def capitulo_6():
model = cobra.test.create_test_model("textbook")
prod_env = production_envelope(model, ["EX_glc__D_e", "EX_o2_e"])
prod_env.head()
prod_env = production_envelope(model, ["EX_o2_e"],
objective="EX_ac_e",
c_source="EX_glc__D_e")
prod_env.head()
prod_env[prod_env.direction == 'maximum'].plot(kind='line',
x='EX_o2_e',
y='carbon_yield')
def productionEnvelopes(): #aka phenotype phase planes
# will show distinct phases of optimal growth with different use of two different substrates.
import cobra.test
from cobra.flux_analysis import production_envelope
model = cobra.test.create_test_model("textbook")
prod_env = production_envelope(model, ["EX_glc__D_e", "EX_o2_e"])
prod_env.head()
prod_env = production_envelope(model, ["EX_o2_e"],
objective="EX_ac_e",
c_source="EX_glc__D_e")
prod_env.head()
prod_env[prod_env.direction == 'maximum'].plot(kind='line',
x='EX_o2_e',
y='carbon_yield')
def test_envelope_two(model: Model) -> None:
"""Test production of envelope."""
df = production_envelope(model, ["EX_glc__D_e", "EX_o2_e"],
objective="EX_ac_e")
assert np.isclose(df["flux_maximum"].sum(), 1737.466, atol=1e-3)
assert np.isclose(df["carbon_yield_maximum"].sum(), 83.579, atol=1e-3)
assert np.isclose(df["mass_yield_maximum"].sum(), 82.176, atol=1e-3)
def _robustness_ppp(self,
conditions,
sheet,
reactions,
points=20,
reactions_constraints=None,
dense_output=False,
columns_to_drop=None,
output=None,
output_sheet=None,
minimum_growth=0.1,
):
if not columns_to_drop:
columns_to_drop = []
if not reactions_constraints:
reactions_constraints = {}
# just a wrapper for cobrapy production_envelope function
df = read_excel(os.path.join(self.conditions_directory, conditions), sheet)
with self.model:
self.apply_conditions(data_frame=df)
for rxn, bds in reactions_constraints.items():
self.get_reaction(rxn).bounds = bds
_growth = self.maximize(is_pfba=True)
if _growth < minimum_growth:
raise ValueError(f'Wrong Environmental Conditions, as growth rate is {_growth}')
sol = production_envelope(model=self.model,
reactions=reactions,
points=points, )
sol.drop(columns_to_drop, axis=1, inplace=True)
# transform the sparse ppp dataframe to dense ppp dataframe
if dense_output:
new_sol = DataFrame()
for row in sol.values:
_val, _col, _row = row
new_sol.loc[_row, _col] = _val
sol = new_sol
sol.fillna(0, inplace=True)
sol.sort_index(inplace=True)
sol.sort_index(axis=1, inplace=True)
return sol
print(maxval)
#model.reactions.get_by_id('PGI').lower_bound = 0
#model.reactions.get_by_id('PGI').upper_bound = 0
#print (model.slim_optimize())
#from cobra .medium import minimal_medium
#max_growth= model.slim_optimize()
#print (minimal_medium(model,max_growth))
#print (len (minimal_medium(model,max_growth)))
cobra.io.write_sbml_model(model, "iRsp_1066_v1.5.xml", use_fbc_package=False)
#en=production_envelope (model,['EX_o2_e','EX_glc__D_e'],objective= 'DM_ipdp', carbon_sources= 'EX_glc__D_e',points = 5)
en = np.array(
production_envelope(model, ["DM_ipdp"],
objective="BIOMASS_aerobic",
carbon_sources='EX_glc__D_e',
points=2000))
np.savetxt('MEP_Product_Nh4.csv', en, fmt='%s')
np.savetxt('MEP_ProductFVA_NH4.csv', FVA, fmt='%s')
print(en)
#OptKnock
'''KO= OptKnock (model)
result_OK = optknock.run(max_knockouts = NrKnockOuts,
target = "RXN0569",
biomass = biomass,
max_results = 50)
OptKnockResult = pandas.DataFrame(result_OK.data_frame)
OptKnockResult.to_csv(path_or_buf = "/home//%s.csv" % RUN, sep = ";", decimal = ",")'''
def test_envelope_one(model: Model) -> None:
"""Test flux of production envelope."""
df = production_envelope(model, ["EX_o2_e"])
assert np.isclose(df["flux_maximum"].sum(), 9.342, atol=1e-3)
def test_multi_variable_envelope(model: Model, variables: str,
num: int) -> None:
"""Test production of envelope (multiple variable)."""
df = production_envelope(model, variables, points=num)
assert len(df) == num**len(variables)
def test_envelope_multi_reaction_objective(model: Model) -> None:
"""Test production of multiple objectives."""
obj = {model.reactions.EX_ac_e: 1, model.reactions.EX_co2_e: 1}
with pytest.raises(ValueError):
production_envelope(model, "EX_o2_e", obj)
for reaction in model.metabolites.get_by_id(
metabolite.id).reactions:
print reaction
result = buscarMetabolito("gln__L")
result = buscarMetabolito("glc__D")
result = buscarMetabolito("xoltri25_e")
result = buscarMetabolito("lac")
result = buscarMetabolito("nh4")
# In[77]:
print
get_ipython().magic(u'matplotlib inline')
prod_env = production_envelope(model, ["EX_gln__L_e", "EX_glc__D_e"])
prod_env.head(20)
# In[86]:
x = np.unique(-1 * prod_env["EX_glc__D_e"])
y = np.unique(-1 * prod_env["EX_gln__L_e"])
z = prod_env["flux_maximum"]
MATRIZ_SOLUCION = np.zeros((20, 20))
for i in range(datos):
print prod_env["flux_maximum"][i * 20:(i + 1) * 20]
MATRIZ_SOLUCION[i, 0:20] = z[i * 20:(i + 1) * 20]
print "Matriz solución"
print "====================="
print MATRIZ_SOLUCION
