notebooks/00_Introductory_infilling.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Introduction to Crunchers\n",
    "\n",
    "In this notebook we demonstrate crunchers, silicone's most fundamental infilling methods. You will need to install silicone from as described in the readme in order to run this code. It introduces one specific cruncher, the 'closest RMS' cruncher, and the basic tools to manipulate it. Other crunchers will be documented in other notebooks. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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     "output_type": "stream",
     "text": [
      "pyam - INFO: Running in a notebook, setting `pyam` logging level to `logging.INFO` and adding stderr handler\n"
     ]
    }
   ],
   "source": [
    "import os.path\n",
    "import traceback\n",
    "\n",
    "import pandas as pd\n",
    "import pyam\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import silicone.database_crunchers\n",
    "from silicone.utils import (\n",
    "    _get_unit_of_variable,\n",
    "    find_matching_scenarios,\n",
    "    _make_interpolator,\n",
    "    _make_wide_db,\n",
    "    download_or_load_sr15,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assembling example data\n",
    "\n",
    "Here we pull some example data by downloading it from the IAMC 1.5°C Scenario Explorer and Data hosted by IIASA (for details, see Huppman et al 2019, Integrated Assessment Modeling Consortium & International Institute for Applied Systems Analysis, 2018). If the data has already been downloaded before, we will use that instead for brevity, handled by a convenient wrapper function. We select only a few cases. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pyam.utils - INFO: Reading `./sr15_scenarios.csv`\n"
     ]
    }
   ],
   "source": [
    "valid_model_ids = [\n",
    "    \"MESSAGE*\",\n",
    "    \"AIM*\",\n",
    "    \"C-ROADS*\",\n",
    "    \"GCAM*\",\n",
    "    # \"IEA*\",\n",
    "    # \"IMAGE*\",\n",
    "    # \"MERGE*\",\n",
    "    # \"POLES*\",\n",
    "    # \"REMIND*\",\n",
    "    \"WITCH*\",\n",
    "]\n",
    "SR15_SCENARIOS = \"./sr15_scenarios.csv\"\n",
    "sr15_data = download_or_load_sr15(SR15_SCENARIOS, valid_model_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Starting point\n",
    "\n",
    "Our starting point is the test data, loaded as a `pyam.IamDataFrame`. It may be helpful for understanding some of this tutorial for you to know more about IamDataFrames, documented at https://pyam-iamc.readthedocs.io/en/latest/. The key functions are `.filter()`, which selects a subset of data, and `.timeseries()`, which restructures the data into columns by date, with long indexes containing information other than the value. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pyam.utils - INFO: Reading `./sr15_scenarios.csv`\n"
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       "      <th rowspan=\"5\" valign=\"top\">AIM/CGE 2.0</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">World</th>\n",
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       "      <th>Mt BC/yr</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3367</td>\n",
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       "      <td>7.0752</td>\n",
       "      <td>5.8486</td>\n",
       "      <td>5.2890</td>\n",
       "      <td>4.7920</td>\n",
       "      <td>4.4694</td>\n",
       "      <td>...</td>\n",
       "      <td>3.4700</td>\n",
       "      <td>3.3654</td>\n",
       "      <td>3.2515</td>\n",
       "      <td>3.1251</td>\n",
       "      <td>3.0047</td>\n",
       "      <td>2.9706</td>\n",
       "      <td>2.9239</td>\n",
       "      <td>2.8850</td>\n",
       "      <td>2.5998</td>\n",
       "      <td>2.5771</td>\n",
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       "      <th>Emissions|CH4</th>\n",
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       "      <th>0.0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>344.9167</td>\n",
       "      <td>367.7457</td>\n",
       "      <td>NaN</td>\n",
       "      <td>380.4086</td>\n",
       "      <td>385.0877</td>\n",
       "      <td>229.1313</td>\n",
       "      <td>182.2792</td>\n",
       "      <td>155.2220</td>\n",
       "      <td>133.4843</td>\n",
       "      <td>...</td>\n",
       "      <td>107.6389</td>\n",
       "      <td>111.0836</td>\n",
       "      <td>115.9752</td>\n",
       "      <td>116.5906</td>\n",
       "      <td>118.0872</td>\n",
       "      <td>120.9023</td>\n",
       "      <td>122.0036</td>\n",
       "      <td>120.1977</td>\n",
       "      <td>133.5733</td>\n",
       "      <td>133.5872</td>\n",
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       "      <th>0.0</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>167.6717</td>\n",
       "      <td>179.6356</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>129.2881</td>\n",
       "      <td>115.4458</td>\n",
       "      <td>103.5424</td>\n",
       "      <td>...</td>\n",
       "      <td>88.7903</td>\n",
       "      <td>92.3224</td>\n",
       "      <td>96.7759</td>\n",
       "      <td>98.0924</td>\n",
       "      <td>100.5173</td>\n",
       "      <td>103.2884</td>\n",
       "      <td>104.7226</td>\n",
       "      <td>103.9322</td>\n",
       "      <td>114.1118</td>\n",
       "      <td>114.5658</td>\n",
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       "      <td>4.5313</td>\n",
       "      <td>4.2217</td>\n",
       "      <td>3.9025</td>\n",
       "      <td>3.7682</td>\n",
       "      <td>3.5064</td>\n",
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       "                                                                                                                       2000  \\\n",
       "model       scenario               region variable                                           unit      subannual meta         \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0      NaN   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      NaN   \n",
       "\n",
       "                                                                                                                           2005  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       8.3367   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     344.9167   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     167.6717   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.4732   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      11.2639   \n",
       "\n",
       "                                                                                                                           2010  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       7.6408   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     367.7457   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     179.6356   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.5168   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      11.1249   \n",
       "\n",
       "                                                                                                                       2014  \\\n",
       "model       scenario               region variable                                           unit      subannual meta         \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0      NaN   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0      NaN   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      NaN   \n",
       "\n",
       "                                                                                                                           2015  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       7.2724   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     380.4086   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     190.3513   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.5587   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      10.9809   \n",
       "\n",
       "                                                                                                                           2020  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       7.0752   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     385.0877   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     198.5217   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.6040   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      10.8317   \n",
       "\n",
       "                                                                                                                           2025  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       5.8486   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     229.1313   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     152.3684   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.5722   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0      10.3109   \n",
       "\n",
       "                                                                                                                           2030  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       5.2890   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     182.2792   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     129.2881   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.5295   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       9.4546   \n",
       "\n",
       "                                                                                                                           2035  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       4.7920   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     155.2220   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     115.4458   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.4992   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       8.6100   \n",
       "\n",
       "                                                                                                                           2040  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       4.4694   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     133.4843   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     103.5424   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.4915   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       7.8718   \n",
       "\n",
       "                                                                                                                       ...  \\\n",
       "model       scenario               region variable                                           unit      subannual meta  ...   \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0     ...   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     ...   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     ...   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0     ...   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0     ...   \n",
       "\n",
       "                                                                                                                           2055  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       3.4700   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     107.6389   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      88.7903   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.5689   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       6.3824   \n",
       "\n",
       "                                                                                                                           2060  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       3.3654   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     111.0836   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      92.3224   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.6136   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       5.9928   \n",
       "\n",
       "                                                                                                                           2065  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       3.2515   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     115.9752   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      96.7759   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.6628   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       5.6423   \n",
       "\n",
       "                                                                                                                           2070  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       3.1251   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     116.5906   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0      98.0924   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7011   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       5.2548   \n",
       "\n",
       "                                                                                                                           2075  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       3.0047   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     118.0872   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     100.5173   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.6871   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       4.8423   \n",
       "\n",
       "                                                                                                                           2080  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       2.9706   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     120.9023   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     103.2884   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7002   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       4.5313   \n",
