idx int64 0 63k | question stringlengths 53 5.28k | target stringlengths 5 805 |
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17,800 | def _prepare_kappa ( model ) : import kappy kappa = kappy . KappaStd ( ) model_str = export ( model , 'kappa' ) kappa . add_model_string ( model_str ) kappa . project_parse ( ) return kappa | Return a Kappa STD with the model loaded . |
17,801 | def send_request ( ** kwargs ) : skiprows = kwargs . pop ( 'skiprows' , None ) res = requests . get ( cbio_url , params = kwargs ) if res . status_code == 200 : if skiprows == - 1 : lines = res . text . split ( '\n' ) skiprows = 0 for line in lines : if line . startswith ( '#' ) : skiprows += 1 else : break csv_StringI... | Return a data frame from a web service request to cBio portal . |
17,802 | def get_mutations ( study_id , gene_list , mutation_type = None , case_id = None ) : genetic_profile = get_genetic_profiles ( study_id , 'mutation' ) [ 0 ] gene_list_str = ',' . join ( gene_list ) data = { 'cmd' : 'getMutationData' , 'case_set_id' : study_id , 'genetic_profile_id' : genetic_profile , 'gene_list' : gene... | Return mutations as a list of genes and list of amino acid changes . |
17,803 | def get_case_lists ( study_id ) : data = { 'cmd' : 'getCaseLists' , 'cancer_study_id' : study_id } df = send_request ( ** data ) case_set_ids = df [ 'case_list_id' ] . tolist ( ) return case_set_ids | Return a list of the case set ids for a particular study . |
17,804 | def get_profile_data ( study_id , gene_list , profile_filter , case_set_filter = None ) : genetic_profiles = get_genetic_profiles ( study_id , profile_filter ) if genetic_profiles : genetic_profile = genetic_profiles [ 0 ] else : return { } gene_list_str = ',' . join ( gene_list ) case_set_ids = get_case_lists ( study_... | Return dict of cases and genes and their respective values . |
17,805 | def get_num_sequenced ( study_id ) : data = { 'cmd' : 'getCaseLists' , 'cancer_study_id' : study_id } df = send_request ( ** data ) if df . empty : return 0 row_filter = df [ 'case_list_id' ] . str . contains ( 'sequenced' , case = False ) num_case = len ( df [ row_filter ] [ 'case_ids' ] . tolist ( ) [ 0 ] . split ( '... | Return number of sequenced tumors for given study . |
17,806 | def get_cancer_studies ( study_filter = None ) : data = { 'cmd' : 'getCancerStudies' } df = send_request ( ** data ) res = _filter_data_frame ( df , [ 'cancer_study_id' ] , 'cancer_study_id' , study_filter ) study_ids = list ( res [ 'cancer_study_id' ] . values ( ) ) return study_ids | Return a list of cancer study identifiers optionally filtered . |
17,807 | def get_cancer_types ( cancer_filter = None ) : data = { 'cmd' : 'getTypesOfCancer' } df = send_request ( ** data ) res = _filter_data_frame ( df , [ 'type_of_cancer_id' ] , 'name' , cancer_filter ) type_ids = list ( res [ 'type_of_cancer_id' ] . values ( ) ) return type_ids | Return a list of cancer types optionally filtered . |
17,808 | def get_ccle_mutations ( gene_list , cell_lines , mutation_type = None ) : mutations = { cl : { g : [ ] for g in gene_list } for cl in cell_lines } for cell_line in cell_lines : mutations_cl = get_mutations ( ccle_study , gene_list , mutation_type = mutation_type , case_id = cell_line ) for gene , aa_change in zip ( mu... | Return a dict of mutations in given genes and cell lines from CCLE . |
17,809 | def get_ccle_lines_for_mutation ( gene , amino_acid_change ) : data = { 'cmd' : 'getMutationData' , 'case_set_id' : ccle_study , 'genetic_profile_id' : ccle_study + '_mutations' , 'gene_list' : gene , 'skiprows' : 1 } df = send_request ( ** data ) df = df [ df [ 'amino_acid_change' ] == amino_acid_change ] cell_lines =... | Return cell lines with a given point mutation in a given gene . |
17,810 | def get_ccle_cna ( gene_list , cell_lines ) : profile_data = get_profile_data ( ccle_study , gene_list , 'COPY_NUMBER_ALTERATION' , 'all' ) profile_data = dict ( ( key , value ) for key , value in profile_data . items ( ) if key in cell_lines ) return profile_data | Return a dict of CNAs in given genes and cell lines from CCLE . |
17,811 | def get_ccle_mrna ( gene_list , cell_lines ) : gene_list_str = ',' . join ( gene_list ) data = { 'cmd' : 'getProfileData' , 'case_set_id' : ccle_study + '_mrna' , 'genetic_profile_id' : ccle_study + '_mrna' , 'gene_list' : gene_list_str , 'skiprows' : - 1 } df = send_request ( ** data ) mrna_amounts = { cl : { g : [ ] ... | Return a dict of mRNA amounts in given genes and cell lines from CCLE . |
17,812 | def _filter_data_frame ( df , data_col , filter_col , filter_str = None ) : if filter_str is not None : relevant_cols = data_col + [ filter_col ] df . dropna ( inplace = True , subset = relevant_cols ) row_filter = df [ filter_col ] . str . contains ( filter_str , case = False ) data_list = df [ row_filter ] [ data_col... | Return a filtered data frame as a dictionary . |
17,813 | def allow_cors ( func ) : def wrapper ( * args , ** kwargs ) : response . headers [ 'Access-Control-Allow-Origin' ] = '*' response . headers [ 'Access-Control-Allow-Methods' ] = 'PUT, GET, POST, DELETE, OPTIONS' response . headers [ 'Access-Control-Allow-Headers' ] = 'Origin, Accept, Content-Type, X-Requested-With, X-C... | This is a decorator which enable CORS for the specified endpoint . |
17,814 | def trips_process_text ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) text = body . get ( 'text' ) tp = trips . process_text ( text ) return _stmts_from_proc ( tp ) | Process text with TRIPS and return INDRA Statements . |
17,815 | def trips_process_xml ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) xml_str = body . get ( 'xml_str' ) tp = trips . process_xml ( xml_str ) return _stmts_from_proc ( tp ) | Process TRIPS EKB XML and return INDRA Statements . |
17,816 | def reach_process_text ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) text = body . get ( 'text' ) offline = True if body . get ( 'offline' ) else False rp = reach . process_text ( text , offline = offline ) return _stmts_fr... | Process text with REACH and return INDRA Statements . |
17,817 | def reach_process_json ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) json_str = body . get ( 'json' ) rp = reach . process_json_str ( json_str ) return _stmts_from_proc ( rp ) | Process REACH json and return INDRA Statements . |
17,818 | def reach_process_pmc ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) pmcid = body . get ( 'pmcid' ) rp = reach . process_pmc ( pmcid ) return _stmts_from_proc ( rp ) | Process PubMedCentral article and return INDRA Statements . |
17,819 | def bel_process_pybel_neighborhood ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) genes = body . get ( 'genes' ) bp = bel . process_pybel_neighborhood ( genes ) return _stmts_from_proc ( bp ) | Process BEL Large Corpus neighborhood and return INDRA Statements . |
17,820 | def bel_process_belrdf ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) belrdf = body . get ( 'belrdf' ) bp = bel . process_belrdf ( belrdf ) return _stmts_from_proc ( bp ) | Process BEL RDF and return INDRA Statements . |
17,821 | def biopax_process_pc_pathsbetween ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) genes = body . get ( 'genes' ) bp = biopax . process_pc_pathsbetween ( genes ) return _stmts_from_proc ( bp ) | Process PathwayCommons paths between genes return INDRA Statements . |
17,822 | def biopax_process_pc_pathsfromto ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) source = body . get ( 'source' ) target = body . get ( 'target' ) bp = biopax . process_pc_pathsfromto ( source , target ) return _stmts_from_p... | Process PathwayCommons paths from - to genes return INDRA Statements . |
17,823 | def biopax_process_pc_neighborhood ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) genes = body . get ( 'genes' ) bp = biopax . process_pc_neighborhood ( genes ) return _stmts_from_proc ( bp ) | Process PathwayCommons neighborhood return INDRA Statements . |
17,824 | def eidos_process_text ( ) : if request . method == 'OPTIONS' : return { } req = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( req ) text = body . get ( 'text' ) webservice = body . get ( 'webservice' ) if not webservice : response . status = 400 response . content_type = 'application/json' retur... | Process text with EIDOS and return INDRA Statements . |
17,825 | def eidos_process_jsonld ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) eidos_json = body . get ( 'jsonld' ) ep = eidos . process_json_str ( eidos_json ) return _stmts_from_proc ( ep ) | Process an EIDOS JSON - LD and return INDRA Statements . |
17,826 | def cwms_process_text ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) text = body . get ( 'text' ) cp = cwms . process_text ( text ) return _stmts_from_proc ( cp ) | Process text with CWMS and return INDRA Statements . |
17,827 | def hume_process_jsonld ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) jsonld_str = body . get ( 'jsonld' ) jsonld = json . loads ( jsonld_str ) hp = hume . process_jsonld ( jsonld ) return _stmts_from_proc ( hp ) | Process Hume JSON - LD and return INDRA Statements . |
17,828 | def sofia_process_text ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) text = body . get ( 'text' ) auth = body . get ( 'auth' ) sp = sofia . process_text ( text , auth = auth ) return _stmts_from_proc ( sp ) | Process text with Sofia and return INDRA Statements . |
17,829 | def assemble_pysb ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) export_format = body . get ( 'export_format' ) stmts = stmts_from_json ( stmts_json ) pa = PysbAssembler ( ) pa . add_... | Assemble INDRA Statements and return PySB model string . |
17,830 | def assemble_cx ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) ca = CxAssembler ( stmts ) model_str = ca . make_model ( ) res = { 'model' : mode... | Assemble INDRA Statements and return CX network json . |
17,831 | def share_model_ndex ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_str = body . get ( 'stmts' ) stmts_json = json . loads ( stmts_str ) stmts = stmts_from_json ( stmts_json [ "statements" ] ) ca = CxAssembler ( stmts ... | Upload the model to NDEX |
17,832 | def fetch_model_ndex ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) network_id = body . get ( 'network_id' ) cx = process_ndex_network ( network_id ) network_attr = [ x for x in cx . cx if x . get ( 'networkAttributes' ) ] n... | Download model and associated pieces from NDEX |
17,833 | def assemble_graph ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) ga = GraphAssembler ( stmts ) model_str = ga . make_model ( ) res = { 'model' ... | Assemble INDRA Statements and return Graphviz graph dot string . |
17,834 | def assemble_cyjs ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) cja = CyJSAssembler ( ) cja . add_statements ( stmts ) cja . make_model ( group... | Assemble INDRA Statements and return Cytoscape JS network . |
17,835 | def assemble_english ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) sentences = { } for st in stmts : enga = EnglishAssembler ( ) enga . add_sta... | Assemble each statement into |
17,836 | def assemble_loopy ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) sa = SifAssembler ( stmts ) sa . make_model ( use_name_as_key = True ) model_s... | Assemble INDRA Statements into a Loopy model using SIF Assembler . |
17,837 | def get_ccle_mrna_levels ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) gene_list = body . get ( 'gene_list' ) cell_lines = body . get ( 'cell_lines' ) mrna_amounts = cbio_client . get_ccle_mrna ( gene_list , cell_lines ) re... | Get CCLE mRNA amounts using cBioClient |
17,838 | def get_ccle_mutations ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) gene_list = body . get ( 'gene_list' ) cell_lines = body . get ( 'cell_lines' ) mutations = cbio_client . get_ccle_mutations ( gene_list , cell_lines ) re... | Get CCLE mutations returns the amino acid changes for a given list of genes and cell lines |
17,839 | def map_grounding ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) stmts_out = ac . map_grounding ( stmts ) return _return_stmts ( stmts_out ) | Map grounding on a list of INDRA Statements . |
17,840 | def run_preassembly ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) scorer = body . get ( 'scorer' ) return_toplevel = body . get ( 'return_tople... | Run preassembly on a list of INDRA Statements . |
17,841 | def map_ontologies ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) om = OntologyMapper ( stmts , wm_ontomap , scored = True , symmetric = False )... | Run ontology mapping on a list of INDRA Statements . |
17,842 | def filter_by_type ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmt_type_str = body . get ( 'type' ) stmt_type_str = stmt_type_str . capitalize ( ) stmt_type = getattr ( sys . modu... | Filter to a given INDRA Statement type . |
17,843 | def filter_grounded_only ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) score_threshold = body . get ( 'score_threshold' ) if score_threshold is not None : score_threshold = float ( s... | Filter to grounded Statements only . |
17,844 | def filter_belief ( ) : if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) belief_cutoff = body . get ( 'belief_cutoff' ) if belief_cutoff is not None : belief_cutoff = float ( belief_cutoff ) ... | Filter to beliefs above a given threshold . |
17,845 | def get_git_info ( ) : start_dir = abspath ( curdir ) try : chdir ( dirname ( abspath ( __file__ ) ) ) re_patt_str = ( r'commit\s+(?P<commit_hash>\w+).*?Author:\s+' r'(?P<author_name>.*?)\s+<(?P<author_email>.*?)>\s+Date:\s+' r'(?P<date>.*?)\n\s+(?P<commit_msg>.*?)(?:\ndiff.*?)?$' ) show_out = check_output ( [ 'git' , ... | Get a dict with useful git info . |
17,846 | def get_version ( with_git_hash = True , refresh_hash = False ) : version = __version__ if with_git_hash : global INDRA_GITHASH if INDRA_GITHASH is None or refresh_hash : with open ( devnull , 'w' ) as nul : try : ret = check_output ( [ 'git' , 'rev-parse' , 'HEAD' ] , cwd = dirname ( __file__ ) , stderr = nul ) except... | Get an indra version string including a git hash . |
17,847 | def _fix_evidence_text ( txt ) : txt = re . sub ( '[ ]?\( xref \)' , '' , txt ) txt = re . sub ( '\[ xref \]' , '[]' , txt ) txt = re . sub ( '[\(]?XREF_BIBR[\)]?[,]?' , '' , txt ) txt = re . sub ( '[\(]?XREF_FIG[\)]?[,]?' , '' , txt ) txt = re . sub ( '[\(]?XREF_SUPPLEMENT[\)]?[,]?' , '' , txt ) txt = txt . strip ( ) ... | Eliminate some symbols to have cleaner supporting text . |
17,848 | def make_model ( self , add_indra_json = True ) : self . add_indra_json = add_indra_json for stmt in self . statements : if isinstance ( stmt , Modification ) : self . _add_modification ( stmt ) if isinstance ( stmt , SelfModification ) : self . _add_self_modification ( stmt ) elif isinstance ( stmt , RegulateActivity ... | Assemble the CX network from the collected INDRA Statements . |
17,849 | def print_cx ( self , pretty = True ) : def _get_aspect_metadata ( aspect ) : count = len ( self . cx . get ( aspect ) ) if self . cx . get ( aspect ) else 0 if not count : return None data = { 'name' : aspect , 'idCounter' : self . _id_counter , 'consistencyGroup' : 1 , 'elementCount' : count } return data full_cx = O... | Return the assembled CX network as a json string . |
17,850 | def save_model ( self , file_name = 'model.cx' ) : with open ( file_name , 'wt' ) as fh : cx_str = self . print_cx ( ) fh . write ( cx_str ) | Save the assembled CX network in a file . |
17,851 | def set_context ( self , cell_type ) : node_names = [ node [ 'n' ] for node in self . cx [ 'nodes' ] ] res_expr = context_client . get_protein_expression ( node_names , [ cell_type ] ) res_mut = context_client . get_mutations ( node_names , [ cell_type ] ) res_expr = res_expr . get ( cell_type ) res_mut = res_mut . get... | Set protein expression data and mutational status as node attribute |
17,852 | def get_publications ( gene_names , save_json_name = None ) : if len ( gene_names ) != 2 : logger . warning ( 'Other than 2 gene names given.' ) return [ ] res_dict = _send_request ( gene_names ) if not res_dict : return [ ] if save_json_name is not None : with open ( save_json_name , 'wt' ) as fh : json . dump ( res_d... | Return evidence publications for interaction between the given genes . |
17,853 | def _n ( name ) : n = name . encode ( 'ascii' , errors = 'ignore' ) . decode ( 'ascii' ) n = re . sub ( '[^A-Za-z0-9_]' , '_' , n ) n = re . sub ( r'(^[0-9].*)' , r'p\1' , n ) return n | Return valid PySB name . |
17,854 | def get_hash_statements_dict ( self ) : res = { stmt_hash : stmts_from_json ( [ stmt ] ) [ 0 ] for stmt_hash , stmt in self . __statement_jsons . items ( ) } return res | Return a dict of Statements keyed by hashes . |
17,855 | def merge_results ( self , other_processor ) : if not isinstance ( other_processor , self . __class__ ) : raise ValueError ( "Can only extend with another %s instance." % self . __class__ . __name__ ) self . statements . extend ( other_processor . statements ) if other_processor . statements_sample is not None : if sel... | Merge the results of this processor with those of another . |
17,856 | def wait_until_done ( self , timeout = None ) : start = datetime . now ( ) if not self . __th : raise IndraDBRestResponseError ( "There is no thread waiting to " "complete." ) self . __th . join ( timeout ) now = datetime . now ( ) dt = now - start if self . __th . is_alive ( ) : logger . warning ( "Timed out after %0.... | Wait for the background load to complete . |
17,857 | def _merge_json ( self , stmt_json , ev_counts ) : self . __evidence_counts . update ( ev_counts ) for k , sj in stmt_json . items ( ) : if k not in self . __statement_jsons : self . __statement_jsons [ k ] = sj else : for evj in sj [ 'evidence' ] : self . __statement_jsons [ k ] [ 'evidence' ] . append ( evj ) if not ... | Merge these statement jsons with new jsons . |
17,858 | def _run_queries ( self , agent_strs , stmt_types , params , persist ) : self . _query_over_statement_types ( agent_strs , stmt_types , params ) assert len ( self . __done_dict ) == len ( stmt_types ) or None in self . __done_dict . keys ( ) , "Done dict was not initiated for all stmt_type's." if not persist : self . _... | Use paging to get all statements requested . |
17,859 | def get_ids ( search_term , ** kwargs ) : use_text_word = kwargs . pop ( 'use_text_word' , True ) if use_text_word : search_term += '[tw]' params = { 'term' : search_term , 'retmax' : 100000 , 'retstart' : 0 , 'db' : 'pubmed' , 'sort' : 'pub+date' } params . update ( kwargs ) tree = send_request ( pubmed_search , param... | Search Pubmed for paper IDs given a search term . |
17,860 | def get_id_count ( search_term ) : params = { 'term' : search_term , 'rettype' : 'count' , 'db' : 'pubmed' } tree = send_request ( pubmed_search , params ) if tree is None : return None else : count = tree . getchildren ( ) [ 0 ] . text return int ( count ) | Get the number of citations in Pubmed for a search query . |
17,861 | def get_ids_for_gene ( hgnc_name , ** kwargs ) : hgnc_id = hgnc_client . get_hgnc_id ( hgnc_name ) if hgnc_id is None : raise ValueError ( 'Invalid HGNC name.' ) entrez_id = hgnc_client . get_entrez_id ( hgnc_id ) if entrez_id is None : raise ValueError ( 'Entrez ID not found in HGNC table.' ) params = { 'db' : 'gene' ... | Get the curated set of articles for a gene in the Entrez database . |
17,862 | def get_article_xml ( pubmed_id ) : if pubmed_id . upper ( ) . startswith ( 'PMID' ) : pubmed_id = pubmed_id [ 4 : ] params = { 'db' : 'pubmed' , 'retmode' : 'xml' , 'id' : pubmed_id } tree = send_request ( pubmed_fetch , params ) if tree is None : return None article = tree . find ( 'PubmedArticle/MedlineCitation/Arti... | Get the XML metadata for a single article from the Pubmed database . |
17,863 | def get_abstract ( pubmed_id , prepend_title = True ) : article = get_article_xml ( pubmed_id ) if article is None : return None return _abstract_from_article_element ( article , prepend_title ) | Get the abstract of an article in the Pubmed database . |
17,864 | def get_metadata_from_xml_tree ( tree , get_issns_from_nlm = False , get_abstracts = False , prepend_title = False , mesh_annotations = False ) : results = { } pm_articles = tree . findall ( './PubmedArticle' ) for art_ix , pm_article in enumerate ( pm_articles ) : medline_citation = pm_article . find ( './MedlineCitat... | Get metadata for an XML tree containing PubmedArticle elements . |
17,865 | def get_metadata_for_ids ( pmid_list , get_issns_from_nlm = False , get_abstracts = False , prepend_title = False ) : if len ( pmid_list ) > 200 : raise ValueError ( "Metadata query is limited to 200 PMIDs at a time." ) params = { 'db' : 'pubmed' , 'retmode' : 'xml' , 'id' : pmid_list } tree = send_request ( pubmed_fet... | Get article metadata for up to 200 PMIDs from the Pubmed database . |
17,866 | def get_issns_for_journal ( nlm_id ) : params = { 'db' : 'nlmcatalog' , 'retmode' : 'xml' , 'id' : nlm_id } tree = send_request ( pubmed_fetch , params ) if tree is None : return None issn_list = tree . findall ( './/ISSN' ) issn_linking = tree . findall ( './/ISSNLinking' ) issns = issn_list + issn_linking if not issn... | Get a list of the ISSN numbers for a journal given its NLM ID . |
17,867 | def remove_im_params ( model , im ) : for param in model . parameters : try : im . remove_node ( param . name ) except : pass | Remove parameter nodes from the influence map . |
17,868 | def _get_signed_predecessors ( im , node , polarity ) : signed_pred_list = [ ] for pred in im . predecessors ( node ) : pred_edge = ( pred , node ) yield ( pred , _get_edge_sign ( im , pred_edge ) * polarity ) | Get upstream nodes in the influence map . |
17,869 | def _get_edge_sign ( im , edge ) : edge_data = im [ edge [ 0 ] ] [ edge [ 1 ] ] signs = list ( set ( [ v [ 'sign' ] for v in edge_data . values ( ) if v . get ( 'sign' ) ] ) ) if len ( signs ) > 1 : logger . warning ( "Edge %s has conflicting polarities; choosing " "positive polarity by default" % str ( edge ) ) sign =... | Get the polarity of the influence by examining the edge sign . |
17,870 | def _add_modification_to_agent ( agent , mod_type , residue , position ) : new_mod = ModCondition ( mod_type , residue , position ) for old_mod in agent . mods : if old_mod . equals ( new_mod ) : return agent new_agent = deepcopy ( agent ) new_agent . mods . append ( new_mod ) return new_agent | Add a modification condition to an Agent . |
17,871 | def _match_lhs ( cp , rules ) : rule_matches = [ ] for rule in rules : reactant_pattern = rule . rule_expression . reactant_pattern for rule_cp in reactant_pattern . complex_patterns : if _cp_embeds_into ( rule_cp , cp ) : rule_matches . append ( rule ) break return rule_matches | Get rules with a left - hand side matching the given ComplexPattern . |
17,872 | def _cp_embeds_into ( cp1 , cp2 ) : if cp1 is None or cp2 is None : return False cp1 = as_complex_pattern ( cp1 ) cp2 = as_complex_pattern ( cp2 ) if len ( cp2 . monomer_patterns ) == 1 : mp2 = cp2 . monomer_patterns [ 0 ] for mp1 in cp1 . monomer_patterns : if _mp_embeds_into ( mp1 , mp2 ) : return True return False | Check that any state in ComplexPattern2 is matched in ComplexPattern1 . |
17,873 | def _mp_embeds_into ( mp1 , mp2 ) : sc_matches = [ ] if mp1 . monomer . name != mp2 . monomer . name : return False for site_name , site_state in mp2 . site_conditions . items ( ) : if site_name not in mp1 . site_conditions or site_state != mp1 . site_conditions [ site_name ] : return False return True | Check that conditions in MonomerPattern2 are met in MonomerPattern1 . |
17,874 | def _monomer_pattern_label ( mp ) : site_strs = [ ] for site , cond in mp . site_conditions . items ( ) : if isinstance ( cond , tuple ) or isinstance ( cond , list ) : assert len ( cond ) == 2 if cond [ 1 ] == WILD : site_str = '%s_%s' % ( site , cond [ 0 ] ) else : site_str = '%s_%s%s' % ( site , cond [ 0 ] , cond [ ... | Return a string label for a MonomerPattern . |
17,875 | def _stmt_from_rule ( model , rule_name , stmts ) : stmt_uuid = None for ann in model . annotations : if ann . predicate == 'from_indra_statement' : if ann . subject == rule_name : stmt_uuid = ann . object break if stmt_uuid : for stmt in stmts : if stmt . uuid == stmt_uuid : return stmt | Return the INDRA Statement corresponding to a given rule by name . |
17,876 | def generate_im ( self , model ) : kappa = kappy . KappaStd ( ) model_str = export . export ( model , 'kappa' ) kappa . add_model_string ( model_str ) kappa . project_parse ( ) imap = kappa . analyses_influence_map ( accuracy = 'medium' ) graph = im_json_to_graph ( imap ) return graph | Return a graph representing the influence map generated by Kappa |
