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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.save | def save(self, model_fname='model.pkl'):
"""Save the state of the IncrementalModel in a pickle file.
Parameters
----------
model_fname : Optional[str]
The name of the pickle file to save the state of the
IncrementalModel in. Default: model.pkl
"""
... | python | def save(self, model_fname='model.pkl'):
"""Save the state of the IncrementalModel in a pickle file.
Parameters
----------
model_fname : Optional[str]
The name of the pickle file to save the state of the
IncrementalModel in. Default: model.pkl
"""
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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.add_statements | def add_statements(self, pmid, stmts):
"""Add INDRA Statements to the incremental model indexed by PMID.
Parameters
----------
pmid : str
The PMID of the paper from which statements were extracted.
stmts : list[indra.statements.Statement]
A list of INDRA ... | python | def add_statements(self, pmid, stmts):
"""Add INDRA Statements to the incremental model indexed by PMID.
Parameters
----------
pmid : str
The PMID of the paper from which statements were extracted.
stmts : list[indra.statements.Statement]
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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.preassemble | def preassemble(self, filters=None, grounding_map=None):
"""Preassemble the Statements collected in the model.
Use INDRA's GroundingMapper, Preassembler and BeliefEngine
on the IncrementalModel and save the unique statements and
the top level statements in class attributes.
Cur... | python | def preassemble(self, filters=None, grounding_map=None):
"""Preassemble the Statements collected in the model.
Use INDRA's GroundingMapper, Preassembler and BeliefEngine
on the IncrementalModel and save the unique statements and
the top level statements in class attributes.
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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.get_model_agents | def get_model_agents(self):
"""Return a list of all Agents from all Statements.
Returns
-------
agents : list[indra.statements.Agent]
A list of Agents that are in the model.
"""
model_stmts = self.get_statements()
agents = []
for stmt in model_... | python | def get_model_agents(self):
"""Return a list of all Agents from all Statements.
Returns
-------
agents : list[indra.statements.Agent]
A list of Agents that are in the model.
"""
model_stmts = self.get_statements()
agents = []
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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.get_statements | def get_statements(self):
"""Return a list of all Statements in a single list.
Returns
-------
stmts : list[indra.statements.Statement]
A list of all the INDRA Statements in the model.
"""
stmt_lists = [v for k, v in self.stmts.items()]
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... | python | def get_statements(self):
"""Return a list of all Statements in a single list.
Returns
-------
stmts : list[indra.statements.Statement]
A list of all the INDRA Statements in the model.
"""
stmt_lists = [v for k, v in self.stmts.items()]
stmts = []
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sorgerlab/indra | indra/tools/incremental_model.py | IncrementalModel.get_statements_noprior | def get_statements_noprior(self):
"""Return a list of all non-prior Statements in a single list.
Returns
-------
stmts : list[indra.statements.Statement]
A list of all the INDRA Statements in the model (excluding
the prior).
"""
stmt_lists = [v fo... | python | def get_statements_noprior(self):
"""Return a list of all non-prior Statements in a single list.
Returns
-------
stmts : list[indra.statements.Statement]
A list of all the INDRA Statements in the model (excluding
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"""
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sorgerlab/indra | indra/sources/bel/api.py | process_ndex_neighborhood | def process_ndex_neighborhood(gene_names, network_id=None,
rdf_out='bel_output.rdf', print_output=True):
"""Return a BelRdfProcessor for an NDEx network neighborhood.
Parameters
----------
gene_names : list
A list of HGNC gene symbols to search the neighborhood of.... | python | def process_ndex_neighborhood(gene_names, network_id=None,
rdf_out='bel_output.rdf', print_output=True):
"""Return a BelRdfProcessor for an NDEx network neighborhood.
Parameters
----------
gene_names : list
A list of HGNC gene symbols to search the neighborhood of.... | [
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sorgerlab/indra | indra/sources/bel/api.py | process_pybel_neighborhood | def process_pybel_neighborhood(gene_names, network_file=None,
network_type='belscript', **kwargs):
"""Return PybelProcessor around neighborhood of given genes in a network.
This function processes the given network file and filters the returned
Statements to ones that contain... | python | def process_pybel_neighborhood(gene_names, network_file=None,
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"""Return PybelProcessor around neighborhood of given genes in a network.
This function processes the given network file and filters the returned
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sorgerlab/indra | indra/sources/bel/api.py | process_pybel_graph | def process_pybel_graph(graph):
"""Return a PybelProcessor by processing a PyBEL graph.
Parameters
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graph : pybel.struct.BELGraph
A PyBEL graph to process
Returns
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bp : PybelProcessor
A PybelProcessor object which contains INDRA Statements in
bp.sta... | python | def process_pybel_graph(graph):
"""Return a PybelProcessor by processing a PyBEL graph.
Parameters
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graph : pybel.struct.BELGraph
A PyBEL graph to process
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bp : PybelProcessor
A PybelProcessor object which contains INDRA Statements in
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sorgerlab/indra | indra/sources/bel/api.py | process_belscript | def process_belscript(file_name, **kwargs):
"""Return a PybelProcessor by processing a BEL script file.
Key word arguments are passed directly to pybel.from_path,
for further information, see
pybel.readthedocs.io/en/latest/io.html#pybel.from_path
Some keyword arguments we use here differ from the d... | python | def process_belscript(file_name, **kwargs):
"""Return a PybelProcessor by processing a BEL script file.
Key word arguments are passed directly to pybel.from_path,
for further information, see
pybel.readthedocs.io/en/latest/io.html#pybel.from_path
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sorgerlab/indra | indra/sources/bel/api.py | process_json_file | def process_json_file(file_name):
"""Return a PybelProcessor by processing a Node-Link JSON file.
For more information on this format, see:
http://pybel.readthedocs.io/en/latest/io.html#node-link-json
Parameters
----------
file_name : str
The path to a Node-Link JSON file.
Returns... | python | def process_json_file(file_name):
"""Return a PybelProcessor by processing a Node-Link JSON file.
For more information on this format, see:
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The path to a Node-Link JSON file.
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sorgerlab/indra | indra/sources/bel/api.py | process_cbn_jgif_file | def process_cbn_jgif_file(file_name):
"""Return a PybelProcessor by processing a CBN JGIF JSON file.
Parameters
----------
file_name : str
The path to a CBN JGIF JSON file.
Returns
-------
bp : PybelProcessor
A PybelProcessor object which contains INDRA Statements in
... | python | def process_cbn_jgif_file(file_name):
"""Return a PybelProcessor by processing a CBN JGIF JSON file.
Parameters
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file_name : str
The path to a CBN JGIF JSON file.
Returns
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bp : PybelProcessor
A PybelProcessor object which contains INDRA Statements in
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sorgerlab/indra | indra/resources/update_resources.py | update_famplex | def update_famplex():
"""Update all the CSV files that form the FamPlex resource."""
famplex_url_pattern = \
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csv_names = ['entities', 'equivalences', 'gene_prefixes',
'grounding_map', 'relations']
for csv_name i... | python | def update_famplex():
"""Update all the CSV files that form the FamPlex resource."""
famplex_url_pattern = \
'https://raw.githubusercontent.com/sorgerlab/famplex/master/%s.csv'
csv_names = ['entities', 'equivalences', 'gene_prefixes',
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sorgerlab/indra | indra/resources/update_resources.py | update_lincs_small_molecules | def update_lincs_small_molecules():
"""Load the csv of LINCS small molecule metadata into a dict.
Produces a dict keyed by HMS LINCS small molecule ids, with the metadata
contained in a dict of row values keyed by the column headers extracted
from the csv.
"""
url = 'http://lincs.hms.harvard.ed... | python | def update_lincs_small_molecules():
"""Load the csv of LINCS small molecule metadata into a dict.
Produces a dict keyed by HMS LINCS small molecule ids, with the metadata
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sorgerlab/indra | indra/resources/update_resources.py | update_lincs_proteins | def update_lincs_proteins():
"""Load the csv of LINCS protein metadata into a dict.
Produces a dict keyed by HMS LINCS protein ids, with the metadata
contained in a dict of row values keyed by the column headers extracted
from the csv.
"""
url = 'http://lincs.hms.harvard.edu/db/proteins/'
p... | python | def update_lincs_proteins():
"""Load the csv of LINCS protein metadata into a dict.
Produces a dict keyed by HMS LINCS protein ids, with the metadata
contained in a dict of row values keyed by the column headers extracted
from the csv.
"""
url = 'http://lincs.hms.harvard.edu/db/proteins/'
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sorgerlab/indra | indra/assemblers/index_card/assembler.py | _get_is_direct | def _get_is_direct(stmt):
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sorgerlab/indra | indra/assemblers/index_card/assembler.py | IndexCardAssembler.make_model | def make_model(self):
"""Assemble statements into index cards."""
for stmt in self.statements:
if isinstance(stmt, Modification):
card = assemble_modification(stmt)
elif isinstance(stmt, SelfModification):
card = assemble_selfmodification(stmt)
... | python | def make_model(self):
"""Assemble statements into index cards."""
for stmt in self.statements:
if isinstance(stmt, Modification):
card = assemble_modification(stmt)
elif isinstance(stmt, SelfModification):
card = assemble_selfmodification(stmt)
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sorgerlab/indra | indra/assemblers/index_card/assembler.py | IndexCardAssembler.print_model | def print_model(self):
"""Return the assembled cards as a JSON string.
Returns
-------
cards_json : str
The JSON string representing the assembled cards.
"""
cards = [c.card for c in self.cards]
# If there is only one card, print it as a single
... | python | def print_model(self):
"""Return the assembled cards as a JSON string.
Returns
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cards_json : str
The JSON string representing the assembled cards.
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cards = [c.card for c in self.cards]
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sorgerlab/indra | indra/sources/geneways/processor.py | geneways_action_to_indra_statement_type | def geneways_action_to_indra_statement_type(actiontype, plo):
"""Return INDRA Statement corresponding to Geneways action type.
Parameters
----------
actiontype : str
The verb extracted by the Geneways processor
plo : str
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"""Return INDRA Statement corresponding to Geneways action type.
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actiontype : str
The verb extracted by the Geneways processor
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sorgerlab/indra | indra/sources/geneways/processor.py | GenewaysProcessor.make_statement | def make_statement(self, action, mention):
"""Makes an INDRA statement from a Geneways action and action mention.
Parameters
----------
action : GenewaysAction
The mechanism that the Geneways mention maps to. Note that
several text mentions can correspond to the ... | python | def make_statement(self, action, mention):
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----------
action : GenewaysAction
The mechanism that the Geneways mention maps to. Note that
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.load_from_rdf_file | def load_from_rdf_file(self, rdf_file):
"""Initialize given an RDF input file representing the hierarchy."
Parameters
----------
rdf_file : str
Path to an RDF file.
"""
self.graph = rdflib.Graph()
self.graph.parse(os.path.abspath(rdf_file), format='nt... | python | def load_from_rdf_file(self, rdf_file):
"""Initialize given an RDF input file representing the hierarchy."
Parameters
----------
rdf_file : str
Path to an RDF file.
"""
self.graph = rdflib.Graph()
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.load_from_rdf_string | def load_from_rdf_string(self, rdf_str):
"""Initialize given an RDF string representing the hierarchy."
Parameters
----------
rdf_str : str
An RDF string.
"""
self.graph = rdflib.Graph()
self.graph.parse(data=rdf_str, format='nt')
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"""Initialize given an RDF string representing the hierarchy."
Parameters
----------
rdf_str : str
An RDF string.
"""
self.graph = rdflib.Graph()
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.extend_with | def extend_with(self, rdf_file):
"""Extend the RDF graph of this HierarchyManager with another RDF file.
Parameters
----------
rdf_file : str
An RDF file which is parsed such that the current graph and the
graph described by the file are merged.
"""
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"""Extend the RDF graph of this HierarchyManager with another RDF file.
Parameters
----------
rdf_file : str
An RDF file which is parsed such that the current graph and the
graph described by the file are merged.
"""
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.build_transitive_closures | def build_transitive_closures(self):
"""Build the transitive closures of the hierarchy.
This method constructs dictionaries which contain terms in the
hierarchy as keys and either all the "isa+" or "partof+" related terms
as values.
"""
self.component_counter = 0
... | python | def build_transitive_closures(self):
"""Build the transitive closures of the hierarchy.
This method constructs dictionaries which contain terms in the
hierarchy as keys and either all the "isa+" or "partof+" related terms
as values.
"""
self.component_counter = 0
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.build_transitive_closure | def build_transitive_closure(self, rel, tc_dict):
"""Build a transitive closure for a given relation in a given dict."""
# Make a function with the righ argument structure
rel_fun = lambda node, graph: rel(node)
for x in self.graph.all_nodes():
rel_closure = self.graph.transi... | python | def build_transitive_closure(self, rel, tc_dict):
"""Build a transitive closure for a given relation in a given dict."""