       "\n",
       "                                                                                                                           2085  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       2.9239   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     122.0036   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     104.7226   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7086   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       4.2217   \n",
       "\n",
       "                                                                                                                           2090  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       2.8850   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     120.1977   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     103.9322   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7063   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       3.9025   \n",
       "\n",
       "                                                                                                                           2095  \\\n",
       "model       scenario               region variable                                           unit      subannual meta             \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       2.5998   \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     133.5733   \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     114.1118   \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7735   \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       3.7682   \n",
       "\n",
       "                                                                                                                           2100  \n",
       "model       scenario               region variable                                           unit      subannual meta            \n",
       "AIM/CGE 2.0 ADVANCE_2020_1.5C-2100 World  Emissions|BC                                       Mt BC/yr  0.0       0       2.5771  \n",
       "                                          Emissions|CH4                                      Mt CH4/yr 0.0       0     133.5872  \n",
       "                                          Emissions|CH4|AFOLU                                Mt CH4/yr 0.0       0     114.5658  \n",
       "                                          Emissions|CH4|Energy|Demand|Industry               Mt CH4/yr 0.0       0       0.7577  \n",
       "                                          Emissions|CH4|Energy|Demand|Residential and Com... Mt CH4/yr 0.0       0       3.5064  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sr15_data = pyam.IamDataFrame(SR15_SCENARIOS)\n",
    "sr15_data.timeseries().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Crunchers\n",
    "\n",
    "Silicone's 'crunchers' are used to determine the relationship between a 'follower variable' and 'lead variable(s)' from a given database. The 'follower variable' is the variable for which we want to generate data e.g. `Emissions|C3F8` while the 'lead variable(s)' is the variable we want to use in order to infer a timeseries of the 'follower variable'. The lead variable is currently always a list with only a single item, e.g. `[Emissions|HFC]` but in future may be able to deal with several elements. The follower is always a single string - to infill multiple values in a collective way (e.g. splitting HFC into its various components) see Multiple Infillers. \n",
    "\n",
    "Each cruncher needs to be initialised with a database and has a `derive_relationship` method, which returns the infilling function. Its docstring describes what it does."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "        Derive the relationship between two variables from the database\n",
      "\n",
      "        Parameters\n",
      "        ----------\n",
      "        variable_follower : str\n",
      "            The variable for which we want to calculate timeseries (e.g.\n",
      "            ``\"Emissions|C5F12\"``).\n",
      "\n",
      "        variable_leaders : list[str]\n",
      "            The variables we want to use in order to infer timeseries of\n",
      "            ``variable_follower`` (e.g. ``[\"Emissions|CO2\", \"Emissions|CH4\"]``)\n",
      "\n",
      "        **kwargs\n",
      "            Keyword arguments used by this class to derive the relationship between\n",
      "            ``variable_follower`` and ``variable_leaders``.\n",
      "\n",
      "        Returns\n",
      "        -------\n",
      "        :obj:`func`\n",
      "            Function which takes a :obj:`pyam.IamDataFrame` containing\n",
      "            ``variable_leaders`` timeseries and returns timeseries for\n",
      "            ``variable_follower`` based on the derived relationship between the two.\n",
      "            Please see the source code for the exact definition (and docstring) of the\n",
      "            returned function.\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    silicone.database_crunchers.base._DatabaseCruncher.derive_relationship.__doc__\n",
    ")\n",
    "# # an alternative, pop-up interface is shown if you uncomment the line below\n",
    "# silicone.database_crunchers.base._DatabaseCruncher.derive_relationship?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These crunchers are best explored by looking at the examples below.\n",
    "\n",
    "### Closest Root Mean Square cruncher\n",
    "\n",
    "This cruncher finds the scenario and model in the infiller database that minimises the RMS distance between the the lead emissions in the infiller and infillee data. The follow data is then directly taken from that scenario. \n",
    "The full documentation is as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    Database cruncher which uses the 'closest RMS' technkque.\n",
      "\n",
      "    This cruncher derives the relationship between two variables by finding the\n",
      "    scenario which has the closest lead gas timeseries in the database.  The follower\n",
      "    gas timeseries is then simply copied from the closest scenario.\n",
      "\n",
      "    Here, 'closest' is defined as the smallest time-averaged root mean squared (L2)\n",
      "    difference.\n",
      "\n",
      "    .. math::\n",
      "        RMS = \\left ( \\frac{1}{n} \\sum_{t=0}^n (E_l(t) - E_l^{d}(t))^2 \\right )^{1/2}\n",
      "\n",
      "    where :math:`n` is the total number of timesteps in the lead gas' timeseries,\n",
      "    :math:`E_l(t)` is the lead gas emissions timeseries and :math:`E_l^d(t)` is a lead\n",
      "    gas emissions timeseries in the database.\n",
