def generalize_reactions(model, s_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=None):
vk2r = get_vk2r_ids(model, s_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=r_ids_to_ignore)
r_id2clu, i = {}, 0
for r_ids in vk2r.values():
for r_id in r_ids:
r_id2clu[r_id] = i
i += 1
return r_id2clu
def suggest_clusters(model,
unmapped_s_ids,
term_id2clu,
s_id2term_id,
ubiquitous_chebi_ids,
r_ids_to_ignore=None):
# TODO: double check it
return
if not unmapped_s_ids:
return
s_id2clu = compute_s_id2clu(set(), model, s_id2term_id, term_id2clu)
term_id2s_ids = invert_map(s_id2term_id)
vk2r_ids = get_vk2r_ids(model,
s_id2clu,
s_id2term_id,
ubiquitous_chebi_ids,
r_ids_to_ignore=r_ids_to_ignore)
vk2r_ids = {
vk: r_ids
for (vk, r_ids) in vk2r_ids.items() if len(r_ids) > 1
}
processed_r_ids = reduce(lambda s1, s2: s1 | s2, vk2r_ids.values(), set())
s_vk2vk = defaultdict(set)
for vk in vk2r_ids.keys():
s_vk2vk[vertical_key2simplified_vertical_key(vk)].add(vk)
s_id2r_ids = defaultdict(list)
for r in (r for r in model.getListOfReactions()
if r.getNumReactants() + r.getNumProducts() > 2):
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
r_id = r.getId()
for s_id in chain((species_ref.getSpecies()
for species_ref in r.getListOfReactants()),
(species_ref.getSpecies()
for species_ref in r.getListOfProducts())):
s_id2r_ids[s_id].append(r_id)
for r in model.getListOfReactions():
if r.getId(
) in processed_r_ids or not unmapped_s_ids & get_metabolites(r):
continue
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
ub_rs, ub_ps, rs, ps = get_vertical_key(model, r, s_id2clu,
s_id2term_id,
ubiquitous_chebi_ids)
vk = ub_rs, ub_ps, rs, ps
rs, ps = set(rs), set(ps)
partial_rs, partial_ps = {(s_id, c_id) for (s_id, c_id) in rs if s_id not in unmapped_s_ids}, \
{(s_id, c_id) for (s_id, c_id) in ps if s_id not in unmapped_s_ids}
if vk in vk2r_ids or len(ub_rs) + len(ub_ps) + len(partial_rs) + len(
partial_ps) < 2:
continue
s_vk = vertical_key2simplified_vertical_key(vk)
if s_vk in s_vk2vk:
ub_rs, ub_ps = tuple(sorted(ub_rs)), tuple(sorted(ub_ps))
for (vk_ub_rs, vk_ub_ps, vk_rs, vk_ps) in s_vk2vk[s_vk]:
vk_rs, vk_ps = {(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_rs}, \
{(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_ps}
proposal = {}
if vk_ub_rs == ub_ps and vk_ub_ps == ub_rs and not partial_rs - vk_ps and not partial_ps - vk_rs:
vk_ub_rs, vk_ub_ps, partial_rs, partial_ps = vk_ub_ps, vk_ub_rs, partial_ps, partial_rs
if vk_ub_rs == ub_rs and vk_ub_ps == ub_ps and not partial_rs - vk_rs and not partial_ps - vk_ps:
r_s_ids = rs - vk_rs
p_s_ids = ps - vk_ps
if 0 < len(r_s_ids) <= 1 and 0 < len(
p_s_ids) <= 1 and r_s_ids or p_s_ids:
if r_s_ids and vk_rs - rs:
s_id, c_id = r_s_ids.pop()
clu, c_id = (vk_rs - rs).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
candidate_sps = {
model.getSpecies(sp_id)
for sp_id in (
term_id2s_ids[s_id2term_id[s_id]]
if s_id in s_id2term_id else [s_id])
}
comp, term = clu
for s in candidate_sps:
proposal[s.getId()] = term
if p_s_ids and vk_ps - ps:
s_id, c_id = p_s_ids.pop()
clu, c_id = (vk_ps - ps).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
candidate_sps = {
model.getSpecies(it)
for it in (term_id2s_ids[s_id2term_id[s_id]]
if s_id in s_id2term_id else {s_id})
}
comp, term = clu
for s in candidate_sps:
proposal[s.getId()] = term
if proposal:
for s_id, clu in proposal.items():
term_id2clu[s_id] = (
clu, ) if not (isinstance(clu, tuple)) else clu
unmapped_s_ids -= {s_id}
def infer_clusters(model,
unmapped_s_ids,
s_id2clu,
s_id2term_id,
ubiquitous_chebi_ids,
r_ids_to_ignore=None):
# TODO: double check it
return
if not unmapped_s_ids:
return
term_id2s_ids = invert_map(s_id2term_id)
clu2s_ids = invert_map(s_id2clu)
vk2r_ids = get_vk2r_ids(model,
s_id2clu,
s_id2term_id,
ubiquitous_chebi_ids,
r_ids_to_ignore=r_ids_to_ignore)
vk2r_ids = {
vk: r_ids
for (vk, r_ids) in vk2r_ids.items() if len(r_ids) > 1
}
simplified_vk2vk_set = defaultdict(set)
for vk in vk2r_ids.keys():
simplified_vk2vk_set[vertical_key2simplified_vertical_key(vk)].add(vk)
s_id2r_ids = defaultdict(list)
for r in (r for r in model.getListOfReactions()
if r.getNumReactants() + r.getNumProducts() > 2):
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
r_id = r.getId()
for s_id in chain((species_ref.getSpecies()
for species_ref in r.getListOfReactants()),
(species_ref.getSpecies()
for species_ref in r.getListOfProducts())):
s_id2r_ids[s_id].append(r_id)
def in_species_conflict(term, candidate_sps, proposal_s_id2clu):
proposal_clu2s_ids = invert_map(proposal_s_id2clu)
for s in candidate_sps:
s_clu = s.getCompartment(), term
rs = {r_id for r_id in s_id2r_ids[s.getId()]}
clu_s_ids = clu2s_ids[s_clu] | proposal_clu2s_ids[s_clu]
for clu_s_id in clu_s_ids:
if {r_id for r_id in s_id2r_ids[clu_s_id]} & rs:
return True
return False
processed_r_ids = reduce(lambda s1, s2: s1 | s2, vk2r_ids.values(), set())
for r in model.getListOfReactions():
if r.getId(
) in processed_r_ids or not unmapped_s_ids & get_metabolites(r):
continue
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
ub_rs, ub_ps, rs, ps = get_vertical_key(model, r, s_id2clu,
s_id2term_id,
ubiquitous_chebi_ids)
vk = ub_rs, ub_ps, rs, ps
rs, ps = set(rs), set(ps)
partial_rs, partial_ps = {(s_id, c_id) for (s_id, c_id) in rs if s_id not in unmapped_s_ids}, \
{(s_id, c_id) for (s_id, c_id) in ps if s_id not in unmapped_s_ids}
if len(ub_rs) + len(ub_ps) + len(partial_rs) + len(partial_ps) < 2:
continue
simplified_vk = vertical_key2simplified_vertical_key(vk)
if simplified_vk in simplified_vk2vk_set:
ub_rs, ub_ps = tuple(sorted(ub_rs)), tuple(sorted(ub_ps))
for (vk_ub_rs, vk_ub_ps, vk_rs,
vk_ps) in simplified_vk2vk_set[simplified_vk]:
vk_rs, vk_ps = {(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_rs}, \
{(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_ps}
proposal = {}
if vk_ub_rs == ub_ps and vk_ub_ps == ub_rs and not partial_rs - vk_ps and not partial_ps - vk_rs:
vk_ub_rs, vk_ub_ps, partial_rs, partial_ps = vk_ub_ps, vk_ub_rs, partial_ps, partial_rs
if vk_ub_rs == ub_rs and vk_ub_ps == ub_ps and not partial_rs - vk_rs and not partial_ps - vk_ps:
r_s_ids = rs - vk_rs
p_s_ids = ps - vk_ps
if 0 < len(r_s_ids) <= 1 and 0 < len(
p_s_ids) <= 1 and r_s_ids or p_s_ids:
if r_s_ids and vk_rs - rs:
s_id, c_id = r_s_ids.pop()
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
clu, c_id = (vk_rs - rs).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
candidate_sps = {
model.getSpecies(it)
for it in (term_id2s_ids[s_id2term_id[s_id]]
if s_id in s_id2term_id else {s_id})
}
comp, term = clu
if not in_species_conflict(term, candidate_sps,
proposal):
for s in candidate_sps:
proposal[
s.getId()] = s.getCompartment(), term
else:
continue
if p_s_ids and vk_ps - ps:
s_id, c_id = p_s_ids.pop()
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
clu, c_id = (vk_ps - ps).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
candidate_sps = {
model.getSpecies(it)
for it in (term_id2s_ids[s_id2term_id[s_id]]
if s_id in s_id2term_id else {s_id})
}
comp, term = clu
if not in_species_conflict(term, candidate_sps,
proposal):
for s in candidate_sps:
proposal[
s.getId()] = s.getCompartment(), term
else:
continue
if proposal:
s_id2clu.update(proposal)
for s_id, clu in proposal.items():
clu2s_ids[clu].add(s_id)
unmapped_s_ids -= set(proposal.keys())
def suggest_clusters(model, unmapped_s_ids, term_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=None):
# TODO: double check it
return
if not unmapped_s_ids:
return
s_id2clu = compute_s_id2clu(set(), model, s_id2term_id, term_id2clu)
term_id2s_ids = invert_map(s_id2term_id)
vk2r_ids = get_vk2r_ids(model, s_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=r_ids_to_ignore)
vk2r_ids = {vk: r_ids for (vk, r_ids) in vk2r_ids.items() if len(r_ids) > 1}
processed_r_ids = reduce(lambda s1, s2: s1 | s2, vk2r_ids.values(), set())
s_vk2vk = defaultdict(set)
for vk in vk2r_ids.keys():
s_vk2vk[vertical_key2simplified_vertical_key(vk)].add(vk)
s_id2r_ids = defaultdict(list)
for r in (r for r in model.getListOfReactions() if r.getNumReactants() + r.getNumProducts() > 2):
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
r_id = r.getId()
for s_id in chain((species_ref.getSpecies() for species_ref in r.getListOfReactants()),
(species_ref.getSpecies() for species_ref in r.getListOfProducts())):
s_id2r_ids[s_id].append(r_id)
for r in model.getListOfReactions():
if r.getId() in processed_r_ids or not unmapped_s_ids & get_metabolites(r):
continue
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
ub_rs, ub_ps, rs, ps = get_vertical_key(model, r, s_id2clu, s_id2term_id, ubiquitous_chebi_ids)
vk = ub_rs, ub_ps, rs, ps
rs, ps = set(rs), set(ps)
partial_rs, partial_ps = {(s_id, c_id) for (s_id, c_id) in rs if s_id not in unmapped_s_ids}, \
{(s_id, c_id) for (s_id, c_id) in ps if s_id not in unmapped_s_ids}
if vk in vk2r_ids or len(ub_rs) + len(ub_ps) + len(partial_rs) + len(partial_ps) < 2:
continue
s_vk = vertical_key2simplified_vertical_key(vk)
if s_vk in s_vk2vk:
ub_rs, ub_ps = tuple(sorted(ub_rs)), tuple(sorted(ub_ps))
for (vk_ub_rs, vk_ub_ps, vk_rs, vk_ps) in s_vk2vk[s_vk]:
vk_rs, vk_ps = {(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_rs}, \
{(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_ps}
proposal = {}
if vk_ub_rs == ub_ps and vk_ub_ps == ub_rs and not partial_rs - vk_ps and not partial_ps - vk_rs:
vk_ub_rs, vk_ub_ps, partial_rs, partial_ps = vk_ub_ps, vk_ub_rs, partial_ps, partial_rs
if vk_ub_rs == ub_rs and vk_ub_ps == ub_ps and not partial_rs - vk_rs and not partial_ps - vk_ps:
r_s_ids = rs - vk_rs
p_s_ids = ps - vk_ps
if 0 < len(r_s_ids) <= 1 and 0 < len(p_s_ids) <= 1 and r_s_ids or p_s_ids:
if r_s_ids and vk_rs - rs:
s_id, c_id = r_s_ids.pop()
clu, c_id = (vk_rs - rs).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
candidate_sps = {model.getSpecies(sp_id) for sp_id in
(term_id2s_ids[s_id2term_id[s_id]] if s_id in s_id2term_id else [s_id])}
comp, term = clu
for s in candidate_sps:
proposal[s.getId()] = term
if p_s_ids and vk_ps - ps:
s_id, c_id = p_s_ids.pop()
clu, c_id = (vk_ps - ps).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
candidate_sps = {model.getSpecies(it) for it in
(term_id2s_ids[s_id2term_id[s_id]] if s_id in s_id2term_id else {s_id})}
comp, term = clu
for s in candidate_sps:
proposal[s.getId()] = term
if proposal:
for s_id, clu in proposal.items():
term_id2clu[s_id] = (clu, ) if not (isinstance(clu, tuple)) else clu
unmapped_s_ids -= {s_id}
def infer_clusters(model, unmapped_s_ids, s_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=None):
# TODO: double check it
return
if not unmapped_s_ids:
return
term_id2s_ids = invert_map(s_id2term_id)
clu2s_ids = invert_map(s_id2clu)
vk2r_ids = get_vk2r_ids(model, s_id2clu, s_id2term_id, ubiquitous_chebi_ids, r_ids_to_ignore=r_ids_to_ignore)
vk2r_ids = {vk: r_ids for (vk, r_ids) in vk2r_ids.items() if len(r_ids) > 1}
simplified_vk2vk_set = defaultdict(set)
for vk in vk2r_ids.keys():
simplified_vk2vk_set[vertical_key2simplified_vertical_key(vk)].add(vk)
s_id2r_ids = defaultdict(list)
for r in (r for r in model.getListOfReactions() if r.getNumReactants() + r.getNumProducts() > 2):
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
r_id = r.getId()
for s_id in chain((species_ref.getSpecies() for species_ref in r.getListOfReactants()),
(species_ref.getSpecies() for species_ref in r.getListOfProducts())):
s_id2r_ids[s_id].append(r_id)
def in_species_conflict(term, candidate_sps, proposal_s_id2clu):
proposal_clu2s_ids = invert_map(proposal_s_id2clu)
for s in candidate_sps:
s_clu = s.getCompartment(), term
rs = {r_id for r_id in s_id2r_ids[s.getId()]}
clu_s_ids = clu2s_ids[s_clu] | proposal_clu2s_ids[s_clu]
for clu_s_id in clu_s_ids:
if {r_id for r_id in s_id2r_ids[clu_s_id]} & rs:
return True
return False
processed_r_ids = reduce(lambda s1, s2: s1 | s2, vk2r_ids.values(), set())
for r in model.getListOfReactions():
if r.getId() in processed_r_ids or not unmapped_s_ids & get_metabolites(r):
continue
if r_ids_to_ignore and r.getId() in r_ids_to_ignore:
continue
ub_rs, ub_ps, rs, ps = get_vertical_key(model, r, s_id2clu, s_id2term_id, ubiquitous_chebi_ids)
vk = ub_rs, ub_ps, rs, ps
rs, ps = set(rs), set(ps)
partial_rs, partial_ps = {(s_id, c_id) for (s_id, c_id) in rs if s_id not in unmapped_s_ids}, \
{(s_id, c_id) for (s_id, c_id) in ps if s_id not in unmapped_s_ids}
if len(ub_rs) + len(ub_ps) + len(partial_rs) + len(partial_ps) < 2:
continue
simplified_vk = vertical_key2simplified_vertical_key(vk)
if simplified_vk in simplified_vk2vk_set:
ub_rs, ub_ps = tuple(sorted(ub_rs)), tuple(sorted(ub_ps))
for (vk_ub_rs, vk_ub_ps, vk_rs, vk_ps) in simplified_vk2vk_set[simplified_vk]:
vk_rs, vk_ps = {(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_rs}, \
{(s_id if s_id not in s_id2clu else s_id2clu[s_id], c_id) for (s_id, c_id) in vk_ps}
proposal = {}
if vk_ub_rs == ub_ps and vk_ub_ps == ub_rs and not partial_rs - vk_ps and not partial_ps - vk_rs:
vk_ub_rs, vk_ub_ps, partial_rs, partial_ps = vk_ub_ps, vk_ub_rs, partial_ps, partial_rs
if vk_ub_rs == ub_rs and vk_ub_ps == ub_ps and not partial_rs - vk_rs and not partial_ps - vk_ps:
r_s_ids = rs - vk_rs
p_s_ids = ps - vk_ps
if 0 < len(r_s_ids) <= 1 and 0 < len(p_s_ids) <= 1 and r_s_ids or p_s_ids:
if r_s_ids and vk_rs - rs:
s_id, c_id = r_s_ids.pop()
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
clu, c_id = (vk_rs - rs).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
candidate_sps = {model.getSpecies(it) for it in
(term_id2s_ids[s_id2term_id[s_id]] if s_id in s_id2term_id else {s_id})}
comp, term = clu
if not in_species_conflict(term, candidate_sps, proposal):
for s in candidate_sps:
proposal[s.getId()] = s.getCompartment(), term
else:
continue
if p_s_ids and vk_ps - ps:
s_id, c_id = p_s_ids.pop()
# if it is not a species id but a cluster, continue
if not isinstance(s_id, str):
continue
clu, c_id = (vk_ps - ps).pop()
# if it is a species id instead of a cluster, continue
if not isinstance(clu, tuple):
continue
candidate_sps = {model.getSpecies(it) for it in
(term_id2s_ids[s_id2term_id[s_id]] if s_id in s_id2term_id else {s_id})}
comp, term = clu
if not in_species_conflict(term, candidate_sps, proposal):
for s in candidate_sps:
proposal[s.getId()] = s.getCompartment(), term
else:
continue
if proposal:
s_id2clu.update(proposal)
for s_id, clu in proposal.items():
clu2s_ids[clu].add(s_id)
unmapped_s_ids -= set(proposal.keys())