def test_c_se_sim():
c = new("C", value=1)
se = new("Se")
r = new("R", value=1)
kcl = new("1")
bg = new()
bg.add([c, se, kcl, r])
connect(c, (kcl, kcl.non_inverting))
connect(r, (kcl, kcl.non_inverting))
connect(se, (kcl, kcl.non_inverting))
def u(t, x, dx):
return -np.exp(-t)
assert str(bg.constitutive_relations) == '[dx_0 + u_0 + x_0]'
with pytest.raises(ModelException) as ex:
_ = simulate(
c, timespan=[0, 10], x0=[0]
)
assert "Control variable u_0 must be specified" in ex.args
t, x = simulate(
bg, timespan=[0, 10], x0=[0], control_vars=[u]
)
assert t[0] == 0
assert t[-1] == 10
assert (len(t), 1) == x.shape
assert x[0, 0] == 0
solution = t * np.exp(-t)
res = abs(x - solution)
assert (res < 0.001).all()
def test_c_se_sim():
c = new("C", value=1)
se = new("Se")
r = new("R", value=1)
kcl = new("1")
bg = new()
bg.add([c, se, kcl, r])
connect(c, (kcl, kcl.non_inverting))
connect(r, (kcl, kcl.non_inverting))
connect(se, (kcl, kcl.non_inverting))
with pytest.raises(ModelException) as ex:
t, x = simulate(c, timespan=[0, 10], x0=[0], dx0=[1])
assert "Control variable not specified" in ex.args
t, x = simulate(bg,
timespan=[0, 10],
x0=[0],
dx0=[1],
control_vars=['-exp(-t)'])
assert t[0] == 0
assert t[-1] == 10
t_cols, _ = t.shape
assert t_cols > 1
assert (t_cols, 1) == x.shape
assert x[0, 0] == 0
solution = (1 + t) * np.exp(-t)
solution = solution.reshape(t_cols, 1)
assert ((x - solution) < 0.001).all()
def test_rlc():
c = new("C", value=1)
se = new("Se")
r = new("R", value=1)
l = new("I", value=1)
kvl = new("0")
bg = new()
bg.add([c, se, kvl, r, l])
connect(c, kvl)
connect(r, kvl)
connect(se, kvl)
connect(l, kvl)
t, x = simulate(bg, timespan=[0, 10], x0=[1, 0], control_vars=[1])
def test_closed_cycle():
model = biochemical_cycle()
x0 = [2.0, 2.0, 2.0]
tspan = (0, 1.0)
K_X_vals = [1.0, 2.0, 3.0, 4.0]
r1 = (model / "R:r1").params['r']['value']
K_Y = (model / "C:Y").params['k']['value']
def v1(r, K_X, K_Y, x_X, x_Y): return r * K_X * x_X - r * K_Y * x_Y
for K_X in K_X_vals:
(model / "C:X").set_param('k', K_X)
t, x = simulate(model, tspan, x0, dt=0.01)
# Check initial reaction rate
assert v1(r1, K_X, K_Y, x[0][0], x[0][1]) == -4 + 2 * K_X
# Check that the final reaction rate is small
assert v1(r1, K_X, K_Y, x[-1][0], x[-1][1]) < 1e-4
def test_c_se_sum_switch():
c = new("C", value=1)
se = new("Se")
r = new("R", value=1)
kcl = new("1")
bg = new()
bg.add([c, se, kcl, r])
connect(c, (kcl, kcl.non_inverting))
connect(r, (kcl, kcl.non_inverting))
connect(se, (kcl, kcl.non_inverting))
def bang_bang(t, x, dx):
return 1.5 if x >= 1 else -2.0
t, x = simulate(
bg, timespan=[0, 10], x0=[0], dx0=[1], control_vars=[bang_bang])
assert (x[0, -1] - 1) < 0.001
def test_c_se_sum_switch():
c = new("C", value=1)
se = new("Se")
r = new("R", value=1)
kcl = new("1")
bg = new()
bg.add([c, se, kcl, r])
connect(c, (kcl, kcl.non_inverting))
connect(r, (kcl, kcl.non_inverting))
connect(se, (kcl, kcl.non_inverting))
bang_bang = ["x_0 >= 1 ? 1.5: -2 "]
t, x = simulate(bg,
timespan=[0, 10],
x0=[0],
dx0=[1],
control_vars=bang_bang)
assert (x[0, -1] - 1) < 0.001
def test_open_cycle():
model = open_cycle()
x0 = [2.0,2.0,2.0]
tspan = (0,10.0)
K_A = 1
x_A_vals = [0.02,2.0,200]
expected_fluxes = [-3.0906200316489003,0.0,10.860335195530652]
r1 = (model/"R:r1").params['r']['value']
K_X = (model/"C:X").params['k']['value']
K_Y = (model/"C:Y").params['k']['value']
def v1(r,K_X,K_Y,K_A,x_X,x_Y,x_A): return r*K_X*x_X*K_A*x_A - r*K_Y*x_Y
for x_A,v_true in zip(x_A_vals,expected_fluxes):
mu_A = np.log(K_A*x_A)
(model/"SS:A").set_param('e',mu_A)
t,x = simulate(model,tspan,x0)
x_end = x[-1]
flux = v1(r1,K_X,K_Y,K_A,x_end[0],x_end[1],x_A)
assert flux == pytest.approx(v_true,abs=1e-6)
def test_c_sim_fail():
c = new("C")
with pytest.raises(ModelException):
t, x = simulate(c, timespan=[0, 1], x0=[1], dx0=[1])