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@wiso
Created March 6, 2019 11:27
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Atlas Style in matplotlib
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"import matplotlib as mpl\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [],
"source": [
"mpl.rcParams['lines.linewidth'] = 1\n",
"mpl.rcParams['figure.figsize'] = 8.75, 5.92\n",
"\n",
"# not very useful\n",
"mpl.rcParams['figure.facecolor'] = 'white'\n",
"mpl.rcParams['figure.subplot.bottom'] = 0.16\n",
"mpl.rcParams['figure.subplot.top'] = 0.95\n",
"mpl.rcParams['figure.subplot.left'] = 0.16\n",
"mpl.rcParams['figure.subplot.right'] = 0.95\n",
"\n",
"# font\n",
"mpl.rcParams['font.family'] = 'sans-serif'\n",
"mpl.rcParams['mathtext.fontset'] = 'stixsans'\n",
"mpl.rcParams['mathtext.default'] = 'rm'\n",
"# helvetica usually not present on linux\n",
"mpl.rcParams['font.sans-serif'] = 'helvetica, Helvetica, Nimbus Sans L, Mukti Narrow, FreeSans'\n",
"\n",
"\n",
"mpl.rcParams['axes.labelsize'] = 20\n",
"mpl.rcParams['xtick.labelsize'] = 19\n",
"mpl.rcParams['ytick.labelsize'] = 19\n",
"\n",
"mpl.rcParams['xtick.direction'] = 'in'\n",
"mpl.rcParams['ytick.direction'] = 'in'\n",
"mpl.rcParams['xtick.major.size'] = 12\n",
"mpl.rcParams['xtick.minor.size'] = 6\n",
"mpl.rcParams['ytick.major.size'] = 14\n",
"mpl.rcParams['ytick.minor.size'] = 7\n",
"\n",
"mpl.rcParams['xtick.top'] = True\n",
"mpl.rcParams['ytick.right'] = True\n",
"\n",
"mpl.rcParams['xtick.minor.visible'] = True\n",
"mpl.rcParams['ytick.minor.visible'] = True\n",
"\n",
"mpl.rcParams['legend.frameon'] = False"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Basic Example"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 630x426.24 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data = np.random.normal(size=25000)\n",
"\n",
"fig, ax = plt.subplots()\n",
"ax.hist(data, bins=np.linspace(-4, 4, 100), histtype='step', color='k', lw=2)\n",
"ax.set_xlabel('random variable [unit]', horizontalalignment='right', x=1.0)\n",
"ax.set_ylabel(r'$\\frac{dN}{dr} [\\mathrm{unit}^{-1}]$', horizontalalignment='right', y=1.0)\n",
"\n",
"# not really needed, need some tuning time by time\n",
"ax.set_xlim(-4, 4)\n",
"ax.set_ylim(0, 1000)\n",
"ax.yaxis.set_major_locator(mpl.ticker.MaxNLocator(steps=[10]))\n",
"ax.yaxis.set_minor_locator(mpl.ticker.AutoMinorLocator(n=5))"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_xs = np.array([ 150., 250., 350., 450., 550., 650., 750., 850., 950.,\n",
" 1050., 1150., 1250., 1350., 1450., 1550., 1650., 1750., 1850.,\n",
" 1950., 2050., 2150., 2250., 2350., 2450., 2550., 2650., 2750.,\n",
" 2850., 2950., 3050., 3150., 3250., 3350., 3450., 3550., 3650.,\n",
" 3750., 3850., 3950., 4050., 4150., 4250., 4350., 4450., 4550.,\n",
" 4650., 4750., 4850., 4950., 5050., 5150., 5250., 5350., 5450.,\n",
" 5550., 5650., 5750., 5850., 5950., 6050., 6150., 6250., 6350.,\n",
" 6450., 6550., 6650., 6750., 6850., 6950.])\n",
"\n",
"data_ys = np.array([6.08053e+06, 2.84153e+05, 5.72335e+04, 1.11327e+04, 3.57190e+03,\n",
" 1.14149e+03, 5.16090e+02, 2.28247e+02, 1.01396e+02, 4.91510e+01,\n",
" 2.73734e+01, 1.82679e+01, 1.10116e+01, 6.32152e+00, 3.43354e+00,\n",
" 2.11244e+00, 1.62043e+00, 1.13207e+00, 7.22957e-01, 3.64806e-01,\n",
" 2.64400e-01, 2.00142e-01, 1.39045e-01, 1.34701e-01, 8.82416e-02,\n",
" 7.38804e-02, 7.02962e-02, 5.47373e-02, 6.45647e-02, 6.00438e-02,\n",
" 6.74864e-02, 5.74554e-02, 8.32830e-02, 7.46757e-02, 5.27417e-02,\n",
" 5.86759e-02, 6.99723e-02, 9.45986e-02, 8.48813e-02, 6.73939e-02,\n",
" 1.16813e-01, 8.94630e-02, 5.47304e-02, 9.81258e-02, 1.07985e-01,\n",
" 5.32451e-02, 6.32456e-02, 7.89139e-02, 1.04499e-01, 1.01160e-01,\n",
" 1.24366e-01, 1.28086e-01, 6.46936e-02, 1.14120e-01, 8.09755e-02,\n",
" 7.23701e-02, 1.41394e-01, 9.73835e-02, 1.85729e-01, 1.01855e-01,\n",
" 1.57262e-01, 1.25150e-01, 1.89784e-01, 1.58515e-01, 1.62190e-01,\n",
" 1.33725e-01, 1.13545e-01, 1.14935e-01, 1.71703e-01])\n",
"\n",
"data_eys = np.array([3.89889e+02, 8.42842e+01, 3.78264e+01, 1.66829e+01, 9.44974e+00,\n",
" 5.34202e+00, 3.59197e+00, 2.38876e+00, 1.59213e+00, 1.10850e+00,\n",
" 8.27245e-01, 6.75794e-01, 5.24681e-01, 3.97540e-01, 2.92982e-01,\n",
" 2.29806e-01, 2.01273e-01, 1.68231e-01, 1.34439e-01, 9.54995e-02,\n",
" 8.13019e-02, 7.07358e-02, 5.89586e-02, 5.80304e-02, 4.69685e-02,\n",
" 4.29769e-02, 4.19214e-02, 3.69923e-02, 4.01761e-02, 3.87440e-02,\n",
" 4.10751e-02, 3.78997e-02, 4.56298e-02, 4.32075e-02, 3.63117e-02,\n",
" 3.83001e-02, 4.18247e-02, 4.86309e-02, 4.60655e-02, 4.10469e-02,\n",
" 5.40400e-02, 4.72925e-02, 3.69900e-02, 4.95292e-02, 5.19579e-02,\n",
" 3.64846e-02, 3.97635e-02, 4.44167e-02, 5.11124e-02, 5.02893e-02,\n",
" 5.57598e-02, 5.65876e-02, 4.02162e-02, 5.34134e-02, 4.49932e-02,\n",
" 4.25353e-02, 5.94547e-02, 4.93415e-02, 6.81413e-02, 5.04616e-02,\n",
" 6.27021e-02, 5.59352e-02, 6.88810e-02, 6.29514e-02, 6.36769e-02,\n",
" 5.78198e-02, 5.32789e-02, 5.36040e-02, 6.55178e-02])\n",
"\n",
"mc_xs = np.array([ 150., 250., 350., 450., 550., 650., 750., 850., 950.,\n",
" 1050., 1150., 1250., 1350., 1450., 1550., 1650., 1750., 1850.,\n",
