v0lta · v0lta · Nov 22, 2025 · Nov 17, 2025 · Nov 17, 2025 · Nov 17, 2025
diff --git a/README.rst b/README.rst
@@ -71,7 +71,7 @@ convolution. Consider the following example:
   import torch
   import numpy as np
   import pywt
-  import ptwt  # use "from src import ptwt" for a cloned the repo
+  import ptwt
 
   # generate an input of even length.
   data = np.array([0, 1, 2, 3, 4, 5, 6, 7, 7, 6, 5, 4, 3, 2, 1, 0])
@@ -133,7 +133,7 @@ Reconsidering the 1d case, try:
 
   import torch
   import pywt
-  import ptwt  # use "from src import ptwt" for a cloned the repo
+  import ptwt
 
   # generate an input of even length.
   data = torch.arange(16, dtype=torch.float32)

diff --git a/docs/citation.rst b/docs/citation.rst
@@ -7,17 +7,16 @@ If you use this work in a scientific context, please cite the following paper:
 
 .. code-block::
 
-   @article{JMLR:v25:23-0636,
-   author  = {Moritz Wolter and Felix Blanke and Jochen Garcke and Charles Tapley Hoyt},
-   title   = {ptwt - The PyTorch Wavelet Toolbox},
-   journal = {Journal of Machine Learning Research},
-   year    = {2024},
-   volume  = {25},
-   number  = {80},
-   pages   = {1--7},
-   url     = {http://jmlr.org/papers/v25/23-0636.html}
-   }
-
+    @article{JMLR:v25:23-0636,
+        author  = {Moritz Wolter and Felix Blanke and Jochen Garcke and Charles Tapley Hoyt},
+        title   = {ptwt - The PyTorch Wavelet Toolbox},
+        journal = {Journal of Machine Learning Research},
+        year    = {2024},
+        volume  = {25},
+        number  = {80},
+        pages   = {1--7},
+        url     = {http://jmlr.org/papers/v25/23-0636.html}
+    }
 
 This work builds upon `PyWavelets <https://pywavelets.readthedocs.io/en/latest/>`_
 please consider citing them as well.
diff --git a/docs/examples.rst b/docs/examples.rst
@@ -3,4 +3,5 @@
 Wavelet transforms by example
 =============================
 
-Worked examples are available in the examples folder of the `GitHub repository <https://github.com/v0lta/PyTorch-Wavelet-Toolbox/tree/main/examples>`_ .
+Worked examples are available in the examples folder of the `GitHub repository
+<https://github.com/v0lta/PyTorch-Wavelet-Toolbox/tree/main/examples>`_ .
diff --git a/docs/ref/index.rst b/docs/ref/index.rst
@@ -4,17 +4,17 @@ The ptwt package -- API reference
 =================================
 
 .. toctree::
-   :maxdepth: 2
+    :maxdepth: 2
 
-   conv-fwt
-   conv-inverse-fwt
-   matrix-fwt
-   matrix-inverse-fwt
-   packets
-   stationary
-   cwt
-   return-types
-   boundary
-   wavelets-learnable
-   sparse-math
-   other
+    conv-fwt
+    conv-inverse-fwt
+    matrix-fwt
+    matrix-inverse-fwt
+    packets
+    stationary
+    cwt
+    return-types
+    boundary
+    wavelets-learnable
+    sparse-math
+    other
diff --git a/docs/ref/matrix-fwt.rst b/docs/ref/matrix-fwt.rst
@@ -9,34 +9,35 @@ Sparse-matrix based Fast Wavelet Transform (FWT)
 ---------------------------------------------
 
 .. autoclass:: MatrixWavedec
-   :members:
-   :special-members: __call__
-   :undoc-members:
-   :show-inheritance:
+    :members:
+    :special-members: __call__
+    :undoc-members:
+    :show-inheritance:
 
 2d decomposition using :class:`MatrixWavedec2`
 ----------------------------------------------
 
 .. autoclass:: MatrixWavedec2
-   :members:
-   :special-members: __call__
-   :undoc-members:
-   :show-inheritance:
+    :members:
+    :special-members: __call__
+    :undoc-members:
+    :show-inheritance:
 
 3d decomposition using :class:`MatrixWavedec3`
 ----------------------------------------------
 
 .. autoclass:: MatrixWavedec3
-   :members:
-   :special-members: __call__
-   :undoc-members:
-   :show-inheritance:
-
+    :members:
+    :special-members: __call__
+    :undoc-members:
+    :show-inheritance:
 
 Sparse-matrix FWT base class
 ----------------------------
-All sparse-matrix decomposition classes extend :class:`ptwt.matmul_transform.BaseMatrixWaveDec`.
+
+All sparse-matrix decomposition classes extend
+:class:`ptwt.matmul_transform.BaseMatrixWaveDec`.
 
 .. autoclass:: ptwt.matmul_transform.BaseMatrixWaveDec
-   :members:
-   :undoc-members:
+    :members:
+    :undoc-members:
diff --git a/docs/ref/matrix-inverse-fwt.rst b/docs/ref/matrix-inverse-fwt.rst
@@ -9,22 +9,22 @@ Sparse-matrix based Inverse Fast Wavelet Transform (iFWT)
 ---------------------------------------------
 
 .. autoclass:: MatrixWaverec
-   :members:
-   :special-members: __call__
-   :undoc-members:
+    :members:
+    :special-members: __call__
+    :undoc-members:
 
 2d reconstrucion using :class:`MatrixWaverec2`
 ----------------------------------------------
 
 .. autoclass:: MatrixWaverec2
-   :members:
-   :special-members: __call__
-   :undoc-members:
+    :members:
+    :special-members: __call__
+    :undoc-members:
 
 3d reconstrucion using :class:`MatrixWaverec3`
 ----------------------------------------------
 
 .. autoclass:: MatrixWaverec3
-   :members:
-   :special-members: __call__
-   :undoc-members:
+    :members:
+    :special-members: __call__
+    :undoc-members:
diff --git a/docs/ref/other.rst b/docs/ref/other.rst
@@ -9,6 +9,6 @@ Version information
 -------------------
 
 .. automodule:: ptwt.version
-   :members:
-   :undoc-members:
-   :show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/ref/packets.rst b/docs/ref/packets.rst
@@ -3,23 +3,23 @@
 .. currentmodule:: ptwt
 
 Wavelet Packet Transform (WPT)
-====================================
+==============================
 
 Packets in 1d using :class:`WaveletPacket`
 ------------------------------------------
 
 .. autoclass:: WaveletPacket
-   :members:
-   :special-members: __getitem__
-   :undoc-members:
+    :members:
+    :special-members: __getitem__
+    :undoc-members:
 
 Packets in 2d using :class:`WaveletPacket2D`
 --------------------------------------------
 
 .. autoclass:: WaveletPacket2D
-   :members:
-   :special-members: __getitem__
-   :undoc-members:
+    :members:
+    :special-members: __getitem__
+    :undoc-members:
 
 Node ordering
 -------------

diff --git a/docs/ref/return-types.rst b/docs/ref/return-types.rst
@@ -10,7 +10,6 @@ Transforms in one dimension
 
 .. autoclass:: WaveletCoeff1d
 
-
 Transforms in two dimensions
 ----------------------------
 
@@ -22,7 +21,6 @@ Transforms in two dimensions
     :show-inheritance:
     :member-order: bysource
 
-
 Transforms in N dimensions
 --------------------------
 

diff --git a/docs/ref/sparse-math.rst b/docs/ref/sparse-math.rst
@@ -4,6 +4,6 @@ Sparse-matrix backend functions
 ===============================
 
 .. automodule:: ptwt.sparse_math
-   :members:
-   :undoc-members:
-   :show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/ref/wavelets-learnable.rst b/docs/ref/wavelets-learnable.rst
@@ -1,9 +1,9 @@
 .. _ref-wavelets-learnable:
 
 Learnable adaptive wavelets
--------------------------------
+===========================
 
 .. automodule:: ptwt.wavelets_learnable
-   :members:
-   :undoc-members:
-   :show-inheritance:
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/release_notes.rst b/docs/release_notes.rst
@@ -3,4 +3,5 @@
 Release Notes
 =============
 
-We publish releases via GitHub. The notes are available at the `GitHub release page <https://github.com/v0lta/PyTorch-Wavelet-Toolbox/releases>`_ .
+We publish releases via GitHub. The notes are available at the `GitHub release page
+<https://github.com/v0lta/PyTorch-Wavelet-Toolbox/releases>`_ .
diff --git a/examples/deepfake_analysis/packet_plot.py b/examples/deepfake_analysis/packet_plot.py
@@ -1,5 +1,4 @@
 import os
-from itertools import product
 
 import matplotlib.pyplot as plt
 import numpy as np

diff --git a/examples/network_compression/mnist_compression.py b/examples/network_compression/mnist_compression.py
@@ -239,7 +239,7 @@ def main():
         ),
         batch_size=args.batch_size,
         shuffle=True,
-        **kwargs
+        **kwargs,
     )
     test_loader = torch.utils.data.DataLoader(
         datasets.MNIST(
@@ -251,7 +251,7 @@ def main():
         ),
         batch_size=args.test_batch_size,
         shuffle=True,
-        **kwargs
+        **kwargs,
     )
 
     if args.compression == "Wavelet":

diff --git a/examples/network_compression/wavelet_linear.py b/examples/network_compression/wavelet_linear.py
@@ -70,9 +70,9 @@ def wavelet_analysis(self, x):
         c_lst = wavedec(x.unsqueeze(1), self.wavelet, level=self.scales)
         shape_lst = [c_el.shape[-1] for c_el in c_lst]
         c_tensor = torch.cat([c for c in c_lst], -1)
-        assert (
-            shape_lst == self.coefficient_len_lst[::-1]
-        ), "Wavelet shape assumptions false. This is a bug."
+        assert shape_lst == self.coefficient_len_lst[::-1], (
+            "Wavelet shape assumptions false. This is a bug."
+        )
         return c_tensor
 
     def wavelet_reconstruction(self, x):

diff --git a/examples/speed_tests/timeitconv_1d.py b/examples/speed_tests/timeitconv_1d.py
@@ -1,5 +1,4 @@
 import time
-from typing import NamedTuple
 
 import matplotlib.pyplot as plt
 import numpy as np

diff --git a/examples/speed_tests/timeitconv_2d.py b/examples/speed_tests/timeitconv_2d.py
@@ -1,5 +1,4 @@
 import time
-from typing import NamedTuple
 
 import matplotlib.pyplot as plt
 import numpy as np

diff --git a/examples/speed_tests/timeitconv_2d_separable.py b/examples/speed_tests/timeitconv_2d_separable.py
@@ -1,5 +1,4 @@
 import time
-from typing import NamedTuple
 
 import matplotlib.pyplot as plt
 import numpy as np

diff --git a/examples/speed_tests/timeitconv_3d.py b/examples/speed_tests/timeitconv_3d.py
@@ -1,5 +1,4 @@
 import time
-from typing import NamedTuple
 
 import matplotlib.pyplot as plt
 import numpy as np

diff --git a/examples/wavelet_packet_chirp_analysis/chirp_analysis.py b/examples/wavelet_packet_chirp_analysis/chirp_analysis.py
@@ -1,10 +1,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pywt
-import scipy.signal
 import torch
 
-# use from src.ptwt.packets if you cloned the repo instead of using pip.
 from ptwt import WaveletPacket
 
 fs = 1000

diff --git a/noxfile.py b/noxfile.py
@@ -17,6 +17,13 @@ def run_test_fast(session):
     session.run("pytest", "-m", "not slow")
 
 
+@nox.session(name="doctests")
+def run_doctests(session):
+    """Run tests in docstrings."""
+    session.install(".[tests]", "xdoctest", "pygments", "matplotlib")
+    session.run("xdoctest", "-m", "ptwt", "--quiet")
+
+
 @nox.session(name="lint")
 def lint(session):
     """Check code conventions."""

diff --git a/src/ptwt/__init__.py b/src/ptwt/__init__.py
@@ -19,3 +19,34 @@
 from .packets import WaveletPacket, WaveletPacket2D
 from .separable_conv_transform import fswavedec2, fswavedec3, fswaverec2, fswaverec3
 from .stationary_transform import iswt, swt
+
+__all__ = [
+    "Wavelet",
+    "WaveletDetailTuple2d",
+    "WaveletCoeff2d",
+    "WaveletCoeff2dSeparable",
+    "WaveletCoeffNd",
+    "WaveletDetailDict",
+    "WaveletTensorTuple",
+    "cwt",
+    "wavedec",
+    "waverec",
+    "wavedec2",
+    "waverec2",
+    "wavedec3",
+    "waverec3",
+    "MatrixWavedec",
+    "MatrixWaverec",
+    "MatrixWavedec2",
+    "MatrixWaverec2",
+    "MatrixWavedec3",
+    "MatrixWaverec3",
+    "WaveletPacket",
+    "WaveletPacket2D",
+    "fswavedec2",
+    "fswavedec3",
+    "fswaverec2",
+    "fswaverec3",
+    "iswt",
+    "swt",
+]
diff --git a/src/ptwt/constants.py b/src/ptwt/constants.py
@@ -21,6 +21,7 @@
     "WaveletCoeffNd",
     "WaveletDetailDict",
     "WaveletTensorTuple",
+    "WaveletCoeff1d",
 ]
 
 SUPPORTED_DTYPES = {torch.float32, torch.float64}