{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a3082d18-56df-4834-8963-586a5500bced",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.00463,
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     "exception": false,
     "start_time": "2025-01-30T07:35:54.792075",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Decoding Speed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "afceb91f-5b83-487f-96f9-5015002f5daf",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.012004,
     "end_time": "2025-01-30T07:35:54.811724",
     "exception": false,
     "start_time": "2025-01-30T07:35:54.799720",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# This cell is tagged `parameters` and will be override by `papermill`\n",
    "decoder: str = \"mwpm\"\n",
    "json_filename: str = \"speed-rsc-mwpm.json\"  # where to save the result, must be provided\n",
    "\n",
    "rounds: int = 200\n",
    "kwargs = dict(\n",
    "    min_time = 60,\n",
    "    min_shots = 50,\n",
    "    min_init_time = 0.1,\n",
    "    min_init_shots = 1,\n",
    ")\n",
    "max_per_round_time: float = 0.1  # if each round takes more than 100ms to decode, then do not run the next `d`, since it is not meaningful anymore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a8db5135",
   "metadata": {
    "papermill": {
     "duration": 0.007032,
     "end_time": "2025-01-30T07:35:54.820965",
     "exception": false,
     "start_time": "2025-01-30T07:35:54.813933",
     "status": "completed"
    },
    "tags": [
     "injected-parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "decoder = \"bposd\"\n",
    "json_filename = \"speed-rsc-bposd.json\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5e4bf8f4-0e7c-453e-aacd-18c9061a999c",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.015878,
     "end_time": "2025-01-30T07:35:54.839021",
     "exception": false,
     "start_time": "2025-01-30T07:35:54.823143",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "552dcc10-a319-487b-a20b-09221382176b",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.011235,
     "end_time": "2025-01-30T07:35:54.851885",
     "exception": false,
     "start_time": "2025-01-30T07:35:54.840650",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import psutil\n",
    "# psutil.Process().nice(0)# if on *ux\n",
    "# psutil.Process().nice(psutil.IDLE_PRIORITY_CLASS)# if on win"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f4ce38b6-65b8-4ec5-b097-aab9f6943e10",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 1.196476,
     "end_time": "2025-01-30T07:35:56.049860",
     "exception": false,
     "start_time": "2025-01-30T07:35:54.853384",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from qec_lego_bench.cli.decoding_speed import decoding_speed, DecodingSpeedResult\n",
    "from qec_lego_bench.hpc.job_store import Job, JobStore\n",
    "from qec_lego_bench.hpc.plotter.logical_error_rate_plotter import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2eb79028-afab-46a7-a36e-f567fd486716",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 70.781509,
     "end_time": "2025-01-30T07:37:06.832826",
     "exception": false,
     "start_time": "2025-01-30T07:35:56.051317",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "d_vec: [3, 5, 7, 9, 11, 13, 15, 17, 19, 23, 27, 31, 37, 43, 51]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating initialization of 4 shots, elapsed: 0.011766s, average: 2.942e-03s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating initialization of 8 shots, elapsed: 0.022475s, average: 2.809e-03s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating initialization of 16 shots, elapsed: 0.043854s, average: 2.741e-03s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating initialization of 32 shots, elapsed: 0.088681s, average: 2.771e-03s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating initialization of 64 shots, elapsed: 0.179157s, average: 2.799e-03s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "initialization time: 2.799e-03s\n",
      "\r\n",
      "\u001b[KEvaluating decoding of 50 shots, elapsed: 0.000803s, average: 1.606e-05s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 100 shots, elapsed: 0.000892s, average: 8.919e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 200 shots, elapsed: 0.002007s, average: 1.004e-05s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 400 shots, elapsed: 0.003434s, average: 8.586e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 800 shots, elapsed: 0.006883s, average: 8.604e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 1600 shots, elapsed: 0.013231s, average: 8.269e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 3200 shots, elapsed: 0.025951s, average: 8.110e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 6400 shots, elapsed: 0.050566s, average: 7.901e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 12800 shots, elapsed: 0.102120s, average: 7.978e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 25600 shots, elapsed: 0.197386s, average: 7.710e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 51200 shots, elapsed: 0.398926s, average: 7.792e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 102400 shots, elapsed: 0.794225s, average: 7.756e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 204800 shots, elapsed: 1.586909s, average: 7.749e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\u001b[KEvaluating decoding of 8517691 shots, elapsed: 66.012081s, average: 7.750e-06s per shot\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "decoding time: 7.750e-06s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "DecodingSpeedResult(elapsed=66.0120811343968, shots=8517691)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def generate_d_vec(ratio: float = 1.18, max_d: int = 51) -> list[int]:\n",
    "    d = 3\n",
    "    d_vec = [d]\n",
    "    while d <= max_d:\n",
    "        int_d = 2 * round(d / 2) + 1\n",
    "        if int_d != d_vec[-1]:\n",
    "            d_vec.append(int_d)\n",
    "        d *= ratio\n",
    "    return d_vec\n",
    "d_vec = generate_d_vec()\n",
    "print(\"d_vec:\", d_vec)\n",
    "p_vec = [0.00001, 0.0001, 0.001, 0.003, 0.01]\n",
    "\n",
    "def evaluation_function(d: int, p: float, rounds: int, verbose: bool = True) -> DecodingSpeedResult:\n",
    "    if verbose:\n",
    "        print(f\"d: {d}, p: {p}\")\n",
    "    return decoding_speed(decoder=decoder, code=f\"rsc(d={d},p={p})\", **kwargs, no_print=not verbose)\n",
    "\n",
    "jobs = [Job(d=d, p=p, rounds=rounds) for p in p_vec for d in d_vec[:1]]  # only add the smallest d and dynamically add others\n",
    "# evaluation_function(min(d_vec), min(p_vec), rounds)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebd460d0-efa9-4075-9a1d-a62791230623",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.001784,
     "end_time": "2025-01-30T07:37:06.836786",
     "exception": false,
     "start_time": "2025-01-30T07:37:06.835002",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Define the plot functionality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aea5f255-0cca-4a5b-a43d-f5d4b460d502",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.021905,
     "end_time": "2025-01-30T07:37:06.860853",
     "exception": false,
     "start_time": "2025-01-30T07:37:06.838948",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from decoding_time_plotter import DecodingTimePlotter\n",
    "\n",
    "plotter = DecodingTimePlotter(p_vec=p_vec, d_vec=d_vec, rounds=rounds, max_per_round_time=max_per_round_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1cfa5901-2d84-4321-90e2-220ac77b9da1",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.378912,
     "end_time": "2025-01-30T07:37:07.241863",
     "exception": false,
     "start_time": "2025-01-30T07:37:06.862951",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_store = JobStore(evaluation_function, jobs, result_type=DecodingSpeedResult, filename=json_filename)\n",
    "job_store.execute(loop_callback=plotter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2edb553-f1b5-41ba-9643-86978a83b3e8",
   "metadata": {
    "editable": true,
    "papermill": {
     "duration": 0.002206,
     "end_time": "2025-01-30T07:37:07.246485",
     "exception": false,
     "start_time": "2025-01-30T07:37:07.244279",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.6"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 73.771939,
   "end_time": "2025-01-30T07:37:07.670337",
   "environment_variables": {},
   "exception": null,
   "input_path": "decoding_speed_mwpm.ipynb",
   "output_path": "decoding_speed_bposd.ipynb",
   "parameters": {
    "decoder": "bposd",
    "json_filename": "speed-rsc-bposd.json"
   },
   "start_time": "2025-01-30T07:35:53.898398",
   "version": "2.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}