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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Correlation Matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example illustrates how to create a correlation matrix between input variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from freeforestml import Variable, correlation_matrix\n",
    "from freeforestml import toydata, example_style\n",
    "example_style()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = toydata.get()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_higgs_m = Variable(r\"$m^H$\", \"higgs_m\", \"GeV\")\n",
    "v_jet_1_pt = Variable(r\"$p_{\\mathrm{T}}^{j_1}$\", \"jet_1_pt\", \"GeV\")\n",
    "v_jet_2_pt = Variable(r\"$p_{\\mathrm{T}}^{j_2}$\", \"jet_2_pt\", \"GeV\")\n",
    "v_m_jj = Variable(r\"$m^{jj}$\", \"m_jj\", \"GeV\")\n",
    "v_jet_1_eta = Variable(r\"$\\eta^{j_1}$\" ,\"jet_1_eta\") \n",
    "v_jet_2_eta = Variable(r\"$\\eta^{j_2}$\" ,\"jet_2_eta\")\n",
    "v_tau_pt = Variable(r\"$p_{\\mathrm{T}}^{\\tau}$\", \"tau_pt\", \"GeV\")\n",
    "v_lep_pt = Variable(r\"$p_{\\mathrm{T}}^{\\ell}$\", \"lep_pt\", \"GeV\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "fig, axes = plt.subplots(figsize=(5, 4.5))\n",
    "correlation_matrix(df, [v_jet_1_pt, v_jet_2_pt, v_m_jj, v_higgs_m,\n",
    "                        v_tau_pt, v_lep_pt, v_jet_1_eta, v_jet_2_eta],\n",
    "                  figure=fig, axes=axes)"
   ]
  }
 ],
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