def on_message(data):
global last_seen_msg_id
global stmts
if isinstance(data, dict) and data['id'] != last_seen_msg_id:
last_seen_msg_id = data['id']
if {'id': user_id} in data['targets']:
if data['comment'].startswith('indra:'):
text = data['comment'][6:].strip()
if text.strip().lower() in ['start over', 'cls', 'clear']:
clear_model(data['userName'])
# Retrieve cached REACH JSON for demo purposes
elif text.strip().lower().startswith('read pmc4338247'):
pmcid = 'PMC4338247'
say("%s: Got it. Reading %s via INDRA. This usually "
"takes about a minute." % (data['userName'], pmcid))
rp = reach.process_json_file('reach_PMC4338247.json')
stmts += rp.statements
assemble_model(data['userName'])
elif text.strip().lower().startswith('read'):
pmcid = text[4:].strip()
update_model_from_paper(pmcid, data['userName'])
elif text.strip().lower().startswith('remove'):
remove_arg = text[6:].strip()
if len(remove_arg.split(' ')) == 1:
remove_agent(remove_arg, data['userName'])
print "Remove agent:", remove_arg
else:
remove_mechanism(remove_arg, data['userName'])
print "Remove mechanism:", remove_arg
else:
update_model_from_text(text, data['userName'])
if data['comment'] == 'biopax':
print 'BIOPAX'
call_biopax()
print '<%s> %s' % (data['userName'], data['comment'])
def process_paper(model_name, pmid):
json_path = os.path.join(model_path, 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:
txt, txt_format = get_full_text(pmid, 'pmid')
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
from indra import trips, reach
from indra.literature import id_lookup
from assembly_eval import have_file, run_assembly
if __name__ == "__main__":
pmc_ids = ["PMC1234335", "PMC3178447", "PMC3690480", "PMC4345513", "PMC534114"]
pmids = [id_lookup(pmcid)["pmid"] for pmcid in pmc_ids]
for pmid, pmcid in zip(pmids, pmc_ids):
print "Processing %s..." % pmcid
trips_fname = "trips/" + pmcid + "-20160503T1152.ekb"
tp = trips.process_xml(open(trips_fname).read())
for s in tp.statements:
for e in s.evidence:
e.pmid = pmid
reach_fname = "reach/" + pmcid + ".json"
rp = reach.process_json_file(reach_fname)
all_statements = tp.statements + rp.statements
run_assembly(all_statements, "combined", pmcid)
rerun = False
# Download the papers if they are not available yet
for pmcid in pmc_ids:
prefix = folder + "/" + pmcid
if not have_file(prefix + ".nxml") and not have_file(prefix + ".txt"):
txt, txt_format = get_full_text(pmcid)
if txt_format == "nxml":
fname = prefix + ".nxml"
else:
fname = prefix + ".txt"
with open(fname, "wt") as fh:
fh.write(txt.encode("utf-8"))
# Read each paper if it hasn't been read yet.
# Otherwise use the existing json extractions.
for pmcid, pmid in zip(pmc_ids, pmids):
prefix = folder + "/" + pmcid
print "Processing %s..." % pmcid
# If REACH already processed it then don't run it again
if rerun or not have_file(prefix + ".json"):
if have_file(prefix + ".txt"):
txt = open(prefix + ".txt").read().decode("utf-8")
rp = reach.process_text(txt, citation=pmid, offline=True)
elif have_file(prefix + ".nxml"):
rp = reach.process_nxml_file(prefix + ".nxml", citation=pmid, offline=True)
shutil.move("reach_output.json", prefix + ".json")
else:
rp = reach.process_json_file(prefix + ".json", citation=pmid)
run_assembly(rp.statements, folder, pmcid)
for pmcid in pmc_ids:
prefix = folder + '/' + pmcid
if not have_file(prefix + '.nxml') and\
not have_file(prefix + '.txt'):
txt, txt_format = get_full_text(pmcid)
if txt_format == 'nxml':
fname = prefix + '.nxml'
else:
fname = prefix + '.txt'
with open(fname, 'wt') as fh:
fh.write(txt.encode('utf-8'))
pmids.append(id_lookup(pmcid)['pmid'])
# Read each paper if it hasn't been read yet.
# Otherwise use the existing json extractions.
for pmcid, pmid in zip(pmc_ids, pmids):
prefix = folder + '/' + pmcid
print 'Processing %s...' % pmcid
# If REACH already processed it then don't run it again
if rerun or not have_file(prefix + '.json'):
if have_file(prefix + '.txt'):
txt = open(prefix + '.txt').read().decode('utf-8')
rp = reach.process_text(txt, citation=pmid)
elif have_file(prefix + '.nxml'):
rp = reach.process_nxml_file(prefix + '.nxml', citation=pmid)
shutil.move('reach_output.json', prefix + '.json')
else:
rp = reach.process_json_file(prefix + '.json', citation=pmid)
run_assembly(rp.statements, folder, pmcid)
import sys
import pickle
from indra import reach
from indra.assemblers import GraphAssembler
if len(sys.argv) < 2:
process_type = 'text'
else:
process_type = sys.argv[1]
if process_type == 'text':
txt = open('ras_pathway.txt', 'rt').read()
rp = reach.process_text(txt, offline=True)
st = rp.statements
elif process_type == 'json':
rp = reach.process_json_file('reach_output.json')
st = rp.statements
else:
st = pickle.load(open('statements.pkl', 'rb'))
for s in st:
print '%s\t%s' % (s, s.evidence[0].text)
graphpr = {'rankdir': 'TD'}
nodepr = {'fontsize': 12, 'shape': 'plaintext', 'margin': '0,0', 'pad': 0}
ga = GraphAssembler(st, graph_properties=graphpr, node_properties=nodepr)
ga.make_model()
ga.save_dot('ras_pathway.dot')
ga.save_pdf('ras_pathway.pdf')
