{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1b48863d",
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggplot2)\n",
    "library(reshape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7e338f77",
   "metadata": {},
   "outputs": [],
   "source": [
    "sum1 <- function(m) {\n",
    "    res = 0\n",
    "    \n",
    "    for(i in 1:dim(m)[1]) {\n",
    "        for(j in 1:dim(m)[2]) {\n",
    "            res <- res + m[i,j]\n",
    "        }\n",
    "    }\n",
    "\n",
    "    return(res)\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "be204fce",
   "metadata": {},
   "outputs": [],
   "source": [
    "sum2 <- function(m) {\n",
    "    res = .C(\"sum2\"\n",
    "             ,mtrx=as.double(m)\n",
    "             ,m=as.integer(dim(m)[1])\n",
    "             ,n=as.integer(dim(m)[2])\n",
    "             ,res=as.double(0)\n",
    "            )\n",
    "\n",
    "    return(res$res)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b470f59c",
   "metadata": {},
   "outputs": [],
   "source": [
    "dyn.load(\"sum2.so\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d8c35f6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "msizes = c()\n",
    "times_1 = c()\n",
    "times_2 = c()\n",
    "\n",
    "for(i in (1:100) * 10) {\n",
    "    m <- matrix(rnorm(i^2), i)\n",
    "    \n",
    "    times_1 = append(times_1, summary(system.time(sum1(m)))[1])\n",
    "    times_2 = append(times_2, summary(system.time(sum2(m)))[1])\n",
    "    msizes = append(msizes, i)\n",
    "}\n",
    "\n",
    "df = data.frame(size=msizes, sum_R = times_1, sum_c = times_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8df4275f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3ab35d35",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`geom_smooth()` using method = 'loess' and formula 'y ~ x'\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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qW2pw3kGWLoJoIdAADqyM/Njc3dq9RO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\npKWlqTzDHDmPJzOr86K1//XN4bqmuIcEpIJoCuq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bwpcaTL5IlCtnJEk95NYMOrVul8bl1DoHtK4BRto39cMAABTrSURBVBSVZ7PM6RMt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\nLekMZqMAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(data=melt(df, id.vars=\"size\"), aes(x=size, y=value)) +\n",
    "geom_point(aes(shape=variable)) + geom_smooth(aes(color=variable))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5fc59dc9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.0.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
