Update app.py

app.py

@@ -17,6 +17,24 @@ from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
 from matplotlib.colors import to_hex
 import os
 
+# --- Data definition in global scope ---
+data_dict = {
+    'Tratamiento': ['T1', 'T2', 'T3', 'T4', 'T5', 'T6', 'T7', 'T8', 'T9', 'T10', 'T11', 'T12', 'T13', 'T14', 'T15'] * 3,
+    'Tiempo_fermentacion_h': [16] * 15 + [23] * 15 + [40] * 15,
+    'pH': [6.02, 5.39, 6.27, 4.82, 6.25, 4.87, 4.76, 4.68, 4.64, 6.35, 4.67, 6.43, 4.58, 4.60, 6.96,
+           5.17, 5.95, 6.90, 5.50, 5.08, 4.95, 5.41, 5.52, 4.98, 7.10, 5.36, 6.91, 5.21, 4.66, 7.10,
+           5.42, 5.60, 7.36, 5.36, 4.66, 4.93, 5.18, 5.26, 4.92, 7.28, 5.26, 6.84, 5.19, 4.58, 7.07],
+    'Abs_600nm': [1.576, 1.474, 1.293, 1.446, 1.537, 1.415, 1.481, 1.419, 1.321, 1.224, 1.459, 0.345, 1.279, 1.181, 0.662,
+                  1.760, 1.690, 1.485, 1.658, 1.728, 1.594, 1.673, 1.607, 1.531, 1.424, 1.595, 0.344, 1.477, 1.257, 0.660,
+                  1.932, 1.780, 1.689, 1.876, 1.885, 1.824, 1.913, 1.810, 1.852, 1.694, 1.831, 0.347, 1.752, 1.367, 0.656],
+    'Glucosa_g_L': [5,10,0,5,10,5,10,5,10,0,5,0,5,5,0] * 3,
+    'Proteina_Pescado_g_L': [1.4,1.4,3.2,3.2,3.2,3.2,3.2,5,5,5,5,0,5,5,0] * 3,
+    'Sulfato_Manganeso_g_L': [0.75,0.5,0.75,0.5,0.75,0.5,0.75,0.5,0.25,0.75,0.5,0.25,0.5,0.25,0.5] * 3
+}
+data = pd.DataFrame(data_dict)
+# --- End of data definition in global scope ---
+
+
 # --- Clase RSM_BoxBehnken ---
 class RSM_BoxBehnken:
     def __init__(self, data, x1_name, x2_name, x3_name, y_name, x1_levels, x2_levels, x3_levels):
@@ -603,21 +621,8 @@ def load_data(data_str): # Modified load_data to only take data_str
     Carga los datos del diseño Box-Behnken desde cajas de texto y crea la instancia de RSM_BoxBehnken.
     """
     try:
-        # Use the data dictionary directly
-        data_dict = {
-            'Tratamiento': ['T1', 'T2', 'T3', 'T4', 'T5', 'T6', 'T7', 'T8', 'T9', 'T10', 'T11', 'T12', 'T13', 'T14', 'T15'] * 3,
-            'Tiempo_fermentacion_h': [16] * 15 + [23] * 15 + [40] * 15,
-            'pH': [6.02, 5.39, 6.27, 4.82, 6.25, 4.87, 4.76, 4.68, 4.64, 6.35, 4.67, 6.43, 4.58, 4.60, 6.96,
-                   5.17, 5.95, 6.90, 5.50, 5.08, 4.95, 5.41, 5.52, 4.98, 7.10, 5.36, 6.91, 5.21, 4.66, 7.10,
-                   5.42, 5.60, 7.36, 5.36, 4.66, 4.93, 5.18, 5.26, 4.92, 7.28, 5.26, 6.84, 5.19, 4.58, 7.07],
-            'Abs_600nm': [1.576, 1.474, 1.293, 1.446, 1.537, 1.415, 1.481, 1.419, 1.321, 1.224, 1.459, 0.345, 1.279, 1.181, 0.662,
-                          1.760, 1.690, 1.485, 1.658, 1.728, 1.594, 1.673, 1.607, 1.531, 1.424, 1.595, 0.344, 1.477, 1.257, 0.660,
-                          1.932, 1.780, 1.689, 1.876, 1.885, 1.824, 1.913, 1.810, 1.852, 1.694, 1.831, 0.347, 1.752, 1.367, 0.656],
-            'Glucosa_g_L': [5,10,0,5,10,5,10,5,10,0,5,0,5,5,0] * 3,
-            'Proteina_Pescado_g_L': [1.4,1.4,3.2,3.2,3.2,3.2,3.2,5,5,5,5,0,5,5,0] * 3,
-            'Sulfato_Manganeso_g_L': [0.75,0.5,0.75,0.5,0.75,0.5,0.75,0.5,0.25,0.75,0.5,0.25,0.5,0.25,0.5] * 3
-        }
-        data = pd.DataFrame(data_dict)
+        # Use the global data DataFrame
+        global rsm, data
 
         x1_name = "Glucosa_g_L"
         x2_name = "Proteina_Pescado_g_L"
@@ -629,7 +634,6 @@ def load_data(data_str): # Modified load_data to only take data_str
 
 
         # Crear la instancia de RSM_BoxBehnken
-        global rsm
         rsm = RSM_BoxBehnken(data, x1_name, x2_name, x3_name, y_name, x1_levels, x2_levels, x3_levels)
 
         return data.round(3), gr.update(visible=True) # Removed other outputs, only return data_output and analysis_row
@@ -705,7 +709,7 @@ def navigate_plot(direction, current_index, all_figures):
     selected_fig = all_figures[new_index]
     plot_info_text = f"Gráfico {new_index + 1} de {len(all_figures)}"
 
-    return selected_fig, plot_info_text, new_index
+    return selected_fig, plot_info_text, current_index
 
 def download_current_plot(all_figures, current_index):
     """