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sorgerlab/indra | indra/assemblers/pysb/export.py | _prepare_kappa | def _prepare_kappa(model):
"""Return a Kappa STD with the model loaded."""
import kappy
kappa = kappy.KappaStd()
model_str = export(model, 'kappa')
kappa.add_model_string(model_str)
kappa.project_parse()
return kappa | python | def _prepare_kappa(model):
"""Return a Kappa STD with the model loaded."""
import kappy
kappa = kappy.KappaStd()
model_str = export(model, 'kappa')
kappa.add_model_string(model_str)
kappa.project_parse()
return kappa | [
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sorgerlab/indra | indra/databases/cbio_client.py | send_request | def send_request(**kwargs):
"""Return a data frame from a web service request to cBio portal.
Sends a web service requrest to the cBio portal with arguments given in
the dictionary data and returns a Pandas data frame on success.
More information about the service here:
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"""Return a data frame from a web service request to cBio portal.
Sends a web service requrest to the cBio portal with arguments given in
the dictionary data and returns a Pandas data frame on success.
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sorgerlab/indra | indra/databases/cbio_client.py | get_mutations | def get_mutations(study_id, gene_list, mutation_type=None,
case_id=None):
"""Return mutations as a list of genes and list of amino acid changes.
Parameters
----------
study_id : str
The ID of the cBio study.
Example: 'cellline_ccle_broad' or 'paad_icgc'
gene_list :... | python | def get_mutations(study_id, gene_list, mutation_type=None,
case_id=None):
"""Return mutations as a list of genes and list of amino acid changes.
Parameters
----------
study_id : str
The ID of the cBio study.
Example: 'cellline_ccle_broad' or 'paad_icgc'
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sorgerlab/indra | indra/databases/cbio_client.py | get_case_lists | def get_case_lists(study_id):
"""Return a list of the case set ids for a particular study.
TAKE NOTE the "case_list_id" are the same thing as "case_set_id"
Within the data, this string is referred to as a "case_list_id".
Within API calls it is referred to as a 'case_set_id'.
The documentation does ... | python | def get_case_lists(study_id):
"""Return a list of the case set ids for a particular study.
TAKE NOTE the "case_list_id" are the same thing as "case_set_id"
Within the data, this string is referred to as a "case_list_id".
Within API calls it is referred to as a 'case_set_id'.
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sorgerlab/indra | indra/databases/cbio_client.py | get_profile_data | def get_profile_data(study_id, gene_list,
profile_filter, case_set_filter=None):
"""Return dict of cases and genes and their respective values.
Parameters
----------
study_id : str
The ID of the cBio study.
Example: 'cellline_ccle_broad' or 'paad_icgc'
gene_list... | python | def get_profile_data(study_id, gene_list,
profile_filter, case_set_filter=None):
"""Return dict of cases and genes and their respective values.
Parameters
----------
study_id : str
The ID of the cBio study.
Example: 'cellline_ccle_broad' or 'paad_icgc'
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sorgerlab/indra | indra/databases/cbio_client.py | get_num_sequenced | def get_num_sequenced(study_id):
"""Return number of sequenced tumors for given study.
This is useful for calculating mutation statistics in terms of the
prevalence of certain mutations within a type of cancer.
Parameters
----------
study_id : str
The ID of the cBio study.
Exam... | python | def get_num_sequenced(study_id):
"""Return number of sequenced tumors for given study.
This is useful for calculating mutation statistics in terms of the
prevalence of certain mutations within a type of cancer.
Parameters
----------
study_id : str
The ID of the cBio study.
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sorgerlab/indra | indra/databases/cbio_client.py | get_cancer_studies | def get_cancer_studies(study_filter=None):
"""Return a list of cancer study identifiers, optionally filtered.
There are typically multiple studies for a given type of cancer and
a filter can be used to constrain the returned list.
Parameters
----------
study_filter : Optional[str]
A st... | python | def get_cancer_studies(study_filter=None):
"""Return a list of cancer study identifiers, optionally filtered.
There are typically multiple studies for a given type of cancer and
a filter can be used to constrain the returned list.
Parameters
----------
study_filter : Optional[str]
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sorgerlab/indra | indra/databases/cbio_client.py | get_cancer_types | def get_cancer_types(cancer_filter=None):
"""Return a list of cancer types, optionally filtered.
Parameters
----------
cancer_filter : Optional[str]
A string used to filter cancer types. Its value is the name or
part of the name of a type of cancer. Example: "melanoma",
"pancrea... | python | def get_cancer_types(cancer_filter=None):
"""Return a list of cancer types, optionally filtered.
Parameters
----------
cancer_filter : Optional[str]
A string used to filter cancer types. Its value is the name or
part of the name of a type of cancer. Example: "melanoma",
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sorgerlab/indra | indra/databases/cbio_client.py | get_ccle_mutations | def get_ccle_mutations(gene_list, cell_lines, mutation_type=None):
"""Return a dict of mutations in given genes and cell lines from CCLE.
This is a specialized call to get_mutations tailored to CCLE cell lines.
Parameters
----------
gene_list : list[str]
A list of HGNC gene symbols to get ... | python | def get_ccle_mutations(gene_list, cell_lines, mutation_type=None):
"""Return a dict of mutations in given genes and cell lines from CCLE.
This is a specialized call to get_mutations tailored to CCLE cell lines.
Parameters
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gene_list : list[str]
A list of HGNC gene symbols to get ... | [
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sorgerlab/indra | indra/databases/cbio_client.py | get_ccle_lines_for_mutation | def get_ccle_lines_for_mutation(gene, amino_acid_change):
"""Return cell lines with a given point mutation in a given gene.
Checks which cell lines in CCLE have a particular point mutation
in a given gene and return their names in a list.
Parameters
----------
gene : str
The HGNC symbo... | python | def get_ccle_lines_for_mutation(gene, amino_acid_change):
"""Return cell lines with a given point mutation in a given gene.
Checks which cell lines in CCLE have a particular point mutation
in a given gene and return their names in a list.
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gene : str
The HGNC symbo... | [
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sorgerlab/indra | indra/databases/cbio_client.py | get_ccle_cna | def get_ccle_cna(gene_list, cell_lines):
"""Return a dict of CNAs in given genes and cell lines from CCLE.
CNA values correspond to the following alterations
-2 = homozygous deletion
-1 = hemizygous deletion
0 = neutral / no change
1 = gain
2 = high level amplification
Parameters
... | python | def get_ccle_cna(gene_list, cell_lines):
"""Return a dict of CNAs in given genes and cell lines from CCLE.
CNA values correspond to the following alterations
-2 = homozygous deletion
-1 = hemizygous deletion
0 = neutral / no change
1 = gain
2 = high level amplification
Parameters
... | [
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sorgerlab/indra | indra/databases/cbio_client.py | get_ccle_mrna | def get_ccle_mrna(gene_list, cell_lines):
"""Return a dict of mRNA amounts in given genes and cell lines from CCLE.
Parameters
----------
gene_list : list[str]
A list of HGNC gene symbols to get mRNA amounts for.
cell_lines : list[str]
A list of CCLE cell line names to get mRNA amou... | python | def get_ccle_mrna(gene_list, cell_lines):
"""Return a dict of mRNA amounts in given genes and cell lines from CCLE.
Parameters
----------
gene_list : list[str]
A list of HGNC gene symbols to get mRNA amounts for.
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sorgerlab/indra | indra/databases/cbio_client.py | _filter_data_frame | def _filter_data_frame(df, data_col, filter_col, filter_str=None):
"""Return a filtered data frame as a dictionary."""
if filter_str is not None:
relevant_cols = data_col + [filter_col]
df.dropna(inplace=True, subset=relevant_cols)
row_filter = df[filter_col].str.contains(filter_str, cas... | python | def _filter_data_frame(df, data_col, filter_col, filter_str=None):
"""Return a filtered data frame as a dictionary."""
if filter_str is not None:
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sorgerlab/indra | rest_api/api.py | allow_cors | def allow_cors(func):
"""This is a decorator which enable CORS for the specified endpoint."""
def wrapper(*args, **kwargs):
response.headers['Access-Control-Allow-Origin'] = '*'
response.headers['Access-Control-Allow-Methods'] = \
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response.he... | python | def allow_cors(func):
"""This is a decorator which enable CORS for the specified endpoint."""
def wrapper(*args, **kwargs):
response.headers['Access-Control-Allow-Origin'] = '*'
response.headers['Access-Control-Allow-Methods'] = \
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sorgerlab/indra | rest_api/api.py | trips_process_text | def trips_process_text():
"""Process text with TRIPS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
tp = trips.process_text(text)
return _stmts_from_proc(tp) | python | def trips_process_text():
"""Process text with TRIPS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
tp = trips.process_text(text)
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sorgerlab/indra | rest_api/api.py | trips_process_xml | def trips_process_xml():
"""Process TRIPS EKB XML and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
xml_str = body.get('xml_str')
tp = trips.process_xml(xml_str)
return _stmts_from_proc... | python | def trips_process_xml():
"""Process TRIPS EKB XML and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
xml_str = body.get('xml_str')
tp = trips.process_xml(xml_str)
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sorgerlab/indra | rest_api/api.py | reach_process_text | def reach_process_text():
"""Process text with REACH and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
offline = True if body.get('offline') else False
rp = reac... | python | def reach_process_text():
"""Process text with REACH and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
offline = True if body.get('offline') else False
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sorgerlab/indra | rest_api/api.py | reach_process_json | def reach_process_json():
"""Process REACH json and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
json_str = body.get('json')
rp = reach.process_json_str(json_str)
return _stmts_from_pr... | python | def reach_process_json():
"""Process REACH json and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
json_str = body.get('json')
rp = reach.process_json_str(json_str)
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sorgerlab/indra | rest_api/api.py | reach_process_pmc | def reach_process_pmc():
"""Process PubMedCentral article and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
pmcid = body.get('pmcid')
rp = reach.process_pmc(pmcid)
return _stmts_from_pr... | python | def reach_process_pmc():
"""Process PubMedCentral article and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
pmcid = body.get('pmcid')
rp = reach.process_pmc(pmcid)
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sorgerlab/indra | rest_api/api.py | bel_process_pybel_neighborhood | def bel_process_pybel_neighborhood():
"""Process BEL Large Corpus neighborhood and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
bp = bel.process_pybel_neighborhoo... | python | def bel_process_pybel_neighborhood():
"""Process BEL Large Corpus neighborhood and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
bp = bel.process_pybel_neighborhoo... | [
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sorgerlab/indra | rest_api/api.py | bel_process_belrdf | def bel_process_belrdf():
"""Process BEL RDF and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
belrdf = body.get('belrdf')
bp = bel.process_belrdf(belrdf)
return _stmts_from_proc(bp) | python | def bel_process_belrdf():
"""Process BEL RDF and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
belrdf = body.get('belrdf')
bp = bel.process_belrdf(belrdf)
return _stmts_from_proc(bp) | [
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sorgerlab/indra | rest_api/api.py | biopax_process_pc_pathsbetween | def biopax_process_pc_pathsbetween():
"""Process PathwayCommons paths between genes, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
bp = biopax.process_pc_pathsbetw... | python | def biopax_process_pc_pathsbetween():
"""Process PathwayCommons paths between genes, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
bp = biopax.process_pc_pathsbetw... | [
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sorgerlab/indra | rest_api/api.py | biopax_process_pc_pathsfromto | def biopax_process_pc_pathsfromto():
"""Process PathwayCommons paths from-to genes, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
