def run_reading(text_contents, cached=True):
organism_preference = None
stmts = {}
for trid, text_content in text_contents.items():
print('Reading %s' % trid)
output_fname = os.path.join(NEW_REACH_PATH, '%s.json' % trid)
if cached and os.path.exists(output_fname):
rp = reach.process_json_file(output_fname)
if rp is None:
continue
else:
if text_content.startswith('<!DOCTYPE'):
rp = reach.process_nxml_str(
text_content,
url=reach.local_nxml_url,
output_fname=output_fname,
organism_priority=organism_preference)
else:
rp = reach.process_text(text_content,
url=reach.local_text_url,
output_fname=output_fname,
organism_priority=organism_preference)
if rp is not None:
stmts[trid] = rp.statements
return stmts
def process_paper(model_name, pmid):
json_path = os.path.join(model_name, 'jsons', 'PMID%s.json' % pmid)
if pmid.startswith('api') or pmid.startswith('PMID'):
logger.warning('Invalid PMID: %s' % pmid)
# If the paper has been read, use the json output file
if os.path.exists(json_path):
rp = reach.process_json_file(json_path, citation=pmid)
txt_format = 'existing_json'
# If the paper has not been read, download the text and read
else:
try:
txt, txt_format = get_full_text(pmid, 'pmid')
except:
return None, None
if txt_format == 'pmc_oa_xml':
rp = reach.process_nxml_str(txt, citation=pmid, offline=True)
if os.path.exists('reach_output.json'):
shutil.move('reach_output.json', json_path)
elif txt_format == 'elsevier_xml':
# Extract the raw text from the Elsevier XML
txt = elsevier_client.extract_text(txt)
rp = reach.process_text(txt, citation=pmid, offline=True)
if os.path.exists('reach_output.json'):
shutil.move('reach_output.json', json_path)
elif txt_format == 'abstract':
rp = reach.process_text(txt, citation=pmid, offline=True)
if os.path.exists('reach_output.json'):
shutil.move('reach_output.json', json_path)
else:
rp = None
if rp is not None:
check_pmids(rp.statements)
return rp, txt_format
def test_phosphorylation_regulation():
here = os.path.dirname(os.path.abspath(__file__))
test_file = os.path.join(here, 'reach_reg_phos.json')
rp = reach.process_json_file(test_file)
assert rp is not None
assert len(rp.statements) == 1
stmt = rp.statements[0]
assert isinstance(stmt, Phosphorylation), stmt
assert not stmt.sub.mods
def test_amount_embedded_in_activation():
here = os.path.dirname(os.path.abspath(__file__))
test_file = os.path.join(here, 'reach_act_amt.json')
rp = reach.process_json_file(test_file)
assert rp is not None
assert len(rp.statements) == 1
assert isinstance(rp.statements[0], IncreaseAmount)
assert rp.statements[0].subj is not None
assert rp.statements[0].obj is not None
def process_paper(model_name, pmid):
"""Process a paper with the given pubmed identifier
Parameters
----------
model_name : str
The directory for the INDRA machine
pmid : str
The PMID to process.
Returns
-------
rp : ReachProcessor
A ReachProcessor containing the extracted INDRA Statements
in rp.statements.
