Fixed randomness in tl.diffmap - compute_eigen (v0 argument)

scanpy/neighbors/__init__.py

@@ -937,6 +937,7 @@ def compute_eigen(
         n_comps: int = 15,
         sym: Optional[bool] = None,
         sort: Literal['decrease', 'increase'] = 'decrease',
+        random_state: AnyRandom = 0,
     ):
         """\
         Compute eigen decomposition of transition matrix.
@@ -950,6 +951,8 @@ def compute_eigen(
             Instead of computing the eigendecomposition of the assymetric
             transition matrix, computed the eigendecomposition of the symmetric
             Ktilde matrix.
+        random_state
+            A numpy random seed
 
         Returns
         -------
@@ -978,8 +981,14 @@ def compute_eigen(
             which = 'LM' if sort == 'decrease' else 'SM'
             # it pays off to increase the stability with a bit more precision
             matrix = matrix.astype(np.float64)
+
+            # Setting the random initial vector
+            random_state = check_random_state(random_state)
+            np.random.set_state(random_state.get_state())
+            v0 = np.random.randn((matrix.shape[0]))
+
             evals, evecs = scipy.sparse.linalg.eigsh(
-                matrix, k=n_comps, which=which, ncv=ncv
+                matrix, k=n_comps, which=which, ncv=ncv, v0=v0
             )
             evals, evecs = evals.astype(np.float32), evecs.astype(np.float32)
         if sort == 'decrease':

scanpy/tools/_diffmap.py

@@ -2,12 +2,14 @@
 from typing import Optional
 
 from ._dpt import _diffmap
+from .._utils import AnyRandom
 
 
 def diffmap(
     adata: AnnData,
     n_comps: int = 15,
     neighbors_key: Optional[str] = None,
+    random_state: AnyRandom = 0,
     copy: bool = False,
 ):
     """\
@@ -39,6 +41,8 @@ def diffmap(
         .obsp[.uns[neighbors_key]['connectivities_key']],
         .obsp[.uns[neighbors_key]['distances_key']] for connectivities and distances
         respectively.
+    random_state
+            A numpy random seed
     copy
         Return a copy instead of writing to adata.
 
@@ -70,5 +74,7 @@ def diffmap(
     if n_comps <= 2:
         raise ValueError('Provide any value greater than 2 for `n_comps`. ')
     adata = adata.copy() if copy else adata
-    _diffmap(adata, n_comps=n_comps, neighbors_key=neighbors_key)
+    _diffmap(
+        adata, n_comps=n_comps, neighbors_key=neighbors_key, random_state=random_state
+    )
     return adata if copy else None

scanpy/tools/_dpt.py

@@ -10,11 +10,11 @@
 from ..neighbors import Neighbors, OnFlySymMatrix
 
 
-def _diffmap(adata, n_comps=15, neighbors_key=None):
+def _diffmap(adata, n_comps=15, neighbors_key=None, random_state=0):
     start = logg.info(f'computing Diffusion Maps using n_comps={n_comps}(=n_dcs)')
     dpt = DPT(adata, neighbors_key=neighbors_key)
     dpt.compute_transitions()
-    dpt.compute_eigen(n_comps=n_comps)
+    dpt.compute_eigen(n_comps=n_comps, random_state=random_state)
     adata.obsm['X_diffmap'] = dpt.eigen_basis
     adata.uns['diffmap_evals'] = dpt.eigen_values
     logg.info(