From f3dbe5d9329547b03256fe824a541c8a89123c3b Mon Sep 17 00:00:00 2001
From: Ben Mares <services-git-throwaway1@tensorial.com>
Date: Mon, 26 Feb 2024 18:32:12 +0100
Subject: [PATCH 1/2] pre-commit autoupdate

---
 .pre-commit-config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index cb256a7d1..fea90ce6b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -3,11 +3,11 @@ ci:
 
 repos:
 - repo: https://github.com/psf/black
-  rev: 23.7.0
+  rev: 24.2.0
   hooks:
     - id: black-jupyter
 - repo: https://github.com/nbQA-dev/nbQA
-  rev: 1.7.0
+  rev: 1.7.1
   hooks:
     - id: nbqa-isort
       additional_dependencies: [isort==5.6.4]

From 9d13e84d1810d0811d58e3f172764c4f0e579140 Mon Sep 17 00:00:00 2001
From: Ben Mares <services-git-throwaway1@tensorial.com>
Date: Mon, 26 Feb 2024 18:47:57 +0100
Subject: [PATCH 2/2] Autoformatting

---
 examples/howto/blackbox_external_likelihood_numpy.ipynb   | 2 --
 examples/howto/blackbox_external_likelihood_numpy.myst.md | 2 --
 examples/ode_models/ODE_with_manual_gradients.ipynb       | 6 +++---
 examples/ode_models/ODE_with_manual_gradients.myst.md     | 6 +++---
 examples/samplers/samplers_mvnormal.py                    | 1 -
 scripts/rerun.py                                          | 1 +
 sphinxext/thumbnail_extractor.py                          | 1 +
 7 files changed, 8 insertions(+), 11 deletions(-)

diff --git a/examples/howto/blackbox_external_likelihood_numpy.ipynb b/examples/howto/blackbox_external_likelihood_numpy.ipynb
index 7499d002e..e48339344 100644
--- a/examples/howto/blackbox_external_likelihood_numpy.ipynb
+++ b/examples/howto/blackbox_external_likelihood_numpy.ipynb
@@ -164,7 +164,6 @@
    "source": [
     "# define a pytensor Op for our likelihood function\n",
     "class LogLike(pt.Op):\n",
-    "\n",
     "    \"\"\"\n",
     "    Specify what type of object will be passed and returned to the Op when it is\n",
     "    called. In our case we will be passing it a vector of values (the parameters\n",
@@ -446,7 +445,6 @@
     "\n",
     "\n",
     "class LogLikeGrad(pt.Op):\n",
-    "\n",
     "    \"\"\"\n",
     "    This Op will be called with a vector of values and also return a vector of\n",
     "    values - the gradients in each dimension.\n",
diff --git a/examples/howto/blackbox_external_likelihood_numpy.myst.md b/examples/howto/blackbox_external_likelihood_numpy.myst.md
index 8d63f61d2..dad89f5d9 100644
--- a/examples/howto/blackbox_external_likelihood_numpy.myst.md
+++ b/examples/howto/blackbox_external_likelihood_numpy.myst.md
@@ -119,7 +119,6 @@ So, what we actually need to do is create a {ref}`PyTensor Op <pytensor:creating
 ```{code-cell} ipython3
 # define a pytensor Op for our likelihood function
 class LogLike(pt.Op):
-
     """
     Specify what type of object will be passed and returned to the Op when it is
     called. In our case we will be passing it a vector of values (the parameters
@@ -294,7 +293,6 @@ class LogLikeWithGrad(pt.Op):
 
 
 class LogLikeGrad(pt.Op):
-
     """
     This Op will be called with a vector of values and also return a vector of
     values - the gradients in each dimension.
diff --git a/examples/ode_models/ODE_with_manual_gradients.ipynb b/examples/ode_models/ODE_with_manual_gradients.ipynb
index d3aa0a67f..d5062af4b 100644
--- a/examples/ode_models/ODE_with_manual_gradients.ipynb
+++ b/examples/ode_models/ODE_with_manual_gradients.ipynb
@@ -189,9 +189,9 @@
     "                ret = np.zeros(\n",
     "                    (self._n_states, self._n_odeparams + self._n_ivs)\n",
     "                )  # except the following entries\n",
-    "                ret[\n",
-    "                    0, 0\n",
-    "                ] = X  # \\frac{\\partial  [\\alpha X - \\beta XY]}{\\partial \\alpha}, and so on...\n",
+    "                ret[0, 0] = (\n",
+    "                    X  # \\frac{\\partial  [\\alpha X - \\beta XY]}{\\partial \\alpha}, and so on...\n",
+    "                )\n",
     "                ret[0, 1] = -X * Y\n",
     "                ret[1, 2] = -Y\n",
     "                ret[1, 3] = X * Y\n",
diff --git a/examples/ode_models/ODE_with_manual_gradients.myst.md b/examples/ode_models/ODE_with_manual_gradients.myst.md
index 18f93de97..5e1bf8d2d 100644
--- a/examples/ode_models/ODE_with_manual_gradients.myst.md
+++ b/examples/ode_models/ODE_with_manual_gradients.myst.md
@@ -157,9 +157,9 @@ class LotkaVolterraModel:
                 ret = np.zeros(
                     (self._n_states, self._n_odeparams + self._n_ivs)
                 )  # except the following entries
-                ret[
-                    0, 0
-                ] = X  # \frac{\partial  [\alpha X - \beta XY]}{\partial \alpha}, and so on...
+                ret[0, 0] = (
+                    X  # \frac{\partial  [\alpha X - \beta XY]}{\partial \alpha}, and so on...
+                )
                 ret[0, 1] = -X * Y
                 ret[1, 2] = -Y
                 ret[1, 3] = X * Y
diff --git a/examples/samplers/samplers_mvnormal.py b/examples/samplers/samplers_mvnormal.py
index b219356e1..726bc8785 100644
--- a/examples/samplers/samplers_mvnormal.py
+++ b/examples/samplers/samplers_mvnormal.py
@@ -6,7 +6,6 @@
 normalized effective sampling rates.
 """
 
-
 import time
 
 import arviz as az
diff --git a/scripts/rerun.py b/scripts/rerun.py
index 2c817f2e3..cd0362b77 100644
--- a/scripts/rerun.py
+++ b/scripts/rerun.py
@@ -14,6 +14,7 @@
 python scripts/rerun.py --fp_notebook=examples/case_studies/BEST.ipynb --commit_to=rerun-best --push_to=mine
 ```
 """
+
 import argparse
 import logging
 import pathlib
diff --git a/sphinxext/thumbnail_extractor.py b/sphinxext/thumbnail_extractor.py
index fb83b4413..cdef70ec3 100644
--- a/sphinxext/thumbnail_extractor.py
+++ b/sphinxext/thumbnail_extractor.py
@@ -3,6 +3,7 @@
 
 Modified from the seaborn project, which modified the mpld3 project.
 """
+
 import base64
 import json
 import os