chore: pre-commit autoupdate (#322)

* chore: pre-commit autoupdate

updates:
- [github.com/psf/black: 23.12.1 → 24.3.0](psf/black@23.12.1...24.3.0)
- [github.com/PyCQA/flake8: 6.1.0 → 7.0.0](PyCQA/flake8@6.1.0...7.0.0)
- [github.com/kynan/nbstripout: 0.6.1 → 0.7.1](kynan/nbstripout@0.6.1...0.7.1)
- [github.com/nbQA-dev/nbQA: 1.7.1 → 1.8.5](nbQA-dev/nbQA@1.7.1...1.8.5)

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 - repo: https://github.com/psf/black
-  rev: 23.12.1
+  rev: 24.3.0
   hooks:
     - id: black
       language_version: python3
@@ -25,20 +25,20 @@ repos:
       args: [--in-place]
       exclude: mkdocs_macros.py
 - repo: https://github.com/PyCQA/flake8
-  rev: 6.1.0
+  rev: 7.0.0
   hooks:
     - id: flake8
       # additional_dependencies: [flake8-docstrings, flake8-bugbear, flake8-spellcheck, flake8-import-order]
 - repo: https://github.com/kynan/nbstripout
-  rev: 0.6.1
+  rev: 0.7.1
   hooks:
     - id: nbstripout
 -   repo: https://github.com/asottile/blacken-docs
     rev: 1.16.0
     hooks:
     - id: blacken-docs
 - repo: https://github.com/nbQA-dev/nbQA
-  rev: 1.7.1
+  rev: 1.8.5
   hooks:
     - id: nbqa-black
       args: [--nbqa-mutate]

docs/examples/merging-cost-functions.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e07961b1-a84a-4749-ad7f-0d3fc617efd3",
+   "id": "0",
    "metadata": {
     "tags": []
    },
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dbdf7dce-47f1-415b-9d89-e2899b1f4e6c",
+   "id": "1",
    "metadata": {},
    "source": [
     "## Setup\n",
@@ -47,7 +47,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0998be59-5a69-4617-b931-2c9d4fd6595d",
+   "id": "2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "11388466-a41d-4e44-9789-0161e3cc5e88",
+   "id": "3",
    "metadata": {},
    "source": [
     "The merging procedure of cost functions is applied on the following 2D toy signal, where each dimension contains three mean-shifts.\n",
@@ -82,7 +82,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "84089dda-f638-42a2-a429-b5365860cd1f",
+   "id": "4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -104,7 +104,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e43b33e1-f056-4d23-ad58-d7e5da754347",
+   "id": "5",
    "metadata": {},
    "source": [
     "## Detection with a single cost function\n",
@@ -115,7 +115,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "64e93a45-7a4c-42f8-b7aa-95365e831203",
+   "id": "6",
    "metadata": {
     "tags": []
    },
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "78eaafde-ae84-4ff1-9c80-426040185d90",
+   "id": "7",
    "metadata": {},
    "source": [
     "Combining this cost function with the [window search method](../user-guide/detection/window.md) yields the following change-points.\n",
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "63af12a7-bd4a-4732-92eb-a8599999a82c",
+   "id": "8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -194,7 +194,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "dfceeaa3-2c26-48ea-8af9-5cfa8d0fcdbe",
+   "id": "9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -218,7 +218,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ce63eac0-5cd5-474a-bafa-2b4c53425d57",
+   "id": "10",
    "metadata": {},
    "source": [
     "Observe that, depending on the considered cost function (`CostL2OnSingleDim(dim=0)` or `CostL2OnSingleDim(dim=1)`), the detected changes are not the same even though the input signal is the same.\n",
@@ -229,7 +229,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "03da2de4-9339-4280-afa8-b04d094213e4",
+   "id": "11",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -242,7 +242,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5b967d36-1dfa-42e8-a5e1-3085d4325624",
+   "id": "12",
    "metadata": {},
    "source": [
     "\n",
@@ -251,7 +251,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7fb9ee7e-469e-4a11-a48b-6e3f152aa6d1",
+   "id": "13",
    "metadata": {},
    "source": [
     "## Detection with an aggregated cost function\n",
@@ -265,7 +265,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1b8ffd8d-8d41-4189-ba25-16ddaf09c063",
+   "id": "14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -298,7 +298,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "71c261aa-9287-4e47-b331-28ddb3a66c06",
+   "id": "15",
    "metadata": {},
    "source": [
     "### Union\n",
@@ -312,7 +312,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f1571dca-0674-45d8-b9aa-e4200eed3e78",
+   "id": "16",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -339,7 +339,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ffff426b-2ab7-41fb-972c-2ef9ade72ed8",
+   "id": "17",
    "metadata": {},
    "source": [
     "## Conclusion\n",
@@ -355,7 +355,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1a6d5256-67f3-4d3c-8192-4043ff6abce5",
+   "id": "18",
    "metadata": {},
    "source": [
     "## Authors\n",
@@ -365,7 +365,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e100e594-eced-42db-9841-4bff2d737c1d",
+   "id": "19",
    "metadata": {},
    "source": [
     "## References\n",

docs/user-guide/costs/costcustom.md

@@ -25,7 +25,6 @@ from ruptures.base import BaseCost
 
 
 class MyCost(BaseCost):
-
     """Custom cost for exponential signals."""
 
