MAINT: Update tests to ensure deprecated functions are unused (#302)

* MAINT: Use new support and remove discontinued functions

* MAINT: Bumpy minimum cogent3 version

Author: rmcar17

docs/quickstart/construct_ml_tree.md

@@ -22,7 +22,7 @@ log_likelihood = tree.params["lnL"]
 ### Ultrafast Bootstrap
 
 To perform ultrafast bootstrapping, the number of replicates can be specified. The number of replicates must be at least 1000.
-The support for each node in the tree object can be accessed from `#!py3 node.params["support"]`.
+The support for each node in the tree object can be accessed from `#!py3 node.support`.
 
 ```python
 from cogent3 import load_aligned_seqs

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "piqtree"
-dependencies = ["cogent3>=2025.7.10a1", "pyyaml", "requests"]
+dependencies = ["cogent3>=2025.7.10a8", "pyyaml", "requests"]
 requires-python = ">=3.11, <3.14"
 
 authors = [

tests/test_app/test_app.py

@@ -18,7 +18,7 @@ def test_piq_build_tree_support(four_otu: Alignment) -> None:
     app = get_app("piq_build_tree", model=make_model("JC"), bootstrap_reps=1000)
     got = app(four_otu)
     supports = [
-        node.params.get("support", None)
+        node.support
         for node in got.postorder()
         if not node.is_tip() and node.name != "root"
     ]

tests/test_iqtree/test_build_tree.py

@@ -118,7 +118,7 @@ def test_build_tree_bootstrapping(four_otu: Alignment) -> None:
     )
 
     supported_node = max(tree.children, key=lambda x: len(x.children))
-    assert "support" in supported_node.params
+    assert supported_node.support is not None
 
 
 @pytest.mark.parametrize(

tests/test_iqtree/test_fit_tree.py

@@ -54,8 +54,8 @@ def check_rate_parameters(got: PhyloNode, expected: PhyloNode) -> None:
 
 
 def check_branch_lengths(got: PhyloNode, expected: PhyloNode) -> None:
-    got = got.get_distances()
-    expected = expected.get_distances()
+    got = got.tip_to_tip_distances()
+    expected = expected.tip_to_tip_distances()
     # make sure the distance matrices have the same name order
     # so we can just compare entire numpy arrays
     expected = expected.take_dists(got.names)