{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Machine learning technique for signal-background separation of nuclear interaction vertices in the CMS detector \n", "\n", "Phil Baringer: baringer@ku.edu, Anna Kropivnitskaya (speaker): kropiv@cern.ch \n", "
\n", "University of Kansas\n", "
\n", "_for CMS Collaboration_\n", "\n", "_Code with Toy data is available at_ [Binder](https://mybinder.org/v2/gh/kropiv/MLforNIatPyHEP/master)\n", "\n", "## Abstract:\n", "The CMS inner tracking system is a fully silicon-based high precision detector. Accurate knowledge of the positions of active and inactive elements is important for simulating the detector, planning detector upgrades, and reconstructing charged particle tracks. Nuclear interactions of hadrons with the detector material create secondary vertices whose positions map the material with a sub-millimeter precision in situ, while the detector is collecting data from LHC collisions. \n", "\n", "A neural network (NN) with two hidden layers was used to separate secondary vertices due to combinatorial background from those arising from nuclear interactions with material. The NN was trained and tested on data from proton-proton collisions at a center-of-mass energy of 13 TeV, recorded in 2018 at the LHC. \n", "\n", "NN training is performed using Keras and Matplotlib in a Jupyter notebook. Secondary vertices in the training data are classified as signal or background, based on their geometrical position. Even though the variables used in training show only small differences between background and signal, the NN has impressive separation power. Hadrographies of the CMS inner tracker detector before and after background cleaning are presented." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Table of contents\n", "\n", "* [Introduction](#Intro)\n", "* [CMS detectors](#CMSdet)\n", " * [Pixel detector](#PixelDet)\n", "* [Nuclear interactions](#NIs) \n", " * [Data selection and reconstruction](#Data)\n", " * [Toy Data](#ToyData)\n", " * [Connect/Generate data](#Import-data)\n", "* [Neural network (NN) motivation and strategy](#NNmotivation)\n", "* [Classification strategy for NN](#Classification)\n", " * [Set Signal and Background regions for beam pipe](#SetBP)\n", " * [Set Signal and Background regions for BPIX](#SetBPIX)\n", " * [Set Signal and Background regions for pixel support tube](#SetTube)\n", " * [Set Signal and Background regions for rails, by using x position of NI candidate](#SetRails)\n", " * [Classify NI candidates as Signal, as Background, and as Non-classified regions](#ClassifyEvents)\n", " * [Check classification result](#CheckClassification)\n", " * [Estimate background-signal ratio (B/S) of each signal region](#BkgEstimation) \n", " * [Shuffle Data](#DataShufle)\n", " * [Sort track parameters by $p_T$ decreasing and normalize subleading $p_T$ tracks](#SortPt)\n", " * [Plot variables, injected to NN](#VariablesToNN)\n", " * [Divide data into Train and Test data sets](#DataSplit)\n", " * [Data preparation and classification for the NN](#FinalClassification)\n", "* [Principal component analysis (PCA)](#PCA)\n", "* [Keras mode: NN with 2 hidden layers](#KerasModel)\n", " * [Import libraries](#ImportKeras)\n", " * [Create function for NN model with 2 hidden layers](#NNfunction)\n", " * [Create NN model structure and compile it](#ModelCompile)\n", " * [NN model training](#ModelTraining)\n", " * [Save/Load NN model to/from file](#Save-Load-Model)\n", " * [Monitor performance during training](#MonitorTraining)\n", " * [Model results](#ModelResults)\n", " * [Predict the probability distribution of NN classes for Train and Test sets](#PredictY)\n", " * [The probability distribution for injected vertex to be a signal](#PlotY)\n", " * [NN model optimization with Test set](#YpredOptimization)\n", " * [Plot Train and Test prediction for Signal-Background separation as function of BPIX radius](#PlotPredictedResultsR)\n", " * [Background to Signal (B/S) ratios in Signal regions (S0-S6)](#BSafterClass)\n", " * [Tracker tomography with Test set for Signal-Background separation in x-y plane](#PlotPredictedTomography)\n", "* [Summary](#Summary)\n", "* [Documentation](#Doc)\n", "* [Acknowledgment](#Acknowledgment)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction \n", "[jump to top](#Top)\n", "\n", "In HEP, very often problem of signal-background (noise) separation appears:\n", "* resonant peaks from decay particle,\n", "* physics objects reconstruction/identification, for example, pions, photons, electrons, b(t)-jets… \n", "* nuclear interactions with material (this analysis),\n", "* photon conversions with material,\n", "which are on top of combinatorial background.\n", "\n", "Very often, there is no clean sample of signal to train a neural network (NN), but regions with enhanced contribution of signal could be known (by mass, geometrical, or any phase space cuts).\n", "\n", "Machine learning technique of NN with floating classification could be helpful:\n", "* input classification is done on mixed samples with different fractions of background to signal,\n", "* output classification is optimized for real signal and combinatorial background separation.\n", "\n", "This analysis is performed with [Jupyter notebook](http://ebooks.iospress.nl/publication/42900) \n", "at [SWAN](https://www.sciencedirect.com/science/article/abs/pii/S0167739X16307105?via%3Dihub) platform:\n", "https://github.com/kropiv/MLforNIatPyHEP and [Binder](https://mybinder.org/v2/gh/kropiv/MLforNIatPyHEP/master)\n", "and is based on the CMS public results, [public twiki](https://twiki.cern.ch/twiki/bin/view/CMSPublic/TrackerMaterialNIwithML2018).\n", "\n", "# CMS detectors \n", "[jump to top](#Top)\n", "\n", "

\n", " \n", " $\\bf{Fig. 1}$: CMS detectors.\n", "

\n", "\n", "CMS detectors are designed to study different particle properties, created during p-p collisions, with high performance and resolutions: \n", "\n", "* muon system detects and measures muons, \n", "* central tracking system gives accurate momentum measurements, as well as the position of primary and secondary vertices\n", "* an electromagnetic calorimeter detects and measures electrons and photons,\n", "* hadron calorimeter detects and measures hadrons. \n", "\n", "In this analysis, material of [the pixel detector](#PixelDet) (part of the tracking system) is studied with [nuclear interactions](#NIs).\n", "\n", "\n", "## Pixel detector \n", "\n", "Inner tracker system consists of Pixel and Strip detectors, \n", "which reconstruct charged particles momentum with high precision.\n", "\n", "

\n", " \n", " $\\bf{Fig. 2}$: Pixel detector. \n", "

\n", "\n", "Pixel detector consists of Barrel pixel (BPIX) and Forward pixel detectors.\n", "Data from barrel region only are analyzed in this analysis. \n", "\n", "[jump to top](#Top)\n", "\n", "\n", "# Nuclear interactions \n", "\n", "* Nuclear interactions (NIs) are interactions of hadrons with the detector material, which create secondary vertices. \n", "* For Physics analysis, the NIs play the role of background (noise) in the data. \n", "* Due to its interaction with material of the detector, the positions of these secondary vertices map the material with a sub-millimeter precision. Accurate knowledge of the positions of active and inactive elements is important for simulating the detector, planning detector upgrades, and reconstructing charged particle tracks.\n", "\n", "

\n", " \n", " $\\bf{Fig. 3}$: Nuclear interaction schematic view. \n", "

\n", "\n", "Example, of material mapping with NIs for BPIX detector is presented at Fig. 4, taken from [CERN-CMS-DP-2019-001](http://cds.cern.ch/record/2664786?ln=en). \n", "\n", "NI candidates reproduce inner tracker hadrography, but a big combinatorial background from random vertices is observed near the beam pipe, 1st, 2nd and 3rd layers of the barrel pixel (BPIX) detector.\n", "\n", "

\n", " \n", " $\\bf{Fig. 4}$: Hadrography of the tracking system in the x-y plane in the barrel region ($|z| < 25$ cm). The density of NI vertices reproduces structure of the BPIX detector. \n", "

\n", "\n", "[jump to top](#Top)\n", "\n", "\n", "## Data selection and reconstruction\n", "\n", "* p-p collisions at 13 TeV from the single muon collection:\n", " * Study with part of 2018 promptly reconstructed data (4.3 fb-1)\n", "* The nuclear interaction (NI) reconstruction technique is presented at:\n", " * [DOI:10.1088/1748-0221/13/10/P10034](http://dx.doi.org/10.1088/1748-0221/13/10/P10034)\n", " * [CERN-CMS-DP-2019-001](http://cds.cern.ch/record/2664786?ln=en)\n", "\n", "* NI is a displaced vertex with following requirements:\n", " * at least 3 tracks incoming or outgoing from the vertex;\n", " * invariant mass of the outgoing system > 1 GeV to suppress light mesons, baryons, and photon conversions.\n", "\n", "Only NI vertex candidates (NI candidates) from barrel region of the tracker detector (BPIX, |z| < 25 cm) are analyzed: around 1.5×106 NI candidates.\n", "\n", "[jump to top](#Top)\n", "\n", "## Toy Data\n", "\n", "There is no public CMS data sample for this notebook, so a Toy sample was generated in the next section:\n", "\n", "* Background radius distribution was simulated with a non-central chi-squared shape.\n", "* Signal radius distributions were simulated with Gaussian (normal) functions, except the rails simulation, which used a box-shape.\n", "* Input variables for neural network:\n", " * were randomly generated using Gaussian distributions (mean, $\\sigma$) with sigma taken from real data;\n", " * mean value for signal and background was slightly scaled according to the radius of the NI candidate: mean*(1+Radius/50);\n", " * mean value of the background was randomly varied between $\\pm(0.4\\sigma:0.5\\sigma)$ about the mean value of the signal.\n", "\n", "Results with CMS data are available in the notebook as an output, but, during presentation, Toy data will be used to show the notebook functionality.\n", "\n", "[jump to top](#Top)\n", "\n", "\n", "## Connect/Generate data " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:shape of data = (1397381, 27)\n" ] } ], "source": [ "# DataType = \"CMS\"\n", "DataType = \"Toy\" # for PyHEP only Toy could be used\n", "#import matplotlib and numpy\n", "import matplotlib\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from matplotlib.colors import LogNorm\n", "\n", "import logging, sys\n", "from importlib import reload\n", "reload(logging) # you need it if want switch logging level\n", "\n", "\n", "#logging.basicConfig(stream=sys.stdout, level=logging.INFO) # it could make settings for all logger, what we don't want\n", "logging.basicConfig(stream=sys.stdout) # it could make settings for all logger, what we don't want\n", "#logging.disable(sys.maxsize) # desiable logging\n", "\n", "logger = logging.getLogger('log')\n", "# logger.setLevel(level=logging.DEBUG)\n", "logger.setLevel(level=logging.INFO)\n", "\n", "plt.rc('axes', labelsize = 15)\n", "plt.rc('axes', titlesize= 17)\n", "plt.rc('font', size=12) \n", "plt.rc('legend', fontsize=15)\n", "\n", "# set CMS label at each plot:\n", "if DataType == \"Toy\":\n", " labelData = \"Toy Data\"\n", " CMSlabel = \"Generator\"\n", " CMSlumi = \" \"\n", "else:\n", " labelData = 'Data 2018, |z| < 25 cm'\n", " CMSlabel = \"Preliminary\"\n", " CMSlumi = \" 4.3 fb$^{-1}$ (13 TeV) \"\n", "# CMSlabel = \"internal\"\n", "def SetCMSlabel(px, label = CMSlabel, size = 17, label_lumi = CMSlumi):\n", " if DataType == \"Toy\":\n", " TitleCMS = r\"$\\bf{Toy}$\"+\" \"+r\"$\\it{\"+label+\"}$\"\n", " else:\n", " TitleCMS = r\"$\\bf{CMS}$\"+\" \"+r\"$\\it{\"+label+\"}$\"\n", " text = px.text(0.,1.,TitleCMS, size = size, transform=px.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", " text2 = px.text(1.,1.,label_lumi, size = size, transform=px.transAxes,\n", " verticalalignment='bottom', horizontalalignment='right')\n", " return text, text2\n", "\n", "def CalcRad(xpos, ypos):\n", " Rad = np.sqrt(np.square(xpos)+np.square(ypos))\n", " Rad_BP = np.sqrt(np.square(xpos-0.171)+np.square(ypos+0.176))\n", " Rad_BPIX = np.sqrt(np.square(xpos-0.086)+np.square(ypos+0.102))\n", " Rad_Tube = np.sqrt(np.square(xpos+0.080)+np.square(ypos+0.318))\n", " return Rad, Rad_BP, Rad_BPIX, Rad_Tube\n", "\n", "def gaussian(x, mu, sig):\n", " return np.exp(-np.power(x - mu, 2.) / (2 * np.power(sig, 2.)))\n", "\n", "# connect data\n", "if DataType == \"Toy\":\n", " \n", " np.random.seed(10) # to fix random generator\n", " scale = 1 # (should be int) scale amount of your Toy Data\n", " Diff_SB = 0.5 # variation of background mean by \\pm Diff_SB*sigma \n", " Diff_SB_min = 0.4\n", "\n", " def StructureGen(pos, lw, lw_corr, ngen, x0, y0):\n", " lenth = np.size(ngen)\n", " for i in range(0,lenth):\n", " r_gen = np.random.normal(loc=pos[i], scale=lw[i]/lw_corr[i], size=ngen[i])\n", " phi_gen = np.random.uniform(low=-np.pi, high=np.pi, size=ngen[i])\n", " x_gen = np.multiply(r_gen, np.cos(phi_gen)) + x0\n", " y_gen = np.multiply(r_gen, np.sin(phi_gen)) + y0\n", " z_gen = np.random.uniform(low=-25., high=25., size=ngen[i])\n", " if i == 0:\n", " x_str, y_str, z_str = x_gen, y_gen, z_gen\n", " else:\n", " x_str = np.concatenate(([x_str,x_gen]),axis=0)\n", " y_str = np.concatenate(([y_str,y_gen]),axis=0)\n", " z_str = np.concatenate(([z_str,z_gen]),axis=0)\n", " return x_str, y_str, z_str\n", "\n", " def varGen(varName, varMean, varSigma, Rad):\n", " var_lenth = np.size(varName)\n", " logger.debug(\"var_lenth size = \" + str(np.size(varName)))\n", " sample_size = np.size(Rad)\n", " for i in range(0,var_lenth):\n", " varM = varMean[i]*(1. + Rad/50.) # small scale: with Raduis variable are changes slightly Rad between 0 and 25\n", " varS = varSigma[i]*(1. + Rad/50.)\n", " # print(\"varM shape = \" + str(varM.shape))\n", " var_gen = np.random.normal(loc=varM, scale=varS, size=sample_size)\n", " if i == 0:\n", " var_tot = var_gen\n", " else:\n", " var_tot = np.c_[var_tot,var_gen]\n", "\n", " return var_tot\n", "\n", " # generate background:\n", " # https://en.wikipedia.org/wiki/Noncentral_chi-squared_distribution\n", " n_bkg = 400000*scale\n", " r_bkg = np.random.noncentral_chisquare(df=3, nonc=2, size=n_bkg)\n", " r_bkg = r_bkg + 1.\n", " phi_bkg = np.random.uniform(low=-np.pi, high=np.pi, size=n_bkg)\n", " x_bkg = np.multiply(r_bkg, np.cos(phi_bkg))\n", " y_bkg = np.multiply(r_bkg, np.sin(phi_bkg))\n", " z_bkg = np.random.uniform(low=-25., high=25., size=n_bkg)\n", "\n", " # beam pipe position and Radius is taken from CMS-DP-2019-001 (http://cds.cern.ch/record/2664786?ln=en)\n", " # generate beam pipe (BP):\n", " n_BP = [30000*scale]\n", " # in R_BP centered at BP\n", " xSignal_BP = [2.21]\n", " lw_Signal_BP = [0.1]\n", " lw_corr_BP = [3.5]\n", " x0_BP, y0_BP = 0.171, -0.176\n", " x_BP, y_BP, z_BP = StructureGen(xSignal_BP, lw_Signal_BP, lw_corr_BP, n_BP, x0_BP, y0_BP)\n", "\n", "\n", " # BPIX position is taken from Figure. 4.1 at CMS-TDR-11 (https://cds.cern.ch/record/1481838?ln=en)\n", " # generate BPIX: \n", " # Inner Shield L1_1 L1_2 L2_1 L2_2 L3_1 L3_2 L4_1 L4_2 Outer Shield \n", " xSignal_BPIX = [2.49, 2.8, 3.10, 6.65, 6.98, 10.80, 11.10, 15.84, 16.13, 18.65]\n", " lw_Signal_BPIX = [0.055, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]\n", " lw_corr_BPIX = [2., 3., 6., 3., 6., 3., 3., 3., 3., 3.]\n", " n_BPIX = [2000, 10000, 5000, 8000, 3500, 4000, 4000, 3000, 3000, 1000]\n", " logger.debug(\"n_BPIX befor = \" +str(n_BPIX ))\n", " n_BPIX = np.multiply(n_BPIX,scale)\n", " logger.debug(\"n_BPIX after = \" +str(n_BPIX ))\n", "\n", " x0_BPIX, y0_BPIX = 0.086, -0.102\n", " x_BPIX, y_BPIX, z_BPIX = StructureGen(xSignal_BPIX, lw_Signal_BPIX, lw_corr_BPIX, n_BPIX, x0_BPIX, y0_BPIX)\n", "\n", " #tube position and Radius is taken from CMS-DP-2019-001 (http://cds.cern.ch/record/2664786?ln=en)\n", " # generate Tube:\n", " xSignal_Tube = [21.75] # avarige of Rx and Ry\n", " lw_Signal_Tube = [0.4]\n", " lw_corr_Tube = [3.5]\n", " n_Tube = [10000*scale]\n", " x0_Tube, y0_Tube = -0.080, -0.318\n", " x_Tube, y_Tube, z_Tube = StructureGen(xSignal_Tube, lw_Signal_Tube, lw_corr_Tube, n_Tube, x0_Tube, y0_Tube)\n", "\n", " #Rails position and Radius is taken from CMS-DP-2019-001 (http://cds.cern.ch/record/2664786?ln=en)\n", " # generate Rails:\n", " n_Rails = 1000*scale\n", " ySignal_TopRail = 19.08\n", " ySignal_BotRail = -19.73\n", " lw_yRail = 1.\n", " xmin, xmax = -5, 5\n", " x_TopRail = np.random.uniform(low=xmin, high=xmax, size=n_Rails)\n", " y_TopRail = np.random.uniform(low=ySignal_TopRail, high=(ySignal_TopRail+lw_yRail), size=n_Rails)\n", " z_TopRail = np.random.uniform(low=-25., high=25., size=n_Rails)\n", " x_BotRail = np.random.uniform(low=xmin, high=xmax, size=n_Rails)\n", " y_BotRail = np.random.uniform(low=(ySignal_BotRail-lw_yRail), high=ySignal_BotRail, size=n_Rails)\n", " z_BotRail = np.random.uniform(low=-25., high=25., size=n_Rails)\n", "\n", " x_sig = np.concatenate(([x_BP,x_BPIX,x_Tube,x_TopRail,x_BotRail]),axis=0)\n", " y_sig = np.concatenate(([y_BP,y_BPIX,y_Tube,y_TopRail,y_BotRail]),axis=0)\n", " z_sig = np.concatenate(([z_BP,z_BPIX,z_Tube,z_TopRail,z_BotRail]),axis=0)\n", " x = np.concatenate(([x_bkg,x_sig]),axis=0)\n", " y = np.concatenate(([y_bkg,y_sig]),axis=0)\n", " z = np.concatenate(([z_bkg,z_sig]),axis=0)\n", "\n", " logger.debug(\"x shape = \" +str(x.shape))\n", " logger.debug(\"y shape = \" +str(y.shape))\n", " logger.debug(\"z shape = \" +str(z.shape))\n", "\n", " lenth_sig = np.size(x_sig)\n", " lenth_bkg = np.size(x_bkg)\n", " \n", " # create 23 input variables with gaussian, the same sigma for S and B, but with some shift in mean for S and B \n", " var_Name = np.asarray([\"ver\", \"NI\", \"pT1\",\"pT2\", \"pT3\", \"eta1\", \"eta2\", \"eta3\", \"phi1\", \"phi2\", \"phi3\", \n", " \"chi2_1\", \"chi2_2\", \"chi2_3\", \"normchi2_1\", \"normchi2_2\",\"normchi2_3\",\n", " \"hits1\",\"hits2\", \"hits3\", \"algo1\", \"algo2\", \"algo3\"])\n", " # print(\"var_Name shape = \" + str(var_Name.shape))\n", " var_Mean_Sig = np.asarray([20., 1.1, 1.5, 1., 0.5, 0., 0., 0., 0., 0., 0.,\n", " 20., 15., 12., 1.2, 1., 0.8,\n", " 20., 15., 10., 10., 9., 8.])\n", " var_Sigma = np.asarray([10., 0.3, 0.3, 0.3, 0.3, 1., 1., 1., np.pi, np.pi, np.pi,\n", " 10., 8., 5., 0.5, 0.4, 0.3,\n", " 5., 4., 3., 5., 4., 3.])\n", " # variation of background mean by \\pm (Diff_SB_min, Diff_SB)*sigma\n", " fracRandom = np.random.uniform(low=Diff_SB_min, high=Diff_SB, size=var_Sigma.size)\n", " IntRandom = np.random.randint(2, size=var_Sigma.size) #genrate 0 or 1\n", " fracRandom[IntRandom==0] = -fracRandom[IntRandom==0]\n", " var_Mean_Bkg = var_Mean_Sig-np.multiply(fracRandom,var_Sigma)\n", " logger.info(\"Background mean value shift in $\\sigma$ = \" + str(fracRandom))\n", "\n", " # generate signal input variables:\n", " Radius = CalcRad(x_sig,y_sig)[0]\n", " var_Signal = varGen(var_Name, var_Mean_Sig, var_Sigma, np.asarray(Radius))\n", "\n", " # generate background input variables:\n", " Radius = CalcRad(x_bkg,y_bkg)[0]\n", " var_Bkg = varGen(var_Name, var_Mean_Bkg, var_Sigma, np.asarray(Radius))\n", "\n", " logger.debug(\"var_Signal shape = \" + str(var_Signal.shape))\n", " logger.debug(\"var_Bkg shape = \" + str(var_Bkg.shape))\n", "\n", " # merge Signal and Background\n", " var = np.r_[var_Bkg,var_Signal]\n", " logger.debug(\"var shape = \" + str(var.shape))\n", "\n", " # merge var and positions 1st bkg, after signal\n", " num = np.asarray(range(0,np.size(x)))\n", " data = np.c_[num,np.asarray(x),np.asarray(y),np.asarray(z),var]\n", " print(\"Toy data.shape = \" + str(data.shape))\n", "\n", "else:\n", " data = np.genfromtxt(\"/eos/user/k/kropiv/root-files/NI/NN_X_2018D_barrel.csv\", delimiter=',')\n", "logger.info(\"shape of data = \" + str(data.shape))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Display generated Toy data:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "if DataType == \"Toy\":\n", " # using the variable ax for single a Axes\n", " fig, (ax,bx) = plt.subplots(1,2, figsize=(17,7))\n", "# fig, ax = plt.subplots(figsize=(15,7))\n", " nb = 200\n", "\n", " Rad = CalcRad(x, y)[2] # 2nd element centered at BPIX\n", " cut = 23.\n", " Xmax = 25.\n", " xcut = x[Rad < cut]\n", " ycut = y[Rad < cut]\n", " # to add color pallete to figure: cmap = 'viridis' (default), 'jet' \n", " counts, xedges, yedges, im = ax.hist2d(xcut, ycut, bins=nb, range = [[-Xmax, Xmax], [-Xmax, Xmax]], norm=LogNorm(),\n", " cmap = 'viridis')\n", " ax.set_xlabel('x (cm)')\n", " ax.set_ylabel('y (cm)')\n", " SetCMSlabel(ax) \n", " ax_cbar = plt.colorbar(im, ax=ax)\n", " \n", " x_values = np.linspace(-1.5, 2, 100)\n", " for mu, sig in [(0, 0.5), (Diff_SB*0.5, 0.5)]:\n", " bx.plot(x_values, gaussian(x_values, mu, sig))\n", " bx.text(0.05, 0.9, \"Gaussian\",\n", " verticalalignment='bottom', horizontalalignment='left',\n", " transform=bx.transAxes, color='black', fontsize=15)\n", " bx.legend(['mean = 0', 'mean = 0.5$\\sigma$'],loc=\"upper right\",framealpha=1.)\n", " \n", " fig.tight_layout()\n", " plt.savefig('Results/Toy_Generator.pdf')\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Neural network (NN) motivation and strategy \n", "\n", "For each NI candidate, monitoring variables are available, which are very similar for real NIs (signal) and combinatorial background (background).\n", "\n", "* Machine learning technique could be helpful for signal-background separation.\n", "* A NN with 2 hidden layer (with 12 neurons in each hidden layer) is selected:\n", " \n", "* For simplicity, only vertices for a NI candidate with exactly 3 tracks are used:\n", " 1.4×106 (=3 tracks, majority of the vertices) from 1.5×106 (≥ 3 tracks) vertices.\n", "\n", "* 23 variables are injected to the input layer of NN (23 input variables for NN):\n", " * number of primary vertices; \n", " * number of NI candidates per one event; \n", " * 3 tracks for each NI vertex candidate:\n", " * $p_T$, $\\eta$, and $\\phi$;\n", " * $\\chi^2$, and normalized $\\chi^2$;\n", " * number of valid hits;\n", " * track reconstruction algorithm.\n", "\n", "* The vertex position (x, y, and z) is used for classification of NI candidates.\n", " * N.B.: It is not injected as input variable for NN.\n", "\n", "[jump to top](#Top)\n", "\n", "# Classification strategy for NN \n", "\n", "Classification for signal and background regions is done by using radius of the NI candidate, r, where\n", "$r = \\sqrt{(x-x_0)^2 + (y-y_0)^2}$:\n", "* $(x,y)$ is the vertex position of the NI candidate;\n", "* $(x_0,y_0)$ is the central position of material structures in CMS coordinates, which are installed with millimeter precision, and is taken from [CERN-CMS-DP-2019-001](http://cds.cern.ch/record/2664786?ln=en).\n", "\n", "Classification is done for 7 signal regions (S0-S6) and for 5 background regions (B7-B11), defined in sections below.\n", "\n", "| Material structure | Radius definition | Material center position |\n", "| --- | --- | --- |\n", "| beam pipe (BP) | r, centered at BP | (1.71, -1.76) mm |\n", "| BPIX  inner/outer shields, layers 1-4 | r, centered at BPIX | (0.86, -1.02) mm |\n", "| BPIX rails and pixel support tube | r, centered at tube | (0.80,  3.18) mm |\n", "\n", "\n", "[jump to top](#Top)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Set Signal and Background regions for beam pipe \n", "\n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def makeBand(xStart, xWidth, px, bandColor):\n", " transperance = 0.3\n", " for p, lw in zip(xStart,xWidth):\n", " #plt.axvline(p, color=bandColor, alpha = transperance)\n", " lab = \"\"\n", " if bandColor == \"green\" and p == xStart[0]:\n", " lab = \"Background region\"\n", " elif bandColor ==\"red\" and p == xStart[0]:\n", " lab = \"Signal region\"\n", " px.axvspan(p, p+lw, alpha = transperance, color=bandColor, label = lab)\n", "\n", "def makeSBtext(xPos,yPos, px, text, textColor, fontS = 15):\n", " for i_xPos, i_text in zip(xPos,text):\n", " px.text(i_xPos, yPos, i_text,\n", " verticalalignment='bottom', horizontalalignment='left',\n", " transform=px.transAxes, color=textColor, fontsize=fontS)\n", "\n", "# the histogram of the data\n", "Radius, Radius_BP, Radius_BPIX, Radius_Tube = CalcRad(data[:,1], data[:,2])\n", "\n", "# using the variable ax for single a Axes\n", "fig, ax = plt.subplots(figsize=(15,7))\n", "#num_bins = 180\n", "num_bins = 750\n", "\n", "#correction to beam pipe\n", "Rmin, Rmax = 1.5, 3.\n", "n, bins, patches = ax.hist(Radius_BP[np.logical_and(Radius_BP >Rmin, Radius_BP \n", "\n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# using the variable ax for single a Axes\n", "fig, ax = plt.subplots(figsize=(15,7))\n", "num_bins = 2100\n", "\n", "#correction to BPIX\n", "\n", "Rmin, Rmax = 2.34, 23.\n", "if DataType == \"Toy\":\n", " Rmin = 2.33\n", "n, bins, patches = ax.hist(Radius_BPIX[np.logical_and(Radius_BPIX >Rmin, Radius_BPIX \n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# using the variable ax for single a Axes\n", "fig, ax = plt.subplots(figsize=(15,7))\n", "num_bins = 350\n", "\n", "#correction to pixel support tube\n", "Rmin, Rmax = 18., 25.\n", "n, bins, patches = ax.hist(Radius_Tube[np.logical_and(Radius_Tube > Rmin, Radius_Tube < Rmax)], num_bins,\n", " range = [Rmin, Rmax],label=labelData)\n", "ax.set_ylim(0., 1.15 * np.max(n))\n", "# Tube \n", "xSignal_Tube = [21.55]\n", "lw_Signal_Tube = [0.4]\n", "makeBand(xSignal_Tube, lw_Signal_Tube, ax, \"red\")\n", "\n", "# OS-Tube Rails-Tube Tube-TIB1\n", "xBkg_Tube = [19., 21., 22.1]\n", "lw_Bkg_Tube = [0.3, 0.45, 1.2]\n", "makeBand(xBkg_Tube, lw_Bkg_Tube, ax, \"green\")\n", "\n", "\n", "#plt.xscale('log')\n", "#plt.yscale('log')\n", "\n", "yBkgPos = 0.9\n", "#background L4-TIB1\n", "xBkgPos = [0.18, 0.45, 0.64]\n", "textPos = [\"B11\", \"B11\", \"B11\"]\n", "#plot backgrounds' titles:\n", "makeSBtext(xBkgPos, yBkgPos, ax, textPos, \"darkgreen\")\n", "\n", "ySPos = 0.9\n", "#Signal BPIX support tube\n", "xSPos = [0.52]\n", "textPos = [\"S6\"]\n", "makeSBtext(xSPos, ySPos, ax, textPos, \"darkred\")\n", "\n", "Xtitle = \"r at pixel support tube center\"\n", "ax.set_xlabel(Xtitle+' (cm)')\n", "ax.set_ylabel('Entries/(%1.1f mm)'%(10*(bins[1]-bins[0]))) \n", "\n", "SetCMSlabel(ax)\n", "ax.legend(loc=\"upper right\",framealpha=1.)\n", "\n", "a=ax.get_xticks().tolist()\n", "a_pos = ax.xaxis.get_ticklocs().tolist()\n", "logger.debug (\"a_pos = \" +str(a_pos))\n", "a = np.round(a,2)\n", "a = [\"%.0f\" % number for number in a]\n", "a[5]='support tube'\n", "a_pos[5] = 21.75\n", "del a[-1]\n", "del a_pos[-1]\n", "del a[0]\n", "del a_pos[0]\n", "# ax.set_xticklabels(a,rotation=0)\n", "plt.xticks(a_pos, a)\n", "\n", "if DataType == \"Toy\":\n", " plt.savefig('Results/Toy_R_atTube.pdf')\n", "else:\n", " plt.savefig('Results/R_atTube.pdf')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Classification for signal, S6 (red) and background, B11 (green) regions is done. \n", "* Background-signal ratio (B/S) for the support tube is estimated from sidebands to be around 0.06 (S6).\n", "\n", "## Set Signal and Background regions for rails, by using x position of NI candidate \n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# using the variable ax for single a Axes\n", "fig, (ax,bx) = plt.subplots(2,1, figsize=(15,14))\n", "num_bins = 350\n", "\n", "#correction to pixel support tube\n", "Rmin, Rmax = 18., 25.\n", "n, bins, patches = ax.hist(Radius_Tube[np.logical_and(np.logical_and(Radius_Tube >Rmin, Radius_Tube -5, data[:,1]<5))], num_bins,\n", " range = [Rmin, Rmax],label=labelData)\n", "n_b, bins_b, patches_b = bx.hist(Radius_Tube[np.logical_and(np.logical_and(Radius_Tube >Rmin, Radius_Tube 10))], num_bins,\n", " range = [Rmin, Rmax],label=labelData)\n", "Xtitle = \"r at pixel support tube center\"\n", "\n", "# Rails \n", "xSignal_Rails = [19.4]\n", "lw_Signal_Rails = [1.5]\n", "makeBand(xSignal_Rails, lw_Signal_Rails, ax, \"red\")\n", "\n", "# the same background as for pixel support tube:\n", "makeBand(xBkg_Tube, lw_Bkg_Tube, ax, \"green\")\n", "\n", "# noRails region: |PFDV_X| > 10 cm, PFDV_X = data[:,1]\n", "xBkg_noRails = [19.1]\n", "lw_Bkg_noRails = [2.3]\n", "makeBand(xBkg_noRails, lw_Bkg_noRails, bx, \"green\")\n", "\n", "yBkgPos = 0.9\n", "#background L4-TIB1\n", "xBkgPos = [0.18, 0.45, 0.64]\n", "textPos = [\"B11\", \"B11\", \"B11\"]\n", "#plot backgrounds' titles:\n", "makeSBtext(xBkgPos, yBkgPos, ax, textPos, \"darkgreen\")\n", "\n", "ySPos = 0.9\n", "#Signal BPIX rails\n", "xSPos = [0.3]\n", "textPos = [\"S6\"]\n", "makeSBtext(xSPos, ySPos, ax, textPos, \"darkred\")\n", "\n", "yBkgPos = 0.9\n", "#background L4-TIB1\n", "xBkgPos = [0.32]\n", "textPos = [\"B11\"]\n", "#plot backgrounds' titles:\n", "makeSBtext(xBkgPos, yBkgPos, bx, textPos, \"darkgreen\")\n", "\n", "Xtitle = \"r at pixel support tube center\"\n", "ax.set_xlabel(Xtitle+' (cm)')\n", "ax.set_ylabel('Entries/(%1.1f mm)'%(10*(bins[1]-bins[0]))) \n", "bx.set_xlabel(Xtitle+' (cm)')\n", "bx.set_ylabel('Entries/(%1.1f mm)'%(10*(bins[1]-bins[0])))\n", "\n", "SetCMSlabel(ax)\n", "SetCMSlabel(bx)\n", "ax.legend(loc=\"upper right\",framealpha=1.)\n", "bx.legend(loc=\"upper right\",framealpha=1.)\n", "ax.text(0.25,0.7,\"rails enhanced:\\n |x| < 5 cm\", size = 17, transform=ax.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "bx.text(0.25,0.7,\"rails suppressed:\\n |x| > 10 cm\", size = 17, transform=bx.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "\n", "a=ax.get_xticks().tolist()\n", "a = np.round(a,2)\n", "a = [\"%.0f\" % number for number in a]\n", "a[3]='rails'\n", "logger.debug(\"a = \" +str(a))\n", "ax.set_xticklabels(a,rotation=0)\n", "#ax.set_xticks(a_pos, a)\n", "\n", "if DataType == \"Toy\":\n", " plt.savefig('Results/Toy_R_atTube_forRails.pdf')\n", "else:\n", " plt.savefig('Results/R_atTube_forRails.pdf')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Top plot corresponds to the enhanced region for the BPIX detector rails (|𝑥| < 5 cm, where 𝑥 is the 𝑥 coordinate of the vertex), while bottom plot corresponds to the suppressed region for the rails (|𝑥| > 10 cm).\n", "* Classification for signal, S6 (red), and background, B11 (green) regions is done. Background-signal ratio (B/S) for the BPIX detector rails is estimated from sidebands to be around 0.13 (S6).\n", "\n", "## Classify NI candidates as Signal, as Background, and as Non-classified regions \n", "[jump to top](#Top)\n", "\n", "Pre-classification for NN is done:\n", "* 0-6 for signal regions,\n", "* 7-11 for background regions,\n", "* -1 for non-classified regions." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:data shape = (1397381, 27)\n", "INFO:log:shape of Y = (1397381,)\n" ] } ], "source": [ "def SetYval(xStart, xWidth, Yval, Rad): \n", " for p, lw, yVal in zip(xStart, xWidth, Yval):\n", " logicVal = np.logical_and(Rad > p, Rad < (p+lw))\n", " Y[logicVal] = yVal\n", "\n", "def SetYvalRails(xStart, xWidth, Yval, Rad):\n", " for p, lw, yVal in zip(xStart, xWidth, Yval):\n", " logicVal = np.logical_and(np.logical_and(Rad > p, Rad < (p+lw)),\n", " np.logical_and(data[:,1] > -5, data[:,1] < 5))\n", " # assinge yVal only if logicVal\n", " Y[logicVal] = yVal \n", "def SetYvalnoRails(xStart, xWidth, Yval, Rad):\n", " for p, lw, yVal in zip(xStart, xWidth, Yval):\n", " logicVal = np.logical_and(np.logical_and(Rad > p, Rad < (p+lw)),\n", " np.logical_or(data[:,1] < -10, data[:,1] > 10))\n", " # assinge yVal only if logicVal\n", " Y[logicVal] = yVal \n", " \n", "logger.info (\"data shape = \"+str(data.shape))\n", "Y = np.zeros((data.shape[0])) - 1\n", "logger.info (\"shape of Y = \" +str(Y.shape))\n", "\n", "#Define values for Y: 0-6 - Signal, 7-11 - Background:\n", "\n", "# Inner Shield L1_1 L1_2 L2_1 L2_2 L3_1 L3_2 L4_1_2 Outer Shield \n", "Y_Signal_BPIX = [1, 2, 2, 3, 3, 4, 4, 5, 6]\n", "logger.debug(\"Signal BPIX = \" + str(xSignal_BPIX))\n", "logger.debug(\"Signal width BPIX = \" + str(lw_Signal_BPIX))\n", "# BP-S S-L1 L1-L2 L2-L3 L3-L4 L4-OS OS-Rails\n", "Y_Bkg_BPIX = [7, 7, 8, 9, 10, 11, 11]\n", "logger.debug(\"Bkg BPIX = \" + str(xBkg_BPIX))\n", "logger.debug(\"BKg width BPIX = \" + str(lw_Bkg_BPIX))\n", "\n", "Y_Signal_BP = [0]\n", "logger.debug(\"Signal BP = \" + str(xSignal_BP))\n", "logger.debug(\"Signal width BP = \" + str(lw_Signal_BP))\n", "Y_Bkg_BP = [7]\n", "logger.debug(\"Bkg BP = \" + str(xBkg_BP))\n", "logger.debug(\"Bkg width BP = \" + str(lw_Bkg_BP))\n", "\n", "# Tube\n", "Y_Signal_Tube = [6]\n", "logger.debug(\"Signal Tube = \" + str(xSignal_Tube))\n", "logger.debug(\"Signal width Tube = \" + str(lw_Signal_Tube))\n", "# OS-Tube Rails-Tube Tube-TIB1\n", "Y_Bkg_Tube = [11, 11, 11]\n", "logger.debug(\"Bkg Tube = \" + str(xBkg_Tube))\n", "logger.debug(\"Bkg width Tube = \" + str(lw_Bkg_Tube))\n", "\n", "# Special case for Rails with cut on PFDV_X\n", "# Rails region: |PFDV_X| < 5 cm, PFDV_X = data[:,1]\n", "# the same background as for Tube\n", "Y_Signal_Rails = [6]\n", "logger.debug(\"Signal Rails = \" + str(xSignal_Rails))\n", "logger.debug(\"Signal width Rails = \" + str(lw_Signal_Rails))\n", "# noRails region: |PFDV_X| > 10 cm, PFDV_X = data[:,1]\n", "# OS-Tube\n", "Y_Bkg_noRails = [11]\n", "logger.debug(\"Bkg noRails = \" + str(xBkg_noRails))\n", "logger.debug(\"Bkg width noRails = \" + str(lw_Bkg_noRails))\n", "\n", "# Set up values for Y: start with Singnal, finish with Background\n", "\n", "SetYval(xSignal_BPIX, lw_Signal_BPIX, Y_Signal_BPIX, Radius_BPIX)\n", "SetYval(xBkg_BPIX, lw_Bkg_BPIX, Y_Bkg_BPIX, Radius_BPIX)\n", "SetYval(xSignal_BP, lw_Signal_BP, Y_Signal_BP, Radius_BP)\n", "SetYval(xBkg_BP, lw_Bkg_BP, Y_Bkg_BP, Radius_BP)\n", "SetYval(xSignal_Tube, lw_Signal_Tube, Y_Signal_Tube, Radius_Tube)\n", "SetYval(xBkg_Tube, lw_Bkg_Tube, Y_Bkg_Tube, Radius_Tube)\n", "SetYvalRails(xSignal_Rails, lw_Signal_Rails, Y_Signal_Rails, Radius_Tube)\n", "SetYvalnoRails(xBkg_noRails, lw_Bkg_noRails, Y_Bkg_noRails, Radius_Tube)\n", "\n", "logger.debug (\"count (Y >= 0) = %d \" % (np.count_nonzero(Y >= 0)))\n", "for i in range(-1,12):\n", " logger.debug (\"count (Y = %d) = %d \" % (i, np.count_nonzero(Y == i)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Check classification result \n", "\n", "In this section, you could check signal region classification for all structures but beam pipe.\n", "\n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "# using the variable ax for single a Axes\n", "fig, ax = plt.subplots(figsize=(15,7))\n", "num_bins = 2000\n", "\n", "#correction to BPIX\n", "#Signal\n", "n, bins, patches = ax.hist(Radius_BPIX[np.logical_and(np.logical_and(Radius_BPIX >2.33, Radius_BPIX <23),\n", " np.logical_and(Y > 0, Y < 7))], num_bins)\n", "\n", "#n, bins, patches = ax.hist(Radius_BPIX[np.logical_and(Radius_BPIX >2.4, Radius_BPIX <18)], num_bins)\n", "Xtitle = \"r at BPIX center\"\n", "\n", "\n", "ax.set_xlabel(Xtitle+', cm')\n", "ax.set_ylabel('Entries')\n", "ax.set_title(Xtitle+' for |z| < 25 cm for signal cut test')\n", "\n", "if DataType == \"Toy\":\n", " plt.savefig('Results/Toy_R_atBPIX_testSignalCuts.pdf')\n", "else:\n", " plt.savefig('Results/R_atBPIX_testSignalCuts.pdf')\n", " \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimate background-signal ratio (B/S) of each signal region\n", "[jump to top](#Top)\n", "\n", "* Estimation of the background, $B_{underS}$, and signal, $S_{underS}$, under signal region is done by sideband technique:\n", "\n", "$B_{underS}(w) = B_{before}(w/2) + B_{after}(w/2) $, where w is the width of the signal region, $B_{before}$ and $B_{after}$ are taken from neighbor background regions, respectively. \n", "\n", "$S_{underS} = All_{underS} - B_{underS}$, where $All_{underS}$ is the total number of the NI candidates in the signal region. \n", "\n", "* B/S ratio under each signal region is done:\n", "\n", "B/S ratio $= B_{underS}/S_{underS}$ \n", "\n", "* Signal weight for cross entropy is estimated: \n", "\n", "$w_{Signal} = B_{estimated}/S_{estimated} $, \n", "\n", "where\n", "\n", "$S_{estimated} = \\Sigma_{\\text {signal region}} S_{underS}$ \n", "and $B_{estimated} = \\Sigma_{\\text {signal region}} B_{underS} + \\Sigma_{\\text {background region}} B_{underB}$ \n", "\n", "N.B.: \n", "* For beam pipe, $B_{after}$ is started at $R_{BP}$ = 2.3 cm. It is true that we have smeared signals from inner shield and layer 1, but their contributions are much smaller than combinatorial background. \n", "* For layer 1, $B_{before}$ has width less then $w/2$, that its why $B_{before}$ in this region was calculated, using width of the background band, $w_b$ and scaled to $w/2$: $scale = (w/2)/w_b$" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:Recommended signal weight for NN = 3.04\n" ] }, { "data": { "text/html": [ "

