Update modules/text_analysis/discourse_analysis.py
Browse files
modules/text_analysis/discourse_analysis.py
CHANGED
@@ -2,7 +2,6 @@ import streamlit as st
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import spacy
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import networkx as nx
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import matplotlib.pyplot as plt
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from collections import defaultdict
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from .semantic_analysis import (
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create_concept_graph,
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visualize_concept_graph,
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@@ -16,15 +15,13 @@ def compare_semantic_analysis(text1, text2, nlp, lang):
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doc1 = nlp(text1)
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doc2 = nlp(text2)
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# Identificar
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# Crear grafos de conceptos para ambos documentos
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G1 = create_concept_graph(text1, concepts1)
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G2 = create_concept_graph(text2, concepts2)
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# Visualizar los grafos de conceptos
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fig1 = visualize_concept_graph(G1, lang)
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@@ -34,19 +31,17 @@ def compare_semantic_analysis(text1, text2, nlp, lang):
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fig1.suptitle("Documento 1: Relaciones Conceptuales", fontsize=16, fontweight='bold')
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fig2.suptitle("Documento 2: Relaciones Conceptuales", fontsize=16, fontweight='bold')
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return fig1, fig2,
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def perform_discourse_analysis(text1, text2, nlp, lang):
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graph1, graph2,
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# Aquí puedes añadir más análisis de discurso si lo necesitas
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# Por ejemplo, podrías comparar
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return {
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'graph1': graph1,
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'graph2': graph2,
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'entities1': entities1,
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'entities2': entities2,
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'key_concepts1': key_concepts1,
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'key_concepts2': key_concepts2
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}
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import spacy
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import networkx as nx
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import matplotlib.pyplot as plt
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from .semantic_analysis import (
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create_concept_graph,
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visualize_concept_graph,
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doc1 = nlp(text1)
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doc2 = nlp(text2)
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# Identificar conceptos clave para ambos documentos
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key_concepts1 = identify_key_concepts(doc1)
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key_concepts2 = identify_key_concepts(doc2)
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# Crear grafos de conceptos para ambos documentos
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G1 = create_concept_graph(doc1, key_concepts1)
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G2 = create_concept_graph(doc2, key_concepts2)
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# Visualizar los grafos de conceptos
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fig1 = visualize_concept_graph(G1, lang)
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fig1.suptitle("Documento 1: Relaciones Conceptuales", fontsize=16, fontweight='bold')
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fig2.suptitle("Documento 2: Relaciones Conceptuales", fontsize=16, fontweight='bold')
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return fig1, fig2, key_concepts1, key_concepts2
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def perform_discourse_analysis(text1, text2, nlp, lang):
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graph1, graph2, key_concepts1, key_concepts2 = compare_semantic_analysis(text1, text2, nlp, lang)
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# Aquí puedes añadir más análisis de discurso si lo necesitas
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# Por ejemplo, podrías comparar los conceptos clave entre los dos textos
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return {
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'graph1': graph1,
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'graph2': graph2,
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'key_concepts1': key_concepts1,
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'key_concepts2': key_concepts2
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}
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