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   "source": [
    "# OPTaaS Batching\n",
    "\n",
    "### <span style=\"color:red\">Note:</span> To run this notebook, you need an API Key. You can get one <a href=\"mailto:info@mindfoundry.ai\">here</a>.\n",
    "\n",
    "OPTaaS can facilitate parallel computation, where you generate a batch of configurations, pass them to a number of workers to calculate the results, and then store the results to get the next batch of configurations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connect to OPTaaS using your API Key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(optaas.client)\n",
    "\n",
    "client <- OPTaaSClient$new(\"https://optaas.mindfoundry.ai\", \"Your OPTaaS API Key\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create your Task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "task <- client$create_task(\n",
    "    title=\"Batching Example\",\n",
    "    parameters=list(\n",
    "        FloatParameter('x', minimum = 0, maximum = 1),\n",
    "        FloatParameter('y', minimum = 0.1, maximum = 2)\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up your workers\n",
    "This is just a simple example of how you would pass a Configuration to a worker and get a Result back. Your process will of course likely be more complex!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(parallel)\n",
    "\n",
    "number_of_workers <- 4\n",
    "\n",
    "scoring_function <- function(configuration) {\n",
    "    x <- configuration$values[[\"x\"]]\n",
    "    y <- configuration$values[[\"y\"]]\n",
    "    Sys.sleep(1)  # Calculating score...\n",
    "    score <- (x * y) - (x / y)\n",
    "    Result$new(configuration=configuration, score=score)\n",
    "}\n",
    "\n",
    "spin_off_workers_and_get_results <- function(configurations) {\n",
    "    mclapply(configurations, scoring_function)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate the first batch of configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"list(x = 0.5, y = 1.05)\"     \"list(x = 0.25, y = 1.525)\"  \n",
      "[3] \"list(x = 0.75, y = 0.575)\"   \"list(x = 0.375, y = 0.8125)\"\n"
     ]
    }
   ],
   "source": [
    "configurations <- task$generate_configurations(number_of_workers)\n",
    "print(paste(lapply(configurations, `[[`, \"values\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Record results to get the next batch of configurations\n",
    "\n",
    "The next batch will be the same size as the number of results you record."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Batch 1\"\n",
      "[[1]]\n",
      "[1] 0.04880952\n",
      "\n",
      "[[2]]\n",
      "[1] 0.2173156\n",
      "\n",
      "[[3]]\n",
      "[1] -0.8730978\n",
      "\n",
      "[[4]]\n",
      "[1] -0.156851\n",
      "\n",
      "[1] \"Batch 2\"\n",
      "[[1]]\n",
      "[1] 1.045734\n",
      "\n",
      "[[2]]\n",
      "[1] 0.06385012\n",
      "\n",
      "[[3]]\n",
      "[1] -1.640914\n",
      "\n",
      "[[4]]\n",
      "[1] -0.5423534\n",
      "\n",
      "[1] \"Batch 3\"\n",
      "[[1]]\n",
      "[1] 0.5648003\n",
      "\n",
      "[[2]]\n",
      "[1] 0.08435553\n",
      "\n",
      "[[3]]\n",
      "[1] 1.5\n",
      "\n",
      "[[4]]\n",
      "[1] 0.9496137\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for (batch in seq(1, 3)) {\n",
    "    results <- spin_off_workers_and_get_results(configurations)\n",
    "    print(paste(\"Batch\", batch))\n",
    "    print(lapply(results, function(result) { result$score }))\n",
    "    flush.console()\n",
    "\n",
    "    configurations <- task$record_results(results)\n",
    "}"
   ]
  }
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