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# modules/studentact/current_situation_interface.py
import streamlit as st
import logging
from ..utils.widget_utils import generate_unique_key
import matplotlib.pyplot as plt
import numpy as np
from ..database.current_situation_mongo_db import store_current_situation_result
from .current_situation_analysis import (
analyze_text_dimensions,
analyze_clarity,
analyze_vocabulary_diversity,
analyze_cohesion,
analyze_structure,
get_dependency_depths,
normalize_score,
generate_sentence_graphs,
generate_word_connections,
generate_connection_paths,
create_vocabulary_network,
create_syntax_complexity_graph,
create_cohesion_heatmap,
)
# Configuración del estilo de matplotlib para el gráfico de radar
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['axes.grid'] = True
plt.rcParams['axes.spines.top'] = False
plt.rcParams['axes.spines.right'] = False
logger = logging.getLogger(__name__)
####################################
TEXT_TYPES = {
'academic_article': {
'name': 'Artículo Académico',
'thresholds': {
'vocabulary': {'min': 0.70, 'target': 0.85},
'structure': {'min': 0.75, 'target': 0.90},
'cohesion': {'min': 0.65, 'target': 0.80},
'clarity': {'min': 0.70, 'target': 0.85}
}
},
'student_essay': {
'name': 'Trabajo Universitario',
'thresholds': {
'vocabulary': {'min': 0.60, 'target': 0.75},
'structure': {'min': 0.65, 'target': 0.80},
'cohesion': {'min': 0.55, 'target': 0.70},
'clarity': {'min': 0.60, 'target': 0.75}
}
},
'general_communication': {
'name': 'Comunicación General',
'thresholds': {
'vocabulary': {'min': 0.50, 'target': 0.65},
'structure': {'min': 0.55, 'target': 0.70},
'cohesion': {'min': 0.45, 'target': 0.60},
'clarity': {'min': 0.50, 'target': 0.65}
}
}
}
####################################
def display_current_situation_interface(lang_code, nlp_models, current_situation_t):
"""
Interfaz simplificada con gráfico de radar para visualizar métricas.
"""
# Inicializar estados si no existen
if 'text_input' not in st.session_state:
st.session_state.text_input = ""
if 'text_area' not in st.session_state: # Añadir inicialización de text_area
st.session_state.text_area = ""
if 'show_results' not in st.session_state:
st.session_state.show_results = False
if 'current_doc' not in st.session_state:
st.session_state.current_doc = None
if 'current_metrics' not in st.session_state:
st.session_state.current_metrics = None
try:
# Container principal con dos columnas
with st.container():
input_col, results_col = st.columns([1,2])
with input_col:
# Text area con manejo de estado
text_input = st.text_area(
current_situation_t.get('input_prompt', 'Escribe tu texto aquí'),
height=400,
key="text_area",
value=st.session_state.text_input,
help=current_situation_t.get('help', 'Ayuda sobre el campo de texto')
)
# Función para manejar cambios de texto
if text_input != st.session_state.text_input:
st.session_state.text_input = text_input
st.session_state.show_results = False
if st.button(
current_situation_t.get('analyze_button', 'Analizar texto'),
type="primary",
disabled=not text_input.strip(),
use_container_width=True,
):
try:
with st.spinner(current_situation_t.get('processing', 'Analizando...')):
doc = nlp_models[lang_code](text_input)
metrics = analyze_text_dimensions(doc)
storage_success = store_current_situation_result(
username=st.session_state.username,
text=text_input,
metrics=metrics,
feedback=None
)
if not storage_success:
logger.warning("No se pudo guardar el análisis en la base de datos")
st.session_state.current_doc = doc
st.session_state.current_metrics = metrics
st.session_state.show_results = True
except Exception as e:
logger.error(f"Error en análisis: {str(e)}")
st.error(current_situation_t.get('analysis_error', 'Error analyzing text'))
# Mostrar resultados en la columna derecha
with results_col:
if st.session_state.show_results and st.session_state.current_metrics is not None:
# Primero los radio buttons para tipo de texto
st.markdown(f"### {current_situation_t.get('text_type_header', 'Tipo de texto')}")
text_type = st.radio(
"Selecciona el tipo de texto",
options=list(TEXT_TYPES.keys()),
format_func=lambda x: TEXT_TYPES[x]['name'],
horizontal=True,
key="text_type_radio",
help=current_situation_t.get('text_type_help', 'Select the type of text to adjust the evaluation criteria')
)
st.session_state.current_text_type = text_type
# Obtener umbrales basados en el tipo de texto
thresholds = TEXT_TYPES[text_type]['thresholds']
# Preparar configuración de métricas para el gráfico de radar
metrics_config = [
{
'label': current_situation_t.get('vocabulary_label', 'Vocabulario'),
'value': st.session_state.current_metrics['vocabulary'],
'thresholds': {
'min': thresholds['vocabulary']['min'],
'target': thresholds['vocabulary']['target']
}
},
{
'label': current_situation_t.get('structure_label', 'Estructura'),
'value': st.session_state.current_metrics['structure'],
'thresholds': {
'min': thresholds['structure']['min'],
'target': thresholds['structure']['target']
}
},
{
'label': current_situation_t.get('cohesion_label', 'Cohesión'),
'value': st.session_state.current_metrics['cohesion'],
'thresholds': {
'min': thresholds['cohesion']['min'],
'target': thresholds['cohesion']['target']
}
},
{
'label': current_situation_t.get('clarity_label', 'Claridad'),
'value': st.session_state.current_metrics['clarity'],
'thresholds': {
'min': thresholds['clarity']['min'],
'target': thresholds['clarity']['target']
}
}
]
# Usar la función display_radar_chart que ya existe
display_radar_chart(
metrics_config=metrics_config,
thresholds=thresholds,
current_situation_t=current_situation_t
)
except Exception as e:
logger.error(f"Error en interfaz principal: {str(e)}")
st.error(current_situation_t.get('error_chart', 'Error al mostrar el gráfico'))
######################################
def display_radar_chart(metrics_config, thresholds, current_situation_t):
"""
Muestra el gráfico radar con los resultados.
"""
try:
# Preparar datos para el gráfico
categories = [m['label'] for m in metrics_config]
values_user = [m['value'] for m in metrics_config]
min_values = [m['thresholds']['min'] for m in metrics_config]
target_values = [m['thresholds']['target'] for m in metrics_config]
# Crear y configurar gráfico
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(111, projection='polar')
# Configurar radar
angles = [n / float(len(categories)) * 2 * np.pi for n in range(len(categories))]
angles += angles[:1]
values_user += values_user[:1]
min_values += min_values[:1]
target_values += target_values[:1]
# Configurar ejes
ax.set_xticks(angles[:-1])
ax.set_xticklabels(categories, fontsize=10)
circle_ticks = np.arange(0, 1.1, 0.2)
ax.set_yticks(circle_ticks)
ax.set_yticklabels([f'{tick:.1f}' for tick in circle_ticks], fontsize=8)
ax.set_ylim(0, 1)
# Dibujar áreas de umbrales
ax.plot(angles, min_values, '#e74c3c', linestyle='--', linewidth=1, label='Mínimo', alpha=0.5)
ax.plot(angles, target_values, '#2ecc71', linestyle='--', linewidth=1, label='Meta', alpha=0.5)
ax.fill_between(angles, target_values, [1]*len(angles), color='#2ecc71', alpha=0.1)
ax.fill_between(angles, [0]*len(angles), min_values, color='#e74c3c', alpha=0.1)
# Dibujar valores del usuario
ax.plot(angles, values_user, '#3498db', linewidth=2, label='Tu escritura')
ax.fill(angles, values_user, '#3498db', alpha=0.2)
# Ajustar leyenda
ax.legend(
loc='upper right',
bbox_to_anchor=(1.3, 1.1),
fontsize=10,
frameon=True,
facecolor='white',
edgecolor='none',
shadow=True
)
plt.tight_layout()
st.pyplot(fig)
plt.close()
except Exception as e:
logger.error(f"Error mostrando gráfico radar: {str(e)}")
st.error(current_situation_t['error_chart'])
####################################### |