BF: make_cost_thresh_lookup has correct order of costs and associated thresholds

Author: CindeeM

brainx/tests/test_util.py

@@ -38,7 +38,19 @@ def test_all_positive():
     jnk = jnk - 0.5
     npt.assert_equal(util.all_positive(jnk), False) 
 
-    
+def test_make_cost_thresh_lookup():
+    adj_mat = np.zeros((10,10))
+    ind = np.triu_indices(10,1)
+    thresholds = np.linspace(.1, .8, 45)
+    adj_mat[ind] = thresholds
+    lookup = util.make_cost_thresh_lookup(adj_mat)
+
+    npt.assert_equal(sorted(thresholds, reverse=True), lookup[0,:])
+    npt.assert_equal(lookup[1,0] < lookup[1,-1], True) 
+    # costs in ascending order
+    ## last vecore is same as second vector rounded to 2 decimals
+    npt.assert_almost_equal(lookup[1], lookup[2], decimal=2)
+
 def test_cost_size():
     n_nodes = 5
     npt.assert_warns(DeprecationWarning, util.cost_size, n_nodes)

brainx/util.py

@@ -130,18 +130,18 @@ def make_cost_thresh_lookup(adjacency_matrix):
     -------
     lookup : numpy array
         3 X number_of_edges, numpy array
-        row 0 is sorted thresholds
-        row 1 is cost at each threshold
+        row 0 is sorted thresholds (largest -> smallest)
+        row 1 is cost at each threshold (smallest -> largest)
         row 2 is costs rounded to one decimal point
     """
 
     ind = np.triu_indices_from(adjacency_matrix, k = 1)
     edges = adjacency_matrix[ind]
     nedges = edges.shape[0]
     lookup = np.zeros((3, nedges))
-    lookup[0,:] = sorted(edges)
+    lookup[0,:] = sorted(edges, reverse = True)
     lookup[1,:] = np.arange(nedges) / float(nedges)
-    lookup[2,:] = np.round(lookup[1,:], decimals = 1)
+    lookup[2,:] = np.round(lookup[1,:], decimals = 2)
     return lookup
 
 def cost_size(nnodes):