txt_format : str
A string representing the format of the text
"""
json_directory = os.path.join(model_name, 'jsons')
json_path = os.path.join(json_directory, 'PMID%s.json' % pmid)
if pmid.startswith('api') or pmid.startswith('PMID'):
logger.warning('Invalid PMID: %s' % pmid)
# If the paper has been read, use the json output file
if os.path.exists(json_path):
rp = reach.process_json_file(json_path, citation=pmid)
txt_format = 'existing_json'
# If the paper has not been read, download the text and read
else:
try:
txt, txt_format = get_full_text(pmid, 'pmid')
except Exception:
return None, None
if txt_format == 'pmc_oa_xml':
rp = reach.process_nxml_str(txt,
citation=pmid,
offline=True,
output_fname=json_path)
elif txt_format == 'elsevier_xml':
# Extract the raw text from the Elsevier XML
txt = elsevier_client.extract_text(txt)
rp = reach.process_text(txt,
citation=pmid,
offline=True,
output_fname=json_path)
elif txt_format == 'abstract':
rp = reach.process_text(txt,
citation=pmid,
offline=True,
output_fname=json_path)
else:
rp = None
if rp is not None:
check_pmids(rp.statements)
return rp, txt_format
def test_agent_coordinates():
path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'reach_coordinates.json')
stmts = reach.process_json_file(path).statements
pa = Preassembler(bio_ontology, stmts)
unique_stmt = pa.combine_duplicates()[0]
agent_annots = [ev.annotations['agents'] for ev in unique_stmt.evidence]
assert all(a['raw_text'] == ['MEK1', 'ERK2'] for a in agent_annots)
assert {tuple(a['coords'])
for a in agent_annots} == {((21, 25), (0, 4)), ((0, 4), (15, 19))}
def test_conversions():
here = os.path.dirname(os.path.abspath(__file__))
test_file = os.path.join(here, 'reach_conversion.json')
rp = reach.process_json_file(test_file)
assert rp is not None
assert len(rp.statements) == 1
stmt = rp.statements[0]
assert stmt.subj.name == 'ACE'
assert len(stmt.obj_from) == 1
assert stmt.obj_from[0].name == 'angiotensin-I'
assert stmt.obj_to[0].name == 'angiotensin-II'
def test_agent_coordinates():
path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'reach_coordinates.json')
stmts = reach.process_json_file(path).statements
pa = Preassembler(hierarchies, stmts)
unique_stmt = pa.combine_duplicates()[0]
evidence_list = unique_stmt.evidence
agent_annots = [ev.annotations['agents'] for ev in unique_stmt.evidence]
assert all(a['raw_text'] == ['MEK1', 'ERK2'] for a in agent_annots)
assert {tuple(a['coords']) for a in agent_annots} == {((21, 25), (0, 4)),
((0, 4), (15, 19))}
def process_paper(model_name, pmid):
"""Process a paper with the given pubmed identifier
Parameters
----------
model_name : str
The directory for the INDRA machine
pmid : str
The PMID to process.
Returns
-------
rp : ReachProcessor
A ReachProcessor containing the extracted INDRA Statements
in rp.statements.
txt_format : str
A string representing the format of the text
"""
json_directory = os.path.join(model_name, 'jsons')
json_path = os.path.join(json_directory, 'PMID%s.json' % pmid)
if pmid.startswith('api') or pmid.startswith('PMID'):
logger.warning('Invalid PMID: %s' % pmid)
# If the paper has been read, use the json output file
if os.path.exists(json_path):
rp = reach.process_json_file(json_path, citation=pmid)
txt_format = 'existing_json'
# If the paper has not been read, download the text and read
else:
try:
txt, txt_format = get_full_text(pmid, 'pmid')
except Exception:
return None, None
if txt_format == 'pmc_oa_xml':
rp = reach.process_nxml_str(txt, citation=pmid, offline=True,
output_fname=json_path)
elif txt_format == 'elsevier_xml':
# Extract the raw text from the Elsevier XML
txt = elsevier_client.extract_text(txt)
rp = reach.process_text(txt, citation=pmid, offline=True,
output_fname=json_path)
elif txt_format == 'abstract':
rp = reach.process_text(txt, citation=pmid, offline=True,
output_fname=json_path)
else:
rp = None
if rp is not None:
check_pmids(rp.statements)
return rp, txt_format
def process(organism_priority, expected_up_id):
rp = reach.process_json_file(test_file,
organism_priority=organism_priority)
assert rp.statements[0].subj.db_refs['UPPRO'] == expected_up_id, \
rp.statements[0].subj.db_refs['UPPRO']
