From 941031a352536085088c4e07c634a540c301de3a Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 18 Mar 2024 17:10:27 +0000 Subject: [PATCH 1/3] chore: update pre-commit hooks MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/psf/black-pre-commit-mirror: 24.2.0 → 24.3.0](https://github.com/psf/black-pre-commit-mirror/compare/24.2.0...24.3.0) - [github.com/astral-sh/ruff-pre-commit: v0.3.2 → v0.3.3](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.2...v0.3.3) - [github.com/shellcheck-py/shellcheck-py: v0.9.0.6 → v0.10.0.1](https://github.com/shellcheck-py/shellcheck-py/compare/v0.9.0.6...v0.10.0.1) --- .pre-commit-config.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 520c889a..4d42a896 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -4,7 +4,7 @@ ci: repos: - repo: https://github.com/psf/black-pre-commit-mirror - rev: "24.2.0" + rev: "24.3.0" hooks: - id: black-jupyter args: [--line-length=100] @@ -47,7 +47,7 @@ repos: # args: [--prose-wrap=always] - repo: https://github.com/astral-sh/ruff-pre-commit - rev: "v0.3.2" + rev: "v0.3.3" hooks: - id: ruff args: ["--fix", "--show-fixes"] @@ -70,7 +70,7 @@ repos: args: ["--ignore-words", ".codespell-whitelist.txt"] - repo: https://github.com/shellcheck-py/shellcheck-py - rev: "v0.9.0.6" + rev: "v0.10.0.1" hooks: - id: shellcheck From 359a12abb384640196a4e621a7140a2bc19c5683 Mon Sep 17 00:00:00 2001 From: Raghav Kansal Date: Mon, 18 Mar 2024 15:55:03 -0500 Subject: [PATCH 2/3] Quarterly pre-commit updates --- .pre-commit-config.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 4d42a896..c1acd148 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,6 +1,7 @@ ci: autoupdate_commit_msg: "chore: update pre-commit hooks" autofix_commit_msg: "style: pre-commit fixes" + autoupdate_schedule: quarterly repos: - repo: https://github.com/psf/black-pre-commit-mirror From eb182edc21d064c873974886376e5e970465e5e5 Mon Sep 17 00:00:00 2001 From: rkansal47 Date: Tue, 19 Mar 2024 19:24:52 -0500 Subject: [PATCH 3/3] add preselection to matching eff --- .../VBF_binder/VBFKinematicsStudyRK.ipynb | 136 ++++++++++++++---- 1 file changed, 109 insertions(+), 27 deletions(-) diff --git a/src/HHbbVV/VBF_binder/VBFKinematicsStudyRK.ipynb b/src/HHbbVV/VBF_binder/VBFKinematicsStudyRK.ipynb index ce390363..ebd7a1dd 100644 --- a/src/HHbbVV/VBF_binder/VBFKinematicsStudyRK.ipynb +++ b/src/HHbbVV/VBF_binder/VBFKinematicsStudyRK.ipynb @@ -49,7 +49,8 @@ "source": [ "events = nanoevents.NanoEventsFactory.from_root(\n", " # \"root://cmseos.fnal.gov///store/user/lpcpfnano/cmantill/v2_3/2018/HH/VBF_HHTobbVV_CV_1_C2V__C3_1_TuneCP5_13TeV-madgraph-pythia8/VBF_HHTobbVV_CV_1_C2V_1_C3_1/220808_150149/0000/nano_mc2018_1-1.root\",\n", - " \"root://cmseos.fnal.gov///store/user/lpcpfnano/cmantill/v2_3/2018/HH/VBF_HHTobbVV_CV_1_C2V_0_C3_1_TuneCP5_13TeV-madgraph-pythia8/VBF_HHTobbVV_CV_1_C2V_0_C3_1/220808_150000/0000/nano_mc2018_1-1.root\",\n", + " # \"root://cmseos.fnal.gov///store/user/lpcpfnano/cmantill/v2_3/2018/HH/VBF_HHTobbVV_CV_1_C2V_0_C3_1_TuneCP5_13TeV-madgraph-pythia8/VBF_HHTobbVV_CV_1_C2V_0_C3_1/220808_150000/0000/nano_mc2018_1-1.root\",\n", + " \"/uscms/home/rkansal/nobackup/vbf.root\",\n", " schemaclass=nanoevents.NanoAODSchema,\n", ").events()\n", "\n", @@ -223,15 +224,6 @@ "metadata": {}, "outputs": [], "source": [ - "ak4_jet_selection = { # noqa: RUF012\n", - " \"pt\": 25,\n", - " \"eta\": 2.7,\n", - " \"jetId\": \"tight\",\n", - " \"puId\": \"medium\",\n", - " \"dR_fatjetbb\": 1.2,\n", - " \"dR_fatjetVV\": 0.8,\n", - "}\n", - "\n", "# ak8 jet preselection\n", "preselection = { # noqa: RUF012\n", " \"pt\": 300.0,\n", @@ -259,6 +251,10 @@ "source": [ "fatjets = events.FatJet\n", "\n", + "fatjets = ak.pad_none(\n", + " fatjets[(fatjets.pt > 300) * (fatjets.isTight) * (np.abs(fatjets.eta) <= 2.4)], 2, axis=1\n", + ")\n", + "\n", "# particlenet xbb vs qcd\n", "\n", "txbb = pad_val(\n", @@ -273,6 +269,28 @@ "bb_mask = np.stack((bb_mask, ~bb_mask)).T" ] }, + { + "cell_type": "markdown", + "id": "6922c210", + "metadata": {}, + "source": [ + "Leptons" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa386f98", + "metadata": {}, + "outputs": [], + "source": [ + "electrons = events.Electron\n", + "electrons = electrons[(electrons.pt > 5) & (electrons.cutBased >= electrons.LOOSE)]\n", + "\n", + "muons = events.Muon\n", + "muons = muons[(muons.pt > 7) & (muons.looseId)]" + ] + }, { "cell_type": "code", "execution_count": null, @@ -280,6 +298,16 @@ "metadata": {}, "outputs": [], "source": [ + "ak4_jet_selection = { # noqa: RUF012\n", + " \"pt\": 15,\n", + " \"eta_min\": 0,\n", + " \"eta_max\": 4.9,\n", + " \"jetId\": \"tight\",\n", + " \"puId\": \"medium\",\n", + " \"dR_fatjetbb\": 1.15,\n", + " \"dR_fatjetVV\": 0.95,\n", + "}\n", + "\n", "jets = events.Jet\n", "\n", "# dR_fatjetVV = 0.8 used from last two cells of VBFgenInfoTests.ipynb with data generated from SM signal vbf\n", @@ -288,32 +316,47 @@ "vbf_jet_mask = (\n", " jets.isTight\n", " & (jets.pt > ak4_jet_selection[\"pt\"])\n", - " & (np.abs(jets.eta) < 4.7)\n", + " & (np.abs(jets.eta) < ak4_jet_selection[\"eta_max\"])\n", + " & (np.abs(jets.eta) >= ak4_jet_selection[\"eta_min\"])\n", " # medium puId https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetIDUL\n", " & ((jets.pt > 50) | ((jets.puId & 2) == 2))\n", " & (\n", - " ak.all(\n", - " jets.metric_table(\n", - " ak.singletons(ak.pad_none(fatjets, num_jets, axis=1, clip=True)[bb_mask])\n", - " )\n", - " > ak4_jet_selection[\"dR_fatjetbb\"],\n", - " axis=-1,\n", - " )\n", + " ak.pad_none(fatjets, num_jets, axis=1, clip=True)[bb_mask].delta_r(jets)\n", + " > ak4_jet_selection[\"dR_fatjetbb\"]\n", " )\n", " & (\n", - " ak.all(\n", - " jets.metric_table(\n", - " ak.singletons(ak.pad_none(fatjets, num_jets, axis=1, clip=True)[~bb_mask])\n", - " )\n", - " > ak4_jet_selection[\"dR_fatjetVV\"],\n", - " axis=-1,\n", - " )\n", + " ak.pad_none(fatjets, num_jets, axis=1, clip=True)[~bb_mask].delta_r(jets)\n", + " > ak4_jet_selection[\"dR_fatjetVV\"]\n", " )\n", + " & ak.all(jets.metric_table(electrons) > 0.4, axis=2)\n", + " & ak.all(jets.metric_table(muons) > 0.4, axis=2)\n", ")\n", "\n", "vbf_jets = jets[vbf_jet_mask]" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "b44eb17d", + "metadata": {}, + "outputs": [], + "source": [ + "sel = ak.fill_none(\n", + " (\n", + " (txbb[bb_mask] > 0.97)\n", + " * (fatjets.particleNet_H4qvsQCD[~bb_mask] > 0.6)\n", + " * (fatjets.pt[:, 0] > 500)\n", + " * (fatjets.pt[:, 1] > 400)\n", + " * (np.abs(fatjets[:, 0].delta_phi(fatjets[:, 1])) > 2.6)\n", + " * (np.abs(fatjets[:, 0].eta - fatjets[:, 1].eta) < 2.0)\n", + " ),\n", + " False,\n", + ")\n", + "\n", + "matching_efficiency(gen_quarks[sel], vbf_jets[sel])" + ] + }, { "cell_type": "code", "execution_count": null, @@ -321,15 +364,54 @@ "metadata": {}, "outputs": [], "source": [ - "etas = pad_val(vbf_jets.eta, 2, axis=1)\n", + "etas = pad_val(\n", + " vbf_jets[ak.fill_none(sel & (ak.count(vbf_jets.pt, axis=1) >= 2), False)].eta, 2, axis=1\n", + ")\n", "\n", "plt.rcParams.update({\"font.size\": 24})\n", "plt.figure(figsize=(12, 12))\n", - "plt.hist(np.abs(etas[:, 0] - etas[:, 1]), np.arange(0, 6, 0.25), histtype=\"step\", density=True)\n", + "plt.hist(np.abs(etas[:, 0] - etas[:, 1]), np.arange(0, 10, 0.25), histtype=\"step\", density=True)\n", "plt.xlabel(r\"$\\eta_{jj}$\")\n", "plt.ylabel(\"Events (A. U.)\")\n", "plt.show()" ] + }, + { + "cell_type": "markdown", + "id": "f820fb8e", + "metadata": {}, + "source": [ + "Checking how many events have jets which match with the gen quarks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5c0658f", + "metadata": {}, + "outputs": [], + "source": [ + "jets = events.Jet\n", + "np.mean(ak.all(ak.any(gen_quarks.metric_table(jets) < 0.4, axis=2), axis=1))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7901612f", + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(8, 8))\n", + "plt.hist(\n", + " ak.sum(ak.any(gen_quarks.metric_table(jets) < 0.4, axis=2), axis=1),\n", + " [0, 1, 2, 3],\n", + " histtype=\"step\",\n", + " density=True,\n", + ")\n", + "plt.title(\"Fraction of Gen VBF Quarks which have\\n a matching AK4 jet in the event\")\n", + "plt.show()" + ] } ], "metadata": {