def create_initial_assignment(sid: str, value: str) -> None:
"""Create initial assignments helper."""
# check if valid identifier
if "(" in sid:
warnings.warn(
f"sid is not valid: {sid}. Initial assignment is not generated"
)
return
try:
f_value = float(value)
parameters.append(
fac.Parameter(
sid=sid,
value=f_value,
name=f"{sid} = {value}",
constant=False,
))
except ValueError:
"""
Initial data are optional, XPP sets them to zero by default (many
xpp model don't write the p(0)=0.
"""
parameters.append(
fac.Parameter(sid=sid, value=0.0, name=sid, constant=False))
initial_assignments.append(
fac.InitialAssignment(sid=sid,
value=value,
name=f"{sid} = {value}"))
def add_default_flux_bounds(doc, lower=0.0, upper=100.0, unit='mole_per_s'):
""" Adds default flux bounds to SBMLDocument.
:param doc:
:type doc:
:param lower:
:type lower:
:param upper:
:type upper:
"""
# FIXME: overwrites lower/upper parameter (check if existing)
# TODO: the units are very specific (more generic)
warnings.warn('Adding default flux bounds', UserWarning)
model = doc.getModel()
parameters = [
factory.Parameter(sid='upper', value=upper, unit=unit),
factory.Parameter(sid='lower', value=lower, unit=unit),
]
factory.create_objects(model, parameters)
for r in model.reactions:
rfbc = r.getPlugin("fbc")
if not rfbc.isSetLowerFluxBound():
rfbc.setLowerFluxBound('lower')
if not rfbc.isSetUpperFluxBound():
rfbc.setUpperFluxBound('upper')
def create_initial_assignment(sid, value):
""" Helper for creating initial assignments """
# check if valid identifier
if "(" in sid:
warnings.warn(
"sid is not valid: {}. Initial assignment is not generated".
format(sid))
return
try:
f_value = float(value)
parameters.append(
fac.Parameter(
sid=sid,
value=f_value,
name="{} = {}".format(sid, value),
constant=False,
))
except ValueError:
"""
Initial data are optional, XPP sets them to zero by default (many xpp model don't write the p(0)=0.
"""
parameters.append(
fac.Parameter(sid=sid, value=0.0, name=sid, constant=False))
initial_assignments.append(
fac.InitialAssignment(sid=sid,
value=value,
name="{} = {}".format(sid, value)))
def bounds_model(sbml_file, directory, doc_fba, annotations=None):
""""
Bounds model.
"""
bounds_notes = notes.format("""
<h2>BOUNDS submodel</h2>
<p>Submodel for dynamically calculating the flux bounds.
The dynamically changing flux bounds are the input to the
FBA model.</p>
""")
doc = builder.template_doc_bounds(settings.MODEL_ID)
model = doc.getModel()
utils.set_model_info(model,
notes=bounds_notes,
creators=creators,
units=units, main_units=main_units)
builder.create_dfba_dt(model, step_size=DT_SIM, time_unit=UNIT_TIME, create_port=True)
# compartment
compartment_id = 'extern'
builder.create_dfba_compartment(model, compartment_id=compartment_id, unit_volume=UNIT_VOLUME,
create_port=True)
# species
model_fba = doc_fba.getModel()
builder.create_dfba_species(model, model_fba, compartment_id=compartment_id, unit_amount=UNIT_AMOUNT,
hasOnlySubstanceUnits=True, create_port=True)
# exchange bounds
builder.create_exchange_bounds(model, model_fba=model_fba, unit_flux=UNIT_FLUX, create_ports=True)
objects = [
# exchange bounds
# FIXME: readout the FBA network bounds
mc.Parameter(sid="lb_default", value=builder.LOWER_BOUND_DEFAULT, unit=UNIT_FLUX, constant=True),
# kinetic bound parameter & calculation
mc.Parameter(sid='ub_R1', value=1.0, unit=UNIT_FLUX, constant=False, sboTerm="SBO:0000625"),
mc.Parameter(sid='k1', value=-0.2, unit="per_s", name="k1", constant=False),
mc.RateRule(sid="ub_R1", value="k1*ub_R1"),
# bound assignment rules
mc.AssignmentRule(sid="lb_EX_A", value='max(lb_default, -A/dt)'),
mc.AssignmentRule(sid="lb_EX_C", value='max(lb_default, -C/dt)'),
]
mc.create_objects(model, objects)
# ports
comp.create_ports(model, portType=comp.PORT_TYPE_PORT,
idRefs=["ub_R1"])
if annotations:
annotator.annotate_sbml_doc(doc, annotations)
sbmlio.write_sbml(doc, filepath=os.path.join(directory, sbml_file), validate=True)
def bounds_model(sbml_file, directory, doc_fba=None):
""""
Submodel for dynamically calculating the flux bounds.
The dynamically changing flux bounds are the input to the
FBA model.
"""
doc = builder.template_doc_bounds(settings.MODEL_ID)
model = doc.getModel()
bounds_notes = notes.format("""
<h2>BOUNDS submodel</h2>
<p>Submodel for dynamically calculating the flux bounds.
The dynamically changing flux bounds are the input to the
FBA model.</p>
""")
utils.set_model_info(model, notes=bounds_notes, creators=creators, units=units, main_units=main_units)
# dt
compartment_id = "blood"
builder.create_dfba_dt(model, time_unit=UNIT_TIME, create_port=True)
# compartment
builder.create_dfba_compartment(model, compartment_id=compartment_id, unit_volume=UNIT_VOLUME, create_port=True)
# dynamic species
model_fba = doc_fba.getModel()
builder.create_dfba_species(model, model_fba, compartment_id=compartment_id, unit_amount=UNIT_AMOUNT,
create_port=True)
# bounds
builder.create_exchange_bounds(model, model_fba=model_fba, unit_flux=UNIT_FLUX, create_ports=True)
# bounds
fba_prefix = "fba"
model_fba = doc_fba.getModel()
objects = []
ex_rids = utils.find_exchange_reactions(model_fba)
for ex_rid, sid in ex_rids.items():
r = model_fba.getReaction(ex_rid)
# lower & upper bound parameters
r_fbc = r.getPlugin(builder.SBML_FBC_NAME)
lb_id = r_fbc.getLowerFluxBound()
fba_lb_id = fba_prefix + lb_id
lb_value = model_fba.getParameter(lb_id).getValue()
objects.extend([
# default bounds from fba
mc.Parameter(sid=fba_lb_id, value=lb_value, unit=UNIT_FLUX, constant=False),
# uptake bounds (lower bound)
mc.AssignmentRule(sid=lb_id, value="max({}, -{}*{}/dt)".format(fba_lb_id, compartment_id, sid)),
])
mc.create_objects(model, objects)
sbmlio.write_sbml(doc, filepath=pjoin(directory, sbml_file), validate=True)
def create_port_doc():
sbmlns = libsbml.SBMLNamespaces(3, 1, "comp", 1)
doc = libsbml.SBMLDocument(sbmlns)
doc.setPackageRequired("comp", True)
model = doc.createModel()
model.setId("toy_update")
model.setName("toy (UPDATE submodel)")
model.setSBOTerm(SBO_CONTINOUS_FRAMEWORK)
objects = [
fac.Compartment(
sid="extern",
value=1.0,
unit="m3",
constant=True,
name="external compartment",
),
fac.Species(
sid="A",
name="A",
initialConcentration=10.0,
hasOnlySubstanceUnits=True,
compartment="extern",
),
fac.Species(
sid="C",
name="C",
initialConcentration=0,
hasOnlySubstanceUnits=True,
compartment="extern",
),
fac.Parameter(sid="EX_A",
value=1.0,
constant=False,
sboTerm="SBO:0000613"),
fac.Parameter(sid="EX_C",
value=1.0,
constant=False,
sboTerm="SBO:0000613"),
]
fac.create_objects(model, obj_iter=objects)
return doc
def bounds_model(sbml_file, directory, doc_fba=None):
""""
Submodel for dynamically calculating the flux bounds.
The dynamically changing flux bounds are the input to the
FBA model.
The units of the exchange fluxes must fit to the transported species.
"""
doc = builder.template_doc_bounds("ecoli")
model = doc.getModel()
bounds_notes = notes.format("""
<h2>BOUNDS submodel</h2>
<p>Submodel for dynamically calculating the flux bounds.
The dynamically changing flux bounds are the input to the
FBA model.</p>
""")
utils.set_model_info(model, notes=bounds_notes, creators=creators, units=units, main_units=main_units)
# dt
compartment_id = "bioreactor"
builder.create_dfba_dt(model, time_unit=UNIT_TIME, create_port=True)
# compartment
builder.create_dfba_compartment(model, compartment_id=compartment_id, unit_volume=UNIT_VOLUME, create_port=True)
# dynamic species
model_fba = doc_fba.getModel()
builder.create_dfba_species(model, model_fba, compartment_id=compartment_id, unit_amount=UNIT_AMOUNT, create_port=True,
exclude_sids=['X'])
# FIXME: define biomass separately, also port needed for biomass
mc.create_objects(model, [
mc.Parameter(sid='cf_X', value=1.0, unit="g_per_mmol", name="biomass conversion factor", constant=True),
mc.Species(sid='X', initialAmount=0.001, compartment=compartment_id, name='biomass', substanceUnit='g', hasOnlySubstanceUnits=True,
conversionFactor='cf_X')
])
# exchange & dynamic bounds
if not biomass_weighting:
builder.create_exchange_bounds(model, model_fba=model_fba, unit_flux=UNIT_FLUX, create_ports=True)
builder.create_dynamic_bounds(model, model_fba, unit_flux=UNIT_FLUX)
else:
builder.create_exchange_bounds(model, model_fba=model_fba, unit_flux=UNIT_FLUX_PER_G, create_ports=True)
builder.create_dynamic_bounds(model, model_fba, unit_flux=UNIT_FLUX_PER_G)
sbmlio.write_sbml(doc, filepath=pjoin(directory, sbml_file), validate=True)
def update_model(sbml_file, directory, doc_fba=None):
"""
Submodel for dynamically updating the metabolite count/concentration.
This updates the ode model based on the FBA fluxes.
"""
doc = builder.template_doc_update("ecoli")
model = doc.getModel()
update_notes = notes.format("""
<h2>UPDATE submodel</h2>
<p>Submodel for dynamically updating the metabolite count.
This updates the ode model based on the FBA fluxes.</p>
""")
utils.set_model_info(model, notes=update_notes, creators=creators, units=units, main_units=main_units)
# compartment
compartment_id = "bioreactor"
builder.create_dfba_compartment(model, compartment_id=compartment_id, unit_volume=UNIT_VOLUME, create_port=True)
# dynamic species
model_fba = doc_fba.getModel()
# creates all the exchange reactions, biomass must be handeled separately
builder.create_dfba_species(model, model_fba, compartment_id=compartment_id, unit_amount=UNIT_AMOUNT, create_port=True)
# FIXME: biomass via function
mc.create_objects(model, [
mc.Parameter(sid='cf_biomass', value=1.0, unit="g_per_mmol", name="biomass conversion factor", constant=True),
mc.Species(sid='X', initialAmount=0.001, compartment='c', name='biomass', substanceUnit='g', hasOnlySubstanceUnits=True,
conversionFactor='cf_biomass')
])
# update reactions
# FIXME: weight with X (biomass)
builder.create_update_reactions(model, model_fba=model_fba, formula="-{}", unit_flux=UNIT_FLUX,
modifiers=[])
# write SBML file
sbmlio.write_sbml(doc, filepath=pjoin(directory, sbml_file), validate=True)
def top_model(sbml_file, directory, emds, doc_fba, annotations=None):
""" Create top comp model.
Creates full comp model by combining fba, update and bounds
model with additional kinetics in the top model.
