def clamp_species(r: roadrunner.RoadRunner,
sids,
boundary_condition=True) -> roadrunner.RoadRunner:
""" Clamp/Free specie(s) via setting boundaryCondition=True/False.
This requires changing the SBML and ODE system.
:param r: roadrunner.RoadRunner
:param sids: sid or iterable of sids
:param boundary_condition: boolean flag to clamp (True) or free (False) species
:return: modified roadrunner.RoadRunner
"""
# get model for current SBML state
sbml_str = r.getCurrentSBML()
doc = libsbml.readSBMLFromString(sbml_str) # type: libsbml.SBMLDocument
model = doc.getModel() # type: libsbml.Model
if isinstance(sids, str):
sids = [sids]
for sid in sids:
# set boundary conditions
sbase = model.getElementBySId(sid) # type: libsbml.SBase
if not sbase:
logging.error("No element for SId in model: {}".format(sid))
return None
else:
if sbase.getTypeCode() == libsbml.SBML_SPECIES:
species = sbase # type: libsbml.Species
species.setBoundaryCondition(boundary_condition)
else:
logging.error(
"SId in clamp does not match species: {}".format(sbase))
return None
# create modified roadrunner instance
sbmlmod_str = libsbml.writeSBMLToString(doc)
rmod = load_model(sbmlmod_str) # type: roadrunner.RoadRunner
set_timecourse_selections(rmod, r.timeCourseSelections)
return rmod
def species_df(r: roadrunner.RoadRunner) -> pd.DataFrame:
"""
Create FloatingSpecies DataFrame.
:return: pandas DataFrame
"""
r_model = r.model # type: roadrunner.ExecutableModel
sbml_str = r.getCurrentSBML()
doc = libsbml.readSBMLFromString(sbml_str) # type: libsbml.SBMLDocument
model = doc.getModel() # type: libsbml.Model
sids = r_model.getFloatingSpeciesIds() + r_model.getBoundarySpeciesIds()
species = [model.getSpecies(sid)
for sid in sids] # type: List[libsbml.Species]
data = {
'sid':
sids,
'concentration':
np.concatenate([
r_model.getFloatingSpeciesConcentrations(),
r_model.getBoundarySpeciesConcentrations()
],
axis=0),
'amount':
np.concatenate([
r.model.getFloatingSpeciesAmounts(),
r.model.getBoundarySpeciesAmounts()
],
axis=0),
'unit': [s.getUnits() for s in species],
'constant': [s.getConstant() for s in species],
'boundaryCondition': [s.getBoundaryCondition() for s in species],
'name': [s.getName() for s in species],
}
return pd.DataFrame(data,
columns=[
'sid', 'concentration', 'amount', 'unit',
'constant', 'boundaryCondition', 'species', 'name'
])
def parameter_df(r: roadrunner.RoadRunner) -> pd.DataFrame:
"""
Create GlobalParameter DataFrame.
:return: pandas DataFrame
"""
r_model = r.model # type: roadrunner.ExecutableModel
doc = libsbml.readSBMLFromString(
r.getCurrentSBML()) # type: libsbml.SBMLDocument
model = doc.getModel() # type: libsbml.Model
sids = r_model.getGlobalParameterIds()
parameters = [model.getParameter(sid)
for sid in sids] # type: List[libsbml.Parameter]
data = {
'sid': sids,
'value': r_model.getGlobalParameterValues(),
'unit': [p.units for p in parameters],
'constant': [p.constant for p in parameters],
'name': [p.name for p in parameters],
}
df = pd.DataFrame(data,
columns=['sid', 'value', 'unit', 'constant', 'name'])
return df
