Update _Dist/NeuralNetworks

Author: carefree0910

_Dist/NeuralNetworks/Base.py

@@ -711,7 +711,7 @@ def transform_arr(arr):
         return self
 
     def visualize2d(self, x, y, padding=0.1, dense=200, title=None,
-                    show_org=False, draw_background=True, emphasize=None, extra=None):
+                    scatter=True, show_org=False, draw_background=True, emphasize=None, extra=None):
         axis, labels = np.asarray(x).T, np.asarray(y)
 
         print("=" * 30 + "\n" + str(self))
@@ -764,7 +764,8 @@ def get_base(_nx, _ny):
             plt.pcolormesh(xy_xf, xy_yf, z, cmap=plt.cm.Pastel1)
         else:
             plt.contour(xf, yf, z, c='k-', levels=[0])
-        plt.scatter(axis[0], axis[1], c=colors)
+        if scatter:
+            plt.scatter(axis[0], axis[1], c=colors)
         if emphasize is not None:
             indices = np.array([False] * len(axis[0]))
             indices[np.asarray(emphasize)] = True

_Dist/NeuralNetworks/d_Traditional2NN/Toolbox.py

@@ -172,18 +172,3 @@ def _transform(self):
         w2 *= max_route_length
         self._transform_ws = [w1, w2, w3]
         self._transform_bs = [b]
-
-
-if __name__ == '__main__':
-    from Util.Util import DataUtil
-
-    centers = (1, 1)
-    slopes = (0.5, -2)
-    x, y = DataUtil.gen_x_set(1000, centers, slopes, one_hot=False)
-    x_test, y_test = DataUtil.gen_x_set(100, centers, slopes, one_hot=False)
-
-    (x, y), (x_test, y_test), *_ = DataUtil.get_dataset("cifar10", "../../../_Data/cifar10.txt", 400, quantized=True)
-
-    DT2NN().fit(x, y, x_test, y_test).scatter2d(
-        x, y, padding=0.1, title="X set"
-    ).visualize2d(x, y).visualize2d(x_test, y_test, padding=1)