{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8f1994c5-bb2a-4c52-8405-fd240cf965ba",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## GRIB: create fieldlist from array and metadata"
   ]
  },
  {
   "cell_type": "raw",
   "id": "a8eca176-b7fc-41d8-a1ac-e243c5f8070b",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "In this notebook we will show how to do some computations with GRIB data and generate a array fieldlist from the results.\n",
    "\n",
    "First we :ref:`read <data-sources-file>` some GRIB data containing pressure level fields."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "348564d3-1e60-455f-9081-499ce083d27c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import earthkit.data as ekd\n",
    "from earthkit.data import FieldList\n",
    "import numpy as np\n",
    "\n",
    "ekd.download_example_file(\"tuv_pl.grib\")\n",
    "ds = ekd.from_source(\"file\", \"tuv_pl.grib\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e6a80f5-77fc-40f8-a0be-86b80275c390",
   "metadata": {},
   "source": [
    "We will use the following method to compute the potential temperature:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bce2d006-4c44-4726-82fe-2b70f7d81df2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def potential_temperature(t, p):\n",
    "    # t: temperature in K\n",
    "    # p: pressure in Pa\n",
    "    return t*(100000./p)**0.285611"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03513bab-1a94-430c-b740-695f3f6c7d07",
   "metadata": {},
   "source": [
    "#### Working with a single field"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea335181-87a5-4bee-8a2e-8bd93084e75b",
   "metadata": {},
   "source": [
    "In this example we compute the potential temperature for the 850 hPa level using the 4th field from the fieldlist."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7586daef-1098-483b-9747-4aac9386e45b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(GribField(t,850,20180801,1200,0,0), 'K')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = ds[3]\n",
    "f, f.metadata(\"units\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78801efa-c8da-4e35-abe0-33aa7d7974c0",
   "metadata": {},
   "source": [
    "The computations are done with numpy arrays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "60db0219-044d-4977-abf5-e30065400a8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "typeOfLevel= isobaricInhPa\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([285.48786915, 285.48786915, 285.48786915, 285.48786915,\n",
       "       285.48786915, 285.48786915, 285.48786915, 285.48786915,\n",
       "       285.48786915, 285.48786915])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = f.values\n",
    "print(\"typeOfLevel=\", f.metadata(\"typeOfLevel\"))\n",
    "p = f.metadata(\"level\")*100. #hPa -> Pa\n",
    "t_new = potential_temperature(t, p)\n",
    "t_new[:10]"
   ]
  },
  {
   "cell_type": "raw",
   "id": "07e29bb2-1410-4d4d-8feb-e6aa1af0215a",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "We create a new :py:class:`~data.readers.grib.metadata.GribMetadata` object from the source field's :py:meth:`~data.readers.grib.codes.GribField.metadata` using :py:meth:`~data.readers.grib.metadata.GribMetadata.override`. The original metadata remains the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f8dcc33c-6818-415d-8088-6a01666ca87f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pt\n",
      "t\n"
     ]
    }
   ],
   "source": [
    "md_new = f.metadata().override(shortName=\"pt\")\n",
    "print(md_new[\"shortName\"])\n",
    "print(f.metadata(\"shortName\"))"
   ]
  },
  {
   "cell_type": "raw",
   "id": "058c2fd8-569b-4ddb-b8bb-217854e9ff73",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "A new FieldList (type of :py:class:`~data.indexing.fieldlist.SimpleFieldList`) can be created from the resulting ndarray and the modified metadata. It will store a list of :py:class:`~data.sources.array_list.ArrayField` fields each containing a values array and a metadata object entirely in memory. This fieldlist behaves as if it were a :py:class:`~data.readers.grib.index.GribFieldList`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5a2557a6-091c-4345-a792-d3bfa7876c77",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>centre</th>\n",
       "      <th>shortName</th>\n",
       "      <th>typeOfLevel</th>\n",
       "      <th>level</th>\n",
       "      <th>dataDate</th>\n",
       "      <th>dataTime</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ecmf</td>\n",
       "      <td>pt</td>\n",
       "      <td>isobaricInhPa</td>\n",
       "      <td>850</td>\n",
       "      <td>20180801</td>\n",
       "      <td>1200</td>\n",
       "      <td>0</td>\n",
       "      <td>an</td>\n",
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       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf        pt  isobaricInhPa    850  20180801      1200         0   \n",
       "\n",
       "  dataType  number    gridType  \n",
       "0       an       0  regular_ll  "
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_new = FieldList.from_array(t_new, md_new)\n",
    "ds_new.ls()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2ccde1fc-f8c4-4d4d-abda-3ca3feebd02e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ArrayField(pt,850,20180801,1200,0,0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_new[0]"
   ]
  },
  {
   "cell_type": "raw",
   "id": "c7733bdd-1a47-4dba-aac4-b6ed43e15337",
   "metadata": {
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    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "The new fieldlist can be saved into a GRIB file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c22a23fc-fccd-45ef-887e-95ab61b0dee1",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>shortName</th>\n",
       "      <th>typeOfLevel</th>\n",
       "      <th>level</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ecmf</td>\n",
       "      <td>pt</td>\n",
       "      <td>isobaricInhPa</td>\n",
       "      <td>850</td>\n",
       "      <td>20180801</td>\n",
