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sorgerlab/indra | indra/literature/pmc_client.py | id_lookup | def id_lookup(paper_id, idtype=None):
"""This function takes a Pubmed ID, Pubmed Central ID, or DOI
and use the Pubmed ID mapping
service and looks up all other IDs from one
of these. The IDs are returned in a dictionary."""
if idtype is not None and idtype not in ('pmid', 'pmcid', 'doi'):
r... | python | def id_lookup(paper_id, idtype=None):
"""This function takes a Pubmed ID, Pubmed Central ID, or DOI
and use the Pubmed ID mapping
service and looks up all other IDs from one
of these. The IDs are returned in a dictionary."""
if idtype is not None and idtype not in ('pmid', 'pmcid', 'doi'):
r... | [
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sorgerlab/indra | indra/literature/pmc_client.py | get_xml | def get_xml(pmc_id):
"""Returns XML for the article corresponding to a PMC ID."""
if pmc_id.upper().startswith('PMC'):
pmc_id = pmc_id[3:]
# Request params
params = {}
params['verb'] = 'GetRecord'
params['identifier'] = 'oai:pubmedcentral.nih.gov:%s' % pmc_id
params['metadataPrefix']... | python | def get_xml(pmc_id):
"""Returns XML for the article corresponding to a PMC ID."""
if pmc_id.upper().startswith('PMC'):
pmc_id = pmc_id[3:]
# Request params
params = {}
params['verb'] = 'GetRecord'
params['identifier'] = 'oai:pubmedcentral.nih.gov:%s' % pmc_id
params['metadataPrefix']... | [
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sorgerlab/indra | indra/literature/pmc_client.py | extract_paragraphs | def extract_paragraphs(xml_string):
"""Returns list of paragraphs in an NLM XML.
Parameters
----------
xml_string : str
String containing valid NLM XML.
Returns
-------
list of str
List of extracted paragraphs in an NLM XML
"""
tree = etree.fromstring(xml_string.enc... | python | def extract_paragraphs(xml_string):
"""Returns list of paragraphs in an NLM XML.
Parameters
----------
xml_string : str
String containing valid NLM XML.
Returns
-------
list of str
List of extracted paragraphs in an NLM XML
"""
tree = etree.fromstring(xml_string.enc... | [
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sorgerlab/indra | indra/literature/pmc_client.py | filter_pmids | def filter_pmids(pmid_list, source_type):
"""Filter a list of PMIDs for ones with full text from PMC.
Parameters
----------
pmid_list : list of str
List of PMIDs to filter.
source_type : string
One of 'fulltext', 'oa_xml', 'oa_txt', or 'auth_xml'.
Returns
-------
list o... | python | def filter_pmids(pmid_list, source_type):
"""Filter a list of PMIDs for ones with full text from PMC.
Parameters
----------
pmid_list : list of str
List of PMIDs to filter.
source_type : string
One of 'fulltext', 'oa_xml', 'oa_txt', or 'auth_xml'.
Returns
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list o... | [
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sorgerlab/indra | indra/sources/cwms/util.py | get_example_extractions | def get_example_extractions(fname):
"Get extractions from one of the examples in `cag_examples`."
with open(fname, 'r') as f:
sentences = f.read().splitlines()
rdf_xml_dict = {}
for sentence in sentences:
logger.info("Reading \"%s\"..." % sentence)
html = tc.send_query(sentence, ... | python | def get_example_extractions(fname):
"Get extractions from one of the examples in `cag_examples`."
with open(fname, 'r') as f:
sentences = f.read().splitlines()
rdf_xml_dict = {}
for sentence in sentences:
logger.info("Reading \"%s\"..." % sentence)
html = tc.send_query(sentence, ... | [
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sorgerlab/indra | indra/sources/cwms/util.py | make_example_graphs | def make_example_graphs():
"Make graphs from all the examples in cag_examples."
cag_example_rdfs = {}
for i, fname in enumerate(os.listdir('cag_examples')):
cag_example_rdfs[i+1] = get_example_extractions(fname)
return make_cag_graphs(cag_example_rdfs) | python | def make_example_graphs():
"Make graphs from all the examples in cag_examples."
cag_example_rdfs = {}
for i, fname in enumerate(os.listdir('cag_examples')):
cag_example_rdfs[i+1] = get_example_extractions(fname)
return make_cag_graphs(cag_example_rdfs) | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_agent_str | def _assemble_agent_str(agent):
"""Assemble an Agent object to text."""
agent_str = agent.name
# Only do the more detailed assembly for molecular agents
if not isinstance(agent, ist.Agent):
return agent_str
# Handle mutation conditions
if agent.mutations:
is_generic = False
... | python | def _assemble_agent_str(agent):
"""Assemble an Agent object to text."""
agent_str = agent.name
# Only do the more detailed assembly for molecular agents
if not isinstance(agent, ist.Agent):
return agent_str
# Handle mutation conditions
if agent.mutations:
is_generic = False
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sorgerlab/indra | indra/assemblers/english/assembler.py | _join_list | def _join_list(lst, oxford=False):
"""Join a list of words in a gramatically correct way."""
if len(lst) > 2:
s = ', '.join(lst[:-1])
if oxford:
s += ','
s += ' and ' + lst[-1]
elif len(lst) == 2:
s = lst[0] + ' and ' + lst[1]
elif len(lst) == 1:
s = l... | python | def _join_list(lst, oxford=False):
"""Join a list of words in a gramatically correct way."""
if len(lst) > 2:
s = ', '.join(lst[:-1])
if oxford:
s += ','
s += ' and ' + lst[-1]
elif len(lst) == 2:
s = lst[0] + ' and ' + lst[1]
elif len(lst) == 1:
s = l... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_activeform | def _assemble_activeform(stmt):
"""Assemble ActiveForm statements into text."""
subj_str = _assemble_agent_str(stmt.agent)
if stmt.is_active:
is_active_str = 'active'
else:
is_active_str = 'inactive'
if stmt.activity == 'activity':
stmt_str = subj_str + ' is ' + is_active_str... | python | def _assemble_activeform(stmt):
"""Assemble ActiveForm statements into text."""
subj_str = _assemble_agent_str(stmt.agent)
if stmt.is_active:
is_active_str = 'active'
else:
is_active_str = 'inactive'
if stmt.activity == 'activity':
stmt_str = subj_str + ' is ' + is_active_str... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_modification | def _assemble_modification(stmt):
"""Assemble Modification statements into text."""
sub_str = _assemble_agent_str(stmt.sub)
if stmt.enz is not None:
enz_str = _assemble_agent_str(stmt.enz)
if _get_is_direct(stmt):
mod_str = ' ' + _mod_process_verb(stmt) + ' '
else:
... | python | def _assemble_modification(stmt):
"""Assemble Modification statements into text."""
sub_str = _assemble_agent_str(stmt.sub)
if stmt.enz is not None:
enz_str = _assemble_agent_str(stmt.enz)
if _get_is_direct(stmt):
mod_str = ' ' + _mod_process_verb(stmt) + ' '
else:
... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_association | def _assemble_association(stmt):
"""Assemble Association statements into text."""
member_strs = [_assemble_agent_str(m.concept) for m in stmt.members]
stmt_str = member_strs[0] + ' is associated with ' + \
_join_list(member_strs[1:])
return _make_sentence(stmt_str) | python | def _assemble_association(stmt):
"""Assemble Association statements into text."""
member_strs = [_assemble_agent_str(m.concept) for m in stmt.members]
stmt_str = member_strs[0] + ' is associated with ' + \
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_complex | def _assemble_complex(stmt):
"""Assemble Complex statements into text."""
member_strs = [_assemble_agent_str(m) for m in stmt.members]
stmt_str = member_strs[0] + ' binds ' + _join_list(member_strs[1:])
return _make_sentence(stmt_str) | python | def _assemble_complex(stmt):
"""Assemble Complex statements into text."""
member_strs = [_assemble_agent_str(m) for m in stmt.members]
stmt_str = member_strs[0] + ' binds ' + _join_list(member_strs[1:])
return _make_sentence(stmt_str) | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_autophosphorylation | def _assemble_autophosphorylation(stmt):
"""Assemble Autophosphorylation statements into text."""
enz_str = _assemble_agent_str(stmt.enz)
stmt_str = enz_str + ' phosphorylates itself'
if stmt.residue is not None:
if stmt.position is None:
mod_str = 'on ' + ist.amino_acids[stmt.residu... | python | def _assemble_autophosphorylation(stmt):
"""Assemble Autophosphorylation statements into text."""
enz_str = _assemble_agent_str(stmt.enz)
stmt_str = enz_str + ' phosphorylates itself'
if stmt.residue is not None:
if stmt.position is None:
mod_str = 'on ' + ist.amino_acids[stmt.residu... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_regulate_activity | def _assemble_regulate_activity(stmt):
"""Assemble RegulateActivity statements into text."""
subj_str = _assemble_agent_str(stmt.subj)
obj_str = _assemble_agent_str(stmt.obj)
if stmt.is_activation:
rel_str = ' activates '
else:
rel_str = ' inhibits '
stmt_str = subj_str + rel_str... | python | def _assemble_regulate_activity(stmt):
"""Assemble RegulateActivity statements into text."""
subj_str = _assemble_agent_str(stmt.subj)
obj_str = _assemble_agent_str(stmt.obj)
if stmt.is_activation:
rel_str = ' activates '
else:
rel_str = ' inhibits '
stmt_str = subj_str + rel_str... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_regulate_amount | def _assemble_regulate_amount(stmt):
"""Assemble RegulateAmount statements into text."""
obj_str = _assemble_agent_str(stmt.obj)
if stmt.subj is not None:
subj_str = _assemble_agent_str(stmt.subj)
if isinstance(stmt, ist.IncreaseAmount):
rel_str = ' increases the amount of '
... | python | def _assemble_regulate_amount(stmt):
"""Assemble RegulateAmount statements into text."""
obj_str = _assemble_agent_str(stmt.obj)
if stmt.subj is not None:
subj_str = _assemble_agent_str(stmt.subj)
if isinstance(stmt, ist.IncreaseAmount):
rel_str = ' increases the amount of '
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_translocation | def _assemble_translocation(stmt):
"""Assemble Translocation statements into text."""
agent_str = _assemble_agent_str(stmt.agent)
stmt_str = agent_str + ' translocates'
if stmt.from_location is not None:
stmt_str += ' from the ' + stmt.from_location
if stmt.to_location is not None:
s... | python | def _assemble_translocation(stmt):
"""Assemble Translocation statements into text."""
agent_str = _assemble_agent_str(stmt.agent)
stmt_str = agent_str + ' translocates'
if stmt.from_location is not None:
stmt_str += ' from the ' + stmt.from_location
if stmt.to_location is not None:
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_gap | def _assemble_gap(stmt):
"""Assemble Gap statements into text."""
subj_str = _assemble_agent_str(stmt.gap)
obj_str = _assemble_agent_str(stmt.ras)
stmt_str = subj_str + ' is a GAP for ' + obj_str
return _make_sentence(stmt_str) | python | def _assemble_gap(stmt):
"""Assemble Gap statements into text."""
subj_str = _assemble_agent_str(stmt.gap)
obj_str = _assemble_agent_str(stmt.ras)
stmt_str = subj_str + ' is a GAP for ' + obj_str
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_gef | def _assemble_gef(stmt):
"""Assemble Gef statements into text."""
subj_str = _assemble_agent_str(stmt.gef)
obj_str = _assemble_agent_str(stmt.ras)
stmt_str = subj_str + ' is a GEF for ' + obj_str
return _make_sentence(stmt_str) | python | def _assemble_gef(stmt):
"""Assemble Gef statements into text."""
subj_str = _assemble_agent_str(stmt.gef)
obj_str = _assemble_agent_str(stmt.ras)
stmt_str = subj_str + ' is a GEF for ' + obj_str
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_conversion | def _assemble_conversion(stmt):
"""Assemble a Conversion statement into text."""
reactants = _join_list([_assemble_agent_str(r) for r in stmt.obj_from])
products = _join_list([_assemble_agent_str(r) for r in stmt.obj_to])
if stmt.subj is not None:
subj_str = _assemble_agent_str(stmt.subj)
... | python | def _assemble_conversion(stmt):
"""Assemble a Conversion statement into text."""
reactants = _join_list([_assemble_agent_str(r) for r in stmt.obj_from])
products = _join_list([_assemble_agent_str(r) for r in stmt.obj_to])
if stmt.subj is not None:
subj_str = _assemble_agent_str(stmt.subj)
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sorgerlab/indra | indra/assemblers/english/assembler.py | _assemble_influence | def _assemble_influence(stmt):
"""Assemble an Influence statement into text."""
subj_str = _assemble_agent_str(stmt.subj.concept)
obj_str = _assemble_agent_str(stmt.obj.concept)
# Note that n is prepended to increase to make it "an increase"
if stmt.subj.delta['polarity'] is not None:
subj_... | python | def _assemble_influence(stmt):
"""Assemble an Influence statement into text."""
subj_str = _assemble_agent_str(stmt.subj.concept)
obj_str = _assemble_agent_str(stmt.obj.concept)
# Note that n is prepended to increase to make it "an increase"
if stmt.subj.delta['polarity'] is not None:
subj_... | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _make_sentence | def _make_sentence(txt):
"""Make a sentence from a piece of text."""
