project Refactor, CNN Classifier Basics

lib/objects/map.py

@@ -12,6 +12,7 @@ import networkx as nx
 from matplotlib import pyplot as plt
 
 from lib.objects.trajectory import Trajectory
+import lib.variables as V
 
 
 class Map(object):
@@ -145,14 +146,14 @@ class Map(object):
 
         img = Image.new('L', (self.height, self.width), 0)
         draw = ImageDraw.Draw(img)
-        draw.polygon(polyline, outline=1, fill=1)
+        draw.polygon(polyline, outline=self.white, fill=self.white)
 
-        a = (np.where(np.asarray(img) == self.white, 1, 0) * np.where(self.as_2d_array == self.white, 1, 0)).sum()
+        a = (np.where(np.asarray(img) == self.white, 1, 0) * np.where(self.as_2d_array == self.black, 1, 0)).sum()
 
         if a:
-            return False  # Non-Homotoph
+            return V.ALTERNATIVE  # Non-Homotoph
         else:
-            return True  # Homotoph
+            return V.HOMOTOPIC  # Homotoph
 
     def draw(self):
         fig, ax = plt.gcf(), plt.gca()

lib/objects/trajectory.py

@@ -1,78 +1,80 @@
-from math import atan2
-from typing import List, Tuple, Union
-
-from matplotlib import pyplot as plt
-from lib import variables as V
-
-import numpy as np
-
-class Trajectory(object):
-
-    @property
-    def vertices(self):
-        return self._vertices
-
-    @property
-    def xy_vertices(self):
-        return [(x, y) for _, y, x in self._vertices]
-
-    @property
-    def endpoints(self):
-        return self.start, self.dest
-
-    @property
-    def start(self):
-        return self._vertices[0]
-
-    @property
-    def dest(self):
-        return self._vertices[-1]
-
-    @property
-    def xs(self):
-        return [x[2] for x in self._vertices]
-
-    @property
-    def ys(self):
-        return [x[1] for x in self._vertices]
-
-    @property
-    def as_paired_list(self):
-        return list(zip(self._vertices[:-1], self._vertices[1:]))
-
-    @property
-    def np_vertices(self):
-        return [np.array(vertice) for vertice in self._vertices]
-
-    def __init__(self, vertices: Union[List[Tuple[int]], None] = None):
-        assert any((isinstance(vertices, list), vertices is None))
-        if vertices is not None:
-            self._vertices = vertices
-        pass
-
-    def is_equal_to(self, other_trajectory):
-        # ToDo: do further equality Checks here
-        return self._vertices == other_trajectory.vertices
-
-    def draw(self, highlights=True, label=None, **kwargs):
-        if label is not None:
-            kwargs.update(color='red' if label == V.HOMOTOPIC else 'green',
-                          label='Homotopic' if label == V.HOMOTOPIC else 'Alternative')
-        if highlights:
-            kwargs.update(marker='o')
-        fig, ax = plt.gcf(), plt.gca()
-        img = plt.plot(self.xs, self.ys, **kwargs)
-        return dict(img=img, fig=fig, ax=ax)
-
-    def min_vertices(self, vertices):
-        vertices, last_angle = [self.start], 0
-        for (x1, y1), (x2, y2) in self.as_paired_list:
-            current_angle = atan2(x1-x2, y1-y2)
-            if current_angle != last_angle:
-                vertices.append((x2, y2))
-                last_angle = current_angle
-            else:
-                continue
-        if vertices[-1] != self.dest:
-            vertices.append(self.dest)
-        return self.__class__(vertices=vertices)
+from math import atan2
+from typing import List, Tuple, Union
+
+from matplotlib import pyplot as plt
+from lib import variables as V
+
+import numpy as np
+
+
+class Trajectory(object):
+
+    @property
+    def vertices(self):
+        return self._vertices
+
+    @property
+    def xy_vertices(self):
+        return [(x, y) for _, y, x in self._vertices]
+
+    @property
+    def endpoints(self):
+        return self.start, self.dest
+
+    @property
+    def start(self):
+        return self._vertices[0]
+
+    @property
+    def dest(self):
+        return self._vertices[-1]
+
+    @property
+    def xs(self):
+        return [x[2] for x in self._vertices]
+
+    @property
+    def ys(self):
+        return [x[1] for x in self._vertices]
+
+    @property
+    def as_paired_list(self):
+        return list(zip(self._vertices[:-1], self._vertices[1:]))
+
+    @property
+    def np_vertices(self):
+        return [np.array(vertice) for vertice in self._vertices]
+
+    def __init__(self, vertices: Union[List[Tuple[int]], None] = None):
+        assert any((isinstance(vertices, list), vertices is None))
+        if vertices is not None:
+            self._vertices = vertices
+        pass
+
+    def is_equal_to(self, other_trajectory):
+        # ToDo: do further equality Checks here
+        return self._vertices == other_trajectory.vertices
+
+    def draw(self, highlights=True, label=None, **kwargs):
+        if label is not None:
+            kwargs.update(color='red' if label == V.HOMOTOPIC else 'green',
+                          label='Homotopic' if label == V.HOMOTOPIC else 'Alternative',
+                          lw=1)
+        if highlights:
+            kwargs.update(marker='o')
+        fig, ax = plt.gcf(), plt.gca()
+        img = plt.plot(self.xs, self.ys, **kwargs)
+        return dict(img=img, fig=fig, ax=ax)
+
+    def min_vertices(self, vertices):
+        vertices, last_angle = [self.start], 0
+        for (x1, y1), (x2, y2) in self.as_paired_list:
+            current_angle = atan2(x1-x2, y1-y2)
+            if current_angle != last_angle:
+                vertices.append((x2, y2))
+                last_angle = current_angle
+            else:
+                continue
+        if vertices[-1] != self.dest:
+            vertices.append(self.dest)
+        return self.__class__(vertices=vertices)