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import streamlit as st | |
import spacy | |
import networkx as nx | |
import matplotlib.pyplot as plt | |
import pandas as pd | |
import numpy as np | |
from .semantic_analysis import ( | |
create_concept_graph, | |
visualize_concept_graph, | |
identify_key_concepts, | |
POS_COLORS, | |
POS_TRANSLATIONS, | |
ENTITY_LABELS | |
) | |
def compare_semantic_analysis(text1, text2, nlp, lang): | |
""" | |
Realiza el análisis semántico comparativo entre dos textos | |
""" | |
doc1 = nlp(text1) | |
doc2 = nlp(text2) | |
# Identificar conceptos clave para ambos documentos | |
key_concepts1 = identify_key_concepts(doc1) | |
key_concepts2 = identify_key_concepts(doc2) | |
# Crear grafos de conceptos para ambos documentos | |
G1 = create_concept_graph(doc1, key_concepts1) | |
G2 = create_concept_graph(doc2, key_concepts2) | |
# Visualizar los grafos de conceptos | |
fig1 = visualize_concept_graph(G1, lang) | |
fig2 = visualize_concept_graph(G2, lang) | |
# Remover los títulos superpuestos | |
fig1.suptitle("") | |
fig2.suptitle("") | |
return fig1, fig2, key_concepts1, key_concepts2 | |
def create_concept_table(key_concepts): | |
""" | |
Crea una tabla de conceptos clave con sus frecuencias | |
""" | |
df = pd.DataFrame(key_concepts, columns=['Concepto', 'Frecuencia']) | |
df['Frecuencia'] = df['Frecuencia'].round(2) | |
return df | |
def perform_discourse_analysis(text1, text2, nlp, lang): | |
""" | |
Realiza el análisis completo del discurso | |
""" | |
try: | |
# Procesar documentos | |
doc1 = nlp(text1) | |
doc2 = nlp(text2) | |
# Identificar conceptos clave | |
key_concepts1 = identify_key_concepts(doc1) | |
key_concepts2 = identify_key_concepts(doc2) | |
# Crear grafos de conceptos | |
G1 = create_concept_graph(doc1, key_concepts1) | |
G2 = create_concept_graph(doc2, key_concepts2) | |
# Visualizar grafos | |
fig1 = visualize_concept_graph(G1, lang) | |
fig2 = visualize_concept_graph(G2, lang) | |
fig1.suptitle("") | |
fig2.suptitle("") | |
# Crear tablas | |
table1 = create_concept_table(key_concepts1) | |
table2 = create_concept_table(key_concepts2) | |
return { | |
'graph1': fig1, | |
'graph2': fig2, | |
'key_concepts1': key_concepts1, | |
'key_concepts2': key_concepts2, | |
'table1': table1, | |
'table2': table2, | |
'success': True | |
} | |
except Exception as e: | |
logger.error(f"Error en análisis del discurso: {str(e)}") | |
return { | |
'success': False, | |
'error': str(e) | |
} | |