def boundsStringFromReaction(reaction: libsbml.Reaction,
model: libsbml.Model) -> str:
"""Render string of bounds from the reaction.
:param reaction: SBML reaction instance
:param model: SBML model instance
:return: String of bounds extracted from the reaction
"""
bounds = ""
rfbc = reaction.getPlugin("fbc")
if rfbc is not None:
# get values for bounds
lb_id, ub_id = None, None
lb_value, ub_value = None, None
if rfbc.isSetLowerFluxBound():
lb_id = rfbc.getLowerFluxBound()
lb_p = model.getParameter(lb_id)
if lb_p.isSetValue():
lb_value = lb_p.getValue()
if rfbc.isSetUpperFluxBound():
ub_id = rfbc.getUpperFluxBound()
ub_p = model.getParameter(ub_id)
if ub_p.isSetValue():
ub_value = ub_p.getValue()
if (lb_value is not None) or (ub_value is not None):
bounds = f"""
<code>[{lb_value}
<i class="fa fa-sort fa-rotate-90" aria-hidden="true"></i>
{ub_value}]
</code>
"""
return bounds
def get_model_parameters(sbml_model: libsbml.Model) -> List[str]:
"""Return list of SBML model parameter IDs which are not AssignmentRule
targets for observables or sigmas"""
return [
p.getId() for p in sbml_model.getListOfParameters()
if sbml_model.getAssignmentRuleByVariable(p.getId()) is None
]
def _create_port_map(self, model: libsbml.Model) -> Dict:
"""Create dictionary of symbols:port for symbols in model.
This allows to lookup port for a given Sbase.
:return: port dictionary for model
"""
ports: Dict[str, Dict] = {}
port: libsbml.Port
comp_model: libsbml.CompModelPlugin = model.getPlugin("comp")
if comp_model:
for port in comp_model.getListOfPorts():
port_info = self.sbaseref_dict(port)
if port.isSetIdRef():
ports[port.getIdRef()] = port_info
elif port.isSetUnitRef():
udef: libsbml.UnitDefinition = model.getUnitDefinition(
port.getUnitRef())
# Be careful, this is a different namespace.
# I.e. for UnitDefinitions you have to check ports in a different namespace
ports[f"units:{udef.getId()}"] = port_info
elif port.isSetMetaIdRef():
metaid = port.getMetaIdRef()
sbase: libsbml.SBase = model.getElementByMetaId(metaid)
if not sbase:
sbase = model.getElementFromPluginsByMetaId(metaid)
if sbase.isSetId():
ports[sbase.getId()] = port_info
return ports
def _apply_condition_parameters(par_mapping: ParMappingDict,
scale_mapping: ScaleMappingDict,
condition_id: str, condition_df: pd.DataFrame,
sbml_model: libsbml.Model) -> None:
"""Replace parameter IDs in parameter mapping dictionary by condition
table parameter values (in-place).
Arguments:
par_mapping: see get_parameter_mapping_for_condition
condition_id: ID of condition to work on
condition_df: PEtab condition table
"""
for overridee_id in condition_df.columns:
if overridee_id == CONDITION_NAME:
continue
# Species and compartments are handled elsewhere
if sbml_model.getSpecies(overridee_id) is not None:
continue
if sbml_model.getCompartment(overridee_id) is not None:
continue
par_mapping[overridee_id] = core.to_float_if_float(
condition_df.loc[condition_id, overridee_id])
scale_mapping[overridee_id] = LIN
def is_complex_assembly(reaction: libsbml.Reaction, model: libsbml.Model):
"""
Returns true iff 'reaction' can be classified as a biomolecular complex assembly.
Rules:
- The reaction must have at least two reactants and exactly one product
- The product must be annotated with the same non-empty set
of identifiers as the full set of identifiers for all reactants.
(This is assumed to mean that the product contains all and consists
only of the specified reactants, so the reaction is a complex assembly.)
:param reaction: libSBML Reaction object to classify as a transport.
:param model: libsbml Model containing the 'reaction' object.
:rtype: bool
"""
if len(reaction.getListOfReactants()) < 2 or len(
reaction.getListOfProducts()) != 1:
return False
reactant_identifiers = set()
for reactant in reaction.getListOfReactants():
reactant_species = model.getSpecies(
reactant.toXMLNode().getAttrValue('species'))
reactant_identifiers.update(
extract_annotation_identifiers(
reactant_species.getAnnotationString()))
product = reaction.getListOfProducts()[0]
product_species = model.getSpecies(
product.toXMLNode().getAttrValue('species'))
product_identifiers = set(
extract_annotation_identifiers(product_species.getAnnotationString()))
return len(reactant_identifiers
) > 0 and reactant_identifiers == product_identifiers
def _create_species(model: sbml.Model, species_id: str, initial_amount: str):
"""
Creates a species and adds it to the given SBML model.
