Seed-related bug in numpy has been fixed

src/random.py

@@ -78,17 +78,10 @@ objects, generate new ones via :func:`spawn_sseq()`.
 import numpy as np
 
 
-# fix for numpy issue #16539
-def _fix_seed(seed):
-    if isinstance(seed, int):
-        return (seed, 0, 0, 0)
-    raise TypeError("random seed should have integer type")
-
-
 # Stack of SeedSequence objects. Will always start out with a well-defined
 # default. Users can change the "random seed" used by a calculation by pushing
 # a different SeedSequence before invoking any other nifty8.random calls
-_sseq = [np.random.SeedSequence(_fix_seed(42))]
+_sseq = [np.random.SeedSequence(42)]
 # Stack of random number generators associated with _sseq.
 _rng = [np.random.default_rng(_sseq[-1])]
 
@@ -204,7 +197,7 @@ def push_sseq_from_seed(seed):
     In all other situations, it is highly recommended to use the
     :class:`Context` class for managing the RNG state.
     """
-    _sseq.append(np.random.SeedSequence(_fix_seed(seed)))
+    _sseq.append(np.random.SeedSequence(seed))
     _rng.append(np.random.default_rng(_sseq[-1]))
 
 
@@ -284,7 +277,7 @@ class Context:
 
     def __init__(self, inp):
         if not isinstance(inp, np.random.SeedSequence):
-            inp = np.random.SeedSequence(_fix_seed(inp))
+            inp = np.random.SeedSequence(inp)
         self._sseq = inp
 
     def __enter__(self):