notebooks/_poc_flux_bottom_velocity_inputs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.017761,
     "end_time": "2020-06-18T18:34:25.701032",
     "exception": false,
     "start_time": "2020-06-18T18:34:25.683271",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Compute input datasets for sedflux generation from model output\n",
    "\n",
    "Generate a set of files for each of the following groups:\n",
    "\n",
    "- POC-FLUX: ['POC_FLUX_IN']\n",
    "- Velocity: ['UVEL', 'VVEL']\n",
    "\n",
    "Steps:\n",
    "1. Produce files on a set of source grids\n",
    "1. Optionally generate on a set of destination grids\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:25.750044Z",
     "iopub.status.busy": "2020-06-18T18:34:25.749271Z",
     "iopub.status.idle": "2020-06-18T18:34:28.832960Z",
     "shell.execute_reply": "2020-06-18T18:34:28.833296Z"
    },
    "papermill": {
     "duration": 3.104887,
     "end_time": "2020-06-18T18:34:28.833450",
     "exception": false,
     "start_time": "2020-06-18T18:34:25.728563",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Cannot write to data cache '/glade/p/cesmdata/cseg'. Will not be able to download remote data files. Use environment variable 'CESMDATAROOT' to specify another directory.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import shutil\n",
    "from glob import glob\n",
    "\n",
    "from itertools import product\n",
    "\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import esmlab\n",
    "import esmlab_regrid\n",
    "\n",
    "import pop_tools\n",
    "\n",
    "import util"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:28.879383Z",
     "iopub.status.busy": "2020-06-18T18:34:28.878999Z",
     "iopub.status.idle": "2020-06-18T18:34:28.881446Z",
     "shell.execute_reply": "2020-06-18T18:34:28.881851Z"
    },
    "papermill": {
     "duration": 0.024983,
     "end_time": "2020-06-18T18:34:28.881952",
     "exception": false,
     "start_time": "2020-06-18T18:34:28.856969",
     "status": "completed"
    },
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "clobber = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.015041,
     "end_time": "2020-06-18T18:34:28.912448",
     "exception": false,
     "start_time": "2020-06-18T18:34:28.897407",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Build and test horizontal regridding\n",
    "\n",
    "### Generate SCRIP grid files for each of the supported grids.\n",
    "\n",
    "Ideally, a regridding workflow would support this in situ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:28.945673Z",
     "iopub.status.busy": "2020-06-18T18:34:28.945276Z",
     "iopub.status.idle": "2020-06-18T18:34:37.061558Z",
     "shell.execute_reply": "2020-06-18T18:34:37.062079Z"
    },
    "papermill": {
     "duration": 8.134762,
     "end_time": "2020-06-18T18:34:37.062212",
     "exception": false,
     "start_time": "2020-06-18T18:34:28.927450",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "grids = {\n",
    "    grid_name: pop_tools.get_grid(grid_name) \n",
    "    for grid_name in util.POP_grids\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.015868,
     "end_time": "2020-06-18T18:34:37.097193",
     "exception": false,
     "start_time": "2020-06-18T18:34:37.081325",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Construct weight file names and ensure they are present\n",
    "\n",
    "`esmlab_regrid` should support generating weight files, but I am getting and ESMF error about PIO not being available. Probably this requires some `module loads` before launching...but that's not acceptable if that's the case, there should be no dependencies outside of the `conda` environment.\n",
    "\n",
    "As a workaround, I wrote [esmf_gen_weights_pop2pop.pbs](esmf_gen_weights_pop2pop.pbs) and run this on the batch nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:37.134189Z",
