Build_analogues-control.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cathy NANGINI<br>\n",
    "Dataviz Scientist at LSCE (Climate and Environment Sciences Laboratory)<br>\n",
    "<img align=\"left\" width=\"40%\" src=\"http://www.lsce.ipsl.fr/Css/img/banniere_LSCE_75.png\"><br><br>\n",
    "<hr>\n",
    "\n",
    "Coded: 15.02.2016\n",
    "Last modified: 18.02.2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#CREATE A CONTROL FILE TO TEST ANALOGUES VIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import collections\n",
    "import os\n",
    "import datetime\n",
    "from datetime import date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "num_analogues = 10 #number of analogues per time of interest\n",
    "num_adate = num_analogues * 2\n",
    "\n",
    "numdays = 2  #number of days in one decade\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2000, 5, 1)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.date(2000, 5, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['19550201',\n",
       " '19550131',\n",
       " '19550130',\n",
       " '19550129',\n",
       " '19550128',\n",
       " '19550127',\n",
       " '19550126',\n",
       " '19550125',\n",
       " '19550124',\n",
       " '19550123',\n",
       " '19550122',\n",
       " '19550121',\n",
       " '19550120',\n",
       " '19550119',\n",
       " '19550118',\n",
       " '19550117',\n",
       " '19550116',\n",
       " '19550115',\n",
       " '19550114',\n",
       " '19550113']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#DEFINE DATE LIST FOR REF PERIOD AND DATE LIST FOR CORRESPONDING ANALOGUES\n",
    "\n",
    "#REF PERIOD - DECADE 1\n",
    "base1 = datetime.date.today() #yr 2016\n",
    "date_list1 = [base1 - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "#str(date_list[0])\n",
    "date_list1[0].strftime(\"%Y%m%d\")\n",
    "\n",
    "for i, item in enumerate(date_list1):\n",
    "    date_list1[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#date_list1\n",
    "\n",
    "#ANLG PERIOD 1 - num_analogues DAYS IN 1955\n",
    "abase1 = datetime.date(1955, 2, 1)\n",
    "adate_list1 = [abase1 - datetime.timedelta(days=x) for x in range(0, num_adate)]\n",
    "\n",
    "for i, item in enumerate(adate_list1):\n",
    "    adate_list1[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "adate_list1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#DECADE 2\n",
    "\n",
    "base2 = datetime.date(2000, 5, 1) #yr 2000\n",
    "date_list2 = [base2 - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "\n",
    "for i, item in enumerate(date_list2):\n",
    "    date_list2[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#date_list2\n",
    "\n",
    "#ANLG PERIOD 2 - num_analogues DAYS IN 1984\n",
    "abase2 = datetime.date(1984, 6, 30)\n",
    "adate_list2 = [abase2 - datetime.timedelta(days=x) for x in range(0, num_adate)]\n",
    "\n",
    "for i, item in enumerate(adate_list2):\n",
    "    adate_list2[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#adate_list2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#DECADE 3\n",
    "\n",
    "base3 = datetime.date(1990, 7, 10) #yr 1990\n",
    "date_list3 = [base3 - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "\n",
    "for i, item in enumerate(date_list3):\n",
    "    date_list3[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#date_list3\n",
    "\n",
    "#ANLG PERIOD 3 - num_analogues DAYS IN 1968\n",
    "abase3 = datetime.date(1968, 11, 11)\n",
    "adate_list3 = [abase3 - datetime.timedelta(days=x) for x in range(0, num_adate)]\n",
    "\n",
    "for i, item in enumerate(adate_list3):\n",
    "    adate_list3[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#adate_list3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#DECADE 4\n",
    "\n",
    "base4 = datetime.date(1970, 6, 11) #yr 1970\n",
    "date_list4 = [base4 - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "\n",
    "for i, item in enumerate(date_list4):\n",
    "    date_list4[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#date_list4\n",
    "\n",
    "#ANLG PERIOD 4 - num_analogues DAYS IN 2006\n",
    "abase4 = datetime.date(2006, 9, 15)\n",
    "adate_list4 = [abase4 - datetime.timedelta(days=x) for x in range(0, num_adate)]\n",
    "\n",
    "for i, item in enumerate(adate_list4):\n",
    "    adate_list4[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#adate_list4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#DECADE 5\n",
    "\n",
    "base5 = datetime.date(1950, 6, 11) #yr 1950\n",
    "date_list5 = [base5 - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "\n",
    "for i, item in enumerate(date_list5):\n",
    "    date_list5[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#date_list5\n",
    "\n",
    "#ANLG PERIOD 5 - num_analogues DAYS IN 1973\n",
    "abase5 = datetime.date(1973, 8, 22)\n",
    "adate_list5 = [abase5 - datetime.timedelta(days=x) for x in range(0, num_adate)]\n",
    "\n",
    "for i, item in enumerate(adate_list5):\n",
    "    adate_list5[i] = item.strftime(\"%Y%m%d\")\n",
    "\n",
    "#adate_list5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#CONCATENATE REF DAYS ACROSS DECADES\n",
    "date_list = date_list1 + date_list2 + date_list3 + date_list4 + date_list5\n",
    "date_list\n",
    "\n",
    "#CONCATENATE CORRESPONDING ANALOGUE DAYS IN EACH DECADE\n",
    "adate_list = adate_list1 + adate_list2 + adate_list3 + adate_list4 + adate_list5\n",
    "len(adate_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#my_date_list = [base - datetime.timedelta(days=x) for x in range(0, numdays)]\n",
    "#my_date_list #= [d.date() for d in my_date_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
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       "Empty DataFrame\n",
       "Columns: []\n",
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     "execution_count": 12,
     "metadata": {},
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   ],
   "source": [
    "#CREATE A DATAFRAME WITH INDEX = DATE LIST\n",
    "\n",
    "dfA = pd.DataFrame(index=date_list)\n",
    "dfA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
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   "outputs": [
    {
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       "<div>\n",
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       "  <thead>\n",
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       "      <th>20160218</th>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [20160219, 20160219, 20160219, 20160219, 20160219, 20160219, 20160219, 20160219, 20160219, 20160219, 20160218, 20160218, 20160218, 20160218, 20160218, 20160218, 20160218, 20160218, 20160218, 20160218, 20000501, 20000501, 20000501, 20000501, 20000501]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "#REPLICATE INDEX COL num_analogues TIMES PER ROW\n",
    "\n",
    "dfA = dfA.loc[np.repeat(dfA.index.values,num_analogues)]\n",
    "dfA.head(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
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    {
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       "(100, 0)"
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     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "dfA.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateAnlg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500611</th>\n",
       "      <td>19730813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19500610</th>\n",
       "      <td>19730803</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          dateAnlg\n",
       "20160219  19550201\n",
       "20160219  19550131\n",
       "20160219  19550130\n",
       "20160219  19550129\n",
       "20160219  19550128\n",
       "20160219  19550127\n",
       "20160219  19550126\n",
       "20160219  19550125\n",
       "20160219  19550124\n",
       "20160219  19550123\n",
       "20160218  19550122\n",
       "20160218  19550121\n",
       "20160218  19550120\n",
       "20160218  19550119\n",
       "20160218  19550118\n",
       "20160218  19550117\n",
       "20160218  19550116\n",
       "20160218  19550115\n",
       "20160218  19550114\n",
       "20160218  19550113\n",
       "20000501  19840630\n",
       "20000501  19840629\n",
       "20000501  19840628\n",
       "20000501  19840627\n",
       "20000501  19840626\n",
       "20000501  19840625\n",
       "20000501  19840624\n",
       "20000501  19840623\n",
       "20000501  19840622\n",
       "20000501  19840621\n",
       "...            ...\n",
       "19700610  20060905\n",
       "19700610  20060904\n",
       "19700610  20060903\n",
       "19700610  20060902\n",
       "19700610  20060901\n",
       "19700610  20060831\n",
       "19700610  20060830\n",
       "19700610  20060829\n",
       "19700610  20060828\n",
       "19700610  20060827\n",
       "19500611  19730822\n",
       "19500611  19730821\n",
       "19500611  19730820\n",
       "19500611  19730819\n",
       "19500611  19730818\n",
       "19500611  19730817\n",
       "19500611  19730816\n",
       "19500611  19730815\n",
       "19500611  19730814\n",
       "19500611  19730813\n",
       "19500610  19730812\n",
       "19500610  19730811\n",
       "19500610  19730810\n",
       "19500610  19730809\n",
       "19500610  19730808\n",
       "19500610  19730807\n",
       "19500610  19730806\n",
       "19500610  19730805\n",
       "19500610  19730804\n",
       "19500610  19730803\n",
       "\n",
       "[100 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfA['dateAnlg'] = adate_list\n",
    "#dfA.loc[:,'dateAnlg'] = adate_list\n",
    "dfA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 1)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfA.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateAnlg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dateRef</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20160219</th>\n",
       "      <td>19550123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          dateAnlg\n",
       "dateRef           \n",
       "20160219  19550201\n",
       "20160219  19550131\n",
       "20160219  19550130\n",
       "20160219  19550129\n",
       "20160219  19550128\n",
       "20160219  19550127\n",
       "20160219  19550126\n",
       "20160219  19550125\n",
       "20160219  19550124\n",
       "20160219  19550123"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfA.index.name = 'dateRef'\n",
    "dfA.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#SAVE TO TSV FILE\n",
    "\n",
    "dfA.to_csv('analogues_control.tsv', sep='\\t')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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