'wminkowski' metric not working - weight array not passing through properly to the distance function

Hi - I'm trying to use the weighted minkowski metric:

   clusterer = hdbscan.HDBSCAN(algorithm='best', alpha=1.0, approx_min_span_tree=True,
    gen_min_span_tree=False, leaf_size=40, 
    metric='wminkowski', min_cluster_size=20, min_samples=5, 
    core_dist_n_jobs=1, p=2,  w=[2, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.1, 0.1])

hdb_clusters = clusterer.fit(data)

Here is the error I get - it looks like the p and w arguments are not passing through all the way:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-174-0c6dd011773f> in <module>()
----> 1 hdb_clusters = clusterer.fit(data)

/usr/local/anaconda/lib/python3.5/site-packages/hdbscan/hdbscan_.py in fit(self, X, y)
    862          self._condensed_tree,
    863          self._single_linkage_tree,
--> 864          self._min_spanning_tree) = hdbscan(X, **kwargs)
    865 
    866         if self.prediction_data:

/usr/local/anaconda/lib/python3.5/site-packages/hdbscan/hdbscan_.py in hdbscan(X, min_cluster_size, min_samples, alpha, metric, p, leaf_size, algorithm, memory, approx_min_span_tree, gen_min_span_tree, core_dist_n_jobs, cluster_selection_method, allow_single_cluster, match_reference_implementation, **kwargs)
    604                                                approx_min_span_tree,
    605                                                gen_min_span_tree,
--> 606                                                core_dist_n_jobs, **kwargs)
    607 
    608     return _tree_to_labels(X,

/usr/local/anaconda/lib/python3.5/site-packages/sklearn/externals/joblib/memory.py in __call__(self, *args, **kwargs)
    281 
    282     def __call__(self, *args, **kwargs):
--> 283         return self.func(*args, **kwargs)
    284 
    285     def call_and_shelve(self, *args, **kwargs):

/usr/local/anaconda/lib/python3.5/site-packages/hdbscan/hdbscan_.py in _hdbscan_boruvka_balltree(X, min_samples, alpha, metric, p, leaf_size, approx_min_span_tree, gen_min_span_tree, core_dist_n_jobs, **kwargs)
    313         X = X.astype(np.float64)
    314 
--> 315     tree = BallTree(X, metric=metric, leaf_size=leaf_size, **kwargs)
    316     alg = BallTreeBoruvkaAlgorithm(tree, min_samples, metric=metric,
    317                                    leaf_size=leaf_size // 3,

sklearn/neighbors/binary_tree.pxi in sklearn.neighbors.ball_tree.BinaryTree.__init__ (sklearn/neighbors/ball_tree.c:9223)()

sklearn/neighbors/dist_metrics.pyx in sklearn.neighbors.dist_metrics.DistanceMetric.get_metric (sklearn/neighbors/dist_metrics.c:4824)()

sklearn/neighbors/dist_metrics.pyx in sklearn.neighbors.dist_metrics.WMinkowskiDistance.__init__ (sklearn/neighbors/dist_metrics.c:7811)()

TypeError: __init__() takes exactly 2 positional arguments (0 given)