diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 7403759f..a93e7182 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -9,7 +9,7 @@ jobs:
     strategy:
       matrix:
         os: [ ubuntu-latest ]
-        python-version: [3.9, 3.11]
+        python-version: [3.12, 3.11]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -26,7 +26,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.9, 3.11]
+        python-version: [3.12, 3.11]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -42,7 +42,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.9, 3.11]
+        python-version: [3.12, 3.11]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -58,7 +58,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.11]
+        python-version: [3.12]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
diff --git a/noxfile.py b/noxfile.py
index 011e123e..25f5bf30 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -1,4 +1,5 @@
 """This module implements our CI function calls."""
+
 import nox
 
 
diff --git a/setup.cfg b/setup.cfg
index 6b6c4b3d..5b72a4ef 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -40,8 +40,8 @@ classifiers =
     Intended Audience :: Science/Research
     Operating System :: OS Independent
     Programming Language :: Python
-    Programming Language :: Python :: 3.9
     Programming Language :: Python :: 3.11
+    Programming Language :: Python :: 3.12
     Programming Language :: Python :: 3 :: Only
     Topic :: Scientific/Engineering :: Artificial Intelligence
 
@@ -56,7 +56,7 @@ install_requires =
     pytest
     nox
 
-python_requires = >=3.9
+python_requires = >=3.11
 
 packages = find:
 package_dir =
diff --git a/src/ptwt/__init__.py b/src/ptwt/__init__.py
index 03a6f6da..34808704 100644
--- a/src/ptwt/__init__.py
+++ b/src/ptwt/__init__.py
@@ -1,4 +1,5 @@
 """Differentiable and gpu enabled fast wavelet transforms in PyTorch."""
+
 from ._util import Wavelet
 from .continuous_transform import cwt
 from .conv_transform import wavedec, waverec
diff --git a/src/ptwt/_stationary_transform.py b/src/ptwt/_stationary_transform.py
index 5d2028b7..2beaf9f8 100644
--- a/src/ptwt/_stationary_transform.py
+++ b/src/ptwt/_stationary_transform.py
@@ -1,4 +1,5 @@
 """This module implements stationary wavelet transforms."""
+
 # Created by moritz wolter, in 2024
 
 from typing import List, Optional, Union
diff --git a/src/ptwt/_util.py b/src/ptwt/_util.py
index 50277b42..f76f973a 100644
--- a/src/ptwt/_util.py
+++ b/src/ptwt/_util.py
@@ -1,4 +1,5 @@
 """Utility methods to compute wavelet decompositions from a dataset."""
+
 from typing import Any, Callable, List, Optional, Protocol, Sequence, Tuple, Union
 
 import numpy as np
diff --git a/src/ptwt/continuous_transform.py b/src/ptwt/continuous_transform.py
index d91ccb1f..db95d06b 100644
--- a/src/ptwt/continuous_transform.py
+++ b/src/ptwt/continuous_transform.py
@@ -2,6 +2,7 @@
 
 This module is based on pywt's cwt implementation.
 """
+
 # Written by the Pytorch wavelet toolbox team in 2024
 from typing import Any, Tuple, Union
 
@@ -195,7 +196,7 @@ def _integrate(
         if type(arr) is np.ndarray:
             integral = np.cumsum(arr)
         elif type(arr) is torch.Tensor:
-            integral = torch.cumsum(arr, -1)
+            integral = torch.cumsum(arr, -1)  # type: ignore
         else:
             raise TypeError("Only ndarrays or tensors are integratable.")
         integral *= step
@@ -271,8 +272,8 @@ def wavefun(
         """Define a grid and evaluate the wavelet on it."""
         length = 2**precision
         # load the bounds from untyped pywt code.
-        lower_bound: float = float(self.lower_bound)
-        upper_bound: float = float(self.upper_bound)
+        lower_bound: float = float(self.lower_bound)  # type: ignore
+        upper_bound: float = float(self.upper_bound)  # type: ignore
         grid = torch.linspace(
             lower_bound,
             upper_bound,
@@ -291,10 +292,10 @@ def __call__(self, grid_values: torch.Tensor) -> torch.Tensor:
         shannon = (
             torch.sqrt(self.bandwidth)
             * (
-                torch.sin(torch.pi * self.bandwidth * grid_values)  # type: ignore
+                torch.sin(torch.pi * self.bandwidth * grid_values)
                 / (torch.pi * self.bandwidth * grid_values)
             )
-            * torch.exp(1j * 2 * torch.pi * self.center * grid_values)  # type: ignore
+            * torch.exp(1j * 2 * torch.pi * self.center * grid_values)
         )
         return shannon
 
@@ -306,8 +307,8 @@ def __call__(self, grid_values: torch.Tensor) -> torch.Tensor:
         """Return numerical values for the wavelet on a grid."""
         morlet = (
             1.0
-            / torch.sqrt(torch.pi * self.bandwidth)  # type: ignore
+            / torch.sqrt(torch.pi * self.bandwidth)
             * torch.exp(-(grid_values**2) / self.bandwidth)
-            * torch.exp(1j * 2 * torch.pi * self.center * grid_values)  # type: ignore
+            * torch.exp(1j * 2 * torch.pi * self.center * grid_values)
         )
         return morlet
diff --git a/src/ptwt/conv_transform.py b/src/ptwt/conv_transform.py
index 475f3aa3..e34f9c2f 100644
--- a/src/ptwt/conv_transform.py
+++ b/src/ptwt/conv_transform.py
@@ -2,6 +2,7 @@
 
 This module treats boundaries with edge-padding.
 """
+
 # Created by moritz wolter, 14.04.20
 from typing import List, Optional, Sequence, Tuple, Union
 
diff --git a/src/ptwt/conv_transform_2.py b/src/ptwt/conv_transform_2.py
index b933f727..f0091612 100644
--- a/src/ptwt/conv_transform_2.py
+++ b/src/ptwt/conv_transform_2.py
@@ -3,6 +3,7 @@
 The implementation relies on torch.nn.functional.conv2d and
 torch.nn.functional.conv_transpose2d under the hood.
 """
+
 # Written by the Pytorch wavelet toolbox team in 2024
 
 
@@ -215,7 +216,7 @@ def wavedec2(
         result_lst = _map_result(result_lst, _unfold_axes2)
 
     if axes != (-2, -1):
-        undo_swap_fn = partial(_undo_swap_axes, axes=axes)
+        undo_swap_fn = partial(_undo_swap_axes, axes=list(axes))
         result_lst = _map_result(result_lst, undo_swap_fn)
 
     return result_lst
diff --git a/src/ptwt/conv_transform_3.py b/src/ptwt/conv_transform_3.py
index dc82cee4..8744e2cf 100644
--- a/src/ptwt/conv_transform_3.py
+++ b/src/ptwt/conv_transform_3.py
@@ -2,6 +2,7 @@
 
 The functions here are based on torch.nn.functional.conv3d and it's transpose.
 """
+
 # Written by the Pytorch wavelet toolbox team in 2024
 
 from functools import partial
@@ -204,7 +205,7 @@ def wavedec3(
         result_lst = _map_result(result_lst, _unfold_axes_fn)
 
     if tuple(axes) != (-3, -2, -1):
-        undo_swap_fn = partial(_undo_swap_axes, axes=axes)
+        undo_swap_fn = partial(_undo_swap_axes, axes=list(axes))
         result_lst = _map_result(result_lst, undo_swap_fn)
 
     return result_lst
@@ -212,7 +213,10 @@ def wavedec3(
 
 def _waverec3d_fold_channels_3d_list(
     coeffs: List[Union[torch.Tensor, Dict[str, torch.Tensor]]],
-) -> Tuple[List[Union[torch.Tensor, Dict[str, torch.Tensor]]], List[int],]:
+) -> Tuple[
+    List[Union[torch.Tensor, Dict[str, torch.Tensor]]],
+    List[int],
+]:
     # fold the input coefficients for processing conv2d_transpose.
     fold_coeffs: List[Union[torch.Tensor, Dict[str, torch.Tensor]]] = []
     ds = list(_check_if_tensor(coeffs[0]).shape)
diff --git a/src/ptwt/matmul_transform.py b/src/ptwt/matmul_transform.py
index a31191d9..ce7b1876 100644
--- a/src/ptwt/matmul_transform.py
+++ b/src/ptwt/matmul_transform.py
@@ -6,6 +6,7 @@
 in Strang Nguyen (p. 32), as well as the description
 of boundary filters in "Ripples in Mathematics" section 10.3 .
 """
+
 # Created by moritz (wolter@cs.uni-bonn.de) at 14.04.20
 import sys
 from typing import List, Optional, Union
@@ -281,7 +282,7 @@ def _construct_analysis_matrices(
                     f"level {curr_level}, the current signal length {curr_length} is "
                     f"smaller than the filter length {filt_len}. Therefore, the "
                     "transformation is only computed up to the decomposition level "
-                    f"{curr_level-1}.\n"
+                    f"{curr_level - 1}.\n"
                 )
                 break
 
@@ -563,7 +564,7 @@ def _construct_synthesis_matrices(
                     f"level {curr_level}, the current signal length {curr_length} is "
                     f"smaller than the filter length {filt_len}. Therefore, the "
                     "transformation is only computed up to the decomposition level "
-                    f"{curr_level-1}.\n"
+                    f"{curr_level - 1}.\n"
                 )
                 break
 
diff --git a/src/ptwt/matmul_transform_2.py b/src/ptwt/matmul_transform_2.py
index 1a1642ab..084eaa44 100644
--- a/src/ptwt/matmul_transform_2.py
+++ b/src/ptwt/matmul_transform_2.py
@@ -2,6 +2,7 @@
 
 This module uses boundary filters to minimize padding.
 """
+
 # Written by moritz ( @ wolter.tech ) in 2021
 import sys
 from functools import partial
@@ -364,7 +365,8 @@ def _construct_analysis_matrices(
                     f". At level {curr_level}, at least one of the current signal "
                     f"height and width ({current_height}, {current_width}) is smaller "
                     f"then the filter length {filt_len}. Therefore, the transformation "
-                    f"is only computed up to the decomposition level {curr_level-1}.\n"
+                    f"is only computed up to the decomposition "
+                    f" level {curr_level - 1}.\n"
                 )
                 break
             # the conv matrices require even length inputs.
@@ -544,7 +546,7 @@ def __call__(
             split_list = _map_result(split_list, _unfold_axes2)
 
         if self.axes != (-2, -1):
-            undo_swap_fn = partial(_undo_swap_axes, axes=self.axes)
+            undo_swap_fn = partial(_undo_swap_axes, axes=list(self.axes))
             split_list = _map_result(split_list, undo_swap_fn)
 
         return split_list[::-1]
@@ -678,7 +680,8 @@ def _construct_synthesis_matrices(
                     f". At level {curr_level}, at least one of the current signal "
                     f"height and width ({current_height}, {current_width}) is smaller "
                     f"then the filter length {filt_len}. Therefore, the transformation "
-                    f"is only computed up to the decomposition level {curr_level-1}.\n"
+                    f"is only computed up to the "
+                    f" decomposition level {curr_level - 1}.\n"
                 )
                 break
             current_height, current_width, pad_tuple = _matrix_pad_2(
diff --git a/src/ptwt/matmul_transform_3.py b/src/ptwt/matmul_transform_3.py
index cbf02de8..a7898668 100644
--- a/src/ptwt/matmul_transform_3.py
+++ b/src/ptwt/matmul_transform_3.py
@@ -1,4 +1,5 @@
 """Implement 3D separable boundary transforms."""
+
 # Written by the Pytorch wavelet toolbox team in 2024
 
 import sys
@@ -122,7 +123,8 @@ def _construct_analysis_matrices(
                     f"depth, height, and width ({current_depth}, {current_height},"
                     f"{current_width}) is smaller "
                     f"then the filter length {filt_len}. Therefore, the transformation "
-                    f"is only computed up to the decomposition level {curr_level-1}.\n"
+                    f"is only computed up to the "
+                    f" decomposition level {curr_level - 1}.\n"
                 )
                 break
             # the conv matrices require even length inputs.
@@ -137,7 +139,7 @@ def _construct_analysis_matrices(
             matrix_construction_fun = partial(
                 construct_boundary_a,
                 wavelet=self.wavelet,
-                boundary=self.boundary,
+                boundary=self.boundary,  # type: ignore
                 device=device,
                 dtype=dtype,
             )
@@ -265,7 +267,7 @@ def _split_rec(
             split_list = _map_result(split_list, _unfold_axes_fn)
 
         if self.axes != (-3, -2, -1):
-            undo_swap_fn = partial(_undo_swap_axes, axes=self.axes)
+            undo_swap_fn = partial(_undo_swap_axes, axes=list(self.axes))
             split_list = _map_result(split_list, undo_swap_fn)
 
         return split_list[::-1]
@@ -340,7 +342,8 @@ def _construct_synthesis_matrices(
                     f" depth, height and width ({current_depth}, {current_height}, "
                     f"{current_width}) is smaller than the filter length {filt_len}."
                     f" Therefore, the transformation "
-                    f"is only computed up to the decomposition level {curr_level-1}.\n"
+                    f"is only computed up to the "
+                    f"decomposition level {curr_level - 1}.\n"
                 )
                 break
             # the conv matrices require even length inputs.
diff --git a/src/ptwt/packets.py b/src/ptwt/packets.py
index b1cecc66..4fabeba9 100644
--- a/src/ptwt/packets.py
+++ b/src/ptwt/packets.py
@@ -1,4 +1,5 @@
 """Compute analysis wavelet packet representations."""
+
 # Created on Fri Apr 6 2021 by moritz (wolter@cs.uni-bonn.de)
 
 import collections
@@ -104,7 +105,7 @@ def __init__(
             if len(data.shape) == 1:
                 # add a batch dimension.
                 data = data.unsqueeze(0)
-            self.transform(data, maxlevel)  # type: ignore
+            self.transform(data, maxlevel)
         else:
             self.data = {}
 
@@ -176,7 +177,11 @@ def _get_wavedec(
             return self._matrix_wavedec_dict[length]
         else:
             return partial(
-                wavedec, wavelet=self.wavelet, level=1, mode=self.mode, axis=self.axis
+                wavedec,
+                wavelet=self.wavelet,
+                level=1,
+                mode=self.mode,  # type: ignore
+                axis=self.axis,
             )
 
     def _get_waverec(
@@ -382,9 +387,7 @@ def get_natural_order(self, level: int) -> List[str]:
         """
         return ["".join(p) for p in product(["a", "h", "v", "d"], repeat=level)]
 
-    def _get_wavedec(
-        self, shape: Tuple[int, ...]
-    ) -> Callable[
+    def _get_wavedec(self, shape: Tuple[int, ...]) -> Callable[
         [torch.Tensor],
         List[Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor, torch.Tensor]]],
     ]:
@@ -415,9 +418,7 @@ def _get_wavedec(
                 wavedec2, wavelet=self.wavelet, level=1, mode=self.mode, axes=self.axes
             )
 
-    def _get_waverec(
-        self, shape: Tuple[int, ...]
-    ) -> Callable[
+    def _get_waverec(self, shape: Tuple[int, ...]) -> Callable[
         [List[Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor, torch.Tensor]]]],
         torch.Tensor,
     ]:
@@ -471,7 +472,7 @@ def _transform_tuple_to_fsdict_func(
         def _fsdict_func(
             coeffs: List[
                 Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor, torch.Tensor]]
-            ]
+            ],
         ) -> torch.Tensor:
             a, (h, v, d) = coeffs
             return fsdict_func([cast(torch.Tensor, a), {"ad": h, "da": v, "dd": d}])
diff --git a/src/ptwt/separable_conv_transform.py b/src/ptwt/separable_conv_transform.py
index 1cd1a322..ddaea945 100644
--- a/src/ptwt/separable_conv_transform.py
+++ b/src/ptwt/separable_conv_transform.py
@@ -6,6 +6,7 @@
 Under the hood, code in this module transforms all dimensions
 using torch.nn.functional.conv1d and it's transpose.
 """
+
 # Written by the Pytorch wavelet toolbox team in 2024
 from functools import partial
 from typing import Dict, List, Optional, Tuple, Union
@@ -164,9 +165,9 @@ def _separable_conv_waverecn(
 
     approx: torch.Tensor = coeffs[0]
     for level_dict in coeffs[1:]:
-        keys = list(level_dict.keys())
-        level_dict["a" * max(map(len, keys))] = approx
-        approx = _separable_conv_idwtn(level_dict, wavelet)
+        keys = list(level_dict.keys())  # type: ignore
+        level_dict["a" * max(map(len, keys))] = approx  # type: ignore
+        approx = _separable_conv_idwtn(level_dict, wavelet)  # type: ignore
     return approx
 
 
@@ -235,7 +236,7 @@ def fswavedec2(
         res = _map_result(res, _unfold_axes2)
 
     if axes != (-2, -1):
-        undo_swap_fn = partial(_undo_swap_axes, axes=axes)
+        undo_swap_fn = partial(_undo_swap_axes, axes=list(axes))
         res = _map_result(res, undo_swap_fn)
 
     return res
@@ -307,7 +308,7 @@ def fswavedec3(
         res = _map_result(res, _unfold_axes3)
 
     if axes != (-3, -2, -1):
-        undo_swap_fn = partial(_undo_swap_axes, axes=axes)
+        undo_swap_fn = partial(_undo_swap_axes, axes=list(axes))
         res = _map_result(res, undo_swap_fn)
 
     return res
diff --git a/src/ptwt/sparse_math.py b/src/ptwt/sparse_math.py
index aa1ec232..e4eb91d0 100644
--- a/src/ptwt/sparse_math.py
+++ b/src/ptwt/sparse_math.py
@@ -1,4 +1,5 @@
 """Efficiently construct fwt operations using sparse matrices."""
+
 # Written by moritz ( @ wolter.tech ) 17.09.21
 from itertools import product
 from typing import List
diff --git a/src/ptwt/wavelets_learnable.py b/src/ptwt/wavelets_learnable.py
index 196b90c0..240abd26 100644
--- a/src/ptwt/wavelets_learnable.py
+++ b/src/ptwt/wavelets_learnable.py
@@ -2,6 +2,7 @@
 
 See https://arxiv.org/pdf/2004.09569.pdf for more information.
 """
+
 # Created by moritz wolter@cs.uni-bonn.de, 14.05.20
 # Inspired by Ripples in Mathematics, Jensen and La Cour-Harbo, Chapter 7.7
 # import pywt
diff --git a/tests/_mackey_glass.py b/tests/_mackey_glass.py
index fb8e9d8c..63f17ee3 100644
--- a/tests/_mackey_glass.py
+++ b/tests/_mackey_glass.py
@@ -1,4 +1,5 @@
 """Generate artificial time-series data for debugging purposes."""
+
 from typing import Optional, Union
 
 import torch
diff --git a/tests/test_convolution_fwt.py b/tests/test_convolution_fwt.py
index d7663c28..001a41e6 100644
--- a/tests/test_convolution_fwt.py
+++ b/tests/test_convolution_fwt.py
@@ -1,4 +1,5 @@
 """Test the conv-fwt code."""
+
 # Written by moritz ( @ wolter.tech ) in 2021
 import numpy as np
 import pytest
diff --git a/tests/test_cwt.py b/tests/test_cwt.py
index 01979d36..44148bb3 100644
--- a/tests/test_cwt.py
+++ b/tests/test_cwt.py
@@ -1,4 +1,5 @@
 """Test the continuous transformation code."""
+
 from typing import Union
 
