[pre-commit.ci] pre-commit autoupdate (#417)

* [pre-commit.ci] pre-commit autoupdate

updates:
- https://github.com/psf/black → https://github.com/psf/black-pre-commit-mirror
- [github.com/astral-sh/ruff-pre-commit: v0.13.1 → v0.14.0](astral-sh/ruff-pre-commit@v0.13.1...v0.14.0)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -1,13 +1,13 @@
 repos:
--   repo: https://github.com/psf/black
+-   repo: https://github.com/psf/black-pre-commit-mirror
     rev: 25.9.0
     hooks:
     - id: black
       additional_dependencies: ['click==8.0.4']
       args: # arguments to configure black
        - --line-length=89
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.13.1
+    rev: v0.14.0
     hooks:
     - id: ruff
       args: [ --fix, --exit-non-zero-on-fix]

pydeseq2/default_inference.py

@@ -113,7 +113,7 @@ def irls(  # noqa: D102
                 )
                 for i in range(counts.shape[1])
             )
-        res = zip(*res)
+        res = zip(*res, strict=False)
         MLE_lfcs_, mu_hat_, hat_diagonals_, converged_ = (np.array(m) for m in res)
 
         return (
@@ -156,7 +156,7 @@ def alpha_mle(  # noqa: D102
                 )
                 for i in range(counts.shape[1])
             )
-        res = zip(*res)
+        res = zip(*res, strict=False)
         dispersions_, l_bfgs_b_converged_ = (np.array(m) for m in res)
         return dispersions_, l_bfgs_b_converged_
 
@@ -192,7 +192,7 @@ def wald_test(  # noqa: D102
                 )
                 for i in range(num_genes)
             )
-        res = zip(*res)
+        res = zip(*res, strict=False)
         pvals, stats, se = (np.array(m) for m in res)
 
         return pvals, stats, se
@@ -259,6 +259,6 @@ def lfc_shrink_nbinom_glm(  # noqa: D102
                 )
                 for i in range(num_genes)
             )
-        res = zip(*res)
+        res = zip(*res, strict=False)
         lfcs, inv_hessians, l_bfgs_b_converged_ = (np.array(m) for m in res)
         return lfcs, inv_hessians, l_bfgs_b_converged_

pydeseq2/utils.py

@@ -1284,7 +1284,7 @@ def make_scatter(
     kwargs.setdefault("s", 0.6)
 
     # create scatter plot per trace
-    for disp, color in list(zip(disps, colors)):
+    for disp, color in list(zip(disps, colors, strict=False)):
         plt.scatter(x=x_val, y=disp, c=color, **kwargs)
 
     # label legend + axes