From fb280b93ec1c41a3428e566f39e8b2110d261c7d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 27 Jan 2025 12:18:44 +0000
Subject: [PATCH] style: pre-commit fixes

---
 tests/unit/test_likelihoods.py | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/tests/unit/test_likelihoods.py b/tests/unit/test_likelihoods.py
index 12af5a74..8aa9e66c 100644
--- a/tests/unit/test_likelihoods.py
+++ b/tests/unit/test_likelihoods.py
@@ -215,25 +215,27 @@ def test_scaled_log_likelihood(self, one_signal_problem):
 
     @pytest.mark.unit
     def test_observed_fisher(self, one_signal_problem):
-        likelihood = pybop.GaussianLogLikelihoodKnownSigma(one_signal_problem, sigma0=0.1)
-        
+        likelihood = pybop.GaussianLogLikelihoodKnownSigma(
+            one_signal_problem, sigma0=0.1
+        )
+
         # Create mock data and sensitivities
         y = {"Voltage [V]": np.array([3.7, 3.6, 3.5])}
         dy = np.array([[0.1, 0.2, 0.3]])
-        
+
         # Compute observed Fisher Information Matrix
         fim = likelihood.observed_fisher(y, dy)
-        
+
         # Check that FIM is a 1x1 array (since we have one parameter)
         assert fim.shape == (1, 1)
-        
+
         # Check that FIM is positive (for a single parameter, it should be)
         assert fim[0, 0] > 0
-        
+
         # Check that FIM is computed correctly
         expected_fim = np.sum(np.square(dy)) / likelihood.n_data
         np.testing.assert_allclose(fim, expected_fim, rtol=1e-7)
-        
+
         # Test without providing dy
         fim_without_dy = likelihood.observed_fisher(y)
         assert fim_without_dy.shape == (1, 1)