Units are set as dimensionless by default.
Arguments:
model: the SBML model to which the species will be added.
species_id: the species ID
initial_amount: the species initial amount
Returns:
s: the SBML species
Raises:
"""
s = model.createSpecies()
s.setId(species_id)
try:
s.setInitialAmount(float(initial_amount))
except ValueError:
init = model.createInitialAssignment()
init.setId('init_' + species_id)
init.setSymbol(species_id)
init.setMath(sbml.parseL3Formula(initial_amount))
s.setConstant(False)
s.setBoundaryCondition(False)
s.setHasOnlySubstanceUnits(False)
s.setCompartment('Compartment')
s.setSubstanceUnits('dimensionless')
return s
def model(self, model: libsbml.Model) -> Dict[str, str]:
"""Info for SBML Model.
:param model: Model
:return: information dictionary for Model
"""
d = self.sbase_dict(model)
for key in [
"substanceUnits",
"timeUnits",
"volumeUnits",
"areaUnits",
"lengthUnits",
"extentUnits",
]:
d[f"{key}_unit"] = _get_sbase_attribute(model, key)
d[key] = udef_to_string(d[f"{key}_unit"], model)
# FIXME: handle analoque to species
if model.isSetConversionFactor():
cf_sid = model.getConversionFactor()
cf_p: libsbml.Parameter = model.getParameter(cf_sid)
cf_value = cf_p.getValue()
cf_units = cf_p.getUnits()
d["conversionFactor"] = {
"sid": cf_sid,
"value": cf_value,
"units": cf_units,
}
else:
d["conversionFactor"] = {}
return d
def _elements_from_ids(model: libsbml.Model,
sbml_ids: Iterable[str],
sbml_type: str = None) -> List[libsbml.SBase]:
"""
Get list of SBML elements from given ids.
:param model: SBML model
:param sbml_ids: SBML SIds
:param sbml_type: type of SBML objects
:return:
"""
elements = []
for sid in sbml_ids:
if sbml_type == "rule":
e = model.getRuleByVariable(sid)
elif sbml_type == "unit":
e = model.getUnitDefinition(sid)
else:
# returns the first element with id
e = model.getElementBySId(sid)
if e is None:
if sid == model.getId():
e = model
else:
logging.warning(f"Element not found for sid: '{sid}'.")
continue
elements.append(e)
return elements
def get_required_parameters_for_parameter_table(
sbml_model: libsbml.Model,
condition_df: pd.DataFrame,
observable_df: pd.DataFrame,
measurement_df: pd.DataFrame) -> Set[str]:
"""
Get set of parameters which need to go into the parameter table
Arguments:
sbml_model: PEtab SBML model
condition_df: PEtab condition table
observable_df: PEtab observable table
measurement_df: PEtab measurement table
Returns:
Set of parameter IDs which PEtab requires to be present in the
parameter table. That is all {observable,noise}Parameters from the
measurement table as well as all parametric condition table overrides
that are not defined in the SBML model.
"""
# use ordered dict as proxy for ordered set
parameter_ids = OrderedDict()
# Add parameters from measurement table, unless they are fixed parameters
def append_overrides(overrides):
for p in overrides:
if isinstance(p, str) and p not in condition_df.columns:
parameter_ids[p] = None
for _, row in measurement_df.iterrows():
# we trust that the number of overrides matches
append_overrides(measurements.split_parameter_replacement_list(
row.get(OBSERVABLE_PARAMETERS, None)))
append_overrides(measurements.split_parameter_replacement_list(
row.get(NOISE_PARAMETERS, None)))
# Add output parameters except for placeholders
for kwargs in [dict(observables=True, noise=False),
dict(observables=False, noise=True)]:
output_parameters = observables.get_output_parameters(
observable_df, sbml_model, **kwargs)
placeholders = observables.get_placeholders(
observable_df, **kwargs)
for p in output_parameters:
if p not in placeholders and sbml_model.getParameter(p) is None:
parameter_ids[p] = None
# Add condition table parametric overrides unless already defined in the
# SBML model
for p in conditions.get_parametric_overrides(condition_df):
if sbml_model.getParameter(p) is None:
parameter_ids[p] = None
return parameter_ids.keys()
def determineCD(model: libsbml.Model):
'''
if the provided SBML is exported from cell designer,
loads of meta information need to be processed.
