update-mcp: added tests for newly added features.

Also fix in existing test related to how the traceback arrays is initialized:
first it was initialized with all -1, now with -2, and -1 at the seed points.

skimage/graph/tests/test_anisotropy.py

@@ -0,0 +1,53 @@
+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)
+
+
+horizontal_ramp = np.array( [[  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,],
+                            [  0.,   1.,   2.,   3.,   4.,  5.,  6.,  7.,]])
+
+vertical_ramp = np.array(  [[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,],
+                            [ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,],
+                            [ 2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,],
+                            [ 3.,  3.,  3.,  3.,  3.,  3.,  3.,  3.,],
+                            [ 4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,],
+                            [ 5.,  5.,  5.,  5.,  5.,  5.,  5.,  5.,],
+                            [ 6.,  6.,  6.,  6.,  6.,  6.,  6.,  6.,],
+                            [ 7.,  7.,  7.,  7.,  7.,  7.,  7.,  7.,]])
+
+
+def test_anisotropy():
+    
+    # Create seeds; vertical seeds create a horizonral ramp
+    seeds_for_horizontal = [(i,0) for i in range(8) ]
+    seeds_for_vertcal = [(0,i) for i in range(8) ]
+    
+    
+    for sy in range(1, 5):
+        for sx in range(1,5):
+            sampling = sy, sx
+        # Trace horizontally
+        m1 = mcp.MCP_Geometric(a, sampling=sampling, fully_connected=True)
+        costs1, traceback = m1.find_costs(seeds_for_horizontal)
+        # Trace vertically
+        m2 = mcp.MCP_Geometric(a, sampling=sampling, fully_connected=True)
+        costs2, traceback = m2.find_costs(seeds_for_vertcal)
+        
+        # Check
+        assert_array_equal(costs1, horizontal_ramp * sx)
+        assert_array_equal(costs2, vertical_ramp * sy)
+
+
+if __name__ == "__main__":
+    np.testing.run_module_suite()

skimage/graph/tests/test_connect.py

@@ -0,0 +1,83 @@
+import skimage.graph.mcp as mcp
+# import stentseg.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)
+
+count = 0
+class MCP(mcp.MCP_Connect):
+    
+    def _reset(self):
+        """ Reset the id map.
+        """
+        mcp.MCP_Connect._reset(self)
+        self._conn = {}
+        self._bestconn = {}
+    
+    
+    def create_connection(self, id1, id2, pos1, pos2, cost1, cost2):
+        # Process data
+        hash = min(id1, id2), max(id1, id2)
+        val = min(pos1, pos2), max(pos1, pos2)
+        cost = min(cost1, cost2)
+        # Add to total list 
+        self._conn.setdefault(hash, []).append(val)
+        # Keep track of connection with lowest cost
+        curcost = self._bestconn.get(hash, (np.inf,))[0]
+        if cost < curcost:
+            self._bestconn[hash] = (cost,) + val
+
+
+def test_connections():
+    
+    # Create MCP object with three seed points
+    mcp = MCP(a)
+    costs, traceback = mcp.find_costs([ (1,1), (7,7), (1,7) ])
+    
+    # Test that all three seed points are connected
+    connections = set(mcp._conn.keys())
+    assert (0, 1) in connections
+    assert (1, 2) in connections
+    assert (0, 2) in connections
+    
+    # Test that any two neighbors have only been connected once
+    for position_tuples in mcp._conn.values():
+        n1 = len(position_tuples)
+        n2 = len(set(position_tuples))
+        assert n1 == n2
+    
+    # For seed 0 and 1
+    cost, pos1, pos2 = mcp._bestconn[(0,1)]
+    # Test meeting points
+    assert (pos1, pos2) == ( (3,3), (4,4) )
+    # Test the whole path
+    path = mcp.traceback(pos1) + list(reversed(mcp.traceback(pos2)))
+    assert_array_equal(path, 
+                    [(1, 1), (2, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7)])
+    
+    # For seed 1 and 2
+    cost, pos1, pos2 = mcp._bestconn[(1,2)]
+    # Test meeting points
+    assert (pos1, pos2) == ( (3,7), (4,7) )
+    # Test the whole path
+    path = mcp.traceback(pos1) + list(reversed(mcp.traceback(pos2)))
+    assert_array_equal(path, 
+                    [(1, 7), (2, 7), (3, 7), (4, 7), (5, 7), (6, 7), (7, 7)])
+    
+    # For seed 0 and 2
+    cost, pos1, pos2 = mcp._bestconn[(0,2)]
+    # Test meeting points
+    assert (pos1, pos2) == ( (1,3), (1,4) )
+    # Test the whole path
+    path = mcp.traceback(pos1) + list(reversed(mcp.traceback(pos2)))
+    assert_array_equal(path, 
+                    [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7)])
+
+
+if __name__ == "__main__":
+    np.testing.run_module_suite()

skimage/graph/tests/test_mcp.py

@@ -116,8 +116,8 @@ def test_offsets():
     m = mcp.MCP(a, offsets=offsets)
     costs, traceback = m.find_costs([(1, 6)])
     assert_array_equal(traceback,
-                       [[-1, -1, -1, -1, -1, -1, -1, -1],
-                        [-1, -1, -1, -1, -1, -1, -1, -1],
+                       [[-2, -2, -2, -2, -2, -2, -2, -2],
+                        [-2, -2, -2, -2, -2, -2, -1, -2],
                         [15, 14, 13, 12, 11, 10,  0,  1],
                         [10,  0,  1,  2,  3,  4,  5,  6],
                         [10,  0,  1,  2,  3,  4,  5,  6],
@@ -151,5 +151,6 @@ def _test_random(shape):
     return a, costs, offsets
 
 
+
 if __name__ == "__main__":
     np.testing.run_module_suite()