# Make a function with the righ argument structure
rel_fun = lambda node, graph: rel(node)
for x in self.graph.all_nodes():
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.directly_or_indirectly_related | def directly_or_indirectly_related(self, ns1, id1, ns2, id2, closure_dict,
relation_func):
"""Return True if two entities have the speicified relationship.
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the two entities directly or... | python | def directly_or_indirectly_related(self, ns1, id1, ns2, id2, closure_dict,
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"""Return True if two entities have the speicified relationship.
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.isa | def isa(self, ns1, id1, ns2, id2):
"""Return True if one entity has an "isa" relationship to another.
Parameters
----------
ns1 : str
Namespace code for an entity.
id1 : string
URI for an entity.
ns2 : str
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"""Return True if one entity has an "isa" relationship to another.
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ns1 : str
Namespace code for an entity.
id1 : string
URI for an entity.
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.partof | def partof(self, ns1, id1, ns2, id2):
"""Return True if one entity is "partof" another.
Parameters
----------
ns1 : str
Namespace code for an entity.
id1 : str
URI for an entity.
ns2 : str
Namespace code for an entity.
id2 : st... | python | def partof(self, ns1, id1, ns2, id2):
"""Return True if one entity is "partof" another.
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----------
ns1 : str
Namespace code for an entity.
id1 : str
URI for an entity.
ns2 : str
Namespace code for an entity.
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.isa_or_partof | def isa_or_partof(self, ns1, id1, ns2, id2):
"""Return True if two entities are in an "isa" or "partof" relationship
Parameters
----------
ns1 : str
Namespace code for an entity.
id1 : str
URI for an entity.
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Namespace code for an entity.
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URI for an entity.
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ns1 : str
Namespace code for an entity.
id1 : str
URI for an entity.
ns2 : str
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Namespace code for an entity.
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sorgerlab/indra | indra/preassembler/hierarchy_manager.py | HierarchyManager.get_parents | def get_parents(self, uri, type='all'):
"""Return parents of a given entry.
Parameters
----------
uri : str
The URI of the entry whose parents are to be returned. See the
get_uri method to construct this URI from a name space and id.
type : str
... | python | def get_parents(self, uri, type='all'):
"""Return parents of a given entry.
Parameters
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uri : str
The URI of the entry whose parents are to be returned. See the
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sorgerlab/indra | indra/sources/trips/drum_reader.py | _get_perf | def _get_perf(text, msg_id):
"""Return a request message for a given text."""
msg = KQMLPerformative('REQUEST')
msg.set('receiver', 'READER')
content = KQMLList('run-text')
content.sets('text', text)
msg.set('content', content)
msg.set('reply-with', msg_id)
return msg | python | def _get_perf(text, msg_id):
"""Return a request message for a given text."""
msg = KQMLPerformative('REQUEST')
msg.set('receiver', 'READER')
content = KQMLList('run-text')
content.sets('text', text)
msg.set('content', content)
msg.set('reply-with', msg_id)
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sorgerlab/indra | indra/sources/trips/drum_reader.py | DrumReader.read_pmc | def read_pmc(self, pmcid):
"""Read a given PMC article.
Parameters
----------
pmcid : str
The PMC ID of the article to read. Note that only
articles in the open-access subset of PMC will work.
"""
msg = KQMLPerformative('REQUEST')
msg.set(... | python | def read_pmc(self, pmcid):
"""Read a given PMC article.
Parameters
----------
pmcid : str
The PMC ID of the article to read. Note that only
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sorgerlab/indra | indra/sources/trips/drum_reader.py | DrumReader.read_text | def read_text(self, text):
"""Read a given text phrase.
Parameters
----------
text : str
The text to read. Typically a sentence or a paragraph.
"""
logger.info('Reading: "%s"' % text)
msg_id = 'RT000%s' % self.msg_counter
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"""Read a given text phrase.
Parameters
----------
text : str
The text to read. Typically a sentence or a paragraph.
"""
logger.info('Reading: "%s"' % text)
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sorgerlab/indra | indra/sources/trips/drum_reader.py | DrumReader.receive_reply | def receive_reply(self, msg, content):
"""Handle replies with reading results."""
reply_head = content.head()
if reply_head == 'error':
comment = content.gets('comment')
logger.error('Got error reply: "%s"' % comment)
else:
extractions = content.gets('... | python | def receive_reply(self, msg, content):
"""Handle replies with reading results."""
reply_head = content.head()
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sorgerlab/indra | indra/sources/hume/visualize_causal.py | split_long_sentence | def split_long_sentence(sentence, words_per_line):
"""Takes a sentence and adds a newline every "words_per_line" words.
Parameters
----------
sentence: str
Sentene to split
words_per_line: double
Add a newline every this many words
"""
words = sentence.split(' ')
split_s... | python | def split_long_sentence(sentence, words_per_line):
"""Takes a sentence and adds a newline every "words_per_line" words.
Parameters
----------
sentence: str
Sentene to split
words_per_line: double
Add a newline every this many words
"""
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sorgerlab/indra | indra/sources/hume/visualize_causal.py | shorter_name | def shorter_name(key):
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sorgerlab/indra | indra/sources/hume/visualize_causal.py | add_event_property_edges | def add_event_property_edges(event_entity, entries):
"""Adds edges to the graph for event properties."""
do_not_log = ['@type', '@id',
'http://worldmodelers.com/DataProvenance#sourced_from']
for prop in event_entity:
if prop not in do_not_log:
value = event_entity[prop]
... | python | def add_event_property_edges(event_entity, entries):
"""Adds edges to the graph for event properties."""
do_not_log = ['@type', '@id',
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sorgerlab/indra | indra/sources/hume/visualize_causal.py | get_sourced_from | def get_sourced_from(entry):
"""Get a list of values from the source_from attribute"""
sourced_from = 'http://worldmodelers.com/DataProvenance#sourced_from'
if sourced_from in entry:
values = entry[sourced_from]
values = [i['@id'] for i in values]
return values | python | def get_sourced_from(entry):
"""Get a list of values from the source_from attribute"""
sourced_from = 'http://worldmodelers.com/DataProvenance#sourced_from'
if sourced_from in entry:
values = entry[sourced_from]
values = [i['@id'] for i in values]
return values | [
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sorgerlab/indra | indra/sources/hume/visualize_causal.py | get_entry_compact_text_repr | def get_entry_compact_text_repr(entry, entries):
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If the entry has a source_from value, return the text value of the source.
Otherwise, return None."""
text = get_shortest_text_value(entry)
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text = get_shortest_text_value(entry)
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sorgerlab/indra | indra/sources/sparser/api.py | process_text | def process_text(text, output_fmt='json', outbuf=None, cleanup=True, key='',
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"""Return processor with Statements extracted by reading text with Sparser.
Parameters
----------
text : str
The text to be processed
output_fmt: Optional[str]
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text : str
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nxml_str : str
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----------
fname : str
The path to the NXML file to be read.
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The path to the NXML file to be read.
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sorgerlab/indra | indra/sources/sparser/api.py | process_sparser_output | def process_sparser_output(output_fname, output_fmt='json'):
"""Return a processor with Statements extracted from Sparser XML or JSON
Parameters
----------
output_fname : str
The path to the Sparser output file to be processed. The file can
either be JSON or XML output from Sparser, wit... | python | def process_sparser_output(output_fname, output_fmt='json'):
"""Return a processor with Statements extracted from Sparser XML or JSON
Parameters
----------
output_fname : str
The path to the Sparser output file to be processed. The file can
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"""Return processor with Statements extracted from a Sparser XML.
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----------
xml_str : str
The XML string obtained by reading content with Sparser, using the
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Returns
-------
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A SparserXM... | python | def process_xml(xml_str):
"""Return processor with Statements extracted from a Sparser XML.
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xml_str : str
The XML string obtained by reading content with Sparser, using the
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sorgerlab/indra | indra/sources/sparser/api.py | run_sparser | def run_sparser(fname, output_fmt, outbuf=None, timeout=600):
"""Return the path to reading output after running Sparser reading.
Parameters
----------
fname : str
The path to an input file to be processed. Due to the Spaser
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"""Return the path to reading output after running Sparser reading.
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fname : str
The path to an input file to be processed. Due to the Spaser
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sorgerlab/indra | indra/sources/sparser/api.py | get_version | def get_version():
"""Return the version of the Sparser executable on the path.
Returns
-------
version : str
The version of Sparser that is found on the Sparser path.
"""
assert sparser_path is not None, "Sparser path is not defined."
with open(os.path.join(sparser_path, 'version.t... | python | def get_version():
"""Return the version of the Sparser executable on the path.
Returns
-------
version : str
The version of Sparser that is found on the Sparser path.
"""
assert sparser_path is not None, "Sparser path is not defined."
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sorgerlab/indra | indra/sources/sparser/api.py | make_nxml_from_text | def make_nxml_from_text(text):
"""Return raw text wrapped in NXML structure.
Parameters
----------
text : str
The raw text content to be wrapped in an NXML structure.
Returns
-------
nxml_str : str
The NXML string wrapping the raw text input.
"""
text = _escape_xml(... | python | def make_nxml_from_text(text):
"""Return raw text wrapped in NXML structure.
Parameters
----------
text : str
The raw text content to be wrapped in an NXML structure.
Returns
-------
nxml_str : str
The NXML string wrapping the raw text input.
"""
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sorgerlab/indra | indra/databases/hgnc_client.py | get_hgnc_name | def get_hgnc_name(hgnc_id):
"""Return the HGNC symbol corresponding to the given HGNC ID.
Parameters
----------
hgnc_id : str
The HGNC ID to be converted.
Returns
-------
hgnc_name : str
The HGNC symbol corresponding to the given HGNC ID.
"""
try:
hgnc_name ... | python | def get_hgnc_name(hgnc_id):
"""Return the HGNC symbol corresponding to the given HGNC ID.
Parameters
----------
hgnc_id : str
The HGNC ID to be converted.
Returns
-------
hgnc_name : str
The HGNC symbol corresponding to the given HGNC ID.
"""
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sorgerlab/indra | indra/databases/hgnc_client.py | get_hgnc_entry | def get_hgnc_entry(hgnc_id):
"""Return the HGNC entry for the given HGNC ID from the web service.
Parameters
----------
hgnc_id : str
The HGNC ID to be converted.
Returns
-------
xml_tree : ElementTree
The XML ElementTree corresponding to the entry for the
given HGN... | python | def get_hgnc_entry(hgnc_id):
"""Return the HGNC entry for the given HGNC ID from the web service.
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hgnc_id : str
The HGNC ID to be converted.
Returns
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xml_tree : ElementTree
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sorgerlab/indra | indra/tools/reading/util/log_analysis_tools.py | analyze_reach_log | def analyze_reach_log(log_fname=None, log_str=None):
"""Return unifinished PMIDs given a log file name."""
assert bool(log_fname) ^ bool(log_str), 'Must specify log_fname OR log_str'
started_patt = re.compile('Starting ([\d]+)')
# TODO: it might be interesting to get the time it took to read
# each ... | python | def analyze_reach_log(log_fname=None, log_str=None):
"""Return unifinished PMIDs given a log file name."""
assert bool(log_fname) ^ bool(log_str), 'Must specify log_fname OR log_str'
started_patt = re.compile('Starting ([\d]+)')
# TODO: it might be interesting to get the time it took to read
# each ... | [
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sorgerlab/indra | indra/tools/reading/util/log_analysis_tools.py | get_logs_from_db_reading | def get_logs_from_db_reading(job_prefix, reading_queue='run_db_reading_queue'):
"""Get the logs stashed on s3 for a particular reading."""
s3 = boto3.client('s3')
gen_prefix = 'reading_results/%s/logs/%s' % (job_prefix, reading_queue)
job_log_data = s3.list_objects_v2(Bucket='bigmech',
... | python | def get_logs_from_db_reading(job_prefix, reading_queue='run_db_reading_queue'):
"""Get the logs stashed on s3 for a particular reading."""
s3 = boto3.client('s3')
gen_prefix = 'reading_results/%s/logs/%s' % (job_prefix, reading_queue)
job_log_data = s3.list_objects_v2(Bucket='bigmech',
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sorgerlab/indra | indra/tools/reading/util/log_analysis_tools.py | separate_reach_logs | def separate_reach_logs(log_str):
"""Get the list of reach logs from the overall logs."""
log_lines = log_str.splitlines()
reach_logs = []
reach_lines = []
adding_reach_lines = False
for l in log_lines[:]:
if not adding_reach_lines and 'Beginning reach' in l:
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"""Get the list of reach logs from the overall logs."""
log_lines = log_str.splitlines()
reach_logs = []
reach_lines = []
adding_reach_lines = False
for l in log_lines[:]:
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sorgerlab/indra | indra/tools/reading/util/log_analysis_tools.py | get_unyielding_tcids | def get_unyielding_tcids(log_str):
"""Extract the set of tcids for which no statements were created."""
tcid_strs = re.findall('INFO: \[.*?\].*? - Got no statements for (\d+).*',
log_str)
return {int(tcid_str) for tcid_str in tcid_strs} | python | def get_unyielding_tcids(log_str):
"""Extract the set of tcids for which no statements were created."""
tcid_strs = re.findall('INFO: \[.*?\].*? - Got no statements for (\d+).*',
log_str)
return {int(tcid_str) for tcid_str in tcid_strs} | [
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sorgerlab/indra | indra/tools/reading/util/log_analysis_tools.py | analyze_db_reading | def analyze_db_reading(job_prefix, reading_queue='run_db_reading_queue'):
"""Run various analysis on a particular reading job."""
# Analyze reach failures
log_strs = get_logs_from_db_reading(job_prefix, reading_queue)
indra_log_strs = []
all_reach_logs = []
log_stats = []
for log_str in log_... | python | def analyze_db_reading(job_prefix, reading_queue='run_db_reading_queue'):
"""Run various analysis on a particular reading job."""
# Analyze reach failures
log_strs = get_logs_from_db_reading(job_prefix, reading_queue)
indra_log_strs = []
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log_stats = []
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sorgerlab/indra | indra/sources/biopax/api.py | process_pc_neighborhood | def process_pc_neighborhood(gene_names, neighbor_limit=1,
database_filter=None):
"""Returns a BiopaxProcessor for a PathwayCommons neighborhood query.
The neighborhood query finds the neighborhood around a set of source genes.
http://www.pathwaycommons.org/pc2/#graph
http:... | python | def process_pc_neighborhood(gene_names, neighbor_limit=1,
database_filter=None):
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http://www.pathwaycommons.org/pc2/#graph
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sorgerlab/indra | indra/sources/biopax/api.py | process_pc_pathsbetween | def process_pc_pathsbetween(gene_names, neighbor_limit=1,
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"""Returns a BiopaxProcessor for a PathwayCommons paths-between query.
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database_filter=None, block_size=None):
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The paths-between query finds the paths between a set of genes. Here
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sorgerlab/indra | indra/sources/biopax/api.py | process_pc_pathsfromto | def process_pc_pathsfromto(source_genes, target_genes, neighbor_limit=1,
database_filter=None):
"""Returns a BiopaxProcessor for a PathwayCommons paths-from-to query.
The paths-from-to query finds the paths from a set of source genes to
a set of target genes.
http://www.path... | python | def process_pc_pathsfromto(source_genes, target_genes, neighbor_limit=1,
database_filter=None):
"""Returns a BiopaxProcessor for a PathwayCommons paths-from-to query.
The paths-from-to query finds the paths from a set of source genes to
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sorgerlab/indra | indra/sources/biopax/api.py | process_model | def process_model(model):
"""Returns a BiopaxProcessor for a BioPAX model object.
Parameters
----------
model : org.biopax.paxtools.model.Model
A BioPAX model object.
Returns
-------
bp : BiopaxProcessor
A BiopaxProcessor containing the obtained BioPAX model in bp.model.
... | python | def process_model(model):
"""Returns a BiopaxProcessor for a BioPAX model object.
Parameters
----------
model : org.biopax.paxtools.model.Model
A BioPAX model object.
Returns
-------
bp : BiopaxProcessor
A BiopaxProcessor containing the obtained BioPAX model in bp.model.
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sorgerlab/indra | indra/benchmarks/assembly_eval/batch4/assembly_eval.py | is_background_knowledge | def is_background_knowledge(stmt):
'''Return True if Statement is only supported by background knowledge.'''
any_background = False
# Iterate over all evidence for the statement
for ev in stmt.evidence:
epi = ev.epistemics
if epi is not None:
sec = epi.get('section_type')
... | python | def is_background_knowledge(stmt):
'''Return True if Statement is only supported by background knowledge.'''
any_background = False
# Iterate over all evidence for the statement
for ev in stmt.evidence:
epi = ev.epistemics
if epi is not None:
sec = epi.get('section_type')
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sorgerlab/indra | indra/benchmarks/assembly_eval/batch4/assembly_eval.py | multiple_sources | def multiple_sources(stmt):
'''Return True if statement is supported by multiple sources.
Note: this is currently not used and replaced by BeliefEngine score cutoff
'''
sources = list(set([e.source_api for e in stmt.evidence]))
if len(sources) > 1:
return True
return False | python | def multiple_sources(stmt):
'''Return True if statement is supported by multiple sources.
Note: this is currently not used and replaced by BeliefEngine score cutoff
'''
sources = list(set([e.source_api for e in stmt.evidence]))
if len(sources) > 1:
return True
return False | [
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sorgerlab/indra | indra/sources/geneways/symbols_parser.py | GenewaysSymbols.id_to_symbol | def id_to_symbol(self, entrez_id):
"""Gives the symbol for a given entrez id)"""
entrez_id = str(entrez_id)
if entrez_id not in self.ids_to_symbols:
m = 'Could not look up symbol for Entrez ID ' + entrez_id
raise Exception(m)
return self.ids_to_symbols[entrez_id] | python | def id_to_symbol(self, entrez_id):
"""Gives the symbol for a given entrez id)"""
entrez_id = str(entrez_id)
if entrez_id not in self.ids_to_symbols:
m = 'Could not look up symbol for Entrez ID ' + entrez_id
raise Exception(m)
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sorgerlab/indra | indra/assemblers/tsv/assembler.py | TsvAssembler.make_model | def make_model(self, output_file, add_curation_cols=False, up_only=False):
"""Export the statements into a tab-separated text file.
Parameters
----------
output_file : str
Name of the output file.
add_curation_cols : bool
Whether to add columns to facilit... | python | def make_model(self, output_file, add_curation_cols=False, up_only=False):
"""Export the statements into a tab-separated text file.
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----------
output_file : str
Name of the output file.
add_curation_cols : bool
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgentSet.get_create_base_agent | def get_create_base_agent(self, agent):
"""Return base agent with given name, creating it if needed."""
try:
base_agent = self.agents[_n(agent.name)]
except KeyError:
base_agent = BaseAgent(_n(agent.name))
self.agents[_n(agent.name)] = base_agent
# If... | python | def get_create_base_agent(self, agent):
"""Return base agent with given name, creating it if needed."""
try:
base_agent = self.agents[_n(agent.name)]
except KeyError:
base_agent = BaseAgent(_n(agent.name))
self.agents[_n(agent.name)] = base_agent
# If... | [
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgent.create_site | def create_site(self, site, states=None):
"""Create a new site on an agent if it doesn't already exist."""
if site not in self.sites:
self.sites.append(site)
if states is not None:
self.site_states.setdefault(site, [])
try:
states = list(states... | python | def create_site(self, site, states=None):
"""Create a new site on an agent if it doesn't already exist."""