'''
cd = False
for i in range(model.getNamespaces().getNumNamespaces()):
if model.getNamespaces().getPrefix(i) == 'celldesigner':
cd = True
return cd
def constant_species_to_parameters(sbml_model: libsbml.Model) -> list:
"""Convert constant species in the SBML model to constant parameters.
This can be used e.g. for setting up models with condition-specific
constant species for PEtab, since there it is not possible to specify
constant species in the condition table.
Arguments:
sbml_model: libsbml model instance
Returns:
species IDs that have been turned into constants
Raises:
"""
transformables = []
for species in sbml_model.getListOfSpecies():
if not species.getConstant() and not species.getBoundaryCondition():
continue
if species.getHasOnlySubstanceUnits():
logger.warning(
f"Ignoring {species.getId()} which has only substance units."
" Conversion not yet implemented.")
continue
if math.isnan(species.getInitialConcentration()):
logger.warning(
f"Ignoring {species.getId()} which has no initial "
"concentration. Amount conversion not yet implemented.")
continue
transformables.append(species.getId())
# Must not remove species while iterating over getListOfSpecies()
for speciesId in transformables:
species = sbml_model.removeSpecies(speciesId)
par = sbml_model.createParameter()
par.setId(species.getId())
par.setName(species.getName())
par.setConstant(True)
par.setValue(species.getInitialConcentration())
par.setUnits(species.getUnits())
# Remove from reactants and products
for reaction in sbml_model.getListOfReactions():
for speciesId in transformables:
reaction.removeReactant(speciesId)
reaction.removeProduct(speciesId)
reaction.removeModifier(speciesId)
return transformables
def _get_eplugin_by_sid(model: libsbml.Model, sid: str) -> Any:
"""Get the comp plugin by sid.
:param model: SBMLModel instance
:param sid: SBase id of object
:return:
"""
e = model.getElementBySId(sid)
if not e:
e = model.getUnitDefinition(sid)
eplugin = e.getPlugin("comp")
return eplugin
def create_sbml(self, model: libsbml.Model):
layout_model = model.getPlugin("layout") # type: libsbml.LayoutModelPlugin
if not layout_model:
doc = model.getSBMLDocument() # type: libsbml.SBMLDocument
doc.enablePackage("http://www.sbml.org/sbml/level3/version1/layout/version{}".format(LAYOUT_VERSION), "layout", True)
doc.setPackageRequired("layout", False)
layout_model = model.getPlugin("layout") # type: libsbml.LayoutModelPlugin
layout = layout_model.createLayout() # type: libsbml.Layout
self.set_fields(layout)
return layout
def _create_assignment_map(self, model: libsbml.Model) -> Dict:
"""Create dictionary of symbols:assignment for symbols in model.
This allows to lookup assignments for a given variable.
:return: assignment dictionary for model
"""
assignments: Dict[str, Dict] = {}
initial_assignment: libsbml.InitialAssignment
for initial_assignment in model.getListOfInitialAssignments():
pk_symbol = (initial_assignment.getSymbol()
if initial_assignment.isSetSymbol() else None)
if pk_symbol:
assignments[pk_symbol] = {
"pk": self._get_pk(initial_assignment),
"id": pk_symbol,
"sbmlType": self._sbml_type(initial_assignment),
}
math_str = (
symbol_to_latex(pk_symbol) + "(0) = "
f"{astnode_to_latex(initial_assignment.getMath())}")
assignments[pk_symbol]["math"] = math_str
rule: libsbml.Rule
for rule in model.getListOfRules():
pk_symbol = rule.getVariable() if rule.isSetVariable() else None
if pk_symbol:
assignments[pk_symbol] = {
"pk": self._get_pk(rule),
"id": pk_symbol,
"sbmlType": self._sbml_type(rule),
}
math_str = ""
if assignments[pk_symbol]["sbmlType"] == "AssignmentRule":
math_str = (
symbol_to_latex(pk_symbol) + " = "
f"{astnode_to_latex(rule.getMath()) if rule.isSetMath() else None}"
)
elif assignments[pk_symbol]["sbmlType"] == "RateRule":
derivative = "\\frac{d" + symbol_to_latex(
pk_symbol) + "}{{dt}}"
math_str = f"{derivative} = {astnode_to_latex(rule.getMath()) if rule.isSetMath() else None}"
assignments[pk_symbol]["math"] = math_str
return assignments
def add_global_parameter(sbml_model: libsbml.Model,
parameter_id: str,
parameter_name: str = None,
constant: bool = False,
units: str = 'dimensionless',
value: float = 0.0) -> libsbml.Parameter:
"""Add new global parameter to SBML model
Arguments:
sbml_model: SBML model
parameter_id: ID of the new parameter
parameter_name: Name of the new parameter
constant: Is parameter constant?
