idx int64 0 63k | question stringlengths 61 4.03k | target stringlengths 6 1.23k |
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15,900 | def _regex_strings ( self ) : domain = 0 if domain not in self . domains : self . register_domain ( domain = domain ) return self . domains [ domain ] . _regex_strings | A property to link into IntentEngine s _regex_strings . |
15,901 | def regular_expressions_entities ( self ) : domain = 0 if domain not in self . domains : self . register_domain ( domain = domain ) return self . domains [ domain ] . regular_expressions_entities | A property to link into IntentEngine s regular_expressions_entities . |
15,902 | def register_domain ( self , domain = 0 , tokenizer = None , trie = None ) : self . domains [ domain ] = IntentDeterminationEngine ( tokenizer = tokenizer , trie = trie ) | Register a domain with the intent engine . |
15,903 | def register_entity ( self , entity_value , entity_type , alias_of = None , domain = 0 ) : if domain not in self . domains : self . register_domain ( domain = domain ) self . domains [ domain ] . register_entity ( entity_value = entity_value , entity_type = entity_type , alias_of = alias_of ) | Register an entity to be tagged in potential parse results . |
15,904 | def register_intent_parser ( self , intent_parser , domain = 0 ) : if domain not in self . domains : self . register_domain ( domain = domain ) self . domains [ domain ] . register_intent_parser ( intent_parser = intent_parser ) | Register a intent parser with a domain . |
15,905 | def tokenize ( self , string ) : s = string s = re . sub ( '\t' , " " , s ) s = re . sub ( "(" + regex_separator + ")" , " \g<1> " , s ) s = re . sub ( "([^0-9])," , "\g<1> , " , s ) s = re . sub ( ",([^0-9])" , " , \g<1>" , s ) s = re . sub ( "^(')" , "\g<1> " , s ) s = re . sub ( "(" + regex_not_letter_number + ")'" ... | Used to parce a string into tokens |
15,906 | def parse ( self , utterance , context = None , N = 1 ) : start = time . time ( ) context_trie = None if context and isinstance ( context , list ) : context . sort ( key = lambda x : x . get ( 'confidence' ) ) context_trie = Trie ( ) for entity in context : entity_value , entity_type = entity . get ( 'data' ) [ 0 ] con... | Used to find tags within utterance with a given confidence |
15,907 | def metadata_matches ( self , query = { } ) : result = len ( query . keys ( ) ) > 0 for key in query . keys ( ) : result = result and query [ key ] == self . metadata . get ( key ) return result | Returns key matches to metadata |
15,908 | def merge_context ( self , tag , metadata ) : self . entities . append ( tag ) for k in metadata . keys ( ) : if k not in self . metadata : self . metadata [ k ] = k | merge into contextManagerFrame new entity and metadata . |
15,909 | def get_context ( self , max_frames = None , missing_entities = [ ] ) : if not max_frames or max_frames > len ( self . frame_stack ) : max_frames = len ( self . frame_stack ) missing_entities = list ( missing_entities ) context = [ ] for i in xrange ( max_frames ) : frame_entities = [ entity . copy ( ) for entity in se... | Constructs a list of entities from the context . |
15,910 | def find_first_tag ( tags , entity_type , after_index = - 1 ) : for tag in tags : for entity in tag . get ( 'entities' ) : for v , t in entity . get ( 'data' ) : if t . lower ( ) == entity_type . lower ( ) and tag . get ( 'start_token' , 0 ) > after_index : return tag , v , entity . get ( 'confidence' ) return None , N... | Searches tags for entity type after given index |
15,911 | def choose_1_from_each ( lists ) : if len ( lists ) == 0 : yield [ ] else : for el in lists [ 0 ] : for next_list in choose_1_from_each ( lists [ 1 : ] ) : yield [ el ] + next_list | Takes a list of lists and returns a list of lists with one item from each list . This new list should be the length of each list multiplied by the others . 18 for an list with lists of 3 2 and 3 . Also the lenght of each sub list should be same as the length of lists passed in . |
15,912 | def resolve_one_of ( tags , at_least_one ) : if len ( tags ) < len ( at_least_one ) : return None for possible_resolution in choose_1_from_each ( at_least_one ) : resolution = { } pr = possible_resolution [ : ] for entity_type in pr : last_end_index = - 1 if entity_type in resolution : last_end_index = resolution . get... | This searches tags for Entites in at_least_one and returns any match |
15,913 | def validate ( self , tags , confidence ) : intent , tags = self . validate_with_tags ( tags , confidence ) return intent | Using this method removes tags from the result of validate_with_tags |
15,914 | def validate_with_tags ( self , tags , confidence ) : result = { 'intent_type' : self . name } intent_confidence = 0.0 local_tags = tags [ : ] used_tags = [ ] for require_type , attribute_name in self . requires : required_tag , canonical_form , confidence = find_first_tag ( local_tags , require_type ) if not required_... | Validate weather tags has required entites for this intent to fire |
15,915 | def require ( self , entity_type , attribute_name = None ) : if not attribute_name : attribute_name = entity_type self . requires += [ ( entity_type , attribute_name ) ] return self | The intent parser should require an entity of the provided type . |
15,916 | def optionally ( self , entity_type , attribute_name = None ) : if not attribute_name : attribute_name = entity_type self . optional += [ ( entity_type , attribute_name ) ] return self | Parsed intents from this parser can optionally include an entity of the provided type . |
15,917 | def build ( self ) : return Intent ( self . name , self . requires , self . at_least_one , self . optional ) | Constructs an intent from the builder s specifications . |
15,918 | def term_matrix ( idlist , subject_category , taxon , ** kwargs ) : results = search_associations ( objects = idlist , subject_taxon = taxon , subject_category = subject_category , select_fields = [ M . SUBJECT , M . OBJECT_CLOSURE ] , facet_fields = [ ] , rows = - 1 , include_raw = True , ** kwargs ) docs = results [ ... | Intersection between annotated objects |
15,919 | def get_ancestors_through_subont ( self , go_term , relations ) : all_ancestors = self . ontology . ancestors ( go_term , reflexive = True ) subont = self . ontology . subontology ( all_ancestors ) return subont . ancestors ( go_term , relations ) | Returns the ancestors from the relation filtered GO subontology of go_term s ancestors . |
15,920 | def go_aspect ( self , go_term ) : if not go_term . startswith ( "GO:" ) : return None else : if self . is_molecular_function ( go_term ) : return 'F' elif self . is_cellular_component ( go_term ) : return 'C' elif self . is_biological_process ( go_term ) : return 'P' | For GO terms returns F C or P corresponding to its aspect |
15,921 | def _neighbors_graph ( self , ** params ) -> Dict : response = self . _get_response ( "graph/neighbors" , format = "json" , ** params ) return response . json ( ) | Get neighbors of a node |
15,922 | def rdfgraph_to_ontol ( rg ) : digraph = networkx . MultiDiGraph ( ) from rdflib . namespace import RDF label_map = { } for c in rg . subjects ( RDF . type , OWL . Class ) : cid = contract_uri_wrap ( c ) logging . info ( "C={}" . format ( cid ) ) for lit in rg . objects ( c , RDFS . label ) : label_map [ cid ] = lit . ... | Return an Ontology object from an rdflib graph object |
15,923 | def get_association ( id , ** kwargs ) : results = search_associations ( id = id , ** kwargs ) assoc = results [ 'associations' ] [ 0 ] if len ( results [ 'associations' ] ) > 0 else { } return assoc | Fetch an association object by ID |
15,924 | def search_associations ( ** kwargs ) : logging . info ( "CREATING_GOLR_QUERY {}" . format ( kwargs ) ) q = GolrAssociationQuery ( ** kwargs ) return q . exec ( ) | Fetch a set of association objects based on a query . |
15,925 | def bulk_fetch ( subject_category , object_category , taxon , rows = MAX_ROWS , ** kwargs ) : assert subject_category is not None assert object_category is not None time . sleep ( 1 ) logging . info ( "Bulk query: {} {} {}" . format ( subject_category , object_category , taxon ) ) assocs = search_associations_compact (... | Fetch associations for a species and pair of categories in bulk . |
15,926 | def search_associations_go ( subject_category = None , object_category = None , relation = None , subject = None , ** kwargs ) : go_golr_url = "http://golr.geneontology.org/solr/" go_solr = pysolr . Solr ( go_golr_url , timeout = 5 ) go_solr . get_session ( ) . headers [ 'User-Agent' ] = get_user_agent ( caller_name = ... | Perform association search using Monarch golr |
15,927 | def select_distinct ( distinct_field = None , ** kwargs ) : results = search_associations ( rows = 0 , select_fields = [ ] , facet_field_limits = { distinct_field : - 1 } , facet_fields = [ distinct_field ] , ** kwargs ) return list ( results [ 'facet_counts' ] [ distinct_field ] . keys ( ) ) | select distinct values for a given field for a given a query |
15,928 | def pw_score_cosine ( self , s1 : ClassId , s2 : ClassId ) -> SimScore : df = self . assoc_df slice1 = df . loc [ s1 ] . values slice2 = df . loc [ s2 ] . values return 1 - cosine ( slice1 , slice2 ) | Cosine similarity of two subjects |
15,929 | def calculate_mrcas ( self , c1 : ClassId , c2 : ClassId ) -> Set [ ClassId ] : G = self . G ancs1 = self . _ancestors ( c1 ) | { c1 } ancs2 = self . _ancestors ( c2 ) | { c2 } common_ancestors = ancs1 & ancs2 redundant = set ( ) for a in common_ancestors : redundant = redundant | nx . ancestors ( G , a ) return common... | Calculate the MRCA for a class pair |
15,930 | def pw_compare_class_sets ( self , cset1 : Set [ ClassId ] , cset2 : Set [ ClassId ] ) -> Tuple [ ICValue , ICValue , ICValue ] : pairs = self . mica_ic_df . loc [ cset1 , cset2 ] max0 = pairs . max ( axis = 0 ) max1 = pairs . max ( axis = 1 ) idxmax0 = pairs . idxmax ( axis = 0 ) idxmax1 = pairs . idxmax ( axis = 1 ) ... | Compare two class profiles |
15,931 | def process_file ( self , filename = None , format = None ) : rdfgraph = rdflib . Graph ( ) if format is None : if filename . endswith ( ".ttl" ) : format = 'turtle' elif filename . endswith ( ".rdf" ) : format = 'xml' rdfgraph . parse ( filename , format = format ) return self . process_rdfgraph ( rdfgraph ) | Parse a file into an ontology object using rdflib |
15,932 | def process_rdfgraph ( self , rg , ont = None ) : if ont is None : ont = Ontology ( ) subjs = list ( rg . subjects ( RDF . type , SKOS . ConceptScheme ) ) if len ( subjs ) == 0 : logging . warning ( "No ConceptScheme" ) else : ont . id = self . _uri2id ( subjs [ 0 ] ) subset_map = { } for concept in rg . subjects ( RDF... | Transform a skos terminology expressed in an rdf graph into an Ontology object |
15,933 | def get_attribute_information_profile ( url : str , profile : Optional [ Tuple [ str ] ] = None , categories : Optional [ Tuple [ str ] ] = None ) -> Dict : owlsim_url = url + 'getAttributeInformationProfile' params = { 'a' : profile , 'r' : categories } return requests . get ( owlsim_url , params = params , timeout = ... | Get the information content for a list of phenotypes and the annotation sufficiency simple and and categorical scores if categories are provied |
15,934 | def search ( self , id_list : List , negated_classes : List , limit : Optional [ int ] = 100 , method : Optional [ SimAlgorithm ] = SimAlgorithm . PHENODIGM ) -> SimResult : return self . filtered_search ( id_list = id_list , negated_classes = negated_classes , limit = limit , taxon_filter = None , category_filter = No... | Owlsim2 search calls search_by_attribute_set and converts to SimResult object |
15,935 | def filtered_search ( self , id_list : List , negated_classes : List , limit : Optional [ int ] = 100 , taxon_filter : Optional [ int ] = None , category_filter : Optional [ str ] = None , method : Optional [ SimAlgorithm ] = SimAlgorithm . PHENODIGM ) -> SimResult : if len ( negated_classes ) > 0 : logging . warning (... | Owlsim2 filtered search resolves taxon and category to a namespace calls search_by_attribute_set and converts to SimResult object |
15,936 | def matchers ( ) -> List [ SimAlgorithm ] : return [ SimAlgorithm . PHENODIGM , SimAlgorithm . JACCARD , SimAlgorithm . SIM_GIC , SimAlgorithm . RESNIK , SimAlgorithm . SYMMETRIC_RESNIK ] | Matchers in owlsim2 |
15,937 | def get_profile_ic ( self , profile : List ) -> Dict : sim_response = get_attribute_information_profile ( self . url , tuple ( profile ) ) profile_ic = { } try : for cls in sim_response [ 'input' ] : profile_ic [ cls [ 'id' ] ] = cls [ 'IC' ] except JSONDecodeError as json_exc : raise JSONDecodeError ( "Cannot parse ow... | Given a list of individuals return their information content |
15,938 | def _simsearch_to_simresult ( self , sim_resp : Dict , method : SimAlgorithm ) -> SimResult : sim_ids = get_nodes_from_ids ( sim_resp [ 'query_IRIs' ] ) sim_resp [ 'results' ] = OwlSim2Api . _rank_results ( sim_resp [ 'results' ] , method ) ids = [ result [ 'j' ] [ 'id' ] for result in sim_resp [ 'results' ] ] id_type_... | Convert owlsim json to SimResult object |
15,939 | def _rank_results ( results : List [ Dict ] , method : SimAlgorithm ) -> List [ Dict ] : sorted_results = sorted ( results , reverse = True , key = lambda k : k [ OwlSim2Api . method2key [ method ] ] ) if len ( sorted_results ) > 0 : rank = 1 previous_score = sorted_results [ 0 ] [ OwlSim2Api . method2key [ method ] ] ... | Ranks results - for phenodigm results are ranks but ties need to accounted for for other methods results need to be reranked |
15,940 | def translate_facet_field ( fcs , invert_subject_object = False ) : if 'facet_fields' not in fcs : return { } ffs = fcs [ 'facet_fields' ] rs = { } for ( facet , facetresults ) in ffs . items ( ) : if invert_subject_object : for ( k , v ) in INVERT_FIELDS_MAP . items ( ) : if facet == k : facet = v break elif facet == ... | Translates solr facet_fields results into something easier to manipulate |
15,941 | def goassoc_fieldmap ( relationship_type = ACTS_UPSTREAM_OF_OR_WITHIN ) : return { M . SUBJECT : 'bioentity' , M . SUBJECT_CLOSURE : 'bioentity' , M . SUBJECT_CATEGORY : None , M . SUBJECT_LABEL : 'bioentity_label' , M . SUBJECT_TAXON : 'taxon' , M . SUBJECT_TAXON_LABEL : 'taxon_label' , M . SUBJECT_TAXON_CLOSURE : 'ta... | Returns a mapping of canonical monarch fields to amigo - golr . |
15,942 | def map_field ( fn , m ) : if m is None : return fn if fn in m : return m [ fn ] else : return fn | Maps a field name given a mapping file . Returns input if fieldname is unmapped . |
15,943 | def search ( self ) : params = self . solr_params ( ) logging . info ( "PARAMS=" + str ( params ) ) results = self . solr . search ( ** params ) logging . info ( "Docs found: {}" . format ( results . hits ) ) return self . _process_search_results ( results ) | Execute solr search query |
15,944 | def autocomplete ( self ) : self . facet = False params = self . solr_params ( ) logging . info ( "PARAMS=" + str ( params ) ) results = self . solr . search ( ** params ) logging . info ( "Docs found: {}" . format ( results . hits ) ) return self . _process_autocomplete_results ( results ) | Execute solr autocomplete |
15,945 | def _process_search_results ( self , results : pysolr . Results ) -> SearchResults : for doc in results . docs : if 'entity' in doc : doc [ 'id' ] = doc [ 'entity' ] doc [ 'label' ] = doc [ 'entity_label' ] highlighting = { doc [ 'id' ] : self . _process_highlight ( results , doc ) . _asdict ( ) for doc in results . do... | Convert solr docs to biolink object |
15,946 | def autocomplete ( self ) : params = self . set_lay_params ( ) logging . info ( "PARAMS=" + str ( params ) ) results = self . solr . search ( ** params ) logging . info ( "Docs found: {}" . format ( results . hits ) ) return self . _process_layperson_results ( results ) | Execute solr query for autocomplete |
15,947 | def translate_objs ( self , d , fname ) : if fname not in d : return None v = d [ fname ] if not isinstance ( v , list ) : v = [ v ] objs = [ { 'id' : idval } for idval in v ] return objs | Translate a field whose value is expected to be a list |
15,948 | def translate_obj ( self , d , fname ) : if fname not in d : return None lf = M . label_field ( fname ) id = d [ fname ] id = self . make_canonical_identifier ( id ) obj = { 'id' : id } if id : if self . _use_amigo_schema ( self . object_category ) : iri = expand_uri ( id ) else : iri = expand_uri ( id , [ get_curie_ma... | Translate a field value from a solr document . |
15,949 | def translate_docs ( self , ds , ** kwargs ) : for d in ds : self . map_doc ( d , { } , self . invert_subject_object ) return [ self . translate_doc ( d , ** kwargs ) for d in ds ] | Translate a set of solr results |
15,950 | def translate_docs_compact ( self , ds , field_mapping = None , slim = None , map_identifiers = None , invert_subject_object = False , ** kwargs ) : amap = { } logging . info ( "Translating docs to compact form. Slim={}" . format ( slim ) ) for d in ds : self . map_doc ( d , field_mapping , invert_subject_object = inve... | Translate golr association documents to a compact representation |
15,951 | def map_id ( self , id , prefix , closure_list ) : prefixc = prefix + ':' ids = [ eid for eid in closure_list if eid . startswith ( prefixc ) ] if len ( ids ) == 0 : return id return ids [ 0 ] | Map identifiers based on an equivalence closure list . |
15,952 | def create ( self , ontology = None , subject_category = None , object_category = None , evidence = None , taxon = None , relation = None , file = None , fmt = None , skim = True ) : meta = AssociationSetMetadata ( subject_category = subject_category , object_category = object_category , taxon = taxon ) if file is not ... | creates an AssociationSet |
15,953 | def create_from_assocs ( self , assocs , ** args ) : amap = defaultdict ( list ) subject_label_map = { } for a in assocs : subj = a [ 'subject' ] subj_id = subj [ 'id' ] subj_label = subj [ 'label' ] subject_label_map [ subj_id ] = subj_label if not a [ 'negated' ] : amap [ subj_id ] . append ( a [ 'object' ] [ 'id' ] ... | Creates from a list of association objects |
15,954 | def create_from_file ( self , file = None , fmt = 'gaf' , skim = True , ** args ) : if fmt is not None and not fmt . startswith ( '.' ) : fmt = '.{}' . format ( fmt ) d = { '.gaf' : GafParser , '.gpad' : GpadParser , '.hpoa' : HpoaParser , } if fmt is None : filename = file if isinstance ( file , str ) else file . name... | Creates from a file . If fmt is set to None then the file suffixes will be used to choose a parser . |
15,955 | def create_from_remote_file ( self , group , snapshot = True , ** args ) : import requests url = "http://snapshot.geneontology.org/annotations/{}.gaf.gz" . format ( group ) r = requests . get ( url , stream = True , headers = { 'User-Agent' : get_user_agent ( modules = [ requests ] , caller_name = __name__ ) } ) p = Ga... | Creates from remote GAF |
15,956 | def render ( ont , query_ids , args ) : if args . slim . find ( 'm' ) > - 1 : logging . info ( "SLIMMING" ) g = get_minimal_subgraph ( g , query_ids ) w = GraphRenderer . create ( args . to ) if args . showdefs : w . config . show_text_definition = True if args . render : if 'd' in args . render : logging . info ( "Sho... | Writes or displays graph |
15,957 | def get_object_closure ( subject , object_category = None , ** kwargs ) : results = search_associations ( subject = subject , object_category = object_category , select_fields = [ ] , facet_fields = [ M . OBJECT_CLOSURE ] , facet_limit = - 1 , rows = 0 , ** kwargs ) return set ( results [ 'facet_counts' ] [ M . OBJECT_... | Find all terms used to annotate subject plus ancestors |
15,958 | def namespace_to_taxon ( ) -> Dict [ str , Node ] : human_taxon = Node ( id = 'NCBITaxon:9606' , label = 'Homo sapiens' ) return { 'MGI' : Node ( id = 'NCBITaxon:10090' , label = 'Mus musculus' ) , 'MONDO' : human_taxon , 'OMIM' : human_taxon , 'MONARCH' : human_taxon , 'HGNC' : human_taxon , 'FlyBase' : Node ( id = 'N... | namespace to taxon mapping |
15,959 | def get_scigraph_nodes ( id_list ) -> Iterator [ Dict ] : scigraph = OntologyFactory ( ) . create ( 'scigraph:data' ) chunks = [ id_list [ i : i + 400 ] for i in range ( 0 , len ( list ( id_list ) ) , 400 ) ] for chunk in chunks : params = { 'id' : chunk , 'depth' : 0 } try : result_graph = scigraph . _neighbors_graph ... | Queries scigraph neighbors to get a list of nodes back |
15,960 | def get_taxon ( id : str ) -> Optional [ Node ] : taxon = None namespace = id . split ( ":" ) [ 0 ] if namespace in namespace_to_taxon ( ) : taxon = namespace_to_taxon ( ) [ namespace ] return taxon | get taxon for id |
15,961 | def typed_node_from_id ( id : str ) -> TypedNode : filter_out_types = [ 'cliqueLeader' , 'Class' , 'Node' , 'Individual' , 'quality' , 'sequence feature' ] node = next ( get_scigraph_nodes ( [ id ] ) ) if 'lbl' in node : label = node [ 'lbl' ] else : label = None types = [ typ . lower ( ) for typ in node [ 'meta' ] [ '... | Get typed node from id |
15,962 | def to_report_json ( self ) : return self . reporter . json ( self . n_lines , self . n_assocs , self . skipped ) | Generate a summary in json format |
15,963 | def to_markdown ( self ) : json = self . to_report_json ( ) s = "# Group: {group} - Dataset: {dataset}\n" . format ( group = json [ "group" ] , dataset = json [ "dataset" ] ) s += "\n## SUMMARY\n\n" s += "This report generated on {}\n\n" . format ( datetime . date . today ( ) ) s += " * Associations: {}\n" . format ( ... | Generate a summary in markdown format |
15,964 | def parse ( self , file , skipheader = False , outfile = None ) : associations = self . association_generator ( file , skipheader = skipheader , outfile = outfile ) a = list ( associations ) return a | Parse a line - oriented association file into a list of association dict objects |
15,965 | def association_generator ( self , file , skipheader = False , outfile = None ) -> Dict : file = self . _ensure_file ( file ) for line in file : parsed_result = self . parse_line ( line ) self . report . report_parsed_result ( parsed_result , outfile , self . config . filtered_evidence_file , self . config . filter_out... | Returns a generator that yields successive associations from file |
15,966 | def map_to_subset ( self , file , outfile = None , ontology = None , subset = None , class_map = None , relations = None ) : if subset is not None : logging . info ( "Creating mapping for subset: {}" . format ( subset ) ) class_map = ontology . create_slim_mapping ( subset = subset , relations = relations ) if class_ma... | Map a file to a subset writing out results |
15,967 | def get_config ( ) : if session . config is None : path = session . default_config_path if os . path . isfile ( path ) : logging . info ( "LOADING FROM: {}" . format ( path ) ) session . config = load_config ( path ) else : session . config = Config ( ) logging . info ( "using default session: {}, path does not exist: ... | Return configuration for current session . |
15,968 | def set_config ( path ) : logging . info ( "LOADING FROM: {}" . format ( path ) ) session . config = load_config ( path ) return session . config | Set configuration for current session . |
15,969 | def get_solr_search_url ( self , use_amigo = False ) : url = self . endpoint_url ( self . solr_search ) if use_amigo : url = self . endpoint_url ( self . amigo_solr_search ) return url | Return solr URL to be used for lexical entity searches |
15,970 | def download_source_gafs ( group_metadata , target_dir , exclusions = [ ] , base_download_url = None ) : gaf_urls = [ ( data , data [ "source" ] ) for data in group_metadata [ "datasets" ] if data [ "type" ] == "gaf" and data [ "dataset" ] not in exclusions ] click . echo ( "Found {}" . format ( ", " . join ( [ kv [ 0 ... | This looks at a group metadata dictionary and downloads each GAF source that is not in the exclusions list . For each downloaded file keep track of the path of the file . If the file is zipped it will unzip it here . This function returns a list of tuples of the dataset dictionary mapped to the downloaded source path . |
15,971 | def get_annotation_sufficiency ( self , profile : List [ str ] , negated_classes : List [ str ] , categories : Optional [ List ] = None , negation_weight : Optional [ float ] = .25 , category_weight : Optional [ float ] = .5 ) -> AnnotationSufficiency : if categories is None : categories = [ enum . value for enum in Hp... | Given a list of individuals return the simple scaled and categorical scores |
15,972 | def _get_scaled_score ( simple_score : float , categorical_score : float , category_weight : Optional [ float ] = .5 ) -> float : return np . average ( [ simple_score , categorical_score ] , weights = [ 1 , category_weight ] ) | Scaled score is the weighted average of the simple score and categorical score |
15,973 | def _get_categorical_score ( self , profile : List , negated_classes : List , categories : List , negation_weight : Optional [ float ] = 1 , ic_map : Optional [ Dict [ str , float ] ] = None ) -> float : if ic_map is None : ic_map = self . ic_store . get_profile_ic ( profile + negated_classes ) scores = [ ] for cat in ... | The average of the simple scores across a list of categories |
15,974 | def write_entity ( self , entity ) : db , db_object_id = self . _split_prefix ( entity ) taxon = normalize_taxon ( entity [ "taxon" ] [ "id" ] ) vals = [ db , db_object_id , entity . get ( 'label' ) , entity . get ( 'full_name' ) , entity . get ( 'synonyms' ) , entity . get ( 'type' ) , taxon , entity . get ( 'parents'... | Write a single entity to a line in the output file |
15,975 | def search ( self , id_list : Iterable , negated_classes : Iterable , limit : Optional [ int ] , method : Optional ) -> List [ SimResult ] : pass | Given an input list of classes searches for similar lists of classes and provides a ranked list of matches |
15,976 | def filtered_search ( self , id_list : Iterable , negated_classes : Iterable , limit : Optional [ int ] , taxon_filter : Optional , category_filter : Optional , method : Optional ) -> SimResult : pass | Given an input iterable of classes or individuals provides a ranking of similar profiles |
15,977 | def index_ontology ( self , ont ) : self . merged_ontology . merge ( [ ont ] ) syns = ont . all_synonyms ( include_label = True ) include_id = self . _is_meaningful_ids ( ) logging . info ( "Include IDs as synonyms: {}" . format ( include_id ) ) if include_id : for n in ont . nodes ( ) : v = n if v . startswith ( 'http... | Adds an ontology to the index |
15,978 | def index_synonym ( self , syn , ont ) : if not syn . val : if syn . pred == 'label' : if not self . _is_meaningful_ids ( ) : if not ont . is_obsolete ( syn . class_id ) : pass else : logging . warning ( "Incomplete syn: {}" . format ( syn ) ) return if self . exclude_obsolete and ont . is_obsolete ( syn . class_id ) :... | Index a synonym |
15,979 | def _normalize_label ( self , s , wsmap ) : toks = [ ] for tok in list ( set ( self . npattern . sub ( ' ' , s ) . split ( ' ' ) ) ) : if tok in wsmap : tok = wsmap [ tok ] if tok != "" : toks . append ( tok ) toks . sort ( ) return " " . join ( toks ) | normalized form of a synonym |
15,980 | def _sim ( self , xg , ancs1 , ancs2 , pfx1 , pfx2 ) : xancs1 = set ( ) for a in ancs1 : if a in xg : for n in xg . neighbors ( a ) : pfx = self . _id_to_ontology ( n ) if pfx == pfx2 : xancs1 . add ( n ) logging . debug ( 'SIM={}/{} ## {}' . format ( len ( xancs1 . intersection ( ancs2 ) ) , len ( xancs1 ) , xancs1 . ... | Compare two lineages |
15,981 | def compare_to_xrefs ( self , xg1 , xg2 ) : ont = self . merged_ontology for ( i , j , d ) in xg1 . edges ( data = True ) : ont_left = self . _id_to_ontology ( i ) ont_right = self . _id_to_ontology ( j ) unique_lr = True num_xrefs_left = 0 same_left = False if i in xg2 : for j2 in xg2 . neighbors ( i ) : ont_right2 = ... | Compares a base xref graph with another one |
15,982 | def assign_best_matches ( self , xg ) : logging . info ( "assigning best matches for {} nodes" . format ( len ( xg . nodes ( ) ) ) ) for i in xg . nodes ( ) : xrefmap = self . _neighborscores_by_ontology ( xg , i ) for ( ontid , score_node_pairs ) in xrefmap . items ( ) : score_node_pairs . sort ( reverse = True ) ( be... | For each node in the xref graph tag best match edges |
15,983 | def _best_match_syn ( self , sx , sys , scope_map ) : SUBSTRING_WEIGHT = 0.2 WBEST = None sbest = None sxv = self . _standardize_label ( sx . val ) sxp = self . _id_to_ontology ( sx . class_id ) for sy in sys : syv = self . _standardize_label ( sy . val ) syp = self . _id_to_ontology ( sy . class_id ) W = None if sxv =... | The best match is determined by the highest magnitude weight |
15,984 | def grouped_mappings ( self , id ) : g = self . get_xref_graph ( ) m = { } for n in g . neighbors ( id ) : [ prefix , local ] = n . split ( ':' ) if prefix not in m : m [ prefix ] = [ ] m [ prefix ] . append ( n ) return m | return all mappings for a node grouped by ID prefix |
15,985 | def cliques ( self , xg ) : g = nx . DiGraph ( ) for ( x , y ) in self . merged_ontology . get_graph ( ) . edges ( ) : g . add_edge ( x , y ) for ( x , y ) in xg . edges ( ) : g . add_edge ( x , y ) g . add_edge ( y , x ) return list ( strongly_connected_components ( g ) ) | Return all equivalence set cliques assuming each edge in the xref graph is treated as equivalent and all edges in ontology are subClassOf |
15,986 | def add_triples ( self , ontol ) : rg = self . rdfgraph g = ontol . get_graph ( ) typemap = { } inds = rg . subjects ( RDF . type , OWL . NamedIndividual ) for s in inds : for ( s , p , o ) in rg . triples ( ( s , None , None ) ) : s_id = id ( s ) p_id = id ( p ) g . add_node ( s_id ) if isinstance ( o , URIRef ) : o_i... | Adds triples to an ontology object . |
15,987 | def write ( self , ontol , ** args ) : s = self . render ( ontol , ** args ) if self . outfile is None : print ( s ) else : f = open ( self . outfile , 'w' ) f . write ( s ) f . close ( ) | Write a ontology object |
15,988 | def render_subgraph ( self , ontol , nodes , ** args ) : subont = ontol . subontology ( nodes , ** args ) return self . render ( subont , ** args ) | Render a ontology object after inducing a subgraph |
15,989 | def write_subgraph ( self , ontol , nodes , ** args ) : subont = ontol . subontology ( nodes , ** args ) self . write ( subont , ** args ) | Write a ontology object after inducing a subgraph |
15,990 | def render_relation ( self , r , ** args ) : if r is None : return "." m = self . config . relsymbolmap if r in m : return m [ r ] return r | Render an object property |
15,991 | def render_noderef ( self , ontol , n , query_ids = None , ** args ) : if query_ids is None : query_ids = [ ] marker = "" if n in query_ids : marker = " * " label = ontol . label ( n ) s = None if label is not None : s = '{} ! {}{}' . format ( n , label , marker ) else : s = str ( n ) if self . config . show_text_defin... | Render a node object |
15,992 | def create ( fmt ) : w = None if fmt == 'tree' : w = AsciiTreeGraphRenderer ( ) elif fmt == 'dot' : w = DotGraphRenderer ( image_format = 'dot' ) elif fmt == 'png' : w = DotGraphRenderer ( image_format = 'png' ) elif fmt == 'ndot' : w = NativeDotGraphRenderer ( ) elif fmt == 'obo' : w = OboFormatGraphRenderer ( ) elif ... | Creates a GraphRenderer |
15,993 | def get_user_agent ( name = "ontobio" , version = ontobio_version , modules = None , caller_name = None ) : user_agent_array = [ "{}/{}" . format ( name , version ) ] if modules : module_info_array = [ ] for m in modules : mod_name = m . __name__ mod_version = None if hasattr ( m , 'get_version' ) : mod_version = m . g... | Create a User - Agent string |
15,994 | def search ( self , id_list : List , negated_classes : List , limit : Optional [ int ] , method : Optional ) -> List [ SimResult ] : raise NotImplementedError | Given an input list of classes or individuals provides a ranking of similar profiles |
15,995 | def convert_association ( self , association : Association ) -> Entity : if "header" not in association or association [ "header" ] == False : gpi_obj = { 'id' : association [ "subject" ] [ "id" ] , 'label' : association [ "subject" ] [ "label" ] , 'full_name' : association [ "subject" ] [ "fullname" ] , 'synonyms' : a... | id is already join ed in both the Association and the Entity so we don t have to worry about what that looks like . We assume it s correct . |
15,996 | def get_filtered_graph ( self , relations = None , prefix = None ) : self . all_synonyms ( ) self . all_obsoletes ( ) srcg = self . get_graph ( ) if prefix is not None : srcg = srcg . subgraph ( [ n for n in srcg . nodes ( ) if n . startswith ( prefix + ":" ) ] ) if relations is None : logger . info ( "No filtering on ... | Returns a networkx graph for the whole ontology for a subset of relations |
15,997 | def merge ( self , ontologies ) : if self . xref_graph is None : self . xref_graph = nx . MultiGraph ( ) logger . info ( "Merging source: {} xrefs: {}" . format ( self , len ( self . xref_graph . edges ( ) ) ) ) for ont in ontologies : logger . info ( "Merging {} into {}" . format ( ont , self ) ) g = self . get_graph ... | Merges specified ontology into current ontology |
15,998 | def subontology ( self , nodes = None , minimal = False , relations = None ) : g = None if nodes is not None : g = self . subgraph ( nodes ) else : g = self . get_graph ( ) if minimal : from ontobio . slimmer import get_minimal_subgraph g = get_minimal_subgraph ( g , nodes ) ont = Ontology ( graph = g , xref_graph = se... | Return a new ontology that is an extract of this one |
15,999 | def create_slim_mapping ( self , subset = None , subset_nodes = None , relations = None , disable_checks = False ) : if subset is not None : subset_nodes = self . extract_subset ( subset ) logger . info ( "Extracting subset: {} -> {}" . format ( subset , subset_nodes ) ) if subset_nodes is None or len ( subset_nodes ) ... | Create a dictionary that maps between all nodes in an ontology to a subset |
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