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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.find_event_with_outgoing_edges | def find_event_with_outgoing_edges(self, event_name, desired_relations):
"""Gets a list of event nodes with the specified event_name and
outgoing edges annotated with each of the specified relations.
Parameters
----------
event_name : str
Look for event nodes with th... | python | def find_event_with_outgoing_edges(self, event_name, desired_relations):
"""Gets a list of event nodes with the specified event_name and
outgoing edges annotated with each of the specified relations.
Parameters
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event_name : str
Look for event nodes with th... | [
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.get_related_node | def get_related_node(self, node, relation):
"""Looks for an edge from node to some other node, such that the edge
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returns the name of the node it points to. Otherwise, returns None."""
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"""Looks for an edge from node to some other node, such that the edge
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.get_entity_text_for_relation | def get_entity_text_for_relation(self, node, relation):
"""Looks for an edge from node to some other node, such that the edge is
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.process_increase_expression_amount | def process_increase_expression_amount(self):
"""Looks for Positive_Regulation events with a specified Cause
and a Gene_Expression theme, and processes them into INDRA statements.
"""
statements = []
pwcs = self.find_event_parent_with_event_child(
'Positive_regul... | python | def process_increase_expression_amount(self):
"""Looks for Positive_Regulation events with a specified Cause
and a Gene_Expression theme, and processes them into INDRA statements.
"""
statements = []
pwcs = self.find_event_parent_with_event_child(
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.process_phosphorylation_statements | def process_phosphorylation_statements(self):
"""Looks for Phosphorylation events in the graph and extracts them into
INDRA statements.
In particular, looks for a Positive_regulation event node with a child
Phosphorylation event node.
If Positive_regulation has an outgoing Caus... | python | def process_phosphorylation_statements(self):
"""Looks for Phosphorylation events in the graph and extracts them into
INDRA statements.
In particular, looks for a Positive_regulation event node with a child
Phosphorylation event node.
If Positive_regulation has an outgoing Caus... | [
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.process_binding_statements | def process_binding_statements(self):
"""Looks for Binding events in the graph and extracts them into INDRA
statements.
In particular, looks for a Binding event node with outgoing edges
with relations Theme and Theme2 - the entities these edges point to
are the two constituents ... | python | def process_binding_statements(self):
"""Looks for Binding events in the graph and extracts them into INDRA
statements.
In particular, looks for a Binding event node with outgoing edges
with relations Theme and Theme2 - the entities these edges point to
are the two constituents ... | [
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.node_to_evidence | def node_to_evidence(self, entity_node, is_direct):
"""Computes an evidence object for a statement.
We assume that the entire event happens within a single statement, and
get the text of the sentence by getting the text of the sentence
containing the provided node that corresponds to on... | python | def node_to_evidence(self, entity_node, is_direct):
"""Computes an evidence object for a statement.
We assume that the entire event happens within a single statement, and
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sorgerlab/indra | indra/sources/tees/processor.py | TEESProcessor.connected_subgraph | def connected_subgraph(self, node):
"""Returns the subgraph containing the given node, its ancestors, and
its descendants.
Parameters
----------
node : str
We want to create the subgraph containing this node.
Returns
-------
subgraph : networ... | python | def connected_subgraph(self, node):
"""Returns the subgraph containing the given node, its ancestors, and
its descendants.
Parameters
----------
node : str
We want to create the subgraph containing this node.
Returns
-------
subgraph : networ... | [
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sorgerlab/indra | indra/sources/trips/api.py | process_text | def process_text(text, save_xml_name='trips_output.xml', save_xml_pretty=True,
offline=False, service_endpoint='drum'):
"""Return a TripsProcessor by processing text.
Parameters
----------
text : str
The text to be processed.
save_xml_name : Optional[str]
The name o... | python | def process_text(text, save_xml_name='trips_output.xml', save_xml_pretty=True,
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"""Return a TripsProcessor by processing text.
Parameters
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text : str
The text to be processed.
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sorgerlab/indra | indra/sources/trips/api.py | process_xml_file | def process_xml_file(file_name):
"""Return a TripsProcessor by processing a TRIPS EKB XML file.
Parameters
----------
file_name : str
Path to a TRIPS extraction knowledge base (EKB) file to be processed.
Returns
-------
tp : TripsProcessor
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"""Return a TripsProcessor by processing a TRIPS EKB XML file.
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file_name : str
Path to a TRIPS extraction knowledge base (EKB) file to be processed.
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"""Return a TripsProcessor by processing a TRIPS EKB XML string.
Parameters
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xml_string : str
A TRIPS extraction knowledge base (EKB) string to be processed.
http://trips.ihmc.us/parser/api.html
Returns
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tp : TripsProcessor
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"""Return a TripsProcessor by processing a TRIPS EKB XML string.
Parameters
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xml_string : str
A TRIPS extraction knowledge base (EKB) string to be processed.
