j)
F_expressions[5] = (-j + j_inf)/tau_j
# Expressions for the Sodium background current component
i_b_Na = g_bna*(-E_Na + V)
# Expressions for the L_type Ca current component
i_CaL = 4*g_CaL*(F*F)*(Ca_i*ufl.exp(2*F*V/(R*T)) -\
0.341*Ca_o)*V*d*f*fCa/(R*T*(-1 + ufl.exp(2*F*V/(R*T))))
# Expressions for the d gate component
d_inf = 1.0/(1 + 0.513417119033*ufl.exp(-0.133333333333*V))
alpha_d = 0.25 + 1.4/(1 + ufl.exp(-35/13 - V/13))
beta_d = 1.4/(1 + ufl.exp(1 + V/5))
gamma_d = 1.0/(1 + ufl.exp(5/2 - V/20))
tau_d = alpha_d*beta_d + gamma_d
F_expressions[6] = (-d + d_inf)/tau_d
# Expressions for the f gate component
f_inf = 1.0/(1 + ufl.exp(20/7 + V/7))
tau_f = 80 + 1125*ufl.exp(-((27 + V)*(27 + V))/240) + 165/(1 +\
ufl.exp(5/2 - V/10))
F_expressions[7] = (f_inf - f)/tau_f
# Expressions for the FCa gate component
alpha_fCa = 1.0/(1 + 8.03402376702e+27*ufl.elem_pow(Ca_i, 8))
exp_arg_0 = -5.0 + 10000.0*Ca_i
exp_arg_00 = ufl.conditional(ufl.lt(exp_arg_0, 500.0), exp_arg_0,\
500.0)
beta_fCa = 0.1/(1 + ufl.exp(exp_arg_00))
exp_arg_1 = -0.9375 + 1250.0*Ca_i
exp_arg_11 = ufl.conditional(ufl.lt(exp_arg_1, 500.0), exp_arg_1,\
500.0)
gama_fCa = 0.2/(1 + ufl.exp(exp_arg_11))
fCa_inf = 0.157534246575 + 0.684931506849*gama_fCa +\
0.684931506849*alpha_fCa + 0.684931506849*beta_fCa
tau_fCa = 2
d_fCa = (-fCa + fCa_inf)/tau_fCa
F_expressions[8] = ufl.conditional(ufl.And(ufl.gt(V, -60),\
ufl.gt(fCa_inf, fCa)), 0, d_fCa)
# Expressions for the Calcium background current component
i_b_Ca = g_bca*(-E_Ca + V)
# Expressions for the Transient outward current component
i_to = g_to*(-E_K + V)*r*s
# Expressions for the s gate component
s_inf = 1.0/(1 + ufl.exp(4 + V/5))
tau_s = 3 + 5/(1 + ufl.exp(-4 + V/5)) + 85*ufl.exp(-((45 + V)*(45 +\
V))/320)
F_expressions[9] = (s_inf - s)/tau_s
# Expressions for the r gate component
r_inf = 1.0/(1 + ufl.exp(10/3 - V/6))
tau_r = 0.8 + 9.5*ufl.exp(-((40 + V)*(40 + V))/1800)
F_expressions[10] = (r_inf - r)/tau_r
# Expressions for the Sodium potassium pump current component
i_NaK = K_o*P_NaK*Na_i/((K_mNa + Na_i)*(K_mk + K_o)*(1 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the Sodium calcium exchanger current component
i_NaCa = K_NaCa*(-alpha*(Na_o*Na_o*Na_o)*Ca_i*ufl.exp(F*(-1 +\
gamma)*V/(R*T)) +\
Ca_o*(Na_i*Na_i*Na_i)*ufl.exp(F*gamma*V/(R*T)))/((1 +\
K_sat*ufl.exp(F*(-1 + gamma)*V/(R*T)))*(Km_Ca +\
Ca_o)*((Na_o*Na_o*Na_o) + (Km_Nai*Km_Nai*Km_Nai)))
# Expressions for the Calcium pump current component
i_p_Ca = g_pCa*Ca_i/(Ca_i + K_pCa)
# Expressions for the Potassium pump current component
i_p_K = g_pK*(-E_K + V)/(1 + 65.4052157419*ufl.exp(-0.167224080268*V))
# Expressions for the Calcium dynamics component
i_rel = (c_rel + a_rel*(Ca_SR*Ca_SR)/((b_rel*b_rel) +\
(Ca_SR*Ca_SR)))*d*g
i_up = Vmax_up/(1 + (K_up*K_up)/(Ca_i*Ca_i))
i_leak = V_leak*(Ca_SR - Ca_i)
g_inf = 1/((1 + 0.0301973834223*ufl.exp(10000.0*Ca_i))*(1 +\
5.43991024148e+20*ufl.elem_pow(Ca_i, 6))) + (1 - 1/(1 +\
0.0301973834223*ufl.exp(10000.0*Ca_i)))/(1 +\
1.9720198874e+55*ufl.elem_pow(Ca_i, 16))
d_g = (-g + g_inf)/tau_g
F_expressions[13] = (1 - 1.0/((1 + ufl.exp(60 + V))*(1 +\
ufl.exp(10.0*g_inf - 10.0*g))))*d_g
Ca_i_bufc = 1.0/(1 + Buf_c*K_buf_c/((Ca_i + K_buf_c)*(Ca_i + K_buf_c)))
Ca_sr_bufsr = 1.0/(1 + Buf_sr*K_buf_sr/((Ca_SR + K_buf_sr)*(Ca_SR +\
K_buf_sr)))
F_expressions[12] = (i_rel - i_up - Cm*(i_b_Ca + i_p_Ca - 2*i_NaCa +\
i_CaL)/(2*F*V_c) + i_leak)*Ca_i_bufc
F_expressions[11] = V_c*(i_up - i_leak - i_rel)*Ca_sr_bufsr/V_sr
# Expressions for the Sodium dynamics component
F_expressions[14] = Cm*(-i_b_Na - i_Na - 3*i_NaCa - 3*i_NaK)/(F*V_c)
# Expressions for the Membrane component
i_Stim = -stim_amplitude*(1 - 1/(1 + ufl.exp(5.0*time -\
5.0*stim_start)))/(1 + ufl.exp(5.0*time - 5.0*stim_start -\
5.0*stim_duration))
# Expressions for the Potassium dynamics component
F_expressions[15] = Cm*(2*i_NaK - i_Ks - i_Kr - i_to - i_Stim - i_p_K\
- i_K1)/(F*V_c)
# Return results
return dolfin.as_vector(F_expressions)
def _I(self, v, s, time):
"""
Original gotran transmembrane current dV/dt
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert(len(s) == 16)
Xr1, Xr2, Xs, m, h, j, d, f, fCa, s, r, g, Ca_i, Ca_SR, Na_i, K_i = s
# Assign parameters
P_kna = self._parameters["P_kna"]
g_K1 = self._parameters["g_K1"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_Na = self._parameters["g_Na"]
g_bna = self._parameters["g_bna"]
g_CaL = self._parameters["g_CaL"]
g_bca = self._parameters["g_bca"]
g_to = self._parameters["g_to"]
K_mNa = self._parameters["K_mNa"]
K_mk = self._parameters["K_mk"]
P_NaK = self._parameters["P_NaK"]
K_NaCa = self._parameters["K_NaCa"]
K_sat = self._parameters["K_sat"]
Km_Ca = self._parameters["Km_Ca"]
Km_Nai = self._parameters["Km_Nai"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
K_pCa = self._parameters["K_pCa"]
g_pCa = self._parameters["g_pCa"]
g_pK = self._parameters["g_pK"]
Ca_o = self._parameters["Ca_o"]
Na_o = self._parameters["Na_o"]
F = self._parameters["F"]
R = self._parameters["R"]
T = self._parameters["T"]
stim_amplitude = self._parameters["stim_amplitude"]
stim_duration = self._parameters["stim_duration"]
stim_period = self._parameters["stim_period"]
stim_start = self._parameters["stim_start"]
K_o = self._parameters["K_o"]
# Init return args
current = [ufl.zero()]*1
# Expressions for the Reversal potentials component
E_Na = R*T*ufl.ln(Na_o/Na_i)/F
E_K = R*T*ufl.ln(K_o/K_i)/F
E_Ks = R*T*ufl.ln((K_o + Na_o*P_kna)/(P_kna*Na_i + K_i))/F
E_Ca = 0.5*R*T*ufl.ln(Ca_o/Ca_i)/F
# Expressions for the Inward rectifier potassium current component
alpha_K1 = 0.1/(1.0 + 6.14421235332821e-06*ufl.exp(0.06*V - 0.06*E_K))
beta_K1 = (0.36787944117144233*ufl.exp(0.1*V - 0.1*E_K) +\
3.0606040200802673*ufl.exp(0.0002*V - 0.0002*E_K))/(1.0 +\
ufl.exp(0.5*E_K - 0.5*V))
xK1_inf = alpha_K1/(alpha_K1 + beta_K1)
i_K1 = 0.4303314829119352*g_K1*ufl.sqrt(K_o)*(-E_K + V)*xK1_inf
# Expressions for the Rapid time dependent potassium current component
i_Kr = 0.4303314829119352*g_Kr*ufl.sqrt(K_o)*(-E_K + V)*Xr1*Xr2
# Expressions for the Slow time dependent potassium current component
i_Ks = g_Ks*ufl.elem_pow(Xs, 2.0)*(-E_Ks + V)
# Expressions for the Fast sodium current component
i_Na = g_Na*ufl.elem_pow(m, 3.0)*(-E_Na + V)*h*j
# Expressions for the Sodium background current component
i_b_Na = g_bna*(-E_Na + V)
# Expressions for the L_type Ca current component
i_CaL = 4.0*g_CaL*ufl.elem_pow(F, 2.0)*(-0.341*Ca_o +\
Ca_i*ufl.exp(2.0*F*V/(R*T)))*V*d*f*fCa/(R*T*(-1.0 +\
ufl.exp(2.0*F*V/(R*T))))
# Expressions for the Calcium background current component
i_b_Ca = g_bca*(-E_Ca + V)
# Expressions for the Transient outward current component
i_to = g_to*(-E_K + V)*r*s
# Expressions for the Sodium potassium pump current component
i_NaK = K_o*P_NaK*Na_i/((K_mNa + Na_i)*(K_mk + K_o)*(1.0 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the Sodium calcium exchanger current component
i_NaCa = K_NaCa*(Ca_o*ufl.elem_pow(Na_i,\
3.0)*ufl.exp(F*gamma*V/(R*T)) - alpha*ufl.elem_pow(Na_o,\
3.0)*Ca_i*ufl.exp(F*(-1.0 + gamma)*V/(R*T)))/((1.0 +\
K_sat*ufl.exp(F*(-1.0 + gamma)*V/(R*T)))*(Ca_o +\
Km_Ca)*(ufl.elem_pow(Km_Nai, 3.0) + ufl.elem_pow(Na_o, 3.0)))
# Expressions for the Calcium pump current component
i_p_Ca = g_pCa*Ca_i/(K_pCa + Ca_i)
# Expressions for the Potassium pump current component
i_p_K = g_pK*(-E_K + V)/(1.0 +\
65.40521574193832*ufl.exp(-0.16722408026755853*V))
# Expressions for the Membrane component
i_Stim = ufl.conditional(ufl.And(ufl.ge(time -\
stim_period*ufl.floor(time/stim_period), stim_start), ufl.le(time\
- stim_period*ufl.floor(time/stim_period), stim_duration +\
stim_start)), -stim_amplitude, 0)
current[0] = -1.0*i_CaL - 1.0*i_K1 - 1.0*i_Kr - 1.0*i_Ks - 1.0*i_Na -\
1.0*i_NaCa - 1.0*i_NaK - 1.0*i_Stim - 1.0*i_b_Ca - 1.0*i_b_Na -\
1.0*i_p_Ca - 1.0*i_p_K - 1.0*i_to
# Return results
return current[0]
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V_m = v
assert (len(s) == 38)
h, j, m, x_kr, x_ks, x_to_f, x_to_s, y_to_f, y_to_s, d, f, f_Ca_Bj,\
f_Ca_Bsl, Ry_Ri, Ry_Ro, Ry_Rr, Na_Bj, Na_Bsl, CaM, Myo_c, Myo_m,\
SRB, Tn_CHc, Tn_CHm, Tn_CL, SLH_j, SLH_sl, SLL_j, SLL_sl, Ca_sr,\
Csqn_b, Na_i, Na_j, Na_sl, K_i, Ca_i, Ca_j, Ca_sl = s
# Assign parameters
Fjunc = self._parameters["Fjunc"]
Fjunc_CaL = self._parameters["Fjunc_CaL"]
cellLength = self._parameters["cellLength"]
cellRadius = self._parameters["cellRadius"]
