Fixup: Use markers in clustering

vamb/cluster.py

@@ -20,7 +20,7 @@
 from math import ceil as _ceil
 from torch.functional import Tensor as _Tensor
 import vamb.vambtools as _vambtools
-from vamb import markers as _markers
+from vamb.parsemarkers import Markers
 from typing import Optional
 from collections.abc import Sequence, Iterable
 
@@ -172,7 +172,7 @@ def __str__(self) -> str:
 """
 
     def _check_params(
-        self, matrix: _np.ndarray, markers: _markers.Markers, maxsteps: int, windowsize: int, minsuccesses: int
+        self, matrix: _np.ndarray, markers: Markers, maxsteps: int, windowsize: int, minsuccesses: int
     ) -> None:
         """Checks matrix, and maxsteps."""
 
@@ -211,7 +211,7 @@ def _init_histogram_kept_mask(self, N: int) -> tuple[_Tensor, _Tensor]:
     def __init__(
         self,
         matrix: _np.ndarray,
-        markers: _markers.Markers,
+        markers: Markers,
         maxsteps: int = 25,
         windowsize: int = 200,
         minsuccesses: int = 20,
@@ -472,7 +472,7 @@ def _find_threshold(
 
 # NB: These points here MUST be the original indices of the contigs, NOT
 # the re-ordered points which the clusterer operates on!!
-def calc_marker_score(points: _Tensor, markers: _markers.Markers) -> float:
+def calc_marker_score(points: _Tensor, markers: Markers) -> float:
     n_markers = markers.n_markers
     counts = _np.zeros(n_markers, dtype=_np.uint32)
     for point in points: