def test_clamp_sid():
r = load_model(MODEL_REPRESSILATOR)
# Perform clamping
r_clamp = clamp_species(r, sids=["X"], boundary_condition=True)
assert r_clamp
assert isinstance(r_clamp, roadrunner.RoadRunner)
def test_plotting():
r = load_model(MODEL_REPRESSILATOR)
simulator = Simulator(MODEL_REPRESSILATOR)
changeset = ChangeSet.parameter_sensitivity_changeset(r, sensitivity=0.5)
tcsims = ensemble(
TimecourseSim([
Timecourse(start=0, end=400, steps=400),
]), changeset)
result = simulator.timecourses(tcsims)
# create figure
fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(5, 5))
fig.subplots_adjust(wspace=0.3, hspace=0.3)
add_line(ax=ax1, data=result, xid='time', yid="X", label="X")
add_line(ax=ax1,
data=result,
xid='time',
yid="Y",
label="Y",
color="darkblue")
ax1.legend()
plt.show()
def run_sensitivity():
""" Parameter sensitivity simulations.
:return:
"""
simulator = Simulator(MODEL_REPRESSILATOR)
# parameter sensitivity
# FIXME: make work with parallel
r = load_model(MODEL_REPRESSILATOR)
changeset = ChangeSet.parameter_sensitivity_changeset(r)
tc_sim = TimecourseSim([
Timecourse(start=0, end=100, steps=100),
Timecourse(start=0,
end=200,
steps=100,
model_changes={"boundary_condition": {
"X": True
}}),
Timecourse(start=0,
end=100,
steps=100,
model_changes={"boundary_condition": {
"X": False
}}),
])
tc_sims = ensemble(tc_sim, changeset=changeset)
result = simulator.timecourses(tc_sims)
# create figure
fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(5, 5))
fig.subplots_adjust(wspace=0.3, hspace=0.3)
add_line(ax=ax1, data=result, xid='time', yid="X", label="X")
add_line(ax=ax1,
data=result,
xid='time',
yid="Y",
label="Y",
color="darkblue")
add_line(ax=ax1,
data=result,
xid='time',
yid="Z",
label="Z",
color="darkorange")
ax1.legend()
plt.show()
ax.plot(x,
data.mean[yid],
'-',
color=color,
label="sim {}".format(label))
else:
x = data[xid] * xf
ax.plot(x, data[yid], '-', color=color, label="sim {}".format(label))
if __name__ == "__main__":
from sbmlsim.tests.constants import MODEL_REPRESSILATOR
from sbmlsim.model import load_model
from sbmlsim.parametrization import ChangeSet
from sbmlsim.simulation_serial import TimecourseSimulation, Timecourse, timecourses
r = load_model(MODEL_REPRESSILATOR)
# parameter sensitivity
changeset = ChangeSet.parameter_sensitivity_changeset(r, sensitivity=0.05)
tc_sims = TimecourseSimulation([
Timecourse(start=0, end=100, steps=100),
Timecourse(start=0,
end=200,
steps=100,
model_changes={"boundary_condition": {
"X": True
}}),
Timecourse(start=0,
end=100,
steps=100,
model_changes={"boundary_condition": {
def test_species_df():
r = load_model(MODEL_REPRESSILATOR)
df = species_df(r)
assert df is not None
assert "sid" in df
def test_parameter_df():
r = load_model(MODEL_REPRESSILATOR)
df = parameter_df(r)
assert df is not None
assert "sid" in df
def __init__(self, path, selections: List[str] = None):
self.r = load_model(path=path, selections=selections)
changes_init = pkpd.init_concentrations_changes(r, 'som', 0E-6) # [0 nmol/L]
tcsims = ensemble(
TimecourseSim([
Timecourse(start=0, end=60, steps=120, changes=changes_init),
Timecourse(start=0, end=60, steps=120, changes={'Ri_som': 10.0E-6}), # [mg/min],
Timecourse(start=0, end=60, steps=120, changes={'Ri_som': 20.0E-6}), # [mg/min],
Timecourse(start=0, end=60, steps=120, changes={'Ri_som': 40.0E-6}), # [mg/min],
Timecourse(start=0, end=60, steps=120, changes={'Ri_som': 80.0E-6}), # [mg/min],
]), ChangeSet.parameter_sensitivity_changeset(r, 0.1)
)
return simulator.timecourses(tcsims)
if __name__ == "__main__":
import sys
r = load_model(MODEL_GLCWB)
simulator = Simulator(MODEL_GLCWB)
results = {}
for f_simulate in [po_bolus, iv_bolus, iv_infusion, clamp, mix, stepped_clamp]:
f_key = f_simulate.__name__
print(f_key)
result = f_simulate(simulator, r)
print(result)
print("results:", len(result), sys.getsizeof(result))
results[f_key] = result
for key, result in results.items():
somatostatin_plot(result, title=key)
plt.show()
import ray