{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(\"seaborn-notebook\")\n",
    "\n",
    "from ipywidgets import interact, interactive, fixed\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "\n",
    "import notes_tools.tools as tools\n",
    "from notes_tools.generate_bilan import texenv\n",
    "from notes_tools.tools.df_marks_manip import round_half_point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "classe = \"509\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ws = tools.get_class_ws(classe)\n",
    "flat = tools.extract_flat_marks(ws)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "quest_pov, exo_pov, eval_pov = tools.digest_flat_df(flat)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Création des bilans trimestriels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def create_summary_table(pv_table, coefs = \"\"):\n",
    "    if coefs:\n",
    "        cols = [(\"Evaluations\",[\"Note\", \"Note sur 20\", \"Coefficient\"])]\n",
    "    else:\n",
    "        cols = [(\"Evaluations\",[\"Note\", \"Note sur 20\"])]\n",
    "    for k,v in pv_table.iterrows():\n",
    "        if coefs:\n",
    "            cols.append((k[1], [\"{}/{}\".format(v.iloc[1], v.iloc[0]), \"\", coefs[k[1]]]))\n",
    "        else:\n",
    "            cols.append((k[1], [\"{}/{}\".format(v.iloc[1], v.iloc[0]), \"\"]))\n",
    "            #cols[k[1]] = [\"{}/{}\".format(v.iloc[1], v.iloc[0]), \"\"]\n",
    "    #df = pd.DataFrame.from_dict(cols)\n",
    "    df = pd.DataFrame.from_items(cols)\n",
    "    #return df.set_index('Evaluations')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def build_latex_content(eval_pov, coefs=\"\"):\n",
    "    table = pd.pivot_table(eval_pov,\n",
    "              index = [\"Eleve\", \"Nom\"],\n",
    "              values = [\"Mark\", \"Bareme\"],\n",
    "              #columns = [\"Nom\"],\n",
    "              )\n",
    "    content = {}\n",
    "    content[\"students\"] = []\n",
    "    for e in eval_pov[\"Eleve\"].unique():\n",
    "        eleve = {\"name\":e}\n",
    "        e_table = table.query('Eleve == \"{}\"'.format(e))\n",
    "        summary = create_summary_table(e_table, coefs)\n",
    "        \n",
    "        col_format = \"|\"+\"c|\"*len(summary.columns)\n",
    "        #print(len(summary.columns))\n",
    "        eleve['latex_table'] = summary.to_latex(index=False, column_format=col_format)\n",
    "        content[\"students\"].append(eleve)\n",
    "    return content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coefs = {\"DM1\":0.5, \"DM2\":0.5, \"DS1\":1, \"DS2\":1, \"ConnT1\":1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#build_latex_content(eval_pov)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#content = build_latex_content(eval_pov, coefs)\n",
    "content = build_latex_content(eval_pov)\n",
    "tpl = texenv.get_template(\"./tpl_bilan_trim.tex\")\n",
    "with open(\"./{}/trim1.tex\".format(classe), \"w\")  as f:\n",
    "    f.write(tpl.render(content))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
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