Add data plot

regularization.py

@@ -51,8 +51,6 @@ class Regularization:
         self.canvas_width = width
         self.canvas_height = height
 
-        self.plot_regularization_path = False
-
         self.css ="""
 #my-button {
     height: 30px;
@@ -110,6 +108,8 @@ class Regularization:
         self.w2_range = (-100, 100)
         self.num_dots = 100
 
+        self.plot_regularization_path = False
+
     def plot(self):
         '''
         '''
@@ -166,24 +166,23 @@ class Regularization:
         print(loss_levels)
 
         # plot contour plots
-        fig = plt.figure(figsize=(5, 5))
-        ax = plt.gca()
-        ax.set_title("")
-        ax.set_xlabel("w1")
-        ax.set_ylabel("w2")
-
+        # fig = plt.figure(figsize=(5, 5))
+        fig, axs = plt.subplots(1, 2, figsize=(10, 5))
+        axs[0].set_title("")
+        axs[0].set_xlabel("w1")
+        axs[0].set_ylabel("w2")
 
         cmap = plt.get_cmap("viridis")   
         N = len(reg_levels)
         colors = [cmap(i / (N - 1)) for i in range(N)]
 
         # regularizer contours
-        cs1 = ax.contour(W1, W2, regs, levels=reg_levels, colors=colors, linestyles="dashed")
-        ax.clabel(cs1, inline=True, fontsize=8) # show contour levels
+        cs1 = axs[0].contour(W1, W2, regs, levels=reg_levels, colors=colors, linestyles="dashed")
+        axs[0].clabel(cs1, inline=True, fontsize=8) # show contour levels
 
         # loss contours
-        cs2 = ax.contour(W1, W2, losses, levels=loss_levels, colors=colors[::-1])
-        ax.clabel(cs2, inline=True, fontsize=8)
+        cs2 = axs[0].contour(W1, W2, losses, levels=loss_levels, colors=colors[::-1])
+        axs[0].clabel(cs2, inline=True, fontsize=8)
 
         # plot path
         if self.plot_regularization_path:
@@ -198,7 +197,7 @@ class Regularization:
                 path_w.append(stacked[mask][idx])
             
             path_w = np.array(path_w)
-            ax.plot(path_w[:, 0], path_w[:, 1], "r-")
+            axs[0].plot(path_w[:, 0], path_w[:, 1], "r-")
 
         # custom legend
         loss_line = mlines.Line2D([], [], color='black', linestyle='-', label='loss')
@@ -207,7 +206,13 @@ class Regularization:
         if self.plot_regularization_path:
             path_line = mlines.Line2D([], [], color='red', linestyle='-', label='regularization path')
             handles.append(path_line)
-        ax.legend(handles=handles)
+        axs[0].legend(handles=handles)
+
+        # plot data points
+        axs[1].set_xlabel("X1")
+        axs[1].set_ylabel("X2")
+        sc = axs[1].scatter(X[:, 0], X[:, 1], c=y, cmap="viridis")
+        fig.colorbar(sc, ax=axs[1], label="y")
 
         # plot solutions
         #for alpha, w, norm, mse in solutions:
@@ -215,7 +220,7 @@ class Regularization:
             ##ax.text(w[0], w[1], f"α={alpha}", fontsize=8)
 
         buf = io.BytesIO()
-        ax.figure.savefig(buf, format="png", bbox_inches="tight", pad_inches=0)
+        fig.savefig(buf, format="png", bbox_inches="tight", pad_inches=0)
         plt.close(fig)
         buf.seek(0)
         img = Image.open(buf)