{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hsum\n",
"Simple example illustrating how to use the C++ interpreter\n",
"\n",
"\n",
"\n",
"\n",
"**Author:** Wim Lavrijsen \n",
"This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Wednesday, March 03, 2021 at 09:41 AM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Welcome to JupyROOT 6.23/01\n"
]
}
],
"source": [
"from ROOT import TCanvas, TH1F, TSlider\n",
"from ROOT import gROOT, gBenchmark, gRandom"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Create a new canvas, and customize it."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"c1 = TCanvas( 'c1', 'The HSUM example', 200, 10, 600, 400 )\n",
"c1.SetGrid();\n",
"\n",
"gBenchmark.Start( 'hsum' )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Create some histograms."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"total = TH1F( 'total', 'This is the total distribution', 100, -4, 4 )\n",
"main = TH1F( 'main', 'Main contributor', 100, -4, 4 )\n",
"s1 = TH1F( 's1', 'This is the first signal', 100, -4, 4 )\n",
"s2 = TH1F( 's2', 'This is the second signal', 100, -4, 4 )\n",
"total.Sumw2() # this makes sure that the sum of squares of weights will be stored"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set canvas/frame attributes."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"total.SetMarkerStyle( 21 )\n",
"total.SetMarkerSize( 0.7 )\n",
"main.SetFillColor( 16 )\n",
"s1.SetFillColor( 42 )\n",
"s2.SetFillColor( 46 )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Initialize random number generator."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"gRandom.SetSeed()\n",
"gauss, landau = gRandom.Gaus, gRandom.Landau"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"for speed, bind and cache the Fill member functions"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"histos = [ 'total', 'main', 's1', 's2' ]\n",
"for name in histos:\n",
" exec('%sFill = %s.Fill' % (name,name))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fill histograms randomly"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"kUPDATE = 500\n",
"for i in range( 10000 ):\n",
" # Generate random values.\n",
" xmain = gauss( -1, 1.5 )\n",
" xs1 = gauss( -0.5, 0.5 )\n",
" xs2 = landau( 1, 0.15 )\n",
" mainFill( xmain )\n",
"\n",
" # Fill histograms.\n",
" s1Fill( xs1, 0.3 )\n",
" s2Fill( xs2, 0.2 )\n",
" totalFill( xmain )\n",
" totalFill( xs1, 0.3 )\n",
" totalFill( xs2, 0.2 )\n",
"\n",
" # Update display every kUPDATE events.\n",
" if i and (i%kUPDATE) == 0 :\n",
" if i == kUPDATE :\n",
" total.Draw( 'e1p' )\n",
" main.Draw( 'same' )\n",
" s1.Draw( 'same' )\n",
" s2.Draw( 'same' )\n",
" c1.Update()\n",
" slider = TSlider( 'slider', 'test', 4.2, 0, 4.6, total.GetMaximum(), 38 )\n",
" slider.SetFillColor( 46 )\n",
"\n",
" if slider:\n",
" slider.SetRange( 0, float(i) / 10000. )\n",
"\n",
" c1.Modified()\n",
" c1.Update()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Destroy member functions cache."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"for name in histos:\n",
" exec('del %sFill' % name)\n",
"del histos"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Done, finalized and trigger an update."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"hsum : Real Time = 0.95 seconds Cpu Time = 0.21 seconds\n"
]
}
],
"source": [
"slider.SetRange( 0, 1 )\n",
"total.Draw( 'sameaxis' ) # to redraw axis hidden by the fill area\n",
"c1.Modified()\n",
"c1.Update()\n",
"\n",
"gBenchmark.Show( 'hsum' )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Draw all canvases "
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"
\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%jsroot on\n",
"from ROOT import gROOT \n",
"gROOT.GetListOfCanvases().Draw()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}