Warning, /tutorials/HEPData/GenerateDummyTree.ipynb is written in an unsupported language. File is not indexed.
0001 {
0002 "cells": [
0003 {
0004 "cell_type": "code",
0005 "execution_count": 28,
0006 "id": "9f128160",
0007 "metadata": {
0008 "scrolled": false
0009 },
0010 "outputs": [
0011 {
0012 "name": "stderr",
0013 "output_type": "stream",
0014 "text": [
0015 "Warning in <TROOT::Append>: Replacing existing TH1: hist_stat (Potential memory leak).\n",
0016 "Warning in <TROOT::Append>: Replacing existing TH1: hist_halved (Potential memory leak).\n",
0017 "Warning in <TROOT::Append>: Replacing existing TH1: corr_matrix (Potential memory leak).\n",
0018 "Warning in <TCanvas::Constructor>: Deleting canvas with same name: c\n",
0019 "Info in <TCanvas::Print>: png file spectrum.png has been created\n",
0020 "Warning in <TCanvas::Constructor>: Deleting canvas with same name: c1\n",
0021 "Info in <TCanvas::Print>: png file corr_matrix.png has been created\n"
0022 ]
0023 },
0024 {
0025 "data": {
0026 "text/html": [
0027 "\n",
0028 "\n",
0029 "<div id=\"root_plot_1750178505837\" style=\"width: 1200px; height: 1200px; position: relative\">\n",
0030 "</div>\n",
0031 "\n",
0032 "<script>\n",
0033 "\n",
0034 "function display_root_plot_1750178505837(Core) {\n",
0035 " let obj = 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0037 " Core.draw(\"root_plot_1750178505837\", obj, \"\");\n",
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0039 "\n",
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0044 " script.onerror = function() { script.remove(); on_error(); };\n",
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0050 " // We are in jupyter notebooks, use require.js which should be configured already\n",
0051 " requirejs.config({\n",
0052 " paths: { 'JSRootCore' : [ 'build/jsroot', 'https://root.cern/js/7.7.4/build/jsroot', 'https://jsroot.gsi.de/7.7.4/build/jsroot' ] }\n",
0053 " })(['JSRootCore'], function(Core) {\n",
0054 " display_root_plot_1750178505837(Core);\n",
0055 " });\n",
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0059 " // JSROOT already loaded, just use it\n",
0060 " display_root_plot_1750178505837(JSROOT);\n",
0061 "\n",
0062 "} else {\n",
0063 "\n",
0064 " // We are in jupyterlab without require.js, directly loading jsroot\n",
0065 " // Jupyterlab might be installed in a different base_url so we need to know it.\n",
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0067 " var base_url = JSON.parse(document.getElementById('jupyter-config-data').innerHTML).baseUrl;\n",
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0070 " }\n",
0071 "\n",
0072 " // Try loading a local version of requirejs and fallback to cdn if not possible.\n",
0073 " script_load_root_plot_1750178505837(base_url + 'static/build/jsroot.js', function(){\n",
0074 " console.error('Fail to load JSROOT locally, please check your jupyter_notebook_config.py file');\n",
0075 " script_load_root_plot_1750178505837('https://root.cern/js/7.7.4/build/jsroot.js', function(){\n",
0076 " document.getElementById(\"root_plot_1750178505837\").innerHTML = \"Failed to load JSROOT\";\n",
0077 " });\n",
0078 " });\n",
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0100 "function display_root_plot_1750178505842(Core) {\n",
0101 " let obj = 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0105 "\n",
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0115 "\n",
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0117 " requirejs.config({\n",
0118 " paths: { 'JSRootCore' : [ 'build/jsroot', 'https://root.cern/js/7.7.4/build/jsroot', 'https://jsroot.gsi.de/7.7.4/build/jsroot' ] }\n",
0119 " })(['JSRootCore'], function(Core) {\n",
0120 " display_root_plot_1750178505842(Core);\n",
0121 " });\n",
0122 "\n",
0123 "} else if (typeof JSROOT !== 'undefined') {\n",
0124 "\n",
0125 " // JSROOT already loaded, just use it\n",
0126 " display_root_plot_1750178505842(JSROOT);\n",
0127 "\n",
0128 "} else {\n",
0129 "\n",
0130 " // We are in jupyterlab without require.js, directly loading jsroot\n",
0131 " // Jupyterlab might be installed in a different base_url so we need to know it.\n",
0132 " try {\n",
0133 " var base_url = JSON.parse(document.getElementById('jupyter-config-data').innerHTML).baseUrl;\n",
0134 " } catch(_) {\n",
0135 " var base_url = '/';\n",
0136 " }\n",
0137 "\n",
