Update modules/studentact/current_situation_analysis.py
Browse files
modules/studentact/current_situation_analysis.py
CHANGED
@@ -10,6 +10,8 @@ import numpy as np
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import matplotlib.patches as patches
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import logging
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# 2. Configuraci贸n b谩sica del logging
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logging.basicConfig(
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level=logging.INFO,
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@@ -23,9 +25,6 @@ logging.basicConfig(
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# 3. Obtener el logger espec铆fico para este m贸dulo
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logger = logging.getLogger(__name__)
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# Importaciones locales
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from translations.recommendations import RECOMMENDATIONS
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#########################################################################
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def correlate_metrics(scores):
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@@ -250,7 +249,7 @@ def analyze_clarity(doc):
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logger.error(f"Error en analyze_clarity: {str(e)}")
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return 0.0, {}
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def analyze_vocabulary_diversity(doc):
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"""An谩lisis mejorado de la diversidad y calidad del vocabulario"""
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try:
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@@ -308,7 +307,6 @@ def analyze_vocabulary_diversity(doc):
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logger.error(f"Error en analyze_vocabulary_diversity: {str(e)}")
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return 0.0, {}
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#############################################################################################
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def analyze_cohesion(doc):
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"""Analiza la cohesi贸n textual"""
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try:
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@@ -390,7 +388,6 @@ def analyze_cohesion(doc):
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logger.error(f"Error en analyze_cohesion: {str(e)}")
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return 0.0
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#############################################################################################################
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def analyze_structure(doc):
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try:
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if len(doc) == 0:
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@@ -518,8 +515,6 @@ def get_dependency_depths(token, depth=0, analyzed_tokens=None):
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return current_result
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#############################################################################################################
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def normalize_score(value, metric_type,
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min_threshold=0.0, target_threshold=1.0,
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range_factor=2.0, optimal_length=None,
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@@ -623,9 +618,6 @@ def normalize_score(value, metric_type,
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return 0.0
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#####################################################################################
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# Funciones de generaci贸n de gr谩ficos
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def generate_sentence_graphs(doc):
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"""Genera visualizaciones de estructura de oraciones"""
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@@ -694,7 +686,6 @@ def create_vocabulary_network(doc):
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plt.axis('off')
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return fig
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#############################################################################
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def create_syntax_complexity_graph(doc):
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"""
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Genera el diagrama de arco de complejidad sint谩ctica.
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@@ -774,7 +765,7 @@ def create_syntax_complexity_graph(doc):
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logger.error(f"Error en create_syntax_complexity_graph: {str(e)}")
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return None
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def create_cohesion_heatmap(doc):
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"""Genera un mapa de calor que muestra la cohesi贸n entre p谩rrafos/oraciones."""
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try:
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@@ -818,194 +809,4 @@ def create_cohesion_heatmap(doc):
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except Exception as e:
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logger.error(f"Error en create_cohesion_heatmap: {str(e)}")
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return None
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########################################################################################
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def generate_recommendations(metrics, text_type, lang_code='es'):
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"""
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Genera recomendaciones personalizadas basadas en las m茅tricas del texto y el tipo de texto.
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Args:
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metrics: Diccionario con las m茅tricas analizadas
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text_type: Tipo de texto ('academic_article', 'student_essay', 'general_communication')
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lang_code: C贸digo del idioma para las recomendaciones (es, en, fr, pt)
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Returns:
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dict: Recomendaciones organizadas por categor铆a en el idioma correspondiente
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"""
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try:
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# Obtener umbrales seg煤n el tipo de texto
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thresholds = TEXT_TYPES[text_type]['thresholds']
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# Verificar que el idioma est茅 soportado, usar espa帽ol como respaldo
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if lang_code not in RECOMMENDATIONS:
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logger.warning(f"Idioma {lang_code} no soportado para recomendaciones, usando espa帽ol")
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lang_code = 'es'
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# Obtener traducciones para el idioma seleccionado
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translations = RECOMMENDATIONS[lang_code]
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# Inicializar diccionario de recomendaciones
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recommendations = {
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'vocabulary': [],
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'structure': [],
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'cohesion': [],
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'clarity': [],
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'specific': [],
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'priority': {
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'area': 'general',
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'tips': []
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},
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'text_type_name': translations['text_types'][text_type],
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'dimension_names': translations['dimension_names'],
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'ui_text': {
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'priority_intro': translations['priority_intro'],
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'detailed_recommendations': translations['detailed_recommendations'],
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'save_button': translations['save_button'],
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'save_success': translations['save_success'],
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'save_error': translations['save_error'],
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'area_priority': translations['area_priority']
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}
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}
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# Determinar nivel para cada dimensi贸n y asignar recomendaciones
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dimensions = ['vocabulary', 'structure', 'cohesion', 'clarity']
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scores = {}
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for dim in dimensions:
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score = metrics[dim]['normalized_score']
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scores[dim] = score
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# Determinar nivel (bajo, medio, alto)
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if score < thresholds[dim]['min']:
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level = 'low'
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elif score < thresholds[dim]['target']:
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level = 'medium'
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else:
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level = 'high'
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# Asignar recomendaciones para ese nivel
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recommendations[dim] = translations[dim][level]
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# Asignar recomendaciones espec铆ficas por tipo de texto
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recommendations['specific'] = translations[text_type]
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# Determinar 谩rea prioritaria (la que tiene menor puntuaci贸n)
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priority_dimension = min(scores, key=scores.get)
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recommendations['priority']['area'] = priority_dimension
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recommendations['priority']['tips'] = recommendations[priority_dimension]
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logger.info(f"Generadas recomendaciones en {lang_code} para texto tipo {text_type}")
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return recommendations
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except Exception as e:
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logger.error(f"Error en generate_recommendations: {str(e)}")
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# Retornar mensajes gen茅ricos en caso de error
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if lang_code == 'en':
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return {
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'vocabulary': ["Try enriching your vocabulary"],
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'structure': ["Work on the structure of your sentences"],
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'cohesion': ["Improve the connection between your ideas"],
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'clarity': ["Try to express your ideas more clearly"],
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'specific': ["Adapt your text according to its purpose"],
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'priority': {
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'area': 'general',
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'tips': ["Seek specific feedback from a tutor or teacher"]
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},
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'dimension_names': {
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'vocabulary': 'Vocabulary',
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'structure': 'Structure',
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'cohesion': 'Cohesion',
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'clarity': 'Clarity',
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'general': 'General'
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},
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'ui_text': {
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'priority_intro': "This is where you should focus your efforts.",
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'detailed_recommendations': "Detailed recommendations",
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'save_button': "Save analysis",
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'save_success': "Analysis saved successfully",
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'save_error': "Error saving analysis",
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'area_priority': "Priority area"
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}
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}
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elif lang_code == 'fr':
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return {
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'vocabulary': ["Essayez d'enrichir votre vocabulaire"],
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'structure': ["Travaillez sur la structure de vos phrases"],
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'cohesion': ["Am茅liorez la connexion entre vos id茅es"],
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'clarity': ["Essayez d'exprimer vos id茅es plus clairement"],
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'specific': ["Adaptez votre texte en fonction de son objectif"],
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'priority': {
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'area': 'general',
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'tips': ["Demandez des commentaires sp茅cifiques 脿 un tuteur ou un professeur"]
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},
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'dimension_names': {
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'vocabulary': 'Vocabulaire',
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'structure': 'Structure',
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'cohesion': 'Coh茅sion',
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'clarity': 'Clart茅',
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'general': 'G茅n茅ral'
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},
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'ui_text': {
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'priority_intro': "C'est l脿 que vous devriez concentrer vos efforts.",
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'detailed_recommendations': "Recommandations d茅taill茅es",
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'save_button': "Enregistrer l'analyse",
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'save_success': "Analyse enregistr茅e avec succ猫s",
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'save_error': "Erreur lors de l'enregistrement de l'analyse",
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'area_priority': "Domaine prioritaire"
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}
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}
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elif lang_code == 'pt':
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return {
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'vocabulary': ["Tente enriquecer seu vocabul谩rio"],
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'structure': ["Trabalhe na estrutura de suas frases"],
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'cohesion': ["Melhore a conex茫o entre suas ideias"],
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'clarity': ["Tente expressar suas ideias com mais clareza"],
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'specific': ["Adapte seu texto de acordo com seu prop贸sito"],
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'priority': {
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'area': 'general',
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'tips': ["Busque feedback espec铆fico de um tutor ou professor"]
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},
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'dimension_names': {
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'vocabulary': 'Vocabul谩rio',
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'structure': 'Estrutura',
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'cohesion': 'Coes茫o',
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'clarity': 'Clareza',
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'general': 'Geral'
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},
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'ui_text': {
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'priority_intro': "脡 aqui que voc锚 deve concentrar seus esfor莽os.",
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'detailed_recommendations': "Recomenda莽玫es detalhadas",
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'save_button': "Salvar an谩lise",
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'save_success': "An谩lise salva com sucesso",
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'save_error': "Erro ao salvar an谩lise",
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'area_priority': "脕rea priorit谩ria"
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}
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}
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else: # Espa帽ol por defecto
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return {
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'vocabulary': ["Intenta enriquecer tu vocabulario"],
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'structure': ["Trabaja en la estructura de tus oraciones"],
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'cohesion': ["Mejora la conexi贸n entre tus ideas"],
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'clarity': ["Busca expresar tus ideas con mayor claridad"],
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'specific': ["Adapta tu texto seg煤n su prop贸sito"],
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'priority': {
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'area': 'general',
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'tips': ["Busca retroalimentaci贸n espec铆fica de un tutor o profesor"]
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},
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'dimension_names': {
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'vocabulary': 'Vocabulario',
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'structure': 'Estructura',
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'cohesion': 'Cohesi贸n',
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'clarity': 'Claridad',
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'general': 'General'
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},
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'ui_text': {
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'priority_intro': "Esta es el 谩rea donde debes concentrar tus esfuerzos.",
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'detailed_recommendations': "Recomendaciones detalladas",
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'save_button': "Guardar an谩lisis",
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'save_success': "An谩lisis guardado con 茅xito",
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'save_error': "Error al guardar el an谩lisis",
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'area_priority': "脕rea prioritaria"
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}
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}
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import matplotlib.patches as patches
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import logging
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from translations.recommendations import RECOMMENDATIONS
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# 2. Configuraci贸n b谩sica del logging
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logging.basicConfig(
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level=logging.INFO,
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# 3. Obtener el logger espec铆fico para este m贸dulo
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logger = logging.getLogger(__name__)
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#########################################################################
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def correlate_metrics(scores):
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logger.error(f"Error en analyze_clarity: {str(e)}")
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return 0.0, {}
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def analyze_vocabulary_diversity(doc):
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"""An谩lisis mejorado de la diversidad y calidad del vocabulario"""
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try:
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logger.error(f"Error en analyze_vocabulary_diversity: {str(e)}")
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return 0.0, {}
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def analyze_cohesion(doc):
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"""Analiza la cohesi贸n textual"""
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try:
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logger.error(f"Error en analyze_cohesion: {str(e)}")
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return 0.0
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def analyze_structure(doc):
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try:
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if len(doc) == 0:
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return current_result
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def normalize_score(value, metric_type,
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min_threshold=0.0, target_threshold=1.0,
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range_factor=2.0, optimal_length=None,
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return 0.0
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# Funciones de generaci贸n de gr谩ficos
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def generate_sentence_graphs(doc):
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"""Genera visualizaciones de estructura de oraciones"""
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plt.axis('off')
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return fig
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def create_syntax_complexity_graph(doc):
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"""
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Genera el diagrama de arco de complejidad sint谩ctica.
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logger.error(f"Error en create_syntax_complexity_graph: {str(e)}")
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return None
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+
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def create_cohesion_heatmap(doc):
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"""Genera un mapa de calor que muestra la cohesi贸n entre p谩rrafos/oraciones."""
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try:
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except Exception as e:
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logger.error(f"Error en create_cohesion_heatmap: {str(e)}")
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return None
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