def open_meta_ns(meta_graph, ns):
root = meta_graph.getRoot()
for n in sorted(ns, key=lambda mn: -root[VIEW_META_GRAPH][mn].getId()):
inner_ns = root[VIEW_META_GRAPH][n].getNodes()
meta_graph.openMetaNode(n)
for inner_n in inner_ns:
root[VIEW_SIZE][inner_n] = get_n_size(meta_graph, inner_n)
def open_meta_ns(meta_graph, ns):
root = meta_graph.getRoot()
for n in sorted(ns, key=lambda mn: -root[VIEW_META_GRAPH][mn].getId()):
inner_ns = root[VIEW_META_GRAPH][n].getNodes()
meta_graph.openMetaNode(n)
for inner_n in inner_ns:
root[VIEW_SIZE][inner_n] = get_n_size(meta_graph, inner_n)
def comp_to_meta_node(meta_graph, c_id, go_id, c_name, out_comp, do_layout=True, n2xy=None):
root = meta_graph.getRoot()
ns = [n for n in meta_graph.getNodes() if root[COMPARTMENT_ID][n] == c_id]
if not ns:
return None
comp_n = meta_graph.createMetaNode(ns, False)
comp_graph = root[VIEW_META_GRAPH][comp_n]
if do_layout:
if n2xy:
apply_node_coordinates(comp_graph, n2xy)
else:
layout(comp_graph)
root[NAME][comp_n] = c_name
root[COMPARTMENT_ID][comp_n] = out_comp
root[TYPE][comp_n] = TYPE_COMPARTMENT
root[VIEW_SHAPE][comp_n] = COMPARTMENT_SHAPE
root[ID][comp_n] = c_id
root[TERM][comp_n] = go_id
root[VIEW_SIZE][comp_n] = get_n_size(meta_graph, comp_n)
for meta_e in root.getInOutEdges(comp_n):
sample_e = next((ee for ee in root[VIEW_META_GRAPH][meta_e] if not root[UBIQUITOUS][ee]),
next(iter(root[VIEW_META_GRAPH][meta_e])))
root[UBIQUITOUS][meta_e] = root[UBIQUITOUS][sample_e]
root[STOICHIOMETRY][meta_e] = sum(root[STOICHIOMETRY][ee] for ee in root[VIEW_META_GRAPH][meta_e])
# todo: this is not True but will help with cycle detection
root[REVERSIBLE][meta_e] = root[REVERSIBLE][sample_e] and not root[UBIQUITOUS][sample_e]
return comp_n
def factor_nodes(graph, ns=None):
root = graph.getRoot()
if not ns:
ns = graph.getNodes()
ancestor2nodes = defaultdict(list)
for node in ns:
ancestor = root[ANCESTOR_ID][node]
if ancestor:
ancestor = ancestor, root[TYPE][node], root[COMPARTMENT_ID][node]
ancestor2nodes[ancestor].append(node)
meta_ns = []
for (ancestor, type_, c_id), nodes in ((k, ns) for (k, ns) in ancestor2nodes.items() if len(ns) > 1):
sample_n = nodes[0]
meta_n = graph.createMetaNode(nodes, False)
for prop in [COMPARTMENT_ID, TYPE, REVERSIBLE, UBIQUITOUS, VIEW_SHAPE, RELATED_COMPARTMENT_IDS]:
root[prop][meta_n] = root[prop][sample_n]
root[ID][meta_n] = root[ANCESTOR_ID][sample_n]
root[VIEW_SIZE][meta_n] = get_n_size(root, meta_n)
root[NAME][meta_n] = root[ANCESTOR_NAME][sample_n]
if TYPE_REACTION == type_:
root[REVERSIBLE][meta_n] = False
root[TRANSPORT][meta_n] = False
for sample_n in nodes:
if root[REVERSIBLE][sample_n]:
root[REVERSIBLE][meta_n] = True
if root[TRANSPORT][sample_n]:
root[TRANSPORT][meta_n] = True
root[TERM][meta_n] = "\nor\n".join({root[TERM][it] for it in nodes})
for ub in root.getInOutNodes(meta_n):
if root[UBIQUITOUS][ub]:
clone_ids = set(root[CLONE_ID][ub].split(',')) if root[CLONE_ID][ub] else set()
clone_ids.add(root[ID][meta_n])
root[CLONE_ID][ub] = ','.join(sorted(clone_ids))
else:
root[TERM][meta_n] = root[ANCESTOR_TERM][sample_n]