 import numpy as np
diff --git a/tests/test_dtypes.py b/tests/test_dtypes.py
new file mode 100644
index 00000000..a6c84d41
--- /dev/null
+++ b/tests/test_dtypes.py
@@ -0,0 +1,48 @@
+"""Test dtype support for the fwt code."""
+
+# Written by moritz ( @ wolter.tech ) in 2025
+import numpy as np
+import pytest
+import pywt
+import torch
+from scipy import datasets
+
+from src.ptwt.conv_transform import _flatten_2d_coeff_lst
+from src.ptwt.conv_transform_2 import wavedec2, waverec2
+
+
+@pytest.mark.slow
+@pytest.mark.parametrize(
+    "dtype", [torch.float64, torch.float32, torch.float16, torch.bfloat16]
+)
+def test_2d_wavedec_rec(dtype):
+    """Ensure pywt.wavedec2 and ptwt.wavedec2 produce the same coefficients.
+
+    wavedec2 and waverec2 must invert each other.
+    """
+    mode = "reflect"
+    level = 2
+    size = (32, 32)
+    face = np.transpose(
+        datasets.face()[256 : (512 + size[0]), 256 : (512 + size[1])], [2, 0, 1]
+    ).astype(np.float32)
+    wavelet = pywt.Wavelet("db2")
+    to_transform = torch.from_numpy(face).to(torch.float32)
+    coeff2d = wavedec2(to_transform, wavelet, mode=mode, level=level)
+    pywt_coeff2d = pywt.wavedec2(face, wavelet, mode=mode, level=level)
+    for pos, coeffs in enumerate(pywt_coeff2d):
+        if type(coeffs) is tuple:
+            for tuple_pos, tuple_el in enumerate(coeffs):
+                assert (
+                    tuple_el.shape == coeff2d[pos][tuple_pos].shape
+                ), "pywt and ptwt should produce the same shapes."
+        else:
+            assert (
+                coeffs.shape == coeff2d[pos].shape
+            ), "pywt and ptwt should produce the same shapes."
+    flat_coeff_list_pywt = np.concatenate(_flatten_2d_coeff_lst(pywt_coeff2d), -1)
+    flat_coeff_list_ptwt = torch.cat(_flatten_2d_coeff_lst(coeff2d), -1)
+    assert np.allclose(flat_coeff_list_pywt, flat_coeff_list_ptwt.numpy(), atol=1e-3)
+    rec = waverec2(coeff2d, wavelet)
+    rec = rec.numpy().squeeze().astype(np.float32)
+    assert np.allclose(face, rec[:, : face.shape[1], : face.shape[2]], atol=1e-3)
diff --git a/tests/test_jit.py b/tests/test_jit.py
index 1f34e482..b9a28725 100644
--- a/tests/test_jit.py
+++ b/tests/test_jit.py
@@ -1,4 +1,5 @@
 """Ensure pytorch's torch.jit.trace feature works properly."""
+
 from typing import NamedTuple
 
 import numpy as np
diff --git a/tests/test_matrix_fwt.py b/tests/test_matrix_fwt.py
index 0cc82484..edbd12bd 100644
--- a/tests/test_matrix_fwt.py
+++ b/tests/test_matrix_fwt.py
@@ -1,4 +1,5 @@
 """Test the fwt and ifwt matrices."""
+
 # Written by moritz ( @ wolter.tech ) in 2021
 from typing import List
 
diff --git a/tests/test_matrix_fwt_2.py b/tests/test_matrix_fwt_2.py
index d975a32e..9ccdb010 100644
--- a/tests/test_matrix_fwt_2.py
+++ b/tests/test_matrix_fwt_2.py
@@ -1,4 +1,5 @@
 """Test code for the 2d boundary wavelets."""
+
 # Created by moritz ( wolter@cs.uni-bonn.de ), 08.09.21
 import numpy as np
 import pytest
diff --git a/tests/test_matrix_fwt_3.py b/tests/test_matrix_fwt_3.py
index 09790810..9d555043 100644
--- a/tests/test_matrix_fwt_3.py
+++ b/tests/test_matrix_fwt_3.py
@@ -1,4 +1,5 @@
 """Test the 3d matrix-fwt code."""
+
 from typing import List
 
 import numpy as np
diff --git a/tests/test_packets.py b/tests/test_packets.py
index 488b8035..6b2c0e90 100644
--- a/tests/test_packets.py
+++ b/tests/test_packets.py
@@ -1,4 +1,5 @@
 """Test the wavelet packet code."""
+
 # Created on Fri Apr 6 2021 by moritz (wolter@cs.uni-bonn.de)
 from itertools import product
 
diff --git a/tests/test_sparse_math.py b/tests/test_sparse_math.py
index 3cc45679..06068269 100644
--- a/tests/test_sparse_math.py
+++ b/tests/test_sparse_math.py
@@ -1,4 +1,5 @@
 """Test the sparse math code from ptwt.sparse_math."""
+
 # Written by moritz ( @ wolter.tech ) in 2021
 import numpy as np
 import pytest
diff --git a/tests/test_util.py b/tests/test_util.py
index a6b6016c..9123acc9 100644
--- a/tests/test_util.py
+++ b/tests/test_util.py
@@ -1,4 +1,5 @@
 """Test the util methods."""
+
 from typing import Tuple
 
 import numpy as np
diff --git a/tests/test_wavelet.py b/tests/test_wavelet.py
index eea5baf2..b9f8a8bc 100644
--- a/tests/test_wavelet.py
+++ b/tests/test_wavelet.py
@@ -1,4 +1,5 @@
 """Test the adaptive wavelet cost functions."""
+
 import pytest
 import pywt
 import torch