     "iopub.status.busy": "2020-06-18T18:34:37.133791Z",
     "iopub.status.idle": "2020-06-18T18:34:37.136907Z",
     "shell.execute_reply": "2020-06-18T18:34:37.137215Z"
    },
    "papermill": {
     "duration": 0.02463,
     "end_time": "2020-06-18T18:34:37.137342",
     "exception": false,
     "start_time": "2020-06-18T18:34:37.112712",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "all weight files are present\n"
     ]
    }
   ],
   "source": [
    "method = 'conservative'\n",
    "get_key = lambda src, dst: f'{src}_to_{dst}_{method}'    \n",
    "\n",
    "weight_files = {}\n",
    "for src, dst in product(grids.keys(), grids.keys()): \n",
    "    if src == dst: continue\n",
    "    key = get_key(src, dst)\n",
    "    value = util.file_name_weight(src, dst, method)\n",
    "    weight_files[key] = value\n",
    "    \n",
    "missing = {k: f for k, f in weight_files.items() if not os.path.exists(f)}\n",
    "if missing:\n",
    "    missing_some = True\n",
    "    print(f'missing weight files:\\n{list(missing.keys())}\\n\\nrun the following:\\nqsub < esmf_gen_weights_POP_to_POP.pbs\\n')\n",
    "else:\n",
    "    print('all weight files are present')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:37.171962Z",
     "iopub.status.busy": "2020-06-18T18:34:37.171270Z",
     "iopub.status.idle": "2020-06-18T18:34:37.180314Z",
     "shell.execute_reply": "2020-06-18T18:34:37.180617Z"
    },
    "papermill": {
     "duration": 0.02769,
     "end_time": "2020-06-18T18:34:37.180727",
     "exception": false,
     "start_time": "2020-06-18T18:34:37.153037",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#%%bash\n",
    "# qsub not available from Casper\n",
    "#qsub < esmf_gen_weights_POP_to_POP.pbs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.020605,
     "end_time": "2020-06-18T18:34:37.217951",
     "exception": false,
     "start_time": "2020-06-18T18:34:37.197346",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Construct dictionary of horizontal regridding operators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:37.253682Z",
     "iopub.status.busy": "2020-06-18T18:34:37.253269Z",
     "iopub.status.idle": "2020-06-18T18:34:51.718422Z",
     "shell.execute_reply": "2020-06-18T18:34:51.718731Z"
    },
    "papermill": {
     "duration": 14.48531,
     "end_time": "2020-06-18T18:34:51.718844",
     "exception": false,
     "start_time": "2020-06-18T18:34:37.233534",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'POP_tx0.1v3_to_POP_gx3v7_conservative': <esmlab_regrid.core.Regridder at 0x2b4a254e0c90>,\n",
       " 'POP_tx0.1v3_to_POP_gx1v7_conservative': <esmlab_regrid.core.Regridder at 0x2b4a254e9110>,\n",
       " 'POP_gx3v7_to_POP_tx0.1v3_conservative': <esmlab_regrid.core.Regridder at 0x2b4a2568c790>,\n",
       " 'POP_gx3v7_to_POP_gx1v7_conservative': <esmlab_regrid.core.Regridder at 0x2b4a25695410>,\n",
       " 'POP_gx1v7_to_POP_tx0.1v3_conservative': <esmlab_regrid.core.Regridder at 0x2b4a0129d810>,\n",
       " 'POP_gx1v7_to_POP_gx3v7_conservative': <esmlab_regrid.core.Regridder at 0x2b4a012a7b90>}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regrid_operator = {}\n",
    "for src_grid, dst_grid in product(grids.keys(), grids.keys()): \n",
    "    if src_grid == dst_grid: continue\n",
    "    key = get_key(src_grid, dst_grid)\n",
    "    regrid_operator[key] = esmlab_regrid.regridder(\n",
    "        name_grid_src=src_grid, \n",
    "        name_grid_dst=dst_grid, \n",
    "        method=method, \n",
    "        overwrite_existing=False\n",
    "    )\n",
    "regrid_operator        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.015781,
     "end_time": "2020-06-18T18:34:51.753167",
     "exception": false,
     "start_time": "2020-06-18T18:34:51.737386",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "\"Test\" regridding with `TAREA` field from the grid. Here I am just aiming to pass a sniff test: does the remapped field look right.\n",
    "\n",
    "What's a better way to test this? The differing land-mask will mean integrals don't match....\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:34:51.801087Z",
     "iopub.status.busy": "2020-06-18T18:34:51.800203Z",
     "iopub.status.idle": "2020-06-18T18:35:08.991186Z",
     "shell.execute_reply": "2020-06-18T18:35:08.991522Z"
    },
    "papermill": {
     "duration": 17.2229,
     "end_time": "2020-06-18T18:35:08.991642",
     "exception": false,
     "start_time": "2020-06-18T18:34:51.768742",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for src_grid, dst_grid in product(grids.keys(), grids.keys()): \n",
    "    if src_grid == dst_grid: continue\n",
    "    key = get_key(src_grid, dst_grid)\n",
    "\n",
    "    da_src = grids[src_grid].TAREA.where(grids[src_grid].KMT > 0)\n",
    "    \n",
    "    da_dst = regrid_operator[key](\n",
    "        da_src,\n",
    "        renormalize=True, \n",
    "        apply_mask=True\n",
    "    )\n",
    "    \n",
    "    fig = plt.figure(figsize=(8, 3))\n",
    "    ax = fig.add_subplot(1, 2, 1)\n",
    "    da_src.plot()\n",
    "    ax.set_title(f'From grid: {src_grid}')\n",
    "    ax = fig.add_subplot(1, 2, 2)\n",
    "    da_dst.plot()\n",
    "    ax.set_title(f'To grid: {dst_grid}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.023037,
     "end_time": "2020-06-18T18:35:09.040770",
     "exception": false,
     "start_time": "2020-06-18T18:35:09.017733",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Define vertical interpolation\n",
    "\n",
    "Generate pseudo-data for each grid, a DataArray with 0:km-1 in each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:09.100194Z",
     "iopub.status.busy": "2020-06-18T18:35:09.099353Z",
     "iopub.status.idle": "2020-06-18T18:35:15.765947Z",
     "shell.execute_reply": "2020-06-18T18:35:15.766259Z"
    },
    "papermill": {
     "duration": 6.7052,
     "end_time": "2020-06-18T18:35:15.766406",
     "exception": false,
     "start_time": "2020-06-18T18:35:09.061206",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "da_test_src = {}\n",
    "for src_grid, grid in grids.items():\n",
    "    nk, nj, ni = len(grid.z_t), len(grid.nlat), len(grid.nlon)\n",
    "    k = xr.DataArray(np.arange(0, nk), dims=('z_t'), coords={'z_t': grids[src_grid].z_t})\n",
    "    ones = xr.DataArray(\n",
    "        np.ones((nk, nj, ni)), \n",
    "        dims=('z_t', 'nlat', 'nlon'), \n",
    "        coords={'z_t': grids[src_grid].z_t}\n",
    "    )\n",
    "    \n",
    "    da_test_src[src_grid] = k * ones "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.022027,
     "end_time": "2020-06-18T18:35:15.811575",
     "exception": false,
     "start_time": "2020-06-18T18:35:15.789548",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Test vertical remappiong function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:15.867589Z",
     "iopub.status.busy": "2020-06-18T18:35:15.866786Z",
     "iopub.status.idle": "2020-06-18T18:35:28.104110Z",
     "shell.execute_reply": "2020-06-18T18:35:28.104452Z"
    },
    "papermill": {
     "duration": 12.265846,
     "end_time": "2020-06-18T18:35:28.104582",
     "exception": false,
     "start_time": "2020-06-18T18:35:15.838736",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# unit test: apply remapping and confirm that values match\n",
    "for src_grid, dst_grid in product(grids.keys(), grids.keys()): \n",
    "    if src_grid == dst_grid: \n",
    "        continue\n",
    "\n",
    "    da_src = da_test_src[src_grid]\n",
    "    \n",
    "    da_dst = util.remap_z_t(\n",
    "        da_src, \n",
    "        src_grid,\n",
    "        dst_grid,\n",
    "    )\n",
    "    \n",
    "    nk_src, nk_dst = len(da_src.z_t), len(da_dst.z_t)\n",
    "\n",
    "    if nk_src < nk_dst:\n",
    "        assert (da_src[:, 0, 0] == da_dst[:nk_src, 0, 0]).all()\n",
    "        assert (da_src[-1, 0, 0] == da_dst[-(nk_dst-nk_src):, 0, 0]).all()        \n",
    "\n",
    "    elif nk_src > nk_dst:\n",
    "        assert (da_src[:nk_dst, 0, 0] == da_dst[:, 0, 0]).all()        \n",
    "    \n",
    "    else:\n",
    "        assert (da_dst[:, 0, 0] == da_src[:, 0, 0]).all()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.035465,
     "end_time": "2020-06-18T18:35:28.171324",
     "exception": false,
     "start_time": "2020-06-18T18:35:28.135859",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Define a fill procedure based on `pop_tools`. \n",
    "\n",
    "First, define a function to generate a 3D mask."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:28.235306Z",
     "iopub.status.busy": "2020-06-18T18:35:28.234533Z",
     "iopub.status.idle": "2020-06-18T18:35:28.642385Z",
     "shell.execute_reply": "2020-06-18T18:35:28.642742Z"
    },
    "papermill": {
     "duration": 0.448843,
     "end_time": "2020-06-18T18:35:28.642861",
     "exception": false,
     "start_time": "2020-06-18T18:35:28.194018",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_mask(ds_pop):\n",
    "    required_vars = ['z_t', 'KMT']\n",
    "    missing_vars = set(required_vars) - set(ds_pop.variables)\n",
    "    if missing_vars:\n",
    "        raise ValueError(f'missing required vars:\\n {missing_vars}')\n",
    "    \n",
    "    nk, nj, ni = len(ds_pop.z_t), len(ds_pop.nlat), len(ds_pop.nlon)\n",
    "\n",
    "    # make 3D array of 0:km\n",
    "    zero_to_km = xr.DataArray(np.arange(0, nk), dims=('z_t'))\n",
    "    ONES_3d = xr.DataArray(np.ones((nk, nj, ni)), dims=('z_t', 'nlat', 'nlon'))\n",
    "    ZERO_TO_KM = (zero_to_km * ONES_3d)\n",
    "\n",
    "    # mask out cells where k is below KMT\n",
    "    MASK = ZERO_TO_KM.where(ZERO_TO_KM < ds_pop.KMT)\n",
    "    MASK = xr.where(MASK.notnull(), True, False)\n",
    "\n",
    "    return MASK.assign_coords({'z_t': ds_pop.z_t})\n",
    "\n",
    "MASK = get_mask(grids['POP_gx3v7'])\n",
    "\n",
    "fig = plt.figure(figsize=(8, 3))\n",
    "ax = fig.add_subplot(1, 2, 1)\n",
    "MASK.isel(z_t=0).plot()\n",
    "h = plt.title('Surface mask')\n",
    "\n",
    "ax = fig.add_subplot(1, 2, 2)\n",
    "MASK.isel(nlon=65).plot(yincrease=False)\n",
    "h = plt.title('Pacific transect')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:28.704277Z",
     "iopub.status.busy": "2020-06-18T18:35:28.703241Z",
     "iopub.status.idle": "2020-06-18T18:35:31.037621Z",
     "shell.execute_reply": "2020-06-18T18:35:31.037999Z"
    },
    "papermill": {
     "duration": 2.370766,
     "end_time": "2020-06-18T18:35:31.038134",
     "exception": false,
     "start_time": "2020-06-18T18:35:28.667368",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def fill_unmapped_points(da, grid_name):\n",
    "    \"\"\"fill unmapped points\"\"\"\n",
    "    \n",
    "    ds_grid = grids[grid_name]\n",
    "    MASK = get_mask(ds_grid)\n",
    "    ltripole = (ds_grid.type == 'tripole')\n",
    "    \n",
    "    da_fill = pop_tools.lateral_fill(da.copy(), MASK, ltripole=ltripole)\n",
    "    \n",
    "    # propagate values down to fill vertically, if necessary\n",
    "    unfilled = da_fill.isnull() & (MASK == 1.) \n",
    "    if not unfilled.any():\n",
    "        return da_fill\n",
    "    \n",
    "    nk = len(da_fill.z_t)\n",
    "    for k in range(1, nk):\n",
    "        da_fill[k, :, :] = xr.where(\n",
    "            unfilled[k, :, :], \n",
    "            da_fill[k-1, :, :], \n",
    "            da_fill[k, :, :]\n",
    "        )    \n",
    "    return da_fill\n",
    "\n",
    "\n",
    "# Check to see if it works\n",
    "grid = 'POP_gx3v7'\n",
    "test_field = (get_mask(grids[grid]) * grids[grid].TAREA).where(get_mask(grids[grid]) > 0)\n",
    "test_field[:, 60:80, 60:80] = np.nan\n",
    "test_field_fill = fill_unmapped_points(test_field, grid)\n",
    "\n",
    "fig = plt.figure(figsize=(8, 3))\n",
    "\n",
    "ax = fig.add_subplot(1, 2, 1)\n",
    "test_field.isel(z_t=0).plot()\n",
    "h = plt.title('Surface mask')\n",
    "\n",
    "ax = fig.add_subplot(1, 2, 2)\n",
    "test_field_fill.isel(z_t=0).plot()\n",
    "h = plt.title('Surface mask')\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(8, 3))\n",
    "\n",
    "ax = fig.add_subplot(1, 2, 1)\n",
    "test_field.isel(nlon=65).plot(yincrease=False)\n",
    "h = plt.title('Pacific transect')\n",
    "ax = fig.add_subplot(1, 2, 2)\n",
    "test_field_fill.isel(nlon=60).plot(yincrease=False)\n",
    "h = plt.title('Pacific transect')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:31.108269Z",
     "iopub.status.busy": "2020-06-18T18:35:31.107551Z",
     "iopub.status.idle": "2020-06-18T18:35:31.109476Z",
     "shell.execute_reply": "2020-06-18T18:35:31.109817Z"
    },
    "papermill": {
     "duration": 0.034077,
     "end_time": "2020-06-18T18:35:31.109932",
     "exception": false,
     "start_time": "2020-06-18T18:35:31.075855",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def ugrid_to_tgrid(arr_ugrid):\n",
    "    \"\"\"\n",
    "    Interpolates values at U points on a B grid to T points.\n",
    "    \"\"\"\n",
    "    with xr.set_options(keep_attrs=True):\n",
    "        return 0.25 * (\n",
    "            arr_ugrid +  # j, i\n",
    "            arr_ugrid.roll(nlat=1, roll_coords=False) + # j-1, i\n",
    "            arr_ugrid.roll(nlon=1, roll_coords=False) + # j, i-1\n",
    "            arr_ugrid.roll(nlat=1, nlon=1, roll_coords=False) #j-1, i-1\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.025372,
     "end_time": "2020-06-18T18:35:31.160245",
     "exception": false,
     "start_time": "2020-06-18T18:35:31.134873",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Get model data and generate zarr archives "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:31.225395Z",
     "iopub.status.busy": "2020-06-18T18:35:31.224483Z",
     "iopub.status.idle": "2020-06-18T18:35:34.089237Z",
     "shell.execute_reply": "2020-06-18T18:35:34.076137Z"
    },
    "papermill": {
     "duration": 2.903589,
     "end_time": "2020-06-18T18:35:34.089336",
     "exception": false,
     "start_time": "2020-06-18T18:35:31.185747",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5dde1127bbc7455ab8ac1abd7a45df4b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<h2>NCARCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n  <style scoped>\\n    .…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ncar_jobqueue import NCARCluster\n",
    "cluster = NCARCluster()\n",
    "cluster.scale(36)\n",
    "cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:34.326791Z",
     "iopub.status.busy": "2020-06-18T18:35:34.325886Z",
     "iopub.status.idle": "2020-06-18T18:35:47.331457Z",
     "shell.execute_reply": "2020-06-18T18:35:47.341614Z"
    },
    "papermill": {
     "duration": 13.220979,
     "end_time": "2020-06-18T18:35:47.341820",
     "exception": false,
     "start_time": "2020-06-18T18:35:34.120841",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://10.12.205.30:35412</li>\n",
       "  <li><b>Dashboard: </b><a href='https://jupyterhub.ucar.edu/dav/user/mclong/proxy/8787/status' target='_blank'>https://jupyterhub.ucar.edu/dav/user/mclong/proxy/8787/status</a>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>0</li>\n",
       "  <li><b>Cores: </b>0</li>\n",
       "  <li><b>Memory: </b>0 B</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://10.12.205.30:35412' processes=0 threads=0, memory=0 B>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dask.distributed import Client\n",
    "client = Client(cluster) # Connect this local process to remote workers\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:47.414339Z",
     "iopub.status.busy": "2020-06-18T18:35:47.413927Z",
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    },
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     "end_time": "2020-06-18T18:35:47.417093",
     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def ds_mean_time(ds, variables):\n",
    "    \"\"\"Compute the temporal mean of a dataset\n",
    "       using weights computed from `time_bound`.\n",
    "    \"\"\"\n",
    "    time_weights = ds.time_bound.diff('d2').squeeze()\n",
    "    time_total = time_weights.sum()\n",
    "    wgt = time_weights / time_total\n",
    "    np.testing.assert_allclose(wgt.sum(), 1.0, rtol=1e-7)\n",
    "\n",
    "    with xr.set_options(keep_attrs=True):\n",
    "        return (ds[variables] * wgt).sum('time')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.030019,
     "end_time": "2020-06-18T18:35:47.478042",
     "exception": false,
     "start_time": "2020-06-18T18:35:47.448023",
     "status": "completed"
    },
    "tags": []
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:47.537367Z",
     "iopub.status.busy": "2020-06-18T18:35:47.536932Z",
     "iopub.status.idle": "2020-06-18T18:35:47.870910Z",
     "shell.execute_reply": "2020-06-18T18:35:47.871232Z"
    },
    "papermill": {
     "duration": 0.36764,
     "end_time": "2020-06-18T18:35:47.871358",
     "exception": false,
     "start_time": "2020-06-18T18:35:47.503718",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "%%bash\n",
    "pth=/glade/campaign/cesm/development/omwg\n",
    "case=g.e20.G.TL319_t13.control.001_hfreq\n",
    "pth=${pth}/${case}/ocn/hist/mavg\n",
    "sc=/glade/scratch/mclong/campaign-mirror/${case}/ocn/hist/mavg\n",
    "\n",
    "# cp -v ${pth}/${case}.pop.h.004?-??.nc ${sc}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:47.965941Z",
     "iopub.status.busy": "2020-06-18T18:35:47.965033Z",
     "iopub.status.idle": "2020-06-18T18:35:47.974051Z",
     "shell.execute_reply": "2020-06-18T18:35:47.974546Z"
    },
    "papermill": {
     "duration": 0.057969,
     "end_time": "2020-06-18T18:35:47.974671",
     "exception": false,
     "start_time": "2020-06-18T18:35:47.916702",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dsets = dict()\n",
    "\n",
    "grid_vars = ['TAREA', 'KMT', 'TLONG', 'TLAT', 'ULONG', 'ULAT', 'z_t'] #, 'time', 'time_bound']\n",
    "\n",
    "def get_data(src_grid, variables):\n",
    "    \"\"\"return a time-mean dataset\"\"\"\n",
    "    \n",
    "    if src_grid == 'POP_gx1v7':\n",
    "        \n",
    "        case = 'b.e21.B1850.f09_g17.CMIP6-piControl.001'\n",
    "        droot = f'/glade/campaign/collections/cmip/CMIP6/timeseries-cmip6/{case}'\n",
    "        droot = f'{droot}/ocn/proc/tseries/month_1'\n",
    "        datestr = '060001-069912'\n",
    "\n",
    "        ds_grid = pop_tools.get_grid('POP_gx1v7')\n",
    "\n",
    "        ds = xr.Dataset()\n",
    "        input_files = []\n",
    "        for v in variables:\n",
    "            files = f'{droot}/{case}.pop.h.{v}.{datestr}.nc'\n",
    "            input_files += ','.join(files)+'; '\n",
    "            dsv = xr.open_dataset(\n",
    "                files, \n",
    "                decode_times=False,\n",
    "                decode_coords=False,\n",
    "                chunks={'time': 24, 'z_t': 20},\n",
    "            )\n",
    "            ds = xr.merge((ds, dsv))\n",
    "\n",
    "        with util.timer('computing time mean'):\n",
    "            ds = ds_mean_time(ds, variables).drop('z_t').compute()\n",
    "\n",
    "    elif src_grid == 'POP_tx0.1v3':\n",
    "       \n",
    "        case = 'g.e20.G.TL319_t13.control.001_hfreq'        \n",
    "        #droot = '/glade/campaign/cesm/development/omwg'        \n",
    "        droot = '/glade/scratch/mclong/campaign-mirror'\n",
    "        droot = f'{droot}/{case}/ocn/hist/mavg'\n",
    "\n",
    "        ds_grid = pop_tools.get_grid('POP_tx0.1v3')\n",
    "\n",
    "        years = np.arange(50, 60, 1)\n",
    "\n",
    "        print('computing each annual mean')    \n",
    "        ds_sum = xr.Dataset()\n",
    "        n = 0\n",
    "        input_files = []\n",
    "        for y in years:\n",
    "            files = sorted(glob(f'{droot}/{case}.pop.h.{y:04d}-??.nc'))        \n",
    "            if len(files) != 12:\n",
    "                raise ValueError('expected 12 files')                \n",
    "            \n",
    "            input_files.extend(files)\n",
    "            \n",
    "            print(f'averaging {len(files)} files')\n",
    "            with util.timer(f'year: {y:04d}'):                            \n",
    "                ds = xr.open_mfdataset(\n",
    "                    files, \n",
    "                    combine='nested', \n",
    "                    concat_dim='time',\n",
    "                    chunks={'time': 1, 'nlon': 900, 'nlat': 600},\n",
    "                    decode_times=False,\n",
    "                    decode_coords=False,\n",
    "                )\n",
    "                ds = ds_mean_time(ds, variables).drop('z_t').compute()\n",
    "\n",
    "                if n == 0:\n",
    "                    ds_sum = ds\n",
    "                else:\n",
    "                    ds_sum = ds_sum + ds\n",
    "                n += 1\n",
    "\n",
    "        with util.timer('computing long-term mean'):\n",
    "            ds = ds_sum / n\n",
    "\n",
    "    else:\n",
    "        raise ValueError(f'unknown grid: {grid}')\n",
    "        \n",
    "    ds.attrs['input_files'] = ','.join(input_files)\n",
    "    \n",
    "    return xr.merge((ds, ds_grid[grid_vars]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:48.050269Z",
     "iopub.status.busy": "2020-06-18T18:35:48.049808Z",
     "iopub.status.idle": "2020-06-18T18:35:48.053187Z",
     "shell.execute_reply": "2020-06-18T18:35:48.052816Z"
    },
    "papermill": {
     "duration": 0.046657,
     "end_time": "2020-06-18T18:35:48.053274",
     "exception": false,
     "start_time": "2020-06-18T18:35:48.006617",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "var_groups = dict(\n",
    "    poc_flux=['POC_FLUX_IN'],\n",
    "    velocity=['UVEL', 'VVEL'],\n",
    ")\n",
    "\n",
    "        \n",
    "def proc_var_group(var_group, src_grid, dst_grid=None):\n",
    "    \"\"\"Generate output dataset    \n",
    "    \"\"\"\n",
    "\n",
    "    if dst_grid is None:\n",
    "        dst_grid = src_grid\n",
    "\n",
    "    variables = var_groups[var_group]\n",
    "    key = f'{src_grid}-{var_group}'\n",
    "       \n",
    "    # get the input dataset\n",
    "    if key in dsets:\n",
    "        print('cached dataset')               \n",
    "        ds_src = dsets[key]\n",
    "        \n",
    "    else:\n",
    "        print('generating dataset from files')       \n",
    "        ds_src = get_data(src_grid, variables)\n",
    "        \n",
    "        # put UVEL and VVEL on T-Grid\n",
    "        if var_group == 'velocity':\n",
    "            for v in variables:\n",
    "                ds_src[v] = ugrid_to_tgrid(ds_src[v])\n",
    "\n",
    "        dsets[key] = ds_src           \n",
    "       \n",
    "    # return dataset, performing regridding if necesssary\n",
    "    if src_grid == dst_grid:\n",
    "        return ds_src\n",
    "    \n",
    "    else:       \n",
    "        ds_dst = xr.Dataset()\n",
    "\n",
    "        for v in variables:\n",
    "            # perform lateral regridding\n",
    "            key = get_key(src_grid, dst_grid)\n",
    "            da_dst = regrid_operator[key](\n",
    "                ds_src[v], \n",
    "                renormalize=True, \n",
    "                apply_mask=True\n",
    "            )\n",
    "            \n",
    "            # perform vertical regridding\n",
    "            da_dst = util.remap_z_t(da_dst, src_grid, dst_grid)\n",
    "            \n",
    "            # fill missing values left on dst_grid\n",
    "            da_dst = fill_unmapped_points(da_dst, dst_grid)\n",
    "            \n",
    "            # copy DataArray to outgoing Dataset\n",
    "            ds_dst[v] = da_dst\n",
    "            \n",
    "        return ds_dst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-06-18T18:35:48.114074Z",
     "iopub.status.busy": "2020-06-18T18:35:48.113289Z",
     "iopub.status.idle": "2020-06-18T18:35:48.137079Z",
     "shell.execute_reply": "2020-06-18T18:35:48.137422Z"
    },
    "papermill": {
     "duration": 0.059042,
     "end_time": "2020-06-18T18:35:48.137555",
     "exception": false,
     "start_time": "2020-06-18T18:35:48.078513",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "poc_flux: POP_gx1v7 --> POP_gx1v7\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/poc_flux.POP_gx1v7_to_POP_gx1v7.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "poc_flux: POP_gx1v7 --> POP_gx3v7\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/poc_flux.POP_gx1v7_to_POP_gx3v7.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "poc_flux: POP_gx1v7 --> POP_tx0.1v3\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/poc_flux.POP_gx1v7_to_POP_tx0.1v3.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "velocity: POP_gx1v7 --> POP_gx1v7\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/velocity.POP_gx1v7_to_POP_gx1v7.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "velocity: POP_gx1v7 --> POP_gx3v7\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/velocity.POP_gx1v7_to_POP_gx3v7.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "velocity: POP_tx0.1v3 --> POP_tx0.1v3\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/velocity.POP_tx0.1v3_to_POP_tx0.1v3.zarr\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "velocity: POP_tx0.1v3 --> POP_gx1v7\n",
      "existing file: /glade/work/mclong/cesm_inputdata/work/velocity.POP_tx0.1v3_to_POP_gx1v7.zarr\n",
      "\n"
     ]
    }
   ],
   "source": [
    "var_group_grids = dict(\n",
    "    poc_flux=[\n",
    "        ('POP_gx1v7', 'POP_gx1v7'), \n",
    "        ('POP_gx1v7', 'POP_gx3v7'), \n",
    "        ('POP_gx1v7', 'POP_tx0.1v3'),         \n",
    "    ],\n",
    "    velocity=[\n",
    "        ('POP_gx1v7', 'POP_gx1v7'), \n",
    "        ('POP_gx1v7', 'POP_gx3v7'),         \n",
    "        ('POP_tx0.1v3', 'POP_tx0.1v3'), \n",
    "        ('POP_tx0.1v3', 'POP_gx1v7'),\n",
    "    ],\n",
    ")\n",
    "\n",
    "for var_group, src_dst_list in var_group_grids.items():\n",
    "    for src_grid, dst_grid in src_dst_list:\n",
    "        print('-'*80)\n",
    "        print(f'{var_group}: {src_grid} --> {dst_grid}')\n",
    "        \n",
    "        file_out = f'{util.dirwork}/{var_group}.{src_grid}_to_{dst_grid}.zarr'\n",
    "        \n",
    "        if clobber and os.path.exists(file_out):\n",
    "            shutil.rmtree(file_out)            \n",
    "        \n",
    "        if os.path.exists(file_out):\n",
    "            print(f'existing file: {file_out}')\n",
    "            #dso = xr.open_zarr(file_out)\n",
    "        else: \n",
    "            dso = proc_var_group(var_group, src_grid, dst_grid)\n",
    "            dso.to_zarr(file_out)\n",
    "            dso.info()\n",
    "        print()            "
   ]
  },
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