Future Sale_Prediction using CatBoost  .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Read Sales dataset \n",
    "sales_train = pd.read_csv('sale/sales_train.csv', parse_dates=['date'], infer_datetime_format=True, dayfirst=True)\n",
    "#item_cat = pd.read_csv('sale/item_categories.csv')\n",
    "#items = pd.read_csv('sale/items.csv')\n",
    "#shops = pd.read_csv('sale/shops.csv')\n",
    "sales_test = pd.read_csv('sale/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>date</th>\n",
       "      <th>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>0</td>\n",
       "      <td>59</td>\n",
       "      <td>22154</td>\n",
       "      <td>999.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2013-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2013-01-06</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2554</td>\n",
       "      <td>1709.05</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2013-01-15</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2555</td>\n",
       "      <td>1099.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  date_block_num  shop_id  item_id  item_price  item_cnt_day\n",
       "0 2013-01-02               0       59    22154      999.00           1.0\n",
       "1 2013-01-03               0       25     2552      899.00           1.0\n",
       "2 2013-01-05               0       25     2552      899.00          -1.0\n",
       "3 2013-01-06               0       25     2554     1709.05           1.0\n",
       "4 2013-01-15               0       25     2555     1099.00           1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2348fb6f9c8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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E2NIb9VV1YpJn7WbYP3X34avxV09ycpJfy/JDsskS6E9P8sL1b9qvjjkhyZFJbpslbF81y5vv5yV5TXe/Y934G2f5sdo7Jblxkusl+VaST2aJ/i9Z/1b7mrk9LslvJ7l1li8VvpJlffqXdPc7d3Ofl59nezZ/o/7OSZ6ZZa37A7MsdXN+kld099lbOT8AAAAAAFcOW176BgAAAAAAuOJdZXoCAAAAAABwZSbUAwAAAADAIKEeAAAAAAAGCfUAAAAAADBIqAcAAAAAgEFCPQAAAAAADBLqAQAAAABgkFAPAAAAAACDhHoAAAAAABj0v/n/HAa9ivJ9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import missingno as msno\n",
    "msno.matrix(sales_train) # For finding missing values. Below figure shows no missing values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ID</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  shop_id  item_id\n",
       "0   0        5     5037\n",
       "1   1        5     5320\n",
       "2   2        5     5233\n",
       "3   3        5     5232\n",
       "4   4        5     5268"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>date</th>\n",
       "      <th>item_id</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>2013-01</th>\n",
       "      <th>2013-02</th>\n",
       "      <th>2013-03</th>\n",
       "      <th>2013-04</th>\n",
       "      <th>2013-05</th>\n",
       "      <th>2013-06</th>\n",
       "      <th>2013-07</th>\n",
       "      <th>2013-08</th>\n",
       "      <th>...</th>\n",
       "      <th>2015-01</th>\n",
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      "text/plain": [
       "date  item_id  shop_id  2013-01  2013-02  2013-03  2013-04  2013-05  2013-06  \\\n",
       "0           0       54        0        0        0        0        0        0   \n",
       "1           1       55        0        0        0        0        0        0   \n",
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       "\n",
       "date  2013-07  2013-08  ...  2015-01  2015-02  2015-03  2015-04  2015-05  \\\n",
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       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert raw sales to monthly sales and combine with item_id and shop_id column of test data file. \n",
    "df_tain = sales_train.groupby([sales_train.date.apply(lambda x: x.strftime('%Y-%m')),'item_id','shop_id']).sum().reset_index()\n",
    "df = df_train[['date','item_id','shop_id','item_cnt_day']]\n",
    "df_train = df.pivot_table(index=['item_id','shop_id'], columns='date',values='item_cnt_day',fill_value=0).reset_index()\n",
    "df_trian.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "   ID  shop_id  item_id  2013-01  2013-02  2013-03  2013-04  2013-05  2013-06  \\\n",
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     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dataframe format now looks similar to train dataframe. \n",
    "df_test = pd.merge(sales_test, df, on=['item_id','shop_id'], how='left')\n",
    "df_test = df_test.fillna(0)\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# As we have to predict sales in the test dataset. Lets drop ID, shop_id, item_id from test dataframe. \n",
    "df_test = df_test.drop(labels=['ID', 'shop_id', 'item_id'], axis=1)\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(214200,)\n",
      "(214200, 33)\n"
     ]
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     "execution_count": 15,
     "metadata": {},
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   "source": [
    "# Lets preapre dataset for the model building. \n",
    "target = '2015-10'\n",
    "y_train = df_test[target]\n",
    "x_train = df_test.drop(labels=[target], axis=1)\n",
    "\n",
    "print(y_train.shape)\n",
    "print(x_train.shape)\n",
    "x_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(214200, 33)\n"
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       "\n",
       "   2015-06  2015-07  2015-08  2015-09  2015-10  \n",
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     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Drop the first month so that trained model can predict beyond the known range  \n",
    "x_test = df_test.drop(labels=['2013-01'],axis=1)\n",
    "print(x_test.shape)\n",
    "x_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build a catBoost and train a Model.\n",
    "from catboost import CatBoostRegressor, Pool\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_tr, X_val, y_tr, y_val = train_test_split(x_train, y_train, train_size=0.80, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
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n=t(\"./arrow_paths\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/cartesian/constants\"),i=t(\"../../lib/extend\").extendFlat;e.exports={_isLinkedToArray:\"annotation\",visible:{valType:\"boolean\",dflt:!0},text:{valType:\"string\"},textangle:{valType:\"angle\",dflt:0},font:i({},a,{}),width:{valType:\"number\",min:1,dflt:null},height:{valType:\"number\",min:1,dflt:null},opacity:{valType:\"number\",min:0,max:1,dflt:1},align:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"center\"},valign:{valType:\"enumerated\",values:[\"top\",\"middle\",\"bottom\"],dflt:\"middle\"},bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},bordercolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},borderpad:{valType:\"number\",min:0,dflt:1},borderwidth:{valType:\"number\",min:0,dflt:1},showarrow:{valType:\"boolean\",dflt:!0},arrowcolor:{valType:\"color\"},arrowhead:{valType:\"integer\",min:0,max:n.length,dflt:1},arrowsize:{valType:\"number\",min:.3,dflt:1},arrowwidth:{valType:\"number\",min:.1},standoff:{valType:\"number\",min:0,dflt:0},ax:{valType:\"any\"},ay:{valType:\"any\"},axref:{valType:\"enumerated\",dflt:\"pixel\",values:[\"pixel\",o.idRegex.x.toString()]},ayref:{valType:\"enumerated\",dflt:\"pixel\",values:[\"pixel\",o.idRegex.y.toString()]},xref:{valType:\"enumerated\",values:[\"paper\",o.idRegex.x.toString()]},x:{valType:\"any\"},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"auto\"},xshift:{valType:\"number\",dflt:0},yref:{valType:\"enumerated\",values:[\"paper\",o.idRegex.y.toString()]},y:{valType:\"any\"},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"auto\"},yshift:{valType:\"number\",dflt:0},clicktoshow:{valType:\"enumerated\",values:[!1,\"onoff\",\"onout\"],dflt:!1},xclick:{valType:\"any\"},yclick:{valType:\"any\"},hovertext:{valType:\"string\"},hoverlabel:{bgcolor:{valType:\"color\"},bordercolor:{valType:\"color\"},font:i({},a,{})},captureevents:{valType:\"boolean\"},_deprecated:{ref:{valType:\"string\"}}}},{\"../../lib/extend\":132,\"../../plots/cartesian/constants\":176,\"../../plots/font_attributes\":195,\"./arrow_paths\":15}],17:[function(t,e,r){\"use 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J=1/0;for(I=0;I<Y.length;I++)if((R=Y[I])&&R[0]&&R[0].trace&&R[0].trace.visible===!0&&(F=R[0].trace,[\"carpet\",\"contourcarpet\"].indexOf(F._module.name)===-1)){if(j=w.getSubplot(F),B=n.indexOf(j),q=D,U={cd:R,trace:F,xa:T[B],ya:L[B],name:t.data.length>1||F.hoverinfo.indexOf(\"name\")!==-1?F.name:void 0,index:!1,distance:Math.min(J,k.MAXDIST),color:y.defaultLine,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},d[j]&&(U.subplot=d[j]._subplot),X=G.length,\"array\"===q){var K=e[I];\"pointNumber\"in K?(U.index=K.pointNumber,q=\"closest\"):(q=\"\",\"xval\"in K&&(H=K.xval,q=\"x\"),\"yval\"in K&&(V=K.yval,q=q?\"closest\":\"y\"))}else H=P[B],V=E[B];if(F._module&&F._module.hoverPoints){var tt=F._module.hoverPoints(U,H,V,q);if(tt)for(var et,rt=0;rt<tt.length;rt++)et=tt[rt],f(et.x0)&&f(et.y0)&&G.push(l(et,D))}else h.log(\"Unrecognized trace type in hover:\",F);\"closest\"===D&&G.length>X&&(G.splice(0,X),J=G[0].distance)}if(0===G.length)return x.unhoverRaw(t,e);G.sort(function(t,e){return t.distance-e.distance});var nt=t._hoverdata,at=[];for(N=0;N<G.length;N++){var ot=G[N],it={data:ot.trace._input,fullData:ot.trace,curveNumber:ot.trace.index,pointNumber:ot.index};ot.trace._module.eventData?it=ot.trace._module.eventData(it,ot):(it.x=ot.xVal,it.y=ot.yVal,it.xaxis=ot.xa,it.yaxis=ot.ya,void 0!==ot.zLabelVal&&(it.z=ot.zLabelVal)),at.push(it)}if(t._hoverdata=at,c(t,e,nt)&&d._hasCartesian){s(G,{hovermode:D,fullLayout:d,container:d._hoverlayer,outerContainer:d._paperdiv})}var lt=\"y\"===D&&Y.length>1,st=y.combine(d.plot_bgcolor||y.background,d.paper_bgcolor),ct={hovermode:D,rotateLabels:lt,bgColor:st,container:d._hoverlayer,outerContainer:d._paperdiv,commonLabelOpts:d.hoverlabel},ut=a(G,ct);if(o(G,lt?\"xa\":\"ya\"),i(ut,lt),e.target&&e.target.tagName){var ft=_.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,at);v(u.select(e.target),ft?\"pointer\":\"\")}e.target&&c(t,e,nt)&&(nt&&t.emit(\"plotly_unhover\",{event:e,points:nt}),t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:T,yaxes:L,xvals:P,yvals:E}))}function a(t,e){var r,n,a=e.hovermode,o=e.rotateLabels,i=e.bgColor,l=e.container,s=e.outerContainer,c=e.commonLabelOpts||{},f=e.fontFamily||k.HOVERFONT,d=e.fontSize||k.HOVERFONTSIZE,h=t[0],p=h.xa,v=h.ya,x=\"y\"===a?\"yLabel\":\"xLabel\",b=h[x],_=(String(b)||\"\").split(\" \")[0],w=s.node().getBoundingClientRect(),A=w.top,T=w.width,L=w.height,C=h.distance<=k.MAXDIST&&(\"x\"===a||\"y\"===a);for(r=0;r<t.length;r++){n=t[r].trace.hoverinfo;var O=n.split(\"+\");if(O.indexOf(\"all\")===-1&&O.indexOf(a)===-1){C=!1;break}}var D=l.selectAll(\"g.axistext\").data(C?[0]:[]);D.enter().append(\"g\").classed(\"axistext\",!0),D.exit().remove(),D.each(function(){var e=u.select(this),r=e.selectAll(\"path\").data([0]),n=e.selectAll(\"text\").data([0]);r.enter().append(\"path\").style({fill:c.bgcolor||y.defaultLine,stroke:c.bordercolor||y.background,\"stroke-width\":\"1px\"}),n.enter().append(\"text\").call(m.font,c.font.family||f,c.font.size||d,c.font.color||y.background).attr(\"data-notex\",1),n.text(b).call(g.convertToTspans).call(m.setPosition,0,0).selectAll(\"tspan.line\").call(m.setPosition,0,0),e.attr(\"transform\",\"\");var o=n.node().getBoundingClientRect();if(\"x\"===a){n.attr(\"text-anchor\",\"middle\").call(m.setPosition,0,\"top\"===p.side?A-o.bottom-S-z:A-o.top+S+z).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var i=\"top\"===p.side?\"-\":\"\";r.attr(\"d\",\"M0,0L\"+S+\",\"+i+S+\"H\"+(z+o.width/2)+\"v\"+i+(2*z+o.height)+\"H-\"+(z+o.width/2)+\"V\"+i+S+\"H-\"+S+\"Z\"),e.attr(\"transform\",\"translate(\"+(p._offset+(h.x0+h.x1)/2)+\",\"+(v._offset+(\"top\"===p.side?0:v._length))+\")\")}else{n.attr(\"text-anchor\",\"right\"===v.side?\"start\":\"end\").call(m.setPosition,(\"right\"===v.side?1:-1)*(z+S),A-o.top-o.height/2).selectAll(\"tspan.line\").attr({x:n.attr(\"x\"),y:n.attr(\"y\")});var l=\"right\"===v.side?\"\":\"-\";r.attr(\"d\",\"M0,0L\"+l+S+\",\"+S+\"V\"+(z+o.height/2)+\"h\"+l+(2*z+o.width)+\"V-\"+(z+o.height/2)+\"H\"+l+S+\"V-\"+S+\"Z\"),e.attr(\"transform\",\"translate(\"+(p._offset+(\"right\"===v.side?p._length:0))+\",\"+(v._offset+(h.y0+h.y1)/2)+\")\")}t=t.filter(function(t){return void 0!==t.zLabelVal||(t[x]||\"\").split(\" \")[0]===_})});var P=l.selectAll(\"g.hovertext\").data(t,function(t){return[t.trace.index,t.index,t.x0,t.y0,t.name,t.attr,t.xa,t.ya||\"\"].join(\",\")});return P.enter().append(\"g\").classed(\"hovertext\",!0).each(function(){var t=u.select(this);t.append(\"rect\").call(y.fill,y.addOpacity(i,.8)),t.append(\"text\").classed(\"name\",!0),t.append(\"path\").style(\"stroke-width\",\"1px\"),t.append(\"text\").classed(\"nums\",!0).call(m.font,f,d)}),P.exit().remove(),P.each(function(t){var e=u.select(this).attr(\"transform\",\"\"),r=\"\",n=\"\",l=y.opacity(t.color)?t.color:y.defaultLine,s=y.combine(l,i),c=t.borderColor||y.contrast(s);void 0!==t.nameOverride&&(t.name=t.nameOverride),t.name&&(r=g.plainText(t.name||\"\"),r.length>15&&(r=r.substr(0,12)+\"...\")),void 0!==t.extraText&&(n+=t.extraText),void 0!==t.zLabel?(void 0!==t.xLabel&&(n+=\"x: \"+t.xLabel+\"<br>\"),void 0!==t.yLabel&&(n+=\"y: \"+t.yLabel+\"<br>\"),n+=(n?\"z: \":\"\")+t.zLabel):C&&t[a+\"Label\"]===b?n=t[(\"x\"===a?\"y\":\"x\")+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&(n=t.yLabel):n=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",t.text&&!Array.isArray(t.text)&&(n+=(n?\"<br>\":\"\")+t.text),\"\"===n&&(\"\"===r&&e.remove(),n=r);var h=e.select(\"text.nums\").call(m.font,t.fontFamily||f,t.fontSize||d,t.fontColor||c).call(m.setPosition,0,0).text(n).attr(\"data-notex\",1).call(g.convertToTspans);h.selectAll(\"tspan.line\").call(m.setPosition,0,0);var p=e.select(\"text.name\"),v=0;r&&r!==n?(p.call(m.font,t.fontFamily||f,t.fontSize||d,s).text(r).call(m.setPosition,0,0).attr(\"data-notex\",1).call(g.convertToTspans),p.selectAll(\"tspan.line\").call(m.setPosition,0,0),v=p.node().getBoundingClientRect().width+2*z):(p.remove(),e.select(\"rect\").remove()),e.select(\"path\").style({fill:s,stroke:c});var x,_,w=h.node().getBoundingClientRect(),k=t.xa._offset+(t.x0+t.x1)/2,O=t.ya._offset+(t.y0+t.y1)/2,D=Math.abs(t.x1-t.x0),P=Math.abs(t.y1-t.y0),E=w.width+S+z+v;t.ty0=A-w.top,t.bx=w.width+2*z,t.by=w.height+2*z,t.anchor=\"start\",t.txwidth=w.width,t.tx2width=v,t.offset=0,o?(t.pos=k,x=O+P/2+E<=L,_=O-P/2-E>=0,\"top\"!==t.idealAlign&&x||!_?x?(O+=P/2,t.anchor=\"start\"):t.anchor=\"middle\":(O-=P/2,t.anchor=\"end\")):(t.pos=O,x=k+D/2+E<=T,_=k-D/2-E>=0,\"left\"!==t.idealAlign&&x||!_?x?(k+=D/2,t.anchor=\"start\"):t.anchor=\"middle\":(k-=D/2,t.anchor=\"end\")),h.attr(\"text-anchor\",t.anchor),v&&p.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",\"translate(\"+k+\",\"+O+\")\"+(o?\"rotate(\"+M+\")\":\"\"))}),P}function o(t,e){function r(t){var e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,o=r.pos+r.dp+r.size-e.pmax,a>.01){for(l=t.length-1;l>=0;l--)t[l].dp+=a;n=!1}if(!(o<.01)){if(a<-.01){for(l=t.length-1;l>=0;l--)t[l].dp-=o;n=!1}if(n){var c=0;for(i=0;i<t.length;i++)s=t[i],s.pos+s.dp+s.size>e.pmax&&c++;for(i=t.length-1;i>=0&&!(c<=0);i--)s=t[i],s.pos>e.pmax-1&&(s.del=!0,c--);for(i=0;i<t.length&&!(c<=0);i++)if(s=t[i],s.pos<e.pmin+1)for(s.del=!0,c--,o=2*s.size,l=t.length-1;l>=0;l--)t[l].dp-=o;for(i=t.length-1;i>=0&&!(c<=0);i--)s=t[i],s.pos+s.dp+s.size>e.pmax&&(s.del=!0,c--)}}}for(var n,a,o,i,l,s,c,u=0,f=t.map(function(t,r){var n=t[e];return[{i:r,dp:0,pos:t.pos,posref:t.posref,size:t.by*(\"x\"===n._id.charAt(0)?T:1)/2,pmin:n._offset,pmax:n._offset+n._length}]}).sort(function(t,e){return t[0].posref-e[0].posref});!n&&u<=t.length;){for(u++,n=!0,i=0;i<f.length-1;){var d=f[i],h=f[i+1],p=d[d.length-1],g=h[0];if((a=p.pos+p.dp+p.size-g.pos-g.dp+g.size)>.01&&p.pmin===g.pmin&&p.pmax===g.pmax){for(l=h.length-1;l>=0;l--)h[l].dp+=a;for(d.push.apply(d,h),f.splice(i+1,1),c=0,l=d.length-1;l>=0;l--)c+=d[l].dp;for(o=c/d.length,l=d.length-1;l>=0;l--)d[l].dp-=o;n=!1}else i++}f.forEach(r)}for(i=f.length-1;i>=0;i--){var v=f[i];for(l=v.length-1;l>=0;l--){var m=v[l],y=t[m.i];y.offset=m.dp,y.del=m.del}}}function i(t,e){t.each(function(t){var r=u.select(this);if(t.del)return void r.remove();var n=\"end\"===t.anchor?-1:1,a=r.select(\"text.nums\"),o={start:1,end:-1,middle:0}[t.anchor],i=o*(S+z),l=i+o*(t.txwidth+z),s=0,c=t.offset;\"middle\"===t.anchor&&(i-=t.tx2width/2,l-=t.tx2width/2),e&&(c*=-C,s=t.offset*L),r.select(\"path\").attr(\"d\",\"middle\"===t.anchor?\"M-\"+t.bx/2+\",-\"+t.by/2+\"h\"+t.bx+\"v\"+t.by+\"h-\"+t.bx+\"Z\":\"M0,0L\"+(n*S+s)+\",\"+(S+c)+\"v\"+(t.by/2-S)+\"h\"+n*t.bx+\"v-\"+t.by+\"H\"+(n*S+s)+\"V\"+(c-S)+\"Z\"),a.call(m.setPosition,i+s,c+t.ty0-t.by/2+z).selectAll(\"tspan.line\").attr({x:a.attr(\"x\"),y:a.attr(\"y\")}),t.tx2width&&(r.select(\"text.name, text.name tspan.line\").call(m.setPosition,l+o*z+s,c+t.ty0-t.by/2+z),r.select(\"rect\").call(m.setRect,l+(o-1)*t.tx2width/2+s,c-t.by/2-1,t.tx2width,t.by+2))})}function l(t,e){function r(e,r,i){var l;if(o[r])l=o[r];else if(a[r]){var s=a[r];Array.isArray(s)&&Array.isArray(s[t.index[0]])&&(l=s[t.index[0]][t.index[1]])}else l=h.nestedProperty(n,i).get();l&&(t[e]=l)}var n=t.trace||{},a=t.cd[0],o=t.cd[t.index]||{};t.posref=\"y\"===e?(t.x0+t.x1)/2:(t.y0+t.y1)/2,t.x0=h.constrain(t.x0,0,t.xa._length),t.x1=h.constrain(t.x1,0,t.xa._length),t.y0=h.constrain(t.y0,0,t.ya._length),t.y1=h.constrain(t.y1,0,t.ya._length);var i;if(void 0!==t.xLabelVal){i=\"log\"===t.xa.type&&t.xLabelVal<=0;var l=b.tickText(t.xa,t.xa.c2l(i?-t.xLabelVal:t.xLabelVal),\"hover\");i?0===t.xLabelVal?t.xLabel=\"0\":t.xLabel=\"-\"+l.text:t.xLabel=l.text,t.xVal=t.xa.c2d(t.xLabelVal)}if(void 0!==t.yLabelVal){i=\"log\"===t.ya.type&&t.yLabelVal<=0;var s=b.tickText(t.ya,t.ya.c2l(i?-t.yLabelVal:t.yLabelVal),\"hover\");i?0===t.yLabelVal?t.yLabel=\"0\":t.yLabel=\"-\"+s.text:t.yLabel=s.text,t.yVal=t.ya.c2d(t.yLabelVal)}if(void 0!==t.zLabelVal&&(t.zLabel=String(t.zLabelVal)),!(isNaN(t.xerr)||\"log\"===t.xa.type&&t.xerr<=0)){var c=b.tickText(t.xa,t.xa.c2l(t.xerr),\"hover\").text;void 0!==t.xerrneg?t.xLabel+=\" +\"+c+\" / -\"+b.tickText(t.xa,t.xa.c2l(t.xerrneg),\"hover\").text:t.xLabel+=\" \\xb1 \"+c,\"x\"===e&&(t.distance+=1)}if(!(isNaN(t.yerr)||\"log\"===t.ya.type&&t.yerr<=0)){var u=b.tickText(t.ya,t.ya.c2l(t.yerr),\"hover\").text;void 0!==t.yerrneg?t.yLabel+=\" +\"+u+\" / -\"+b.tickText(t.ya,t.ya.c2l(t.yerrneg),\"hover\").text:t.yLabel+=\" \\xb1 \"+u,\"y\"===e&&(t.distance+=1)}var f=t.trace.hoverinfo;return\"all\"!==f&&(f=f.split(\"+\"),f.indexOf(\"x\")===-1&&(t.xLabel=void 0),f.indexOf(\"y\")===-1&&(t.yLabel=void 0),f.indexOf(\"z\")===-1&&(t.zLabel=void 0),f.indexOf(\"text\")===-1&&(t.text=void 0),f.indexOf(\"name\")===-1&&(t.name=void 0)),r(\"color\",\"hbg\",\"hoverlabel.bgcolor\"),r(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),r(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),r(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),r(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),t}function s(t,e){var r=e.hovermode,n=e.container,a=t[0],o=a.xa,i=a.ya,l=o.showspikes,s=i.showspikes;if(n.selectAll(\".spikeline\").remove(),\"closest\"===r&&(l||s)){var c=e.fullLayout,u=o._offset+(a.x0+a.x1)/2,f=i._offset+(a.y0+a.y1)/2,h=y.combine(c.plot_bgcolor,c.paper_bgcolor),p=d.readability(a.color,h)<1.5?y.contrast(h):a.color;if(s){var g=i.spikemode,v=i.spikethickness,x=i.spikecolor||p,b=i._boundingBox,_=(b.left+b.right)/2<u?b.right:b.left;if(g.indexOf(\"toaxis\")!==-1||g.indexOf(\"across\")!==-1){var w=_,k=u;g.indexOf(\"across\")!==-1&&(w=i._counterSpan[0],k=i._counterSpan[1]),n.append(\"line\").attr({x1:w,x2:k,y1:f,y2:f,\"stroke-width\":v+2,stroke:h}).classed(\"spikeline\",!0).classed(\"crisp\",!0),n.append(\"line\").attr({x1:w,x2:k,y1:f,y2:f,\"stroke-width\":v,stroke:x,\"stroke-dasharray\":m.dashStyle(i.spikedash,v)}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}g.indexOf(\"marker\")!==-1&&n.append(\"circle\").attr({cx:_+(\"right\"!==i.side?v:-v),cy:f,r:v,fill:x}).classed(\"spikeline\",!0)}if(l){var M=o.spikemode,A=o.spikethickness,T=o.spikecolor||p,L=o._boundingBox,C=(L.top+L.bottom)/2<f?L.bottom:L.top;if(M.indexOf(\"toaxis\")!==-1||M.indexOf(\"across\")!==-1){var S=C,z=f;M.indexOf(\"across\")!==-1&&(S=o._counterSpan[0],z=o._counterSpan[1]),n.append(\"line\").attr({x1:u,x2:u,y1:S,y2:z,\"stroke-width\":A+2,stroke:h}).classed(\"spikeline\",!0).classed(\"crisp\",!0),n.append(\"line\").attr({x1:u,x2:u,y1:S,y2:z,\"stroke-width\":A,stroke:T,\"stroke-dasharray\":m.dashStyle(o.spikedash,A)}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}M.indexOf(\"marker\")!==-1&&n.append(\"circle\").attr({cx:u,cy:C-(\"top\"!==o.side?A:-A),r:A,fill:T}).classed(\"spikeline\",!0)}}}function c(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var a=r[n],o=t._hoverdata[n];if(a.curveNumber!==o.curveNumber||String(a.pointNumber)!==String(o.pointNumber))return!0}return!1}var u=t(\"d3\"),f=t(\"fast-isnumeric\"),d=t(\"tinycolor2\"),h=t(\"../../lib\"),p=t(\"../../lib/events\"),g=t(\"../../lib/svg_text_utils\"),v=t(\"../../lib/override_cursor\"),m=t(\"../drawing\"),y=t(\"../color\"),x=t(\"../dragelement\"),b=t(\"../../plots/cartesian/axes\"),_=t(\"../../registry\"),w=t(\"./helpers\"),k=t(\"./constants\"),M=k.YANGLE,A=Math.PI*M/180,T=1/Math.sin(A),L=Math.cos(A),C=Math.sin(A),S=k.HOVERARROWSIZE,z=k.HOVERTEXTPAD;r.hover=function(t,e,r){if(\"string\"==typeof t&&(t=document.getElementById(t)),void 0===t._lastHoverTime&&(t._lastHoverTime=0),void 0!==t._hoverTimer&&(clearTimeout(t._hoverTimer),t._hoverTimer=void 0),Date.now()>t._lastHoverTime+k.HOVERMINTIME)return n(t,e,r),void(t._lastHoverTime=Date.now());t._hoverTimer=setTimeout(function(){n(t,e,r),t._lastHoverTime=Date.now(),t._hoverTimer=void 0},k.HOVERMINTIME)},r.loneHover=function(t,e){var r={color:t.color||y.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,trace:{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0},n=u.select(e.container),o=e.outerContainer?u.select(e.outerContainer):n,l={hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||y.background,container:n,outerContainer:o},s=a([r],l);return i(s,l.rotateLabels),s.node()}},{\"../../lib\":136,\"../../lib/events\":131,\"../../lib/override_cursor\":145,\"../../lib/svg_text_utils\":153,\"../../plots/cartesian/axes\":171,\"../../registry\":206,\"../color\":25,\"../dragelement\":46,\"../drawing\":49,\"./constants\":61,\"./helpers\":63,d3:7,\"fast-isnumeric\":10,tinycolor2:13}],65:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e,r,a){a=a||{},r(\"hoverlabel.bgcolor\",a.bgcolor),r(\"hoverlabel.bordercolor\",a.bordercolor),n.coerceFont(r,\"hoverlabel.font\",a.font)}},{\"../../lib\":136}],66:[function(t,e,r){\"use strict\";function n(t){var e=i.isD3Selection(t)?t:o.select(t);e.selectAll(\"g.hovertext\").remove(),e.selectAll(\".spikeline\").remove()}function a(t,e,r){var n=t.hoverlabel||{},a=i.nestedProperty(n,r).get();return Array.isArray(a)?Array.isArray(e)&&Array.isArray(a[e[0]])?a[e[0]][e[1]]:a[e]:a}var 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n=o({},t);return[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]].forEach(function(t,r){i.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",n.dotVisible===!0?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var a=i.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var n=a.indexOf(t.geometry);n!=-1&&(r.data[e].groupId=n)})}if(t.layout){var l=o({},t.layout);if([[l,[\"plot_bgcolor\"],[\"backgroundColor\"]],[l,[\"showlegend\"],[\"showLegend\"]],[l,[\"radialaxis\"],[\"radialAxis\"]],[l,[\"angularaxis\"],[\"angularAxis\"]],[l.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[l.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[l.angularaxis,[\"nticks\"],[\"ticksCount\"]],[l.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[l.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[l.angularaxis,[\"range\"],[\"domain\"]],[l.angularaxis,[\"endpadding\"],[\"endPadding\"]],[l.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[l.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[l.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[l.radialaxis,[\"range\"],[\"domain\"]],[l.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[l.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[l.angularAxis,[\"nticks\"],[\"ticksCount\"]],[l.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[l.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[l.angularAxis,[\"range\"],[\"domain\"]],[l.angularAxis,[\"endpadding\"],[\"endPadding\"]],[l.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[l.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[l.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[l.radialAxis,[\"range\"],[\"domain\"]],[l.font,[\"outlinecolor\"],[\"outlineColor\"]],[l.legend,[\"traceorder\"],[\"reverseOrder\"]],[l,[\"labeloffset\"],[\"labelOffset\"]],[l,[\"defaultcolorrange\"],[\"defaultColorRange\"]]].forEach(function(t,r){i.util.translator.apply(null,t.concat(e))}),e?(void 0!==l.tickLength&&(l.angularaxis.ticklen=l.tickLength,delete l.tickLength),l.tickColor&&(l.angularaxis.tickcolor=l.tickColor,delete l.tickColor)):(l.angularAxis&&void 0!==l.angularAxis.ticklen&&(l.tickLength=l.angularAxis.ticklen),l.angularAxis&&void 0!==l.angularAxis.tickcolor&&(l.tickColor=l.angularAxis.tickcolor)),l.legend&&\"boolean\"!=typeof l.legend.reverseOrder&&(l.legend.reverseOrder=\"normal\"!=l.legend.reverseOrder),l.legend&&\"boolean\"==typeof l.legend.traceorder&&(l.legend.traceorder=l.legend.traceorder?\"reversed\":\"normal\",delete l.legend.reverseOrder),l.margin&&void 0!==l.margin.t){var s=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],u={};n.entries(l.margin).forEach(function(t,e){u[c[s.indexOf(t.key)]]=t.value}),l.margin=u}e&&(delete l.needsEndSpacing,delete l.minorTickColor,delete l.minorTicks,delete l.angularaxis.ticksCount,delete l.angularaxis.ticksCount,delete l.angularaxis.ticksStep,delete l.angularaxis.rewriteTicks,delete l.angularaxis.nticks,delete l.radialaxis.ticksCount,delete l.radialaxis.ticksCount,delete l.radialaxis.ticksStep,delete l.radialaxis.rewriteTicks,delete l.radialaxis.nticks),r.layout=l}return r},t}},{\"../../lib\":136,d3:7}],204:[function(t,e,r){\"use strict\";var n=t(\"d3\"),a=t(\"../../lib\"),o=t(\"../../components/color\"),i=t(\"./micropolar\"),l=t(\"./undo_manager\"),s=a.extendDeepAll,c=e.exports={};c.framework=function(t){function e(e,a){return a&&(f=a),n.select(n.select(f).node().parentNode).selectAll(\".svg-container>*:not(.chart-root)\").remove(),r=r?s(r,e):e,o||(o=i.Axis()),u=i.adapter.plotly().convert(r),o.config(u).render(f),t.data=r.data,t.layout=r.layout,c.fillLayout(t),r}var r,a,o,u,f,d=new l;return e.isPolar=!0,e.svg=function(){return o.svg()},e.getConfig=function(){return r},e.getLiveConfig=function(){return i.adapter.plotly().convert(o.getLiveConfig(),!0)},e.getLiveScales=function(){return{t:o.angularScale(),r:o.radialScale()}},e.setUndoPoint=function(){var t=this,e=i.util.cloneJson(r);!function(e,r){d.add({undo:function(){r&&t(r)},redo:function(){t(e)}})}(e,a),a=i.util.cloneJson(e)},e.undo=function(){d.undo()},e.redo=function(){d.redo()},e},c.fillLayout=function(t){var e=n.select(t).selectAll(\".plot-container\"),r=e.selectAll(\".svg-container\"),a=t.framework&&t.framework.svg&&t.framework.svg(),i={width:800,height:600,paper_bgcolor:o.background,_container:e,_paperdiv:r,_paper:a};t._fullLayout=s(i,t.layout)}},{\"../../components/color\":25,\"../../lib\":136,\"./micropolar\":203,\"./undo_manager\":205,d3:7}],205:[function(t,e,r){\"use strict\";e.exports=function(){function t(t,e){return t?(a=!0,t[e](),a=!1,this):this}var e,r=[],n=-1,a=!1;return{add:function(t){return a?this:(r.splice(n+1,r.length-n),r.push(t),n=r.length-1,this)},setCallback:function(t){e=t},undo:function(){var a=r[n];return a?(t(a,\"undo\"),n-=1,e&&e(a.undo),this):this},redo:function(){var a=r[n+1];return 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Array(h.length),r=0;r<h.length;r++)p[r]=String(e.label0+r*e.dlabel);for(r=0;r<h.length;r++)s=h[r],a(s)&&((s=+s)<0||(c=p[r],void 0!==c&&\"\"!==c||(c=r),c=String(c),void 0===y[c]&&(y[c]=!0,u=o(e.marker.colors[r]),u.isValid()?(u=i.addOpacity(u,u.getAlpha()),m[c]||(m[c]=u)):m[c]?u=m[c]:(u=!1,x=!0),f=_.indexOf(c)!==-1,f||(b+=s),g.push({v:s,label:c,color:u,i:r,hidden:f}))));if(e.sort&&g.sort(function(t,e){return e.v-t.v}),x)for(r=0;r<g.length;r++)d=g[r],d.color===!1&&(m[d.label]=d.color=n(v._piedefaultcolorcount),v._piedefaultcolorcount++);if(g[0]&&(g[0].vTotal=b),e.textinfo&&\"none\"!