" 1950., 2050., 2150., 2250., 2350., 2450., 2550., 2650., 2750.,\n",
" 2850., 2950., 3050., 3150., 3250., 3350., 3450., 3550., 3650.,\n",
" 3750., 3850., 3950., 4050., 4150., 4250., 4350., 4450., 4550.,\n",
" 4650., 4750., 4850., 4950., 5050., 5150., 5250., 5350., 5450.,\n",
" 5550., 5650., 5750., 5850., 5950., 6050., 6150., 6250., 6350.,\n",
" 6450., 6550., 6650., 6750., 6850., 6950.])\n",
"\n",
"mc_ys = np.array([6.65960e+06, 3.18321e+05, 4.83803e+04, 1.09572e+04, 3.23547e+03,\n",
" 1.23235e+03, 5.12050e+02, 2.30488e+02, 1.14084e+02, 6.05025e+01,\n",
" 3.11572e+01, 1.76683e+01, 1.03007e+01, 6.14975e+00, 3.71552e+00,\n",
" 2.52298e+00, 1.44746e+00, 1.01675e+00, 6.41863e-01, 3.87250e-01,\n",
" 2.63351e-01, 2.07581e-01, 1.03852e-01, 8.13621e-02, 5.07964e-02,\n",
" 3.74186e-02, 2.39413e-02, 1.79119e-02, 1.05439e-02, 7.24193e-03,\n",
" 5.13062e-03, 3.53234e-03, 2.37385e-03, 1.37003e-03, 9.49618e-04,\n",
" 6.70692e-04, 4.55441e-04, 2.78849e-04, 1.75337e-04, 1.21832e-04,\n",
" 8.35938e-05, 4.20491e-05, 2.53419e-05, 1.83000e-05, 1.05427e-05,\n",
" 5.73383e-06, 3.57256e-06, 2.47147e-06, 1.32182e-06, 5.26587e-07,\n",
" 3.89889e-07, 1.85564e-07, 1.05617e-07, 5.02298e-08, 2.37682e-08,\n",
" 1.00941e-08, 4.17607e-09, 1.74077e-09, 6.47905e-10, 2.90492e-10,\n",
" 8.31421e-11, 2.45835e-11, 5.51966e-12, 1.23854e-12, 2.12108e-13,\n",
" 3.51307e-14, 3.83912e-15, 2.02972e-16, 1.93257e-17])\n",
"\n",
"mc_eylow = np.array([5.12873e+05, 2.39871e+04, 4.29078e+03, 9.39510e+02, 2.68099e+02,\n",
" 1.13077e+02, 4.75873e+01, 2.13316e+01, 1.07863e+01, 6.08552e+00,\n",
" 2.84878e+00, 1.64925e+00, 9.83585e-01, 5.89329e-01, 3.56251e-01,\n",
" 2.80985e-01, 1.33465e-01, 1.10517e-01, 6.78830e-02, 3.63539e-02,\n",
" 2.63022e-02, 2.65535e-02, 8.33570e-03, 8.87006e-03, 5.04804e-03,\n",
" 4.21068e-03, 2.64407e-03, 2.25260e-03, 1.11355e-03, 7.60601e-04,\n",
" 6.17437e-04, 4.48741e-04, 3.10115e-04, 1.49610e-04, 1.07957e-04,\n",
" 8.34786e-05, 6.08065e-05, 3.60620e-05, 2.13503e-05, 1.69903e-05,\n",
" 1.30819e-05, 4.84334e-06, 2.92574e-06, 2.72812e-06, 1.49759e-06,\n",
" 7.27449e-07, 5.02387e-07, 4.22674e-07, 2.12623e-07, 5.45116e-08,\n",
" 6.19066e-08, 2.85893e-08, 1.90962e-08, 8.23247e-09, 3.93711e-09,\n",
" 1.66203e-09, 6.37106e-10, 3.03910e-10, 1.10885e-10, 5.87120e-11,\n",
" 1.71702e-11, 4.54579e-12, 1.21478e-12, 2.46177e-13, 3.69386e-14,\n",
" 8.11562e-15, 8.78069e-16, 3.87447e-17, 4.28127e-18])\n",
"\n",
"mc_eyhi = np.array([ 4.38824e+05, 1.48594e+04, 3.12489e+03, 6.01350e+02,\n",
" 1.50732e+02, 7.59130e+01, 3.18253e+01, 1.37678e+01,\n",
" 7.12250e+00, 4.40825e+00, 1.67123e+00, 9.95420e-01,\n",
" 6.09970e-01, 3.61298e-01, 2.14546e-01, 2.19364e-01,\n",
" 6.91610e-02, 8.05900e-02, 4.61989e-02, 1.80353e-02,\n",
" 1.51374e-02, 2.34741e-02, 1.50450e-03, 5.79818e-03,\n",
" 2.54437e-03, 2.82585e-03, 1.66446e-03, 1.79272e-03,\n",
" 5.85990e-04, 3.81152e-04, 4.27734e-04, 3.37875e-04,\n",
" 2.41473e-04, 7.30810e-05, 5.75159e-05, 5.51904e-05,\n",
" 4.56894e-05, 2.47222e-05, 1.21245e-05, 1.29133e-05,\n",
" 1.19057e-05, 1.95643e-06, 1.11909e-06, 2.16121e-06,\n",
" 1.04433e-06, 3.46211e-07, 3.19918e-07, 3.91131e-07,\n",
" 1.72776e-07, -5.25020e-09, 4.62701e-08, 1.91509e-08,\n",
" 1.74185e-08, 5.98442e-09, 2.81432e-09, 1.12336e-09,\n",
" 3.01254e-10, 2.16839e-10, 7.08026e-11, 5.38550e-11,\n",
" 1.57799e-11, 3.02418e-12, 1.17792e-12, 1.79173e-13,\n",
" 1.41588e-14, 7.97913e-15, 8.65087e-16, 2.53887e-17,\n",
" 4.43126e-18])\n",
"\n",
"my_dpi = 96\n",
"fig, ax = plt.subplots(figsize=(600/my_dpi, 600/my_dpi), dpi=my_dpi)\n",
"ax.errorbar(data_xs, data_ys, data_eys, fmt='ko', label='Data 2009')\n",
"ax.errorbar(mc_xs, mc_ys, 0, 50, marker=None, ls='', color='k', lw=2, label='NLO QCD')\n",
"\n",
"ax.bar(mc_xs, mc_eyhi + mc_eylow,\n",
" bottom=mc_ys-mc_eylow, width=100, color='yellow', align='center')\n",
"\n",
"\n",
"\n",
"ax.set_yscale('log')\n",
"\n",
"ax.set_xlim(50, 3500)\n",
"ax.set_xlabel('$E_{T,jet}$ [GeV]', horizontalalignment='right', x=1.0)\n",
"ax.set_ylabel('$d\\sigma_{jet}/dE_{T, jet}$ [fb/GeV]', horizontalalignment='right', y=1.0)\n",
"ax.set_ylim(1E-3, 2E7)\n",
"\n",
"ax.legend(bbox_to_anchor=(0.35, 0.7, 0.1, 0.1), fontsize=19, labelspacing=0.6, handletextpad=0.)\n",
"\n",
"ax.text(0.2, 0.87, '$\\sqrt{s}=14$ TeV', transform=ax.transAxes, fontsize=18)\n",
"ax.text(0.52, 0.87, '$|\\eta_{jet}|<0.5$', transform=ax.transAxes, fontsize=18)\n",
"ax.text(0.06, 0.05, 'ATLAS', style='italic', fontweight='bold', transform=ax.transAxes, fontsize=19)\n",
"ax.text(0.26, 0.05, 'Preliminary', transform=ax.transAxes, fontsize=19)\n",
"\n",
"\n",
"ax.yaxis.set_major_locator(mpl.ticker.LogLocator(numticks=10)) # bad solution\n",
"#ax.yaxis.set_minor_locator(mpl.ticker.LogLocator(base=10, subs=(1.2, 0.2,0.4,0.6,0.8)))\n",
"#ax.yaxis.set_minor_locator(mpl.ticker.MaxNLocator(100))\n",
"ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(500))\n",
"ax.xaxis.set_minor_locator(mpl.ticker.AutoMinorLocator(n=5))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.7.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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