"""
top_notes = notes.format("""
<h2>TOP model</h2>
<p>Main comp DFBA model by combining fba, update and bounds
model with additional kinetics in the top model.</p>
""")
working_dir = os.getcwd()
os.chdir(directory)
doc = builder.template_doc_top(settings.MODEL_ID, emds)
model = doc.getModel()
utils.set_model_info(model,
notes=top_notes,
creators=creators,
units=units,
main_units=main_units)
# dt
builder.create_dfba_dt(model,
step_size=DT_SIM,
time_unit=UNIT_TIME,
create_port=False)
# compartment
compartment_id = "cell"
builder.create_dfba_compartment(model,
compartment_id=compartment_id,
unit_volume=UNIT_VOLUME,
create_port=False)
# dynamic species
model_fba = doc_fba.getModel()
builder.create_dfba_species(model,
model_fba,
compartment_id=compartment_id,
hasOnlySubstanceUnits=False,
unit_amount=UNIT_AMOUNT,
create_port=False)
# dummy species
builder.create_dummy_species(model,
compartment_id=compartment_id,
hasOnlySubstanceUnits=False,
unit_amount=UNIT_AMOUNT)
# exchange flux bounds
builder.create_exchange_bounds(model,
model_fba=model_fba,
unit_flux=UNIT_FLUX,
create_ports=False)
# dummy reactions & flux assignments
builder.create_dummy_reactions(model,
model_fba=model_fba,
unit_flux=UNIT_FLUX)
# replacedBy (fba reactions)
builder.create_top_replacedBy(model, model_fba=model_fba)
# replaced
builder.create_top_replacements(model,
model_fba,
compartment_id=compartment_id)
objects = [
# kinetic parameters
mc.Parameter(sid="Vmax_RATP", value=1, unit=UNIT_FLUX, constant=True),
mc.Parameter(sid='k_RATP',
value=0.1,
unit=UNIT_CONCENTRATION,
constant=True),
# balancing rules
mc.AssignmentRule(sid="atp_tot",
value="atp + adp",
unit=UNIT_CONCENTRATION),
mc.AssignmentRule(sid="c3_tot",
value="2 dimensionless * glc + pyr",
unit="mM")
]
mc.create_objects(model, objects)
ratp = mc.create_reaction(model,
rid="RATP",
name="atp -> adp",
fast=False,
reversible=False,
reactants={"atp": 1},
products={"adp": 1},
compartment=compartment_id,
formula='Vmax_RATP * atp/(k_RATP + atp)')
# initial concentrations for fba exchange species
initial_c = {'atp': 2.0, 'adp': 1.0, 'glc': 5.0, 'pyr': 0.0}
for sid, value in initial_c.items():
species = model.getSpecies(sid)
species.setInitialConcentration(value)
# write SBML file
if annotations:
annotator.annotate_sbml_doc(doc, annotations)
sbmlio.write_sbml(doc,
filepath=os.path.join(directory, sbml_file),
validate=True)
# change back the working dir
os.chdir(working_dir)
def fba_model(sbml_file, directory, annotations=None):
""" FBA model
:param sbml_file: output file name
:param directory: output directory
:return: SBMLDocument
"""
fba_notes = notes.format("""
<h2>FBA submodel</h2>
<p>DFBA fba submodel. Unbalanced metabolites are encoded via exchange fluxes.</p>
""")
doc = builder.template_doc_fba(settings.MODEL_ID)
model = doc.getModel()
utils.set_model_info(model,
notes=fba_notes,
creators=creators,
units=units,
main_units=main_units)
objects = [
# compartments
mc.Compartment(sid='cell',
value=1.0,
unit=UNIT_VOLUME,
constant=True,
name='cell',
spatialDimensions=3),
# exchange species
mc.Species(sid='atp',
name="ATP",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
mc.Species(sid='adp',
name="ADP",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
mc.Species(sid='glc',
name="Glucose",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
mc.Species(sid='pyr',
name='Pyruvate',
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
# internal species
mc.Species(sid='fru16bp',
name='Fructose 1,6-bisphospate',
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
mc.Species(sid='pg2',
name='2-Phosphoglycerate',
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=False,
compartment="cell"),
# bounds
mc.Parameter(sid="ub_R3",
value=1.0,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
mc.Parameter(sid="zero",
value=0.0,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
mc.Parameter(sid="ub_default",
value=builder.UPPER_BOUND_DEFAULT,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
]
mc.create_objects(model, objects)
# reactions
r1 = mc.create_reaction(model,
rid="R1",
name="glu + 2 atp -> fru16bp + 2 adp",
fast=False,
reversible=False,
reactants={
"glc": 1,
"atp": 2
},
products={
"fru16bp": 1,
'adp': 2
},
compartment='cell')
r2 = mc.create_reaction(model,
rid="R2",
name="fru16bp -> 2 pg2",
fast=False,
reversible=False,
reactants={"fru16bp": 1},
products={"pg2": 2},
compartment='cell')
r3 = mc.create_reaction(model,
rid="R3",
name="pg2 + adp -> pyr + atp",
fast=False,
reversible=False,
reactants={
"pg2": 1,
"adp": 2
},
products={
"pyr": 1,
"atp": 2
},
compartment='cell')
# flux bounds
fbc.set_flux_bounds(r1, lb="zero", ub="ub_default")
fbc.set_flux_bounds(r2, lb="zero", ub="ub_default")
fbc.set_flux_bounds(r3, lb="zero", ub="ub_R3")
# fbc.set_flux_bounds(ratp, lb="zero", ub="ub_RATP")
# exchange reactions
for sid in ['atp', 'adp', 'glc', 'pyr']:
builder.create_exchange_reaction(model,
species_id=sid,
flux_unit=UNIT_FLUX)
# objective function
model_fbc = model.getPlugin("fbc")
fbc.create_objective(model_fbc,
oid="RATP_maximize",
otype="maximize",
fluxObjectives={"R3": 1.0},
active=True)
if annotations:
annotator.annotate_sbml_doc(doc, annotations)
# write SBML
sbmlio.write_sbml(doc,
filepath=os.path.join(directory, sbml_file),
validate=True)
return doc
mc.Species('lacRBC',
compartment="Vrbc",
initialConcentration=0,
unit='mmole',
name="lactate",
hasOnlySubstanceUnits=True,
constant=False),
]
##############################################################
# Parameters
##############################################################
parameters = [
mc.Parameter('alpha',
0.9,
'-',
constant=True,
name='volume fraction erythrocytes'),
]
##############################################################
# Assignments
##############################################################
assignments = []
##############################################################
# AssignmentRules
##############################################################
rules = [
# volumes
mc.AssignmentRule('Vrbc', 'Vpl * alpha', UNIT_KIND_LITRE),
name="{} ({})".format(s_dict['name'], c_name),
hasOnlySubstanceUnits=True))
species.append(
mc.Species('Aurine_{}'.format(s_id),
0,
compartment="Vurine",
unit='mmole',
name="{} (urine)".format(s_dict['name']),
hasOnlySubstanceUnits=True), )
##############################################################
# Parameters
##############################################################
parameters = [
# whole body data
mc.Parameter('BW', 75, 'kg', constant=True, name='body weight [kg]'),
mc.Parameter('HEIGHT', 170, 'cm', constant=True, name='height [cm]'),
mc.Parameter('HR', 70, 'per_min', constant=True,
name='heart rate [1/min]'),
mc.Parameter('HRrest',
70,
'per_min',
constant=True,
name='heart rate [1/min]'),
mc.Parameter('BSA',
0,
'm2',
constant=False,
name='body surface area [m^2]'),
mc.Parameter('COBW',
1.548,
def xpp2sbml(
xpp_file: Path,
sbml_file: Path,
force_lower: bool = False,
validate: bool = True,
debug: bool = False,
):
"""Reads given xpp_file and converts to SBML file.
