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  {
   "cell_type": "markdown",
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   "source": [
    "# Tutorial 3: Plot clusters\n",
    "\n",
    "This tutorial will talk about how to plot the clusters created from the data in Tutorial 1.\n",
    "\n",
    "**NOTE FOR CONTRIBUTORS: Always clear all output before committing (``Cell`` > ``All Output`` > ``Clear``)**!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Magic\n",
    "%matplotlib inline\n",
    "# Reload modules whenever they change\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "# Make clusterking package available even without installation\n",
    "import sys\n",
    "sys.path = [\"../../\"] + sys.path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import clusterking as ck"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As in tutorial 3 we load the data created in tutorial 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = ck.Data(\"output/tutorial_basics.sql\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.configure_variable(\"CVL_bctaunutau\", r\"$C_{V_L}$\")\n",
    "d.configure_variable(\"CSL_bctaunutau\", r\"$C_{S_L}$\")\n",
    "d.configure_variable(\"CT_bctaunutau\", r\"$C_T$\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3D plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scatter plot: The list is the list of the columns on the axes. \n",
    "Changing the order of the columns will turn around the cube. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_scatter(['CVL_bctaunutau', 'CSL_bctaunutau', 'CT_bctaunutau']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If it is still not easy to get an overview, use the ``clusters`` argument to limit ourselves to certain clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_scatter(['CVL_bctaunutau', 'CSL_bctaunutau', 'CT_bctaunutau'], clusters=[1, 2, 3]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If only two columns are given, several cuts will be presented (up to 16 by default):"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2D cuts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the benchmark points are denoted by a larger symbol."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_scatter(['CVL_bctaunutau', 'CSL_bctaunutau']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, we can also limit ourselves on the clusters that we want to display:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_scatter(['CVL_bctaunutau', 'CSL_bctaunutau'], clusters=[1,2]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also fill the space between sample points:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_fill(['CVL_bctaunutau', 'CSL_bctaunutau']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Several options to configure the ClusterPlot object can be changed after the object has been initialized."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The number of plots for the 'slices' can be selected as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.plot_clusters_fill(['CVL_bctaunutau', 'CSL_bctaunutau'], max_subplots=3);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "help(d.plot_clusters_scatter)"
   ]
  }
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