Update modules/studentact/current_situation_interface.py
Browse files
modules/studentact/current_situation_interface.py
CHANGED
@@ -63,6 +63,26 @@ TEXT_TYPES = {
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}
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####################################
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def display_current_situation_interface(lang_code, nlp_models, t):
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"""
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Interfaz simplificada con gráfico de radar para visualizar métricas.
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@@ -83,7 +103,7 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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# Container principal con dos columnas
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with st.container():
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input_col, results_col = st.columns([1,2])
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-
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with input_col:
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# Text area con manejo de estado
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text_input = st.text_area(
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@@ -149,12 +169,115 @@ def display_current_situation_interface(lang_code, nlp_models, t):
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metrics=st.session_state.current_metrics,
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text_type=text_type
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)
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except Exception as e:
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logger.error(f"Error en interfaz principal: {str(e)}")
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st.error("Ocurrió un error al cargar la interfaz")
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-
###################################
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def display_results(metrics, text_type=None):
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"""
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@@ -233,16 +356,20 @@ def display_results(metrics, text_type=None):
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logger.error(f"Error mostrando resultados: {str(e)}")
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st.error("Error al mostrar los resultados")
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-
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######################################
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-
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"""
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Muestra el gráfico radar con los resultados.
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"""
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try:
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# Preparar datos para el gráfico
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categories = [m['label'] for m in metrics_config]
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-
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min_values = [m['thresholds']['min'] for m in metrics_config]
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target_values = [m['thresholds']['target'] for m in metrics_config]
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@@ -253,7 +380,7 @@ def display_radar_chart(metrics_config, thresholds):
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# Configurar radar
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angles = [n / float(len(categories)) * 2 * np.pi for n in range(len(categories))]
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angles += angles[:1]
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-
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min_values += min_values[:1]
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target_values += target_values[:1]
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@@ -266,19 +393,53 @@ def display_radar_chart(metrics_config, thresholds):
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ax.set_ylim(0, 1)
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# Dibujar áreas de umbrales
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ax.plot(angles, min_values, '#e74c3c', linestyle='--', linewidth=1,
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-
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ax.
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-
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-
# Dibujar valores
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-
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-
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# Ajustar leyenda
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ax.legend(
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loc='upper right',
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-
bbox_to_anchor=(1.3, 1.1),
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fontsize=10,
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frameon=True,
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facecolor='white',
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@@ -293,4 +454,5 @@ def display_radar_chart(metrics_config, thresholds):
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except Exception as e:
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logger.error(f"Error mostrando gráfico radar: {str(e)}")
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st.error("Error al mostrar el gráfico")
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#######################################
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}
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####################################
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+
ANALYSIS_DIMENSION_MAPPING = {
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'morphosyntactic': {
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'primary': ['vocabulary', 'clarity'],
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'secondary': ['structure'],
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'tools': ['arc_diagrams', 'word_repetition']
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},
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'semantic': {
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'primary': ['cohesion', 'structure'],
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'secondary': ['vocabulary'],
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'tools': ['concept_graphs', 'semantic_networks']
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},
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'discourse': {
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'primary': ['cohesion', 'structure'],
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'secondary': ['clarity'],
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'tools': ['comparative_analysis']
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}
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}
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####################################
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def display_current_situation_interface(lang_code, nlp_models, t):
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"""
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Interfaz simplificada con gráfico de radar para visualizar métricas.
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# Container principal con dos columnas
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with st.container():
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input_col, results_col = st.columns([1,2])
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+
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with input_col:
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# Text area con manejo de estado
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text_input = st.text_area(
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metrics=st.session_state.current_metrics,
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text_type=text_type
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)
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# Agregar selector de modo
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analysis_mode = st.radio(
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"Modo de análisis",
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["Establecer línea base", "Comparar progreso"],
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key="analysis_mode"
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)
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if analysis_mode == "Establecer línea base":
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# Mostrar interfaz normal
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display_baseline_interface(lang_code, nlp_models, t)
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else:
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# Mostrar interfaz de comparación
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display_comparison_interface(lang_code, nlp_models, t)
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except Exception as e:
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logger.error(f"Error en interfaz principal: {str(e)}")
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st.error("Ocurrió un error al cargar la interfaz")
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###################################
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def display_baseline_interface(lang_code, nlp_models, t):
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"""Interfaz para establecer línea base"""
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# ... código existente de entrada de texto ...
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if st.button("Establecer como línea base"):
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metrics = analyze_text_dimensions(doc)
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store_baseline_metrics(
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username=st.session_state.username,
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metrics=metrics,
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text=text_input,
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timestamp=datetime.now()
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)
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st.success("Línea base establecida")
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def display_comparison_interface(lang_code, nlp_models, t):
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"""Interfaz para comparar progreso"""
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# Obtener línea base
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baseline = get_baseline_metrics(st.session_state.username)
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if not baseline:
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st.warning("Primero debes establecer una línea base")
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return
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# Mostrar entrada de texto actual
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current_text = st.text_area("Nuevo texto")
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if st.button("Analizar progreso"):
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current_metrics = analyze_text_dimensions(nlp_models[lang_code](current_text))
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# Mostrar comparación
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display_comparison_results(
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baseline_metrics=baseline['metrics'],
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current_metrics=current_metrics
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)
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# Opción para guardar progreso
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if st.button("Guardar este progreso"):
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store_progress_metrics(
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username=st.session_state.username,
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metrics=current_metrics,
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text=current_text,
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timestamp=datetime.now()
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)
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st.success("Progreso guardado")
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###################################
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def display_comparison_results(baseline_metrics, current_metrics):
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"""Muestra comparación entre línea base y métricas actuales"""
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# Crear columnas para métricas y gráfico
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metrics_col, graph_col = st.columns([1, 1.5])
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with metrics_col:
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for dimension in ['vocabulary', 'structure', 'cohesion', 'clarity']:
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baseline = baseline_metrics[dimension]['normalized_score']
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current = current_metrics[dimension]['normalized_score']
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delta = current - baseline
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st.metric(
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dimension.title(),
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f"{current:.2f}",
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f"{delta:+.2f}",
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delta_color="normal" if delta >= 0 else "inverse"
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)
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# Sugerir herramientas de mejora
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if delta < 0:
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suggest_improvement_tools(dimension)
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with graph_col:
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display_radar_chart_comparison(
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baseline_metrics,
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current_metrics
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)
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def suggest_improvement_tools(dimension):
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"""Sugiere herramientas basadas en la dimensión"""
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suggestions = []
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for analysis, mapping in ANALYSIS_DIMENSION_MAPPING.items():
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if dimension in mapping['primary']:
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suggestions.extend(mapping['tools'])
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st.info(f"Herramientas sugeridas para mejorar {dimension}:")
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for tool in suggestions:
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st.write(f"- {tool}")
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###################################
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def display_results(metrics, text_type=None):
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"""
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logger.error(f"Error mostrando resultados: {str(e)}")
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st.error("Error al mostrar los resultados")
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######################################
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+
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def display_radar_chart(metrics_config, thresholds, baseline_metrics=None):
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"""
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Muestra el gráfico radar con los resultados.
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Args:
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metrics_config: Configuración actual de métricas
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thresholds: Umbrales para las métricas
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baseline_metrics: Métricas de línea base (opcional)
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"""
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try:
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# Preparar datos para el gráfico
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categories = [m['label'] for m in metrics_config]
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values_current = [m['value'] for m in metrics_config]
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min_values = [m['thresholds']['min'] for m in metrics_config]
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target_values = [m['thresholds']['target'] for m in metrics_config]
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# Configurar radar
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angles = [n / float(len(categories)) * 2 * np.pi for n in range(len(categories))]
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angles += angles[:1]
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values_current += values_current[:1]
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min_values += min_values[:1]
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target_values += target_values[:1]
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ax.set_ylim(0, 1)
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# Dibujar áreas de umbrales
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ax.plot(angles, min_values, '#e74c3c', linestyle='--', linewidth=1,
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label='Mínimo', alpha=0.5)
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ax.plot(angles, target_values, '#2ecc71', linestyle='--', linewidth=1,
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label='Meta', alpha=0.5)
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ax.fill_between(angles, target_values, [1]*len(angles),
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color='#2ecc71', alpha=0.1)
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ax.fill_between(angles, [0]*len(angles), min_values,
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color='#e74c3c', alpha=0.1)
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# Si hay línea base, dibujarla primero
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if baseline_metrics is not None:
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values_baseline = [baseline_metrics[m['key']]['normalized_score']
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for m in metrics_config]
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values_baseline += values_baseline[:1]
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ax.plot(angles, values_baseline, '#888888', linewidth=2,
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label='Línea base', linestyle='--')
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ax.fill(angles, values_baseline, '#888888', alpha=0.1)
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# Dibujar valores actuales
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label = 'Actual' if baseline_metrics else 'Tu escritura'
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color = '#3498db' if baseline_metrics else '#3498db'
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ax.plot(angles, values_current, color, linewidth=2, label=label)
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ax.fill(angles, values_current, color, alpha=0.2)
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# Ajustar leyenda
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legend_handles = []
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if baseline_metrics:
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legend_handles.extend([
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plt.Line2D([], [], color='#888888', linestyle='--',
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label='Línea base'),
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plt.Line2D([], [], color='#3498db', label='Actual')
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])
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else:
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legend_handles.extend([
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plt.Line2D([], [], color='#3498db', label='Tu escritura')
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])
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legend_handles.extend([
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plt.Line2D([], [], color='#e74c3c', linestyle='--', label='Mínimo'),
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plt.Line2D([], [], color='#2ecc71', linestyle='--', label='Meta')
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])
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ax.legend(
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handles=legend_handles,
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loc='upper right',
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bbox_to_anchor=(1.3, 1.1),
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fontsize=10,
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frameon=True,
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facecolor='white',
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except Exception as e:
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logger.error(f"Error mostrando gráfico radar: {str(e)}")
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st.error("Error al mostrar el gráfico")
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#######################################
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