Update app.py

app.py

@@ -2,6 +2,12 @@ import gradio as gr
 import numpy as np
 import matplotlib.pyplot as plt
 
+def create_error_plot(error_message):
+    fig, ax = plt.subplots(figsize=(10, 6))
+    ax.text(0.5, 0.5, error_message, color='red', fontsize=16, ha='center', va='center', wrap=True)
+    ax.axis('off')
+    return fig
+
 def linear_interpolation(x, y, x_interp):
     return np.interp(x_interp, x, y)
 
@@ -23,11 +29,20 @@ def lagrange_interpolation(x, y, x_interp):
     return y_interp
 
 def interpolate_and_plot(x_input, y_input, x_predict):
-    x = np.array([float(val.strip()) for val in x_input.split(',')])
-    y = np.array([float(val.strip()) for val in y_input.split(',')])
+    try:
+        x = np.array([float(val.strip()) for val in x_input.split(',')])
+        y = np.array([float(val.strip()) for val in y_input.split(',')])
+    except ValueError:
+        error_msg = "Error: Invalid input. Please enter comma-separated numbers."
+        return create_error_plot(error_msg), f'<p style="color: red;">{error_msg}</p>'
     
     if len(x) != len(y):
-        return "Error: Number of x and y values must be the same.", None
+        error_msg = "Error: Number of x and y values must be the same."
+        return create_error_plot(error_msg), f'<p style="color: red;">{error_msg}</p>'
+    
+    if len(x) < 2:
+        error_msg = "Error: At least two points are required for interpolation."
+        return create_error_plot(error_msg), f'<p style="color: red;">{error_msg}</p>'
     
     x_interp = np.linspace(min(x), max(x), 100)
     
@@ -41,33 +56,39 @@ def interpolate_and_plot(x_input, y_input, x_predict):
         y_interp = lagrange_interpolation(x, y, x_interp)
         method = "Lagrange"
     
-    plt.figure(figsize=(10, 6))
-    plt.scatter(x, y, color='red', label='Input points')
-    plt.plot(x_interp, y_interp, label=f'{method} interpolant')
-    plt.xlabel('x')
-    plt.ylabel('y')
-    plt.title(f'{method} Interpolation')
-    plt.legend()
-    plt.grid(True)
+    fig, ax = plt.subplots(figsize=(10, 6))
+    ax.scatter(x, y, color='red', label='Input points')
+    ax.plot(x_interp, y_interp, label=f'{method} interpolant')
+    ax.set_xlabel('x')
+    ax.set_ylabel('y')
+    ax.set_title(f'{method} Interpolation')
+    ax.legend()
+    ax.grid(True)
     
     # Predict y value for given x
     if x_predict is not None:
-        if x_predict < min(x) or x_predict > max(x):
-            return plt, f"Error: Prediction x value must be between {min(x)} and {max(x)}."
-        
-        if len(x) == 2:
-            y_predict = linear_interpolation(x, y, [x_predict])[0]
-        elif len(x) == 3:
-            y_predict = quadratic_interpolation(x, y, [x_predict])[0]
-        else:
-            y_predict = lagrange_interpolation(x, y, [x_predict])[0]
-        
-        plt.scatter([x_predict], [y_predict], color='green', s=100, label='Predicted point')
-        plt.legend()
-        
-        return plt, f"Predicted y value for x = {x_predict}: {y_predict:.4f}"
+        try:
+            x_predict = float(x_predict)
+            if x_predict < min(x) or x_predict > max(x):
+                error_msg = f"Error: Prediction x value must be between {min(x)} and {max(x)}."
+                return fig, f'<p style="color: red;">{error_msg}</p>'
+            
+            if len(x) == 2:
+                y_predict = linear_interpolation(x, y, [x_predict])[0]
+            elif len(x) == 3:
+                y_predict = quadratic_interpolation(x, y, [x_predict])[0]
+            else:
+                y_predict = lagrange_interpolation(x, y, [x_predict])[0]
+            
+            ax.scatter([x_predict], [y_predict], color='green', s=100, label='Predicted point')
+            ax.legend()
+            
+            return fig, f"Predicted y value for x = {x_predict}: {y_predict:.4f}"
+        except ValueError:
+            error_msg = "Error: Invalid input for x prediction. Please enter a number."
+            return create_error_plot(error_msg), f'<p style="color: red;">{error_msg}</p>'
     
-    return plt, None
+    return fig, None
 
 iface = gr.Interface(
     fn=interpolate_and_plot,
@@ -78,10 +99,10 @@ iface = gr.Interface(
     ],
     outputs=[
         gr.Plot(label="Interpolation Plot"),
-        gr.Textbox(label="Predicted Y value")
+        gr.HTML(label="Result or Error Message")
     ],
     title="Interpolation App",
-    description="Enter x and y values to see the interpolation graph. The method will be chosen based on the number of points:\n2 points: Linear, 3 points: Quadratic, >3 points: Lagrange.\n Optionally, enter an x value (between min and max of input x values) to predict its corresponding y value."
+    description="Enter x and y values to see the interpolation graph. The method will be chosen based on the number of points:\n2 points: Linear, 3 points: Quadratic, >3 points: Lagrange\nOptionally, enter an x value (between min and max of input x values) to predict its corresponding y value."
 )
 
 iface.launch()