0138 " // Try loading a local version of requirejs and fallback to cdn if not possible.\n",
0139 " script_load_root_plot_1750178505842(base_url + 'static/build/jsroot.js', function(){\n",
0140 " console.error('Fail to load JSROOT locally, please check your jupyter_notebook_config.py file');\n",
0141 " script_load_root_plot_1750178505842('https://root.cern/js/7.7.4/build/jsroot.js', function(){\n",
0142 " document.getElementById(\"root_plot_1750178505842\").innerHTML = \"Failed to load JSROOT\";\n",
0143 " });\n",
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0146 "\n",
0147 "</script>\n"
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0157 "source": [
0158 "import ROOT\n",
0159 "import numpy as np\n",
0160 "\n",
0161 "# Parameters\n",
0162 "n_bins = 10\n",
0163 "x_min = 0\n",
0164 "x_max = 10\n",
0165 "\n",
0166 "# TH1D with statistical uncertainties only\n",
0167 "hist_stat = ROOT.TH1D(\"hist_stat\", \"Exponential Spectrum;GeV;Dummy cross-section [mb]\", n_bins, x_min, x_max)\n",
0168 "hist_halved = ROOT.TH1D(\"hist_halved\", \"Exponential Spectrum;GeV;Dummy halved cross-section [mb]\", n_bins, x_min, x_max)\n",
0169 "\n",
0170 "# Prepare arrays for TGraphAsymmErrors\n",
0171 "x_vals, y_vals, ex_low, ex_high, ey_low, ey_high = [], [], [], [], [], []\n",
0172 "\n",
0173 "# Fill both hist_stat and TGraphAsymmErrors with identical points\n",
0174 "for i in range(1, n_bins + 1):\n",
0175 " x_center = hist_stat.GetBinCenter(i)\n",
0176 " y_value = np.exp(-0.5 * x_center)*100 # Shared y value\n",
0177 " y_value_err = np.sqrt(y_value)\n",
0178 " y_value_err = y_value_err / 100\n",
0179 " y_value = y_value/100\n",
0180 "\n",
0181 " # Fill histogram\n",
0182 " hist_stat.SetBinContent(i, y_value)\n",
0183 " hist_halved.SetBinContent(i, y_value/2)\n",
0184 " hist_stat.SetBinError(i, y_value_err)\n",
0185 "\n",
0186 " # Fill graph data (same x, y)\n",
0187 " x_vals.append(x_center)\n",
0188 " y_vals.append(y_value)\n",
0189 " ex_low.append(0.5)\n",
0190 " ex_high.append(0.5)\n",
0191 " ey_low.append(0.1 * y_value *i/2)\n",
0192 " ey_high.append(0.3 * y_value*i/2)\n",
0193 "\n",
0194 "# Create TGraphAsymmErrors\n",
0195 "graph = ROOT.TGraphAsymmErrors(n_bins,\n",
0196 " np.array(x_vals, dtype='float64'),\n",
0197 " np.array(y_vals, dtype='float64'),\n",
0198 " np.array(ex_low, dtype='float64'),\n",
0199 " np.array(ex_high, dtype='float64'),\n",
0200 " np.array(ey_low, dtype='float64'),\n",
0201 " np.array(ey_high, dtype='float64'))\n",
0202 "graph.SetName(\"graph_asym\")\n",
0203 "graph.SetTitle(\"Exponential Spectrum with Systematics;GeV;Cross-section [mb]\")\n",
0204 "graph.SetMarkerStyle(21)\n",
0205 "graph.SetMarkerSize(0)\n",
0206 "graph.SetLineColor(ROOT.kRed)\n",
0207 "graph.SetMarkerColor(ROOT.kRed)\n",
0208 "graph.SetFillColorAlpha(ROOT.kBlue, 0.35)\n",
0209 "\n",
0210 "# Create a random symmetric correlation matrix as TH2D\n",
0211 "np.random.seed(123)\n",
0212 "R = np.random.rand(n_bins, n_bins) * 2 - 1 # Values in [-1, 1]\n",
0213 "R = (R + R.T) / 2\n",
0214 "np.fill_diagonal(R, 1.0)\n",
0215 "\n",
0216 "corr_matrix = ROOT.TH2D(\"corr_matrix\", \"Random Correlation Matrix;Bin Index;Bin Index\",\n",
0217 " n_bins, 0.5, n_bins + 0.5, n_bins, 0.5, n_bins + 0.5)\n",
0218 "\n",
0219 "for i in range(n_bins):\n",
0220 " for j in range(n_bins):\n",
0221 " corr_matrix.SetBinContent(i + 1, j + 1, R[i, j])\n",
0222 "\n",
0223 "hist_stat.GetYaxis().SetRangeUser(1E-3,2)\n",
0224 "\n",
0225 "hist_halved.SetMarkerStyle(21)\n",
0226 " \n",
0227 "canvas = ROOT.TCanvas(\"c\",\"c\",1200,1200)\n",
0228 "canvas.SetLogy()\n",
0229 "hist_stat.Draw(\"E1\")\n",
0230 "graph.Draw(\"P2 same\")\n",
0231 "hist_halved.Draw(\"P same\")\n",
0232 "canvas.Draw()\n",
0233 "canvas.SaveAs(\"spectrum.png\")\n",
0234 "\n",
0235 "\n",
0236 "canvas1 = ROOT.TCanvas(\"c1\",\"c1\",1200,1200)\n",
0237 "corr_matrix.Draw()\n",
0238 "canvas1.Draw()\n",
0239 "canvas1.SaveAs(\"corr_matrix.png\")\n",
0240 "\n"
0241 ]
0242 },
0243 {
0244 "cell_type": "code",
0245 "execution_count": 27,
0246 "id": "a3fbb8bf",
0247 "metadata": {},
0248 "outputs": [],
0249 "source": [
0250 "# Save everything to a ROOT file\n",
0251 "output_file = ROOT.TFile(\"spectrum_output.root\", \"RECREATE\")\n",
0252 "hist_stat.Write()\n",
0253 "hist_halved.Write()\n",
0254 "graph.Write()\n",
0255 "corr_matrix.Write()\n",
0256 "output_file.Close()"
0257 ]
0258 },
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