train running

lib/objects/map.py

@@ -1,4 +1,5 @@
 import shelve
+from collections import UserDict
 from pathlib import Path
 
 import copy
@@ -69,7 +70,7 @@ class Map(object):
 
         # Check pixels for their color (determine if walkable)
         for idx, value in np.ndenumerate(self.map_array):
-            if value == self.white:
+            if value != self.black:
                 # IF walkable, add node
                 graph.add_node(idx, count=0)
                 # Fully connect to all surrounding neighbors
@@ -90,6 +91,7 @@ class Map(object):
             if image.mode != 'L':
                 image = image.convert('L')
             map_array = np.expand_dims(np.array(image), axis=0)
+            map_array = np.where(np.asarray(map_array) == cls.white, 1, 0)
         if embedding_size:
             assert isinstance(embedding_size, tuple), f'embedding_size was of type: {type(embedding_size)}'
             embedding = np.zeros(embedding_size)
@@ -147,9 +149,9 @@ class Map(object):
         img = Image.new('L', (self.height, self.width), 0)
         draw = ImageDraw.Draw(img)
 
-        draw.polygon(polyline, outline=self.white, fill=self.white)
+        draw.polygon(polyline, outline=1, fill=1)
 
-        a = (np.where(np.asarray(img) == self.white, 1, 0) * np.where(self.as_2d_array == self.black, 1, 0)).sum()
+        a = (np.asarray(img) * np.where(self.as_2d_array == self.black, 1, 0)).sum()
 
         if a:
             return V.ALTERNATIVE  # Non-Homotoph
@@ -165,32 +167,25 @@ class Map(object):
         return dict(img=img, fig=fig, ax=ax)
 
 
-class MapStorage(object):
+class MapStorage(UserDict):
 
     @property
-    def keys(self):
-        return list(self.data.keys())
+    def keys_list(self):
+        return list(super(MapStorage, self).keys())
 
-    def __init__(self, map_root, load_all=False):
-        self.data = dict()
+    def __init__(self, map_root, *args, **kwargs):
+        super(MapStorage, self).__init__(*args, **kwargs)
         self.map_root = Path(map_root)
-        if load_all:
-            for map_file in self.map_root.glob('*.bmp'):
-                _ = self[map_file.name]
-
-    def __getitem__(self, item):
-        if item in self.data.keys():
-            return self.data.get(item)
-        else:
-            current_map = Map().from_image(self.map_root / item)
-            self.data.__setitem__(item, np.asarray(current_map))
-        return self[item]
-
-
-
-
-
-
-
-
+        map_files = list(self.map_root.glob('*.bmp'))
+        self.max_map_size = (1, ) + tuple(
+            reversed(
+                tuple(
+                    map(
+                        max, *[Image.open(map_file).size for map_file in map_files])
+                )
+            )
+        )
 
+        for map_file in map_files:
+            current_map = Map().from_image(map_file, embedding_size=self.max_map_size)
+            self.__setitem__(map_file.name, current_map)

lib/objects/trajectory.py

@@ -41,6 +41,12 @@ class Trajectory(object):
     def as_paired_list(self):
         return list(zip(self._vertices[:-1], self._vertices[1:]))
 
+    def draw_in_array(self, shape):
+        trajectory_space = np.zeros(shape)
+        for index in self.vertices:
+            trajectory_space[index] = 1
+        return trajectory_space
+
     @property
     def np_vertices(self):
         return [np.array(vertice) for vertice in self._vertices]