From c8ae32b4e1920e70f420534ada179e989705735e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 29 Jan 2024 14:10:08 -0500
Subject: [PATCH] [pre-commit.ci] pre-commit autoupdate (#172)

---
 .pre-commit-config.yaml                             | 2 +-
 src/stream_mapper/pytorch/_connect/data.py          | 6 +++---
 src/stream_mapper/pytorch/builtin/_skewnorm.py      | 4 +---
 src/stream_mapper/pytorch/builtin/_truncskewnorm.py | 4 +---
 src/stream_mapper/pytorch/builtin/compat/nflow.py   | 8 +++++---
 5 files changed, 11 insertions(+), 13 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 2a6bcda..0b25236 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -39,7 +39,7 @@ repos:
           - --fix
 
   - repo: https://github.com/psf/black
-    rev: 23.12.1
+    rev: 24.1.1
     hooks:
       - id: black
         additional_dependencies: [toml]
diff --git a/src/stream_mapper/pytorch/_connect/data.py b/src/stream_mapper/pytorch/_connect/data.py
index f680b2c..5f2344a 100644
--- a/src/stream_mapper/pytorch/_connect/data.py
+++ b/src/stream_mapper/pytorch/_connect/data.py
@@ -58,6 +58,6 @@ def _from_ndarraytype_to_tensor(
         array.flags.writeable = True
         return replace(data, array=xp.asarray(array, **kwargs))
 
-    ASTYPE_REGISTRY[
-        (asdf.tags.core.ndarray.NDArrayType, xp.Tensor)
-    ] = _from_ndarraytype_to_tensor
+    ASTYPE_REGISTRY[(asdf.tags.core.ndarray.NDArrayType, xp.Tensor)] = (
+        _from_ndarraytype_to_tensor
+    )
diff --git a/src/stream_mapper/pytorch/builtin/_skewnorm.py b/src/stream_mapper/pytorch/builtin/_skewnorm.py
index b9a39f3..48d2d0d 100644
--- a/src/stream_mapper/pytorch/builtin/_skewnorm.py
+++ b/src/stream_mapper/pytorch/builtin/_skewnorm.py
@@ -87,9 +87,7 @@ def ln_likelihood(
             # TODO: I suspect there are better ways to write this
             sigma_o = data[cens].array[idx]
             sigma = self.xp.exp(ln_s)
-            skew = (
-                skew * sigma / self.xp.sqrt(sigma**2 + (1 + skew**2) * sigma_o**2)
-            )
+            skew = skew * sigma / self.xp.sqrt(sigma**2 + (1 + skew**2) * sigma_o**2)
             ln_s = self.xp.log(sigma**2 + sigma_o**2) / 2
 
         # Find where -inf
diff --git a/src/stream_mapper/pytorch/builtin/_truncskewnorm.py b/src/stream_mapper/pytorch/builtin/_truncskewnorm.py
index 46243a6..467583f 100644
--- a/src/stream_mapper/pytorch/builtin/_truncskewnorm.py
+++ b/src/stream_mapper/pytorch/builtin/_truncskewnorm.py
@@ -80,9 +80,7 @@ def ln_likelihood(
             # TODO: I suspect there are better ways to write this
             sigma_o = data[cens].array[idx]
             sigma = self.xp.exp(ln_s)
-            skew = (
-                skew * sigma / self.xp.sqrt(sigma**2 + (1 + skew**2) * sigma_o**2)
-            )
+            skew = skew * sigma / self.xp.sqrt(sigma**2 + (1 + skew**2) * sigma_o**2)
             ln_s = self.xp.log(sigma**2 + sigma_o**2) / 2
 
         # Find where -inf
diff --git a/src/stream_mapper/pytorch/builtin/compat/nflow.py b/src/stream_mapper/pytorch/builtin/compat/nflow.py
index 17b2eb8..c3b9e40 100644
--- a/src/stream_mapper/pytorch/builtin/compat/nflow.py
+++ b/src/stream_mapper/pytorch/builtin/compat/nflow.py
@@ -23,7 +23,9 @@ def _log_prob(self, data: Data[Array], idx: Array) -> Array:
         """Log-probability of the array."""
         return self.net.log_prob(
             inputs=data[self.coord_names].array[idx],
-            context=data[self.indep_coord_names].array[idx]
-            if self.indep_coord_names is not None
-            else None,
+            context=(
+                data[self.indep_coord_names].array[idx]
+                if self.indep_coord_names is not None
+                else None
+            ),
         )