{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "46f16838",
   "metadata": {},
   "source": [
    "# hist003_TH1_draw_uhi\n",
    "Draw a 1D histogram to a canvas.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Rene Brun, Giacomo Parolini, Nursena Bitirgen  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:11 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cd268a15",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:11:51.092205Z",
     "iopub.status.busy": "2026-05-19T20:11:51.092045Z",
     "iopub.status.idle": "2026-05-19T20:11:52.423387Z",
     "shell.execute_reply": "2026-05-19T20:11:52.422573Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import mplhep as hep\n",
    "import numpy as np\n",
    "import ROOT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd33cce6",
   "metadata": {},
   "source": [
    "Create and fill the histogram.\n",
    "See hist002_TH1_fillrandom_userfunc.C for more information about this section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3c0a981c",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:11:52.437509Z",
     "iopub.status.busy": "2026-05-19T20:11:52.437268Z",
     "iopub.status.idle": "2026-05-19T20:11:52.774939Z",
     "shell.execute_reply": "2026-05-19T20:11:52.774227Z"
    }
   },
   "outputs": [],
   "source": [
    "form1 = ROOT.TFormula(\"form1\", \"abs(sin(x)/x)\")\n",
    "rangeMin = 0.0\n",
    "rangeMax = 10.0\n",
    "sqroot = ROOT.TF1(\"sqroot\", \"x*gaus(0) + [3]*form1\", rangeMin, rangeMax)\n",
    "sqroot.SetParameters(10.0, 4.0, 1.0, 20.0)\n",
    "\n",
    "nBins = 200\n",
    "h1d = ROOT.TH1D(\"h1d\", \"Test random numbers\", nBins, rangeMin, rangeMax)\n",
    "\n",
    "random_numbers = np.array([sqroot.GetRandom() for _ in range(10000)])\n",
    "h1d[...] = np.histogram(np.array([sqroot.GetRandom() for _ in range(10000)]), bins=nBins, range=(rangeMin, rangeMax))[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b3916af",
   "metadata": {},
   "source": [
    "Create a canvas and draw the histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c3ae2804",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:11:52.788789Z",
     "iopub.status.busy": "2026-05-19T20:11:52.788636Z",
     "iopub.status.idle": "2026-05-19T20:11:52.902525Z",
     "shell.execute_reply": "2026-05-19T20:11:52.902060Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 700x900 with 0 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 700x900 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab9b4e92",
   "metadata": {},
   "source": [
    "Split the canvas into two sections to plot both the function and the histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6c54c421",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:11:52.904038Z",
     "iopub.status.busy": "2026-05-19T20:11:52.903905Z",
     "iopub.status.idle": "2026-05-19T20:11:53.681743Z",
     "shell.execute_reply": "2026-05-19T20:11:53.681153Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.axes([0.05, 0.55, 0.90, 0.40])\n",
    "x = np.linspace(rangeMin, rangeMax, 500)\n",
    "plt.plot(x, [sqroot.Eval(xi) for xi in x], \"b-\", lw=5)\n",
    "plt.grid()\n",
    "plt.title(\"x*gaus(0) + [3]*form1\")\n",
    "plt.text(5, 40, \"The sqroot function\", fontsize=18, weight=\"bold\", bbox=dict(facecolor=\"white\", edgecolor=\"black\"))\n",
    "plt.xlim(rangeMin, rangeMax)\n",
    "plt.ylim(bottom=0)\n",
    "\n",
    "plt.axes([0.05, 0.05, 0.90, 0.40])\n",
    "hep.histplot(h1d, yerr=False, histtype=\"fill\", color=\"brown\", alpha=0.7, edgecolor=\"blue\", linewidth=1)\n",
    "\n",
    "plt.title(\"Test random numbers\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"Entries\")\n",
    "plt.xlim(rangeMin, rangeMax)\n",
    "plt.ylim(bottom=0)\n",
    "\n",
    "stats_text = (\n",
    "    f\"Entries = {len(random_numbers)}\\nMean = {(np.mean(random_numbers)):.3f}\\nStd Dev = {(np.std(random_numbers)):.2f}\"\n",
    ")\n",
    "plt.text(0.90, 0.90, stats_text, transform=plt.gca().transAxes, ha=\"right\", va=\"top\", bbox=dict(facecolor=\"white\"))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "548e6649",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9ffd3e9b",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:11:53.683419Z",
     "iopub.status.busy": "2026-05-19T20:11:53.683196Z",
     "iopub.status.idle": "2026-05-19T20:11:53.790965Z",
     "shell.execute_reply": "2026-05-19T20:11:53.790395Z"
    }
   },
   "outputs": [],
   "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
}
