prepared_pca.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime\n",
    "import numpy as np\n",
    "data = pd.read_csv('./handel/work1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data['发动机转速']\n",
    "V = data['GPS车速']\n",
    "A = data['加速度']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 转数小于800且速度为0的静止点：怠速点\n",
    "dai_points = data[(V==0) & (X<=800)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 怠速点 下标\n",
    "dai_points_index = data[(V==0) & (X<=800)].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 算法 进行怠速区间划分\n",
    "\n",
    "# 整体区间列表，元素为tuple(consistant，left, right)\n",
    "# 若是连续区间,则consistant为True\n",
    "idling_list = []\n",
    "j = 1\n",
    "n = 0 \n",
    "for i in range(len(dai_points_index)-1):\n",
    "    delt = dai_points_index[j] - dai_points_index[i]\n",
    "    if delt>1.0:\n",
    "        # 保存连续怠速区间下标\n",
    "        idling_list.append((True, dai_points_index[i-n], dai_points_index[i]))\n",
    "        \n",
    "        # 保存不连续的怠速区间下标\n",
    "        idling_list.append((False, dai_points_index[i], dai_points_index[j]))\n",
    "        \n",
    "        n = 0\n",
    "    else:\n",
    "        n = n + 1 \n",
    "    j = j + 1  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       " (False, 58883, 58927),\n",
       " (True, 58927, 58935),\n",
       " (False, 58935, 58961),\n",
       " (True, 58961, 58965),\n",
       " (False, 58965, 58970),\n",
       " (True, 58970, 58970),\n",
       " (False, 58970, 58972),\n",
       " (True, 58972, 58981),\n",
       " (False, 58981, 59070),\n",
       " (True, 59070, 59077),\n",
       " (False, 59077, 59140),\n",
       " (True, 59140, 59158),\n",
       " (False, 59158, 59211),\n",
       " ...]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idling_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 删除所有长度大于180s的怠速区间\n",
    "def delete_three(idlings):\n",
    "    res = []\n",
    "    for tu in idlings:\n",
    "        if (tu[2] - tu[1]) <= 180:\n",
    "            res.append(tu)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 判断不连续怠速区间 是否有速度超过10km/h的点,若有则False\n",
    "def check_idling(tu):\n",
    "    # 不是怠速区间\n",
    "    if np.max(V[tu[1]:tu[2]+1]) > 10.0:\n",
    "        return False\n",
    "    else:\n",
    "        return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "idling_scale = delete_three(idling_list)\n",
    "result_list = []\n",
    "for tu in idling_scale:\n",
    "    # 连续怠速区间 直接加入\n",
    "    if tu[0]:\n",
    "        result_list.append(tu)\n",
    "    # 对不连续的怠速区间进行判断\n",
    "    else:\n",
    "        if check_idling(tu):\n",
    "            result_list.append(tu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       " (True, 41797, 41800),\n",
       " (False, 41800, 41805),\n",
       " (True, 41805, 41805),\n",
       " (False, 41805, 41811),\n",
       " (True, 41811, 41811),\n",
       " (False, 41811, 41813),\n",
       " (True, 41813, 41820),\n",
       " (True, 41934, 41935),\n",
       " (True, 41951, 41953),\n",
       " (True, 42074, 42093),\n",
       " (True, 42190, 42195),\n",
       " (True, 42293, 42293),\n",
       " (False, 42293, 42296),\n",
       " (True, 42296, 42296),\n",
       " (True, 42360, 42445),\n",
       " (True, 42561, 42595),\n",
       " (True, 42697, 42718),\n",
       " (False, 42718, 42725),\n",
       " (True, 42725, 42784),\n",
       " (False, 42784, 42795),\n",
       " (True, 42795, 42807),\n",
       " (False, 42807, 42813),\n",
       " (True, 42813, 42824),\n",
       " (False, 42824, 42831),\n",
       " (True, 42831, 42845),\n",
       " (False, 42845, 42847),\n",
       " (True, 42847, 42851),\n",
       " (True, 44836, 44854),\n",
       " (True, 45010, 45014),\n",
       " (False, 45014, 45019),\n",
       " (True, 45019, 45058),\n",
       " (False, 45058, 45067),\n",
       " (True, 45067, 45104),\n",
       " (True, 45179, 45209),\n",
       " (True, 45329, 45331),\n",
       " (True, 47202, 47228),\n",
       " (False, 47228, 47238),\n",
       " (True, 47238, 47270),\n",
       " (True, 47327, 47327),\n",
       " (False, 47327, 47329),\n",
       " (True, 47329, 47333),\n",
       " (True, 47438, 47439),\n",
       " (False, 47439, 47442),\n",
       " (True, 47442, 47451),\n",
       " (True, 47491, 47494),\n",
       " (True, 48591, 48593),\n",
       " (False, 48593, 48599),\n",
       " (True, 48599, 48632),\n",
       " (False, 48632, 48635),\n",
       " (True, 48635, 48655),\n",
       " (False, 48655, 48664),\n",
       " (True, 48664, 48674),\n",
       " (True, 49101, 49103),\n",
       " (True, 49125, 49134),\n",
       " (True, 49147, 49151),\n",
       " (False, 49151, 49260),\n",
       " (True, 49260, 49260),\n",
       " (False, 49260, 49268),\n",
       " (True, 49268, 49268),\n",
       " (False, 49268, 49270),\n",
       " (True, 49270, 49277),\n",
       " (False, 49277, 49283),\n",
       " (True, 49283, 49287),\n",
       " (False, 49287, 49293),\n",
       " (True, 49293, 49293),\n",
       " (False, 49293, 49295),\n",
       " (True, 49295, 49304),\n",
       " (False, 49304, 49308),\n",
       " (True, 49308, 49312),\n",
       " (True, 51024, 51029),\n",
       " (True, 51765, 51794),\n",
       " (True, 51942, 51945),\n",
       " (True, 52354, 52372),\n",
       " (True, 52744, 52745),\n",
       " (False, 52745, 52750),\n",
       " (True, 52750, 52750),\n",
       " (True, 53078, 53083),\n",
       " (False, 53083, 53106),\n",
       " (True, 53106, 53114),\n",
       " (True, 53211, 53224),\n",
       " (False, 53224, 53226),\n",
       " (True, 53226, 53227),\n",
       " (True, 53385, 53426),\n",
       " (True, 54196, 54197),\n",
       " (True, 54846, 54858),\n",
       " (True, 54877, 54880),\n",
       " (True, 54920, 54934),\n",
       " (True, 54952, 54952),\n",
       " (False, 54952, 54959),\n",
       " (True, 54959, 54975),\n",
       " (False, 54975, 54978),\n",
       " (True, 54978, 54978),\n",
       " (False, 54978, 54980),\n",
       " (True, 54980, 54987),\n",
       " (False, 54987, 54990),\n",
       " (True, 54990, 54990),\n",
       " (True, 55102, 55102),\n",
       " (False, 55102, 55107),\n",
       " (True, 55107, 55107),\n",
       " (False, 55107, 55109),\n",
       " (True, 55109, 55120),\n",
       " (False, 55120, 55123),\n",
       " (True, 55123, 55127),\n",
       " (True, 55247, 55260),\n",
       " (True, 55438, 55444),\n",
       " (False, 55444, 55449),\n",
       " (True, 55449, 55454),\n",
       " (False, 55454, 55457),\n",
       " (True, 55457, 55479),\n",
       " (False, 55479, 55516),\n",
       " (True, 55516, 55519),\n",
       " (False, 55519, 55521),\n",
       " (True, 55521, 55530),\n",
       " (False, 55530, 55536),\n",
       " (True, 55536, 55543),\n",
       " (True, 55829, 55834),\n",
       " (True, 55902, 55902),\n",
       " (True, 56252, 56253),\n",
       " (False, 56253, 56257),\n",
       " (True, 56257, 56258),\n",
       " (False, 56258, 56260),\n",
       " (True, 56260, 56261),\n",
       " (True, 56329, 56340),\n",
       " (False, 56340, 56342),\n",
       " (True, 56342, 56343),\n",
       " (True, 56369, 56370),\n",
       " (True, 56429, 56429),\n",
       " (True, 56563, 56566),\n",
       " (False, 56566, 56571),\n",
       " (True, 56571, 56575),\n",
       " (False, 56575, 56579),\n",
       " (True, 56579, 56589),\n",
       " (True, 56623, 56654),\n",
       " (True, 56722, 56729),\n",
       " (False, 56729, 56733),\n",
       " (True, 56733, 56747),\n",
       " (True, 56908, 56952),\n",
       " (False, 56952, 56958),\n",
       " (True, 56958, 56959),\n",
       " (True, 57009, 57029),\n",
       " (True, 57246, 57255),\n",
       " (True, 57341, 57343),\n",
       " (True, 57683, 57777),\n",
       " (True, 57922, 57935),\n",
       " (True, 58219, 58221),\n",
       " (True, 58267, 58268),\n",
       " (False, 58268, 58271),\n",
       " (True, 58271, 58297),\n",
       " (True, 58332, 58334),\n",
       " (True, 58355, 58361),\n",
       " (False, 58361, 58367),\n",
       " (True, 58367, 58391),\n",
       " (True, 58434, 58466),\n",
       " (True, 58700, 58700),\n",
       " (False, 58700, 58702),\n",
       " (True, 58702, 58703),\n",
       " (True, 58830, 58840),\n",
       " (False, 58840, 58851),\n",
       " (True, 58851, 58883),\n",
       " (True, 58927, 58935),\n",
       " (True, 58961, 58965),\n",
       " (False, 58965, 58970),\n",
       " (True, 58970, 58970),\n",
       " (False, 58970, 58972),\n",
       " (True, 58972, 58981),\n",
       " (True, 59070, 59077),\n",
       " (True, 59140, 59158),\n",
       " (True, 59211, 59276),\n",
       " (True, 59287, 59312),\n",
       " (True, 59487, 59520),\n",
       " (False, 59520, 59528),\n",
       " (True, 59528, 59529),\n",
       " (True, 59620, 59626),\n",
       " (True, 59703, 59723),\n",
       " (True, 59827, 59835),\n",
       " (False, 59835, 59837),\n",
       " (True, 59837, 59837),\n",
       " (True, 59945, 59967),\n",
       " (True, 60046, 60047),\n",
       " (False, 60047, 60056),\n",
       " (True, 60056, 60063),\n",
       " (True, 60172, 60186),\n",
       " (True, 60349, 60350),\n",
       " (False, 60350, 60354),\n",
       " (True, 60354, 60377),\n",
       " (True, 60518, 60529),\n",
       " (True, 60734, 60745),\n",
       " (False, 60745, 60749),\n",
       " (True, 60749, 60759),\n",
       " (True, 60776, 60859),\n",
       " (True, 60907, 60915),\n",
       " (False, 60915, 60917),\n",
       " (True, 60917, 60917),\n",
       " (True, 61028, 61087),\n",
       " (True, 61143, 61178),\n",
       " (True, 61216, 61220),\n",
       " (True, 61249, 61257),\n",
       " (True, 61302, 61302),\n",
       " (True, 61313, 61314),\n",
       " (True, 61394, 61418),\n",
       " (True, 61460, 61469),\n",
       " (True, 61510, 61550),\n",
       " (True, 61570, 61589),\n",
       " (True, 61640, 61643),\n",
       " (False, 61643, 61647),\n",
       " (True, 61647, 61668),\n",
       " (True, 61814, 61823),\n",
       " (False, 61823, 61883),\n",
       " (True, 61883, 61888),\n",
       " (True, 61914, 61915),\n",
       " (False, 61915, 61923),\n",
       " (True, 61923, 61924),\n",
       " (False, 61924, 61933),\n",
       " (True, 61933, 61952),\n",
       " (False, 61952, 61956),\n",
       " (True, 61956, 61961),\n",
       " (True, 62025, 62026),\n",
       " (True, 62137, 62139),\n",
       " (True, 62223, 62227),\n",
       " (True, 62408, 62409),\n",
       " (False, 62409, 62425),\n",
       " (True, 62425, 62427),\n",
       " (True, 62455, 62502),\n",
       " (False, 62502, 62506),\n",
       " (True, 62506, 62540),\n",
       " (True, 62639, 62667),\n",
       " (True, 62748, 62765),\n",
       " (True, 63284, 63324),\n",
       " (True, 63441, 63476),\n",
       " (True, 63489, 63489),\n",
       " (True, 63852, 63853),\n",
       " (True, 63900, 63903),\n",
       " (True, 63975, 63978),\n",
       " (False, 63978, 63980),\n",
       " (True, 63980, 63983),\n",
       " (False, 63983, 63985),\n",
       " (True, 63985, 64011),\n",
       " (False, 64011, 64023),\n",
       " (True, 64023, 64063),\n",
       " (True, 64123, 64134),\n",
       " (True, 64214, 64214),\n",
       " (True, 64280, 64284),\n",
       " (True, 64295, 64312),\n",
       " (True, 64332, 64334),\n",
       " (True, 64412, 64412),\n",
       " (True, 64456, 64460),\n",
       " (True, 64532, 64533),\n",
       " (True, 64653, 64653),\n",
       " (False, 64653, 64659),\n",
       " (True, 64659, 64691),\n",
       " (True, 64738, 64760),\n",
       " (True, 64815, 64820),\n",
       " (False, 64820, 64824),\n",
       " (True, 64824, 64858),\n",
       " (False, 64858, 64863),\n",
       " (True, 64863, 64866),\n",
       " (True, 65084, 65085),\n",
       " (True, 65329, 65329),\n",
       " (True, 65361, 65387),\n",
       " (True, 65507, 65602),\n",
       " (True, 65960, 65970),\n",
       " (True, 65981, 65984),\n",
       " (False, 65984, 65988),\n",
       " (True, 65988, 65991),\n",
       " (False, 65991, 65993),\n",
       " (True, 65993, 66044),\n",
       " (True, 66119, 66120),\n",
       " (True, 66191, 66192),\n",
       " (True, 66247, 66252),\n",
       " (True, 66314, 66314),\n",
       " (False, 66314, 66316),\n",
       " (True, 66316, 66320),\n",
       " (True, 66533, 66553),\n",
       " (True, 66749, 66755),\n",
       " (True, 66831, 66835),\n",
       " (True, 67013, 67035),\n",
       " (True, 67085, 67096),\n",
       " (True, 67134, 67159),\n",
       " (False, 67159, 67165),\n",
       " (True, 67165, 67172),\n",
       " (True, 67404, 67407),\n",
       " (True, 67499, 67500),\n",
       " (False, 67500, 67502),\n",
       " (True, 67502, 67514),\n",
       " (False, 67514, 67523),\n",
       " (True, 67523, 67525),\n",
       " (True, 67610, 67622),\n",
       " (False, 67622, 67635),\n",
       " (True, 67635, 67669),\n",
       " (True, 67748, 67748),\n",
       " (True, 67913, 67923),\n",
       " (True, 67982, 67986),\n",
       " (True, 68034, 68044),\n",
       " (True, 68122, 68137),\n",
       " (True, 68196, 68213),\n",
       " (True, 68254, 68284),\n",
       " (True, 68421, 68431),\n",
       " (False, 68431, 68435),\n",
       " (True, 68435, 68438),\n",
       " (True, 68484, 68490),\n",
       " (True, 68583, 68587),\n",
       " (False, 68587, 68597),\n",
       " (True, 68597, 68597),\n",
       " (False, 68597, 68600),\n",
       " (True, 68600, 68623),\n",
       " (False, 68623, 68713),\n",
       " (True, 68713, 68720),\n",
       " (True, 68816, 68834),\n",
       " (True, 69008, 69077),\n",
       " (True, 69107, 69110),\n",
       " (False, 69110, 69112),\n",
       " (True, 69112, 69113),\n",
       " (True, 69153, 69155),\n",
       " (True, 69182, 69182),\n",
       " (False, 69182, 69186),\n",
       " (True, 69186, 69222),\n",
       " (True, 69439, 69450),\n",
       " (False, 69450, 69457),\n",
       " (True, 69457, 69458),\n",
       " (False, 69458, 69476),\n",
       " (True, 69476, 69480),\n",
       " (False, 69480, 69495),\n",
       " (True, 69495, 69499),\n",
       " (True, 69546, 69546),\n",
       " (False, 69546, 69548),\n",
       " (True, 69548, 69549),\n",
       " (True, 69597, 69622),\n",
       " (False, 69622, 69624),\n",
       " (True, 69624, 69626),\n",
       " (True, 69879, 69895),\n",
       " (True, 69999, 70006),\n",
       " (False, 70006, 70028),\n",
       " (True, 70028, 70029),\n",
       " (False, 70029, 70033),\n",
       " (True, 70033, 70035),\n",
       " (False, 70035, 70041),\n",
       " (True, 70041, 70041),\n",
       " (False, 70041, 70043),\n",
       " (True, 70043, 70043),\n",
       " (True, 70056, 70071),\n",
       " (False, 70071, 70082),\n",
       " (True, 70082, 70089),\n",
       " (False, 70089, 70094),\n",
       " (True, 70094, 70094),\n",
       " (False, 70094, 70099),\n",
       " (True, 70099, 70100),\n",
       " (True, 70118, 70124),\n",
       " (True, 70229, 70259),\n",
       " (True, 70320, 70332),\n",
       " (True, 70583, 70593),\n",
       " (True, 70651, 70659),\n",
       " (True, 70696, 70696),\n",
       " (False, 70696, 70698),\n",
       " (True, 70698, 70699),\n",
       " (False, 70699, 70710),\n",
       " (True, 70710, 70748),\n",
