update-mcp: add tests for MCP_Flexible

skimage/graph/tests/test_flexible.py

@@ -0,0 +1,61 @@
+import skimage.graph.mcp as mcp
+from numpy.testing import (assert_array_equal,
+                           assert_almost_equal,
+                           )
+                           
+import numpy as np
+
+a = np.ones((8, 8), dtype=np.float32)
+a[1::2] *= 2.0
+
+
+class TestFlexibleMCP(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 independant 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 = TestFlexibleMCP(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 )
+    
+    #print(costs)
+
+
+if __name__ == "__main__":
+    np.testing.run_module_suite()