def test_reaction_info():
cobra_model = read_cobra_model(FBC_SBML)
df = cobra_reaction_info(cobra_model)
assert df is not None
assert df.at["v1", "objective_coefficient"] == 1
assert df.at["v2", "objective_coefficient"] == 1
assert df.at["v3", "objective_coefficient"] == 1
assert df.at["v4", "objective_coefficient"] == 1
assert df.at["EX_Ac", "objective_coefficient"] == 0
assert df.at["EX_Glcxt", "objective_coefficient"] == 0
assert df.at["EX_O2", "objective_coefficient"] == 0
assert df.at["EX_X", "objective_coefficient"] == 0
def test_mass_balance(tmp_path):
doc = read_sbml(DEMO_SBML)
# add defaults
add_default_flux_bounds(doc)
filepath = tmp_path / "test.xml"
write_sbml(doc, filepath=filepath)
model = read_cobra_model(filepath)
# mass/charge balance
for r in model.reactions:
mb = r.check_mass_balance()
# all metabolites are balanced
assert len(mb) == 0
def tiny_simulation() -> None:
"""Analysis of the tiny model.
Creates model and runs simulation.
"""
# -----------------------------------------------------------------------------
# create model
# -----------------------------------------------------------------------------
factory_result = tiny_factory.create()
# -----------------------------------------------------------------------------
# run ode simulation
# -----------------------------------------------------------------------------
# tiny_sbml = os.path.join(os.path.dirname(os.path.abspath(__file__)),
# 'results',
# '{}_{}.xml'.format(model.mid, model.version))
tiny_dir = Path(__file__).parent
r = roadrunner.RoadRunner(str(factory_result.sbml_path))
r.timeCourseSelections = (["time"] + r.model.getBoundarySpeciesIds() +
r.model.getFloatingSpeciesIds() +
r.model.getReactionIds() +
r.model.getGlobalParameterIds())
r.timeCourseSelections += [
"[{}]".format(key) for key in r.model.getFloatingSpeciesIds()
]
# print(r)
s = r.simulate(0, 400, steps=400)
df = pd.DataFrame(s, columns=s.colnames)
# r.plot()
f, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)
ax1.set_title("SBML species")
ax1.plot(df.time, df["[glc]"])
ax1.plot(df.time, df["[g6p]"])
ax1.plot(df.time, df["[atp]"])
ax1.plot(df.time, df["[adp]"])
ax1.plot(df.time,
df["a_sum"],
color="grey",
linestyle="--",
label="[atp]+[adp]")
ax1.set_ylabel("concentration [mmole/litre]=[mM]")
ax2.set_title("SBML reactions")
ax2.plot(df.time, 1e6 * df.GK)
ax2.plot(df.time, 1e6 * df.ATPPROD)
ax2.set_ylabel("reaction rate 1E-6[mmole/s]")
for ax in (ax1, ax2):
ax.legend()
ax.set_xlabel("time [s]")
plt.show()
f.savefig(
tiny_dir / "results" /
f"{model_definition.mid}_{model_definition.version}_roadrunner.png",
bbox_inches="tight",
)
# -----------------------------------------------------------------------------
# fba simulation
# -----------------------------------------------------------------------------
model = read_cobra_model(factory_result.sbml_path)
print(model)
# Iterate through the the objects in the model
print("Reactions")
print("---------")
for x in model.reactions:
print("%s : %s [%s<->%s]" %
(x.id, x.reaction, x.lower_bound, x.upper_bound))
print("")
print("Metabolites")
print("-----------")
for x in model.metabolites:
print("%9s (%s) : %s, %s, %s" %
(x.id, x.compartment, x.formula, x.charge, x.annotation))
print("")
print("Genes")
print("-----")
for x in model.genes:
associated_ids = (i.id for i in x.reactions)
print("%s is associated with reactions: %s" %
(x.id, "{" + ", ".join(associated_ids) + "}"))
solution = model.optimize()
print(solution)
def test_load_cobra_model():
model = read_cobra_model(FBC_SBML)
assert model
for ax in (ax1, ax2):
ax.legend()
ax.set_xlabel("time [s]")
plt.show()
f.savefig(
tiny_dir / "results" /
f"{model_definition.mid}_{model_definition.version}_roadrunner.png",
bbox_inches="tight",
)
# -----------------------------------------------------------------------------
# fba simulation
# -----------------------------------------------------------------------------
model = read_cobra_model(tiny_sbml)
print(model)
# Iterate through the the objects in the model
print("Reactions")
print("---------")
for x in model.reactions:
print("%s : %s [%s<->%s]" %
(x.id, x.reaction, x.lower_bound, x.upper_bound))
print("")
print("Metabolites")
print("-----------")
for x in model.metabolites:
print("%9s (%s) : %s, %s, %s" %
(x.id, x.compartment, x.formula, x.charge, x.annotation))
