diff --git a/old_projects/WindingNumber_G.py b/old_projects/WindingNumber_G.py
index c891fb3d..817cbcc3 100644
--- a/old_projects/WindingNumber_G.py
+++ b/old_projects/WindingNumber_G.py
@@ -2351,6 +2351,7 @@ class TransitionFromPathsToBoundariesArrowless(TransitionFromPathsToBoundaries):
 
 class BreakDownLoopWithNonzeroWinding(TransitionFromPathsToBoundaries):
     def construct(self):
+        TransitionFromPathsToBoundaries.construct(self)
         zero_point = 2*LEFT
 
         squares, joint_rect = self.get_squares_and_joint_rect()
diff --git a/old_projects/brachistochrone/cycloid.py b/old_projects/brachistochrone/cycloid.py
index fd62497d..ef624126 100644
--- a/old_projects/brachistochrone/cycloid.py
+++ b/old_projects/brachistochrone/cycloid.py
@@ -337,7 +337,7 @@ class LeviSolution(CycloidScene):
         new_theta.next_to(new_arc, LEFT)
         new_theta.shift(0.1*DOWN)
         kwargs = {
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS,
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH,
         }
         triangle1 = Polygon(
             self.p_point, self.c_point, self.bottom_point,
diff --git a/old_projects/complex_multiplication_article.py b/old_projects/complex_multiplication_article.py
index 18c445e5..656411d8 100644
--- a/old_projects/complex_multiplication_article.py
+++ b/old_projects/complex_multiplication_article.py
@@ -9,7 +9,7 @@ from big_ol_pile_of_manim_imports import *
 from functools import reduce
 
 DEFAULT_PLANE_CONFIG = {
-    "stroke_width" : 2*DEFAULT_POINT_THICKNESS
+    "stroke_width" : 2*DEFAULT_STROKE_WIDTH
     }
 
 
diff --git a/old_projects/matrix_as_transform_2d.py b/old_projects/matrix_as_transform_2d.py
index 4bd7176f..bf03ea97 100644
--- a/old_projects/matrix_as_transform_2d.py
+++ b/old_projects/matrix_as_transform_2d.py
@@ -7,7 +7,7 @@ import sys
 
 from big_ol_pile_of_manim_imports import *
 
-ARROW_CONFIG = {"stroke_width" : 2*DEFAULT_POINT_THICKNESS}
+ARROW_CONFIG = {"stroke_width" : 2*DEFAULT_STROKE_WIDTH}
 LIGHT_RED = RED_E
 
 def matrix_to_string(matrix):
@@ -52,7 +52,7 @@ class ShowMultiplication(NumberLineScene):
     def construct(self, num, show_original_line):
         config = {
             "density" : max(abs(num), 1)*DEFAULT_POINT_DENSITY_1D,
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH
         }
         if abs(num) < 1:
             config["numerical_radius"] = FRAME_X_RADIUS/num
@@ -115,7 +115,7 @@ class ExamplesOfNonlinearOneDimensionalTransforms(NumberLineScene):
         self.clear()
         self.add(self.nonlinear)
         config = {
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS,
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH,
             "density" : 5*DEFAULT_POINT_DENSITY_1D,
         }
         NumberLineScene.construct(self, **config)
@@ -144,7 +144,7 @@ class ShowTwoThenThree(ShowMultiplication):
 
