{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A Pseudoproxy Experiment with GraphEM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected time to run through: 10 mins**\n",
    "\n",
    "This tutorial demonstrates how to get a reconstruction using GraphEM, leveraging a simple pseudoproxy dataset generated from a subset of iCESM gridded dataset.\n",
    "The pseudoproxy are generated based on the original iCESM simulated `tas` plus white noise with `SNR=1`, using below code block:\n",
    "\n",
    "```python\n",
    "# gen pseudoproxy\n",
    "\n",
    "SNR = 1\n",
    "\n",
    "pp = np.copy(tas_sub)\n",
    "nt, nlat, nlon = np.shape(pp)\n",
    "\n",
    "k = 0\n",
    "for i in range(nlat):\n",
    "    for j in range(nlon):\n",
    "        tas_std = np.std(tas_sub[:,i,j])\n",
    "        noise_std = tas_std / SNR\n",
    "        \n",
    "        np.random.seed(k)\n",
    "        pp[:,i,j] += np.random.normal(0, noise_std, size=nt)\n",
    "        \n",
    "        k += 1\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test data preparation\n",
    "\n",
    "To go through this tutorial, please prepare test data following the steps:\n",
    "\n",
    "Download the test case named “PPE” with this [link](https://drive.google.com/drive/folders/1QpXqFgCBA4QMb7vqGIWxptkhWTJp0e8c?usp=sharing).\n",
    "Create a directory named “testcases” in the same directory where this notebook sits.\n",
    "Put the unzipped direcotry “PPE” into “testcases”.\n",
    "\n",
    "Below, we first load some useful packages, including our `GraphEM`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import LMRt\n",
    "import GraphEM\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as  plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reconstruction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "job = GraphEM.ReconJob()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mGraphEM: job.load_configs() >>> loading reconstruction configurations from: ./testcases/PPE/configs.yml\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.load_configs() >>> job.configs created\u001b[0m\n",
      "\u001b[1m\u001b[36mGraphEM: job.load_configs() >>> job.configs[\"job_dirpath\"] = /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/recon\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.load_configs() >>> /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/recon created\u001b[0m\n",
      "{'anom_period': [1951, 1980],\n",
      " 'calib_period': [1750, 1849],\n",
      " 'job_dirpath': '/Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/recon',\n",
      " 'job_id': 'LMRt_quickstart',\n",
      " 'obs_path': {'tas': './data/obs/iCESM_subset.nc'},\n",
      " 'obs_varname': {'lat': 'lat', 'lon': 'lon', 'tas': 'tas'},\n",
      " 'proxydb_path': './data/proxy/pseudoproxy_dataset.pkl',\n",
      " 'ptype_list': ['coral.d18O'],\n",
      " 'recon_period': [850, 1849]}\n"
     ]
    }
   ],
   "source": [
    "job.load_configs('./testcases/PPE/configs.yml', verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mGraphEM: job.load_proxydb() >>> job.configs[\"proxydb_path\"] = /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/data/proxy/pseudoproxy_dataset.pkl\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.load_proxydb() >>> 100 records loaded\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.load_proxydb() >>> job.proxydb created\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.load_proxydb(verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mGraphEM: job.filter_proxydb() >>> filtering proxy records according to: ['coral.d18O']\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.filter_proxydb() >>> 100 records remaining\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.filter_proxydb(verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mGraphEM: job.load_obs() >>> loading instrumental observation fields from: {'tas': '/Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/data/obs/iCESM_subset.nc'}\u001b[0m\n",
      "Time axis not overlap with the reference period [1951, 1980]; use its own time period as reference [850.00, 1849.00].\n",
      "\u001b[1m\u001b[32mGraphEM: job.load_obs() >>> job.obs created\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.load_obs(verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset Overview\n",
      "-----------------------\n",
      "\n",
      "     Name:  tas\n",
      "   Source:  /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/data/obs/iCESM_subset.nc\n",
      "    Shape:  time:1000, lat:10, lon:10\n"
     ]
    }
   ],
   "source": [
    "print(job.obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the loaded iCESM simulation and the pseudoproxy dataset are already annualized, we can skip the `.seasonalize()` steps and run `.prep_data()` directly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.recon_time created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.calib_time created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.calib_idx created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.temp created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.df_proxy created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.proxy created\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.prep_data() >>> job.lonlat created\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.prep_data(verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>1849.0</th>\n",
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       "      <td>...</td>\n",
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       "      <td>299.400078</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            pp_000      pp_001      pp_002      pp_003      pp_004  \\\n",
       "850.0   300.751783  300.699385  299.718651  300.717691  299.793416   \n",
       "851.0   300.496749  300.009875  300.193606  300.365040  300.347096   \n",
       "852.0   300.902166  300.334244  299.602851  300.671260  300.102458   \n",
       "853.0   301.729269  300.347924  301.572955  299.850196  301.104819   \n",
       "854.0   301.378359  300.997108  299.769165  300.429641  300.280460   \n",
       "...            ...         ...         ...         ...         ...   \n",
       "1845.0  300.370235  300.113197  300.144971  299.726555  299.921271   \n",
       "1846.0  299.985712  298.994364  300.207191  299.883894  300.684450   \n",
       "1847.0  300.292753  300.177510  300.033955  300.236235  299.559872   \n",
       "1848.0  299.823016  300.400975  300.223044  300.913630  300.261049   \n",
       "1849.0  300.161352  300.159181  300.246488  299.820504  299.517483   \n",
       "\n",
       "            pp_005      pp_006      pp_007      pp_008      pp_009  ...  \\\n",
       "850.0   299.939352  299.472350  300.551011  299.553801  299.413664  ...   \n",
       "851.0   299.853183  300.380611  299.650771  300.502845  299.614965  ...   \n",
       "852.0   301.886292  300.641600  300.462630  299.210613  299.595454  ...   \n",
       "853.0   300.567805  300.145062  300.817268  299.709402  300.448917  ...   \n",
       "854.0   300.495473  298.998074  299.858000  298.895901  299.967372  ...   \n",
       "...            ...         ...         ...         ...         ...  ...   \n",
       "1845.0  300.382517  299.913085  299.789860  299.300107  299.261318  ...   \n",
       "1846.0  300.181971  300.745885  299.919197  298.775608  299.324020  ...   \n",
       "1847.0  299.877648  299.141349  299.497879  299.952182  299.577197  ...   \n",
       "1848.0  300.159285  299.311807  299.449942  299.660750  298.979497  ...   \n",
       "1849.0  299.951131  299.332212  299.316922  299.630661  299.881939  ...   \n",
       "\n",
       "            pp_090      pp_091      pp_092      pp_093      pp_094  \\\n",
       "850.0   299.249156  299.027787  299.182322  299.526141  299.161496   \n",
       "851.0   299.103565  298.778987  299.141563  299.335989  299.410467   \n",
       "852.0   299.289380  299.249218  299.134434  299.942948  298.988984   \n",
       "853.0   299.573146  299.649931  298.838391  299.710779  300.040319   \n",
       "854.0   300.078972  300.040279  299.551374  300.088576  298.790187   \n",
       "...            ...         ...         ...         ...         ...   \n",
       "1845.0  299.482236  299.063248  299.152310  298.784250  298.994037   \n",
       "1846.0  299.544706  299.056843  299.350263  299.165946  299.459059   \n",
       "1847.0  299.724081  300.424495  299.179294  299.375003  299.475237   \n",
       "1848.0  299.829125  299.592597  300.013318  299.155958  299.107011   \n",
       "1849.0  299.587589  298.878817  298.997188  298.895755  299.134630   \n",
       "\n",
       "            pp_095      pp_096      pp_097      pp_098      pp_099  \n",
       "850.0   298.628304  298.802706  298.107757  298.818966  298.544758  \n",
       "851.0   298.670001  298.838717  298.689713  299.370283  299.494514  \n",
       "852.0   299.277950  298.905532  298.840735  299.414093  299.140887  \n",
       "853.0   299.609617  299.473822  299.656169  299.019936  299.719184  \n",
       "854.0   299.790875  299.441056  299.184892  299.035147  299.345002  \n",
       "...            ...         ...         ...         ...         ...  \n",
       "1845.0  298.300974  299.091353  298.409069  298.584221  298.305443  \n",
       "1846.0  299.227588  299.156746  299.367724  299.111197  298.400678  \n",
       "1847.0  299.947260  300.159204  299.223168  299.384652  299.483399  \n",
       "1848.0  299.086289  299.878042  299.307766  299.593688  298.706442  \n",
       "1849.0  299.284257  299.369434  299.400078  299.026855  299.096824  \n",
       "\n",
       "[1000 rows x 100 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job.df_proxy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1000, 100)\n",
      "(1000, 100)\n",
      "(200, 2)\n"
     ]
    }
   ],
   "source": [
    "print(np.shape(job.temp))\n",
    "print(np.shape(job.proxy))\n",
    "print(np.shape(job.lonlat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mLMRt: job.save_job() >>> Prepration data saved to: /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/recon/job.pkl\u001b[0m\n",
      "\u001b[1m\u001b[36mLMRt: job.save_job() >>> job.configs[\"prep_savepath\"] = /Users/fzhu/Github/GraphEM/docsrc/tutorial/testcases/PPE/recon/job.pkl\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.save(verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estimating graph using neighborhood method\n",
      "Running GraphEM:\n",
      "\n",
      "Iter     dXmis     rdXmis\n",
      "\n",
      "001     0.0514     3.1516\n",
      "002     0.4586     8.5151\n",
      "003     0.0562     0.1136\n",
      "004     0.0292     0.0566\n",
      "005     0.0149     0.0287\n",
      "006     0.0123     0.0235\n",
      "007     0.0107     0.0203\n",
      "008     0.0092     0.0174\n",
      "009     0.0081     0.0152\n",
      "010     0.0073     0.0137\n",
      "011     0.0067     0.0126\n",
      "012     0.0063     0.0117\n",
      "013     0.0059     0.0110\n",
      "014     0.0055     0.0103\n",
      "015     0.0053     0.0098\n",
      "016     0.0050     0.0094\n",
      "017     0.0048     0.0090\n",
      "018     0.0047     0.0087\n",
      "019     0.0045     0.0084\n",
      "020     0.0044     0.0082\n",
      "021     0.0043     0.0079\n",
      "022     0.0041     0.0077\n",
      "023     0.0040     0.0075\n",
      "024     0.0039     0.0072\n",
      "025     0.0038     0.0070\n",
      "026     0.0036     0.0068\n",
      "027     0.0035     0.0065\n",
      "028     0.0034     0.0063\n",
      "029     0.0033     0.0061\n",
      "030     0.0032     0.0059\n",
      "031     0.0031     0.0057\n",
      "032     0.0030     0.0055\n",
      "033     0.0029     0.0053\n",
      "034     0.0028     0.0051\n",
      "035     0.0027     0.0050\n",
      "\u001b[1m\u001b[32mGraphEM: job.run_solver() >>> job.G created and saved to: ./testcases/PPE/recon/G.pkl\u001b[0m\n",
      "\u001b[1m\u001b[32mGraphEM: job.run_solver() >>> job.recon created\u001b[0m\n",
      "CPU times: user 18.2 s, sys: 3.42 s, total: 21.6 s\n",
      "Wall time: 3.45 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "save_path = './testcases/PPE/recon/G.pkl'\n",
    "job.run_solver(save_path=save_path, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[36mLMRt: job.save_recon() >>> Reconstruction saved to: ./testcases/PPE/recon/recon.nc\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "job.save_recon('./testcases/PPE/recon/recon.nc', verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:  (lat: 10, lon: 10, year: 1000)\n",
      "Coordinates:\n",
      "  * year     (year) int64 850 851 852 853 854 855 ... 1845 1846 1847 1848 1849\n",
      "  * lat      (lat) float32 -4.737 -2.842 -0.9474 0.9474 ... 8.526 10.42 12.32\n",
      "  * lon      (lon) float32 162.5 165.0 167.5 170.0 ... 177.5 180.0 182.5 185.0\n",
      "Data variables:\n",
      "    recon    (year, lat, lon) float64 ...\n"
     ]
    }
   ],
   "source": [
    "with xr.open_dataset('./testcases/PPE/recon/recon.nc') as ds:\n",
    "    print(ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "target = job.obs.fields['tas'].value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean MSE = 0.0206, Mean RE = 0.9000, Mean CE = 0.8999, Mean R2 = 0.9022\n"
     ]
    }
   ],
   "source": [
    "nt = np.size(ds['year'])\n",
    "temp_r = job.recon.reshape((nt, -1))\n",
    "V = GraphEM.solver.verif_stats(temp_r,target.reshape((nt, -1)), job.calib_idx)\n",
    "print(V)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Map of CE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, 10)\n"
     ]
    }
   ],
   "source": [
    "ce = LMRt.utils.coefficient_efficiency(target, ds['recon'])\n",
    "print(np.shape(ce))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "\n",
    "fig = plt.figure(figsize=[5, 5])\n",
    "ax = plt.subplot(projection=ccrs.PlateCarree(central_longitude=180))\n",
    "ax.set_title('Coefficient of Efficiency')\n",
    "latlon_range = [50, 300, -45, 45]\n",
    "transform=ccrs.PlateCarree()\n",
    "\n",
    "ax.set_extent(latlon_range, crs=transform)\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=False)\n",
    "lat_formatter = LatitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "lon_ticks=[60, 120, 180, 240, 300]\n",
    "lat_ticks=[-90, -45, 0, 45, 90]\n",
    "lon_ticks = np.array(lon_ticks)\n",
    "lat_ticks = np.array(lat_ticks)\n",
    "lon_min, lon_max, lat_min, lat_max = latlon_range\n",
    "mask_lon = (lon_ticks >= lon_min) & (lon_ticks <= lon_max)\n",
    "mask_lat = (lat_ticks >= lat_min) & (lat_ticks <= lat_max)\n",
    "ax.set_xticks(lon_ticks[mask_lon], crs=ccrs.PlateCarree())\n",
    "ax.set_yticks(lat_ticks[mask_lat], crs=ccrs.PlateCarree())\n",
    "\n",
    "levels = np.linspace(0, 1, 21)\n",
    "cbar_labels = np.linspace(0, 1, 11)\n",
    "cbar_title = 'CE'\n",
    "extend = 'both'\n",
    "cmap = 'Reds'\n",
    "cbar_pad=0.1\n",
    "cbar_orientation='horizontal'\n",
    "cbar_aspect=10\n",
    "cbar_fraction=0.35\n",
    "cbar_shrink=0.8\n",
    "font_scale=1.5\n",
    "land_color=sns.xkcd_rgb['light grey']\n",
    "ocean_color=sns.xkcd_rgb['white']\n",
    "        \n",
    "ax.add_feature(cfeature.LAND, facecolor=land_color, edgecolor=land_color)\n",
    "ax.add_feature(cfeature.OCEAN, facecolor=ocean_color, edgecolor=ocean_color)\n",
    "ax.coastlines()\n",
    "im = ax.contourf(ds['lon'].values, ds['lat'].values, ce, levels, transform=transform, cmap=cmap, extend=extend)\n",
    "cbar = fig.colorbar(\n",
    "    im, ax=ax, orientation=cbar_orientation, pad=cbar_pad, aspect=cbar_aspect,\n",
    "    fraction=cbar_fraction, shrink=cbar_shrink)\n",
    "cbar.set_ticks(cbar_labels)\n",
    "cbar.ax.set_title(cbar_title, x=-0.05, y=0.1)\n",
    "    \n",
    "LMRt.showfig(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean timeseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyleoclim as pyleo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "def geo_mean(field, lat):\n",
    "    m = np.average(\n",
    "        np.average(field, axis=-1), axis=-1, weights=np.cos(np.deg2rad(lat))\n",
    "    )\n",
    "    return m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m_target = geo_mean(job.obs.fields['tas'].value, job.obs.fields['tas'].lat) \n",
    "ts_target = pyleo.Series(time=job.obs.fields['tas'].time, value=m_target)\n",
    "\n",
    "m_recon = geo_mean(ds['recon'].values, ds['lat'].values)\n",
    "ts_recon = pyleo.Series(time=ds['year'].values, value=m_recon)\n",
    "\n",
    "fig, ax = ts_target.plot(mute=True, label='target')\n",
    "ts_recon.plot(ax=ax, label='recon')\n",
    "ax.plot(ds['year'].values, m_target-m_recon, label='diff')\n",
    "ax.legend()\n",
    "pyleo.showfig(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}