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sorgerlab/indra | indra/belief/wm_scorer.py | load_eidos_curation_table | def load_eidos_curation_table():
"""Return a pandas table of Eidos curation data."""
url = 'https://raw.githubusercontent.com/clulab/eidos/master/' + \
'src/main/resources/org/clulab/wm/eidos/english/confidence/' + \
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# Load the table of scores from the URL above into a dat... | python | def load_eidos_curation_table():
"""Return a pandas table of Eidos curation data."""
url = 'https://raw.githubusercontent.com/clulab/eidos/master/' + \
'src/main/resources/org/clulab/wm/eidos/english/confidence/' + \
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sorgerlab/indra | indra/belief/wm_scorer.py | get_eidos_bayesian_scorer | def get_eidos_bayesian_scorer(prior_counts=None):
"""Return a BayesianScorer based on Eidos curation counts."""
table = load_eidos_curation_table()
subtype_counts = {'eidos': {r: [c, i] for r, c, i in
zip(table['RULE'], table['Num correct'],
ta... | python | def get_eidos_bayesian_scorer(prior_counts=None):
"""Return a BayesianScorer based on Eidos curation counts."""
table = load_eidos_curation_table()
subtype_counts = {'eidos': {r: [c, i] for r, c, i in
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sorgerlab/indra | indra/belief/wm_scorer.py | get_eidos_scorer | def get_eidos_scorer():
"""Return a SimpleScorer based on Eidos curated precision estimates."""
table = load_eidos_curation_table()
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total_num = table['COUNT of RULE'].sum()
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precision = weighted_sum / total... | python | def get_eidos_scorer():
"""Return a SimpleScorer based on Eidos curated precision estimates."""
table = load_eidos_curation_table()
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sorgerlab/indra | indra/sources/trrust/api.py | process_from_web | def process_from_web():
"""Return a TrrustProcessor based on the online interaction table.
Returns
-------
TrrustProcessor
A TrrustProcessor object that has a list of INDRA Statements in its
statements attribute.
"""
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A TrrustProcessor object that has a list of INDRA Statements in its
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sorgerlab/indra | indra/sources/rlimsp/api.py | process_from_webservice | def process_from_webservice(id_val, id_type='pmcid', source='pmc',
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Parameters
----------
id_val : str
A PMCID, with the prefix PMC, or pmid, with no prefix, of the paper to
... | python | def process_from_webservice(id_val, id_type='pmcid', source='pmc',
with_grounding=True):
"""Return an output from RLIMS-p for the given PubMed ID or PMC ID.
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sorgerlab/indra | indra/sources/rlimsp/api.py | process_from_json_file | def process_from_json_file(filename, doc_id_type=None):
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Parameters
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filename : str
Path to the JSON file.
doc_id_type : Optional[str]
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sorgerlab/indra | indra/util/nested_dict.py | NestedDict.export_dict | def export_dict(self):
"Convert this into an ordinary dict (of dicts)."
return {k: v.export_dict() if isinstance(v, self.__class__) else v
for k, v in self.items()} | python | def export_dict(self):
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# This could get weird if the actual expected returned value
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sorgerlab/indra | indra/util/nested_dict.py | NestedDict.get_path | def get_path(self, key):
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key_path, res = (None, None)
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sorgerlab/indra | indra/util/nested_dict.py | NestedDict.get_paths | def get_paths(self, key):
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sorgerlab/indra | indra/util/nested_dict.py | NestedDict.get_leaves | def get_leaves(self):
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sorgerlab/indra | indra/sources/reach/processor.py | _read_reach_rule_regexps | def _read_reach_rule_regexps():
"""Load in a file with the regular expressions corresponding to each
reach rule. Why regular expression matching?
The rule name in found_by has instances of some reach rules for each
possible event type
(activation, binding, etc). This makes for too many different typ... | python | def _read_reach_rule_regexps():
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sorgerlab/indra | indra/sources/reach/processor.py | determine_reach_subtype | def determine_reach_subtype(event_name):
"""Returns the category of reach rule from the reach rule instance.
Looks at a list of regular
expressions corresponding to reach rule types, and returns the longest
regexp that matches, or None if none of them match.
Parameters
----------
evidence ... | python | def determine_reach_subtype(event_name):
"""Returns the category of reach rule from the reach rule instance.
Looks at a list of regular
expressions corresponding to reach rule types, and returns the longest
regexp that matches, or None if none of them match.
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.print_event_statistics | def print_event_statistics(self):
"""Print the number of events in the REACH output by type."""
logger.info('All events by type')
logger.info('-------------------')
for k, v in self.all_events.items():
logger.info('%s, %s' % (k, len(v)))
logger.info('-----------------... | python | def print_event_statistics(self):
"""Print the number of events in the REACH output by type."""
logger.info('All events by type')
logger.info('-------------------')
for k, v in self.all_events.items():
logger.info('%s, %s' % (k, len(v)))
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_all_events | def get_all_events(self):
"""Gather all event IDs in the REACH output by type.
These IDs are stored in the self.all_events dict.
"""
self.all_events = {}
events = self.tree.execute("$.events.frames")
if events is None:
return
for e in events:
... | python | def get_all_events(self):
"""Gather all event IDs in the REACH output by type.
These IDs are stored in the self.all_events dict.
"""
self.all_events = {}
events = self.tree.execute("$.events.frames")
if events is None:
return
for e in events:
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_modifications | def get_modifications(self):
"""Extract Modification INDRA Statements."""
# Find all event frames that are a type of protein modification
qstr = "$.events.frames[(@.type is 'protein-modification')]"
res = self.tree.execute(qstr)
if res is None:
return
# Extrac... | python | def get_modifications(self):
"""Extract Modification INDRA Statements."""
