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ATLAS SUSY Reproducible Summary Plots
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import uproot\n", | |
"import numpy as np\n", | |
"import matplotlib.pyplot as plt\n", | |
"import matplotlib.transforms\n", | |
"import matplotlib.lines\n", | |
"import mplhep as hep\n", | |
"import pathlib\n", | |
"import requests" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Reproducible Physics\n", | |
"\n", | |
"The goal of this notebook is to reproduce summary plots from the SUSY group ATLAS. To start with, we'll focus on the following\n", | |
"\n", | |
"<img src=\"https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2020-020/fig_15.png\" width=\"600\" alt=\"may2020 Wh susy summary plot from ATLAS\" />\n", | |
"\n", | |
"which provides a summary of observed and expected exclusion limits from the following analyses:\n", | |
"* 36 ifb summary: https://arxiv.org/abs/1812.09432\n", | |
"* 139 ifb diphoton: https://arxiv.org/abs/2004.10894\n", | |
"* 139 ifb 1Lbb: https://arxiv.org/abs/1909.09226\n", | |
"* 139 ifb 3L-offshell: https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/CONFNOTES/ATLAS-CONF-2020-015/\n", | |
"\n", | |
"each of which have published complimentary data on https://www.hepdata.net/:\n", | |
"* https://www.hepdata.net/record/ins1711261\n", | |
"* https://www.hepdata.net/record/ins1792399\n", | |
"* https://www.hepdata.net/record/ins1755298\n", | |
"\n", | |
"*Note: the CONF note above does not have corresponding hepdata entry - so it is not currently being included in this notebook demonstration.*\n", | |
"\n", | |
"So we need to go one by one through each of the HEPData pages, look through the resources provided for the \"expected limits\" and \"observed limits\" (protip: filter by `limits`) and grab the corresponding `ROOT` URL for each one like I've done below." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"analyses = {\n", | |
" \"0Lbb (36)\": {\n", | |
" \"hepdata\": \"ins1711261\",\n", | |
" \"color\": \"#ff954b\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1711261/Expected%20limit%200lbb/1/root\",\n", | |
" \"obs\": \"https://www.hepdata.net/download/table/ins1711261/Observed%20limit%200lbb/1/root\"\n", | |
" },\n", | |
" \"1Lbb (36)\": {\n", | |
" \"hepdata\": \"ins1711261\",\n", | |
" \"color\": \"#151bff\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1711261/Expected%20limit%201lbb/1/root\",\n", | |
" \"obs\": \"https://www.hepdata.net/download/table/ins1711261/Observed%20limit%201lbb/1/root\"\n", | |
" },\n", | |
" \"1Lyy (36)\": {\n", | |
" \"hepdata\": \"ins1711261\",\n", | |
" \"color\": \"#006601\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1711261/Expected%20limit%201Lyy/1/root\",\n", | |
" \"obs\": \"\" # excess!\n", | |
" },\n", | |
" \"same-sign (36)\": {\n", | |
" \"hepdata\": \"ins1711261\",\n", | |
" \"color\": \"#ff4cfe\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1711261/Expected%20limit%20SS/1/root\",\n", | |
" \"obs\": \"https://www.hepdata.net/download/table/ins1711261/Observed%20limit%20SS/1/root\"\n", | |
" },\n", | |
" \"diphoton\": {\n", | |
" \"hepdata\": \"ins1792399\",\n", | |
" \"color\": \"#93dc93\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1792399/Figure%2010%20Expected/1/root\",\n", | |
" \"obs\": \"https://www.hepdata.net/download/table/ins1792399/Figure%2010%20Observed/1/root\"\n", | |
" },\n", | |
" \"1Lbb\": {\n", | |
" \"hepdata\": \"ins1755298\",\n", | |
" \"color\": \"#9394db\",\n", | |
" \"exp\": \"https://www.hepdata.net/download/table/ins1755298/Expected%20limit%201lbb/3/root\",\n", | |
" \"obs\": \"https://www.hepdata.net/download/table/ins1755298/Observed%20limit%201lbb/3/root\"\n", | |
" }\n", | |
"}" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"We'll defined the `processLabel` as $\\tilde{\\chi}^{0}_{2}\\tilde{\\chi}^{\\pm}_{1} \\rightarrow Wh\\ \\tilde{\\chi}^{0}_{1}\\tilde{\\chi}^{0}_{1}$ and a luminosity/center-of-mass [energy] label as $\\sqrt{s} = \\mathrm{13\\ TeV}, 36\\ -\\ 139\\ \\mathrm{fb}^{-1}$.\n", | |
"\n", | |
"We'll also label our axes with $m(\\tilde{\\chi}^{\\pm}_{1}/\\tilde{\\chi}^{0}_{2})\\ \\mathrm{[GeV]}$ and $m(\\tilde{\\chi}^{0}_{1})\\ \\mathrm{[GeV]}$.\n", | |
"\n", | |
"In addition, we'll also go ahead and set the `x`, `y` ranges for the axes that we'll soon draw." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"processLabel = r\"$\\tilde{\\chi}^{0}_{2}\\tilde{\\chi}^{\\pm}_{1} \\rightarrow Wh\\ \\tilde{\\chi}^{0}_{1}\\tilde{\\chi}^{0}_{1}$\"\n", | |
"lumiLabel = r\"$\\sqrt{s} = \\mathrm{13\\ TeV}, 36\\ -\\ 139\\ \\mathrm{fb}^{-1}$\"\n", | |
"xlabel = r\"$m(\\tilde{\\chi}^{\\pm}_{1}/\\tilde{\\chi}^{0}_{2})\\ \\mathrm{[GeV]}$\"\n", | |
"ylabel = r\"$m(\\tilde{\\chi}^{0}_{1})\\ \\mathrm{[GeV]}$\"\n", | |
"xrange = [150, 1100]\n", | |
"yrange = [0, 525]" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Some helper functions here for drawing the ATLAS label as well as the kinematic exclusion line (not the point of the notebook, but feel free to study this on your own time)." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def atlas_label(ax, suffix=\"Summary\", lumiLabel=\"\"):\n", | |
" text, suffix = hep.atlas.text(ax=ax, loc=2, text=suffix)\n", | |
" bbox = text.get_window_extent(renderer=fig.canvas.get_renderer())\n", | |
" bbox_axes = matplotlib.transforms.Bbox(suffix.get_transform().inverted().transform(bbox))\n", | |
"\n", | |
" label = hep.label.ExpSuffix(*suffix.get_position(),\n", | |
" text=lumiLabel,\n", | |
" transform=suffix.get_transform(),\n", | |
" ha=suffix.get_ha(),\n", | |
" va=suffix.get_va(),\n", | |
" fontsize=suffix.get_fontsize(),\n", | |
" fontname=suffix.get_fontname(),\n", | |
" fontstyle=\"normal\")\n", | |
" ax._add_text(label)\n", | |
" suffix.set_position((text.get_position()[0] + bbox_axes.width + 0.01, text.get_position()[1] + bbox_axes.height))\n", | |
" suffix.set_fontsize(text.get_fontsize())\n", | |
"\n", | |
"def kinematic_exclusion(ax):\n", | |
" line = ax.axline((150, 25), (650, 525), linestyle='-.', color='#cccccc', alpha=0.9)\n", | |
" p1 = ax.transData.transform_point((150, 25))\n", | |
" p2 = ax.transData.transform_point((650, 525))\n", | |
" dy = (p2[1] - p1[1])\n", | |
" dx = (p2[0] - p1[0])\n", | |
" rotn = np.degrees(np.arctan2(dy, dx))\n", | |
" ax.text(200, 100, r\"$m(\\tilde{\\chi}^{\\pm}_{1}/\\tilde{\\chi}^{0}_{2}) < m(\\tilde{\\chi}^{0}_{1}) + 125\\ \\mathrm{GeV}$\", va='baseline', fontsize='x-small', color='#cccccc', alpha=0.9, rotation=rotn)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The first thing we'll need to do is write a function that downloads the ROOT file (if we don't already have it downloaded) and pass the corresponding filename back if so:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def get_filename(analysis, details, kind):\n", | |
" \"\"\"\n", | |
" For a given analysis name and details on where the expected/observed curves are located,\n", | |
" download the corresponding kind of curve locally and cache it at data/{analysis}/{kind}.root.\n", | |
" \n", | |
" Args:\n", | |
" analysis (str): analysis name (the key in the analyses object above)\n", | |
" details (dict): analysis details (the value in the analyses object above)\n", | |
" kind (str): specify either 'exp' or 'obs', according to the details provided\n", | |
" \n", | |
" Returns:\n", | |
" file path (pathlib.Path): The local ROOT file\n", | |
" \"\"\"\n", | |
" assert kind in [\"exp\", \"obs\"], f\"'{kind}' must be either 'exp' or 'obs'\"\n", | |
" \n", | |
" if not details[kind]: # skip empty ones\n", | |
" return None\n", | |
" \n", | |
" analysis = \"\".join([c for c in analysis if c.isalpha() or c.isdigit()]).rstrip()\n", | |
" \n", | |
" folder = pathlib.Path(\"data\").joinpath(details['hepdata']).joinpath(analysis)\n", | |
" fpath = folder.joinpath(f'{kind}.root')\n", | |
" if not fpath.is_file():\n", | |
" fpath.parent.mkdir(parents=True, exist_ok=True)\n", | |
" response = requests.get(details[kind])\n", | |
" response.raise_for_status()\n", | |
" fpath.write_bytes(response.content)\n", | |
" return fpath" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"and let's give it a whirl. The first time will be a little slow since it needs to download the file, but future calls will be faster." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"PosixPath('data/ins1711261/1Lbb36/exp.root')" | |
] | |
}, | |
"execution_count": 6, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"get_filename('1Lbb (36)', analyses['1Lbb (36)'], 'exp')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"So let's quickly download all the files we need:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"data/ins1711261/0Lbb36/exp.root\n", | |
"data/ins1711261/0Lbb36/obs.root\n", | |
"data/ins1711261/1Lbb36/exp.root\n", | |
"data/ins1711261/1Lbb36/obs.root\n", | |
"data/ins1711261/1Lyy36/exp.root\n", | |
"None\n", | |
"data/ins1711261/samesign36/exp.root\n", | |
"data/ins1711261/samesign36/obs.root\n", | |
"data/ins1792399/diphoton/exp.root\n", | |
"data/ins1792399/diphoton/obs.root\n", | |
"data/ins1755298/1Lbb/exp.root\n", | |
"data/ins1755298/1Lbb/obs.root\n" | |
] | |
} | |
], | |
"source": [ | |
"for analysis, details in analyses.items():\n", | |
" for kind in ['exp', 'obs']:\n", | |
" print(get_filename(analysis, details, kind))" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Finally, one last bookkeeping headache is that each of these files will store the corresponding curve we need under a different name / path. Luckily, we can use `uproot` to look through all the keys and just find the right one most of the time (e.g. the first one we find that's not a `TDirectory`)." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def get_graph(root_file):\n", | |
" it = iter(k for k,v in root_file.classnames().items() if v not in ['TDirectory'])\n", | |
" return root_file[next(it)]" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Does it work for us? Let's check..." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"<TGraphAsymmErrors (version 3) at 0x000112288ca0>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8d56d0>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8e2250>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8e9250>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8ee040>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8f3a30>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8ee3a0>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8e9760>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e9425b0>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e8e9d30>\n", | |
"<TGraphAsymmErrors (version 3) at 0x00016e942490>\n" | |
] | |
} | |
], | |
"source": [ | |
"for analysis, details in analyses.items():\n", | |
" for kind in ['exp', 'obs']:\n", | |
" fname = get_filename(analysis, details, kind)\n", | |
" if not fname: continue\n", | |
" with uproot.open(fname) as f:\n", | |
" print(get_graph(f))" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Looks ok, so we have everything we need to make our summary plot..." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 800x600 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"# load atlas style\n", | |
"plt.style.use(hep.style.ATLAS)\n", | |
"\n", | |
"fig, ax = plt.subplots()\n", | |
"\n", | |
"## Axes\n", | |
"ax.set_xlim(xrange)\n", | |
"ax.set_ylim(yrange)\n", | |
"\n", | |
"# add process label\n", | |
"ax.text(0.0, 1.01, processLabel, transform = ax.transAxes, va='bottom')\n", | |
"\n", | |
"# Set up initial legend\n", | |
"leg1_elements = [matplotlib.lines.Line2D([0], [0], linestyle='--', color='k', label='Expected'), matplotlib.lines.Line2D([0], [0], linestyle='-', color='k', label='Observed')]\n", | |
"leg1 = ax.legend(title=\"All limits at 95% CL\", handles=leg1_elements)\n", | |
"\n", | |
"# Create legend for the analyses added\n", | |
"leg2_elements = []\n", | |
"\n", | |
"# ATLAS Labeling\n", | |
"atlas_label(ax, lumiLabel=lumiLabel)\n", | |
"\n", | |
"# get analysis curves\n", | |
"for analysis, details in analyses.items():\n", | |
" leg2_elements.append(matplotlib.lines.Line2D([0], [0], linestyle='-', color=details['color'], label=analysis))\n", | |
"\n", | |
" f_exp_name = get_filename(analysis, details, 'exp')\n", | |
" f_obs_name = get_filename(analysis, details, 'obs')\n", | |
"\n", | |
" if f_exp_name:\n", | |
" f_exp = uproot.open(get_filename(analysis, details, 'exp'))\n", | |
" graph_exp = get_graph(f_exp)\n", | |
" ax.plot(graph_exp.member('fX'), graph_exp.member('fY'), linestyle='--', color=details['color'], alpha=0.9)\n", | |
"\n", | |
" if f_obs_name:\n", | |
" f_obs = uproot.open(get_filename(analysis, details, 'obs'))\n", | |
" graph_obs = get_graph(f_obs)\n", | |
" ax.plot(graph_obs.member('fX'), graph_obs.member('fY'), linestyle='-', color=details['color'], alpha=0.9, label=analysis)\n", | |
"\n", | |
"## Draw Lines\n", | |
"kinematic_exclusion(ax)\n", | |
"\n", | |
"## Axis Labels\n", | |
"hep.atlas.set_xlabel(xlabel)\n", | |
"hep.atlas.set_ylabel(ylabel)\n", | |
"\n", | |
"# for multiple legends\n", | |
"ax.legend(loc='upper left', bbox_to_anchor=(0.01, 0.85), handles=leg2_elements, fontsize='small')\n", | |
"ax.add_artist(leg1);" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.8.6" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 4 | |
} |
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# Ensure matplotlib has font from cursive font family | |
# https://stackoverflow.com/q/65649122/8931942 | |
if [ ! -d "${HOME}/.local/share/fonts/truetype/felipa" ]; then | |
mkdir -p "${HOME}/.local/share/fonts/truetype/felipa" | |
wget --no-clobber https://github.com/google/fonts/blob/master/ofl/felipa/Felipa-Regular.ttf?raw=true -O "${HOME}/.local/share/fonts/truetype/felipa/Felipa-Regular.ttf" | |
fc-cache --force --verbose # force system font cache rebuild | |
fi |
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uproot~=4.0 | |
mplhep~=0.2 |
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