def test_medium_element(community):
medium = media.minimal_medium(community, 0.8, 0.8, weights="C")
assert len(medium) <= 4
assert medium["EX_glc__D_m"] < 9.5
# Anaerobic growth
medium = media.minimal_medium(community, 0.1, 0.1, weights="C")
assert len(medium) <= 4
assert medium["EX_glc__D_m"] < 2.0
def test_medium_mass(community):
medium = media.minimal_medium(community, 0.8, 0.8, weights="mass")
assert len(medium) <= 4
medium["EX_o2_m"] > 20.0
# Anaerobic growth
medium = media.minimal_medium(community, 0.1, 0.1, weights="mass")
assert len(medium) <= 4
medium["EX_o2_m"] > 4.0
def test_medium_mip(community):
medium = media.minimal_medium(community, 0.8, 0.8,
minimize_components=True)
assert len(medium) <= 4
assert all(medium > 1e-9)
# Anaerobic growth
medium = media.minimal_medium(community, 0.1, 0.1,
minimize_components=True)
assert len(medium) <= 3
assert all(medium > 1e-9)
def _growth(args):
p, tradeoff, medium = args
com = load_pickle(p)
ex_ids = [r.id for r in com.exchanges]
logger.info(
"%d/%d import reactions found in model.",
medium.index.isin(ex_ids).sum(),
len(medium),
)
com.medium = medium[medium.index.isin(ex_ids)]
# Get growth rates
try:
sol = com.cooperative_tradeoff(fraction=tradeoff)
rates = sol.members
rates["taxon"] = rates.index
rates["tradeoff"] = tradeoff
rates["sample_id"] = com.id
except Exception:
logger.warning("Could not solve cooperative tradeoff for %s." % com.id)
return None
# Get the minimal medium
med = minimal_medium(com, 0.95 * sol.growth_rate)
# Apply medium and reoptimize
com.medium = med[med > 0]
sol = com.cooperative_tradeoff(fraction=tradeoff, fluxes=True, pfba=False)
fluxes = sol.fluxes.loc[:, sol.fluxes.columns.str.startswith("EX_")].copy()
fluxes["sample_id"] = com.id
return {"growth": rates, "exchanges": fluxes}
def _medium(args):
"""Get minimal medium for a single model."""
p, min_growth = args
com = load_pickle(p)
medium = mm.minimal_medium(com, 0.0, min_growth=min_growth).to_frame()
medium.columns = ["flux"]
medium.index.name = "reaction"
return medium.reset_index()
def _growth(args):
p, tradeoff, medium, weights, atol, rtol = args
com = load_pickle(p)
if atol is None:
atol = com.solver.configuration.tolerances.optimality
if rtol is None:
rtol = com.solver.configuration.tolerances.optimality
com = load_pickle(p)
if "glpk" in interface_to_str(com.solver.interface):
logger.error(
"Community models were not built with a QP-capable solver. "
"This means that you did not install CPLEX or Gurobi. "
"If you did install one of the two please file a bug report "
"at https://github.com/micom-dev/micom/issues."
)
return None
ex_ids = [r.id for r in com.exchanges]
logger.info(
"%d/%d import reactions found in model.",
medium.index.isin(ex_ids).sum(),
len(medium),
)
com.medium = medium[medium.index.isin(ex_ids)]
# Get growth rates
try:
sol = com.cooperative_tradeoff(fraction=tradeoff)
rates = sol.members
rates["taxon"] = rates.index
rates["tradeoff"] = tradeoff
rates["sample_id"] = com.id
except Exception:
logger.warning(
"Could not solve cooperative tradeoff for %s. "
"This can often be fixed by chosing ore permissive atol and rtol "
"arguments." % com.id)
return None
# Get the minimal medium and the solution at the same time
sol = minimal_medium(
com,
exchanges=None,
community_growth=sol.growth_rate,
min_growth=rates.growth_rate.drop("medium"),
solution=True,
weights=weights,
atol=atol,
rtol=rtol
)["solution"]
fluxes = sol.fluxes.loc[:, sol.fluxes.columns.str.startswith("EX_")].copy()
fluxes["sample_id"] = com.id
fluxes["tolerance"] = atol
anns = annotate_metabolites_from_exchanges(com)
return {"growth": rates, "exchanges": fluxes, "annotations": anns}
def test_complete_mip(community):
m = media.minimal_medium(community, 0.85, 0.85, minimize_components=True)
medium = media.complete_medium(community,
m[0:2],
0.8,
0.0,
max_import=20,
minimize_components=True)
assert len(medium) > 2
def _medium(args):
"""Get minimal medium for a single model."""
s, p, min_growth = args
com = load_pickle(p)
# open the bounds
for ex in com.exchanges:
ex.bounds = (-1000.0, 1000.0)
try:
medium = mm.minimal_medium(com, 0.0, min_growth=min_growth).to_frame()
except Exception:
return None
medium.columns = ["flux"]
medium["sample_id"] = s
medium.index.name = "reaction"
return medium.reset_index()
def media_and_gcs(sam):
com = load_pickle("data/models/" + sam + ".pickle")
# Get growth rates
try:
sol = com.cooperative_tradeoff(fraction=0.5)
rates = sol.members["growth_rate"].copy()
rates["community"] = sol.growth_rate
rates.name = sam
except Exception:
logger.warning("Could not solve cooperative tradeoff for %s." % sam)
return None
# Get the minimal medium
med = minimal_medium(com, 0.95 * sol.growth_rate, exports=True)
med.name = sam
# Apply medium and reoptimize
com.medium = med[med > 0]
sol = com.cooperative_tradeoff(fraction=0.5, fluxes=True, pfba=False)
fluxes = sol.fluxes
fluxes["sample"] = sam
return {"medium": med, "gcs": rates, "fluxes": fluxes}
def media_and_gcs(sam):
com = load_pickle(pickles_path +"/"+ sam)
# Get growth rates
try:
sol = com.cooperative_tradeoff(fraction=trade_off)
rates = sol.members["growth_rate"].copy()
rates["community"] = sol.growth_rate
rates.name = sam
except Exception:
logger.warning("Could not solve cooperative tradeoff for %s." % sam)
return None
# Get the minimal medium
med = minimal_medium(com, 0.95 * sol.growth_rate, exports=True)
med.name = sam
# Apply medium and reoptimize
com.medium = med[med > 0]
sol = com.cooperative_tradeoff(fraction=0.5, fluxes=True, pfba=False) # uses the 'classic' FBA instead of the parsimonious FBA
fluxes = sol.fluxes
fluxes["sample"] = sam
return {"medium": med, "gcs": rates, "fluxes": fluxes}
def test_medium_linear(community):
medium = media.minimal_medium(community, 0.8, 0.8)
assert len(medium) <= 4
assert all(medium > 1e-9)
def test_medium_wrong_element(community):
with pytest.raises(ValueError):
medium = media.minimal_medium(community, 0.8, 0.8, weights="Cat")
