def parse():
if request.method == 'POST':
text = request.form['text']
doc_id = '99999999'
print text
#if text == "readfile":
# with open('test.txt', 'r') as myfile:
# text=myfile.read()
rules0 = request.form['rules0']
rule0_lines = rules0.split("\n")
rules1 = request.form['rules1']
rule1_lines = rules1.split("\n")
rules2 = request.form['rules2']
rule2_lines = rules2.split("\n")
param_helper = ParamHelper(text,doc_id,rule0_lines,rule1_lines,rule2_lines)
raw_doc = document_pb2.Document()
edg_rules = edgRules_pb2.EdgRules()
param_helper.setDocProtoAttributes(raw_doc)
param_helper.setRuleProtoAttributes(edg_rules)
##########################
parse_bllip = parse_using_bllip(raw_doc,edg_rules)
#print parse_bllip
brat_bllip = json.dumps(get_brat_data(parse_bllip))
brat_bllip_added = json.dumps(get_brat_data_added(parse_bllip))
return render_template('index_edg.html', text=text, rules0=rules0,rules1=rules1,rules2=rules2,
brat_string_bllip=brat_bllip,
brat_string_bllip_added=brat_bllip_added)
else:
return render_template('index_edg.html')
def parse():
if request.method == 'POST':
text = request.form['text']
split = request.form.getlist('split')
doc = document_pb2.Document()
doc.text = text
parse_doc_bllip_brat = ''
parse_doc_stanford_brat = ''
split_doc_brat = ''
cst_parses = ''
if len(split) == 0:
parse_doc_bllip = parse_using_bllip(doc)
parse_doc_stanford = parse_using_stanford(doc)
parse_doc_bllip_brat = json.dumps(get_brat_data(parse_doc_bllip))
parse_doc_stanford_brat = json.dumps(
get_brat_data(parse_doc_stanford))
parses = {}
for sentence in parse_doc_bllip.sentence:
parses[sentence.index] = sentence.parse
cst_parses = json.dumps(parses)
else:
split_doc = split_sentence_using_stanford(doc)
split_doc_brat = json.dumps(get_brat_data(split_doc))
return render_template('index.html',
text=text,
parse_bllip=parse_doc_bllip_brat,
parse_stanford=parse_doc_stanford_brat,
split_stanford=split_doc_brat,
bllip_cst_parses=cst_parses)
else:
return render_template('index.html')
def run(text):
raw_doc = document_pb2.Document()
raw_doc.doc_id = '26815768'
raw_doc.text = text
# Parse using Bllip parser.
result = parse_using_bllip(raw_doc)
#print(result)
return result
def run():
text = u'MicroRNAs (miRNAs) are small non-coding RNAs of ∼19-24 ' \
'nucleotides (nt) in length and considered as potent ' \
'regulators of gene expression at transcriptional and ' \
'post-transcriptional levels. Here we report the identification ' \
'and characterization of 15 conserved miRNAs belonging to 13 ' \
'families from Rauvolfia serpentina through in silico analysis ' \
'of available nucleotide dataset. The identified mature R. ' \
'serpentina miRNAs (rse-miRNAs) ranged between 20 and 22nt in ' \
'length, and the average minimal folding free energy index (MFEI) ' \
'value of rse-miRNA precursor sequences was found to be ' \
'-0.815kcal/mol. Using the identified rse-miRNAs as query, their ' \
'potential targets were predicted in R. serpentina and other plant ' \
'species. Gene Ontology (GO) annotation showed that predicted ' \
'targets of rse-miRNAs include transcription factors as well as ' \
'genes involved in diverse biological processes such as primary ' \
'and secondary metabolism, stress response, disease resistance, ' \
'growth, and development. Few rse-miRNAs were predicted to target ' \
'genes of pharmaceutically important secondary metabolic pathways ' \
'such as alkaloids and anthocyanin biosynthesis. Phylogenetic ' \
'analysis showed the evolutionary relationship of rse-miRNAs and ' \
'their precursor sequences to homologous pre-miRNA sequences from ' \
'other plant species. The findings under present study besides giving ' \
'first hand information about R. serpentina miRNAs and their targets, ' \
'also contributes towards the better understanding of miRNA-mediated ' \
'gene regulatory processes in plants.'
raw_doc = document_pb2.Document()
raw_doc.doc_id = '26815768'
raw_doc.text = text
one_hundred_docs = [raw_doc] * 100
# This is a simple function to make requests out of a list of documents. We
# put 5 documents in each request.
requests = request_iter_docs(one_hundred_docs,
request_size=5,
request_type=rpc_pb2.Request.PARSE_BLLIP)
# Given a request iterator, send requests in parallel and get responses.
responses_queue = grpcapi.get_queue(server='128.4.20.169',
port=8900,
request_thread_num=10,
iterable_request=requests)
count = 0
for response in responses_queue:
for doc in response.document:
count += 1
print(count, doc.doc_id, len(doc.sentence))
def run():
text = u'MicroRNAs (miRNAs) are small non-coding RNAs of ∼19-24 ' \
'nucleotides (nt) in length and considered as potent ' \
'regulators of gene expression at transcriptional and ' \
'post-transcriptional levels. Here we report the identification ' \
'and characterization of 15 conserved miRNAs belonging to 13 ' \
'families from Rauvolfia serpentina through in silico analysis ' \
'of available nucleotide dataset. The identified mature R. ' \
'serpentina miRNAs (rse-miRNAs) ranged between 20 and 22nt in ' \
'length, and the average minimal folding free energy index (MFEI) ' \
'value of rse-miRNA precursor sequences was found to be ' \
'-0.815kcal/mol. Using the identified rse-miRNAs as query, their ' \
'potential targets were predicted in R. serpentina and other plant ' \
'species. Gene Ontology (GO) annotation showed that predicted ' \
'targets of rse-miRNAs include transcription factors as well as ' \
'genes involved in diverse biological processes such as primary ' \
'and secondary metabolism, stress response, disease resistance, ' \
'growth, and development. Few rse-miRNAs were predicted to target ' \
'genes of pharmaceutically important secondary metabolic pathways ' \
'such as alkaloids and anthocyanin biosynthesis. Phylogenetic ' \
'analysis showed the evolutionary relationship of rse-miRNAs and ' \
'their precursor sequences to homologous pre-miRNA sequences from ' \
'other plant species. The findings under present study besides giving ' \
'first hand information about R. serpentina miRNAs and their targets, ' \
'also contributes towards the better understanding of miRNA-mediated ' \
'gene regulatory processes in plants.'
raw_doc = document_pb2.Document()
raw_doc.doc_id = '26815768'
raw_doc.text = text
# Parse using Bllip parser.
result = parse_using_bllip(raw_doc)
print(result)
# Parse Using Stanford CoreNLP parser.
result = parse_using_stanford(raw_doc)
print(result)
# Only split sentences using Stanford CoreNLP.
for i in range(100):
result = split_using_stanford(raw_doc)
print('Split {} documents'.format(i))
def run():
textFH = open(sys.argv[1], "r")
text = textFH.read()
textFH.close()
#text = u'Surface expression of mir-21 activates tgif beta receptor type II expression. Expression of mir-21 and mir-132 directly mediates cell migration . mir-21 mediates cell migration and proliferation. mir-21 seems to mediate apoptosis. mir-21 is involved in cellular processes, such as cell migration and cell proliferation. mir-21 regulates the ectopic expression of smad2 .'
#text = u'transport of annexin 2 not only to dynamic actin-rich ruffles at the cell cortex but also to cytoplasmic and perinuclear vesicles.'
doc_id = '99999999'
rule_phase0_filename = sys.argv[2]
rule_phase1_filename = sys.argv[3]
rule_phase2_filename = sys.argv[4]
fh0 = open(rule_phase0_filename, "r")
rule0_lines = fh0.readlines()
fh0.close()
fh1 = open(rule_phase1_filename, "r")
rule1_lines = fh1.readlines()
fh1.close()
fh2 = open(rule_phase2_filename, "r")
rule2_lines = fh2.readlines()
fh2.close()
param_helper = ParamHelper(text, doc_id, rule0_lines, rule1_lines,
rule2_lines)
raw_doc = document_pb2.Document()
edg_rules = edgRules_pb2.EdgRules()
param_helper.setDocProtoAttributes(raw_doc)
param_helper.setRuleProtoAttributes(edg_rules)
# Parse using Bllip parser.
#print (ruleList)
# Parse using Bllip parser.
result = parse_using_bllip(raw_doc, edg_rules)
helper = DocHelper(result)
sentences = result.sentence
#print(edg_rules)
for sentence in sentences:
print(helper.text(sentence))
for depExtra in sentence.dependency_extra:
print(helper.printExtraDependency(sentence, depExtra))
print("===============================")
def mask_entity(self, mask_duids=None):
if self.has_overlap_entity():
raise ValueError('Overlapped entities: ' + self.doc.doc_id)
masked = document_pb2.Document()
masked.CopyFrom(self.doc)
slices = []
start = 0
mask_start = 0
# Sort by char start.
entities = masked.entity.values()
entities = sorted(entities, key=lambda a: a.char_start)
for entity in entities:
slices.append(self.doc.text[start:entity.char_start])
mask_start += len(slices[-1])
if mask_duids is not None and entity.duid not in mask_duids:
slices.append(self.text(entity))
else:
# Not using entity type as replacement because it may change
# the parsing, ENTITY seems to affect the parsing less.
if self.text(entity).endswith('s'):
slices.append('BIOENTITIES')
else:
slices.append('BIOENTITY')
entity_end = entity.char_end
entity.char_start = mask_start
entity.char_end = mask_start + len(slices[-1]) - 1
mask_start += len(slices[-1])
start = entity_end + 1
slices.append(self.doc.text[start:])
masked.text = ''.join(slices)
return masked
def run():
# text = u'Surface expression of mir-21 activates tgif beta receptor type II expression. Expression of mir-21 and mir-132 directly mediates cell migration . mir-21 mediates cell migration and proliferation. mir-21 seems to mediate apoptosis. mir-21 is involved in cellular processes, such as cell migration and cell proliferation. mir-21 regulates the ectopic expression of smad2 .'
# text = u'transport of annexin 2 not only to dynamic actin-rich ruffles at the cell cortex but also to cytoplasmic and perinuclear vesicles.'
doc_id = '99999999'
rule_phase0_filename = '/home/leebird/Projects/nlputils/visual/uploads/rules_phase0.txt'
rule_phase1_filename = '/home/leebird/Projects/nlputils/visual/uploads/rules_phase1.txt'
rule_phase2_filename = '/home/leebird/Projects/nlputils/visual/uploads/rules_phase2.txt'
fh0 = open(rule_phase0_filename, "r")
rule0_lines = fh0.readlines()
fh0.close()
fh1 = open(rule_phase1_filename, "r")
rule1_lines = fh1.readlines()
fh1.close()
fh2 = open(rule_phase2_filename, "r")
rule2_lines = fh2.readlines()
fh2.close()
with open('/home/leebird/Projects/nlputils/utils/typing/test.json') as f:
json_doc = json.load(f)
for t in json_doc['entity'].values():
t['entityType'] = t['entityType'].upper()
text = json.dumps(json_doc)
raw_doc = json_format.Parse(text, document_pb2.Document(), True)
param_helper = ParamHelper(text, doc_id, rule0_lines, rule1_lines,
rule2_lines)
# raw_doc = document_pb2.Document()
edg_rules = edgRules_pb2.EdgRules()
# param_helper.setDocProtoAttributes(raw_doc)
param_helper.setRuleProtoAttributes(edg_rules)