      "    \n"
     ]
    }
   ],
   "source": [
    "print(silicone.database_crunchers.RMSClosest.__doc__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Infilling\n",
    "\n",
    "Firstly, let's cut the database down to a size that is comprehensible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    }\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>model</th>\n",
       "      <th>scenario</th>\n",
       "      <th>region</th>\n",
       "      <th>variable</th>\n",
       "      <th>unit</th>\n",
       "      <th>year</th>\n",
       "      <th>subannual</th>\n",
       "      <th>meta</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>237008</th>\n",
       "      <td>WITCH-GLOBIOM 4.2</td>\n",
       "      <td>ADVANCE_2020_1.5C-2100</td>\n",
       "      <td>World</td>\n",
       "      <td>Emissions|BC</td>\n",
       "      <td>Mt BC/yr</td>\n",
       "      <td>2005</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.841478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237009</th>\n",
       "      <td>WITCH-GLOBIOM 4.2</td>\n",
       "      <td>ADVANCE_2020_1.5C-2100</td>\n",
       "      <td>World</td>\n",
       "      <td>Emissions|BC</td>\n",
       "      <td>Mt BC/yr</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.269709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237010</th>\n",
       "      <td>WITCH-GLOBIOM 4.2</td>\n",
       "      <td>ADVANCE_2020_1.5C-2100</td>\n",
       "      <td>World</td>\n",
       "      <td>Emissions|BC</td>\n",
       "      <td>Mt BC/yr</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.450332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237011</th>\n",
       "      <td>WITCH-GLOBIOM 4.2</td>\n",
       "      <td>ADVANCE_2020_1.5C-2100</td>\n",
       "      <td>World</td>\n",
       "      <td>Emissions|BC</td>\n",
       "      <td>Mt BC/yr</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.816950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237012</th>\n",
       "      <td>WITCH-GLOBIOM 4.2</td>\n",
       "      <td>ADVANCE_2020_1.5C-2100</td>\n",
       "      <td>World</td>\n",
       "      <td>Emissions|BC</td>\n",
       "      <td>Mt BC/yr</td>\n",
       "      <td>2025</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.402318</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    model                scenario region      variable  \\\n",
       "237008  WITCH-GLOBIOM 4.2  ADVANCE_2020_1.5C-2100  World  Emissions|BC   \n",
       "237009  WITCH-GLOBIOM 4.2  ADVANCE_2020_1.5C-2100  World  Emissions|BC   \n",
       "237010  WITCH-GLOBIOM 4.2  ADVANCE_2020_1.5C-2100  World  Emissions|BC   \n",
       "237011  WITCH-GLOBIOM 4.2  ADVANCE_2020_1.5C-2100  World  Emissions|BC   \n",
       "237012  WITCH-GLOBIOM 4.2  ADVANCE_2020_1.5C-2100  World  Emissions|BC   \n",
       "\n",
       "            unit  year  subannual  meta     value  \n",
       "237008  Mt BC/yr  2005        0.0     0  7.841478  \n",
       "237009  Mt BC/yr  2010        0.0     0  7.269709  \n",
       "237010  Mt BC/yr  2015        0.0     0  6.450332  \n",
       "237011  Mt BC/yr  2020        0.0     0  5.816950  \n",
       "237012  Mt BC/yr  2025        0.0     0  4.402318  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sr15_data_closest_rms = sr15_data.filter(model=[\"WITCH-GLOBIOM 4.2\"])\n",
    "sr15_data_closest_rms.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we initialise the type of cruncher we want with the infiller database. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cruncher = silicone.database_crunchers.RMSClosest(sr15_data_closest_rms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can derive the relationship between the follower and leader, here `Emissions|CO2` and `Emissions|VOC` respectively. This returns a infiller function, which we will use later. Firstly we will check out the docstring. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "            Filler function derived from :obj:`RMSClosest`.\n",
      "\n",
      "            Parameters\n",
      "            ----------\n",
      "            in_iamdf : :obj:`pyam.IamDataFrame`\n",
      "                Input data to fill data in\n",
      "\n",
      "            Returns\n",
      "            -------\n",
      "            :obj:`pyam.IamDataFrame`\n",
      "                Filled in data (without original source data)\n",
      "\n",
      "            Raises\n",
      "            ------\n",
      "            ValueError\n",
      "                If there are any inconsistencies between the timeseries, units or\n",
      "                expectations of the program and ``in_iamdf``, compared to the database\n",
      "                used to generate this ``filler`` function.\n",
      "            \n"
     ]
    }
   ],
   "source": [
    "filler = cruncher.derive_relationship(\"Emissions|VOC\", [\"Emissions|CO2\"])\n",
    "print(filler.__doc__)\n",
    "# filler info:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use this relationship to do some infilling. As a sanity check, we firstly make sure that if we pass in a CO$_2$ timeseries which is already in the database, we get back its VOC emissions timeseries. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_model_scen = {\n",
    "    \"model\": \"WITCH-GLOBIOM 4.2\",\n",
    "    \"scenario\": \"ADVANCE_INDC\",\n",
    "}\n",
    "example_input = sr15_data_closest_rms.filter(**example_model_scen).data\n",
    "example_input[\"model\"] = \"example\"\n",
    "example_input[\"scenario\"] = \"example\"\n",
    "example_input = pyam.IamDataFrame(example_input)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now use the function we returned above to infill the example data, and see that we recover the data we put in. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <th>scenario</th>\n",
       "      <th>region</th>\n",
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       "      <th>unit</th>\n",
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       "  <tbody>\n",
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       "      <th>example</th>\n",
       "      <th>example</th>\n",
       "      <th>World</th>\n",
       "      <th>Emissions|VOC</th>\n",
       "      <th>Mt VOC/yr</th>\n",
       "      <th>0</th>\n",
       "      <th>0.0</th>\n",
       "      <td>189.212</td>\n",
       "      <td>164.056724</td>\n",
       "      <td>153.575866</td>\n",
       "      <td>145.611005</td>\n",
       "      <td>130.387433</td>\n",
       "      <td>115.465871</td>\n",
       "      <td>102.038923</td>\n",
       "      <td>89.302542</td>\n",
       "      <td>76.60488</td>\n",
       "      <td>62.855685</td>\n",
       "      <td>58.440154</td>\n",
       "      <td>56.971497</td>\n",
       "      <td>55.075327</td>\n",
       "      <td>53.101911</td>\n",
       "      <td>51.074418</td>\n",
       "      <td>49.558506</td>\n",
       "      <td>47.602518</td>\n",
       "      <td>45.377459</td>\n",
       "      <td>43.08547</td>\n",
       "      <td>41.400122</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                   2005  \\\n",
       "model   scenario region variable      unit      meta subannual            \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        189.212   \n",
       "\n",
       "                                                                      2010  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        164.056724   \n",
       "\n",
       "                                                                      2015  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        153.575866   \n",
       "\n",
       "                                                                      2020  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        145.611005   \n",
       "\n",
       "                                                                      2025  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        130.387433   \n",
       "\n",
       "                                                                      2030  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        115.465871   \n",
       "\n",
       "                                                                      2035  \\\n",
       "model   scenario region variable      unit      meta subannual               \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        102.038923   \n",
       "\n",
       "                                                                     2040  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        89.302542   \n",
       "\n",
       "                                                                    2045  \\\n",
       "model   scenario region variable      unit      meta subannual             \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        76.60488   \n",
       "\n",
       "                                                                     2050  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        62.855685   \n",
       "\n",
       "                                                                     2055  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        58.440154   \n",
       "\n",
       "                                                                     2060  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        56.971497   \n",
       "\n",
       "                                                                     2065  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        55.075327   \n",
       "\n",
       "                                                                     2070  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        53.101911   \n",
       "\n",
       "                                                                     2075  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        51.074418   \n",
       "\n",
       "                                                                     2080  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        49.558506   \n",
       "\n",
       "                                                                     2085  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        47.602518   \n",
       "\n",
       "                                                                     2090  \\\n",
       "model   scenario region variable      unit      meta subannual              \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        45.377459   \n",
       "\n",
       "                                                                    2095  \\\n",
       "model   scenario region variable      unit      meta subannual             \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        43.08547   \n",
       "\n",
       "                                                                     2100  \n",
       "model   scenario region variable      unit      meta subannual             \n",
       "example example  World  Emissions|VOC Mt VOC/yr 0    0.0        41.400122  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_input_filled = filler(example_input)\n",
    "example_input_filled.timeseries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2010</th>\n",
       "      <th>2015</th>\n",
       "      <th>2020</th>\n",
       "      <th>2025</th>\n",
       "      <th>2030</th>\n",
       "      <th>2035</th>\n",
       "      <th>2040</th>\n",
       "      <th>2045</th>\n",
       "      <th>2050</th>\n",
       "      <th>2055</th>\n",
       "      <th>2060</th>\n",
       "      <th>2065</th>\n",
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       "      <th>2075</th>\n",
       "      <th>2080</th>\n",
       "      <th>2085</th>\n",
       "      <th>2090</th>\n",
       "      <th>2095</th>\n",
       "      <th>2100</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <th>scenario</th>\n",
       "      <th>region</th>\n",
       "      <th>variable</th>\n",
       "      <th>unit</th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>WITCH-GLOBIOM 4.2</th>\n",
       "      <th>ADVANCE_INDC</th>\n",
       "      <th>World</th>\n",
       "      <th>Emissions|VOC</th>\n",
       "      <th>Mt VOC/yr</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0</th>\n",
       "      <td>189.212</td>\n",
       "      <td>164.056724</td>\n",
       "      <td>153.575866</td>\n",
       "      <td>145.611005</td>\n",
       "      <td>130.387433</td>\n",
       "      <td>115.465871</td>\n",
       "      <td>102.038923</td>\n",
       "      <td>89.302542</td>\n",
       "      <td>76.60488</td>\n",
       "      <td>62.855685</td>\n",
       "      <td>58.440154</td>\n",
       "      <td>56.971497</td>\n",
       "      <td>55.075327</td>\n",
       "      <td>53.101911</td>\n",
       "      <td>51.074418</td>\n",
       "      <td>49.558506</td>\n",
       "      <td>47.602518</td>\n",
       "      <td>45.377459</td>\n",
       "      <td>43.08547</td>\n",
       "      <td>41.400122</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                                                                                 2005  \\\n",
       "model             scenario     region variable      unit      subannual meta            \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     189.212   \n",
       "\n",
       "                                                                                    2010  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     164.056724   \n",
       "\n",
       "                                                                                    2015  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     153.575866   \n",
       "\n",
       "                                                                                    2020  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     145.611005   \n",
       "\n",
       "                                                                                    2025  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     130.387433   \n",
       "\n",
       "                                                                                    2030  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     115.465871   \n",
       "\n",
       "                                                                                    2035  \\\n",
       "model             scenario     region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     102.038923   \n",
       "\n",
       "                                                                                   2040  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     89.302542   \n",
       "\n",
       "                                                                                  2045  \\\n",
       "model             scenario     region variable      unit      subannual meta             \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     76.60488   \n",
       "\n",
       "                                                                                   2050  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     62.855685   \n",
       "\n",
       "                                                                                   2055  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     58.440154   \n",
       "\n",
       "                                                                                   2060  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     56.971497   \n",
       "\n",
       "                                                                                   2065  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     55.075327   \n",
       "\n",
       "                                                                                   2070  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     53.101911   \n",
       "\n",
       "                                                                                   2075  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     51.074418   \n",
       "\n",
       "                                                                                   2080  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     49.558506   \n",
       "\n",
       "                                                                                   2085  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     47.602518   \n",
       "\n",
       "                                                                                   2090  \\\n",
       "model             scenario     region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     45.377459   \n",
       "\n",
       "                                                                                  2095  \\\n",
       "model             scenario     region variable      unit      subannual meta             \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     43.08547   \n",
       "\n",
       "                                                                                   2100  \n",
       "model             scenario     region variable      unit      subannual meta             \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_INDC World  Emissions|VOC Mt VOC/yr 0.0       0     41.400122  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sr15_data_closest_rms.filter(\n",
    "    variable=\"Emissions|VOC\", **example_model_scen\n",
    ").timeseries()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, the cruncher has picked out the scenario which matches and returned its VOC timeseries. This can also be seen in a plot below, where the dashed (infilled) line perfectly matches the pink line. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pkwargs = {\"color\": \"scenario\", \"linewidth\": 2}\n",
    "\n",
    "fig = plt.figure(figsize=(16, 9))\n",
    "ax = fig.add_subplot(121)\n",
    "sr15_data_closest_rms.filter(variable=\"*CO2\").line_plot(ax=ax, **pkwargs)\n",
    "example_input.filter(variable=\"*CO2\").line_plot(\n",
    "    ax=ax, color=\"black\", linestyle=\"--\", dashes=(10, 15), label=\"To infill\"\n",
    ")\n",
    "ax.set_title(\"Database CO$_2$ and lead emissions timeseries\")\n",
    "\n",
    "ax = fig.add_subplot(122)\n",
    "sr15_data_closest_rms.filter(variable=\"*VOC\").line_plot(ax=ax, **pkwargs)\n",
    "example_input_filled.filter(variable=\"*VOC\").line_plot(\n",
    "    ax=ax, color=\"black\", linestyle=\"--\", dashes=(10, 15), label=\"Infilled\"\n",
    ")\n",
    "ax.set_title(\"Database VOC and filled follower emissions timeseries\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use our filler to infill other timeseries not present in our infiller database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pyam.core - WARNING: Filtered IamDataFrame is empty!\n"
     ]
    },
    {
     "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>model</th>\n",
       "      <th>scenario</th>\n",
       "      <th>region</th>\n",
       "      <th>variable</th>\n",
       "      <th>unit</th>\n",
       "      <th>year</th>\n",
       "      <th>subannual</th>\n",
       "      <th>meta</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [model, scenario, region, variable, unit, year, subannual, meta, value]\n",
       "Index: []"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filler_input = sr15_data.filter(\n",
    "    model=\"MESSAGEix-GLOBIOM 1.0\", scenario=\"CD-LINKS_NPi2020_1600\"\n",
    ")\n",
    "# This scenario is missing `Emissions|VOC`.\n",
    "filler_input.filter(variable=\"Emissions|VOC\").data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It can go in the same infiller we defined previously.\n",
    "filler_input_filled = filler(filler_input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pkwargs = {\"color\": \"scenario\", \"linewidth\": 2}\n",
    "\n",
    "fig = plt.figure(figsize=(16, 9))\n",
    "ax = fig.add_subplot(121)\n",
    "sr15_data_closest_rms.filter(variable=\"*CO2\").line_plot(ax=ax, **pkwargs)\n",
    "filler_input.filter(variable=\"*CO2\").line_plot(\n",
    "    ax=ax, color=\"black\", linestyle=\"--\", dashes=(10, 15), label=\"To infill\"\n",
    ")\n",
    "ax.set_title(\"Database CO$_2$ and lead emissions timeseries\")\n",
    "\n",
    "ax = fig.add_subplot(122)\n",
    "sr15_data_closest_rms.filter(variable=\"*VOC\").line_plot(ax=ax, **pkwargs)\n",
    "filler_input_filled.filter(variable=\"*VOC\").line_plot(\n",
    "    ax=ax, color=\"black\", linestyle=\"--\", dashes=(10, 15), label=\"Infilled\"\n",
    ")\n",