17,877 | def draw_im ( self , fname ) : im = self . get_im ( ) im_agraph = nx . nx_agraph . to_agraph ( im ) im_agraph . draw ( fname , prog = 'dot' ) | Draw and save the influence map in a file . |
17,878 | def get_im ( self , force_update = False ) : if self . _im and not force_update : return self . _im if not self . model : raise Exception ( "Cannot get influence map if there is no model." ) def add_obs_for_agent ( agent ) : obj_mps = list ( pa . grounded_monomer_patterns ( self . model , agent ) ) if not obj_mps : log... | Get the influence map for the model generating it if necessary . |
17,879 | def check_model ( self , max_paths = 1 , max_path_length = 5 ) : results = [ ] for stmt in self . statements : result = self . check_statement ( stmt , max_paths , max_path_length ) results . append ( ( stmt , result ) ) return results | Check all the statements added to the ModelChecker . |
17,880 | def check_statement ( self , stmt , max_paths = 1 , max_path_length = 5 ) : self . get_im ( ) if not isinstance ( stmt , ( Modification , RegulateAmount , RegulateActivity , Influence ) ) : return PathResult ( False , 'STATEMENT_TYPE_NOT_HANDLED' , max_paths , max_path_length ) if isinstance ( stmt , Modification ) : t... | Check a single Statement against the model . |
17,881 | def score_paths ( self , paths , agents_values , loss_of_function = False , sigma = 0.15 , include_final_node = False ) : obs_model = lambda x : scipy . stats . norm ( x , sigma ) obs_dict = { } for ag , val in agents_values . items ( ) : obs_list = self . agent_to_obs [ ag ] if obs_list is not None : for obs in obs_li... | Return scores associated with a given set of paths . |
17,882 | def prune_influence_map ( self ) : im = self . get_im ( ) logger . info ( 'Removing self loops' ) edges_to_remove = [ ] for e in im . edges ( ) : if e [ 0 ] == e [ 1 ] : logger . info ( 'Removing self loop: %s' , e ) edges_to_remove . append ( ( e [ 0 ] , e [ 1 ] ) ) im . remove_edges_from ( edges_to_remove ) remove_im... | Remove edges between rules causing problematic non - transitivity . |
17,883 | def prune_influence_map_subj_obj ( self ) : def get_rule_info ( r ) : result = { } for ann in self . model . annotations : if ann . subject == r : if ann . predicate == 'rule_has_subject' : result [ 'subject' ] = ann . object elif ann . predicate == 'rule_has_object' : result [ 'object' ] = ann . object return result i... | Prune influence map to include only edges where the object of the upstream rule matches the subject of the downstream rule . |
17,884 | def add_section ( self , section_name ) : self . section_headings . append ( section_name ) if section_name in self . sections : raise ValueError ( "Section %s already exists." % section_name ) self . sections [ section_name ] = [ ] return | Create a section of the report to be headed by section_name |
17,885 | def set_section_order ( self , section_name_list ) : self . section_headings = section_name_list [ : ] for section_name in self . sections . keys ( ) : if section_name not in section_name_list : self . section_headings . append ( section_name ) return | Set the order of the sections which are by default unorderd . |
17,886 | def add_text ( self , text , * args , ** kwargs ) : section_name = kwargs . pop ( 'section' , None ) para , sp = self . _preformat_text ( text , * args , ** kwargs ) if section_name is None : relevant_list = self . story else : relevant_list = self . sections [ section_name ] relevant_list . append ( para ) relevant_li... | Add text to the document . |
17,887 | def add_image ( self , image_path , width = None , height = None , section = None ) : if width is not None : width = width * inch if height is not None : height = height * inch im = Image ( image_path , width , height ) if section is None : self . story . append ( im ) else : self . sections [ section ] . append ( im )... | Add an image to the document . |
17,888 | def make_report ( self , sections_first = True , section_header_params = None ) : full_story = list ( self . _preformat_text ( self . title , style = 'Title' , fontsize = 18 , alignment = 'center' ) ) if section_header_params is None : section_header_params = { 'style' : 'h1' , 'fontsize' : 14 , 'alignment' : 'center' ... | Create the pdf document with name self . name + . pdf . |
17,889 | def _make_sections ( self , ** section_hdr_params ) : sect_story = [ ] if not self . section_headings and len ( self . sections ) : self . section_headings = self . sections . keys ( ) for section_name in self . section_headings : section_story = self . sections [ section_name ] line = '-' * 20 section_head_text = '%s ... | Flatten the sections into a single story list . |
17,890 | def _preformat_text ( self , text , style = 'Normal' , space = None , fontsize = 12 , alignment = 'left' ) : if space is None : space = ( 1 , 12 ) ptext = ( '<para alignment=\"%s\"><font size=%d>%s</font></para>' % ( alignment , fontsize , text ) ) para = Paragraph ( ptext , self . styles [ style ] ) sp = Spacer ( * sp... | Format the text for addition to a story list . |
17,891 | def get_mesh_name_from_web ( mesh_id ) : url = MESH_URL + mesh_id + '.json' resp = requests . get ( url ) if resp . status_code != 200 : return None mesh_json = resp . json ( ) try : label = mesh_json [ '@graph' ] [ 0 ] [ 'label' ] [ '@value' ] except ( KeyError , IndexError ) as e : return None return label | Get the MESH label for the given MESH ID using the NLM REST API . |
17,892 | def get_mesh_name ( mesh_id , offline = False ) : indra_mesh_mapping = mesh_id_to_name . get ( mesh_id ) if offline or indra_mesh_mapping is not None : return indra_mesh_mapping return get_mesh_name_from_web ( mesh_id ) | Get the MESH label for the given MESH ID . |
17,893 | def get_mesh_id_name ( mesh_term , offline = False ) : indra_mesh_id = mesh_name_to_id . get ( mesh_term ) if indra_mesh_id is not None : return indra_mesh_id , mesh_term indra_mesh_id , new_term = mesh_name_to_id_name . get ( mesh_term , ( None , None ) ) if indra_mesh_id is not None : return indra_mesh_id , new_term ... | Get the MESH ID and name for the given MESH term . |
17,894 | def make ( directory ) : if os . path . exists ( directory ) : if os . path . isdir ( directory ) : click . echo ( 'Directory already exists' ) else : click . echo ( 'Path exists and is not a directory' ) sys . exit ( ) os . makedirs ( directory ) os . mkdir ( os . path . join ( directory , 'jsons' ) ) copy_default_con... | Makes a RAS Machine directory |
17,895 | def run_with_search ( model_path , config , num_days ) : from indra . tools . machine . machine import run_with_search_helper run_with_search_helper ( model_path , config , num_days = num_days ) | Run with PubMed search for new papers . |
17,896 | def run_with_pmids ( model_path , pmids ) : from indra . tools . machine . machine import run_with_pmids_helper run_with_pmids_helper ( model_path , pmids ) | Run with given list of PMIDs . |
17,897 | def id_lookup ( paper_id , idtype = None ) : if idtype is not None and idtype not in ( 'pmid' , 'pmcid' , 'doi' ) : raise ValueError ( "Invalid idtype %s; must be 'pmid', 'pmcid', " "or 'doi'." % idtype ) if paper_id . upper ( ) . startswith ( 'PMC' ) : idtype = 'pmcid' if paper_id . upper ( ) . startswith ( 'PMID' ) :... | This function takes a Pubmed ID Pubmed Central ID or DOI and use the Pubmed ID mapping service and looks up all other IDs from one of these . The IDs are returned in a dictionary . |
17,898 | def get_xml ( pmc_id ) : if pmc_id . upper ( ) . startswith ( 'PMC' ) : pmc_id = pmc_id [ 3 : ] params = { } params [ 'verb' ] = 'GetRecord' params [ 'identifier' ] = 'oai:pubmedcentral.nih.gov:%s' % pmc_id params [ 'metadataPrefix' ] = 'pmc' res = requests . get ( pmc_url , params ) if not res . status_code == 200 : l... | Returns XML for the article corresponding to a PMC ID . |
17,899 | def extract_paragraphs ( xml_string ) : tree = etree . fromstring ( xml_string . encode ( 'utf-8' ) ) paragraphs = [ ] for element in tree . iter ( ) : if isinstance ( element . tag , basestring ) and re . search ( '(^|})[p|title]$' , element . tag ) and element . text : paragraph = ' ' . join ( element . itertext ( ) ... | Returns list of paragraphs in an NLM XML . |
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