Lanzamiento Parabólico - LIVE.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"0941d674-eeaf-4e0a-9daf-316ed702a7e5\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      var el = document.getElementById(\"0941d674-eeaf-4e0a-9daf-316ed702a7e5\");\n",
       "      el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"0941d674-eeaf-4e0a-9daf-316ed702a7e5\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '0941d674-eeaf-4e0a-9daf-316ed702a7e5' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"0941d674-eeaf-4e0a-9daf-316ed702a7e5\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.5.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.5.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"0941d674-eeaf-4e0a-9daf-316ed702a7e5\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.plotting import figure, show\n",
    "from bokeh.io import push_notebook, show, output_notebook\n",
    "from bokeh.models import Span, Arrow, VeeHead, OpenHead\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt1\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lanza_proyectil(altura=1, \n",
    "                    velocidad=20, \n",
    "                    grados=15, \n",
    "                    gravedad=9.8,\n",
    "                    with_plot=True,\n",
    "                    predict=False,\n",
    "                   ):\n",
    "    \n",
    "    # deg2rad - Convert angles from degrees to radians.\n",
    "    vel_x = velocidad * np.cos(np.deg2rad(grados))\n",
    "    vel_theta = velocidad * np.sin(np.deg2rad(grados))\n",
    "    \n",
    "    # Creamos la trayectoria\n",
    "    trayectoria = []\n",
    "    segundos = 0.05\n",
    "    t = 0\n",
    "    y = altura\n",
    "    while y >= 0:\n",
    "        x = vel_x * t\n",
    "        y =  (vel_theta * t - segundos * gravedad * t**2) + altura\n",
    "        trayectoria.append({\"x\": x, \"y\": y})\n",
    "        t = t + segundos\n",
    "    \n",
    "    # Creamos Dataframe y extraemos punto de impacto\n",
    "    trayectoria = pd.DataFrame(trayectoria)\n",
    "    impacto = round(float(trayectoria[\"x\"][-1:]), 2)\n",
    "    \n",
    "    if with_plot==True:\n",
    "        print(\"Velocidad: %s - Grados: %s - Gravedad: %s\" % (velocidad, grados, gravedad))\n",
    "        plot_trayectoria(trayectoria, predict)\n",
    "    \n",
    "    \n",
    "    return trayectoria, impacto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 20 - Grados: 15 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"124cd102-688b-425f-8bd7-2569d1fff69d\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"124cd102-688b-425f-8bd7-2569d1fff69d\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"124cd102-688b-425f-8bd7-2569d1fff69d\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '124cd102-688b-425f-8bd7-2569d1fff69d' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"34990739-20cf-458d-add0-2babf2b25929\":{\"roots\":{\"references\":[{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"c7b9e77f-5d48-428e-b0e0-3c8d789ce973\",\"type\":\"GlyphRenderer\"}]},\"id\":\"b9c0a025-8055-4bde-9bd7-9531aa1fdfc4\",\"type\":\"LegendItem\"},{\"attributes\":{\"items\":[{\"id\":\"b9c0a025-8055-4bde-9bd7-9531aa1fdfc4\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"98b51f8b-2627-4ab3-b10f-873996d7906b\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"45e101e5-2ecb-43cd-bfaf-8c1e948cdaea\",\"type\":\"ToolEvents\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"aa