B/S ratio

BP

IS

L1

L2

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L4

OS

Tube

Rails

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no classification

0.16

2.58

1.2

0.92

0.71

0.17

0.41

0.06

0.13

1000.0

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Background under beam pipe\n", "\n", "def BtoS_BP(Rad):\n", " ratio = 0.\n", " # width BP\n", " width_S = lw_Signal_BP[0]\n", " S_left = xSignal_BP[0]\n", " \n", " # backgound before beam pipe is finished\n", " B_left = xBkg_BP[0] + lw_Bkg_BP[0]\n", " # beckground after beam pipe is start\n", " B_right = 2.3\n", " # count backgound \n", " B_underS = np.count_nonzero(np.logical_and(Rad > (B_left - width_S/2),Rad < B_left)) + np.count_nonzero(np.logical_and(Rad > B_right,Rad < (B_right + width_S/2)))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(Rad > (S_left),Rad < (S_left+width_S)))\n", " S_underS = SandB_udnerS - B_underS\n", " epsilon = 1.0e-6\n", " ratio = B_underS/(S_underS + epsilon)\n", " return ratio, S_underS, B_underS\n", "\n", "\n", "# Background under BPIX (IS, L1-L4, OS)\n", "\n", "def BtoS_BPIX(Rad,Name = \"L1\"):\n", " ratio = 0.\n", " if Name == \"IS\":\n", " iS = 0\n", " iS2 = 0 # don't use iS2 if for IS\n", " iB_left = 0\n", " iB_right = 1\n", " elif Name == \"L1\":\n", " iS = 1\n", " iS2 = 2\n", " iB_left = 1\n", " iB_right = 2\n", " elif Name == \"L2\":\n", " iS = 3\n", " iS2 = 4\n", " iB_left = 2\n", " iB_right = 3\n", " elif Name == \"L3\":\n", " iS = 5\n", " iS2 = 6\n", " iB_left = 3\n", " iB_right = 4\n", " elif Name == \"L4\":\n", " iS = 7\n", " iS2 = 7 # don't use iS2 if for L4\n", " iB_left = 4\n", " iB_right = 5\n", " elif Name == \"OS\":\n", " iS = 8\n", " iS2 = 8 # don't use iS2 if for L4\n", " iB_left = 5\n", " iB_right = 6\n", " else:\n", " print(\"Error in BtoS_BPIX: Name structure is not correct\")\n", " \n", " width_S = lw_Signal_BPIX[iS]\n", " S_left = xSignal_BPIX[iS]\n", " width_S2 = lw_Signal_BPIX[iS2]\n", " S2_left = xSignal_BPIX[iS2]\n", " # backgound before structure is finished\n", " B_left = xBkg_BPIX[iB_left] + lw_Bkg_BPIX[iB_left]\n", " # beckground after structure is start\n", " B_right = xBkg_BPIX[iB_right]\n", " # count backgound\n", " if Name == \"IS\" or Name == \"L4\" or Name == \"OS\": # one signal region\n", " B_underS = np.count_nonzero(np.logical_and(Rad > (B_left - width_S/2),Rad < B_left)) + np.count_nonzero(np.logical_and(Rad > B_right,Rad < (B_right + width_S/2)))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(Rad > (S_left),Rad < (S_left+width_S)))\n", " elif Name == \"L1\": # 2 signal regions with narrow backgound at left\n", " Bwidth_left = lw_Bkg_BPIX[iB_left]\n", " # scale left nerrow backgound slice to (width_S+width_S2)\n", " Scale_left = (width_S+width_S2)/2/Bwidth_left\n", "# print(\"Type of Scale_left = \" + str(type(Scale_left)))\n", " B_underS = np.count_nonzero(np.logical_and(Rad > (B_left - Bwidth_left),Rad < B_left))\n", " B_underS = Scale_left*B_underS \n", " B_underS = B_underS + np.count_nonzero(np.logical_and(Rad > B_right,Rad < (B_right + (width_S+width_S2)/2)))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(Rad > (S_left),Rad < (S_left+width_S)))\n", " SandB_udnerS = SandB_udnerS + np.count_nonzero(np.logical_and(Rad > (S2_left),Rad < (S2_left+width_S2)))\n", " \n", " elif Name == \"L2\" or Name == \"L3\": # 2 signal regions\n", " B_underS = np.count_nonzero(np.logical_and(Rad > (B_left - (width_S+width_S2)/2),Rad < B_left))\n", " B_underS = B_underS + np.count_nonzero(np.logical_and(Rad > B_right,Rad < (B_right + (width_S+width_S2)/2)))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(Rad > (S_left),Rad < (S_left+width_S)))\n", " SandB_udnerS = SandB_udnerS + np.count_nonzero(np.logical_and(Rad > (S2_left),Rad < (S2_left+width_S2)))\n", " \n", " S_underS = SandB_udnerS - B_underS\n", " epsilon = 1.0e-6\n", " ratio = B_underS/(S_underS + epsilon)\n", " return ratio, S_underS, B_underS\n", "\n", "# Backgorund under Tube \n", "def BtoS_Tube(Rad):\n", " ratio = 0.\n", " # width BP\n", " width_S = lw_Signal_Tube[0]\n", " S_left = xSignal_Tube[0]\n", " \n", " # backgound before beam pipe is finished\n", " B_left = xBkg_Tube[1] + lw_Bkg_Tube[1]\n", " # beckground after beam pipe is start\n", " B_right = xBkg_Tube[2]\n", " # count backgound \n", " B_underS = np.count_nonzero(np.logical_and(Rad > (B_left - width_S/2),Rad < B_left)) + np.count_nonzero(np.logical_and(Rad > B_right,Rad < (B_right + width_S/2)))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(Rad > (S_left),Rad < (S_left+width_S)))\n", "\n", " S_underS = SandB_udnerS - B_underS\n", " epsilon = 1.0e-6\n", " ratio = B_underS/(S_underS+epsilon)\n", " return ratio, S_underS, B_underS \n", "\n", "# Backgorund under Rails \n", "def BtoS_Rails(Rad, X_Rails):\n", " ratio = 0.\n", " # width BP\n", " width_S = lw_Signal_Rails[0]\n", " S_left = xSignal_Rails[0]\n", " \n", " # backgound before beam pipe is finished\n", " B_left = xBkg_Tube[0] + lw_Bkg_Tube[0] # the same bkg as for Tube\n", " Bwidth_left = lw_Bkg_Tube[0]\n", " # scale left nerrow backgound slice to width_S\n", " Scale_left = width_S/2/Bwidth_left\n", " # beckground after beam pipe is start\n", " B_right = xBkg_Tube[1]\n", " Bwidth_right = lw_Bkg_Tube[1]\n", " # scale left nerrow backgound slice to width_S\n", " Scale_right = width_S/2/Bwidth_right\n", " \n", " # count backgound \n", " B_underS = Scale_left* np.count_nonzero(np.logical_and(np.abs(X_Rails) < 5, \n", " np.logical_and(Rad > (B_left - Bwidth_left),Rad < B_left)))\n", " B_underS = B_underS + Scale_right*np.count_nonzero(np.logical_and(np.abs(X_Rails) < 5, \n", " np.logical_and(Rad > B_right,Rad < (B_right + Bwidth_right))))\n", " SandB_udnerS = np.count_nonzero(np.logical_and(np.abs(X_Rails) < 5, np.logical_and(Rad > (S_left), Rad < (S_left+width_S))))\n", "\n", " S_underS = SandB_udnerS - B_underS\n", " epsilon = 1.0e-6\n", " ratio = B_underS/(S_underS + epsilon)\n", " return ratio, S_underS, B_underS\n", "\n", "# Backgorund under Background \n", "def BtoS_Bkg(Rad_BP, Rad_BPIX, Rad_Tube):\n", " ratio = 1000. # there is not signal at background region\n", " \n", " # count backgound before BP:\n", " Bx = xBkg_BP[0]\n", " Bwidth = lw_Bkg_BP[0] \n", " B_underB = np.count_nonzero(np.logical_and(Rad_BP > Bx,Rad_BP < (Bx + Bwidth)))\n", " \n", " for Bx, Bwidth in zip(xBkg_BPIX, lw_Bkg_BPIX):\n", " B_underB = B_underB + np.count_nonzero(np.logical_and(Rad_BPIX > Bx,Rad_BPIX < (Bx + Bwidth)))\n", " for Bx, Bwidth in zip(xBkg_Tube, lw_Bkg_Tube):\n", " B_underB = B_underB + np.count_nonzero(np.logical_and(Rad_Tube > Bx,Rad_Tube < (Bx + Bwidth)))\n", "\n", " S_underB = 0.\n", " return ratio, S_underB, B_underB\n", "\n", "# for NN injections:\n", "MaterialOfInterest_NN = [\"BP\", \"L2\", \"L3\", \"L4\", \"Tube\", \"Rails\", \"Background\"]\n", "# for NN injections without background:\n", "MaterialOfInterest_NN_noBkg = [\"BP\", \"L2\", \"L3\", \"L4\", \"Tube\", \"Rails\"]\n", "# for all structures:\n", "MaterialOfInterest_All = [\"BP\", \"IS\",\"L1\",\"L2\", \"L3\", \"L4\",\"OS\", \"Tube\", \"Rails\", \"Background\"]\n", "# Pixel material:\n", "MaterialOfPixel = [\"IS\",\"L1\", \"L2\", \"L3\", \"L4\", \"OS\"]\n", "\n", "def PreReF1(Rad_BP, Rad_BPIX, Rad_Tube, X_Rails, Mat, Mat_Pixel): \n", "\n", " prec_Mat, recall_Mat, f1_Mat= 0., 0., 0.\n", " tp, tn, fp, fn = 0., 0., 0., 0.\n", " \n", " lenth = np.size(Mat)\n", " S_estimate = np.zeros(lenth)\n", " B_estimate = np.zeros(lenth)\n", " ratio_estimate = np.zeros(lenth)\n", "\n", " for i in range(0,lenth):\n", " if Mat[i] == \"BP\":\n", " ratio_estimate[i], S_estimate[i], B_estimate[i] = BtoS_BP(Rad_BP)\n", " fp = fp + B_estimate[i]\n", " if any(Mat[i] == x for x in Mat_Pixel):\n", " ratio_estimate[i], S_estimate[i], B_estimate[i] = BtoS_BPIX(Rad_BPIX, Mat[i])\n", " fp = fp + B_estimate[i]\n", " elif Mat[i] == \"Tube\":\n", " ratio_estimate[i], S_estimate[i], B_estimate[i] = BtoS_Tube(Rad_Tube)\n", " fp = fp + B_estimate[i]\n", " elif Mat[i] == \"Rails\":\n", " ratio_estimate[i], S_estimate[i], B_estimate[i] = BtoS_Rails(Rad_Tube, X_Rails)\n", " fp = fp + B_estimate[i]\n", " elif Mat[i] == \"Background\":\n", " ratio_estimate[i], S_estimate[i], B_estimate[i] = BtoS_Bkg(Rad_BP, Rad_BPIX, Rad_Tube)\n", " tn = tn + B_estimate[i]\n", "\n", " # calculated f1score\n", " tp = np.sum(S_estimate)\n", " fn = 0.\n", " epsilon = 1.0e-6\n", " B_est_tot = np.sum(B_estimate)\n", " w_Signal = B_est_tot/(tp+epsilon)\n", "\n", " prec_Mat = tp / (tp + fp + epsilon)\n", " recall_Mat = tp / (tp + fn + epsilon)\n", "\n", " f1_Mat = 2*prec_Mat*recall_Mat / (prec_Mat+recall_Mat+epsilon)\n", "\n", " return ratio_estimate, S_estimate, B_estimate, prec_Mat, recall_Mat, f1_Mat, w_Signal\n", "\n", "ratio_est, S_est, B_est, prec_NN, recall_NN, f1Score_NNinjected, wSignal_NN = PreReF1(Radius_BP, Radius_BPIX, \n", " Radius_Tube, data[:,1], \n", " MaterialOfInterest_NN, \n", " MaterialOfPixel)[0:7]\n", "\n", "# wSignal_NN = PreReF1(Radius_BP, Radius_BPIX, Radius_Tube, data[:,1], MaterialOfInterest_NN, MaterialOfPixel)[6]\n", "\n", "lenth = np.size(B_est)\n", "\n", "for i in range(0,lenth):\n", " logger.debug(\"Ratio(B/S) at %s = %4.2f, signal = %7.0f, and background = %7.0f\" % \n", " (MaterialOfInterest_NN[i],ratio_est[i], S_est[i], B_est[i]))\n", " \n", "logger.debug(\" Selected material: precison = %3.3f, recall = %3.2f, f1 score = %3.2f\" % \n", " (prec_NN, recall_NN, f1Score_NNinjected))\n", "\n", "logger.debug(\"f1Score_NNinjected = \" + str(f1Score_NNinjected))\n", "logger.info(\"Recommended signal weight for NN = \" + str(round(wSignal_NN,2)))\n", "\n", "\n", "from IPython.display import HTML, display\n", "\n", "def display_table(dataIn):\n", " html = \"\"\n", " for row in dataIn:\n", " html += \"\"\n", " for field in row:\n", " html += \"\"\n", " html += \"

%s

\"%(field)\n", " html += \"
\"\n", " display(HTML(html))\n", "\n", "ratioAll_est = PreReF1(Radius_BP, Radius_BPIX, Radius_Tube, data[:,1],MaterialOfInterest_All, MaterialOfPixel)[0:1]\n", "\n", "lenthAll = np.size(ratioAll_est)\n", "extra = [\"B/S ratio\"]\n", "MaterialOfInterest_All_table = np.r_[np.reshape(extra,(1,)), np.reshape(MaterialOfInterest_All,(lenthAll,))]\n", "logger.debug(\"shape of MaterialOfInterest_All_table = \" + str(np.shape(MaterialOfInterest_All_table)))\n", "extra = [\"no classification\"]\n", "ratio_estAll_table = np.r_[np.reshape(extra,(1,)),np.reshape(np.round(ratioAll_est,2),(lenthAll,))]\n", "\n", "# display_table([MaterialOfInterest_All, np.round(ratio_est,2)])\n", "display_table([MaterialOfInterest_All_table, ratio_estAll_table])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Shuffle Data \n", "[jump to top](#Top)\n", "\n", "Shuffle data ($X\\_\\text{NN}\\_\\text{orig}$) and $Y_{true}$ classification ($Y\\_\\text{NN}$) to avoid run (time)-dependent correlations.\n", "\n", "N.B.: \n", "* Before shuffling random seed was fixed to result in the same splitting for Train and Test sets each time running the code. This way, if we know on which data set (Train set) our model was trained, and we could use it again after re-uploading data.\n", " " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:shape of perm = (1397381,)\n" ] } ], "source": [ "#X_NN = data[:,4:27] # it will be set later, because we need to know R for Test set to plot it...\n", "X_NN_orig = data\n", "\n", "# set rendom seed to avoid different spitting for Train and Test sets each time\n", "np.random.seed(1)\n", "perm = np.random.permutation(X_NN_orig.shape[0])\n", "logger.info(\"shape of perm = \" + str(perm.shape))\n", "logger.debug(\"perm = \" + str(perm[1:100]))\n", "\n", "# permutate X_NN_orig and Y: remove bias, when some parts of detector where not working for exampe...\n", "X_NN_orig = X_NN_orig[perm]\n", "Y_NN = Y[perm]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sort track variables by $p_T$ and normalize $p_T$ tracks \n", "[jump to top](#Top)\n", "\n", "21 of the 23 variables injected into the NN describe track qualities:\n", " * 3 tracks for each NI candidate:\n", " * $p_T$, $\\eta$, and $\\phi$;\n", " * $\\chi^2$, and normalized $\\chi^2$;\n", " * number of valid hits;\n", " * track reconstruction algorithm.\n", "These variables were sorted by track transverse momentum, $p_T$, decreasing. $p_T$ of the leading track, $p_T^{leading}$ stays unchanged, but other 2 tracks were scaled to the $p_T^{leading}$: $p_T^{other}/p_T^{leading}$.\n", "\n", "It could help for the NN training, because the ratio $p_T^{other}/p_T^{leading}$ could be more sensitive to internal NI structure then original $p_T$." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": false }, "outputs": [], "source": [ "TrackNorm = True # sorting by pT decreasing and normalize subleading pT tracks\n", "#TrackNorm = False # no sorting, no scaling\n", "\n", "# Create index fore each trackers' parameter:\n", "# pT eta phi chi2 normalizedChi2 numberOfValidHits algorithm\n", "IndexTrk = np.array([6, 9, 12, 15, 18, 21, 24])\n", "\n", "numTrk = 3 # 3 tracks per vertex\n", "IndexNI = 6 # start from pT of tracks\n", "\n", "Xpt = X_NN_orig[:, IndexNI:(IndexNI+numTrk)]\n", "\n", "logger.debug(\"Xpt befor sort shape = \" +str(Xpt.shape))\n", "logger.debug(\"Xpt befor sort = \" +str(Xpt[1:10,:]))\n", "\n", "# sorting by decreasing (1st element is max,....)\n", "argSortXpt = np.argsort(-Xpt, axis=1)\n", "Xpt = np.array(list(map(lambda x, y: y[x], argSortXpt, Xpt)))\n", "\n", "# Keep max pt track (1st track) and other tracks scale to it\n", "Xpt[:,1:] = Xpt[:,1:]/Xpt[:,0].reshape(Xpt[:,0].size,1)\n", "\n", "logger.debug(\"Xpt after sort = \" +str(Xpt[1:10,:]))\n", "logger.debug(\"argsort of Xpt = \" +str(argSortXpt[1:10,:]))\n", "\n", "# other parameters of tracks should be sorted the same way as pt (like eta, phi, chi2...)\n", "Xtrk_other = np.array([])\n", "\n", "for i_par in range(1,7):\n", " Xtrk = X_NN_orig[:,(IndexNI+numTrk*i_par) : (IndexNI+numTrk*(i_par+1))]\n", " Xtrk = np.array(list(map(lambda x, y: y[x], argSortXpt, Xtrk)))\n", " if i_par == 1 : # check if matrix is empty \n", " Xtrk_other = Xtrk\n", " else:\n", " Xtrk_other = np.c_[Xtrk_other,Xtrk]\n", "\n", "logger.debug(\"X_NN_orig before sort = \" +str(X_NN_orig[1:10,9:]))\n", "logger.debug(\"Xtrk_other after sort = \" +str(Xtrk_other[1:10,:])) \n", "\n", "Xvertex = np.c_[Xpt,Xtrk_other]\n", "if TrackNorm == True:\n", " X_NN = X_NN_orig\n", " X_NN[:, IndexNI:] = Xvertex\n", " logger.debug(\"X_NN after norm pT = \" +str(X_NN[1:10,6:]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot variables, injected to NN \n", "[jump to top](#Top)\n", "\n", "Select signal region of interest and plot variables, injected to NN." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "34c41aab46724c68b5766af7708b70b1", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Dropdown(options=('beam pipe', 'BPIX layer 1', 'BPIX layer 2', 'BPIX layer 3', 'BPIX layer 4', 'Tube/Rails'), …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import ipywidgets as widgets\n", "\n", "d = widgets.Dropdown(options=['beam pipe', 'BPIX layer 1', 'BPIX layer 2', 'BPIX layer 3', 'BPIX layer 4', 'Tube/Rails'], value='beam pipe')\n", "d\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:Region = beam pipe is selected -> ys = 0 and yb = 8\n" ] } ], "source": [ "# Default is beam pipe region:\n", "ys = 0 # BP\n", "yb = 8 # background after BP & layer 1\n", "\n", "if d.value == 'BPIX layer 1':\n", " ys = 2 # l1\n", " yb = 8\n", "elif d.value == 'BPIX layer 2':\n", " ys = 3 # l2\n", " yb = 9\n", "elif d.value == 'BPIX layer 3':\n", " ys = 4 # l3\n", " yb = 10\n", "elif d.value == 'BPIX layer 4':\n", " ys = 5 # l4\n", " yb = 11 \n", "elif d.value == 'Tube/Rails':\n", " ys = 6 # Tube and Raisl\n", " yb = 11 \n", "\n", "logger.info(\"Region = \" + str(d.value) + \" is selected -> ys = \" + str(ys) + \" and yb = \" + str(yb))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def PlotSvsBkg(index_var, varName, picName, num_bins, xmin, xmax, Y_S, Y_B, numPar, locPos = 'upper right'):\n", " fig, ax = plt.subplots(figsize=(9,5))\n", "\n", " XFill = X_NN[:, index_var]\n", " YFill = Y_NN\n", " # Fill (n >1) parameters Track 1, ... numPar\n", " if numPar > 1:\n", " for i_var in range(1,numPar):\n", " XFill = np.concatenate(([XFill,X_NN[:, index_var+i_var]]),axis=0)\n", " YFill = np.concatenate(([YFill,Y_NN]),axis=0)\n", "\n", " flagSigma = \"\\Sigma\" in varName\n", " if numPar == 2 and flagSigma: # it will work only for \\Sigma pT and only there nunPar = 2\n", " XFill = X_NN[:, index_var] +X_NN[:, index_var+1]\n", " YFill = Y_NN \n", "\n", " #Signal\n", " nS, binsS, patches = ax.hist(XFill[np.logical_and(YFill == Y_S,XFill < xmax)], \n", " num_bins, density = True, alpha = 0.7)\n", " n, bins, patches = ax.hist(XFill[np.logical_and(YFill == Y_B,XFill < xmax)], \n", " num_bins, density = True, alpha = 0.7)\n", " ax.set_ylim(0., 1.3 * max(np.max(nS),np.max(n)))\n", "\n", " if numPar == 3 or \"other\" in varName:\n", " Xtitle = varName + \" of the track\"\n", " if varName == \"$\\phi$\": Xtitle = Xtitle + \" (rad)\" \n", " else:\n", " Xtitle = varName + \" for each NI candidate\"\n", " \n", " ax.set_xlabel(Xtitle)\n", " ax.set_ylabel('Density')\n", " if Y_S == 0 and Y_B == 8:\n", " ax.legend(['Signal region for beam pipe', 'Background region around beam pipe'], loc=locPos)\n", " elif Y_S == 5 and Y_B == 11:\n", " ax.legend(['Signal region for layer 4', 'Background region after layer 4'], loc=locPos)\n", " elif Y_S == 2 :\n", " ax.legend(['Signal region for layer 1', 'Background region after layer 1'], loc=locPos)\n", " elif Y_S == 3 :\n", " ax.legend(['Signal region for layer 2', 'Background region after layer 2'], loc=locPos)\n", " elif Y_S == 4 :\n", " ax.legend(['Signal region for layer 3', 'Background region after layer 3'], loc=locPos)\n", " elif Y_S == 6 :\n", " ax.legend(['Signal region for Tube and Rails', 'Background around Tube and Rails'], loc=locPos)\n", " else:\n", " ax.legend(['Signal', 'Background'], loc=locPos)\n", "\n", " ax.text(0.02,0.9,labelData, size = 15, transform=ax.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", " if d.value == \"beam pipe\" or DataType == \"Toy\":\n", " SetCMSlabel(ax)\n", " else:\n", " SetCMSlabel(ax,\"internal\")\n", "\n", " # https://github.com/cms-sw/cmssw/blob/master/DataFormats/TrackReco/interface/TrackBase.h\n", " AlgoName = ['duplicateMerge', 'initialStep', 'lowPtTripletStep', 'pixelPairStep', 'detachedTripletStep',\n", " 'mixedTripletStep', 'pixelLessStep', 'tobTecStep', 'highPtTripletStep', 'lowPtQuadStep', 'detachedQuadStep']\n", " AlgoNumber = [2, 4, 5, 6, 7,\n", " 8, 9, 10, 22, 23, 24]\n", " AlgoPosX = [0.025, 0.1, 0.14, 0.185, 0.225,\n", " 0.265, 0.30, 0.35, 0.85, 0.885, 0.915]\n", " # track algorithms:\n", " if \"algorithm\" in varName and d.value == \"beam pipe\" and DataType != \"Toy\":\n", " for name, x in zip(AlgoName, AlgoPosX):\n", " ax.text(x, 0.04, name, verticalalignment='bottom', horizontalalignment='left',\n", " transform=ax.transAxes, color='darkgreen', fontsize=11, rotation = 90)\n", " logger.debug(\"n in algorithm = \" + str(nS[np.not_equal(nS,0)]) + str(binsS[0:num_bins][np.not_equal(nS,0)]))\n", " \n", " fig.tight_layout()\n", " \n", " if DataType == \"Toy\":\n", " ToyExtra = \"Toy_\"\n", " else:\n", " ToyExtra = \"\" \n", " \n", " if Y_S == 0:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_BP_'+picName+'.pdf')\n", " elif Y_S == 5:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_l4_'+picName+'.pdf')\n", " elif Y_S == 2:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_l1_'+picName+'.pdf')\n", " elif Y_S == 3:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_l2_'+picName+'.pdf')\n", " elif Y_S == 4:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_l3_'+picName+'.pdf')\n", " else:\n", " plt.savefig('Results/'+ToyExtra+'ControlPlots_'+picName+'.pdf')\n", " \n", " plt.show()\n", " \n", "# Y_S and Y_B are for 7 signal + 4 bkg befor converting to 4 categories\n", "# index_var, varName, picName num_bins, xmin, xmax, Y_S, Y_B, numPar locPos\n", "# for BP and bkg BP\n", "PlotSvsBkg(4, \"# of primary vertices\",\"numPV\", 100, 0., 50., ys, yb, 1)\n", "PlotSvsBkg(5, \"# of NIs per event\",\"numPFDV\", 40, 0., 10., ys, yb, 1) # of NIs (barrel and endcap)\n", "if TrackNorm == False:\n", " PlotSvsBkg(6, \"$p_T$ (GeV/c)\", \"pt\", 100, 0., 2., ys, yb, 3)\n", "else:\n", " PlotSvsBkg(6, \"$p_T^{leading}$ (GeV/c)\", \"pt_leading\", 100, 0., 5., ys, yb, 1)\n", " # plot it till 2. to be sure that we don't have anything above 1, and when it sum it could be till 2:\n", " # PlotSvsBkg(7, \"$\\Sigma p_T^{other}/p_T^{leading}$\", \"SumPtToLeading\", 100, 0., 2., ys, yb, 2)\n", " PlotSvsBkg(7, \"$p_T^{other}/p_T^{leading}$\", \"PtToLeading\", 100, 0., 2., ys, yb, 2)\n", "PlotSvsBkg(9, \"$\\eta$\", \"eta\", 100, -5., 5., ys, yb, 3)\n", "PlotSvsBkg(12, \"$\\phi$\", \"phi\", 100, -5., 5., ys, yb, 3)\n", "PlotSvsBkg(15, \"$\\chi^2$\", \"chi2\", 100, 0., 80., ys, yb, 3)\n", "PlotSvsBkg(18, \"normalized $\\chi^2$\",\"normalizedChi2\", 100, 0., 3., ys, yb, 3)\n", "PlotSvsBkg(21, \"# of valid hits\",\"numberOfValidHits\", 70, 0., 35., ys, yb, 3)\n", "PlotSvsBkg(24, \"reconstruction algorithm\",\"algorithm\", 50, 0., 50., ys, yb, 3)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Divide data into Train and Test data sets \n", "[jump to top](#Top) \n", "\n", "Divide data into Train and Test data sets ~50:50% (not much data):\n", "* Test set includes ~0.7×106 NI candidates; \n", "* Train set includes ~0.7×106 NI candidates." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:shape X_Train = (698690, 27)\n", "INFO:log:shape X_Test = (698691, 27)\n" ] } ], "source": [ "if DataType == \"Toy\":\n", " fracTrain = 0.5 #0.25 # set Tainning fraction of data\n", "else:\n", " fracTrain = 0.5 # set Tainning fraction of Toy\n", " \n", "NumTrain = (np.rint(X_NN.shape[0]*fracTrain)).astype(int)\n", "\n", "X_Train = X_NN[:NumTrain,:]\n", "X_Test = X_NN[NumTrain:,:]\n", "Y_Train = Y_NN[:NumTrain]\n", "Y_Test = Y_NN[NumTrain:]\n", "logger.debug(\"Y_Train = \"+str(Y_Train[0:200]))\n", " \n", "logger.info(\"shape X_Train = \" + str(X_Train.shape))\n", "logger.info(\"shape X_Test = \" + str(X_Test.shape))\n", "\n", "# should be selected Y > -1 only for Train sample: use data with defined Y (Y > -1)\n", "#and only after clean Train sample only\n", "logger.debug(\"count (Y_Train >= 0) = %d \" % (np.count_nonzero(Y_Train >= 0)))\n", "for i in range(-1,12):\n", " logger.debug(\"count (Y_Train = %d) = %d \" % (i, np.count_nonzero(Y_Train == i)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data preparation and classification for the NN\n", "\n", "[jump to top](#Top)\n", "\n", "* Data (NI candidates) are presented in NumPy matrix X:\n", " * each column represents: 23 input variables for NN + 3 variables for vertex position (classification);\n", " * each row represents a new NI candidate: if we have n NI candidates per event $\\Rightarrow$ we will have n rows.\n", "\n", "* Classification for NN, 𝑌_𝑡𝑟𝑢𝑒 set includes 2 classes, calculated by using signal and background region definitions, discussed at [Classification Strategy for NN](#Classification):\n", " * Class 0 (signal class): Beam pipe, layer 2-4, rails, and tube signal regions (S0, S3-S6).\n", " * N.B.: inner shield and layer 1 signal regions (S1 and S2), due to high background contamination, are not classified as signal class for NN (not used during training):\n", " * input variable distributions in the beam pipe region should be similar to the inner shield and layer 1;\n", " * great cross-check for NN signal-background separation power in non-trained signal regions.\n", " * Class 1 (background class): all classified background (B7-B11).\n", " * Some NI candidates, including inner shield and layer 1 signal regions, stay in non-classified state, they are not used during training.\n", "\n", "* Normalize each input variable in the X Train set on its mean and standard deviation before injection to NN for better performance.\n", "* Test set uses the same normalization from the Train set.\n", "\n", "* For model training and validation, only classified events (class 0 and 1) were used: \n", " * ~0.4×106 from ~0.7×106 NI candidates.\n", "* For the model prediction, all events (classified and non-classified) are used." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:shape of mean_Norm = (23,)\n", "INFO:log:shape of X_Train_NN to be injected to NN = (415289, 23)\n" ] } ], "source": [ "from keras.utils.np_utils import to_categorical\n", "\n", "def DefClasses(Y_in, nSig,nBkg):\n", " \n", " nClasses = nSig + nBkg\n", " Y_out = Y_in + 0. # if we not add 0. then it will be rewrite original Y_in input too !!!???\n", " #select categorized events only for the Training: Y > -1\n", " Y_out = Y_out[Y_out > -1]\n", " if nSig == 4:\n", " Y_out[Y_out == 3] = 1 # L2\n", " Y_out[Y_out == 4] = 2 # L3\n", " Y_out[Y_out == 5] = 3 # L4\n", " Y_out[Y_out == 6] = 3 # OS, Rails, Tube -> merge with L4\n", " Y_out[Y_out > 6] = 4\n", " if nSig == 1: # 1 singnal and 1 background\n", " Y_out[Y_out < 7] = 0\n", " Y_out[Y_out > 6] = 1\n", "\n", " # set max Y to number of classes...\n", " Y_out[Y_out > (nClasses-1)] = nClasses-1\n", " return Y_out\n", "\n", "# Define number of classes \n", "\n", "#numSig = 7\n", "#numBkg = 5\n", "# interesting results for this model:\n", "# numSig = 4\n", "# numBkg = 1\n", "# train any signal vs any backround\n", "numSig = 1\n", "numBkg = 1\n", "#numClasses = 12 # 7 signals + 5 bkg\n", "numClasses = numSig + numBkg # 7 singnals + 1 bkg(all bkg as one class)\n", "\n", "#convert Y_train_NN to one-hot \n", "#select categorized events only for the Training: Y > -1\n", "logger.debug(\"before Y_Train = \" + str(Y_Train[0:100]))\n", "\n", "if numSig == 4:\n", " # remove class 1 and 2 (IS and L1) from training at all and shift all other classe:\n", " Y_Train[Y_Train == 1] = -1 # IS remove from training\n", " Y_Train[Y_Train == 2] = -1 # L1 remove from training\n", " Y_Train[Y_Train == 9] = -1 # remove L2-L3 background\n", " Y_Train[Y_Train == 10] = -1 # remove L3-L4 background\n", " Y_Train[Y_Train == 11] = -1 # remove > L4 background\n", "if numSig == 1:\n", " # remove class 1 and 2 (IS and L1) from training at all and shift all other classe:\n", " Y_Train[Y_Train == 1] = -1 # IS remove from training\n", " Y_Train[Y_Train == 2] = -1 # L1 remove from training\n", " \n", "Y_Train_NN = DefClasses(Y_Train, numSig, numBkg)\n", "\n", "logger.debug(\"Y_Train = \" + str(Y_Train[0:100]))\n", "logger.debug(\"Y_Train_NN = \" + str(Y_Train_NN[0:100]))\n", "\n", "Y_Train_NN_hot = to_categorical(Y_Train_NN, num_classes = numClasses)\n", "\n", "Xnorm_Train = X_Train[:,4:]\n", "\n", "# normalize after selection events for NN injection \n", "#normalize input data before selecting categorization: \n", "#Test sample should be normalized to the same value of mean and std:\n", "#select categorized events only for the Training: Y > -1\n", "mean_Norm = np.mean(Xnorm_Train[Y_Train > -1], axis = 0)\n", "std_Norm = np.std(Xnorm_Train[Y_Train > -1], axis = 0)\n", "X_Train_NN = (Xnorm_Train[Y_Train > -1] - mean_Norm)/std_Norm\n", "\n", "# for testing model use all Training set:\n", "Xnorm_Train = (Xnorm_Train - mean_Norm)/std_Norm\n", "\n", "logger.info (\"shape of mean_Norm = \" + str(mean_Norm.shape))\n", "\n", "batchSize = 8192\n", "# NumTrain_NN = (np.floor(X_Train_NN.shape[0]/batchSize)).astype(int)*batchSize\n", "# # cut last bach that is small then batchSize\n", "# X_Train_NN = X_Train_NN[:NumTrain_NN,:]\n", "# Y_Train_NN_hot = Y_Train_NN_hot[:NumTrain_NN]\n", "logger.info(\"shape of X_Train_NN to be injected to NN = \" + str(X_Train_NN.shape))\n", "\n", "# normilize Test set and Train one\n", "Xnorm_Test = X_Test[:,4:27]\n", "#normalize input data: Test sample should be normalized to the mean and std of Test:\n", "Xnorm_Test = (Xnorm_Test - mean_Norm)/std_Norm\n", "\n", "if numSig == 4:\n", " # remove class 1 and 2 (IS and L1) from training at all and shift all other classe:\n", " Y_Test[Y_Test == 1] = -1 # IS remove from training\n", " Y_Test[Y_Test == 2] = -1 # L1 remove from training\n", " Y_Test[Y_Test == 9] = -1 # remove L2-L3 background\n", " Y_Test[Y_Test == 10] = -1 # remove L3-L4 background\n", " Y_Test[Y_Test == 11] = -1 # remove > L4 background\n", "if numSig == 1:\n", " # remove class 1 and 2 (IS and L1) from training at all and shift all other classe:\n", " Y_Test[Y_Test == 1] = -1 # IS remove from test set\n", " Y_Test[Y_Test == 2] = -1 # L1 remove from test set\n", " \n", "# select Test for validation where Y > -1\n", "Y_Test_val = DefClasses(Y_Test, numSig, numBkg)\n", "Y_Test_val_hot = to_categorical(Y_Test_val, num_classes = numClasses)\n", "Xnorm_Test_val = Xnorm_Test[Y_Test > -1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Principal Component Analysis (PCA) \n", "\n", "* Perform Principal Component Analysis (PCA) on input variables in the X Train set:\n", " * PCA is defined as an orthogonal linear transformation that transforms the Data to a new coordinate system: 1st PCA variable has greatest variance, 2nd PCA variable has 2nd greatest variance, and so on…\n", " * PCA shows that all 23 variables after PCA transformation have significant variance, that is why all PCA variables were kept for the injection to the NN.