Best_sim.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2acb5f01-8ca1-4fc4-b5bb-3d5e2704eca4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-01-18T06:40:56.244107800Z",
     "start_time": "2024-01-18T06:40:32.836166800Z"
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   "outputs": [],
   "source": [
    "\"\"\"\n",
    "安装pySWATPlus\n",
    "   SPOTPY\n",
    "   mpi4py\n",
    "   MS mpi\n",
    "\n",
    "0、pySWATPlus 下载rar解压，用anaconda prompt界面cd到解压的文件夹，用pytohn setup.py install安装\n",
    "\n",
    "一、TxtinoutReader\n",
    "1.必须指定工作路径，否则工作路径会变成copy里的路径\n",
    "2.必须使用绝对路径\n",
    "3.网页教程的参数格式不对\n",
    "4.改变参数，不指定行id时，用 None\n",
    "\n",
    "二、FileReader\n",
    "1.读取文件不指定index时，必须用None,不可省略\n",
    "2.usecols省略的话，读取的df为空\n",
    "\n",
    "三、定义SWAT函数给SPOTPY用时注意以下几点\n",
    "1、SWAT模型的参数定义不要超过上下界，如(0, 1)用(0.001, 0.999)代替\n",
    "2、用pySWATPlus定义函数给simulation用时，尽量把只修改一次文件的语句放函数外面\n",
    "   例如， reader.set_beginning_and_end_year(2017, 2018)\n",
    "         reader.set_warmup(1)\n",
    "         reader.enable_object_in_print_prt(\"channel_sd\", True, False, False, False)\n",
    "   这些直接在root文件夹里手动改就行，不要写成代码，因为用mpiexec并行处理时，会导致文件被意想不到的修改\n",
    "\"\"\"\n",
    "%reset -f\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import spotpy as sp\n",
    "import shutil\n",
    "import mpi4py\n",
    "import sys\n",
    "from pySWATPlus.TxtinoutReader import TxtinoutReader\n",
    "from pySWATPlus.FileReader import FileReader\n",
    "from matplotlib import pyplot as plt\n",
    "from datetime import datetime\n",
    "cwd = \"E:/SPOTPY-and-pySWATPlus\""
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 用pySWATPlus定义huron_swat函数"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "ae7b3677bc95ebbf"
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  {
   "cell_type": "code",
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   "source": [
    "def huron_swat(reader, params, copy_path, show_output=False, delete_copy=True):\n",
    "    result = reader.copy_and_run(dir=copy_path,\n",
    "                                 params=params,\n",
    "                                 show_output=show_output\n",
    "                                 )\n",
    "    reader = FileReader(os.path.join(result, \"channel_sd_day.txt\"),\n",
    "                        has_units = True,\n",
    "                        index=None,\n",
    "                        usecols=[\"mon\", \"day\", \"yr\", \"unit\", \"flo_out\"],\n",
    "                        filter_by={\"unit\": 1}\n",
    "                        )\n",
    "    res = reader.df\n",
    "    res[\"Date\"] = pd.to_datetime(pd.DataFrame({\"year\": res[\"yr\"],\n",
    "                                               \"month\": res[\"mon\"],\n",
    "                                               \"day\": res[\"day\"]}))\n",
    "    res.drop(columns=[\"mon\", \"day\", \"yr\", \"unit\"], inplace=True)\n",
    "    if delete_copy:\n",
    "        shutil.rmtree(result, ignore_errors=True)\n",
    "    os.chdir(cwd) #改回当前路径\n",
    "    return res"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-18T06:40:56.254600800Z",
     "start_time": "2024-01-18T06:40:56.249757200Z"
    }
   },
   "id": "4e91506c349437fb",
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 定义SPOTPY类"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "e7548bd89a74b697"
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "class spot_swat():\n",
    "    def __init__(self, TxtInOut_abspath, copy_path, start_print, end_print,\n",
    "                 prior=sp.parameter.Uniform, obj_func=None,\n",
    "                 show_output=False, delete_copy=True):\n",
    "        self.reader = TxtinoutReader(TxtInOut_abspath)\n",
    "        self.copy_path = copy_path\n",
    "        self.start = start_print\n",
    "        self.end = end_print\n",
    "        self.obj_func = obj_func\n",
    "        self.show_output = show_output\n",
    "        self.delete_copy = delete_copy\n",
    "\n",
    "        self.params = [prior(\"lat_ttime\",0.51, 179.0, optguess = 39.70),\n",
    "                       prior(\"can_max\",0.01, 99.9, optguess = 89.84),\n",
    "                       prior(\"esco\",0.01,0.99, optguess = 0.018),\n",
    "                       prior(\"epco\",0.01, 0.99, optguess = 0.243),\n",
    "                       prior(\"cn3_swf\",0.01, 0.99, optguess = 0.613),\n",
    "                       prior(\"perco\",0.01, 0.99, optguess = 0.705),\n",
    "                       prior(\"pet_co\",0.71, 1.29, optguess = 0.79),\n",
    "                       prior(\"latq_co\",0.01, 0.99, optguess = 0.945),\n",
    "                       prior(\"cn_a\",30.0, 70.0, optguess = 49.2),\n",
    "                       prior(\"cn_b\",50.0, 80.0, optguess = 62.2),\n",
    "                       prior(\"cn_c\",70.0, 90.0, optguess = 89.3),\n",
    "                       prior(\"cn_d\",80.0, 95.0, optguess = 90.5),\n",
    "                       prior(\"gw_flo\",0.0, 2.0, optguess = 1.80),\n",
    "                       prior(\"dep_bot\",5.0, 50.0, optguess = 27.5),\n",
    "                       prior(\"dep_wt\",2.0, 20.0, optguess = 18.6),\n",
    "                       prior(\"flo_dist\",10.0, 200.0, optguess = 76.6),\n",
    "                       prior(\"bf_max\",0.11, 1.99, optguess =  1.49),\n",
    "                       prior(\"alpha_bf\",0.01, 0.99, optguess =  0.812),\n",
    "                       prior(\"revap\",0.021, 0.199, optguess = 0.119),\n",
    "                       prior(\"rchg_dp\",0.001, 0.100, optguess = 0.014),\n",
    "                       prior(\"spec_yld\",0.01, 0.49, optguess = 0.454),\n",
    "                       prior(\"flo_min\",0.1, 49.0, optguess = 23.9),\n",
    "                       prior(\"revap_min\",0.1, 49.0, optguess = 45.1),\n",
    "                       prior(\"fall_tmp\",-4.9, 4.9, optguess = -4.76),\n",
    "                       prior(\"melt_tmp\",-4.9, 4.9, optguess = 0.87),\n",
    "                       prior(\"melt_max_min\",0.1, 9.9, optguess = 9.28),\n",
    "                       prior(\"melt_lag\",0.01, 0.99, optguess = 0.253),\n",
    "                       prior(\"snow_h2o\",0.1, 499.9, optguess = 299.7),\n",
    "                       prior(\"cov50\",0.01, 0.99, optguess = 0.623),\n",
    "                       prior(\"dp\",0.1, 5999.9, optguess = 642.6),\n",
    "                       prior(\"t_fc\",0.1, 99.9, optguess = 9.45),\n",
    "                       prior(\"lag\",0.1, 99.9, optguess = 23.5),\n",
    "                       prior(\"rad\",3.1, 39.9, optguess = 21.0),\n",
    "                       prior(\"dist\",7601, 29999, optguess = 10673.9),\n",
    "                       prior(\"drain\",10.1, 50.9, optguess = 16.6),\n",
    "                       prior(\"pump\",0.1, 9.9, optguess = 8.80),\n",
    "                       prior(\"lat_kast\",0.02, 3.99, optguess = 3.82),\n",
    "                       prior(\"lai_noevap\",0.1, 9.9, optguess = 7.75),\n",
    "                       prior(\"sw_init\",0.01, 0.99, optguess = 0.021),\n",
    "                       prior(\"surq_lag\",1.1, 23.9, optguess = 13.1),\n",
    "                       prior(\"msk_co1\",0.1, 9.9, optguess = 2.49),\n",
    "                       prior(\"msk_co2\",0.1, 9.9, optguess = 5.99),\n",
    "                       prior(\"msk_x\",0.01, 0.29, optguess = 0.068),\n",
    "                       prior(\"evap_adj\",0.51, 0.99, optguess = 0.685),\n",
    "                       prior(\"scoef\",0.01, 0.99, optguess = 0.882),\n",
    "                       prior(\"surq_exp\",1.1, 2.9, optguess =  1.61),\n",
    "                       ]\n",
    "    def parameters(self):\n",
    "        return sp.parameter.generate(self.params)\n",
    "\n",
    "    def simulation(self, vector):\n",
    "        par = np.array(vector)\n",
    "        swat_params = {\"hydrology.hyd\":(\"name\", [(None,\"lat_ttime\", 39.7),\n",
    "                                                 (None,\"can_max\", 89.84),\n",
    "                                                 (None,\"esco\", 0.018),\n",
    "                                                 (None,\"epco\", 0.243),\n",
    "                                                 (None,\"cn3_swf\", 0.613),\n",
    "                                                 (None,\"perco\", 0.705),\n",
    "                                                 (None,\"pet_co\", 0.79),\n",
    "                                                 (None,\"latq_co\", 0.945),\n",
    "                                                 ],\n",
    "                                        ),\n",
    "                       \"cntable.lum\":(\"description\", [(None,\"cn_a\", 49.2),\n",
    "                                                      (None,\"cn_b\", 62.2),\n",
    "                                                      (None,\"cn_c\", 89.3),\n",
    "                                                      (None,\"cn_d\", 90.5),\n",
    "                                                      ],\n",
    "                                      ),\n",
    "                       \"aquifer.aqu\":(\"name\", [(None, \"gw_flo\", 1.80),\n",
    "                                               (None, \"dep_bot\", 27.5),\n",
    "                                               (None, \"dep_wt\", 18.6),\n",
    "                                               (None, \"flo_dist\", 76.6),\n",
    "                                               (None, \"bf_max\", 1.49),\n",
    "                                               (None, \"alpha_bf\", 0.812),\n",
    "                                               (None, \"revap\", 0.119),\n",
    "                                               (None, \"rchg_dp\", 0.014),\n",
    "                                               (None, \"spec_yld\", 0.454),\n",
    "                                               (None, \"flo_min\", 23.9),\n",
    "                                               (None, \"revap_min\", 45.1),\n",
    "                                              ],\n",
    "                                      ),\n",
    "                       \"snow.sno\":(\"name\", [(None, \"fall_tmp\", -4.76),\n",
    "                                            (None, \"melt_tmp\", 0.87),\n",
    "                                            (None, \"melt_max\", 9.28),\n",
    "                                            (None, \"melt_min\", 9.28),\n",
    "                                            (None, \"tmp_lag\", 0.253),\n",
    "                                            (None, \"snow_h2o\", 299.7),\n",
    "                                            (None, \"cov50\", 0.623),\n",
    "                                           ],\n",
    "                                   ),\n",
    "                       \"tiledrain.str\":(\"name\", [(None, \"dp\", 642.6),\n",
    "                                                 (None, \"t_fc\", 9.45),\n",
    "                                                 (None, \"lag\", 23.5),\n",
    "                                                 (None, \"rad\", 21.0),\n",
    "                                                 (None, \"dist\", 10673.9),\n",
    "                                                 (None, \"drain\", 16.6),\n",
    "                                                 (None, \"pump\", 8.80),\n",
    "                                                 (None, \"lat_ksat\", 3.82),\n",
    "                                                ],\n",
    "                                        ),\n",
    "                       \"parameters.bsn\":(\"igen\", [(None, \"lai_noevap\", 7.75),\n",
    "                                                  (None, \"sw_init\", 0.021),\n",
    "                                                  (None, \"surq_lag\", 13.1),\n",
    "                                                  (None, \"msk_co1\", 2.49),\n",
    "                                                  (None, \"msk_co2\", 5.99),\n",
    "                                                  (None, \"msk_x\", 0.068),\n",
    "                                                  (None, \"evap_adj\", 0.685),\n",
    "                                                  (None, \"scoef\", 0.999),#0.882\n",
    "                                                  (None, \"surq_exp\", 1.61),\n",
    "                                                 ],\n",
    "                                         ),\n",
    "                       }\n",
    "        sim = huron_swat(self.reader, swat_params, self.copy_path,\n",
    "                         show_output=self.show_output, delete_copy=self.delete_copy)\n",
    "        return sim[\"flo_out\"]\n",
    "\n",
    "    def evaluation(self):\n",
    "        obs = pd.read_csv(os.path.join(cwd,'TimeSeries\\\\04199000.csv'))\n",
    "        obs[\"Date\"] = pd.to_datetime(obs[\"Date\"])\n",
    "        obs = obs.loc[((obs[\"Date\"] >= self.start) & (obs[\"Date\"] <= self.end)),\"Q\"]\n",
    "        return obs\n",
    "    def objectivefunction(self, simulation, evaluation):\n",
    "        if not self.obj_func:\n",
    "            like = sp.objectivefunctions.nashsutcliffe(evaluation, simulation)\n",
    "        else:\n",
    "            like = self.obj_func(evaluation, simulation)\n",
    "        return like\n",
    "    "
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-18T06:40:56.281258300Z",
     "start_time": "2024-01-18T06:40:56.274684100Z"
    }
   },
   "id": "5cdefb95b70a4e4f",
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing the  Monte Carlo (MC) sampler  with  2  repetitions\n",
      "Starting the MC algorithm with 2 repetitions...\n",
      "SWAT+\n",
      "Revision 60.5.7\n",
      "Soil & Water Assessment Tool\n",
      "PC Version\n",
      "Program reading . . . executing\n",
      "Date of Sim   1/18/2024 Time  14:40:58\n",
      "reading from precipitation file         Time  14:40:58\n",
      "reading from temperature file           Time  14:40:58\n",
      "reading from solar radiation file       Time  14:40:58\n",
      "reading from relative humidity file     Time  14:40:58\n",
      "reading from wind file                  Time  14:40:58\n",
      "reading from wgn file                   Time  14:40:58\n",
      "reading from wx station file            Time  14:40:58\n",
      "Original Simulation        1   1  2017 Yr    1 of    4 Time  14:40:59\n",
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      "Original Simulation       12  20  2020 Yr    4 of    4 Time  14:42:11\n",
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      "Original Simulation       12  22  2020 Yr    4 of    4 Time  14:42:11\n",
      "Original Simulation       12  23  2020 Yr    4 of    4 Time  14:42:11\n",
      "Original Simulation       12  24  2020 Yr    4 of    4 Time  14:42:11\n",
      "Original Simulation       12  25  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  26  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  27  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  28  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  29  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  30  2020 Yr    4 of    4 Time  14:42:12\n",
      "Original Simulation       12  31  2020 Yr    4 of    4 Time  14:42:12\n",
      "Execution successfully completed\n",
      "Date of Sim   1/18/2024 Time  14:42:12\n",
      "1 of 2, min objf=-0.145871, max objf=-0.145871, time remaining: 00:00:00\n",
      "Initialize database...\n",
      "['csv', 'hdf5', 'ram', 'sql', 'custom', 'noData']\n",
      "* Database file 'Best.csv' created.\n",
      "SWAT+\n",
      "Revision 60.5.7\n",
      "Soil & Water Assessment Tool\n",
      "PC Version\n",
      "Program reading . . . executing\n",
      "Date of Sim   1/18/2024 Time  14:42:18\n",
      "reading from precipitation file         Time  14:42:18\n",
      "reading from temperature file           Time  14:42:18\n",
      "reading from solar radiation file       Time  14:42:18\n",
      "reading from relative humidity file     Time  14:42:18\n",
      "reading from wind file                  Time  14:42:18\n",
      "reading from wgn file                   Time  14:42:18\n",
      "reading from wx station file            Time  14:42:18\n",
      "Original Simulation        1   1  2017 Yr    1 of    4 Time  14:42:18\n",
      "Original Simulation        1   2  2017 Yr    1 of    4 Time  14:42:18\n",
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      "Original Simulation        1  18  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  19  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  20  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  21  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  22  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  23  2017 Yr    1 of    4 Time  14:42:19\n",
      "Original Simulation        1  24  2017 Yr    1 of    4 Time  14:42:19\n",
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      "Original Simulation        1  30  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        1  31  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2   1  2017 Yr    1 of    4 Time  14:42:20\n",
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      "Original Simulation        2   9  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  10  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  11  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  12  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  13  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  14  2017 Yr    1 of    4 Time  14:42:20\n",
      "Original Simulation        2  15  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  16  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  17  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  18  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  19  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  20  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  21  2017 Yr    1 of    4 Time  14:42:21\n",
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      "Original Simulation        2  23  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  24  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        2  25  2017 Yr    1 of    4 Time  14:42:21\n",
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      "Original Simulation        2  28  2017 Yr    1 of    4 Time  14:42:21\n",
      "Original Simulation        3   1  2017 Yr    1 of    4 Time  14:42:21\n",
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      "Original Simulation        3  10  2017 Yr    1 of    4 Time  14:42:22\n",
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      "Original Simulation       12  24  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  25  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  26  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  27  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  28  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  29  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  30  2020 Yr    4 of    4 Time  14:43:32\n",
      "Original Simulation       12  31  2020 Yr    4 of    4 Time  14:43:32\n",
      "Execution successfully completed\n",
      "Date of Sim   1/18/2024 Time  14:43:32\n",
      "2 of 2, min objf=-0.145871, max objf=-0.145871, time remaining: 23:59:06\n",
      "\n",
      "*** Final SPOTPY summary ***\n",
      "Total Duration: 160.73 seconds\n",
      "Total Repetitions: 2\n",
      "Minimal objective value: -0.145871\n",
      "Corresponding parameter setting:\n",
      "lat_ttime: 39.7877\n",
      "can_max: 46.8876\n",
      "esco: 0.952162\n",
      "epco: 0.0198389\n",
      "cn3_swf: 0.0790583\n",
      "perco: 0.253867\n",
      "pet_co: 1.04268\n",
      "latq_co: 0.0379211\n",
      "cn_a: 59.4521\n",
      "cn_b: 55.9783\n",
      "cn_c: 82.9544\n",
      "cn_d: 81.536\n",
      "gw_flo: 0.551905\n",
      "dep_bot: 35.9998\n",
      "dep_wt: 6.53222\n",
      "flo_dist: 160.869\n",
      "bf_max: 0.659625\n",
      "alpha_bf: 0.407095\n",
      "revap: 0.132928\n",
      "rchg_dp: 0.0596564\n",
      "spec_yld: 0.396641\n",
      "flo_min: 38.4179\n",
      "revap_min: 22.2048\n",
      "fall_tmp: 1.77796\n",
      "melt_tmp: 1.29765\n",
      "melt_max_min: 6.34905\n",
      "melt_lag: 0.126533\n",
      "snow_h2o: 210.417\n",
      "cov50: 0.958252\n",
      "dp: 5570.2\n",
      "t_fc: 7.6592\n",
      "lag: 55.6933\n",
      "rad: 24.4845\n",
      "dist: 29361.8\n",
      "drain: 27.3028\n",
      "pump: 1.20285\n",
      "lat_kast: 3.53151\n",
      "lai_noevap: 9.41272\n",
      "sw_init: 0.247397\n",
      "surq_lag: 2.67925\n",
      "msk_co1: 1.86646\n",
      "msk_co2: 2.45545\n",
      "msk_x: 0.070756\n",
      "evap_adj: 0.729859\n",
      "scoef: 0.923922\n",
      "surq_exp: 1.17533\n",
      "Maximal objective value: -0.145871\n",
      "Corresponding parameter setting:\n",
      "lat_ttime: 39.7877\n",
      "can_max: 46.8876\n",
      "esco: 0.952162\n",
      "epco: 0.0198389\n",
      "cn3_swf: 0.0790583\n",
      "perco: 0.253867\n",
      "pet_co: 1.04268\n",
      "latq_co: 0.0379211\n",
      "cn_a: 59.4521\n",
      "cn_b: 55.9783\n",
      "cn_c: 82.9544\n",