# Find all event frames that are a type of protein modification
qstr = "$.events.frames[(@.type is 'protein-modification')]"
res = self.tree.execute(qstr)
if res is None:
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_regulate_amounts | def get_regulate_amounts(self):
"""Extract RegulateAmount INDRA Statements."""
qstr = "$.events.frames[(@.type is 'transcription')]"
res = self.tree.execute(qstr)
all_res = []
if res is not None:
all_res += list(res)
qstr = "$.events.frames[(@.type is 'amount'... | python | def get_regulate_amounts(self):
"""Extract RegulateAmount INDRA Statements."""
qstr = "$.events.frames[(@.type is 'transcription')]"
res = self.tree.execute(qstr)
all_res = []
if res is not None:
all_res += list(res)
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_complexes | def get_complexes(self):
"""Extract INDRA Complex Statements."""
qstr = "$.events.frames[@.type is 'complex-assembly']"
res = self.tree.execute(qstr)
if res is None:
return
for r in res:
epistemics = self._get_epistemics(r)
if epistemics.get('... | python | def get_complexes(self):
"""Extract INDRA Complex Statements."""
qstr = "$.events.frames[@.type is 'complex-assembly']"
res = self.tree.execute(qstr)
if res is None:
return
for r in res:
epistemics = self._get_epistemics(r)
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_activation | def get_activation(self):
"""Extract INDRA Activation Statements."""
qstr = "$.events.frames[@.type is 'activation']"
res = self.tree.execute(qstr)
if res is None:
return
for r in res:
epistemics = self._get_epistemics(r)
if epistemics.get('neg... | python | def get_activation(self):
"""Extract INDRA Activation Statements."""
qstr = "$.events.frames[@.type is 'activation']"
res = self.tree.execute(qstr)
if res is None:
return
for r in res:
epistemics = self._get_epistemics(r)
if epistemics.get('neg... | [
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor.get_translocation | def get_translocation(self):
"""Extract INDRA Translocation Statements."""
qstr = "$.events.frames[@.type is 'translocation']"
res = self.tree.execute(qstr)
if res is None:
return
for r in res:
epistemics = self._get_epistemics(r)
if epistemics... | python | def get_translocation(self):
"""Extract INDRA Translocation Statements."""
qstr = "$.events.frames[@.type is 'translocation']"
res = self.tree.execute(qstr)
if res is None:
return
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor._get_mod_conditions | def _get_mod_conditions(self, mod_term):
"""Return a list of ModConditions given a mod term dict."""
site = mod_term.get('site')
if site is not None:
mods = self._parse_site_text(site)
else:
mods = [Site(None, None)]
mcs = []
for mod in mods:
... | python | def _get_mod_conditions(self, mod_term):
"""Return a list of ModConditions given a mod term dict."""
site = mod_term.get('site')
if site is not None:
mods = self._parse_site_text(site)
else:
mods = [Site(None, None)]
mcs = []
for mod in mods:
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor._get_entity_coordinates | def _get_entity_coordinates(self, entity_term):
"""Return sentence coordinates for a given entity.
Given an entity term return the associated sentence coordinates as
a tuple of the form (int, int). Returns None if for any reason the
sentence coordinates cannot be found.
"""
... | python | def _get_entity_coordinates(self, entity_term):
"""Return sentence coordinates for a given entity.
Given an entity term return the associated sentence coordinates as
a tuple of the form (int, int). Returns None if for any reason the
sentence coordinates cannot be found.
"""
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor._get_section | def _get_section(self, event):
"""Get the section of the paper that the event is from."""
sentence_id = event.get('sentence')
section = None
if sentence_id:
qstr = "$.sentences.frames[(@.frame_id is \'%s\')]" % sentence_id
res = self.tree.execute(qstr)
... | python | def _get_section(self, event):
"""Get the section of the paper that the event is from."""
sentence_id = event.get('sentence')
section = None
if sentence_id:
qstr = "$.sentences.frames[(@.frame_id is \'%s\')]" % sentence_id
res = self.tree.execute(qstr)
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sorgerlab/indra | indra/sources/reach/processor.py | ReachProcessor._get_controller_agent | def _get_controller_agent(self, arg):
"""Return a single or a complex controller agent."""
controller_agent = None
controller = arg.get('arg')
# There is either a single controller here
if controller is not None:
controller_agent, coords = self._get_agent_from_entity(... | python | def _get_controller_agent(self, arg):
"""Return a single or a complex controller agent."""
controller_agent = None
controller = arg.get('arg')
# There is either a single controller here
if controller is not None:
controller_agent, coords = self._get_agent_from_entity(... | [
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sorgerlab/indra | indra/sources/eidos/processor.py | _sanitize | def _sanitize(text):
"""Return sanitized Eidos text field for human readability."""
d = {'-LRB-': '(', '-RRB-': ')'}
return re.sub('|'.join(d.keys()), lambda m: d[m.group(0)], text) | python | def _sanitize(text):
"""Return sanitized Eidos text field for human readability."""
d = {'-LRB-': '(', '-RRB-': ')'}
return re.sub('|'.join(d.keys()), lambda m: d[m.group(0)], text) | [
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sorgerlab/indra | indra/sources/eidos/processor.py | _get_time_stamp | def _get_time_stamp(entry):
"""Return datetime object from a timex constraint start/end entry.
Example string format to convert: 2018-01-01T00:00
"""
if not entry or entry == 'Undef':
return None
try:
dt = datetime.datetime.strptime(entry, '%Y-%m-%dT%H:%M')
except Exception as e... | python | def _get_time_stamp(entry):
"""Return datetime object from a timex constraint start/end entry.