units: SBML unit ID
value: parameter value
Returns:
The created parameter
"""
if parameter_name is None:
parameter_name = parameter_id
p = sbml_model.createParameter()
p.setId(parameter_id)
p.setName(parameter_name)
p.setConstant(constant)
p.setValue(value)
p.setUnits(units)
return p
def get_output_parameters(observable_df: pd.DataFrame,
sbml_model: libsbml.Model) -> List[str]:
"""Get output parameters
Returns IDs of parameters used in observable and noise formulas that are
not defined in the SBML model.
Arguments:
observable_df: PEtab observable table
sbml_model: SBML model
Returns:
List of output parameter IDs
"""
formulas = list(observable_df[OBSERVABLE_FORMULA])
if NOISE_FORMULA in observable_df:
formulas.extend(observable_df[NOISE_FORMULA])
output_parameters = OrderedDict()
for formula in formulas:
free_syms = sorted(sp.sympify(formula).free_symbols,
key=lambda symbol: symbol.name)
for free_sym in free_syms:
sym = str(free_sym)
if sbml_model.getElementBySId(sym) is None and sym != 'time':
output_parameters[sym] = None
return list(output_parameters.keys())
def get_reactant_species_ids(reaction: libsbml.Reaction, model: libsbml.Model):
product = reaction.getListOfProducts()[0]
product_species = model.getSpecies(
product.toXMLNode().getAttrValue('species'))
product_identifiers = set(
extract_annotation_identifiers(product_species.getAnnotationString()))
return product_identifiers
def submodels(self, model: libsbml.Model) -> List[Dict[str, Any]]:
"""Information dictionaries for comp:Submodels.
:return: list of info dictionaries for comp:Submodels
"""
submodels: List[Dict[str, Any]] = []
model_comp = model.getPlugin("comp")
if model_comp:
submodel: libsbml.Submodel
for submodel in model_comp.getListOfSubmodels():
d = self.sbase_dict(submodel)
d["modelRef"] = (
submodel.getModelRef()
if submodel.isSetModelRef() else None #
)
deletions = []
for deletion in submodel.getListOfDeletions():
deletions.append(self._sbaseref(deletion))
d["deletions"] = deletions
d["timeConversion"] = (submodel.getTimeConversionFactor()
if submodel.isSetTimeConversionFactor()
else None)
d["extentConversion"] = (
submodel.getExtentConversionFactor()
if submodel.isSetExtentConversionFactor() else None)
submodels.append(d)
return submodels
def create_assigment_rule(sbml_model: libsbml.Model,
assignee_id: str,
formula: str,
rule_id: str = None,
rule_name: str = None):
"""Create SBML AssignmentRule
Arguments:
sbml_model: Model to add output to
assignee_id: Target of assignment
formula: Formula string for model output
rule_id: SBML id for created rule
rule_name: SBML name for created rule
"""
if rule_id is None:
rule_id = assignee_id
if rule_name is None:
rule_name = rule_id
rule = sbml_model.createAssignmentRule()
rule.setId(rule_id)
rule.setName(rule_name)
rule.setVariable(assignee_id)
rule.setFormula(formula)
return rule
def create_sbml(self, model: libsbml.Model):
obj = model.createFunctionDefinition(
) # type: libsbml.FunctionDefinition
self.set_fields(obj, model)
self.create_port(model)
return obj
def create_assigment_rule(sbml_model: libsbml.Model,
assignee_id: str,
formula: str,
rule_id: str = None,
rule_name: str = None) -> libsbml.AssignmentRule:
"""Create SBML AssignmentRule
Arguments:
sbml_model: Model to add output to
assignee_id: Target of assignment
formula: Formula string for model output
rule_id: SBML id for created rule
rule_name: SBML name for created rule
Returns:
The created ``AssignmentRule``
"""
warn("This function will be removed in future releases.",
DeprecationWarning)
if rule_id is None:
rule_id = assignee_id
if rule_name is None:
rule_name = rule_id
rule = sbml_model.createAssignmentRule()
rule.setId(rule_id)
rule.setName(rule_name)
rule.setVariable(assignee_id)
rule.setFormula(formula)
return rule
def rules(self, model: libsbml.Model) -> Dict:
"""Information for Rules.
:return: list of info dictionaries for Rules
"""
rules: Dict[str, List] = {
"assignmentRules": [],
"rateRules": [],
"algebraicRules": [],
}
rule: libsbml.Rule
for rule in model.getListOfRules():
d = self.sbase_dict(rule)
d["variable"] = self._rule_variable_to_string(rule)
d["math"] = astnode_to_latex(
rule.getMath()) if rule.isSetMath() else None
d["derivedUnits"] = udef_to_string(rule.getDerivedUnitDefinition())
type = d["sbmlType"]
key = f"{type[0].lower()}{type[1:]}s"
rules[key].append(d)
return rules
def compartments(self, model: libsbml.Model,
assignments: Dict[str, Dict[str, str]]) -> List[Dict]:
"""Information for Compartments.
:return: list of info dictionaries for Compartments
"""
compartments = []
c: libsbml.Compartment
for c in model.getListOfCompartments():
d = self.sbase_dict(c)
for key in ["spatialDimensions", "size", "constant"]:
d[key] = _get_sbase_attribute(c, key)
if d["size"] is not None and np.isnan(d["size"]):
# NaN not JSON serializable
d["size"] = "NaN"
d["units_sid"] = c.getUnits() if c.isSetUnits() else None
d["units"] = udef_to_string(d["units_sid"], model)
d["derivedUnits"] = udef_to_string(c.getDerivedUnitDefinition())
key = c.pk.split(":")[-1]
if key in self.maps["assignments"]:
d["assignment"] = self.maps["assignments"][key]
if key in self.maps["ports"]:
d["port"] = self.maps["ports"][key]
compartments.append(d)
return compartments
def create_sbml(self,
model: libsbml.Model) -> libsbml.ExternalModelDefinition:
"""Create ExternalModelDefinition."""
doc = model.getSBMLDocument()
cdoc = doc.getPlugin("comp")
extdef = cdoc.createExternalModelDefinition()
self._set_fields(extdef, model)
return extdef
def create_sbml(self, model: libsbml.Model) -> libsbml.ReplacedElement:
"""Create SBML ReplacedElement."""
# resolve port element
e = model.getElementBySId(self.elementRef)
if not e:
# fallback to units (only working if no name shadowing)
e = model.getUnitDefinition(self.elementRef)
if not e:
raise ValueError(
f"Neither SBML element nor UnitDefinition found for elementRef: "
f"'{self.elementRef}' in '{self}'")
eplugin = e.getPlugin("comp")
obj = eplugin.createReplacedElement()
self._set_fields(obj, model)
return obj
def set_model_history(model: libsbml.Model, creators) -> None:
"""Sets the model history from given creators.
:param model: SBML model
:param creators: list of creators
:return None
"""
if not model.isSetMetaId():
model.setMetaId(create_metaid(sbase=model))
if (creators is None) or (len(creators) == 0):
# at least on
return
else:
# create and set model history
h = _create_history(creators)
check(model.setModelHistory(h), "set model history")
def create_sbml(self, model: libsbml.Model):
layout_model = model.getPlugin(
"layout") # type: libsbml.LayoutModelPlugin
if not layout_model:
doc = model.getSBMLDocument() # type: libsbml.SBMLDocument
doc.enablePackage(
"http://www.sbml.org/sbml/level3/version1/layout/version{}".
format(LAYOUT_VERSION), "layout", True)
doc.setPackageRequired("layout", False)
layout_model = model.getPlugin(
"layout") # type: libsbml.LayoutModelPlugin
layout = layout_model.createLayout() # type: libsbml.Layout
self.set_fields(layout)
return layout
def create_sbml(self, model: libsbml.Model) -> libsbml.Layout:
"""Create SBML in model."""
layout_model: libsbml.LayoutModelPlugin = model.getPlugin("layout")
if not layout_model:
doc: libsbml.SBML_RULE = model.getSBMLDocument()
doc.enablePackage(
f"http://www.sbml.org/sbml/level3/version1/layout/version{LAYOUT_VERSION}",
"layout",
True,
)
doc.setPackageRequired("layout", False)
layout_model = model.getPlugin("layout")
layout: libsbml.Layout = layout_model.createLayout()
self._set_fields(layout, model)
return layout
def _create_parameter(pid: str, model: libsbml.Model) -> libsbml.Parameter:
p: libsbml.Parameter = model.createParameter()
p.setId(pid)
p.setValue(1.0)
p.setConstant(False)
unit = libsbml.UnitKind_toString(libsbml.UNIT_KIND_MOLE)
p.setUnits(unit)
return p
def _create_parameter(pid, model: libsbml.Model):
# parameter
p = model.createParameter() # type: libsbml.Parameter
p.setId(pid)
p.setValue(1.0)
p.setConstant(False)
unit = libsbml.UnitKind_toString(libsbml.UNIT_KIND_MOLE)
p.setUnits(unit)
return p
def globalize_parameters(sbml_model: libsbml.Model,
prepend_reaction_id: bool = False) -> None:
"""Turn all local parameters into global parameters with the same
properties
Local parameters are currently ignored by other PEtab functions. Use this
function to convert them to global parameters. There may exist local
parameters with identical IDs within different kinetic laws. This is not
checked here. If in doubt that local parameter IDs are unique, enable
`prepend_reaction_id` to create global parameters named
${reaction_id}_${local_parameter_id}.
Arguments:
sbml_model:
The SBML model to operate on
prepend_reaction_id:
Prepend reaction id of local parameter when
creating global parameters
"""
warn("This function will be removed in future releases.",
DeprecationWarning)
for reaction in sbml_model.getListOfReactions():
law = reaction.getKineticLaw()
# copy first so we can delete in the following loop
local_parameters = list(
local_parameter for local_parameter in law.getListOfParameters())
for lp in local_parameters:
if prepend_reaction_id:
parameter_id = f'{reaction.getId()}_{lp.getId()}'
else:
parameter_id = lp.getId()
# Create global
p = sbml_model.createParameter()
p.setId(parameter_id)
p.setName(lp.getName())
p.setConstant(lp.getConstant())
p.setValue(lp.getValue())
p.setUnits(lp.getUnits())
# removeParameter, not removeLocalParameter!
law.removeParameter(lp.getId())
def events(self, model: libsbml.Model) -> List[Dict[str, Any]]:
"""Information dictionaries for Events.
:return: list of info dictionaries for Events
"""
events = []
event: libsbml.Event
for event in model.getListOfEvents():
d = self.sbase_dict(event)
d["useValuesFromTriggerTime"] = (
event.getUseValuesFromTriggerTime()
if event.isSetUseValuesFromTriggerTime() else None)
trigger: libsbml.Trigger = (event.getTrigger()
if event.isSetTrigger() else None)
if trigger:
d["trigger"] = {
"math":
astnode_to_latex(trigger.getMath())
if trigger.isSetMath() else None,
"initialValue":
trigger.initial_value,
"persistent":
trigger.persistent,
}
else:
d["trigger"] = None
priority: libsbml.Priority = (event.getPriority()
if event.isSetPriority() else None)
if priority:
d["priority"] = (astnode_to_latex(priority.getMath())
if priority.isSetMath() else None)
delay: libsbml.Delay = event.getDelay() if event.isSetDelay(
) else None
if delay:
d["delay"] = (astnode_to_latex(delay.getMath())
if delay.isSetMath() else None)
assignments = []
eva: libsbml.EventAssignment
for eva in event.getListOfEventAssignments():
assignments.append({
"variable":
eva.getVariable() if eva.isSetVariable() else None,
"math":
astnode_to_latex(eva.getMath())
if eva.isSetMath() else None,
})
d["listOfEventAssignments"] = assignments
events.append(d)
return events
def create_sbml(self, model: libsbml.Model):
""" Create libsbml InitialAssignment.
Creates a required parameter if not existing.
:param model:
:return:
"""
constraint = model.createConstraint() # type: libsbml.Constraint
self.set_fields(constraint, model)
return constraint
def create_sbml(self, model: libsbml.Model):
model_fbc = model.getPlugin("fbc") # type: libsbml.FbcModelPlugin
obj = model_fbc.createObjective() # type: libsbml.Objective
obj.setId(self.sid)
obj.setType(self.objectiveType)
if self.active:
model_fbc.setActiveObjectiveId(self.sid)
for rid, coefficient in self.fluxObjectives.items():
# FIXME: check for rid
fluxObjective = obj.createFluxObjective()
fluxObjective.setReaction(rid)
fluxObjective.setCoefficient(coefficient)
return obj
