[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
   # ruff PyBispectra
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.15.22
+    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: v0.15.22
+    rev: v0.16.0
     hooks:
       - id: ruff
         name: ruff lint examples

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

pyproject.toml

@@ -126,7 +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]

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.

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)

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.

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.

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,)):

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