==e.textinfo){var w,k=e.textinfo.indexOf(\"label\")!==-1,M=e.textinfo.indexOf(\"text\")!==-1,A=e.textinfo.indexOf(\"value\")!==-1,T=e.textinfo.indexOf(\"percent\")!==-1,L=v.separators;for(r=0;r<g.length;r++)d=g[r],w=k?[d.label]:[],M&&e.text[d.i]&&w.push(e.text[d.i]),A&&w.push(l.formatPieValue(d.v,L)),T&&w.push(l.formatPiePercent(d.v/b,L)),d.text=w.join(\"<br>\")}return g};var s},{\"../../components/color\":25,\"./helpers\":232,\"fast-isnumeric\":10,tinycolor2:13}],231:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./attributes\");e.exports=function(t,e,r,o){function i(r,o){return n.coerce(t,e,a,r,o)}var l=n.coerceFont,s=i(\"values\");if(!Array.isArray(s)||!s.length)return void(e.visible=!1);var c=i(\"labels\");Array.isArray(c)||(i(\"label0\"),i(\"dlabel\")),i(\"marker.line.width\")&&i(\"marker.line.color\");var u=i(\"marker.colors\");Array.isArray(u)||(e.marker.colors=[]),i(\"scalegroup\");var f=i(\"text\"),d=i(\"textinfo\",Array.isArray(f)?\"text+percent\":\"percent\");if(i(\"hovertext\"),i(\"hoverinfo\",1===o._dataLength?\"label+text+value+percent\":void 0),d&&\"none\"!==d){var h=i(\"textposition\"),p=Array.isArray(h)||\"auto\"===h,g=p||\"inside\"===h,v=p||\"outside\"===h;if(g||v){var m=l(i,\"textfont\",o.font);g&&l(i,\"insidetextfont\",m),v&&l(i,\"outsidetextfont\",m)}}i(\"domain.x\"),i(\"domain.y\"),i(\"hole\"),i(\"sort\"),i(\"direction\"),i(\"rotation\"),i(\"pull\")}},{\"../../lib\":136,\"./attributes\":228}],232:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");r.formatPiePercent=function(t,e){var r=(100*t).toPrecision(3);return r.lastIndexOf(\".\")!==-1&&(r=r.replace(/[.]?0+$/,\"\")),n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=t.toPrecision(10);return r.lastIndexOf(\".\")!==-1&&(r=r.replace(/[.]?0+$/,\"\")),n.numSeparate(r,e)}},{\"../../lib\":136}],233:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.supplyLayoutDefaults=t(\"./layout_defaults\"),n.layoutAttributes=t(\"./layout_attributes\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.style=t(\"./style\"),n.styleOne=t(\"./style_one\"),n.moduleType=\"trace\",n.name=\"pie\",n.basePlotModule=t(\"./base_plot\"),n.categories=[\"pie\",\"showLegend\"],n.meta={},e.exports=n},{\"./attributes\":228,\"./base_plot\":229,\"./calc\":230,\"./defaults\":231,\"./layout_attributes\":234,\"./layout_defaults\":235,\"./plot\":236,\"./style\":237,\"./style_one\":238}],234:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\"}}},{}],235:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),a=t(\"./layout_attributes\");e.exports=function(t,e){!function(r,o){n.coerce(t,e,a,r,o)}(\"hiddenlabels\")}},{\"../../lib\":136,\"./layout_attributes\":234}],236:[function(t,e,r){\"use strict\";function n(t,e,r){var n=Math.sqrt(t.width*t.width+t.height*t.height),o=t.width/t.height,i=Math.PI*Math.min(e.v/r.vTotal,.5),l=1-r.trace.hole,s=a(e,r),c={scale:s*r.r*2/n,rCenter:1-s,rotate:0};if(c.scale>=1)return c;var u=o+1/(2*Math.tan(i)),f=r.r*Math.min(1/(Math.sqrt(u*u+.5)+u),l/(Math.sqrt(o*o+l/2)+o)),d={scale:2*f/t.height,rCenter:Math.cos(f/r.r)-f*o/r.r,rotate:(180/Math.PI*e.midangle+720)%180-90},h=1/o,p=h+1/(2*Math.tan(i)),g=r.r*Math.min(1/(Math.sqrt(p*p+.5)+p),l/(Math.sqrt(h*h+l/2)+h)),v={scale:2*g/t.width,rCenter:Math.cos(g/r.r)-g/o/r.r,rotate:(180/Math.PI*e.midangle+810)%180-90},m=v.scale>d.scale?v:d;return c.scale<1&&m.scale>c.scale?m:c}function a(t,e){if(t.v===e.vTotal&&!e.trace.hole)return 1;var r=Math.PI*Math.min(t.v/e.vTotal,.5);return Math.min(1/(1+1/Math.sin(r)),(1-e.trace.hole)/2)}function o(t,e){var r=e.pxmid[0],n=e.pxmid[1],a=t.width/2,o=t.height/2;return r<0&&(a*=-1),n<0&&(o*=-1),{scale:1,rCenter:1,rotate:0,x:a+Math.abs(o)*(a>0?1:-1)/2,y:o/(1+r*r/(n*n)),outside:!0}}function i(t,e){function r(t,e){return t.pxmid[1]-e.pxmid[1]}function n(t,e){return e.pxmid[1]-t.pxmid[1]}var a,o,i,l,s,c,u,f,d,h,p,g,v;for(o=0;o<2;o++)for(i=o?r:n,s=o?Math.max:Math.min,u=o?1:-1,a=0;a<2;a++){for(l=a?Math.max:Math.min,c=a?1:-1,f=t[o][a],f.sort(i),d=t[1-o][a],h=d.concat(f),g=[],p=0;p<f.length;p++)void 0!==f[p].yLabelMid&&g.push(f[p]);for(v=!1,p=0;o&&p<d.length;p++)if(void 0!==d[p].yLabelMid){v=d[p];break}for(p=0;p<g.length;p++){var m=p&&g[p-1];v&&!p&&(m=v),function(t,r){r||(r={});var n,a,i,f,d,p,g=r.labelExtraY+(o?r.yLabelMax:r.yLabelMin),v=o?t.yLabelMin:t.yLabelMax,m=o?t.yLabelMax:t.yLabelMin,y=t.cyFinal+s(t.px0[1],t.px1[1]),x=g-v;if(x*u>0&&(t.labelExtraY=x),Array.isArray(e.pull))for(a=0;a<h.length;a++)(i=h[a])===t||(e.pull[t.i]||0)>=e.pull[i.i]||((t.pxmid[1]-i.pxmid[1])*u>0?(f=i.cyFinal+s(i.px0[1],i.px1[1]),(x=f-v-t.labelExtraY)*u>0&&(t.labelExtraY+=x)):(m+t.labelExtraY-y)*u>0&&(n=3*c*Math.abs(a-h.indexOf(t)),d=i.cxFinal+l(i.px0[0],i.px1[0]),(p=d+n-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*c>0&&(t.labelExtraX+=p)))}(g[p],m)}}}function l(t,e){var r,n,a,o,i,l,s,u,f,d,h=[];for(a=0;a<t.length;a++){if(i=t[a][0],l=i.trace,r=e.w*(l.domain.x[1]-l.domain.x[0]),n=e.h*(l.domain.y[1]-l.domain.y[0]),s=l.tiltaxis*Math.PI/180,u=l.pull,Array.isArray(u))for(u=0,o=0;o<l.pull.length;o++)l.pull[o]>u&&(u=l.pull[o]);i.r=Math.min(r/c(l.tilt,Math.sin(s),l.depth),n/c(l.tilt,Math.cos(s),l.depth))/(2+2*u),i.cx=e.l+e.w*(l.domain.x[1]+l.domain.x[0])/2,i.cy=e.t+e.h*(2-l.domain.y[1]-l.domain.y[0])/2,\n",
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n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var u=t(\"d3\"),f=t(\"../../components/fx\"),d=t(\"../../components/color\"),h=t(\"../../components/drawing\"),p=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;l(e,r._size);var c=r._pielayer.selectAll(\"g.trace\").data(e);c.enter().append(\"g\").attr({\"stroke-linejoin\":\"round\",class:\"trace\"}),c.exit().remove(),c.order(),c.each(function(e){var l=u.select(this),c=e[0],v=c.trace,m=(v.depth||0)*c.r*Math.sin(0)/2,y=v.tiltaxis||0,x=y*Math.PI/180,b=[m*Math.sin(x),m*Math.cos(x)],_=c.r*Math.cos(0),w=l.selectAll(\"g.part\").data(v.tilt?[\"top\",\"sides\"]:[\"top\"]);w.enter().append(\"g\").attr(\"class\",function(t){return t+\" part\"}),w.exit().remove(),w.order(),s(e),l.selectAll(\".top\").each(function(){var l=u.select(this).selectAll(\"g.slice\").data(e);l.enter().append(\"g\").classed(\"slice\",!0),l.exit().remove();var s=[[[],[]],[[],[]]],m=!1;l.each(function(e){function i(n){n.originalEvent=u.event;var o=t._fullLayout,i=t._fullData[v.index],l=i.hoverinfo;if(\"all\"===l&&(l=\"label+text+value+percent+name\"),t._dragging||o.hovermode===!1||\"none\"===l||\"skip\"===l||!l)return void f.hover(t,n,\"pie\");var s=a(e,c),d=w+e.pxmid[0]*(1-s),h=k+e.pxmid[1]*(1-s),p=r.separators,m=[];l.indexOf(\"label\")!==-1&&m.push(e.label),l.indexOf(\"text\")!==-1&&(i.hovertext?m.push(Array.isArray(i.hovertext)?i.hovertext[e.i]:i.hovertext):i.text&&i.text[e.i]&&m.push(i.text[e.i])),l.indexOf(\"value\")!==-1&&m.push(g.formatPieValue(e.v,p)),l.indexOf(\"percent\")!==-1&&m.push(g.formatPiePercent(e.v/c.vTotal,p));var y=i.hoverlabel;f.loneHover({x0:d-s*c.r,x1:d+s*c.r,y:h,text:m.join(\"<br>\"),name:l.indexOf(\"name\")!==-1?i.name:void 0,idealAlign:e.pxmid[0]<0?\"left\":\"right\",color:e.hbg||y.bgcolor||e.color,borderColor:e.hbc||y.bordercolor,fontFamily:e.htf||y.font.family,fontSize:e.hts||y.font.size,fontColor:e.htc||y.font.color},{container:o._hoverlayer.node(),outerContainer:o._paper.node()}),f.hover(t,n,\"pie\"),T=!0}function l(e){e.originalEvent=u.event,t.emit(\"plotly_unhover\",{event:u.event,points:[e]}),T&&(f.loneUnhover(r._hoverlayer.node()),T=!1)}function d(){t._hoverdata=[e],t._hoverdata.trace=c.trace,f.click(t,u.event)}function x(t,r,n,a){return\"a\"+a*c.r+\",\"+a*_+\" \"+y+\" \"+e.largeArc+(n?\" 1 \":\" 0 \")+a*(r[0]-t[0])+\",\"+a*(r[1]-t[1])}if(e.hidden)return void u.select(this).selectAll(\"path,g\").remove();s[e.pxmid[1]<0?0:1][e.pxmid[0]<0?0:1].push(e);var w=c.cx+b[0],k=c.cy+b[1],M=u.select(this),A=M.selectAll(\"path.surface\").data([e]),T=!1;if(A.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),M.select(\"path.textline\").remove(),M.on(\"mouseover\",i).on(\"mouseout\",l).on(\"click\",d),v.pull){var L=+(Array.isArray(v.pull)?v.pull[e.i]:v.pull)||0;L>0&&(w+=L*e.pxmid[0],k+=L*e.pxmid[1])}e.cxFinal=w,e.cyFinal=k;var C=v.hole;if(e.v===c.vTotal){var S=\"M\"+(w+e.px0[0])+\",\"+(k+e.px0[1])+x(e.px0,e.pxmid,!0,1)+x(e.pxmid,e.px0,!0,1)+\"Z\";C?A.attr(\"d\",\"M\"+(w+C*e.px0[0])+\",\"+(k+C*e.px0[1])+x(e.px0,e.pxmid,!1,C)+x(e.pxmid,e.px0,!1,C)+\"Z\"+S):A.attr(\"d\",S)}else{var z=x(e.px0,e.px1,!0,1);if(C){var O=1-C;A.attr(\"d\",\"M\"+(w+C*e.px1[0])+\",\"+(k+C*e.px1[1])+x(e.px1,e.px0,!1,C)+\"l\"+O*e.px0[0]+\",\"+O*e.px0[1]+z+\"Z\")}else A.attr(\"d\",\"M\"+w+\",\"+k+\"l\"+e.px0[0]+\",\"+e.px0[1]+z+\"Z\")}var D=Array.isArray(v.textposition)?v.textposition[e.i]:v.textposition,P=M.selectAll(\"g.slicetext\").data(e.text&&\"none\"!==D?[0]:[]);P.enter().append(\"g\").classed(\"slicetext\",!0),P.exit().remove(),P.each(function(){var t=u.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(e.text).attr({class:\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(h.font,\"outside\"===D?v.outsidetextfont:v.insidetextfont).call(p.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var r,a=h.bBox(t.node());\"outside\"===D?r=o(a,e):(r=n(a,e,c),\"auto\"===D&&r.scale<1&&(t.call(h.font,v.outsidetextfont),v.outsidetextfont.family===v.insidetextfont.family&&v.outsidetextfont.size===v.insidetextfont.size||(t.attr({\"data-bb\":\"\"}),a=h.bBox(t.node())),r=o(a,e)));var i=w+e.pxmid[0]*r.rCenter+(r.x||0),l=k+e.pxmid[1]*r.rCenter+(r.y||0);r.outside&&(e.yLabelMin=l-a.height/2,e.yLabelMid=l,e.yLabelMax=l+a.height/2,e.labelExtraX=0,e.labelExtraY=0,m=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+l+\")\"+(r.scale<1?\"scale(\"+r.scale+\")\":\"\")+(r.rotate?\"rotate(\"+r.rotate+\")\":\"\")+\"translate(\"+-(a.left+a.right)/2+\",\"+-(a.top+a.bottom)/2+\")\")})}),m&&i(s,v),l.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=u.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],a=t.cyFinal+t.pxmid[1],o=\"M\"+n+\",\"+a,i=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var l=t.labelExtraX*t.pxmid[1]/t.pxmid[0],s=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(l)>Math.abs(s)?o+=\"l\"+s*t.pxmid[0]/t.pxmid[1]+\",\"+s+\"H\"+(n+t.labelExtraX+i):o+=\"l\"+t.labelExtraX+\",\"+l+\"v\"+(s-l)+\"h\"+i}else 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t[0][0]===e[0]&&t[0][1]===e[1]?s.smoothclosed(t.slice(1),L.smoothing):s.smoothopen(t,L.smoothing)}:function(t){return\"M\"+t.join(\"L\")},j=function(t){return F(t.reverse())},G=f(n,{xaxis:M,yaxis:A,connectGaps:T.connectgaps,baseTolerance:Math.max(L.width||1,3)/4,linear:\"linear\"===L.shape,simplify:L.simplify}),V=T._polygons=new Array(G.length),w=0;w<G.length;w++)T._polygons[w]=h(G[w]);G.length&&(B=G[0][0],q=G[G.length-1],H=q[q.length-1]),Y=G.filter(function(t){return t.length>1}),Z=function(t){return function(e){if(N=R(e),I=j(e),U?O?(U+=\"L\"+N.substr(1),X=I+\"L\"+X.substr(1)):(U+=\"Z\"+N,X=I+\"Z\"+X):(U=N,X=I),u.hasLines(T)&&e.length>1){var r=i.select(this);if(r.datum(n),t)g(r.style(\"opacity\",0).attr(\"d\",N).call(s.lineGroupStyle)).style(\"opacity\",1);else{var a=g(r);a.attr(\"d\",N),s.singleLineStyle(n,a)}}}}}var W=C.selectAll(\".js-line\").data(Y);g(W.exit()).style(\"opacity\",0).remove(),W.each(Z(!1)),W.enter().append(\"path\").classed(\"js-line\",!0).style(\"vector-effect\",\"non-scaling-stroke\").call(s.lineGroupStyle).each(Z(!0)),G.length&&(S?B&&H&&(O?(\"y\"===O?B[1]=H[1]=A.c2p(0,!0):\"x\"===O&&(B[0]=H[0]=M.c2p(0,!0)),g(S).attr(\"d\",\"M\"+H+\"L\"+B+\"L\"+U.substr(1))):g(S).attr(\"d\",U+\"Z\")):\"tonext\"===T.fill.substr(0,6)&&U&&D&&(\"tonext\"===T.fill?g(z).attr(\"d\",U+\"Z\"+D+\"Z\"):g(z).attr(\"d\",U+\"L\"+D.substr(1)+\"Z\"),T._polygons=T._polygons.concat(P)),T._prevRevpath=X,T._prevPolygons=V);var $=C.selectAll(\".points\");_=$.data([n]),$.each(b),_.enter().append(\"g\").classed(\"points\",!0).each(b),_.exit().remove()}}function o(t,e,r,n,a){var o=r.xaxis,s=r.yaxis,c=i.extent(l.simpleMap(o.range,o.r2c)),f=i.extent(l.simpleMap(s.range,s.r2c)),d=n[0].trace;if(u.hasMarkers(d)){var h=d.marker.maxdisplayed;if(0!==h){var p=n.filter(function(t){return 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o,i=a(\"x\"),l=a(\"y\");if(n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\"],r),i)l?(o=Math.min(i.length,l.length),o<i.length&&(e.x=i.slice(0,o)),o<l.length&&(e.y=l.slice(0,o))):(o=i.length,a(\"y0\"),a(\"dy\"));else{if(!l)return 0;o=e.y.length,a(\"x0\"),a(\"dx\")}return o}},{\"../../registry\":206}]},{},[5])(5)});window.define = window.__define;window.require = window.__require;window.__define = undefined; window.__require = undefined;/* global Highcharts, Plotly*/\n",
       "/* eslint-disable */\n",
       "function throttle(fn, timeout, invokeAsap, ctx) {\n",
       "    var typeofInvokeAsap = typeof invokeAsap;\n",
       "    if(typeofInvokeAsap === 'undefined') {\n",
       "        invokeAsap = true;\n",
       "    } else if(arguments.length === 3 && typeofInvokeAsap !== 'boolean') {\n",
       "        ctx = invokeAsap;\n",
       "        invokeAsap = true;\n",
       "    }\n",
       "\n",
       "    var timer, args, needInvoke,\n",
       "        wrapper = function() {\n",
       "            if(needInvoke) {\n",
       "                fn.apply(ctx, args);\n",
       "                needInvoke = false;\n",
       "                timer = setTimeout(wrapper, timeout);\n",
       "            } else {\n",
       "                timer = null;\n",
       "            }\n",
       "        };\n",
       "\n",
       "    return function() {\n",
       "        args = arguments;\n",
       "        ctx || (ctx = this);\n",
       "        needInvoke = true;\n",
       "\n",
       "        if(!timer) {\n",
       "            invokeAsap?\n",
       "                wrapper() :\n",
       "                timer = setTimeout(wrapper, timeout);\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "/* eslint-enable */\n",
       "function CatboostIpython() {\n",
       "\n",
       "}\n",
       "\n",
       "CatboostIpython.prototype.init = function() {\n",
       "    this.charts = {};\n",
       "    /*\n",
       "        {\n",
       "            \"rmse_1\": {\n",
       "                ...\n",
       "            }\n",
       "        }\n",
       "    */\n",
       "    this.traces = {};\n",
       "    /*\n",
       "        {\n",
       "            \"rmse_1\": {\n",
       "                name: \"rmse\",\n",
       "                id: \"rmse_1\",\n",
       "                parent: \"div\",\n",
       "                traces: [\n",
       "                    {\n",
       "                        name: \"current;learn;0;;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;learn;0;smoothed;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;learn;1;;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;learn;1;smoothed;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;test;0;;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;test;0;smoothed;;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;test;0;;best_point;\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    },\n",
       "                    {\n",
       "                        name: \"current;test;0;;;best_value\",\n",
       "                        x: [],\n",
       "                        y: []\n",
       "                    }\n",
       "                ]\n",
       "            }\n",
       "        }\n",
       "    */\n",
       "\n",
       "    this.hovertextParameters = [];\n",
       "    this.chartsToRedraw = {};\n",
       "    this.lastIndexes = {};\n",
       "    this.smoothness = -1;\n",
       "    this.layoutDisabled = {\n",
       "        series: {},\n",
       "        traces: {}\n",
       "    };\n",
       "    this.clickMode = false;\n",
       "    this.logarithmMode = 'linear';\n",
       "    this.lastSmooth = 0;\n",
       "    this.layout = null;\n",
       "    this.activeTab = '';\n",
       "    this.meta = {};\n",
       "    this.timeLeft = {};\n",
       "\n",
       "    this.hasCVMode = false;\n",
       "    this.stddevEnabled = false;\n",
       "\n",
       "    this.colors = [\n",
       "        '#68E256',\n",
       "        '#56AEE2',\n",
       "        '#CF56E2',\n",
       "        '#E28956',\n",
       "        '#56E289',\n",
       "        '#5668E2',\n",
       "        '#E256AE',\n",
       "        '#E2CF56',\n",
       "        '#56E2CF',\n",
       "        '#8A56E2',\n",
       "        '#E25668',\n",
       "        '#AEE256'\n",
       "    ];\n",
       "    this.colorsByPath = {};\n",
       "    this.colorIndex = 0;\n",
       "    this.lossFuncs = {};\n",
       "\n",
       "    this.isCVinited = false;\n",
       "};\n",
       "\n",
       "/* eslint-disable */\n",
       "CatboostIpython.prototype.loadStyles = function(path, fn, scope) {\n",
       "    $('link[catboost=\"1\"]').remove();\n",
       "\n",
       "    var head = document.getElementsByTagName('head')[0], // reference to document.head for appending/ removing link nodes\n",
       "        link = document.createElement('link');           // create the link node\n",
       "    link.setAttribute('href', path);\n",
       "    link.setAttribute('rel', 'stylesheet');\n",
       "    link.setAttribute('type', 'text/css');\n",
       "    link.setAttribute('catboost', '1');\n",
       "\n",
       "    var sheet, cssRules;\n",
       "    // get the correct properties to check for depending on the browser\n",
       "    if ('sheet' in link) {\n",
       "        sheet = 'sheet'; cssRules = 'cssRules';\n",
       "    } else {\n",
       "        sheet = 'styleSheet'; cssRules = 'rules';\n",
       "    }\n",
       "\n",
       "    var interval_id = setInterval(function() {                     // start checking whether the style sheet has successfully loaded\n",
       "        try {\n",
       "            if (link[sheet] && link[sheet][cssRules].length) { // SUCCESS! our style sheet has loaded\n",
       "                clearInterval(interval_id);                      // clear the counters\n",
       "                clearTimeout(timeout_id);\n",
       "                fn.call( scope || window, true, link);           // fire the callback with success == true\n",
       "            }\n",
       "        } catch(e) {} finally {}\n",
       "    }, 50 ),                                                   // how often to check if the stylesheet is loaded\n",
       "    timeout_id = setTimeout( function() {       // start counting down till fail\n",
       "        clearInterval( interval_id );             // clear the counters\n",
       "        clearTimeout( timeout_id );\n",
       "        head.removeChild( link );                // since the style sheet didn't load, remove the link node from the DOM\n",
       "        fn.call( scope || window, false, link ); // fire the callback with success == false\n",
       "    }, 15000 );                                 // how long to wait before failing\n",
       "\n",
       "    head.appendChild( link );  // insert the link node into the DOM and start loading the style sheet\n",
       "\n",
       "    return link; // return the link node;\n",
       "};\n",
       "/* eslint-enable */\n",
       "\n",
       "CatboostIpython.prototype.resizeCharts = function() {\n",
       "    // width fix for development\n",
       "    $('.catboost-graph__charts', this.layout).css({width: $('.catboost-graph').width()});\n",
       "\n",
       "    this.plotly.Plots.resize(this.traces[this.activeTab].parent);\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addMeta = function(path, meta) {\n",
       "    this.meta[path] = meta;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addLayout = function(parent) {\n",
       "    if (this.layout) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var cvAreaControls = '';\n",
       "\n",
       "    if (this.hasCVMode) {\n",
       "        cvAreaControls =    '<div>' +\n",
       "                                '<input type=\"checkbox\" class=\"catboost-panel__control_checkbox\" id=\"catboost-control2-cvstddev' + this.index + '\"' + (this.stddevEnabled ? ' checked=\"checked\"' : '') + '></input>' +\n",
       "                                '<label for=\"catboost-control2-cvstddev' + this.index + '\" class=\"catboost-panel__controls2_label catboost-panel__controls2_label-long\">Standard Deviation</label>' +\n",
       "                            '</div>';\n",
       "    }\n",
       "\n",
       "    this.layout = $('<div class=\"catboost\">' +\n",
       "                        '<div class=\"catboost-panel\">' +\n",
       "                            '<div class=\"catboost-panel__controls\">' +\n",
       "                                '<input type=\"checkbox\" class=\"catboost-panel__controls_checkbox\" id=\"catboost-control-learn' + this.index + '\" ' + (!this.layoutDisabled.learn ? ' checked=\"checked\"' : '') + '></input>' +\n",
       "                                '<label for=\"catboost-control-learn' + this.index + '\" class=\"catboost-panel__controls_label\"><div class=\"catboost-panel__serie_learn_pic\" style=\"border-color:#999\"></div>Learn</label>' +\n",
       "                                '<input type=\"checkbox\" class=\"catboost-panel__controls_checkbox\" id=\"catboost-control-test' + this.index + '\" ' + (!this.layoutDisabled.test ? ' checked=\"checked\"' : '') + '></input>' +\n",
       "                                '<label for=\"catboost-control-test' + this.index + '\" class=\"catboost-panel__controls_label\"><div class=\"catboost-panel__serie_test_pic\" style=\"border-color:#999\"></div>Eval</label>' +\n",
       "                            '</div>' +\n",
       "                            '<div class=\"catboost-panel__series ' + (this.layoutDisabled.learn ? ' catboost-panel__series_learn_disabled' : '') + '\">' +\n",
       "                            '</div>' +\n",
       "                            '<div class=\"catboost-panel__controls2\">' +\n",
       "                                '<input type=\"checkbox\" class=\"catboost-panel__control_checkbox\" id=\"catboost-control2-clickmode' + this.index + '\"></input>' +\n",
       "                                '<label for=\"catboost-control2-clickmode' + this.index + '\" class=\"catboost-panel__controls2_label\">Click Mode</label>' +\n",
       "                                '<input type=\"checkbox\" class=\"catboost-panel__control_checkbox\" id=\"catboost-control2-log' + this.index + '\"></input>' +\n",
       "                                '<label for=\"catboost-control2-log' + this.index + '\" class=\"catboost-panel__controls2_label\">Logarithm</label>' +\n",
       "                                '<div>' +\n",
       "                                    '<input type=\"checkbox\" class=\"catboost-panel__control_checkbox\" id=\"catboost-control2-smooth' + this.index + '\"></input>' +\n",
       "                                    '<label for=\"catboost-control2-smooth' + this.index + '\" class=\"catboost-panel__controls2_label\">Smooth</label>' +\n",
       "                                    '<input id=\"catboost-control2-slider' + this.index + '\" disabled=\"disabled\" class=\"catboost-panel__control_slider\" type =\"range\" value=\"0\" min=\"0\" max=\"1\" step =\"0.01\" for=\"rangeInputValue\" name=\"rangeInput\"/>' +\n",
       "                                    '<input id=\"catboost-control2-slidervalue' + this.index + '\" disabled=\"disabled\" class=\"catboost-panel__control_slidervalue\" value=\"0\" min=\"0\" max=\"1\" for=\"rangeInput\" name=\"rangeInputValue\"/>' +\n",
       "                                '</div>' +\n",
       "                                cvAreaControls +\n",
       "                            '</div>' +\n",
       "                        '</div>' +\n",
       "                        '<div class=\"catboost-graph\">' +\n",
       "                            '<div class=\"catboost-graph__tabs\"></div>' +\n",
       "                            '<div class=\"catboost-graph__charts\"></div>' +\n",
       "                        '</div>' +\n",
       "                    '</div>');\n",
       "    $(parent).append(this.layout);\n",
       "\n",
       "    this.addTabEvents();\n",
       "    this.addControlEvents();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addTabEvents = function() {\n",
       "    var self = this;\n",
       "\n",
       "    $('.catboost-graph__tabs', this.layout).click(function(e) {\n",
       "        if (!$(e.target).is('.catboost-graph__tab:not(.catboost-graph__tab_active)')) {\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var id = $(e.target).attr('tabid');\n",
       "\n",
       "        self.activeTab = id;\n",
       "\n",
       "        $('.catboost-graph__tab_active', self.layout).removeClass('catboost-graph__tab_active');\n",
       "        $('.catboost-graph__chart_active', self.layout).removeClass('catboost-graph__chart_active');\n",
       "\n",
       "        $('.catboost-graph__tab[tabid=\"' + id + '\"]', self.layout).addClass('catboost-graph__tab_active');\n",
       "        $('.catboost-graph__chart[tabid=\"' + id + '\"]', self.layout).addClass('catboost-graph__chart_active');\n",
       "\n",
       "        self.cleanSeries();\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "        self.resizeCharts();\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addControlEvents = function() {\n",
       "    var self = this;\n",
       "\n",
       "    $('#catboost-control-learn' + this.index, this.layout).click(function() {\n",
       "        self.layoutDisabled.learn = !$(this)[0].checked;\n",
       "\n",
       "        $('.catboost-panel__series', self.layout).toggleClass('catboost-panel__series_learn_disabled', self.layoutDisabled.learn);\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    $('#catboost-control-test' + this.index, this.layout).click(function() {\n",
       "        self.layoutDisabled.test = !$(this)[0].checked;\n",
       "\n",
       "        $('.catboost-panel__series', self.layout).toggleClass('catboost-panel__series_test_disabled', self.layoutDisabled.test);\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    $('#catboost-control2-clickmode' + this.index, this.layout).click(function() {\n",
       "        self.clickMode = $(this)[0].checked;\n",
       "    });\n",
       "\n",
       "    $('#catboost-control2-log' + this.index, this.layout).click(function() {\n",
       "        self.logarithmMode = $(this)[0].checked ? 'log' : 'linear';\n",
       "\n",
       "        self.forEveryLayout(function(layout) {\n",
       "            layout.yaxis = {type: self.logarithmMode};\n",
       "        });\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    var slider = $('#catboost-control2-slider' + this.index),\n",
       "        sliderValue = $('#catboost-control2-slidervalue' + this.index);\n",
       "\n",
       "    $('#catboost-control2-smooth' + this.index, this.layout).click(function() {\n",
       "        var enabled = $(this)[0].checked;\n",
       "\n",
       "        self.setSmoothness(enabled ? self.lastSmooth : -1);\n",
       "\n",
       "        slider.prop('disabled', !enabled);\n",
       "        sliderValue.prop('disabled', !enabled);\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    $('#catboost-control2-cvstddev' + this.index, this.layout).click(function() {\n",
       "        var enabled = $(this)[0].checked;\n",
       "\n",
       "        self.setStddev(enabled);\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    slider.on('input change', function() {\n",
       "        var smooth = Number($(this).val());\n",
       "\n",
       "        sliderValue.val(isNaN(smooth) ? 0 : smooth);\n",
       "\n",
       "        self.setSmoothness(smooth);\n",
       "        self.lastSmooth = smooth;\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "\n",
       "    sliderValue.on('input change', function() {\n",
       "        var smooth = Number($(this).val());\n",
       "\n",
       "        slider.val(isNaN(smooth) ? 0 : smooth);\n",
       "\n",
       "        self.setSmoothness(smooth);\n",
       "        self.lastSmooth = smooth;\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.setTraceVisibility = function(trace, visibility) {\n",
       "    if (trace) {\n",
       "        trace.visible = visibility;\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesVisibility = function() {\n",
       "    var tracesHash = this.groupTraces(),\n",
       "        traces,\n",
       "        smoothDisabled = this.getSmoothness() === -1,\n",
       "        self = this;\n",
       "\n",
       "    for (var train in tracesHash) {\n",
       "        if (tracesHash.hasOwnProperty(train)) {\n",
       "            traces = tracesHash[train].traces;\n",
       "\n",
       "            if (this.layoutDisabled.traces[train]) {\n",
       "                traces.forEach(function(trace) {\n",
       "                    self.setTraceVisibility(trace, false);\n",
       "                });\n",
       "            } else {\n",
       "                traces.forEach(function(trace) {\n",
       "                    self.setTraceVisibility(trace, true);\n",
       "                });\n",
       "\n",
       "                if (this.hasCVMode) {\n",
       "                    if (this.stddevEnabled) {\n",
       "                        self.filterTracesOne(traces, {type: 'learn'}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "                        self.filterTracesOne(traces, {type: 'test'}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'learn', cv_avg: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'learn', cv_avg: true, smoothed: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true, smoothed: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true, best_point: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesOne(traces, {cv_stddev_first: true}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "                        self.filterTracesOne(traces, {cv_stddev_last: true}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, true);\n",
       "                        });\n",
       "                    } else {\n",
       "                        self.filterTracesOne(traces, {cv_stddev_first: true}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "                        self.filterTracesOne(traces, {cv_stddev_last: true}).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'learn', cv_avg: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'learn', cv_avg: true, smoothed: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true, smoothed: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "\n",
       "                        self.filterTracesEvery(traces, this.getTraceDefParams({type: 'test', cv_avg: true, best_point: true})).forEach(function(trace) {\n",
       "                            self.setTraceVisibility(trace, false);\n",
       "                        });\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                if (smoothDisabled) {\n",
       "                    self.filterTracesOne(traces, {smoothed: true}).forEach(function(trace) {\n",
       "                        self.setTraceVisibility(trace, false);\n",
       "                    });\n",
       "                }\n",
       "\n",
       "                if (this.layoutDisabled['learn']) {\n",
       "                    self.filterTracesOne(traces, {type: 'learn'}).forEach(function(trace) {\n",
       "                        self.setTraceVisibility(trace, false);\n",
       "                    });\n",
       "                }\n",
       "\n",
       "                if (this.layoutDisabled['test']) {\n",
       "                    self.filterTracesOne(traces, {type: 'test'}).forEach(function(trace) {\n",
       "                        self.setTraceVisibility(trace, false);\n",
       "                    });\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getSmoothness = function() {\n",
       "    return this.smoothness && this.smoothness > -1 ? this.smoothness : -1;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.setSmoothness = function(weight) {\n",
       "    if (weight < 0 && weight !== -1 || weight > 1) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    this.smoothness = weight;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.setStddev = function(enabled) {\n",
       "    this.stddevEnabled = enabled;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.redrawActiveChart = function() {\n",
       "    this.chartsToRedraw[this.activeTab] = true;\n",
       "\n",
       "    this.redrawAll();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.redraw = function() {\n",
       "    if (this.chartsToRedraw[this.activeTab]) {\n",
       "        this.chartsToRedraw[this.activeTab] = false;\n",
       "\n",
       "        this.updateTracesVisibility();\n",
       "        this.updateTracesCV();\n",
       "        this.updateTracesBest();\n",
       "        this.updateTracesValues();\n",
       "        this.updateTracesSmoothness();\n",
       "\n",
       "        this.plotly.redraw(this.traces[this.activeTab].parent);\n",
       "    }\n",
       "\n",
       "    this.drawTraces();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addRedrawFunc = function() {\n",
       "    this.redrawFunc = throttle(this.redraw, 400, false, this);\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.redrawAll = function() {\n",
       "    if (!this.redrawFunc) {\n",
       "        this.addRedrawFunc();\n",
       "    }\n",
       "\n",
       "    this.redrawFunc();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addPoints = function(parent, data) {\n",
       "    var self = this;\n",
       "\n",
       "    data.chunks.forEach(function(item) {\n",
       "        if (typeof item.remaining_time !== 'undefined' && typeof item.passed_time !== 'undefined') {\n",
       "            if (!self.timeLeft[data.path]) {\n",
       "                self.timeLeft[data.path] = [];\n",
       "            }\n",
       "\n",
       "            self.timeLeft[data.path][item.iteration] = [item.remaining_time, item.passed_time];\n",
       "        }\n",
       "\n",
       "        ['test', 'learn'].forEach(function(type) {\n",
       "            var sets = self.meta[data.path][type + '_sets'],\n",
       "                metrics = self.meta[data.path][type + '_metrics'];\n",
       "\n",
       "            for (var i = 0; i < metrics.length; i++) {\n",
       "                var nameOfMetric = metrics[i].name,\n",
       "                    cvAdded = false;\n",
       "                    hovertextParametersAdded = false;\n",
       "\n",
       "                self.lossFuncs[nameOfMetric] = metrics[i].best_value;\n",
       "\n",
       "                for (var j = 0; j < sets.length; j++) {\n",
       "                    var nameOfSet = sets[j],\n",
       "                        params = {\n",
       "                            chartName: nameOfMetric,\n",
       "                            index: i,\n",
       "                            train: data.train,\n",
       "                            type: type,\n",
       "                            path: data.path,\n",
       "                            indexOfSet: j,\n",
       "                            nameOfSet: nameOfSet\n",
       "                        },\n",
       "                        key = self.getKey(params),\n",
       "                        launchMode = self.getLaunchMode(data.path);\n",
       "\n",
       "                    if (!self.activeTab) {\n",
       "                        self.activeTab = key.chartId;\n",
       "                    }\n",
       "\n",
       "                    if (launchMode === 'CV' ) {\n",
       "                        // we need to set launch mode before first getTrace call\n",
       "                        self.hasCVMode = true;\n",
       "\n",
       "                        if (!self.isCVinited) {\n",
       "                            // and we don't need to reset setting for next iterations\n",
       "                            self.layoutDisabled.learn = true;\n",
       "                            self.setStddev(true);\n",
       "\n",
       "                            self.isCVinited = true;\n",
       "                        }\n",
       "                    }\n",
       "\n",
       "                    var valuesOfSet = item[nameOfSet],\n",
       "                        pointValue = valuesOfSet[i],\n",
       "                        pointIndex = item.iteration,\n",
       "                        // traces\n",
       "                        trace = self.getTrace(parent, params),\n",
       "                        smoothedTrace = self.getTrace(parent, $.extend({smoothed: true}, params)),\n",
       "                        bestValueTrace = null;\n",
       "\n",
       "                    if (type === 'test') {\n",
       "                        if (launchMode !== 'CV') {\n",
       "                            self.getTrace(parent, $.extend({best_point: true}, params));\n",
       "                        }\n",
       "\n",
       "                        if (typeof self.lossFuncs[nameOfMetric] === 'number') {\n",
       "                            bestValueTrace = self.getTrace(parent, $.extend({best_value: true}, params));\n",
       "                        }\n",
       "                    }\n",
       "\n",
       "                    if (pointValue !== 'inf' && pointValue !== 'nan') {\n",
       "                        trace.x[pointIndex] = pointIndex;\n",
       "                        trace.y[pointIndex] = valuesOfSet[i];\n",
       "                        trace.hovertext[pointIndex] = nameOfSet + ': ' + valuesOfSet[i].toPrecision(7);\n",
       "                        if (item.hasOwnProperty('parameters')) {\n",
       "                            self.hovertextParameters[pointIndex] = '';\n",
       "                            for (var parameter in item.parameters[0]) {\n",
       "                                if (item.parameters[0].hasOwnProperty(parameter)) {\n",
       "                                    valueOfParameter = item.parameters[0][parameter];\n",
       "                                    self.hovertextParameters[pointIndex] += '<br>' + parameter + ' : ' + valueOfParameter;\n",
       "                                }\n",
       "                            }\n",
       "                        }\n",
       "                        if (!hovertextParametersAdded && type === 'test') {\n",
       "                            hovertextParametersAdded = true;\n",
       "                            trace.hovertext[pointIndex] += self.hovertextParameters[pointIndex];\n",
       "                        }\n",
       "                        smoothedTrace.x[pointIndex] = pointIndex;\n",
       "                    }\n",
       "\n",
       "                    if (bestValueTrace) {\n",
       "                        bestValueTrace.x[pointIndex] = pointIndex;\n",
       "                        bestValueTrace.y[pointIndex] = self.lossFuncs[nameOfMetric];\n",
       "                    }\n",
       "\n",
       "                    if (launchMode === 'CV' && !cvAdded) {\n",
       "                        cvAdded = true;\n",
       "\n",
       "                        self.getTrace(parent, $.extend({cv_stddev_first: true}, params));\n",
       "                        self.getTrace(parent, $.extend({cv_stddev_last: true}, params));\n",
       "\n",
       "                        self.getTrace(parent, $.extend({cv_stddev_first: true, smoothed: true}, params));\n",
       "                        self.getTrace(parent, $.extend({cv_stddev_last: true, smoothed: true}, params));\n",
       "\n",
       "                        self.getTrace(parent, $.extend({cv_avg: true}, params));\n",
       "                        self.getTrace(parent, $.extend({cv_avg: true, smoothed: true}, params));\n",
       "\n",
       "                        if (type === 'test') {\n",
       "                            self.getTrace(parent, $.extend({cv_avg: true, best_point: true}, params));\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "\n",
       "                self.chartsToRedraw[key.chartId] = true;\n",
       "\n",
       "                self.redrawAll();\n",
       "            }\n",
       "        });\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getLaunchMode = function(path) {\n",
       "    return this.meta[path].launch_mode;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getChartNode = function(params, active) {\n",
       "    var node = $('<div class=\"catboost-graph__chart\" tabid=\"' + params.id + '\"></div>');\n",
       "\n",
       "    if (active) {\n",
       "        node.addClass('catboost-graph__chart_active');\n",
       "    }\n",
       "\n",
       "    return node;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getChartTab = function(params, active) {\n",
       "    var node = $('<div class=\"catboost-graph__tab\" tabid=\"' + params.id + '\">' + params.name + '</div>');\n",
       "\n",
       "    if (active) {\n",
       "        node.addClass('catboost-graph__tab_active');\n",
       "    }\n",
       "\n",
       "    return node;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.forEveryChart = function(callback) {\n",
       "    for (var name in this.traces) {\n",
       "        if (this.traces.hasOwnProperty(name)) {\n",
       "            callback(this.traces[name]);\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.forEveryLayout = function(callback) {\n",
       "    this.forEveryChart(function(chart) {\n",
       "        callback(chart.layout);\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getChart = function(parent, params) {\n",
       "    var id = params.id,\n",
       "        self = this;\n",
       "\n",
       "    if (this.charts[id]) {\n",
       "        return this.charts[id];\n",
       "    }\n",
       "\n",
       "    this.addLayout(parent);\n",
       "\n",
       "    var active = this.activeTab === params.id,\n",
       "        chartNode = this.getChartNode(params, active),\n",
       "        chartTab = this.getChartTab(params, active);\n",
       "\n",
       "    $('.catboost-graph__charts', this.layout).append(chartNode);\n",
       "    $('.catboost-graph__tabs', this.layout).append(chartTab);\n",
       "\n",
       "    this.traces[id] = {\n",
       "        id: params.id,\n",
       "        name: params.name,\n",
       "        parent: chartNode[0],\n",
       "        traces: [],\n",
       "        layout: {\n",
       "            xaxis: {\n",
       "                range: [0, Number(this.meta[params.path].iteration_count)],\n",
       "                type: 'linear',\n",
       "                tickmode: 'auto',\n",
