diff --git a/stan/tests/test_stan_functions.py b/stan/tests/test_stan_functions.py
index 2faded6..23e051c 100644
--- a/stan/tests/test_stan_functions.py
+++ b/stan/tests/test_stan_functions.py
@@ -73,7 +73,8 @@ def assert_stan_function_allclose(
         raise RuntimeError(f"failed to compile model for {stan_function} at {line_info}") from ex
 
     try:
-        fit = model.sample(arg_values, fixed_param=True, iter_sampling=1, iter_warmup=1, sig_figs=9, chains=1)
+        fit = model.sample(arg_values, fixed_param=True, iter_sampling=1, iter_warmup=1, sig_figs=9,
+                           chains=1)
         success, = fit.stan_variable("success")
         if not success or np.isnan(success):
             console = pathlib.Path(fit.runset.stdout_files[0]).read_text()
diff --git a/torch/gptools/torch/fft/fft1.py b/torch/gptools/torch/fft/fft1.py
index 4fe22a2..6ff8966 100644
--- a/torch/gptools/torch/fft/fft1.py
+++ b/torch/gptools/torch/fft/fft1.py
@@ -1,4 +1,4 @@
-from gptools.util.fft import transform_rfft, transform_irfft, evaluate_rfft_log_abs_det_jacobian
+from gptools.util.fft import transform_rfft, transform_irfft, evaluate_rfft_log_abs_det_jac
 from gptools.util.fft.fft1 import _get_rfft_scale
 import torch as th
 from torch.distributions import constraints
@@ -44,7 +44,7 @@ def _inv_call(self, y: th.Tensor) -> th.Tensor:
         return transform_irfft(y, self.loc, rfft_scale=self.rfft_scale)
 
     def log_abs_det_jacobian(self, x: th.Tensor, y: th.Tensor) -> th.Tensor:
-        return evaluate_rfft_log_abs_det_jacobian(x.shape[-1], rfft_scale=self.rfft_scale)
+        return evaluate_rfft_log_abs_det_jac(x.shape[-1], rfft_scale=self.rfft_scale)
 
 
 class FourierGaussianProcess1D(th.distributions.TransformedDistribution):
diff --git a/torch/gptools/torch/fft/fft2.py b/torch/gptools/torch/fft/fft2.py
index 884d4ab..ee0e9d0 100644
--- a/torch/gptools/torch/fft/fft2.py
+++ b/torch/gptools/torch/fft/fft2.py
@@ -1,4 +1,4 @@
-from gptools.util.fft import transform_rfft2, transform_irfft2, evaluate_rfft2_log_abs_det_jacobian
+from gptools.util.fft import transform_rfft2, transform_irfft2, evaluate_rfft2_log_abs_det_jac
 from gptools.util.fft.fft2 import _get_rfft2_scale
 import torch as th
 from .. import OptionalTensor
@@ -45,7 +45,7 @@ def _inv_call(self, y: th.Tensor) -> th.Tensor:
         return transform_irfft2(y, self.loc, rfft2_scale=self.rfft2_scale)
 
     def log_abs_det_jacobian(self, x: th.Tensor, y: th.Tensor) -> th.Tensor:
-        return evaluate_rfft2_log_abs_det_jacobian(x.shape[-1], rfft2_scale=self.rfft2_scale)
+        return evaluate_rfft2_log_abs_det_jac(x.shape[-1], rfft2_scale=self.rfft2_scale)
 
 
 class FourierGaussianProcess2D(th.distributions.TransformedDistribution):