Example string format to convert: 2018-01-01T00:00
"""
if not entry or entry == 'Undef':
return None
try:
dt = datetime.datetime.strptime(entry, '%Y-%m-%dT%H:%M')
except Exception as e... | [
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sorgerlab/indra | indra/sources/eidos/processor.py | ref_context_from_geoloc | def ref_context_from_geoloc(geoloc):
"""Return a RefContext object given a geoloc entry."""
text = geoloc.get('text')
geoid = geoloc.get('geoID')
rc = RefContext(name=text, db_refs={'GEOID': geoid})
return rc | python | def ref_context_from_geoloc(geoloc):
"""Return a RefContext object given a geoloc entry."""
text = geoloc.get('text')
geoid = geoloc.get('geoID')
rc = RefContext(name=text, db_refs={'GEOID': geoid})
return rc | [
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sorgerlab/indra | indra/sources/eidos/processor.py | time_context_from_timex | def time_context_from_timex(timex):
"""Return a TimeContext object given a timex entry."""
time_text = timex.get('text')
constraint = timex['intervals'][0]
start = _get_time_stamp(constraint.get('start'))
end = _get_time_stamp(constraint.get('end'))
duration = constraint['duration']
tc = Tim... | python | def time_context_from_timex(timex):
"""Return a TimeContext object given a timex entry."""
time_text = timex.get('text')
constraint = timex['intervals'][0]
start = _get_time_stamp(constraint.get('start'))
end = _get_time_stamp(constraint.get('end'))
duration = constraint['duration']
tc = Tim... | [
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sorgerlab/indra | indra/sources/eidos/processor.py | find_args | def find_args(event, arg_type):
"""Return IDs of all arguments of a given type"""
args = event.get('arguments', {})
obj_tags = [arg for arg in args if arg['type'] == arg_type]
if obj_tags:
return [o['value']['@id'] for o in obj_tags]
else:
return [] | python | def find_args(event, arg_type):
"""Return IDs of all arguments of a given type"""
args = event.get('arguments', {})
obj_tags = [arg for arg in args if arg['type'] == arg_type]
if obj_tags:
return [o['value']['@id'] for o in obj_tags]
else:
return [] | [
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.extract_causal_relations | def extract_causal_relations(self):
"""Extract causal relations as Statements."""
# Get the extractions that are labeled as directed and causal
relations = [e for e in self.doc.extractions if
'DirectedRelation' in e['labels'] and
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"""Extract causal relations as Statements."""
# Get the extractions that are labeled as directed and causal
relations = [e for e in self.doc.extractions if
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.get_evidence | def get_evidence(self, relation):
"""Return the Evidence object for the INDRA Statment."""
provenance = relation.get('provenance')
# First try looking up the full sentence through provenance
text = None
context = None
if provenance:
sentence_tag = provenance[... | python | def get_evidence(self, relation):
"""Return the Evidence object for the INDRA Statment."""
provenance = relation.get('provenance')
# First try looking up the full sentence through provenance
text = None
context = None
if provenance:
sentence_tag = provenance[... | [
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.get_negation | def get_negation(event):
"""Return negation attached to an event.
Example: "states": [{"@type": "State", "type": "NEGATION",
"text": "n't"}]
"""
states = event.get('states', [])
if not states:
return []
negs = [state for state in ... | python | def get_negation(event):
"""Return negation attached to an event.
Example: "states": [{"@type": "State", "type": "NEGATION",
"text": "n't"}]
"""
states = event.get('states', [])
if not states:
return []
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.get_hedging | def get_hedging(event):
"""Return hedging markers attached to an event.
Example: "states": [{"@type": "State", "type": "HEDGE",
"text": "could"}
"""
states = event.get('states', [])
if not states:
return []
hedgings = [state for s... | python | def get_hedging(event):
"""Return hedging markers attached to an event.
Example: "states": [{"@type": "State", "type": "HEDGE",
"text": "could"}
"""
states = event.get('states', [])
if not states:
return []
hedgings = [state for s... | [
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.get_groundings | def get_groundings(entity):
"""Return groundings as db_refs for an entity."""
def get_grounding_entries(grounding):
if not grounding:
return None
entries = []
values = grounding.get('values', [])
# Values could still have been a None entry... | python | def get_groundings(entity):
"""Return groundings as db_refs for an entity."""
def get_grounding_entries(grounding):
if not grounding:
return None
entries = []
values = grounding.get('values', [])
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.get_concept | def get_concept(entity):
"""Return Concept from an Eidos entity."""
# Use the canonical name as the name of the Concept
name = entity['canonicalName']
db_refs = EidosProcessor.get_groundings(entity)
concept = Concept(name, db_refs=db_refs)
return concept | python | def get_concept(entity):
"""Return Concept from an Eidos entity."""
# Use the canonical name as the name of the Concept
name = entity['canonicalName']
db_refs = EidosProcessor.get_groundings(entity)
concept = Concept(name, db_refs=db_refs)
return concept | [
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.time_context_from_ref | def time_context_from_ref(self, timex):
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# If the timex has a value set, it means that it refers to a DCT or
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# need to be taken from there
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosProcessor.geo_context_from_ref | def geo_context_from_ref(self, ref):
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value = ref.get('value')
if value:
# Here we get the RefContext from the stashed geoloc dictionary
rc = self.doc.geolocs.get(value['@id'])
return rc
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sorgerlab/indra | indra/sources/eidos/processor.py | EidosDocument.time_context_from_dct | def time_context_from_dct(dct):
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sorgerlab/indra | indra/statements/util.py | make_hash | def make_hash(s, n_bytes):
"""Make the hash from a matches key."""
raw_h = int(md5(s.encode('utf-8')).hexdigest()[:n_bytes], 16)
# Make it a signed int.
return 16**n_bytes//2 - raw_h | python | def make_hash(s, n_bytes):
"""Make the hash from a matches key."""
