diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index fd69cb9..ab3381c 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -18,9 +18,9 @@ jobs:
   package:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v7
       - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v7
         with:
           python-version: '3.10'
       - name: Install dependencies
@@ -34,7 +34,7 @@ jobs:
       - name: Check env vars
         run: |
           echo "Triggered by: ${{ github.event_name }}"
-      - uses: actions/upload-artifact@v5
+      - uses: actions/upload-artifact@v7
         with:
           name: dist
           path: dist
@@ -48,7 +48,7 @@ jobs:
     permissions:
       id-token: write
     steps:
-      - uses: actions/download-artifact@v6
+      - uses: actions/download-artifact@v8
         with:
           name: dist
           path: dist
diff --git a/.github/workflows/unit_tests.yml b/.github/workflows/unit_tests.yml
index 77f0d1b..4570f90 100644
--- a/.github/workflows/unit_tests.yml
+++ b/.github/workflows/unit_tests.yml
@@ -38,10 +38,10 @@ jobs:
       OPENBLAS_NUM_THREADS: "1"
       PYTHONUNBUFFERED: "1"
     steps:
-      - uses: actions/setup-python@v6
+      - uses: actions/setup-python@v7
         with:
           python-version: ${{ matrix.python-version }}
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v7
       - uses: pyvista/setup-headless-display-action@main
         with:
           qt: true
@@ -64,26 +64,33 @@ jobs:
         run: python -m coverage run && coverage report
 
   test_conda:
-    timeout-minutes: 90
+    timeout-minutes: 60
     runs-on: ubuntu-latest
     defaults:
       run:
         shell: bash -el {0}
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - os: ubuntu-latest
+            python-version: "3.14"
+          - os: macos-15-intel
+            python-version: "3.14"
     env:
       MKL_NUM_THREADS: '1'
       PYTHONUNBUFFERED: '1'
-      PYTHON_VERSION: '3.13'
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v7
       - uses: pyvista/setup-headless-display-action@main
         with:
           qt: true
           pyvista: false
-      - uses: mamba-org/setup-micromamba@v2
+      - uses: mamba-org/setup-micromamba@v3
         with:
           environment-file: environment.yml
           create-args: >- # beware the >- instead of |, we don't split on newlines but on spaces
-            python=${{ env.PYTHON_VERSION }}
+            python=${{ matrix.python-version }}
       - name: Install package and test dependencies
         run: |
           pip install -e .
@@ -108,10 +115,10 @@ jobs:
       OPENBLAS_NUM_THREADS: "1"
       PYTHONUNBUFFERED: "1"
     steps:
-      - uses: actions/setup-python@v6
+      - uses: actions/setup-python@v7
         with:
           python-version: "3.10"
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v7
       - uses: pyvista/setup-headless-display-action@main
         with:
           qt: true
@@ -119,17 +126,14 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip setuptools wheel
-          pip install --upgrade --upgrade-strategy eager .[test]
+          pip install -e . --no-deps
+          pip install -r tools/requirements_old.txt
       - name: Display versions and environment information
         run: |
           echo $TZ
           date
-          python --version
           which python
-      - run: |
-          pip install -e . --no-deps
-          pip install -r tools/requirements_old.txt
-      - run: python -c "import pybispectra; import mne; print(f'PyBispectra {pybispectra.__version__}\n'); mne.sys_info()"
+          python -c "import pybispectra; import mne; print(f'PyBispectra {pybispectra.__version__}\n'); mne.sys_info()"
       - name: Download testing data
         run: python -c "from pybispectra.utils import DATASETS, get_example_data_paths; (get_example_data_paths(data) for data in DATASETS.keys())"
       - name: Run pytest
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index c9a21d0..1c5f94e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,7 +1,7 @@
 repos:
   # ruff PyBispectra
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.14.8
+    rev: v0.16.0
     hooks:
       - id: ruff
         name: ruff lint pybispectra
@@ -10,7 +10,7 @@ repos:
 
   # ruff examples
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.14.8
+    rev: v0.16.0
     hooks:
       - id: ruff
         name: ruff lint examples
@@ -19,7 +19,7 @@ repos:
 
   # codespell
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.4.1
+    rev: v2.4.3
     hooks:
       - id: codespell
         additional_dependencies:
@@ -29,7 +29,7 @@ repos:
 
   # yamllint
   - repo: https://github.com/adrienverge/yamllint.git
-    rev: v1.37.1
+    rev: v1.38.0
     hooks:
       - id: yamllint
         args: [--strict, -c, .yamllint.yml]
@@ -45,7 +45,7 @@ repos:
 
   # toml-sort
   - repo: https://github.com/pappasam/toml-sort.git
-    rev: v0.24.3
+    rev: v0.24.4
     hooks:
       - id: toml-sort-fix
 
diff --git a/LICENSE.txt b/LICENSE.txt
index a7d06ae..364d808 100644
--- a/LICENSE.txt
+++ b/LICENSE.txt
@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2023-2025 Thomas Samuel Binns
+Copyright (c) 2023-2026 Thomas Samuel Binns
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
diff --git a/changelog.md b/changelog.md
index 2f4ac73..0311962 100644
--- a/changelog.md
+++ b/changelog.md
@@ -8,6 +8,20 @@ No changes.
 
 ## [Version 1.3](https://pybispectra.readthedocs.io/1.3/)
 
+### Version 1.3.2
+
+##### Dependencies
+- Dropped max supported Python version being pinned.
+
+<br>
+
+### Version 1.3.1
+
+##### Dependencies
+- Added support for Python 3.14 in the `conda` environment.
+
+<br>
+
 ### Version 1.3.0
 
 ##### Enhancements
diff --git a/docs/Makefile b/docs/Makefile
index d0c3cbf..06e1859 100644
--- a/docs/Makefile
+++ b/docs/Makefile
@@ -18,3 +18,11 @@ help:
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
 %: Makefile
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+clean:
+	rm -rf $(BUILDDIR)/*
+	rm -rf $(SOURCEDIR)/auto_examples/*
+	rm -rf $(SOURCEDIR)/generated/*
+
+view:
+	@python -c "import webbrowser; webbrowser.open_new_tab('file://$(PWD)/build/html/index.html')"
diff --git a/docs/source/_static/css/custom.css b/docs/source/_static/css/custom.css
index ca373b3..d4d7a90 100644
--- a/docs/source/_static/css/custom.css
+++ b/docs/source/_static/css/custom.css
@@ -4,4 +4,49 @@ div {
 
 ul {
     text-align: left
+}
+
+/* widen main content area */
+.bd-page-width {
+    max-width: 100rem;
+}
+
+/* make versionadded smaller and inline with param name */
+/* don't do for deprecated / versionchanged; they have extra info (too long to fit) */
+div.versionadded>p {
+    margin-top: 0;
+    margin-bottom: 0;
+}
+
+div.versionadded {
+    margin: 0;
+    margin-left: 0.5rem;
+    display: inline-block;
+}
+
+/* when FF supports :has(), change to →  dd > p:has(+div.versionadded) */
+dd>p {
+    display: inline;
+}
+
+@media (max-width: 1199.98px) {
+    .bd-header .navbar-header-items__start {
+        flex-shrink: 1;
+        min-width: 0;
+        max-width: 45%;
+    }
+
+    .bd-header .navbar-header-items__start .navbar-item,
+    .bd-header .navbar-brand {
+        min-width: 0;
+        max-width: 100%;
+        flex-shrink: 1;
+    }
+
+    .bd-header .navbar-brand .logo__title {
+        max-width: 100%;
+        overflow: hidden;
+        text-overflow: ellipsis;
+        white-space: nowrap;
+    }
 }
\ No newline at end of file
diff --git a/docs/source/_static/versions.json b/docs/source/_static/versions.json
index 2796258..ec275f0 100644
--- a/docs/source/_static/versions.json
+++ b/docs/source/_static/versions.json
@@ -1,12 +1,12 @@
 [
     {
         "name": "dev",
-        "version": "1.3.1+dev",
+        "version": "1.4.0+dev",
         "url": "https://pybispectra.readthedocs.io/latest/"
     },
     {
         "name": "1.3 (stable)",
-        "version": "1.3.0",
+        "version": "1.3.2",
         "url": "https://pybispectra.readthedocs.io/1.3/"
     },
     {
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 6d28dc0..5a1ac63 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -14,9 +14,9 @@
 from pybispectra.utils._docs import linkcode_resolve
 
 project = "PyBispectra"
-copyright = "2023-2025, Thomas S. Binns"
+copyright = "2023-2026, Thomas S. Binns"
 author = "Thomas S. Binns"
-release = "1.3.0"
+release = "1.3.2"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
@@ -36,6 +36,7 @@
     "sphinxcontrib.bibtex",
     "sphinx_gallery.gen_gallery",
     "sphinx_copybutton",
+    "sphinx_design",
     ### Custom
     "directive_formatting",
 ]
diff --git a/docs/source/installation.rst b/docs/source/installation.rst
index 25998fa..04ee5e6 100644
--- a/docs/source/installation.rst
+++ b/docs/source/installation.rst
@@ -1,40 +1,74 @@
 Installation
 ============
 
-To install PyBispectra, activate the desired environment in which you want the package,
-then install it using `pip <https://pip.pypa.io/en/stable/>`_:
+PyBispectra is available on `PyPI <https://pypi.org/project/pybispectra/>`_, and
+`conda-forge <https://anaconda.org/channels/conda-forge/packages/pybispectra/overview>`_
+for version ≥ 1.2.2.
+
+PyBispectra requires Python ≥ 3.10.
+
+
+Package installation
+--------------------
+
+To install PyBispectra, activate the desired environment or project in which you want
+the package, then install it using `pip <https://pip.pypa.io/en/stable/>`_:
 
 .. code-block::
     
     pip install pybispectra
 
-or `conda <https://docs.conda.io/en/latest/>`_ from
-`conda-forge <https://anaconda.org/conda-forge>`_ (for PyBispectra ≥ 1.2.2):
+`uv <https://docs.astral.sh/uv/>`_:
+
+.. code-block::
+    
+    uv pip install pybispectra
+
+`conda <https://docs.conda.io/en/latest/>`_:
 
 .. code-block::
     
     conda install -c conda-forge pybispectra
 
-PyBispectra requires Python ≥ 3.10.
+or `pixi <https://pixi.prefix.dev/latest/>`_:
 
-If you need to create an environment in which to install PyBispectra, you can do so
-using `conda <https://docs.conda.io/en/latest/>`_,
-`venv <https://docs.python.org/3/library/venv.html>`_, or
-`uv <https://docs.astral.sh/uv/>`_.
+.. code-block::
+    
+    pixi add pybispectra
 
-With ``conda``
---------------
+|
 
-In a shell with ``conda`` available, run the following commands:
+.. dropdown:: Compatibility for newly released Python versions
+    :icon: alert
+    :color: info
 
-.. code-block::
+    If you encounter issues installing PyBispectra in environments with newly released Python versions, this may be due to a lack of compatible ``numba`` releases, one of PyBispectra's core dependencies.
+    
+    ``numba`` is not always immediately compatible with new Python versions, and there may be a delay of several weeks before a compatible version is released.
 
-    conda create -n pybispectra_env
-    conda activate pybispectra_env
-    conda install -c conda-forge pybispectra
+    You can find the supported Python versions for ``numba`` in this `table <https://numba.readthedocs.io/en/stable/user/installing.html#numba-support-info>`_.
+
+    If a compatible ``numba`` release is available for your environment's Python version and you are still encountering installation issues, please report this on the `PyBispectra issue page <https://github.com/braindatalab/PyBispectra/issues>`_.
+
+.. dropdown:: Compatibility with Python ≥ 3.14 on macOS Intel systems
+    :icon: alert
+    :color: info
+
+    Due to wheel availability limitations for ``llvmlite`` on macOS Intel systems with Python ≥ 3.14, installation issues can arise when using ``pip`` and ``uv``. 
+    
+    If you have a macOS Intel system and need to use Python ≥ 3.14, consider using ``conda`` or ``pixi`` for an easier installation.
+
+
+Creating an environment or project for installation
+---------------------------------------------------
+
+If you need to create an environment or project in which to install PyBispectra, you can
+do so using `venv <https://docs.python.org/3/library/venv.html>`_,
+`uv <https://docs.astral.sh/uv/>`_, `pixi <https://pixi.prefix.dev/latest/>`_, or
+`conda <https://docs.conda.io/en/latest/>`_.
 