# Parse using Bllip parser.
doc = parse_using_bllip(raw_doc, edg_rules)
helper = DocHelper(doc)
invalid_deps = constraint_args(helper, {'arg0': {document_pb2.Entity.GENE}})
print(invalid_deps)
propagate(helper, {'arg0': {document_pb2.Entity.GENE}}, invalid_deps)
def upload():
if request.method == 'POST':
# Get the name of the uploaded file
file0 = request.files['ruleFile0']
file1 = request.files['ruleFile1']
file2 = request.files['ruleFile2']
rules0 = save_read_uploaded_file(file0)
rules1 = save_read_uploaded_file(file1)
rules2 = save_read_uploaded_file(file2)
text = request.form['text']
if rules0 == "":
rules0 = request.form['rules0']
if rules1 == "":
rules1 = request.form['rules1']
if rules2 == "":
rules2 = request.form['rules2']
rule0_lines = rules0.split("\n")
rule1_lines = rules1.split("\n")
rule2_lines = rules2.split("\n")
doc_id = "9999999"
param_helper = ParamHelper(text,doc_id,rule0_lines,rule1_lines,rule2_lines)
raw_doc = document_pb2.Document()
edg_rules = edgRules_pb2.EdgRules()
param_helper.setDocProtoAttributes(raw_doc)
param_helper.setRuleProtoAttributes(edg_rules)
##########################
parse_bllip = parse_using_bllip(raw_doc,edg_rules)
#print parse_bllip
brat_bllip = json.dumps(get_brat_data(parse_bllip))
brat_bllip_added = json.dumps(get_brat_data_added(parse_bllip))
return render_template('index_edg.html', text=text, rules0=rules0,rules1=rules1,rules2=rules2,
brat_string_bllip=brat_bllip,
brat_string_bllip_added=brat_bllip_added)
else:
return render_template('index_edg.html')
def run():
#####Iterate through all files in Input directory and create doc_list
input_dir_path = sys.argv[1]
glob_path = input_dir_path + "/*"
input_files = glob.glob(glob_path)
document_list = list()
for input_file in input_files:
textFH = open(input_file, "r")
text = textFH.read()
textFH.close()
raw_doc = document_pb2.Document()
raw_doc = document_pb2.Document()
doc_id = os.path.splitext(os.path.basename(input_file))[0]
raw_doc.text = text
raw_doc.doc_id = doc_id
document_list.append(raw_doc)
rule_phase0_filename = sys.argv[2]
fh0 = open(rule_phase0_filename, "r")
rule0_lines = fh0.readlines()
fh0.close()
####NEED TO UPDDATE PARAM_HELPER
param_helper = ParamHelper("NA", "NA", rule0_lines, [], [])
edg_rules = edgRules_pb2.EdgRules()
param_helper.setRuleProtoAttributes(edg_rules)
#param_helper.setDocProtoAttributes(raw_doc)
# This is a simple function to make requests out of a list of documents. We
# put 5 documents in each request.
requests = edg_request_iter_docs(
document_list,
edg_rules,
request_size=5,
request_type=rpc_pb2.EdgRequest.PARSE_BLLIP)
# Given a request iterator, send requests in parallel and get responses.
responses_queue = grpcapi.get_queue(server='128.4.20.169',
port=8902,
request_thread_num=10,
iterable_request=requests,
edg_request_processor=True)
count = 0
for response in responses_queue:
for doc in response.document:
#print(doc)
helper = DocHelper(doc)
sentences = doc.sentence
doc_id = doc.doc_id
#print(edg_rules)
sentNum = 0
for sentence in sentences:
flag = 0
sentText = helper.text(sentence)
dependenciesExtra = sentence.dependency_extra
edgRelations = EdgRelations(doc_id, sentNum)
edgRelations.setRelations(helper, sentence, dependenciesExtra)
toPrintRel = ["inv", "reg", "ass", "exp", "cmp", "isa", "fnd"]
for edgRelation in edgRelations.relations:
numb_args_list = edgRelation.getEdgRelationNumArgs()
relation_name = edgRelation.name
trigger_head = edgRelation.trigger_head
trigger_phrase = edgRelation.trigger_phrase
if relation_name in toPrintRel:
for numb_args in numb_args_list:
print("Sentence: " + doc_id + "\t" + str(sentNum) +
"\t" + sentText)
print("Relation: " + relation_name + "\t" +
trigger_head + "\t" + trigger_phrase)
print("Arg0: " + numb_args[0])
print("Arg1: " + numb_args[1])
print("Arg2: " + numb_args[2])
print("\n")
sentNum = sentNum + 1
count += 1
def load_from_brat_file(doc_id, text_file, annotation_file):
doc = document_pb2.Document()
doc.doc_id = doc_id
helper = DocHelper(doc)
with codecs.open(text_file, 'r', encoding='utf8') as f:
# Replace newlines with spaces.
text = f.read().replace('\n', ' ')
doc.text = text
with codecs.open(annotation_file, 'r', encoding='utf8') as f:
entities, events, relations = [], [], []
for line in f:
line = line.strip('\r\n')
assert len(line.strip()) > 0
assert line[0] == 'T' or line[0] == 'E' or \
line[0] == 'R' or line[0] == '*' or \
line[0] == 'M' or line[0] == 'A'
if line[0] == 'T':
entity_id, entity_text, entity_type, entity_start, entity_end \
= parser.parse_entity(line)
entity = helper.add_entity(duid=entity_id)
entity.char_start = entity_start
entity.char_end = entity_end - 1
entity.entity_type = entity_type
elif line[0] == 'E':
events.append(parser.parse_event(line))
elif line[0] == 'R' or line[0] == '*':
relations.append(parser.parse_relation(line))
for eid, etype, trigger_id, arguments, attrs in events:
event = helper.add_relation(relation_type=etype, duid=eid)
trigger = event.argument.add()
trigger.entity_duid = trigger_id
trigger.role = 'Trigger'
for role, arg_id in arguments:
arg = event.argument.add()
arg.role = role
arg.entity_duid = arg_id
if attrs is not None:
for key, values in attrs.items():
for value in values:
attr = event.attribute.add()
attr.key = key
attr.value = value
for rid, rtype, arguments, attrs in relations:
if rid.startswith('R'):
relation = helper.add_relation(relation_type=rtype,
duid=rid)
else:
relation = helper.add_relation(relation_type=rtype)
for role, arg_id in arguments:
arg = relation.argument.add()
arg.role = role
arg.entity_duid = arg_id
if attrs is not None:
for key, values in attrs.items():
for value in values:
attr = relation.attribute.add()
attr.key = key
attr.value = value
return doc
def run():
#####Iterate through all files in Input directory and create doc_list
input_dir_path = sys.argv[1]
glob_path = input_dir_path + "/*";
input_files = glob.glob(glob_path)
document_list = list()
for input_file in input_files:
textFH = open(input_file,"r")
text = textFH.read()
textFH.close()
raw_doc = document_pb2.Document()
raw_doc = document_pb2.Document()
doc_id = os.path.splitext(os.path.basename(input_file))[0]
raw_doc.text = text
raw_doc.doc_id = doc_id
document_list.append(raw_doc)
rule_phase0_filename = sys.argv[2]
fh0 = open(rule_phase0_filename, "r")
rule0_lines = fh0.readlines()
fh0.close()
####NEED TO UPDDATE PARAM_HELPER
param_helper = ParamHelper("NA","NA",rule0_lines,[],[])
edg_rules = edgRules_pb2.EdgRules()
param_helper.setRuleProtoAttributes(edg_rules)
#param_helper.setDocProtoAttributes(raw_doc)
# This is a simple function to make requests out of a list of documents. We
# put 5 documents in each request.
requests = edg_request_iter_docs(document_list, edg_rules,
request_size=5,
request_type=rpc_pb2.EdgRequest.PARSE_BLLIP)
# Given a request iterator, send requests in parallel and get responses.
responses_queue = grpcapi.get_queue(server='128.4.20.169',
port=8902,
request_thread_num=10,
iterable_request=requests,
edg_request_processor=True)
count = 0
for response in responses_queue:
for doc in response.document:
#print(doc)
helper = DocHelper(doc)
sentences = doc.sentence
doc_id = doc.doc_id
#print(edg_rules)
sentNum = 0
for sentence in sentences:
flag = 0
sentText = helper.text(sentence)
for depExtra in sentence.dependency_extra:
flag = 1
print(doc_id+"\t"+str(sentNum)+"\t"+helper.printExtraDependencyAnalysis(sentence,depExtra)+"\t"+sentText)
if flag == 0:
print(doc_id+"\t"+str(sentNum)+"\t"+helper.printEmptyExtraDependencyAnalysis(sentence)+"\t"+sentText)
sentNum = sentNum + 1
count += 1