    "ax.set_title(\"Database VOC and filled follower emissions timeseries\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, on an RMS basis our input timeseries is closest to the 'ADVANCE_2030_Med2C' scenario and hence its `Emissions|VOC` pathway is returned."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2010</th>\n",
       "      <th>2015</th>\n",
       "      <th>2020</th>\n",
       "      <th>2025</th>\n",
       "      <th>2030</th>\n",
       "      <th>2035</th>\n",
       "      <th>2040</th>\n",
       "      <th>2045</th>\n",
       "      <th>2050</th>\n",
       "      <th>2055</th>\n",
       "      <th>2060</th>\n",
       "      <th>2065</th>\n",
       "      <th>2070</th>\n",
       "      <th>2075</th>\n",
       "      <th>2080</th>\n",
       "      <th>2085</th>\n",
       "      <th>2090</th>\n",
       "      <th>2095</th>\n",
       "      <th>2100</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <th>scenario</th>\n",
       "      <th>region</th>\n",
       "      <th>variable</th>\n",
       "      <th>unit</th>\n",
       "      <th>meta</th>\n",
       "      <th>subannual</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MESSAGEix-GLOBIOM 1.0</th>\n",
       "      <th>CD-LINKS_NPi2020_1600</th>\n",
       "      <th>World</th>\n",
       "      <th>Emissions|VOC</th>\n",
       "      <th>Mt VOC/yr</th>\n",
       "      <th>0</th>\n",
       "      <th>0.0</th>\n",
       "      <td>189.212</td>\n",
       "      <td>164.056724</td>\n",
       "      <td>153.575866</td>\n",
       "      <td>145.611005</td>\n",
       "      <td>130.387433</td>\n",
       "      <td>115.465871</td>\n",
       "      <td>95.506957</td>\n",
       "      <td>80.043895</td>\n",
       "      <td>68.04429</td>\n",
       "      <td>56.038428</td>\n",
       "      <td>52.164286</td>\n",
       "      <td>50.849028</td>\n",
       "      <td>49.479184</td>\n",
       "      <td>48.134296</td>\n",
       "      <td>47.046133</td>\n",
       "      <td>45.615107</td>\n",
       "      <td>43.948576</td>\n",
       "      <td>42.192038</td>\n",
       "      <td>40.390822</td>\n",
       "      <td>38.480263</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                              2005  \\\n",
       "model                 scenario              region variable      unit      meta subannual            \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        189.212   \n",
       "\n",
       "                                                                                                 2010  \\\n",
       "model                 scenario              region variable      unit      meta subannual               \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        164.056724   \n",
       "\n",
       "                                                                                                 2015  \\\n",
       "model                 scenario              region variable      unit      meta subannual               \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        153.575866   \n",
       "\n",
       "                                                                                                 2020  \\\n",
       "model                 scenario              region variable      unit      meta subannual               \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        145.611005   \n",
       "\n",
       "                                                                                                 2025  \\\n",
       "model                 scenario              region variable      unit      meta subannual               \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        130.387433   \n",
       "\n",
       "                                                                                                 2030  \\\n",
       "model                 scenario              region variable      unit      meta subannual               \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        115.465871   \n",
       "\n",
       "                                                                                                2035  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        95.506957   \n",
       "\n",
       "                                                                                                2040  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        80.043895   \n",
       "\n",
       "                                                                                               2045  \\\n",
       "model                 scenario              region variable      unit      meta subannual             \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        68.04429   \n",
       "\n",
       "                                                                                                2050  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        56.038428   \n",
       "\n",
       "                                                                                                2055  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        52.164286   \n",
       "\n",
       "                                                                                                2060  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        50.849028   \n",
       "\n",
       "                                                                                                2065  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        49.479184   \n",
       "\n",
       "                                                                                                2070  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        48.134296   \n",
       "\n",
       "                                                                                                2075  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        47.046133   \n",
       "\n",
       "                                                                                                2080  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        45.615107   \n",
       "\n",
       "                                                                                                2085  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        43.948576   \n",
       "\n",
       "                                                                                                2090  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        42.192038   \n",
       "\n",
       "                                                                                                2095  \\\n",
       "model                 scenario              region variable      unit      meta subannual              \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        40.390822   \n",
       "\n",
       "                                                                                                2100  \n",