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sorgerlab/indra | indra/sources/tees/parse_tees.py | parse_a1 | def parse_a1(a1_text):
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Text of the TEES a1 output file, specifying the entities
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sorgerlab/indra | indra/sources/tees/parse_tees.py | parse_a2 | def parse_a2(a2_text, entities, tees_sentences):
"""Extracts events from a TEES a2 output into a networkx directed graph.
Parameters
----------
a2_text : str
Text of the TEES a2 file output, specifying the event graph
sentences_xml_gz : str
Filename with the TEES sentence segmentati... | python | def parse_a2(a2_text, entities, tees_sentences):
"""Extracts events from a TEES a2 output into a networkx directed graph.
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Text of the TEES a2 file output, specifying the event graph
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sorgerlab/indra | indra/sources/tees/parse_tees.py | parse_output | def parse_output(a1_text, a2_text, sentence_segmentations):
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a1_text : str
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sorgerlab/indra | indra/sources/tees/parse_tees.py | tees_parse_networkx_to_dot | def tees_parse_networkx_to_dot(G, output_file, subgraph_nodes):
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----------
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sorgerlab/indra | indra/sources/cwms/processor.py | CWMSProcessor._get_event | def _get_event(self, event, find_str):
"""Get a concept referred from the event by the given string."""
# Get the term with the given element id
element = event.find(find_str)
if element is None:
return None
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element_term =... | python | def _get_event(self, event, find_str):
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sorgerlab/indra | indra/sources/cwms/processor.py | CWMSProcessor._extract_time_loc | def _extract_time_loc(self, term):
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loc = term.find('location')
if loc is None:
loc_context = None
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loc_id = loc.attrib.get('id')
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text = l... | python | def _extract_time_loc(self, term):
"""Get the location from a term (CC or TERM)"""
loc = term.find('location')
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sorgerlab/indra | indra/assemblers/cag/assembler.py | CAGAssembler.make_model | def make_model(self, grounding_ontology='UN', grounding_threshold=None):
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sorgerlab/indra | indra/assemblers/cag/assembler.py | CAGAssembler.export_to_cytoscapejs | def export_to_cytoscapejs(self):
"""Return CAG in format readable by CytoscapeJS.
Return
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dict
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"""
def _create_edge_data_dict(e):
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sorgerlab/indra | indra/assemblers/cag/assembler.py | CAGAssembler.generate_jupyter_js | def generate_jupyter_js(self, cyjs_style=None, cyjs_layout=None):
"""Generate Javascript from a template to run in Jupyter notebooks.
Parameters
----------
cyjs_style : Optional[dict]
A dict that sets CytoscapeJS style as specified in
https://github.com/cytoscape... | python | def generate_jupyter_js(self, cyjs_style=None, cyjs_layout=None):
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sorgerlab/indra | indra/assemblers/cag/assembler.py | CAGAssembler._node_name | def _node_name(self, concept):
"""Return a standardized name for a node given a Concept."""
if (# grounding threshold is specified
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | namespace_from_uri | def namespace_from_uri(uri):
"""Return the entity namespace from the URI. Examples:
http://www.openbel.org/bel/p_HGNC_RAF1 -> HGNC
http://www.openbel.org/bel/p_RGD_Raf1 -> RGD
http://www.openbel.org/bel/p_PFH_MEK1/2_Family -> PFH
"""
patterns = ['http://www.openbel.org/bel/[pragm]_([A-Za-z]+)_.*... | python | def namespace_from_uri(uri):
"""Return the entity namespace from the URI. Examples:
http://www.openbel.org/bel/p_HGNC_RAF1 -> HGNC
http://www.openbel.org/bel/p_RGD_Raf1 -> RGD
http://www.openbel.org/bel/p_PFH_MEK1/2_Family -> PFH
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | term_from_uri | def term_from_uri(uri):
"""Removes prepended URI information from terms."""
if uri is None:
return None
# This insures that if we get a Literal with an integer value (as we
# do for modification positions), it will get converted to a string,
# not an integer.
if isinstance(uri, rdflib.Li... | python | def term_from_uri(uri):
"""Removes prepended URI information from terms."""
if uri is None:
return None
# This insures that if we get a Literal with an integer value (as we
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_modifications | def get_modifications(self):
"""Extract INDRA Modification Statements from BEL.
Two SPARQL patterns are used for extracting Modifications from BEL:
- q_phospho1 assumes that the subject is an AbundanceActivity, which
increases/decreases a ModifiedProteinAbundance.
Examples... | python | def get_modifications(self):
"""Extract INDRA Modification Statements from BEL.
Two SPARQL patterns are used for extracting Modifications from BEL:
- q_phospho1 assumes that the subject is an AbundanceActivity, which
increases/decreases a ModifiedProteinAbundance.
Examples... | [
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- q_phospho1 assumes that the subject is an AbundanceActivity, which
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Examples:
kinaseActivity(proteinA... | [
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_activating_mods | def get_activating_mods(self):
"""Extract INDRA ActiveForm Statements with a single mod from BEL.
The SPARQL pattern used for extraction from BEL looks for a
ModifiedProteinAbundance as subject and an Activiy of a
ProteinAbundance as object.
Examples:
proteinAbunda... | python | def get_activating_mods(self):
"""Extract INDRA ActiveForm Statements with a single mod from BEL.
The SPARQL pattern used for extraction from BEL looks for a
ModifiedProteinAbundance as subject and an Activiy of a
ProteinAbundance as object.
Examples:
proteinAbunda... | [
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The SPARQL pattern used for extraction from BEL looks for a
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ProteinAbundance as object.
Examples:
proteinAbundance(HGNC:INSR,proteinModification(P,Y))
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_complexes | def get_complexes(self):
"""Extract INDRA Complex Statements from BEL.
The SPARQL query used to extract Complexes looks for ComplexAbundance
terms and their constituents. This pattern is distinct from other
patterns in this processor in that it queries for terms, not
full statem... | python | def get_complexes(self):
"""Extract INDRA Complex Statements from BEL.
The SPARQL query used to extract Complexes looks for ComplexAbundance
terms and their constituents. This pattern is distinct from other
patterns in this processor in that it queries for terms, not
full statem... | [
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The SPARQL query used to extract Complexes looks for ComplexAbundance
terms and their constituents. This pattern is distinct from other
patterns in this processor in that it queries for terms, not
full statements.
Examples:
... | [
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] | train | https://github.com/sorgerlab/indra/blob/79a70415832c5702d7a820c7c9ccc8e25010124b/indra/sources/bel/rdf_processor.py#L281-L344 |
sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_activating_subs | def get_activating_subs(self):
"""Extract INDRA ActiveForm Statements based on a mutation from BEL.
The SPARQL pattern used to extract ActiveForms due to mutations look
for a ProteinAbundance as a subject which has a child encoding the
amino acid substitution. The object of the statemen... | python | def get_activating_subs(self):
"""Extract INDRA ActiveForm Statements based on a mutation from BEL.
The SPARQL pattern used to extract ActiveForms due to mutations look
for a ProteinAbundance as a subject which has a child encoding the
amino acid substitution. The object of the statemen... | [
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] | train | https://github.com/sorgerlab/indra/blob/79a70415832c5702d7a820c7c9ccc8e25010124b/indra/sources/bel/rdf_processor.py#L346-L421 |
sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_activation | def get_activation(self):
"""Extract INDRA Inhibition/Activation Statements from BEL.
The SPARQL query used to extract Activation Statements looks for
patterns in which the subject is is an ActivityType
(of a ProtainAbundance) or an Abundance (of a small molecule).
The object ha... | python | def get_activation(self):
"""Extract INDRA Inhibition/Activation Statements from BEL.
The SPARQL query used to extract Activation Statements looks for
patterns in which the subject is is an ActivityType
(of a ProtainAbundance) or an Abundance (of a small molecule).
The object ha... | [
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The SPARQL query used to extract Activation Statements looks for
patterns in which the subject is is an ActivityType
(of a ProtainAbundance) or an Abundance (of a small molecule).
The object has to be the ActivityType (typically o... | [
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_transcription | def get_transcription(self):
"""Extract Increase/DecreaseAmount INDRA Statements from BEL.
Three distinct SPARQL patterns are used to extract amount
regulations from BEL.
- q_tscript1 searches for a subject which is a Transcription
ActivityType of a ProteinAbundance and an ob... | python | def get_transcription(self):
"""Extract Increase/DecreaseAmount INDRA Statements from BEL.
Three distinct SPARQL patterns are used to extract amount
regulations from BEL.
- q_tscript1 searches for a subject which is a Transcription
ActivityType of a ProteinAbundance and an ob... | [
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"\"\"\"\n SELECT ?tfName ?targetName ?stmt ?tf ?target ?rel\n WHERE {\n ?stmt a belvoc:Statement .\n ?stmt belvoc:hasRelationship ?rel .\n ?st... | Extract Increase/DecreaseAmount INDRA Statements from BEL.
Three distinct SPARQL patterns are used to extract amount
regulations from BEL.
- q_tscript1 searches for a subject which is a Transcription
ActivityType of a ProteinAbundance and an object which is
an RNAAbundance ... | [
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_conversions | def get_conversions(self):
"""Extract Conversion INDRA Statements from BEL.
The SPARQL query used to extract Conversions searches for
a subject (controller) which is an AbundanceActivity
which directlyIncreases a Reaction with a given list of
Reactants and Products.
Ex... | python | def get_conversions(self):
"""Extract Conversion INDRA Statements from BEL.
The SPARQL query used to extract Conversions searches for
a subject (controller) which is an AbundanceActivity
which directlyIncreases a Reaction with a given list of
Reactants and Products.
Ex... | [
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The SPARQL query used to extract Conversions searches for
a subject (controller) which is an AbundanceActivity
which directlyIncreases a Reaction with a given list of
Reactants and Products.
Examples:
catalyticActivity... | [
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"from",
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_all_direct_statements | def get_all_direct_statements(self):
"""Get all directlyIncreases/Decreases BEL statements.
This method stores the results of the query in self.all_direct_stmts
as a list of strings. The SPARQL query used to find direct BEL
statements searches for all statements whose predicate is eithe... | python | def get_all_direct_statements(self):
"""Get all directlyIncreases/Decreases BEL statements.
This method stores the results of the query in self.all_direct_stmts
as a list of strings. The SPARQL query used to find direct BEL
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_all_indirect_statements | def get_all_indirect_statements(self):
"""Get all indirect increases/decreases BEL statements.
This method stores the results of the query in self.all_indirect_stmts
as a list of strings. The SPARQL query used to find indirect BEL
statements searches for all statements whose predicate i... | python | def get_all_indirect_statements(self):
"""Get all indirect increases/decreases BEL statements.
This method stores the results of the query in self.all_indirect_stmts
as a list of strings. The SPARQL query used to find indirect BEL
statements searches for all statements whose predicate i... | [
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.get_degenerate_statements | def get_degenerate_statements(self):
"""Get all degenerate BEL statements.
