Debugging

lib/objects/map.py

@@ -1,7 +1,5 @@
 import shelve
 from pathlib import Path
-from collections import UserDict
-
 
 import copy
 from math import sqrt
@@ -46,6 +44,10 @@ class Map(object):
         return self.map_array
 
     def __init__(self, name='', array_like_map_representation=None):
+        if array_like_map_representation is not None:
+            if array_like_map_representation.ndim == 2:
+                array_like_map_representation = np.expand_dims(array_like_map_representation, axis=0)
+            assert array_like_map_representation.ndim == 3
         self.map_array: np.ndarray = array_like_map_representation
         self.name = name
         pass
@@ -63,22 +65,19 @@ class Map(object):
         # Check pixels for their color (determine if walkable)
         for idx, value in np.ndenumerate(self.map_array):
             if value == self.white:
-                try:
-                    y, x = idx
-                except ValueError:
-                    y, x, channels = idx
-                    idx = (y, x)
                 # IF walkable, add node
-                graph.add_node((y, x), count=0)
+                graph.add_node(idx, count=0)
                 # Fully connect to all surrounding neighbors
                 for n, (xdif, ydif, weight) in enumerate(neighbors):
                     # Differentiate between 8 and 4 neighbors
                     if not full_neighbors and n >= 2:
                         break
 
-                    query_node = (y + ydif, x + xdif)
+                    # ToDO: make this explicite and less ugly
+                    query_node = idx[:1] + (idx[1] + ydif,) + (idx[2] + xdif,)
                     if graph.has_node(query_node):
                         graph.add_edge(idx, query_node, weight=weight)
+
         return graph
 
     @classmethod
@@ -87,7 +86,7 @@ class Map(object):
             # Turn the image to single Channel Greyscale
             if image.mode != 'L':
                 image = image.convert('L')
-            map_array = np.array(image)
+            map_array = np.expand_dims(np.array(image), axis=0)
             return cls(name=imagepath.name, array_like_map_representation=map_array)
 
     def simple_trajectory_between(self, start, dest):