fc, (n2lo, e2lo), hidden_c_ids, c_id_hidden_ubs = graph2geojson(c_id2info, c_id2outs, graph, n2xy, onto=chebi) c_id2out_c_id = {} for c_id, info in c_id2info.items(): if c_id not in fc: continue _, _, (_, out_c_id) = info if out_c_id and out_c_id in fc: c_id2out_c_id[c_id] = out_c_id if not n2xy or gen_sbml: groups_document = reader.readSBML(groups_sbml) groups_model = groups_document.getModel() gen_document = reader.readSBML(gen_sbml) gen_model = gen_document.getModel() save_as_layout_sbml(groups_model, gen_model, groups_sbml, gen_sbml, n2lo, ub_sps) if sbgn_export_available: logging.info('exporting as SBGN...') try: groups_document = reader.readSBML(groups_sbml) groups_model = groups_document.getModel() save_as_sbgn(n2lo, e2lo, groups_model, groups_sbgn) logging.info(' exported as SBGN %s' % groups_sbgn) if gen_sbml: gen_document = reader.readSBML(gen_sbml) gen_model = gen_document.getModel() save_as_sbgn(n2lo, e2lo, gen_model, gen_sbgn) logging.info(' exported as SBGN %s' % gen_sbgn) except Exception as e: logging.info(e)
n2xy, onto=chebi) c_id2out_c_id = {} for c_id, info in c_id2info.items(): if c_id not in fc: continue _, _, (_, out_c_id) = info if out_c_id and out_c_id in fc: c_id2out_c_id[c_id] = out_c_id if not n2xy or gen_sbml: groups_document = reader.readSBML(groups_sbml) groups_model = groups_document.getModel() gen_document = reader.readSBML(gen_sbml) gen_model = gen_document.getModel() save_as_layout_sbml(groups_model, gen_model, groups_sbml, gen_sbml, n2lo, ub_sps) if sbgn_export_available: logging.info('exporting as SBGN...') try: groups_document = reader.readSBML(groups_sbml) groups_model = groups_document.getModel() save_as_sbgn(n2lo, e2lo, groups_model, groups_sbgn) logging.info(' exported as SBGN %s' % groups_sbgn) if gen_sbml: gen_document = reader.readSBML(gen_sbml) gen_model = gen_document.getModel() save_as_sbgn(n2lo, e2lo, gen_model, gen_sbgn) logging.info(' exported as SBGN %s' % gen_sbgn) except Exception as e: logging.info(e)
def process_sbml(sbml, verbose, ub_ch_ids=None, web_page_prefix=None, generalize=True, log_file=None, id2mask=None, layer2mask=DEFAULT_LAYER2MASK, tab2html=None, title=None, h1=None, id2color=None, tabs={ABOUT_TAB, DOWNLOAD_TAB}, info='', invisible_layers=None, sbgn=True, cytoscape=True): """ Generalizes and visualizes a given SBML model. :param sbml: a path to the input SBML file :param verbose: if logging information should be printed :param ub_ch_ids: optional, ChEBI ids to be considered as ubiquitous. If left None, will be calculated automatically. :param web_page_prefix: optional, how this model's webpage will be identified. If left None an identifier will be generated based on the SBML file's md5. :param generalize: optional, whether the generalization should be performed. The default is True :param log_file: optional, a file where the logging information should be redirected (only needed if verbose is set to True) :param id2mask: optional, :param layer2mask: optional, a dict storing the correspondence between a layer name and an its id mask :param tab2html: optional, :param title: optional, the title for the web page :param h1: optional, the main header of the web page :param id2color: optional, :param tabs: optional, a set of names of tabs that should be shown :param info: optional, additional information to be displayed in the bottom of the web page :param invisible_layers: optional, the layers of the visualized metabolic map that should be hidden :return: void """ # Read the SBML reader = libsbml.SBMLReader() doc = reader.readSBML(sbml) model = doc.getModel() if not model: raise Exception( "The model should be in SBML format, check your file %s" % sbml) model_id = model.getId() if not model_id: sbml_name = os.path.splitext(os.path.basename(sbml))[0] model.setId(sbml_name) model_id = sbml_name # Prepare the output directories web_page_prefix = web_page_prefix if web_page_prefix else check_md5(sbml) sbml_dir = dirname(abspath(sbml)) directory = os.path.join(sbml_dir, web_page_prefix) if not os.path.exists(directory): os.makedirs(directory) lib_path = os.path.join(directory, 'lib') if not os.path.exists(lib_path): copytree(get_lib(), lib_path) # Prepare the logger if verbose: logging.captureWarnings(True) logging.basicConfig(level=logging.INFO, format='%(asctime)s: %(message)s', datefmt="%Y-%m-%d %H:%M:%S", filename=log_file) # Generalize the model if needed groups_sbml = os.path.join(directory, '%s_with_groups.xml' % model_id) gen_sbml = os.path.join(directory, '%s_generalized.xml' % model_id) if check_for_groups(sbml, SBO_CHEMICAL_MACROMOLECULE, GROUP_TYPE_UBIQUITOUS): if sbml != groups_sbml: if not libsbml.SBMLWriter().writeSBMLToFile(doc, groups_sbml): raise Exception("Could not write your model to %s" % groups_sbml) else: chebi = parse_simple(get_chebi()) if generalize: logging.info('Generalizing the model...') generalize_model(sbml, chebi, groups_sbml, gen_sbml, ub_chebi_ids=ub_ch_ids) else: gen_sbml = None logging.info('Ubiquitizing the model...') ubiquitize_model(sbml, chebi, groups_sbml, ub_chebi_ids=ub_ch_ids) # Visualize the model reader = libsbml.SBMLReader() input_document = reader.readSBML(groups_sbml) input_model = input_document.getModel() root, c_id2info, c_id2outs, chebi, ub_sps = import_sbml( input_model, groups_sbml) c_id2out_c_id = {} for c_id, c_info in c_id2info.items(): _, _, (_, out_c_id) = c_info if out_c_id: c_id2out_c_id[c_id] = out_c_id try: n2xy = parse_layout_sbml(sbml) if n2xy: logging.info('Found layout in the model...') r_size = next((n2xy[r.getId()][1][0] for r in input_model.getListOfReactions() if r.getId() in n2xy), None) if r_size: scale_factor = REACTION_SIZE / r_size if scale_factor != 1: keys = n2xy.keys() for n_id in keys: value = n2xy[n_id] if isinstance(value, dict): value = { r_id: (scale(xy, scale_factor), scale(wh, scale_factor)) for (r_id, (xy, wh)) in value.items() } else: xy, wh = value value = scale(xy, scale_factor), scale( wh, scale_factor) n2xy[n_id] = value except LoPlError: n2xy = None fc, (n2lo, e2lo), hidden_c_ids, c_id_hidden_ubs = \ graph2geojson(c_id2info, c_id2outs, root, n2xy, id2mask=id2mask, onto=chebi, colorer=color if not id2color else lambda graph: color_by_id(graph, id2color)) if n2lo: groups_document = reader.readSBML(groups_sbml) groups_model = groups_document.getModel() if gen_sbml: gen_document = reader.readSBML(gen_sbml) gen_model = gen_document.getModel() else: gen_model = False save_as_layout_sbml(groups_model, gen_model, groups_sbml, gen_sbml, n2lo, ub_sps) if sbgn: groups_sbgn = os.path.join(directory, '%s.sbgn' % model_id) gen_sbgn = os.path.join(directory, '%s_generalized.sbgn' % model_id) try: save_as_sbgn(n2lo, e2lo, groups_model, groups_sbgn) logging.info(' exported as SBGN %s' % groups_sbgn) except Exception as e: logging.error("Didn't manage to save to SBGN: %s" % e) if gen_model: try: save_as_sbgn(n2lo, e2lo, gen_model, gen_sbgn) logging.info(' exported as SBGN %s' % groups_sbgn) except Exception as e: logging.error("Didn't manage to save to SBGN: %s" % e) if cytoscape: out_json = os.path.join(directory, '%s.cyjs' % model_id) save_as_cytoscape_json(n2lo, model, out_json, ub_sps) logging.info(' exported as Cytoscape json %s' % out_json) if gen_model: out_json = os.path.join(directory, '%s_generalized.cyjs' % model_id) save_as_cytoscape_json(n2lo, gen_model, out_json, ub_sps) # Serialize the result serialize(directory=directory, m_dir_id=web_page_prefix, input_model=input_model, c_id2level2features=fc, c_id2out_c_id=c_id2out_c_id, hidden_c_ids=hidden_c_ids, c_id_hidden_ubs=c_id_hidden_ubs, tabs=tabs, groups_sbml=groups_sbml, layer2mask=layer2mask, tab2html=tab2html, title=title, h1=h1, invisible_layers=invisible_layers)