fix: restore HRP optimization with current SciPy

pypfopt/hierarchical_portfolio.py

@@ -176,9 +176,6 @@ def optimize(self, linkage_method="single"):
         OrderedDict
             weights for the HRP portfolio
         """
-        if linkage_method not in sch._LINKAGE_METHODS:
-            raise ValueError("linkage_method must be one recognised by scipy")
-
         if self.returns is None:
             cov = self.cov_matrix
             corr = cov_to_corr(self.cov_matrix).round(6)
@@ -192,6 +189,7 @@ def optimize(self, linkage_method="single"):
         matrix = np.sqrt(np.clip((1.0 - corr) / 2.0, a_min=0.0, a_max=1.0))
         dist = ssd.squareform(matrix, checks=False)
 
+        # Let the public API validate methods; SciPy's private registry can change.
         self.clusters = sch.linkage(dist, linkage_method)
         sort_ix = HRPOpt._get_quasi_diag(self.clusters)
         ordered_tickers = corr.index[sort_ix].tolist()

tests/test_hrp.py

@@ -6,6 +6,17 @@
 from tests.utilities_for_tests import get_data, resource
 
 
+@pytest.mark.parametrize(
+    "method", ["single", "complete", "average", "weighted", "centroid", "median", "ward"]
+)
+def test_documented_linkage_methods(method):
+    cov = pd.DataFrame(np.eye(3), index=list("ABC"), columns=list("ABC"))
+    weights = HRPOpt(cov_matrix=cov).optimize(linkage_method=method)
+    assert set(weights) == set("ABC")
+    assert sum(weights.values()) == pytest.approx(1)
+    assert all(weight > 0 for weight in weights.values())
+
+
 def test_hrp_errors():
     with pytest.raises(ValueError):
         hrp = HRPOpt()