{ "cells": [ { "cell_type": "markdown", "id": "f19006ad", "metadata": {}, "source": [ "# gr001_simple\n", "- The first section plots data generated from arrays.\n", "- The second section plots data read from a text file.\n", "\n", "\n", "\n", "\n", "**Author:** Rene Brun, Jamie Gooding \n", "This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Tuesday, May 19, 2026 at 08:37 PM." ] }, { "cell_type": "code", "execution_count": 1, "id": "27824df9", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:40.012208Z", "iopub.status.busy": "2026-05-19T20:37:40.012074Z", "iopub.status.idle": "2026-05-19T20:37:41.155238Z", "shell.execute_reply": "2026-05-19T20:37:41.154530Z" } }, "outputs": [], "source": [ "import re\n", "\n", "import numpy as np\n", "import ROOT\n", "\n", "c1 = ROOT.TCanvas(\"c1\", \"Two simple graphs\", 200, 10, 700, 500)\n", "c1.Divide(\n", " 2, 1\n", ") # Dividing the canvas in subpads for distinguishing the two examples, [See documentation](https://root.cern/doc/master/classTCanvas.html)" ] }, { "cell_type": "markdown", "id": "d9cdd9eb", "metadata": {}, "source": [ "First Example (Available data)" ] }, { "cell_type": "code", "execution_count": 2, "id": "d62c4234", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.164475Z", "iopub.status.busy": "2026-05-19T20:37:41.164265Z", "iopub.status.idle": "2026-05-19T20:37:41.294505Z", "shell.execute_reply": "2026-05-19T20:37:41.293213Z" } }, "outputs": [], "source": [ "c1.cd(1)\n", "\n", "n = 20\n", "x = np.linspace(0, n - 1, n)\n", "y = 10 * np.sin(x + 0.2)\n", "\n", "gr1 = ROOT.TGraph(n, x, y) # Create a TGraph object, storing the number of data n and the x, y variables" ] }, { "cell_type": "markdown", "id": "45b224f5", "metadata": {}, "source": [ "Set the color, width and style for the markers and line" ] }, { "cell_type": "code", "execution_count": 3, "id": "d3bfd27d", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.304489Z", "iopub.status.busy": "2026-05-19T20:37:41.304347Z", "iopub.status.idle": "2026-05-19T20:37:41.439419Z", "shell.execute_reply": "2026-05-19T20:37:41.438623Z" } }, "outputs": [], "source": [ "gr1.SetLineColor(2)\n", "gr1.SetLineWidth(4)\n", "gr1.SetMarkerColor(4)\n", "gr1.SetMarkerStyle(21)\n", "gr1.SetTitle(\"Graph from available data\") # Choose title for the graph\n", "gr1.GetXaxis().SetTitle(\"X title\") # Choose title for the axis\n", "gr1.GetYaxis().SetTitle(\"Y title\")" ] }, { "cell_type": "markdown", "id": "42c9b37a", "metadata": {}, "source": [ "Uncomment the following line to set a custom range for the x-axis (respectively for the y-axis):\n", "gr1.GetXaxis().SetRangeUser(0, 1.8)" ] }, { "cell_type": "code", "execution_count": 4, "id": "47919af8", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.444541Z", "iopub.status.busy": "2026-05-19T20:37:41.444405Z", "iopub.status.idle": "2026-05-19T20:37:41.553464Z", "shell.execute_reply": "2026-05-19T20:37:41.552737Z" } }, "outputs": [], "source": [ "gr1.Draw(\n", " \"ACP\"\n", ") # \"A\" draw axes, \"C\" = draw a smooth line through the markers (optional) and \"P\" = draw markers for data points" ] }, { "cell_type": "markdown", "id": "b2284fc6", "metadata": {}, "source": [ "Optional customization can be done on a ROOT interactive session" ] }, { "cell_type": "markdown", "id": "7e14d879", "metadata": {}, "source": [ "SECOND EXAMPLE (Data stored in a text file)" ] }, { "cell_type": "code", "execution_count": 5, "id": "811ed341", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.560569Z", "iopub.status.busy": "2026-05-19T20:37:41.560433Z", "iopub.status.idle": "2026-05-19T20:37:41.663717Z", "shell.execute_reply": "2026-05-19T20:37:41.663280Z" } }, "outputs": [], "source": [ "c1.cd(2)\n", "\n", "w = np.array([])\n", "z = np.array([])" ] }, { "cell_type": "markdown", "id": "c3ea5084", "metadata": {}, "source": [ "Open the data file" ] }, { "cell_type": "code", "execution_count": 6, "id": "57c79ab5", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.677424Z", "iopub.status.busy": "2026-05-19T20:37:41.677275Z", "iopub.status.idle": "2026-05-19T20:37:41.797280Z", "shell.execute_reply": "2026-05-19T20:37:41.792368Z" } }, "outputs": [], "source": [ "with open(f\"{ROOT.gROOT.GetTutorialDir()}/visualisation/graphs/data_basic.txt\") as file: # Open the data file\n", " for line in file:\n", " w_str, z_str = re.split(r\"\\s+\", line)[:2]\n", " w = np.append(w, float(w_str))\n", " z = np.append(z, float(z_str))\n", "\n", "m = len(w)\n", "\n", "gr2 = ROOT.TGraph(m, w, z) # Create a TGraph object for the file data\n", "gr2.SetLineColor(4)\n", "gr2.SetLineWidth(2)\n", "gr2.SetMarkerColor(2)\n", "gr2.SetMarkerStyle(20)\n", "gr2.SetTitle(\"Graph from data file\")\n", "gr2.GetXaxis().SetTitle(\"W title\")\n", "gr2.GetYaxis().SetTitle(\"Z title\")\n", "\n", "gr2.Draw(\"ACP\")" ] }, { "cell_type": "markdown", "id": "5d104718", "metadata": {}, "source": [ "Draw all canvases " ] }, { "cell_type": "code", "execution_count": 7, "id": "1bad8389", "metadata": { "collapsed": false, "execution": { "iopub.execute_input": "2026-05-19T20:37:41.799328Z", "iopub.status.busy": "2026-05-19T20:37:41.799194Z", "iopub.status.idle": "2026-05-19T20:37:41.992999Z", "shell.execute_reply": "2026-05-19T20:37:41.992665Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "
\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from ROOT import gROOT \n", "gROOT.GetListOfCanvases().Draw()" ] } ], "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": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }