Up to InterpretFirstWeightMatrixRows in NN part 2

mobject/mobject.py

@@ -446,11 +446,14 @@ class Mobject(object):
         return self.color
     ##
 
-    def save_state(self):
+    def save_state(self, use_deepcopy = False):
         if hasattr(self, "saved_state"):
             #Prevent exponential growth of data
             self.saved_state = None
-        self.saved_state = self.copy()
+        if use_deepcopy:
+            self.saved_state = self.deepcopy()
+        else:
+            self.saved_state = self.copy()
         return self
 
     def restore(self):

nn/network.py

@@ -21,12 +21,12 @@ import cPickle
 from nn.mnist_loader import load_data_wrapper
 
 NN_DIRECTORY = os.path.dirname(os.path.realpath(__file__))
-# PRETRAINED_DATA_FILE = os.path.join(NN_DIRECTORY, "pretrained_weights_and_biases_36")
+# PRETRAINED_DATA_FILE = os.path.join(NN_DIRECTORY, "pretrained_weights_and_biases_80")
 # PRETRAINED_DATA_FILE = os.path.join(NN_DIRECTORY, "pretrained_weights_and_biases_ReLU")
 PRETRAINED_DATA_FILE = os.path.join(NN_DIRECTORY, "pretrained_weights_and_biases")
 IMAGE_MAP_DATA_FILE = os.path.join(NN_DIRECTORY, "image_map")
 # PRETRAINED_DATA_FILE = "/Users/grant/cs/manim/nn/pretrained_weights_and_biases_on_zero"
-# DEFAULT_LAYER_SIZES = [28**2, 36, 10]
+# DEFAULT_LAYER_SIZES = [28**2, 80, 10]
 DEFAULT_LAYER_SIZES = [28**2, 16, 16, 10]
 
 class Network(object):

nn/part1.py

@@ -196,19 +196,22 @@ class NetworkMobject(VGroup):
         for l1, l2 in zip(self.layers[:-1], self.layers[1:]):
             edge_group = VGroup()
             for n1, n2 in it.product(l1.neurons, l2.neurons):
-                edge = Line(
+                edge = self.get_edge(n1, n2)
-                    n1.get_center(),
-                    n2.get_center(),
-                    buff = self.neuron_radius,
-                    stroke_color = self.edge_color,
-                    stroke_width = self.edge_stroke_width,
-                )
                 edge_group.add(edge)
                 n1.edges_out.add(edge)
                 n2.edges_in.add(edge)
             self.edge_groups.add(edge_group)
         self.add_to_back(self.edge_groups)
 
+    def get_edge(self, neuron1, neuron2):
+        return Line(
+            neuron1.get_center(),
+            neuron2.get_center(),
+            buff = self.neuron_radius,
+            stroke_color = self.edge_color,
+            stroke_width = self.edge_stroke_width,
+        )
+
     def get_active_layer(self, layer_index, activation_vector):
         layer = self.layers[layer_index].deepcopy()
         n_neurons = len(layer.neurons)
@@ -2980,6 +2983,7 @@ class ContinualEdgeUpdate(ContinualAnimation):
         "max_stroke_width" : 3,
         "stroke_width_exp" : 7,
         "n_cycles" : 5,
+        "colors" : [GREEN, GREEN, GREEN, RED],
     }
     def __init__(self, network_mob, **kwargs):
         digest_config(self, kwargs)
@@ -2988,7 +2992,7 @@ class ContinualEdgeUpdate(ContinualAnimation):
         self.move_to_targets = []
         for edge in edges:
             edge.colors = [
-                random.choice([GREEN, GREEN, GREEN, RED])
+                random.choice(self.colors)
                 for x in range(n_cycles)
             ]
             msw = self.max_stroke_width

topics/geometry.py

@@ -242,9 +242,13 @@ class Arrow(Line):
         if len(args) == 1:
             args = (points[0]+UP+LEFT, points[0])
         Line.__init__(self, *args, **kwargs)
-        self.add_tip()
+        self.init_tip()
         if self.use_rectangular_stem and not hasattr(self, "rect"):
             self.add_rectangular_stem()
+        self.init_colors()
+
+    def init_tip(self):
+        self.tip = self.add_tip()
 
     def add_tip(self, add_at_end = True):
         tip = VMobject(
@@ -253,11 +257,11 @@ class Arrow(Line):
             fill_color = self.color,
             fill_opacity = 1,
             stroke_color = self.color,
+            stroke_width = 0,
         )
         self.set_tip_points(tip, add_at_end, preserve_normal = False)
-        self.tip = tip
+        self.add(tip)
-        self.add(self.tip)
+        return tip
-        self.init_colors()
 
     def add_rectangular_stem(self):
         self.rect = Rectangle(
@@ -283,6 +287,10 @@ class Arrow(Line):
             self.rectangular_stem_width,
             self.max_stem_width_to_tip_width_ratio*tip_base_width,
         )
+        if hasattr(self, "second_tip"):
+            start = center_of_mass(
+                self.second_tip.get_anchors()[1:]
+            )
         self.rect.set_points_as_corners([
             tip_base + perp_vect*width/2,
             start + perp_vect*width/2,
@@ -319,7 +327,6 @@ class Arrow(Line):
             if np.linalg.norm(v) == 0:
                 v[0] = 1
             v *= tip_length/np.linalg.norm(v)
-
         ratio = self.tip_width_to_length_ratio
         tip.set_points_as_corners([
             end_point, 
@@ -374,9 +381,9 @@ class Vector(Arrow):
         Arrow.__init__(self, ORIGIN, direction, **kwargs)
 
 class DoubleArrow(Arrow):
-    def __init__(self, *args, **kwargs):
+    def init_tip(self):
-        Arrow.__init__(self, *args, **kwargs)
+        self.tip = self.add_tip()
-        self.add_tip(add_at_end = False)
+        self.second_tip = self.add_tip(add_at_end = False)
 
 class CubicBezier(VMobject):
     def __init__(self, points, **kwargs):

topics/numerals.py

@@ -11,9 +11,9 @@ class DecimalNumber(VMobject):
         "num_decimal_points" : 2,
         "digit_to_digit_buff" : 0.05
     }
-    def __init__(self, float_num, **kwargs):
+    def __init__(self, number, **kwargs):
-        digest_config(self, kwargs)
+        digest_config(self, kwargs, locals())
-        num_string = '%.*f'%(self.num_decimal_points, float_num)
+        num_string = '%.*f'%(self.num_decimal_points, number)
         VMobject.__init__(self, *[
             TexMobject(char)
             for char in num_string
@@ -22,7 +22,7 @@ class DecimalNumber(VMobject):
             buff = self.digit_to_digit_buff,
             aligned_edge = DOWN
         )
-        if float_num < 0:
+        if number < 0:
             minus = self.submobjects[0]
             minus.next_to(
                 self.submobjects[1], LEFT,
@@ -65,9 +65,9 @@ class ChangingDecimal(Animation):
 
     def update_number(self, alpha):
         decimal = self.decimal_number
+        new_number = self.number_update_func(alpha)
         new_decimal = DecimalNumber(
-            self.number_update_func(alpha),
+            new_number, num_decimal_points = self.num_decimal_points
-            num_decimal_points = self.num_decimal_points
         )
         new_decimal.replace(decimal, dim_to_match = 1)
         new_decimal.highlight(decimal.get_color())
@@ -78,6 +78,7 @@ class ChangingDecimal(Animation):
         ]
         for sm1, sm2 in zip(*families):
             sm1.interpolate(sm1, sm2, 1)
+        self.mobject.number = new_number
 
     def update_position(self):
         if self.position_update_func is not None: