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28 changes: 21 additions & 7 deletions hdbscan/hdbscan_.py
Original file line number Diff line number Diff line change
Expand Up @@ -250,10 +250,12 @@ def _hdbscan_prims_kdtree(
# The Cython routines used require contiguous arrays
if not X.flags["C_CONTIGUOUS"]:
X = np.array(X, dtype=np.double, order="C")


if p!= 2 and 'p' not in kwargs:
kwargs['p'] = p

tree = KDTree(X, metric=metric, leaf_size=leaf_size, **kwargs)

# TO DO: Deal with p for minkowski appropriately

dist_metric = DistanceMetric.get_metric(metric, **kwargs)

# Get distance to kth nearest neighbour
Expand Down Expand Up @@ -292,7 +294,10 @@ def _hdbscan_prims_balltree(
# The Cython routines used require contiguous arrays
if not X.flags["C_CONTIGUOUS"]:
X = np.array(X, dtype=np.double, order="C")


if p!= 2 and 'p' not in kwargs:
kwargs['p'] = p

tree = BallTree(X, metric=metric, leaf_size=leaf_size, **kwargs)

dist_metric = DistanceMetric.get_metric(metric, **kwargs)
Expand Down Expand Up @@ -335,7 +340,10 @@ def _hdbscan_boruvka_kdtree(

if X.dtype != np.float64:
X = X.astype(np.float64)


if p!= 2 and 'p' not in kwargs:
kwargs['p'] = p

tree = KDTree(X, metric=metric, leaf_size=leaf_size, **kwargs)
alg = KDTreeBoruvkaAlgorithm(
tree,
Expand Down Expand Up @@ -379,7 +387,10 @@ def _hdbscan_boruvka_balltree(

if X.dtype != np.float64:
X = X.astype(np.float64)


if p!= 2 and 'p' not in kwargs:
kwargs['p'] = p

tree = BallTree(X, metric=metric, leaf_size=leaf_size, **kwargs)
alg = BallTreeBoruvkaAlgorithm(
tree,
Expand Down Expand Up @@ -1137,7 +1148,10 @@ def __init__(
self.prediction_data = prediction_data

self._metric_kwargs = kwargs


if p is not None:
self._metric_kwargs['p'] = p

self._condensed_tree = None
self._single_linkage_tree = None
self._min_spanning_tree = None
Expand Down