\n", "* Apply the same PCA for X Test set, which is used for model validation during Training (only classified events). In principle, an independent Validation set should be used, but we are restricted in statistics for this task. \n", "* Apply the same PCA for X Train and Test sets during model prediction, using all data (classified and non-classified).\n", "\n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "def PCA_ax(ax_pca, i1_pca,i2_pca, Xmax, Ymax, nb):\n", "\n", " counts, xedges, yedges, im = ax_pca.hist2d(X_Train_NN_PCA[:,i1_pca],X_Train_NN_PCA[:,i2_pca], bins=nb, \n", " range = [[-Xmax, Xmax], [-Ymax, Ymax]], norm=LogNorm(), cmap = 'viridis')\n", "\n", " plt.colorbar(im, ax=ax_pca)\n", " ax_pca.set_xlabel('X_PCA['+str(i1_pca)+']')\n", " ax_pca.set_ylabel('X_PCA['+str(i2_pca)+']')\n", " return ax_pca\n", "\n", "# Calculate covariance matrix\n", "X_Conv = np.dot(X_Train_NN.T,X_Train_NN)/X_Train_NN.shape[0]\n", "# X_Conv = np.cov(X_Train_NN.T)\n", "#logger.debug(\"Covariance matrix X_Conv = \" + np.array2string(X_Conv, separator=', ')) # 1/m X^T X\n", "\n", "# logger: check that X_train_NN mean and std\n", "mean_X = np.mean(X_Train_NN, axis = 0)\n", "std_X = np.std(X_Train_NN, axis = 0)\n", "logger.debug(\"mean_X = \" + str(mean_X))\n", "logger.debug(\" std_X = \" + str(std_X))\n", "\n", "\n", "U, s, vh = np.linalg.svd(X_Conv, full_matrices=True)\n", "\n", "logger.debug(\"s = \" + str(s))\n", "\n", "logger.debug(\"np.linalg.cond(X_Conv) = \" + str(np.linalg.cond(X_Conv)))\n", "# logger.debug(\"checking column orthogonality U.TxU should be 1 = \" +str(np.dot(U.T,U)))\n", "logger.debug(\"checking column orthogonality: np.isclose(np.dot(U.T, U), np.eye(23)).all() = \" + str(np.isclose(np.dot(U.T, U), np.eye(23)).all()))\n", "\n", "k = 23\n", "\n", "U_k = U[:, 0:k]\n", "\n", "#convert all data using for Training, Validation, and Y prediction \n", "X_Train_NN_PCA = X_Train_NN.dot(U_k)\n", "Xnorm_Test_val_PCA = Xnorm_Test_val.dot(U_k)\n", "Xnorm_Train_PCA = Xnorm_Train.dot(U_k)\n", "Xnorm_Test_PCA = Xnorm_Test.dot(U_k)\n", "\n", "logger.debug(\"shape of X_Train_NN_PCA = \" + str(X_Train_NN_PCA.shape))\n", "logger.debug(\"shape of Xnorm_Train_PCA = \" + str(Xnorm_Train_PCA.shape))\n", "logger.debug(\"shape of Xnorm_Test_PCA = \" + str(Xnorm_Test_PCA.shape))\n", "\n", "# calculated varience retained:\n", "X_approx = X_Train_NN_PCA.dot(U_k.T)\n", "logger.debug(\"shape of X_approx = \" + str(X_approx.shape))\n", "\n", "nt = 200\n", "VarOut = np.sum(np.square(X_Train_NN[:nt,:] - X_approx[:nt,:]))/np.sum(np.square(X_Train_NN[:nt,:]))\n", "logger.debug(\"VarOut on 1st \" + str(nt)+ \" vertices = \" + str(VarOut))\n", "VarRest = np.sum(s[:k])/np.sum(s)\n", "logger.info(\"Varience retained = \" + str(VarRest))\n", "\n", "# logger.debug(\"X_Train_NN[:5,:4] = \" +str(X_Train_NN[:5,:4]))\n", "# logger.debug(\"X_approx[:5,:4] = \" +str(X_approx[:5,:4]))\n", "\n", "from matplotlib.colors import LogNorm\n", "\n", "fig, ((ax, bx),(cx,dx),(ex,fx)) = plt.subplots(3,2, figsize=(14,18))\n", "#fig.delaxes(a_null)\n", "\n", "nb = 100\n", "Xmax = 4.\n", "\n", "# 0, 14, 17, 19, 21, 22 are interesting\n", "i1_pca = 0\n", "i2_pca = 1\n", "ax = PCA_ax(ax,i1_pca,i2_pca, Xmax, 2*Xmax, nb)\n", "\n", "Xmax = 3\n", "i2_pca = 14\n", "bx = PCA_ax(bx,i1_pca,i2_pca, Xmax, Xmax, nb)\n", "\n", "i2_pca = 17\n", "cx = PCA_ax(cx,i1_pca,i2_pca, Xmax, Xmax, nb)\n", "\n", "#i2_pca = 19\n", "i2_pca = 5\n", "dx = PCA_ax(dx,i1_pca,i2_pca, Xmax, Xmax, nb)\n", "\n", "Xmax = 8\n", "i1_pca = 1\n", "i2_pca = 3\n", "ex = PCA_ax(ex,i1_pca,i2_pca, Xmax, Xmax, nb)\n", "\n", "i1_pca = 2\n", "i2_pca = 4\n", "fx = PCA_ax(fx,i1_pca,i2_pca, Xmax, Xmax, nb)\n", "\n", "fig.tight_layout()\n", "\n", "if DataType == \"Toy\":\n", " plt.savefig('Results/Toy_ControlPlots_Train_PCA_var.pdf')\n", "else:\n", " plt.savefig('Results/ControlPlots_Train_PCA_var.pdf')\n", " \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Keras mode: NN with 2 hidden layers \n", "[jump to top](#Top)\n", "\n", "* Classification of the input to NN, $Y_{true}$, is done on the mixed samples:\n", " * Signal class (class 0) includes real NIs (S) and combinatorial background (B). For some structures signal-background ratio (B/S) reaches almost 1.\n", " * Background class (class 1) includes mostly combinatorial background (>99%).\n", "\n", "* NN model is trained on the mixed sample and calculates the probability distribution, $p_{Signal}$, for the injected vertex to be a signal.\n", "\n", "* The predicted classification, $Y_{predict}$, is estimated by optimizing cut on the $p_{Signal}$ for real NIs and combinatorial background separation (see this section).\n", "\n", "This is an example of an NN Model with floating classification:\n", "* Input classification is done on mixed samples with different fraction of B/S.\n", "* Output classification is optimized for real NIs and combinatorial background separation.\n", "* This technique is similar to CWoLa method, described in [DOI:10.1007/JHEP10(2017)174](https://doi.org/10.1007/JHEP10(2017)174).\n", "\n", "NN with 2 hidden layers (with 12 neurons in each hidden layer) is selected.\n", "\n", "## Import libraries " ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "import tensorflow as tf\n", "import keras\n", "from keras import optimizers\n", "from keras.models import Model\n", "from keras.layers import Dense, Input, Dropout, LSTM, Activation, BatchNormalization\n", "from keras.layers.embeddings import Embedding\n", "from keras.preprocessing import sequence\n", "from keras.initializers import glorot_uniform\n", "from keras import regularizers\n", "# to write lost function by yourself:\n", "import keras.backend as K\n", "\n", "pythonPath = !echo $PYTHONPATH\n", "# logger.debug(\"python path = \" + str(pythonPath))\n", "logger.debug(\"Keras version = \" + str(keras.__version__))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create function for NN model with 2 hidden layers \n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "def NN_2Layers(input_shape, nClasses):\n", "\n", "\n", " sentence_indices = Input(shape=input_shape)\n", " \n", " RegMode = False\n", " DropoutMode = False # looks like good for big NN (not our case)\n", " NumHidLayers = 2 # 1 - default; 2 - non default; 3 + dropout < 0.3 - need more training data\n", " SigmoidTrue = False # if True then use sigmoid for output level \n", "\n", " #reg_lambda = 0.5\n", " reg_lambda = 0.1\n", " Dropout_frac = 0.3 # which fraction will be dropped\n", "\n", " #kernel_initializer='he_uniform' for relu - bad\n", " #kernel_initializer='he_normal' for relu - similar to default\n", " \n", " #define shape of Layer\n", " #nLayer = aint((sentence_indices.shape[1] + nClasses)/2) # for python 2\n", " numIn = sentence_indices.shape[1].value\n", " nLayer = int((numIn + nClasses)/2)\n", " \n", " if NumHidLayers > 1: # from 2 hidden layers\n", "# nLayer = int((2*numIn + nClasses)/3)\n", "# nLayer = int((numIn + nClasses)/2) # default\n", " nLayer = int(0.4*(numIn + nClasses)*1.2)# modified\n", "\n", "\n", " if RegMode == True:\n", " X = Dense(nLayer, use_bias=False,\n", " kernel_regularizer=regularizers.l2(reg_lambda))(sentence_indices)\n", " else:\n", " X = Dense(nLayer, use_bias=False)(sentence_indices)\n", " \n", " X = BatchNormalization()(X)\n", " X = Activation(\"relu\")(X)\n", "\n", " # Add dropout with a probability of 0.7\n", " if DropoutMode == True:\n", " X = Dropout(Dropout_frac)(X)\n", "\n", " # 2nd hidden layer\n", " if NumHidLayers > 1:\n", "# nLayer2 = int((2*nClasses + numIn)/3)\n", "# nLayer2 = int((nClasses + nLayer)/2)\n", " nLayer2 = nLayer\n", " if RegMode == True:\n", " X = Dense(nLayer2, use_bias=False,\n", " kernel_regularizer=regularizers.l2(reg_lambda))(X)\n", " else:\n", " X = Dense(nLayer2, use_bias=False)(X)\n", "\n", " X = BatchNormalization()(X)\n", " X = Activation(\"relu\")(X)\n", " # Add dropout with a probability of 0.5\n", " if DropoutMode == True:\n", " X = Dropout(Dropout_frac)(X)\n", " \n", " # 3d hidden layer\n", " if NumHidLayers > 2:\n", " nLayer3 = int((nClasses + nLayer2)/2)\n", " if RegMode == True:\n", " X = Dense(nLayer3, use_bias=False,\n", " kernel_regularizer=regularizers.l2(reg_lambda))(X)\n", " else:\n", " X = Dense(nLayer3, use_bias=False)(X)\n", "\n", " X = BatchNormalization()(X)\n", " X = Activation(\"relu\")(X)\n", " # Add dropout with a probability of 0.5\n", " if DropoutMode == True:\n", " X = Dropout(Dropout_frac)(X)\n", "\n", " # output layer: softmax with nClasses outputs as for Y\n", " if nClasses > 2 or SigmoidTrue == False:\n", " if RegMode == True:\n", " X = Dense(nClasses, activation=\"softmax\",\n", " kernel_regularizer=regularizers.l2(reg_lambda),\n", " bias_regularizer=regularizers.l2(reg_lambda))(X)\n", " else:\n", " X = Dense(nClasses, activation=\"softmax\")(X)\n", " else:\n", " if RegMode == True:\n", " X = Dense(1, activation=\"sigmoid\",\n", " kernel_regularizer=regularizers.l2(reg_lambda),\n", " bias_regularizer=regularizers.l2(reg_lambda))(X)\n", " else:\n", " X = Dense(1, activation=\"sigmoid\")(X)\n", " \n", " # Create Model instance which converts sentence_indices into X.\n", " model = Model(inputs=[sentence_indices], outputs=X)\n", "\n", " return model\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create NN model structure and compile it \n", "[jump to top](#Top)\n", "\n", "* model loss – categorical cross entropy is used for the optimization function for the NN\n", "\n", "$-\\frac{1}{N}\\Sigma_{i=1}^N class\\_weight\\times\\log(Y_{predict})[Y_{true}^i Class^i].$\n", "\n", "* epochs = 300 – number of passes of the Train Set to the NN." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", "input_1 (InputLayer) (None, 23) 0 \n", "_________________________________________________________________\n", "dense_1 (Dense) (None, 12) 276 \n", "_________________________________________________________________\n", "batch_normalization_1 (Batch (None, 12) 48 \n", "_________________________________________________________________\n", "activation_1 (Activation) (None, 12) 0 \n", "_________________________________________________________________\n", "dense_2 (Dense) (None, 12) 144 \n", "_________________________________________________________________\n", "batch_normalization_2 (Batch (None, 12) 48 \n", "_________________________________________________________________\n", "activation_2 (Activation) (None, 12) 0 \n", "_________________________________________________________________\n", "dense_3 (Dense) (None, 2) 26 \n", "=================================================================\n", "Total params: 542\n", "Trainable params: 494\n", "Non-trainable params: 48\n", "_________________________________________________________________\n" ] } ], "source": [ "# f1 and f1_loss are taken from here: https://www.kaggle.com/rejpalcz/best-loss-function-for-f1-score-metric\n", "def f1(y_true, y_pred):\n", " y_pred = K.round(y_pred)\n", " tp = K.sum(K.cast(y_true*y_pred, 'float'), axis=0)\n", " tn = K.sum(K.cast((1-y_true)*(1-y_pred), 'float'), axis=0)\n", " fp = K.sum(K.cast((1-y_true)*y_pred, 'float'), axis=0)\n", " fn = K.sum(K.cast(y_true*(1-y_pred), 'float'), axis=0)\n", "\n", " p = tp / (tp + fp + K.epsilon())\n", " r = tp / (tp + fn + K.epsilon())\n", "\n", " f1 = 2*p*r / (p+r+K.epsilon())\n", " f1 = tf.where(tf.is_nan(f1), tf.zeros_like(f1), f1)\n", " return K.mean(f1)\n", "\n", "#### This fix problem for 2 classes of the same value for all metrics, didn't check if it works for n classes\n", "# taken and modified for numClasses from here: https://github.com/keras-team/keras/issues/5400\n", "\n", "def check_units(y_true, y_pred):\n", " if y_pred.shape[1] != 1:\n", "# y_pred = y_pred[:,1:2]\n", "# y_true = y_true[:,1:2]\n", " y_pred = y_pred[:,0:numClasses]\n", " y_true = y_true[:,0:numClasses]\n", "# y_pred = y_pred[:,0:1] # train loss only on the Signal region\n", "# y_true = y_true[:,0:1] # train loss only on the Signal region\n", " return y_true, y_pred\n", "\n", "def precision(y_true, y_pred):\n", " y_true, y_pred = check_units(y_true, y_pred)\n", " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", " predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n", " precision = true_positives / (predicted_positives + K.epsilon())\n", " return precision\n", "\n", "def recall(y_true, y_pred):\n", " y_true, y_pred = check_units(y_true, y_pred)\n", " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", " possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n", " recall = true_positives / (possible_positives + K.epsilon())\n", " return recall\n", "\n", "def f1_score(y_true, y_pred):\n", " def recall(y_true, y_pred):\n", " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", " possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n", " recall = true_positives / (possible_positives + K.epsilon())\n", " return recall\n", "\n", " def precision(y_true, y_pred):\n", " true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n", " predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n", " precision = true_positives / (predicted_positives + K.epsilon())\n", " return precision\n", " y_true, y_pred = check_units(y_true, y_pred)\n", " precision = precision(y_true, y_pred)\n", " recall = recall(y_true, y_pred)\n", " return 2*((precision*recall)/(precision+recall+K.epsilon()))\n", "\n", "def f1_loss(y_true, y_pred):\n", " y_true, y_pred = check_units(y_true, y_pred)\n", " tp = K.sum(K.cast(y_true*y_pred, 'float'), axis=0)\n", " tn = K.sum(K.cast((1-y_true)*(1-y_pred), 'float'), axis=0)\n", " fp = K.sum(K.cast((1-y_true)*y_pred, 'float'), axis=0)\n", " fn = K.sum(K.cast(y_true*(1-y_pred), 'float'), axis=0)\n", "\n", " p = tp / (tp + fp + K.epsilon())\n", " r = tp / (tp + fn + K.epsilon())\n", "\n", " f1 = 2*p*r / (p+r+K.epsilon())\n", "# f1 = f1*r # correct to f1_loss more weithg for recall\n", "# f1 = f1*K.sqrt(r) # correct to f1_loss more weithg for recall\n", " f1 = tf.where(tf.is_nan(f1), tf.zeros_like(f1), f1)\n", " return 1 - K.mean(f1)\n", "\n", "#reset layers counting\n", "K.clear_session()\n", "\n", "model = NN_2Layers((X_Train_NN_PCA.shape[1],),numClasses)\n", "\n", "# problem with same outout form metrisc discussed here: https://github.com/keras-team/keras/issues/5400\n", "# looks like if you have 2 classes and use sigmoid instead of softmax doesn't help...\n", "# check_units (see above) hepls to fix problem for 2 classes, didn't check if it works for n classes\n", "\n", "# sgd is good for shalow NN (our case), adam is good for deep NN\n", "sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)\n", "# default beta_1 = 0.9\n", "adamCorr = optimizers.Adam(lr=0.005, beta_1=0.9, beta_2=0.999, amsgrad=False) # av. by last 100\n", "\n", "# default for categorical_crossentropy loss, :\n", "# customized metrics are not calculated properly if loss in not customized \n", "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy', f1_score, precision, recall])\n", "# some code for f1_loss and customized metrics are calculated properly:\n", "# model.compile(loss=f1_loss, optimizer=adamCorr, metrics=['accuracy', f1_score, precision, recall])\n", "# model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n", "\n", "model.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## NN model training \n", "[jump to top](#Top)\n", "\n", "Skip this section if you are going to upload a trained model.\n", "\n", "Use only classified events (Classes 0 and 1), as discussed at [this section](#FinalClassification), for Train and Validation (Test) sets during model training." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "def generate_sample_weights(training_data, class_weight_dictionary): \n", " sample_weights = [class_weight_dictionary[np.where(one_hot_row==1)[0][0]] for one_hot_row in training_data]\n", " return np.asarray(sample_weights) # correct on dropout\n", "\n", "if numSig == 7:\n", " class_weight = {0: 10., 1: 0.1, 2: 0.1, 3: 10., 4: 5., 5: 5., 6:4., \n", " 7:1., 8: 1., 9: 1., 10: 1., 11: 1.}\n", "if numSig == 4:\n", " # BP L2 L3 L4, OS, Rails, Tube BKG\n", " class_weight = {0: 4.2, 1: 9., 2: 12., 3: 2., 4: 1.} # for ...Epoch1000_L2L3 tune final\n", "\n", "if numSig == 1:\n", " # BP,L2-L4, OS, Rails, Tube BKG\n", " class_weight = {0: 3., 1: 1.} \n", "# class_weight = {0: 1., 1: 1.} \n", "# class_weight = {0: 3.4, 1: 1.} # if remove S6 (OS, Rails, Tube)\n", "\n", "if DataType == \"Toy\":\n", " class_weight = {0: 4.8, 1: 1.}\n", "#train and keep history about model: customize matrics store only accuricy for all parameters (f1score, pres., recall)):\n", "history = model.fit(X_Train_NN_PCA, Y_Train_NN_hot, epochs = 50, \n", " validation_data=(Xnorm_Test_val_PCA, Y_Test_val_hot,\n", " generate_sample_weights(Y_Test_val_hot, class_weight)),\n", " batch_size = batchSize, shuffle=True, class_weight=class_weight)\n", "\n", "# no weights for customized models: customize matrics store all parameters properly in this case\n", "# usually you need 300-500 epochs to train model well, but we set it to 50 for fast results\n", "# history = model.fit(X_Train_NN_PCA, Y_Train_NN_hot, epochs = 100, validation_data=(Xnorm_Test_val_PCA, Y_Test_val_hot),\n", "# batch_size = batchSize, shuffle=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Save/Load NN model to/from file \n", "[jump to top](#Top)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING:tensorflow:From /cvmfs/sft.cern.ch/lcg/views/LCG_97python3/x86_64-centos7-gcc8-opt/lib/python3.7/site-packages/tensorflow/python/ops/math_grad.py:1250: add_dispatch_support..wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n", "Instructions for updating:\n", "Use tf.where in 2.0, which has the same broadcast rule as np.where\n" ] } ], "source": [ "import json\n", "from keras.models import load_model\n", "\n", "SaveMode = False\n", "LoadMode = True\n", "\n", "# lr = 0.1, too large, not train model, even 0.02 is bad too\n", "if DataType == \"Toy\":\n", " SaveMode = True\n", " ModelName = 'model_Toy_Test' # will be done by you for scale = 1 and is Trained on 50% data\n", "else:\n", " # default model for CMS\n", " ModelName = 'model_Sig1_noIS_noL1_Bkg1_2HLmod_CrossEntropy_f1loss_batchSize8192_adamLr0p005_PCA23' # 300 Ephoch\n", "\n", "FileModelName = 'TrainedModels/' + ModelName\n", "\n", "if SaveMode:\n", " #save model:\n", " model.save(FileModelName + '.h5')\n", " # save history:\n", " with open(FileModelName + '.json', 'w') as f:\n", " json.dump(history.history, f)\n", "\n", " # plot model only in SaveMode\n", " # python 3.4 and about only for redirect_stdout\n", " from contextlib import redirect_stdout\n", " NameSum = 'Results/' + ModelName + '_summary.txt'\n", " with open(NameSum, 'w') as f:\n", " with redirect_stdout(f):\n", " model.summary()\n", "# # plot model:\n", "# from keras.utils import plot_model\n", "# plot_model(model, to_file = 'Results/' + ModelName + '.pdf',show_shapes = True)\n", "\n", "# del model\n", "# del history\n", "\n", "FileLoadName = 'TrainedModels/' + ModelName\n", "\n", "# returns a compiled and trained model\n", "f1lossMode = \"f1loss\" in ModelName\n", "if LoadMode : \n", " if f1lossMode:\n", " model_X = load_model(FileLoadName + '.h5', \n", " custom_objects={'f1_loss':f1_loss, 'f1_score':f1_score, \n", " 'precision':precision, 'recall':recall})\n", " history_X = json.load(open(FileLoadName + '.json', 'r'))\n", " else:\n", " model_X = load_model(FileLoadName + '.h5', custom_objects={'f1_score':f1_score, 'precision':precision, 'recall':recall})\n", " history_X = json.load(open(FileLoadName + '.json', 'r'))\n", "\n", "if LoadMode == False:\n", " model_X = model\n", " history_X = history.history" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Monitor performance during training \n", "[jump to top](#Top)\n", "\n", "Monitor Test and Train loss distributions during model training." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#CMS_state = \"Preliminary\"\n", "\n", "def historyModel(px, ParName):\n", " xpos, ypos = 0.61, 0.82 # under data\n", " px.text(0.02,0.9,labelData, size = 15, transform=px.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "\n", " b, t = px.get_ylim()\n", " px.set_ylim(top = 0.2 * (t-b)+t)\n", " SetCMSlabel(px)\n", " px.set_ylabel(ParName)\n", " px.set_xlabel('epoch')\n", " px.legend(['train', 'test'], loc='center right')\n", " \n", " return\n", "\n", "plt.rc('legend', fontsize=15) \n", "# list all data in history\n", "logger.debug(history_X.keys())\n", "# summarize history for accuracy\n", "\n", "# set epoch range\n", "par_acc = np.array(history_X['acc'])\n", "logger.debug(\"shape acc = \" + str(par_acc.shape))\n", "par_val_acc = np.array(history_X['val_acc'])\n", "par_loss = np.array(history_X['loss'])\n", "par_val_loss = np.array(history_X['val_loss'])\n", "par_f1_score = np.array(history_X['f1_score'])\n", "par_val_f1_score = np.array(history_X['val_f1_score'])\n", "par_precision = np.array(history_X['precision'])\n", "par_val_precision = np.array(history_X['val_precision'])\n", "par_recall = np.array(history_X['recall'])\n", "par_val_recall = np.array(history_X['val_recall'])\n", "\n", "nEpoch_min = 10\n", "if DataType == \"Toy\":\n", " nEpoch_min = 10\n", "nEpoch_max = par_acc.shape[0]\n", "xc = range(nEpoch_min,nEpoch_max)\n", "\n", "fig, (a_loss) = plt.subplots(1,1, figsize=(6,6)) \n", "\n", "# summarize history for loss\n", "a_loss.plot(xc,par_loss[nEpoch_min:nEpoch_max])\n", "a_loss.plot(xc,par_val_loss[nEpoch_min:nEpoch_max])\n", "\n", "historyModel(a_loss, 'model loss')\n", "\n", "fig.tight_layout()\n", "#fig.tight_layout(pad=1.0)\n", "plt.savefig('Results/' + ModelName + '_history.pdf')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Test and Train loss distributions are very close and are decreasing during training, which shows that model is not over/under trained.\n", "\n", "## Model results \n", "[jump to top](#Top)\n", "\n", "Use all NI candidates (Signal, Background, and Unclassified regions) for Train and Test sets, as discussed [this section](#FinalClassification).\n", "\n", "### Predict the probability distribution of NN classes for Train and Test sets\n", "\n", "Prediction is done for all regions for the data set, including unclassified region.\n", "\n", "The trained model has 2 classes: signal (class 0) and background (class 1), that is why the probability distribution of NN classes should satisfy:\n", "\n", "$p_{Signal} + p_{Background} = 1$." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "p_hot_Test_pred = model_X.predict(Xnorm_Test_PCA)\n", "p_hot_Train_pred = model_X.predict(Xnorm_Train_PCA)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The probability distribution for injected vertex to be a signal \n", "[jump to top](#Top)\n", "\n", "The probability distribution, $p_{Signal}$, for injected vertex to be a signal for Test set is presented." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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emZ1tZo8QzM69WkFTdjUezCS/DRhoFfS2YgTHYzcQ56mDgHqcIrGE1+x9iWAI6j53j+ciFCJSAShwioiIJEBDtSIiIgnQ6ShAgwYNvGXLlmXdDBERSSLz5s373d0bRqcrcAItW7Zk7ty5Zd0MERFJIma2NFa6hmpFREQSoMApIiKSAAVOERGRBChwioiIJECBU0REJAEKnCIiIgnQ6SgiO9H69etJT09n69atZd0UkQqratWqNGrUiNq1axeeOQYFTpGdZP369fz22280bdqU6tWrE9w7V0R2Jndn06ZN/PLLLwBFCp4aqhXZSdLT02natCk1atRQ0BQpI2ZGjRo1aNq0Kenp6UWqQ4FTZCfZunUr1atXL+tmiAhQvXr1Ih8yUeAU2YnU0xRJDsX5LipwioiIJECBU0TiNmzYMMwMM6NSpUrUrVuXQw45hNtuu41ff/21SHWOHDmS9957r0Tat379eoYOHcqhhx5KnTp1aNy4MX379uWHH37YIe8vv/xC3759SUtLo0GDBgwZMoSMjIw8eSZNmsRpp51GkyZNMDMmTJgQc7szZszgiCOOoE6dOuy+++707duXBQsWFOk9mFlCn8eSJUswM5YsWVKk7SXinXfe4ayzzqJFixbUqFGDjh078sgjj5CdnZ0nX7du3XL/TyKXzMzMUm/jzqBZtSJlbOCET8tku2MHHFKkcnXq1GH69OkArFu3js8++4zHH3+cMWPGMH36dA4++OCE6hs5ciRDhgyhW7duRWpPpGXLlvHkk08ycOBAhg8fTkZGBiNGjOCwww7jq6++onnz5gBkZWVxwgknkJKSwqRJk1i7di3XXnsta9eu5dlnn82t7+WXX2bJkiWccsopPPXUUzG3OW/ePE4++WT69OnD0KFD2bBhA3feeSc9evTgm2++KfIpD8lozJgxZGRk8K9//YvmzZvzwQcfcN1117F48WLuu+++PHmPPfZY7rrrrjxpqampO7O5pUaBU0QSUqVKFbp06ZL7+oQTTuDyyy/n6KOP5qyzzmLBggVUrly5TNrWqlUrFi1alGcS1lFHHcWee+7JuHHjGDp0KAAvvfQS3333HQsXLqRVq1ZAcG5f//79GTp0KG3btgWCHmelSpX4888/8w2cL730EvXq1eP555+nSpXgJ7Vt27Z06tSJDz/8kBNPPLE033KJ+umnn9hrr73yXf/YY4/RoEGD3NfdunUjIyODBx54gLvuuitPYKxXr16e/5NdiYZqRaTYdtttN0aOHMmiRYuYMWNGbvrNN9/MfvvtR1paGs2aNePcc8/NM6TbsmVLVq9ezR133JE7nJczTHnfffdxyCGH5A5/9urVi4ULFxbYjpo1a+4wc7levXq0aNEiz6kH06ZN45BDDskNmgB9+vQhJSUltzcNUKlS4T+RW7dupUaNGrlBM+fzgOCcweKKNeRZ0LBxotLT07n33nvZZ599uPjiiwvMGxk0cxx44IFkZmayfv36EmnPK6+8wqGHHkr16tWpX78+J510EkuXBrfFHDZsGA0aNODjjz+mc+fOVK9enSOPPJLFixeTnp5Onz59SEtLY5999mHmzJkl0p5YFDhFpEQce+yxVKlShTlz5uSmpaenc+utt/LGG28wevRofvrpJ4477rjcY2KvvPIKderUYeDAgcyePZvZs2dz0EEHAbB8+XKGDBnClClTePLJJ8nOzuaII45g3bp1CbVr1apVLFy4kA4dOuSmff/997Rv3z5PvpSUFFq3bs3333+fUP3nnXceK1as4J577mHNmjX8/PPPXHvttbRv357u3bsnVFcsOZ9LznLFFVdgZrRp06bIdW7bto1p06Zx+umn06xZM+6++2569OjBww8/nHBdH330EQ0aNKBhw4Z50t9++21q1KhBjRo1OOGEE/jqq68KrWvixImcdtpptG7dmsmTJzN+/Hj23ntvVq1alZsnIyODQYMGcc011/DCCy+wbNkyzj//fM4++2yOPPJI/vvf/9K0aVP69eu3wzHrkqKhWhEpEampqTRo0IDffvstN23cuHG5z7Ozs+natSvNmjXjww8/5Oijj+bAAw+kSpUqNGvWbIdhvQceeCBP2R49etCoUSOmTJnCBRdcEHe7rrvuOtLS0ujfv39u2po1a3J7hZHq1q3LmjVr4q4bgh7X66+/Tr9+/bj55psBaN++PW+99VaJHNOL/Fw+++wznnzySYYOHcqRRx6ZcF2LFy9m/PjxjB8/npUrV9KjRw+ee+45evfuTUpKSsL1zZ8/nyeeeIKbbropT/oxxxzDhRdeSJs2bVi6dCnDhw/nqKOO4ssvv6Rly5Yx69q2bRs333wzffv25YUXXshNP/XUU/Pk27RpEw899BDHHHMMACtWrGDw4MHccccdXH/99QA0a9aMfffdl/fff79UhsrV4xSREhM9NDlt2jQOP/xw6tSpkxsggZizXKPNmTOHHj16UL9+fapUqUKNGjX4888/4yqb4/HHH+fZZ5/lqaeeon79+nnWxTqPz90TPr/v22+/5ZxzzuG0007jnXfeYcqUKdStW5eTTjqpxIYvIeg59+3bl+OPP55//OMfCZcfOnQorVu35oUXXuDyyy9n6dKlTJs2jX79+hUpaK5Zs4bTTz+d/fffn1tvvTXPujvuuIOLLrqIo446ivPOO49Zs2ZhZowePTrf+hYsWMCKFSu46KKLCtxuSkoKRx11VO7rnJ73cccdt0NazmX1SpoCp4iUiMzMTFavXs3uu+8OwKeffsqpp55Ks2bNmDhxIrNnz84dxi3stIRly5bxl7/8BXfn3//+Nx9++CGffvopjRo1ivuUhqlTp3LFFVdwzz330Ldv3zzr6taty9q1a3cos3bt2pg90YLcfvvttG3blrFjx9K9e3dOPfVU3njjDRYvXpzvhKJEZWVlceaZZ5KSksKzzz5bpJP309LSqFq1Khs3bmTdunXFCuqZmZn07t2bzZs3M3Xq1EIDb+PGjTniiCP47LPP8s2zevVqAJo0aVJgXbVq1cpz7Dln25F/t5y00jr9RUO1IlIiZs2aRVZWFl27dgWC45cNGzZk0qRJuT/0OZM8CjN9+nQyMjKYMmUKNWvWBILg8ccff8RV/qOPPqJ///5cdtll3HDDDTusb9++/Q7HMrds2cJPP/3EZZddFtc2cnz//fcce+yxedLq1q1LixYtWLRoUUJ15ef666/n008/Zc6cOdSpU6dIddxwww1cfPHFPPPMM4wdO5aRI0fSpUsXLrroIs4666y4683Ozuacc87h22+/5aOPPsrdUYpHQQE/Z0Rg5cqVcddXVtTjFJFiW7t2LTfddBNt2rTh+OOPB4JjUVWrVs3zY/ncc8/tUDYlJWWHnsGmTZuoVKlSnpmqkydPJisrq9C2fPvtt5xyyin07NmThx56KGaeE088kU8//TRPIJ86dSqbN2+mZ8+ehW4jUosWLfj888/zpK1evZolS5bkezwvERMnTuTBBx9k7NixdOzYsVh11a9fn2uuuYZvvvmG2bNns++++3LdddfRpEkTzjvvPD744INC6/jb3/7G9OnTee2112jXrl1c2/3tt9/48MMPCzzHt127djRt2pSnn3467vdTVtTjFJGEZGVl5Q65btiwgXnz5vH444+TkZHB9OnTc8/h7NGjB6NHj+bqq6+mV69efPTRR3kuLpCjffv2vPHGG/Ts2ZO0tDTatWuXO/P2oosuYuDAgXz77bfce++9hQ6jpqen59Zz5ZVX8sknn+Suq127du7M2jPOOIPhw4dz2mmn8c9//pN169ZxzTXXcM455+SewwnB5Jf58+fnBva5c+eSlpZGw4YNcyenXHbZZfTp04cBAwZw9tlns3HjRu655x5SUlI499xzc+saMGAA7733XkJX+Fm0aBGDBg3ixBNPpEWLFnlmLLdu3XqHmayJ6NKlC126dGH06NG8+OKLPPXUU9x+++3MmjUr3zJ33XUXY8aM4ZZbbqFSpUp52tOhQwdq167NV199xS233EK/fv1o0aIFy5YtY8SIEVSqVImrr74637orVarEyJEjOffcczn33HM5++yzMTNmzpzJ2WefTefOnYv8XkvaTg2cZjYOOAVId/eOEelXAEOALOANd78xTL8FGAhkA1e6+1th+sHABKA68CZwlbu7maUCzwAHA6uBs9x9yc55dyIVw7p16+jatStmRu3atWnTpg3nnXceV1xxBY0bN87Nd9JJJ3HPPffw8MMP8+STT9K1a1def/119t577zz1jRo1isGDB3PyySeTkZHBrFmz6NatG+PHj+eOO+7glVdeoVOnTrz00kucddZZBbZt/vz5LF++HGCH4dNjjjkm9xzRqlWrMn36dIYMGcKZZ55Jamoq/fv3Z9SoUXnKTJ48mTvuuCP39aOPPsqjjz6ap67evXszadIkRo0aRb9+/ahWrRqdO3fmvffeY4899sgtm5GRQaNGjeL7kEM///wzmZmZTJs2jWnTpuVZN378eAYMGJBQfbGkpaVxySWXcMkll+SZER3L22+/DcCIESMYMWJEnnU5f7f69evj7txyyy2sXr2aWrVq0a1bN1599VX23HPPAus/55xzqFatGsOHD+eMM86gZs2adOnSpVg7CKXC3XfaAhwNHAR8E5F2LPAOkBq+bhQ+dgC+BFKBVsAioHK47hOgK2DANODEMP1vwBPh8/7ApHjadfDBB7tIaZs/f35ZN0HK0J577ukTJkwoNB/gs2bNirvexYsXO+CLFy8ueuMqqMK+k8BcjxEzduoxTnf/HxB9dP9y4G533xzmybm8R2/gRXff7O6LgYXAoWbWBKjt7rPDN/YM0CeiTM4A+ctAd9N9nESkjK1YsYKtW7dy9tlnl3VTpAQkw+SgvYGjzOxjM3vfzHKuPN0U+Dki3/IwrWn4PDo9Txl3zwLWAXlP3hIR2cn22GMPVqxYUaTzJSX5JMPkoCpAXaALcAgw2cz2IhiGjeYFpFPIujzMbBAwCCh03F1ERCRHMgTO5cB/w2HXT8xsG9AgTG8eka8ZsCJMbxYjnYgyy82sClCHHYeGAXD3McAYgM6dOxf/SswiIiXAE7wwfMuWLUvkYvISv2QYqn0VOA7AzPYGUoDfgalAfzNLNbNWQFvgE3dfCWwwsy7h8csLgClhXVOBC8PnZwAzXf9RIiJSgnb26SgvAN2ABma2HBgKjAPGmdk3wBbgwjDYfWtmk4H5BKepDHb3nNuMX87201GmhQvAWGCimS0k6Gluv6qziIhICdipgdPd85tSdl4++YcDw2OkzwV2uISGu2cC/YrTRpHS5EW4iLiIlLziDEYmw1CtSIVQtWpVNm3aVNbNEBG2XxKyKBQ4RXaSRo0a8csvv5CRkaHJHCJlxN3JyMjgl19+SfhKTjmSYVatSIVQu3ZtYPvJ8CJSNqpWrcruu++e+51MlAKnyE5Uu3btIn9ZRSQ5aKhWREQkAQqcIiIiCVDgFBERSYACp4iISAIUOEVERBKgwCkiIpIABU4REZEEKHCKiIgkQIFTREQkAQqcIiIiCVDgFBERSYACp4iISAIUOEVERBKgwCkiIpIABU4REZEEKHCKiIgkQIGznBg2dRj2V8tdagyuwX7D9mPM/8aU+La6jerGGY+fUeL1JpvXv3wd+6ux5PclZd0UkZ3imwkTmHjwwTxYqxYP163LMwceyKxrr81dv27JEu41Y9Hrr5dpG+81Y8uff5ZZGwpTpawbIPGrU70O06+aDsDGLRt57cvXuHTipaSlpnHOYeeUcetEJJl9PGIEH9x+O4feeCNH3X032ZmZ/DpvHt89+yzH3n8/ADWbNOGc2bOp1759Gbc2uSlwliNVKlehS+suua+779OdjxZ9xKufv1puAmfm1kyqVa1W1s0QqXA+f+QROl16KUfddVduWutevTh86NDc11VSU9mjS5dYxSWChmrLuVrVarE1eysAGzdvZMjzQ2j393bUGFyDVje3YvBzg1m/aX2eMtnbshnx5gj2vm1vUi9PpdkNzRgwbkC+21iXsY4j7j6CTnd0YtWGVQCs2biG/mP6U3NwTfa4fg/umXYP1790PS1vbplbbsKHE7C/Gp8s/oRuo7pR/W/VGfXWKAB+3/A7F467kDg+ZEMAACAASURBVPpX16fG4Bp0G9WNuUvm5tmu/dV4ZOYjedKGTR1Gg2sa7LCNr5d/TY/7e1BzcE3a396e/3723zzl3J1hU4fR6NpG1BpSiwvGXsD6zLyfi8iuLHPtWmo2brxDupnlPo81VJu1eTMzLr+ch3fbjUfq1+e9G25g3ujR3BtRbtl773GvGcvee4+p/frxYFoaT+61F58/9lieba2YPZtXTj2Vx/fYg9E1a/L0AQcw/7nnSuHdli4FznImKzuLrOws1m9az7NznuX9H96n74F9AcjYkkH2tmyG9x3OtCun8c8+/2Tm9zPp90S/PHVcOvFShk4dypmdz+T1K17nvjPvY+OWjTG398fGPzj+/uPZkrWFWdfPomGthgAMGD+AGfNn8GD/Bxlz/hjenv82kz6dFLOOs588m1P2P4U3r3yTU/Y/BYA+j/XhrW/f4t5+9zJp0CS2+TaOvfdYFqYvLNLncs5T53Bqp1N55W+v0LZRW/qP6c/yP5bnrn/o3Ye48/U7GXTUIF6+7GWqp1TnxpdvLNK2RMqj3Q86iM8efphvnn6aTatXx13ufzfeyLcTJtB16FBOfu45Nixbxtz77ouZ9+2//pWGnTrR+5VXaN6tG+8OHszKTz7JXb9+6VL2OOIITnjqKU577TX2Pv10pl90Ed+98EKx399O5e4Vfjn44IM92Q2dMtS5hB2WK1+4Mt8yW7O2+gc/fuBcgi/9fam7u3+34jvnEvzBdx7Mt9wxI4/x0x873dPXp/v+w/b3w0cc7usy1uWu/3r5184l+ORPJ+emZWzO8PpX1/cWN7XITRv/wXjnEnz0jNF56p/29TTnEvy979/LTfsz809vcHUDH/TMoNw0LsEffvfhHT6H+lfX32EbY/9vbG7a7xt+98qDKvvjsx53d/es7Cxvcl0Tv2ziZXnqOv6+451L8MWrFuf7WYjsKtK//NLHtGrlo8BHmfm4Dh38/26/3TPXbf9ur1282EeBL3ztNXd3z/j9d3+gWjX/eOTI3Dzbtm3zcR06+CjITVs6a5aPAv+/22/PTcvassUfadDA37/pppjt2bZtm2dv3epvDRrkLx57bG761+PH+yjwzRs2lNh7LypgrseIGTrGWY7UqV6Hd659B4DNWZuZt3Qe/5jyD+rVqMfQU4PjFBNnT+T+GffzY/qPbNy8vRf5w28/sGf9PZm1YBYAAw4fUOC2flv/G8eMOobGtRvz2hWvUTO1Zu66nCHVXp165aZVT6nO8fscz5yf5uxQ18n7n5zn9SeLP6FhrYYc0+6Y3LSaqTU5Zf9T+ODHD+L5KHbwlw5/yX1eP60+jWo1YvmaoMf58x8/s3LdSnof0DtPmdMOOo13vnunSNsTKW8a7r8/F333HUvffpvFb73FspkzmfPPf7LgxRc5/7PPSElL26HMqq+/JiszkzannpqbZma07tWL1fPn75C/5V+2fw8rV61K3bZt2bB8+8hP5po1fDh0KAunTOHPX37Bs7MBSGvatCTfaqlT4CxHqlSuQueWnXNfH9HmCLZmb+XWV27liu5X8P6C97lg3AVc3u1y7up7F/Vq1mPlupX0fawvmVszAVj952pqptakdvXaBW5r/sr5/LHxD2444YY8QRPg1/W/UqtarR0m+TRMaxizrt1r757n9cp1K3dIy8n3R8YfBbYrP7vV2C3P65QqKWRmBe/513W/AtCoVqM8eaJfi+zqqqSm0rpXL1r3CnZ6vx47lrcuuYSvx47l4Kuu2iF/xq/Bd6d6w7zf7ejXOVJ3y/s9rJSSQlZmZu7raQMGsHLOHLrcfjsNOnQgpXZtvnj8cRZNmVKs97WzKXCWcx2adGBL1hYWpS/ipXkvcVirw3js3O0H5N9f8H6e/PXT6rNx80bWb1pfYPA8tt2xHLjngQyaOIgGaQ3y9C4b127MhswNO8yQXfXnqph1GZbndZM6TUhfn75Dvt/W/0a9GvVyX6dWSWVL1pY8ef7YmHhgbVwnmBCRviHvNqNfi1Q0+w0cyPs33sgf338fc32NcDLRplWrqF5v+3dz06rY3/WCZGVm8tMbb9D9kUc44LLLctN927aE6yprmhxUzn2z4hsAmtdrzqYtm0itmppn/XMf552xdlz74wB4ZvYzhdZ928m3cV2P6+j3RD9mfjczNz2n1zv1i6m5aZu2bGLG/BlxtfmwVoeRviGd//3wv9y0jM0ZvPH1GxzZ9sjctGZ1m/Hdr9/lvt62bRszv59JoprXa07jOo2Z8kXevdrombciu7KN6TvuKGasWsXmdeuosfuOI0AADffbjyrVqrEwokfo7ix67bWEt5+9eTOenU3l1O2/UVs2bGDR1KkFlEpO6nGWI1nZWcxZFBxD3JK9hXlL5/GvN/5F7wN607hOY3p06MHg5wcz/I3hHNbqMN78+k3e/f7dPHW0a9yOQUcP4rqXriN9QzpHtz2atZvW8vK8l3lx0Is7bPPu0+9mQ+YGej/amxnXzKBL6y50bNqRXp16cflzl7MhcwON6zTm/hn3UyOlBpWs8H2xEzqewBFtjuCsMWdx92l3U79mfe59+142bdnEDSfckJuv74F9efS9Rzmw+YHs1XAvnvq/p4p0CknlSpW58YQbuf6l62mQ1oCj2h7Ffz77D9+t/K7wwiK7iKf32482vXvT4i9/oUajRqxfupS5995L1Ro12PfCC2OWqV6/Pvv99a98NHQolapWpf4++/DN+PFsWb8ezGKWyU9qnTo0PuQQZt95J6m1a2OVKvHx3XeTWqdOUF85osBZjqzbtI6ud3cFoGrlqrSo34LLjr6Mv5/ydwAuPeZSfvr9Jx5890Eyt2bSo0MPnr/kebqMyHtC82PnPkaLei146oOnuHva3TSq1YgeHXrku91HznmEjZs3cuJDJ/Le9e/RqXknJlw0gcufvZwrX7yStNQ0Bh87mL0a7sWniz+N67288rdXuG7ydVw96Woyt2ZyaKtDmXndTNo0apObZ2ivoaRvSOfvr/6dlCopDDl2CB2bduSRWY8UUHNsVx9/NX9s/IMn3n+C0e+M5tROpzLyjJGc+9S5CdclUh51/cc/WDhlCjOvvJLMP/6gZuPG7HH44ZwyaRK7tWqVb7ljRo5k29atfDRsGFapEh3OP5+OAwfy2ejRCbfh5Oef5+1Bg3jzgguoXr8+Bw4ZwtaMDL54JPHvdFmyYMZtxda5c2efO3du4RklX1nZWXQc1pHDWh3G0xc/XdbNEZFSNPn449m2dSv933+/8MzlmJnNc/fO0enqcUqRvDT3JVasXcF+TfdjfeZ6nvy/J/nxtx955uLCj52KSPmxbNYsVn78MbsfdBDZW7eyYNIklr37Lr1eeqmsm1ZmFDilSGqm1mT8h+NZuGoh2duy2a/pfrx2xWsc2urQsm6aiJSgqmlpLHz1VT4eMYLszEx2a9uWnhMm0O6MXf8OSvnZqUO1ZjYOOAVId/eOUeuuB0YBDd399zDtFmAgkA1c6e5vhekHAxOA6sCbwFXu7maWCjwDHAysBs5y9yWFtUtDtSIiEi2/odqdfTrKBKBndKKZNQd6AMsi0joA/YF9wzKPmVnlcPXjwCCgbbjk1DkQWOPubYAHgHtK5V2IiEiFtVMDp7v/D4h1BvsDwI1AZPe3N/Ciu29298XAQuBQM2sC1Hb32eG1BJ8B+kSUyZmZ8jLQ3SzBOdMiIiIFKPMLIJjZqcAv7v5l1KqmwM8Rr5eHaU3D59Hpecq4exawDqhfCs0WEZEKqkwnB5lZDeA24C+xVsdI8wLSCyoTa9uDCIZ72XPPPQttq4iICJR9j7M10Ar40syWAM2Az8ysMUFPsnlE3mbAijC9WYx0IsuYWRWgDrGHhnH3Me7e2d07N8zngsUiIiLRyjRwuvvX7t7I3Vu6e0uCwHeQu/8KTAX6m1mqmbUimAT0ibuvBDaYWZfw+OUFQM6FFKcCOdeOOgOY6brCg4iIlKCdGjjN7AVgNtDOzJab2cD88rr7t8BkYD4wHRjs7tnh6suBpwgmDC0CpoXpY4H6ZrYQuBa4uVTeiIiIVFi65B46j1NERHaULOdxioiIlGu65J6IiCSlgRO2321p7IBDyrAleanHKSIikgAFThERkQQocIqIiCRAgVNERCQBCpwiIiIJUOAUERFJgAKniIhIAhQ4RUREEqDAKSIikgAFThERkQTokntS5iIvqwXJdWktEZFoCpySdJL1+pQiIqDAKSIi5UAyjUzpGKeIiEgCFDhFREQSoKFa2emih1xERMoT9ThFREQSoB6nJLVkmhAgIgIKnLKTaHhWRHYVGqoVERFJgAKniIhIAhQ4RUREEqDAKSIikgAFThERkQQocIqIiCRAgVNERCQBCpwiIiIJUOAUERFJgAKniIhIAhQ4RUREEqDAKSIikgBd5F3KlciLxetOKSJSFhQ4pVTobigisqvaqUO1ZjbOzNLN7JuItFFm9r2ZfWVmr5jZbhHrbjGzhWa2wMxOiEg/2My+Dtc9ZGYWpqea2aQw/WMza7kz35+IiOz6dvYxzglAz6i0GUBHd98f+AG4BcDMOgD9gX3DMo+ZWeWwzOPAIKBtuOTUORBY4+5tgAeAe0rtnUiZGzjh0zyLiMjOsFOHat39f9G9QHd/O+LlHOCM8Hlv4EV33wwsNrOFwKFmtgSo7e6zAczsGaAPMC0sMyws/zLwiJmZu3upvCERESkx5WUHONlm1V5MEAABmgI/R6xbHqY1DZ9Hp+cp4+5ZwDqgfim2V0REKpikCZxmdhuQBTyXkxQjmxeQXlCZWNsbZGZzzWzuqlWrEm2uiIhUUEkxq9bMLgROAbpHDKsuB5pHZGsGrAjTm8VIjyyz3MyqAHWAP2Jt093HAGMAOnfurKHcElBehllERIqjzHucZtYTuAk41d0zIlZNBfqHM2VbEUwC+sTdVwIbzKxLOJv2AmBKRJkLw+dnADN1fFNERErSTu1xmtkLQDeggZktB4YSzKJNBWaEZ5XMcffL3P1bM5sMzCcYwh3s7tlhVZcTzNCtTnBMNOe46FhgYjiR6A+CWbkiIiIlZmfPqj07RvLYAvIPB4bHSJ8LdIyRngn0K04bpfzSVYVEZGco86FaERGR8kSBU0REJAEKnCIiIglQ4BQREUmAAqeIiEgCFDhFREQSoMApIiKSAAVOERGRBChwioiIJECBU0REJAEKnCIiIglIituKiZS06Fuc6dq1IlJS1OMUERFJgAKniIhIAhQ4RUREEqDAKSIikgAFThERkQQocIqIiCRAp6NIkUWf8iEiUhEocEqFEBnkdU6niBSHhmpFREQSUKQep5mlAA2BasAf7r6mRFslIiIVQnk85BN34DSzfYELgOOB/YDKEetWAx8BLwP/cfdNJdxOERGRpFBo4DSzI4B/AUcDnwLvAw8BvwObgd2AlkBn4AHgYTO7H3jA3f8snWaLFJ2uYysixRFPj/O/BIHyfHdfXlBGM6tM0CO9Okz6Z/GaJyIiklziCZwt3D0znsrcPRt4C3jLzKoVq2UiIiJJqNBZtfEGzZIqJyIiksxK7HQUM6tvZkeXVH0iIiLJqCTP4+wGzCrB+kRERJKOLoAgIiKSgHhOR/kpzrpqFLMtIiIiSS+eWbVNgc+B/ysk397AKcVukYiISBKLJ3B+Afzq7jcUlMnMTkeBU0REdnHxHOP8GDgszvqsGG0RERFJevEEzjuBnoVlcvf/uLsmG4mIyC4tngsg/O7uX5bExsxsnJmlm9k3EWn1zGyGmf0YPtaNWHeLmS00swVmdkJE+sFm9nW47iEzszA91cwmhekfm1nLkmi37NoGTvg0dxERKUzCPcTwQgdtzKy1mdVPsPgEduy93gy86+5tgXfD15hZB6A/sG9Y5rHwWrgAjwODgLbhklPnQGCNu7chuOD8PQm2T0REpEBxBU4z62Bmz5jZKiAdWAD8AKSb2SozezoMdAVy9/8Bf0Ql9waeDp8/DfSJSH/R3Te7+2JgIXComTUBarv7bHd34JmoMjl1vQx0z+mNioiIlIR4zuM8DnidIHA9BHwHrCGYCLQb0B7oB3xqZie7+3sJtmF3d18J4O4rzaxRmN4UmBORb3mYtjV8Hp2eU+bnsK4sM1sH1Ce4BZqIiEixxXM6ykjgJWBA2MPbgZkNB8YD9xLcl7MkxOopegHpBZXZsXKzQQTDvey5555FaZ+IiFRA8QzV7guMyy9oAoTrJoR5E/VbOPxK+Jgepi8HmkfkawasCNObxUjPU8bMqgB12HFoOKfNY9y9s7t3btiwYRGaLSIiFVE8Pc6fgSOA9wvJd0SYN1FTgQuBu8PHKRHpz5vZ/cAeBJOAPnH3bDPbYGZdCM4xvQB4OKqu2cAZwMyCAr5ItOiZtWMHHFJGLRGRZBVP4BwFPG5mrQiGbL8H1hIMgUYe47wIuKygiszsBYK7qDQws+XAUIKAOdnMBgLLwrpw92/NbDIwH8gCBoc3yga4nKCHWx2YFi4AY4GJZraQoKfZP473JyIiErdCA6e7P2lmG4BhBKd7RPfgjGCG7fnu/mIhdZ2dz6ru+eQfDgyPkT4X6BgjPZMw8IqIiJSGeHqchAHxxbDX2R7IuUjBGuD78HQRqQB0kQARqejiCpw5wgCpICkiIkWyK+x869qyIiIiCSixwGlmW80sq6TqExERSUYJDdUW4p/otmKyi9HpKSISrcQCp7vfWVJ1iYiIJCsd4xQREUlAXD1OM0sBzgNOZPvpKE5wIYTvgTeB59x9Sym1U0REJCnEc3eUFsAMoAXwAcGl96LvjvIEcJOZneDuS0uvuSIiImUrnh7nowSXr+vm7itiZTCzPYD/AI8AvUqueSIiIsklnsDZDTg9v6AJ4O4rzOwOgmvZiuyyImfZaoatSMUUz+SgjUCDOPI1ADKK1xwREZHkFk+P81lgtJkBvOLueYKjmVUH+gL3A8+UeAtFRESSSDyB8xYgjeA2XuPD24FF3lasOcFEobFhXhERkV1WPLcV2wJcamZ3AicA7Yi6Owrwtrv/UmqtFBERSRJxXzkoDIzjSrEtIiKyC9oV7ogSqdDJQWaWVpSKzaxWUcqJiIgks3hm1S4zs3+ZWevCMppZqpmdbmb/A64ufvNERESSSzxDtT0I7nxyq5l9CXwEfAP8DmwmmCDUCjgYOAbYBNxLcDEEERGRXUo8k4PmASeZWVvgAqA7cDGQGpFtGfBhmD7V3beWQltFRETKXCKTg34Ebg8XzKwuUA1YrYu7i4hIRRHPRd5HAK8Ds919W066u68pzYZJctjVZsOVJN3kWqRiimdyUCeCu6OsMrPnzexcM6tfyu0SERFJSoUGTnc/CagHXEhwxaDhwK9m9qGZ3WpmnUq5jSIiIkkjnh4n7p7p7q+7+9/cvSVwEDAV6AnMNbOfzezfZnaqmdUoxfaKiIiUqbgnB0Vy96+Br4F7wklCPYGTCK5XmwZUL7EWiohIubKrz40oUuCMFE4SegF4wYJbqHQpdqtERESSVEKB08yOAuq5+5TwdQPgIaAD8C5ws7vPLvFWipQDusm1SMWQaI9zJMGpKVPC1w8SXBDhFWAAwZWEbi2pxomUVzpVRWTXFdfkoAjtgHkA4SSgvsBV7n4ZcCNwVsk2T0REJLkkGjhTgMzw+REEPdY3wtc/AE1KqF0iIiJJKdHA+T3BDFqAcwmuJrQhfL0H8EdJNUxERCQZJXqM807gJTMbCNQBekes6wl8XlINExERSUYJBU53n2pm+wAHAl+7+w8Rq2cDX5Vk40RERJJNwudxuvtPwE8x0seUSItERKRc2dUveBAt0WOcmNn+ZjbJzBaZ2WYzOyhMH25mJxa1IWZ2jZl9a2bfmNkLZlbNzOqZ2Qwz+zF8rBuR/xYzW2hmC8zshIj0g83s63DdQ+FFGUREREpEQoEzDIzzgMbAM0DViNWbgSuK0ggzawpcCXR2945AZaA/cDPwrru3JbzAQpi/Q7h+X4Jjq4+ZWeWwuseBQUDbcOmJiIhICUm0xzkCmODuxxDcJSXSF8ABxWhLFaC6mVUBagArCCYfPR2ufxroEz7vDbzo7pvdfTGwEDjUzJoAtd19trs7QXDvg4iISAlJ9Bhne+D68LlHrVtPcPuxhLn7L2Z2L7AM2AS87e5vm9nu7r4yzLPSzBqFRZoCcyKqWB6mbQ2fR6eLlKmCjgHpqkIi5UuiPc50YK981u1LEPgSFh677A20IjgftKaZnVdQkRhpXkB6rG0OMrO5ZjZ31apViTZZREQqqEQD54vAnWZ2ZESam9newE3Ac0Vsx/HAYndf5e5bgf8ChwO/hcOvhI/pYf7lQPOI8s0IhnaXh8+j03fg7mPcvbO7d27YsGERmy0iIhVNooHzdmAu8D7be5dTgG8IzuG8q4jtWAZ0MbMa4SzY7sB3BDfLvjDMcyHbLy4/FehvZqlm1opgEtAn4bDuBjPrEtZzQUQZERGRYkv0AgibgVPMrDtBcGtAcJm9d919RlEb4e4fm9nLwGdAFsEViMYQ3BR7cnilomVAvzD/t2Y2GZgf5h/s7tlhdZcDEwhupj0tXEREREpEkW5k7e7vEpweUmLcfSgwNCp5M0GAjpV/