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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): | |
| 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): | |
| df = pd.DataFrame(key_concepts, columns=['Concepto', 'Frecuencia']) | |
| df['Frecuencia'] = df['Frecuencia'].round(2) | |
| return df | |
| def perform_discourse_analysis(text1, text2, nlp, lang): | |
| graph1, graph2, key_concepts1, key_concepts2 = compare_semantic_analysis(text1, text2, nlp, lang) | |
| # Crear tablas de conceptos clave | |
| table1 = create_concept_table(key_concepts1) | |
| table2 = create_concept_table(key_concepts2) | |
| return { | |
| 'graph1': graph1, | |
| 'graph2': graph2, | |
| 'key_concepts1': key_concepts1, | |
| 'key_concepts2': key_concepts2 | |
| } | |
| def display_discourse_analysis_results(analysis_result, lang_code): | |
| t = get_translations(lang_code) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| with st.expander(t['doc1_title'], expanded=True): | |
| st.pyplot(analysis_result['graph1']) | |
| st.subheader(t['key_concepts']) | |
| st.table(analysis_result['table1']) | |
| with col2: | |
| with st.expander(t['doc2_title'], expanded=True): | |
| st.pyplot(analysis_result['graph2']) | |
| st.subheader(t['key_concepts']) | |
| st.table(analysis_result['table2']) |