      "cn_d: 81.536\n",
      "gw_flo: 0.551905\n",
      "dep_bot: 35.9998\n",
      "dep_wt: 6.53222\n",
      "flo_dist: 160.869\n",
      "bf_max: 0.659625\n",
      "alpha_bf: 0.407095\n",
      "revap: 0.132928\n",
      "rchg_dp: 0.0596564\n",
      "spec_yld: 0.396641\n",
      "flo_min: 38.4179\n",
      "revap_min: 22.2048\n",
      "fall_tmp: 1.77796\n",
      "melt_tmp: 1.29765\n",
      "melt_max_min: 6.34905\n",
      "melt_lag: 0.126533\n",
      "snow_h2o: 210.417\n",
      "cov50: 0.958252\n",
      "dp: 5570.2\n",
      "t_fc: 7.6592\n",
      "lag: 55.6933\n",
      "rad: 24.4845\n",
      "dist: 29361.8\n",
      "drain: 27.3028\n",
      "pump: 1.20285\n",
      "lat_kast: 3.53151\n",
      "lai_noevap: 9.41272\n",
      "sw_init: 0.247397\n",
      "surq_lag: 2.67925\n",
      "msk_co1: 1.86646\n",
      "msk_co2: 2.45545\n",
      "msk_x: 0.070756\n",
      "evap_adj: 0.729859\n",
      "scoef: 0.923922\n",
      "surq_exp: 1.17533\n",
      "******************************\n"
     ]
    }
   ],
   "source": [
    "# 源文件路径和复制文件路径\n",
    "proj_path = os.path.join(cwd, \"Best_TxtInOut\")\n",
    "copy_path = os.path.join(cwd, \"Best_copy\")\n",
    "\n",
    "# 设置SWAT模拟时间范围\n",
    "start_sim = \"2017-01-01\"\n",
    "end_sim = \"2020-12-31\"\n",
    "\n",
    "# 设置SWAT输出时间范围\n",
    "start_print = \"2018-01-01\"\n",
    "end_print = \"2020-12-31\"\n",
    "\n",
    "# 输出选项\n",
    "show_output = True\n",
    "delete_copy = False\n",
    "\n",
    "# 目标函数\n",
    "obj_func = lambda evaluation, simulation: (\n",
    "    -sp.objectivefunctions.nashsutcliffe(evaluation, simulation)\n",
    ")\n",
    "\n",
    "# 实例化及采样\n",
    "spot_setup = spot_swat(proj_path, copy_path, start_print, end_print, obj_func=obj_func,\n",
    "                       show_output=show_output, delete_copy=delete_copy)\n",
    "\n",
    "spot_setup.reader.set_simulation_time(start_sim, end_sim)\n",
    "spot_setup.reader.set_print_time(start_print, end_print)\n",
    "spot_setup.reader.enable_object_in_print_prt(\"channel_sd\", True, False, False, False)\n",
    "\n",
    "sampler = sp.algorithms.mc(spot_setup,\n",
    "                           dbname=\"Best\", \n",
    "                           dbformat=\"csv\",\n",
    "                           )\n",
    "sampler.sample(repetitions=2,\n",
    "               # ngs=10,\n",
    "               )"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-18T06:43:37.098324900Z",
     "start_time": "2024-01-18T06:40:56.285457600Z"
    }
   },
   "id": "efd6fa65568daefd",
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run number 0 has the lowest objectivefunction with: -0.1459\n"
     ]
    },
    {
     "data": {
      "text/plain": "<matplotlib.legend.Legend at 0x2c095169690>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1800x1800 with 2 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Best_results = sp.analyser.load_csv_results(\"Best\")\n",
    "bestindex, bestobjf = sp.analyser.get_minlikeindex(Best_results)\n",
    "best_model_run = Best_results[bestindex]\n",
    "fields = [word for word in best_model_run.dtype.names if word.startswith(\"sim\")]\n",
    "best_simulation = np.array(list(best_model_run[fields]))\n",
    "obs = np.array(spot_setup.evaluation())\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(18,18))\n",
    "ax1.plot(Best_results['like1'])\n",
    "ax1.set_xlabel(\"iteration\")\n",
    "ax1.set_ylabel(\"-NSE\")\n",
    "\n",
    "ax2.plot(obs, \"r-\", label=\"obs\")\n",
    "ax2.plot(best_simulation, \"--\", markersize = 2 ,label=\"best objf. = \" + str(bestobjf))\n",
    "ax2.set_xlabel(\"Number of obs. points\")\n",
    "ax2.set_ylabel(\"Q (m3/s)\")\n",
    "ax2.legend()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-18T06:43:38.158184400Z",
     "start_time": "2024-01-18T06:43:37.098324900Z"
    }
   },
   "id": "94a2430c36284351",
   "execution_count": 5
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [
    "obs = np.array(spot_setup.evaluation())"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-18T06:43:38.167052Z",
     "start_time": "2024-01-18T06:43:38.157138400Z"
    }
   },
   "id": "131590bfb88b466d",
   "execution_count": 6
  }
 ],
 "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}