Update app.py

app.py

@@ -3,6 +3,7 @@ import matplotlib.pyplot as plt
 from matplotlib_venn import venn3
 from io import BytesIO
 from PIL import Image
+import pandas as pd
 
 def validate_inputs(A, B, C, AB, AC, BC, ABC, U):
     errors = []
@@ -21,11 +22,20 @@ def suggest_intersections(A, B, C, U):
     max_AC = min(A, C, U - (A + B + C - A - C))
     max_BC = min(B, C, U - (A + B + C - B - C))
     max_ABC = min(max_AB, max_AC, max_BC)
-    
+
+    min_AB = max(0, A + B + C - A - B - C + ABC - U)
+    min_AC = max(0, A + C + B - A - C - B + ABC - U)
+    min_BC = max(0, B + C + A - B - C - A + ABC - U)
+    min_ABC = max(0, ABC - (A + B + C - AB - AC - BC + ABC))
+
     suggestions = {
+        "Mínimo valor sugerido para A ∩ B": min_AB,
         "Máximo valor sugerido para A ∩ B": max_AB,
+        "Mínimo valor sugerido para A ∩ C": min_AC,
         "Máximo valor sugerido para A ∩ C": max_AC,
+        "Mínimo valor sugerido para B ∩ C": min_BC,
         "Máximo valor sugerido para B ∩ C": max_BC,
+        "Mínimo valor sugerido para A ∩ B ∩ C": min_ABC,
         "Máximo valor sugerido para A ∩ B ∩ C": max_ABC,
     }
     return suggestions
@@ -50,7 +60,11 @@ def calculate_probabilities(A, B, C, AB, AC, BC, ABC, U):
     P_AC = AC / total
     P_BC = BC / total
     P_ABC = ABC / total
-    
+
+    PA_given_B = P_AB / P_B if P_B > 0 else 0
+    PA_given_C = P_AC / P_C if P_C > 0 else 0
+    PB_given_C = P_BC / P_C if P_C > 0 else 0
+
     formatted_probs = {
         "P(A)": f"{P_A:.2%} ({A}/{total})",
         "P(B)": f"{P_B:.2%} ({B}/{total})",
@@ -59,48 +73,16 @@ def calculate_probabilities(A, B, C, AB, AC, BC, ABC, U):
         "P(A ∩ C)": f"{P_AC:.2%} ({AC}/{total})",
         "P(B ∩ C)": f"{P_BC:.2%} ({BC}/{total})",
         "P(A ∩ B ∩ C)": f"{P_ABC:.2%} ({ABC}/{total})",
+        "P(A | B)": f"{PA_given_B:.2%}",
+        "P(A | C)": f"{PA_given_C:.2%}",
+        "P(B | C)": f"{PB_given_C:.2%}",
+        "U (Universal Set)": total,
+        "Complemento de A U B U C": U - (A + B + C - AB - AC - BC + ABC)
     }
     
-    return formatted_probs
-
-def plot_venn(A, B, C, AB, AC, BC, ABC):
-    plt.figure(figsize=(8, 8))
-    venn = venn3(subsets=(A, B, AB, C, AC, BC, ABC), set_labels=('A', 'B', 'C'))
-    plt.title("Venn Diagram")
-    
-    buf = BytesIO()
-    plt.savefig(buf, format='png')
-    buf.seek(0)
-    img = Image.open(buf)
-    return img
-
-def main(A, B, C, AB, AC, BC, ABC, U):
-    errors = validate_inputs(A, B, C, AB, AC, BC, ABC, U)
-    if errors:
-        suggestions = suggest_intersections(A, B, C, U)
-        return None, {"error": "\n".join(errors), "sugerencias": suggestions}
-    
-    venn_diagram = plot_venn(A, B, C, AB, AC, BC, ABC)
-    probabilities = calculate_probabilities(A, B, C, AB, AC, BC, ABC, U)
-    return venn_diagram, probabilities
-
-iface = gr.Interface(
-    fn=main,
-    inputs=[
-        gr.Number(label="Cantidad en A"),
-        gr.Number(label="Cantidad en B"),
-        gr.Number(label="Cantidad en C"),
-        gr.Number(label="Cantidad en A ∩ B"),
-        gr.Number(label="Cantidad en A ∩ C"),
-        gr.Number(label="Cantidad en B ∩ C"),
-        gr.Number(label="Cantidad en A ∩ B ∩ C"),
-        gr.Number(label="Conjunto Universal (U)")
-    ],
-    outputs=[
-        gr.Image(type="pil", label="Diagrama de Venn"),
-        gr.JSON(label="Resultados")
-    ],
-    live=True
-)
+    # Convert to DataFrame for better visualization
+    df = pd.DataFrame(list(formatted_probs.items()), columns=["Descripción", "Valor"])
+    return df
 
-iface.launch()
+# This function should be integrated with the main part of the app or interface
+# It could be connected to a gradio UI, for example, to allow interactive use