def elasticities_by_medium(com, reactions, fraction, growth_rate, progress):
"""Get the elasticity coefficients for a set of variables.
Arguments
---------
com : micom.Community
The community for wrhich to calculate elasticities.
variables : list of optlang.Variable
The variables for which to calculate the elasticities. All of these
must have non-zero primal vaues in the previous solution.
Returns
-------
pandas.Dataframe
The long/tidy version of the elasticities. Contains columns variable,
effector, and elasticity.
"""
regularize_l2_norm(com, 0.0)
sol = optimize_with_fraction(com, fraction, growth_rate, True)
before = _get_fluxes(sol, reactions)
import_fluxes = pd.Series()
dfs = []
for ex in com.exchanges:
export = len(ex.reactants) == 1
flux = sol.fluxes.loc[ex.community_id, ex.global_id]
if export and (flux < -1e-6):
import_fluxes[ex] = flux
elif not export and (flux > 1e-6):
import_fluxes[ex] = -flux
else:
continue
fluxes = import_fluxes.index
if progress:
fluxes = track(fluxes, description="Metabolites")
for r in fluxes:
flux = import_fluxes[r]
with com:
if flux < -1e-6:
r.lower_bound *= np.exp(STEP)
else:
r.upper_bound *= np.exp(STEP)
sol = optimize_with_fraction(com, fraction, growth_rate, True)
after = _get_fluxes(sol, reactions)
deriv, dirs = _derivatives(before, after)
res = pd.DataFrame({
"reaction": [rx.global_id for rx in reactions],
"taxon": [list(r.compartments)[0] for r in reactions],
"effector":
r.id,
"direction":
dirs,
"elasticity":
deriv,
})
dfs.append(res)
return pd.concat(dfs)
def elasticities_by_abundance(com, reactions, fraction, growth_rate, progress):
"""Get the elasticity coefficients for a set of variables.
Arguments
---------
com : micom.Community
The community for which to calculate elasticities.
variables : list of optlang.Variable
The variables for which to calculate the elasticities. All of these
must have non-zero primal vaues in the previous solution.
Returns
-------
pandas.Dataframe
The long/tidy version of the elasticities. Contains columns variable,
effector, and elasticity.
"""
regularize_l2_norm(com, 0.0)
sol = optimize_with_fraction(com, fraction, growth_rate, True)
before = _get_fluxes(sol, reactions)
dfs = []
abundance = com.abundances.copy()
taxa = abundance.index
if progress:
taxa = track(taxa, description="Taxa")
for sp in taxa:
old = abundance[sp]
abundance.loc[sp] *= np.exp(STEP)
com.set_abundance(abundance, normalize=False)
sol = optimize_with_fraction(com, fraction, growth_rate, True)
after = _get_fluxes(sol, reactions)
abundance.loc[sp] = old
com.set_abundance(abundance, normalize=False)
deriv, dirs = _derivatives(before, after)
res = pd.DataFrame({
"reaction": [r.global_id for r in reactions],
"taxon": [list(r.compartments)[0] for r in reactions],
"effector":
sp,
"direction":
dirs,
"elasticity":
deriv,
})
dfs.append(res)
return pd.concat(dfs)