ODvO7MXd5wIdS7JtIiIiOQoNnGZWw90zcp4Xlj8nr4iI7Loq2tWCIsXT49xgZl3d/RPgT/KZpRqhciHrRUREyq14AufFwKLw+UWl2BYREZG4RPZ4d/a50IUGTnd/GsDMqhJcoWexu8c8xUN2DRV5CKYslOUPgIgkLpHJQdnATOAk8jk3UkREdk3aod4u7sDp7tvM7Edg91Jsj0iFFv3jpB6oSPJJ9AIItwH/MLP9SqMxIiIiyS7R8zj/DtQHvjCzX4DfiJpl6+6HllDbREREkk6igfNbgsvriYiIVEiJXnJvQCm1Q0REpFxI6BinmY0LL6oea10LMxtXMs0SERFJTokO1Q4AngAWx1jXgOAOJhcXs00iEtIsWylLOgUltkRn1UL+l9zrCOiO0CIiskuL5yLvVwFXhS8deNXMNkdlq0ZwfueEEm2diOShqwyJlL14hmrnA/8BDLgWmAWsjMqzBfgemFyirRMREUky8VyrdgYwA8DMNgBPufsvpd0wERGRZJTo6Sh3lFZDREREyoNEZ9ViZmcApwHNCI5t5qErB4mIlE+aRRufhAKnmQ0D/gF8SXDsc0sptElE4qBTVUTKRqI9zoHA3e5+a2k0RkREJNkleh5nLeDd0miIiIhIeZBoj/NFoCcKniJJR+d4iuwciQbOd4F7zKwBwSkqa6MzuPubJdEwERGRZJRo4JwUPrYkuC5tNAcqF6dBIiIiySzRwBnzzigiklw041ak9BQ6OcjMzjGzegDuvtTdlxL0LH/JeR2mbQXOLd3mioiIlK14epwTga7AJwBmVpngtmKHAJ9F5GsO/BO4q4TbKKVMJz2LiMQvnsBpcaaJiEg5ox3nxBXlfpwiIiIVVsLXqhURkfJLPcziizdwepxpIpKEdHEEkZITb+B8y8yyotLejUpT71VEJAmpl1my4gl2ugeniIhIqNDAqZtXi4iIbKdZtSIiIglImsBpZruZ2ctm9r2ZfWdmXc2snpnNMLMfw8e6EflvMbOFZrbAzE6ISD/YzL4O1z1kZjrnVERESkwyTeh5EJju7meYWQpQA7gVeNfd7zazm4GbgZvMrAPQH9gX2AN4x8z2dvds4HFgEDAHeJPgNmjTdv7bEUlOBU0U0YxbkcIlRY/TzGoDRwNjAdx9i7uvBXoDT4fZngb6hM97Ay+6+2Z3XwwsBA41syZAbXef7e4OPBNRRkREpNiSpce5F7AKGG9mnYB5wFXA7u6+EsDdV5pZozB/U4IeZY7lYdrW8Hl0uojILkt3w9m5kiVwVgEOAq5w94/N7EGCYdn8xDpu6QWk71iB2SCCIV323HPPxForsovSD/CuQedtlq6kGKol6Bkud/ePw9cvEwTS38LhV8LH9Ij8zSPKNwNWhOnNYqTvwN3HuHtnd+/csGHDEnsjIiKya0uKwOnuvwI/m1m7MKk7MB+YClwYpl0ITAmfTwX6m1mqmbUC2gKfhMO6G8ysSzib9oKIMiIiIsWWLEO1AFcAz4Uzan8CLiII7JPNbCCwDOgH4O7fmtlkguCaBQwOZ9QCXA5MAKoTzKbVjFoRESkxSRM43f0LoHOMVd3zyT8cGB4jfS7QsWRbJ1Ix6eLwIjtKiqFaERGR8iJpepwiktw04za5aOZs2VHgFBEpBxQok4eGakVERBKgHmcFpD1XkfJB39XkpMApIkWii8VLRaXAKSKlTqe1yK5EgVNESpyGGGVXpslBIiIiCVCPU0SkDGkYu/xR4BQRSRIa4i4fFDhFZKeq6FcgUnAs/xQ4RURKmYLlrkWBU0TKVDId46vovWGJjwKniCStZAqqIjkUOEUkaRQ0pFmeeoMamt216TxOERGRBKjHKSK7hNIe1lUvUnIocIpIuVTUQJbIkK+CpcSiwCkiuzwFQClJCpwiUqEpqEqiNDlIREQkAepxVhDaq5aKRP/vUprU4xQREUmAAqeIiEgCFDhFREQSoMApIiKSAAVOERGRBChwioiIJECBU0REJAEKnCIiIglQ4BQREUmAAqeIiEgCFDhFREQSoMApIiKSgKQKnGZW2cw+N7PXw9f1zGyGmf0YPtaNyHuLmS00swVmdkJE+sFm9nW47iEzs7J4LyIismtKqsAJXAV8F/H6ZuBdd28LvBu+xsw6AP2BfYGewGNmVjks8zgwCGgbLj13TtNFRKQiSJrAaWbNgJOBpyKSewNPh8+fBvpEpL/o7pvdfTGwEDjUzJoAtd19trs78ExEGRERkWJLpvtxjgZuBGpFpO3u7isB3H2lmTUK05sCcyLyLQ/TtobPo9MrHN2PUESkdCRFj9PMTgHS3X1evEVipHkB6bG2OcjM5prZ3FWrVsW5WRERqeiSInACRwCnmtkS4EXglR5rowAAEnhJREFUODN7FvgtHH4lfEwP8y8HmkeUbwasCNObxUjfgbuPcffO7t65YcOGJfleRERkF5YUgdPdb3H3Zu7ekmDSz0x3Pw+YClwYZrsQmBI+nwr0N7NUM2tFMAnok3BYd4OZdQln014QUUZERKTYkukYZyx3A5PNbCCwDOgH4O7fmtlkYD6QBQx29+ywzOXABKA6MC1cRERESkTSBU53fw94L3y+GuieT77hwPD/b+/Oo+6qyjuOf38ljEZlSIAYoEDFQsJQkCGCDBYsAbTMNMpgWJYsBRGLtoAUSsvCSqEsB6ZSiAFqmZFBpkWRkDBFQgxDCJQIFANBAgmjCRB4+sferxxu7n3fc968d8h9f5+17sp79j3nnufs3Hufu/fZZ5865dOBzZsXoZmZDWYd0VVrZma2vHDiNDMzq8CJ08zMrAInTjMzswqcOM3MzCpw4jQzM6vAidPMzKyCjruO0/rPE7ubmTWfW5xmZmYVOHGamZlV4MRpZmZWgROnmZlZBU6cZmZmFThxmpmZVeDEaWZmVoETp5mZWQVOnGZmZhV45qDlmGcKMjNrPbc4zczMKnDiNDMzq8CJ08zMrAInTjMzswqcOM3MzCpw4jQzM6vAidPMzKwCJ04zM7MKnDjNzMwqcOI0MzOrwInTzMysAidOMzOzCjzJ+3LGE7ubmbWXW5xmZmYVOHGamZlV4MRpZmZWgROnmZlZBR2ROCWtL+luSbMlzZJ0XC5fU9Kdkp7O/65R2OYkSXMkPSVpz0L5ZyU9lp/7iSS145jMzKw7dUTiBJYA342IzYAxwDGSRgEnAndFxCbAXXmZ/Nw4YDQwFjhf0gr5tS4AJgCb5MfYVh6ImZl1t45InBExLyJm5L/fBGYDI4F9gUvzapcC++W/9wWujIh3IuJZYA6wvaQRwCci4oGICOCywjZmZmbLrCMSZ5GkDYGtgWnAOhExD1JyBdbOq40EflfYbG4uG5n/ri03MzMbEB2VOCUNBa4DvhMRb/S2ap2y6KW83r4mSJouafr8+fOrB2tmZoNSxyROSSuSkubPI+L6XPz73P1K/vflXD4XWL+w+XrAi7l8vTrlS4mIiyJi24jYdvjw4QN3IGZm1tU6InHmka+XALMj4pzCUzcBX8t/fw24sVA+TtLKkjYiDQL6de7OfVPSmPyaRxS2MTMzW2adMlftTsDhwGOSZuay7wM/BK6W9HXgeeBggIiYJelq4AnSiNxjIuL9vN03gUnAqsBt+WFmZjYgOiJxRsS91D8/CbB7g23OAM6oUz4d2HzgomsvT+puZtZZOqKr1szMbHnhxGlmZlaBE6eZmVkFTpxmZmYVOHGamZlV0BGjas3MzPqr9uqDS8Zv19T9ucVpZmZWgROnmZlZBU6cZmZmFThxmpmZVeDEaWZmVoETp5mZWQW+HKUDeWJ3M7PO5RanmZlZBU6cZmZmFThxmpmZVeDEaWZmVoETp5mZWQVOnGZmZhU4cZqZmVXgxGlmZlaBE6eZmVkFTpxmZmYVOHGamZlV4LlqO4DnpjUzW364xWlmZlaBE6eZmVkFTpxmZmYVOHGamZlV4MRpZmZWgROnmZlZBU6cZmZmFThxmpmZVeDEaWZmVoFnDmoDzxRkZrb86soWp6Sxkp6SNEfSie2Ox8zMukfXJU5JKwDnAXsBo4CvSBrV3qjMzKxbdGNX7fbAnIh4BkDSlcC+wBPtDMrds2Zm3aEbE+dI4HeF5bnADq3YsZOjmVn368bEqTplsdRK0gRgQl58S9JTA7DvYcArA/A63ch105jrpjHXTWOumwYmHjlgdfOn9Qq7MXHOBdYvLK8HvFi7UkRcBFw0kDuWND0ith3I1+wWrpvGXDeNuW4ac9001uy66brBQcBDwCaSNpK0EjAOuKnNMZmZWZfouhZnRCyR9C3gDmAFYGJEzGpzWGZm1iW6LnECRMStwK1t2PWAdv12GddNY66bxlw3jbluGmtq3ShiqXEzZmZm1kA3nuM0MzNrGifOivqazk/JT/Lzj0raph1xtkOJujk018mjku6XtFU74myHstNAStpO0vuSDmplfO1Wpn4k7SZppqRZku5pdYztUuJz9UlJN0t6JNfNke2Is9UkTZT0sqTHGzzfvO/iiPCj5IM02Oi3wMbASsAjwKiadfYGbiNdTzoGmNbuuDuobnYE1sh/7+W6qbver0jn5w9qd9ydVD/A6qTZvzbIy2u3O+4OqpvvA2fmv4cDC4CV2h17C+pmF2Ab4PEGzzftu9gtzmr+OJ1fRLwL9EznV7QvcFkkDwKrSxrR6kDboM+6iYj7I2JhXnyQdI3tYFDmfQNwLHAd8HIrg+sAZernq8D1EfE8QEQMljoqUzcBfFySgKGkxLmktWG2XkRMIR1rI037LnbirKbedH4j+7FON6p63F8n/RocDPqsG0kjgf2BC1sYV6co8975DLCGpMmSHpZ0RMuia68ydXMusBlpopfHgOMi4oPWhNfRmvZd3JWXozRRmen8Sk3514VKH7ekL5AS5+ebGlHnKFM3PwJOiIj3U8NhUClTP0OAzwK7A6sCD0h6MCL+t9nBtVmZutkTmAn8JfBnwJ2SpkbEG80OrsM17bvYibOaMtP5lZryrwuVOm5JWwIXA3tFxKstiq3dytTNtsCVOWkOA/aWtCQibmhNiG1V9nP1SkS8DbwtaQqwFdDtibNM3RwJ/DDSib05kp4FNgV+3ZoQO1bTvovdVVtNmen8bgKOyCO6xgCvR8S8VgfaBn3WjaQNgOuBwwdBS6Goz7qJiI0iYsOI2BC4Fjh6kCRNKPe5uhHYWdIQSauR7ng0u8VxtkOZunme1BJH0jrAnwPPtDTKztS072K3OCuIBtP5SfpGfv5C0ojIvYE5wB9Ivwa7Xsm6ORVYCzg/t6yWxCCYpLpk3QxaZeonImZLuh14FPgAuDgi6l6G0E1KvndOByZJeozUPXlCRHT9XVMkXQHsBgyTNBf4J2BFaP53sWcOMjMzq8BdtWZmZhU4cZqZmVXgxGlmZlaBE6eZmVkFTpxmZmYVOHFa0+Vp0q5tcwyRh/W3laTnJJ09QK/V5zFJGp/XG5qXN8zLX2oUk6RDJI0fiBj7o2w8/Xlf5W2ij8dpy34UIGk1SadJ2nwgXq/E/kbl/Q1txf4GM1/Haa1wNPBeu4MYpG4BPke6jq2R/YHiLE6HkGYvmtS8sHrVzHiOBj5RWP4ZabKA0wtlcwdgPwCrka4tfBJoxTWno/L+LgTeasH+Bi0nTmu6iHii3TE0k6RVImJxu+OoJyLmA/P7WOc3LQqnlGbGU/telPQ2MD/fPcOsFHfV2jKTNFrS7ZIWSHpb0mxJxxSeX6pLTdLBkp6WtEjS3ZK2zt1k4wvrPCfpbEl/J2mupIWSrpS0emGdj0k6V+lGv3+Q9Kyk8yQVWxVljyMkHS/px/lYXpP00zzVWc86PV2f2+fjWgT8fX5umKRLJb2aY5ksqe7MSJJOkfSSpLck/VzSJ/t5TCuVjLdh912xa1TSJOBAYNdi16WkYyS9Wfs6kr6Q19mywWtPkXRRYXnPvP45hbIDJb2rNJVeqXhq9vFVpZsVvyHpNkkDcru63NV6jqQXJL0jaYakL9asc6Ck3+T/pwWSHpC0o6RV+PAHyxWF2NdtsK+1JE2SNE/SYkn/J+m8mnX+In/O3pT0uqQrJA3Pz40Frsmrzsv7enIg6sGW5hanDYSbSN1RhwHvkObKbJi4cjK5kjQn67GkWyJd1WD1Q0jTrE0gTdJ8DvADUpcbpO6wFYCTSV9U6+e/ryHdNaKq75LuFXooMBo4A1hMTo4FVwAXAP8MvJbLbgA+DXwPeCVvc7ekrSNiTmHbr5CmATsKGAH8G2ni+4P7cUxl4y3rdGAD0o2je+p4Lqnr72zgID7aZToemBERjzZ4vSmkxNdjlxzfzjVlMyKiXndyo3h67AB8ilQPqwI/Bi4iTbXWb5JEmh93C9JUkc+R3t+3SNoqTwE4ivQ+Pgs4nvT/ti2wBulzMBa4HTgF+J/80o1ubPBTYEvg26T7sW5A6mLviWczYCpwH+n/emXS//UvSHcZeoB0Q+sfAPuQ7lO5aFnqwHrR7rt4+7F8P0jnngLYopd1JgPXFpavIZ3zUaHsH/LrjC+UPQf8FhhSKPsR8FIv+xoC7JRfa4NCeQDf6uNYgvQD4E8KZSeTzg+umZfH5/WOq9l2bC7ftVD2MVLi+4+aY1oADC2UHUqaf3WzfhxT2XiH5uUN8/KXamI6u7B8LTC5Thz/BdxTWB5KSqgN65WU6AMYnpenkO4fuaQQ0wzgrH7EMxl4HVijUPadvL9VS75/pwOT6pTvk19nh5ryacDl+e/DgBdKfDbGlYhjDnBUL89fQ7rXZvGzMDq/b3bPywfl/a1b5tj96P/DXbW2rBaQbhZ7oaS/kbR2iW22A26O/GnPau/40OPuiCjezf4JYO2a7sjDc3fZW6RBSPfmpz5T+ig+dGN89CbA15NaMrUjI2+pWd6edK7snp6CSLfA+iVL33f0zogoDt64njQ593Y9BRWOqWy8A+ES0h1KNs7Lh5CS+n/3ss39wPvA5yWtTKqni0kt8s/l7uctSa2p/ngoIhYWlnvOYS7rDYv3ICXwh5XuyDJE0hDgLlKrElJPyAhJF0vao6eruZ9mAidJ+oakTzeI53qAQixPAfMK8ViLOHHaMslf2n8FvARMBF6SNFXS1r1sti5LD1hpNIDltZrld0lJZiUASfsDl5G6qg4GxpBGZQKsUvIwil5usDyipvz3Ncsj6pT1rLdmb/uIiEWkltsIqHxMZeMdCJNJI1DH5+UjSYl7QaMNIuJNUlLYmZQ0F5ESzr25bCfS99B9/Yyp3vsD+vd/XzSM1Dp/r+ZxEvkej5G6pw8gnWq4A3hF0mWSav+/y5hA6tb9F+BpSU9KOgBA0gqkrupT68TzKT56z0lrAZ/jtGUWEU8CB0pakfRleCbpXNB6Na2hHi8Bw2vKapfLOhiYFhE957+QtGs/XwugtsXcs1x7H7/a2wrNq7MtwDqkVnnDfUhaldTt2bOPKsdUNt5lFhEhaSIwQdLlpJb0XiU2nUp6X7wK3BcRH0iaCuxHug3UE9F5NzVfADxLalXX+uN7OtI9U29QGrD2ZdKphA/48MdFKfnHx9FKg+q2IiXoqyVtGhFzJL1BOrd8eZ3Na388WZO5xWkDJiLei4hfkQbwjCD9Sq7nIeDLeQBGj7/u525XJQ3EKDq0n68FsK+k4ufiAFIrqa/r8KaRupB36SnIXXf78GE3a48v1oxOPYCUiKfn5SrH1N94e/MujVtsk0iDtCYCLwB3lni9qcDWpAE7U3LZFNLAnt3pu5u2t3ia5S7ScS6MiOk1jxm1K0fEaxFxOalrflQurtz6jWQmcCJpgFhP1/xdwOg6sUyPiOf7uz/rH7c4bZnkyxDOJo2KfYY0ovAE4JFeuvDOJCWaKyX9jNTVdVR+rl4LtTd3AudJOjm/5t6kL+P++jhwjaT/JA2+OBU4t7fuSICIuEPSfcBVkk4kta6+R0qCZ9WsvojUIj+L9APjLOAX8eE1hlWOqV/x9uFJUkLejzSC9cWIeDEf54tKN5TeB/jXiHi/xOtNJSWBHUmjXwEeIXU1bkdqpfUrnib6JSm53yXpTGA26YfgNgARcaqkb5POz95JauFvSmpFX5DXeUPSPGCcpKdJP4Zm1pyzB0DSNNII3VmkUxHfBN4AHs6rnAI8KOkm0o+XBaTEvidwQUTcT6onSC3X64C3ImLWgNWIfajdo5P8WL4fpK7By0lJczGpG/YKPjr6czKFUbW57BDSSMLFpBbZHqRW136FdZ6jMLoyl43no6NEVyAl7pdJXzTXkVoytSNHy46qPZ406nMhacTmecDKjfZfs/1w0rnJhaTkeA+wXc06zwH/DpxGOv/5dq6v1QvrVDmmSvFSblTtMNJlDgvyuqfVHMPf5vJNKrxPZudjXbFQdhs1I4WrxNPgfbVbXmfzknHVHVWbn1uFdHnHM6TW3DzgVmDP/Pwu+Rjmkd7Hz5AuESke4z6k1v9iehnxSvrx8DjpXPdCUgtzTM06o3M99Ly/ngbOB0YU1jkJeJ40IOvJdn8/dOtDubLN2krSYaQEvHFEPNumGAI4NiLObcf+lxeSriZ9We/c58pmXchdtdYWki4gdXEtJHV//SNwS7uSpvVN0hakSx8OAMa1ORyztnHitHZZi9TNtBbpfOBVpEkQrHPdTOo2PT8i2nq3G7N2cletmZlZBb4cxczMrAInTjMzswqcOM3MzCpw4jQzM6vAidPMzKwCJ04zM7MK/h9j71Y76+Bc0AAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Signal class:\n", "nclass = 0\n", "\n", "Y_Test_pred_nclass = p_hot_Test_pred[:,nclass]\n", "# fig, (ax,bx) = plt.subplots(1,2, figsize=(15,7))\n", "fig, (ax) = plt.subplots(1,1, figsize=(7,7))\n", "num_bins = 100\n", "transperance = 0.7\n", "\n", "# n, bins, patches = ax.hist(Y_Train_pred_nclass, \n", "# num_bins, range =[0,1], alpha = transperance)\n", "n, bins, patches = ax.hist(Y_Test_pred_nclass, \n", " num_bins, range =[0,1], alpha = transperance)\n", "b, t = ax.get_ylim()\n", "ax.set_ylim(top = 0.2 * (t-b)+t)\n", "#SetCMSlabel(ax,CMS_state)\n", "SetCMSlabel(ax)\n", "# n, bins, patches = bx.hist(Y_Test_pred_nclass, \n", "# num_bins, range =[1.0e-3,1-1.0e-3], alpha = transperance)\n", "Xtitle = 'signal probability with Test set'\n", "ax.set_xlabel(Xtitle)\n", "ax.set_ylabel('Entries/(%1.2f)'%(bins[1]-bins[0]))\n", "ax.legend([labelData], loc='upper right')\n", "x_B, y_B = 0.1, 0.82\n", "x_S, y_S = 0.8, 0.82\n", "ax.text(x_B, y_B, \"Background\",\n", " verticalalignment='bottom', horizontalalignment='left',\n", " transform=ax.transAxes, color='darkgreen', fontsize=15)\n", "ax.text(x_S, y_S, \"Signal\",\n", " verticalalignment='bottom', horizontalalignment='left',\n", " transform=ax.transAxes, color='darkred', fontsize=15)\n", "\n", "plt.savefig('Results/' + ModelName +'_SignalProbability.pdf')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### NN model optimization with Test set \n", "[jump to top](#Top)\n", "\n", "Output of the NN is a probability for the NI candidate to be classified as a signal : $p_{Signal}$.\n", "\n", "Class prediction, $Y_{predict}$, is defined by $p_{Cut}$ : \n", "* class 0 (signal): $p_{Signal}\\ge p_{Cut}$;\n", "* class 1 (background): $p_{Signal}\\lt p_{Cut}$.\n", "\n", "For signal-background classification $p_{Cut}$ is optimized to maximize \n", "\n", "$f1 score = 2\\frac{precision\\times recall}{precision + recall}$ , \n", "\n", "calculated on real NIs and combinatorial background, which requires high\n", "precision (purity) = $\\frac{\\Sigma Y_{true}\\times Y_{predict}}{\\Sigma Y_{predict}}$\n", "and high recall(efficiency) = $\\frac{\\Sigma Y_{true}\\times Y_{predict}}{\\Sigma Y_{true}}$ at the same time. \n", "\n", "N.B.: $f1 score$ is calculated on real NIs and combinatorial background, estimated from sidebands, but not on the Signal (mixed sample, which includes combinatorial background) and Background classes prediction ($Y_{predict}$).\n", "\n", "* Optimal value for $p_{Signal}$ is 0.47 to separate signal from background. $f1 score$ is calculated with the assumption that false-negative prediction (inefficiency) could be reliably estimated only until 10% from true-positive signal. $Y_{predict}$ is calculated based on this optimal cut. \n", "* $Y_{predict}$ optimization should be done on the Validation set, but due to lack of data, Train set is used. " ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:log:Optimized values: CutSel = 0.47, f1 score = 0.90, and recall = 0.90\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def YpredCut(Y_hot_pred, cutHot):\n", "\n", " if numSig == 1:\n", " Y_pred = Y_hot_pred[:,0] # signal probability\n", " Y_pred = 1.*np.invert(Y_pred > cutHot)\n", " else:\n", " Y_pred = np.argmax(Y_hot_pred, axis = 1)\n", " return Y_pred\n", "#for categorical_crossentropy, could make scane from 0.2 to 0.7\n", "\n", "Radius_BP_Train, Radius_BPIX_Train, Radius_Tube_Train = CalcRad(X_Train[:,1], X_Train[:,2])[1:4]\n", "Radius_BP_Test, Radius_BPIX_Test, Radius_Tube_Test = CalcRad(X_Test[:,1], X_Test[:,2])[1:4]\n", "\n", "# only Train Set is using for optimization:\n", "MaterialforOptimization = [\"BP\", \"L2\", \"L3\", \"L4\", \"Tube\", \"Rails\"]\n", "def f1score_Ypred (Mat, Y_pred, Rad_BP, Rad_BPIX, Rad_Tube, X_Rails):\n", "\n", " # [1] for S estimate, [2] for B_estimate\n", " S_est_forS, B_est_forS = PreReF1(Rad_BP[Y_pred==0], Rad_BPIX[Y_pred ==0], Rad_Tube[Y_pred ==0], \n", " X_Rails[Y_pred ==0], Mat, MaterialOfPixel)[1:3]\n", " S_est_forB, B_est_forB = PreReF1(Rad_BP[Y_pred==1], Rad_BPIX[Y_pred ==1], Rad_Tube[Y_pred ==1], \n", " X_Rails[Y_pred ==1], Mat, MaterialOfPixel)[1:3]\n", "\n", " epsilon = 1.0e-6\n", "\n", " # for background classification, signal estimation could be < 0, so make reset to 0 \n", " # to not confuse calculations, in future better signal estimation should be perform\n", " scut = 0.10\n", " S_est_forB[S_est_forB < scut*S_est_forS] = scut*S_est_forS[S_est_forB < scut*S_est_forS]\n", "# logger.debug(\"S_est_forB = \" +str(S_est_forB))\n", "\n", " \n", " tp = np.sum(S_est_forS) # Signal, classified as Signal\n", " fp = np.sum(B_est_forS) # Background, classified as Signal\n", " fn = np.sum(S_est_forB) # Signal, classified s Background\n", "\n", " prec_Mat = tp / (tp + fp + epsilon)\n", " recall_Mat = tp / (tp + fn + epsilon)\n", "\n", " f1_Mat = 2*prec_Mat*recall_Mat / (prec_Mat+recall_Mat+epsilon)\n", "\n", " return f1_Mat, prec_Mat, recall_Mat\n", "\n", "ymin = 0.2\n", "ymax = 0.7\n", "n_frac = 50\n", "CutSel = np.zeros(n_frac) \n", "f1ScoreOpt = np.zeros(n_frac)\n", "precisionOpt = np.zeros(n_frac)\n", "recallOpt = np.zeros(n_frac)\n", "\n", "f1ScoreMax = -1.\n", "recallMax = -1\n", "CutSel_Opt = -1.\n", "\n", "for i in range(0,n_frac):\n", " CutSel[i] = ymin +i*(ymax-ymin)/n_frac\n", " Y_Train_pred_Cut = YpredCut(p_hot_Train_pred, CutSel[i])\n", " f1ScoreOpt[i], precisionOpt[i], recallOpt[i] = f1score_Ypred (MaterialforOptimization, Y_Train_pred_Cut, \n", " Radius_BP_Train, Radius_BPIX_Train, \n", " Radius_Tube_Train, X_Train[:,1])\n", " if f1ScoreOpt[i] > f1ScoreMax:\n", " f1ScoreMax = f1ScoreOpt[i]\n", " CutSel_Opt = CutSel[i]\n", " recallMax = recallOpt[i]\n", "\n", "# assign predictions for Train and Test sets with optimal cut:\n", "Y_Train_pred = YpredCut(p_hot_Train_pred, CutSel_Opt)\n", "Y_Test_pred = YpredCut(p_hot_Test_pred, CutSel_Opt)\n", "\n", "logger.debug(\"Optimized material: f1score opt = \" +str(f1ScoreOpt))\n", "logger.info(\"Optimized values: CutSel = %3.2f, f1 score = %3.2f, and recall = %3.2f\" %\n", " (CutSel_Opt, f1ScoreMax, recallMax))\n", "\n", "fig, (ax,bx) = plt.subplots(1,2, figsize=(15,7))\n", "\n", "ax.plot(CutSel,f1ScoreOpt)\n", "b, t = ax.get_ylim()\n", "ax.set_ylim(top = 0.15 * (t-b)+t)\n", "SetCMSlabel(ax)\n", "ax.legend([\"optimization curve\"], loc='upper right')\n", "ax.text(0.02,0.93,labelData, size = 15, transform=ax.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "# ax.set_title('Optimization with Train Set for Y prediction')\n", "ax.set_ylabel('f1 score')\n", "ax.set_xlabel('probability cut with Train set')\n", "#ax.legend(['train', 'test'], loc='upper right')\n", "\n", "bx.plot(CutSel,precisionOpt)\n", "bx.plot(CutSel,recallOpt)\n", "b, t = bx.get_ylim()\n", "bx.set_ylim(top = 0.15 * (t-b)+t)\n", "#SetCMSlabel(bx,CMS_state)\n", "SetCMSlabel(bx)\n", "bx.text(0.02,0.93,labelData, size = 15, transform=bx.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "\n", "bx.set_ylabel('precision, recall')\n", "bx.set_xlabel('probability cut with Train set')\n", "bx.legend(['precision', 'recall'], loc='upper right')\n", "\n", "fig.tight_layout()\n", "#fig.tight_layout(pad=1.0)\n", "plt.savefig('Results/' + ModelName + '_Yoptimization.pdf')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot Train and Test prediction for Signal-Background separation as function of BPIX radius \n", "[jump to top](#Top)\n", "\n", "NN model suppresses background by a factor of 4-5 for Test set, \n", "and keeps around 90% of the signal (real NIs).\n", "\n", "N.B.: NN model wasn’t trained in the signal regions of inner shield and layer 1, but still has similar separation power as for beam pipe region." ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def PlotR_pred(Rad, Y_pred, Rmin, Rmax, Tit, nb):\n", "\n", " fig, (ax) = plt.subplots(1,1, figsize=(15,7))\n", " num_bins = nb\n", " transperance = 0.7\n", " \n", " #Signal\n", " n_Sig, bins, patches = ax.hist(Rad[np.logical_and(np.logical_and(Rad > Rmin, Rad < Rmax),\n", " np.logical_and(Y_pred > -1, Y_pred < numSig))], \n", " num_bins, range =[Rmin,Rmax], alpha = transperance)\n", " #Background\n", " n_Bkg, bins, patches = ax.hist(Rad[np.logical_and(np.logical_and(Rad > Rmin, Rad < Rmax),\n", " np.logical_and(Y_pred > (numSig-1), Y_pred < numClasses))], \n", " num_bins, range =[Rmin,Rmax], alpha = transperance)\n", " \n", " b, t = ax.get_ylim()\n", " ax.set_ylim(top = 0.1 * (t-b)+t)\n", " SetCMSlabel(ax)\n", " ax.text(0.02,0.93,labelData, size = 15, transform=ax.transAxes,\n", " verticalalignment='bottom', horizontalalignment='left')\n", "\n", " Xtitle = 'r at BPIX center (cm)'\n", " ax.set_xlabel(Xtitle)\n", " ax.set_ylabel('Entries/(%1.1f mm)'%(10*(bins[1]-bins[0])))\n", " ax.legend([Tit + ' set for signal class', Tit + ' set for background class'], loc='upper right')\n", "\n", " ax.tick_params(axis='x', which='minor', length=0) # remove minor ticks from 'log' scale\n", " labBPIX = [\"beam pipe\",\"inner shield\", \"layer 1\", \"5 cm\", \"layer 2\", \"10 cm \", \"layer 3\", \"15 cm \", \n", " \"layer 4\", \"outer shield\", \"rails\", \"support tube\", \"23 cm\"]\n", " xlabBPIX = [ 2.2, 2.5, 2.95, 5.0, 6.8, 10.0, 10.9, 15.0, \n", " 16.0, 18.6, 20.3, 21.8, 23.]\n", " plt.xticks(xlabBPIX, labBPIX,rotation=80)\n", "\n", " fig.tight_layout()\n", "\n", " plt.savefig('Results/' + ModelName + '_' + Tit + '_Pred.pdf')\n", " plt.show()\n", "\n", "\n", "PlotR_pred(Radius_BPIX_Train, Y_Train_pred, 1.5, 23., \"Train\", 1075)\n", "\n", "PlotR_pred(Radius_BPIX_Test, Y_Test_pred, 1.5, 23.,\"Test\", 1075)\n", "#PlotR_pred(Radius_BP_Test, Y_Test_pred, 1.5, 3.,\"Test\", 400)\n", "#PlotR_pred(Radius_Tube_Test, Y_Test_pred, 17., 21.,\"Test\", 100)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Background to Signal (B/S) ratios in Signal regions (S0-S6)\n", "\n", "[jump to top](#Top)\n", "\n", "B/S ratios in Signal Regions (S0-S6), discussed in [classification section](#Classification) is estimated from sidebands and is presented for:\n", "* Whole Data set without classification,\n", "* Train set for Signal class of NN prediction, \n", "* Test set for Signal class of NN prediction.\n", "\n", "Significant background suppression is observed in Train/Test sets after NN signal classification." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

Background to Signal ratio

BP

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Tube

Rails

no classification

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signal class with Train set_

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signal class with Test set__

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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Mat_All = [\"BP\", \"IS\",\"L1\",\"L2\", \"L3\", \"L4\",\"OS\", \"Tube\", \"Rails\", \"Background\"] # to avoid changes on MaterialOfInterest_All\n", "del Mat_All[-1]\n", "ratioAll_est = PreReF1(Radius_BP, Radius_BPIX, Radius_Tube, data[:,1],Mat_All, MaterialOfPixel)[0:1]\n", "\n", "lenthAll = np.size(ratioAll_est)\n", "extra = [\"Background to Signal ratio\"]\n", "Mat_All_table = np.r_[np.reshape(extra,(1,)), np.reshape(Mat_All,(lenthAll,))]\n", "\n", "extra = [\"no classification\"]\n", "ratioAll_est = np.round(ratioAll_est,2)\n", "ratio_estAll_table = np.r_[np.reshape(extra,(1,)),np.reshape(np.round(ratioAll_est,2),(lenthAll,))]\n", "\n", "# for signal classified at Signal with Train set\n", "ratioTrain_est = PreReF1(Radius_BP_Train[Y_Train_pred == 0], Radius_BPIX_Train[Y_Train_pred == 0], \n", " Radius_Tube_Train[Y_Train_pred == 0], X_Train[:,1][Y_Train_pred == 0],\n", " Mat_All, MaterialOfPixel)[0:1]\n", "extra = [\"signal class with Train set_\"]\n", "ratio_estTrain_table = np.r_[np.reshape(extra,(1,)),np.reshape(np.round(ratioTrain_est,2),(lenthAll,))]\n", "\n", "# for signal classified at Signal with Test set\n", "ratioTest_est = PreReF1(Radius_BP_Test[Y_Test_pred == 0], Radius_BPIX_Test[Y_Test_pred == 0], \n", " Radius_Tube_Test[Y_Test_pred == 0], X_Test[:,1][Y_Test_pred == 0],\n", " Mat_All, MaterialOfPixel)[0:1]\n", "extra = [\"signal class with Test set__\"]\n", "ratio_estTest_table = np.r_[np.reshape(extra,(1,)),np.reshape(np.round(ratioTest_est,2),(lenthAll,))]\n", "\n", "display_table([Mat_All_table, ratio_estAll_table])\n", "display_table([ratio_estTrain_table])\n", "display_table([ratio_estTest_table])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Tracker tomography with Test set for Signal-Background separation in x-y plane \n", "[jump to top](#Top)\n", "\n", "The signatures of \n", "* the beam pipe with radius around 2.2 cm, \n", "* BPIX detector inner shield with radius around 2.5 cm, \n", "* layer 1 with radius around 3 cm \n", "* layer 2 with radius around 6.8 cm \n", "can be observed above the combinatorial background.\n", "\n", "Radial lines between layers 1 and 2 are classified as background as expected.\n", "\n", "NN model has impressive signal-background separation power." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def labelXY(px, Tit, className):\n", " Xtitle = 'x (cm)'\n", " Ytitle = 'y (cm)'\n", " px.set_xlabel(Xtitle)\n", " px.set_ylabel(Ytitle)\n", "\n", " SetCMSlabel(px)\n", " if DataType == \"Toy\":\n", " t = px.text(0.02,0.89,\"Toy Data\", size = 15, transform=px.transAxes, \n", " verticalalignment='bottom', horizontalalignment='left')\n", " else:\n", " t = px.text(0.02,0.89,\"Data 2018\\n|z| < 25 cm\", size = 15, transform=px.transAxes, \n", " verticalalignment='bottom', horizontalalignment='left')\n", " t = px.text(0.98,0.89,Tit + \" set\\n\"+className+\" class\", size = 15, transform=px.transAxes, \n", " verticalalignment='bottom', horizontalalignment='right')\n", "# t.set_bbox(dict(facecolor='white', alpha=0.8, edgecolor='white'))\n", " x0 = [0]\n", " y0 = [0]\n", " px.plot(x0,y0, color = 'black',marker='o', markersize=3, linestyle=\"None\", label = \"(0,0)\")\n", " px.legend(loc='upper right',bbox_to_anchor=(1.02, 0.92),handletextpad=0.0,framealpha=0.)\n", "# bug: \\bullet and \\cdot plots as square...\n", "# t = px.text(0.98,0.83,r\"$\\bf{\\bullet}$\"+\" (0,0)\", size = 15, transform=px.transAxes, \n", "# verticalalignment='bottom', horizontalalignment='right')\n", "# t = px.text(0.98,0.83,\"${\\cdot}$\"+\" (0,0)\", size = 15, transform=px.transAxes, \n", "# verticalalignment='bottom', horizontalalignment='right')\n", "\n", "def PlotXY(x, y, Y_pred, Xmax, Rcut, Tit, nb):\n", " # using the variable ax for single a Axes\n", " fig, ((ax, a_null),(bx,dx)) = plt.subplots(2,2, figsize=(15,12))\n", " fig.delaxes(a_null)\n", " num_bins = nb\n", "\n", " Rad = CalcRad(x, y)[2] # 2nd element centered at BPIX\n", " cut = Rcut\n", " xcut = x[Rad < cut]\n", " ycut = y[Rad < cut]\n", " Y_cut = Y_pred[Rad < cut]\n", " x0 = [0]\n", " y0 = [0]\n", "# to add color pallete to figure: cmap = 'viridis' (default), 'jet' \n", " counts, xedges, yedges, im = ax.hist2d(xcut, ycut, bins=nb, range = [[-Xmax, Xmax], [-Xmax, Xmax]], norm=LogNorm(),\n", " cmap = 'viridis')\n", " \n", " counts, xedges, yedges, im2 = bx.hist2d(xcut[np.logical_and(Y_cut > -1, Y_cut < numSig)], \n", " ycut[np.logical_and(Y_cut > -1, Y_cut < numSig)], bins=nb,\n", " range = [[-Xmax, Xmax], [-Xmax, Xmax]], norm=LogNorm())\n", "\n", " counts, xedges, yedges, im3 = dx.hist2d(xcut[np.logical_and(Y_cut > (numSig-1), Y_cut < numClasses)], \n", " ycut[np.logical_and(Y_cut > (numSig-1), Y_cut < numClasses)], bins=nb, \n", " range = [[-Xmax, Xmax], [-Xmax, Xmax]], norm=LogNorm())\n", "\n", " vmin, vmax = im2.get_clim()\n", " im3.set_clim(vmin, vmax)\n", " ax_cbar = plt.colorbar(im, ax=ax)\n", " wbin = 2*Xmax/nb\n", " cbarTitle = r'Entries/(%1.1f$\\times$%1.1f) mm$^2$'%(10*wbin, 10*wbin)\n", " ax_cbar.ax.set_ylabel(cbarTitle)\n", " bx_cbar = plt.colorbar(im2, ax=bx)\n", " bx_cbar.ax.set_ylabel(cbarTitle)\n", " dx_cbar = plt.colorbar(im3, ax=dx)\n", " dx_cbar.ax.set_ylabel(cbarTitle)\n", "\n", " labelXY(ax, Tit, 'any')\n", " labelXY(bx, Tit, 'signal')\n", " labelXY(dx, Tit, 'bkg.')\n", " \n", " fig.tight_layout()\n", " plt.savefig('Results/' + ModelName + '_' + Tit + '_size'+str(Xmax)+'_XY_Pred.pdf')\n", " plt.show()\n", "\n", "#PlotXY(X_Test[:,1], X_Test[:,2], Y_Test_pred, 25., 23., \"Test\", 1250)\n", "PlotXY(X_Test[:,1], X_Test[:,2], Y_Test_pred, 9., 8., \"Test\", 225)\n", "PlotXY(X_Test[:,1], X_Test[:,2], Y_Test_pred, 4., 3.7, \"Test\", 200)\n", "\n", "###[//]: # 'Nice link to citing packages in the SciPy ecosystem: https://www.scipy.org/citing.html'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Summary \n", "\n", "* Machine learning method for reducing combinatorial background in data without Monte Carlo is presented:\n", "\n", " * NN model with floating classification on the mixed samples is constructed\n", " * Even though the variables used for the training show only small differences between background and signal, the NN has impressive separation power\n", " * NN model wasn’t trained in the signal regions of inner shield and layer 1, but still has similar separation power as for beam pipe region.\n", " * Combinatorial background suppression could decrease systematic uncertainties for material position and material density measurements\n", " * This technique could be used for any analysis, where you could perform classification on mixed samples with different ratios of background to signal\n", " \n", "[jump to top](#Top)\n", " \n", "# Documentation \n", "\n", "* **A guide to NumPy.** Travis E. Oliphant. USA: Trelgol Publishing, (2006), http://www.numpy.org/\n", "\n", "* **The NumPy Array: A Structure for Efficient Numerical Computation.** Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. Computing in Science & Engineering, 13, 22-30 (2011), [DOI:10.1109/MCSE.2011.37](https://ieeexplore.ieee.org/document/5725236)\n", "\n", "* **Matplotlib: A 2D Graphics Environment.** John D. Hunter., Computing in Science & Engineering **9** (2007) 90-95, [DOI:10.1109/MCSE.2007.55](https://ieeexplore.ieee.org/document/4160265)\n", "\n", "* **Keras.** Chollet, François and others (2015), https://keras.io\n", "\n", "* **Precision measurement of the structure of the CMS inner tracking system using nuclear interactions.** CMS Collaboration. JINST **13** (2018) 10034, [DOI:10.1088/1748-0221/13/10/P10034](http://dx.doi.org/10.1088/1748-0221/13/10/P10034)\n", "\n", "* **Precision measurement of the structure of the CMS inner tracking system using nuclear interactions with data collected in 2018.** CMS Collaboration. [CERN-CMS-DP-2019-001](http://cds.cern.ch/record/2664786?ln=en)\n", "\n", "* **Jupyter Notebooks – a publishing format for reproducible computational workflows.** T. Kluyver, B. Ragan-Kelley and others. IOS Press (2016) 87, [DOI:10.3233/978-1-61499-649-1-87](http://ebooks.iospress.nl/publication/42900)\n", "\n", "* **SWAN: A service for interactive analysis in the cloud**. Future Generation Computer Systems **78 part 3** (2018) 1071, [DOI:10.1016/j.future.2016.11.035](https://doi.org/10.1016/j.future.2016.11.035)\n", "\n", "* **2017 tracking performance plots**. CMS Collaboration. [CERN-CMS-DP-2017-015](https://cds.cern.ch/record/2290524?ln=en)\n", "\n", "* **Classification without labels: Learning from mixed samples in high energy physics.** Eric M. Metodiev, Benjamin Nachman, Jesse Thaler. JHEP **10** (2017) 174 [DOI:10.1007/JHEP10(2017)174](https://doi.org/10.1007/JHEP10(2017)174)\n", "\n", "[jump to top](#Top)\n", "\n", "# Acknowledgment \n", "\n", "We are grateful to support from the National Science Foundation.\n", "\n", "[jump to top](#Top)\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }