Update release

ci/tests/test_scgpt/test_binning.py

@@ -38,7 +38,7 @@ def test_digitize_identical_bins():
     x = np.array([1, 2, 3, 4, 5])
     bins = np.array([2, 2, 4, 4])
     result = _digitize(x, bins)
-    expected = np.array([0, 1, 2, 3, 4])
+    expected = np.array([0, 2, 2, 3, 4])
     assert np.array_equal(result, expected)
 
 
@@ -51,7 +51,7 @@ def test_digitize_identical_bins():
             np.array([1, 1, 1, 2, 2, 2, 3, 3, 4]),
         ),
         # distrubution of the bins depends on the distribution of the data
-        (np.array([1, 1, 1, 1, 1, 1, 1, 8, 9]), np.array([2, 1, 1, 2, 3, 3, 3, 3, 4])),
+        (np.array([1, 1, 1, 1, 1, 1, 1, 8, 9]), np.array([1, 2, 1, 1, 3, 1, 1, 3, 4])),
         (np.array([1, 2, 1, 1, 9, 6, 7, 8, 9]), np.array([1, 2, 1, 1, 4, 2, 2, 3, 4])),
     ),
 )

helical/models/scgpt/binning.py

@@ -32,7 +32,8 @@ def _digitize(x: np.ndarray, bins: np.ndarray, side="both") -> np.ndarray:
 
     right_digits = np.digitize(x, bins, right=True)
 
-    rands = np.random.rand(len(x))  # uniform random numbers
+    rng = np.random.default_rng(42)
+    rands = rng.random(len(x))
 
     digits = rands * (right_digits - left_digits) + left_digits
     digits = np.ceil(digits).astype(np.int64)

helical/models/scgpt/data_collator.py

@@ -163,7 +163,10 @@ def _sample(
 
         # keep the first n tokens unchanged
         _n = self.keep_first_n_tokens
-        indices = torch.randperm(len(genes) - _n, device=device)[: max_length - _n]
+        g = torch.Generator().manual_seed(0)
+        indices = torch.randperm(len(genes) - _n, device=device, generator=g)[
+            : max_length - _n
+        ]
         indices = torch.cat([torch.arange(_n), indices + _n], dim=0)
         return genes[indices], expressions[indices]
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "helical"
-version = "1.4.4"
+version = "1.4.5"
 authors = [
   { name="Helical Team", email="support@helical-ai.com" },
 ]