def create_layout(n2lo, layout_model, layout_plugin, ub_sps, model):
h_min, (x_shift, y_shift), (w, h) = get_layout_characteristics(n2lo)
scale_factor = MARGIN * 1.0 / (h_min if h_min else 1)
(w, h) = scale((w, h), scale_factor)
(x_shift, y_shift) = shift(scale((x_shift, y_shift), scale_factor), MARGIN, MARGIN)
layout = layout_plugin.createLayout()
layout.setId(generate_unique_id(layout_model, "l_"))
l_id = layout.getId()
layout.setDimensions(create_dimensions(w + 2 * MARGIN, h + 2 * MARGIN))
for comp in model.getListOfCompartments():
c_id = comp.getId()
c_name = comp.getName()
if c_id in n2lo:
(x, y), (w, h) = n2lo[c_id]
(x, y), (w, h) = shift(scale((x, y), scale_factor), x_shift, y_shift), scale((w, h), scale_factor)
comp_glyph = layout.createCompartmentGlyph()
comp_glyph.setId("cg_%s_%s" % (l_id, c_id))
comp_glyph.setCompartmentId(c_id)
comp_glyph.setBoundingBox(create_bounding_box(x, y, w, h))
add_label(c_name, layout, comp_glyph, c_id, w, h, x, y)
for species in model.getListOfSpecies():
s_id = species.getId()
s_name = species.getName()
if s_id in n2lo:
if isinstance(n2lo[s_id], dict):
elements = n2lo[s_id].items()
else:
elements = [('', n2lo[s_id])]
for r_ids, [(x, y), (w, h)] in elements:
if not r_ids or next((it for it in (model.getReaction(r_id) for r_id in r_ids) if it), False):
(x, y), (w, h) = shift(scale((x, y), scale_factor), x_shift, y_shift), scale((w, h), scale_factor)
s_glyph = layout.createSpeciesGlyph()
s_glyph.setSpeciesId(s_id)
s_glyph_suffix = "%s_%s" % (s_id, '_'.join(r_ids)) if r_ids else s_id
s_glyph.setId("sg_%s_%s" % (l_id, s_glyph_suffix))
s_glyph.setBoundingBox(create_bounding_box(x, y, w, h))
add_label(s_name, layout, s_glyph, s_id, w, h, x, y)
for reaction in model.getListOfReactions():
r_id = reaction.getId()
r_name = reaction.getName()
if r_id in n2lo:
(x, y), (w, h) = n2lo[r_id]
(x, y), (w, h) = shift(scale((x, y), scale_factor), x_shift, y_shift), scale((w, h), scale_factor)
r_glyph = layout.createReactionGlyph()
r_glyph.setReactionId(r_id)
r_glyph.setId("rg_%s_%s" % (l_id, r_id))
r_glyph.setBoundingBox(create_bounding_box(x, y, w, h))
add_label(r_name, layout, r_glyph, r_id, w, h, x, y)
link_reaction_to_species(reaction.getListOfReactants(), r_glyph, l_id, r_id, n2lo,
lambda s_id: libsbml.SPECIES_ROLE_SIDESUBSTRATE
if s_id in ub_sps else libsbml.SPECIES_ROLE_SUBSTRATE)
link_reaction_to_species(reaction.getListOfProducts(), r_glyph, l_id, r_id, n2lo,
lambda s_id: libsbml.SPECIES_ROLE_SIDEPRODUCT
if s_id in ub_sps else libsbml.SPECIES_ROLE_PRODUCT)
def save_as_comp_generalized_sbml(input_model, out_sbml, groups_sbml, r_id2clu, clu2s_ids, ub_sps, onto):
logging.info("serializing generalization")
s_id_increment, r_id_increment = 0, 0
if groups_sbml:
doc = convert_to_lev3_v1(input_model)
groups_model = doc.getModel()
groups_plugin = groups_model.getPlugin("groups")
if groups_plugin:
logging.info(" saving ubiquitous species annotations")
s_group = groups_plugin.createGroup()
s_group.setId("g_ubiquitous_sps")
s_group.setKind(libsbml.GROUP_KIND_COLLECTION)
s_group.setSBOTerm(SBO_CHEMICAL_MACROMOLECULE)
s_group.setName("ubiquitous species")
for s_id in ub_sps:
member = s_group.createMember()
member.setIdRef(s_id)
add_annotation(s_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_UBIQUITOUS)
if out_sbml:
# generalized model
generalized_doc = libsbml.SBMLDocument(input_model.getSBMLNamespaces())
generalized_model = generalized_doc.createModel()
copy_elements(input_model, generalized_model)
r_id2g_eq, s_id2gr_id = {}, {}
if not clu2s_ids:
logging.info(" nothing to serialize")
else:
clu2r_ids = invert_map(r_id2clu)
logging.info(" creating species groups")
for ((c_id, t), s_ids) in clu2s_ids.items():
comp = input_model.getCompartment(c_id)
if len(s_ids) > 1:
t = onto.get_term(t)
t_name, t_id = (t.get_name(), t.get_id()) if t \
else (' or '.join(input_model.getSpecies(s_id).getName() for s_id in s_ids), None)
if not t_id:
t = t_name
if out_sbml:
new_species = create_species(model=generalized_model, compartment_id=comp.getId(), type_id=None,
name="{0} ({1}) [{2}]".format(t_name, len(s_ids), comp.getName()))
add_annotation(new_species, libsbml.BQB_IS, t_id, CHEBI_PREFIX)
new_s_id = new_species.getId()
else:
s_id_increment += 1
new_s_id = generate_unique_id(input_model, "s_g_", s_id_increment)
for s_id in s_ids:
s_id2gr_id[s_id] = new_s_id, t
if groups_sbml and groups_plugin:
# save as a group
s_group = groups_plugin.createGroup()
s_group.setId(new_s_id)
s_group.setKind(libsbml.GROUP_KIND_CLASSIFICATION)
s_group.setSBOTerm(SBO_CHEMICAL_MACROMOLECULE)
g_name = "{0} [{1}]".format(t_name, comp.getName())
s_group.setName(g_name)
# logging.info("%s: %d" % (g_name, len(s_ids)))
if t_id:
add_annotation(s_group, libsbml.BQB_IS, t_id, CHEBI_PREFIX)
for s_id in s_ids:
member = s_group.createMember()
member.setIdRef(s_id)
add_annotation(s_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_EQUIV)
generalize_species = lambda species_id: s_id2gr_id[species_id][0] if (species_id in s_id2gr_id) else species_id
s_id_to_generalize = set(s_id2gr_id.keys())
logging.info(" creating reaction groups")
for clu, r_ids in clu2r_ids.items():
representative = input_model.getReaction(list(r_ids)[0])
r_name = "generalized %s" % representative.getName()
if out_sbml:
reactants = dict(get_reactants(representative, stoichiometry=True))
products = dict(get_products(representative, stoichiometry=True))
if (len(r_ids) == 1) and \
not ((set(reactants.keys()) | set(products.keys())) & s_id_to_generalize):
generalized_model.addReaction(representative)
continue
r_id2st = {generalize_species(it): st for (it, st) in reactants.items()}
p_id2st = {generalize_species(it): st for (it, st) in products.items()}
reversible = next((False for r_id in r_ids if not input_model.getReaction(r_id).getReversible()), True)
new_r_id = create_reaction(generalized_model, r_id2st, p_id2st, name=r_name, reversible=reversible,
id_=representative.getId() if len(r_ids) == 1 else None).getId()
elif len(r_ids) > 1:
r_id_increment += 1
new_r_id = generate_unique_id(input_model, "r_g_", r_id_increment)
if len(r_ids) > 1:
for r_id in r_ids:
r_id2g_eq[r_id] = new_r_id, r_name
if groups_sbml and groups_plugin:
# save as a group
r_group = groups_plugin.createGroup()
r_group.setId(new_r_id)
r_group.setKind(libsbml.GROUP_KIND_COLLECTION)
r_group.setSBOTerm(SBO_BIOCHEMICAL_REACTION)
r_group.setName(r_name)
for r_id in r_ids:
member = r_group.createMember()
member.setIdRef(r_id)
add_annotation(r_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_EQUIV)
if out_sbml:
remove_unused_elements(generalized_model)
save_as_sbml(generalized_model, out_sbml)
if groups_sbml and groups_model:
save_as_sbml(groups_model, groups_sbml)
logging.info("serialized to " + groups_sbml)
return r_id2g_eq, s_id2gr_id
def save_as_comp_generalized_sbml(input_model, out_sbml, groups_sbml, r_id2clu, clu2s_ids, ub_sps, onto):
logging.info("serializing generalization")
s_id_increment, r_id_increment = 0, 0
if groups_sbml:
doc = convert_to_lev3_v1(input_model)
groups_model = doc.getModel()
groups_plugin = groups_model.getPlugin("groups")
if groups_plugin:
logging.info(" saving ubiquitous species annotations")
s_group = groups_plugin.createGroup()
s_group.setId("g_ubiquitous_sps")
s_group.setKind(libsbml.GROUP_KIND_COLLECTION)
s_group.setSBOTerm(SBO_CHEMICAL_MACROMOLECULE)
s_group.setName("ubiquitous species")
for s_id in ub_sps:
member = s_group.createMember()
member.setIdRef(s_id)
add_annotation(s_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_UBIQUITOUS)
if out_sbml:
# generalized model
generalized_doc = convert_to_lev3_v1(input_model)
generalized_model = generalized_doc.getModel()
for _ in range(0, generalized_model.getNumReactions()):
generalized_model.removeReaction(0)
r_id2g_eq, s_id2gr_id = {}, {}
if not clu2s_ids:
logging.info(" nothing to serialize")
else:
clu2r_ids = invert_map(r_id2clu)
logging.info(" creating species groups")
for ((c_id, t), s_ids) in clu2s_ids.items():
comp = input_model.getCompartment(c_id)
if len(s_ids) > 1:
t = onto.get_term(t)
t_name, t_id = (t.get_name(), t.get_id()) if t \
else (' or '.join(input_model.getSpecies(s_id).getName() for s_id in s_ids), None)
if not t_id:
t = t_name
if out_sbml:
new_species = create_species(model=generalized_model, compartment_id=comp.getId(), type_id=None,
name="{0} ({1}) [{2}]".format(t_name, len(s_ids), comp.getName()))
add_annotation(new_species, libsbml.BQB_IS, t_id, CHEBI_PREFIX)
new_s_id = new_species.getId()
else:
s_id_increment += 1
new_s_id = generate_unique_id(input_model, "s_g_", s_id_increment)
for s_id in s_ids:
s_id2gr_id[s_id] = new_s_id, t
if groups_sbml and groups_plugin:
# save as a group
s_group = groups_plugin.createGroup()
s_group.setId(new_s_id)
s_group.setKind(libsbml.GROUP_KIND_CLASSIFICATION)
s_group.setSBOTerm(SBO_CHEMICAL_MACROMOLECULE)
g_name = "{0} [{1}]".format(t_name, comp.getName())
s_group.setName(g_name)
# logging.info("%s: %d" % (g_name, len(s_ids)))
if t_id:
add_annotation(s_group, libsbml.BQB_IS, t_id, CHEBI_PREFIX)
for s_id in s_ids:
member = s_group.createMember()
member.setIdRef(s_id)
add_annotation(s_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_EQUIV)
generalize_species = lambda species_id: s_id2gr_id[species_id][0] if (species_id in s_id2gr_id) else species_id
s_id_to_generalize = set(s_id2gr_id.keys())
logging.info(" creating reaction groups")
for clu, r_ids in clu2r_ids.items():
representative = input_model.getReaction(list(r_ids)[0])
r_name = "generalized %s" % representative.getName()
if out_sbml:
reactants = dict(get_reactants(representative, stoichiometry=True))
products = dict(get_products(representative, stoichiometry=True))
if (len(r_ids) == 1) and \
not ((set(reactants.keys()) | set(products.keys())) & s_id_to_generalize):
create_reaction(generalized_model, reactants, products, name=representative.getName(),
reversible=representative.getReversible(), id_=representative.getId())
continue
r_id2st = {generalize_species(it): st for (it, st) in reactants.items()}
p_id2st = {generalize_species(it): st for (it, st) in products.items()}
reversible = next((False for r_id in r_ids if not input_model.getReaction(r_id).getReversible()), True)
new_r_id = create_reaction(generalized_model, r_id2st, p_id2st, name=r_name, reversible=reversible,
id_=representative.getId() if len(r_ids) == 1 else None).getId()
elif len(r_ids) > 1:
r_id_increment += 1
new_r_id = generate_unique_id(input_model, "r_g_", r_id_increment)
if len(r_ids) > 1:
for r_id in r_ids:
r_id2g_eq[r_id] = new_r_id, r_name
if groups_sbml and groups_plugin:
# save as a group
r_group = groups_plugin.createGroup()
r_group.setId(new_r_id)
r_group.setKind(libsbml.GROUP_KIND_COLLECTION)
r_group.setSBOTerm(SBO_BIOCHEMICAL_REACTION)
r_group.setName(r_name)
for r_id in r_ids:
member = r_group.createMember()
member.setIdRef(r_id)
add_annotation(r_group, libsbml.BQB_IS_DESCRIBED_BY, GROUP_TYPE_EQUIV)
if out_sbml:
remove_unused_elements(generalized_model)
save_as_sbml(generalized_model, out_sbml)
if groups_sbml and groups_model:
save_as_sbml(groups_model, groups_sbml)
logging.info("serialized to " + groups_sbml)
return r_id2g_eq, s_id2gr_id