       "model                 scenario              region variable      unit      meta subannual             \n",
       "MESSAGEix-GLOBIOM 1.0 CD-LINKS_NPi2020_1600 World  Emissions|VOC Mt VOC/yr 0    0.0        38.480263  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filler_input_filled.timeseries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2005</th>\n",
       "      <th>2010</th>\n",
       "      <th>2015</th>\n",
       "      <th>2020</th>\n",
       "      <th>2025</th>\n",
       "      <th>2030</th>\n",
       "      <th>2035</th>\n",
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       "      <th>2045</th>\n",
       "      <th>2050</th>\n",
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       "      <th>2065</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>WITCH-GLOBIOM 4.2</th>\n",
       "      <th>ADVANCE_2030_Med2C</th>\n",
       "      <th>World</th>\n",
       "      <th>Emissions|VOC</th>\n",
       "      <th>Mt VOC/yr</th>\n",
       "      <th>0.0</th>\n",
       "      <th>0</th>\n",
       "      <td>189.212</td>\n",
       "      <td>164.056724</td>\n",
       "      <td>153.575866</td>\n",
       "      <td>145.611005</td>\n",
       "      <td>130.387433</td>\n",
       "      <td>115.465871</td>\n",
       "      <td>95.506957</td>\n",
       "      <td>80.043895</td>\n",
       "      <td>68.04429</td>\n",
       "      <td>56.038428</td>\n",
       "      <td>52.164286</td>\n",
       "      <td>50.849028</td>\n",
       "      <td>49.479184</td>\n",
       "      <td>48.134296</td>\n",
       "      <td>47.046133</td>\n",
       "      <td>45.615107</td>\n",
       "      <td>43.948576</td>\n",
       "      <td>42.192038</td>\n",
       "      <td>40.390822</td>\n",
       "      <td>38.480263</td>\n",
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      ],
      "text/plain": [
       "                                                                                       2005  \\\n",
       "model             scenario           region variable      unit      subannual meta            \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     189.212   \n",
       "\n",
       "                                                                                          2010  \\\n",
       "model             scenario           region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     164.056724   \n",
       "\n",
       "                                                                                          2015  \\\n",
       "model             scenario           region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     153.575866   \n",
       "\n",
       "                                                                                          2020  \\\n",
       "model             scenario           region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     145.611005   \n",
       "\n",
       "                                                                                          2025  \\\n",
       "model             scenario           region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     130.387433   \n",
       "\n",
       "                                                                                          2030  \\\n",
       "model             scenario           region variable      unit      subannual meta               \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     115.465871   \n",
       "\n",
       "                                                                                         2035  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     95.506957   \n",
       "\n",
       "                                                                                         2040  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     80.043895   \n",
       "\n",
       "                                                                                        2045  \\\n",
       "model             scenario           region variable      unit      subannual meta             \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     68.04429   \n",
       "\n",
       "                                                                                         2050  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     56.038428   \n",
       "\n",
       "                                                                                         2055  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     52.164286   \n",
       "\n",
       "                                                                                         2060  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     50.849028   \n",
       "\n",
       "                                                                                         2065  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     49.479184   \n",
       "\n",
       "                                                                                         2070  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     48.134296   \n",
       "\n",
       "                                                                                         2075  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     47.046133   \n",
       "\n",
       "                                                                                         2080  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     45.615107   \n",
       "\n",
       "                                                                                         2085  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     43.948576   \n",
       "\n",
       "                                                                                         2090  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     42.192038   \n",
       "\n",
       "                                                                                         2095  \\\n",
       "model             scenario           region variable      unit      subannual meta              \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     40.390822   \n",
       "\n",
       "                                                                                         2100  \n",
       "model             scenario           region variable      unit      subannual meta             \n",
       "WITCH-GLOBIOM 4.2 ADVANCE_2030_Med2C World  Emissions|VOC Mt VOC/yr 0.0       0     38.480263  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sr15_data_closest_rms.filter(\n",
    "    scenario=\"ADVANCE_2030_Med2C\", variable=\"Emissions|VOC\"\n",
    ").timeseries()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This may be regarded as conceptually the simplest of the data-based crunchers. The other crunchers are introduced in other notebooks. "
   ]
  }
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