GNa = self._parameters["GNa"]
GNaB = self._parameters["GNaB"]
IbarNaK = self._parameters["IbarNaK"]
KmKo = self._parameters["KmKo"]
KmNaip = self._parameters["KmNaip"]
Q10CaL = self._parameters["Q10CaL"]
pCa = self._parameters["pCa"]
pNa = self._parameters["pNa"]
IbarNCX = self._parameters["IbarNCX"]
Kdact = self._parameters["Kdact"]
KmCai = self._parameters["KmCai"]
KmCao = self._parameters["KmCao"]
KmNai = self._parameters["KmNai"]
KmNao = self._parameters["KmNao"]
Q10NCX = self._parameters["Q10NCX"]
ksat = self._parameters["ksat"]
nu = self._parameters["nu"]
IbarSLCaP = self._parameters["IbarSLCaP"]
KmPCa = self._parameters["KmPCa"]
Q10SLCaP = self._parameters["Q10SLCaP"]
GCaB = self._parameters["GCaB"]
Kmf = self._parameters["Kmf"]
Kmr = self._parameters["Kmr"]
MaxSR = self._parameters["MaxSR"]
MinSR = self._parameters["MinSR"]
Q10SRCaP = self._parameters["Q10SRCaP"]
Vmax_SRCaP = self._parameters["Vmax_SRCaP"]
ec50SR = self._parameters["ec50SR"]
hillSRCaP = self._parameters["hillSRCaP"]
kiCa = self._parameters["kiCa"]
kim = self._parameters["kim"]
koCa = self._parameters["koCa"]
kom = self._parameters["kom"]
ks = self._parameters["ks"]
Bmax_Naj = self._parameters["Bmax_Naj"]
Bmax_Nasl = self._parameters["Bmax_Nasl"]
koff_na = self._parameters["koff_na"]
kon_na = self._parameters["kon_na"]
Bmax_CaM = self._parameters["Bmax_CaM"]
Bmax_SR = self._parameters["Bmax_SR"]
Bmax_TnChigh = self._parameters["Bmax_TnChigh"]
Bmax_TnClow = self._parameters["Bmax_TnClow"]
Bmax_myosin = self._parameters["Bmax_myosin"]
koff_cam = self._parameters["koff_cam"]
koff_myoca = self._parameters["koff_myoca"]
koff_myomg = self._parameters["koff_myomg"]
koff_sr = self._parameters["koff_sr"]
koff_tnchca = self._parameters["koff_tnchca"]
koff_tnchmg = self._parameters["koff_tnchmg"]
koff_tncl = self._parameters["koff_tncl"]
kon_cam = self._parameters["kon_cam"]
kon_myoca = self._parameters["kon_myoca"]
kon_myomg = self._parameters["kon_myomg"]
kon_sr = self._parameters["kon_sr"]
kon_tnchca = self._parameters["kon_tnchca"]
kon_tnchmg = self._parameters["kon_tnchmg"]
kon_tncl = self._parameters["kon_tncl"]
Bmax_SLhighj0 = self._parameters["Bmax_SLhighj0"]
Bmax_SLhighsl0 = self._parameters["Bmax_SLhighsl0"]
Bmax_SLlowj0 = self._parameters["Bmax_SLlowj0"]
Bmax_SLlowsl0 = self._parameters["Bmax_SLlowsl0"]
koff_slh = self._parameters["koff_slh"]
koff_sll = self._parameters["koff_sll"]
kon_slh = self._parameters["kon_slh"]
kon_sll = self._parameters["kon_sll"]
Bmax_Csqn0 = self._parameters["Bmax_Csqn0"]
J_ca_juncsl = self._parameters["J_ca_juncsl"]
J_ca_slmyo = self._parameters["J_ca_slmyo"]
koff_csqn = self._parameters["koff_csqn"]
kon_csqn = self._parameters["kon_csqn"]
J_na_juncsl = self._parameters["J_na_juncsl"]
J_na_slmyo = self._parameters["J_na_slmyo"]
Nao = self._parameters["Nao"]
Ko = self._parameters["Ko"]
Cao = self._parameters["Cao"]
Mgi = self._parameters["Mgi"]
Cmem = self._parameters["Cmem"]
Frdy = self._parameters["Frdy"]
R = self._parameters["R"]
Temp = self._parameters["Temp"]
g_K1_factor = self._parameters["g_K1_factor"]
g_CaL_factor = self._parameters["g_CaL_factor"]
g_Kr_factor = self._parameters["g_Kr_factor"]
g_Ks_factor = self._parameters["g_Ks_factor"]
g_to_factor = self._parameters["g_to_factor"]
SR_Ca_release_ks_factor = self._parameters["SR_Ca_release_ks_factor"]
# Init return args
F_expressions = [ufl.zero()] * 38
# Expressions for the Geometry component
Vcell = 1e-15 * ufl.pi * cellLength * (cellRadius * cellRadius)
Vmyo = 0.65 * Vcell
Vsr = 0.035 * Vcell
Vsl = 0.02 * Vcell
Vjunc = 0.000539 * Vcell
Fsl = 1 - Fjunc
Fsl_CaL = 1 - Fjunc_CaL
# Expressions for the Reversal potentials component
FoRT = Frdy / (R * Temp)
ena_junc = ufl.ln(Nao / Na_j) / FoRT
ena_sl = ufl.ln(Nao / Na_sl) / FoRT
eca_junc = ufl.ln(Cao / Ca_j) / (2 * FoRT)
eca_sl = ufl.ln(Cao / Ca_sl) / (2 * FoRT)
Qpow = -31 + Temp / 10
# Expressions for the I_Na component
mss = 1.0/((1 + 0.00184221158117*ufl.exp(-0.110741971207*V_m))*(1 +\
0.00184221158117*ufl.exp(-0.110741971207*V_m)))
taum = 0.1292*ufl.exp(-((2.94658944659 +\
0.0643500643501*V_m)*(2.94658944659 + 0.0643500643501*V_m))) +\
0.06487*ufl.exp(-((-0.0943466353678 +\
0.0195618153365*V_m)*(-0.0943466353678 + 0.0195618153365*V_m)))
ah = ufl.conditional(ufl.ge(V_m, -40), 0,\
4.43126792958e-07*ufl.exp(-0.147058823529*V_m))
bh = ufl.conditional(ufl.ge(V_m, -40), 0.77/(0.13 +\
0.0497581410839*ufl.exp(-0.0900900900901*V_m)),\
310000.0*ufl.exp(0.3485*V_m) + 2.7*ufl.exp(0.079*V_m))
tauh = 1.0 / (bh + ah)
hss = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V_m))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V_m)))
aj = ufl.conditional(ufl.ge(V_m, -40), 0, (37.78 +\
V_m)*(-25428.0*ufl.exp(0.2444*V_m) -\
6.948e-06*ufl.exp(-0.04391*V_m))/(1 +\
50262745826.0*ufl.exp(0.311*V_m)))
bj = ufl.conditional(ufl.ge(V_m, -40), 0.6*ufl.exp(0.057*V_m)/(1 +\
0.0407622039784*ufl.exp(-0.1*V_m)),\
0.02424*ufl.exp(-0.01052*V_m)/(1 +\
0.0039608683399*ufl.exp(-0.1378*V_m)))
tauj = 1.0 / (bj + aj)
jss = 1.0/((1 + 15212.5932857*ufl.exp(0.134589502019*V_m))*(1 +\
15212.5932857*ufl.exp(0.134589502019*V_m)))
F_expressions[2] = (-m + mss) / taum
F_expressions[0] = (hss - h) / tauh
F_expressions[1] = (-j + jss) / tauj
I_Na_junc = Fjunc * GNa * (m * m * m) * (-ena_junc + V_m) * h * j
I_Na_sl = GNa * (m * m * m) * (-ena_sl + V_m) * Fsl * h * j
# Expressions for the I_NaBK component
I_nabk_junc = Fjunc * GNaB * (-ena_junc + V_m)
I_nabk_sl = GNaB * (-ena_sl + V_m) * Fsl
# Expressions for the I_NaK component
sigma = -1 / 7 + ufl.exp(0.0148588410104 * Nao) / 7
fnak = 1.0/(1 + 0.1245*ufl.exp(-0.1*FoRT*V_m) +\
0.0365*ufl.exp(-FoRT*V_m)*sigma)
I_nak_junc = Fjunc*IbarNaK*Ko*fnak/((1 + ufl.elem_pow(KmNaip,\
4)/ufl.elem_pow(Na_j, 4))*(KmKo + Ko))
I_nak_sl = IbarNaK*Ko*Fsl*fnak/((1 + ufl.elem_pow(KmNaip,\
4)/ufl.elem_pow(Na_sl, 4))*(KmKo + Ko))
# Expressions for the I_Kr component
xrss = 1.0 / (1 + ufl.exp(-2 - V_m / 5))
tauxr = 230/(1 + ufl.exp(2 + V_m/20)) + 3300/((1 + ufl.exp(-22/9 -\
V_m/9))*(1 + ufl.exp(11/9 + V_m/9)))
F_expressions[3] = (-x_kr + xrss) / tauxr
# Expressions for the I_Ks component
xsss = 1.0 / (1 + 0.765928338365 * ufl.exp(-0.0701754385965 * V_m))
tauxs = 990.1 / (1 + 0.841540408868 * ufl.exp(-0.070821529745 * V_m))
F_expressions[4] = (-x_ks + xsss) / tauxs
# Expressions for the I_to component
xtoss = 1.0 / (1 + ufl.exp(19 / 13 - V_m / 13))
ytoss = 1.0 / (1 + 49.4024491055 * ufl.exp(V_m / 5))
tauxtos = 0.5 + 9 / (1 + ufl.exp(1 / 5 + V_m / 15))
tauytos = 30 + 800 / (1 + ufl.exp(6 + V_m / 10))
F_expressions[6] = (-x_to_s + xtoss) / tauxtos
F_expressions[8] = (ytoss - y_to_s) / tauytos
tauxtof = 0.5 + 8.5 * ufl.exp(-((9 / 10 + V_m / 50) *
(9 / 10 + V_m / 50)))
tauytof = 7 + 85 * ufl.exp(-((40 + V_m) * (40 + V_m)) / 220)
F_expressions[5] = (xtoss - x_to_f) / tauxtof
F_expressions[7] = (ytoss - y_to_f) / tauytof
# Expressions for the I_Ca component
fss = 0.6 / (1 + ufl.exp(5 / 2 - V_m / 20)) + 1.0 / (
1 + ufl.exp(35 / 9 + V_m / 9))
dss = 1.0 / (1 + ufl.exp(-5 / 6 - V_m / 6))
taud = (1 - ufl.exp(-5 / 6 - V_m / 6)) * dss / (0.175 + 0.035 * V_m)
tauf = 1.0/(0.02 + 0.0197*ufl.exp(-((0.48865 + 0.0337*V_m)*(0.48865 +\
0.0337*V_m))))
F_expressions[9] = (-d + dss) / taud
F_expressions[10] = (fss - f) / tauf
F_expressions[11] = 1.7 * (1 - f_Ca_Bj) * Ca_j - 0.0119 * f_Ca_Bj
F_expressions[12] = -0.0119 * f_Ca_Bsl + 1.7 * (1 - f_Ca_Bsl) * Ca_sl
fcaCaMSL = 0
fcaCaj = 0
ibarca_j = 4*Frdy*pCa*(-0.341*Cao +\
0.341*Ca_j*ufl.exp(2*FoRT*V_m))*FoRT*V_m/(-1 +\
ufl.exp(2*FoRT*V_m))
ibarca_sl = 4*Frdy*pCa*(-0.341*Cao +\
0.341*Ca_sl*ufl.exp(2*FoRT*V_m))*FoRT*V_m/(-1 +\
ufl.exp(2*FoRT*V_m))
ibarna_j = Frdy*pNa*(-0.75*Nao +\
0.75*Na_j*ufl.exp(FoRT*V_m))*FoRT*V_m/(-1 + ufl.exp(FoRT*V_m))
ibarna_sl = Frdy*pNa*(0.75*Na_sl*ufl.exp(FoRT*V_m) -\
0.75*Nao)*FoRT*V_m/(-1 + ufl.exp(FoRT*V_m))
I_Ca_junc = g_CaL_factor*0.45*Fjunc_CaL*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bj +\
fcaCaj)*d*f*ibarca_j
I_Ca_sl = g_CaL_factor*0.45*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bsl +\
fcaCaMSL)*Fsl_CaL*d*f*ibarca_sl
I_CaNa_junc = g_CaL_factor*0.45*Fjunc_CaL*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bj\
+ fcaCaj)*d*f*ibarna_j
I_CaNa_sl = g_CaL_factor*0.45*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bsl +\
fcaCaMSL)*Fsl_CaL*d*f*ibarna_sl
# Expressions for the I_NCX component
Ka_junc = 1.0 / (1 + (Kdact * Kdact) / (Ca_j * Ca_j))
Ka_sl = 1.0 / (1 + (Kdact * Kdact) / (Ca_sl * Ca_sl))
s1_junc = Cao * (Na_j * Na_j * Na_j) * ufl.exp(nu * FoRT * V_m)
s1_sl = Cao * (Na_sl * Na_sl * Na_sl) * ufl.exp(nu * FoRT * V_m)
s2_junc = (Nao * Nao * Nao) * Ca_j * ufl.exp((-1 + nu) * FoRT * V_m)
s3_junc = KmCao*(Na_j*Na_j*Na_j) + (Nao*Nao*Nao)*Ca_j +\
Cao*(Na_j*Na_j*Na_j) + KmCai*(Nao*Nao*Nao)*(1 +\
(Na_j*Na_j*Na_j)/(KmNai*KmNai*KmNai)) + (KmNao*KmNao*KmNao)*(1 +\
Ca_j/KmCai)*Ca_j
s2_sl = (Nao * Nao * Nao) * Ca_sl * ufl.exp((-1 + nu) * FoRT * V_m)
s3_sl = KmCai*(Nao*Nao*Nao)*(1 +\
(Na_sl*Na_sl*Na_sl)/(KmNai*KmNai*KmNai)) + (Nao*Nao*Nao)*Ca_sl +\
(KmNao*KmNao*KmNao)*(1 + Ca_sl/KmCai)*Ca_sl +\
Cao*(Na_sl*Na_sl*Na_sl) + KmCao*(Na_sl*Na_sl*Na_sl)
I_ncx_junc = Fjunc*IbarNCX*ufl.elem_pow(Q10NCX, Qpow)*(-s2_junc +\
s1_junc)*Ka_junc/((1 + ksat*ufl.exp((-1 + nu)*FoRT*V_m))*s3_junc)
I_ncx_sl = IbarNCX*ufl.elem_pow(Q10NCX, Qpow)*(-s2_sl +\
s1_sl)*Fsl*Ka_sl/((1 + ksat*ufl.exp((-1 + nu)*FoRT*V_m))*s3_sl)
# Expressions for the I_PCa component
I_pca_junc = Fjunc*IbarSLCaP*ufl.elem_pow(Q10SLCaP,\
Qpow)*ufl.elem_pow(Ca_j, 1.6)/(ufl.elem_pow(Ca_j, 1.6) +\
ufl.elem_pow(KmPCa, 1.6))
I_pca_sl = IbarSLCaP*ufl.elem_pow(Q10SLCaP, Qpow)*ufl.elem_pow(Ca_sl,\
1.6)*Fsl/(ufl.elem_pow(Ca_sl, 1.6) + ufl.elem_pow(KmPCa, 1.6))
# Expressions for the I_CaBK component
I_cabk_junc = Fjunc * GCaB * (-eca_junc + V_m)
I_cabk_sl = GCaB * (-eca_sl + V_m) * Fsl
# Expressions for the SR Fluxes component
kCaSR = MaxSR - (-MinSR + MaxSR) / (1 +
ufl.elem_pow(ec50SR / Ca_sr, 2.5))
koSRCa = koCa / kCaSR
kiSRCa = kiCa * kCaSR
RI = 1 - Ry_Ro - Ry_Ri - Ry_Rr
F_expressions[15] = -(Ca_j*Ca_j)*Ry_Rr*koSRCa + kom*Ry_Ro + kim*RI -\
Ca_j*Ry_Rr*kiSRCa
F_expressions[14] = -kom*Ry_Ro - Ca_j*Ry_Ro*kiSRCa + kim*Ry_Ri +\
(Ca_j*Ca_j)*Ry_Rr*koSRCa
F_expressions[13] = -kim*Ry_Ri + Ca_j*Ry_Ro*kiSRCa - kom*Ry_Ri +\
(Ca_j*Ca_j)*RI*koSRCa
J_SRCarel = SR_Ca_release_ks_factor * ks * (Ca_sr - Ca_j) * Ry_Ro
J_serca = Vmax_SRCaP*ufl.elem_pow(Q10SRCaP,\
Qpow)*(-ufl.elem_pow(Ca_sr/Kmr, hillSRCaP) +\
ufl.elem_pow(Ca_i/Kmf, hillSRCaP))/(1 + ufl.elem_pow(Ca_sr/Kmr,\
hillSRCaP) + ufl.elem_pow(Ca_i/Kmf, hillSRCaP))
J_SRleak = 5.348e-06 * Ca_sr - 5.348e-06 * Ca_j
# Expressions for the Na Buffers component
F_expressions[16] = -koff_na * Na_Bj + kon_na * (-Na_Bj +
Bmax_Naj) * Na_j
F_expressions[17] = kon_na * (-Na_Bsl +
Bmax_Nasl) * Na_sl - koff_na * Na_Bsl
# Expressions for the Cytosolic Ca Buffers component
F_expressions[24] = kon_tncl*(Bmax_TnClow - Tn_CL)*Ca_i -\
koff_tncl*Tn_CL
F_expressions[22] = -koff_tnchca*Tn_CHc + kon_tnchca*(-Tn_CHc +\
Bmax_TnChigh - Tn_CHm)*Ca_i
F_expressions[23] = Mgi*kon_tnchmg*(-Tn_CHc + Bmax_TnChigh - Tn_CHm)\
- koff_tnchmg*Tn_CHm
F_expressions[18] = kon_cam * (-CaM + Bmax_CaM) * Ca_i - koff_cam * CaM
F_expressions[19] = -koff_myoca*Myo_c + kon_myoca*(-Myo_c +\
Bmax_myosin - Myo_m)*Ca_i
F_expressions[20] = Mgi*kon_myomg*(-Myo_c + Bmax_myosin - Myo_m) -\
koff_myomg*Myo_m
F_expressions[21] = kon_sr * (Bmax_SR - SRB) * Ca_i - koff_sr * SRB
J_CaB_cytosol = -koff_tnchca*Tn_CHc - koff_myoca*Myo_c +\
Mgi*kon_myomg*(-Myo_c + Bmax_myosin - Myo_m) +\
Mgi*kon_tnchmg*(-Tn_CHc + Bmax_TnChigh - Tn_CHm) -\
koff_tnchmg*Tn_CHm + kon_tncl*(Bmax_TnClow - Tn_CL)*Ca_i +\
kon_sr*(Bmax_SR - SRB)*Ca_i - koff_myomg*Myo_m + kon_cam*(-CaM +\
Bmax_CaM)*Ca_i - koff_cam*CaM - koff_tncl*Tn_CL +\
kon_myoca*(-Myo_c + Bmax_myosin - Myo_m)*Ca_i +\
kon_tnchca*(-Tn_CHc + Bmax_TnChigh - Tn_CHm)*Ca_i - koff_sr*SRB
# Expressions for the Junctional and SL Ca Buffers component
Bmax_SLlowsl = Bmax_SLlowsl0 * Vmyo / Vsl
Bmax_SLlowj = Bmax_SLlowj0 * Vmyo / Vjunc
Bmax_SLhighsl = Bmax_SLhighsl0 * Vmyo / Vsl
Bmax_SLhighj = Bmax_SLhighj0 * Vmyo / Vjunc
F_expressions[27] = kon_sll * (Bmax_SLlowj -
SLL_j) * Ca_j - koff_sll * SLL_j
F_expressions[28] = kon_sll*(-SLL_sl + Bmax_SLlowsl)*Ca_sl -\
koff_sll*SLL_sl
F_expressions[25] = kon_slh*(Bmax_SLhighj - SLH_j)*Ca_j -\
koff_slh*SLH_j
F_expressions[26] = kon_slh*(-SLH_sl + Bmax_SLhighsl)*Ca_sl -\
koff_slh*SLH_sl
J_CaB_junction = kon_slh*(Bmax_SLhighj - SLH_j)*Ca_j +\
kon_sll*(Bmax_SLlowj - SLL_j)*Ca_j - koff_slh*SLH_j -\
koff_sll*SLL_j
J_CaB_sl = kon_sll*(-SLL_sl + Bmax_SLlowsl)*Ca_sl + kon_slh*(-SLH_sl\
+ Bmax_SLhighsl)*Ca_sl - koff_sll*SLL_sl - koff_slh*SLH_sl
# Expressions for the SR Ca Concentrations component
Bmax_Csqn = Bmax_Csqn0 * Vmyo / Vsr
F_expressions[30] = -koff_csqn*Csqn_b + kon_csqn*(Bmax_Csqn -\
Csqn_b)*Ca_sr
F_expressions[29] = -kon_csqn*(Bmax_Csqn - Csqn_b)*Ca_sr -\
J_SRleak*Vmyo/Vsr + koff_csqn*Csqn_b - J_SRCarel + J_serca
# Expressions for the Na Concentrations component
I_Na_tot_junc = 3*I_nak_junc + 3*I_ncx_junc + I_CaNa_junc + I_Na_junc\
+ I_nabk_junc
I_Na_tot_sl = I_Na_sl + I_nabk_sl + 3 * I_nak_sl + I_CaNa_sl + 3 * I_ncx_sl
F_expressions[32] = -Cmem*I_Na_tot_junc/(Frdy*Vjunc) +\
J_na_juncsl*(Na_sl - Na_j)/Vjunc - F_expressions[16]
F_expressions[33] = -F_expressions[17] + J_na_slmyo*(-Na_sl +\
Na_i)/Vsl + J_na_juncsl*(-Na_sl + Na_j)/Vsl -\
Cmem*I_Na_tot_sl/(Frdy*Vsl)
F_expressions[31] = J_na_slmyo * (Na_sl - Na_i) / Vmyo
# Expressions for the K Concentration component
F_expressions[34] = Constant(0.0)
# Expressions for the Ca Concentrations component
I_Ca_tot_junc = I_pca_junc + I_cabk_junc + I_Ca_junc - 2 * I_ncx_junc
I_Ca_tot_sl = -2 * I_ncx_sl + I_pca_sl + I_cabk_sl + I_Ca_sl
F_expressions[36] = J_ca_juncsl*(Ca_sl - Ca_j)/Vjunc +\
J_SRCarel*Vsr/Vjunc - J_CaB_junction -\
Cmem*I_Ca_tot_junc/(2*Frdy*Vjunc) + J_SRleak*Vmyo/Vjunc
F_expressions[37] = -J_CaB_sl + J_ca_juncsl*(Ca_j - Ca_sl)/Vsl -\
Cmem*I_Ca_tot_sl/(2*Frdy*Vsl) + J_ca_slmyo*(Ca_i - Ca_sl)/Vsl
F_expressions[35] = -J_CaB_cytosol + J_ca_slmyo*(Ca_sl - Ca_i)/Vmyo -\
J_serca*Vsr/Vmyo
# Return results
return dolfin.as_vector(F_expressions)
phi = TestFunction(V)
rho_0_lotnisko_inne = Expression("exp(-a*pow(x[0]-7, 2) - a*pow(x[1]-4, 2))",
degree=2,
a=0.01)
rho_0_lotnisko = Expression("x[1] < 35 ? 1.0 : 0.0", degree=2, a=0.01)
rho_0 = Expression("exp(-a*pow(x[0]-7, 2) - a*pow(x[1]-4, 2))", degree=2, a=1)
F = u * v * dx + sigma * sigma * dot(grad(u), grad(v)) * dx
a, L = lhs(F), rhs(F)
u = Function(V)
velocity = Function(V)
solve(a == L, u, bc_lotnisko)
phi = uf.ln(u)
dx0 = project(phi.dx(0))
dx1 = project(phi.dx(1))
unnormed_grad_phi = project(grad(phi))
module = sqrt(dx0 * dx0 + dx1 * dx1)
normed_phi = unnormed_grad_phi / module
plot(normed_phi)
plt.show()
rhoold = interpolate(rho_0_lotnisko, V)
plot(rhoold)
plt.show()
def _I(self, v, s, time):
"""
Original gotran transmembrane current dV/dt
"""
time = time if time else Constant(0.0)
# Assign states
V_m = v
assert (len(s) == 38)
h, j, m, x_kr, x_ks, x_to_f, x_to_s, y_to_f, y_to_s, d, f, f_Ca_Bj,\
f_Ca_Bsl, Ry_Ri, Ry_Ro, Ry_Rr, Na_Bj, Na_Bsl, CaM, Myo_c, Myo_m,\
SRB, Tn_CHc, Tn_CHm, Tn_CL, SLH_j, SLH_sl, SLL_j, SLL_sl, Ca_sr,\
Csqn_b, Na_i, Na_j, Na_sl, K_i, Ca_i, Ca_j, Ca_sl = s
# Assign parameters
Fjunc = self._parameters["Fjunc"]
Fjunc_CaL = self._parameters["Fjunc_CaL"]
GNa = self._parameters["GNa"]
GNaB = self._parameters["GNaB"]
IbarNaK = self._parameters["IbarNaK"]
KmKo = self._parameters["KmKo"]
KmNaip = self._parameters["KmNaip"]
gkp = self._parameters["gkp"]
pNaK = self._parameters["pNaK"]
epi = self._parameters["epi"]
GClB = self._parameters["GClB"]
GClCa = self._parameters["GClCa"]
KdClCa = self._parameters["KdClCa"]
Q10CaL = self._parameters["Q10CaL"]
pCa = self._parameters["pCa"]
pK = self._parameters["pK"]
pNa = self._parameters["pNa"]
IbarNCX = self._parameters["IbarNCX"]
Kdact = self._parameters["Kdact"]
KmCai = self._parameters["KmCai"]
KmCao = self._parameters["KmCao"]
KmNai = self._parameters["KmNai"]
KmNao = self._parameters["KmNao"]
Q10NCX = self._parameters["Q10NCX"]
ksat = self._parameters["ksat"]
nu = self._parameters["nu"]
IbarSLCaP = self._parameters["IbarSLCaP"]
KmPCa = self._parameters["KmPCa"]
Q10SLCaP = self._parameters["Q10SLCaP"]
GCaB = self._parameters["GCaB"]
Nao = self._parameters["Nao"]
Ko = self._parameters["Ko"]
Cao = self._parameters["Cao"]
Cli = self._parameters["Cli"]
Clo = self._parameters["Clo"]
Frdy = self._parameters["Frdy"]
R = self._parameters["R"]
Temp = self._parameters["Temp"]
g_K1_factor = self._parameters["g_K1_factor"]
g_CaL_factor = self._parameters["g_CaL_factor"]
g_Kr_factor = self._parameters["g_Kr_factor"]
g_Ks_factor = self._parameters["g_Ks_factor"]
g_to_factor = self._parameters["g_to_factor"]
SR_Ca_release_ks_factor = self._parameters["SR_Ca_release_ks_factor"]
# Init return args
current = [ufl.zero()] * 1
# Expressions for the Geometry component
Fsl = 1 - Fjunc
Fsl_CaL = 1 - Fjunc_CaL
# Expressions for the Reversal potentials component
FoRT = Frdy / (R * Temp)
ena_junc = ufl.ln(Nao / Na_j) / FoRT
ena_sl = ufl.ln(Nao / Na_sl) / FoRT
ek = ufl.ln(Ko / K_i) / FoRT
eca_junc = ufl.ln(Cao / Ca_j) / (2 * FoRT)
eca_sl = ufl.ln(Cao / Ca_sl) / (2 * FoRT)
ecl = ufl.ln(Cli / Clo) / FoRT
Qpow = -31 + Temp / 10
# Expressions for the I_Na component
I_Na_junc = Fjunc * GNa * (m * m * m) * (-ena_junc + V_m) * h * j
I_Na_sl = GNa * (m * m * m) * (-ena_sl + V_m) * Fsl * h * j
# Expressions for the I_NaBK component
I_nabk_junc = Fjunc * GNaB * (-ena_junc + V_m)
I_nabk_sl = GNaB * (-ena_sl + V_m) * Fsl
# Expressions for the I_NaK component
sigma = -1 / 7 + ufl.exp(0.0148588410104 * Nao) / 7
fnak = 1.0/(1 + 0.1245*ufl.exp(-0.1*FoRT*V_m) +\
0.0365*ufl.exp(-FoRT*V_m)*sigma)
I_nak_junc = Fjunc*IbarNaK*Ko*fnak/((1 + ufl.elem_pow(KmNaip,\
4)/ufl.elem_pow(Na_j, 4))*(KmKo + Ko))
I_nak_sl = IbarNaK*Ko*Fsl*fnak/((1 + ufl.elem_pow(KmNaip,\
4)/ufl.elem_pow(Na_sl, 4))*(KmKo + Ko))
I_nak = I_nak_junc + I_nak_sl
# Expressions for the I_Kr component
gkr = g_Kr_factor * 0.0150616019019 * ufl.sqrt(Ko)
rkr = 1.0 / (1 + ufl.exp(37 / 12 + V_m / 24))
I_kr = (-ek + V_m) * gkr * rkr * x_kr
# Expressions for the I_Kp component
kp_kp = 1.0 / (1 + 1786.47556538 * ufl.exp(-0.167224080268 * V_m))
I_kp_junc = Fjunc * gkp * (-ek + V_m) * kp_kp
I_kp_sl = gkp * (-ek + V_m) * Fsl * kp_kp
I_kp = I_kp_sl + I_kp_junc
# Expressions for the I_Ks component
eks = ufl.ln((Nao * pNaK + Ko) / (pNaK * Na_i + K_i)) / FoRT
gks_junc = g_Ks_factor * 0.0035
gks_sl = g_Ks_factor * 0.0035
I_ks_junc = Fjunc * gks_junc * (x_ks * x_ks) * (-eks + V_m)
I_ks_sl = gks_sl * (x_ks * x_ks) * (-eks + V_m) * Fsl
I_ks = I_ks_sl + I_ks_junc
# Expressions for the I_to component
GtoSlow = ufl.conditional(ufl.eq(epi, 1), 0.0156, 0.037596)
GtoFast = ufl.conditional(ufl.eq(epi, 1), 0.1144, 0.001404)
I_tos = (-ek + V_m) * GtoSlow * x_to_s * y_to_s
I_tof = (-ek + V_m) * g_to_factor * GtoFast * x_to_f * y_to_f
I_to = I_tos + I_tof
# Expressions for the I_Ki component
aki = 1.02 / (1 +
7.35454251046e-07 * ufl.exp(0.2385 * V_m - 0.2385 * ek))
bki = (0.762624006506*ufl.exp(0.08032*V_m - 0.08032*ek) +\
1.15340563519e-16*ufl.exp(0.06175*V_m - 0.06175*ek))/(1 +\
0.0867722941577*ufl.exp(-0.5143*V_m + 0.5143*ek))
kiss = aki / (aki + bki)
I_ki = g_K1_factor * 0.150616019019 * ufl.sqrt(Ko) * (-ek + V_m) * kiss
# Expressions for the I_ClCa component
I_ClCa_junc = Fjunc * GClCa * (-ecl + V_m) / (1 + KdClCa / Ca_j)
I_ClCa_sl = GClCa * (-ecl + V_m) * Fsl / (1 + KdClCa / Ca_sl)
I_ClCa = I_ClCa_sl + I_ClCa_junc
I_Clbk = GClB * (-ecl + V_m)
# Expressions for the I_Ca component
fcaCaMSL = 0
fcaCaj = 0
ibarca_j = 4*Frdy*pCa*(-0.341*Cao +\
0.341*Ca_j*ufl.exp(2*FoRT*V_m))*FoRT*V_m/(-1 +\
ufl.exp(2*FoRT*V_m))
ibarca_sl = 4*Frdy*pCa*(-0.341*Cao +\
0.341*Ca_sl*ufl.exp(2*FoRT*V_m))*FoRT*V_m/(-1 +\
ufl.exp(2*FoRT*V_m))
ibark = Frdy*pK*(-0.75*Ko + 0.75*K_i*ufl.exp(FoRT*V_m))*FoRT*V_m/(-1 +\
ufl.exp(FoRT*V_m))
ibarna_j = Frdy*pNa*(-0.75*Nao +\
0.75*Na_j*ufl.exp(FoRT*V_m))*FoRT*V_m/(-1 + ufl.exp(FoRT*V_m))
ibarna_sl = Frdy*pNa*(0.75*Na_sl*ufl.exp(FoRT*V_m) -\
0.75*Nao)*FoRT*V_m/(-1 + ufl.exp(FoRT*V_m))
I_Ca_junc = g_CaL_factor*0.45*Fjunc_CaL*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bj +\
fcaCaj)*d*f*ibarca_j
I_Ca_sl = g_CaL_factor*0.45*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bsl +\
fcaCaMSL)*Fsl_CaL*d*f*ibarca_sl
I_CaK = g_CaL_factor*0.45*ufl.elem_pow(Q10CaL, Qpow)*(Fjunc_CaL*(1 - f_Ca_Bj +\
fcaCaj) + (1 - f_Ca_Bsl + fcaCaMSL)*Fsl_CaL)*d*f*ibark
I_CaNa_junc = g_CaL_factor*0.45*Fjunc_CaL*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bj\
+ fcaCaj)*d*f*ibarna_j
I_CaNa_sl = g_CaL_factor*0.45*ufl.elem_pow(Q10CaL, Qpow)*(1 - f_Ca_Bsl +\
fcaCaMSL)*Fsl_CaL*d*f*ibarna_sl
# Expressions for the I_NCX component
Ka_junc = 1.0 / (1 + (Kdact * Kdact) / (Ca_j * Ca_j))
Ka_sl = 1.0 / (1 + (Kdact * Kdact) / (Ca_sl * Ca_sl))
s1_junc = Cao * (Na_j * Na_j * Na_j) * ufl.exp(nu * FoRT * V_m)
s1_sl = Cao * (Na_sl * Na_sl * Na_sl) * ufl.exp(nu * FoRT * V_m)
s2_junc = (Nao * Nao * Nao) * Ca_j * ufl.exp((-1 + nu) * FoRT * V_m)
s3_junc = KmCao*(Na_j*Na_j*Na_j) + (Nao*Nao*Nao)*Ca_j +\
Cao*(Na_j*Na_j*Na_j) + KmCai*(Nao*Nao*Nao)*(1 +\
(Na_j*Na_j*Na_j)/(KmNai*KmNai*KmNai)) + (KmNao*KmNao*KmNao)*(1 +\
Ca_j/KmCai)*Ca_j
s2_sl = (Nao * Nao * Nao) * Ca_sl * ufl.exp((-1 + nu) * FoRT * V_m)
s3_sl = KmCai*(Nao*Nao*Nao)*(1 +\
(Na_sl*Na_sl*Na_sl)/(KmNai*KmNai*KmNai)) + (Nao*Nao*Nao)*Ca_sl +\
(KmNao*KmNao*KmNao)*(1 + Ca_sl/KmCai)*Ca_sl +\
Cao*(Na_sl*Na_sl*Na_sl) + KmCao*(Na_sl*Na_sl*Na_sl)
I_ncx_junc = Fjunc*IbarNCX*ufl.elem_pow(Q10NCX, Qpow)*(-s2_junc +\
s1_junc)*Ka_junc/((1 + ksat*ufl.exp((-1 + nu)*FoRT*V_m))*s3_junc)
I_ncx_sl = IbarNCX*ufl.elem_pow(Q10NCX, Qpow)*(-s2_sl +\
s1_sl)*Fsl*Ka_sl/((1 + ksat*ufl.exp((-1 + nu)*FoRT*V_m))*s3_sl)
# Expressions for the I_PCa component
I_pca_junc = Fjunc*IbarSLCaP*ufl.elem_pow(Q10SLCaP,\
Qpow)*ufl.elem_pow(Ca_j, 1.6)/(ufl.elem_pow(Ca_j, 1.6) +\
ufl.elem_pow(KmPCa, 1.6))
I_pca_sl = IbarSLCaP*ufl.elem_pow(Q10SLCaP, Qpow)*ufl.elem_pow(Ca_sl,\
1.6)*Fsl/(ufl.elem_pow(Ca_sl, 1.6) + ufl.elem_pow(KmPCa, 1.6))
# Expressions for the I_CaBK component
I_cabk_junc = Fjunc * GCaB * (-eca_junc + V_m)
I_cabk_sl = GCaB * (-eca_sl + V_m) * Fsl
# Expressions for the Na Concentrations component
I_Na_tot_junc = 3*I_nak_junc + 3*I_ncx_junc + I_CaNa_junc + I_Na_junc\
+ I_nabk_junc
I_Na_tot_sl = I_Na_sl + I_nabk_sl + 3 * I_nak_sl + I_CaNa_sl + 3 * I_ncx_sl
# Expressions for the K Concentration component
I_K_tot = -2 * I_nak + I_ks + I_CaK + I_kr + I_kp + I_ki + I_to
# Expressions for the Ca Concentrations component
I_Ca_tot_junc = I_pca_junc + I_cabk_junc + I_Ca_junc - 2 * I_ncx_junc
I_Ca_tot_sl = -2 * I_ncx_sl + I_pca_sl + I_cabk_sl + I_Ca_sl
# Expressions for the Membrane potential component
i_Stim = 0
I_Na_tot = I_Na_tot_junc + I_Na_tot_sl
I_Cl_tot = I_Clbk + I_ClCa
I_Ca_tot = I_Ca_tot_junc + I_Ca_tot_sl
I_tot = I_Na_tot + I_K_tot + I_Cl_tot + I_Ca_tot
current[0] = -I_tot - i_Stim
# Return results
return current[0]
def test_neohooke():
mesh = dolfinx.mesh.create_unit_cube(MPI.COMM_WORLD, 7, 7, 7)
V = dolfinx.fem.VectorFunctionSpace(mesh, ("P", 1))
P = dolfinx.fem.FunctionSpace(mesh, ("P", 1))
L = dolfinx.fem.FunctionSpace(mesh, ("DG", 0))
u = dolfinx.fem.Function(V, name="u")
v = ufl.TestFunction(V)
p = dolfinx.fem.Function(P, name="p")
q = ufl.TestFunction(P)
lmbda0 = dolfinx.fem.Function(L)
d = mesh.topology.dim
Id = ufl.Identity(d)
F = Id + ufl.grad(u)
C = F.T * F
J = ufl.det(F)
E_, nu_ = 10.0, 0.3
mu, lmbda = E_ / (2 * (1 + nu_)), E_ * nu_ / ((1 + nu_) * (1 - 2 * nu_))
psi = (mu / 2) * (ufl.tr(C) -
3) - mu * ufl.ln(J) + lmbda / 2 * ufl.ln(J)**2 + (p -
1.0)**2
pi = psi * ufl.dx
F0 = ufl.derivative(pi, u, v)
F1 = ufl.derivative(pi, p, q)
# Number of eigenvalues to find
nev = 8
opts = PETSc.Options("neohooke")
opts["eps_smallest_magnitude"] = True
opts["eps_nev"] = nev
opts["eps_ncv"] = 50 * nev
opts["eps_conv_abs"] = True
# opts["eps_non_hermitian"] = True
opts["eps_tol"] = 1.0e-14
opts["eps_max_it"] = 1000
opts["eps_error_relative"] = "ascii::ascii_info_detail"
opts["eps_monitor"] = "ascii"
slepcp = dolfiny.slepcblockproblem.SLEPcBlockProblem([F0, F1], [u, p],
lmbda0,
prefix="neohooke")
slepcp.solve()
# mat = dolfiny.la.petsc_to_scipy(slepcp.eps.getOperators()[0])
# eigvals, eigvecs = linalg.eigsh(mat, which="SM", k=nev)
with dolfinx.io.XDMFFile(MPI.COMM_WORLD, "eigvec.xdmf", "w") as ofile:
ofile.write_mesh(mesh)
for i in range(nev):
eigval, ur, ui = slepcp.getEigenpair(i)
# Expect first 6 eignevalues 0, i.e. rigid body modes
if i < 6:
assert np.isclose(eigval, 0.0)
for func in ur:
name = func.name
func.name = f"{name}_eigvec_{i}_real"
ofile.write_function(func)
func.name = name
def assemble_test(cell_batch_size: int):
mesh = dolfin.UnitCubeMesh(MPI.comm_world, 40, 40, 40)
def isochoric(F):
C = F.T*F
I_1 = tr(C)
I4_f = dot(e_f, C*e_f)
I4_s = dot(e_s, C*e_s)
I8_fs = dot(e_f, C*e_s)
def cutoff(x):
return 1.0/(1.0 + ufl.exp(-(x - 1.0)*30.0))
def scaled_exp(a0, a1, argument):
return a0/(2.0*a1)*(ufl.exp(b*argument) - 1)
E_1 = scaled_exp(a, b, I_1 - 3.)
E_f = cutoff(I4_f)*scaled_exp(a_f, b_f, (I4_f - 1.)**2)
E_s = cutoff(I4_s)*scaled_exp(a_s, b_s, (I4_s - 1.)**2)
E_3 = scaled_exp(a_fs, b_fs, I8_fs**2)
E = E_1 + E_f + E_s + E_3
return E
cell = mesh.ufl_cell()
lamda = dolfin.Constant(0.48, cell)
a = dolfin.Constant(1.0, cell)
b = dolfin.Constant(1.0, cell)
a_s = dolfin.Constant(1.0, cell)
b_s = dolfin.Constant(1.0, cell)
a_f = dolfin.Constant(1.0, cell)
b_f = dolfin.Constant(1.0, cell)
a_fs = dolfin.Constant(1.0, cell)
b_fs = dolfin.Constant(1.0, cell)
# For more fun, make these general vector fields rather than
# constants:
e_s = dolfin.Constant([0.0, 1.0, 0.0], cell)
e_f = dolfin.Constant([1.0, 0.0, 0.0], cell)
V = dolfin.FunctionSpace(mesh, ufl.VectorElement("CG", cell, 1))
u = dolfin.Function(V)
du = dolfin.function.argument.TrialFunction(V)
v = dolfin.function.argument.TestFunction(V)
# Misc elasticity related tensors and other quantities
F = grad(u) + ufl.Identity(3)
F = ufl.variable(F)
J = det(F)
Fbar = J**(-1.0/3.0)*F
# Define energy
E_volumetric = lamda*0.5*ln(J)**2
psi = isochoric(Fbar) + E_volumetric
# Find first Piola-Kircchoff tensor
P = ufl.diff(psi, F)
# Define the variational formulation
F = inner(P, grad(v))*dx
# Take the derivative
J = ufl.derivative(F, u, du)
a, L = J, F
if cell_batch_size > 1:
cxx_flags = "-O2 -ftree-vectorize -funroll-loops -march=native -mtune=native"
else:
cxx_flags = "-O2"
assembler = dolfin.fem.assembling.Assembler([[a]], [L], [],
form_compiler_parameters={"cell_batch_size": cell_batch_size,
"enable_cross_cell_gcc_ext": True,
"cpp_optimize_flags": cxx_flags})
t = -time.time()
A, b = assembler.assemble(
mat_type=dolfin.cpp.fem.Assembler.BlockType.monolithic)
t += time.time()
return A, b, t
chi = 0.2
po = Gdry / lamo
muo = Rg*T*(math.log(Omega*cod/(1+Omega*cod))+1/(1+Omega*cod)+ chi/pow((1+Omega*cod),2)) \
+Omega*po
mus = muo
mutop = -10000
# Kinematics
I = Identity(3)
F = I + grad(u)
J = det(F)
# Constitutive equations
S = (Gdry / lamo) * F - p * cofac(F)
mu = Rg*T*(ufl.ln(Omega*Jo*c/(1+Omega*Jo*c)) + 1./(1.+Omega*Jo*c)+ \
chi/pow((1.+Omega*Jo*c),2))+Omega*p
h = g(c) * grad(c) + (-c * D / (Rg * T)) * Omega * grad(p)
dmudp = Omega
dmu = mu - mus
# Boundary conditions
def left_boundary(x, on_boundary): # x = 0
return on_boundary and abs(x[0]) < DOLFIN_EPS
def back_boundary(x, on_boundary): # y = 0
def F(self, v, s, time=None):
"""
Right hand side for ODE system
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert (len(s) == 17)
m, h, j, d, f1, f2, fCa, Xr1, Xr2, Xs, Xf, q, r, Nai, g, Cai, Ca_SR = s
# Assign parameters
TTX_10uM = self._parameters["TTX_10uM"]
TTX_30uM = self._parameters["TTX_30uM"]
TTX_3uM = self._parameters["TTX_3uM"]
nifed_100nM = self._parameters["nifed_100nM"]
nifed_10nM = self._parameters["nifed_10nM"]
nifed_30nM = self._parameters["nifed_30nM"]
nifed_3nM = self._parameters["nifed_3nM"]
g_Na = self._parameters["g_Na"]
g_CaL = self._parameters["g_CaL"]
tau_fCa = self._parameters["tau_fCa"]
L0 = self._parameters["L0"]
Q = self._parameters["Q"]
g_b_Na = self._parameters["g_b_Na"]
g_b_Ca = self._parameters["g_b_Ca"]
Km_K = self._parameters["Km_K"]
Km_Na = self._parameters["Km_Na"]
PNaK = self._parameters["PNaK"]
KmCa = self._parameters["KmCa"]
KmNai = self._parameters["KmNai"]
Ksat = self._parameters["Ksat"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
kNaCa = self._parameters["kNaCa"]
KPCa = self._parameters["KPCa"]
g_PCa = self._parameters["g_PCa"]
Cao = self._parameters["Cao"]
Cm = self._parameters["Cm"]
F = self._parameters["F"]
Ko = self._parameters["Ko"]
Nao = self._parameters["Nao"]
R = self._parameters["R"]
T = self._parameters["T"]
V_SR = self._parameters["V_SR"]
Vc = self._parameters["Vc"]
Buf_C = self._parameters["Buf_C"]
Buf_SR = self._parameters["Buf_SR"]
Kbuf_C = self._parameters["Kbuf_C"]
Kbuf_SR = self._parameters["Kbuf_SR"]
Kup = self._parameters["Kup"]
V_leak = self._parameters["V_leak"]
VmaxUp = self._parameters["VmaxUp"]
a_rel = self._parameters["a_rel"]
b_rel = self._parameters["b_rel"]
c_rel = self._parameters["c_rel"]
tau_g = self._parameters["tau_g"]
# Init return args
F_expressions = [ufl.zero()] * 17
# Expressions for the Electric potentials component
E_Na = R * T * ufl.ln(Nao / Nai) / F
E_Ca = 0.5 * R * T * ufl.ln(Cao / Cai) / F
# Expressions for the i_Na component
TTX_coeff = ufl.conditional(ufl.eq(TTX_3uM, 1), 0.18,\
ufl.conditional(ufl.eq(TTX_10uM, 1), 0.06,\
ufl.conditional(ufl.eq(TTX_30uM, 1), 0.02, 1)))
i_Na = g_Na * (m * m * m) * (-E_Na + V) * TTX_coeff * h * j
# Expressions for the m gate component
m_inf = 1.0*ufl.elem_pow(1 +\
0.00308976260789*ufl.exp(-169.491525424*V), -0.333333333333)
alpha_m = 1.0 / (1 + 6.14421235333e-06 * ufl.exp(-200.0 * V))
beta_m = 0.1/(1 + 1096.63315843*ufl.exp(200.0*V)) + 0.1/(1 +\
0.778800783071*ufl.exp(5.0*V))
tau_m = 0.001 * alpha_m * beta_m
F_expressions[0] = (-m + m_inf) / tau_m
# Expressions for the h gate component
h_inf = 1.0 / ufl.sqrt(1 + 311490.091283 * ufl.exp(175.438596491 * V))
alpha_h = ufl.conditional(ufl.lt(V, -0.04),\
4.43126792958e-07*ufl.exp(-147.058823529*V), 0)
beta_h = ufl.conditional(ufl.lt(V, -0.04), 310000.0*ufl.exp(348.5*V)\
+ 2.7*ufl.exp(79.0*V), 0.77/(0.13 +\
0.0497581410839*ufl.exp(-90.0900900901*V)))
tau_h = ufl.conditional(ufl.lt(V, -0.04), 1.5/(1000*alpha_h +\
1000*beta_h), 0.002542)
F_expressions[1] = (-h + h_inf) / tau_h
# Expressions for the j gate component
j_inf = 1.0 / ufl.sqrt(1 + 311490.091283 * ufl.exp(175.438596491 * V))
alpha_j = ufl.conditional(ufl.lt(V, -0.04), (37.78 +\
1000*V)*(-25428*ufl.exp(244.4*V) -\
6.948e-06*ufl.exp(-43.91*V))/(1 +\
50262745826.0*ufl.exp(311.0*V)), 0)
beta_j = ufl.conditional(ufl.lt(V, -0.04),\
0.02424*ufl.exp(-10.52*V)/(1 +\
0.0039608683399*ufl.exp(-137.8*V)), 0.6*ufl.exp(57.0*V)/(1 +\
0.0407622039784*ufl.exp(-100.0*V)))
tau_j = 7.0 / (1000 * alpha_j + 1000 * beta_j)
F_expressions[2] = (-j + j_inf) / tau_j
# Expressions for the i_CaL component
nifed_coeff = ufl.conditional(ufl.eq(nifed_3nM, 1), 0.93,\
ufl.conditional(ufl.eq(nifed_10nM, 1), 0.79,\
ufl.conditional(ufl.eq(nifed_30nM, 1), 0.56,\
ufl.conditional(ufl.eq(nifed_100nM, 1), 0.28, 1))))
i_CaL = 4*g_CaL*(F*F)*(-0.341*Cao +\
Cai*ufl.exp(2*F*V/(R*T)))*V*d*f1*f2*fCa*nifed_coeff/(R*T*(-1 +\
ufl.exp(2*F*V/(R*T))))
# Expressions for the d gate component
d_infinity = 1.0 / (1 + 0.272531793034 * ufl.exp(-1000 * V / 7))
alpha_d = 0.25 + 1.4 / (1 + ufl.exp(-35 / 13 - 1000 * V / 13))
beta_d = 1.4 / (1 + ufl.exp(1 + 200 * V))
gamma_d = 1.0 / (1 + ufl.exp(5 / 2 - 50 * V))
tau_d = 0.001 * gamma_d + 0.001 * alpha_d * beta_d
F_expressions[3] = (-d + d_infinity) / tau_d
# Expressions for the F1 gate component
f1_inf = 1.0 / (1 + ufl.exp(26 / 3 + 1000 * V / 3))
constf1 = ufl.conditional(ufl.gt(-f1 + f1_inf, 0), 0.92835 +\
1433*Cai, 1)
tau_f1 = 0.001*(20 + 200.0/(1 + ufl.exp(13/10 - 100*V)) + 180.0/(1 +\
ufl.exp(3 + 100*V)) +\
1102.5*ufl.exp(-0.00444444444444*ufl.elem_pow(27 + 1000*V,\
4)))*constf1
F_expressions[4] = (-f1 + f1_inf) / tau_f1
# Expressions for the F2 gate component
f2_inf = 0.33 + 0.67 / (1 + ufl.exp(35 / 4 + 250 * V))
constf2 = 1
tau_f2 = 0.001*constf2*(600*ufl.exp(-((25 + 1000*V)*(25 +\
1000*V))/170) + 16.0/(1 + ufl.exp(3 + 100*V)) + 31.0/(1 +\
ufl.exp(5/2 - 100*V)))
F_expressions[5] = (-f2 + f2_inf) / tau_f2
# Expressions for the FCa gate component
alpha_fCa = 1.0 / (1 + 5.95374180765e+25 * ufl.elem_pow(Cai, 8))
beta_fCa = 0.1 / (1 + 0.000123409804087 * ufl.exp(10000.0 * Cai))
gamma_fCa = 0.3 / (1 + 0.391605626677 * ufl.exp(1250.0 * Cai))
fCa_inf = 0.760109455762*alpha_fCa + 0.760109455762*beta_fCa +\
0.760109455762*gamma_fCa
constfCa = ufl.conditional(ufl.And(ufl.gt(V, -0.06), ufl.gt(fCa_inf,\
fCa)), 0, 1)
F_expressions[6] = (-fCa + fCa_inf) * constfCa / tau_fCa
# Expressions for the Xr1 gate component
V_half = -19.0 - 1000*R*T*ufl.ln(ufl.elem_pow(1 + 0.384615384615*Cao,\
4)/(L0*ufl.elem_pow(1 + 1.72413793103*Cao, 4)))/(F*Q)
Xr1_inf = 1.0 / (1 +
ufl.exp(0.204081632653 * V_half - 204.081632653 * V))
alpha_Xr1 = 450.0 / (1 + ufl.exp(-9 / 2 - 100 * V))
beta_Xr1 = 6.0 / (1 + 13.5813245226 * ufl.exp(86.9565217391 * V))
tau_Xr1 = 0.001 * alpha_Xr1 * beta_Xr1
F_expressions[7] = (-Xr1 + Xr1_inf) / tau_Xr1
# Expressions for the Xr2 gate component
Xr2_infinity = 1.0 / (1 + ufl.exp(44 / 25 + 20 * V))
alpha_Xr2 = 3.0 / (1 + ufl.exp(-3 - 50 * V))
beta_Xr2 = 1.12 / (1 + ufl.exp(-3 + 50 * V))
tau_Xr2 = 0.001 * alpha_Xr2 * beta_Xr2
F_expressions[8] = (-Xr2 + Xr2_infinity) / tau_Xr2
# Expressions for the Xs gate component
Xs_infinity = 1.0 / (1 + ufl.exp(-5 / 4 - 125 * V / 2))
alpha_Xs = 1100.0 / ufl.sqrt(1 + ufl.exp(-5 / 3 - 500 * V / 3))
beta_Xs = 1.0 / (1 + ufl.exp(-3 + 50 * V))
tau_Xs = alpha_Xs * beta_Xs / 1000
F_expressions[9] = (-Xs + Xs_infinity) / tau_Xs
# Expressions for the Xf gate component
Xf_infinity = 1.0 / (1 + 5780495.71031 * ufl.exp(200 * V))
tau_Xf = 1.9 / (1 + ufl.exp(3 / 2 + 100 * V))
F_expressions[10] = (-Xf + Xf_infinity) / tau_Xf
# Expressions for the i_b Na component
i_b_Na = g_b_Na * (-E_Na + V)
# Expressions for the i_b Ca component
i_b_Ca = g_b_Ca * (-E_Ca + V)
# Expressions for the i_NaK component
i_NaK = Ko*PNaK*Nai/((Km_K + Ko)*(Km_Na + Nai)*(1 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the i_NaCa component
i_NaCa = kNaCa*(Cao*(Nai*Nai*Nai)*ufl.exp(F*gamma*V/(R*T)) -\
alpha*(Nao*Nao*Nao)*Cai*ufl.exp(F*(-1 + gamma)*V/(R*T)))/((1 +\
Ksat*ufl.exp(F*(-1 + gamma)*V/(R*T)))*(Cao +\
KmCa)*((KmNai*KmNai*KmNai) + (Nao*Nao*Nao)))
# Expressions for the i_PCa component
i_PCa = g_PCa * Cai / (KPCa + Cai)
# Expressions for the q gate component
q_inf = 1.0 / (1 + ufl.exp(53 / 13 + 1000 * V / 13))
tau_q = 0.00606 + 0.039102/(0.0168716780457*ufl.exp(-80.0*V) +\
6.42137321286*ufl.exp(100.0*V))
F_expressions[11] = (-q + q_inf) / tau_q
# Expressions for the r gate component
r_inf = 1.0 / (1 + 3.28489055021 * ufl.exp(-53.3333333333 * V))
tau_r = 0.00275352 + 0.01440516/(16.3010892258*ufl.exp(90.0*V) +\
0.0211152735604*ufl.exp(-120.0*V))
F_expressions[12] = (-r + r_inf) / tau_r
# Expressions for the Sodium dynamics component
F_expressions[13] = -1e+18*Cm*(3*i_NaCa + 3*i_NaK + i_Na +\
i_b_Na)/(F*Vc)
# Expressions for the Calcium dynamics component
i_rel = 0.0411*(c_rel + a_rel*(Ca_SR*Ca_SR)/((b_rel*b_rel) +\
(Ca_SR*Ca_SR)))*d*g
i_up = VmaxUp / (1 + (Kup * Kup) / (Cai * Cai))
i_leak = V_leak * (-Cai + Ca_SR)
g_inf = ufl.conditional(ufl.le(Cai, 0.00035), 1.0/(1 +\
5.43991024148e+20*ufl.elem_pow(Cai, 6)), 1.0/(1 +\
1.9720198874e+55*ufl.elem_pow(Cai, 16)))
const2 = ufl.conditional(ufl.And(ufl.gt(V, -0.06), ufl.gt(g_inf, g)),\
0, 1)
F_expressions[14] = (-g + g_inf) * const2 / tau_g
Cai_bufc = 1.0 / (1 + Buf_C * Kbuf_C / ((Kbuf_C + Cai) *
(Kbuf_C + Cai)))
Ca_SR_bufSR = 1.0/(1 + Buf_SR*Kbuf_SR/((Kbuf_SR + Ca_SR)*(Kbuf_SR +\
Ca_SR)))
F_expressions[15] = (-i_up - 5e+17*Cm*(-2*i_NaCa + i_CaL + i_PCa +\
i_b_Ca)/(F*Vc) + i_leak + i_rel)*Cai_bufc
F_expressions[16] = Vc * (-i_leak - i_rel + i_up) * Ca_SR_bufSR / V_SR
# Return results
return dolfin.as_vector(F_expressions)
def rhs(states, time, parameters, dy=None):
"""
Compute right hand side
"""
# Imports
import ufl
import dolfin
# Assign states
assert(isinstance(states, dolfin.Function))
assert(states.function_space().depth() == 1)
assert(states.function_space().num_sub_spaces() == 17)
Xr1, Xr2, Xs, m, h, j, d, f, fCa, s, r, Ca_SR, Ca_i, g, Na_i, V, K_i =\
dolfin.split(states)
# Assign parameters
assert(isinstance(parameters, (dolfin.Function, dolfin.Constant)))
if isinstance(parameters, dolfin.Function):
assert(parameters.function_space().depth() == 1)
assert(parameters.function_space().num_sub_spaces() == 45)
else:
assert(parameters.value_size() == 45)
P_kna, g_K1, g_Kr, g_Ks, g_Na, g_bna, g_CaL, g_bca, g_to, K_mNa, K_mk,\
P_NaK, K_NaCa, K_sat, Km_Ca, Km_Nai, alpha, gamma, K_pCa, g_pCa,\
g_pK, Buf_c, Buf_sr, Ca_o, K_buf_c, K_buf_sr, K_up, V_leak, V_sr,\
Vmax_up, a_rel, b_rel, c_rel, tau_g, Na_o, Cm, F, R, T, V_c,\
stim_amplitude, stim_duration, stim_period, stim_start, K_o =\
dolfin.split(parameters)
# Reversal potentials
E_Na = R*T*ufl.ln(Na_o/Na_i)/F
E_K = R*T*ufl.ln(K_o/K_i)/F
E_Ks = R*T*ufl.ln((Na_o*P_kna + K_o)/(Na_i*P_kna + K_i))/F
E_Ca = 0.5*R*T*ufl.ln(Ca_o/Ca_i)/F
# Inward rectifier potassium current
alpha_K1 = 0.1/(1.0 + 6.14421235332821e-6*ufl.exp(0.06*V - 0.06*E_K))
beta_K1 = (3.06060402008027*ufl.exp(0.0002*V - 0.0002*E_K) +\
0.367879441171442*ufl.exp(0.1*V - 0.1*E_K))/(1.0 + ufl.exp(0.5*E_K -\
0.5*V))
xK1_inf = alpha_K1/(alpha_K1 + beta_K1)
i_K1 = 0.430331482911935*ufl.sqrt(K_o)*(-E_K + V)*g_K1*xK1_inf
# Rapid time dependent potassium current
i_Kr = 0.430331482911935*ufl.sqrt(K_o)*(-E_K + V)*Xr1*Xr2*g_Kr
# Rapid time dependent potassium current xr1 gate
xr1_inf = 1.0/(1.0 + 0.0243728440732796*ufl.exp(-0.142857142857143*V))
alpha_xr1 = 450.0/(1.0 + ufl.exp(-9/2 - V/10.0))
beta_xr1 = 6.0/(1.0 + 13.5813245225782*ufl.exp(0.0869565217391304*V))
tau_xr1 = alpha_xr1*beta_xr1
# Rapid time dependent potassium current xr2 gate
xr2_inf = 1.0/(1.0 + 39.1212839981532*ufl.exp(0.0416666666666667*V))
alpha_xr2 = 3.0/(1.0 + 0.0497870683678639*ufl.exp(-0.05*V))
beta_xr2 = 1.12/(1.0 + 0.0497870683678639*ufl.exp(0.05*V))
tau_xr2 = alpha_xr2*beta_xr2
# Slow time dependent potassium current
i_Ks = (Xs*Xs)*(V - E_Ks)*g_Ks
# Slow time dependent potassium current xs gate
xs_inf = 1.0/(1.0 + 0.69967253737513*ufl.exp(-0.0714285714285714*V))
alpha_xs = 1100.0/ufl.sqrt(1.0 +\
0.188875602837562*ufl.exp(-0.166666666666667*V))
beta_xs = 1.0/(1.0 + 0.0497870683678639*ufl.exp(0.05*V))
tau_xs = alpha_xs*beta_xs
# Fast sodium current
i_Na = (m*m*m)*(-E_Na + V)*g_Na*h*j
# Fast sodium current m gate
m_inf = 1.0/((1.0 +\
0.00184221158116513*ufl.exp(-0.110741971207087*V))*(1.0 +\
0.00184221158116513*ufl.exp(-0.110741971207087*V)))
alpha_m = 1.0/(1.0 + ufl.exp(-12.0 - V/5.0))
beta_m = 0.1/(1.0 + 0.778800783071405*ufl.exp(0.005*V)) + 0.1/(1.0 +\
ufl.exp(7.0 + V/5.0))
tau_m = alpha_m*beta_m
# Fast sodium current h gate
h_inf = 1.0/((1.0 + 15212.5932856544*ufl.exp(0.134589502018843*V))*(1.0 +\
15212.5932856544*ufl.exp(0.134589502018843*V)))
alpha_h = 4.43126792958051e-7*ufl.exp(-0.147058823529412*V)/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))
beta_h = (310000.0*ufl.exp(0.3485*V) + 2.7*ufl.exp(0.079*V))/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)) + 0.77*(1.0 - 1.0/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)))/(0.13 +\
0.0497581410839387*ufl.exp(-0.0900900900900901*V))
tau_h = 1.0/(alpha_h + beta_h)
# Fast sodium current j gate
j_inf = 1.0/((1.0 + 15212.5932856544*ufl.exp(0.134589502018843*V))*(1.0 +\
15212.5932856544*ufl.exp(0.134589502018843*V)))
alpha_j = (37.78 + V)*(-6.948e-6*ufl.exp(-0.04391*V) -\
25428.0*ufl.exp(0.2444*V))/((1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))*(1.0 +\
50262745825.954*ufl.exp(0.311*V)))
beta_j = 0.6*(1.0 - 1.0/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)))*ufl.exp(0.057*V)/(1.0 +\
0.0407622039783662*ufl.exp(-0.1*V)) +\
0.02424*ufl.exp(-0.01052*V)/((1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))*(1.0 +\
0.00396086833990426*ufl.exp(-0.1378*V)))
tau_j = 1.0/(alpha_j + beta_j)
# Sodium background current
i_b_Na = (-E_Na + V)*g_bna
# L type ca current
i_CaL = 4.0*(F*F)*(-0.341*Ca_o +\
Ca_i*ufl.exp(2.0*F*V/(R*T)))*V*d*f*fCa*g_CaL/((-1.0 +\
ufl.exp(2.0*F*V/(R*T)))*R*T)
# L type ca current d gate
d_inf = 1.0/(1.0 + 0.513417119032592*ufl.exp(-0.133333333333333*V))
alpha_d = 0.25 + 1.4/(1.0 +\
0.0677244716592409*ufl.exp(-0.0769230769230769*V))
beta_d = 1.4/(1.0 + ufl.exp(1.0 + V/5.0))
gamma_d = 1.0/(1.0 + 12.1824939607035*ufl.exp(-0.05*V))
tau_d = gamma_d + alpha_d*beta_d
# L type ca current f gate
f_inf = 1.0/(1.0 + 17.4117080633276*ufl.exp(0.142857142857143*V))
tau_f = 80.0 + 165.0/(1.0 + ufl.exp(5/2 - V/10.0)) +\
1125.0*ufl.exp(-0.00416666666666667*((27.0 + V)*(27.0 + V)))
# L type ca current fca gate
alpha_fCa = 1.0/(1.0 + 8.03402376701711e+27*ufl.elem_pow(Ca_i, 8.0))
beta_fCa = 0.1/(1.0 + 0.00673794699908547*ufl.exp(10000.0*Ca_i))
gama_fCa = 0.2/(1.0 + 0.391605626676799*ufl.exp(1250.0*Ca_i))
fCa_inf = 0.157534246575342 + 0.684931506849315*gama_fCa +\
0.684931506849315*beta_fCa + 0.684931506849315*alpha_fCa
tau_fCa = 2.0
d_fCa = (-fCa + fCa_inf)/tau_fCa
# Calcium background current
i_b_Ca = (V - E_Ca)*g_bca
# Transient outward current
i_to = (-E_K + V)*g_to*r*s
# Transient outward current s gate
s_inf = 1.0/(1.0 + ufl.exp(4.0 + V/5.0))
tau_s = 3.0 + 85.0*ufl.exp(-0.003125*((45.0 + V)*(45.0 + V))) + 5.0/(1.0 +\
ufl.exp(-4.0 + V/5.0))
# Transient outward current r gate
r_inf = 1.0/(1.0 + 28.0316248945261*ufl.exp(-0.166666666666667*V))
tau_r = 0.8 + 9.5*ufl.exp(-0.000555555555555556*((40.0 + V)*(40.0 + V)))
# Sodium potassium pump current
i_NaK = K_o*Na_i*P_NaK/((K_mk + K_o)*(Na_i + K_mNa)*(1.0 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Sodium calcium exchanger current
i_NaCa = (-(Na_o*Na_o*Na_o)*Ca_i*alpha*ufl.exp((-1.0 + gamma)*F*V/(R*T))\
+ (Na_i*Na_i*Na_i)*Ca_o*ufl.exp(F*V*gamma/(R*T)))*K_NaCa/((1.0 +\
K_sat*ufl.exp((-1.0 + gamma)*F*V/(R*T)))*((Na_o*Na_o*Na_o) +\
(Km_Nai*Km_Nai*Km_Nai))*(Km_Ca + Ca_o))
# Calcium pump current
i_p_Ca = Ca_i*g_pCa/(K_pCa + Ca_i)
# Potassium pump current
i_p_K = (-E_K + V)*g_pK/(1.0 +\
65.4052157419383*ufl.exp(-0.167224080267559*V))
# Calcium dynamics
i_rel = ((Ca_SR*Ca_SR)*a_rel/((Ca_SR*Ca_SR) + (b_rel*b_rel)) + c_rel)*d*g
i_up = Vmax_up/(1.0 + (K_up*K_up)/(Ca_i*Ca_i))
i_leak = (-Ca_i + Ca_SR)*V_leak
g_inf = (1.0 - 1.0/(1.0 + 0.0301973834223185*ufl.exp(10000.0*Ca_i)))/(1.0 +\
1.97201988740492e+55*ufl.elem_pow(Ca_i, 16.0)) + 1.0/((1.0 +\
0.0301973834223185*ufl.exp(10000.0*Ca_i))*(1.0 +\
5.43991024148102e+20*ufl.elem_pow(Ca_i, 6.0)))
d_g = (-g + g_inf)/tau_g
Ca_i_bufc = 1.0/(1.0 + Buf_c*K_buf_c/((K_buf_c + Ca_i)*(K_buf_c + Ca_i)))
Ca_sr_bufsr = 1.0/(1.0 + Buf_sr*K_buf_sr/((K_buf_sr + Ca_SR)*(K_buf_sr +\
Ca_SR)))
# Sodium dynamics
# Membrane
i_Stim = -(1.0 - 1.0/(1.0 + ufl.exp(-5.0*stim_start +\
5.0*time)))*stim_amplitude/(1.0 + ufl.exp(-5.0*stim_start + 5.0*time\
- 5.0*stim_duration))
# Potassium dynamics
# The ODE system: 17 states
# Init test function
_v = dolfin.TestFunction(states.function_space())
# Derivative for state Xr1
dy = ((-Xr1 + xr1_inf)/tau_xr1)*_v[0]
# Derivative for state Xr2
dy += ((-Xr2 + xr2_inf)/tau_xr2)*_v[1]
# Derivative for state Xs
dy += ((-Xs + xs_inf)/tau_xs)*_v[2]
# Derivative for state m
dy += ((-m + m_inf)/tau_m)*_v[3]
# Derivative for state h
dy += ((-h + h_inf)/tau_h)*_v[4]
# Derivative for state j
dy += ((j_inf - j)/tau_j)*_v[5]
# Derivative for state d
dy += ((d_inf - d)/tau_d)*_v[6]
# Derivative for state f
dy += ((-f + f_inf)/tau_f)*_v[7]
# Derivative for state fCa
dy += ((1.0 - 1.0/((1.0 + ufl.exp(60.0 + V))*(1.0 + ufl.exp(-10.0*fCa +\
10.0*fCa_inf))))*d_fCa)*_v[8]
# Derivative for state s
dy += ((-s + s_inf)/tau_s)*_v[9]
# Derivative for state r
dy += ((-r + r_inf)/tau_r)*_v[10]
# Derivative for state Ca_SR
dy += ((-i_leak + i_up - i_rel)*Ca_sr_bufsr*V_c/V_sr)*_v[11]
# Derivative for state Ca_i
dy += ((-i_up - (i_CaL + i_p_Ca + i_b_Ca - 2.0*i_NaCa)*Cm/(2.0*F*V_c) +\
i_leak + i_rel)*Ca_i_bufc)*_v[12]
# Derivative for state g
dy += ((1.0 - 1.0/((1.0 + ufl.exp(60.0 + V))*(1.0 + ufl.exp(-10.0*g +\
10.0*g_inf))))*d_g)*_v[13]
# Derivative for state Na_i
dy += ((-3.0*i_NaK - 3.0*i_NaCa - i_Na - i_b_Na)*Cm/(F*V_c))*_v[14]
# Derivative for state V
dy += (-i_Ks - i_to - i_Kr - i_p_K - i_NaK - i_NaCa - i_Na - i_p_Ca -\
i_b_Na - i_CaL - i_Stim - i_K1 - i_b_Ca)*_v[15]
# Derivative for state K_i
dy += ((-i_Ks - i_to - i_Kr - i_p_K - i_Stim - i_K1 +\
2.0*i_NaK)*Cm/(F*V_c))*_v[16]
# Return dy
return dy
def _I(self, v, s, time):
"""
Original gotran transmembrane current dV/dt
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert (len(s) == 17)
m, h, j, d, f1, f2, fCa, Xr1, Xr2, Xs, Xf, q, r, Nai, g, Cai, Ca_SR = s
# Assign parameters
Chromanol_iKs30 = self._parameters["Chromanol_iKs30"]
Chromanol_iKs50 = self._parameters["Chromanol_iKs50"]
Chromanol_iKs70 = self._parameters["Chromanol_iKs70"]
Chromanol_iKs90 = self._parameters["Chromanol_iKs90"]
E4031_100nM = self._parameters["E4031_100nM"]
E4031_30nM = self._parameters["E4031_30nM"]
TTX_10uM = self._parameters["TTX_10uM"]
TTX_30uM = self._parameters["TTX_30uM"]
TTX_3uM = self._parameters["TTX_3uM"]
nifed_100nM = self._parameters["nifed_100nM"]
nifed_10nM = self._parameters["nifed_10nM"]
nifed_30nM = self._parameters["nifed_30nM"]
nifed_3nM = self._parameters["nifed_3nM"]
PkNa = self._parameters["PkNa"]
g_Na = self._parameters["g_Na"]
g_CaL = self._parameters["g_CaL"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_K1 = self._parameters["g_K1"]
E_f = self._parameters["E_f"]
g_f = self._parameters["g_f"]
g_b_Na = self._parameters["g_b_Na"]
g_b_Ca = self._parameters["g_b_Ca"]
Km_K = self._parameters["Km_K"]
Km_Na = self._parameters["Km_Na"]
PNaK = self._parameters["PNaK"]
KmCa = self._parameters["KmCa"]
KmNai = self._parameters["KmNai"]
Ksat = self._parameters["Ksat"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
kNaCa = self._parameters["kNaCa"]
KPCa = self._parameters["KPCa"]
g_PCa = self._parameters["g_PCa"]
g_to = self._parameters["g_to"]
Cao = self._parameters["Cao"]
F = self._parameters["F"]
Ki = self._parameters["Ki"]
Ko = self._parameters["Ko"]
Nao = self._parameters["Nao"]
R = self._parameters["R"]
T = self._parameters["T"]
# Init return args
current = [ufl.zero()] * 1
# Expressions for the Electric potentials component
E_Na = R * T * ufl.ln(Nao / Nai) / F
E_K = R * T * ufl.ln(Ko / Ki) / F
E_Ks = R * T * ufl.ln((Ko + Nao * PkNa) / (Ki + PkNa * Nai)) / F
E_Ca = 0.5 * R * T * ufl.ln(Cao / Cai) / F
# Expressions for the i_Na component
TTX_coeff = ufl.conditional(ufl.eq(TTX_3uM, 1), 0.18,\
ufl.conditional(ufl.eq(TTX_10uM, 1), 0.06,\
ufl.conditional(ufl.eq(TTX_30uM, 1), 0.02, 1)))
i_Na = g_Na * (m * m * m) * (-E_Na + V) * TTX_coeff * h * j
# Expressions for the i_CaL component
nifed_coeff = ufl.conditional(ufl.eq(nifed_3nM, 1), 0.93,\
ufl.conditional(ufl.eq(nifed_10nM, 1), 0.79,\
ufl.conditional(ufl.eq(nifed_30nM, 1), 0.56,\
ufl.conditional(ufl.eq(nifed_100nM, 1), 0.28, 1))))
i_CaL = 4*g_CaL*(F*F)*(-0.341*Cao +\
Cai*ufl.exp(2*F*V/(R*T)))*V*d*f1*f2*fCa*nifed_coeff/(R*T*(-1 +\
ufl.exp(2*F*V/(R*T))))
# Expressions for the i_Kr component
E4031_coeff = ufl.conditional(ufl.eq(E4031_30nM, 1), 0.77,\
ufl.conditional(ufl.eq(E4031_100nM, 1), 0.5, 1))
i_Kr = 0.430331482912 * g_Kr * ufl.sqrt(Ko) * (
-E_K + V) * E4031_coeff * Xr1 * Xr2
# Expressions for the i_Ks component
Chromanol_coeff = ufl.conditional(ufl.eq(Chromanol_iKs30, 1), 0.7,\
ufl.conditional(ufl.eq(Chromanol_iKs50, 1), 0.5,\
ufl.conditional(ufl.eq(Chromanol_iKs70, 1), 0.3,\
ufl.conditional(ufl.eq(Chromanol_iKs90, 1), 0.1, 1))))
i_Ks = g_Ks*(Xs*Xs)*(1 + 0.6/(1 +\
6.48182102606e-07*ufl.elem_pow(1.0/Cai, 1.4)))*(-E_Ks +\
V)*Chromanol_coeff
# Expressions for the i_K1 component
alpha_K1 = 3.91 / (
1 + 2.44592857399e-52 * ufl.exp(594.2 * V - 594.2 * E_K))
beta_K1 = (0.00277806676906*ufl.exp(588.6*V - 588.6*E_K) -\
1.5394838221*ufl.exp(0.2*V - 0.2*E_K))/(1 + ufl.exp(454.7*V -\
454.7*E_K))
XK1_inf = alpha_K1 / (alpha_K1 + beta_K1)
i_K1 = 0.430331482912 * g_K1 * ufl.sqrt(Ko) * (-E_K + V) * XK1_inf
# Expressions for the i_f component
i_f = g_f * (-E_f + V) * Xf
# Expressions for the i_b Na component
i_b_Na = g_b_Na * (-E_Na + V)
# Expressions for the i_b Ca component
i_b_Ca = g_b_Ca * (-E_Ca + V)
# Expressions for the i_NaK component
i_NaK = Ko*PNaK*Nai/((Km_K + Ko)*(Km_Na + Nai)*(1 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the i_NaCa component
i_NaCa = kNaCa*(Cao*(Nai*Nai*Nai)*ufl.exp(F*gamma*V/(R*T)) -\
alpha*(Nao*Nao*Nao)*Cai*ufl.exp(F*(-1 + gamma)*V/(R*T)))/((1 +\
Ksat*ufl.exp(F*(-1 + gamma)*V/(R*T)))*(Cao +\
KmCa)*((KmNai*KmNai*KmNai) + (Nao*Nao*Nao)))
# Expressions for the i_PCa component
i_PCa = g_PCa * Cai / (KPCa + Cai)
# Expressions for the i_to component
i_to = g_to * (-E_K + V) * q * r
# Expressions for the Membrane component
current[0] = -i_CaL - i_K1 - i_Kr - i_Ks - i_Na - i_NaCa - i_NaK -\
i_PCa - i_b_Ca - i_b_Na - i_f - i_to
# Return results
return current[0]
def _I(self, v, s, time):
"""
Original gotran transmembrane current dV/dt
"""
time = time if time else Constant(0.0)
# Assign states
V = v
assert (len(s) == 18)
Xr1, Xr2, Xs, m, h, j, d, f, f2, fCass, s, r, Ca_SR, Ca_i, Ca_ss,\
R_prime, Na_i, K_i = s
# Assign parameters
P_kna = self._parameters["P_kna"]
g_K1 = self._parameters["g_K1"]
g_Kr = self._parameters["g_Kr"]
g_Ks = self._parameters["g_Ks"]
g_Na = self._parameters["g_Na"]
g_bna = self._parameters["g_bna"]
g_CaL = self._parameters["g_CaL"]
g_bca = self._parameters["g_bca"]
g_to = self._parameters["g_to"]
K_mNa = self._parameters["K_mNa"]
K_mk = self._parameters["K_mk"]
P_NaK = self._parameters["P_NaK"]
K_NaCa = self._parameters["K_NaCa"]
K_sat = self._parameters["K_sat"]
Km_Ca = self._parameters["Km_Ca"]
Km_Nai = self._parameters["Km_Nai"]
alpha = self._parameters["alpha"]
gamma = self._parameters["gamma"]
K_pCa = self._parameters["K_pCa"]
g_pCa = self._parameters["g_pCa"]
g_pK = self._parameters["g_pK"]
Ca_o = self._parameters["Ca_o"]
Na_o = self._parameters["Na_o"]
F = self._parameters["F"]
R = self._parameters["R"]
T = self._parameters["T"]
K_o = self._parameters["K_o"]
# Init return args
current = [ufl.zero()] * 1
# Expressions for the Reversal potentials component
E_Na = R * T * ufl.ln(Na_o / Na_i) / F
E_K = R * T * ufl.ln(K_o / K_i) / F
E_Ks = R * T * ufl.ln((Na_o * P_kna + K_o) / (K_i + P_kna * Na_i)) / F
E_Ca = 0.5 * R * T * ufl.ln(Ca_o / Ca_i) / F
# Expressions for the Inward rectifier potassium current component
alpha_K1 = 0.1 / (1 +
6.14421235333e-06 * ufl.exp(-0.06 * E_K + 0.06 * V))
beta_K1 = (3.06060402008*ufl.exp(0.0002*V - 0.0002*E_K) +\
0.367879441171*ufl.exp(0.1*V - 0.1*E_K))/(1 + ufl.exp(0.5*E_K -\
0.5*V))
xK1_inf = alpha_K1 / (alpha_K1 + beta_K1)
i_K1 = 0.430331482912 * g_K1 * ufl.sqrt(K_o) * (-E_K + V) * xK1_inf
# Expressions for the Rapid time dependent potassium current component
i_Kr = 0.430331482912 * g_Kr * ufl.sqrt(K_o) * (-E_K + V) * Xr1 * Xr2
# Expressions for the Slow time dependent potassium current component
i_Ks = g_Ks * (Xs * Xs) * (-E_Ks + V)
# Expressions for the Fast sodium current component
i_Na = g_Na * (m * m * m) * (-E_Na + V) * h * j
# Expressions for the Sodium background current component
i_b_Na = g_bna * (-E_Na + V)
# Expressions for the L_type Ca current component
i_CaL = 4*g_CaL*(F*F)*(-15 + V)*(0.25*Ca_ss*ufl.exp(F*(-30 +\
2*V)/(R*T)) - Ca_o)*d*f*f2*fCass/(R*T*(-1 + ufl.exp(F*(-30 +\
2*V)/(R*T))))
# Expressions for the Calcium background current component
i_b_Ca = g_bca * (-E_Ca + V)
# Expressions for the Transient outward current component
i_to = g_to * (-E_K + V) * r * s
# Expressions for the Sodium potassium pump current component
i_NaK = K_o*P_NaK*Na_i/((K_mNa + Na_i)*(K_mk + K_o)*(1 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Expressions for the Sodium calcium exchanger current component
i_NaCa = K_NaCa*(-alpha*(Na_o*Na_o*Na_o)*Ca_i*ufl.exp(F*(-1 +\
gamma)*V/(R*T)) +\
Ca_o*(Na_i*Na_i*Na_i)*ufl.exp(F*gamma*V/(R*T)))/((1 +\
K_sat*ufl.exp(F*(-1 + gamma)*V/(R*T)))*(Km_Ca +\
Ca_o)*((Na_o*Na_o*Na_o) + (Km_Nai*Km_Nai*Km_Nai)))
# Expressions for the Calcium pump current component
i_p_Ca = g_pCa * Ca_i / (Ca_i + K_pCa)
# Expressions for the Potassium pump current component
i_p_K = g_pK * (-E_K +
V) / (1 + 65.4052157419 * ufl.exp(-0.167224080268 * V))
# Expressions for the Membrane component
i_Stim = 0
current[0] = -i_CaL - i_Ks - i_NaCa - i_b_Na - i_Stim - i_Kr - i_p_Ca\
- i_to - i_b_Ca - i_Na - i_p_K - i_NaK - i_K1
# Return results
return current[0]
def rhs(states, time, parameters, dy=None):
"""
Compute right hand side
"""
# Imports
import ufl
import dolfin
# Assign states
assert(isinstance(states, dolfin.Function))
assert(states.function_space().depth() == 1)
assert(states.function_space().num_sub_spaces() == 17)
Xr1, Xr2, Xs, m, h, j, d, f, fCa, s, r, Ca_SR, Ca_i, g, Na_i, V, K_i =\
dolfin.split(states)
# Assign parameters
assert(isinstance(parameters, (dolfin.Function, dolfin.Constant)))
if isinstance(parameters, dolfin.Function):
assert(parameters.function_space().depth() == 1)
assert(parameters.function_space().num_sub_spaces() == 45)
else:
assert(parameters.value_size() == 45)
P_kna, g_K1, g_Kr, g_Ks, g_Na, g_bna, g_CaL, g_bca, g_to, K_mNa, K_mk,\
P_NaK, K_NaCa, K_sat, Km_Ca, Km_Nai, alpha, gamma, K_pCa, g_pCa,\
g_pK, Buf_c, Buf_sr, Ca_o, K_buf_c, K_buf_sr, K_up, V_leak, V_sr,\
Vmax_up, a_rel, b_rel, c_rel, tau_g, Na_o, Cm, F, R, T, V_c,\
stim_amplitude, stim_duration, stim_period, stim_start, K_o =\
dolfin.split(parameters)
# Reversal potentials
E_Na = R*T*ufl.ln(Na_o/Na_i)/F
E_K = R*T*ufl.ln(K_o/K_i)/F
E_Ks = R*T*ufl.ln((Na_o*P_kna + K_o)/(Na_i*P_kna + K_i))/F
E_Ca = 0.5*R*T*ufl.ln(Ca_o/Ca_i)/F
# Inward rectifier potassium current
alpha_K1 = 0.1/(1.0 + 6.14421235332821e-6*ufl.exp(0.06*V - 0.06*E_K))
beta_K1 = (3.06060402008027*ufl.exp(0.0002*V - 0.0002*E_K) +\
0.367879441171442*ufl.exp(0.1*V - 0.1*E_K))/(1.0 + ufl.exp(0.5*E_K -\
0.5*V))
xK1_inf = alpha_K1/(alpha_K1 + beta_K1)
i_K1 = 0.430331482911935*ufl.sqrt(K_o)*(-E_K + V)*g_K1*xK1_inf
# Rapid time dependent potassium current
i_Kr = 0.430331482911935*ufl.sqrt(K_o)*(-E_K + V)*Xr1*Xr2*g_Kr
# Rapid time dependent potassium current xr1 gate
xr1_inf = 1.0/(1.0 + 0.0243728440732796*ufl.exp(-0.142857142857143*V))
alpha_xr1 = 450.0/(1.0 + ufl.exp(-9/2 - V/10.0))
beta_xr1 = 6.0/(1.0 + 13.5813245225782*ufl.exp(0.0869565217391304*V))
tau_xr1 = alpha_xr1*beta_xr1
# Rapid time dependent potassium current xr2 gate
xr2_inf = 1.0/(1.0 + 39.1212839981532*ufl.exp(0.0416666666666667*V))
alpha_xr2 = 3.0/(1.0 + 0.0497870683678639*ufl.exp(-0.05*V))
beta_xr2 = 1.12/(1.0 + 0.0497870683678639*ufl.exp(0.05*V))
tau_xr2 = alpha_xr2*beta_xr2
# Slow time dependent potassium current
i_Ks = (Xs*Xs)*(V - E_Ks)*g_Ks
# Slow time dependent potassium current xs gate
xs_inf = 1.0/(1.0 + 0.69967253737513*ufl.exp(-0.0714285714285714*V))
alpha_xs = 1100.0/ufl.sqrt(1.0 +\
0.188875602837562*ufl.exp(-0.166666666666667*V))
beta_xs = 1.0/(1.0 + 0.0497870683678639*ufl.exp(0.05*V))
tau_xs = alpha_xs*beta_xs
# Fast sodium current
i_Na = (m*m*m)*(-E_Na + V)*g_Na*h*j
# Fast sodium current m gate
m_inf = 1.0/((1.0 +\
0.00184221158116513*ufl.exp(-0.110741971207087*V))*(1.0 +\
0.00184221158116513*ufl.exp(-0.110741971207087*V)))
alpha_m = 1.0/(1.0 + ufl.exp(-12.0 - V/5.0))
beta_m = 0.1/(1.0 + 0.778800783071405*ufl.exp(0.005*V)) + 0.1/(1.0 +\
ufl.exp(7.0 + V/5.0))
tau_m = alpha_m*beta_m
# Fast sodium current h gate
h_inf = 1.0/((1.0 + 15212.5932856544*ufl.exp(0.134589502018843*V))*(1.0 +\
15212.5932856544*ufl.exp(0.134589502018843*V)))
alpha_h = 4.43126792958051e-7*ufl.exp(-0.147058823529412*V)/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))
beta_h = (310000.0*ufl.exp(0.3485*V) + 2.7*ufl.exp(0.079*V))/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)) + 0.77*(1.0 - 1.0/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)))/(0.13 +\
0.0497581410839387*ufl.exp(-0.0900900900900901*V))
tau_h = 1.0/(alpha_h + beta_h)
# Fast sodium current j gate
j_inf = 1.0/((1.0 + 15212.5932856544*ufl.exp(0.134589502018843*V))*(1.0 +\
15212.5932856544*ufl.exp(0.134589502018843*V)))
alpha_j = (37.78 + V)*(-6.948e-6*ufl.exp(-0.04391*V) -\
25428.0*ufl.exp(0.2444*V))/((1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))*(1.0 +\
50262745825.954*ufl.exp(0.311*V)))
beta_j = 0.6*(1.0 - 1.0/(1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V)))*ufl.exp(0.057*V)/(1.0 +\
0.0407622039783662*ufl.exp(-0.1*V)) +\
0.02424*ufl.exp(-0.01052*V)/((1.0 +\
2.3538526683702e+17*ufl.exp(1.0*V))*(1.0 +\
0.00396086833990426*ufl.exp(-0.1378*V)))
tau_j = 1.0/(alpha_j + beta_j)
# Sodium background current
i_b_Na = (-E_Na + V)*g_bna
# L type ca current
i_CaL = 4.0*(F*F)*(-0.341*Ca_o +\
Ca_i*ufl.exp(2.0*F*V/(R*T)))*V*d*f*fCa*g_CaL/((-1.0 +\
ufl.exp(2.0*F*V/(R*T)))*R*T)
# L type ca current d gate
d_inf = 1.0/(1.0 + 0.513417119032592*ufl.exp(-0.133333333333333*V))
alpha_d = 0.25 + 1.4/(1.0 +\
0.0677244716592409*ufl.exp(-0.0769230769230769*V))
beta_d = 1.4/(1.0 + ufl.exp(1.0 + V/5.0))
gamma_d = 1.0/(1.0 + 12.1824939607035*ufl.exp(-0.05*V))
tau_d = gamma_d + alpha_d*beta_d
# L type ca current f gate
f_inf = 1.0/(1.0 + 17.4117080633276*ufl.exp(0.142857142857143*V))
tau_f = 80.0 + 165.0/(1.0 + ufl.exp(5/2 - V/10.0)) +\
1125.0*ufl.exp(-0.00416666666666667*((27.0 + V)*(27.0 + V)))
# L type ca current fca gate
alpha_fCa = 1.0/(1.0 + 8.03402376701711e+27*ufl.elem_pow(Ca_i, 8.0))
beta_fCa = 0.1/(1.0 + 0.00673794699908547*ufl.exp(10000.0*Ca_i))
gama_fCa = 0.2/(1.0 + 0.391605626676799*ufl.exp(1250.0*Ca_i))
fCa_inf = 0.157534246575342 + 0.684931506849315*gama_fCa +\
0.684931506849315*beta_fCa + 0.684931506849315*alpha_fCa
tau_fCa = 2.0
d_fCa = (-fCa + fCa_inf)/tau_fCa
# Calcium background current
i_b_Ca = (V - E_Ca)*g_bca
# Transient outward current
i_to = (-E_K + V)*g_to*r*s
# Transient outward current s gate
s_inf = 1.0/(1.0 + ufl.exp(4.0 + V/5.0))
tau_s = 3.0 + 85.0*ufl.exp(-0.003125*((45.0 + V)*(45.0 + V))) + 5.0/(1.0 +\
ufl.exp(-4.0 + V/5.0))
# Transient outward current r gate
r_inf = 1.0/(1.0 + 28.0316248945261*ufl.exp(-0.166666666666667*V))
tau_r = 0.8 + 9.5*ufl.exp(-0.000555555555555556*((40.0 + V)*(40.0 + V)))
# Sodium potassium pump current
i_NaK = K_o*Na_i*P_NaK/((K_mk + K_o)*(Na_i + K_mNa)*(1.0 +\
0.0353*ufl.exp(-F*V/(R*T)) + 0.1245*ufl.exp(-0.1*F*V/(R*T))))
# Sodium calcium exchanger current
i_NaCa = (-(Na_o*Na_o*Na_o)*Ca_i*alpha*ufl.exp((-1.0 + gamma)*F*V/(R*T))\
+ (Na_i*Na_i*Na_i)*Ca_o*ufl.exp(F*V*gamma/(R*T)))*K_NaCa/((1.0 +\
K_sat*ufl.exp((-1.0 + gamma)*F*V/(R*T)))*((Na_o*Na_o*Na_o) +\
(Km_Nai*Km_Nai*Km_Nai))*(Km_Ca + Ca_o))
# Calcium pump current
i_p_Ca = Ca_i*g_pCa/(K_pCa + Ca_i)
# Potassium pump current
i_p_K = (-E_K + V)*g_pK/(1.0 +\
65.4052157419383*ufl.exp(-0.167224080267559*V))
# Calcium dynamics
i_rel = ((Ca_SR*Ca_SR)*a_rel/((Ca_SR*Ca_SR) + (b_rel*b_rel)) + c_rel)*d*g
i_up = Vmax_up/(1.0 + (K_up*K_up)/(Ca_i*Ca_i))
i_leak = (-Ca_i + Ca_SR)*V_leak
g_inf = (1.0 - 1.0/(1.0 + 0.0301973834223185*ufl.exp(10000.0*Ca_i)))/(1.0 +\
1.97201988740492e+55*ufl.elem_pow(Ca_i, 16.0)) + 1.0/((1.0 +\
0.0301973834223185*ufl.exp(10000.0*Ca_i))*(1.0 +\
5.43991024148102e+20*ufl.elem_pow(Ca_i, 6.0)))
d_g = (-g + g_inf)/tau_g
Ca_i_bufc = 1.0/(1.0 + Buf_c*K_buf_c/((K_buf_c + Ca_i)*(K_buf_c + Ca_i)))
Ca_sr_bufsr = 1.0/(1.0 + Buf_sr*K_buf_sr/((K_buf_sr + Ca_SR)*(K_buf_sr +\
Ca_SR)))
# Sodium dynamics
# Membrane
i_Stim = -(1.0 - 1.0/(1.0 + ufl.exp(-5.0*stim_start +\
5.0*time)))*stim_amplitude/(1.0 + ufl.exp(-5.0*stim_start + 5.0*time\
- 5.0*stim_duration))
# Potassium dynamics
# The ODE system: 17 states
# Init test function
_v = dolfin.TestFunction(states.function_space())
# Derivative for state Xr1
dy = ((-Xr1 + xr1_inf)/tau_xr1)*_v[0]
# Derivative for state Xr2
dy += ((-Xr2 + xr2_inf)/tau_xr2)*_v[1]
# Derivative for state Xs
dy += ((-Xs + xs_inf)/tau_xs)*_v[2]
# Derivative for state m
dy += ((-m + m_inf)/tau_m)*_v[3]
# Derivative for state h
dy += ((-h + h_inf)/tau_h)*_v[4]
# Derivative for state j
dy += ((j_inf - j)/tau_j)*_v[5]
# Derivative for state d
dy += ((d_inf - d)/tau_d)*_v[6]
# Derivative for state f
dy += ((-f + f_inf)/tau_f)*_v[7]
# Derivative for state fCa
dy += ((1.0 - 1.0/((1.0 + ufl.exp(60.0 + V))*(1.0 + ufl.exp(-10.0*fCa +\
10.0*fCa_inf))))*d_fCa)*_v[8]
# Derivative for state s
dy += ((-s + s_inf)/tau_s)*_v[9]
# Derivative for state r
dy += ((-r + r_inf)/tau_r)*_v[10]
# Derivative for state Ca_SR
dy += ((-i_leak + i_up - i_rel)*Ca_sr_bufsr*V_c/V_sr)*_v[11]
# Derivative for state Ca_i
dy += ((-i_up - (i_CaL + i_p_Ca + i_b_Ca - 2.0*i_NaCa)*Cm/(2.0*F*V_c) +\
i_leak + i_rel)*Ca_i_bufc)*_v[12]
# Derivative for state g
dy += ((1.0 - 1.0/((1.0 + ufl.exp(60.0 + V))*(1.0 + ufl.exp(-10.0*g +\
10.0*g_inf))))*d_g)*_v[13]
# Derivative for state Na_i
dy += ((-3.0*i_NaK - 3.0*i_NaCa - i_Na - i_b_Na)*Cm/(F*V_c))*_v[14]
# Derivative for state V
dy += (-i_Ks - i_to - i_Kr - i_p_K - i_NaK - i_NaCa - i_Na - i_p_Ca -\
i_b_Na - i_CaL - i_Stim - i_K1 - i_b_Ca)*_v[15]
# Derivative for state K_i
dy += ((-i_Ks - i_to - i_Kr - i_p_K - i_Stim - i_K1 +\
2.0*i_NaK)*Cm/(F*V_c))*_v[16]
# Return dy
return dy