       "                showspikes: true,\n",
       "                spikethickness: 1,\n",
       "                spikedash: 'longdashdot',\n",
       "                spikemode: 'across',\n",
       "                zeroline: false,\n",
       "                showgrid: false\n",
       "            },\n",
       "            yaxis: {\n",
       "                zeroline: false\n",
       "                //showgrid: false\n",
       "                //hoverformat : '.7f'\n",
       "            },\n",
       "            separators: '. ',\n",
       "            //hovermode: 'x',\n",
       "            margin: {l: 38, r: 0, t: 35, b: 30},\n",
       "            autosize: true,\n",
       "            showlegend: false\n",
       "        },\n",
       "        options: {\n",
       "            scrollZoom: false,\n",
       "            modeBarButtonsToRemove: ['toggleSpikelines'],\n",
       "            displaylogo: false\n",
       "        }\n",
       "    };\n",
       "\n",
       "    this.charts[id] = this.plotly.plot(chartNode[0], this.traces[id].traces, this.traces[id].layout, this.traces[id].options);\n",
       "\n",
       "    chartNode[0].on('plotly_hover', function(e) {\n",
       "        self.updateTracesValues(e.points[0].x);\n",
       "    });\n",
       "\n",
       "    chartNode[0].on('plotly_click', function(e) {\n",
       "        self.updateTracesValues(e.points[0].x, true);\n",
       "    });\n",
       "\n",
       "    return this.charts[id];\n",
       "};\n",
       "\n",
       "\n",
       "CatboostIpython.prototype.getTrace = function(parent, params) {\n",
       "    var key = this.getKey(params),\n",
       "        chartSeries = [];\n",
       "\n",
       "    if (this.traces[key.chartId]) {\n",
       "        chartSeries = this.traces[key.chartId].traces.filter(function(trace) {\n",
       "            return trace.name === key.traceName;\n",
       "        });\n",
       "    }\n",
       "\n",
       "    if (chartSeries.length) {\n",
       "        return chartSeries[0];\n",
       "    } else {\n",
       "        this.getChart(parent, {id: key.chartId, name: params.chartName, path: params.path});\n",
       "\n",
       "        var plotParams = {\n",
       "                color: this.getNextColor(params.path, params.smoothed ? 0.2 : 1),\n",
       "                fillsmoothcolor: this.getNextColor(params.path, 0.1),\n",
       "                fillcolor: this.getNextColor(params.path, 0.4),\n",
       "                hoverinfo: params.cv_avg ? 'skip' : 'text+x',\n",
       "                width: params.cv_avg ? 2 : 1,\n",
       "                dash: params.type === 'test' ? 'solid' : 'dot'\n",
       "            },\n",
       "            trace = {\n",
       "                name: key.traceName,\n",
       "                _params: params,\n",
       "                x: [],\n",
       "                y: [],\n",
       "                hovertext: [],\n",
       "                hoverinfo: plotParams.hoverinfo,\n",
       "                line: {\n",
       "                    width: plotParams.width,\n",
       "                    dash: plotParams.dash,\n",
       "                    color: plotParams.color\n",
       "                },\n",
       "                mode: 'lines',\n",
       "                hoveron: 'points',\n",
       "                connectgaps: true\n",
       "            };\n",
       "\n",
       "        if (params.best_point) {\n",
       "            trace = {\n",
       "                name: key.traceName,\n",
       "                _params: params,\n",
       "                x: [],\n",
       "                y: [],\n",
       "                marker: {\n",
       "                    width: 2,\n",
       "                    color: plotParams.color\n",
       "                },\n",
       "                hovertext: [],\n",
       "                hoverinfo: 'text',\n",
       "                mode: 'markers',\n",
       "                type: 'scatter'\n",
       "            };\n",
       "        }\n",
       "\n",
       "        if (params.best_value) {\n",
       "            trace = {\n",
       "                name: key.traceName,\n",
       "                _params: params,\n",
       "                x: [],\n",
       "                y: [],\n",
       "                line: {\n",
       "                    width: 1,\n",
       "                    dash: 'dash',\n",
       "                    color: '#CCCCCC'\n",
       "                },\n",
       "                mode: 'lines',\n",
       "                connectgaps: true,\n",
       "                hoverinfo: 'skip'\n",
       "            };\n",
       "        }\n",
       "\n",
       "        if (params.cv_stddev_last) {\n",
       "            trace.fill = 'tonexty';\n",
       "        }\n",
       "\n",
       "        trace._params.plotParams = plotParams;\n",
       "\n",
       "        this.traces[key.chartId].traces.push(trace);\n",
       "\n",
       "        return trace;\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getKey = function(params) {\n",
       "    var traceName = [\n",
       "        params.train,\n",
       "        params.type,\n",
       "        params.indexOfSet,\n",
       "        (params.smoothed ? 'smoothed' : ''),\n",
       "        (params.best_point ? 'best_pount' : ''),\n",
       "        (params.best_value ? 'best_value' : ''),\n",
       "        (params.cv_avg ? 'cv_avg' : ''),\n",
       "        (params.cv_stddev_first ? 'cv_stddev_first' : ''),\n",
       "        (params.cv_stddev_last ? 'cv_stddev_last' : '')\n",
       "    ].join(';');\n",
       "\n",
       "    return {\n",
       "        chartId: params.chartName,\n",
       "        traceName: traceName,\n",
       "        colorId: params.train\n",
       "    };\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.filterTracesEvery = function(traces, filter) {\n",
       "    traces = traces || this.traces[this.activeTab].traces;\n",
       "\n",
       "    return traces.filter(function(trace) {\n",
       "        for (var prop in filter) {\n",
       "            if (filter.hasOwnProperty(prop)) {\n",
       "                if (filter[prop] !== trace._params[prop]) {\n",
       "                    return false;\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "\n",
       "        return true;\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.filterTracesOne = function(traces, filter) {\n",
       "    traces = traces || this.traces[this.activeTab].traces;\n",
       "\n",
       "    return traces.filter(function(trace) {\n",
       "        for (var prop in filter) {\n",
       "            if (filter.hasOwnProperty(prop)) {\n",
       "                if (filter[prop] === trace._params[prop]) {\n",
       "                    return true;\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "\n",
       "        return false;\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.cleanSeries = function() {\n",
       "    $('.catboost-panel__series', this.layout).html('');\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.groupTraces = function() {\n",
       "    var traces = this.traces[this.activeTab].traces,\n",
       "        index = 0,\n",
       "        tracesHash = {};\n",
       "\n",
       "    traces.map(function(trace) {\n",
       "        var train = trace._params.train;\n",
       "\n",
       "        if (!tracesHash[train]) {\n",
       "            tracesHash[train] = {\n",
       "                index: index,\n",
       "                traces: [],\n",
       "                info: {\n",
       "                    path: trace._params.path,\n",
       "                    color: trace._params.plotParams.color\n",
       "                }\n",
       "            };\n",
       "\n",
       "            index++;\n",
       "        }\n",
       "\n",
       "        tracesHash[train].traces.push(trace);\n",
       "    });\n",
       "\n",
       "    return tracesHash;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.drawTraces = function() {\n",
       "    if ($('.catboost-panel__series .catboost-panel__serie', this.layout).length) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var html = '',\n",
       "        tracesHash = this.groupTraces();\n",
       "\n",
       "    for (var train in tracesHash) {\n",
       "        if (tracesHash.hasOwnProperty(train)) {\n",
       "            html += this.drawTrace(train, tracesHash[train]);\n",
       "        }\n",
       "    }\n",
       "\n",
       "    $('.catboost-panel__series', this.layout).html(html);\n",
       "\n",
       "    this.updateTracesValues();\n",
       "\n",
       "    this.addTracesEvents();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getTraceDefParams = function(params) {\n",
       "    var defParams =  {\n",
       "        smoothed: undefined,\n",
       "        best_point: undefined,\n",
       "        best_value: undefined,\n",
       "        cv_avg: undefined,\n",
       "        cv_stddev_first: undefined,\n",
       "        cv_stddev_last: undefined\n",
       "    };\n",
       "\n",
       "    if (params) {\n",
       "        return $.extend(defParams, params);\n",
       "    } else {\n",
       "        return defParams;\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.drawTrace = function(train, hash) {\n",
       "    var info = hash.info,\n",
       "        id = 'catboost-serie-' + this.index + '-' + hash.index,\n",
       "        traces = {\n",
       "            learn: this.filterTracesEvery(hash.traces, this.getTraceDefParams({type: 'learn'})),\n",
       "            test: this.filterTracesEvery(hash.traces, this.getTraceDefParams({type: 'test'}))\n",
       "        },\n",
       "        items = {\n",
       "            learn: {\n",
       "                middle: '',\n",
       "                bottom: ''\n",
       "            },\n",
       "            test: {\n",
       "                middle: '',\n",
       "                bottom: ''\n",
       "            }\n",
       "        },\n",
       "        tracesNames = '';\n",
       "\n",
       "    ['learn', 'test'].forEach(function(type) {\n",
       "        traces[type].forEach(function(trace) {\n",
       "            items[type].middle += '<div class=\"catboost-panel__serie_' + type + '_pic\" style=\"border-color:' + info.color + '\"></div>' +\n",
       "                                  '<div data-index=\"' + trace._params.indexOfSet + '\" class=\"catboost-panel__serie_' + type + '_value\"></div>';\n",
       "\n",
       "            items[type].bottom += '<div class=\"catboost-panel__serie_' + type + '_pic\" style=\"border-color:transparent\"></div>' +\n",
       "                                  '<div data-index=\"' + trace._params.indexOfSet + '\" class=\"catboost-panel__serie_best_' + type + '_value\"></div>';\n",
       "\n",
       "            tracesNames += '<div class=\"catboost-panel__serie_' + type + '_pic\" style=\"border-color:' + info.color + '\"></div>' +\n",
       "                           '<div class=\"catboost-panel__serie_' + type + '_name\">' + trace._params.nameOfSet + '</div>';\n",
       "        });\n",
       "    });\n",
       "\n",
       "    var timeSpendHtml = '<div class=\"catboost-panel__serie_time\">' +\n",
       "                             '<div class=\"catboost-panel__serie_time_spend\" title=\"Time spend\"></div>' +\n",
       "                        '</div>';\n",
       "\n",
       "    var html = '<div id=\"' + id + '\" class=\"catboost-panel__serie\" style=\"color:' + info.color + '\">' +\n",
       "                    '<div class=\"catboost-panel__serie_top\">' +\n",
       "                        '<input type=\"checkbox\" data-seriename=\"' + train + '\" class=\"catboost-panel__serie_checkbox\" id=\"' + id + '-box\" ' + (!this.layoutDisabled.series[train] ? 'checked=\"checked\"' : '') + '></input>' +\n",
       "                        '<label title=' + this.meta[info.path].name + ' for=\"' + id + '-box\" class=\"catboost-panel__serie_label\">' + train + '<div class=\"catboost-panel__serie_time_left\" title=\"Estimate time\"></div></label>' +\n",
       "                        (this.getLaunchMode(info.path) !== 'Eval' ? timeSpendHtml : '') +\n",
       "                    '</div>' +\n",
       "                    '<div class=\"catboost-panel__serie_hint catboost-panel__serie__learn_hint\">curr</div>' +\n",
       "                    '<div class=\"catboost-panel__serie_hint catboost-panel__serie__test_hint\">best</div>' +\n",
       "                    '<div class=\"catboost-panel__serie_iteration\" title=\"curr iteration\"></div>' +\n",
       "                    '<div class=\"catboost-panel__serie_best_iteration\" title=\"best ' + (this.hasCVMode ? 'avg ' : '') + 'iteration\"></div>' +\n",
       "                    '<div class=\"catboost-panel__serie_scroll\">' +\n",
       "                        '<div class=\"catboost-panel__serie_names\">' +\n",
       "                            tracesNames +\n",
       "                        '</div>' +\n",
       "                        '<div class=\"catboost-panel__serie_middle\">' +\n",
       "                            items.learn.middle +\n",
       "                            items.test.middle +\n",
       "                        '</div>' +\n",
       "                        '<div class=\"catboost-panel__serie_bottom\">' +\n",
       "                            items.learn.bottom +\n",
       "                            items.test.bottom +\n",
       "                        '</div>' +\n",
       "                    '</div>' +\n",
       "                '</div>';\n",
       "\n",
       "    return html;\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesValues = function(iteration, click) {\n",
       "    var tracesHash = this.groupTraces();\n",
       "\n",
       "    for (var train in tracesHash) {\n",
       "        if (tracesHash.hasOwnProperty(train) && !this.layoutDisabled.traces[train]) {\n",
       "            this.updateTraceValues(train, tracesHash[train], iteration, click);\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesBest = function() {\n",
       "    var tracesHash = this.groupTraces();\n",
       "\n",
       "    for (var train in tracesHash) {\n",
       "        if (tracesHash.hasOwnProperty(train) && !this.layoutDisabled.traces[train]) {\n",
       "            this.updateTraceBest(train, tracesHash[train]);\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getBestValue = function(data) {\n",
       "    if (!data.length) {\n",
       "        return {\n",
       "            best: undefined,\n",
       "            index: -1\n",
       "        };\n",
       "    }\n",
       "\n",
       "    var best = data[0],\n",
       "        index = 0,\n",
       "        func = this.lossFuncs[this.traces[this.activeTab].name],\n",
       "        bestDiff = typeof func === 'number' ? Math.abs(data[0] - func) : 0;\n",
       "\n",
       "    for (var i = 1, l = data.length; i < l; i++) {\n",
       "        if (func === 'Min' && data[i] < best) {\n",
       "            best = data[i];\n",
       "            index = i;\n",
       "        }\n",
       "\n",
       "        if (func === 'Max' && data[i] > best) {\n",
       "            best = data[i];\n",
       "            index = i;\n",
       "        }\n",
       "\n",
       "        if (typeof func === 'number' && Math.abs(data[i] - func) < bestDiff) {\n",
       "            best = data[i];\n",
       "            bestDiff = Math.abs(data[i] - func);\n",
       "            index = i;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    return {\n",
       "        best: best,\n",
       "        index: index,\n",
       "        func: func\n",
       "    };\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesCV = function() {\n",
       "    this.updateTracesCVAvg();\n",
       "\n",
       "    if (this.hasCVMode && this.stddevEnabled) {\n",
       "        this.updateTracesCVStdDev();\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesCVAvg = function() {\n",
       "    var tracesHash = this.groupTraces(),\n",
       "        avgTraces = this.filterTracesEvery(tracesHash.traces, this.getTraceDefParams({\n",
       "            cv_avg: true\n",
       "        })),\n",
       "        self = this;\n",
       "\n",
       "    avgTraces.forEach(function(trace) {\n",
       "        var origTraces = self.filterTracesEvery(tracesHash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: trace._params.type,\n",
       "                smoothed: trace._params.smoothed\n",
       "            }));\n",
       "\n",
       "        if (origTraces.length) {\n",
       "            self.cvAvgFunc(origTraces, trace);\n",
       "        }\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.cvAvgFunc = function(origTraces, avgTrace) {\n",
       "    var maxCount = origTraces.length,\n",
       "        maxLength = -1,\n",
       "        count,\n",
       "        sum;\n",
       "\n",
       "    origTraces.forEach(function(origTrace) {\n",
       "        if (origTrace.y.length > maxLength) {\n",
       "            maxLength = origTrace.y.length;\n",
       "        }\n",
       "    });\n",
       "\n",
       "    for (var i = 0; i < maxLength; i++) {\n",
       "        sum = 0;\n",
       "        count = 0;\n",
       "\n",
       "        for (var j = 0; j < maxCount; j++) {\n",
       "            if (typeof origTraces[j].y[i] !== 'undefined') {\n",
       "                sum += origTraces[j].y[i];\n",
       "                count++;\n",
       "            }\n",
       "        }\n",
       "\n",
       "        if (count > 0) {\n",
       "            avgTrace.x[i] = i;\n",
       "            avgTrace.y[i] = sum / count;\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesCVStdDev = function() {\n",
       "    var tracesHash = this.groupTraces(),\n",
       "        firstTraces = this.filterTracesOne(tracesHash.traces, {cv_stddev_first: true}),\n",
       "        self = this;\n",
       "\n",
       "    firstTraces.forEach(function(trace) {\n",
       "        var origTraces = self.filterTracesEvery(tracesHash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: trace._params.type,\n",
       "                smoothed: trace._params.smoothed\n",
       "            })),\n",
       "            lastTraces = self.filterTracesEvery(tracesHash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: trace._params.type,\n",
       "                smoothed: trace._params.smoothed,\n",
       "                cv_stddev_last: true\n",
       "            }));\n",
       "\n",
       "        if (origTraces.length && lastTraces.length === 1) {\n",
       "            self.cvStdDevFunc(origTraces, trace, lastTraces[0]);\n",
       "        }\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.cvStdDevFunc = function(origTraces, firstTrace, lastTrace) {\n",
       "    var maxCount = origTraces.length,\n",
       "        maxLength = -1,\n",
       "        count,\n",
       "        sum,\n",
       "        i, j;\n",
       "\n",
       "    origTraces.forEach(function(origTrace) {\n",
       "        if (origTrace.y.length > maxLength) {\n",
       "            maxLength = origTrace.y.length;\n",
       "        }\n",
       "    });\n",
       "\n",
       "    for (i = 0; i < maxLength; i++) {\n",
       "        sum = 0;\n",
       "        count = 0;\n",
       "\n",
       "        for (j = 0; j < maxCount; j++) {\n",
       "            if (typeof origTraces[j].y[i] !== 'undefined') {\n",
       "                sum += origTraces[j].y[i];\n",
       "                count++;\n",
       "            }\n",
       "        }\n",
       "\n",
       "        if (count <= 0) {\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var std = 0,\n",
       "            avg = sum / count;\n",
       "\n",
       "        for (j = 0; j < maxCount; j++) {\n",
       "            if (typeof origTraces[j].y[i] !== 'undefined') {\n",
       "                std += Math.pow(origTraces[j].y[i] - avg, 2);\n",
       "            }\n",
       "        }\n",
       "\n",
       "        std /= (count - 1);\n",
       "        std = Math.pow(std, 0.5);\n",
       "\n",
       "        firstTrace.x[i] = i;\n",
       "        firstTrace.y[i] = avg - std;\n",
       "        firstTrace.hovertext[i] = firstTrace._params.type + ' std: ' + avg.toFixed(7) + '-' + std.toFixed(7);\n",
       "        lastTrace.x[i] = i;\n",
       "        lastTrace.y[i] = avg + std;\n",
       "        lastTrace.hovertext[i] = lastTrace._params.type + ' std: ' + avg.toFixed(7) + '+' + std.toFixed(7);\n",
       "        if (this.hovertextParameters.length > i) {\n",
       "            firstTrace.hovertext[i] += this.hovertextParameters[i];\n",
       "            lastTrace.hovertext[i] += this.hovertextParameters[i];\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTracesSmoothness = function() {\n",
       "    var tracesHash = this.groupTraces(),\n",
       "        smoothedTraces = this.filterTracesOne(tracesHash.traces, {smoothed: true}),\n",
       "        enabled = this.getSmoothness() > -1,\n",
       "        self = this;\n",
       "\n",
       "    smoothedTraces.forEach(function(trace) {\n",
       "        var origTraces = self.filterTracesEvery(tracesHash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: trace._params.type,\n",
       "                indexOfSet: trace._params.indexOfSet,\n",
       "                cv_avg: trace._params.cv_avg,\n",
       "                cv_stddev_first: trace._params.cv_stddev_first,\n",
       "                cv_stddev_last: trace._params.cv_stddev_last\n",
       "            })),\n",
       "            colorFlag = false;\n",
       "\n",
       "        if (origTraces.length === 1) {\n",
       "            origTraces = origTraces[0];\n",
       "\n",
       "            if (origTraces.visible) {\n",
       "                if (enabled) {\n",
       "                    self.smoothFunc(origTraces, trace);\n",
       "                    colorFlag = true;\n",
       "                }\n",
       "\n",
       "                self.highlightSmoothedTrace(origTraces, trace, colorFlag);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.highlightSmoothedTrace = function(trace, smoothedTrace, flag) {\n",
       "    if (flag) {\n",
       "        smoothedTrace.line.color = trace._params.plotParams.color;\n",
       "        trace.line.color = smoothedTrace._params.plotParams.color;\n",
       "        trace.hoverinfo = 'skip';\n",
       "\n",
       "        if (trace._params.cv_stddev_last) {\n",
       "            trace.fillcolor = trace._params.plotParams.fillsmoothcolor;\n",
       "        }\n",
       "    } else {\n",
       "        trace.line.color = trace._params.plotParams.color;\n",
       "        trace.hoverinfo = trace._params.plotParams.hoverinfo;\n",
       "\n",
       "        if (trace._params.cv_stddev_last) {\n",
       "            trace.fillcolor = trace._params.plotParams.fillcolor;\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.smoothFunc = function(origTrace, smoothedTrace) {\n",
       "    var data = origTrace.y,\n",
       "        smoothedPoints = this.smooth(data, this.getSmoothness()),\n",
       "        smoothedIndex = 0,\n",
       "        self = this;\n",
       "\n",
       "    if (smoothedPoints.length) {\n",
       "        data.forEach(function (d, index) {\n",
       "            if (!smoothedTrace.x[index]) {\n",
       "                smoothedTrace.x[index] = index;\n",
       "            }\n",
       "\n",
       "            var nameOfSet = smoothedTrace._params.nameOfSet;\n",
       "\n",
       "            if (smoothedTrace._params.cv_stddev_first || smoothedTrace._params.cv_stddev_last) {\n",
       "                nameOfSet = smoothedTrace._params.type + ' std';\n",
       "            }\n",
       "\n",
       "            smoothedTrace.y[index] = smoothedPoints[smoothedIndex];\n",
       "            smoothedTrace.hovertext[index] = nameOfSet + '`: ' + smoothedPoints[smoothedIndex].toPrecision(7);\n",
       "            if (self.hovertextParameters.length > index) {\n",
       "                smoothedTrace.hovertext[index] += self.hovertextParameters[index];\n",
       "            }\n",
       "            smoothedIndex++;\n",
       "        });\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.formatItemValue = function(value, index, suffix) {\n",
       "    if (typeof value === 'undefined') {\n",
       "        return '';\n",
       "    }\n",
       "\n",
       "    suffix = suffix || '';\n",
       "\n",
       "    return '<span title=\"' + suffix + 'value ' + value + '\">' + value + '</span>';\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTraceBest = function(train, hash) {\n",
       "    var traces = this.filterTracesOne(hash.traces, {best_point: true}),\n",
       "        self = this;\n",
       "\n",
       "    traces.forEach(function(trace) {\n",
       "        var testTrace = self.filterTracesEvery(hash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: 'test',\n",
       "                indexOfSet: trace._params.indexOfSet\n",
       "            }));\n",
       "\n",
       "        if (self.hasCVMode) {\n",
       "            testTrace = self.filterTracesEvery(hash.traces, self.getTraceDefParams({\n",
       "                train: trace._params.train,\n",
       "                type: 'test',\n",
       "                cv_avg: true\n",
       "            }));\n",
       "        }\n",
       "\n",
       "        var bestValue = self.getBestValue(testTrace.length === 1 ? testTrace[0].y : []);\n",
       "\n",
       "        if (bestValue.index !== -1) {\n",
       "            trace.x[0] = bestValue.index;\n",
       "            trace.y[0] = bestValue.best;\n",
       "            trace.hovertext[0] = bestValue.func + ' (' + (self.hasCVMode ? 'avg' : trace._params.nameOfSet) + '): ' + bestValue.index + ' ' + bestValue.best;\n",
       "        }\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.updateTraceValues = function(name, hash, iteration, click) {\n",
       "    var id = 'catboost-serie-' + this.index + '-' + hash.index,\n",
       "        traces = {\n",
       "            learn: this.filterTracesEvery(hash.traces, this.getTraceDefParams({type: 'learn'})),\n",
       "            test: this.filterTracesEvery(hash.traces, this.getTraceDefParams({type: 'test'}))\n",
       "        },\n",
       "        path = hash.info.path,\n",
       "        self = this;\n",
       "\n",
       "    ['learn', 'test'].forEach(function(type) {\n",
       "        traces[type].forEach(function(trace) {\n",
       "            var data = trace.y || [],\n",
       "                index = typeof iteration !== 'undefined' && iteration < data.length - 1 ? iteration : data.length - 1,\n",
       "                value = data.length ? data[index] : undefined,\n",
       "                testTrace = self.filterTracesEvery(hash.traces, self.getTraceDefParams({\n",
       "                    type: 'test',\n",
       "                    indexOfSet: trace._params.indexOfSet\n",
       "                })),\n",
       "                bestValue = self.getBestValue(testTrace.length === 1 ? testTrace[0].y : []),\n",
       "                timeLeft = '',\n",
       "                timeSpend = '';\n",
       "\n",
       "            if (click || !self.clickMode) {\n",
       "                $('#' + id + ' .catboost-panel__serie_' + type + '_value[data-index=' + trace._params.indexOfSet + ']', self.layout)\n",
       "                    .html(self.formatItemValue(value, index, type + ' '));\n",
       "                $('#' + id + ' .catboost-panel__serie_iteration', self.layout).html(index);\n",
       "\n",
       "                if (self.timeLeft[path] && self.timeLeft[path][data.length - 1]) {\n",
       "                    timeLeft = self.timeLeft[path][data.length - 1][0];\n",
       "                }\n",
       "                $('#' + id + ' .catboost-panel__serie_time_left', self.layout).html(timeLeft ? ('~' + self.convertTime(timeLeft)) : '');\n",
       "\n",
       "                if (self.timeLeft[path] && self.timeLeft[path][index]) {\n",
       "                    timeSpend = self.timeLeft[path][index][1];\n",
       "                }\n",
       "\n",
       "                $('#' + id + ' .catboost-panel__serie_time_spend', self.layout).html(self.convertTime(timeSpend));\n",
