{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Checking pyaerocom installation and access to data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import pyaerocom\n",
    "\n",
    "It all begins with an import:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jonasg/miniconda3/envs/pyadev/lib/python3.9/site-packages/geonum/__init__.py:26: UserWarning: Plotting of maps etc. is deactivated, please install Basemap\n",
      "  warn('Plotting of maps etc. is deactivated, please install Basemap')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0.12.0.dev1'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyaerocom as pya\n",
    "pya.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When imported, pyaerocom will automatically check access to different default data locations (e.g. mount to PPI at MET Norway, or ~/MyPyaerocom/data), and in case a data source location is detected, associated data directories for accessing these data are instantiated (details below)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check available datasets and directories\n",
    "\n",
    "Accessible data and default paths for certain datasets are available (and can be updated via the `const` module)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyaerocom.config.Config at 0x7f3a0f5932b0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pya.const"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data search directories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/jonasg/MyPyaerocom/data/modeldata/',\n",
       " '/home/jonasg/MyPyaerocom/data/obsdata/']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pya.const.DATA_SEARCH_DIRS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This list contains all directories where pyaerocom will search for model and observation data. pyaerocom will search for both model and observation data in all directories that are specified here. Searching can be done using and if nothing can be found for a certain query, an Exception is raised. Let's try to find some data from the [TM5](http://tm5.sourceforge.net/) chemistry-transport-model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No matches could be found for search pattern *TM5*\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    pya.browse_database('*TM5*')\n",
    "except pya.exceptions.DataSearchError as e:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, that's expected as no data search directories are specified (and most likely, no TM5 data is available on whatever which machine this notebook is executed). Let's make this a little more interesting. We need some data!\n",
    "\n",
    "## Downloading the pyaerocom testdata-minimal dataset\n",
    "\n",
    "The testdata-minimal dataset was developed for automatic testing of pyaerocom and is well suited to illustrate the main features of pyaerocom, without too requiring too heavy computing resources or data storage. It is very easy to get these data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading pyaerocom testdata into /home/jonasg/MyPyaerocom\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyaerocom.testdata_access import TestDataAccess\n",
    "TestDataAccess().download()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have a path, where there is supposed to be some data. Awesomeness!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jonasg/MyPyaerocom/testdata-minimal/'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataloc = f'{pya.const.HOMEDIR}MyPyaerocom/testdata-minimal/'\n",
    "dataloc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Side comment: If this way of formatting python strings looks weird to you, don't worry, this is because it is a [rather new feature](https://www.geeksforgeeks.org/formatted-string-literals-f-strings-python/) (as of Nov 2020)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['README.md', 'scripts', 'coldata', 'obsdata', 'modeldata', 'config']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "os.listdir(dataloc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look into the modeldata directory (obsdata follows later)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['EMEP_2017', 'TM5-met2010_CTRL-TEST']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(dataloc + 'modeldata')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding data search directories"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great, found something. Let's tell pyaerocom about it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pya.const.add_data_search_dir(dataloc + 'modeldata')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's repeat what we did before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/jonasg/MyPyaerocom/data/modeldata/',\n",
       " '/home/jonasg/MyPyaerocom/data/obsdata/',\n",
       " '/home/jonasg/MyPyaerocom/testdata-minimal/modeldata']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pya.const.DATA_SEARCH_DIRS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Pyaerocom ReadGridded\n",
      "---------------------\n",
      "Data ID: TM5-met2010_CTRL-TEST\n",
      "Data directory: /home/jonasg/MyPyaerocom/testdata-minimal/modeldata/TM5-met2010_CTRL-TEST/renamed\n",
      "Available experiments: ['AP3']\n",
      "Available years: [2010, 9999]\n",
      "Available frequencies ['daily' 'monthly']\n",
      "Available variables: ['abs550aer', 'od550aer']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['TM5-met2010_CTRL-TEST']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pya.browse_database('*TM5*')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nice! This worked, and there is even a lot of additional information, that comes in handy. The latter is because the underlying NetCDF files in the data directory are stored using AeroCom file naming conventions. Each dataset has it's own ID (usually the directory name and can be accessed via this ID). For this example TM5 dataset the ID is *TM5-met2010_CTRL-TEST* as can be seen in the output from the browsing method.\n",
    "\n",
    "pyaerocom makes extensive use og these conventions, which makes it easy to streamline analyses of many different models and observation records. However, as we shall see below, the latter are often formatted in many different ways, as observations from many different databases are used. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Pyaerocom ReadGridded\n",
       "---------------------\n",
       "Data ID: TM5-met2010_CTRL-TEST\n",
       "Data directory: /home/jonasg/MyPyaerocom/testdata-minimal/modeldata/TM5-met2010_CTRL-TEST/renamed\n",
       "Available experiments: ['AP3']\n",
       "Available years: [2010, 9999]\n",
       "Available frequencies ['daily' 'monthly']\n",
       "Available variables: ['abs550aer', 'od550aer']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reader = pya.io.ReadGridded('TM5-met2010_CTRL-TEST')\n",
    "reader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tiny detour: AeroCom file naming conventions\n",
    "\n",
    "Let's have a brief look at such a filename (taking the first file in the data directory):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Column_2010_daily.nc'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_file = reader.files[0]\n",
    "os.path.basename(first_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The template is:\n",
    "\n",
    "`\n",
    "aerocom3_<ModelName>-<MeteoConfigSpecifier>_<ExperimentName>-<PerturbationName>_<VariableName>_<VerticalCoordinateType>_<Period>_<Frequency>.nc\n",
    "`\n",
    "\n",
    "So the above filename uses **TM5** model, 2010 meteorology (**met2010**), and this version is for AeroCom Phase III (**AP3**) experiment, particularly for the 2019 Control (**CTRL2019**) perturbation. Variable is **abs550aer** (which is the aerosol absorption optical depth, or AAOD), which is representative for a whole atmospheric **Column**, the simulated year is **2010** (here it is the same as meteorology, but this must not always be the case) and the temporal resolution is **daily**.\n",
    "\n",
    "If you want to learn more about AeroCom conventions and ongoing experiments, [see here](https://docs.google.com/spreadsheets/d/1NiHLVTDsBo0JEBSnnDECNI2ojUnCVlxuy2PFrsRJW38/edit#gid=1475397852)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The metadata that is extracted from the filenames is accessible via:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>var_name</th>\n",
       "      <th>year</th>\n",
       "      <th>ts_type</th>\n",
       "      <th>vert_code</th>\n",
       "      <th>data_id</th>\n",
       "      <th>name</th>\n",
       "      <th>meteo</th>\n",
       "      <th>experiment</th>\n",
       "      <th>perturbation</th>\n",
       "      <th>is_at_stations</th>\n",
       "      <th>3D</th>\n",
       "      <th>filename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>abs550aer</td>\n",
       "      <td>2010</td>\n",
       "      <td>daily</td>\n",
       "      <td>Column</td>\n",
       "      <td>TM5-met2010_CTRL-TEST</td>\n",
       "      <td>TM5</td>\n",
       "      <td>met2010</td>\n",
       "      <td>AP3</td>\n",
       "      <td>CTRL2019</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abs550aer</td>\n",
       "      <td>2010</td>\n",
       "      <td>monthly</td>\n",
       "      <td>Column</td>\n",
       "      <td>TM5-met2010_CTRL-TEST</td>\n",
       "      <td>TM5</td>\n",
       "      <td>met2010</td>\n",
       "      <td>AP3</td>\n",
       "      <td>CTRL2019</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>abs550aer</td>\n",
       "      <td>9999</td>\n",
       "      <td>daily</td>\n",
       "      <td>Column</td>\n",
       "      <td>TM5-met2010_CTRL-TEST</td>\n",
       "      <td>TM5</td>\n",
       "      <td>met2010</td>\n",
       "      <td>AP3</td>\n",
       "      <td>CTRL2019</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>od550aer</td>\n",
       "      <td>2010</td>\n",
       "      <td>daily</td>\n",
       "      <td>Column</td>\n",
       "      <td>TM5-met2010_CTRL-TEST</td>\n",
       "      <td>TM5</td>\n",
       "      <td>met2010</td>\n",
       "      <td>AP3</td>\n",
       "      <td>CTRL2019</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>aerocom3_TM5-met2010_AP3-CTRL2019_od550aer_Col...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>od550aer</td>\n",
       "      <td>2010</td>\n",
       "      <td>monthly</td>\n",
       "      <td>Column</td>\n",
       "      <td>TM5-met2010_CTRL-TEST</td>\n",
       "      <td>TM5</td>\n",
       "      <td></td>\n",
       "      <td>AP3</td>\n",
       "      <td>CTRL2016</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>aerocom3_TM5_AP3-CTRL2016_od550aer_Column_2010...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    var_name  year  ts_type vert_code                data_id name    meteo  \\\n",
       "0  abs550aer  2010    daily    Column  TM5-met2010_CTRL-TEST  TM5  met2010   \n",
       "4  abs550aer  2010  monthly    Column  TM5-met2010_CTRL-TEST  TM5  met2010   \n",
       "1  abs550aer  9999    daily    Column  TM5-met2010_CTRL-TEST  TM5  met2010   \n",
       "2   od550aer  2010    daily    Column  TM5-met2010_CTRL-TEST  TM5  met2010   \n",
       "3   od550aer  2010  monthly    Column  TM5-met2010_CTRL-TEST  TM5            \n",
       "\n",
       "  experiment perturbation  is_at_stations     3D  \\\n",
       "0        AP3     CTRL2019           False  False   \n",
       "4        AP3     CTRL2019           False  False   \n",
       "1        AP3     CTRL2019           False  False   \n",
       "2        AP3     CTRL2019           False  False   \n",
       "3        AP3     CTRL2016           False  False   \n",
       "\n",
       "                                            filename  \n",
       "0  aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...  \n",
       "4  aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...  \n",
       "1  aerocom3_TM5-met2010_AP3-CTRL2019_abs550aer_Co...  \n",
       "2  aerocom3_TM5-met2010_AP3-CTRL2019_od550aer_Col...  \n",
       "3  aerocom3_TM5_AP3-CTRL2016_od550aer_Column_2010...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reader.file_info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How do I know what the variable names mean?\n",
    "\n",
    "You can check all variables via `pyaerocom.const.VARS`, which is a dictionary-like object that allows access to variables and in most cases, provides relevant additional information such as the [CF standard_name](https://cfconventions.org/standard-names.html). For instance, for the above `abs550aer`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "abs550aer\n",
       "standard_name: atmosphere_absorption_optical_thickness_due_to_ambient_aerosol_particles; Unit: 1"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var = pya.const.VARS['abs550aer']\n",
    "var"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Absorption aerosol optical depth (AAOD) at 550nm'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var.long_name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or the extinction (scattering + absorption) aerosol optical depth (AOD), called `od550aer`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "od550aer\n",
       "standard_name: atmosphere_optical_thickness_due_to_ambient_aerosol_particles; Unit: 1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var = pya.const.VARS['od550aer']\n",
    "var"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading of model data using `ReadGridded` class\n",
    "\n",
    "The above instantiated `ReadGridded` interface relies on and makes use of these conventions. This class is also the standard interface to read the modeldata into instances of the `pyaerocom.GriddedData`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pyaerocom.GriddedData: (abs550aer, TM5-met2010_CTRL-TEST)\n",
       "<iris 'Cube' of atmosphere_absorption_optical_thickness_due_to_ambient_aerosol / (1) (time: 12; latitude: 90; longitude: 120)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aaod_tm5 = reader.read_var('abs550aer', start=2010, ts_type='monthly')\n",
    "aaod_tm5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Under the hood, the `GriddedData` object is an [iris.Cube](https://scitools.org.uk/iris/docs/latest/userguide/iris_cubes.html), and it is **single variable**, that is, it does not support reading of multiple variable fields (e.g. AOD and AAOD sharing the same lat, lon and time dimensions). \n",
    "\n",
    "The `GriddedData` object is introduced in more detail in other tutorials, but what is a tutorial without a nice, self-explanatory plot anyways?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jonasg/github/pya/pyaerocom/pyaerocom/plot/mapping.py:438: MatplotlibDeprecationWarning: The 'cmap' parameter to Colorbar has no effect because it is overridden by the mappable; it is deprecated since 3.3 and will be removed two minor releases later.\n",
      "  cbar = fig.colorbar(disp, cmap=cmap, norm=norm, #boundaries=bounds,\n",
      "/home/jonasg/github/pya/pyaerocom/pyaerocom/plot/mapping.py:438: MatplotlibDeprecationWarning: The 'norm' parameter to Colorbar has no effect because it is overridden by the mappable; it is deprecated since 3.3 and will be removed two minor releases later.\n",
      "  cbar = fig.colorbar(disp, cmap=cmap, norm=norm, #boundaries=bounds,\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "aaod_tm5.sel(latitude=(-30, 30), longitude=(-150, 150)).quickplot_map('06/2010');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Registering and reading of *ungridded* observational data\n",
    "\n",
    "### ... COMING VERY SOON!!\n",
    "\n",
    "Until then, checkout the section on ungridded observations in the following tutorial [getting_started_analysis](https://github.com/metno/pyaerocom-tutorials/blob/master/getting_started_analysis.ipynb)."
   ]
  }
 ],
 "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": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}