 With ``venv``
--------------
+~~~~~~~~~~~~~
 
 In a shell with Python available, navigate to your project location and create the
 environment:
@@ -52,7 +86,7 @@ then install the package:
     pip install pybispectra
 
 With ``uv``
------------
+~~~~~~~~~~~
 
 In a shell with ``uv`` available, navigate to your project location and create the
 environment:
@@ -68,3 +102,25 @@ then install the package:
 .. code-block::
 
     uv pip install pybispectra
+
+With ``pixi``
+~~~~~~~~~~~~~
+
+In a shell with ``pixi`` available, run the following commands:
+
+.. code-block::
+
+    pixi init
+    pixi shell-hook
+    pixi add pybispectra
+
+With ``conda``
+~~~~~~~~~~~~~~
+
+In a shell with ``conda`` available, run the following commands:
+
+.. code-block::
+
+    conda create -n pybispectra_env
+    conda activate pybispectra_env
+    conda install -c conda-forge pybispectra
diff --git a/environment.yml b/environment.yml
index cbb450d..631712f 100644
--- a/environment.yml
+++ b/environment.yml
@@ -2,10 +2,10 @@ name: pybispectra
 channels:
   - conda-forge
 dependencies:
-  - python>=3.10,<3.14
+  - python>=3.10
   - joblib>=1.2
   - matplotlib>=3.6
-  - mne>=1.7
+  - mne-base>=1.7
   - numba>=0.56
   - numpy>=1.22
   - scikit-learn>=1.1
diff --git a/examples/plot_compute_time_resolved.py b/examples/plot_compute_time_resolved.py
index ba9cd46..7759b03 100644
--- a/examples/plot_compute_time_resolved.py
+++ b/examples/plot_compute_time_resolved.py
@@ -18,7 +18,7 @@
 from matplotlib import pyplot as plt
 from numpy.random import RandomState
 
-from pybispectra import WaveShape, get_example_data_paths, compute_tfr
+from pybispectra import WaveShape, compute_tfr, get_example_data_paths
 
 ########################################################################################
 # Background
diff --git a/pyproject.toml b/pyproject.toml
index 3361588..2b80b9f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,7 +16,7 @@ dynamic = [
 ] # check tools/hatch_build.py for details
 name = "pybispectra"
 readme = "README.md"
-version = "1.3.0"
+version = "1.3.2"
 
 [project.optional-dependencies]
 dev = ["pybispectra[doc]", "pybispectra[lint]", "pybispectra[test]"]
@@ -30,6 +30,7 @@ doc = [
   "pydata-sphinx-theme",
   "sphinx",
   "sphinx-copybutton",
+  "sphinx-design",
   "sphinx-gallery>=0.18",
   "sphinxcontrib-bibtex",
 ]
@@ -125,7 +126,11 @@ ignore_roles = [
 report_level = "WARNING"
 
 [tool.ruff]
-extend-exclude = ["docs", "examples/compute_*.py"]
+extend-exclude = [
+  "docs",
+  "examples/compute_*.py",
+  "src/pybispectra/utils/_docs.py",
+]
 line-length = 88
 
 [tool.ruff.lint.per-file-ignores]
diff --git a/src/pybispectra/__init__.py b/src/pybispectra/__init__.py
index b05bf70..1a66d0f 100644
--- a/src/pybispectra/__init__.py
+++ b/src/pybispectra/__init__.py
@@ -1,6 +1,6 @@
 """Initialisation of the PyBispectra package."""
 
-__version__ = "1.3.0"
+__version__ = "1.3.2"
 
 from .cfc import AAC, PAC, PPC
 from .general import Bispectrum, Threenorm
diff --git a/src/pybispectra/cfc/aac.py b/src/pybispectra/cfc/aac.py
index 9335d8c..5067b9f 100644
--- a/src/pybispectra/cfc/aac.py
+++ b/src/pybispectra/cfc/aac.py
@@ -7,9 +7,9 @@
 from pybispectra.utils._defaults import _precision
 from pybispectra.utils._process import _ProcessFreqBase
 from pybispectra.utils._utils import (
+    _compute_in_parallel,
     _compute_pearsonr_2d,
     _fast_find_first,
-    _compute_in_parallel,
 )
 
 
@@ -61,7 +61,7 @@ class AAC(_ProcessFreqBase):
 
     verbose : bool
         Whether or not to report the progress of the processing.
-    """  # noqa: E501
+    """
 
     _data_precision: type = _precision.real  # Real-valued TFR power
 
@@ -72,9 +72,9 @@ class AAC(_ProcessFreqBase):
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_jobs: int = 1,
     ) -> None:
         r"""Compute AAC, averaged over epochs.
diff --git a/src/pybispectra/cfc/pac.py b/src/pybispectra/cfc/pac.py
index 937b69c..feaab72 100644
--- a/src/pybispectra/cfc/pac.py
+++ b/src/pybispectra/cfc/pac.py
@@ -80,9 +80,9 @@ class PAC(_ProcessBispectrum):
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         antisym: bool | tuple[bool] = False,
         norm: bool | tuple[bool] = False,
         n_jobs: int = 1,
@@ -181,7 +181,7 @@ def compute(
         References
         ----------
         .. footbibliography::
-        """  # noqa: E501
+        """
         self._reset_attrs()
 
         self._sort_metrics(antisym, norm)
diff --git a/src/pybispectra/cfc/ppc.py b/src/pybispectra/cfc/ppc.py
index b09f280..361eab2 100644
--- a/src/pybispectra/cfc/ppc.py
+++ b/src/pybispectra/cfc/ppc.py
@@ -6,7 +6,7 @@
 from pybispectra.utils import ResultsCFC
 from pybispectra.utils._defaults import _precision
 from pybispectra.utils._process import _ProcessFreqBase
-from pybispectra.utils._utils import _fast_find_first, _compute_in_parallel
+from pybispectra.utils._utils import _compute_in_parallel, _fast_find_first
 
 
 class PPC(_ProcessFreqBase):
@@ -73,9 +73,9 @@ class PPC(_ProcessFreqBase):
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_jobs: int = 1,
     ) -> None:
         r"""Compute PPC, averaged over epochs.
diff --git a/src/pybispectra/general/general.py b/src/pybispectra/general/general.py
index 98d3be8..fdbacc2 100644
--- a/src/pybispectra/general/general.py
+++ b/src/pybispectra/general/general.py
@@ -22,16 +22,14 @@ class _General(_ProcessBispectrum):
     def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
         """Sort kmn channel indices inputs."""
         if indices is None:
-            indices = tuple(
-                [
-                    tuple(np.tile(range(self._n_chans), self._n_chans**2).tolist()),
-                    tuple(
-                        np.repeat(
-                            np.tile(range(self._n_chans), self._n_chans), self._n_chans
-                        ).tolist()
-                    ),
-                    tuple(np.repeat(range(self._n_chans), self._n_chans**2).tolist()),
-                ]
+            indices = (
+                tuple(np.tile(range(self._n_chans), self._n_chans**2).tolist()),
+                tuple(
+                    np.repeat(
+                        np.tile(range(self._n_chans), self._n_chans), self._n_chans
+                    ).tolist()
+                ),
+                tuple(np.repeat(range(self._n_chans), self._n_chans**2).tolist()),
             )
         if not isinstance(indices, tuple):
             raise TypeError("`indices` must be a tuple.")
@@ -118,9 +116,9 @@ class Bispectrum(_General):
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_jobs: int = 1,
     ) -> None:
         r"""Compute the bispectrum, averaged over epochs.
@@ -167,7 +165,7 @@ def compute(
         .. warning::
             For values of ``f1s`` higher than ``f2s`` or where ``f2s + f1s`` exceeds the
             Nyquist frequency, a :obj:`numpy.nan` value is returned.
-        """  # noqa: E501
+        """
         self._reset_attrs()
 
         self._sort_indices(indices)
@@ -305,9 +303,9 @@ class Threenorm(_General):
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_jobs: int = 1,
     ) -> None:
         r"""Compute the threenorm, averaged over epochs.
diff --git a/src/pybispectra/tde/tde.py b/src/pybispectra/tde/tde.py
index 748cfff..bfffea5 100644
--- a/src/pybispectra/tde/tde.py
+++ b/src/pybispectra/tde/tde.py
@@ -1,7 +1,8 @@
 """Tools for handling TDE analysis."""
 
+from collections.abc import Callable
 from copy import deepcopy
-from typing import Callable
+from typing import ClassVar
 
 import numpy as np
 from numba import njit
@@ -10,7 +11,7 @@
 from pybispectra.utils import ResultsTDE
 from pybispectra.utils._defaults import _precision
 from pybispectra.utils._process import _ProcessBispectrum
-from pybispectra.utils._utils import _compute_in_parallel, _number_like, _int_like
+from pybispectra.utils._utils import _compute_in_parallel, _int_like, _number_like
 
 
 class TDE(_ProcessBispectrum):
@@ -97,7 +98,7 @@ class TDE(_ProcessBispectrum):
     _tde_iv_nosym: np.ndarray = None
     _tde_iv_antisym: np.ndarray = None
 
-    _kmn: dict = {
+    _kmn: ClassVar[dict] = {
         "xxx": (0, 0, 0),
         "yyy": (1, 1, 1),
         "xyx": (0, 1, 0),
@@ -109,9 +110,9 @@ def __init__(
         self,
         data: np.ndarray,
         freqs: np.ndarray,
-        sampling_freq: int | float,
+        sampling_freq: float,
         verbose: bool = True,
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, freqs, sampling_freq, times=None, verbose=verbose)
         self._sort_fft_coeffs()
 
@@ -130,8 +131,8 @@ def _sort_fft_coeffs(self) -> None:
     def compute(
         self,
         indices: tuple[tuple[int]] | None = None,
-        fmin: int | float | tuple[int | float] = 0.0,
-        fmax: int | float | tuple[int | float] = np.inf,
+        fmin: float | tuple[float] = 0.0,
+        fmax: float | tuple[float] = np.inf,
         antisym: bool | tuple[bool] = False,
         method: int | tuple[int] = 1,
         n_jobs: int = 1,
@@ -284,9 +285,7 @@ def _reset_attrs(self) -> None:
         self._xyz = None
 
     def _sort_freq_bands(
-        self,
-        fmin: int | float | tuple[int | float],
-        fmax: int | float | tuple[int | float],
+        self, fmin: float | tuple[float], fmax: float | tuple[float]
     ) -> None:
         """Sort inputs for the frequency bounds."""
         if not isinstance(fmin, _number_like + (tuple,)):
diff --git a/src/pybispectra/utils/_defaults.py b/src/pybispectra/utils/_defaults.py
index fc35a9b..14156cf 100644
--- a/src/pybispectra/utils/_defaults.py
+++ b/src/pybispectra/utils/_defaults.py
@@ -9,7 +9,7 @@ class _Precision:
     Double precision (i.e., float64 and complex128) used by default.
     """
 
-    def __init__(self) -> None:  # noqa: D107
+    def __init__(self) -> None:
         self.type = "double"
         self.real = np.float64
         self.complex = np.complex128
diff --git a/src/pybispectra/utils/_plot.py b/src/pybispectra/utils/_plot.py
index e7eb70d..c28a3e9 100644
--- a/src/pybispectra/utils/_plot.py
+++ b/src/pybispectra/utils/_plot.py
@@ -44,8 +44,8 @@ def _sort_plot_inputs(
         nodes: int | tuple[int] | None,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
     ) -> tuple[int]:
         """Sort the plotting inputs.
 
@@ -142,7 +142,7 @@ def _sort_freq_inputs(
         return f1s, f2s, f1_idcs, f2_idcs
 
     def _sort_time_inputs(
-        self, times: tuple[int | float] | None
+        self, times: tuple[float] | None
     ) -> tuple[np.ndarray | None, np.ndarray | None]:
         """Sort `times` input.
 
@@ -234,7 +234,7 @@ def __init__(
         f2s: np.ndarray,
         times: np.ndarray | None,
         name: str,
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, indices, name)
 
         self.f1s = f1s.copy()
@@ -244,13 +244,13 @@ def __init__(
     def plot(
         self,
         nodes: int | tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 5.0,
-        minor_tick_intervals: int | float = 1.0,
+        major_tick_intervals: float = 5.0,
+        minor_tick_intervals: float = 1.0,
         plot_absolute: bool = False,
         mirror_cbar_range: bool = True,
         cbar_range_abs: tuple[float] | list[tuple[float]] | None = None,
@@ -400,13 +400,13 @@ def plot(
     def _sort_plot_inputs(
         self,
         nodes: int | tuple[int] | None,
-        f1s: tuple[int | float] | None,
-        f2s: tuple[int | float] | None,
-        times: tuple[int | float] | None,
+        f1s: tuple[float] | None,
+        f2s: tuple[float] | None,
+        times: tuple[float] | None,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
         plot_absolute: bool,
         mirror_cbar_range: bool,
         cbar_range_abs: tuple[float] | list[tuple[float]] | None,
@@ -469,8 +469,9 @@ def _sort_plot_inputs(
             cbar_range_phase,
         ]
         cbar_names = ["abs", "real", "imag", "phase"]
-        cbar_idx = 0
-        for cbar_range, cbar_name in zip(cbar_ranges, cbar_names):
+        for cbar_idx, (cbar_range, cbar_name) in enumerate(
+            zip(cbar_ranges, cbar_names)
+        ):
             if not isinstance(cbar_range, (list, tuple, type(None))):
                 raise TypeError(
                     f"`cbar_range_{cbar_name}` must be a list, tuple, or None."
@@ -490,7 +491,6 @@ def _sort_plot_inputs(
                         f"Limits in `cbar_range_{cbar_name}` must have length of 2."
                     )
             cbar_ranges[cbar_idx] = cbar_range
-            cbar_idx += 1
 
         return (nodes, f1s, f2s, f1_idcs, f2_idcs, times, time_idcs, cbar_ranges)
 
@@ -555,8 +555,8 @@ def _plot_results(
         time_idcs: np.ndarray | None,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
         plot_absolute: bool,
         mirror_cbar_range: bool,
         cbar_ranges: list[list[tuple[float | None]]],
@@ -711,8 +711,8 @@ def _plot_results(
     def _set_axis_ticks(
         self,
         axis: plt.Axes,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
     ) -> None:
         """Set major and minor tick intervals of x- and y-axes."""
         axis.xaxis.set_major_locator(plt.MultipleLocator(major_tick_intervals))
@@ -757,7 +757,7 @@ def __init__(
         f2s: np.ndarray,
         times: np.ndarray | None,
         name: str,
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, indices, name)
 
         self.f1s = f1s.copy()
@@ -767,13 +767,13 @@ def __init__(
     def plot(
         self,
         nodes: int | tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 5.0,
-        minor_tick_intervals: int | float = 1.0,
+        major_tick_intervals: float = 5.0,
+        minor_tick_intervals: float = 1.0,
         cbar_range: tuple[float] | list[tuple[float]] | None = None,
         show: bool = True,
     ) -> tuple[list[Figure], list[np.ndarray]]:
@@ -836,7 +836,7 @@ def plot(
         -----
         ``n_rows`` and ``n_cols`` of ``1`` will plot the results for each node on a new
         figure.
-        """  # noqa: E501
+        """
         nodes, f1s, f2s, f1_idcs, f2_idcs, times, time_idcs, cbar_range = (
             self._sort_plot_inputs(
                 nodes,
@@ -876,13 +876,13 @@ def plot(
     def _sort_plot_inputs(
         self,
         nodes: int | tuple[int] | None,
-        f1s: tuple[int | float] | None,
-        f2s: tuple[int | float] | None,
-        times: tuple[int | float] | None,
+        f1s: tuple[float] | None,
+        f2s: tuple[float] | None,
+        times: tuple[float] | None,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
         cbar_range: tuple[float] | list[tuple[float]] | None,
     ) -> tuple[
         tuple[int],
@@ -956,8 +956,8 @@ def _plot_results(
         time_idcs: np.ndarray | None,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
         cbar_range: list[tuple[float | None]],
     ) -> tuple[list[Figure], list[np.ndarray]]:
         """Plot results on the relevant figures/subplots."""
@@ -1043,8 +1043,8 @@ def _plot_results(
     def _set_axis_ticks(
         self,
         axis: plt.Axes,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
     ) -> None:
         """Set major and minor tick intervals of x- and y-axes."""
         axis.xaxis.set_major_locator(plt.MultipleLocator(major_tick_intervals))
@@ -1086,7 +1086,7 @@ def __init__(
         freq_bands: tuple[tuple[float]] | None,
         times: np.ndarray,
         name: str,
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, indices, name)
 
         self.tau = tau
@@ -1102,11 +1102,11 @@ def plot(
         self,
         nodes: int | tuple[int] | None = None,
         freq_bands: int | tuple[int] | None = None,
-        times: tuple[int | float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 500.0,
-        minor_tick_intervals: int | float = 100.0,
+        major_tick_intervals: float = 500.0,
+        minor_tick_intervals: float = 100.0,
         show: bool = True,
     ) -> tuple[list[Figure], list[np.ndarray]]:
         """Plot the results.
@@ -1189,7 +1189,7 @@ def _sort_plot_inputs(
         self,
         nodes: int | tuple[int] | None,
         freq_bands: int | tuple[int] | None,
-        times: tuple[int | float] | None,
+        times: tuple[float] | None,
         n_rows: int,
         n_cols: int,
         major_tick_intervals: float,
@@ -1290,8 +1290,8 @@ def _plot_results(
         time_idcs: np.ndarray,
         n_rows: int,
         n_cols: int,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
     ) -> tuple[list[Figure], list[np.ndarray]]:
         """Plot results on the relevant figures/subplots."""
         fig_i = 0
@@ -1385,8 +1385,8 @@ def _mark_delay(
     def _set_axis_ticks(
         self,
         axis: plt.Axes,
-        major_tick_intervals: int | float,
-        minor_tick_intervals: int | float,
+        major_tick_intervals: float,
+        minor_tick_intervals: float,
     ) -> None:
         """Set major and minor tick intervals of the x-axis."""
         axis.xaxis.set_major_locator(plt.MultipleLocator(major_tick_intervals))
diff --git a/src/pybispectra/utils/_process.py b/src/pybispectra/utils/_process.py
index ddc49f2..6a66dc5 100644
--- a/src/pybispectra/utils/_process.py
+++ b/src/pybispectra/utils/_process.py
@@ -39,7 +39,7 @@ def __init__(
         self,
         data: np.ndarray,
         freqs: np.ndarray,
-        sampling_freq: int | float,
+        sampling_freq: float,
         times: np.ndarray | None = None,
         verbose: bool = True,
     ) -> None:
@@ -49,7 +49,7 @@ def _sort_init_inputs(
         self,
         data: np.ndarray,
         freqs: np.ndarray,
-        sampling_freq: int | float,
+        sampling_freq: float,
         times: np.ndarray | None,
         verbose: bool,
     ) -> None:
@@ -135,11 +135,9 @@ def _sort_init_inputs(
     def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
         """Sort seed-target indices inputs."""
         if indices is None:
-            indices = tuple(
-                [
-                    tuple(np.tile(range(self._n_chans), self._n_chans).tolist()),
-                    tuple(np.repeat(range(self._n_chans), self._n_chans).tolist()),
-                ]
+            indices = (
+                tuple(np.tile(range(self._n_chans), self._n_chans).tolist()),
+                tuple(np.repeat(range(self._n_chans), self._n_chans).tolist()),
             )
         if not isinstance(indices, tuple):
             raise TypeError("`indices` must be a tuple.")
@@ -167,9 +165,7 @@ def _sort_indices(self, indices: tuple[tuple[int]] | None) -> None:
 
         self._n_cons = len(seeds)
 
-    def _sort_freqs(
-        self, f1s: tuple[int | float] | None, f2s: tuple[int | float] | None
-    ) -> None:
+    def _sort_freqs(self, f1s: tuple[float] | None, f2s: tuple[float] | None) -> None:
         """Sort frequency inputs."""
         check_f1s = True
         check_f2s = True
@@ -208,15 +204,14 @@ def _sort_freqs(
                 )
             self._f2s = self.freqs[f2_idcs]
 
-        if self.verbose:
-            if self._f1s.max() >= self._f2s.min():
-                warn(
-                    "At least one value in `f1s` is >= a value in `f2s`. The "
-                    "corresponding result(s) will have a value of NaN.",
-                    UserWarning,
-                )
+        if self.verbose and self._f1s.max() >= self._f2s.min():
+            warn(
+                "At least one value in `f1s` is >= a value in `f2s`. The corresponding "
+                "result(s) will have a value of NaN.",
+                UserWarning,
+            )
 
-    def _sort_tmin_tmax(self, times: tuple[int | float] | None) -> None:
+    def _sort_tmin_tmax(self, times: tuple[float] | None) -> None:
         """Sort time range inputs."""
         if times is None:
             times = (-np.inf, np.inf)
@@ -308,34 +303,33 @@ def _sort_indices(self, indices: tuple[tuple[int]]) -> None:
         """Sort seed-target indices inputs."""
         super()._sort_indices(indices)
 
-        if self.verbose:
-            if self._return_antisym and (
+        if (
+            self.verbose
+            and self._return_antisym
+            and (
                 any(seed == target for seed, target in zip(self._seeds, self._targets))
-            ):
-                warn(
-                    "The seed and target for at least one connection is the same "
-                    "channel. The corresponding antisymmetrised result(s) will be "
-                    "NaN-valued.",
-                    UserWarning,
-                )
+            )
+        ):
+            warn(
+                "The seed and target for at least one connection is the same channel. "
+                "The corresponding antisymmetrised result(s) will be NaN-valued.",
+                UserWarning,
+            )
 
-    def _sort_freqs(
-        self, f1s: tuple[int | float] | None, f2s: tuple[int | float] | None
-    ) -> None:
+    def _sort_freqs(self, f1s: tuple[float] | None, f2s: tuple[float] | None) -> None:
         """Sort frequency inputs."""
         super()._sort_freqs(f1s, f2s)
 
-        if self.verbose:
-            if any(
-                hfreq + lfreq not in self.freqs
-                for hfreq in self._f2s
-                for lfreq in self._f1s
-            ):
-                warn(
-                    "At least one value of `f2s` + `f1s` is not present in the "
-                    "frequencies. The corresponding result(s) will be NaN-valued.",
-                    UserWarning,
-                )
+        if self.verbose and any(
+            hfreq + lfreq not in self.freqs
+            for hfreq in self._f2s
+            for lfreq in self._f1s
+        ):
+            warn(
+                "At least one value of `f2s` + `f1s` is not present in the "
+                "frequencies. The corresponding result(s) will be NaN-valued.",
+                UserWarning,
+            )
 
 
 @njit
diff --git a/src/pybispectra/utils/_utils.py b/src/pybispectra/utils/_utils.py
index d455351..f1eedb3 100644
--- a/src/pybispectra/utils/_utils.py
+++ b/src/pybispectra/utils/_utils.py
@@ -8,7 +8,6 @@
 
 from pybispectra.utils._defaults import _precision
 
-
 # Aliases for type checking
 _int_like = (int, np.integer)
 _float_like = (float, np.floating)
@@ -109,7 +108,7 @@ def _get_block_indices(block_i: int, limit: int, n_jobs: int) -> np.ndarray:
 
 @njit
 def _fast_find_first(
-    vector: np.ndarray, value: int | float, start_idx: int = 0
+    vector: np.ndarray, value: float, start_idx: int = 0
 ) -> int:  # pragma: no cover
     """Quickly find the first index of a value in a 1D array using Numba.
 
diff --git a/src/pybispectra/utils/ged.py b/src/pybispectra/utils/ged.py
index b04db4c..9131313 100644
--- a/src/pybispectra/utils/ged.py
+++ b/src/pybispectra/utils/ged.py
@@ -1,14 +1,15 @@
 """Tools for performing generalised eigendecompositions."""
 
-from packaging.version import Version
 from multiprocessing import cpu_count
 from warnings import warn
 
 import numpy as np
 import scipy as sp
-from mne import Info, __version__ as mne_version
+from mne import Info
+from mne import __version__ as mne_version
 from mne.decoding import SSD
 from mne.time_frequency import csd_array_fourier, csd_array_multitaper
+from packaging.version import Version
 
 from pybispectra.utils._defaults import _precision
 from pybispectra.utils._utils import _create_mne_info, _int_like, _number_like
@@ -168,9 +169,9 @@ class SpatioSpectralFilter:
     def __init__(
         self,
         data: np.ndarray,
-        sampling_freq: int | float,
+        sampling_freq: float,
         verbose: bool = True,
-    ) -> None:  # noqa: D107
+    ) -> None:
         self.verbose = verbose
         self._sort_init_inputs(data, sampling_freq)
 
@@ -193,9 +194,9 @@ def _sort_init_inputs(self, data: np.ndarray, sampling_freq: float) -> None:
 
     def _sort_freq_bounds(
         self,
-        signal_bounds: tuple[int | float],
-        noise_bounds: tuple[int | float],
-        signal_noise_gap: int | float,
+        signal_bounds: tuple[float],
+        noise_bounds: tuple[float],
+        signal_noise_gap: float,
     ) -> None:
         """Sort frequency bound inputs."""
         if not isinstance(signal_bounds, tuple) or not all(
@@ -307,9 +308,9 @@ def _sort_csd_method(self, csd_method: str) -> None:
 
     def fit_ssd(
         self,
-        signal_bounds: tuple[int | float],
-        noise_bounds: tuple[int | float],
-        signal_noise_gap: int | float = 1.0,
+        signal_bounds: tuple[float],
+        noise_bounds: tuple[float],
+        signal_noise_gap: float = 1.0,
         bandpass_filter: bool = False,
         indices: tuple[int] | None = None,
         rank: int | None = None,
@@ -373,9 +374,9 @@ def fit_ssd(
 
     def _create_mne_filt_params(
         self,
-        signal_bounds: tuple[int | float],
-        noise_bounds: tuple[int | float],
-        signal_noise_gap: int | float,
+        signal_bounds: tuple[float],
+        noise_bounds: tuple[float],
+        signal_noise_gap: float,
     ) -> tuple[dict, dict]:
         """Create filter parameters for use with MNE's SSD implementation.
 
@@ -452,14 +453,14 @@ def _compute_ssd(
 
     def fit_hpmax(
         self,
-        signal_bounds: tuple[int | float],
-        noise_bounds: tuple[int | float],
+        signal_bounds: tuple[float],
+        noise_bounds: tuple[float],
         n_harmonics: int = -1,
         indices: tuple[int] | None = None,
         rank: int | None = None,
         csd_method: str = "multitaper",
         n_fft: int | None = None,
-        mt_bandwidth: int | float = 5.0,
+        mt_bandwidth: float = 5.0,
         mt_adaptive: bool = True,
         mt_low_bias: bool = True,
         n_jobs: int = 1,
@@ -563,7 +564,7 @@ def _compute_csd(
         self,
         csd_method: str,
         n_fft: int | None,
-        mt_bandwidth: int | float,
+        mt_bandwidth: float,
         mt_adaptive: bool,
         mt_low_bias: bool,
         n_jobs: int,
@@ -837,7 +838,7 @@ def fit_transform_hpmax(self, *args: tuple, **kwargs: dict) -> np.ndarray:
         return self.transform()
 
     def get_transformed_data(
-        self, min_ratio: int | float = -np.inf, copy: bool = True
+        self, min_ratio: float = -np.inf, copy: bool = True
     ) -> np.ndarray:
         """Return the transformed data.
 
diff --git a/src/pybispectra/utils/results.py b/src/pybispectra/utils/results.py
index 8cf3569..184fdd6 100644
--- a/src/pybispectra/utils/results.py
+++ b/src/pybispectra/utils/results.py
@@ -5,9 +5,9 @@
 import numpy as np
 from matplotlib.figure import Figure
 
+from pybispectra.utils._defaults import _precision
 from pybispectra.utils._plot import _PlotCFC, _PlotGeneral, _PlotTDE, _PlotWaveShape
 from pybispectra.utils._utils import _int_like
-from pybispectra.utils._defaults import _precision
 
 
 class _ResultsBase(ABC):
@@ -316,7 +316,7 @@ def __init__(
         f2s: np.ndarray,
         times: np.ndarray | None = None,
         name: str = "CFC",
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, (3, 4), name)
         self._sort_init_inputs(indices, f1s, f2s, times)
 
@@ -368,13 +368,13 @@ def _get_compact_results_child(self) -> tuple[np.ndarray, tuple[tuple[int]]]:
     def plot(
         self,
         nodes: int | tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 5.0,
-        minor_tick_intervals: int | float = 1.0,
+        major_tick_intervals: float = 5.0,
+        minor_tick_intervals: float = 1.0,
         cbar_range: tuple[float] | list[tuple[float]] | None = None,
         show: bool = True,
     ) -> tuple[list[Figure], list[np.ndarray]]:
@@ -509,9 +509,9 @@ class ResultsTDE(_ResultsBase):
 
     tau : ~numpy.ndarray, shape of [nodes, frequency_bands]
         Estimated time delay (in ms) for each connection and frequency band.
-    """  # noqa: E501
+    """
 
-    freq_bands: tuple[tuple[int | float]] = None
+    freq_bands: tuple[tuple[float]] = None
     _n_fbands: int = None
 
     def __repr__(self) -> str:
@@ -535,9 +535,9 @@ def __init__(
         data: np.ndarray,
         indices: tuple[tuple[int]],
         times: np.ndarray,
-        freq_bands: tuple[tuple[int | float]] | None = None,
+        freq_bands: tuple[tuple[float]] | None = None,
         name: str = "TDE",
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, (3,), name)
         self._sort_init_inputs(indices, times, freq_bands)
 
@@ -553,10 +553,7 @@ def __init__(
         )
 
     def _sort_init_inputs(
-        self,
-        indices: tuple[tuple[int]],
-        times: np.ndarray,
-        freq_bands: tuple[int | float],
+        self, indices: tuple[tuple[int]], times: np.ndarray, freq_bands: tuple[float]
     ) -> None:
         """Sort inputs to the object."""
         super()._sort_indices_seeds_targets(indices)
@@ -575,7 +572,7 @@ def _sort_times(self, times: np.ndarray) -> None:
 
         self.times = times
 
-    def _sort_freq_bands(self, freq_bands: tuple[tuple[int | float]]) -> None:
+    def _sort_freq_bands(self, freq_bands: tuple[tuple[float]]) -> None:
         """Sort ``freq_bands`` input."""
         if freq_bands is not None:
             if not isinstance(freq_bands, tuple):
@@ -621,11 +618,11 @@ def plot(
         self,
         nodes: int | tuple[int] | None = None,
         freq_bands: int | tuple[int] | None = None,
-        times: tuple[int | float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 500.0,
-        minor_tick_intervals: int | float = 100.0,
+        major_tick_intervals: float = 500.0,
+        minor_tick_intervals: float = 100.0,
         show: bool = True,
     ) -> tuple[list[Figure], list[np.ndarray]]:
         """Plot the results.
@@ -780,7 +777,7 @@ def __init__(
         f2s: np.ndarray,
         times: np.ndarray | None = None,
         name: str = "Waveshape",
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, (3, 4), name)
         self._sort_init_inputs(indices, f1s, f2s, times)
 
@@ -831,13 +828,13 @@ def get_results(self, copy: bool = True) -> np.ndarray:
     def plot(
         self,
         nodes: int | tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 5.0,
-        minor_tick_intervals: int | float = 1.0,
+        major_tick_intervals: float = 5.0,
+        minor_tick_intervals: float = 1.0,
         plot_absolute: bool = False,
         mirror_cbar_range: bool = True,
         cbar_range_abs: tuple[float] | list[tuple[float]] | None = None,
@@ -1048,7 +1045,7 @@ def __init__(
         f2s: np.ndarray,
         times: np.ndarray | None = None,
         name: str = "General",
-    ) -> None:  # noqa: D107
+    ) -> None:
         super().__init__(data, (3, 4), name)
         self._sort_init_inputs(indices, f1s, f2s, times)
 
@@ -1145,13 +1142,13 @@ def _get_compact_results_child(self) -> tuple[np.ndarray, tuple[tuple[int]]]:
     def plot(
         self,
         nodes: int | tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         n_rows: int = 1,
         n_cols: int = 1,
-        major_tick_intervals: int | float = 5.0,
-        minor_tick_intervals: int | float = 1.0,
+        major_tick_intervals: float = 5.0,
+        minor_tick_intervals: float = 1.0,
         plot_absolute: bool = False,
         mirror_cbar_range: bool = True,
         cbar_range_abs: tuple[float] | list[tuple[float]] | None = None,
@@ -1254,7 +1251,7 @@ def plot(
         -----
         ``n_rows`` and ``n_cols`` of ``1`` will plot the results for each node on a new
         figure.
-        """  # noqa: E501
+        """
         figures, axes = self._plotting.plot(
             nodes=nodes,
             f1s=f1s,
diff --git a/src/pybispectra/utils/utils.py b/src/pybispectra/utils/utils.py
index aa7635b..0ba7134 100644
--- a/src/pybispectra/utils/utils.py
+++ b/src/pybispectra/utils/utils.py
@@ -1,13 +1,14 @@
 """Public tools for handling data and processing results."""
 
+from collections.abc import Callable
 from multiprocessing import cpu_count
-from typing import Callable
-from packaging.version import Version
 
-import pooch
 import numpy as np
+import pooch
 import scipy as sp
-from mne import time_frequency, __version__ as mne_version
+from mne import __version__ as mne_version
+from mne import time_frequency
+from packaging.version import Version
 
 from pybispectra import __version__ as version
 from pybispectra.utils._defaults import _precision
@@ -16,7 +17,7 @@
 
 def compute_fft(
     data: np.ndarray,
-    sampling_freq: int | float,
+    sampling_freq: float,
     n_points: int | None = None,
     window: str = "hanning",
     n_jobs: int = 1,
@@ -100,7 +101,7 @@ def compute_fft(
 
 def _compute_fft_input_checks(
     data: np.ndarray,
-    sampling_freq: int | float,
+    sampling_freq: float,
     n_points: int | None,
     window: str,
     n_jobs: int,
@@ -156,13 +157,13 @@ def _compute_fft_input_checks(
 
 def compute_tfr(
     data: np.ndarray,
-    sampling_freq: int | float,
+    sampling_freq: float,
     freqs: np.ndarray,
     tfr_mode: str = "morlet",
-    n_cycles: np.ndarray | int | float = 7.0,
+    n_cycles: np.ndarray | float = 7.0,
     zero_mean_wavelets: bool | None = None,
     use_fft: bool = True,
-    multitaper_time_bandwidth: int | float = 4.0,
+    multitaper_time_bandwidth: float = 4.0,
     output: str = "power",
     n_jobs: int = 1,
     verbose: bool = True,
@@ -206,10 +207,10 @@ def compute_tfr(
     output : ``"power"`` | ``"complex"`` (default ``"power"``)
         Type of TFR output to return.
 
+        .. versionadded:: 1.3
         .. note::
             If ``output = "complex"`` and ``tfr_mode = "multitaper"``, returning weights
             for each taper requires MNE version 1.10 or higher.
-        .. versionadded:: 1.3
 
     n_jobs : int (default ``1``)
         Number of jobs to run in parallel. If ``-1``, all available CPUs are used.
@@ -290,13 +291,13 @@ def compute_tfr(
 
 def _compute_tfr_input_checks(
     data: np.ndarray,
-    sampling_freq: int | float,
+    sampling_freq: float,
     freqs: np.ndarray,
     tfr_mode: str,
-    n_cycles: np.ndarray | int | float,
+    n_cycles: np.ndarray | float,
     zero_mean_wavelets: bool | None,
     use_fft: bool,
-    multitaper_time_bandwidth: int | float,
+    multitaper_time_bandwidth: float,
     output: str,
     n_jobs: int,
     verbose: bool,
@@ -362,9 +363,10 @@ def _compute_tfr_input_checks(
     if not isinstance(use_fft, bool):
         raise TypeError("`use_fft` must be a bool.")
 
-    if tfr_mode == "multitaper":
-        if not isinstance(multitaper_time_bandwidth, _number_like):
-            raise TypeError("`multitaper_time_bandwidth` must be an int or a float.")
+    if tfr_mode == "multitaper" and not isinstance(
+        multitaper_time_bandwidth, _number_like
+    ):
+        raise TypeError("`multitaper_time_bandwidth` must be an int or a float.")
 
     outputs = ["power", "complex"]
     if not isinstance(output, str):
@@ -394,7 +396,7 @@ def _compute_tfr_input_checks(
     return tfr_func, return_weights, n_jobs
 
 
-def compute_rank(data: np.ndarray, sv_tol: int | float = 1e-5) -> int:
+def compute_rank(data: np.ndarray, sv_tol: float = 1e-5) -> int:
     """Compute the minimum rank of data from non-zero singular values.
 
     Parameters
@@ -536,7 +538,7 @@ def get_example_data_paths(name: str, verbose: bool = False) -> str:
     If the file is not found in the local cache (see :func:`pooch.os_cache` for the
     location), it will be downloaded automatically.
     """
-    if name not in DATASETS.keys():
+    if name not in DATASETS:
         raise ValueError(f"`name` must be one of: {list(DATASETS.keys())}")
 
     return _pooch.fetch(fname=DATASETS[name], progressbar=verbose)
diff --git a/src/pybispectra/waveshape/waveshape.py b/src/pybispectra/waveshape/waveshape.py
index 61bd186..79a9641 100644
--- a/src/pybispectra/waveshape/waveshape.py
+++ b/src/pybispectra/waveshape/waveshape.py
@@ -8,8 +8,8 @@
     _compute_threenorm,
     _ProcessBispectrum,
 )
-from pybispectra.utils.results import ResultsWaveShape
 from pybispectra.utils._utils import _compute_in_parallel, _int_like
+from pybispectra.utils.results import ResultsWaveShape
 
 np.seterr(divide="ignore", invalid="ignore")  # no warning for NaN division
 
@@ -78,7 +78,7 @@ class WaveShape(_ProcessBispectrum):
     References
     ----------
     .. footbibliography::
-    """  # noqa: E501
+    """
 
     _return_nonorm = False
     _return_threenorm = False
@@ -86,9 +86,9 @@ class WaveShape(_ProcessBispectrum):
     def compute(
         self,
         indices: tuple[int] | None = None,
-        f1s: tuple[int | float] | None = None,
-        f2s: tuple[int | float] | None = None,
-        times: tuple[int | float] | None = None,
+        f1s: tuple[float] | None = None,
+        f2s: tuple[float] | None = None,
+        times: tuple[float] | None = None,
         norm: bool | tuple[bool] = True,
         n_jobs: int = 1,
     ) -> None: