{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import pandas as pd\n",
    "from IPython.display import HTML, IFrame, Image, SVG, Latex\n",
    "import ROOT\n",
    "from ROOT import RooFit, RooStats\n",
    "%matplotlib inline\n",
    "from ipywidgets import interact, interactive, fixed\n",
    "\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.NumIntegration)\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Fitting)\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Minimization)\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.InputArguments)\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.Eval)\n",
    "ROOT.RooMsgService.instance().getStream(1).removeTopic(ROOT.RooFit.DataHandling)\n",
    "ROOT.RooMsgService.instance().setGlobalKillBelow(ROOT.RooFit.ERROR)\n",
    "ROOT.RooMsgService.instance().setSilentMode(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<link rel=\"stylesheet\" href=\"custom.css\" type=\"text/css\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib import rcParams\n",
    "rcParams.update({'font.size': 18})\n",
    "HTML('<link rel=\"stylesheet\" href=\"custom.css\" type=\"text/css\">')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "#from notebook.services.config import ConfigManager\n",
    "#cm = ConfigManager()\n",
    "#cm.update('livereveal', {\n",
    "#          'theme': 'sans',\n",
    "#          'transition': 'zoom',\n",
    "#})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def iter_collection(rooAbsCollection):\n",
    "    iterator = rooAbsCollection.createIterator()\n",
    "    object = iterator.Next()\n",
    "    while object:\n",
    "        yield object\n",
    "        object = iterator.Next()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def RooDataSet2pandas(data):\n",
    "    nevents = data.numEntries()\n",
    "    columns = [x.GetName() for x in iter_collection(data.get(0))]\n",
    "    return pd.DataFrame([[x.getVal() for x in iter_collection(data.get(ievent))] for ievent in xrange(nevents)], columns=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def p2z(p_value, onetail=True):\n",
    "    \"\"\" pvalue to significance \"\"\"\n",
    "    if not onetail:\n",
    "        p_value /= 2\n",
    "    return stats.norm.isf(p_value)  # inverse of the survival function\n",
    "\n",
    "def z2p(z, onetail=True):\n",
    "    \"\"\" significance to pvalue \"\"\"\n",
    "    if onetail:\n",
    "        return stats.norm.sf(z)\n",
    "    else:\n",
    "        return stats.norm.sf(z) * 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Lecture 2\n",
    "\n",
    "<p style=\"text-align: center;\"><i class=\"icon-user icon-2x\"><a href=\"mailto:ruggero.turra@mi.infn.it\">ruggero.turra@mi.infn.it</a></i></p>\n",
    "<br/>\n",
    "\n",
    "## Content of the lecture\n",
    "\n",
    "   * Hypothesis testing\n",
    "   * Type or errors\n",
    "   * Likelihood ratio\n",
    "   * Neyman–Pearson lemma\n",
    "   * Exclusions\n",
    "   * Profiled likelihood ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Simple and composite hypothesis\n",
    "\n",
    "* A simple hypothesis is one in which all parameters of the distribution are specified"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Error type\n",
    "\n",
    "   * Type I error: false positive (excessive credulity). Rate = $\\alpha = P(\\text{reject } H_0|H_0 \\text{ is true})$\n",
    "   * Type II error: false negative (excessive skepticism). Rate = $\\beta = P(\\text{don't reject } H_0|H_0 \\text{ is false})$\n",
    "   \n",
    "   * Power of the test: $1-\\beta$\n",
    "   * Remember that \"positive\" / \"negative\" refers to $H_1$, the alternative hypothesis, e.g. positive means reject $H_0$\n",
    "   * If $H_0$ is background only Type I is false discovery, Type II is missed discovery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 21,
     "metadata": {
      "image/jpeg": {
       "width": "70%"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"img/type-i-and-type-ii-errors.jpg\", width=\"70%\")  # from https://effectsizefaq.files.wordpress.com/2010/05/type-i-and-type-ii-errors.jpg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Question:\n",
    "what is $H_0$ and $H_1$ in this sketch?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 7))\n",
    "x = np.linspace(-5, 5, 200)\n",
    "y0 = stats.norm.pdf(x, 0, 1)\n",
    "y1 = stats.norm.pdf(x, 1, 1)\n",
    "mask = x >= 2\n",
    "ax.plot(x, y0, x, y1, '-')\n",
    "ax.fill_between(x[mask], y0[mask], alpha=0.5)\n",
    "ax.fill_between(x[~mask], y1[~mask], alpha=0.5)\n",
    "ax.vlines(2, 0, 0.5, linestyle='--', lw=2)\n",
    "#ax.set_xticklabels([])\n",
    "#ax.set_yticklabels([])\n",
    "ax.set_xlabel(\"$q$\")\n",
    "ax.annotate(\"$f(q|H_1)$\", xy=(x[100], y1[100]), xytext=(0.2, 0.7), textcoords=\"figure fraction\", size=20,\n",
    "            arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\"), color='C1')\n",
    "ax.annotate(\"$f(q|H_0)$\", xy=(x[90], y0[90]), xytext=(0.3, 0.8), textcoords=\"figure fraction\", size=20,\n",
    "            arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\"), color='C0')\n",
    "ax.annotate(r\"$\\beta$\", xy=(x[100], 0.1), xytext=(0.1, 0.5), textcoords=\"figure fraction\", size=20,\n",
    "            arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\"), color='red')\n",
    "ax.annotate(r\"$\\alpha$\", xy=(x[142], 0.01), xytext=(0.8, 0.25), textcoords=\"figure fraction\", size=20,\n",
    "            arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\"), color='blue')\n",
    "ax.text(2, 0.4, r'$q_\\alpha$', rotation='vertical', ha='right', size=20)\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that to evaluate $\\beta = P(\\text{don't reject } H_0|H_0 \\text{ is false})$ we have used an alternative hypothesis $H_1$, but remember that if $H_0$ is false doesn't mean that $H_1$ is true.\n",
    "\n",
    "The region $q > q_\\alpha$ is the rejection region where we reject $H_0$. The complementary is the acceptance region."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Hypothesis testing in practice\n",
    "\n",
    "   * Define the null hypothesis you want to try to reject\n",
    "   * Define the observables (number of events in the signal region, ...)\n",
    "   * Fix the rate of type I error $\\alpha$ of the test statistics (5%, $5\\sigma$, ...)\n",
    "   * Define the test statistic (trying to maximize the power $1-\\beta$)\n",
    "   * Find the rejection region ($q_{obs}>q_\\alpha$), which is the region where $H_0$ is rejected (p-value $<\\alpha$) (Reject $\\Leftrightarrow q_{obs} > q_\\alpha$)\n",
    "   * Do the experiment\n",
    "   * If the outcome is outside the acceptance region reject the null-hypothesis\n",
    "   \n",
    "In complex example one don't compute the acceptance region, but just compute the observed p-value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Exercize: Lady tasting tea (Fisher \"The Design of Experiments\" - 1935)\n",
    "\n",
    "A lady claimed to be able to tell whether the tea or the milk was added first to a cup. Fisher proposed to give her eight cups, four of each variety, in random order. What is the critical region at 5%? If we ask for a $5\\sigma$ evidence, what's the minimum amount of cups we have to prepare? (Hint: look at the [Hypergeometric distribution](https://en.wikipedia.org/wiki/Hypergeometric_distribution), answer should be 26)\n",
    "\n",
    "Are we interested in the rare case when the lady never guess? What is \"more extreme\" in this case?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Example: Lady tasting tea 2.0\n",
    "\n",
    "Suppose that the lady doesn't know how many cups of a kind are present. The acceptance region and the power (using p=90% as alternative hypothesis) can be computed easily from the binomial distribution.\n",
    "\n",
    "To compute the rejection region we have to find the minimum $q_\\alpha$ such that:\n",
    "\n",
    "$$\\sum_{n\\geq q_{\\alpha}} B(n|p=50\\%, N=8) \\leq \\alpha$$\n",
    "\n",
    "with $\\alpha=5\\%$. The solution can be found iteratively or inverting the formula (see the code). The lady has to guess correctly at least 7 cups. To compute the power simply using the definition\n",
    "\n",
    "$$\\text{power} = 1 - \\beta = 1 - P(\\text{don't reject $H_0$} | \\text{$H_0$ is false}) = 1 - \\sum_{n<7} B(n|p=90\\%, N=8) = 81\\%$$\n",
    "\n",
    "Since $H_1$ is not a simple hypothesis (it doesn't tell us automatically how much is $p$) we have to assume one particular $H_1$ ($p=90\\%$) to compute the power."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "N = np.arange(1, 70)\n",
    "alpha = np.sort(np.concatenate((np.logspace(-8, -3, 20), np.arange(0.001, 0.2, 0.002))))\n",
    "\n",
    "kalpha = stats.binom.isf(alpha.reshape(len(alpha), 1), N, 0.5)\n",
    "results_must_guess = kalpha.T + 1 \n",
    "power = stats.binom.sf(kalpha, N, 0.9).T\n",
    "min_N = np.ceil(np.log(alpha) / np.log(0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(15, 6))\n",
    "p = ax[1].pcolormesh(alpha, N, power, vmin=0, vmax=1, cmap='viridis')\n",
    "div = make_axes_locatable(ax[1])\n",
    "cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
    "cbar = plt.colorbar(p, cax=cax)\n",
    "ax[0].set_xscale('log')\n",
    "ax[1].set_xscale('log')\n",
    "p = ax[0].pcolormesh(alpha, N, results_must_guess, vmin=0, cmap='viridis')\n",
    "div = make_axes_locatable(ax[0])\n",
    "cax = div.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
    "cbar = plt.colorbar(p, cax=cax)\n",
    "\n",
    "ax[0].fill_between(alpha, min_N, color='white')\n",
    "ax[1].fill_between(alpha, min_N, color='white')\n",
    "\n",
    "ax[1].set_title('power')\n",
    "ax[0].set_title('minimum corrected guess to reject H0', fontsize=15)\n",
    "ax[1].set_xlabel('alpha')\n",
    "ax[1].set_ylabel('number of cups')\n",
    "ax[0].set_xlabel('alpha')\n",
    "ax[0].set_ylabel('number of cups')\n",
    "\n",
    "ax[0].plot(5E-2, 10, 'ro')\n",
    "ax[1].plot(5E-2, 10, 'ro')\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x600 with 4 Axes>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Neyman–Pearson lemma\n",
    "Having two simple hypotheses (no additional parameters) $H_0: \\theta = \\theta_0$ and $H_1: \\theta = \\theta_1$, define the likelihood-ratio test:\n",
    "$$\n",
    "\\Lambda(\\vec x) = \\frac{L(\\theta_0|\\vec x)}{L(\\theta_1|\\vec x)}\n",
    "$$\n",
    "\n",
    "which rejects $H_0$ in favour of $H_1$ when $\\Lambda < q_\\alpha$ (rejection region) with $\\alpha=P(\\Lambda(\\vec x)\\leq q_\\alpha|H_0)$. The likelihood-ratio test ***is the most powerful test with size $\\alpha$***."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Example\n",
    "Suppose you have a rock that seems to be opal (density 2.2 g/cm<sup>3</sup>), but may be also quartz (2.6 g/cm<sup>3</sup>). You have two instruments to measure the density, the first with resolution 0.2 g/cm<sup>3</sup>, the second with resolution 0.5 g/cm<sup>3</sup>. Opal is much expensive, we want to check if it is opal. $H_0:$quartz. What is the rejection region at 5%? Assume gaussian errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "ws = ROOT.RooWorkspace()\n",
    "true_density = ws.factory(\"true_density[2, 3]\")\n",
    "ws.factory(\"Gaussian::pdf1(density1[0,50], true_density, resolution1[0.5])\")\n",
    "ws.factory(\"Gaussian::pdf2(density2[0,50], true_density, resolution2[0.2])\")\n",
    "pdf = ws.factory(\"PROD::pdf(pdf1, pdf2)\")\n",
    "\n",
    "pdf_opal = ws.factory(\"EDIT:pdf_opal(pdf, true_density=density_opal[2.2])\")\n",
    "pdf_quartz = ws.factory(\"EDIT:pdf_quartz(pdf, true_density=density_quartz[2.6])\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  1) RooRealVar:: density1 = 2.69947\n",
      "  2) RooRealVar:: density2 = 2.11305\n"
     ]
    }
   ],
   "source": [
    "# do the experiment, use H1 to generate (opal)\n",
    "data = pdf_opal.generate(ROOT.RooArgSet(ws.var('density1'),\n",
    "                                        ws.var('density2')), 1)  # generate with 1 entry\n",
    "data.get(0).Print(\"V\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "opal_model = RooStats.ModelConfig(\"opal (H1)\", ws)   \n",
    "opal_model.SetPdf(pdf_opal)\n",
    "opal_model.SetParametersOfInterest('density_opal')  # not useful\n",
    "opal_model.SetObservables('density1,density2')  # no space\n",
    "opal_model.SetSnapshot(ROOT.RooArgSet(ws.var('density_opal')))\n",
    "\n",
    "quartz_model = opal_model.Clone(\"quartz (H0)\")\n",
    "quartz_model.SetParametersOfInterest('density_quartz')  # not useful\n",
    "quartz_model.SetPdf(pdf_quartz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# define the test-statistic: -log L(H0)/L(H1)\n",
    "\n",
    "test = RooStats.SimpleLikelihoodRatioTestStat(pdf_quartz, pdf_opal)  # null, alt\n",
    "test.EnableDetailedOutput(True)\n",
    "\n",
    "hypoCalc = RooStats.FrequentistCalculator(data, opal_model, quartz_model)  # alt, null\n",
    "hypoCalc.SetToys(20000, 1000)  # generate much more toys for bkg-only\n",
    "\n",
    "toy_sampler = hypoCalc.GetTestStatSampler()\n",
    "toy_sampler.SetTestStatistic(test)  # our test statistics\n",
    "toy_sampler.SetNEventsPerToy(1)\n",
    "\n",
    "htr = hypoCalc.GetHypoTest()\n",
    "htr.SetPValueIsRightTail(True)  # the \"extreme\" cases are on the right tail\n",
    "htr.SetBackgroundAsAlt(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ktTZZ8pHOGflWIQqsnvtHZ5rvPO4I+WnfkUuYUh+i5u70KrVA+zfqkFlI4zlBA633rgXU+NcMqPajujX5T5j4aOf7LWyytc6Rb8gjj5Uf5Oom+Z2Twmo7NfbxFE+rB3BkJ0fOYn+rrZ2fPtODGxZTrLxr6LPq/91t3RizLMswDKsvs/Q22FqNoAA0Tn1QAMp4YlCw1nZdFxLcNE35sSXL89UICkDjCArAJYqVd22Nekhqw/KxLt77uIXpmSNVAAAoppWgsHpPlNWgEC/8aGAuAAD4VNN3j9zPAdLukPdEPTFlAlWgAACsajoobLUsSLdHszHBFqU+AABXaaXp4bhxHPu+l9Gu9FEAAOCnGup4bK2NawiSP4XUJezM1M2oB6BxjHoALlGsvGuo6aHrur7v5bTDpCLyL7ljinMunvgibEi9AnBH3IEFuIW2Qn38xRGqDeJahNVvFuZRAG5EPsThY5r8CdydvmKoufNZHSd5nL5XCFCGoADd9BVD6s5H3SsEKENQgG76iqGG+ihcZavhU9krBwBAAQqDAoEAKGk1mfMpBNS43zwKANrBwAVAPYU1CgAKi+sPiA6AMgQFoBlU4gNoD00PQBu4EgfQJGoUgJZQiQ+gMQQFANdLQk6B9pM8VtFoA1xCYVBgHgXgaah8AX5HYVAgEAAVJZ+/kkV4MtsjgEvQmRGAKqQE4FoEBQB6WEvXBOBiBAUASpASgF8gKABQgpQA/AJBAQAAbFI46oHhkVCl/IwEABBRGBQIBLgHeucDuAOFQQG4gSMpoeKMBO1h4kWglmpBYRxHY4xzzjn3dk1ZOfDee+8Pbg60i7LumI8y0rMDFXC9Cp0ZvffWWins+75PQkDCOSeZIBjHse/7g5sD2lib/jzG6/W/nx2MkAQuZ8u36Ftru66T4n8cx2maVo/BObcsizEmrBw2n+dZKhLyza2tcEbAx6SA/+i9upUJqr7h355HvkKy5Mgz8XaT8NzIwhPPLnAVfcVQneGRoRpAfknqDIRzbhiG/f3Q7oAHCRfUR66s9dqpQ3nqUwL8Vuk+CqFvQbIwL/K3MkTXdX3fz/NsjOn7vuu63xwpgHIO9lWUloUntbcA9TUx6mG1RmFnZWtt3/db227No7BDWTURoBL9D4AqmpiZ8aMWBGvtMAyv1+v1enVdl8eC1+euPBkAnzjeosInFaiiiaBwnLRHhC4OoUdkreMBAEC30kFBKg+S9gL6JAK4Cj0YgGtVqFGQ3ojye5h2Kfy5318hjIpc3RxAm4rN+0A/BuByFTozSm/E0LdAxi/I8mma9kt9GTM5TdM0TbJkGAaCAu6BS90fIyUAv1BtXojVcZLfb65vpgsosZoSvnyvNjCv0C8OYX+OpmRupdVNGnhi8Fz6iiF156PuFYISZUrU4goHhXgeBYIC2qSvGGpiHoVrbc2joOyVA56GlgWgCoVBgUAAqMQnG6jiZvMoAACAkggKAFRhcAlwLYICAD3oxwBcjqAAQAlSAvALBAUAd7LTskBKAH5B4agHoAk0lf9API8CgDIUBgXmUUB9JYuy5LH0vs9pWQCqUBgUCARoBW/FS/F0AlUoDArAUyQlJzXyAH6AzowAVCEvAdciKADQg34MwOUICgCUICUAv0BQAHAnzKMAFKawMyPDIwGtmEcBKE9hUCAQACrRsgBUoTAoAHVwnftjpASgimp9FMZxHMfRe39kzdWFzrnVfwEVkBIAKFUhKHjvrbXee+993/f7hb1zLgkTYXNjzDRNzrnfHSrwmdfrzw9qILMB17LlW/SttV3XSUk/juM0TavH4JxblsUYE1bON5eoEW9ubYUzAv5XOtV979U4hl88Zr7PZMnOCnFvR74JUIW+YqhO00OoRZBfVhsgnHPDMCQLQz4I6yh7PYBvWZv+PAa9HYFfKN2ZUcr4pL3Ae5+3IKxmiPCn/Nc5R9MD8CjMowAU1sSES0e6NMbiLg55ULCfu+pEgJqSHhIai03qDIDymhge+WmtwDzPsolkhaRCgsYIQCVSAlBFEzUKnwqxIMSFescCoBBSAlBF6aCwWrQfr1GgRwIAACVVqFHouq7ve/k99EkMf+5XD8ia8fpmY0YmALptDeyg0xFwrQp9FGTGpNCFcJ7nsPzIBErzPPd9n28OANw1CrhctXkhVsdJfr+5vpkucA9tTvHz+6OqNeHS6iOG5W2+GngIfcWQuvNR9wrhHtosmjQGhbcp4UdHBRykrxhqYnjktbbmRVD2ygEPdCQlALiWwqBAIABUIiUAVdxyHgUAD0RKAKogKAC4K1ICUABBAUBrrNyz5c1K2y0RAC5EUABwP/RXAIohKAC4GVICUBJBAcCdkBKAwhQOj2QeBUArUgJQnsKgQCAAVCIlAFXQ9ADgHkgJQBUEBQB3RUoACiAoALgl5lEAyiAoALgf+isAxRAUANwMKQEoiaAA4E5ICUBhCodHMo8CoBUpAShPYVAgEAAqkRKAKqo1PYzjOI6j9/7Imlv/cs5dd0SAUtb++bktUgJQRYWg4L231nrvvfd93+/kAGOMc24rTDjnlmX5xRECuAVSAlBAhaDQ933XdRIUhmGYpml1NeectXYrCozjSEoA3ni9/vzowjwKQBl1mh5CLYL8slpn4JwbhmF1c+/9NE1b/wWgHv0VgGJKBwXJBEnfgtWgIJ0Yuq7L/9X3/TAMdFAAnomUAJTUxDwKR7o0Bs65rut2ejbYz31/CgDKICUAhTUxPPJ43YD3flmW/QGQDI8EtCIlAOU1ERSOk4oECRbSmdE555zbHzoBXI+KqOJICUAVpYOClPHe+7gW4XiNQjL1wrIsEhQuOz7gCFJCDaQEoApbvqJe5j+Qxx3HcZqmcAzjOCYFfwgW+X5kGobk+K2tcEZ4HAkKt3un/eCwf/FMhG5D4bO89Sj7IyRv9/pAB33FUIWmB5lwKXwXzPMclk/TRPUAALFfccM8CkAZ1YLP6jjJ7+mLcmjRTa9Y71ajYMyf/caPst9f4aavD3TQVwypOx91rxBadNOC6IZB4aN+CWH5TV8f6KCvGLrZqIcjuM00oMO5lADgWgqDAoEA0IqUAJTXxMyMAPAWKQGogqAA4AZICUAtBAUArSMlABUp7KMA/ATD8yv5NCXwQgHXokYBOIDCp5ITKYE6BuBa1CgAh1EElUVKAFqgMCgwjwKgAykBaIHCoEAgALQiJQDl0UcBwD2QEoAqCAoAboCUANRCUADQOlICUBFBAUDTmEcBqIugAKBdjJAEqiMoAGgUKQFogcLhkcyjAOhASgBaoDAoEAiAC60G71ofMlICUF61podxHMdx9N4fWTNZ4r13zjnnjmwO4LSmOgaSEoAqKgQF77211nvvve/7Ps8BsTwNjOPY97383ve9c+5XBwrAGGPM6/XfTy2kBKAWW76i3lrbdZ0U/+M4TtO0egzOuWVZjDFh5bD5MAwSLyRqzPMc4oK1Fc4I+smV9d3fWlv1A9vnlZ93suQXT0zoZhQ+y+dGSN795cJN6SuG6jQ9hFqEUN7n6zjnhmFIFoZ4EdbZ2hyADsyjANRVujOjFOpJe4H0OUjWXM0Qzrk4qa3uDcC6vFxtvlA9N0JSTuvEyem6DgSu0cSoh3NVAtLu0HVdEhS2hkfuUFZNBOjAPApAC5qYcOlElYBzru/7YRjykPH63CVnAeBap1NC0vsy/nNrOYAtTdQofCRUJFDAA09zVR0DdQ/AcaVrFFa7H35Uo7BVkQBAN1ICUEWFGoWu6/q+l/oA6bEYgsI4jjKT0ta2Yf04KNCZEVCPlADUUiEoyIRLocvhPM9h+TRNR0r9MOGSCNMqAFDp1ymh+cEfQE3V5oX40chGfTNdoI6m7nDwO+9mJmphwqUCKSGMqNT3CqM8fcWQuvNR9wqhgs9nMLyr5oNCmZRgmMwR19FXDN1v1MNb3GYa1+ANU1uxlABgh8KgQCAAdCAlAC1oYsIlADiClACUR1AAcA+kBKAKggKAGyAlALUQFAC0jnkUgIoICgCaxtgHoC6Fox4AbEkunV+rS837oaHFLsFJCUB1CoMC8ygAq25XwU5KAFqgMCgQCIAdf6dZfCVL3qaJkh8vUgLQAvooALgNUgJQHkEBwD2QEoAqFDY9APhSg70ZqqSEz3t5AgpRowCgdVXmUWgwLQFVUKMAINXUdXOZsQ9vby1ObsBjUaMAoF2MkASqU1ijwDwKgA6kBKAFCoMCgQAfo1q5SaQEoAU0PeDxSAn3USsl8B7Bk7UbFMZxHMfRe39kzZ8fDdR7vdIfNKZiSuDtgCdrMSh476213nvvfd/3+znAOXckTAC4NVICUEuLQaHv+67rJCgMwzBN0+pqzjlr7bIshQ8PQGFV5lEQpASgxaBgotYE+WW1zsA5NwxDuWMCUANjH4C6mhv1IJnAOZcsTJaY3QwBQIfCKYFOi0CuuaCw6qM0sDWPwg5GVAINoi4BaME9gkJenbCDUh/4VpK2K32mSqaEeKpmvkKAWKN9FAAgV6uOgSYJPFlzQUEqD5K2ho9qFACcZs3LmkYnk6iYEhp7JoCimgsKxpiu6/q+l9+lx2IICgenYAKgDCkBqKXFPgoy4VLokzjPc1g+TRO1C8DTkBKAimyzXf9Wx0m+ZW27Z4RGSSR9wNsmP9H3S2o8OeEiQT7LjaSEx7xN8C19xZC689nudKTsTHGZx5QAdwwKjaQE86C3Cb6lLyi02PTwJWWvEPBY7aQE4MkUBgUAH2l27B8pAWhBi6MeAGAV8ygA5VGjADzXvS6d67ZEkBXwWNQoALgB+isAtRAUALSOlABURFAA0DRSAlCXwj4KW1MpMGwSuB1SAlCdwqBAIAB0ICUALaDpAUCjSAlACxTWKADvMdbtnphHASiPGgU8D9/690RLBFAFNQp4Kr77b4WUANRCjQKA1pESgIoICgCaRkoA6lLY9MA8CoAapASgOoVBgUAA6EBKAFpA0wOARpESgBZUq1EYx9EY45xzzu2s4713zsnKgffee/92cwDKMI8CUF6FGgXvvbVWCvu+75MQEDjnpmkyxkzTFHc7GMex7/u3mwNQhpYIoApbvkXfWtt1nVQJjOM4TVN+DBIC5nmWCgNr7TAMkgmstWF5vrm1Fc4INyO583nvkzPnXeO5ChcGfz/alVPCU981+Ji+YqhOH4VQDSC/SGjIVwjNCsMwSO1CgnYH4AmqpwTgyUoHhdC3IF8YW5al67rwZ7x+13Vx00O8GoCfsDb9KfvgpASgoiaGR+ZBwWzXFkgXh77vt7bdmkdhh7JqIkANUgJQXRPDIz9qQZD+Cq/X6/V6dV2Xx4LX5648GUCT1yv9KYiUALSgiaCQC70dE9J3IXRxCD0iCx0WgIJICUALSgcFqTxIQkBeo+CcW5Yl/EkUAGCYRwGooUKNgvRGlN+T0Q0yw5LJRkMsyzIMQ1gzGTTB2AfgCWiJAKqoM9wz7lgQJkVI5k6QORJknbglIl5ujAnzK4Q90+cAbzx1RPw15/37Z495FHBr+oqhauezOk5ydbXVdbY21/cK4XpP/cq/b1ConhLMc981+Ji+Ykjd+ah7hXCB1Rbm571PbhoUWkgJhqCAw/QVQ03Mo3CtrXkUlL1yOIp+aHfWSEoAnkxhUCAQYAXvihsiJQAtaHQeBQAgJQAtICgAuA3mUQDKIygAuAdaIoAqCAoAboCUANRCUADQOlICUJHCUQ8MjwQ0ISUAdSkMCgQCQA1SAlAdTQ8AGkVKAFpAUADQKFIC0AKCAoDbYB4FoDyFfRQABJpKuLotEZqeSeAj1CgAamkq2+ivANRCjQKgnIJyjpQAVKQwKDCPAvBzyafslx8uUgJQl8KgQCAA1CAlANUpDAoAfigpP3/ZD4KUALSgWmfGcRzHcfTe76/jnBvH8aN/AdCBlAC0oEJQ8N5ba7333vu+77cKe+fcNE3GmGma4m4HYXP5l3OuwDEDaAHzKADl2fIt+tbaruukpB/HcZqm/BgkQ8zzLDnAWjsMg0SKeHNZLd7c2gpnhDI3RD4AABEeSURBVKbJd/wj3xUlTv0HjxEuDJLPcgvzKDzyfYTP6CuG6gSFkADyP4VzblmWcGwhT+TJIN+5slcI33rwF7ymoFC9v8KD30f4jL5iqHTTg9QEJLEg76mwLEvXdeHPsH5Y80gXB0A9a9MflaqnhJ0De8Lzj4drYmbG1fJ+p/NB3MUhX81+7sqTAUp5yDu35ZQAPEETwyM/7ZAYmiokK3jv4z0oq/MB9oX3e81yK3/siz6GzaaEIG6YAFRqokYhF7orrgqxIMSFAoeEO6EuWIX2U8K59YF7KR0UVov2vEZBOjOGP8MQSgZD4j3CQUmvV/pz6b5zpASgsAo1Cl3X9X0vv0sCCMV/6J8oy0OeWJZlGIawZry+iWIE8J+flV6oqMF5FHhzQb0KfRRkxqTQhXCe57A8nkBpGIaQJ7quC2lgnue+7/PNAejWwjwKwANVG+65Ok5ydbXVdbY21zeAFR97zID35ETz867zTHz9qHeZR+Ht849n0lcMqTsfda8QPvaYL+znBIXqKcEQFHCYvmKoieGR19qaF0HZKwc8RAspAXgyhUGBQACocZeUEC5PfjajBFBNo/MoAMCNUgJpAIoprFEAoMO9UkKyFaMkoAY1CgBu4y7zKFDHAE0ICgDugZYIoAqaHnB/VPI+ACkBqEVhUGB45LOQEh6AlABUpDAoEAieiBddL1ICUBd9FAC0i5QAVEdQANAoUgLQAoICgEbdOiXQeQZqKOyjAECr6vMoHJyhOb4zdbIJdQ+4HWoUANwDLRFAFdQoALiB6ikhn6H57X7ye1IDd6QwKDCPAqBM9ZRwyXKyAm5KYVAgEACatFnqf78cuAuFQQF4slYuWy/qwtda6U5KwANV68w4juM4jt77/XWcc+M4bq3gnLv6uAC0orXSnZSAZ6oQFLz31lrvvfe+7/utHOCcm6bJGDNN02q3A+fcsiw/PVTgRl6v9Z/Kx/HdnnKtlfqkBKhXISj0fd91nQSFYRgkDSS898uyzPPsvZc+B0meGMeRlAA8TWulPikBT2DLd/2z1s7zHFoNkj+F1BaEYxvHcZqm8KdURUjISI7f2gpnhJqktumRL/o9Tv3zoww1iNmnu61S/9ysTa2/XviavmKodI2CdEpIYkHeU2FZlq7rwp/J+pIS6KAAPEeDpf65uR2B22liZsbVLo1bOcA513XdTg9H+7lrTgPAbzRY6tMSgedoYnjk8boB6buwX6ujrM4HeLjWSndSAp6miaCQk96O+XKpSJBgIZ0ZnXP7QygB3FdrpTspAQ9UOihIGe+9j2sR8hqFMDZShByQTL2wLIsEhZ8cK4CqWivdSQl4pgqdM+MRDclwBplhSQr+eDSEtXYYhqTaQMY+MOrh6R7clfwep37dqIewv6ZK/ePL7/F64Wv6iqEKTQ8y4VL4LpjnOSyfpilUDwzD0Pe9/L7fexGPQ//Tp2qn1D+3HLijasFndZzk6moftSzoi3JIraaER77o97hCZR6FaLlp//XC1/QVQ+rOR90rhBRft//c45m4KCg0WOqfm0eh9dcLX9NXDDU66uEbW/MiKHvlgOdosNQ/sZwWM9yUwqBAIMAt0IRyUJul/vfLgbtoYmZG4Gm4uDyotdKdlIAHUlijANxFXIQQHXKtle6kBDwTNQoAGtVU6U5KwGNRo4Dmca2Nf1or9UkJeAKCAtpGStAhfx0/L0hbK/VJCXgIggLugO9dY8yzU1Nrpf7peRSA21EYFJhHASrdtaTJP3efn0mDpT7zKOA5FAYFAgEUe+C7u81S//vlwF0w6gFAu1or3UkJeCCCAoBGtVa6kxLwTAqbHgDo0FTpXrJXI/ECTaFGAcBtNFjqU5cA9ahRQGPoGo4NrZX6J1LC2/V5+6NBCoMCwyNvjK9JbGit1KfuAc+hMCgQCG6PV/AJklC4+6K3VoqTEvAo9FEA0LTWSnFSAp6mWlAYx3EcR+/9/jrOuXEck+Xee+ecc25/cwAter3+/OxqrRQnJeCBKgQF77211nvvve/7Ps8Bwjk3TZMxZpqmuNvBOI5938vvfd87535+xABqaK0Ub2HkJFDBqzhjTNd18vswDKvHMM+zMWae57DJMAz578lq8t/fHDWKMOb1jFcwP9G3p672uclObP/baetJ0LFc7av8JPqKIfsqXv9lrZ3nOdQEJH8K59yyLOHYxnGcpun1ekklRHzM1tphGEK1hLUVzgiXkUuqB7yC+Ym+PXW1z012YqEGMf8sN1gHcO1yta/yk+grhko3PUivgiQW5F0NlmXpui78GdZ3zsUvwOreAKhUvRQvvBxoRBPDI1f7JL4t/qV2oeu6ZM2teRR2KEt/gD6tleKkBDxHE8MjT1QJOOf6vh+GIQ8ZJxpgLjkLAD/SWilOSsCjNFGjkOu6bmvoY6hIoIAHnqC1UpyUgKcpXaMglQdJCMhrFKQzY/gzHkK5VZEA4Mas/e/n7+KmSnFSAh6oQtND13VhIgRJACEohCmYZHlIA8uyyEDKsL6PlDt04AsbReHmOvtrPkFrpXixeRR4D6ApFZoeZMKl0OVQ5kKQ5dM0hdAwDEPIE13XJZUK8Q7j4ZG4n2d8ET7jLE/Jy8z/hkeurN5g6X7hct4naFC14Z4HRzbKbM3Hd6tvAKs2R74INb6CJ8bHJ5s8Z4T9k+dRyJebZ7zomugrhtSdj7pXSJWtlPCAl4ygcNxWUGiwFC/TEvGEF10TfcVQo6MevrE1j4KyV+7GeCFw0N/P8upHuMHSnZYIKKMwKBAIgIdos3T/3XKgCoVBAdDk0deUr5eRUtOsPAutleKkBGjVxMyMALCqtdKalIAHokYBaBQFhtnoFNZaKU5KgG4EBQCtku58ycAPY17GGJsmqdZKd1IC1KDpAUDDjnX9b610JyVAE4ICgLZJEfp6WfMyr1deorZWul8+jwJQl8KmB+ZRALR5vZ7ZX4GsgBYoDAoEAkAZa80r6a/w3/Kt9RUuB6pQGBTQFq6J8J3/Ss2sb+P/ejUGYd6Flkp3UgLujqCAXyIl4DtpqblfHW+tCWMizJ9hEa2V+qQE3AhB4REq36Sk1W8+ffduuURDT8vqkay1QexH0u9La3lOGkkJ+bl+8mSsb3JOQ28V/BKjHgC0aq3+wNq15WFMhNE2v0K+2pcrAJ+iRgGX4lsK1/pbf7DVXyFd/s+FpXULKSE/nq0PXF7HEHXt+OyBAIICvsO3Dn7tXyZY76+wtfz38xlUnEfho1RBvwd8SWFQYB6Fclafap5nXG5rHoXt+RWMMS9j07tOnu1nkL/T7zKPAikB31MYFAgEP3TPZPCLo6YmpaTdeRTW+jbu7ed+y0/3S9h5Yk68gZv/oONX7hoUxnE0xjjnnHOX7PBc993TnX4LP9w56cMd/mpp6mm5vES31soQvBObntiw8JN52u+Oc7VfgrwK2/0VXunGMnLytfJwPy31/xzn4f2ce6vI1mHDD+sSTj/iGXzf3sv9Rj1476213nvvfd/3khhQzuuV/tzBL443fyb2f3DCzjwKh/olJNX38ru18c/LRH9uPe7Z5elxfrif+M2z9V5Klssv+/tffXPuLMfD3S8xWWu7rvPeG2PGcZymKT6Fu0TORh/u79X3+iXGgf009bTIOeU1I6sXlwcfTp6YTzdt9EW/aMMLHy50M9p8lreu0w90C3xz4fy/6op0N6fnUVj9jn27n+Q5Of64PzrO/EMUP9zKHt+p/h5r8OFadr8aBfOv3SH8IqEBH/t7XUWrO5rz2p5HIWNX51eI1/977fxn3oWtUjn+aEjdw9rjXlL3cJfleKCb9VGQTJD0S/De/1lyusA7t6Guh7N/Lresza++jj1++89KqIRG014b8yX8/WO1H8OJ5Sa/f0Qie8dsrf/f8r+bvF//7wMdXf+/5dlYj6+P89+ztrL5DT7qVR5Ol5sFhVVJjcLpF/bchuoezu7++YMHvGbDN1ttf97PP9ypdHLm4c5tVX7Dyx/uv+V/ew/875eN5Vvrhz+szV6+A0fe1hu6mQ15uCfQEBTi6gRlLUMAANR1yz4KAACgjJsFBak8SNoarppKAQAAJG4WFIwxXdf1fS+/h2mXKh4PAACK3S8oSHWCtdZaO03TPM/hX/nkS+6vxw6kXJ2WahzHJz8nQobMxGofUWXjOI7j+PB3RcDbI8eXSU590XO/oGCMeb1e8zzP8/x6vcJH13s/TVP8enjvl2WpcoRNyZ8ZY4zELGNM3/dP/vrjTRIw52mOt0eCL5PcI4qe1/3N89x1nZyOpIewXMcJnrb1zAzDED8zyX8fpeu6rutqH0UTjDHhqUjeIY/F2yPgyyT3nKLnljUKOeecvF9jd6/tucTqMzNNU3h/G2O6rnvs5eOyLA+8BtrCnKcJ3h4xvkxyTyl6aieVK5m/sS5++xpjhmGodmS1Jc9M8mw8+fLRGBPeJ13XPediKJFfAz38IyN4e+T4MsmpL3qU1CjsGIZhnudhGKZpelTUxXHS5cUYEwbUwKi8MDqFtwdO0FT03GZmRuljlS/feQHi9aXfqYIXLHHiaXma/afoFU3lKb35pNt/oYNrG7XuvD1wgr6iR3+NQnDr1wllhDuYAzneHjhBQ9FTu+3jSiZrKNrpnfso+TMT9+V+bNdu6bQcLzEqGhTPMVnb88Ob5Hl7rOLLJKe+6Ln30Sfybzrzd9zOYz/kZm30jiyJf3+g+F0hn+fHPhXSA0t+V/DVdgneHjm+THLqix5V3wX5ezSuO3lgzg3yZyYe0nP3N/E34pk9H/5UvP5+Xh74dZ/j7ZHjyySnvuixL+33ZZY2RbplrZIZamsfRX28SQKeihzPyRF8mSRUvW1qJxUAQHPM17VK4Ura7NY0DMNwvB4i7ziyusPkyN9OlXiiKEyO5MiB3deDRj0AAMo4Pjzko6GDzrllWfZ3Pk3TR9fx4zgmUySdOJIjB3Zft5lHAQBwF33fJz08Vp0opOd57vv+tdFo7r3/dIfTNG3t7aMj2T+wW6NGAQCwZxxH+0989S+TUAn5PSw3x5rn4+qEZM9bV+ey263/eu8/mrcgSSoHj2H1SPYP7NYICgCATeM4TtMk3QiSCYn7vpflcjEdNjl4WZ/kifhmzfszYO7MfPVpu0PSB/P4MaweidYpuQgKAIBNcn9IKTLl+nuaJvOvgJflyU0UD46AOF2myrzIq//6tN3hyxuEJkeyc2C3RlAAAOyJL6zj3+NwEBe3y7Ic3POJXoQ7DzGOY/nhiMmRHD/3GyEoAAA+tl8iVpk/4NMOCjiIoAAA2BNXp4ffk/b4pMr9YA386evv01URl0uOpJ0DuxBBAQCwSTowhj+lY6MxZhzHeOaAeJ28T5/PmLVaB6kP8N6HALEaOFb7QLxtd8gPYPVQDx7D6pGonZ6y3lxPAIBGmWhmxvgqOZ5/MLnLQyhQkpkQd4qe1dVkrkazfZcEszZr5M7EiKszOoRxHPGGx49h9UhWD0wBggIA4L2tIjC+dWRYeLDI7LouDLA8OAXy1nzMp0voON98NA1zciRvJ4q+L51nBQD4qeRe5F3XJZUNBwtd2cnxO5uHbHGVsMNP766eHMnlB9YO/XePBAD8gtzgIPyZlCbWHipfwjiF/amUpWOBzBF5ebEl+5SppbZ2Hk52nmfpiJAcyS8OrBFqTwwAUECBHnxSSA/DUGv0o2SUEFZUzqq0g1EPAIDzCvTz997HHSfLC2EoqUR5CIICAABv6Bz3eAxBAQCAN57W3BAjKAAAsEfr3Z4OIigAALAndFCw1q5O36Qbox4AAMAmahQAAMAmggIAANhEUAAAAJsICgAAYBNBAQAAbCIoAACATQQFAACwiaAAAAA2ERQAAMAmggIAANj0/wFaUMqawWXRhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = RooStats.HypoTestPlot(htr, 100, -15, 15)\n",
    "canvas = ROOT.TCanvas()\n",
    "plot.Draw()\n",
    "canvas.Draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "observed qvalue:  2.390387917655447\n",
      "observed p-value:  0.015\n",
      "k_alpha = 1.1855245352433044\n",
      "power = 0.694\n"
     ]
    }
   ],
   "source": [
    "print(\"observed qvalue: \", test.Evaluate(data, ROOT.RooArgSet(ws.var('density_quartz'))))\n",
    "print(\"observed p-value: \", htr.NullPValue())\n",
    "alpha = 0.05\n",
    "kalpha = htr.GetNullDistribution().InverseCDF(1 - alpha)\n",
    "beta = htr.GetAltDistribution().CDF(kalpha)\n",
    "print(f\"k_alpha = {kalpha}\")\n",
    "print(f\"power = {1 - beta}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Exercize\n",
    "Show that the in this case the likelihood ratio is equivalent to the weighted mean of the two measurements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def eval_test_stat():\n",
    "    d = ROOT.RooDataSet(\"d\", \"d\", ROOT.RooArgSet(ws.var('density1'), ws.var('density2')))\n",
    "    d.add(ROOT.RooArgSet(ws.var('density1'), ws.var('density2')))\n",
    "    return test.Evaluate(d, ROOT.RooArgSet(ws.var('true_density')))\n",
    "\n",
    "fig_opal, ax = plt.subplots(figsize=(12, 7))\n",
    "\n",
    "x = np.linspace(1.3, 3.5, 100)\n",
    "y = np.linspace(1.5, 3.5, 100)\n",
    "\n",
    "qvalues = np.zeros((len(x), len(y)))\n",
    "pdf_opal_values = np.zeros((len(x), len(y)))\n",
    "pdf_quartz_values = np.zeros((len(x), len(y)))\n",
    "for ix, xx in enumerate(x):\n",
    "    for iy, yy in enumerate(y):        \n",
    "        ws.var('density1').setVal(xx)\n",
    "        ws.var('density2').setVal(yy)\n",
    "        qvalues[iy, ix] = eval_test_stat()\n",
    "        pdf_opal_values[iy, ix] = pdf_opal.getVal()\n",
    "        pdf_quartz_values[iy, ix] = pdf_quartz.getVal()\n",
    "        \n",
    "c = plt.pcolormesh(x, y, qvalues, cmap='viridis')\n",
    "cs = ax.contour(x, y, qvalues, [kalpha], linestyles='dashed')\n",
    "ax.clabel(cs, fontsize=14, fmt=r\"$k_\\alpha$ = %1.3f\", inline_spacing=30, use_clabeltext=True)\n",
    "ax.contour(x, y, pdf_opal_values, cmap='Blues', alpha=0.6)\n",
    "ax.contour(x, y, pdf_quartz_values, cmap='Oranges', alpha=0.6)\n",
    "ax.plot(ws.var('density_opal').getVal(), ws.var('density_opal').getVal(), 'o', label='opal (H1)')\n",
    "ax.plot(ws.var('density_quartz').getVal(), ws.var('density_quartz').getVal(), 'o', label='quartz (H0)')\n",
    "ax.text(1.5, 1.6, \"reject\", size=20)\n",
    "ax.text(1.8, 3.2, \"accept\", size=20)\n",
    "datalist = [x.getVal() for x in iter_collection(data.get(0))]\n",
    "ax.plot(datalist[0], datalist[1], 'v', label='observed', color='red')\n",
    "\n",
    "ax.set_xlabel('density1')\n",
    "ax.set_ylabel('density2')\n",
    "ax.legend()\n",
    "ax.set_aspect('equal')\n",
    "plt.colorbar(c)\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can easily show the acceptance / rejection region in the space of the observables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig_opal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercize\n",
    "Compute the acceptance region using the simple mean as test-statistics: show that it is less powerful. What kind of shape is the acceptance region in this case?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Plot the power as a function of the size of the test for the likelihood ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphas = np.linspace(0, 1, 100)\n",
    "powers = []\n",
    "\n",
    "for alpha in alphas:\n",
    "    kalpha = htr.GetNullDistribution().InverseCDF(1 - alpha)\n",
    "    beta = htr.GetAltDistribution().CDF(kalpha)\n",
    "    powers.append(1 - beta)\n",
    "    \n",
    "plt.plot(alphas, powers)   \n",
    "plt.xlabel(r'$\\alpha$')\n",
    "plt.ylabel(r'power')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Exercize\n",
    "Compute $\\text{power}(\\alpha)$ for the simple mean and compare with the weighted mean.\n",
    "### Exercize\n",
    "Explain why the previous plot remembers the ROC curve (bkg-rejection vs signal-efficiency)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Exclusion and frequentist intervals\n",
    "\n",
    "By now we have done statistical test to discover something (a signal), defining the null hypothesis to be the background only case. Suppose we have counted $n_{obs}$ events in a Poissonian process with mean $\\lambda$. What are the values $[\\lambda_{up}, \\infty]$ that we can exclude? This is something called hypothesis inversion. As usual we define the null hypothesis: $H_0: \\lambda = N$ with $N > n_{obs}$. The likelihood:\n",
    "\n",
    "$$L = \\text{Pois}(n|N)$$\n",
    "\n",
    "than the p-value of our observation $n_{obs}$:\n",
    "\n",
    "$$\\text{p-value} = \\sum_{n\\geq n_{obs}} \\text{Pois}(n|N)$$\n",
    "\n",
    "if p-value $<\\alpha$ we consider $N$ to be inside the exluded region $[\\lambda_{up}, \\infty]$. The general approach is to scan for many value of $N$ until we found the one with p-value $=\\alpha$, which is $n_{up}$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Example: RooFit asymmetric error bars\n",
    "\n",
    "Let's do a two-side test and compute the excluded intervals $[-\\infty, \\lambda_{down}]$ and $[\\lambda_{up}, \\infty]$ with $\\alpha=1 - 0.6827$. This means that every single interval should be tested with $\\alpha=(1-0.6827)/2.=0.15865$. We can solve it analytically or with a scan. Suppose $n_{obs} = 4$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "NOBS = 4\n",
    "ALPHA = z2p(1)  # 0.158...\n",
    "\n",
    "def compute_pvalue(nobs, ntrue, left):\n",
    "    if left:\n",
    "        return stats.poisson(ntrue).cdf(nobs)\n",
    "    else:\n",
    "        return stats.poisson(ntrue).sf(nobs) + stats.poisson(ntrue).pmf(nobs)\n",
    "\n",
    "fig, axs = plt.subplots(1, 3, figsize=(13, 4))\n",
    "x = np.linspace(NOBS, NOBS + 3 * NOBS, 20)\n",
    "\n",
    "axs[1].plot(x, compute_pvalue(NOBS, x, left=True), 'r')\n",
    "axs[1].hlines(ALPHA, np.min(x), np.max(x), linestyles='--')\n",
    "\n",
    "x = np.linspace(max(NOBS - NOBS * 3, 0), NOBS, 100)\n",
    "axs[0].plot(x, compute_pvalue(NOBS, x, left=False), 'b')\n",
    "axs[0].hlines(ALPHA, np.min(x), np.max(x), linestyles='--')\n",
    "\n",
    "from scipy.optimize import brenth\n",
    "lambda_up = brenth(lambda x: compute_pvalue(NOBS, x, True) - ALPHA, NOBS, NOBS * 3)\n",
    "lambda_down = brenth(lambda x: compute_pvalue(NOBS, x, False) - ALPHA, 1E-5, NOBS)\n",
    "\n",
    "axs[1].plot(lambda_up, compute_pvalue(NOBS, lambda_up, True), 'ro')\n",
    "axs[0].plot(lambda_down, compute_pvalue(NOBS, lambda_down, False), 'bo')\n",
    "axs[1].set_xlabel('$\\lambda$'); axs[0].set_xlabel('$\\lambda$')\n",
    "axs[1].set_ylabel('$P(n\\leq n_{obs})$')\n",
    "axs[0].set_ylabel('$P(n\\geq n_{obs})$')\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "x = np.arange(0, NOBS * 3)\n",
    "axs[2].step(x, stats.poisson(lambda_up).pmf(x), 'r', label='Pois[$\\lambda=\\lambda_{up}$]')\n",
    "axs[2].step(x, stats.poisson(lambda_down).pmf(x), 'b', label='Pois[$\\lambda=\\lambda_{down}$]')\n",
    "axs[2].vlines(NOBS, 0, 0.3, linestyles='--')\n",
    "axs[2].legend(fontsize=12, loc=0)\n",
    "axs[2].set_xlabel('n')\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1300x400 with 3 Axes>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0856608137771175 7.1627531722609445\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "$\\lambda = 4.00^{+3.16}_{-1.91}$"
      ],
      "text/plain": [
       "<IPython.core.display.Latex object>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(lambda_down, lambda_up)\n",
    "Latex(\"$\\lambda = %.2f^{+%.2f}_{-%.2f}$\" % (NOBS, lambda_up - NOBS, NOBS - lambda_down))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question:\n",
    "why we assumed that the central value for $\\lambda$ is $n_{obs}=4$?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.085660813777117, 7.162753172260944)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_confiderence_poisson(n):\n",
    "    ym = np.array([0], dtype=np.float64)\n",
    "    yp = np.array([0], dtype=np.float64)\n",
    "    ROOT.RooHistError.instance().getPoissonInterval(n, ym, yp, 1)\n",
    "    return ym[0], yp[0]\n",
    "\n",
    "get_confiderence_poisson(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the function used by RooFit to draw error bands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(7, 5))\n",
    "trues = np.linspace(1E-5, NOBS * 4, 100)\n",
    "obss = np.arange(0, NOBS * 3, dtype=np.int32)\n",
    "v = np.zeros((len(trues), len(obss)))\n",
    "limits = []\n",
    "for ix, obs in enumerate(obss):\n",
    "    limits.append(get_confiderence_poisson(int(obs)))\n",
    "    for iy, true in enumerate(trues):\n",
    "        v[iy, ix] = stats.poisson(true).pmf(obs)\n",
    "ax.pcolormesh(obss, trues, v, vmax=np.percentile(v, 99))\n",
    "ax.plot(obss, np.array(limits).T[0], 'k', drawstyle='steps-post')\n",
    "ax.plot(obss, np.array(limits).T[1], 'k', drawstyle='steps-post')\n",
    "ax.set_xlim(0, np.max(obss))\n",
    "ax.set_xlabel('obs')\n",
    "ax.set_ylabel('$\\lambda$'); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question: explain why this is a frequentist procedure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bayesian approach\n",
    "\n",
    "$$P(\\lambda|n_{obs}) = P(n_{obs}|\\lambda)P(\\lambda)$$\n",
    "\n",
    "We assume the prior $P(\\lambda)$ to be flat (and zero for negative values), equivalent to a constant we can ignore. Everybody agree?\n",
    "\n",
    "$$P(\\lambda|n_{obs}) = P(n_{obs}|\\lambda)$$\n",
    "\n",
    "note that $n_{obs}$ is fixed, so this is a real function $f(\\lambda)$. Let find a region [low, high] such that\n",
    "\n",
    "$$\\int_{low}^{high} P(\\lambda|n_{obs}) = 68\\%$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.8403088555932197 7.162753172255066\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "$\\lambda = 4.00_{-1.16}^{+3.16}$"
      ],
      "text/plain": [
       "<IPython.core.display.Latex object>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def f(true):\n",
    "    return stats.poisson(true).pmf(NOBS)\n",
    "\n",
    "import scipy\n",
    "from scipy.optimize import brenth, brentq\n",
    "def f_low(x):\n",
    "    return scipy.integrate.quad(f, 0, x)[0] - z2p(1)\n",
    "\n",
    "def f_hi(x):\n",
    "    return scipy.integrate.quad(f, x, NOBS * 10)[0] - z2p(1)\n",
    "\n",
    "lo_bayes, hi_bayes = brentq(f_low, 1E-5, NOBS), brentq(f_hi, NOBS, NOBS * 5)\n",
    "print(lo_bayes, hi_bayes)\n",
    "Latex(\"$\\lambda = %.2f_{-%.2f}^{+%.2f}$\" % (NOBS, NOBS - lo_bayes, hi_bayes - NOBS))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.289882379081169 6.402859007849325\n"
     ]
    }
   ],
   "source": [
    "def invert(f, y, a, b):\n",
    "    return brentq(lambda x: f(x) - y, a, b)\n",
    "\n",
    "lo_bayes_el = brenth(\n",
    "    lambda x: scipy.integrate.quad(f, x, invert(f, f(x), x * (1 + 1E-5), NOBS * 20))[0] - (1 - z2p(1) * 2),\n",
    "    1E-2, NOBS - 1E-2)\n",
    "hi_bayes_el = invert(f, f(lo_bayes_el), NOBS, NOBS * 5)\n",
    "print(lo_bayes_el, hi_bayes_el)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.289882286599089 6.402858915367273\n"
     ]
    }
   ],
   "source": [
    "def width_interval(x):\n",
    "    return brenth(lambda y: scipy.integrate.quad(f, x, y)[0] - (1 - z2p(1) * 2), x, NOBS * 20) - x\n",
    "\n",
    "sol = scipy.optimize.minimize_scalar(width_interval, (1E-1, 3), bounds=(0, NOBS), method='bounded')\n",
    "lo_bayes_min, hi_bayes_min = sol.x, sol.x + width_interval(sol.x)\n",
    "print(lo_bayes_min, hi_bayes_min)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0, NOBS * 3, 100)\n",
    "\n",
    "fig, axs = plt.subplots(1, 3, figsize=(14, 4))\n",
    "\n",
    "axs[0].plot(x, f(x))\n",
    "axs[0].fill_between(np.linspace(0, lo_bayes, 50), f(np.linspace(0, lo_bayes, 50)))\n",
    "axs[0].fill_between(np.linspace(hi_bayes, NOBS * 3, 50), f(np.linspace(hi_bayes, NOBS * 3, 50)))\n",
    "axs[0].set_title('equal probability (central)', fontsize=15)\n",
    "axs[0].text(7, 0.16, '$\\lambda = %.2f_{-%.2f}^{+%.2f}$' % (NOBS, NOBS - lo_bayes, hi_bayes - NOBS), size=15)\n",
    "axs[0].text(4, 0.04, '68%', size=15)\n",
    "axs[0].set_xlabel('$\\lambda$')\n",
    "axs[1].plot(x, f(x))\n",
    "axs[1].fill_between(np.linspace(0, lo_bayes_el, 50), f(np.linspace(0, lo_bayes_el, 50)))\n",
    "axs[1].fill_between(np.linspace(hi_bayes_el, NOBS * 3, 50), f(np.linspace(hi_bayes_el, NOBS * 3, 50)))\n",
    "axs[1].set_title('equal likelihood', fontsize=15)\n",
    "axs[1].text(7, 0.16, '$\\lambda = %.2f_{-%.2f}^{+%.2f}$' % (NOBS, NOBS - lo_bayes_el, hi_bayes_el - NOBS), size=15)\n",
    "axs[1].text(3.5, 0.04, '68%', size=15)\n",
    "axs[1].set_xlabel('$\\lambda$')\n",
    "axs[2].plot(x, f(x))\n",
    "axs[2].fill_between(np.linspace(0, lo_bayes_min, 50), f(np.linspace(0, lo_bayes_min, 50)))\n",
    "axs[2].fill_between(np.linspace(hi_bayes_min, NOBS * 3, 50), f(np.linspace(hi_bayes_min, NOBS * 3, 50)))\n",
    "axs[2].set_title('minimum interval', fontsize=15)\n",
    "axs[2].text(7, 0.16, '$\\lambda = %.2f_{-%.2f}^{+%.2f}$' % (NOBS, NOBS - lo_bayes_min, hi_bayes_min - NOBS), size=15)\n",
    "axs[2].text(3.5, 0.04, '68%', size=15)\n",
    "axs[2].set_xlabel('$\\lambda$')\n",
    "for ax in axs: ax.set_yticklabels([])\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x400 with 3 Axes>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Profile likelihood ratio\n",
    "\n",
    "Suppose you have composite hypothesis as \n",
    "\n",
    "$$H_0: \\theta\\in\\Theta_0 \\quad H_1: \\theta\\in\\Theta_0^C \\quad \\Theta_0\\subset\\Theta$$\n",
    "\n",
    "where $\\Theta_0 = \\{s=0, \\ldots\\}$, $\\Theta_0^C = \\{s\\neq 0, \\ldots\\}$. $x$ are the data.\n",
    "\n",
    "$$\\lambda(x) = \\frac{\\sup_{\\theta\\in\\Theta_0}{L(\\theta|x)}}{\\sup_{\\theta\\in\\Theta}{L(\\theta|x)}}$$\n",
    "\n",
    "For example it can be $H_0: s=0$, $H_1: s\\neq 0$\n",
    "\n",
    "$$\\lambda(x) = \\frac{\\sup_{\\theta}L(s=0, \\theta|x)}{\\sup_{\\theta,s} L(s, \\theta|x)}=\\frac{L(s=0, \\hat{\\hat\\theta}(0)|x)}{L(\\hat{s}, \\hat\\theta|x)}$$\n",
    "\n",
    "<small>\n",
    "where $\\hat{\\hat\\theta}(0)$ is the value of $\\theta$ which optimize the likelihood for $s=0$ (conditioned likelihood), while $\\hat{s}$ and $\\hat{\\theta}$ are the values that optimize the likelihood without any constrains (unconditioned likelihood).\n",
    "</small>\n",
    "\n",
    "It varies between 0 and 1, low values mean that the observed result is less likely to occur under the null hypothesis as compared to the alternative. (numerator $\\leq$ denominator)\n",
    "\n",
    "The profile likelihood ratio is nearly an optimal test-statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "As shown it is important to have an analytically expression $f_q$ of the distribution of the test-statistics $q$ to compute the p-value: $\\text{p-value} = \\int_{q^\\text{obs}}^{\\infty} f_q(q) dq$. Otherwise toys must be run.\n",
    "\n",
    "## Wilks's theorem\n",
    "\n",
    "The quantity $t=-2\\log(\\lambda)$ is aymptotically (large sample) distributed as a $\\chi^2$ distribution with $n=\\text{dim}(\\Theta)-\\text{dim}(\\Theta_0)$ degrees of freedom when $H_0$ is true."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Let resurrect the simple Poisson model $\\text{Poisson}(n|s + b)$. This time, instead of using the number of observed events as test-statistics, let use the profile likelihood ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "observed =  229.0\n"
     ]
    }
   ],
   "source": [
    "S, B = 30, 200  # expected values\n",
    "\n",
    "ws_poisson = ROOT.RooWorkspace('ws_poisson')\n",
    "b = ws_poisson.factory(\"b[%f]\" % B)\n",
    "n_exp = ws_poisson.factory(\"sum::n_exp(s[%f, -500, 500], b)\" % S)\n",
    "pdf = ws_poisson.factory(\"Poisson::pdf(n_obs[0, 1000], n_exp)\")\n",
    "aset = ROOT.RooArgSet(ws_poisson.var('n_obs'))\n",
    "data = pdf.generate(aset, 1)  # generate with 1 entry\n",
    "print(\"observed = \", data.get(0).first().getVal())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# create a MC linked to the ws\n",
    "sbModel = RooStats.ModelConfig(\"sbmodel\", ws_poisson)   \n",
    "sbModel.SetPdf(pdf)\n",
    "sbModel.SetObservables('n_obs')  # it understands variable-names\n",
    "sbModel.SetParametersOfInterest('s')\n",
    "# save the value of s for (s+b)-hypothesis\n",
    "sbModel.SetSnapshot(ROOT.RooArgSet(ws_poisson.var('s')))\n",
    "getattr(ws_poisson, 'import')(sbModel)  # import is a keyword in python\n",
    "\n",
    "bModel = sbModel.Clone(\"bmodel\")  # create a bkg-only model\n",
    "ws_poisson.var('s').setVal(0)             # with no signal\n",
    "bModel.SetSnapshot(ROOT.RooArgSet(ws_poisson.var('s')))\n",
    "getattr(ws_poisson, 'import')(bModel);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "profll = RooStats.ProfileLikelihoodTestStat(bModel.GetPdf())\n",
    "# this modify a bit our test statistics\n",
    "profll.SetOneSidedDiscovery(1)\n",
    "\n",
    "hypoCalc = RooStats.FrequentistCalculator(data, sbModel, bModel)\n",
    "hypoCalc.SetToys(100000, 5000)  # generate much more toys for bkg-only\n",
    "\n",
    "toy_sampler = hypoCalc.GetTestStatSampler()\n",
    "toy_sampler.SetTestStatistic(profll)\n",
    "toy_sampler.SetNEventsPerToy(1)\n",
    "\n",
    "htr = hypoCalc.GetHypoTest()\n",
    "htr.SetPValueIsRightTail(True)  # the \"extreme\" cases are on the right tail\n",
    "htr.SetBackgroundAsAlt(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue =  0.02451  significance =  1.9684176737724473\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = RooStats.HypoTestPlot(htr, 50, 0, 10)\n",
    "canvas = ROOT.TCanvas()\n",
    "plot.Draw()\n",
    "canvas.SetLogy(); canvas.Draw()\n",
    "print(\"pvalue = \", htr.NullPValue(), \" significance = \", htr.Significance())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The distribution under the $H_0$ has a peak at 0, which does not follow the $\\chi^2$ distribution. Explain why (see test statistics for one-side-discovery and SetOneSideDiscovery(True) option)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can also use the AsymtoticCalculator, which instead of using the empirical distribution of the likelihood ratio from toys, it uses the asymptotic distribution ($\\chi^2_1$ distribution for the simple likelihood ratio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue = 0.022544284300433422  significance = 2.003827251118166\n",
      "AsymptoticCalculator::EvaluateNLL  ........ using Minuit / Migrad with strategy  1 and tolerance 1\n",
      " **********\n",
      " **840010 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 s            0.00000e+00  1.00000e+02   -5.00000e+02  5.00000e+02\n",
      " **********\n",
      " **840011 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **840012 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **840013 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **840014 **MIGRAD         500           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=3.63616 FROM MIGRAD    STATUS=CONVERGED      17 CALLS          18 TOTAL\n",
      "                     EDM=9.65173e-08    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  s            2.89953e+01   1.51301e+01   4.22724e-05  -1.02478e-02\n",
      "                               ERR DEF= 0.5\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 3.63616\tfit time : Real time 0:00:00, CP time 0.000\n",
      "MakeAsimov: Setting poi s to a constant value = 30\n",
      "Generated Asimov data for observables RooArgSet:: = (n_obs)\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 3.63834 for poi fixed at = 30\n",
      "\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 5.64383 for poi fixed at = 0\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 5.78359 for poi fixed at = 0\n"
     ]
    }
   ],
   "source": [
    "hypoCalc = RooStats.AsymptoticCalculator(data, sbModel, bModel)\n",
    "hypoCalc.SetOneSidedDiscovery(True)\n",
    "htr_asym = hypoCalc.GetHypoTest()\n",
    "print(\"pvalue =\", htr_asym.NullPValue(), \" significance =\", htr_asym.Significance())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## On/off problem\n",
    "\n",
    "Let's introduce a classical problem in high-energy / astro / ... physics. Suppose you have a source that can contain signal and background events. You have an other source that contains only background events and the background in the two source is correlated.\n",
    "\n",
    "This is the case when you have a control region, with only background, and a signal region with signal plus background. Usually the correlation of the background between the two region comes from a simulation. In astrophysics this can be the case when with telescope one wants to see if there is source in a particular region of the sky, using as control region the average of regions where there are no known source.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "In term of random variables:\n",
    "\n",
    "$$ N_{SR} = S + B \\qquad N_{CR} = \\alpha B$$\n",
    "\n",
    "with $S$ and $B$ distributed as Poisson distribution. What we observe are the number of events in the signal region $n_{SR}$ and in the control region $n_{CR}$. $\\alpha$ is assumed to be a known constant. We can write the likelihood as:\n",
    "\n",
    "$$L(s, b|n_{SR}, n_{CR}) = \\text{Pois}(n_{SR}|s + b) \\text{Pois}(n_{CR}|\\alpha b)$$\n",
    "\n",
    "remember that $\\alpha$ is a known constant. The test statistics is based on the profiled likelihood ratio:\n",
    "\n",
    "$$-2\\log\\lambda = -2\\log\\frac{\\sup_{b \\in [0, \\infty], s\\in\\{0\\}}{L(s, b)}}{\\sup_{b\\in [0, \\infty], s\\in [0, \\infty]}{L(s, b)}} = -2\\log\\frac{L(0, \\hat{\\hat{b}}(s=0))}{L(\\hat{s}, \\hat{b})}$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RooWorkspace(ws_onoff) ws_onoff contents\n",
      "\n",
      "variables\n",
      "---------\n",
      "(alpha,b,n_cr,n_sr,s)\n",
      "\n",
      "p.d.f.s\n",
      "-------\n",
      "RooPoisson::N_CR[ x=n_cr mean=alpha_x_b ] = 0\n",
      "RooPoisson::N_SR[ x=n_sr mean=s_plus_b ] = 0\n",
      "RooProdPdf::model[ N_SR * N_CR ] = 0\n",
      "\n",
      "functions\n",
      "--------\n",
      "RooProduct::alpha_x_b[ alpha * b ] = 500\n",
      "RooAddition::s_plus_b[ s + b ] = 50\n",
      "\n",
      "parameter snapshots\n",
      "-------------------\n",
      "sbModel__snapshot = (s=15)\n",
      "bModel__snapshot = (s=0)\n",
      "\n",
      "named sets\n",
      "----------\n",
      "bModel__snapshot:(s)\n",
      "sbModel_Observables:(n_sr,n_cr)\n",
      "sbModel_POI:(s)\n",
      "sbModel__snapshot:(s)\n",
      "\n",
      "generic objects\n",
      "---------------\n",
      "RooStats::ModelConfig::sbModel\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ws_onoff = ROOT.RooWorkspace('ws_onoff')\n",
    "model_sr = ws_onoff.factory(\"Poisson:N_SR(n_sr[0, 5000], sum:s_plus_b(s[15, 0, 100], b[50, 0, 100] ))\")\n",
    "model_cr = ws_onoff.factory(\"Poisson:N_CR(n_cr[0, 5000], prod:alpha_x_b(alpha[10, 0, 10], b))\")\n",
    "model = ws_onoff.factory(\"PROD:model(N_SR, N_CR)\")\n",
    "ws_onoff.var(\"alpha\").setConstant(True)\n",
    "\n",
    "sbModel = RooStats.ModelConfig('sbModel', ws_onoff)\n",
    "sbModel.SetObservables('n_sr,n_cr')\n",
    "sbModel.SetParametersOfInterest('s')\n",
    "sbModel.SetPdf('model')\n",
    "sbModel.SetSnapshot(ROOT.RooArgSet(ws_onoff.var('s')))\n",
    "getattr(ws_onoff, 'import')(sbModel)\n",
    "\n",
    "bModel = sbModel.Clone(\"bModel\")\n",
    "ws_onoff.var('s').setVal(0)\n",
    "bModel.SetSnapshot(bModel.GetParametersOfInterest())\n",
    "\n",
    "ws_onoff.Print()\n",
    "ws_onoff.writeToFile('onoff.root')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"551pt\" height=\"416pt\" viewBox=\"0.00 0.00 550.92 415.81\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 411.81)\">\n",
       "<title>model</title>\n",
       "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-411.81 546.92,-411.81 546.92,4 -4,4\"/>\n",
       "<!-- model -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>model</title>\n",
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       "<text text-anchor=\"middle\" x=\"275.23\" y=\"-381.64\" font-family=\"Times,serif\" font-size=\"14.00\">RooProdPdf</text>\n",
       "<text text-anchor=\"middle\" x=\"275.23\" y=\"-366.64\" font-family=\"Times,serif\" font-size=\"14.00\">model</text>\n",
       "<text text-anchor=\"middle\" x=\"275.23\" y=\"-351.64\" font-family=\"Times,serif\" font-size=\"14.00\">0.000000</text>\n",
       "</g>\n",
       "<!-- N_SR -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>N_SR</title>\n",
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       "</g>\n",
       "<!-- N_SR&#45;&gt;n_sr -->\n",
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       "<title>N_SR-&gt;n_sr</title>\n",
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       "<!-- s_plus_b -->\n",
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       "<title>s_plus_b-&gt;s</title>\n",
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      ],
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.graphVizTree(\"on_off_graph.dot\")\n",
    "!dot -Tsvg on_off_graph.dot > on_off_graph.svg; rm on_off_graph.dot\n",
    "SVG(\"on_off_graph.svg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "observed  N_SR = 57, N_CR = 447\n",
      "\n",
      "best fit     s        b\n",
      "SR        12.3     44.7\n",
      "CR                447.0\n"
     ]
    }
   ],
   "source": [
    "sbModel.LoadSnapshot()\n",
    "data = model.generate(bModel.GetObservables(), 1)\n",
    "print(\"observed  N_SR = %.f, N_CR = %.f\" % tuple([x.getVal() for x in iter_collection(data.get(0))]))\n",
    "model.fitTo(data)\n",
    "print(\"\\nbest fit     s        b\")\n",
    "print(\"SR    {:>8.1f} {:>8.1f}\".format(ws_onoff.var('s').getVal(), ws_onoff.var('b').getVal()))\n",
    "print(\"CR             {:>8.1f}\".format(ws_onoff.function('alpha_x_b').getVal()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "profll = RooStats.ProfileLikelihoodTestStat(bModel.GetPdf())\n",
    "# this modify a bit our test statistics\n",
    "profll.SetOneSidedDiscovery(True)\n",
    "\n",
    "hypoCalc = RooStats.FrequentistCalculator(data, sbModel, bModel)\n",
    "hypoCalc.SetToys(10000, 500)\n",
    "\n",
    "toy_sampler = hypoCalc.GetTestStatSampler()\n",
    "toy_sampler.SetTestStatistic(profll)\n",
    "toy_sampler.SetNEventsPerToy(1)\n",
    "\n",
    "htr = hypoCalc.GetHypoTest()\n",
    "htr.SetPValueIsRightTail(True)  # the \"extreme\" cases are on the right tail\n",
    "htr.SetBackgroundAsAlt(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue =  0.0443  significance =  1.702829395744341\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = RooStats.HypoTestPlot(htr, 50, 0, 20)\n",
    "canvas = ROOT.TCanvas()\n",
    "plot.Draw()\n",
    "canvas.SetLogy()\n",
    "canvas.Draw()\n",
    "print(\"pvalue = \", htr.NullPValue(), \" significance = \", htr.Significance())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue = 0.04696458131669854  significance = 1.6750258361478902\n",
      "expected p-value =  0.04258026360170343  significance = 1.721497821219153\n",
      "AsymptoticCalculator::EvaluateNLL  ........ using Minuit / Migrad with strategy  1 and tolerance 1\n",
      " **********\n",
      " **    1 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **    2 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 b            4.47048e+01  2.11370e+00    0.00000e+00  1.00000e+02\n",
      "     2 s            1.23328e+01  6.16639e+00    0.00000e+00  1.00000e+02\n",
      " **********\n",
      " **    3 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **    4 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **    5 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **    6 **MIGRAD        1000           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=6.91233 FROM MIGRAD    STATUS=CONVERGED      24 CALLS          25 TOTAL\n",
      "                     EDM=2.54682e-07    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  b            4.46991e+01   2.11354e+00   7.69949e-05  -8.62256e-03\n",
      "   2  s            1.23028e+01   7.76596e+00   4.31671e-04   1.09648e-03\n",
      "                               ERR DEF= 0.5\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 6.91233\tfit time : Real time 0:00:00, CP time 0.000\n",
      "MakeAsimov: Setting poi s to a constant value = 15\n",
      "MakeAsimov: doing a conditional fit for finding best nuisance values \n",
      " **********\n",
      " **    1 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **    2 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 b            4.46991e+01  2.11354e+00    0.00000e+00  1.00000e+02\n",
      " **********\n",
      " **    3 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **    4 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **    5 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **    6 **MIGRAD         500           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=6.97007 FROM MIGRAD    STATUS=CONVERGED      12 CALLS          13 TOTAL\n",
      "                     EDM=1.04731e-07    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  b            4.45114e+01   2.03345e+00   7.75168e-05  -7.90713e-03\n",
      "                               ERR DEF= 0.5\n",
      "fit time Real time 0:00:00, CP time 0.000\n",
      "Generated Asimov data for observables RooArgSet:: = (n_sr,n_cr)\n",
      "AsymptoticCalculator::EvaluateNLL  ........ using Minuit / Migrad with strategy  1 and tolerance 1\n",
      " **********\n",
      " **    7 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **    8 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 b            4.45114e+01  2.03345e+00    0.00000e+00  1.00000e+02\n",
      " **********\n",
      " **    9 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **   10 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **   11 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **   12 **MIGRAD         500           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=6.93171 FROM MIGRAD    STATUS=CONVERGED      24 CALLS          25 TOTAL\n",
      "                     EDM=5.00781e-14    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  b            4.45114e+01   2.03447e+00   7.70842e-05   5.46498e-06\n",
      "                               ERR DEF= 0.5\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 6.93171 for poi fixed at = 15\tfit time : Real time 0:00:00, CP time 0.000\n",
      "\n",
      "AsymptoticCalculator::EvaluateNLL  ........ using Minuit / Migrad with strategy  1 and tolerance 1\n",
      " **********\n",
      " **   13 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **   14 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 b            4.46991e+01  2.11354e+00    0.00000e+00  1.00000e+02\n",
      " **********\n",
      " **   15 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **   16 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **   17 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **   18 **MIGRAD         500           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=8.31519 FROM MIGRAD    STATUS=CONVERGED      15 CALLS          16 TOTAL\n",
      "                     EDM=6.06417e-08    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  b            4.58177e+01   2.04031e+00   8.39421e-05  -6.01192e-03\n",
      "                               ERR DEF= 0.5\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 8.31519 for poi fixed at = 0\tfit time : Real time 0:00:00, CP time 0.000\n",
      "AsymptoticCalculator::EvaluateNLL  ........ using Minuit / Migrad with strategy  1 and tolerance 1\n",
      " **********\n",
      " **   19 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **   20 **SET NOGRAD\n",
      " **********\n",
      " PARAMETER DEFINITIONS:\n",
      "    NO.   NAME         VALUE      STEP SIZE      LIMITS\n",
      "     1 b            4.58177e+01  2.04031e+00    0.00000e+00  1.00000e+02\n",
      " **********\n",
      " **   21 **SET ERR         0.5\n",
      " **********\n",
      " **********\n",
      " **   22 **SET PRINT           0\n",
      " **********\n",
      " **********\n",
      " **   23 **SET STR           1\n",
      " **********\n",
      " **********\n",
      " **   24 **MIGRAD         500           1\n",
      " **********\n",
      " MIGRAD MINIMIZATION HAS CONVERGED.\n",
      " MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.\n",
      " FCN=8.98771 FROM MIGRAD    STATUS=CONVERGED      12 CALLS          13 TOTAL\n",
      "                     EDM=9.64486e-10    STRATEGY= 1      ERROR MATRIX ACCURATE \n",
      "  EXT PARAMETER                                   STEP         FIRST   \n",
      "  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE \n",
      "   1  b            4.58750e+01   2.04160e+00   8.70742e-05  -7.57780e-04\n",
      "                               ERR DEF= 0.5\n",
      "AsymptoticCalculator::EvaluateNLL -  value = 8.98771 for poi fixed at = 0\tfit time : Real time 0:00:00, CP time 0.000\n"
     ]
    }
   ],
   "source": [
    "hypoCalc = RooStats.AsymptoticCalculator(data, sbModel, bModel)\n",
    "hypoCalc.SetOneSidedDiscovery(True)\n",
    "htr = hypoCalc.GetHypoTest()\n",
    "print(\"pvalue =\", htr.NullPValue(), \" significance =\", htr.Significance())\n",
    "\n",
    "pvalue_exp = RooStats.AsymptoticCalculator.GetExpectedPValues(htr.NullPValue(), htr.AlternatePValue(), False, True)\n",
    "significance_exp = ROOT.Math.normal_quantile_c(pvalue_exp, 1)\n",
    "print(\"expected p-value = \", pvalue_exp, \" significance =\", significance_exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pkbNVFMZ/WUcB4HAGHZKTYVCIgcC5CHA2Bh1SlO3Qg0oFgDPzFS4V2QYFAE5FR2+icg4KOhUATsKHcLpyDgoAnJDuhLRkHhR0KgAczqBD0jIPCgAcy5e01GU4PbJcPCvvZSnMAhzGJ3CKMgwKjwsrybMAhzDokIFLDD2oVADYn8/bPJyrRyH8U9d113VP71PX9eyfS/cE4CR0J6TrRD0KXdc1TRNCKIqi7/ulUoPb7bbiwXUqAOzJoEM2yvNcKqksy7Ztx+6B2T+nd3uxzS9+66wF2Mfs+9ilPnJfN1IpOlGPQvFzWKGqqti7MPV4y/t0KgDsL69G84pOFBTu9/s0KNxut1k5QvEvKNR1XZZlWZaqEwDORvdtZk4UFEYhhFig8KKecRiGtm37vn8ME+Wyovjffz9vB2ADPlDzc7qhlLqub7fb03GHR13X9X0/3YVfB4dEXYDv8RmrRuG74pf7YRjerEWI3Ql/KlxQqQDwJVJClk4UFMqyjB0Jj6MJo67rHmPBi/sDsA9fvXJ1lgWXxirFWQ6IIaDrurqu42+nYw1N01RV9dfnut//d0K7+gPA5nyu5uQsQymx2mB2Y+xgCCE0TTMMQwwNsYhheofpn7w5OKR/DGBDPlRH+dUopLo/Yw/E7Pb3XyGnNcBWfKKOBIWzExQAdubjdCq/oHCWGoUNLa2LMHvlVCoAfE4NY/YyDAqZRTmA07ryNR2u40TTI/dnTQWArUgJubp0UABgNaUJF3H1oKBTAWAFH5jXcfWgAMBfKU24FEFBpwLAelJC9gQFAP5AacLVZDg98s11FH7+ypoKAL/T7XpBGQYF6ygA7MBn7UUYevgvlQoArxl0uCZBAYDf+QZ1WYLC/+hUAHiH7oRLERQA+IVBhysTFH7QqQAAU4ICAK/oTri4DKdHrlhH4efdrKkA8F/6VskwKGy7joKsAFyWazpQGHp4ypsBYMYH42UJCs+pagQuTmkCkaAAwJwvSIwEhUU6FYBrUprAlKDwLlkBuCApAUHhFe8Q4GqUJjCT4fTID9dRePgryyoAV6HrlEcZBoVt11GYkRWAi/BZR2To4XfeLcAVGHTgqSSDQgih67q6rruu2+cZzYAA8uaTjSXpBYWu65qmCSEURdH3/VJFwld5RwEZ053AVHpBoe/7tm1DCCGEWI6wT7+Cdw6QK4MOvJBeUCiKoq7r8eeqqmLvwg4MQABwNenNephNarjdbm3bHrUxAKnTncBr5VcnE35VCKFpmuJndFhXsvCng+BNBWTDas2bK8uEG9ankhx6KIqiruumaaqqenw97n93yC4AHEtK4B1JBoXYbTAMw27VCVMqFYD8SAksSa9GoSzLPQsYAbJkFJU3JRYUYj6o63oWFKbzIHbgAhBA0vSG8r7Eai66ruv7fnbjtINhtyoSYRxIlNKEr8qvmDG7/dnxFZIVgBT57Pqq/IJCksWMAKwjJfBXidUovGNpKYXNI55KBSAtShNYIcOgcFSfj6wAnJnSBNYx9PAR7zQgCVICqwkKn7L+EpAWKYE/ERQ2JisAZ6OAkU8IChvwxgNOy7cXPiQobMMABHBCShP4nKDwFbICcDgpgU1kOD1yt3UUHh5fPgBOSkpgtQyDwoFrZ1qCCTgJBYxsxdDDF+lgAA7hw4cNCQobk9yBYylNYFuCwvbMgABOQkrgc4ICQD6UJrA5QeErdCoA+/NpwzcICgA5UJrAl2Q4PfKodRQens5USeAYPnDYUIZB4cB1FAAOoTSB7zH08EUqFYAd+HjhqwSF/XgzA5tTmsC3CQrf5U0L7MYHDt8gKHydAQjgS5QmsANBYW+yArAJHybsI8NZDyeZHvnzqX+8pc2WBD6kNIHdZBgUzjk9cpYVAFaTEtiToYf9KFYANicl8G1n7FHouq7ruqXf1nU9++eLO5+ZAQhgBQWM7Ox0PQohhL7vQwhLd7jdbjtuzsZm72r9CsCf+NBgfyfqUQghdF33Tg54ESPOT7ECsI7SBA5xrh6Fuq7btn1xh6QjwkixAvBXUgJHOVFQiNUGrwsOYlCo67osy7IsE61OAPgTKYEDnSgovK+u62EY2rbt+35W21gURfl3+++CTgVgHSmBnZUnXHWgLMthGB4TwKOu6/q+n+5CWZ5xj57yFQF4h2kOaUmoGXpTkj0KoxgmEi1cyOtEAr5CjyOHSywodF33GAve6Xs4JwMQwAv6HTmDNILCmA9CCE3TjLc3TVNV1WGbtTVZARhJCZxEAkEhLsE0/lxV1ViEWFVVouMOI29+4Fc+KDhQqjUX4zzJ2e2JVpEoVgKmfCakK9Fm6IXs9ifNV0gfIzDygZC0RJuhF060hPNWltZFOPMrN1vX2fWi4LKkBM4mw6Bw5kDwgmtAADNpfpiRmwSKGa/DbEm4OKUJnJCgcF6yAlyKtzznJCicy+w7hA8OuAilCZyWoHA6PiDgaqQEzkxQOCPFCnAdUgInJygAHEZK4PwynB6Z4joKj6azJS2rAFmSEkhChkEhrUDwJlkBMiMlkApDD+flgwNyJSWQEEHh1FQ1Qn6kBNIiKKREVoDUSQkkR1A4O0swQTakBFIkKCRAVoAMSAkkSlBIg88USJqUQLoynB6ZxzoKj6ysAImSEkhahkEh9UDwJlkBkiAlkDpDDylRrABJkxJIkaCQGFkBEjJ9h0oJJEpQSI+sAEnw3iQPgkKSZAU4OaUJZENQSJXPHTgtKYGcCAoJcyUIOCEpgcxkOD0y13UUfmXCJBxOSiA/GQaF7APB1HQVpkJWgENJCWTJ0EPyFDbCGUgJ5Cr5oNB13dGbcDwfSXAsKYGMpR0UQgh934cQjt6Q4ylshKNICeQt1aAQQqjrummaozfkpGQF2IeUQPZSDQpFUdR13bbt0VtxIooV4FhSAlkqU58jUJblMAx1XY//TH2PPmRtediNtxuP8muGMpweubSOwgs5vajTCZNmS8L36LTjIjIMCjm1+p+TFeAblCZwHQnXKLBEsQJ8T1lKCVyLoJAnWQG+4fGtJCWQPUEhW7ICbEtK4JoEhZzJCrCVx+EGKYGLSL6YUenia64aBZ9TlMCV6VHIn34F+ISUwMUl36PwaGkdhSv3PehXgHWkBMgwKFw5ELwwywrAX/lo4ZoMPVyIK0zCn1ihGQpB4cpkBXjBGwQiQeFaFDbCO5QmwEhQuBxZAV6wQjPMCApXJCvAU9ZehEeCwkXJCjAjJcBTGU6PtI7CmyyuACPDDbAkw6AgELxPVoBCSoCXDD1cnTEIrkzpIvxKUEBW4KIUJcA7BAWKQlbgeqQEeJOgwH/5lOQ6HocbnP+wRFDgf1wMgitQlAB/IiiwSFYgM0oXYYUMp0daR+ETJkySK0UJsE6GQUEg+JCsQH6kBFjN0ANPPE6CMAxBupQuwicEBZ57/CSVFUiOogT4nKDAIlmBpBlugE0ICrzy2EkrK5AEKQG2IijwO1mBtChKgA0JCrxFeSOpUJQA28pweqR1FL5kNm2yMHOSkzHcAN+QYVAQCL5HVuC0pAT4EkMP/I3yRk5ISoDvOV2PQtd1RVHUdV3X9dM7zG6v6zr+CXuyeiPnoSgBvupEPQohhLIsQwghhKZplpr/2+2273bxnPJGDmc9JdhBeZ4R/bIsq6oKIRRF0XVd3/dPt60sX23z69+yOV2+HMW5xznl1wydqEeh+DfuMP4QQ8PU4y0cy+qNHEJKgN2cJSjEBDCrP1gKCnVdl2VZlqXqhDNQ3sjOrKcEezpLUHhqqf+gruthGNq27fv+seax/Ltv78gVKFlgB4oSYH+nm/Uw9RgCuq4bexHib/u+n90ns8GhhFhlge95mjudXbCDU/co/CpmBYUL56FkgW+QEuBAZwkKT5v8pz0Kj7FgacUFDqFkgQ09HcNSlAB7OktQKIqiqqqmaeLP47JL4z9jPohLLIx/0jRNVVX7biZvkRX4nIgAZ3CiGoW44NJYWjgMw3j7WLQYQohTHuKvxnUXOKHH1RsL3cW8x1gDnMfp1oV4Ok/y/bvlt9JF6sx356+cMyQtv2You/1Z7uPObE8T4nOfN+lIIAP5BYUTDT1sJbNXKAPxBTEMwWsCJZzTiYoZyZuZkyxZmtoAnIGgwH6eZgVx4eJMbYCTExTY1dM2QFa4Jh0JkIQMaxQ4v6eLPRcaictQtAgJERQ4xmOFYyEuXMBS75EXHU7L0ANHeto8GInI0lI9iooEOLkMexSWllIwbfKcdC1kTy8CJC3DoCAQpGgpLngxU6ccAVKXYVAgXYoccyIiQB4EBc7FSEQGRATIiWJGzmipyFGd48m9qFgEEqVHgZN62rVQ6F04KxWLkCtBgVN7ERe0QCchIkDeBAUSoHDhtAw0QPYyDArWUciVuHAqIgJcRIZBQSDI2+MUykJc2JeIAJeSYVAge6/rHAuN1tcoR4ALEhRI1VJcKCSGrb2YleoIQ/YEBdL2Ii4UhiQ+83rVCkcVLkJQIAdjo6WDYRMiAjASFMjKO4lBO7dEPgAeCQrk6dcKBs3eSD4AXsgwKFhHgdGLDgbjEb9eOOOyRwaYyjAoCAQ8emeKRHGNplE+AP4kw6AAS15PkSjy7WZ456qbme0ysJVUg0LXdUVR1HVd1/XBm0JqXhc8Pv1VWo3ony7GndauAfv7v6M34M9CCGVZhhBCCE3TxMQAK9zv//vvtbL88d/ZrNi8N3ccoExuRL8sy6qqQghFUXRd1/f9dBfKMr094lTW5YA9T7rVScU7A3aQXzOU3v6UZTkMwzji8PjP5PaIMztDbjjDNgBvyq8ZSmzoIXYkzOoS4o3wDdPhifff+7OxgA//++qmAryWajHj1CwoLK2j8EJm6Y/veTxTjipZcM4C+8ghKMw6GLT67Gl2un0vNzivgUPkEBTgPDTnQGYSq1GInQezsQZLKQDAlyQWFIqiqKqqaZr487js0oHbAwAZS2/oIS64NFYsDsNw7PYAQMbSCwpFUdzv96fzJFmS37zeTTgsTzksjxyTpxyWi8jtZXbiPuWwPOWwPOWwPHJMnnJYnsrvsCTZo/Da0joKmb1yALCDDIOCQAAAW0lv1gMAsBtBAQBYJCj814orRKz+q/2fbp2d9271H+Z9WPZ/FXZ+Oodlq7865A/3fLpUzrH8CAoAwCJBAQBYJCgAAIsynB5pHQUA2EpuC0gpPwHgWLk1rJntDwCwITUKAMAiQQEAWCQoAACLsgoKXdd1XRdCOHpDziKEUP909BYdr+u6pzfWdX3ZM+fxmMxOm6sdmRBCPCUej8xlT5WlY3LxU6WYHJnHfc/mbMkkKIQQyrIMIYQQmqZ52hhcUAjhdrsdvRUnEkLo+372vi3Lsu/7oiiaprlglno8Jhc/bbqua5omHpC+76cTqS57qiwdk4ufKsXPIzM7K7I6W+5ZKIqiqqr4c9u22ezXh6qqGg/LxQ3DUFVVPOeHYRhvn50ts9/mbemYDMNw5XdQURRt2z7+88qnytIxufipcv95ZKZnSGZnSyY9CsWk+zT+kEFvz+dut1vySXY7dV3Hd+9U3/djY1kURVVVl+qOenpMvHem75qqqsZv0hc/Vcafx2Ny8VMl7v7TpiezsyWHoBBfmFmLePEzeBQHZcqyzGOobLU4tvr0vTo9c+q6vk5X6tIxiedJ+U/SH3Ar3O/36SkxTduXPVWWjsnFT5W6ru+ThYjiMcnybMkhKDx15UZxZhiG2EPYNM3R20Iy2rYdhqFt277vr9YARDFkFwsFsNf09Jg4Veq6LsvydrvFT9r8ZHith0iXe/FzGdH4Dl/6Vg2jaciOHVEXbADiV8Cxj53i2TFxqkThn6Zp7jkudpxtjwKPfOqxwgU/9+OX5mEYvF9G7xyTC54qo3HiaJYHIYegMB0tm914ZXERhektahsfzcJTCGFagnRNs3KWqzWWZVnGs2L2ZrnyqbJ0TC5+qnRdt3QZwtzOlkPnXGwmvgbxZ9MjR8XD1J2kp+hsong2FTDeMv35UmZ7PftkKH5OjctbPAfioPvU/cKnyotjcn1+dI0AAAFbSURBVOVTJZru8tIZksHZkk+DOk0/Sb8kG5pV1lztPfzU4+kxnR94zUP0eEymp82lluJ4nCxaPKzRcrVT5fUxueypEs0OzvSsyOlsyeoy00/nSeKwvOOxW/XinDZLnCozTpUXRyCPsyWroAAAbCuHYkYA4EsEBQBgkaAAACwSFACARYICALBIUAAAFgkKALBSvN5elMGSCU8JCgCwUtM0cUnKYRhut1uWF4XK9jLTAPBVcU3GGA7qup6tmp8NKzMCwErxApJVVY1Xms6PoQcAWOn+7/J7fd+XZZllVtCjAAArTS/7VNf17XbLr1XVowAAa4QQmqaJlQoZ06MAACvFXoTxn8Mw5DdJUlAAgPXGHoX8IkIkKAAAi9QoAACLBAUAYJGgAAAsEhQAgEWCAgCwSFAAABYJCgDAIkEBAFgkKAAAiwQFAGCRoAAALBIUAIBFggIAsEhQAAAW/T851pu+9Yz7eAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create profiled log-likelihood\n",
    "prof = model.createNLL(data).createProfile(ROOT.RooArgSet(ws_onoff.var('s')))\n",
    "# multiply by 2\n",
    "minus2LL = ROOT.RooFormulaVar(\"minus2LL\", \"2 * @0\", ROOT.RooArgList(prof))\n",
    "frame = ws_onoff.var('s').frame(0, 30)\n",
    "minus2LL.plotOn(frame)\n",
    "frame.SetYTitle(\"-2 log#Lambda(s)\")\n",
    "canvas = ROOT.TCanvas()\n",
    "frame.Draw()\n",
    "canvas.Draw()"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.16"
  },
  "latex_envs": {
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 0
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}