chore: update pre-commit hooks

.pre-commit-config.yaml

@@ -5,18 +5,18 @@ ci:
 
 repos:
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: "24.3.0"
+    rev: "24.8.0"
     hooks:
       - id: black-jupyter
 
   - repo: https://github.com/adamchainz/blacken-docs
-    rev: "1.16.0"
+    rev: "1.18.0"
     hooks:
       - id: blacken-docs
         additional_dependencies: [black==23.*]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: "v4.5.0"
+    rev: "v5.0.0"
     hooks:
       - id: check-added-large-files
         args: ["--maxkb=10000"]
@@ -47,7 +47,7 @@ repos:
   #       args: [--prose-wrap=always]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.3.4"
+    rev: "v0.6.9"
     hooks:
       - id: ruff
         args: ["--fix", "--show-fixes"]
@@ -63,7 +63,7 @@ repos:
   #         - pytest
 
   - repo: https://github.com/codespell-project/codespell
-    rev: "v2.2.6"
+    rev: "v2.3.0"
     hooks:
       - id: codespell
         types_or: [python, rst, markdown]
@@ -84,12 +84,12 @@ repos:
   #       exclude: .pre-commit-config.yaml
 
   - repo: https://github.com/abravalheri/validate-pyproject
-    rev: v0.16
+    rev: v0.20.2
     hooks:
       - id: validate-pyproject
 
   - repo: https://github.com/python-jsonschema/check-jsonschema
-    rev: 0.28.1
+    rev: 0.29.3
     hooks:
       - id: check-dependabot
       - id: check-github-workflows

CheckOutputs.ipynb

@@ -6,6 +6,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from __future__ import annotations\n",
+    "\n",
     "import pandas as pd"
    ]
   },

src/HH4b/BDT/BDTSemiBoosted.ipynb

@@ -15,17 +15,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
+    "from __future__ import annotations\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "import pandas as pd\n",
+    "import vector\n",
+    "from sklearn.metrics import auc, roc_curve\n",
     "from sklearn.model_selection import train_test_split\n",
     "from xgboost import XGBClassifier\n",
-    "from sklearn.metrics import accuracy_score, roc_auc_score\n",
-    "import HH4b.utils as utils\n",
-    "import HH4b.plotting as plotting\n",
-    "from sklearn.metrics import roc_curve, auc\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
-    "import vector"
+    "\n",
+    "import HH4b.utils as utils"
    ]
   },
   {
@@ -563,7 +563,7 @@
     "\n",
     "samples_loaded = list(events_dict.keys())\n",
     "keys_loaded = list(events_dict[samples_loaded[0]].keys())\n",
-    "print(f\"Keys in events_dict\")\n",
+    "print(\"Keys in events_dict\")\n",
     "for i in keys_loaded:\n",
     "    print(i)"
    ]

src/HH4b/BDT/BDT_HH4b.ipynb

@@ -15,17 +15,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
+    "from __future__ import annotations\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "import pandas as pd\n",
+    "import vector\n",
+    "from sklearn.metrics import auc, roc_curve\n",
     "from sklearn.model_selection import train_test_split\n",
     "from xgboost import XGBClassifier\n",
-    "from sklearn.metrics import accuracy_score, roc_auc_score\n",
-    "import HH4b.utils as utils\n",
-    "import HH4b.plotting as plotting\n",
-    "from sklearn.metrics import roc_curve, auc\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
-    "import vector"
+    "\n",
+    "import HH4b.utils as utils"
    ]
   },
   {
@@ -136,7 +136,7 @@
     "\n",
     "samples_loaded = list(events_dict.keys())\n",
     "keys_loaded = list(events_dict[samples_loaded[0]].keys())\n",
-    "print(f\"Keys in events_dict\")\n",
+    "print(\"Keys in events_dict\")\n",
     "for i in keys_loaded:\n",
     "    print(i)"
    ]

src/HH4b/BDT/BDT_HH4b_Collin_Soper_Angle.ipynb

@@ -15,17 +15,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
+    "from __future__ import annotations\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "import pandas as pd\n",
+    "import vector\n",
+    "from sklearn.metrics import auc, roc_curve\n",
     "from sklearn.model_selection import train_test_split\n",
     "from xgboost import XGBClassifier\n",
-    "from sklearn.metrics import accuracy_score, roc_auc_score\n",
-    "import HH4b.utils as utils\n",
-    "import HH4b.plotting as plotting\n",
-    "from sklearn.metrics import roc_curve, auc\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
-    "import vector"
+    "\n",
+    "import HH4b.utils as utils"
    ]
   },
   {
@@ -563,7 +563,7 @@
     "\n",
     "samples_loaded = list(events_dict.keys())\n",
     "keys_loaded = list(events_dict[samples_loaded[0]].keys())\n",
-    "print(f\"Keys in events_dict\")\n",
+    "print(\"Keys in events_dict\")\n",
     "for i in keys_loaded:\n",
     "    print(i)"
    ]

src/HH4b/boosted/BDTRun2Check.ipynb

@@ -6,16 +6,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from __future__ import annotations\n",
+    "\n",
     "import os\n",
+    "import pickle\n",
+    "\n",
+    "import numpy as np\n",
     "import pandas as pd\n",
     "import uproot\n",
-    "import numpy as np\n",
-    "import pickle\n",
     "import vector\n",
     "\n",
     "from HH4b.postprocessing import bb_assignment\n",
-    "from HH4b.utils import ShapeVar, CUT_MAX_VAL, load_samples\n",
-    "from HH4b.utils import get_feat, make_vector"
+    "from HH4b.utils import get_feat, load_samples, make_vector"
    ]
   },
   {
@@ -766,8 +768,8 @@
    "source": [
     "import hist\n",
     "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
     "import matplotlib.ticker as mticker\n",
+    "import mplhep as hep\n",
     "\n",
     "hep.style.use([\"CMS\", \"firamath\"])\n",
     "\n",

src/HH4b/boosted/BDT_boosted.ipynb

@@ -16,27 +16,20 @@
     }
    ],
    "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
+    "from __future__ import annotations\n",
     "\n",
     "import hist\n",
-    "import pickle\n",
-    "\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from xgboost import XGBClassifier\n",
-    "from sklearn.metrics import accuracy_score, roc_auc_score\n",
-    "from sklearn.metrics import roc_curve, auc\n",
-    "\n",
-    "import HH4b.utils as utils\n",
-    "import HH4b.plotting as plotting\n",
-    "\n",
     "import matplotlib.pyplot as plt\n",
+    "import matplotlib.ticker as mticker\n",
     "import mplhep as hep\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
     "import vector\n",
+    "from sklearn.metrics import accuracy_score, auc, roc_auc_score, roc_curve\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from xgboost import XGBClassifier\n",
     "\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
-    "import matplotlib.ticker as mticker\n",
+    "import HH4b.utils as utils\n",
     "\n",
     "hep.style.use([\"CMS\", \"firamath\"])\n",
     "\n",

src/HH4b/boosted/DataMCPlots2018.ipynb

@@ -24,11 +24,12 @@
    "outputs": [],
    "source": [
     "# import utilities for post-process\n",
-    "import utils\n",
+    "from __future__ import annotations\n",
     "\n",
-    "import vector\n",
+    "import numpy as np\n",
     "import pandas as pd\n",
-    "import numpy as np"
+    "import utils\n",
+    "import vector"
    ]
   },
   {
@@ -278,7 +279,7 @@
    "source": [
     "samples_loaded = list(events_dict.keys())\n",
     "keys_loaded = list(events_dict[samples_loaded[0]].keys())\n",
-    "print(f\"Keys in events_dict\")\n",
+    "print(\"Keys in events_dict\")\n",
     "print(keys_loaded)"
    ]
   },

