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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"See as example https://indico.cern.ch/event/147827/material/slides/1?contribId=9, slide 16" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"NTOYS = 50\n", | |
"NEVENTS = [100, 1000]" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"try:\n", | |
" from ipy_progressbar import ProgressBar\n", | |
"except ImportError:\n", | |
" print \"intalling ipy_progressbar\"\n", | |
" import pip\n", | |
" pip.main(['install', '--user', 'ipy_progressbar'])\n", | |
" print \"*** you have to restart this kernel ***\"" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"application/javascript": [ | |
"IPython.notebook.set_autosave_interval(30000)" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"Autosaving every 30 seconds\n" | |
] | |
} | |
], | |
"source": [ | |
"import numpy as np\n", | |
"import matplotlib.pyplot as plt\n", | |
"import scipy.stats\n", | |
"import matplotlib as mpl\n", | |
"\n", | |
"%matplotlib inline\n", | |
"%autosave 30" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"ROOT version = 5.34/28\n" | |
] | |
} | |
], | |
"source": [ | |
"import ROOT\n", | |
"from ROOT import RooFit\n", | |
"print \"ROOT version =\", ROOT.gROOT.GetVersion()\n", | |
"\n", | |
"import urllib\n", | |
"urllib.urlretrieve (\"https://gist.githubusercontent.com/mazurov/6194738/raw/67e851fdac969e670a11296642478f1801324b8d/rootnotes.py\", \"rootnotes.py\")\n", | |
"from rootnotes import default_canvas" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"def iterateRooFit(q):\n", | |
" it = q.iterator()\n", | |
" while True:\n", | |
" r = it.Next()\n", | |
" if r:\n", | |
" yield r\n", | |
" else:\n", | |
" break" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"def eval_pdf(pdf, var, values):\n", | |
" result = np.zeros_like(values, dtype=float)\n", | |
" for i, val in enumerate(values):\n", | |
" var.setVal(val)\n", | |
" result[i] = pdf.getVal()\n", | |
" return result" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"def copy_values(ws, prefix1, prefix2):\n", | |
" for v in iterateRooFit(ws.allVars().selectByName(prefix1 + \"*\")):\n", | |
" ndof = v.GetName().split(prefix1)[1]\n", | |
" ws.var(prefix2 + ndof).setVal(v.getVal())" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"def data2array(data):\n", | |
" if not data.numEntries():\n", | |
" return None\n", | |
" \n", | |
" s0 = data.get(0)\n", | |
" result = np.zeros((s0.getSize(), data.numEntries()))\n", | |
" \n", | |
" for i in xrange(data.numEntries()):\n", | |
" s = data.get(i)\n", | |
" result[:, i] = [xvar.getVal() for x in iterateRooFit(s)]\n", | |
" return result" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"def compute_Ftest(chi1, chi2, ndof1, ndof2, n):\n", | |
" num = (chi1 - chi2) / (ndof2 - ndof1)\n", | |
" den = chi2 / (n - ndof2)\n", | |
"\n", | |
" return num / den" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"colors = (ROOT.kBlue, ROOT.kRed, ROOT.kViolet, ROOT.kGreen, ROOT.kYellow, ROOT.kOrange, ROOT.kAzure)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"def parameters_string(prefix, nstart, nstop):\n", | |
" return \",\".join([\"%s_%d[0, -100, 100]\" % (prefix, n) for n in xrange(nstart, nstop + 1)])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"True" | |
] | |
}, | |
"execution_count": 12, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"ws = ROOT.RooWorkspace()\n", | |
"ws.factory('RooExponential::true_bkg(x[0,100], q[-0.05, -1, 1])')\n", | |
"poly_pdf = []\n", | |
"ndofs_poly = np.arange(1, 7) # RooChebychev.cxx, line 128: Higher order Chebychev polynomials currently unimplemented.\n", | |
"for n in ndofs_poly:\n", | |
" pdf_name = \"poly%d\" % n\n", | |
" parameters = parameters_string(pdf_name, 1, n)\n", | |
" poly_pdf.append(ws.factory(\"RooChebychev::%s(x, {%s})\" % (pdf_name, parameters)))\n", | |
"\n", | |
"xvar = ws.var('x')\n", | |
"xvar.setBins(50)\n", | |
"true_bkg = ws.pdf('true_bkg')\n", | |
"\n", | |
"ws.saveSnapshot(\"initial\", ws.allVars())" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Generate toys" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Generate toys using as model a simple exponential. Then fit with polynomials with various nDOFs. Toys are generate with various number of events (2 set).\n", | |
"\n", | |
"When fitting with (n+1) nDOF the parameter are initially set to the one obtained with the n nDOF poly. Unfortunately, even with this prescription, sometimes $\\chi^2$-with-(n+1)-nDOF > $\\chi^2$-with-n-nDOF, event if it should not happen. If this happen then $\\chi^2$-with-(n+1)-nDOF is forced to be equal to $\\chi^2$-with-n-nDOF." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 94, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"\n", | |
"Toy generation: 100% [█████████████████████████████] 50/50 [22.8 s] [eta 0+-0 s]\n", | |
"\n", | |
"Toy generation: 100% [█████████████████████████████] 50/50 [15.9 s] [eta 0+-0 s]\n" | |
] | |
} | |
], | |
"source": [ | |
"chi2s_poly = np.zeros((len(NEVENTS), NTOYS, len(poly_pdf)))\n", | |
"nlls_poly = np.zeros((len(NEVENTS), NTOYS, len(poly_pdf)))\n", | |
"chi2s_true_model = np.zeros((len(NEVENTS), NTOYS))\n", | |
"nlls_true_model = np.zeros_like(chi2s_true_model)\n", | |
"\n", | |
"Fs_poly = np.zeros((len(NEVENTS), NTOYS, len(poly_pdf) - 1))\n", | |
"pvalues_F_poly = np.zeros((len(NEVENTS), NTOYS, len(poly_pdf) - 1))\n", | |
"\n", | |
"Lratios_poly = np.zeros_like(Fs_poly)\n", | |
"pvalues_L_poly = np.zeros_like(pvalues_F_poly)\n", | |
"\n", | |
"for inevents, nevents in enumerate(NEVENTS):\n", | |
" pb = ProgressBar(NTOYS, title='Toy generation', key='outer')\n", | |
" for itoy in pb:\n", | |
" ws.loadSnapshot(\"initial\")\n", | |
" xset = ROOT.RooArgSet(xvar)\n", | |
" data = true_bkg.generateBinned(xset, nevents)\n", | |
"\n", | |
" previous_prefix = None\n", | |
" chi2_previous = None\n", | |
" nll_previous = None\n", | |
" ndof_previous = None\n", | |
"\n", | |
" for ipdf, (ndof, pdf) in enumerate(zip(ndofs_poly, poly_pdf)):\n", | |
" if previous_prefix is not None:\n", | |
" copy_values(ws, previous_prefix, pdf.GetName() + \"_\") \n", | |
" r = pdf.fitTo(data, RooFit.Save())\n", | |
"\n", | |
" chi2 = pdf.createChi2(data).getVal()\n", | |
" nll = r.minNll()\n", | |
" if chi2_previous and chi2_previous < chi2:\n", | |
" # if the new chi2 is worse take the previous (it should not happen)\n", | |
" chi2 = chi2_previous\n", | |
" \n", | |
" if nll_previous and nll_previous < nll:\n", | |
" nll = nll_previous\n", | |
"\n", | |
" chi2s_poly[inevents, itoy, ipdf] = chi2\n", | |
" nlls_poly[inevents, itoy, ipdf] = r.minNll()\n", | |
"\n", | |
" if ndof_previous is not None:\n", | |
" f = compute_Ftest(chi2_previous, chi2, ndof_previous, ndof, xvar.getBins())\n", | |
" Fs_poly[inevents, itoy, ipdf - 1] = f\n", | |
" pvalues_F_poly[inevents, itoy, ipdf - 1] = 1 - scipy.stats.f.cdf(f , ndof - ndof_previous, xvar.getBin() - ndof)\n", | |
" \n", | |
" t = 2 * (nll_previous - nll)\n", | |
" Lratios_poly[inevents, itoy, ipdf - 1] = t\n", | |
" pvalues_L_poly[inevents, itoy, ipdf - 1] = 1 - scipy.stats.chi2.cdf(t, 1)\n", | |
"\n", | |
" previous_prefix = pdf.GetName() + \"_\"\n", | |
" ndof_previous = ndof\n", | |
" chi2_previous = chi2\n", | |
" nll_previous = nll\n", | |
"\n", | |
" rtrue = true_bkg.fitTo(data, RooFit.Save()) \n", | |
" chi2s_true_model[inevents, itoy] = true_bkg.createChi2(data).getVal()\n", | |
" nlls_true_model[inevents, itoy] = rtrue.minNll()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Last toy plot" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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CFVyoKoPRQQDoDO2siqJoNBpp4rHBSBNVHMcaiaIo0iSkyxN0HY1Q7sZFROOa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\nTkSuQmCC\n", | |
"text/plain": [ | |
"<ROOT.TCanvas object (\"icanvas\") at 0x5ea4f30>" | |
] | |
}, | |
"execution_count": 14, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"canvas = default_canvas()\n", | |
"frame = xvar.frame()\n", | |
"data.plotOn(frame)\n", | |
"true_bkg.plotOn(frame, RooFit.LineColor(ROOT.kBlack))\n", | |
"legend = ROOT.TLegend(0.7, 0.6, 0.8, 0.9)\n", | |
"for color, pdf in zip(colors, poly_pdf):\n", | |
" curve_name = \"curve_%s\" % pdf.GetName()\n", | |
" pdf.plotOn(frame, RooFit.LineColor(color), RooFit.Name(curve_name), RooFit.FillColor(0))\n", | |
" legend.AddEntry(frame.findObject(curve_name), pdf.GetName())\n", | |
"frame.addObject(legend)\n", | |
"frame.Draw()\n", | |
"canvas" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Check $\\chi^2$ distribution for true-model postfit" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"chi2 mean = 50.9641253896\n", | |
"nbins = 50\n", | |
"chi2 mean = 45.9642446003\n", | |
"nbins = 50\n" | |
] | |
}, | |
{ | |
"data": { | |
"image/png": 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7bzezYcCTZrbG3Z9718pmcxMm69y9rmMxRSSXmdkMou45XaaCTNLOjL7ABcBL6dieO2+Z\nsQaYDtSlY5tS9LYBlQnTlURnwNpqUxHPw923x//uNrNfEl0CfVdB5u5z0xdZRHJN/CGrrnnazO7s\n7LZ0yVIyYRqw0p3DadzmU8D70rg9KW5LgFozqzazXsCNwIKkNguAWwDMbDqw390bzayfmZXE8/sD\nHwBWZC+6iBQiFWSSCZeT/oeCP40KMkkTd28C5gCPA6uAh9x9tZnNNrPZcZtHgQ1mVg/MAz4Tr14O\nPGdmy4DFwK/c/YmsvwkRKSi6ZCmZcAXw72ne5gvAeWaUuHMozduWIuTui4BFSfPmJU3PaWG9DcCU\nzKYTkWKjM2SSVmb0JOrr9UI6t+vOMeBlomJPRESkoKggk3SbCjS4szcD29ZlSxERKUgqyCTdriD9\n/ceaPQVcnaFti4iIBKOCTNJtOvC7DG37FWCMGcMytH0REZEgVJBJul1INKRA2rnTRDTW01WZ2L6I\niEgoKsgkbcw4CxgCrM/gbp4lGlZDRESkYKQsyMxsppmtMbP1ZnZHK23ujpcvN7Op8bw+ZrbYzJaZ\n2Soz+5eE9nPNbKuZLY1fM9P3liSgC4keKH4mg/t4Abg0g9sXERHJujbHITOz7sA9wDVEjwx5xcwW\nuPvqhDazgBp3rzWzS4B7genuftzMrnL3o2bWA3jezC5z9xeIniP3LXf/VqbemASRscuVCV4DJpgx\nIM1PAhAREQkm1RmyaUC9uze4+yngQeD6pDbXAfcBuPtioNTMyuLpo3GbXkB3YF/Ceq09tFfy10XA\nq5ncQfxw8WVEP5siIiIFIVVBNgrYkjC9NZ6Xqk0FRGfY4seLNALPuPuqhHafiy9xzjez0k6ll1yT\njTNkAC8Cl2VhPyIiIlmRqiDzdm4n+WyXA7j7aXefQlSgXWFmM+Ll9wJjiB4/sgP4Zjv3IznKjKFA\nKfBmFnb3AirIRESkgKR6luU2oDJhupLoDFhbbSrieW9z9wNm9muiS1p17r6reZmZfQ9Y2FoAM5ub\nMFnn7nUpMksYFwKvZbhDf7PfAT80o1uW9icZEn9ImxE4hohIcKkKsiVArZlVA9uBG4Gbk9osAOYA\nD5rZdGC/uzea2VCgyd33m1lf4P3AVwHMbIS774jX/yiworUA7j63Q+9IQsl4/7Fm7jSasRuYTBs/\nO5L74g9Ydc3TZnZnsDCS12ywfYkSBrXZ6BAHfJ9/I0uRRDqkzYLM3ZvMbA7wOFGn/PnuvtrMZsfL\n57n7o2Y2y8zqgSPArfHqI4D7zKwb0aXRH7n7U/Gyu8xsCtGlzY3A7LS/M8m2C4GHsri/F4mGv1BB\nJiJQwiBuY3ObbeZTlaU0Ih2W6gwZ7r4IWJQ0b17S9JwW1lsBXNDKNm/pWEzJAxcCX87i/l4A3gvM\nS9VQREQk12mkfukyMwYDg4ENWdxt8xkyERGRvKeCTNLhXGBlljvYrwbKzBiSxX2KiIhkhAoySYdz\nyXJfLndOE43af1E29ysiIpIJKsgkHbJekMVeRiP2i4hIAVBBJulwLrAywH5fAS4OsF8REZG0UkEm\nXWKGAecQ8AxZnEFERCRvqSCTrqoCjrizJ8C+NxEN3ZL8fFUREZG8ooJMuirU2THccaKzZLpsKSIi\neU0FmXRVqA79zV5BHftFRCTPqSCTrgpdkOkMmYiI5L2Uj04Sadbiw3u7bbuGwXOOWdUva9tcOXMP\n9X0FuMiMblkemFZERCRtVJBJ+yU/vPfEgO58ffhgPv38Uvpzqs11M/RQX3d2m7EPqAXWZmIfIiIi\nmaZLltJ56/+gjN4H99B/d9vFWOYtIXq4uYiISF5SQSadt+U9Ixmwc3voGESPUFJBJiIieUsFmXTe\nW2ePZNDmHaFjEBVkF4QOISIi0lkqyKTzDlaWc9a6XCnIpprp51lERPKT/oBJ5x0pK2fUkuAFmTu7\ngYPA2NBZREREOkMFmXTOqb7dOFY6nHFP7AodJabLliIikrdUkEnnbLh6KL2OHGRA48nQUWKvooJM\nRETylAoy6Zyt7ymn3+7glysT6E5LERHJWyrIpHN2Tyxn4PadoWMkeA24wAwLHURERKSjVJBJ5xyo\nHsHgN3PmDJk7O4CTkJknAoiIiGRSyoLMzGaa2RozW29md7TS5u54+XIzmxrP62Nmi81smZmtMrN/\nSWg/xMyeNLN1ZvaEmZWm7y1JVhwuK6d8WS6dIYOoH5kuW0q7dPbYlrCsu5ktNbOF2UksIoWszYLM\nzLoD9wAzgUnAzWY2ManNLKDG3WuB24F7Adz9OHCVu08BzgOuMrPL4tW+Ajzp7uOBp+JpyRdnusHR\noSMY83SuFWS601LapSvHtgRfAFYBnvnEkovMGGBGWegcUhhSPVx8GlDv7g0AZvYgcD2wOqHNdcB9\nAO6+2MxKzazM3Rvd/WjcphfQHdiXsM6V8df3AXWoKMsf2y8ahJ05TdnKw6GjJHmN6A+nSCpdOraZ\nWQUwC/gn4C+zmlw67zjTrcq+1mabJqYDm1tdfrqH8daPrzBjPTAKOGnGT4B/iLtOiHRKqoJsFLAl\nYXorcEk72lQAjfGn0FeBccC97r4qblPm7o3x142gTxh5pWFGOf3eysUDzzJgSugQkhc6e2wbRXTM\n+jbwJWBgBjNKuvWhN7e1UWwBzH/7ZMG7nerbje8//6ecLK0CPgSsAQYBfwOsNOPj7jyTxsRSRFL1\nIWvvqfjkO9scwN1Px5csK4ArzGzGu3bg7h3Yj+SCXeeWM2BHrl2uBNgE9NUlBGmHzh7bzMyuBXa5\n+9IWlkuhOt3DmPfq7RwfNIiySx5wZ6U7Te7sceevgT8CfmKmJ4ZI56Q6Q7YNqEyYriT6lNhWm4p4\n3tvc/YCZ/Zqow3Ud0dmzcnffaWYjgFZHezezuQmTde5elyKzZNq+MSMobci5M2TuuBnLgPOBJ0Ln\nkdTiD2kzAuy6K8e2PwSui/uY9QEGmtn97n5L8k50/Cogv5p3GScGDuKzk/6NHx8clbzYnafN+Cfg\nETMudedQgJSSZek8hqUqyJYAtWZWDWwHbgRuTmqzAJgDPGhm04H9cR+LoUCTu+83s77A+4GvJqzz\nSeCu+N+HWwvg7nM78oYkCw6NLGfskytCx2jFMmAqKsjyQlyg1DVPm9mdWdp1Z49tO4G/jV+Y2ZXA\nX7dUjIGOXwVj94R+rLjpI1z7me/S5+DpNlreQ/SB8LvAp7MTTkJK5zGszYLM3ZvMbA7wOFGn/Pnu\nvtrMZsfL57n7o2Y2y8zqgSPArfHqI4D7zKwb0aXRH7n7U/GyrwP/a2a3AQ3ADZ19AxLA0aFlVL2Y\ni5csAZYS9e0QaVUXj23v2lx2Ukswj8y/nvLlrzHlvi1tNYvP0v8lsN6M89x5PUsJpQCkOkOGuy8C\nFiXNm5c0PaeF9VbQyhAE7r4XuKZDSSU3HC7rxam+JYz+7d7QUVqxjKiDrUibOntsS1r+LPBs+tNJ\nzlj+JxXsnHIhsy/8v+1p7s7B+NLl14nuxBVpF43ULx2z4X3D6HPgLXqcyNWzAquB0Wb0Dx1ERArA\ni1/6AOMffZxha46mbvy2ecAEM67KVCwpPCrIpGN2XFBGv92NqRuG4c4poqLs3NBZRCTP7ZhSwltn\nn8vVf/dCR1Zz5wTwd8Bder6utJcKMumYPbVllGzP2YIs1tyxX0Sk8+ruvIzhK5cydF1Hzo41ewgo\nAS5PcyopUCrIpGMOVpQxeGOuF2RL0QCxItIVTb2NjVdfwbT/qOvM6u6cAf4T+Exac0nBUkEmHXOk\nrIzhK3O9INOI/SLSNc/+/bn0OnyQqT9se2T/tt0PfNCMEemKJYVLBZl0zLEhwxn921wvyF4HzjFL\nfRexiEiL3rjhCs5e2KU7aN05QHTp8s/SE0oKmQoyab+msX3xbt0pX5bTI1C7cxDYAdSGziIieWj3\nhH4cqKphxldfTcPW/hO43YyeadiWFDAVZNJ+Jy4ZQt+9u+h2JnSS9tBlSxHpnJf+v/MZvGENJTtO\ndnVT8eCwG4Frux5MCpkKMmm/U+cNoX/uDnmRZDnRI0xERDqm4aoLGPP0a2nc4g+AT6Rxe1KAVJBJ\n+zXVDKFka74UZDpDJiIdd6a0O/uqxzP9O+l8Xu8vgGvMGJTGbUqBUUEm7dc0+iyG1OdLQaYzZCLS\ncUdvGMygzfWcVX8sXZt0Zz/RA6g/kq5tSuFRQSbtd2bEEMqX50tBtgXobUZZ6CAikkeOfXQo1c+m\n83Jls58AN2Vgu1IgVJBJu5jRjdPDhzDm6V2hs7SHO47OkolIRxwZ1pMTlw3mkruXZ2DrC4H3mDEs\nA9uWAqCCTNprJHbiJIMbjocO0gHLUT8yEWmvlz8znh7rDlP++uF0b9qdI8CjwMfTvW0pDCrIpL1q\n6b5zT+gQHbQMnSETkfZquHoSfZ7Zn8E96LKltEoFmbRXLd237wsdooN0hkxE2m/3xIn0eSyTBdmT\nwBQzhmZwH5KnVJBJe9XQfdPe0CE6aBUw1oy+oYOISI7bdtFATpQMpnddxp5E4s5x4DfArEztQ/KX\nCjJpr1p6rM+rgsydE8B6YHLoLCKS45bdOpHBG9dipzO9pwXAdZneieQfFWTSXjX0ej3fLlmCBogV\nkfbYMn0iI5eszsKeHiUaJLZPFvYleUQFmaRkRjdgHL1eyqszZDENfSEibTvTDfaMn8jkhzJekLmz\nG1gBzMj0viS/9AgdQPLCSGA/3XedChXABtuXKOnEY0cGz67mwB2XwpjPZSCWiBSC1R8bgZ05Te2i\nXTyflT02X7Z8rK1G7TruHeKA7/NvpDGbBKKCTNqjFqgPmqCEQdzG5g6v1/jCXu4t/7gZFg8WKyLy\nTqs/NpGh61bT7Uy29rgAeMqMz7Z5XGrPcW8+VWnOJoGkvGRpZjPNbI2ZrTezO1ppc3e8fLmZTY3n\nVZrZM2b2hpmtNLPPJ7Sfa2ZbzWxp/JqZvrckGVBD1Dk+/5StPIydOAlUh44iIjlqx9Szqfjd2mzt\nzp21wBFgarb2KbmvzYLMzLoD9wAzgUnAzWY2ManNLKDG3WuB24F740WngC+6+2RgOvBZM5sQL3Pg\nW+4+NX61edpWggt/hqwremxpRP3IRKQlZ7rBgdE1TPpptj90PgZ8MMv7lByW6gzZNKDe3Rvc/RTw\nIHB9UpvrgPsA3H0xUGpmZe6+092XxfMPA6uBUQnrWTregGRF/p4hA+ixrhHdaSkiLVn34TK6nTpJ\n9XPZvotcBZm8Q6qCbBSwJWF6K+8sqlprU5HYwMyqiU7NLk6Y/bn4Eud8MyvtQGbJvvw+Q9bzdZ0h\nE5GWrf1wDYMbQhzfngUuNGNggH1LDkpVkLW3E3Ty2a631zOzAcDPgC/EZ8oguqw5huisxQ7gm+3c\nj2TZ20Ne5HNB1vu3KshEpGU7p9RQtjzrxzd3jgIvAVdle9+Sm1LdZbkNqEyYriQ6A9ZWm4p4HmbW\nE/g58D/u/nBzA3ff1fy1mX0PWNhaADObmzBZ5+51KTJLeo0EDrhz2PL1Xp7eL+wDhpsxyJ0DoePI\n75nZDDQek4S0b2wNl/7bbwLt/XGiy5aPBNq/5JBUBdkSoDa+5LgduBG4OanNAmAO8KCZTQf2u3uj\nmRkwH1jl7t9JXMHMRrj7jnjyo0SD5LXI3ee2761IhuR3/zEAO+VEP2PnAc8FTiMJ4g9Ydc3TZnZn\nsDBSfLZfUMKpvgOY9LPtgRI8BizQsDwCKQoyd28yszlEVXx3YL67rzaz2fHyee7+qJnNMrN6ott4\nb41Xvwz4BPC6mS2N5/1NfEflXWY2hejS5kZgdtrfmaRLfvcf+73lRJfIVZCJSGTlTTUM2vIm3ZtC\nFUNvAL0ohA++0mUpB4Z190XAoqR585Km57Sw3vO00kfN3W/pWEwJqIbCKMiWAReFDiEiOWTbJTUM\nWxXs+OaOm/EE0WVLFWRFTs+ylFQK5ZNb8xkyEZHIntoaqutCf+B8AvhA4AySA1SQSSqFcoZsBTDR\nTI8LExHgcFkvjg4dyXk/3hQ4ydPAFTo2iQoyaZUZRjTkxZuhs3SVO4eJ7hA+O3QWEckBb9xQSb+3\ndtB/96mQMdzZBWxCXSqKngoyaUs5cMSdg6GDpMkydNlSRAA2vbea0oaNoWPEngLeFzqEhKWCTNpS\nKJcrm6lHzeWGAAAgAElEQVQgE5HIWxPHUL5cBZnkDBVk0hYVZCJSmA5UjWHc4w2hY8R+C1xsRt/Q\nQSQcFWTSloIsyOK+cSJSrHaeN4CmPv0Z/6vG0FEA3DkEvE40fqcUKRVk0pZCK8h2AmeIHgclRc7M\nZprZGjNbb2Z3tNLm7nj5cjObGs/rY2aLzWyZma0ys3/JbnLpstUfq6Zk+6aAA8K2RJcti5wKMmlL\nQRVk8aNJdNlSMLPuwD3ATGAScLOZTUxqMwuocfda4HbgXgB3Pw5c5e5TiB7HdZWZvTeb+aWLtk0b\nw5D6XOk/1uwp4JrQISQcjXsiLYov66WvIDvOdKuyr3V6/SamA5vTkKS5IPt1GrYl+WsaUO/uDQBm\n9iBwPbA6oc11wH0A7r7YzErNrMzdG939aNymF9Fj5fZmLbl03Z7aaib/9LehYyR5CZhgRqk7+0OH\nkexTQSatGQo0ubMvLVvrQ29u60JBNZ8r05IjKsg+lqZtSf4aBWxJmN4KXNKONhVAY3yG7VWicfru\ndfdVGcwq6XSmGxwaVc2Eh+8PHSWROyfMeAm4HFgYOo9knwoyaU1BXa5MsAz4h9AhJLj29h1KvgHE\nAdz9NDDFzAYBj5vZDHeve9fKZnMTJutaaiNZ9uYHhtGt6RQVLx8IHaUFdcBVqCDLG2Y2A5iRjm2p\nIJPWFGpBtg4YaUZJfGeTFKdtQGXCdCXRGbC22lTE897m7gfM7NdEo6zXJe/E3eemIauk0/oPVTNw\na0PoGK14hqhvo+SJ+ENWXfO0md3Z2W2pU7+0piALMndOAyuB80NnkaCWALVmVm1mvYAbgQVJbRYA\ntwCY2XRgv7s3mtlQMyuN5/cF3g8szV506ZLG80Zz1rqG0DFasQSoMWNI6CCSfSrIpDUFWZDFlgJT\nQ4eQcNy9CZgDPA6sAh5y99VmNtvMZsdtHgU2mFk9MA/4TLz6COBpM1sGLAYWuvtTWX8T0jn7x1Qx\n8pV03CCUdu6cBH5H1I9MiowuWUprCr0gS+7ALUXG3RcBi5LmzUuantPCeiuACzKbTjLCu8Hh8iom\nPJKTBVmsjqhP0iNhY0i2qSCT1tQAb4YOkSGvAX8ROoSIZNmpc/rQ/cQxylYe7tJ2Ug3jc4gDvs+/\n0cmtPwP8VyfXlTymgkzeJe6/0APYHTpLhqwAxpvR250TocOISJacnD6Agds2dXk7qYbxmU9VF7b+\nKjDWjCHvuKVECp76kElLaoD6eGT7guPOcaKzf5NDZxGRLDp50QCG1He9IMsgd04BL0Daxl6UPKGC\nTFpSA6wPHSLDXkP9gESKy6nzShjxai73H2tWR5rGtpL8oYJMWlJL4Xbob6Y7LUWKyZlucGpif85e\nmA8F2bPoDFnRUUEmLSnkOyybqSATKSYbrhmKHT/DyNfyYUDoV4GxNFX3CR1EsidlQWZmM81sjZmt\nN7M7Wmlzd7x8uZlNjedVmtkzZvaGma00s88ntB9iZk+a2Toze6J5kEXJGcVwyXIZcJ4Z3UMHEZEs\nqP/gaHq+0bW7K7Mk7kf2Ekdv6MrNAZJn2izI4gfo3gPMBCYBN5vZxKQ2s4Aad68FbgfujRedAr7o\n7pOB6cBnzWxCvOwrwJPuPh54Kp6W3FHwlyzdOQDsBMaHziIiWdB4fhU9l+VFQRar48QVKsiKSKoz\nZNOAendvcPdTwIPA9UltrgPuA3D3xUCpmZW5+053XxbPPwysBkYlrxP/+5EuvxNJCzMGA72BXaGz\nZIEuW4oUi31jqui1JJ8Ksmc5dd7o0CEke1IVZKOALQnTW/l9UdVWm4rEBmZWTfSHb3E8q8zdG+Ov\nG4GydieWTBsHrC/UIS+SLEV3WooUvjPd4PCIKnq/mE8F2SucHj6EPTV9QweR7EhVkLX3j7K1tp6Z\nDQB+BnwhPlP2zobu3oH9SOYVQ4f+Zhr6QqQYbL5sMLjTfdPJ0FHay52T9NiwneWfrAmdRbIj1Uj9\n2+AdYwVXEp0Ba6tNRTwPM+sJ/Bz4H3d/OKFNo5mVu/tOMxtBG5fHzGxuwmSdu9elyCxdU/D9xxK8\nClxghhXJGcGcY2Yz0HhLkmlvfrCSkh2bsTz7Ne+1dBOb3ns20dNFpMClKsiWALXxJcftwI3AzUlt\nFgBzgAfNbDqw390bzcyA+cAqd/9OC+t8Ergr/vdhWuHuc9v1TiRdaogGJSx47uw24wDRZdpiKUJz\nSvwBq6552szuDBZGCtfOKZWUNmyhiQGho3RI799s5q1/viJ0DMmONgsyd28ysznA40B3YL67rzaz\n2fHyee7+qJnNMrN64Ahwa7z6ZcAngNfNbGk872/c/THg68D/mtltQANwQ7rfmHRaDfC90CHSqq0H\nAfd89Rh9F/6rVc1d1er6XXtQsIiEtndcFTWPvcJ2JqZunEP6/WIbB+aVs3dsX4ZsOBY6jmRWyoeL\nu/siYFHSvHlJ03NaWO95Wumj5u57gWs6lFSypfAuWbb1IOAHtq3m5BX9+VTGHhQsIqEdHlHJ2Kd/\nnncFWbcDpynZ3sDyW8Zx1dyVoeNIZmmkfnmbGYOAfkTjcxWHUa9sYt8Y3VouUqjeGt+PU30HULNo\nd+gonTJs1Xo2Xa7xEouACjJJNA6oL6oO7hN+uZnDI6o4o18FkYK09vpK+u/aSvem/DyujXlmHW9N\nUEFWBPRXSBIV3uXKVMpWHqb7iWPUzxwWOoqIZMC2iyoYtHlL6oY5asoPN3B02EgOVPQOHUUySwWZ\nJKql8J9h+W4Dt23izQ/osqVIIdo7vophq1vvI5rr+u8+xYCdW1h267jQUSSzVJBJovHAutAhsm7I\n+k006hElIgXpYEUlVc/n7xkygGGr1rLpCl22LHAqyCRRcZ4hG7VEHftFCtGRYT05VjqcCQ9vDx2l\nS6qfXcdu9SMrdCrIJFFxniFr7th/ukfyI8BEJJ+tvW4kffc10nd/U+goXTLlhxs4UlbJ4bJeoaNI\n5qggEwDMOItoXLr8vDW8K8pWHqbH8aPUf0gd+0UKyZZLKxm4Jb8vVwKU7DhJ/8YtLP302NBRJHNU\nkEmzWmBdUQ15kWjglo3UzxwTOoaIpNHuCZWctT7/CzKAYavX0XClLlsWMBVk0mw8xdh/rNnQtQ3s\nPL86dAwRSaMDVRWMXFIYBVl13Vp2Tzo7dAzJHBVk0qyWYuw/1qzqhQb2V1eHjiEiaXK6h3FkeAVn\nL9gaOkpaTP3BmxwuVz+yAqaCTJoV9xmyST/dzJHhFRwf2D10FBFJgzc/MJQex48wdN3R0FHSIupH\ntpWlt6ofWYFK+XBxKRrFfYZs0NYT9Nm/m1UfH8UF38/fQSRFJLLx6kpKtoe5XHmc6VZlX2uzzSGm\nUMKyNts0MR34/fFo2Op1NMwYz+VfX5OOmJJbVJAJZhjFOgZZokGbGmiYMUYFmUgBaDy3ksEbw1yu\n7ENvbqPt48h8rmxXm0TVdWtZ8ufXdjmf5CRdshSAcuCYO/tDBwlq+Bsb2T25OnQMEUmD/WMqKVte\nGB36m6kfWUFTQSZQ7P3Hmo15poH9VdWhY4hIGhwaUcm43xRWQfb2eGTqR1aIVJAJFHv/sWYTf76d\nE4POYn9V79BRRKQLdp43gDM9e1P9zJ7QUdJu2Kp1bLxKw18UIBVkecTSoJVN6wwZQO/Dp+m/axtv\n3KDnWorks/V/UMGAxi10OxM6SfqN0XhkhUqd+vPJIP6MQYyGTo2mb+xnqFXZux+N1PO16+n7ixVW\n9bW27wpKvuOnEA3esJEtl44h8Yxhe+6Yas0hDvg+/0aa0olIe2y/sJJBmwrrcmWzqd/fwDNfreBA\nRW8GbT0ROo6kjwqyfFJCCX/ITgbR8V/CNZTxW0q4jVffteyuqhLet3EV59P2HUnJd/wUohGvbqB+\n5sXvmNeeO6ZaM5+qdMQSkQ7YW1PJqJcLc2iIAY0nKdmxiaWfrmHGP7wROo6kjy5ZFrtTfbtxfNAw\nap5oDB0lJ0x8eAMHqsZxRr8aInnrYEUVo58r3LP5w1esoWHGhNAxJL30V6fYbbh6KL2OHKD/7lOh\no+SEquf2YmdOs+GaoaGjiEgnHBnWkxMDz+LsR3aEjpIxY3+zlt0T1Y+swKQsyMxsppmtMbP1ZnZH\nK23ujpcvN7OpCfO/b2aNZrYiqf1cM9tqZkvj18yuvxXplK3vKaffWztDx8gZ3c7AoM0bWHudbisv\ncJ09tplZpZk9Y2ZvmNlKM/t8dpNLm9ZcP5K++xrpc/B06CgZM/X7Gzk2pJy3xvcLHUXSp82CzMy6\nA/cAM4FJwM1mNjGpzSygxt1rgduBexMW/yBeN5kD33L3qfHrsS68B+mKtyaUUbJdBVmi4as2sGPq\nuNAxJHO6eGw7BXzR3ScD04HPJq8rAW25rIqBWwuzQ3+zPgdPM3Drmyz7VG3oKJI+qc6QTQPq3b3B\n3U8BDwLXJ7W5DrgPwN0XA6VmVh5PPwfsa2XbrQ3BINl0YHQ5gzeqIEs0+tk32TdOZ8gKW2ePbWXu\nvtPdl8XzDwOrgZHZiy5teuvsSs5aW9gFGUDZ62vZdLn6kRWQVAXZKCDxB3trPK+jbVryufgywHwz\nK21He8mEw2XlDF+pDv2Jzv3JZo4NKefQCD2epHB19thWkdjAzKqBqcDitCeUzjlQVcmoVwq/IKtd\ntIY9E9SPrICkKsjaO95V8tmuVOvdC4wBpgA7gG+2cz+SbkeHljP6WZ0hS9RvTxP9dm9jxc0aILZw\ndfnYZmYDgJ8BX4jPlEloTb2NI8NHcfYjYR4qnk3n/2gzJ0qGcGpS/9BRJD1SjUO2DahMmK6Ed41V\nldymIp7XKnff1fy1mX0PWNhaWzObmzBZ5+51bSaW9ts1qT/erTsjlxwIHSXnnFX/JpsuH8el39IT\nDDLIzGYAMwLsukvHNjPrCfwc+B93f7i1nej4lWXrP1RGzyMHGbLhWOgoGdfz2BlKN67l6E3VoaMU\ns3Qew1IVZEuA2vi0/HbgRuDmpDYLgDnAg2Y2Hdjv7m1eAjOzEe7efEvyR4EVrbV197kpMkpnbby6\njL57Gwvy8SJdNWLJBtb/wSWhYxS6uECpa542szuztOtOH9viR5DNB1a5+3fa2omOX1nWMKOCkh2F\nf3as2chXV7PuykmhYxSzdB7D2rxk6e5NRAekx4FVwEPuvtrMZpvZ7LjNo8AGM6sH5gGfSQj2E+BF\nYLyZbTGzW+NFd5nZ62a2HLgS+GJn34B0QeN55Qxo1OXKlkz6+ZscqBrH6R66+aQAdfHYdhnwCeAq\nDd2TY3adU8mQNwt3QNhkk3+6mpPnjTHTTXKFIOWjk9x9EbAoad68pOk5rayb/Imzef4tHcgombJ3\nXDkDt6gga0nVi/vpfvI4az5SHnUTkkLT2WObuz+PBtXOTfvGVHHeA0+HjpE14xc2X40aD6wNGUW6\nTgeVYnZoZBlD16oga83gDetZd21N6Bgi0g5ucLi8kppFhX+HZbNuZ6DX6xuBa0JHka5TQVbMjgwv\nZ+TLKshaM2JpPTunaOBFkXxw6pwBYEbFS/tDR8mq3s9uBN4fOoZ0nQqyYnViQHdODBzKuCd3h46S\ns85esJ59Y1SQieSD4+8vp2T7pqK7SanfAw3ADLPUXZAkt6kgK1Yb3zeUXof30Xd/U+goOWv8wkbO\n9OjJqdreoaOISAqnLhrB4I3F06G/Wc81R4BNwEWho0jXqCArVlsuHcGAXTtSNyxi3c5A6aZ6jn9g\nYOgoIpLCqQnllC0vvoIs8iTwwdAhpGtUkBWr3ZNGMnDL9tAxct7wFes58d5BoWOISApN1eWMe6JY\nC7LHUUGW91SQFav9o0dy1joVZKnUPFHPyWk6QyaSw8wYBr17MfY3b4XOEshzwDlmDA4dRDpPnQCL\n1eHyEYx6+YnQMXLeuQ9sYeF3e7NrUn+GrzoSOo5IoTGz0Qyk7ZtnmjjDUZa4+8FWWkyl+5aifeqI\nO8fNeI5o+Iufhs4jnaOCrBid6tuN46XDqV2kIS9S6XnsDD2XHWTZp8bzgS8vDR1HpAAN5UKuZRh7\nW22xmn5s4kqrsu4tLu/3w0vxM8U+Wv3jwExUkOUtFWTF6M0PDKPnkQMMaDwZOkpe6P3bA2y54mxA\nBZlIJpRwmEm0/gGxnlGUMJDbWN3i8v+4aCan/rPwHyjetseAL5th7njoMNJx6kNWjHSHZcf0eXw/\nb02YEDqGiLTi4Kgqev/ucOgYga0HTgKTQweRzlFBVox0h2XH9H7+MCf7D2L7BSWho4hIkj01fTnV\nbyA9Xy/qM2TxWbHmy5aSh1SQFSPdYdkxdhpKG9ax/JazQ0cRkSRrPlJJ/11bsNOhk+SCx1BBlrdU\nkBWj6A5LXbLsiBFL17LlPbpsKZJrtk4fTemm4nmgeNueBi4xQ0P15CEVZMVGd1h2ztkL1rJnvAoy\nkVyzZ3w1ZSsaQsfIBe4cAl5EDxvPSyrIio3usOycST/bzulefdh41ZDQUUQkwYHK0Yx9siF0jByy\nELg2dAjpOBVkxUZ3WHZO9yZn8Ia1rLxJ/chEcsWuSf1p6juAsxc0ho6SQ34NzDLT3/d8o/+wYqM7\nLDtv5Ktr2DptYugYIhJb/YejGbBzM92bNO5WzJ2NwG7g4tBZpGNUkBWbfWMqGLpmW+gYeem8H69i\nz/hJnO5R7COCi+SGbRePZvCGTaFj5KBfocuWeUcFWbE5NKKC0c9tDR0jL417cg89jh/h9U9Uho4i\nIsCe2mrKlzWEjpGDVJDlIRVkxeRMaXdOlgym9tfqb9FZw994g9Uf1UjYIrngYEU1tYsaQsfIQS8B\nlWbow2MeUUFWTE5eVkrfvTvpfVgjKHbWmKfeYOdUFWQioW2ZPgjv3oMxT+0JHSXXuNMEPApcHzqL\ntF/KgszMZprZGjNbb2Z3tNLm7nj5cjObmjD/+2bWaGYrktoPMbMnzWydmT1hZqVdfyuS0smLSxm4\nTZcru+Li/1rP4bIq9o7tGzqKSFFb++HRlGzfRLczoZPkql8AHw0dQtqvzYLMzLoD9xA9imEScLOZ\nTUxqMwuocfda4Hbg3oTFP6Dlxzh8BXjS3ccDT8XTkmlN5w5myHoVZF0xoPEkA7e+yauzNfyFSEg7\nLqxmSH1D6Bg57AngIjPOCh1E2ifVGbJpQL27N7j7KeBB3n0K9DrgPgB3XwyUmll5PP0csK+F7b69\nTvzvRzoXXzqk6exSRr6qgqyrRi5ZScOMc0LHEClqe2uqGfFqQ+gYucqdo8BvgA+HziLtk6ogGwUk\nPiNsazyvo22Slbl7c8fyRqAsRXvpqjM9jKYxgxm/UM9866rJP13F7gmTOaMumCJBnO5hHBw1hom/\nbAgdJcf9El22zBup/qK0d7C95HGZ2j1In7t7R9pLJ701vRQ7epJha46GjpL3Jv5iB+bOGzek+uAh\nIpmw9royepw4yqglB0NHyXG/Bq4yY0DoIJJajxTLt8E7bputJDoD1labinheWxrNrNzdd5rZCGBX\naw3NbG7CZJ2716XYtrRk11Xl9Khv6fKxdFS3MzB8xXJW/Mn5nPugBtntAjObAcwIHEPyTf2HxlK6\naUPoGLnOnX1m/I6oL/fPQueRtqUqyJYAtWZWDWwHbgRuTmqzAJgDPGhm04H9CZcjW7MA+CRwV/zv\nw601dPe5KbYl7bH//BH0WL0/dIyCMf7Xy1n8+Y8S3Vqek2ywfYkSBnV6A4c44Pv8G2mM9C7xB6y6\n5mkzuzOT+5MCsfO8sQxf8WboGHniF8DHUUGW89osyNy9yczmAI8D3YH57r7azGbHy+e5+6NmNsvM\n6oEjwK3N65vZT4ArgbPMbAvwf939B8DXgf81s9uABuCGDLw3SXSoppye338rdIyCMe2e9dTdOZwt\n0wdR+dKB0HFaVMIgbmNzp9efT1Ua04ikz/6xY7no/38udIw88QvgX83o786R0GGkdanOkOHui4BF\nSfPmJU3PaWXd5LNpzfP3Ate0P6Z02dHKcga9VB86RsHoffg0Q9etZMlfnE/lS78NHUekaOwd25fj\ng4Yy+SHdMd4O7uyOL1teCzwUOo+0TreJFYPdE/pxul9fer52OHSUglL99HI2X3p+6BgiRWXlTdUM\n2LlZTxzpkAeBm0KHkLapICsGq/6omn5bd2BNups1naZ/dyUHqmrYX9U7dBSRorHl0rEMWa8O/R3z\nMHC1WRf6lErGqSArBtumVVOyVncDptvghuMM3LqBxZ/Xsy1FsuWtCeMY9bIKsg5wZz/RzTN6tmUO\nU0FWDPbUVjNkifpbZMLo516j/oMXho4hUhSaB4Sd/FPdYdlxumyZ41SQFYODFdWMeFxnyDLh0n9b\nyt7ayRwa0St0FJGC1zwg7MjXDoWOkocWApeaMTx0EGmZCrJCt/nSUrxbd85arDHIMqFs5WFKtm3k\n+S+fFzqKSMFbe10tgzesDx0jH7lzGHgE+OPQWaRlKsgK3doPV1OyrQE7EzpJ4Rr79Cu8+cGLQscQ\nKXg7po5n5KvrQsfIY/cBnwodQlqmgqzQ7biwmrPqG0LHKGiXfmMZ+8ZOYF91n9BRpP3MbKaZrTGz\n9WZ2Rytt7o6XLzezqQnzv29mjWa2InuJi5wb7Bs7nok/1xmyzqsDBpsxJXQQeTcVZIVub001I5c0\nhI5R0IauO8qgzfW8+CWNSZYnzKw7cA/RM/4mATeb2cSkNrOAGnevBW4H7k1Y/IN4XcmWU5dEQzaM\ne2J34CR5y50zRGfJPhk6i7ybCrJCdqYbHBoxmgm/bAgdpeCN/c0rvHmNLlvmj2lAvbs3uPspojvQ\nkocEuI7ojxfuvhgoNbPyePo5YF8W88qx6yoYvGEd3dT9oovuB/7EDN2IlGNUkBWy9R8aTvdTx3VH\nUha89+vLODC6lh1TSkJHkXYZBWxJmN4az+toG8mWk++pYMRS9R/rInfqgbXArNBZ5J1SPstS8lj9\nh6oZuHVT6BhFoXTzCYatWsZzfzONG258KnQcSam9T62wTq4XrWw2N2Gyzt3rOrK+JGg6ZxQTvvtg\n6BgF4r+B2UQj+EsXmNkMYEY6tqWCrJBtv7CG4SvUATZbzn3gRV748k2c6faULqvkvG1AZcJ0JdEZ\nsLbaVMTz2s3d53YmnCQ5cvFAvFcPzl6wM3SUAvFT4JtmjHVHTz3ogvhDVl3ztJnd2dlt6ZJlIdtb\nO56aJ+pDxyga07+zntO9+rD8lqrQUSSlJUCtmVWbWS/gRmBBUpsFwC0AZjYd2O/ujdmNKQDs/1g1\nPVZt0wed9HDnGFFfstmhs8jvqSArVLsm9edEyWDOfWBL6saSFt2bnMoXXuS1/3Np6CjSNndvAuYA\njwOrgIfcfbWZzTaz2XGbR4ENZlYPzAM+07y+mf0EeBEYb2ZbzOzWrL+JYnLk0tH0WqzHv6XXfwG3\nmtE7dBCJ6JJloXr9EzUM3LqBnsf0kTKbLv3W73hg4d9yrPRn9N3fFDqOtM7dFwGLkubNS5qe08q6\nN2cwmiQ60w2OnTeOwX//y9BRCok7681YDnwc+HHoPKIzZIVry3tqGb5K/ceybexTexiwcyvPfHVq\n6sYiktLqj42AM06v5zTMSPrdC3w2dAiJqCArVHvOrqX6GRVkIUz+6TOs/thVoWOIFIQ3/mgSfZfX\nYx26wVXaZwFQbsZ7QgcRFWSF6UBFb44OHcn5P2oIHaUozZj7OicGDmbpp9S5X6Srdlw4mZKn3gwd\noxC50wR8G/ir0FlEBVlhev1Px9C/cTP9d58KHaUo9Tx2hjFPP8vLn50ROopIXjt6Vg8OVNZw1v0b\nQ0cpYD8ArjRjXOggxU4FWSFquGI8Q9douIuQrrrzeXadM5WmsX1DRxHJW0tm19J/11Z6bTkROkqh\ncucw0UCxXwydpdipICtEb02qpeoF9R8Lqfz1wwxbtZwDfz8ldBSRvPXm+ydTvvyN0DGKwL8TPd9y\naOggxSxlQWZmM81sjZmtN7M7Wmlzd7x8uZlNTbWumc01s61mtjR+zUzP2xH2V/XmUPloLpqnZ76F\n9p7v/IZjH71Y4/yIdNLucyYxfuGq0DEKnTs7gP8F/jJ0lmLWZkFmZt2Be4CZwCTgZjObmNRmFlDj\n7rXA7US30aZa14FvufvU+PVYGt9TcXvlLyYycNsGSnacDB2l6J3/o6302NwIfDJ0FJG8s/GqIZzs\nP4ipP2wIHaVI/DMwW2fJwkl1hmwaUO/uDe5+CngQuD6pzXXAfQDuvhgoNbPydqyb/NBeSYeGqyYz\n8lWd4s8VJd94AbjDTIMwi3TIktlTGfbGcnqc0HgXWeDOJqJnXOqOy0BSFWSjgMRH72yN57WnzcgU\n634uvsQ538xKO5RaWnamG+yeOJnJD60MHUVi/X+0lehn/4bQUUTyypZLp1L76NLQMYrMPwO3mzEs\ndJBilKoga+8nk46e7boXGANMAXYA3+zg+tKSNR8pBzMm/mJH6CjyDv8M/K2ZbqIRaZftF5RwZHgF\n0+9eHTpKMXFnM/AQ8OXQWYpRqsso24DKhOlKok/7bbWpiNv0bG1dd9/VPNPMvgcsbC2Amc1NmKxz\n97oUmYvXyhsnM2z1G3TT4ytzzBPAYeAm4IHAWXKKmc0AZgSOIbnm5c9N4ax1K+m3R8+Dzb5/BFaY\nca87G0KHKSapCrIlQK2ZVQPbgRuB5IfqLgDmAA+a2XRgv7s3mtme1tY1sxHu3nwW56PAitYCuPvc\n9r+dIrf9onOY/LNnQ8eQd3LHzbgD+IEZP3dHYyrF4g9Ydc3TZnZnsDCSOzZdPpWzF7wQOkYxcmeH\nGd8Bvo66WmRVm5dQ3L2JqNh6HFgFPOTuq81stpnNjts8Cmwws3pgHvCZttb9f+3debRV5XnH8e9P\nUBCQKXExqzghIioKEY0KUlAhDUkT42xsa6Mm2qiJNaDtsmm0znWMUxUcWGqsrYqtEHGojaI4oKJR\nFBXEicGBSQFRnv6xN3oZLvdeOJd373N/n7Xedaa9D8+7OPc5z9n7fd+dv/VFkqZJegkYhBek23hL\nOm65LqgAAA9XSURBVG3Bou470P+66alDsbVF8DjwGnBS6ljMCu3jHbdkYY8dGHiFx8KmcxkwUGL/\n1IE0JXXO/IqICcCENZ67YY3Hp9Z33/z5nzYsTKvT5DP70Pb9t+kwa1nqUKxWo4FJErdEsCh1MGaF\n9NSvdqf9rDdoP9tHkhOJYKnEaOByiX0i8DiYTcBT8avFjOED6Pnos6nDsNpFME1iAnAOsM5Fls2a\nvDcP3Zde9z+ROozSWMZAbaPzan19MQvj07hkA975TuDnwMnAtRsYnTWAC7JqsGCbFnyy464cfti4\n1KFYnUaRDZi9PQKfkjGradagjizusg2DznsxdSil0ZIWnMDsWl+/mW025G0jWClxIvC4xPiItSb0\nWYV5Gn41ePKsPWg3+022nv556lBs/SKYA5wLXOdlMMzWMPnMgXR54TnPriyGCF4lOzp2depYmgJ/\nIVSDt4YNYIdJPl1ZHjcALfEllcy+sXIzeGf//eg3xrMri+VfgV0kfpI6kGrngqzs5u/SioXb7sR+\nl7yUOhSrnwi+IptteaG01pUvzJqmKaftxGZfrqDfmHdSh2LfyJfpOR64RlptbVGrMBdkZTf5zH50\neOs1z64slwimAtcAt/jUpRkw7Zj92O7xyV7YungieAa4Ahgn0Sx1PNXKXwRlN2P4Aexy/9Opw7AN\ncgHQGvhl6kDMklrcqxXz+uzJgec5lxXXxcBK4OzUgVQrz7Iss+f/bltWtG7L4N9OSx2K1WJ9U9J7\nAMu/O5X5E8/Xt4/rQ6v75q61zYZPWTcrj9f/pT+dpz1PlxcXpw7F1i2CrySOA56ReD6CB1PHVG1c\nkJXZs6cMYftH/pfmy+t7EXjb1Oqaks6Ts5l44zim3vpjDht0wVpfSBs4Zd2sPPq0ZO6IvTn86AtS\nR2LrF8F7+eD+eyUOjMBXhqkgn7Isqw/33Ir5u+zOkHO8gGLZHfrr5+n+9BTuHH8Sy9p6fIY1MTd9\nnzZvvEuvB+aljsTqFsGTZOspjpfomDqeauKCrKwe+90BdHp5qtceqxLHfG88my9dym2PHM1K/1la\n0yDRHPY8lu0v99ixEolgDHAvMEFiq9TxVAtn/jL6/FvNmTl4EAOveDR1KFYhzb4Mjht2E4u6duO2\nh3/sosyaiJ/Csnn0GOdV4MtnFPAicL9Ey9TBVANn/TJ64MYhtH1vFrvf8X7qUKyC2s9ezvF/cRXz\n+vbhrvuGpw7HrDHlR1bOg1svTx2LNVwEAfwCmEtWlLVOHFLpuSArm092bsWM4YcwdPS9qUOxRrD1\n9M85+ntXMvu7+3L7xJGEUkdk1lhGAQ/D6a+mDsQ2TL7I9XHAB8AkjynbOC7IyubRaw+m07Sp9L5v\nTupQrJF0f2Yhf33QxczZYzfmPzzCCzFatZHYDjgZr2lVehF8CZwAPAX8n0TPxCGVlguyMll+QAc+\n2G8fRpz6QOpQrJF1nraEn+1zGV916QD8t395WrWQENnFqq+MwGPHqkAEK4EzgRuBpySGJQ6plFyQ\nlYREMz4ZewQ9H3yEbs8tSh2PbQLtZy+n0953Aq8Bz0n0Sx2SWQWcAnQGLkwdiFVOBBHBVcARwG0S\n/yyxeeq4ysQFWXmcCRLDj34kdSC2CW22dGUEvwJGAw9JjM6WCjArH4k9gHOBoyL4InU8VnkRPA70\nBwYCkyV6Jw6pNFyQlYDEAODXdDzmDpp/4VX5m6AI/kCW5IaQJbm9E4dk1iASHYC7gDMieDN1PNZ4\nIngfGA7cDPxJ4kKJNonDKjwXZAUnsS3wH8AvaPH0wtTxWDoRvAMcDFxPNq7sFonuicMyq5NEW2Ai\n8GAE41LHY40vP4V5PdAX6AJMlzhZokXi0ArLBVmBSXQDHgEuj+Ce1PFYenmSGwP0Aj4EpkncILFD\n4tDM1kmiFfAAMJVs4Lc1IRF8GMHxwI+AkcAMib/Pi3SrwQVZQUlsT1aM3RjBlanjsWKJYFEEo8kK\ns3nAFIn/kRjpMWZWFHkeewJ4CzglX0zUmqAInolgBPAT4ABglsTvJQbkM2+bvDoLMkmHSpouaYak\n39SyzVX56y9J6lfXvpI6Spok6Q1JD0lqX5nuVAeJw4GngasjuDh1PFZcEcyP4J+AbYB7yAb/fyBx\nPUt+vh1L27s4q0Vj5Db7hsQPyNamugU4IV8awZq4CKZEcDiwO9mPyTuA1yXOlxgoNd0DRevtuKRm\nwDXAocCuwFGSeq+xzQhgx4jYCTgRuK4e+44CJkXEzmRHgUZVrEcFJGlw/bajl8RdwPnAoRH8vlED\n2xBPsnPqECqmSvoiaXAEn0cwNoJ9yWY3zWTRWQdx6ZxLufr1U7j77qE8e1JPlrX1IrM0am6rSvXN\nYdm27C7xR+AS4K8iuKowR8aW0i51CBVT8vwVwXsR/BbYGU74N7J65CZgrsQ9EqdI7NWUls6oqxL9\nDvBmRMyKiBVkM2R+sMY2I4FbASJiCtBeUuc69v16n/z2hxvdk2IbXNsLEs0lhkmMIzu0Pw3oF8HU\nTRVcg8ykV+oQKqZ6+jK45oMI3o7gIrr2HMuJ/f+RHSdMYVH3rXnsd8dy8UdXcMmcc7jx2eO4++6h\nPHZuH2YcujXL2zS1Qq2xclu1Gry+FyVaShyRF2KTyMaM9Ylg8qYIrt6WVVFBViX5KyvWx3SOYHQE\nuwF7Affnt7cBCySekbhZ4nSJERI7SWyRNPBGUNfpjG7AuzUevwfsU49tugFd17Nvp4iYm9+fC3Rq\nQMyllR+K7QzsAOxNdiRjCDAL+APZGAvPpLTK6fTKEoaf/hzwHABLOm3Baz/qxrv7bsOn23fhg/59\nefqMrfmiTTs2/2wRLRYvoOWCT2m5YBEfz9pM4iTgE+BjYGHeFudtaWGOfDRcY+W2qifREtiO7Ohg\nX2AQMIBsmMVY4IcRLE0WoJVaBO8Ct+dt1Qzd3YHd8jYC2AnoJjEfmE02welDslOg88ny1afAAmBR\n3pYAn+XX3yykugqy+ibb+gzI07reLyJCUq3/jsRl9YyhsWmN21X3N8tvm+X3mwObAy2A1lk7o7fE\n3wJbk32hzQReACYAoyOYWa8IVrKSV+hKc75scPRLaF3ar06rnDZzv2DAdTMZcN3qn7nlbZrx3r7t\nmd+7A59u354lndry0ZbdydY+6wh8C2iXtzZ5aymxFL5uy4Bx+WmIoqtkbqt95+Llr5r3tcb9zcjy\nWM0c1hJoBaf1kTiC7Mdza7KC9NW8XQb8KYINv4LIR7RlCj1qfX1p0zltZavLP1dP5O1r+eSlrkAP\nsmU1upB9x/Yly1cd8rYVWd5qDbSSWMHqOWt53r4AFkUwtPF7VYvI59Gvq5EdwZlY4/Fo4DdrbHM9\ncGSNx9PJ/mhr3TffpnN+vwswvZZ/P9zc3JpWW19OqlSjkXKb85ebm9uG5qW6jpA9B+wkaTvgA7Jr\nVB21xjbjgVOBuyQNBBZExFxJH69n3/HA8cBF+e196/rHI8JTYc2sMTRWbvua85eZNcR6C7KI+FLS\nqcAfyQ5l3xwRr0k6KX/9hoh4UNIISW8CnwF/s75987e+ELhb0glk46cOb4S+mZmtUyPmNjOzDaL8\n0LqZmZmZJVLIBdjKvOiipB6SHpP0Z0mvSPpl/nwpF8OV1EzSC5IeyB+XtR/tJd0j6TVJr0rap8R9\nGZ1/vl6WdIekFmXpi6QxkuZKernGc7XGnvd1Rp4PDk4TdcM4fxVLNeQw569iaOz8VbiCTOVfdHEF\ncEZE9CEb/HtKHn9ZF8M9jWwm1apDqWXtx5XAgxHRm2wK9XRK2Jd83NLPgL0ioi/ZKbMjKU9fxpL9\nbde0ztgl7Uo2PmvXfJ9rJRUuZ9Xk/FVI1ZDDnL+KoXHz16aY0dTA2U/7svoMplHAqNRxbUR/7gOG\nks/Qyp/rTC0zS4vUgO7Aw8BBwAP5c2XsRzvg7XU8X8a+dAReJ5vO3ZxsAc5hZeoL2RpWL9f1/8Aa\nsxeBicDA1PHX0TfnrwK1ashhzl/Fao2Zv4r4a7O2xRhLJ/810A+YQjkXw70c+AdY7Rp0ZexHT2C+\npLGSpkr6d0mtKWFfIuITsnWfZpPN8FsQEZMoYV9qqC32rmR//6uUIRc4fxVLNeQw569iq1j+KmJB\nVhWzDCS1Af4TOC0iFtd8LbJyudD9lPSXwLyIeIFaFscsQz9yzckuw3FtROxFNmNutUPiZemLpB2A\n08l+pXUF2kg6tuY2ZenLutQj9qL3q+jx1UvZ8xdUVQ5z/iqJjc1fRSzI3ofVVmzuwepVZuFJ2pws\nmd0eEavWWJur7Dp4SOpCdomHItsPGClpJnAnMETS7ZSvH5B9ft6LiGfzx/eQJbg5JexLf2ByRHwc\nEV8C/0V2mqyMfVmlts/Umrmge/5ckTl/FUe15DDnr2KrWP4qYkH29YKNkrYgGxQ3PnFM9SZJwM3A\nqxFxRY2XVi2GC+tZDLcoIuLsiOgRET3JBl0+GhHHUbJ+AETEHOBdSTvnTw0F/kw2fqFUfSEbrzBQ\n0pb5Z20o2YDlMvZlldo+U+OBIyVtIakn2fXrnkkQX0M4fxVEteQw56/Cq1z+Sj1ArpZBc8PJBv69\nCYxOHU8DY9+fbLzCi2TXq3yBbIZFR7LBpW8ADwHtU8fagD4NAsbn90vZD2AP4FngJbJfZe1K3Jez\nyBLyy8CtZNcdLEVfyI5UfEB23bh3yRZbrTV24Ow8D0wHDkkdfz376PxVsFb2HOb8VYzW2PnLC8Oa\nmZmZJVbEU5ZmZmZmTYoLMjMzM7PEXJCZmZmZJeaCzMzMzCwxF2RmZmZmibkgMzMzM0vMBZmZmZlZ\nYi7IzMzMzBJzQWaFJam/pEGSzkodi5lZQzh/WUO5ILMi6w9MAb4tqU3qYMzMGsD5yxrEBZkVVkRc\nD6wAmkfEktTxmJnVl/OXNZSvZWmFJulosgu2LoyIFanjMTOrL+cvawgXZJacpN7A94HlEXFl/txh\nQGvgQGAlcHJEfJUuSjOztTl/WaW4ILNCkCTgJaAfMAyYHBGL0kZlZlY35y+rBI8hs0KI7JfBo8Cp\nwHQnMzMrC+cvqwQXZFYkjwM9I2JW6kDMzBrI+cs2igsyKwRJLYAAvpM6FjOzhnD+skpwQWZFMTIi\n7gPmSNo5dTBmZg3g/GUbzQWZJSfpEGBi/vBS4DRJgxKGZGZWL85fVimeZWlmZmaWmI+QmZmZmSXm\ngszMzMwsMRdkZmZmZom5IDMzMzNLzAWZmZmZWWIuyMzMzMwSc0FmZmZmlpgLMjMzM7PEXJCZmZmZ\nJfb/5YBSx1gR9n8AAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x8389dd0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, len(NEVENTS), figsize=(10, 5))\n", | |
"rv = scipy.stats.chi2(xvar.getBins())\n", | |
"xx = np.linspace(0, np.percentile(chi2s_true_model.flat, 90) * 1.5, 100)\n", | |
"\n", | |
"for ax, nevents, chi2 in zip(axs.flat, NEVENTS, chi2s_true_model):\n", | |
" \n", | |
" ax.plot(xx, rv.pdf(xx))\n", | |
" ax.hist(chi2, bins=10, normed=True, alpha=0.4);\n", | |
" ax.set_xlabel('$\\chi^2$')\n", | |
" ax.set_title('nevents/toy = %d' % nevents)\n", | |
" \n", | |
" print \"chi2 mean =\", np.mean(chi2)\n", | |
" print \"nbins =\", xvar.getBins()\n", | |
" \n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Check MinNll distribution for true model" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 22, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"minnll mean = 395.627138236\n", | |
"minnll mean = 3954.18436119\n" | |
] | |
}, | |
{ | |
"data": { | |
"image/png": 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ShxicSZIkdYjBmSRJUocYnEmSJHWIwZkkSVKHGJxJkiR1iMGZJElSh+y32B2QJGlckmPO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\nSUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x8810a10>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, len(NEVENTS), figsize=(10, 5))\n", | |
"\n", | |
"\n", | |
"for ax, nevents, minnll in zip(axs.flat, NEVENTS, nlls_true_model):\n", | |
" \n", | |
" ax.hist(2 * minnll, bins=10, normed=True, alpha=0.4);\n", | |
" ax.set_xlabel('-2 NLL')\n", | |
" ax.set_title('nevents/toy = %d' % nevents)\n", | |
" \n", | |
" print \"minnll mean =\", np.mean(minnll)\n", | |
" \n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Check $\\chi^2$ evolution for some toys" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 55, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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N4Ksqa9sGdf4T6AN0q/9gzczMzMwMpGFjpNHzpWMXpOdhYzqhmQC624DeU8CZwG2k+Oyd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\nERGpAQrwIiIiIiIiIjXg/wMtyXA3F1/IJwAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x875cb10>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, ax = plt.subplots(figsize=(17, 9))\n", | |
"for color, nevents, chi2s_set in zip(mpl.rcParams['axes.color_cycle'], NEVENTS, chi2s_poly[:,:4,:]):\n", | |
" for itoy, chis in enumerate(chi2s_set):\n", | |
" ax.plot(ndofs_poly, chis, '-o', label='toy = %d, events = %d' % (itoy, nevents), color=color)\n", | |
"ax.set_ylim(20, np.percentile(chi2s_poly[:,:4,:].flat, 99))\n", | |
"ax.grid()\n", | |
"ax.legend(loc='best', numpoints=1, title=\"toy\")\n", | |
"ax.set_xlabel('ndof')\n", | |
"ax.set_ylabel('$\\chi^2$ poly')\n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Check -2 NLL evolution for some toys" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 56, | |
"metadata": { | |
"collapsed": false, | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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AZv5Jr1V/23ufiNgdOBK4YUQKpR3ie+AlSZIkjTr+th95EfGHwOeAT2Tmle0u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\nrkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xd858510>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, ax = plt.subplots(figsize=(17, 9))\n", | |
"for color, nevents, nll_set in zip(mpl.rcParams['axes.color_cycle'], NEVENTS, nlls_poly[:,:4,:]):\n", | |
" for itoy, nll in enumerate(nll_set):\n", | |
" ax.plot(ndofs_poly, 2 * nll, '-o', label='toy = %d, events = %d' % (itoy, nevents), color=color)\n", | |
"ax.set_ylim(20, np.percentile((2 * nlls_poly[:,:4,:]).flat, 99))\n", | |
"ax.grid()\n", | |
"ax.legend(loc='best', numpoints=1, title=\"toy\")\n", | |
"ax.set_xlabel('ndof')\n", | |
"ax.set_ylabel('-2 NLL poly')\n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## $\\chi^2$-value distribution as a function of nDOF" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 57, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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8H61h9fuSnFBVDzQ3j3yQKfj0LU1nCJ/AZaxoKA1hrEjqbqA5Bcwrmpo5RRou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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xd81fcd0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, ndofs_poly.shape[0], figsize=(17, 4))\n", | |
"range_x = np.linspace(0, np.max(np.percentile(chi2s_poly, 95, axis=(0,1))), 50)\n", | |
"for ndof, ax, chis in zip(ndofs_poly, axs, chi2s_poly.T):\n", | |
" ax.hist(chis, range_x, normed=True, histtype='stepfilled', alpha=0.8)\n", | |
" ax.set_title(\"poly %s nDOF, $<\\chi^2>$=%s\" % (ndof, \", \".join([\"%.0f\" %s for s in np.average(chis, axis=0)])))\n", | |
" ax.set_xlabel('$\\chi^2$')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## -2 NLL distribution as a function of nDOF" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 58, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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BT87MpwI3AW/vyxZJNTAnUjVzIlUzJ5IkSYPRzRFgZwA7M/OWzNwHXA5sbFvm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\nTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xbe7f810>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, ndofs_poly.shape[0], figsize=(17, 4))\n", | |
"range_x = np.linspace(0, np.max(np.percentile(2 * nlls_poly, 95, axis=(0,1))), 50)\n", | |
"for ndof, ax, nlls in zip(ndofs_poly, axs, nlls_poly.T):\n", | |
" ax.hist(2 * nlls, range_x, normed=True, histtype='stepfilled', alpha=0.8)\n", | |
" ax.set_title(\"poly %s nDOF\" % ndof)\n", | |
" ax.set_xlabel('-2 NLL')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 59, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"chi2s_poly_ave = np.average(chi2s_poly, axis=1)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 60, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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SJC0wczqnPclh9Bb5OgP4ClBVdeI6R7kOLNq1LhI2BP6c3n3fHwgcB3ywioub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\nxo6ySNoBAABgStoBAABgKmZKYxr9MVz0AAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x8642ed0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, ax = plt.subplots(figsize=(17, 4))\n", | |
"lineobj = ax.plot(ndofs_poly, chi2s_poly_ave[0], 'o-', ndofs_poly, chi2s_poly_ave[1], 'o-')\n", | |
"ax.set_xlim(0.5, len(ndofs_poly) + 0.5)\n", | |
"ax.set_ylim(40, np.percentile(chi2s_poly[:,:5,:].flat, 90))\n", | |
"ax.set_xlabel('ndof')\n", | |
"ax.set_ylabel('$<\\chi^2>$')\n", | |
"ax.legend(iter(lineobj), NEVENTS, title='#events', numpoints=1)\n", | |
"ax.grid()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## F-value distribution as a function of nDOF\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 61, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"F_poly_ave = np.average(Fs_poly, axis=0)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 62, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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TirWumumoHiPiV4GPUVxA4FVjmVsF1rUqzjouWcuqOGsZ61jV0q4B1umJ2EZeteCJeeUJ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\ntdyzOgZreYRK1bKfrwE/XwPW8Qh+vq5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| |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x89e5c10>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"chi2f, axs = plt.subplots(1, len(ndofs_poly) - 1, figsize=(17, 4))\n", | |
"range_x = np.linspace(0, np.percentile(Fs_poly.flat, 90), 25)\n", | |
"for ndof, ax, Fs in zip(ndofs_poly[1:], axs, Fs_poly.T):\n", | |
" ax.hist(Fs, range_x, normed=True, histtype='stepfilled', alpha=0.8)\n", | |
" ax.set_title(\"poly %s nDOF, F=%s\" % (ndof, \", \".join([\"%.0f\" %s for s in np.average(Fs, axis=0)])))\n", | |
" ax.set_xlabel('F')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 63, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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Gqu/Sh8A2AH5CVfT/BTgQGEn1x+WbqIazT8rMGd3Os0jvg4jYttPQKGlAmHcD\nK4I24ERge6oF5cYCFwHfylqeVDS4AWTeqQTzTiWYdyrBvOu9hdW0vbqXbmY+DVwcEX2al56Zd1L1\nznf3nr68riS1ukxmA4dG8F/AjUzOSUyOLYHLoh6rAMdmLdvLRilJkqTuetWTXpo96ZK06CJ4L/Br\n4Bgmx3lUc9b/AhyUtXy1aHCSJEktaGE17aLcgo2I2Csi3tjD9iP6GpwkqbkyuQL4D+BYJucxPLbF\n+4BlgQuiHuPKRidJkqTOFqlIBy4EPtp5Q0S8FXiqvwNS83W/ZYI0EMy7sjK5n2oB0E346U2nc+p1\n+wN/A66OeqxQNrrmMe9UgnmnEsw7lWDeNcciFemZ+QrwWESs0WnzJKoF3iRJQ0AmzwA7Ak/y6NbX\n8bWXjqMa+n5j1GPtstFJkiQJFmNOekSMAI7NzOMi4l3Acpl5WVOjW3AszkmXpF6KIIAjgKOAvZkc\nbwPqwO5Zy9uKBidJktQC+jwnHSAz24G7GrdN26lUgS5J6ptMMpMTgYOBaUzOl4BDgIujHjuVjU6S\nJKm1LXKRDpCZFwCfAy5vTjgaCM4dUQnm3eCTycXAdkCdybk5s0dPBKZEPQ4oHFq/Me9UgnmnEsw7\nlWDeNcdiFekNn8jMW/s9EknSgMvkHmAzYGu+9spneXLDnYF61OPYqIfTiiRJkgaY90mXJBHBGOCH\nwIZsM/ljbFf/KXAdcGTWck7Z6CRJkoaXhdW0FumSJGDugnKfA45ktRs/zEFbfRl4GvhI1vLlstFJ\nkiQNH/2ycJyGD+eOqATzbvBrLCj3beCTPLblmRz/z58C7cBlUY/xhcPrFfNOJZh3KsG8UwnmXXNY\npEuSusjkfOA9vLT8cdRn3U9yO3B91GPV0rFJkiQNdw53lyT1KIIVgXOh/VG+MO4ORs/8BLBz1vLe\n0rFJkiQNZQ53lyQttkyeAraDEbP4+r8/wNNv/TZwddRjq9KxSZIkDVcW6S3IuSMqwbwbmjJ5GfgI\ncB4n3380d+9bB86JenygcGiLxLxTCeadSjDvVIJ51xwW6ZKkhWosKHcccCRTf1PnkhO/Dfxv1OMT\npWOTJEkabpyTLklaZBFsDJzH6tecyUe3253gN8CXszYEf5lIkiQV4n3SJUn9JoKVgfMY//AjHL72\nBEa03wUckrWcXTo2SZKkocCF49SFc0dUgnk3fGTyd2AbZqzRzvHPzGHWEhOAaVGPpQuHNh/zTiWY\ndyrBvFMzPKisAAAcdUlEQVQJ5l1zWKRLkhZbJjOB/Xhl/KV847m1eGHFOcBVUY/lS8cmSZI0lDnc\nXZLUJxHsB+3f56Atr2a1WzYAdspaPlw6LkmSpMHK4e6SpKbJ5DcwYld+evOW/PGge0luiHpsVDou\nSZKkocgivQU5d0QlmHfDWya3Aptz/k8mcNkJfya5LOrxntJxmXcqwbxTCeadSjDvmsMiXZLULzJ5\nDNiKWz49g9MueJL2EadFPT5YOi5JkqShxDnpkqR+FcEI4Kus+Mf9+djmbYyc9Z2s5XdLxyVJkjRY\neJ90SdKAi+AjLPvI//Cpd/ybMS9MBT6ftWwvHZckSVJpLhynLpw7ohLMu9aTyS95bsLunPjX0cx4\n00SSX0U9xgxkDOadSjDvVIJ5pxLMu+awSJckNU0mN/HS8pvzv/e+xOObb0HGxVGPZUrHJUmSNFgV\nH+4eESOB3wOPZ+ZuEbEccAawOvAIMCkzZ3Q7x+HukjSERDCOEbNO4wMf2Yj1zn6WkbN3zFo+WTou\nSZKkEgb7cPcjgHuBjk8LjgGuyMy3AFc22pKkISyTF2gfNZGzTzudG49amTmjbot6vLV0XJIkSYNN\n0SI9IlYFdgF+AnR8irA78PPG858DEwuENqw5d0QlmHfKZE7miM9z1XFHcfFJ45g95qaox2bNfE/z\nTiWYdyrBvFMJ5l1zlO5J/x/g80Dn1X5XyMzpjefTgRUGPCpJUtNkcip/+MTuTD19BLOW/G3UY9fS\nMUmSJA0WbaXeOCJ2Bf6Rmbcv6BOYzMyI6HHSfERMoZqzDjADuCMzr2ns27Zxvu0e2h3bBks8tm3b\nbs12xAc24ZT6Deww+az40pjD86uvnOL1zrZt27a93tm2PUzbGwLjqUxgIYotHBcRXwc+AswGlgCW\nAc4B3gVsm5lPRcRKwNWZuU63czNdOE6ShrwIlmXFP17Af+66CaNmnsASz30pa4VXNJUkSWqyhdW0\nxYa7Z+YXMnO1zFwD2A+4KjM/ApwPHNA47ABgWqkYh6uOT3akgWTeqSeZPMdTG2/PlKt+xfOrfpYX\n3/irqMfI/np9804lmHcqwbxTCeZdc5Sek95ZR8/JN4H3RsQDwPaNtiRpmMpkdj69zsc57YJjeHqd\nvXl+5WuiHkuWjkuSJKmE4vdJ7w2Hu0vS8BRL/2NH3n/oNFa76XGWeWKzrOWzpWOSJEnqbwuraS3S\nJUmDSox54a289+ibWWdaMmLWO/Nb/3ykdEySJEn9aVDOSVc5zh1RCeadFlW+Mu7PXPSDtbj9wGcg\n7ouPv2vz3r6WeacSzDuVYN6pBPOuOSzSJUmDTib/4qrj1ufmz9zA6/56Q3x4531LxyRJkjQQHO4u\nSRq0Igje/e3vseXx/8XftqnlGWd/rXRMkiRJfeWcdEnSkBZbfueTbHHCyfxtq1/nWWfuXzoeSZKk\nvnBOurpw7ohKMO/UF3nj5/6PWw97Hyv/cb/Yd6+bY/0zF+n3l3mnEsw7lWDeqQTzrjks0iVJQ0Je\nf+yV3Lv3+rz+gfXZaMoj8dYLxpeOSZIkqb853F2SNKTEPvuN53V/uZNZS72OGz+/aT6w6/2lY5Ik\nSVocDneXJA0bedZvZhDtazHy1XvZ/kt3xVsv2Ll0TJIkSf3FIr0FOXdEJZh36k/5oz/MZrVbtmD2\nklPZ+YgLYp1pR/Z0nHmnEsw7lWDeqQTzrjnaSgcgSVJvZC0T+FB8/F0Pstsh34n1Zq/PfXsfkkl7\n6dgkSZJ6yznpkqQhLw5d9wDGTj+FS068hbv23ymTmaVjkiRJWhDvky5JGvbiqDduy8hXL+HK457k\n3u+fw+ueOoDRMYpXcxYzRpycLzxbLx2jJEkSWKSrm4jYNjOvKR2HWot5p4EQXx69Lg+M/AMPsSS7\nvQwPA2sAU8fO4pFRx1moayB4vVMJ5p1KMO96z9XdJUktIb/y6n3cMuoldnu56469XxzF+PZDy0Ql\nSZK06CzSW5CfdqkE804DZuTIkXOfr9Fp+6illo3ggAheP/BBqZV4vVMJ5p1KMO+awyJdkjS8vJqz\nety+8pNt/OfOdd5ywaPR9vK1ERwZ0aWMlyRJKs4ivQV5P0OVYN5pwMwYcTJTx1aF+sONbWctPYu/\njTuBN196AvtNvJMvLLMRH37fJ3nzhX+MtlfujKAewUYRuN6J+szrnUow71SCedcc3iddkjSs5AvP\n1mPccvCTZQ9lzuwlGdn2UrfV3U+KeqzG2lfszVpXTKK9bV3+9h8TueXTB/HQjnMiRp0HTAOuz6Tn\nXnlJkqQmcXV3SVJLi3qsDuxDMokcuRaPbvkQN31uGR7c+Y1k28VUBftlmbxYOFRJkjRMeAs2SZIW\nQdRjDWASMIn2Eavx+Ob3cuPnl+KBXdch264FzgMuyGR62UglSdJQZpGuLryfoUow71RCX/Iu6rE2\nsA+wLxkr8Pd33sH1x47iz3tsQo68m6qH/bxMHuzHkDUMeL1TCeadSjDves/7pEuStJiylg9lLb+R\ntdyQyG1Z5fc3st9eb+TLbS/yiQ3+wbpT303MuTaCeyI4LoJNI/y9KkmS+saedEmSFkPUYz3m9rAz\nlmfech1Xf2UW9+yzGYxYlmpI/DTgmkxeLRqsJEkalBzuLklSP4t6BLA+1Rz2fYHRPLfab7nimzO5\ne79NYMR6wKVUBfslmTxfMFxJkjSIWKSrC+eOqATzTiUMVN41CvZ3MK9gD2a+/iIu++4M7vzIO2HE\n1sBNVAX7+Zn8vdkxqRyvdyrBvFMJ5l3vOSddkqQmylpm1vLOrOUXgTcDe7PUMzP5wEc/zOSRb+YL\nY3/IxqdcDu1bAXdHcGsEx0awbgR+6CxJkuayJ12SpCZp9LC/k6p3fRIwkzltU7nsuw/zu8M3AiYC\nM5k3j/2WTNqLBSxJkgbEoBzuHhGrAb8A3ggk8OPMPCkilgPOAFYHHgEmZeaMbudapEuShpRGwb4p\nVcG+D/AcGWdydf1urvvShlQF+xuB86mK9iszeblYwJIkqWkGa5G+IrBiZt4REWOBP1D9gXIg8HRm\nfisijgZel5nHdDvXIr0PnDuiEsw7lTBY8y7qMQLYnKp3fR/gaeBMbvrMzVz+3Q2BPYANgCuoCvaL\nMvlXqXi1eAZr3ml4M+9UgnnXe4NyTnpmPpWZdzSevwjcB6wC7A78vHHYz6kKd0mSho2sZXvW8qas\n5ZHAasChwIq8+4RfMzk+zOS4hL0++B7gYqoi/m8R/DaCQyNYrWTskiSpuQbFnPSImABcC7wNeDQz\nX9fYHsCzHe1Ox9uTLkkadqIeI4GtqXrY9wIeBc7k0XdfyKk3vpXqg+tdgb9RzWGfBtydSflf5pIk\naZENyuHucwOohrpfC3w1M6dFxL86F+UR8WxmLtftHIt0SdKwFvVoA7ahKtj3BP4KnMHzq5zDCY+v\nTlWwT6Ra16WjYL8pk9mFQpYkSYto0BbpETEKuBC4JDNPbGy7H9g2M5+KiJWAqzNznW7nJdVQ+Eca\nm2YAd3TMh4iIbQFsL7B9pD8v2wPd7tg2WOKx3TLtYXG9YzI3AttxF0cwlq1Yk3uAM/hpPMFj+y0D\np60KTITfrgn/uBk+9EPgCohNB0P8rdbu2DZY4rHdMu1hcb2zPbTaHdsGSzyDvL0hML7xY5sAHJCD\nrUiPiKAqtJ/JzE932v6txrbjI+IYYHy6cFy/inCBBw08804lDMe8i3qMAt5D1cO+B3APcCYwlck5\nmmptl4nAJsDVVD3sF2bydJmIW89wzDsNfuadSjDvem9hNW3JIn0r4DrgLpg7l+5Y4HdUf2y8CW/B\nJknSAkU9xlAV7PsCuwF3Uv0OPZvJOQvYhapgfy9wO9VK8edl8tcyEUuSJBikRXpfWKRLktRV1GMJ\n4H1UBfv7qW5teiZwDpPzRWAHqp733YGnqAr2acDtLjwnSdLAskhXFw5LUQnmnUpo1byLeiwJ7EQ1\nJH5n5o1SO5fJOYPqHu0dC8+NoSrWzwOuy2RWkaCHkVbNO5Vl3qkE8673FlbTtg10MJIkqbmyli8B\n5wLnRj2Wohr2Pgn4LpPjJqqC/etMzqOAdamK9a8Da0dwMVXRflkmLxb5BiRJamH2pEuS1CKiHmOp\nhsJPoprLfj1VwX5e1vK5CFZh3sJzW1CtHTMNuCCT6WWiliRp+HG4uyRJ6iLqMY5qsblJwHbANVQF\n+wVZy+cjWJZqqPxEqqHz99C4H3smDxYJWpKkYcIiXV04d0QlmHcqwbxbNFGPZal60CcB/wFcBZwB\nXJi1fDGCMcC2VAX7HsAMGgU78PtM2kvEPViZdyrBvFMJ5l3vLaymHTHQwUiSpMEla/lc1vKXWcvd\ngNWpFpHbH3gi6jGVybE7k+OGTD4JrAp8tHHqFOCxCP4vgh0jGF0ifkmShhN70iVJUo+iHstR9Z7v\nS7Ui/KVUQ+IvbixORwRvoepdnwisB1xG1cN+SSbPlYhbkqTBzuHukiSpT6IeywMfoCrYNwEupirY\nL81avgwQwYpU89z3oBo2fxNVr/z5mTxRIm5JkgYji3R14dwRlWDeqQTzrjmiHm8E9qQq2DcELqQq\n2C/PWr4CEME4YEeqHvZdgAeZdz/2+zIZen+ALCLzTiWYdyrBvOs9i3R14f9MKsG8UwnmXfNFPVYE\n9qJadO7twPlUBftvs5avAkQwiqpnfWLj8RLzCvZbMplTIPSmMe9UgnmnEsy73rNIlyRJTRf1WIV5\nBfu6VEX4GcBVWctZABEEsBHzCvYVqAr7acCVmbxcIHRJkgaURbokSRpQUY/VgL2pCvY3A+dSFezX\nZC1nzz0uWJN5C89tCFxBVbBflMm/BjpuSZIGgkW6unBYikow71SCeTc4RD1WB/ahKtgnAOdQFezX\nZS3nDnWP4A3A+6kK9u2B22gMi8/k0QEOu9fMO5Vg3qkE8673FlbTtg10MJIkqbVkLf8GfAf4TtRj\nDapi/TvAKlGPs6kK9hsz859U916fEsHSwHupetlrETxKVbBPA/40nBeekyS1NnvSJUlSEVGPtal6\n2PcF3ghMpVp07qasZfvc44I2YEvmzWNPqvnu04AbM5mNJElDiMPdJUnSoBb1eCvzhsQvB5xFVbDf\nkrV5f6w0Fp57O1WxvgfwJqpbwJ0HXJ7JzAEOXZKkxWaRri6cO6ISzDuVYN4NTVGP9ZjXw7408wr2\n2zoX7AARrA7sTlW0vwu4iqpgvzCTfw5k3PNiMu808Mw7lWDe9d7CatoRAx2MJEnSwmQt781a1oH1\nqRaSmwn8Evhr1OP4qMc7ox4BkMnfMvl+JjtQLUo3tXHOQxFcG8GnGyvIS5I0JNiTLkmSBr1GUf4O\nquHw+zY2n9l43NlDD/sSwA5UPey7A9OZt/Dc7S48J0kqyeHukiRp2GgU7BtRFeyTgNlUxfoZwN09\nFOwjgc2oCvYPAGOYt/DcdZnMGrjoJUmySFc3zh1RCeadSjDvhr9Gwb4J8wr2mTQK9qzlvfMdXy08\nty7VonMTgTcDF1MV7Jdl8kKfYzLvVIB5pxLMu97zPumSJGlYavSa3wbcFvU4CtiUajj8ZVGP55hX\nsP8ZoDHM/d7G4xsRrEI1HP5g4NQIrqcq2C/I5KkB/4YkSS3PnnRJkjTsRD1GAJtT9a7vAzxNYw57\n1vLBHs8JlgV2puph35GqkD8PmJbJAwMRtySpNTjcXZIktaxGwb4lVcG+N/Ak8wr2v/Z4TjAG2JZ5\n92Ofwbx57Ldl0t78yCVJw5VFurpw7ohKMO9Ugnmn7qIeI4GtqQr2vYBHqQr2s7KWj/R4TjCCat77\nxMZjPFXBfh5wdSavVMe9bRdY7XB4fkVY5il47KTMuy9u9vckgdc7lWHe9Z5FurrwfyaVYN6pBPNO\nCxP1aAO2oSrY9wT+wryC/bEFnhe8hXkLz60PXArf+Rs8uDf8aE24hqoT/mMPwc1HWKhrIHi9Uwnm\nXe9ZpEuSJC1E1GMUsB1VwT4ReIDqlm5Ts5ZPLPC8YEVgNzjyODjxDfMfcciD8KMfAi8t5mOW93KX\npOHLIl2SJGkRNQr291AV7HsA91AV7GdnLZ/s8ZyYdA2cuc38e454FL53DrDkYj5GsPiFfefHy4t7\njvPsJWngDLkiPSJ2Ak4ERgI/yczju+23SO8Dh6WoBPNOJZh36quoxxiqgn1fYDfgTqoh8WdnLafP\nPS52vhQu2bFqXUM13B1gl0szL955sd83aGPxC/slgSX6cN4s+vbBwOJ+OPCqowX6j9c7lWDe9d6Q\nKtIjYiTwZ6pfiE9Q3fv0g5l5X6djLNL7ICKOzMwTS8eh1mLeqQTzTv0p6rEE8D6qgv39wB+oCvZz\nmLz+uxi94iksP3JlXvoLLLkWPD37SV6dfvBQmJMeQQBj6F2B39sPCEbSix7/BTwW6XUymdNvP7RB\nIsYtV2N8+6HMfGUsS415kRkjTs4Xnq2XjkvDW6wQu7AMhzODtRnPQzzPSTk9B/21bjBZWE3bNtDB\nLIJNgYcyqxVWI+I3VEPN7lvYSVos40sHoJZk3qkE8079Jmv5MnA+cH7UY0lgJ6qC/Vt88J6HeOie\npXk/cDWw3V9gWsDfB1dnyII0erRfbjz+NRDvGcFIev+BwOt72PaaHxJEMJv++VBgUT8ceKWZowVi\n3HI1Jsz6Inu/OKrKu5eXYOrYL8a45bBQV7PECrELK8dPmJgrVXnHWkyLd8QKcbCFev8YjEX6KkDn\nFVUfBzYrFIskSdJ8spYvAecC50Y9luIebmJPlu1y0MRcid9ybtTjOSAbDwo8L/Ger/18cr+/ZkfB\n3PMxCeTIYM6oEbS3jaS942vbyHnb2sbR3jae9rYRtLe1NbaNIEe2zT22feRI2ke2kd2e54jqeXvb\nSHJEW7V95IjYtX020T6byDnEnNlEzob22Yzo2N4+q9o+p7Ft9qzq65xZjJg9u3rMmcWIWbMZMXsW\nI2bNYuTs2Yx8dRZrzvwQe74yis72fnEU54w5Or6wzDhoDJmNjt66zu25zwGi27E590cX3VIpOv1o\no9O/zPd8cdt9Odc4BjKO1dme92fXD8En5kpMafsKYJHeDwZjkT40PnIe2iaUDkAtaULpANSSJpQO\nQMNf1nJmnBkz5m6Y0Wnnc/ye6vZuHX/oxhB9Xvr9+/48CGJOMGLOwL3vnLZg1lKjmbXUaGYvOYpZ\nS4xmzhKjmT1mFHNGj248RtHeNpr2UaOYPXoU7UuNJttG0d42ivaRY8gRY2lvG0WOqB7tI+c9j/8b\nA69U79g572KJJbnp04c2GlVMVZ0+r+DKmLevancqxkZ0Lcy67ItgvhG6wdwif96+nG/f3HaXD1E6\nHd/t3M7/BjnvtbPLpwR0+QSh4/OFmHfe3Li6xNFxYOfXym77qn8y5r1O19fqFkfHti41bnZ534xs\nvFXObc97iewaZ3SKN7NaT3Ih38Pc125sy8bxXX52Hcd3//Sly3+Prt9zdvrvFcDMY8fNTbjOeTdi\nyTVQvxiMc9I3ByZn5k6N9rFAe+fF4yJicAUtSZIkSdJiGEoLx7VRLRy3A/B34Hd0WzhOkiRJkqTh\naNANd8/M2RFxKHAZ1aqfP7VAlyRJkiS1gkHXky5JkiRJUqsaUToADYyIODUipkfEn0rHotYREatF\nxNURcU9E3B0Rh5eOScNfRCwREbdGxB0RcW9EfKN0TGodETEyIm6PiAtKx6LWERGPRMRdjdz7Xel4\n1BoiYnxETI2I+xq/bzcvHdNwYU96i4iIrYEXgV9k5ttLx6PWEBErAitm5h0RMRb4AzDRKSxqtohY\nKjNnNtY5uQH4XGbeUDouDX8R8RngncC4zNy9dDxqDRHxMPDOzHy2dCxqHRHxc+DazDy18ft26cx8\nrnRcw4E96S0iM68H/lU6DrWWzHwqM+9oPH8RuA9YuWxUagWZObPxdDTV+ib+4aqmi4hVgV2An9D1\nHkzSQDDnNGAiYllg68w8Fap1xSzQ+49FuqQBERETgI2AW8tGolYQESMi4g5gOnB1Zt5bOia1hP8B\nPg+0lw5ELSeB30bE7yPiY6WDUUtYA/hnRPwsIv4YEadExFKlgxouLNIlNV1jqPtU4IhGj7rUVJnZ\nnpkbAqsC/xER2xYOScNcROwK/CMzb8ceTQ28LTNzI2Bn4L8a0xylZmoDNgZ+kJkbA/8Gjikb0vBh\nkS6pqSJiFHA28KvMnFY6HrWWxtC7i4BNSseiYe/dwO6NucGnA9tHxC8Kx6QWkZlPNr7+EzgX2LRs\nRGoBjwOPZ+ZtjfZUqqJd/cAiXVLTREQAPwXuzcwTS8ej1hARy0fE+MbzJYH3AreXjUrDXWZ+ITNX\ny8w1gP2AqzJz/9JxafiLiKUiYlzj+dLA+wDv5qOmysyngMci4i2NTe8B7ikY0rDSVjoADYyIOB3Y\nBnh9RDwGfDnz/7d3LyFalXEcx7+/mkRwMVREiSQuykVUakVFCgptgowWURYG6SKCxFpFtRG3LtMu\n0MLBvGWLWhhkkiIZhYlp0w0D6bapILLLIlH5t3jPwGEcdaaL73Hm+1md5zzPec7/vJvh9z7PnLeG\n+lyWJr+FwKPAcJKRkPR8Ve3qY02a/GYCm5JcQu/L6M1VtafPNWnq8edzdKFcDbzV+16cAWBrVe3u\nb0maIlYDW5NMA44BK/tcz6ThT7BJkiRJktQRbneXJEmSJKkjDOmSJEmSJHWEIV2SJEmSpI4wpEuS\nJEmS1BGGdEmSJEmSOsKQLkmSJElSRxjSJUnquCRzknw2jnHbk3ya5OkLUVfrviuSbDjPmKuSHEhy\nKMnCCcy9MclP43l+SZImg4F+FyBJkv69JNcAt1XV9f2u5SzuBoar6vEJXjcEbABe++9LkiSpe1xJ\nlySpT5oV8q+SvJrk8yTvJpne9N3arIofAZ5sXTM9yVCS4SSfJFnSdO0GZiU5nGRRa/xgkm9b7RlJ\nvk8ykOSpJF8099k+Rn0rkryZ5J0kXydZ1+pbmeRokgPAXaOeaW8z53tJrk0yH1gH3N/UN328n1FV\n7Qd+He94SZIudoZ0SZL66zrgxaq6ETgOPNCcHwJWVdX8UeNXAaer6mbgEWBTkmnAfcCxqlpQVR+M\nDK6q34AjrTC/FNhVVaeAZ4H5VTUPeOIs9c0DHgJuApYlmZVkJrCWXjhfBNwAVDN+AzDUzLkVWF9V\nR4A1wOtNfX9N7COSJGnqMKRLktRf31TVcHN8CJiTZBAYbIXtza3xC4EtAFV1FPgOmAvkHPfYASxr\njh9u2gDDwLYky4HTY1xXwJ6q+qOqTgBfAnOAO4B9VfVLVZ1szQdwJ7CtOd5CL8TT1HeuGiVJEoZ0\nSZL67UTr+DRjvy9mdLidaNjdCdyT5HLgFmBvc/5e4KXm3MEkl46zvho15h/Xl+T2Zgv84SRLx3ud\nJEmTlSFdkqSOabaoH2+9BX15q3v/SDvJXGA2cPQ88/0JHATWAzurqpIEmF1V+4DngEFgxqhLxwrb\nBRwAFie5IsllwIOt/g/prdaP1P3+eWr7uNkCv6Cq3j7XWEmSpgLf7i5JUn+NXpUeaa8ENiYpei+F\nGzn/MvBKkmHgFPBYVZ3sZe4z5mrbAbwBLGnaA8DmZmt9gBeq6vcxajljzqr6Mcla4CN6/0d/uNW9\nGhhK8gzwc/McZ53rfJoX2i0GrkzyA7CmqoYmOo8kSReLVE3476UkSZIkSfofuN1dkiRJkqSOMKRL\nkiRJktQRhnRJkiRJkjrCkC5JkiRJUkcY0iVJkiRJ6ghDuiRJkiRJHWFIlyRJkiSpIwzpkiRJkiR1\nxN8TNljgR4gwXgAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xd84b850>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, ax = plt.subplots(figsize=(17, 4))\n", | |
"lineobj = ax.plot(ndofs_poly[1:], F_poly_ave[0], 'o-', ndofs_poly[1:], F_poly_ave[1], 'o-')\n", | |
"ax.set_xlim(0.5, len(ndofs_poly) + 0.5)\n", | |
"ax.set_xlabel('ndof vs ndof - 1')\n", | |
"ax.set_ylabel('$<F>$')\n", | |
"ax.legend(iter(lineobj), NEVENTS, title='#events', numpoints=1)\n", | |
"ax.grid()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 64, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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PoHJg/i8RcdjzOsjMCfQjaXK1E+OzgFcBX8rMVwHrcSan1AnGsdQbjGWpS02DUyAlTYIH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\nRK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xcab57d0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, len(ndofs_poly) - 1, figsize=(17, 4))\n", | |
"range_x = np.linspace(0, np.percentile(Lratios_poly.flat, 90), 25)\n", | |
"for ndof, ax, Lr in zip(ndofs_poly[1:], axs, Lratios_poly.T):\n", | |
" ax.hist(Lr, range_x, normed=True, histtype='stepfilled', alpha=0.8)\n", | |
" ax.set_title(\"poly %s nDOF\" % ndof)\n", | |
" ax.set_xlabel('-2 log likelihood ratio')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## p values of F" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 65, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"p_values_F_ave = np.average(pvalues_F_poly, axis=0)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 66, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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D8s/H/Pz9fVX+udq9u+2BVDlsoOT5HyE7D9Yk2S62t5J1Vlab9rB8He2+4thXmL6baN3z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\ntJIkSZIkSVLheHigJEmSJEl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DnmMoZpaLmON66iqZbk5nuWg5zpfZ2SynlJq+ke3ueA1w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\nX0XflwQCAAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x8812690>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, len(ndofs_poly) - 1, figsize=(17, 4))\n", | |
"for ndof, ax, p in zip(ndofs_poly, axs, pvalues_F_poly.T):\n", | |
" ax.hist(p, np.linspace(0, 1, 30), normed=True, histtype='stepfilled', alpha=0.7)\n", | |
" ax.set_title(\"poly %d vs %d nDOF, <p>=%s\" % (ndof, ndof + 1, \", \".join([\"%.2f\" %s for s in np.average(p, axis=0)])))\n", | |
" ax.set_xlabel('p-value')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## p values of -2 NLL" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 67, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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kSZKknmYDTJIkSWqhiFgdERsiYu24aUsi4rKIuCEivhERi9tZo6TqzLHUfWyA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\nmgMwSZIkSZIkDc0BmCRJkiRJkob2B+/MLaUIvuNpAAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x864b9d0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, axs = plt.subplots(1, len(ndofs_poly) - 1, figsize=(17, 4))\n", | |
"for ndof, ax, p in zip(ndofs_poly, axs, pvalues_L_poly.T):\n", | |
" ax.hist(p, np.linspace(0, 1, 30), normed=True, histtype='stepfilled', alpha=0.7)\n", | |
" ax.set_title(\"poly %d vs %d nDOF\" % (ndof, ndof + 1))\n", | |
" ax.set_xlabel('p-value')\n", | |
"plt.tight_layout()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Degree of freedom choosen by F-test" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 73, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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wgkANAAAAIwjUAAAAMIJADQAAACMI1AAAADCCQA0AAAAjCNQAAAAwgkANAAAAIwjUAAAA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\nrkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xba52690>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"predicates = pvalues_F_poly > 0.05\n", | |
"f, axs = plt.subplots(len(NEVENTS), 1, figsize=(17, 6), sharex=True, sharey=True, squeeze=True)\n", | |
"\n", | |
"for color, nevents, pre, ax in zip(mpl.rcParams['axes.color_cycle'], NEVENTS, predicates, axs):\n", | |
" choices = ndofs_poly[np.array([np.where(p)[0][0] for p in pre])]\n", | |
" ax.hist(choices, np.arange(1, 8), alpha=0.5, label=\"#events/toy = %d\" % nevents, color=color)\n", | |
" ax.set_xlim(1, 8)\n", | |
" ax.legend()\n", | |
"ax.set_xlabel('nDOF chosen by F-test')\n", | |
"f.subplots_adjust(hspace=0)\n", | |
"plt.show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Degree of freedom choosen by likelihood ratio test" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 97, | |
"metadata": { | |
"collapsed": false, | |
"scrolled": true | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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JG40JA3VV3VVVVzfbDwA3ArsDrwaWNqctBQ6bzSIlSZIkSRo0U76HOskCYB/g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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0xc5bced0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"predicates = pvalues_L_poly > 0.05\n", | |
"f, axs = plt.subplots(len(NEVENTS), 1, figsize=(17, 6), sharex=True, sharey=True, squeeze=True)\n", | |
"\n", | |
"for color, nevents, pre, ax in zip(mpl.rcParams['axes.color_cycle'], NEVENTS, predicates, axs):\n", | |
" choices = ndofs_poly[np.array([np.where(p)[0][0] if any(p) else 0 for p in pre])]\n", | |
" ax.hist(choices, np.arange(1, 8), alpha=0.5, label=\"#events/toy = %d\" % nevents, color=color)\n", | |
" ax.set_xlim(1, 8)\n", | |
" ax.legend()\n", | |
"ax.set_xlabel('nDOF chosen by -2NLL-test')\n", | |
"f.subplots_adjust(hspace=0)\n", | |
"plt.show()" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 2", | |
"language": "python", | |
"name": "python2" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 2 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.5" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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