Macro2_cpp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading points from a file and produce a graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's inspect the input file, which is in the appropriate format for filling a TGraphErrors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[?1034h# Measurement of Friday 26 March\n",
      "# Experiment 2 Physics Lab\n",
      "\n",
      "1   5   2\n",
      "2   11  2\n",
      "3   17  3\n",
      "4   22  4\n",
      "5   28  4\n",
      "6   35  4\n",
      "7   40  4\n",
      "8   45  4\n",
      "9   50  4\n",
      "10  60  5\n"
     ]
    }
   ],
   "source": [
    ".! cat macro2_input.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's start with the creation of the graphs as well as making it look presentable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x[0]=1, y[0]=5, ex[0]=0, ey[0]=2\n",
      "x[1]=2, y[1]=11, ex[1]=0, ey[1]=2\n",
      "x[2]=3, y[2]=17, ex[2]=0, ey[2]=3\n",
      "x[3]=4, y[3]=22, ex[3]=0, ey[3]=4\n",
      "x[4]=5, y[4]=28, ex[4]=0, ey[4]=4\n",
      "x[5]=6, y[5]=35, ex[5]=0, ey[5]=4\n",
      "x[6]=7, y[6]=40, ex[6]=0, ey[6]=4\n",
      "x[7]=8, y[7]=45, ex[7]=0, ey[7]=4\n",
      "x[8]=9, y[8]=50, ex[8]=0, ey[8]=4\n",
      "x[9]=10, y[9]=60, ex[9]=0, ey[9]=5\n"
     ]
    }
   ],
   "source": [
    "TGraphErrors graph_expected(\"./macro2_input.txt\",\"%lg %lg %lg\");\n",
    "graph_expected.SetTitle(\"Measurement XYZ and Expectation;lenght [cm];Arb.Units\");\n",
    "graph_expected.SetFillColor(kYellow);\n",
    "graph_expected.Print(\"all\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TFile**\t\toutputfromMacro1.root\t\n",
      " TFile*\t\toutputfromMacro1.root\t\n",
      "  KEY: TGraphErrors\tgInput;1\tMeasurement XYZ;length [cm];Arb.Units\n"
     ]
    }
   ],
   "source": [
    "TFile * fin = TFile::Open(\"outputfromMacro1.root\");\n",
    "fin->ls();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "TGraphErrors * graph = (TGraphErrors*)fin->Get(\"gInput\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x[0]=1, y[0]=6, ex[0]=0, ey[0]=5\n",
      "x[1]=2, y[1]=12, ex[1]=0, ey[1]=5\n",
      "x[2]=3, y[2]=14, ex[2]=0, ey[2]=4.7\n",
      "x[3]=4, y[3]=20, ex[3]=0, ey[3]=4.5\n",
      "x[4]=5, y[4]=22, ex[4]=0, ey[4]=4.2\n",
      "x[5]=6, y[5]=24, ex[5]=0, ey[5]=5.1\n",
      "x[6]=7, y[6]=35, ex[6]=0, ey[6]=2.9\n",
      "x[7]=8, y[7]=45, ex[7]=0, ey[7]=4.1\n",
      "x[8]=9, y[8]=44, ex[8]=0, ey[8]=4.8\n",
      "x[9]=10, y[9]=53, ex[9]=0, ey[9]=5.43\n"
     ]
    }
   ],
   "source": [
    "graph->SetMarkerStyle(kCircle);\n",
    "graph->SetFillColor(0);\n",
    "graph->Print(\"all\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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D+Uiv8FJLvQjuw6E+vX5N9/d0c0NElCS0XtPZGe33KXIxjCIiO2849cbxZlUADqIPjxZX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\n/wHHTdpZWaa+HAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TCanvas * c = new TCanvas(\"c\", \"test\", 400, 500);\n",
    "c->SetGrid();\n",
    "// E3 draws the band\n",
    "graph_expected.DrawClone(\"E3AL\"); \n",
    "graph->DrawClone(\"PESame\");\n",
    "c->Draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We add a legend to improve the clarity of the plot. It is always reccomended to make the plot \"self descriptive\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LDsVnVoP1BCZVh90xbEvARLBLIheZ1YBJ8V7BTnApMKk62EXL7ARbZsFLmF3x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\nYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TLegend leg(.1,.7,.3,.9,\"Lab. Lesson 2\");\n",
    "leg.SetFillColor(0);\n",
    "leg.AddEntry(&graph_expected,\"Expected Points\");                                                                                          \n",
    "leg.AddEntry(graph,\"Measured Points\");                                                                                                   \n",
    "leg.DrawClone(\"Same\");\n",
    "c->Draw();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ROOT C++",
   "language": "c++",
   "name": "root"
  },
  "language_info": {
   "codemirror_mode": "text/x-c++src",
   "file_extension": ".C",
   "mimetype": " text/x-c++src",
   "name": "c++"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}