Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/graph/tests/test_flexible.py

@@ -0,0 +1,53 @@
+import numpy as np
+import skimage.graph.mcp as mcp
+
+from skimage._shared.testing import assert_array_equal
+
+
+a = np.ones((8, 8), dtype=np.float32)
+a[1::2] *= 2.0
+
+
+class FlexibleMCP(mcp.MCP_Flexible):
+    """ Simple MCP subclass that allows the front to travel 
+    a certain distance from the seed point, and uses a constant
+    cost factor that is independent of the cost array.
+    """
+    
+    def _reset(self):
+        mcp.MCP_Flexible._reset(self)
+        self._distance = np.zeros((8, 8), dtype=np.float32).ravel()
+    
+    def goal_reached(self, index, cumcost):
+        if self._distance[index] > 4:
+            return 2
+        else:
+            return 0
+    
+    def travel_cost(self, index, new_index, offset_length):
+        return 1.0  # fixed cost
+    
+    def examine_neighbor(self, index, new_index, offset_length):
+        pass  # We do not test this
+        
+    def update_node(self, index, new_index, offset_length):
+        self._distance[new_index] = self._distance[index] + 1
+
+
+def test_flexible():
+    # Create MCP and do a traceback
+    mcp = FlexibleMCP(a)
+    costs, traceback = mcp.find_costs([(0, 0)])
+    
+    # Check that inner part is correct. This basically
+    # tests whether travel_cost works.
+    assert_array_equal(costs[:4, :4], [[1, 2, 3, 4],
+                                       [2, 2, 3, 4],
+                                       [3, 3, 3, 4],
+                                       [4, 4, 4, 4]])
+    
+    # Test that the algorithm stopped at the right distance.
+    # Note that some of the costs are filled in but not yet frozen,
+    # so we take a bit of margin
+    assert np.all(costs[-2:, :] == np.inf)
+    assert np.all(costs[:, -2:] == np.inf)