       " (True, 70772, 70782),\n",
       " (True, 70837, 70848),\n",
       " (True, 70933, 70944),\n",
       " (True, 70985, 70987),\n",
       " (False, 70987, 70989),\n",
       " (True, 70989, 70990),\n",
       " (True, 71042, 71050),\n",
       " (False, 71050, 71065),\n",
       " (True, 71065, 71073),\n",
       " (True, 71112, 71117),\n",
       " (False, 71117, 71121),\n",
       " (True, 71121, 71122),\n",
       " (True, 71290, 71294),\n",
       " (True, 71310, 71315),\n",
       " (False, 71315, 71317),\n",
       " (True, 71317, 71318),\n",
       " (False, 71318, 71320),\n",
       " (True, 71320, 71327),\n",
       " (False, 71327, 71347),\n",
       " (True, 71347, 71349),\n",
       " (False, 71349, 71351),\n",
       " (True, 71351, 71352),\n",
       " (True, 71514, 71515),\n",
       " (False, 71515, 71517),\n",
       " (True, 71517, 71518),\n",
       " (True, 71626, 71627),\n",
       " (False, 71627, 71634),\n",
       " (True, 71634, 71656),\n",
       " (True, 71897, 71901),\n",
       " (True, 71947, 71956),\n",
       " (False, 71956, 71963),\n",
       " (True, 71963, 71964),\n",
       " (False, 71964, 71969),\n",
       " (True, 71969, 71969),\n",
       " (True, 72005, 72006),\n",
       " (False, 72006, 72008),\n",
       " (True, 72008, 72008),\n",
       " (True, 72083, 72083),\n",
       " (True, 72224, 72228),\n",
       " (False, 72228, 72235),\n",
       " (True, 72235, 72236),\n",
       " (True, 72301, 72313),\n",
       " (True, 72390, 72392),\n",
       " (True, 72479, 72494),\n",
       " (True, 72510, 72588),\n",
       " (False, 72588, 72603),\n",
       " (True, 72603, 72619),\n",
       " (True, 72644, 72699),\n",
       " (True, 72716, 72733),\n",
       " (True, 72783, 72799),\n",
       " (True, 72970, 72989),\n",
       " (True, 73053, 73054),\n",
       " (True, 73093, 73097),\n",
       " (False, 73097, 73099),\n",
       " (True, 73099, 73100),\n",
       " (True, 73186, 73263),\n",
       " (True, 73422, 73427),\n",
       " (True, 73610, 73639),\n",
       " (True, 73816, 73868),\n",
       " (True, 73892, 73893),\n",
       " (False, 73893, 73895),\n",
       " (True, 73895, 73898),\n",
       " (True, 73947, 73948),\n",
       " (True, 73963, 73967),\n",
       " (False, 73967, 73971),\n",
       " (True, 73971, 73985),\n",
       " (True, 74193, 74207),\n",
       " (True, 74275, 74289),\n",
       " (False, 74289, 74291),\n",
       " (True, 74291, 74293),\n",
       " (False, 74293, 74308),\n",
       " (True, 74308, 74317),\n",
       " (False, 74317, 74319),\n",
       " (True, 74319, 74320),\n",
       " (False, 74320, 74322),\n",
       " (True, 74322, 74332),\n",
       " (False, 74332, 74335),\n",
       " (True, 74335, 74337),\n",
       " (True, 74365, 74438),\n",
       " (False, 74438, 74442),\n",
       " (True, 74442, 74444),\n",
       " (True, 74611, 74629),\n",
       " (True, 74835, 74852),\n",
       " (True, 75862, 75883),\n",
       " (True, 76036, 76081),\n",
       " (True, 76194, 76198),\n",
       " (True, 76226, 76261),\n",
       " (True, 76313, 76315),\n",
       " (False, 76315, 76320),\n",
       " (True, 76320, 76327),\n",
       " (False, 76327, 76329),\n",
       " (True, 76329, 76329),\n",
       " (False, 76329, 76347),\n",
       " (True, 76347, 76351),\n",
       " (False, 76351, 76359),\n",
       " (True, 76359, 76361),\n",
       " (False, 76361, 76364),\n",
       " (True, 76364, 76375),\n",
       " (True, 76404, 76409),\n",
       " (False, 76409, 76412),\n",
       " (True, 76412, 76412),\n",
       " (True, 76430, 76434),\n",
       " (True, 76489, 76497),\n",
       " (True, 76569, 76619),\n",
       " (False, 76619, 76622),\n",
       " (True, 76622, 76622),\n",
       " (False, 76622, 76624),\n",
       " (True, 76624, 76672),\n",
       " (False, 76672, 76687),\n",
       " (True, 76687, 76690),\n",
       " (False, 76690, 76697),\n",
       " (True, 76697, 76703),\n",
       " (False, 76703, 76711),\n",
       " (True, 76711, 76711),\n",
       " (True, 76736, 76750),\n",
       " (True, 76838, 76870),\n",
       " (True, 76995, 77018),\n",
       " (True, 77340, 77362),\n",
       " (True, 77765, 77766),\n",
       " (False, 77766, 77768),\n",
       " (True, 77768, 77768),\n",
       " (True, 77789, 77789),\n",
       " ...]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 最终怠速区间\n",
    "result_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3810"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 原始怠速区间\n",
    "len(idling_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3555"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去掉>180\n",
    "len(idling_scale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2643"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 去掉<10km/h，最终怠速区间\n",
    "len(result_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_v_list = []\n",
    "a_s_list = []\n",
    "a_plus_list = []\n",
    "a_mis_list = []\n",
    "idling_rate_list = []\n",
    "a_pos_list = []\n",
    "a_neg_list = []\n",
    "v_std_list = []\n",
    "a_std_list = []\n",
    "\n",
    "for i in range(len(result_list)-1):\n",
    "    end_tu = result_list[i+1]\n",
    "    start_tu = result_list[i]\n",
    "    \n",
    "    # 怠速区间[idling_start,idling_end]\n",
    "    idling_start = start_tu[1]\n",
    "    idling_end = start_tu[2]\n",
    "    \n",
    "    # 运动学片段区间[idling_start,idling_end]\n",
    "    fragment_start = idling_start\n",
    "    fragment_end = end_tu[1]\n",
    "    \n",
    "    # 全区间时间点长度\n",
    "    all_length = fragment_end - fragment_start + 1\n",
    "    \n",
    "    # 怠速区间时间点个数\n",
    "    idling_length = idling_end - idling_start + 1\n",
    "    \n",
    "    # 平均速度\n",
    "    a_v = np.mean(V[fragment_start:fragment_end+1])\n",
    "    a_v_list.append(a_v)\n",
    "    # 平均行驶速度\n",
    "    a_s = np.mean(V[idling_end:fragment_end+1])\n",
    "    a_s_list.append(a_s)\n",
    "    \n",
    "    \n",
    "    # 全区间加速度\n",
    "    a_list = A[fragment_start:fragment_end+1]\n",
    "    # 全区间加速度\n",
    "    a_jia = a_list[a_list>=0]\n",
    "    # 全区间减速度\n",
    "    a_jian = a_list[a_list<0]\n",
    "    \n",
    "    # 平均加速度\n",
    "    a_plus = np.sum(a_jia) / all_length\n",
    "    a_plus_list.append(a_plus)\n",
    "    \n",
    "    # 平均减速度\n",
    "    a_mis = np.sum(a_jian) / all_length\n",
    "    a_mis_list.append(a_mis)\n",
    "    \n",
    "    # 怠速时间比\n",
    "    idling_rate = idling_length / all_length\n",
    "    idling_rate_list.append(idling_rate)\n",
    "    \n",
    "    # 加速时间比\n",
    "    a_pos = len(a_jia) / all_length\n",
    "    a_pos_list.append(a_pos)\n",
    "    \n",
    "    # 减速时间比\n",
    "    a_neg = len(a_jian) / all_length\n",
    "    a_neg_list.append(a_neg)\n",
    "    \n",
    "    # 速度标准差\n",
    "    v_std = np.std(V[fragment_start:fragment_end+1])\n",
    "    v_std_list.append(v_std)\n",
    "    \n",
    "    # 加速度标准差\n",
    "    a_std = np.std(a_jia)\n",
    "    a_std_list.append(a_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "prepare_pca = pd.DataFrame({\n",
    "    '平均速度': a_v_list,\n",
    "    '平均行驶速度': a_s_list,\n",
    "    '平均加速度': a_plus_list,\n",
    "    '平均减速度': a_mis_list,\n",
    "    '怠速时间比': idling_rate_list,\n",
    "    '加速时间比': a_pos_list,\n",
    "    '减速时间比': a_neg_list,\n",
    "    '速度标准差': v_std_list,\n",
    "    '加速度标准差': a_std_list\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "prepare_pca.to_csv('prepare_pca1.csv', index=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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