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       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf        pt  isobaricInhPa    850  20180801      1200         0   \n",
       "\n",
       "  dataType  number    gridType  \n",
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     "metadata": {},
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   ],
   "source": [
    "path = \"_pt_single.grib\"\n",
    "ds_new.to_target(\"file\", path)\n",
    "\n",
    "# read file back and check content\n",
    "ds1 = ekd.from_source(\"file\",path)\n",
    "ds1.ls()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b717b7f9-dd46-43cc-81d7-570164954a0d",
   "metadata": {},
   "source": [
    "#### Working with multiple fields"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "671716f8-19cf-47e9-bb8f-45c9651bf76e",
   "metadata": {},
   "source": [
    "In this example we compute the potential temperature for 3 pressure levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bedb28e0-dc98-4145-8559-da96cadca828",
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf         t  isobaricInhPa    850  20180801      1200         0   \n",
       "1   ecmf         t  isobaricInhPa    700  20180801      1200         0   \n",
       "2   ecmf         t  isobaricInhPa    500  20180801      1200         0   \n",
       "\n",
       "  dataType  number    gridType units  \n",
       "0       an       0  regular_ll     K  \n",
       "1       an       0  regular_ll     K  \n",
       "2       an       0  regular_ll     K  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs = ds.sel(shortName=\"t\", level=[850, 700, 500])\n",
    "fs.ls(extra_keys=[\"units\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "74881517-ce58-4692-b1f1-cf281c5c1df2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 84)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = np.asarray(fs.metadata(\"level\")).reshape(-1, 1)*100. # hPa -> Pa\n",
    "t_new = potential_temperature(fs.values, p)\n",
    "t_new.shape"
   ]
  },
  {
   "cell_type": "raw",
   "id": "8f2f7612-3ff9-4982-9cb0-a91a426f1b0f",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "We create an array fieldlist from the resulting ndarray and the modified metadata."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ab0c805e-9e33-40f1-a816-501c2cff64a1",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>ecmf</td>\n",
       "      <td>pt</td>\n",
       "      <td>isobaricInhPa</td>\n",
       "      <td>850</td>\n",
       "      <td>20180801</td>\n",
       "      <td>1200</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ecmf</td>\n",
       "      <td>pt</td>\n",
       "      <td>isobaricInhPa</td>\n",
       "      <td>500</td>\n",
       "      <td>20180801</td>\n",
       "      <td>1200</td>\n",
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      ],
      "text/plain": [
       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf        pt  isobaricInhPa    850  20180801      1200         0   \n",
       "1   ecmf        pt  isobaricInhPa    700  20180801      1200         0   \n",
       "2   ecmf        pt  isobaricInhPa    500  20180801      1200         0   \n",
       "\n",
       "  dataType  number    gridType  \n",
       "0       an       0  regular_ll  \n",
       "1       an       0  regular_ll  \n",
       "2       an       0  regular_ll  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md_new = [f.metadata().override(shortName=\"pt\") for f in fs]\n",
    "ds_new = FieldList.from_array(t_new, md_new)\n",
    "ds_new.ls()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "ca785b7b-d7a8-424b-99c5-19056a0b23b0",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "The new fieldlist can be saved into a GRIB file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
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    "path = \"_pt_multi.grib\"\n",
    "ds_new.to_target(\"file\", path)\n",
    "\n",
    "# read file back and check content\n",
    "ds1 = ekd.from_source(\"file\", path)\n",
    "ds1.ls()"
   ]
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   "source": [
    "#### Performing the computations in a loop"
   ]
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   "source": [
    "In this example we create an **empty** :py:class:`~data.core.fieldlist.FieldList` and add the results of the computations to it in a loop."
   ]
  },
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   "execution_count": 13,
   "id": "6c6e8651-f5a3-4534-9227-812e8e69407d",
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    "fs = ds.sel(shortName=\"t\", level=[850, 700, 500])\n",
    "\n",
    "# create an empty fieldlist\n",
    "ds_r = FieldList()\n",
    "\n",
    "for f in fs:\n",
    "    p = f.metadata(\"level\")*100. # hPa -> Pa\n",
    "    t_new = potential_temperature(f.values, p)\n",
    "    md_new = f.metadata().override(shortName=\"pt\")\n",
    "    \n",
    "    # create new numpy fieldlist with a single field\n",
    "    ds_new = FieldList.from_array(t_new, md_new)\n",
    "\n",
    "    # add it to the resulting fieldlist\n",
    "    ds_r += ds_new"
   ]
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   "execution_count": 14,
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       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
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    "ds_r.ls()"
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    "The new fieldlist can be saved into a GRIB file:"
   ]
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       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
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       "1   ecmf        pt  isobaricInhPa    700  20180801      1200         0   \n",
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    "path = \"_pt_from_loop.grib\"\n",
    "ds_r.to_target(\"file\", path)\n",
    "\n",
    "# read file back and check content\n",
    "ds1 = ekd.from_source(\"file\", path)\n",
    "ds1.ls()"
   ]
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