:param xpp_file: xpp input ode file
:param sbml_file: sbml output file
:param force_lower: force lower case for all lines
:param validate: perform validation on the generated SBML file
:return:
"""
print("-" * 80)
print("xpp2sbml: ", xpp_file, "->", sbml_file)
print("-" * 80)
doc = libsbml.SBMLDocument(3, 1)
model = doc.createModel()
parameters = []
initial_assignments = []
rate_rules = []
assignment_rules = []
functions = [
# definition of min and max
fac.Function("max",
"lambda(x,y, piecewise(x,gt(x,y),y) )",
name="minimum"),
fac.Function("min",
"lambda(x,y, piecewise(x,lt(x,y),y) )",
name="maximum"),
# heav (heavyside)
fac.Function(
"heav",
"lambda(x, piecewise(0,lt(x,0), 0.5, eq(x, 0), 1,gt(x,0), 0))",
name="heavyside",
),
# mod (modulo)
fac.Function("mod", "lambda(x,y, x % y)", name="modulo"),
]
function_definitions = []
events = []
def replace_fdef():
""" Replace all arguments within the formula definitions."""
changes = False
for k, fdata in enumerate(function_definitions):
for i in range(len(function_definitions)):
if i != k:
# replace i with k
formula = function_definitions[i]["formula"]
new_formula = xpp_helpers.replace_formula(
formula,
fid=function_definitions[k]["fid"],
old_args=function_definitions[k]["old_args"],
new_args=function_definitions[k]["new_args"],
)
if new_formula != formula:
function_definitions[i]["formula"] = new_formula
function_definitions[i]["new_args"] = list(
sorted(
set(function_definitions[i]["new_args"] +
function_definitions[k]["new_args"])))
changes = True
return changes
def create_initial_assignment(sid, value):
""" Helper for creating initial assignments """
# check if valid identifier
if "(" in sid:
warnings.warn(
"sid is not valid: {}. Initial assignment is not generated".
format(sid))
return
try:
f_value = float(value)
parameters.append(
fac.Parameter(
sid=sid,
value=f_value,
name="{} = {}".format(sid, value),
constant=False,
))
except ValueError:
"""
Initial data are optional, XPP sets them to zero by default (many xpp model don't write the p(0)=0.
"""
parameters.append(
fac.Parameter(sid=sid, value=0.0, name=sid, constant=False))
initial_assignments.append(
fac.InitialAssignment(sid=sid,
value=value,
name="{} = {}".format(sid, value)))
###########################################################################
# First iteration to parse relevant lines and get the replacement patterns
###########################################################################
parsed_lines = []
# with open(xpp_file, encoding="utf-8") as f:
with open(xpp_file) as f:
lines = f.readlines()
# add info to sbml
text = escape_string("".join(lines))
fac.set_notes(model, NOTES.format(text))
old_line = None
for line in lines:
if force_lower:
line = line.lower()
# clean up the ends
line = line.rstrip("\n").strip()
# handle douple continuation characters in some models
line = line.replace("\\\\", "\\")
# handle semicolons
line = line.rstrip(";")
# join continuation
if old_line:
line = old_line + line
old_line = None
# empty line
if len(line) == 0:
continue
# comment line
if line[0] in XPP_COMMENT_CHARS:
continue
# xpp setting
if line.startswith(XPP_SETTING_CHAR):
continue
# end word
if line == XPP_END_WORD:
continue
# line continuation
if line.endswith(XPP_CONTINUATION_CHAR):
old_line = line.rstrip(XPP_CONTINUATION_CHAR)
continue
# handle the power function
line = line.replace("**", "^")
# handle if(...)then(...)else()
pattern_ite = re.compile(
r"if\s*\((.*)\)\s*then\s*\((.*)\)\s*else\s*\((.*)\)")
pattern_ite_sub = re.compile(
r"if\s*\(.*\)\s*then\s*\(.*\)\s*else\s*\(.*\)")
groups = re.findall(pattern_ite, line)
for group in groups:
condition = group[0]
assignment = group[1]
otherwise = group[2]
f_piecewise = "piecewise({}, {}, {})".format(
assignment, condition, otherwise)
line = re.sub(pattern_ite_sub, f_piecewise, line)
################################
# Function definitions
################################
""" Functions are defined in xpp via fid(arguments) = formula
f(x,y) = x^2/(x^2+y^2)
They can have up to 9 arguments.
The difference to SBML functions is that xpp functions have access to the global parameter values
"""
f_pattern = re.compile(r"(.*)\s*\((.*)\)\s*=\s*(.*)")
groups = re.findall(f_pattern, line)
if groups:
# function definitions found
fid, args, formula = groups[0]
# handles the initial assignments which look like function definitions
if args == "0":
parsed_lines.append(line)
continue
# necessary to find the additional arguments from the ast_node
ast = libsbml.parseL3Formula(formula)
names = set(xpp_helpers.find_names_in_ast(ast))
old_args = [t.strip() for t in args.split(",")]
new_args = [a for a in names if a not in old_args]
# handle special functions
if fid == "power":
warnings.warn(
"power function cannot be added to model, rename function."
)
else:
# store functions with additional arguments
function_definitions.append({
"fid": fid,
"old_args": old_args,
"new_args": new_args,
"formula": formula,
})
# don't append line, function definition has been handeled
continue
parsed_lines.append(line)
if debug:
print("\n\nFUNCTION_DEFINITIONS")
pprint(function_definitions)
# functions can use functions so this also must be replaced
changes = True
while changes:
changes = replace_fdef()
# clean the new arguments
for fdata in function_definitions:
fdata["new_args"] = list(sorted(set(fdata["new_args"])))
if debug:
print("\nREPLACED FUNCTION_DEFINITIONS")
pprint(function_definitions)
# Create function definitions
for k, fdata in enumerate(function_definitions):
fid = fdata["fid"]
formula = fdata["formula"]
arguments = ",".join(fdata["old_args"] + fdata["new_args"])
functions.append(
fac.Function(fid, "lambda({}, {})".format(arguments, formula)), )
###########################################################################
# Second iteration
###########################################################################
if debug:
print("\nPARSED LINES")
pprint(parsed_lines)
print("\n\n")
for line in parsed_lines:
# replace function definitions in lines
new_line = line
for fdata in function_definitions:
new_line = xpp_helpers.replace_formula(new_line, fdata["fid"],
fdata["old_args"],
fdata["new_args"])
if new_line != line:
if False:
print("\nReplaced FD", fdata["fid"], ":", new_line)
print("->", new_line, "\n")
line = new_line
if debug:
# line after function replacements
print("*" * 3, line, "*" * 3)
################################
# Start parsing the given line
################################
# check for the equal sign
tokens = line.split("=")
tokens = [t.strip() for t in tokens]
#######################
# Line without '=' sign
#######################
# wiener
if len(tokens) == 1:
items = [t.strip() for t in tokens[0].split(" ") if len(t) > 0]
# keyword, value
if len(items) == 2:
xid, sid = items[0], items[1]
xpp_type = parse_keyword(xid)
# wiener
if xpp_type == XPP_WIE:
"""Wiener parameters are normally distributed numbers with zero mean
and unit standard deviation. They are useful in stochastic simulations since
they automatically scale with change in the integration time step.
Their names are listed separated by commas or spaces."""
# FIXME: this should be encoded using dist
parameters.append(fac.Parameter(sid=sid, value=0.0))
continue # line finished
else:
warnings.warn("XPP line not parsed: '{}'".format(line))
#####################
# Line with '=' sign
#####################
# parameter, aux, ode, initial assignments
elif len(tokens) >= 2:
left = tokens[0]
items = [t.strip() for t in left.split(" ") if len(t) > 0]
# keyword based information, i.e 2 items are on the left of the first '=' sign
if len(items) == 2:
xid = items[0] # xpp keyword
xpp_type = parse_keyword(xid)
expression = (" ".join(items[1:]) + "=" + "=".join(tokens[1:])
) # full expression after keyword
parts = parts_from_expression(expression)
if False:
print("xid:", xid)
print("expression:", expression)
print("parts:", parts)
# parameter & numbers
if xpp_type in [XPP_PAR, XPP_NUM]:
"""Parameter values are optional; if not they are set to zero.
Number declarations are like parameter declarations, except that they cannot be
changed within the program and do not appear in the parameter window."""
for part in parts:
sid, value = sid_value_from_part(part)
create_initial_assignment(sid, value)
# aux
elif xpp_type == XPP_AUX:
"""Auxiliary quantities are expressions that depend on all of your dynamic
variables which you want to keep track of. Energy is one such example. They are declared
like fixed quantities, but are prefaced by aux ."""
for part in parts:
sid, value = sid_value_from_part(part)
if sid == value:
# avoid circular dependencies (no information in statement)
pass
else:
assignment_rules.append(
fac.AssignmentRule(sid=sid, value=value))
# init
elif xpp_type == XPP_INIT:
for part in parts:
sid, value = sid_value_from_part(part)
create_initial_assignment(sid, value)
# table
elif xpp_type == XPP_TAB:
"""The Table declaration allows the user to specify a function of 1 variable in terms
of a lookup table which uses linear interpolation. The name of the function follows the
declaration and this is followed by (i) a filename (ii) or a function of "t"."""
warnings.warn(
"XPP_TAB not supported: XPP line not parsed: '{}'".
format(line))
else:
warnings.warn("XPP line not parsed: '{}'".format(line))
elif len(items) >= 2:
xid = items[0]
xpp_type = parse_keyword(xid)
# global
if xpp_type == XPP_GLO:
"""Global flags are expressions that signal events when they change sign, from less than
to greater than zero if sign=1 , greater than to less than if sign=-1 or either way
if sign=0. The condition should be delimited by braces {} The events are of the form
variable=expression, are delimited by braces, and separated by semicolons. When the
condition occurs all the variables in the event set are changed possibly discontinuously.
"""
# global sign {condition} {name1 = form1; ...}
pattern_global = re.compile(
r"([+,-]{0,1}\d{1})\s+\{{0,1}(.*)\{{0,1}\s+\{(.*)\}")
groups = re.findall(pattern_global, line)
if groups:
g = groups[0]
sign = int(g[0])
trigger = g[1]
# FIXME: handle sign=-1, sign=0, sign=+1
if sign == -1:
trigger = g[1] + ">= 0"
elif sign == 1:
trigger = g[1] + ">= 0"
elif sign == 0:
trigger = g[1] + ">= 0"
assignment_parts = [t.strip() for t in g[2].split(";")]
assignments = {}
for p in assignment_parts:
key, value = p.split("=")
assignments[key] = value
events.append(
fac.Event(
sid="e{}".format(len(events)),
trigger=trigger,
assignments=assignments,
))
else:
warnings.warn(
"global expression could not be parsed: {}".format(
line))
else:
warnings.warn("XPP line not parsed: '{}'".format(line))
# direct assignments
elif len(items) == 1:
right = tokens[1]
# init
if left.endswith("(0)"):
sid, value = left[0:-3], right
create_initial_assignment(sid, value)
# difference equations
elif left.endswith("(t+1)"):
warnings.warn(
"Difference Equations not supported: XPP line not parsed: '{}'"
.format(line))
# ode
elif left.endswith("'"):
sid = left[0:-1]
rate_rules.append(fac.RateRule(sid=sid, value=right))
elif left.endswith("/dt"):
sid = left[1:-3]
rate_rules.append(fac.RateRule(sid=sid, value=right))
# assignment rules
else:
assignment_rules.append(
fac.AssignmentRule(sid=left, value=right))
else:
warnings.warn("XPP line not parsed: '{}'".format(line))
# add time
assignment_rules.append(
fac.AssignmentRule(sid="t", value="time", name="model time"))
# create SBML objects
objects = (parameters + initial_assignments + functions + rate_rules +
assignment_rules + events)
fac.create_objects(model, obj_iter=objects, debug=False)
"""
Parameter values are optional; if not they are set to zero in xpp.
Many models do not encode the initial zeros.
"""
for p in doc.getModel().getListOfParameters():
if not p.isSetValue():
p.setValue(0.0)
sbml.write_sbml(
doc,
sbml_file,
validate=validate,
program_name="sbmlutils",
program_version=__version__,
units_consistency=False,
)
mc.AssignmentRule(f'C{s.sid[1:]}', f'{s.sid}/{s.compartment}',
'mM', name=f'{s.name} concentration ({s.compartment})'),
)
##############################################################
# Reactions
##############################################################
reactions = [
ReactionTemplate(
rid="GLCIM",
name="GLCIM (glc_ext <-> glc)",
equation="Aext_glc <-> Ali_glc",
compartment='Vli',
pars=[
mc.Parameter('GLCIM_Vmax', 1E3, 'mmole_per_hl',
name='Glucose utilization brain'),
mc.Parameter('GLCIM_Km', 0.1, 'mM'),
],
rules=[],
formula=(
"GLCIM_Vmax/GLCIM_Km * Vli * (Cext_glc-Cli_glc)/(1 dimensionless + Cext_glc/GLCIM_Km + Cli_glc/GLCIM_Km)",
'mmole_per_h'),
),
ReactionTemplate(
rid="LACIM",
name="LACIM (lac_ext <-> lac)",
equation="Aext_lac <-> Ali_lac",
compartment='Vli',
pars=[
def top_model(sbml_file, directory, emds, doc_fba, annotations=None):
""" Create top comp model.
Creates full comp model by combining fba, update and bounds
model with additional kinetics in the top model.
"""
top_notes = notes.format("""
<h2>TOP model</h2>
<p>Main comp DFBA model by combining fba, update and bounds
model with additional kinetics in the top model.</p>
""")
working_dir = os.getcwd()
os.chdir(directory)
doc = builder.template_doc_top(settings.MODEL_ID, emds)
model = doc.getModel()
utils.set_model_info(model,
notes=top_notes,
creators=creators,
units=units,
main_units=main_units)
# dt
builder.create_dfba_dt(model,
step_size=DT_SIM,
time_unit=UNIT_TIME,
create_port=False)
# compartment
compartment_id = "extern"
builder.create_dfba_compartment(model,
compartment_id=compartment_id,
unit_volume=UNIT_VOLUME,
create_port=False)
# dynamic species
model_fba = doc_fba.getModel()
builder.create_dfba_species(model,
model_fba,
compartment_id=compartment_id,
hasOnlySubstanceUnits=True,
unit_amount=UNIT_AMOUNT,
create_port=False)
# dummy species
builder.create_dummy_species(model,
compartment_id=compartment_id,
hasOnlySubstanceUnits=True,
unit_amount=UNIT_AMOUNT)
# exchange flux bounds
builder.create_exchange_bounds(model,
model_fba=model_fba,
unit_flux=UNIT_FLUX,
create_ports=False)
# dummy reactions & flux assignments
builder.create_dummy_reactions(model,
model_fba=model_fba,
unit_flux=UNIT_FLUX)
# replacedBy (fba reactions)
builder.create_top_replacedBy(model, model_fba=model_fba)
# replaced
builder.create_top_replacements(model,
model_fba,
compartment_id=compartment_id)
# initial concentrations for fba exchange species
initial_c = {
'A': 10.0,
'C': 0.0,
}
for sid, value in initial_c.items():
species = model.getSpecies(sid)
species.setInitialConcentration(value)
# kinetic model
mc.create_objects(
model,
[
# kinetic species
mc.Species(sid='D',
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=True,
compartment="extern"),
# kinetic
mc.Parameter(sid="k_R4",
value=0.1,
constant=True,
unit="per_s",
sboTerm="SBO:0000009"),
# bounds parameter
mc.Parameter(sid='ub_R1',
value=1.0,
unit=UNIT_FLUX,
constant=False,
sboTerm="SBO:0000625"),
])
# kinetic reaction (MMK)
mc.create_reaction(model,
rid="R4",
name="R4: C -> D",
fast=False,
reversible=False,
reactants={"C": 1},
products={"D": 1},
formula="k_R4*C",
compartment="extern")
# kinetic flux bounds
comp.replace_elements(model,
'ub_R1',
ref_type=comp.SBASE_REF_TYPE_PORT,
replaced_elements={
'bounds': ['ub_R1_port'],
'fba': ['ub_R1_port']
})
# write SBML file
if annotations:
annotator.annotate_sbml_doc(doc, annotations)
sbml.write_sbml(doc,
filepath=os.path.join(directory, sbml_file),
validate=True)
# change back the working dir
os.chdir(working_dir)
def fba_model(sbml_file, directory, annotations=None):
""" FBA model
:param sbml_file: output file name
:param directory: output directory
:return: SBMLDocument
"""
fba_notes = notes.format("""
<h2>FBA submodel</h2>
<p>DFBA fba submodel. Unbalanced metabolites are encoded via exchange fluxes.</p>
""")
doc = builder.template_doc_fba(settings.MODEL_ID)
model = doc.getModel()
utils.set_model_info(model,
notes=fba_notes,
creators=creators,
units=units,
main_units=main_units)
objects = [
# compartments
mc.Compartment(sid='extern',
value=1.0,
unit=UNIT_VOLUME,
constant=True,
name='external compartment',
spatialDimensions=3),
mc.Compartment(sid='cell',
value=1.0,
unit=UNIT_VOLUME,
constant=True,
name='cell',
spatialDimensions=3),
mc.Compartment(sid='membrane',
value=1.0,
unit=UNIT_AREA,
constant=True,
name='membrane',
spatialDimensions=2),
# exchange species
mc.Species(sid='A',
name="A",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=True,
compartment="extern"),
mc.Species(sid='C',
name="C",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=True,
compartment="extern"),
# internal species
mc.Species(sid='B1',
name="B1",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=True,
compartment="cell"),
mc.Species(sid='B2',
name="B2",
initialConcentration=0,
substanceUnit=UNIT_AMOUNT,
hasOnlySubstanceUnits=True,
compartment="cell"),
# bounds
mc.Parameter(sid="ub_R1",
value=1.0,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
mc.Parameter(sid="zero",
value=0.0,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
mc.Parameter(sid="ub_default",
value=builder.UPPER_BOUND_DEFAULT,
unit=UNIT_FLUX,
constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
]
mc.create_objects(model, objects)
# reactions
r1 = mc.create_reaction(model,
rid="R1",
name="A import (R1)",
fast=False,
reversible=True,
reactants={"A": 1},
products={"B1": 1},
compartment='membrane')
r2 = mc.create_reaction(model,
rid="R2",
name="B1 <-> B2 (R2)",
fast=False,
reversible=True,
reactants={"B1": 1},
products={"B2": 1},
compartment='cell')
r3 = mc.create_reaction(model,
rid="R3",
name="B2 export (R3)",
fast=False,
reversible=True,
reactants={"B2": 1},
products={"C": 1},
compartment='membrane')
# flux bounds
fbc.set_flux_bounds(r1, lb="zero", ub="ub_R1")
fbc.set_flux_bounds(r2, lb="zero", ub="ub_default")
fbc.set_flux_bounds(r3, lb="zero", ub="ub_default")
# exchange reactions
builder.create_exchange_reaction(model,
species_id="A",
flux_unit=UNIT_FLUX)
builder.create_exchange_reaction(model,
species_id="C",
flux_unit=UNIT_FLUX)
# objective function
model_fbc = model.getPlugin("fbc")
fbc.create_objective(model_fbc,
oid="R3_maximize",
otype="maximize",
fluxObjectives={"R3": 1.0},
active=True)
# create ports for kinetic bounds
comp.create_ports(model, portType=comp.PORT_TYPE_PORT, idRefs=["ub_R1"])
# write SBML
if annotations:
annotator.annotate_sbml_doc(doc, annotations)
sbml.write_sbml(doc,
filepath=os.path.join(directory, sbml_file),
validate=True)
return doc
# Compartments
##############################################################
compartments = []
##############################################################
# Species
##############################################################
species = []
##############################################################
# Parameters
##############################################################
parameters = [
# state variables (initial values)
mc.Parameter('Gp', 178, 'mg_per_kg', constant=False,
name='glucose plasma'),
mc.Parameter('Gt', 135, 'mg_per_kg', constant=False,
name='glucose tissue'),
mc.Parameter('Il',
4.5,
'pmol_per_kg',
constant=False,
name='insulin mass liver'),
mc.Parameter('Ip',
1.25,
'pmol_per_kg',
constant=False,
name='insulin mass plasma'),
mc.Parameter('Qsto1', 78000, '?', constant=False),
mc.Parameter('Qsto2', 0, '?', constant=False),
mc.Parameter('Qgut', 0, '?', constant=False),
def fba_model(sbml_file, directory):
""" Create FBA submodel.