#Make sure first letter is capitalized
txt = txt.strip(' ')
txt = txt[0].upper() + txt[1:] + '.'
return txt | python | def _make_sentence(txt):
"""Make a sentence from a piece of text."""
#Make sure first letter is capitalized
txt = txt.strip(' ')
txt = txt[0].upper() + txt[1:] + '.'
return txt | [
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sorgerlab/indra | indra/assemblers/english/assembler.py | _get_is_hypothesis | def _get_is_hypothesis(stmt):
'''Returns true if there is evidence that the statement is only
hypothetical. If all of the evidences associated with the statement
indicate a hypothetical interaction then we assume the interaction
is hypothetical.'''
for ev in stmt.evidence:
if not ev.epistemi... | python | def _get_is_hypothesis(stmt):
'''Returns true if there is evidence that the statement is only
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indicate a hypothetical interaction then we assume the interaction
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for ev in stmt.evidence:
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sorgerlab/indra | indra/assemblers/english/assembler.py | EnglishAssembler.make_model | def make_model(self):
"""Assemble text from the set of collected INDRA Statements.
Returns
-------
stmt_strs : str
Return the assembled text as unicode string. By default, the text
is a single string consisting of one or more sentences with
periods at... | python | def make_model(self):
"""Assemble text from the set of collected INDRA Statements.
Returns
-------
stmt_strs : str
Return the assembled text as unicode string. By default, the text
is a single string consisting of one or more sentences with
periods at... | [
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler.add_statements | def add_statements(self, stmts):
"""Add INDRA Statements to the assembler's list of statements.
Parameters
----------
stmts : list[indra.statements.Statement]
A list of :py:class:`indra.statements.Statement`
to be added to the statement list of the assembler.
... | python | def add_statements(self, stmts):
"""Add INDRA Statements to the assembler's list of statements.
Parameters
----------
stmts : list[indra.statements.Statement]
A list of :py:class:`indra.statements.Statement`
to be added to the statement list of the assembler.
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler.make_model | def make_model(self):
"""Assemble the SBGN model from the collected INDRA Statements.
This method assembles an SBGN model from the set of INDRA Statements.
The assembled model is set as the assembler's sbgn attribute (it is
represented as an XML ElementTree internally). The model is ret... | python | def make_model(self):
"""Assemble the SBGN model from the collected INDRA Statements.
This method assembles an SBGN model from the set of INDRA Statements.
The assembled model is set as the assembler's sbgn attribute (it is
represented as an XML ElementTree internally). The model is ret... | [
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler.print_model | def print_model(self, pretty=True, encoding='utf8'):
"""Return the assembled SBGN model as an XML string.
Parameters
----------
pretty : Optional[bool]
If True, the SBGN string is formatted with indentation (for human
viewing) otherwise no indentation is used. De... | python | def print_model(self, pretty=True, encoding='utf8'):
"""Return the assembled SBGN model as an XML string.
Parameters
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pretty : Optional[bool]
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler.save_model | def save_model(self, file_name='model.sbgn'):
"""Save the assembled SBGN model in a file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the SBGN network to.
Default: model.sbgn
"""
model = self.print_model()
... | python | def save_model(self, file_name='model.sbgn'):
"""Save the assembled SBGN model in a file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the SBGN network to.
Default: model.sbgn
"""
model = self.print_model()
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler._glyph_for_complex_pattern | def _glyph_for_complex_pattern(self, pattern):
"""Add glyph and member glyphs for a PySB ComplexPattern."""
# Make the main glyph for the agent
monomer_glyphs = []
for monomer_pattern in pattern.monomer_patterns:
glyph = self._glyph_for_monomer_pattern(monomer_pattern)
... | python | def _glyph_for_complex_pattern(self, pattern):
"""Add glyph and member glyphs for a PySB ComplexPattern."""
# Make the main glyph for the agent
monomer_glyphs = []
for monomer_pattern in pattern.monomer_patterns:
glyph = self._glyph_for_monomer_pattern(monomer_pattern)
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sorgerlab/indra | indra/assemblers/sbgn/assembler.py | SBGNAssembler._glyph_for_monomer_pattern | def _glyph_for_monomer_pattern(self, pattern):
"""Add glyph for a PySB MonomerPattern."""
pattern.matches_key = lambda: str(pattern)
agent_id = self._make_agent_id(pattern)
# Handle sources and sinks
if pattern.monomer.name in ('__source', '__sink'):
return None
... | python | def _glyph_for_monomer_pattern(self, pattern):
"""Add glyph for a PySB MonomerPattern."""
pattern.matches_key = lambda: str(pattern)
agent_id = self._make_agent_id(pattern)
# Handle sources and sinks
if pattern.monomer.name in ('__source', '__sink'):
return None
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sorgerlab/indra | indra/databases/go_client.py | load_go_graph | def load_go_graph(go_fname):
"""Load the GO data from an OWL file and parse into an RDF graph.
Parameters
----------
go_fname : str
Path to the GO OWL file. Can be downloaded from
http://geneontology.org/ontology/go.owl.
Returns
-------
rdflib.Graph
RDF graph contai... | python | def load_go_graph(go_fname):
"""Load the GO data from an OWL file and parse into an RDF graph.
Parameters
----------
go_fname : str
Path to the GO OWL file. Can be downloaded from
http://geneontology.org/ontology/go.owl.
Returns
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rdflib.Graph
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sorgerlab/indra | indra/databases/go_client.py | update_id_mappings | def update_id_mappings(g):
"""Compile all ID->label mappings and save to a TSV file.
Parameters
----------
g : rdflib.Graph
RDF graph containing GO data.
"""
g = load_go_graph(go_owl_path)
query = _prefixes + """
SELECT ?id ?label
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?class oboInOwl... | python | def update_id_mappings(g):
"""Compile all ID->label mappings and save to a TSV file.
Parameters
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g : rdflib.Graph
RDF graph containing GO data.
"""
g = load_go_graph(go_owl_path)
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sorgerlab/indra | indra/databases/ndex_client.py | get_default_ndex_cred | def get_default_ndex_cred(ndex_cred):
"""Gets the NDEx credentials from the dict, or tries the environment if None"""
if ndex_cred:
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sorgerlab/indra | indra/databases/ndex_client.py | send_request | def send_request(ndex_service_url, params, is_json=True, use_get=False):
"""Send a request to the NDEx server.
Parameters
----------
ndex_service_url : str
The URL of the service to use for the request.
params : dict
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"""Send a request to the NDEx server.
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ndex_service_url : str
The URL of the service to use for the request.
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sorgerlab/indra | indra/databases/ndex_client.py | create_network | def create_network(cx_str, ndex_cred=None, private=True):
"""Creates a new NDEx network of the assembled CX model.
To upload the assembled CX model to NDEx, you need to have
a registered account on NDEx (http://ndexbio.org/) and have
the `ndex` python package installed. The uploaded network
is priv... | python | def create_network(cx_str, ndex_cred=None, private=True):
"""Creates a new NDEx network of the assembled CX model.
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sorgerlab/indra | indra/databases/ndex_client.py | update_network | def update_network(cx_str, network_id, ndex_cred=None):
"""Update an existing CX network on NDEx with new CX content.
Parameters
----------
cx_str : str
String containing the CX content.
network_id : str
UUID of the network on NDEx.
ndex_cred : dict
A dictionary with the... | python | def update_network(cx_str, network_id, ndex_cred=None):
"""Update an existing CX network on NDEx with new CX content.
Parameters
----------
cx_str : str
String containing the CX content.
network_id : str
UUID of the network on NDEx.
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sorgerlab/indra | indra/databases/ndex_client.py | set_style | def set_style(network_id, ndex_cred=None, template_id=None):
"""Set the style of the network to a given template network's style
Parameters
----------
network_id : str
The UUID of the NDEx network whose style is to be changed.
ndex_cred : dict
A dictionary of NDEx credentials.
t... | python | def set_style(network_id, ndex_cred=None, template_id=None):
"""Set the style of the network to a given template network's style
Parameters
----------
network_id : str
The UUID of the NDEx network whose style is to be changed.
ndex_cred : dict
A dictionary of NDEx credentials.
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.initialize | def initialize(self, cfg_file=None, mode=None):
"""Initialize the model for simulation, possibly given a config file.
Parameters
----------
cfg_file : Optional[str]
The name of the configuration file to load, optional.
"""
self.sim = ScipyOdeSimulator(self.mo... | python | def initialize(self, cfg_file=None, mode=None):
"""Initialize the model for simulation, possibly given a config file.
Parameters
----------
cfg_file : Optional[str]
The name of the configuration file to load, optional.
"""
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.update | def update(self, dt=None):
"""Simulate the model for a given time interval.
Parameters
----------
dt : Optional[float]
The time step to simulate, if None, the default built-in time step
is used.
"""
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"""Simulate the model for a given time interval.
Parameters
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dt : Optional[float]
The time step to simulate, if None, the default built-in time step
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.set_value | def set_value(self, var_name, value):
"""Set the value of a given variable to a given value.
Parameters
----------
var_name : str
The name of the variable in the model whose value should be set.
value : float
The value the variable should be set to
... | python | def set_value(self, var_name, value):
"""Set the value of a given variable to a given value.
Parameters
----------
var_name : str
The name of the variable in the model whose value should be set.
value : float
The value the variable should be set to
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.get_value | def get_value(self, var_name):
"""Return the value of a given variable.
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----------
var_name : str
The name of the variable whose value should be returned
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-------
value : float
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.get_input_var_names | def get_input_var_names(self):
"""Return a list of variables names that can be set as input.
Returns
-------
var_names : list[str]
A list of variable names that can be set from the outside
"""
in_vars = copy.copy(self.input_vars)
for idx, var in enume... | python | def get_input_var_names(self):
"""Return a list of variables names that can be set as input.
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var_names : list[str]
A list of variable names that can be set from the outside
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.get_output_var_names | def get_output_var_names(self):
"""Return a list of variables names that can be read as output.
Returns
-------
var_names : list[str]
A list of variable names that can be read from the outside
"""
# Return all the variables that aren't input variables
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.make_repository_component | def make_repository_component(self):
"""Return an XML string representing this BMI in a workflow.
This description is required by EMELI to discover and load models.
Returns
-------
xml : str
String serialized XML representation of the component in the
mo... | python | def make_repository_component(self):
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xml : str
String serialized XML representation of the component in the
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel.export_into_python | def export_into_python(self):
"""Write the model into a pickle and create a module that loads it.
The model basically exports itself as a pickle file and a Python
file is then written which loads the pickle file. This allows importing
the model in the simulation workflow.
"""
... | python | def export_into_python(self):
"""Write the model into a pickle and create a module that loads it.
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file is then written which loads the pickle file. This allows importing
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sorgerlab/indra | indra/assemblers/pysb/bmi_wrapper.py | BMIModel._map_in_out | def _map_in_out(self, inside_var_name):
"""Return the external name of a variable mapped from inside."""
for out_name, in_name in self.outside_name_map.items():
if inside_var_name == in_name:
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return None | python | def _map_in_out(self, inside_var_name):
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | join_json_files | def join_json_files(prefix):
"""Join different REACH output JSON files into a single JSON object.
The output of REACH is broken into three files that need to be joined
before processing. Specifically, there will be three files of the form:
`<prefix>.uaz.<subcategory>.json`.
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--------... | python | def join_json_files(prefix):
"""Join different REACH output JSON files into a single JSON object.
The output of REACH is broken into three files that need to be joined
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | read_pmid | def read_pmid(pmid, source, cont_path, sparser_version, outbuf=None,
cleanup=True):
"Run sparser on a single pmid."
signal.signal(signal.SIGALRM, _timeout_handler)
signal.alarm(60)
try:
if (source is 'content_not_found'
or source.startswith('unhandled_content_type')
... | python | def read_pmid(pmid, source, cont_path, sparser_version, outbuf=None,
cleanup=True):
"Run sparser on a single pmid."
signal.signal(signal.SIGALRM, _timeout_handler)
signal.alarm(60)
try:
if (source is 'content_not_found'
or source.startswith('unhandled_content_type')
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | get_stmts | def get_stmts(pmids_unread, cleanup=True, sparser_version=None):
"Run sparser on the pmids in pmids_unread."
if sparser_version is None:
sparser_version = sparser.get_version()
stmts = {}
now = datetime.now()
outbuf_fname = 'sparser_%s_%s.log' % (
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sparser_version = sparser.get_version()
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | run_sparser | def run_sparser(pmid_list, tmp_dir, num_cores, start_index, end_index,
force_read, force_fulltext, cleanup=True, verbose=True):
'Run the sparser reader on the pmids in pmid_list.'
reader_version = sparser.get_version()
_, _, _, pmids_read, pmids_unread, _ =\
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... | python | def run_sparser(pmid_list, tmp_dir, num_cores, start_index, end_index,
force_read, force_fulltext, cleanup=True, verbose=True):
'Run the sparser reader on the pmids in pmid_list.'
reader_version = sparser.get_version()
_, _, _, pmids_read, pmids_unread, _ =\
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | upload_process_reach_files | def upload_process_reach_files(output_dir, pmid_info_dict, reader_version,
num_cores):
# At this point, we have a directory full of JSON files
# Collect all the prefixes into a set, then iterate over the prefixes
# Collect prefixes
json_files = glob.glob(os.path.join(outp... | python | def upload_process_reach_files(output_dir, pmid_info_dict, reader_version,
num_cores):
# At this point, we have a directory full of JSON files
# Collect all the prefixes into a set, then iterate over the prefixes
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failures_file = os.path.join(output_dir, 'failures.txt')
with open(failures_file, 'wt') as f:
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sorgerlab/indra | indra/tools/reading/pmid_reading/read_pmids.py | run_reach | def run_reach(pmid_list, base_dir, num_cores, start_index, end_index,
force_read, force_fulltext, cleanup=False, verbose=True):
"""Run reach on a list of pmids."""
logger.info('Running REACH with force_read=%s' % force_read)
logger.info('Running REACH with force_fulltext=%s' % force_fulltext)
... | python | def run_reach(pmid_list, base_dir, num_cores, start_index, end_index,
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logger.info('Running REACH with force_read=%s' % force_read)
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sorgerlab/indra | indra/statements/statements.py | get_all_descendants | def get_all_descendants(parent):
"""Get all the descendants of a parent class, recursively."""
children = parent.__subclasses__()
descendants = children[:]
for child in children:
descendants += get_all_descendants(child)
return descendants | python | def get_all_descendants(parent):
"""Get all the descendants of a parent class, recursively."""
children = parent.__subclasses__()
descendants = children[:]
for child in children:
descendants += get_all_descendants(child)
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sorgerlab/indra | indra/statements/statements.py | get_type_hierarchy | def get_type_hierarchy(s):
"""Get the sequence of parents from `s` to Statement.
Parameters
----------
s : a class or instance of a child of Statement
For example the statement `Phosphorylation(MEK(), ERK())` or just the
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Returns
-------
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"""Get the sequence of parents from `s` to Statement.
Parameters
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sorgerlab/indra | indra/statements/statements.py | get_statement_by_name | def get_statement_by_name(stmt_name):
"""Get a statement class given the name of the statement class."""
stmt_classes = get_all_descendants(Statement)
for stmt_class in stmt_classes:
if stmt_class.__name__.lower() == stmt_name.lower():
return stmt_class
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"""Get a statement class given the name of the statement class."""
stmt_classes = get_all_descendants(Statement)
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sorgerlab/indra | indra/statements/statements.py | get_unresolved_support_uuids | def get_unresolved_support_uuids(stmts):
"""Get uuids unresolved in support from stmts from stmts_from_json."""
return {s.uuid for stmt in stmts for s in stmt.supports + stmt.supported_by
if isinstance(s, Unresolved)} | python | def get_unresolved_support_uuids(stmts):
"""Get uuids unresolved in support from stmts from stmts_from_json."""
return {s.uuid for stmt in stmts for s in stmt.supports + stmt.supported_by
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sorgerlab/indra | indra/statements/statements.py | stmt_type | def stmt_type(obj, mk=True):
"""Return standardized, backwards compatible object type String.
This is a temporary solution to make sure type comparisons and
matches keys of Statements and related classes are backwards
compatible.
"""
if isinstance(obj, Statement) and mk:
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"""Return standardized, backwards compatible object type String.
This is a temporary solution to make sure type comparisons and
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"""
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sorgerlab/indra | indra/statements/statements.py | Statement.get_hash | def get_hash(self, shallow=True, refresh=False):
"""Get a hash for this Statement.
There are two types of hash, "shallow" and "full". A shallow hash is
as unique as the information carried by the statement, i.e. it is a hash
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"""Get a hash for this Statement.
There are two types of hash, "shallow" and "full". A shallow hash is
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sorgerlab/indra | indra/statements/statements.py | Statement._tag_evidence | def _tag_evidence(self):
"""Set all the Evidence stmt_tag to my deep matches-key hash."""
h = self.get_hash(shallow=False)
for ev in self.evidence:
ev.stmt_tag = h
return | python | def _tag_evidence(self):
"""Set all the Evidence stmt_tag to my deep matches-key hash."""
h = self.get_hash(shallow=False)
for ev in self.evidence:
ev.stmt_tag = h
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sorgerlab/indra | indra/statements/statements.py | Statement.agent_list | def agent_list(self, deep_sorted=False):
"""Get the canonicallized agent list."""
ag_list = []
for ag_name in self._agent_order:
ag_attr = getattr(self, ag_name)
if isinstance(ag_attr, Concept) or ag_attr is None:
ag_list.append(ag_attr)
elif i... | python | def agent_list(self, deep_sorted=False):
"""Get the canonicallized agent list."""
ag_list = []
for ag_name in self._agent_order:
ag_attr = getattr(self, ag_name)
if isinstance(ag_attr, Concept) or ag_attr is None:
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sorgerlab/indra | indra/statements/statements.py | Statement.to_json | def to_json(self, use_sbo=False):
"""Return serialized Statement as a JSON dict.
Parameters
----------
use_sbo : Optional[bool]
If True, SBO annotations are added to each applicable element of
the JSON. Default: False
Returns
-------
json... | python | def to_json(self, use_sbo=False):
"""Return serialized Statement as a JSON dict.
Parameters
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use_sbo : Optional[bool]
If True, SBO annotations are added to each applicable element of
the JSON. Default: False
Returns
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sorgerlab/indra | indra/statements/statements.py | Statement.to_graph | def to_graph(self):
"""Return Statement as a networkx graph."""
def json_node(graph, element, prefix):
if not element:
return None
node_id = '|'.join(prefix)
if isinstance(element, list):
graph.add_node(node_id, label='')
... | python | def to_graph(self):
"""Return Statement as a networkx graph."""
def json_node(graph, element, prefix):
if not element:
return None
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if isinstance(element, list):
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sorgerlab/indra | indra/statements/statements.py | Statement.make_generic_copy | def make_generic_copy(self, deeply=False):
"""Make a new matching Statement with no provenance.
All agents and other attributes besides evidence, belief, supports, and
supported_by will be copied over, and a new uuid will be assigned.
Thus, the new Statement will satisfy `new_stmt.match... | python | def make_generic_copy(self, deeply=False):
"""Make a new matching Statement with no provenance.
All agents and other attributes besides evidence, belief, supports, and
supported_by will be copied over, and a new uuid will be assigned.
Thus, the new Statement will satisfy `new_stmt.match... | [
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sorgerlab/indra | indra/databases/lincs_client.py | load_lincs_csv | def load_lincs_csv(url):
"""Helper function to turn csv rows into dicts."""
resp = requests.get(url, params={'output_type': '.csv'}, timeout=120)
resp.raise_for_status()
if sys.version_info[0] < 3:
csv_io = BytesIO(resp.content)
else:
csv_io = StringIO(resp.text)
data_rows = list... | python | def load_lincs_csv(url):
"""Helper function to turn csv rows into dicts."""
resp = requests.get(url, params={'output_type': '.csv'}, timeout=120)
resp.raise_for_status()
if sys.version_info[0] < 3:
csv_io = BytesIO(resp.content)
else:
csv_io = StringIO(resp.text)
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sorgerlab/indra | indra/databases/lincs_client.py | LincsClient.get_small_molecule_name | def get_small_molecule_name(self, hms_lincs_id):
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Parameters
----------
hms_lincs_id : str
The HMS LINCS ID of the small molecule.
Returns
-------
str
The name of the small mo... | python | def get_small_molecule_name(self, hms_lincs_id):
"""Get the name of a small molecule from the LINCS sm metadata.
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hms_lincs_id : str
The HMS LINCS ID of the small molecule.
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sorgerlab/indra | indra/databases/lincs_client.py | LincsClient.get_small_molecule_refs | def get_small_molecule_refs(self, hms_lincs_id):
"""Get the id refs of a small molecule from the LINCS sm metadata.
Parameters
----------
hms_lincs_id : str
The HMS LINCS ID of the small molecule.
Returns
-------
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"""Get the id refs of a small molecule from the LINCS sm metadata.
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hms_lincs_id : str
The HMS LINCS ID of the small molecule.
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sorgerlab/indra | indra/databases/lincs_client.py | LincsClient.get_protein_refs | def get_protein_refs(self, hms_lincs_id):
"""Get the refs for a protein from the LINCs protein metadata.
Parameters
----------
hms_lincs_id : str
The HMS LINCS ID for the protein
Returns
-------
dict
A dictionary of protein references.
... | python | def get_protein_refs(self, hms_lincs_id):
"""Get the refs for a protein from the LINCs protein metadata.
Parameters
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hms_lincs_id : str
The HMS LINCS ID for the protein
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sorgerlab/indra | indra/tools/gene_network.py | GeneNetwork.get_bel_stmts | def get_bel_stmts(self, filter=False):
"""Get relevant statements from the BEL large corpus.
Performs a series of neighborhood queries and then takes the union of
all the statements. Because the query process can take a long time for
large gene lists, the resulting list of statements ar... | python | def get_bel_stmts(self, filter=False):
"""Get relevant statements from the BEL large corpus.
Performs a series of neighborhood queries and then takes the union of
all the statements. Because the query process can take a long time for
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sorgerlab/indra | indra/tools/gene_network.py | GeneNetwork.get_biopax_stmts | def get_biopax_stmts(self, filter=False, query='pathsbetween',
database_filter=None):
"""Get relevant statements from Pathway Commons.
Performs a "paths between" query for the genes in :py:attr:`gene_list`
and uses the results to build statements. This function caches t... | python | def get_biopax_stmts(self, filter=False, query='pathsbetween',
database_filter=None):
"""Get relevant statements from Pathway Commons.
Performs a "paths between" query for the genes in :py:attr:`gene_list`
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sorgerlab/indra | indra/tools/gene_network.py | GeneNetwork.get_statements | def get_statements(self, filter=False):
"""Return the combined list of statements from BEL and Pathway Commons.
Internally calls :py:meth:`get_biopax_stmts` and
:py:meth:`get_bel_stmts`.
Parameters
----------
filter : bool
If True, includes only those statem... | python | def get_statements(self, filter=False):
"""Return the combined list of statements from BEL and Pathway Commons.
Internally calls :py:meth:`get_biopax_stmts` and
:py:meth:`get_bel_stmts`.
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----------
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sorgerlab/indra | indra/tools/gene_network.py | GeneNetwork.run_preassembly | def run_preassembly(self, stmts, print_summary=True):
"""Run complete preassembly procedure on the given statements.
Results are returned as a dict and stored in the attribute
:py:attr:`results`. They are also saved in the pickle file
`<basename>_results.pkl`.
Parameters
... | python | def run_preassembly(self, stmts, print_summary=True):
"""Run complete preassembly procedure on the given statements.
Results are returned as a dict and stored in the attribute
:py:attr:`results`. They are also saved in the pickle file
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sorgerlab/indra | indra/sources/hume/processor.py | _get_grounding | def _get_grounding(entity):
"""Return Hume grounding."""
db_refs = {'TEXT': entity['text']}
groundings = entity.get('grounding')
if not groundings:
return db_refs
def get_ont_concept(concept):
"""Strip slash, replace spaces and remove example leafs."""
# In the WM context, g... | python | def _get_grounding(entity):
"""Return Hume grounding."""
db_refs = {'TEXT': entity['text']}
groundings = entity.get('grounding')
if not groundings:
return db_refs
def get_ont_concept(concept):
"""Strip slash, replace spaces and remove example leafs."""
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._find_relations | def _find_relations(self):
"""Find all relevant relation elements and return them in a list."""
# Get all extractions
extractions = \
list(self.tree.execute("$.extractions[(@.@type is 'Extraction')]"))
# Get relations from extractions
relations = []
for e in ... | python | def _find_relations(self):
"""Find all relevant relation elements and return them in a list."""
# Get all extractions
extractions = \
list(self.tree.execute("$.extractions[(@.@type is 'Extraction')]"))
# Get relations from extractions
relations = []
for e in ... | [
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._get_documents | def _get_documents(self):
"""Populate sentences attribute with a dict keyed by document id."""
documents = self.tree.execute("$.documents")
for doc in documents:
sentences = {s['@id']: s['text'] for s in doc.get('sentences', [])}
self.document_dict[doc['@id']] = {'sentenc... | python | def _get_documents(self):
"""Populate sentences attribute with a dict keyed by document id."""
documents = self.tree.execute("$.documents")
for doc in documents:
sentences = {s['@id']: s['text'] for s in doc.get('sentences', [])}
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._make_context | def _make_context(self, entity):
"""Get place and time info from the json for this entity."""
loc_context = None
time_context = None
# Look for time and place contexts.
for argument in entity["arguments"]:
if argument["type"] == "place":
entity_id = a... | python | def _make_context(self, entity):
"""Get place and time info from the json for this entity."""
loc_context = None
time_context = None
# Look for time and place contexts.
for argument in entity["arguments"]:
if argument["type"] == "place":
entity_id = a... | [
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._make_concept | def _make_concept(self, entity):
"""Return Concept from a Hume entity."""
# Use the canonical name as the name of the Concept by default
name = self._sanitize(entity['canonicalName'])
# But if there is a trigger head text, we prefer that since
# it almost always results in a clea... | python | def _make_concept(self, entity):
"""Return Concept from a Hume entity."""
# Use the canonical name as the name of the Concept by default
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# But if there is a trigger head text, we prefer that since
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._get_event_and_context | def _get_event_and_context(self, event, arg_type):
"""Return an INDRA Event based on an event entry."""
eid = _choose_id(event, arg_type)
ev = self.concept_dict[eid]
concept, metadata = self._make_concept(ev)
ev_delta = {'adjectives': [],
'states': get_states(... | python | def _get_event_and_context(self, event, arg_type):
"""Return an INDRA Event based on an event entry."""
eid = _choose_id(event, arg_type)
ev = self.concept_dict[eid]
concept, metadata = self._make_concept(ev)
ev_delta = {'adjectives': [],
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sorgerlab/indra | indra/sources/hume/processor.py | HumeJsonLdProcessor._get_evidence | def _get_evidence(self, event, adjectives):
"""Return the Evidence object for the INDRA Statement."""
provenance = event.get('provenance')
# First try looking up the full sentence through provenance
doc_id = provenance[0]['document']['@id']
sent_id = provenance[0]['sentence']
... | python | def _get_evidence(self, event, adjectives):
"""Return the Evidence object for the INDRA Statement."""
provenance = event.get('provenance')
# First try looking up the full sentence through provenance
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sent_id = provenance[0]['sentence']
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sorgerlab/indra | indra/sources/medscan/processor.py | _is_statement_in_list | def _is_statement_in_list(new_stmt, old_stmt_list):
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sorgerlab/indra | indra/sources/medscan/processor.py | normalize_medscan_name | def normalize_medscan_name(name):
"""Removes the "complex" and "complex complex" suffixes from a medscan
agent name so that it better corresponds with the grounding map.
Parameters
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name: str
The Medscan agent name
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-------
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name: str
The Medscan agent name
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sorgerlab/indra | indra/sources/medscan/processor.py | _urn_to_db_refs | def _urn_to_db_refs(urn):
"""Converts a Medscan URN to an INDRA db_refs dictionary with grounding
information.
Parameters
----------
urn : str
A Medscan URN
Returns
-------
db_refs : dict
A dictionary with grounding information, mapping databases to database
ide... | python | def _urn_to_db_refs(urn):
"""Converts a Medscan URN to an INDRA db_refs dictionary with grounding
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Parameters
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urn : str
A Medscan URN
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-------
db_refs : dict
A dictionary with grounding information, mapping databases to database
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sorgerlab/indra | indra/sources/medscan/processor.py | _untag_sentence | def _untag_sentence(tagged_sentence):
"""Removes all tags in the sentence, returning the original sentence
without Medscan annotations.
Parameters
----------
tagged_sentence : str
The tagged sentence
Returns
-------
untagged_sentence : str
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tagged_sentence : str
The tagged sentence
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sorgerlab/indra | indra/sources/medscan/processor.py | _extract_sentence_tags | def _extract_sentence_tags(tagged_sentence):
"""Given a tagged sentence, extracts a dictionary mapping tags to the words
or phrases that they tag.
Parameters
----------
tagged_sentence : str
The sentence with Medscan annotations and tags
Returns
-------
tags : dict
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"""Given a tagged sentence, extracts a dictionary mapping tags to the words
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Parameters
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tagged_sentence : str
The sentence with Medscan annotations and tags
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sorgerlab/indra | indra/sources/medscan/processor.py | ProteinSiteInfo.get_sites | def get_sites(self):
"""Parse the site-text string and return a list of sites.
Returns
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sites : list[Site]
A list of position-residue pairs corresponding to the site-text
"""
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"""Parse the site-text string and return a list of sites.
Returns
-------
sites : list[Site]
A list of position-residue pairs corresponding to the site-text
"""
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sorgerlab/indra | indra/sources/medscan/processor.py | MedscanProcessor.process_csxml_file | def process_csxml_file(self, filename, interval=None, lazy=False):
"""Processes a filehandle to MedScan csxml input into INDRA
statements.
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containing a series of `<doc>` (document) elements, in turn containing
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sorgerlab/indra | indra/sources/medscan/processor.py | MedscanProcessor.process_relation | def process_relation(self, relation, last_relation):
"""Process a relation into an INDRA statement.
Parameters
----------
relation : MedscanRelation
The relation to process (a CONTROL svo with normalized verb)
last_relation : MedscanRelation
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"""Process a relation into an INDRA statement.
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----------
relation : MedscanRelation
The relation to process (a CONTROL svo with normalized verb)
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sorgerlab/indra | indra/sources/medscan/processor.py | MedscanProcessor.agent_from_entity | def agent_from_entity(self, relation, entity_id):
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"""Create a (potentially grounded) INDRA Agent object from a given
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sorgerlab/indra | indra/tools/reading/util/script_tools.py | get_parser | def get_parser(description, input_desc):
"""Get a parser that is generic to reading scripts.
Parameters
----------
description : str
A description of the tool, usually about one line long.
input_desc: str
A string describing the nature of the input file used by the reading
t... | python | def get_parser(description, input_desc):
"""Get a parser that is generic to reading scripts.
Parameters
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description : str
A description of the tool, usually about one line long.
input_desc: str
A string describing the nature of the input file used by the reading
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sorgerlab/indra | indra/literature/newsapi_client.py | send_request | def send_request(endpoint, **kwargs):
"""Return the response to a query as JSON from the NewsAPI web service.
The basic API is limited to 100 results which is chosen unless explicitly
given as an argument. Beyond that, paging is supported through the "page"
argument, if needed.
Parameters
----... | python | def send_request(endpoint, **kwargs):
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sorgerlab/indra | indra/sources/ndex_cx/api.py | process_cx_file | def process_cx_file(file_name, require_grounding=True):
"""Process a CX JSON file into Statements.
Parameters
----------
file_name : str
Path to file containing CX JSON.
require_grounding: bool
Whether network nodes lacking grounding information should be included
among the ... | python | def process_cx_file(file_name, require_grounding=True):
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Parameters
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file_name : str
Path to file containing CX JSON.
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sorgerlab/indra | indra/sources/ndex_cx/api.py | process_ndex_network | def process_ndex_network(network_id, username=None, password=None,
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"""Process an NDEx network into Statements.
Parameters
----------
network_id : str
NDEx network ID.
username : str
NDEx username.
password : str
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network_id : str
NDEx network ID.
username : str
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sorgerlab/indra | indra/sources/ndex_cx/api.py | process_cx | def process_cx(cx_json, summary=None, require_grounding=True):
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Parameters
----------
cx_json : list
CX JSON object.
summary : Optional[dict]
The network summary object which can be obtained via
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CX JSON object.
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sorgerlab/indra | indra/tools/reading/read_files.py | read_files | def read_files(files, readers, **kwargs):
"""Read the files in `files` with the reader objects in `readers`.
Parameters
----------
files : list [str]
A list of file paths to be read by the readers. Supported files are
limited to text and nxml files.
readers : list [Reader instances]... | python | def read_files(files, readers, **kwargs):
"""Read the files in `files` with the reader objects in `readers`.
Parameters
----------
files : list [str]
A list of file paths to be read by the readers. Supported files are
limited to text and nxml files.
readers : list [Reader instances]... | [
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sorgerlab/indra | indra/tools/expand_families.py | Expander.expand_families | def expand_families(self, stmts):
"""Generate statements by expanding members of families and complexes.
"""
new_stmts = []
for stmt in stmts:
# Put together the lists of families, with their members. E.g.,
# for a statement involving RAF and MEK, should return a ... | python | def expand_families(self, stmts):
"""Generate statements by expanding members of families and complexes.
"""
new_stmts = []
for stmt in stmts:
# Put together the lists of families, with their members. E.g.,
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sorgerlab/indra | indra/preassembler/make_eidos_hume_ontologies.py | update_ontology | def update_ontology(ont_url, rdf_path):
"""Load an ontology formatted like Eidos' from github."""
yaml_root = load_yaml_from_url(ont_url)
G = rdf_graph_from_yaml(yaml_root)
save_hierarchy(G, rdf_path) | python | def update_ontology(ont_url, rdf_path):
"""Load an ontology formatted like Eidos' from github."""
yaml_root = load_yaml_from_url(ont_url)
G = rdf_graph_from_yaml(yaml_root)
save_hierarchy(G, rdf_path) | [
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sorgerlab/indra | indra/preassembler/make_eidos_hume_ontologies.py | rdf_graph_from_yaml | def rdf_graph_from_yaml(yaml_root):
"""Convert the YAML object into an RDF Graph object."""
G = Graph()
for top_entry in yaml_root:
assert len(top_entry) == 1
node = list(top_entry.keys())[0]
build_relations(G, node, top_entry[node], None)
return G | python | def rdf_graph_from_yaml(yaml_root):
"""Convert the YAML object into an RDF Graph object."""
G = Graph()
for top_entry in yaml_root:
assert len(top_entry) == 1
node = list(top_entry.keys())[0]
build_relations(G, node, top_entry[node], None)
return G | [
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sorgerlab/indra | indra/preassembler/make_eidos_hume_ontologies.py | load_yaml_from_url | def load_yaml_from_url(ont_url):
"""Return a YAML object loaded from a YAML file URL."""
res = requests.get(ont_url)
if res.status_code != 200:
raise Exception('Could not load ontology from %s' % ont_url)
root = yaml.load(res.content)
return root | python | def load_yaml_from_url(ont_url):
"""Return a YAML object loaded from a YAML file URL."""
res = requests.get(ont_url)
if res.status_code != 200:
raise Exception('Could not load ontology from %s' % ont_url)
root = yaml.load(res.content)
return root | [
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sorgerlab/indra | indra/sources/isi/preprocessor.py | IsiPreprocessor.register_preprocessed_file | def register_preprocessed_file(self, infile, pmid, extra_annotations):
"""Set up already preprocessed text file for reading with ISI reader.
This is essentially a mock function to "register" already preprocessed
files and get an IsiPreprocessor object that can be passed to
the IsiProces... | python | def register_preprocessed_file(self, infile, pmid, extra_annotations):
"""Set up already preprocessed text file for reading with ISI reader.
This is essentially a mock function to "register" already preprocessed
files and get an IsiPreprocessor object that can be passed to
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sorgerlab/indra | indra/sources/isi/preprocessor.py | IsiPreprocessor.preprocess_plain_text_string | def preprocess_plain_text_string(self, text, pmid, extra_annotations):
"""Preprocess plain text string for use by ISI reader.
Preprocessing is done by tokenizing into sentences and writing
each sentence on its own line in a plain text file. All other
preprocessing functions ultimately c... | python | def preprocess_plain_text_string(self, text, pmid, extra_annotations):
"""Preprocess plain text string for use by ISI reader.
Preprocessing is done by tokenizing into sentences and writing
each sentence on its own line in a plain text file. All other
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sorgerlab/indra | indra/sources/isi/preprocessor.py | IsiPreprocessor.preprocess_plain_text_file | def preprocess_plain_text_file(self, filename, pmid, extra_annotations):
"""Preprocess a plain text file for use with ISI reder.
Preprocessing results in a new text file with one sentence
per line.
Parameters
----------
filename : str
The name of the plain t... | python | def preprocess_plain_text_file(self, filename, pmid, extra_annotations):
"""Preprocess a plain text file for use with ISI reder.
Preprocessing results in a new text file with one sentence
per line.
Parameters
----------
filename : str
The name of the plain t... | [
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sorgerlab/indra | indra/sources/isi/preprocessor.py | IsiPreprocessor.preprocess_nxml_file | def preprocess_nxml_file(self, filename, pmid, extra_annotations):
"""Preprocess an NXML file for use with the ISI reader.
Preprocessing is done by extracting plain text from NXML and then
creating a text file with one sentence per line.
Parameters
----------
filename :... | python | def preprocess_nxml_file(self, filename, pmid, extra_annotations):
"""Preprocess an NXML file for use with the ISI reader.
Preprocessing is done by extracting plain text from NXML and then
creating a text file with one sentence per line.
Parameters
----------
filename :... | [
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