     # The 2 following attributes must be specified for compatibility.

src/ruptures/base.py

@@ -3,6 +3,7 @@
 [`BaseEstimator`][ruptures.base.BaseEstimator] and
 [`BaseCost`][ruptures.base.BaseCost] respectively.
 """
+
 import abc
 from ruptures.utils import pairwise
 

src/ruptures/costs/costclinear.py

@@ -1,4 +1,5 @@
 r"""Continuous linear change."""
+
 import numpy as np
 
 from ruptures.base import BaseCost

src/ruptures/costs/costcosine.py

@@ -1,4 +1,5 @@
 r"""CostCosine (kernel change point detection with the cosine similarity)"""
+
 import numpy as np
 from ruptures.base import BaseCost
 from ruptures.costs import NotEnoughPoints

src/ruptures/costs/costl1.py

@@ -1,4 +1,5 @@
 r"""CostL1 (least absolute deviation)"""
+
 import numpy as np
 
 from ruptures.base import BaseCost

src/ruptures/costs/costl2.py

@@ -1,4 +1,5 @@
 r"""CostL2 (least squared deviation)"""
+
 from ruptures.costs import NotEnoughPoints
 
 from ruptures.base import BaseCost

src/ruptures/costs/costlinear.py

@@ -1,4 +1,5 @@
 r"""Linear model change."""
+
 from numpy.linalg import lstsq
 
 from ruptures.base import BaseCost

src/ruptures/costs/costml.py

@@ -1,4 +1,5 @@
 r"""Change detection with a Mahalanobis-type metric."""
+
 import numpy as np
 from numpy.linalg import inv
 

src/ruptures/costs/costnormal.py

@@ -1,4 +1,5 @@
 r"""Gaussian process changes (CostNormal)"""
+
 import warnings
 
 import numpy as np

src/ruptures/costs/costrank.py

@@ -1,4 +1,5 @@
 r"""Rank-based cost function (CostRank)"""
+
 import numpy as np
 from numpy.linalg import pinv, LinAlgError
 from scipy.stats.mstats import rankdata

src/ruptures/costs/costrbf.py

@@ -1,4 +1,5 @@
 r"""Kernelized mean change."""
+
 import numpy as np
 from scipy.spatial.distance import pdist, squareform
 

src/ruptures/datasets/__init__.py

@@ -1,4 +1,5 @@
 """Utility functions to load or generate data sets."""
+
 from .pw_constant import pw_constant
 from .pw_linear import pw_linear
 from .pw_normal import pw_normal

src/ruptures/datasets/pw_linear.py

@@ -1,4 +1,5 @@
 r"""Shift in linear model."""
+
 import numpy as np
 
 from . import pw_constant

src/ruptures/datasets/pw_normal.py

@@ -1,4 +1,5 @@
 """2D piecewise Gaussian process (pw_normal)"""
+
 from itertools import cycle
 
 import numpy as np

src/ruptures/datasets/pw_wavy.py

@@ -1,4 +1,5 @@
 """Piecewise sinusoidal (pw_wavy)"""
+
 from itertools import cycle
 
 import numpy as np

src/ruptures/detection/binseg.py

@@ -1,4 +1,5 @@
 r"""Binary segmentation."""
+
 from functools import lru_cache
 
 import numpy as np

src/ruptures/detection/bottomup.py

@@ -1,4 +1,5 @@
 r"""Bottom-up segmentation."""
+
 import heapq
 from bisect import bisect_left
 from functools import lru_cache

src/ruptures/detection/dynp.py

@@ -1,4 +1,5 @@
 r"""Dynamic programming."""
+
 from functools import lru_cache
 
 from ruptures.utils import sanity_check

src/ruptures/detection/pelt.py

@@ -1,4 +1,5 @@
 r"""Pelt."""
+
 from math import floor
 
 from ruptures.costs import cost_factory

src/ruptures/detection/window.py

@@ -1,6 +1,5 @@
 r"""Window-based change point detection."""
 
-
 import numpy as np
 from scipy.signal import argrelmax
 

src/ruptures/metrics/__init__.py

@@ -16,6 +16,7 @@
     display
 
 """
+
 from .hausdorff import hausdorff
 from .timeerror import meantime
 from .precisionrecall import precision_recall

src/ruptures/metrics/hamming.py

@@ -1,4 +1,5 @@
 """Hamming metric for segmentation."""
+
 from ruptures.metrics.randindex import randindex
 
 

src/ruptures/metrics/hausdorff.py

@@ -1,4 +1,5 @@
 r"""Hausdorff metric."""
+
 import numpy as np
 from scipy.spatial.distance import cdist
 from ruptures.metrics.sanity_check import sanity_check

src/ruptures/metrics/precisionrecall.py

@@ -1,4 +1,5 @@
 r"""Precision and recall."""
+
 from itertools import product
 
 from ruptures.metrics.sanity_check import sanity_check

src/ruptures/metrics/randindex.py

@@ -1,4 +1,5 @@
 r"""Rand index (`randindex`)"""
+
 from ruptures.metrics.sanity_check import sanity_check
 
 

src/ruptures/metrics/timeerror.py

@@ -1,4 +1,5 @@
 """Mean time error."""
+
 import numpy as np
 from scipy.spatial.distance import cdist
 

src/ruptures/utils/__init__.py

@@ -1,4 +1,5 @@
 """Import utils functions."""
+
 from ruptures.utils._utils.convert_path_matrix import from_path_matrix_to_bkps_list
 
 from .bnode import Bnode

src/ruptures/utils/bnode.py

@@ -1,4 +1,5 @@
 """Binary node."""
+
 import functools
 import numpy as np