Update app.py

app.py

@@ -3,6 +3,7 @@ import pandas as pd
 import statsmodels.api as sm
 import numpy as np
 import matplotlib.pyplot as plt
+import seaborn as sns
 from itertools import product
 
 # Function to apply transformations to both features and target
@@ -66,25 +67,29 @@ def load_excel(file):
 
                         # Plot 1: Transformed_target vs. Predicted values
                         predicted = model.predict(transformed_features)
-                        axes[0].scatter(transformed_target, predicted)
-                        axes[0].set_title('Transformed_target vs. Predicted')
-                        axes[0].set_xlabel('Transformed_target')
-                        axes[0].set_ylabel('Predicted')
+                        plt.figure(figsize=(18, 6))
+                        sns.scatterplot(x=transformed_target, y=predicted)
+                        plt.xlabel("Observados")
+                        plt.ylabel("Previstos")
+                        plt.tight_layout()
+                        plt.plot(X_plot, Y_plot, color='r')
+                        plt.savefig("scatterplot.png")
+                        plt.close()
 
                         # Plot 2: Residuals
                         residuals = model.resid
-                        axes[1].hist(residuals, bins=30, edgecolor='k')
-                        axes[1].set_title('Residuals Histogram')
-                        axes[1].set_xlabel('Residuals')
-                        axes[1].set_ylabel('Frequency')
+                        plt.figure(figsize=(18, 6))
+                        sns.histplot(data = residuals, kde=True)
+                        plt.savefig("histplot.png")
+                        plt.close()
 
                         # Create a table for residuals
                         residuals_table = pd.DataFrame({'Residuals': residuals})
 
                         results.append({
                             'best_equation': model.summary().as_text(),
-                            'plot_transformed_vs_predicted': fig,  # Use the figure object
-                            'plot_residuals_histogram': fig,  # Use the figure object
+                            'plot_transformed_vs_predicted': "scatterplot.png",  # Use the figure object
+                            'plot_residuals_histogram': "histplot.png",  # Use the figure object
                             'residuals_table': residuals_table
                         })
 
@@ -96,10 +101,10 @@ iface = gr.Interface(
     fn=load_excel,
     inputs="file",
     outputs=[
-        gr.Textbox(label="Best Equation", type="text"),
-        gr.Plot(label="Transformed_target vs. Predicted", type="plot"),
-        gr.Plot(label="Residuals Histogram", type="plot"),
-        gr.DataFrame(label="Residuals Table", type="pandas"),
+        gr.Textbox(label="Resultados Estatísticos", type="text"),
+        gr.Image(label="Gráfico - Observados X Previstos"),
+        gr.Image(label="Histograma de Resíduos"),
+        gr.DataFrame(label="Tabela dos Resíduos", type="pandas"),
     ],
     live=False,
     theme=gr.themes.Monochrome(),