def reco_quali(phrase_test): #tagg known qualitativ
quali_reco = []
for j in range(1,5):
words = generate_ngrams(phrase_test, j)
words = racinisation(words)
for word in words:
for i in range(0,len(qualif)):
if word == qualif[i].replace('é','e'):
quali_reco.append(quali[i])
mots_reconu.append(word)
quali_reco = filtrage_solution(quali_reco)
return quali_reco
def reco_concept(phrase_test): #tagg known troubles
concept_reco =[]
for j in range(1,5):
words = generate_ngrams(phrase_test, j)
words = racinisation(words)
for word in words:
for i in range(0,len(concepts)):
if word == concepts[i][0]:
concept_reco.append(concepts[i][1])
mots_reconu.append(word)
concept_reco = filtrage_solution(concept_reco)
return concept_reco
def reco_nega(neg,phrase_test): #tagg negation marker
neg_reco =[]
for j in range(1,5):
words = generate_ngrams(phrase_test, j)
words = racinisation(words)
for word in words:
for i in range(0,len(neg)):
if word == neg[i]:
neg_reco.append(neg[i])
mot_neg.append(word)
neg_reco = filtrage_solution(neg_reco)
neg_reco = set(neg_reco)
return neg_reco
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 4 10:15:28 2019
@author: oni
"""
from lemmat import tagger, generate_ngrams, racinisation
from treatment_file import treat_line
from tagg_concepts import mots_reconu, filtrage_solution
s = 'rythme sinusal permanent pas de troubles rythmiques pas d episodes de bradycardie cardiaque significative extrasystolie ventriculaire charge autour de 7.5% pas de pauses cardiaques significatives'
new_s = ''
words = generate_ngrams(s, 1)
temp = tagger(words)
tag = temp[0]
for i in range(0, len(tag)):
if tag[i][1] == 'ADJ' or tag[i][1] == 'NC':
new_s = new_s + tag[i][0] + ' '
print(new_s)
treat_line(new_s)
mots = []
for i in range(1, 5):
temp = generate_ngrams(new_s, i)
mots = mots + racinisation(temp)
result = []
reco = mots_reconu