source = body.get('source')
target = body.get('target')
... | python | def biopax_process_pc_pathsfromto():
"""Process PathwayCommons paths from-to genes, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
source = body.get('source')
target = body.get('target')
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sorgerlab/indra | rest_api/api.py | biopax_process_pc_neighborhood | def biopax_process_pc_neighborhood():
"""Process PathwayCommons neighborhood, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
bp = biopax.process_pc_neighborhood(gen... | python | def biopax_process_pc_neighborhood():
"""Process PathwayCommons neighborhood, return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
genes = body.get('genes')
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sorgerlab/indra | rest_api/api.py | eidos_process_text | def eidos_process_text():
"""Process text with EIDOS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
req = request.body.read().decode('utf-8')
body = json.loads(req)
text = body.get('text')
webservice = body.get('webservice')
if not webservice:
respo... | python | def eidos_process_text():
"""Process text with EIDOS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
req = request.body.read().decode('utf-8')
body = json.loads(req)
text = body.get('text')
webservice = body.get('webservice')
if not webservice:
respo... | [
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sorgerlab/indra | rest_api/api.py | eidos_process_jsonld | def eidos_process_jsonld():
"""Process an EIDOS JSON-LD and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
eidos_json = body.get('jsonld')
ep = eidos.process_json_str(eidos_json)
return ... | python | def eidos_process_jsonld():
"""Process an EIDOS JSON-LD and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
eidos_json = body.get('jsonld')
ep = eidos.process_json_str(eidos_json)
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sorgerlab/indra | rest_api/api.py | cwms_process_text | def cwms_process_text():
"""Process text with CWMS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
cp = cwms.process_text(text)
return _stmts_from_proc(cp) | python | def cwms_process_text():
"""Process text with CWMS and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
cp = cwms.process_text(text)
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sorgerlab/indra | rest_api/api.py | hume_process_jsonld | def hume_process_jsonld():
"""Process Hume JSON-LD and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
jsonld_str = body.get('jsonld')
jsonld = json.loads(jsonld_str)
hp = hume.process_js... | python | def hume_process_jsonld():
"""Process Hume JSON-LD and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
jsonld_str = body.get('jsonld')
jsonld = json.loads(jsonld_str)
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sorgerlab/indra | rest_api/api.py | sofia_process_text | def sofia_process_text():
"""Process text with Sofia and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
auth = body.get('auth')
sp = sofia.process_text(text, auth... | python | def sofia_process_text():
"""Process text with Sofia and return INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
text = body.get('text')
auth = body.get('auth')
sp = sofia.process_text(text, auth... | [
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sorgerlab/indra | rest_api/api.py | assemble_pysb | def assemble_pysb():
"""Assemble INDRA Statements and return PySB model string."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
export_format = body.get('export_format')
stmts ... | python | def assemble_pysb():
"""Assemble INDRA Statements and return PySB model string."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
export_format = body.get('export_format')
stmts ... | [
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sorgerlab/indra | rest_api/api.py | assemble_cx | def assemble_cx():
"""Assemble INDRA Statements and return CX network json."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
ca = CxAssembler... | python | def assemble_cx():
"""Assemble INDRA Statements and return CX network json."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
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sorgerlab/indra | rest_api/api.py | share_model_ndex | def share_model_ndex():
"""Upload the model to NDEX"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_str = body.get('stmts')
stmts_json = json.loads(stmts_str)
stmts = stmts_from_json(stmts_json["statements"... | python | def share_model_ndex():
"""Upload the model to NDEX"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_str = body.get('stmts')
stmts_json = json.loads(stmts_str)
stmts = stmts_from_json(stmts_json["statements"... | [
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sorgerlab/indra | rest_api/api.py | fetch_model_ndex | def fetch_model_ndex():
"""Download model and associated pieces from NDEX"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
network_id = body.get('network_id')
cx = process_ndex_network(network_id)
network_attr = [... | python | def fetch_model_ndex():
"""Download model and associated pieces from NDEX"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
network_id = body.get('network_id')
cx = process_ndex_network(network_id)
network_attr = [... | [
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sorgerlab/indra | rest_api/api.py | assemble_graph | def assemble_graph():
"""Assemble INDRA Statements and return Graphviz graph dot string."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
ga ... | python | def assemble_graph():
"""Assemble INDRA Statements and return Graphviz graph dot string."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
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sorgerlab/indra | rest_api/api.py | assemble_cyjs | def assemble_cyjs():
"""Assemble INDRA Statements and return Cytoscape JS network."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
cja = CyJ... | python | def assemble_cyjs():
"""Assemble INDRA Statements and return Cytoscape JS network."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
cja = CyJ... | [
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sorgerlab/indra | rest_api/api.py | assemble_english | def assemble_english():
"""Assemble each statement into """
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
sentences = {}
for st in stmts:... | python | def assemble_english():
"""Assemble each statement into """
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
sentences = {}
for st in stmts:... | [
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sorgerlab/indra | rest_api/api.py | assemble_loopy | def assemble_loopy():
"""Assemble INDRA Statements into a Loopy model using SIF Assembler."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
s... | python | def assemble_loopy():
"""Assemble INDRA Statements into a Loopy model using SIF Assembler."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
s... | [
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sorgerlab/indra | rest_api/api.py | get_ccle_mrna_levels | def get_ccle_mrna_levels():
"""Get CCLE mRNA amounts using cBioClient"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
gene_list = body.get('gene_list')
cell_lines = body.get('cell_lines')
mrna_amounts = cbio_clie... | python | def get_ccle_mrna_levels():
"""Get CCLE mRNA amounts using cBioClient"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
gene_list = body.get('gene_list')
cell_lines = body.get('cell_lines')
mrna_amounts = cbio_clie... | [
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sorgerlab/indra | rest_api/api.py | get_ccle_mutations | def get_ccle_mutations():
"""Get CCLE mutations
returns the amino acid changes for a given list of genes and cell lines
"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
gene_list = body.get('gene_list')
cell_... | python | def get_ccle_mutations():
"""Get CCLE mutations
returns the amino acid changes for a given list of genes and cell lines
"""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
gene_list = body.get('gene_list')
cell_... | [
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sorgerlab/indra | rest_api/api.py | map_grounding | def map_grounding():
"""Map grounding on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
stmts_out = ac.map_grou... | python | def map_grounding():
"""Map grounding on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
stmts_out = ac.map_grou... | [
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sorgerlab/indra | rest_api/api.py | run_preassembly | def run_preassembly():
"""Run preassembly on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
scorer = body.get('... | python | def run_preassembly():
"""Run preassembly on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
scorer = body.get('... | [
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sorgerlab/indra | rest_api/api.py | map_ontologies | def map_ontologies():
"""Run ontology mapping on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
om = OntologyMa... | python | def map_ontologies():
"""Run ontology mapping on a list of INDRA Statements."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmts = stmts_from_json(stmts_json)
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sorgerlab/indra | rest_api/api.py | filter_by_type | def filter_by_type():
"""Filter to a given INDRA Statement type."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmt_type_str = body.get('type')
stmt_type_str = stmt_type_str.... | python | def filter_by_type():
"""Filter to a given INDRA Statement type."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
stmt_type_str = body.get('type')
stmt_type_str = stmt_type_str.... | [
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sorgerlab/indra | rest_api/api.py | filter_grounded_only | def filter_grounded_only():
"""Filter to grounded Statements only."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
score_threshold = body.get('score_threshold')
if score_thresh... | python | def filter_grounded_only():
"""Filter to grounded Statements only."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
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sorgerlab/indra | rest_api/api.py | filter_belief | def filter_belief():
"""Filter to beliefs above a given threshold."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
belief_cutoff = body.get('belief_cutoff')
if belief_cutoff is... | python | def filter_belief():
"""Filter to beliefs above a given threshold."""
if request.method == 'OPTIONS':
return {}
response = request.body.read().decode('utf-8')
body = json.loads(response)
stmts_json = body.get('statements')
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sorgerlab/indra | indra/util/get_version.py | get_git_info | def get_git_info():
"""Get a dict with useful git info."""
start_dir = abspath(curdir)
try:
chdir(dirname(abspath(__file__)))
re_patt_str = (r'commit\s+(?P<commit_hash>\w+).*?Author:\s+'
r'(?P<author_name>.*?)\s+<(?P<author_email>.*?)>\s+Date:\s+'
... | python | def get_git_info():
"""Get a dict with useful git info."""
start_dir = abspath(curdir)
try:
chdir(dirname(abspath(__file__)))
re_patt_str = (r'commit\s+(?P<commit_hash>\w+).*?Author:\s+'
r'(?P<author_name>.*?)\s+<(?P<author_email>.*?)>\s+Date:\s+'
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sorgerlab/indra | indra/util/get_version.py | get_version | def get_version(with_git_hash=True, refresh_hash=False):
"""Get an indra version string, including a git hash."""
version = __version__
if with_git_hash:
global INDRA_GITHASH
if INDRA_GITHASH is None or refresh_hash:
with open(devnull, 'w') as nul:
try:
... | python | def get_version(with_git_hash=True, refresh_hash=False):
"""Get an indra version string, including a git hash."""
version = __version__
if with_git_hash:
global INDRA_GITHASH
if INDRA_GITHASH is None or refresh_hash:
with open(devnull, 'w') as nul:
try:
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sorgerlab/indra | indra/assemblers/cx/assembler.py | _fix_evidence_text | def _fix_evidence_text(txt):
"""Eliminate some symbols to have cleaner supporting text."""
txt = re.sub('[ ]?\( xref \)', '', txt)
# This is to make [ xref ] become [] to match the two readers
txt = re.sub('\[ xref \]', '[]', txt)
txt = re.sub('[\(]?XREF_BIBR[\)]?[,]?', '', txt)
txt = re.sub('[\... | python | def _fix_evidence_text(txt):
"""Eliminate some symbols to have cleaner supporting text."""
txt = re.sub('[ ]?\( xref \)', '', txt)
# This is to make [ xref ] become [] to match the two readers
txt = re.sub('\[ xref \]', '[]', txt)
txt = re.sub('[\(]?XREF_BIBR[\)]?[,]?', '', txt)
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sorgerlab/indra | indra/assemblers/cx/assembler.py | CxAssembler.make_model | def make_model(self, add_indra_json=True):
"""Assemble the CX network from the collected INDRA Statements.
This method assembles a CX network from the set of INDRA Statements.
The assembled network is set as the assembler's cx argument.
Parameters
----------
add_indra_j... | python | def make_model(self, add_indra_json=True):
"""Assemble the CX network from the collected INDRA Statements.
This method assembles a CX network from the set of INDRA Statements.
The assembled network is set as the assembler's cx argument.
Parameters
----------
add_indra_j... | [
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sorgerlab/indra | indra/assemblers/cx/assembler.py | CxAssembler.print_cx | def print_cx(self, pretty=True):
"""Return the assembled CX network as a json string.
Parameters
----------
pretty : bool
If True, the CX string is formatted with indentation (for human
viewing) otherwise no indentation is used.
Returns
-------
... | python | def print_cx(self, pretty=True):
"""Return the assembled CX network as a json string.
Parameters
----------
pretty : bool
If True, the CX string is formatted with indentation (for human
viewing) otherwise no indentation is used.
Returns
-------
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sorgerlab/indra | indra/assemblers/cx/assembler.py | CxAssembler.save_model | def save_model(self, file_name='model.cx'):
"""Save the assembled CX network in a file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the CX network to. Default: model.cx
"""
with open(file_name, 'wt') as fh:
cx_str ... | python | def save_model(self, file_name='model.cx'):
"""Save the assembled CX network in a file.
Parameters
----------
file_name : Optional[str]
The name of the file to save the CX network to. Default: model.cx
"""
with open(file_name, 'wt') as fh:
cx_str ... | [
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sorgerlab/indra | indra/assemblers/cx/assembler.py | CxAssembler.set_context | def set_context(self, cell_type):
"""Set protein expression data and mutational status as node attribute
This method uses :py:mod:`indra.databases.context_client` to get
protein expression levels and mutational status for a given cell type
and set a node attribute for proteins according... | python | def set_context(self, cell_type):
"""Set protein expression data and mutational status as node attribute
This method uses :py:mod:`indra.databases.context_client` to get
protein expression levels and mutational status for a given cell type
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sorgerlab/indra | indra/databases/biogrid_client.py | get_publications | def get_publications(gene_names, save_json_name=None):
"""Return evidence publications for interaction between the given genes.
Parameters
----------
gene_names : list[str]
A list of gene names (HGNC symbols) to query interactions between.
Currently supports exactly two genes only.
... | python | def get_publications(gene_names, save_json_name=None):
"""Return evidence publications for interaction between the given genes.
Parameters
----------
gene_names : list[str]
A list of gene names (HGNC symbols) to query interactions between.
Currently supports exactly two genes only.
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sorgerlab/indra | indra/assemblers/pysb/common.py | _n | def _n(name):
"""Return valid PySB name."""
n = name.encode('ascii', errors='ignore').decode('ascii')
n = re.sub('[^A-Za-z0-9_]', '_', n)
n = re.sub(r'(^[0-9].*)', r'p\1', n)
return n | python | def _n(name):
"""Return valid PySB name."""
n = name.encode('ascii', errors='ignore').decode('ascii')
n = re.sub('[^A-Za-z0-9_]', '_', n)
n = re.sub(r'(^[0-9].*)', r'p\1', n)
return n | [
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sorgerlab/indra | indra/sources/indra_db_rest/processor.py | IndraDBRestProcessor.get_hash_statements_dict | def get_hash_statements_dict(self):
"""Return a dict of Statements keyed by hashes."""
res = {stmt_hash: stmts_from_json([stmt])[0]
for stmt_hash, stmt in self.__statement_jsons.items()}
return res | python | def get_hash_statements_dict(self):
"""Return a dict of Statements keyed by hashes."""
res = {stmt_hash: stmts_from_json([stmt])[0]
for stmt_hash, stmt in self.__statement_jsons.items()}
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sorgerlab/indra | indra/sources/indra_db_rest/processor.py | IndraDBRestProcessor.merge_results | def merge_results(self, other_processor):
"""Merge the results of this processor with those of another."""
if not isinstance(other_processor, self.__class__):
raise ValueError("Can only extend with another %s instance."
% self.__class__.__name__)
self.sta... | python | def merge_results(self, other_processor):
"""Merge the results of this processor with those of another."""
if not isinstance(other_processor, self.__class__):
raise ValueError("Can only extend with another %s instance."
% self.__class__.__name__)
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sorgerlab/indra | indra/sources/indra_db_rest/processor.py | IndraDBRestProcessor.wait_until_done | def wait_until_done(self, timeout=None):
"""Wait for the background load to complete."""
start = datetime.now()
if not self.__th:
raise IndraDBRestResponseError("There is no thread waiting to "
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self.__th.join(timeout)
... | python | def wait_until_done(self, timeout=None):
"""Wait for the background load to complete."""
start = datetime.now()
if not self.__th:
raise IndraDBRestResponseError("There is no thread waiting to "
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self.__th.join(timeout)
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sorgerlab/indra | indra/sources/indra_db_rest/processor.py | IndraDBRestProcessor._merge_json | def _merge_json(self, stmt_json, ev_counts):
"""Merge these statement jsons with new jsons."""
# Where there is overlap, there _should_ be agreement.
self.__evidence_counts.update(ev_counts)
for k, sj in stmt_json.items():
if k not in self.__statement_jsons:
... | python | def _merge_json(self, stmt_json, ev_counts):
"""Merge these statement jsons with new jsons."""
# Where there is overlap, there _should_ be agreement.
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sorgerlab/indra | indra/sources/indra_db_rest/processor.py | IndraDBRestProcessor._run_queries | def _run_queries(self, agent_strs, stmt_types, params, persist):
"""Use paging to get all statements requested."""
self._query_over_statement_types(agent_strs, stmt_types, params)
assert len(self.__done_dict) == len(stmt_types) \
or None in self.__done_dict.keys(), \
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"""Use paging to get all statements requested."""
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sorgerlab/indra | indra/literature/pubmed_client.py | get_ids | def get_ids(search_term, **kwargs):
"""Search Pubmed for paper IDs given a search term.
Search options can be passed as keyword arguments, some of which are
custom keywords identified by this function, while others are passed on
as parameters for the request to the PubMed web service
For details on... | python | def get_ids(search_term, **kwargs):
"""Search Pubmed for paper IDs given a search term.
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sorgerlab/indra | indra/literature/pubmed_client.py | get_id_count | def get_id_count(search_term):
"""Get the number of citations in Pubmed for a search query.
Parameters
----------
search_term : str
A term for which the PubMed search should be performed.
Returns
-------
int or None
The number of citations for the query, or None if the quer... | python | def get_id_count(search_term):
"""Get the number of citations in Pubmed for a search query.
Parameters
----------
search_term : str
A term for which the PubMed search should be performed.
Returns
-------
int or None
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sorgerlab/indra | indra/literature/pubmed_client.py | get_ids_for_gene | def get_ids_for_gene(hgnc_name, **kwargs):
"""Get the curated set of articles for a gene in the Entrez database.
Search parameters for the Gene database query can be passed in as
keyword arguments.
Parameters
----------
hgnc_name : string
The HGNC name of the gene. This is used to obt... | python | def get_ids_for_gene(hgnc_name, **kwargs):
"""Get the curated set of articles for a gene in the Entrez database.
Search parameters for the Gene database query can be passed in as
keyword arguments.
Parameters
----------
hgnc_name : string
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sorgerlab/indra | indra/literature/pubmed_client.py | get_article_xml | def get_article_xml(pubmed_id):
"""Get the XML metadata for a single article from the Pubmed database.
"""
if pubmed_id.upper().startswith('PMID'):
pubmed_id = pubmed_id[4:]
params = {'db': 'pubmed',
'retmode': 'xml',
'id': pubmed_id}
tree = send_request(pubmed_fe... | python | def get_article_xml(pubmed_id):
"""Get the XML metadata for a single article from the Pubmed database.
"""
if pubmed_id.upper().startswith('PMID'):
pubmed_id = pubmed_id[4:]
params = {'db': 'pubmed',
'retmode': 'xml',
'id': pubmed_id}
tree = send_request(pubmed_fe... | [
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sorgerlab/indra | indra/literature/pubmed_client.py | get_abstract | def get_abstract(pubmed_id, prepend_title=True):
"""Get the abstract of an article in the Pubmed database."""
article = get_article_xml(pubmed_id)
if article is None:
return None
return _abstract_from_article_element(article, prepend_title) | python | def get_abstract(pubmed_id, prepend_title=True):
"""Get the abstract of an article in the Pubmed database."""
article = get_article_xml(pubmed_id)
if article is None:
return None
return _abstract_from_article_element(article, prepend_title) | [
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sorgerlab/indra | indra/literature/pubmed_client.py | get_metadata_from_xml_tree | def get_metadata_from_xml_tree(tree, get_issns_from_nlm=False,
get_abstracts=False, prepend_title=False,
mesh_annotations=False):
"""Get metadata for an XML tree containing PubmedArticle elements.
Documentation on the XML structure can be found at:
... | python | def get_metadata_from_xml_tree(tree, get_issns_from_nlm=False,
get_abstracts=False, prepend_title=False,
mesh_annotations=False):
"""Get metadata for an XML tree containing PubmedArticle elements.
Documentation on the XML structure can be found at:
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sorgerlab/indra | indra/literature/pubmed_client.py | get_metadata_for_ids | def get_metadata_for_ids(pmid_list, get_issns_from_nlm=False,
get_abstracts=False, prepend_title=False):
"""Get article metadata for up to 200 PMIDs from the Pubmed database.
Parameters
----------
pmid_list : list of PMIDs as strings
Can contain 1-200 PMIDs.
get_iss... | python | def get_metadata_for_ids(pmid_list, get_issns_from_nlm=False,
get_abstracts=False, prepend_title=False):
"""Get article metadata for up to 200 PMIDs from the Pubmed database.
Parameters
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pmid_list : list of PMIDs as strings
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sorgerlab/indra | indra/literature/pubmed_client.py | get_issns_for_journal | def get_issns_for_journal(nlm_id):
"""Get a list of the ISSN numbers for a journal given its NLM ID.
Information on NLM XML DTDs is available at
https://www.nlm.nih.gov/databases/dtd/
"""
params = {'db': 'nlmcatalog',
'retmode': 'xml',
'id': nlm_id}
tree = send_reque... | python | def get_issns_for_journal(nlm_id):
"""Get a list of the ISSN numbers for a journal given its NLM ID.
Information on NLM XML DTDs is available at
https://www.nlm.nih.gov/databases/dtd/
"""
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sorgerlab/indra | indra/explanation/model_checker.py | remove_im_params | def remove_im_params(model, im):
"""Remove parameter nodes from the influence map.
Parameters
----------
model : pysb.core.Model
PySB model.
im : networkx.MultiDiGraph
Influence map.
Returns
-------
networkx.MultiDiGraph
Influence map with the parameter nodes re... | python | def remove_im_params(model, im):
"""Remove parameter nodes from the influence map.
Parameters
----------
model : pysb.core.Model
PySB model.
im : networkx.MultiDiGraph
Influence map.
Returns
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sorgerlab/indra | indra/explanation/model_checker.py | _get_signed_predecessors | def _get_signed_predecessors(im, node, polarity):
"""Get upstream nodes in the influence map.
Return the upstream nodes along with the overall polarity of the path
to that node by account for the polarity of the path to the given node
and the polarity of the edge between the given node and its immediat... | python | def _get_signed_predecessors(im, node, polarity):
"""Get upstream nodes in the influence map.
Return the upstream nodes along with the overall polarity of the path
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sorgerlab/indra | indra/explanation/model_checker.py | _get_edge_sign | def _get_edge_sign(im, edge):
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edge_data = im[edge[0]][edge[1]]
# Handle possible multiple edges between nodes
signs = list(set([v['sign'] for v in edge_data.values()
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if len(signs... | python | def _get_edge_sign(im, edge):
"""Get the polarity of the influence by examining the edge sign."""
edge_data = im[edge[0]][edge[1]]
# Handle possible multiple edges between nodes
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sorgerlab/indra | indra/explanation/model_checker.py | _add_modification_to_agent | def _add_modification_to_agent(agent, mod_type, residue, position):
"""Add a modification condition to an Agent."""
new_mod = ModCondition(mod_type, residue, position)
# Check if this modification already exists
for old_mod in agent.mods:
if old_mod.equals(new_mod):
return agent
... | python | def _add_modification_to_agent(agent, mod_type, residue, position):
"""Add a modification condition to an Agent."""
new_mod = ModCondition(mod_type, residue, position)
# Check if this modification already exists
for old_mod in agent.mods:
if old_mod.equals(new_mod):
return agent
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sorgerlab/indra | indra/explanation/model_checker.py | _match_lhs | def _match_lhs(cp, rules):
"""Get rules with a left-hand side matching the given ComplexPattern."""
rule_matches = []
for rule in rules:
reactant_pattern = rule.rule_expression.reactant_pattern
for rule_cp in reactant_pattern.complex_patterns:
if _cp_embeds_into(rule_cp, cp):
... | python | def _match_lhs(cp, rules):
"""Get rules with a left-hand side matching the given ComplexPattern."""
rule_matches = []
for rule in rules:
reactant_pattern = rule.rule_expression.reactant_pattern
for rule_cp in reactant_pattern.complex_patterns:
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sorgerlab/indra | indra/explanation/model_checker.py | _cp_embeds_into | def _cp_embeds_into(cp1, cp2):
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# Check that any state in cp2 is matched in cp1
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sorgerlab/indra | indra/explanation/model_checker.py | _mp_embeds_into | def _mp_embeds_into(mp1, mp2):
"""Check that conditions in MonomerPattern2 are met in MonomerPattern1."""
sc_matches = []
if mp1.monomer.name != mp2.monomer.name:
return False
# Check that all conditions in mp2 are met in mp1
for site_name, site_state in mp2.site_conditions.items():
... | python | def _mp_embeds_into(mp1, mp2):
"""Check that conditions in MonomerPattern2 are met in MonomerPattern1."""
sc_matches = []
if mp1.monomer.name != mp2.monomer.name:
return False
# Check that all conditions in mp2 are met in mp1
for site_name, site_state in mp2.site_conditions.items():
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sorgerlab/indra | indra/explanation/model_checker.py | _monomer_pattern_label | def _monomer_pattern_label(mp):
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sorgerlab/indra | indra/explanation/model_checker.py | _stmt_from_rule | def _stmt_from_rule(model, rule_name, stmts):
"""Return the INDRA Statement corresponding to a given rule by name."""
stmt_uuid = None
for ann in model.annotations:
if ann.predicate == 'from_indra_statement':
if ann.subject == rule_name:
stmt_uuid = ann.object
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"""Return the INDRA Statement corresponding to a given rule by name."""
stmt_uuid = None
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if ann.subject == rule_name:
stmt_uuid = ann.object
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.generate_im | def generate_im(self, model):
"""Return a graph representing the influence map generated by Kappa
Parameters
----------
model : pysb.Model
The PySB model whose influence map is to be generated
Returns
-------
graph : networkx.MultiDiGraph
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"""Return a graph representing the influence map generated by Kappa
Parameters
----------
model : pysb.Model
The PySB model whose influence map is to be generated
Returns
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graph : networkx.MultiDiGraph
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.draw_im | def draw_im(self, fname):
"""Draw and save the influence map in a file.
Parameters
----------
fname : str
The name of the file to save the influence map in.
The extension of the file will determine the file format,
typically png or pdf.
"""
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"""Draw and save the influence map in a file.
Parameters
----------
fname : str
The name of the file to save the influence map in.
The extension of the file will determine the file format,
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.get_im | def get_im(self, force_update=False):
"""Get the influence map for the model, generating it if necessary.
Parameters
----------
force_update : bool
Whether to generate the influence map when the function is called.
If False, returns the previously generated influ... | python | def get_im(self, force_update=False):
"""Get the influence map for the model, generating it if necessary.
Parameters
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force_update : bool
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.check_model | def check_model(self, max_paths=1, max_path_length=5):
"""Check all the statements added to the ModelChecker.
Parameters
----------
max_paths : Optional[int]
The maximum number of specific paths to return for each Statement
to be explained. Default: 1
max... | python | def check_model(self, max_paths=1, max_path_length=5):
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max_paths : Optional[int]
The maximum number of specific paths to return for each Statement
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.check_statement | def check_statement(self, stmt, max_paths=1, max_path_length=5):
"""Check a single Statement against the model.
Parameters
----------
stmt : indra.statements.Statement
The Statement to check.
max_paths : Optional[int]
The maximum number of specific paths ... | python | def check_statement(self, stmt, max_paths=1, max_path_length=5):
"""Check a single Statement against the model.
Parameters
----------
stmt : indra.statements.Statement
The Statement to check.
max_paths : Optional[int]
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.score_paths | def score_paths(self, paths, agents_values, loss_of_function=False,
sigma=0.15, include_final_node=False):
"""Return scores associated with a given set of paths.
Parameters
----------
paths : list[list[tuple[str, int]]]
A list of paths obtained from path ... | python | def score_paths(self, paths, agents_values, loss_of_function=False,
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.prune_influence_map | def prune_influence_map(self):
"""Remove edges between rules causing problematic non-transitivity.
First, all self-loops are removed. After this initial step, edges are
removed between rules when they share *all* child nodes except for each
other; that is, they have a mutual relationshi... | python | def prune_influence_map(self):
"""Remove edges between rules causing problematic non-transitivity.
First, all self-loops are removed. After this initial step, edges are
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sorgerlab/indra | indra/explanation/model_checker.py | ModelChecker.prune_influence_map_subj_obj | def prune_influence_map_subj_obj(self):
"""Prune influence map to include only edges where the object of the
upstream rule matches the subject of the downstream rule."""
def get_rule_info(r):
result = {}
for ann in self.model.annotations:
if ann.subject ==... | python | def prune_influence_map_subj_obj(self):
"""Prune influence map to include only edges where the object of the
upstream rule matches the subject of the downstream rule."""
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result = {}
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter.add_section | def add_section(self, section_name):
"""Create a section of the report, to be headed by section_name
Text and images can be added by using the `section` argument of the
`add_text` and `add_image` methods. Sections can also be ordered by
using the `set_section_order` method.
By ... | python | def add_section(self, section_name):
"""Create a section of the report, to be headed by section_name
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter.set_section_order | def set_section_order(self, section_name_list):
"""Set the order of the sections, which are by default unorderd.
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"""
self.section_headings = section_name_list[:]
for sectio... | python | def set_section_order(self, section_name_list):
"""Set the order of the sections, which are by default unorderd.
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter.add_text | def add_text(self, text, *args, **kwargs):
"""Add text to the document.
Text is shown on the final document in the order it is added, either
within the given section or as part of the un-sectioned list of content.
Parameters
----------
text : str
The text to... | python | def add_text(self, text, *args, **kwargs):
"""Add text to the document.
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter.add_image | def add_image(self, image_path, width=None, height=None, section=None):
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter.make_report | def make_report(self, sections_first=True, section_header_params=None):
"""Create the pdf document with name `self.name + '.pdf'`.
Parameters
----------
sections_first : bool
If True (default), text and images with sections are presented first
and un-sectioned co... | python | def make_report(self, sections_first=True, section_header_params=None):
"""Create the pdf document with name `self.name + '.pdf'`.
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sections_first : bool
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter._make_sections | def _make_sections(self, **section_hdr_params):
"""Flatten the sections into a single story list."""
sect_story = []
if not self.section_headings and len(self.sections):
self.section_headings = self.sections.keys()
for section_name in self.section_headings:
secti... | python | def _make_sections(self, **section_hdr_params):
"""Flatten the sections into a single story list."""
sect_story = []
if not self.section_headings and len(self.sections):
self.section_headings = self.sections.keys()
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sorgerlab/indra | indra/tools/reading/util/reporter.py | Reporter._preformat_text | def _preformat_text(self, text, style='Normal', space=None, fontsize=12,
alignment='left'):
"""Format the text for addition to a story list."""
if space is None:
space=(1,12)
ptext = ('<para alignment=\"%s\"><font size=%d>%s</font></para>'
% (... | python | def _preformat_text(self, text, style='Normal', space=None, fontsize=12,
alignment='left'):
"""Format the text for addition to a story list."""
if space is None:
space=(1,12)
ptext = ('<para alignment=\"%s\"><font size=%d>%s</font></para>'
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sorgerlab/indra | indra/databases/mesh_client.py | get_mesh_name_from_web | def get_mesh_name_from_web(mesh_id):
"""Get the MESH label for the given MESH ID using the NLM REST API.
Parameters
----------
mesh_id : str
MESH Identifier, e.g. 'D003094'.
Returns
-------
str
Label for the MESH ID, or None if the query failed or no label was
found... | python | def get_mesh_name_from_web(mesh_id):
"""Get the MESH label for the given MESH ID using the NLM REST API.
Parameters
----------
mesh_id : str
MESH Identifier, e.g. 'D003094'.
Returns
-------
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Label for the MESH ID, or None if the query failed or no label was
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sorgerlab/indra | indra/databases/mesh_client.py | get_mesh_name | def get_mesh_name(mesh_id, offline=False):
"""Get the MESH label for the given MESH ID.
Uses the mappings table in `indra/resources`; if the MESH ID is not listed
there, falls back on the NLM REST API.
Parameters
----------
mesh_id : str
MESH Identifier, e.g. 'D003094'.
offline : b... | python | def get_mesh_name(mesh_id, offline=False):
"""Get the MESH label for the given MESH ID.
Uses the mappings table in `indra/resources`; if the MESH ID is not listed
there, falls back on the NLM REST API.
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mesh_id : str
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sorgerlab/indra | indra/databases/mesh_client.py | get_mesh_id_name | def get_mesh_id_name(mesh_term, offline=False):
"""Get the MESH ID and name for the given MESH term.
Uses the mappings table in `indra/resources`; if the MESH term is not
listed there, falls back on the NLM REST API.
Parameters
----------
mesh_term : str
MESH Descriptor or Concept name... | python | def get_mesh_id_name(mesh_term, offline=False):
"""Get the MESH ID and name for the given MESH term.
Uses the mappings table in `indra/resources`; if the MESH term is not
listed there, falls back on the NLM REST API.
Parameters
----------
mesh_term : str
MESH Descriptor or Concept name... | [
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sorgerlab/indra | indra/tools/machine/cli.py | make | def make(directory):
"""Makes a RAS Machine directory"""
if os.path.exists(directory):
if os.path.isdir(directory):
click.echo('Directory already exists')
else:
click.echo('Path exists and is not a directory')
sys.exit()
os.makedirs(directory)
os.mkdir(o... | python | def make(directory):
"""Makes a RAS Machine directory"""
if os.path.exists(directory):
if os.path.isdir(directory):
click.echo('Directory already exists')
else:
click.echo('Path exists and is not a directory')
sys.exit()
os.makedirs(directory)
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sorgerlab/indra | indra/tools/machine/cli.py | run_with_search | def run_with_search(model_path, config, num_days):
"""Run with PubMed search for new papers."""
from indra.tools.machine.machine import run_with_search_helper
run_with_search_helper(model_path, config, num_days=num_days) | python | def run_with_search(model_path, config, num_days):
"""Run with PubMed search for new papers."""
from indra.tools.machine.machine import run_with_search_helper
run_with_search_helper(model_path, config, num_days=num_days) | [
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sorgerlab/indra | indra/tools/machine/cli.py | run_with_pmids | def run_with_pmids(model_path, pmids):
"""Run with given list of PMIDs."""
from indra.tools.machine.machine import run_with_pmids_helper
run_with_pmids_helper(model_path, pmids) | python | def run_with_pmids(model_path, pmids):
"""Run with given list of PMIDs."""
from indra.tools.machine.machine import run_with_pmids_helper
run_with_pmids_helper(model_path, pmids) | [
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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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