     def construct(self):
         config = {
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS,
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH,
             "density" : 6*DEFAULT_POINT_DENSITY_1D,
         }
         NumberLineScene.construct(self, **config)
@@ -163,7 +163,7 @@ class TransformScene2D(Scene):
             "x_radius" : FRAME_WIDTH,
             "y_radius" : FRAME_WIDTH,
             "density" : DEFAULT_POINT_DENSITY_1D*density_factor,
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH
         }
         if not use_faded_lines:
             config["x_faded_line_frequency"] = None
@@ -323,7 +323,7 @@ class ExamplesOfNonlinearTwoDimensionalTransformations(Scene):
             "x_radius" : FRAME_WIDTH,
             "y_radius" : FRAME_WIDTH,
             "density" : 3*DEFAULT_POINT_DENSITY_1D,
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH
         }
         number_plane = NumberPlane(**config)
         numbers = number_plane.get_coordinate_labels()
@@ -377,7 +377,7 @@ class TrickyExamplesOfNonlinearTwoDimensionalTransformations(Scene):
             "x_radius" : 0.6*FRAME_WIDTH,
             "y_radius" : 0.6*FRAME_WIDTH,
             "density" : 10*DEFAULT_POINT_DENSITY_1D,
-            "stroke_width" : 2*DEFAULT_POINT_THICKNESS
+            "stroke_width" : 2*DEFAULT_STROKE_WIDTH
         }
         number_plane = NumberPlane(**config)
         phrase1, phrase2 = TextMobject([
diff --git a/old_projects/nn/image_map b/old_projects/nn/image_map
index ca5133bb..88d8277f 100644
Binary files a/old_projects/nn/image_map and b/old_projects/nn/image_map differ
diff --git a/old_projects/nn/mnist_loader.py b/old_projects/nn/mnist_loader.py
index 74e6360f..f05bc29f 100644
--- a/old_projects/nn/mnist_loader.py
+++ b/old_projects/nn/mnist_loader.py
@@ -40,7 +40,11 @@ def load_data():
     below.
     """
     f = gzip.open('/Users/grant/cs/neural-networks-and-deep-learning/data/mnist.pkl.gz', 'rb')
-    training_data, validation_data, test_data = pickle.load(f)
+    u = pickle._Unpickler(f)
+    u.encoding = 'latin1'
+    # p = u.load()
+    # training_data, validation_data, test_data = pickle.load(f)
+    training_data, validation_data, test_data = u.load()
     f.close()
     return (training_data, validation_data, test_data)
 
diff --git a/old_projects/nn/network.py b/old_projects/nn/network.py
index b8386028..392ad01d 100644
--- a/old_projects/nn/network.py
+++ b/old_projects/nn/network.py
@@ -165,8 +165,8 @@ class Network(object):
         return sum(int(x == y) for (x, y) in test_results)
 
     def cost_derivative(self, output_activations, y):
-        """Return the vector of partial derivatives \partial C_x /
-        \partial a for the output activations."""
+        """Return the vector of partial derivatives \\partial C_x /
+        \\partial a for the output activations."""
         return (output_activations-y)
 
 #### Miscellaneous functions
@@ -195,8 +195,8 @@ def ReLU_prime(z):
     return (np.array(z) > 0).astype('int')
 
 def get_pretrained_network():
-    data_file = open(PRETRAINED_DATA_FILE)
-    weights, biases = pickle.load(data_file)
+    data_file = open(PRETRAINED_DATA_FILE, 'rb')
+    weights, biases = pickle.load(data_file, encoding='latin1')
     sizes = [w.shape[1] for w in weights]
     sizes.append(weights[-1].shape[0])
     network = Network(sizes)
@@ -275,13 +275,13 @@ def save_organized_images(n_images_per_number = 10):
         if len(image_map[value]) >= n_images_per_number:
             continue
         image_map[value].append(im)
-    data_file = open(IMAGE_MAP_DATA_FILE, mode = 'w')
+    data_file = open(IMAGE_MAP_DATA_FILE, mode = 'wb')
     pickle.dump(image_map, data_file)
     data_file.close()
 
 def get_organized_images():
     data_file = open(IMAGE_MAP_DATA_FILE, mode = 'r')
-    image_map = pickle.load(data_file)
+    image_map = pickle.load(data_file, encoding='latin1')
     data_file.close()
     return image_map
 
diff --git a/old_projects/nn/part1.py b/old_projects/nn/part1.py
index a1123bd9..00e0d5e3 100644
--- a/old_projects/nn/part1.py
+++ b/old_projects/nn/part1.py
@@ -144,10 +144,10 @@ class NetworkMobject(VGroup):
         if size > n_neurons:
             dots = TexMobject("\\vdots")
             dots.move_to(neurons)
-            VGroup(*neurons[:len(neurons)/2]).next_to(
+            VGroup(*neurons[:len(neurons) // 2]).next_to(
                 dots, UP, MED_SMALL_BUFF
             )
-            VGroup(*neurons[len(neurons)/2:]).next_to(
+            VGroup(*neurons[len(neurons) // 2:]).next_to(
                 dots, DOWN, MED_SMALL_BUFF
             )
             layer.dots = dots
diff --git a/old_projects/wcat.py b/old_projects/wcat.py
index d04ba6e5..30b670c9 100644
--- a/old_projects/wcat.py
+++ b/old_projects/wcat.py
@@ -453,7 +453,7 @@ class DefineInscribedSquareProblem(ClosedLoopScene):
         pi_loop.set_fill(opacity = 0)
         pi_loop.set_stroke(
             color = WHITE,
-            width = DEFAULT_POINT_THICKNESS
+            width = DEFAULT_STROKE_WIDTH
         )
         pi_loop.set_height(4)
         randy = Randolph()