def write_detailed_r_id2c(model, r_id2c, f):
c2r_ids = invert_map(r_id2c)
for c, r_ids in sorted(c2r_ids.items(), key=lambda it: (-abs(it[0]), -it[0])):
for r_id in sorted(r_ids):
f.write('%g\t%s:\t%s\n'
% (c, r_id, get_sbml_r_formula(model, model.getReaction(r_id), show_compartments=False,
show_metabolite_ids=True)))
f.write('\n')
def serialize(sbml, model, m_name, r_id2rev, path, get_f_path):
logging.info("Serializing model info...")
info_prefix = os.path.join(path, 'model_info_')
c_csv, m_csv, r_csv = serialize_model_info(model, info_prefix)
r_string = lambda r, rev: '<b>%s</b>%s: %s' % (r.getId(), ' (reversed)' if rev else '',
get_sbml_r_formula(model, r, show_metabolite_ids=False))
return describe('input_data.html', model_name=m_name, sbml_filepath=get_f_path(sbml),
c_csv=get_f_path(c_csv), m_csv=get_f_path(m_csv), r_csv=get_f_path(r_csv),
in_rn_len=len(r_id2rev),
in_rns=[r_string(model.getReaction(r_id), rev)
for (r_id, rev) in r_id2rev.items()] if r_id2rev else [])
model.getCompartment(species.getCompartment()).getName(),
ch_term.get_id() if ch_term else ''])
row += 1
unm_l += 1
print unm_l
ws = wb.create_sheet(2, "Reaction Groups")
row = 1
add_values(ws, row, 1, ["Group Id", "Id", "Name", "Formula", "Gene Association"], HEADER_STYLE)
row += 1
processed_r_ids = set()
for (g_id, g_name), r_ids in sorted(clu2r_ids.items(), key=lambda ((g_id, g_name), _): g_id):
add_values(ws, row, 1, [g_id])
for r_id in sorted(r_ids, key=lambda r_id: r_id[r_id.find('__'):]):
r = model.getReaction(r_id)
add_values(ws, row, 2, [r_id, r.getName(), get_sbml_r_formula(model, r, show_compartments=True, show_metabolite_ids=True),
get_gene_association(r)])
row += 1
processed_r_ids |= r_ids
ws = wb.create_sheet(3, "Ungrouped reactions")
row = 1
add_values(ws, row, 1, ["Id", "Name", "Formula", "Gene Association"], HEADER_STYLE)
row += 1
unm_l = 0
for r in sorted(model.getListOfReactions(), key=lambda r: r.getId()[r.getId().find('__'):]):
if r.getId() not in processed_r_ids:
add_values(ws, row, 1, [r.getId(), r.getName(), get_sbml_r_formula(model, r, show_compartments=True, show_metabolite_ids=True),
get_gene_association(r)])
row += 1
unm_l += 1
print unm_l