for meta_e in root.getInOutEdges(meta_n):
sample_e = next(iter(root[VIEW_META_GRAPH][meta_e]))
root[UBIQUITOUS][meta_e] = root[UBIQUITOUS][sample_e]
root[STOICHIOMETRY][meta_e] = root[STOICHIOMETRY][sample_e]
# todo: this is not True but will help with cycle detection
root[REVERSIBLE][meta_e] = not root[UBIQUITOUS][meta_e]
meta_ns.append(meta_n)
return meta_ns
def species2nodes(graph, input_model, ub_sps):
id2n = {}
for s in input_model.getListOfSpecies():
_id = s.getId()
ub = (_id in ub_sps)
# todo
if SKIP_UBS and ub:
continue
n = graph.addNode()
comp = input_model.getCompartment(s.getCompartment())
graph[COMPARTMENT_ID][n] = comp.getId()
graph[ID][n] = _id
id2n[_id] = n
chebi_id = get_chebi_id(s)
if chebi_id:
graph[TERM][n] = get_chebi_id(s)
name = s.getName()
if name:
# remove compartment from the name,
# e.g. H2O [peroxisome] --> H2O
if comp.getName():
name = name.replace('[%s]' % comp.getName(), '').strip()
name = name.replace('[%s]' % comp.getId(), '').strip()
graph[NAME][n] = name
graph[TYPE][n] = TYPE_SPECIES
graph[UBIQUITOUS][n] = ub
graph[VIEW_SHAPE][n] = SPECIES_SHAPE
graph[VIEW_SIZE][n] = get_n_size(graph, n)
formulas = get_formulas(s)
if formulas:
formula = next(iter(formulas))
if formula and formula != '.':
graph[FORMULA][n] = formula
return id2n
def reactions2nodes(get_r_comp, graph, id2n, input_model):
# get_sp_comp = lambda _id: graph[COMPARTMENT][id2n[_id]]
get_sp_comp = lambda _id: input_model.getSpecies(_id).getCompartment()
def link_reaction_to_species(reaction_node,
sp_ref,
all_comps,
is_reactant=True,
reversible=False):
s_id = sp_ref.getSpecies()
all_comps.add(get_sp_comp(s_id))
# todo:
if SKIP_UBS and s_id not in id2n:
return
species_node = id2n[s_id]
e = graph.addEdge(species_node,
reaction_node) if is_reactant else graph.addEdge(
reaction_node, species_node)
stoich = sp_ref.getStoichiometry()
if not stoich:
stoich = sp_ref.getStoichiometryMath()
if not stoich:
stoich = 1
graph[STOICHIOMETRY][e] = stoich
graph[NAME][e] = input_model.getSpecies(s_id).getName()
ub = graph[UBIQUITOUS][species_node]
graph[UBIQUITOUS][e] = ub
graph[REVERSIBLE][e] = reversible and not ub
for r in input_model.getListOfReactions():
name = r.getName()
# do not add fake isa reactions
# if name.find("isa ") != -1 and 1 == r.getNumReactants() == r.getNumProducts() and get_sp_comp(
# r.getListOfReactants().get(0).getSpecies()) == get_sp_comp(
# r.getListOfProducts().get(0).getSpecies()):
# continue
n = graph.addNode()
graph[TERM][n] = get_gene_association(r)
graph[ID][n] = r.getId()
graph[NAME][n] = name
graph[TYPE][n] = TYPE_REACTION
graph[REVERSIBLE][n] = r.getReversible()
graph[VIEW_SHAPE][n] = REACTION_SHAPE
graph[VIEW_SIZE][n] = get_n_size(graph, n)
all_comps = set()
for sp_ref in r.getListOfReactants():
link_reaction_to_species(n,
sp_ref,
all_comps,
is_reactant=True,
reversible=r.getReversible())
for sp_ref in r.getListOfProducts():
link_reaction_to_species(n,
sp_ref,
all_comps,
is_reactant=False,
reversible=r.getReversible())
graph[TRANSPORT][n] = len(all_comps) > 1
graph[COMPARTMENT_ID][n] = get_r_comp(all_comps)
