{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b0a4b001-444e-477c-b77a-75b4961b19c5",
   "metadata": {},
   "source": [
    "# Returning to the Theme Defaults with `flavor_standard()`\n",
    "\n",
    "Use `flavor_standard()` to override other flavors or to make defaults explicit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f121962e-83d5-4dfd-be9d-de64733829cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <div id=\"THYLwb\"></div>\n",
       "            <script type=\"text/javascript\" data-lets-plot-script=\"library\">\n",
       "                if(!window.letsPlotCallQueue) {\n",
       "                    window.letsPlotCallQueue = [];\n",
       "                }; \n",
       "                window.letsPlotCall = function(f) {\n",
       "                    window.letsPlotCallQueue.push(f);\n",
       "                };\n",
       "                (function() {\n",
       "                    var script = document.createElement(\"script\");\n",
       "                    script.type = \"text/javascript\";\n",
       "                    script.src = \"https://cdn.jsdelivr.net/gh/JetBrains/lets-plot@v4.8.0rc1/js-package/distr/lets-plot.min.js\";\n",
       "                    script.onload = function() {\n",
       "                        window.letsPlotCall = function(f) {f();};\n",
       "                        window.letsPlotCallQueue.forEach(function(f) {f();});\n",
       "                        window.letsPlotCallQueue = [];\n",
       "                        \n",
       "                    };\n",
       "                    script.onerror = function(event) {\n",
       "                        window.letsPlotCall = function(f) {};    // noop\n",
       "                        window.letsPlotCallQueue = [];\n",
       "                        var div = document.createElement(\"div\");\n",
       "                        div.style.color = 'darkred';\n",
       "                        div.textContent = 'Error loading Lets-Plot JS';\n",
       "                        document.getElementById(\"THYLwb\").appendChild(div);\n",
       "                    };\n",
       "                    var e = document.getElementById(\"THYLwb\");\n",
       "                    e.appendChild(script);\n",
       "                })()\n",
       "            </script>\n",
       "            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from lets_plot import *\n",
    "\n",
    "LetsPlot.setup_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70c03e39-79bd-48d6-af48-4d4fee042167",
   "metadata": {},
   "outputs": [],
   "source": [
    "# A reusable style layer for consistent plots across the project.\n",
    "\n",
    "my_theme = (\n",
    "    theme_classic() +\n",
    "    theme(\n",
    "        axis_title=element_text(size=13),\n",
    "        axis_text=element_text(size=15),\n",
    "        legend_position=\"left\",\n",
    "        axis_ticks_length=7,\n",
    "        panel_grid_major=element_line(color=\"spring_green\"),\n",
    "        panel_grid_minor=element_blank()\n",
    "    ) + flavor_darcula()\n",
    ")\n",
    "\n",
    "LetsPlot.set_theme(my_theme)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ce3cb8cf-08f4-4e87-b42b-68bb32482425",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpg_df = pd.read_csv (\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c3d9b68d-62ec-46b2-b9f8-ed2e9c7eac58",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "   <div id=\"pocjrb\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   const forceImmediateRender = false;\n",
       "   const responsive = false;\n",
       "   \n",
       "   let sizing = {\n",
       "       width_mode: \"MIN\",\n",
       "       height_mode: \"SCALED\",\n",
       "       width: null, \n",
       "       height: null \n",
       "   };\n",
       "   \n",
       "   const preferredWidth = document.body.dataset.letsPlotPreferredWidth;\n",
       "   if (preferredWidth !== undefined) {\n",
       "       sizing = {\n",
       "           width_mode: 'FIXED',\n",
       "           height_mode: 'SCALED',\n",
       "           width: parseFloat(preferredWidth)\n",
       "       };\n",
       "   }\n",
       "   \n",
       "   const containerDiv = document.getElementById(\"pocjrb\");\n",
       "   let fig = null;\n",
       "   \n",
       "   function renderPlot() {\n",
       "       if (fig === null) {\n",
       "           const plotSpec = {\n",
       "\"data\":{\n",
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       "\"column\":\"manufacturer\"\n",
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       "\"column\":\"model\"\n",
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       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
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       "\"theme\":{\n",
       "\"name\":\"classic\",\n",
       "\"axis_title\":{\n",
       "\"size\":13.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"axis_text\":{\n",
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       "},\n",
       "\"panel_grid_minor\":{\n",
       "\"blank\":true\n",
       "},\n",
       "\"flavor\":\"darcula\"\n",
       "},\n",
       "\"ggtitle\":{\n",
       "\"text\":\"Fuel Economy: City and Highway Mileage by Drive Type\"\n",
       "},\n",
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       "\"scales\":[],\n",
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       "           }\n",
       "       });\n",
       "       \n",
       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x13d1c0be0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A base plot with the common project style\n",
    "\n",
    "p = ggplot(mpg_df, aes(\"cty\",\"hwy\", color='drv')) + \\\n",
    "    geom_point(tooltips=layer_tooltips().line('@manufacturer @model')) + \\\n",
    "    ggtitle(\"Fuel Economy: City and Highway Mileage by Drive Type\")\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "05857077-dd40-4917-815e-8a9246fcbe2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fontconfig error: Cannot load default config file: No such file: (null)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To restore the theme defaults without affecting other settings, apply flavor_standard(). \n",
    "# This can be useful, for example, when exporting the plot for printing.\n",
    "\n",
    "fullpath_png = ggsave(p+flavor_standard(), \"plot.png\", scale=1)\n",
    "\n",
    "from IPython.display import Image\n",
    "Image(filename=fullpath_png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.23"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}