Add OptimalK init config validation

Also fix setup deps

gap_statistic/optimalK.py

@@ -50,6 +50,11 @@ def __init__(
         :param clusterer:
         :param clusterer_kwargs:
         """
+        if clusterer is not None and parallel_backend == "rust":
+            raise ValueError(
+                "Cannot use 'rust' backend with a user defined clustering function, only KMeans"
+                " is supported on the rust implementation"
+            )
         self.parallel_backend = (
             parallel_backend
             if parallel_backend in ["joblib", "multiprocessing", "rust"]

tests/test_optimalK.py

@@ -3,11 +3,19 @@
 
 import numpy as np
 from sklearn.datasets.samples_generator import make_blobs
-from sklearn.cluster import SpectralClustering, KMeans, MeanShift
+from sklearn.cluster import KMeans, MeanShift
 
 from gap_statistic import OptimalK
 
 
+def test_bad_init_config():
+    """
+    Cannot define own clustering function and try to use Rust backend
+    """
+    with pytest.raises(ValueError):
+        OptimalK(parallel_backend="rust", clusterer=lambda x, k: print("just testing"))
+
+
 @pytest.mark.parametrize("ClusterModel", [KMeans, MeanShift])
 def test_alternative_clusting_method(ClusterModel):
     """