Stores the results of the query in self.degenerate_stmts.
"""
logger.info("Checking for 'degenerate' statements...\n")
# Get rules of type protein X -> activity Y
q_stmts = prefixes + """
... | python | def get_degenerate_statements(self):
"""Get all degenerate BEL statements.
Stores the results of the query in self.degenerate_stmts.
"""
logger.info("Checking for 'degenerate' statements...\n")
# Get rules of type protein X -> activity Y
q_stmts = prefixes + """
... | [
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.print_statement_coverage | def print_statement_coverage(self):
"""Display how many of the direct statements have been converted.
Also prints how many are considered 'degenerate' and not converted."""
if not self.all_direct_stmts:
self.get_all_direct_statements()
if not self.degenerate_stmts:
... | python | def print_statement_coverage(self):
"""Display how many of the direct statements have been converted.
Also prints how many are considered 'degenerate' and not converted."""
if not self.all_direct_stmts:
self.get_all_direct_statements()
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sorgerlab/indra | indra/sources/bel/rdf_processor.py | BelRdfProcessor.print_statements | def print_statements(self):
"""Print all extracted INDRA Statements."""
logger.info('--- Direct INDRA statements ----------')
for i, stmt in enumerate(self.statements):
logger.info("%s: %s" % (i, stmt))
logger.info('--- Indirect INDRA statements ----------')
for i, st... | python | def print_statements(self):
"""Print all extracted INDRA Statements."""
logger.info('--- Direct INDRA statements ----------')
for i, stmt in enumerate(self.statements):
logger.info("%s: %s" % (i, stmt))
logger.info('--- Indirect INDRA statements ----------')
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sorgerlab/indra | indra/sources/medscan/api.py | process_directory_statements_sorted_by_pmid | def process_directory_statements_sorted_by_pmid(directory_name):
"""Processes a directory filled with CSXML files, first normalizing the
character encoding to utf-8, and then processing into INDRA statements
sorted by pmid.
Parameters
----------
directory_name : str
The name of a direct... | python | def process_directory_statements_sorted_by_pmid(directory_name):
"""Processes a directory filled with CSXML files, first normalizing the
character encoding to utf-8, and then processing into INDRA statements
sorted by pmid.
Parameters
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The name of a direct... | [
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sorgerlab/indra | indra/sources/medscan/api.py | process_directory | def process_directory(directory_name, lazy=False):
"""Processes a directory filled with CSXML files, first normalizing the
character encodings to utf-8, and then processing into a list of INDRA
statements.
Parameters
----------
directory_name : str
The name of a directory filled with cs... | python | def process_directory(directory_name, lazy=False):
"""Processes a directory filled with CSXML files, first normalizing the
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directory_name : str
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sorgerlab/indra | indra/sources/medscan/api.py | process_file_sorted_by_pmid | def process_file_sorted_by_pmid(file_name):
"""Processes a file and returns a dictionary mapping pmids to a list of
statements corresponding to that pmid.
Parameters
----------
file_name : str
A csxml file to process
Returns
-------
s_dict : dict
Dictionary mapping pmid... | python | def process_file_sorted_by_pmid(file_name):
"""Processes a file and returns a dictionary mapping pmids to a list of
statements corresponding to that pmid.
Parameters
----------
file_name : str
A csxml file to process
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-------
s_dict : dict
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sorgerlab/indra | indra/sources/medscan/api.py | process_file | def process_file(filename, interval=None, lazy=False):
"""Process a CSXML file for its relevant information.
Consider running the fix_csxml_character_encoding.py script in
indra/sources/medscan to fix any encoding issues in the input file before
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sorgerlab/indra | indra/explanation/reporting.py | stmts_from_path | def stmts_from_path(path, model, stmts):
"""Return source Statements corresponding to a path in a model.
Parameters
----------
path : list[tuple[str, int]]
A list of tuples where the first element of the tuple is the
name of a rule, and the second is the associated polarity along
... | python | def stmts_from_path(path, model, stmts):
"""Return source Statements corresponding to a path in a model.
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A list of tuples where the first element of the tuple is the
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sorgerlab/indra | indra/sources/bel/processor.py | extract_context | def extract_context(annotations, annot_manager):
"""Return a BioContext object extracted from the annotations.
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sorgerlab/indra | indra/util/plot_formatting.py | format_axis | def format_axis(ax, label_padding=2, tick_padding=0, yticks_position='left'):
"""Set standardized axis formatting for figure."""
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"""Set standardized axis formatting for figure."""
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sorgerlab/indra | indra/assemblers/html/assembler.py | tag_text | def tag_text(text, tag_info_list):
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sorgerlab/indra | indra/assemblers/html/assembler.py | HtmlAssembler.make_model | def make_model(self):
"""Return the assembled HTML content as a string.
Returns
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stmts_formatted = []
stmt_rows = group_and_sort_statements(self.statements,
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sorgerlab/indra | indra/assemblers/html/assembler.py | HtmlAssembler.append_warning | def append_warning(self, msg):
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assert self.model is not None, "You must already have run make_model!"
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sorgerlab/indra | indra/assemblers/html/assembler.py | HtmlAssembler.save_model | def save_model(self, fname):
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The path to the file to save the HTML into.
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sorgerlab/indra | indra/sources/reach/api.py | process_pmc | def process_pmc(pmc_id, offline=False, output_fname=default_output_fname):
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sorgerlab/indra | indra/sources/reach/api.py | process_pubmed_abstract | def process_pubmed_abstract(pubmed_id, offline=False,
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sorgerlab/indra | indra/sources/reach/api.py | process_text | def process_text(text, citation=None, offline=False,
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sorgerlab/indra | indra/sources/reach/api.py | process_nxml_str | def process_nxml_str(nxml_str, citation=None, offline=False,
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... | Return a ReachProcessor by processing the given REACH json file.
The output from the REACH parser is in this json format. This function is
useful if the output is saved as a file and needs to be processed.
For more information on the format, see: https://github.com/clulab/reach
Parameters
--------... | [
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sorgerlab/indra | indra/sources/reach/api.py | process_json_str | def process_json_str(json_str, citation=None):
"""Return a ReachProcessor by processing the given REACH json string.
The output from the REACH parser is in this json format.
For more information on the format, see: https://github.com/clulab/reach
Parameters
----------
json_str : str
Th... | python | def process_json_str(json_str, citation=None):
"""Return a ReachProcessor by processing the given REACH json string.
The output from the REACH parser is in this json format.
For more information on the format, see: https://github.com/clulab/reach
Parameters
----------
json_str : str
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For more information on the format, see: https://github.com/clulab/reach
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json_str : str
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sorgerlab/indra | indra/tools/reading/wait_for_complete.py | make_parser | def make_parser():
"""Generate the parser for this script."""
parser = ArgumentParser(
'wait_for_complete.py',
usage='%(prog)s [-h] queue_name [options]',
description=('Wait for a set of batch jobs to complete, and monitor '
'them as they run.'),
epilog=('Job... | python | def make_parser():
"""Generate the parser for this script."""
parser = ArgumentParser(
'wait_for_complete.py',
usage='%(prog)s [-h] queue_name [options]',
description=('Wait for a set of batch jobs to complete, and monitor '
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epilog=('Job... | [
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sorgerlab/indra | indra/literature/__init__.py | id_lookup | def id_lookup(paper_id, idtype):
"""Take an ID of type PMID, PMCID, or DOI and lookup the other IDs.
If the DOI is not found in Pubmed, try to obtain the DOI by doing a
reverse-lookup of the DOI in CrossRef using article metadata.
Parameters
----------
paper_id : str
ID of the article.... | python | def id_lookup(paper_id, idtype):
"""Take an ID of type PMID, PMCID, or DOI and lookup the other IDs.
If the DOI is not found in Pubmed, try to obtain the DOI by doing a
reverse-lookup of the DOI in CrossRef using article metadata.
Parameters
----------
paper_id : str
ID of the article.... | [
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paper_id : str
ID of the article.
idtype : str
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sorgerlab/indra | indra/literature/__init__.py | get_full_text | def get_full_text(paper_id, idtype, preferred_content_type='text/xml'):
"""Return the content and the content type of an article.
This function retreives the content of an article by its PubMed ID,
PubMed Central ID, or DOI. It prioritizes full text content when available
and returns an abstract from P... | python | def get_full_text(paper_id, idtype, preferred_content_type='text/xml'):
"""Return the content and the content type of an article.
This function retreives the content of an article by its PubMed ID,
PubMed Central ID, or DOI. It prioritizes full text content when available
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This function retreives the content of an article by its PubMed ID,
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Parameters
----------
paper_id : string
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sorgerlab/indra | indra/sources/reach/reader.py | ReachReader.get_api_ruler | def get_api_ruler(self):
"""Return the existing reader if it exists or launch a new one.
Returns
-------
api_ruler : org.clulab.reach.apis.ApiRuler
An instance of the REACH ApiRuler class (java object).
"""
if self.api_ruler is None:
try:
... | python | def get_api_ruler(self):
"""Return the existing reader if it exists or launch a new one.
Returns
-------
api_ruler : org.clulab.reach.apis.ApiRuler
An instance of the REACH ApiRuler class (java object).
"""
if self.api_ruler is None:
try:
... | [
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... | Return the existing reader if it exists or launch a new one.
Returns
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api_ruler : org.clulab.reach.apis.ApiRuler
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sorgerlab/indra | indra/sources/biogrid.py | _download_biogrid_data | def _download_biogrid_data(url):
"""Downloads zipped, tab-separated Biogrid data in .tab2 format.
Parameters:
-----------
url : str
URL of the BioGrid zip file.
Returns
-------
csv.reader
A csv.reader object for iterating over the rows (header has already
been skipp... | python | def _download_biogrid_data(url):
"""Downloads zipped, tab-separated Biogrid data in .tab2 format.
Parameters:
-----------
url : str
URL of the BioGrid zip file.
Returns
-------
csv.reader
A csv.reader object for iterating over the rows (header has already
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url : str
URL of the BioGrid zip file.
Returns
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A csv.reader object for iterating over the rows (header has already
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sorgerlab/indra | indra/sources/biogrid.py | BiogridProcessor._make_agent | def _make_agent(self, entrez_id, text_id):
"""Make an Agent object, appropriately grounded.
Parameters
----------
entrez_id : str
Entrez id number
text_id : str
A plain text systematic name, or None if not listed.
Returns
-------
... | python | def _make_agent(self, entrez_id, text_id):
"""Make an Agent object, appropriately grounded.
Parameters
----------
entrez_id : str
Entrez id number
text_id : str
A plain text systematic name, or None if not listed.
Returns
-------
... | [
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Parameters
----------
entrez_id : str
Entrez id number
text_id : str
A plain text systematic name, or None if not listed.
Returns
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agent : indra.statements.Agent
A grounded ... | [
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