src/HH4b/boosted/FitB_0.95.ipynb

@@ -20,25 +20,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import vector\n",
-    "import os\n",
-    "from xgboost import XGBClassifier\n",
-    "from pathlib import Path\n",
+    "from __future__ import annotations\n",
     "\n",
-    "import HH4b.utils as utils\n",
-    "from HH4b.utils import ShapeVar\n",
-    "import HH4b.plotting as plotting\n",
-    "from HH4b.postprocessing import PostProcess, Region\n",
-    "import HH4b.postprocessing as postprocessing\n",
-    "from HH4b.hh_vars import samples, years, samples_run3\n",
+    "from pathlib import Path\n",
     "\n",
-    "import hist\n",
     "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
     "import matplotlib.ticker as mticker\n",
-    "import importlib\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "import HH4b.plotting as plotting\n",
+    "from HH4b.hh_vars import samples\n",
     "\n",
     "formatter = mticker.ScalarFormatter(useMathText=True)\n",
     "formatter.set_powerlimits((-3, 3))"
@@ -281,10 +273,7 @@
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "\n",
-    "from matplotlib import cm\n",
-    "from matplotlib.ticker import LinearLocator"
+    "import numpy as np"
    ]
   },
   {
@@ -317,7 +306,7 @@
     "\n",
     "# select data in the plotting region\n",
     "Txbb_cond = Txbb >= txbb_low\n",
-    "BDT_cond = BDT >= bdt_low\n",
+    "BDT_cond = bdt_low <= BDT\n",
     "cond = Txbb_cond & BDT_cond\n",
     "\n",
     "Txbb = Txbb[cond]\n",
@@ -1464,7 +1453,7 @@
     "\n",
     "# select data in the plotting region\n",
     "Txbb_cond = Txbb >= txbb_low\n",
-    "BDT_cond = BDT >= bdt_low\n",
+    "BDT_cond = bdt_low <= BDT\n",
     "cond = Txbb_cond & BDT_cond\n",
     "\n",
     "Txbb = Txbb[cond]\n",

src/HH4b/boosted/FitB_0.95_PoissonCDF_separate.ipynb

@@ -13,6 +13,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from __future__ import annotations\n",
+    "\n",
     "B_max = 150435.0  # obtained from nevents_regionB at (0,0)"
    ]
   },
@@ -29,25 +31,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import vector\n",
-    "import os\n",
-    "from xgboost import XGBClassifier\n",
-    "from pathlib import Path\n",
-    "\n",
-    "import HH4b.utils as utils\n",
-    "from HH4b.utils import ShapeVar\n",
-    "import HH4b.plotting as plotting\n",
-    "from HH4b.postprocessing import PostProcess, Region\n",
-    "import HH4b.postprocessing as postprocessing\n",
-    "from HH4b.hh_vars import samples, years, samples_run3\n",
-    "\n",
-    "import hist\n",
+    "\n",
     "import matplotlib.pyplot as plt\n",
-    "import mplhep as hep\n",
     "import matplotlib.ticker as mticker\n",
-    "import importlib\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
     "\n",
     "formatter = mticker.ScalarFormatter(useMathText=True)\n",
     "formatter.set_powerlimits((-3, 3))"
@@ -85,10 +73,7 @@
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "\n",
-    "from matplotlib import cm\n",
-    "from matplotlib.ticker import LinearLocator"
+    "import numpy as np"
    ]
   },
   {
@@ -121,7 +106,7 @@
     "\n",
     "# select data in the plotting region\n",
     "Txbb_cond = Txbb >= txbb_low\n",
-    "BDT_cond = BDT >= bdt_low\n",
+    "BDT_cond = bdt_low <= BDT\n",
     "cond = Txbb_cond & BDT_cond\n",
     "\n",
     "Txbb = Txbb[cond]\n",
@@ -243,8 +228,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from scipy.special import gammainc, gamma\n",
-    "from scipy.optimize import curve_fit"
+    "from scipy.optimize import curve_fit\n",
+    "from scipy.special import gamma, gammainc"
    ]
   },
   {