       "                $('#' + id + ' .catboost-panel__serie_best_iteration', self.layout).html(bestValue.index > -1 ? bestValue.index : '');\n",
       "\n",
       "                $('#' + id + ' .catboost-panel__serie_best_test_value[data-index=' + trace._params.indexOfSet + ']', self.layout)\n",
       "                    .html(self.formatItemValue(bestValue.best, bestValue.index, 'best ' + trace._params.nameOfSet + ' '));\n",
       "            }\n",
       "        });\n",
       "    });\n",
       "\n",
       "    if (this.hasCVMode) {\n",
       "        var testTrace = this.filterTracesEvery(hash.traces, this.getTraceDefParams({\n",
       "                type: 'test',\n",
       "                cv_avg: true\n",
       "            })),\n",
       "            bestValue = this.getBestValue(testTrace.length === 1 ? testTrace[0].y : []);\n",
       "\n",
       "            $('#' + id + ' .catboost-panel__serie_best_iteration', this.layout).html(bestValue.index > -1 ? bestValue.index : '');\n",
       "    }\n",
       "\n",
       "    if (click) {\n",
       "        this.clickMode = true;\n",
       "\n",
       "        $('#catboost-control2-clickmode' + this.index, this.layout)[0].checked = true;\n",
       "    }\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.addTracesEvents = function() {\n",
       "    var self = this;\n",
       "\n",
       "    $('.catboost-panel__serie_checkbox', this.layout).click(function() {\n",
       "        var name = $(this).data('seriename');\n",
       "\n",
       "        self.layoutDisabled.traces[name] = !$(this)[0].checked;\n",
       "\n",
       "        self.redrawActiveChart();\n",
       "    });\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.getNextColor = function(path, opacity) {\n",
       "    var color;\n",
       "\n",
       "    if (this.colorsByPath[path]) {\n",
       "        color = this.colorsByPath[path];\n",
       "    } else {\n",
       "        color = this.colors[this.colorIndex];\n",
       "        this.colorsByPath[path] = color;\n",
       "\n",
       "        this.colorIndex++;\n",
       "\n",
       "        if (this.colorIndex > this.colors.length - 1) {\n",
       "            this.colorIndex = 0;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    return this.hexToRgba(color, opacity);\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.hexToRgba = function(value, opacity) {\n",
       "    if (value.length < 6) {\n",
       "        var pattern = /^#?([a-f\\d])([a-f\\d])([a-f\\d])/i;\n",
       "        value = value.replace(pattern, function(m, r, g, b) {\n",
       "            return '#' + r + r + g + g + b + b;\n",
       "        });\n",
       "    }\n",
       "\n",
       "    var result = /^#?([a-f\\d]{2})([a-f\\d]{2})([a-f\\d]{2})/i.exec(value);\n",
       "    var rgb = {\n",
       "        r: parseInt(result[1], 16),\n",
       "        g: parseInt(result[2], 16),\n",
       "        b: parseInt(result[3], 16)\n",
       "    };\n",
       "\n",
       "    return 'rgba(' + rgb.r + ',' + rgb.g + ',' + rgb.b + ',' + opacity + ')';\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.convertTime = function(time) {\n",
       "    if (!time) {\n",
       "        return '0s';\n",
       "    }\n",
       "\n",
       "    time = Math.floor(time * 1000);\n",
       "\n",
       "    var millis = time % 1000;\n",
       "    time = parseInt(time / 1000, 10);\n",
       "    var seconds = time % 60;\n",
       "    time = parseInt(time / 60, 10);\n",
       "    var minutes = time % 60;\n",
       "    time = parseInt(time / 60, 10);\n",
       "    var hours = time % 24;\n",
       "    var out = \"\";\n",
       "    if (hours && hours > 0) {\n",
       "        out += hours + 'h ';\n",
       "        seconds = 0;\n",
       "        millis = 0;\n",
       "    }\n",
       "    if (minutes && minutes > 0) {\n",
       "        out += minutes + 'm ';\n",
       "        millis = 0;\n",
       "    }\n",
       "    if (seconds && seconds > 0) {\n",
       "        out += seconds + 's ';\n",
       "    }\n",
       "    if (millis && millis > 0) {\n",
       "        out += millis + 'ms';\n",
       "    }\n",
       "\n",
       "    return out.trim();\n",
       "};\n",
       "\n",
       "CatboostIpython.prototype.mean = function(values, valueof) {\n",
       "    var n = values.length,\n",
       "        m = n,\n",
       "        i = -1,\n",
       "        value,\n",
       "        sum = 0,\n",
       "        number = function(x) {\n",
       "            return x === null ? NaN : +x;\n",
       "        };\n",
       "\n",
       "    if (valueof === null) {\n",
       "        while (++i < n) {\n",
       "            if (!isNaN(value = number(values[i]))) {\n",
       "                sum += value;\n",
       "            } else {\n",
       "                --m;\n",
       "            }\n",
       "        }\n",
       "    } else {\n",
       "        while (++i < n) {\n",
       "            if (!isNaN(value = number(valueof(values[i], i, values)))) {\n",
       "                sum += value;\n",
       "            } else {\n",
       "                --m;\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "\n",
       "    if (m) {\n",
       "        return sum / m;\n",
       "    }\n",
       "};\n",
       "\n",
       "// from TensorBoard\n",
       "CatboostIpython.prototype.smooth = function(data, weight) {\n",
       "    // When increasing the smoothing window, it smoothes a lot with the first\n",
       "    // few points and then starts to gradually smooth slower, so using an\n",
       "    // exponential function makes the slider more consistent. 1000^x has a\n",
       "    // range of [1, 1000], so subtracting 1 and dividing by 999 results in a\n",
       "    // range of [0, 1], which can be used as the percentage of the data, so\n",
       "    // that the kernel size can be specified as a percentage instead of a\n",
       "    // hardcoded number, what would be bad with multiple series.\n",
       "    var factor = (Math.pow(1000, weight) - 1) / 999,\n",
       "        kernelRadius = Math.floor(data.length * factor / 2),\n",
       "        res = [],\n",
       "        self = this;\n",
       "\n",
       "    data.forEach(function (d, i) {\n",
       "        var actualKernelRadius = Math.min(kernelRadius, i, data.length - i - 1);\n",
       "        var start = i - actualKernelRadius;\n",
       "        var end = i + actualKernelRadius + 1;\n",
       "        var point = d;\n",
       "        // Only smooth finite numbers.\n",
       "        if (!isFinite(point)) {\n",
       "            res.push(point);\n",
       "        } else {\n",
       "            res.push(self.mean(data.slice(start, end).filter(function(d) {\n",
       "                return isFinite(d);\n",
       "            }), null));\n",
       "        }\n",
       "    });\n",
       "\n",
       "    return res;\n",
       "};\n",
       "var debug = false;\n",
       "\n",
       "if (debug) {\n",
       "    require.config({\n",
       "        shim:{\n",
       "            \"custom/CatboostIpythonPlotly\":{\n",
       "                deps:[\"custom/plotly-basic.min\"]\n",
       "            }\n",
       "        }\n",
       "    })\n",
       "\n",
       "    require.undef('catboost_module');\n",
       "    require.undef('custom/CatboostIpythonPlotly');\n",
       "}\n",
       "\n",
       "var moduleBase = '@jupyter-widgets/base';\n",
       "var modules = [moduleBase];\n",
       "\n",
       "if (debug) {\n",
       "    modules.push('custom/CatboostIpythonPlotly');\n",
       "}\n",
       "\n",
       "define('catboost_module', modules, function(widgets) {\n",
       "    var getInstance = function(el) {\n",
       "            var id = $(el).attr('catboost-id');\n",
       "\n",
       "            if (!id) {\n",
       "                return null;\n",
       "            }\n",
       "\n",
       "            id = id.replace('catboost_', '');\n",
       "\n",
       "            if (!window.catboostIpythonInstances[id]) {\n",
       "                return null;\n",
       "            }\n",
       "\n",
       "            return window.catboostIpythonInstances[id];\n",
       "        },\n",
       "        addInstance = function(el) {\n",
       "            $(el).attr('catboost-id', 'catboost_' + window.catboostIpythonIndex);\n",
       "\n",
       "            var catboostIpython = new CatboostIpython();\n",
       "            catboostIpython.index = window.catboostIpythonIndex;\n",
       "            catboostIpython.plotly = window.Plotly;\n",
       "            if (debug) {\n",
       "                catboostIpython.loadStyles('/custom/CatboostIpython.css', function(){catboostIpython.resizeCharts();})\n",
       "            }\n",
       "\n",
       "            window.catboostIpythonInstances[window.catboostIpythonIndex] = catboostIpython;\n",
       "\n",
       "            window.catboostIpythonIndex++;\n",
       "\n",
       "            return catboostIpython;\n",
       "        };\n",
       "\n",
       "    var CatboostIpythonWidget = widgets.DOMWidgetView.extend({\n",
       "\n",
       "        initialize: function() {\n",
       "            CatboostIpythonWidget.__super__.initialize.apply(this, arguments);\n",
       "\n",
       "            if (!window.catboostIpythonInstances) {\n",
       "                window.catboostIpythonInstances = {};\n",
       "            }\n",
       "\n",
       "            if (typeof window.catboostIpythonIndex === 'undefined') {\n",
       "                window.catboostIpythonIndex = 0;\n",
       "            }\n",
       "\n",
       "            var catboostIpythonInstance = getInstance(this.el);\n",
       "\n",
       "            if (!catboostIpythonInstance) {\n",
       "                catboostIpythonInstance = addInstance(this.el);\n",
       "            }\n",
       "\n",
       "            catboostIpythonInstance.init();\n",
       "        },\n",
       "\n",
       "        render: function() {\n",
       "            this.value_changed();\n",
       "            this.model.on('change:value', this.value_changed, this);\n",
       "        },\n",
       "\n",
       "        update: function() {\n",
       "            this.value_changed();\n",
       "        },\n",
       "\n",
       "        value_changed: function() {\n",
       "            this.el.style['width'] = this.model.get('width');\n",
       "            this.el.style['height'] = this.model.get('height');\n",
       "            this.displayed.then(_.bind(this.render_charts, this));\n",
       "        },\n",
       "\n",
       "        process_all: function(parent, params) {\n",
       "            var data = params.data;\n",
       "\n",
       "            for (var path in data) {\n",
       "                if (data.hasOwnProperty(path)) {\n",
       "                    this.process_row(parent, data[path])\n",
       "                }\n",
       "            }\n",
       "        },\n",
       "\n",
       "        process_row: function(parent, data) {\n",
       "            var catboostIpython = getInstance(parent),\n",
       "                path = data.path,\n",
       "                content = data.content,\n",
       "                items = content.data.iterations,\n",
       "                firstIndex = 0,\n",
       "                chunks = [];\n",
       "\n",
       "            if (!items || !items.length) {\n",
       "                return;\n",
       "            }\n",
       "\n",
       "            if (!catboostIpython.lastIndex) {\n",
       "                catboostIpython.lastIndex = {}\n",
       "            }\n",
       "\n",
       "            if (catboostIpython.lastIndex[path]) {\n",
       "                firstIndex = catboostIpython.lastIndex[path] + 1;\n",
       "            }\n",
       "\n",
       "            catboostIpython.lastIndex[path] = items.length - 1;\n",
       "\n",
       "            for (var i = firstIndex; i < items.length; i++) {\n",
       "                chunks.push(items[i]);\n",
       "            }\n",
       "\n",
       "            catboostIpython.addMeta(data.path, content.data.meta);\n",
       "\n",
       "            catboostIpython.addPoints(parent, {\n",
       "                chunks: chunks,\n",
       "                train: data.name,\n",
       "                path: data.path\n",
       "            });\n",
       "        },\n",
       "\n",
       "        render_charts: function () {\n",
       "            this.process_all(this.el, {\n",
       "                data: this.model.get('data')\n",
       "            });\n",
       "\n",
       "            return this;\n",
       "        }\n",
       "    });\n",
       "\n",
       "    return {\n",
       "        CatboostIpythonWidgetView: CatboostIpythonWidget\n",
       "    };\n",
       "});\n",
       "\n",
       "            </script>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6005fbf6cf9b4c9299a81095a629a488",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "MetricVisualizer(layout=Layout(align_self='stretch', height='500px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<catboost.core.CatBoostRegressor at 0x2349d38bdc8>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features_indices = np.where(x_train.dtypes != np.float)[0]\n",
    "cat_model = CatBoostRegressor(loss_function='RMSE', depth=3, learning_rate=0.01, iterations=1500, \n",
    "    random_seed=18, od_type='Iter',od_wait=20)\n",
    "\n",
    "cat_model.fit(\n",
    "    X_tr, y_tr, use_best_model=True,\n",
    "    cat_features=categorical_features_indices,\n",
    "    eval_set=(X_val, y_val),\n",
    "    verbose=False,  \n",
    "    plot=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the test set predictions and clip values to the specified range\n",
    "y_pred = cat_model.predict(x_test).clip(0., 20.)\n",
    "\n",
    "# Create the submission file and submit!\n",
    "preds = pd.DataFrame(y_pred, columns=['item_cnt_month'])\n",
    "preds.to_csv('submission.csv',index_label='ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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