Remove edge_diffs

python/tests/test_haplotype_matching.py

@@ -32,6 +32,7 @@
 
 import _tskit
 import tskit
+from tests import tsutil
 
 MISSING = -1
 
@@ -112,8 +113,8 @@ def __init__(
         self.N = np.zeros(ts.num_nodes, dtype=int)
         # Efficiently compute the allelic state at a site
         self.allelic_state = np.zeros(ts.num_nodes, dtype=int) - 1
-        # Diffs so we can can update T and T_index between trees.
-        self.edge_diffs = self.ts.edge_diffs()
+        # TreePosition so we can can update T and T_index between trees.
+        self.tree_pos = tsutil.TreePosition(ts)
         self.parent = np.zeros(self.ts.num_nodes, dtype=int) - 1
         self.tree = tskit.Tree(self.ts)
         self.output = None
@@ -239,9 +240,12 @@ def update_tree(self):
         parent = self.parent
         T_index = self.T_index
         T = self.T
-        _, edges_out, edges_in = next(self.edge_diffs)
+        self.tree_pos.next()
+        assert self.tree_pos.index == self.tree.index
 
-        for edge in edges_out:
+        for j in range(self.tree_pos.out_range.start, self.tree_pos.out_range.stop):
+            e = self.tree_pos.out_range.order[j]
+            edge = self.ts.edge(e)
             u = edge.child
             if T_index[u] == -1:
                 # Make sure the subtree we're detaching has an T_index-value at the root.
@@ -254,7 +258,9 @@ def update_tree(self):
                 )
             parent[edge.child] = -1
 
-        for edge in edges_in:
+        for j in range(self.tree_pos.in_range.start, self.tree_pos.in_range.stop):
+            e = self.tree_pos.in_range.order[j]
+            edge = self.ts.edge(e)
             parent[edge.child] = edge.parent
             u = edge.parent
             if parent[edge.parent] == -1:
@@ -776,12 +782,10 @@ def ls_backward_tree_mirrored(
     return ba.run(h)
 
 
-def ls_backward_tree(
-    h, ts_mirror, rho, mu, normalisation_factor, precision=30, alleles=None
-):
-    alleles, n_alleles = get_site_alleles(ts_mirror, h, alleles)
+def ls_backward_tree(h, ts, rho, mu, normalisation_factor, precision=30, alleles=None):
+    alleles, n_alleles = get_site_alleles(ts, h, alleles)
     ba = BackwardAlgorithm(
-        ts_mirror,
+        ts,
         rho,
         mu,
         alleles,