if site not in self.sites:
self.sites.append(site)
if states is not None:
self.site_states.setdefault(site, [])
try:
states = list(states... | [
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgent.create_mod_site | def create_mod_site(self, mc):
"""Create modification site for the BaseAgent from a ModCondition."""
site_name = get_mod_site_name(mc)
(unmod_site_state, mod_site_state) = states[mc.mod_type]
self.create_site(site_name, (unmod_site_state, mod_site_state))
site_anns = [Annotation(... | python | def create_mod_site(self, mc):
"""Create modification site for the BaseAgent from a ModCondition."""
site_name = get_mod_site_name(mc)
(unmod_site_state, mod_site_state) = states[mc.mod_type]
self.create_site(site_name, (unmod_site_state, mod_site_state))
site_anns = [Annotation(... | [
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgent.add_site_states | def add_site_states(self, site, states):
"""Create new states on an agent site if the state doesn't exist."""
for state in states:
if state not in self.site_states[site]:
self.site_states[site].append(state) | python | def add_site_states(self, site, states):
"""Create new states on an agent site if the state doesn't exist."""
for state in states:
if state not in self.site_states[site]:
self.site_states[site].append(state) | [
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgent.add_activity_form | def add_activity_form(self, activity_pattern, is_active):
"""Adds the pattern as an active or inactive form to an Agent.
Parameters
----------
activity_pattern : dict
A dictionary of site names and their states.
is_active : bool
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"""Adds the pattern as an active or inactive form to an Agent.
Parameters
----------
activity_pattern : dict
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sorgerlab/indra | indra/assemblers/pysb/base_agents.py | BaseAgent.add_activity_type | def add_activity_type(self, activity_type):
"""Adds an activity type to an Agent.
Parameters
----------
activity_type : str
The type of activity to add such as 'activity', 'kinase',
'gtpbound'
"""
if activity_type not in self.activity_types:
... | python | def add_activity_type(self, activity_type):
"""Adds an activity type to an Agent.
Parameters
----------
activity_type : str
The type of activity to add such as 'activity', 'kinase',
'gtpbound'
"""
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysAction.make_annotation | def make_annotation(self):
"""Returns a dictionary with all properties of the action
and each of its action mentions."""
annotation = dict()
# Put all properties of the action object into the annotation
for item in dir(self):
if len(item) > 0 and item[0] != '_' and \... | python | def make_annotation(self):
"""Returns a dictionary with all properties of the action
and each of its action mentions."""
annotation = dict()
# Put all properties of the action object into the annotation
for item in dir(self):
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysActionParser._search_path | def _search_path(self, directory_name, filename):
"""Searches for a given file in the specified directory."""
full_path = path.join(directory_name, filename)
if path.exists(full_path):
return full_path
# Could not find the requested file in any of the directories
ret... | python | def _search_path(self, directory_name, filename):
"""Searches for a given file in the specified directory."""
full_path = path.join(directory_name, filename)
if path.exists(full_path):
return full_path
# Could not find the requested file in any of the directories
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysActionParser._init_action_list | def _init_action_list(self, action_filename):
"""Parses the file and populates the data."""
self.actions = list()
self.hiid_to_action_index = dict()
f = codecs.open(action_filename, 'r', encoding='latin-1')
first_line = True
for line in f:
line = line.rstrip... | python | def _init_action_list(self, action_filename):
"""Parses the file and populates the data."""
self.actions = list()
self.hiid_to_action_index = dict()
f = codecs.open(action_filename, 'r', encoding='latin-1')
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysActionParser._link_to_action_mentions | def _link_to_action_mentions(self, actionmention_filename):
"""Add action mentions"""
parser = GenewaysActionMentionParser(actionmention_filename)
self.action_mentions = parser.action_mentions
for action_mention in self.action_mentions:
hiid = action_mention.hiid
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"""Add action mentions"""
parser = GenewaysActionMentionParser(actionmention_filename)
self.action_mentions = parser.action_mentions
for action_mention in self.action_mentions:
hiid = action_mention.hiid
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysActionParser._lookup_symbols | def _lookup_symbols(self, symbols_filename):
"""Look up symbols for actions and action mentions"""
symbol_lookup = GenewaysSymbols(symbols_filename)
for action in self.actions:
action.up_symbol = symbol_lookup.id_to_symbol(action.up)
action.dn_symbol = symbol_lookup.id_to... | python | def _lookup_symbols(self, symbols_filename):
"""Look up symbols for actions and action mentions"""
symbol_lookup = GenewaysSymbols(symbols_filename)
for action in self.actions:
action.up_symbol = symbol_lookup.id_to_symbol(action.up)
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sorgerlab/indra | indra/sources/geneways/action_parser.py | GenewaysActionParser.get_top_n_action_types | def get_top_n_action_types(self, top_n):
"""Returns the top N actions by count."""
# Count action types
action_type_to_counts = dict()
for action in self.actions:
actiontype = action.actiontype
if actiontype not in action_type_to_counts:
action_typ... | python | def get_top_n_action_types(self, top_n):
"""Returns the top N actions by count."""
# Count action types
action_type_to_counts = dict()
for action in self.actions:
actiontype = action.actiontype
if actiontype not in action_type_to_counts:
action_typ... | [
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler.get_string | def get_string(self):
"""Return the assembled graph as a string.
Returns
-------
graph_string : str
The assembled graph as a string.
"""
graph_string = self.graph.to_string()
graph_string = graph_string.replace('\\N', '\\n')
return graph_strin... | python | def get_string(self):
"""Return the assembled graph as a string.
Returns
-------
graph_string : str
The assembled graph as a string.
"""
graph_string = self.graph.to_string()
graph_string = graph_string.replace('\\N', '\\n')
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler.save_dot | def save_dot(self, file_name='graph.dot'):
"""Save the graph in a graphviz dot file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the graph dot string to.
"""
s = self.get_string()
with open(file_name, 'wt') as fh:
... | python | def save_dot(self, file_name='graph.dot'):
"""Save the graph in a graphviz dot file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the graph dot string to.
"""
s = self.get_string()
with open(file_name, 'wt') as fh:
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler.save_pdf | def save_pdf(self, file_name='graph.pdf', prog='dot'):
"""Draw the graph and save as an image or pdf file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the graph as. Default: graph.pdf
prog : Optional[str]
The graphviz prog... | python | def save_pdf(self, file_name='graph.pdf', prog='dot'):
"""Draw the graph and save as an image or pdf file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the graph as. Default: graph.pdf
prog : Optional[str]
The graphviz prog... | [
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler._add_edge | def _add_edge(self, source, target, **kwargs):
"""Add an edge to the graph."""
# Start with default edge properties
edge_properties = self.edge_properties
# Overwrite ones that are given in function call explicitly
for k, v in kwargs.items():
edge_properties[k] = v
... | python | def _add_edge(self, source, target, **kwargs):
"""Add an edge to the graph."""
# Start with default edge properties
edge_properties = self.edge_properties
# Overwrite ones that are given in function call explicitly
for k, v in kwargs.items():
edge_properties[k] = v
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler._add_node | def _add_node(self, agent):
"""Add an Agent as a node to the graph."""
if agent is None:
return
node_label = _get_node_label(agent)
if isinstance(agent, Agent) and agent.bound_conditions:
bound_agents = [bc.agent for bc in agent.bound_conditions if
... | python | def _add_node(self, agent):
"""Add an Agent as a node to the graph."""
if agent is None:
return
node_label = _get_node_label(agent)
if isinstance(agent, Agent) and agent.bound_conditions:
bound_agents = [bc.agent for bc in agent.bound_conditions if
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler._add_stmt_edge | def _add_stmt_edge(self, stmt):
"""Assemble a Modification statement."""
# Skip statements with None in the subject position
source = _get_node_key(stmt.agent_list()[0])
target = _get_node_key(stmt.agent_list()[1])
edge_key = (source, target, stmt.__class__.__name__)
if e... | python | def _add_stmt_edge(self, stmt):
"""Assemble a Modification statement."""
# Skip statements with None in the subject position
source = _get_node_key(stmt.agent_list()[0])
target = _get_node_key(stmt.agent_list()[1])
edge_key = (source, target, stmt.__class__.__name__)
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sorgerlab/indra | indra/assemblers/graph/assembler.py | GraphAssembler._add_complex | def _add_complex(self, members, is_association=False):
"""Assemble a Complex statement."""
params = {'color': '#0000ff',
'arrowhead': 'dot',
'arrowtail': 'dot',
'dir': 'both'}
for m1, m2 in itertools.combinations(members, 2):
if s... | python | def _add_complex(self, members, is_association=False):
"""Assemble a Complex statement."""
params = {'color': '#0000ff',
'arrowhead': 'dot',
'arrowtail': 'dot',
'dir': 'both'}
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sorgerlab/indra | indra/sources/signor/api.py | process_from_file | def process_from_file(signor_data_file, signor_complexes_file=None):
"""Process Signor interaction data from CSV files.
Parameters
----------
signor_data_file : str
Path to the Signor interaction data file in CSV format.
signor_complexes_file : str
Path to the Signor complexes data ... | python | def process_from_file(signor_data_file, signor_complexes_file=None):
"""Process Signor interaction data from CSV files.
Parameters
----------
signor_data_file : str
Path to the Signor interaction data file in CSV format.
signor_complexes_file : str
Path to the Signor complexes data ... | [
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sorgerlab/indra | indra/sources/signor/api.py | _handle_response | def _handle_response(res, delimiter):
"""Get an iterator over the CSV data from the response."""
if res.status_code == 200:
# Python 2 -- csv.reader will need bytes
if sys.version_info[0] < 3:
csv_io = BytesIO(res.content)
# Python 3 -- csv.reader needs str
else:
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"""Get an iterator over the CSV data from the response."""
if res.status_code == 200:
# Python 2 -- csv.reader will need bytes
if sys.version_info[0] < 3:
csv_io = BytesIO(res.content)
# Python 3 -- csv.reader needs str
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sorgerlab/indra | indra/databases/context_client.py | get_protein_expression | def get_protein_expression(gene_names, cell_types):
"""Return the protein expression levels of genes in cell types.
Parameters
----------
gene_names : list
HGNC gene symbols for which expression levels are queried.
cell_types : list
List of cell type names in which expression levels... | python | def get_protein_expression(gene_names, cell_types):
"""Return the protein expression levels of genes in cell types.
Parameters
----------
gene_names : list
HGNC gene symbols for which expression levels are queried.
cell_types : list
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_aspect | def get_aspect(cx, aspect_name):
"""Return an aspect given the name of the aspect"""
if isinstance(cx, dict):
return cx.get(aspect_name)
for entry in cx:
if list(entry.keys())[0] == aspect_name:
return entry[aspect_name] | python | def get_aspect(cx, aspect_name):
"""Return an aspect given the name of the aspect"""
if isinstance(cx, dict):
return cx.get(aspect_name)
for entry in cx:
if list(entry.keys())[0] == aspect_name:
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | classify_nodes | def classify_nodes(graph, hub):
"""Classify each node based on its type and relationship to the hub."""
node_stats = defaultdict(lambda: defaultdict(list))
for u, v, data in graph.edges(data=True):
# This means the node is downstream of the hub
if hub == u:
h, o = u, v
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"""Classify each node based on its type and relationship to the hub."""
node_stats = defaultdict(lambda: defaultdict(list))
for u, v, data in graph.edges(data=True):
# This means the node is downstream of the hub
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_attributes | def get_attributes(aspect, id):
"""Return the attributes pointing to a given ID in a given aspect."""
attributes = {}
for entry in aspect:
if entry['po'] == id:
attributes[entry['n']] = entry['v']
return attributes | python | def get_attributes(aspect, id):
"""Return the attributes pointing to a given ID in a given aspect."""
attributes = {}
for entry in aspect:
if entry['po'] == id:
attributes[entry['n']] = entry['v']
return attributes | [
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | cx_to_networkx | def cx_to_networkx(cx):
"""Return a MultiDiGraph representation of a CX network."""
graph = networkx.MultiDiGraph()
for node_entry in get_aspect(cx, 'nodes'):
id = node_entry['@id']
attrs = get_attributes(get_aspect(cx, 'nodeAttributes'), id)
attrs['n'] = node_entry['n']
grap... | python | def cx_to_networkx(cx):
"""Return a MultiDiGraph representation of a CX network."""
graph = networkx.MultiDiGraph()
for node_entry in get_aspect(cx, 'nodes'):
id = node_entry['@id']
attrs = get_attributes(get_aspect(cx, 'nodeAttributes'), id)
attrs['n'] = node_entry['n']
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_quadrant_from_class | def get_quadrant_from_class(node_class):
"""Return the ID of the segment of the plane corresponding to a class."""
up, edge_type, _ = node_class
if up == 0:
return 0 if random.random() < 0.5 else 7
mappings = {(-1, 'modification'): 1,
(-1, 'amount'): 2,
(-1, 'acti... | python | def get_quadrant_from_class(node_class):
"""Return the ID of the segment of the plane corresponding to a class."""
up, edge_type, _ = node_class
if up == 0:
return 0 if random.random() < 0.5 else 7
mappings = {(-1, 'modification'): 1,
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_coordinates | def get_coordinates(node_class):
"""Generate coordinates for a node in a given class."""
quadrant_size = (2 * math.pi / 8.0)
quadrant = get_quadrant_from_class(node_class)
begin_angle = quadrant_size * quadrant
r = 200 + 800*random.random()
alpha = begin_angle + random.random() * quadrant_size
... | python | def get_coordinates(node_class):
"""Generate coordinates for a node in a given class."""
quadrant_size = (2 * math.pi / 8.0)
quadrant = get_quadrant_from_class(node_class)
begin_angle = quadrant_size * quadrant
r = 200 + 800*random.random()
alpha = begin_angle + random.random() * quadrant_size
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_layout_aspect | def get_layout_aspect(hub, node_classes):
"""Get the full layout aspect with coordinates for each node."""
aspect = [{'node': hub, 'x': 0.0, 'y': 0.0}]
for node, node_class in node_classes.items():
if node == hub:
continue
x, y = get_coordinates(node_class)
aspect.append(... | python | def get_layout_aspect(hub, node_classes):
"""Get the full layout aspect with coordinates for each node."""
aspect = [{'node': hub, 'x': 0.0, 'y': 0.0}]
for node, node_class in node_classes.items():
if node == hub:
continue
x, y = get_coordinates(node_class)
aspect.append(... | [
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | get_node_by_name | def get_node_by_name(graph, name):
"""Return a node ID given its name."""
for id, attrs in graph.nodes(data=True):
if attrs['n'] == name:
return id | python | def get_node_by_name(graph, name):
"""Return a node ID given its name."""
for id, attrs in graph.nodes(data=True):
if attrs['n'] == name:
return id | [
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sorgerlab/indra | indra/assemblers/cx/hub_layout.py | add_semantic_hub_layout | def add_semantic_hub_layout(cx, hub):
"""Attach a layout aspect to a CX network given a hub node."""
graph = cx_to_networkx(cx)
hub_node = get_node_by_name(graph, hub)
node_classes = classify_nodes(graph, hub_node)
layout_aspect = get_layout_aspect(hub_node, node_classes)
cx['cartesianLayout'] =... | python | def add_semantic_hub_layout(cx, hub):
"""Attach a layout aspect to a CX network given a hub node."""
graph = cx_to_networkx(cx)
hub_node = get_node_by_name(graph, hub)
node_classes = classify_nodes(graph, hub_node)
layout_aspect = get_layout_aspect(hub_node, node_classes)
cx['cartesianLayout'] =... | [
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sorgerlab/indra | indra/literature/crossref_client.py | get_metadata | def get_metadata(doi):
"""Returns the metadata of an article given its DOI from CrossRef
as a JSON dict"""
url = crossref_url + 'works/' + doi
res = requests.get(url)
if res.status_code != 200:
logger.info('Could not get CrossRef metadata for DOI %s, code %d' %
(doi, res.... | python | def get_metadata(doi):
"""Returns the metadata of an article given its DOI from CrossRef
as a JSON dict"""
url = crossref_url + 'works/' + doi
res = requests.get(url)
if res.status_code != 200:
logger.info('Could not get CrossRef metadata for DOI %s, code %d' %
(doi, res.... | [
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sorgerlab/indra | indra/literature/crossref_client.py | doi_query | def doi_query(pmid, search_limit=10):
"""Get the DOI for a PMID by matching CrossRef and Pubmed metadata.
Searches CrossRef using the article title and then accepts search hits only
if they have a matching journal ISSN and page number with what is obtained
from the Pubmed database.
"""
# Get ar... | python | def doi_query(pmid, search_limit=10):
"""Get the DOI for a PMID by matching CrossRef and Pubmed metadata.
Searches CrossRef using the article title and then accepts search hits only
if they have a matching journal ISSN and page number with what is obtained
from the Pubmed database.
"""
# Get ar... | [
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sorgerlab/indra | indra/assemblers/pysb/assembler.py | get_agent_rule_str | def get_agent_rule_str(agent):
"""Construct a string from an Agent as part of a PySB rule name."""
rule_str_list = [_n(agent.name)]
# If it's a molecular agent
if isinstance(agent, ist.Agent):
for mod in agent.mods:
mstr = abbrevs[mod.mod_type]
if mod.residue is not None:... | python | def get_agent_rule_str(agent):
"""Construct a string from an Agent as part of a PySB rule name."""
rule_str_list = [_n(agent.name)]
# If it's a molecular agent
if isinstance(agent, ist.Agent):
for mod in agent.mods:
mstr = abbrevs[mod.mod_type]
if mod.residue is not None:... | [
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sorgerlab/indra | indra/assemblers/pysb/assembler.py | add_rule_to_model | def add_rule_to_model(model, rule, annotations=None):
"""Add a Rule to a PySB model and handle duplicate component errors."""
try:
model.add_component(rule)
# If the rule was actually added, also add the annotations
if annotations:
model.annotations += annotations
# If th... | python | def add_rule_to_model(model, rule, annotations=None):
"""Add a Rule to a PySB model and handle duplicate component errors."""
try:
model.add_component(rule)
# If the rule was actually added, also add the annotations
if annotations:
model.annotations += annotations
# If th... | [
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sorgerlab/indra | indra/assemblers/pysb/assembler.py | get_create_parameter | def get_create_parameter(model, param):
"""Return parameter with given name, creating it if needed.
If unique is false and the parameter exists, the value is not changed; if
it does not exist, it will be created. If unique is true then upon conflict
a number is added to the end of the parameter name.
... | python | def get_create_parameter(model, param):
"""Return parameter with given name, creating it if needed.
If unique is false and the parameter exists, the value is not changed; if
it does not exist, it will be created. If unique is true then upon conflict
a number is added to the end of the parameter name.
... | [
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sorgerlab/indra | indra/assemblers/pysb/assembler.py | get_uncond_agent | def get_uncond_agent(agent):
"""Construct the unconditional state of an Agent.
The unconditional Agent is a copy of the original agent but
without any bound conditions and modification conditions.
Mutation conditions, however, are preserved since they are static.
"""
agent_uncond = ist.Agent(_n... | python | def get_uncond_agent(agent):
"""Construct the unconditional state of an Agent.
The unconditional Agent is a copy of the original agent but
without any bound conditions and modification conditions.
Mutation conditions, however, are preserved since they are static.
"""
agent_uncond = ist.Agent(_n... | [
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