"""
# Read the model
fba_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'data/ecoli_fba.xml')
doc_fba = sbml.read_sbml(fba_path)
# add comp
doc_fba.enablePackage(
"http://www.sbml.org/sbml/level3/version1/comp/version1", "comp", True)
doc_fba.setPackageRequired("comp", True)
# add notes
model = doc_fba.getModel()
fba_notes = notes.format("""DFBA FBA submodel.""")
utils.set_model_info(model,
notes=fba_notes,
creators=None,
units=units,
main_units=main_units)
# clip R_ reaction and M_ metabolite prefixes
utils.clip_prefixes_in_model(model)
# set id & framework
model.setId('ecoli_fba')
model.setName('ecoli (FBA)')
model.setSBOTerm(comp.SBO_FLUX_BALANCE_FRAMEWORK)
# add units and information
for species in model.getListOfSpecies():
species.setInitialConcentration(0.0)
species.setHasOnlySubstanceUnits(False)
species.setUnits(UNIT_AMOUNT)
for compartment in model.getListOfCompartments():
compartment.setUnits(UNIT_VOLUME)
# The ATPM (atp maintainance reactions creates many problems in the DFBA)
# mainly resulting in infeasible solutions when some metabolites run out.
# ATP -> ADP is part of the biomass, so we set the lower bound to zero
r_ATPM = model.getReaction('ATPM')
r_ATPM_fbc = r_ATPM.getPlugin(builder.SBML_FBC_NAME)
lb_id = r_ATPM_fbc.getLowerFluxBound()
model.getParameter(lb_id).setValue(0.0) # 8.39 before
# make unique upper and lower bounds for exchange reaction
if not biomass_weighting:
builder.update_exchange_reactions(model=model, flux_unit=UNIT_FLUX)
else:
builder.update_exchange_reactions(model=model,
flux_unit=UNIT_FLUX_PER_G)
# add exchange reaction for biomass (X)
# we are adding the biomass component to the biomass function and create an
# exchange reaction for it
r_biomass = model.getReaction('BIOMASS_Ecoli_core_w_GAM')
# FIXME: refactor in function
# FIXME: annotate biomass species (SBO for biomass missing)
mc.create_objects(model, [
mc.Parameter(sid='cf_X',
value=1.0,
unit="g_per_mmol",
name="biomass conversion factor",
constant=True),
mc.Species(sid='X',
initialAmount=0.001,
compartment='c',
name='biomass',
substanceUnit='g',
hasOnlySubstanceUnits=True,
conversionFactor='cf_X')
])
pr_biomass = r_biomass.createProduct()
pr_biomass.setSpecies('X')
pr_biomass.setStoichiometry(1.0)
pr_biomass.setConstant(True)
# FIXME: the flux units must fit to the species units.
if not biomass_weighting:
builder.create_exchange_reaction(model,
species_id='X',
flux_unit=UNIT_FLUX,
exchange_type=builder.EXCHANGE_EXPORT)
else:
builder.create_exchange_reaction(model,
species_id='X',
flux_unit=UNIT_FLUX_PER_G,
exchange_type=builder.EXCHANGE_EXPORT)
# write SBML file
sbml.write_sbml(doc_fba,
filepath=pjoin(directory, sbml_file),
validate=True)
# Set kinetic laws to zero for kinetic simulation
'''
for reaction in model.getListOfReactions():
ast_node = mc.ast_node_from_formula(model=model, formula='0 {}'.format(UNIT_FLUX))
law = reaction.createKineticLaw()
law.setMath(ast_node)
'''
return doc_fba
f'{s.sid}/{s.compartment}',
'mM',
name=f'{s.name} concentration ({s.compartment})'), )
##############################################################
# Reactions
##############################################################
reactions = [
ReactionTemplate(
rid="GLCIM",
name="GLCIM (glc_ext <-> glc)",
equation="Aext_glc <-> Abr_glc",
compartment='Vbr',
pars=[
mc.Parameter('GLCIM_Vmax',
1E3,
'mmole_per_hl',
name='Glucose utilization brain'),
mc.Parameter('GLCIM_Km', 0.1, 'mM'),
],
rules=[],
formula=
("GLCIM_Vmax/GLCIM_Km * Vbr * (Cext_glc-Cbr_glc)/(1 dimensionless + Cext_glc/GLCIM_Km + Cbr_glc/GLCIM_Km)",
'mmole_per_h'),
),
ReactionTemplate(
rid="LACIM",
name="LACIM (lac_ext <-> lac)",
equation="Aext_lac <-> Abr_lac",
compartment='Vbr',
pars=[
mc.Parameter('LACIM_Vmax',
"""
from sbmlutils import factory as mc
from sbmlutils.modelcreator.processes import ReactionTemplate
#############################################################################################
# REACTIONS
#############################################################################################
GLUT2 = ReactionTemplate(
rid='GLUT2',
name='GLUT2 glucose transporter',
equation='Aglc_ext <-> Aglc []',
# C6H1206 (0) <-> C6H12O6 (0)
compartment='pm',
pars=[
mc.Parameter('GLUT2_keq', 1, 'dimensionless'),
mc.Parameter('GLUT2_k_glc', 42, 'mM'),
mc.Parameter('GLUT2_Vmax', 420, 'mmole_per_min'),
],
rules=[],
formula=('f_gly * (GLUT2_Vmax/GLUT2_k_glc) * (glc_ext - glc/GLUT2_keq)/'
'(1 dimensionless + glc_ext/GLUT2_k_glc + glc/GLUT2_k_glc)',
'mmole_per_min'))
GK = ReactionTemplate(
rid='GK',
name='Glucokinase',
equation='Aglc + Aatp => Aglc6p + Aadp + Ah [Aglc1p, Afru6p]',
# C6H1206 (0) + C10H12N5O13P3 (-4) <-> C6H11O9P (-2) + C10H12N5O10P2 (-3) + H (1)
compartment='cyto',
pars=[
unit=UNIT_KIND_LITRE,
constant=False,
name='venous plasma'),
mc.Compartment('Vplas_art',
value=1,
unit=UNIT_KIND_LITRE,
constant=False,
name='arterial plasma'),
]
##############################################################
# Parameters
##############################################################
parameters = [
# whole body data
mc.Parameter('BW', 70, 'kg', constant=True, name='body weight'),
mc.Parameter('CO',
108.33,
'ml_per_s',
constant=True,
name='cardiac output [ml/s]'),
mc.Parameter('QC',
108.33 * 1000 * 60 * 60,
'litre_per_h',
constant=False,
name='cardiac output [L/hr]'),
# fractional tissue volumes
mc.Parameter('FVre',
0.9049,
'litre_per_kg',
def test_modelcreator_notebook():
"""
If this test fails the respective notebook must be updated:
:return:
"""
import libsbml
from libsbml import (UNIT_KIND_SECOND, UNIT_KIND_ITEM, UNIT_KIND_MOLE,
UNIT_KIND_KILOGRAM, UNIT_KIND_METRE, UNIT_KIND_LITRE)
from sbmlutils import comp
from sbmlutils import fbc
from sbmlutils import sbmlio
from sbmlutils import factory as fac
from sbmlutils.dfba import builder, utils
main_units = {
'time': 's',
'extent': UNIT_KIND_ITEM,
'substance': UNIT_KIND_ITEM,
'length': 'm',
'area': 'm2',
'volume': 'm3',
}
units = [
fac.Unit('s', [(UNIT_KIND_SECOND, 1.0)]),
fac.Unit('item', [(UNIT_KIND_ITEM, 1.0)]),
fac.Unit('kg', [(UNIT_KIND_KILOGRAM, 1.0)]),
fac.Unit('m', [(UNIT_KIND_METRE, 1.0)]),
fac.Unit('m2', [(UNIT_KIND_METRE, 2.0)]),
fac.Unit('m3', [(UNIT_KIND_METRE, 3.0)]),
fac.Unit('mM', [(UNIT_KIND_MOLE, 1.0, 0),
(UNIT_KIND_METRE, -3.0)]),
fac.Unit('per_s', [(UNIT_KIND_SECOND, -1.0)]),
fac.Unit('item_per_s', [(UNIT_KIND_ITEM, 1.0),
(UNIT_KIND_SECOND, -1.0)]),
fac.Unit('item_per_m3', [(UNIT_KIND_ITEM, 1.0),
(UNIT_KIND_METRE, -3.0)]),
]
UNIT_TIME = 's'
UNIT_AMOUNT = 'item'
UNIT_AREA = 'm2'
UNIT_VOLUME = 'm3'
UNIT_CONCENTRATION = 'item_per_m3'
UNIT_FLUX = 'item_per_s'
# Create SBMLDocument with fba
doc = builder.template_doc_fba(model_id="toy")
model = doc.getModel()
utils.set_units(model, units)
utils.set_main_units(model, main_units)
objects = [
# compartments
fac.Compartment(sid='extern', value=1.0, unit=UNIT_VOLUME, constant=True, name='external compartment',
spatialDimensions=3),
fac.Compartment(sid='cell', value=1.0, unit=UNIT_VOLUME, constant=True, name='cell', spatialDimensions=3),
fac.Compartment(sid='membrane', value=1.0, unit=UNIT_AREA, constant=True, name='membrane', spatialDimensions=2),
# exchange species
fac.Species(sid='A', name="A", value=0, substanceUnit=UNIT_AMOUNT, hasOnlySubstanceUnits=True,
compartment="extern"),
fac.Species(sid='C', name="C", value=0, substanceUnit=UNIT_AMOUNT, hasOnlySubstanceUnits=True,
compartment="extern"),
# internal species
fac.Species(sid='B1', name="B1", value=0, substanceUnit=UNIT_AMOUNT, hasOnlySubstanceUnits=True,
compartment="cell"),
fac.Species(sid='B2', name="B2", value=0, substanceUnit=UNIT_AMOUNT, hasOnlySubstanceUnits=True,
compartment="cell"),
# bounds
fac.Parameter(sid="ub_R1", value=1.0, unit=UNIT_FLUX, constant=True, sboTerm=builder.FLUX_BOUND_SBO),
fac.Parameter(sid="zero", value=0.0, unit=UNIT_FLUX, constant=True, sboTerm=builder.FLUX_BOUND_SBO),
fac.Parameter(sid="ub_default", value=builder.UPPER_BOUND_DEFAULT, unit=UNIT_FLUX, constant=True,
sboTerm=builder.FLUX_BOUND_SBO),
]
fac.create_objects(model, objects)
# reactions
r1 = fac.create_reaction(model, rid="R1", name="A import (R1)", fast=False, reversible=True,
reactants={"A": 1}, products={"B1": 1}, compartment='membrane')
r2 = fac.create_reaction(model, rid="R2", name="B1 <-> B2 (R2)", fast=False, reversible=True,
reactants={"B1": 1}, products={"B2": 1}, compartment='cell')
r3 = fac.create_reaction(model, rid="R3", name="B2 export (R3)", fast=False, reversible=True,
reactants={"B2": 1}, products={"C": 1}, compartment='membrane')
# flux bounds
fbc.set_flux_bounds(r1, lb="zero", ub="ub_R1")
fbc.set_flux_bounds(r2, lb="zero", ub="ub_default")
fbc.set_flux_bounds(r3, lb="zero", ub="ub_default")
# exchange reactions
builder.create_exchange_reaction(model, species_id="A", flux_unit=UNIT_FLUX)
builder.create_exchange_reaction(model, species_id="C", flux_unit=UNIT_FLUX)
# objective function
model_fbc = model.getPlugin("fbc")
fac.create_objective(model_fbc, oid="R3_maximize", otype="maximize",
fluxObjectives={"R3": 1.0}, active=True)
# write SBML file
import tempfile
sbml_file = tempfile.NamedTemporaryFile(suffix=".xml")
sbmlio.write_sbml(doc=doc, filepath=sbml_file.name)
mc.Species('Ah_mito', compartment='mito', initialConcentration=0.0, unit='mmole', boundaryCondition=True, hasOnlySubstanceUnits=True, name='H+'),
])
# ---------------------------------
# Concentration
# ---------------------------------
for s in species:
aid = s.sid[1:]
rules.append(
mc.AssignmentRule(f'{aid}', f'{s.sid}/{s.compartment}', 'mM', name=f'{s.name} concentration'),
)
##############################################################
# Parameters
##############################################################
parameters.extend([
mc.Parameter('V_cyto', 1.0, UNIT_KIND_LITRE, True, name='cytosolic volume'),
mc.Parameter('f_mito', 0.2, 'dimensionless', True, name='mitochondrial volume factor'),
mc.Parameter('Vliver', 1.5, UNIT_KIND_LITRE, True, name='liver volume'),
mc.Parameter('fliver', 0.583333333333334, 'dimensionless', True, name='parenchymal fraction liver'),
mc.Parameter('bodyweight', 70, 'kg', True, name='bodyweight'),
mc.Parameter('sec_per_min', 60, 's_per_min', True, name='time conversion'),
mc.Parameter('mumole_per_mmole', 1000, 'mumole_per_mmole', True, name='amount conversion'),
# hormonal regulation
mc.Parameter('x_ins1', 818.9, 'pM', True),
mc.Parameter('x_ins2', 0, 'pM', True),
mc.Parameter('x_ins3', 8.6, 'mM', True),
mc.Parameter('x_ins4', 4.2, 'dimensionless', True),
mc.Parameter('x_glu1', 190, 'pM', True),