64e0c6-414b-40d5-9b87-74377325b5b3\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"d3911406-180e-47b8-a23f-b26a59177963\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"c68183dd-48fc-4b29-bb8f-e8997f43d9fc\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"1b15b153-b319-4eda-a80b-7c9d452f7f53\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":208.64},\"x_start\":{\"value\":208.64},\"y_end\":{\"value\":0},\"y_start\":{\"value\":7.335359390433599}},\"id\":\"ba7d1ded-86ce-4599-8542-fd86cdd6beb7\",\"type\":\"Arrow\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":14.670718780867197,\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6602f99a-ffa4-4973-ba63-f71566b6d8fd\",\"type\":\"Span\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"87dfc4de-6cbb-4397-9971-634a47d8f28d\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"fd59f364-af9f-44ed-96fb-99198b5307ea\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"c77c8bbd-a5ea-4b74-ade0-610f37634c50\",\"type\":\"BasicTicker\"}},\"id\":\"cae2e1e0-5976-4242-bb32-546693f7b9d7\",\"type\":\"LinearAxis\"},{\"attributes\":{\"below\":[{\"id\":\"cae2e1e0-5976-4242-bb32-546693f7b9d7\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"3741b826-cc68-4767-8ceb-ed3956ecadc9\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"cae2e1e0-5976-4242-bb32-546693f7b9d7\",\"type\":\"LinearAxis\"},{\"id\":\"cea8281f-8e62-46dc-8883-d80702bfdd20\",\"type\":\"Grid\"},{\"id\":\"3741b826-cc68-4767-8ceb-ed3956ecadc9\",\"type\":\"LinearAxis\"},{\"id\":\"a9737d83-1d09-4695-8f78-f707b96d1d24\",\"type\":\"Grid\"},{\"id\":\"a598814b-bf46-40a0-bddc-39e12ffad600\",\"type\":\"BoxAnnotation\"},{\"id\":\"98b51f8b-2627-4ab3-b10f-873996d7906b\",\"type\":\"Legend\"},{\"id\":\"c7b9e77f-5d48-428e-b0e0-3c8d789ce973\",\"type\":\"GlyphRenderer\"},{\"id\":\"ba7d1ded-86ce-4599-8542-fd86cdd6beb7\",\"type\":\"Arrow\"},{\"id\":\"6602f99a-ffa4-4973-ba63-f71566b6d8fd\",\"type\":\"Span\"}],\"title\":{\"id\":\"279e1876-6f01-4217-8bbf-04cc8a89f42a\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"45e101e5-2ecb-43cd-bfaf-8c1e948cdaea\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"b37e5136-fa5f-419d-bd57-6a8be0cf3980\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"d09eae1b-e7fe-4b75-90cc-c01ea41e8706\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"f330e94e-1844-4245-a8c4-9bca7128118c\",\"type\":\"DataRange1d\"}},\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"callback\":null},\"id\":\"d09eae1b-e7fe-4b75-90cc-c01ea41e8706\",\"type\":\"DataRange1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"b227de98-4c60-452b-920d-81fcdf5527a6\",\"type\":\"PanTool\"},{\"id\":\"0da9f8d8-493b-4c34-92c6-4be7df3143ac\",\"type\":\"WheelZoomTool\"},{\"id\":\"7c8349f0-29ec-455d-87fb-7c1fa6600626\",\"type\":\"BoxZoomTool\"},{\"id\":\"d8198975-6be4-499d-abb3-3f63179571f5\",\"type\":\"SaveTool\"},{\"id\":\"aa64e0c6-414b-40d5-9b87-74377325b5b3\",\"type\":\"ResetTool\"},{\"id\":\"d3911406-180e-47b8-a23f-b26a59177963\",\"type\":\"HelpTool\"}]},\"id\":\"b37e5136-fa5f-419d-bd57-6a8be0cf3980\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"955809b4-2aaf-42d3-984d-9b4e403e6cd3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"87dfc4de-6cbb-4397-9971-634a47d8f28d\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"b2fa1b85-0887-49ff-b364-8fe1032888aa\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"c7b9e77f-5d48-428e-b0e0-3c8d789ce973\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 208.64 \"},\"id\":\"279e1876-6f01-4217-8bbf-04cc8a89f42a\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null},\"id\":\"f330e94e-1844-4245-a8c4-9bca7128118c\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"f94e4898-4394-43e5-8b6b-4f676646b1a7\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"c77c8bbd-a5ea-4b74-ade0-610f37634c50\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"c68183dd-48fc-4b29-bb8f-e8997f43d9fc\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f94e4898-4394-43e5-8b6b-4f676646b1a7\",\"type\":\"BasicTicker\"}},\"id\":\"3741b826-cc68-4767-8ceb-ed3956ecadc9\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"c77c8bbd-a5ea-4b74-ade0-610f37634c50\",\"type\":\"BasicTicker\"}},\"id\":\"cea8281f-8e62-46dc-8883-d80702bfdd20\",\"type\":\"Grid\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f94e4898-4394-43e5-8b6b-4f676646b1a7\",\"type\":\"BasicTicker\"}},\"id\":\"a9737d83-1d09-4695-8f78-f707b96d1d24\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b227de98-4c60-452b-920d-81fcdf5527a6\",\"type\":\"PanTool\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"b2fa1b85-0887-49ff-b364-8fe1032888aa\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[217]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[217]}}},\"id\":\"955809b4-2aaf-42d3-984d-9b4e403e6cd3\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"a598814b-bf46-40a0-bddc-39e12ffad600\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"fd59f364-af9f-44ed-96fb-99198b5307ea\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0da9f8d8-493b-4c34-92c6-4be7df3143ac\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"1b15b153-b319-4eda-a80b-7c9d452f7f53\",\"type\":\"OpenHead\"},{\"attributes\":{\"overlay\":{\"id\":\"a598814b-bf46-40a0-bddc-39e12ffad600\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7c8349f0-29ec-455d-87fb-7c1fa6600626\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"ef365040-24bd-4224-9158-34505751a0ae\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"d8198975-6be4-499d-abb3-3f63179571f5\",\"type\":\"SaveTool\"}],\"root_ids\":[\"ef365040-24bd-4224-9158-34505751a0ae\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"34990739-20cf-458d-add0-2babf2b25929\",\"elementid\":\"124cd102-688b-425f-8bd7-2569d1fff69d\",\"modelid\":\"ef365040-24bd-4224-9158-34505751a0ae\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"124cd102-688b-425f-8bd7-2569d1fff69d\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(              x         y\n",
       " 0      0.000000  1.000000\n",
       " 1      0.965926  1.257594\n",
       " 2      1.931852  1.512738\n",
       " 3      2.897777  1.765432\n",
       " 4      3.863703  2.015676\n",
       " 5      4.829629  2.263470\n",
       " 6      5.795555  2.508814\n",
       " 7      6.761481  2.751708\n",
       " 8      7.727407  2.992152\n",
       " 9      8.693332  3.230146\n",
       " 10     9.659258  3.465690\n",
       " 11    10.625184  3.698784\n",
       " 12    11.591110  3.929429\n",
       " 13    12.557036  4.157623\n",
       " 14    13.522962  4.383367\n",
       " 15    14.488887  4.606661\n",
       " 16    15.454813  4.827505\n",
       " 17    16.420739  5.045899\n",
       " 18    17.386665  5.261843\n",
       " 19    18.352591  5.475337\n",
       " 20    19.318517  5.686381\n",
       " 21    20.284442  5.894975\n",
       " 22    21.250368  6.101119\n",
       " 23    22.216294  6.304813\n",
       " 24    23.182220  6.506057\n",
       " 25    24.148146  6.704851\n",
       " 26    25.114071  6.901195\n",
       " 27    26.079997  7.095089\n",
       " 28    27.045923  7.286533\n",
       " 29    28.011849  7.475527\n",
       " ..          ...       ...\n",
       " 187  180.628130  6.562136\n",
       " 188  181.594055  6.361580\n",
       " 189  182.559981  6.158575\n",
       " 190  183.525907  5.953119\n",
       " 191  184.491833  5.745213\n",
       " 192  185.457759  5.534857\n",
       " 193  186.423684  5.322051\n",
       " 194  187.389610  5.106795\n",
       " 195  188.355536  4.889089\n",
       " 196  189.321462  4.668933\n",
       " 197  190.287388  4.446327\n",
       " 198  191.253314  4.221271\n",
       " 199  192.219239  3.993765\n",
       " 200  193.185165  3.763809\n",
       " 201  194.151091  3.531403\n",
       " 202  195.117017  3.296547\n",
       " 203  196.082943  3.059241\n",
       " 204  197.048869  2.819485\n",
       " 205  198.014794  2.577279\n",
       " 206  198.980720  2.332623\n",
       " 207  199.946646  2.085517\n",
       " 208  200.912572  1.835961\n",
       " 209  201.878498  1.583955\n",
       " 210  202.844424  1.329499\n",
       " 211  203.810349  1.072594\n",
       " 212  204.776275  0.813238\n",
       " 213  205.742201  0.551432\n",
       " 214  206.708127  0.287176\n",
       " 215  207.674053  0.020470\n",
       " 216  208.639978 -0.248686\n",
       " \n",
       " [217 rows x 2 columns], 208.64)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lanza_proyectil()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_trayectoria(trayectoria, predict=False):\n",
    "    \n",
    "    impacto = round(float(trayectoria[\"x\"][-1:]), 2)\n",
    "    altura_maxima = trayectoria[\"y\"].max()\n",
    "    \n",
    "    p = figure(\n",
    "        title=\"Impacto: %s \" % impacto,\n",
    "        x_axis_label=\"Distancia - Metros\",\n",
    "        y_axis_label=\"Altura - Metros\",\n",
    "        width = 750, height=200)\n",
    "\n",
    "    # Pintar la trayectoria\n",
    "    p.line(trayectoria[\"x\"], trayectoria[\"y\"],\n",
    "          legend=\"Trayectoria\",\n",
    "           line_width=1,\n",
    "           line_color=\"darkred\"\n",
    "          )\n",
    "    \n",
    "    # Pintamos el pundo de impacto\n",
    "    p.add_layout(Arrow(end=OpenHead(size=10),\n",
    "                      line_color=\"green\",\n",
    "                       line_dash=\"dashed\",\n",
    "                       line_width=2,\n",
    "                       x_start=impacto, y_start=altura_maxima/2,\n",
    "                       x_end=impacto, y_end=0\n",
    "                      ))\n",
    "    \n",
    "    # Pintamos la línea de altura máxima\n",
    "    altitude_line = Span(location=altura_maxima,\n",
    "                        line_color=\"orange\",\n",
    "                         line_dash=\"dotted\",\n",
    "                         line_width=1.5)\n",
    "    p.add_layout(altitude_line)\n",
    "    \n",
    "    # Pintamos la marca de predicción\n",
    "    if predict:\n",
    "        p.add_layout(Arrow(end=VeeHead(size=5),\n",
    "                           line_color=\"blue\",\n",
    "                           line_dash=\"dotdash\",\n",
    "                           line_width=2,\n",
    "                           x_start=predict, y_start=altura_maxima/2,\n",
    "                           x_end=predict, y_end=0))\n",
    "    \n",
    "    show(p)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"9e165b15-4130-4686-894f-7455d8616c3f\":{\"roots\":{\"references\":[{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"26135dc4-4e31-46bb-817a-f437cf0d3dd9\",\"type\":\"BasicTicker\"}},\"id\":\"f58d695e-1761-4983-8d47-9f59c33ffa67\",\"type\":\"Grid\"},{\"attributes\":{\"below\":[{\"id\":\"1449c036-60e2-459a-9377-460a7242fb1a\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"d9c46e5b-604e-402a-8a18-8b8571bdf297\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"1449c036-60e2-459a-9377-460a7242fb1a\",\"type\":\"LinearAxis\"},{\"id\":\"6c025c97-119e-43cb-bc4c-9845776b71b8\",\"type\":\"Grid\"},{\"id\":\"d9c46e5b-604e-402a-8a18-8b8571bdf297\",\"type\":\"LinearAxis\"},{\"id\":\"f58d695e-1761-4983-8d47-9f59c33ffa67\",\"type\":\"Grid\"},{\"id\":\"51855fa8-9327-4623-94cb-842bf82dd8c8\",\"type\":\"BoxAnnotation\"},{\"id\":\"0b7e559b-81d4-40ee-8471-45d73ca5e1ef\",\"type\":\"Legend\"},{\"id\":\"2efe716c-eef9-49dd-b19c-463990cf149e\",\"type\":\"GlyphRenderer\"},{\"id\":\"e0212946-6ef2-41ad-a42a-142537b310da\",\"type\":\"Arrow\"},{\"id\":\"dcab9956-cc73-4272-90ba-b0d9bc63d116\",\"type\":\"Span\"}],\"title\":{\"id\":\"e42b94d6-ab92-482c-9b3c-64d73adddd0b\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"39caa4bf-b20a-4c72-a05f-87cae938ae70\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"f2c47484-cdf0-457a-99a9-535d54c65cb1\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"a6e23f0c-376f-440b-be4b-8d7e7b1300e1\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"b558d7e8-ec16-44ac-a7ee-810979446af8\",\"type\":\"DataRange1d\"}},\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"39caa4bf-b20a-4c72-a05f-87cae938ae70\",\"type\":\"ToolEvents\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 208.64 \"},\"id\":\"e42b94d6-ab92-482c-9b3c-64d73adddd0b\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"8132f086-bb8d-4277-8e64-39df181bdf66\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"2e1db1a1-d656-4d7a-90cd-eb085029ff81\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"ea3ee1c3-8709-4f50-b01f-08bb86f8b501\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"2efe716c-eef9-49dd-b19c-463990cf149e\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"f239e42d-c6f3-426e-b7b9-436977a9018c\",\"type\":\"PanTool\"},{\"id\":\"bab9a5f8-4984-4766-8ec5-0bc778d0f384\",\"type\":\"WheelZoomTool\"},{\"id\":\"e0c1c016-5bde-453c-8cf0-6bf6f650ef57\",\"type\":\"BoxZoomTool\"},{\"id\":\"e8f8322d-944f-499c-9551-e29a5780ac70\",\"type\":\"SaveTool\"},{\"id\":\"08beca01-4ce1-46ef-87a1-8d5ad514e261\",\"type\":\"ResetTool\"},{\"id\":\"ba4a7359-2ae4-452e-9ff0-fd8f69b2ceab\",\"type\":\"HelpTool\"}]},\"id\":\"f2c47484-cdf0-457a-99a9-535d54c65cb1\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"a6e23f0c-376f-440b-be4b-8d7e7b1300e1\",\"type\":\"DataRange1d\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2e1db1a1-d656-4d7a-90cd-eb085029ff81\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"b558d7e8-ec16-44ac-a7ee-810979446af8\",\"type\":\"DataRange1d\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"1da421c9-f51d-4cb0-bb67-6ed1b734cc18\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"096427ef-6de5-4877-82a4-9f31098e3594\",\"type\":\"BasicTicker\"}},\"id\":\"1449c036-60e2-459a-9377-460a7242fb1a\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"ea3ee1c3-8709-4f50-b01f-08bb86f8b501\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"26135dc4-4e31-46bb-817a-f437cf0d3dd9\",\"type\":\"BasicTicker\"},{\"attributes\":{\"items\":[{\"id\":\"72fa15e2-4dcb-44bb-acb4-f16a8835d1ed\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0b7e559b-81d4-40ee-8471-45d73ca5e1ef\",\"type\":\"Legend\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"2ae4dc1d-b8cd-4649-a2c1-c0c0dacf66d4\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"26135dc4-4e31-46bb-817a-f437cf0d3dd9\",\"type\":\"BasicTicker\"}},\"id\":\"d9c46e5b-604e-402a-8a18-8b8571bdf297\",\"type\":\"LinearAxis\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"2efe716c-eef9-49dd-b19c-463990cf149e\",\"type\":\"GlyphRenderer\"}]},\"id\":\"72fa15e2-4dcb-44bb-acb4-f16a8835d1ed\",\"type\":\"LegendItem\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e8f8322d-944f-499c-9551-e29a5780ac70\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"eef07914-d6a3-4732-84bf-2da170dd15f8\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"096427ef-6de5-4877-82a4-9f31098e3594\",\"type\":\"BasicTicker\"}},\"id\":\"6c025c97-119e-43cb-bc4c-9845776b71b8\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"096427ef-6de5-4877-82a4-9f31098e3594\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f239e42d-c6f3-426e-b7b9-436977a9018c\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"2ae4dc1d-b8cd-4649-a2c1-c0c0dacf66d4\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"eef07914-d6a3-4732-84bf-2da170dd15f8\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":208.64},\"x_start\":{\"value\":208.64},\"y_end\":{\"value\":0},\"y_start\":{\"value\":7.335359390433599}},\"id\":\"e0212946-6ef2-41ad-a42a-142537b310da\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"08beca01-4ce1-46ef-87a1-8d5ad514e261\",\"type\":\"ResetTool\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":14.670718780867197,\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"dcab9956-cc73-4272-90ba-b0d9bc63d116\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ba4a7359-2ae4-452e-9ff0-fd8f69b2ceab\",\"type\":\"HelpTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"51855fa8-9327-4623-94cb-842bf82dd8c8\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"overlay\":{\"id\":\"51855fa8-9327-4623-94cb-842bf82dd8c8\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e0c1c016-5bde-453c-8cf0-6bf6f650ef57\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"bab9a5f8-4984-4766-8ec5-0bc778d0f384\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1da421c9-f51d-4cb0-bb67-6ed1b734cc18\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[217]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[217]}}},\"id\":\"8132f086-bb8d-4277-8e64-39df181bdf66\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"0004c2dd-1ca2-4217-b99e-13e7202d8183\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"9e165b15-4130-4686-894f-7455d8616c3f\",\"elementid\":\"9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746\",\"modelid\":\"0004c2dd-1ca2-4217-b99e-13e7202d8183\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"9d18e1a2-5dbf-4cfc-bdc1-a577aa83a746\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trayectoria, impacto = lanza_proyectil()\n",
    "plot_trayectoria(trayectoria)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 10 - Grados: 0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"3f338121-46c7-401e-8719-fb219436512c\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"3f338121-46c7-401e-8719-fb219436512c\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"3f338121-46c7-401e-8719-fb219436512c\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3f338121-46c7-401e-8719-fb219436512c' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"0e3648a6-ca57-42ec-abea-5b669574df2c\":{\"roots\":{\"references\":[{\"attributes\":{\"overlay\":{\"id\":\"c428acd1-4657-4b5d-88c7-7ff74ce41709\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"d4a52ccc-4923-431e-aecd-1188d932fa6d\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b14f7809-e04a-4334-a84d-7608e3f006ab\",\"type\":\"BasicTicker\"}},\"id\":\"e5890984-eff6-4741-b93c-369b7d984c77\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null},\"id\":\"d88c99ba-2433-481b-8a72-290d0de851d2\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f56859b7-9d23-4704-a801-d9a2f8bc6660\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"a8da1bf8-8571-42bc-a5c6-86b499c8fd73\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"b14f7809-e04a-4334-a84d-7608e3f006ab\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":1.5,\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fac232a2-0b3c-42e7-92d3-fca23e22ee55\",\"type\":\"Span\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7ad57c20-635c-4176-956a-e7871d7b34dc\",\"type\":\"BasicTicker\"}},\"id\":\"7ba1e7dd-17ac-434e-badd-d0c438317967\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"59e8c098-c58a-44d5-9956-c4c8d44433cb\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"20c9e7a8-0ee6-478b-a782-ecbfc8b79ede\",\"type\":\"GlyphRenderer\"}]},\"id\":\"2a04b511-b260-4210-9873-a9170f34dc90\",\"type\":\"LegendItem\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"c428acd1-4657-4b5d-88c7-7ff74ce41709\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"a8da1bf8-8571-42bc-a5c6-86b499c8fd73\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7ad57c20-635c-4176-956a-e7871d7b34dc\",\"type\":\"BasicTicker\"}},\"id\":\"bbc38b5e-4a15-4088-ad47-07b97c025763\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1f39981a-5fe4-41a1-b1bf-396bb8953c8c\",\"type\":\"ToolEvents\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"f56859b7-9d23-4704-a801-d9a2f8bc6660\",\"type\":\"PanTool\"},{\"id\":\"8cc7a765-0a61-46a1-a83d-bca7a93f9ed8\",\"type\":\"WheelZoomTool\"},{\"id\":\"d4a52ccc-4923-431e-aecd-1188d932fa6d\",\"type\":\"BoxZoomTool\"},{\"id\":\"50f0e1bd-ae4a-46ab-be30-5be33fdb4628\",\"type\":\"SaveTool\"},{\"id\":\"35b6e281-74e7-44ab-9b1e-08475ab03cf8\",\"type\":\"ResetTool\"},{\"id\":\"844764fa-777b-4b73-8d91-fac75a6796fd\",\"type\":\"HelpTool\"}]},\"id\":\"88816981-ae3f-454f-abb1-c010cbe15e32\",\"type\":\"Toolbar\"},{\"attributes\":{\"items\":[{\"id\":\"2a04b511-b260-4210-9873-a9170f34dc90\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6bde4ea7-a65e-4f47-bce0-784d527d2e25\",\"type\":\"Legend\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAADgPwAAAAAAAPA/AQAAAAAA+D8AAAAAAAAAQAAAAAAAAARAAAAAAAAACEAAAAAAAAAMQP///////w9AAAAAAAAAEkD///////8TQP///////xVAAAAAAAAAGEAAAAAAAAAaQAEAAAAAABxAAQAAAAAAHkABAAAAAAAgQAEAAAAAACFAAQAAAAAAIkACAAAAAAAjQAEAAAAAACRAAgAAAAAAJUACAAAAAAAmQAIAAAAAACdAAgAAAAAAKEACAAAAAAApQAMAAAAAACpAAwAAAAAAK0ADAAAAAAAsQAQAAAAAAC1ABAAAAAAALkAEAAAAAAAvQAIAAAAAADBAAgAAAACAMEACAAAAAAAxQAIAAAAAgDFA\",\"dtype\":\"float64\",\"shape\":[36]},\"y\":{\"__ndarray__\":\"AAAAAAAA+D+X/5B++/r3P13+Q/rt6/c/UPwYc9fS9z9y+Q/pt6/3P8P1KFyPgvc/QfFjzF1L9z/u68A5Iwr3P8nlP6TfvvY/097gC5Np9j8K16NwPQr2P3DOiNLeoPU/BMWPMXct9T/HuriNBrD0P7ivA+eMKPQ/16NwPQqX8z8kl/+QfvvyP5+JsOHpVfI/SXuDL0ym8T8hbHh6pezwPyhcj8L1KPA/uZaQD3q27j9/c0aU9gbtP6BOQBNhQ+s/Hyh+jLlr6T/6/////3/nPzLWxW00gOU/x6rP1VZs4z+4fR04Z0ThPwieXinLEN4/YD0K16Nw2T9s2T15WKjUP2Dk8h/Sb88/WA96Nqs+xT+gZyJseHq1PwBQrkfhekS/\",\"dtype\":\"float64\",\"shape\":[36]}}},\"id\":\"52abc10c-e605-4658-8765-88247d68bc20\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null},\"id\":\"10daf0dd-4e18-4e28-848c-7ba5f5cfaffa\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"94a2a0ba-70db-400b-9def-93f55a1660ae\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"844764fa-777b-4b73-8d91-fac75a6796fd\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 17.5 \"},\"id\":\"d723a33b-45e0-4d1d-8e48-a71f5f9c924f\",\"type\":\"Title\"},{\"attributes\":{\"below\":[{\"id\":\"cd40239c-2def-4e43-b18d-6c541616471b\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"bbc38b5e-4a15-4088-ad47-07b97c025763\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"cd40239c-2def-4e43-b18d-6c541616471b\",\"type\":\"LinearAxis\"},{\"id\":\"e5890984-eff6-4741-b93c-369b7d984c77\",\"type\":\"Grid\"},{\"id\":\"bbc38b5e-4a15-4088-ad47-07b97c025763\",\"type\":\"LinearAxis\"},{\"id\":\"7ba1e7dd-17ac-434e-badd-d0c438317967\",\"type\":\"Grid\"},{\"id\":\"c428acd1-4657-4b5d-88c7-7ff74ce41709\",\"type\":\"BoxAnnotation\"},{\"id\":\"6bde4ea7-a65e-4f47-bce0-784d527d2e25\",\"type\":\"Legend\"},{\"id\":\"20c9e7a8-0ee6-478b-a782-ecbfc8b79ede\",\"type\":\"GlyphRenderer\"},{\"id\":\"0e74632b-4480-407b-af4f-3b301ff40632\",\"type\":\"Arrow\"},{\"id\":\"fac232a2-0b3c-42e7-92d3-fca23e22ee55\",\"type\":\"Span\"}],\"title\":{\"id\":\"d723a33b-45e0-4d1d-8e48-a71f5f9c924f\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"1f39981a-5fe4-41a1-b1bf-396bb8953c8c\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"88816981-ae3f-454f-abb1-c010cbe15e32\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"10daf0dd-4e18-4e28-848c-7ba5f5cfaffa\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"d88c99ba-2433-481b-8a72-290d0de851d2\",\"type\":\"DataRange1d\"}},\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"50f0e1bd-ae4a-46ab-be30-5be33fdb4628\",\"type\":\"SaveTool\"},{\"attributes\":{\"end\":{\"id\":\"94a2a0ba-70db-400b-9def-93f55a1660ae\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":17.5},\"x_start\":{\"value\":17.5},\"y_end\":{\"value\":0},\"y_start\":{\"value\":0.75}},\"id\":\"0e74632b-4480-407b-af4f-3b301ff40632\",\"type\":\"Arrow\"},{\"attributes\":{},\"id\":\"7ad57c20-635c-4176-956a-e7871d7b34dc\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"59e8c098-c58a-44d5-9956-c4c8d44433cb\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b14f7809-e04a-4334-a84d-7608e3f006ab\",\"type\":\"BasicTicker\"}},\"id\":\"cd40239c-2def-4e43-b18d-6c541616471b\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8cc7a765-0a61-46a1-a83d-bca7a93f9ed8\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6ad4e7b7-94a4-42bd-9167-b9db0f5bf70d\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"35b6e281-74e7-44ab-9b1e-08475ab03cf8\",\"type\":\"ResetTool\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"29c0e76e-0d88-4dd5-87dc-1f88cf9b0aca\",\"type\":\"Line\"},{\"attributes\":{\"data_source\":{\"id\":\"52abc10c-e605-4658-8765-88247d68bc20\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"6ad4e7b7-94a4-42bd-9167-b9db0f5bf70d\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"29c0e76e-0d88-4dd5-87dc-1f88cf9b0aca\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"20c9e7a8-0ee6-478b-a782-ecbfc8b79ede\",\"type\":\"GlyphRenderer\"}],\"root_ids\":[\"b4a053c4-5068-497c-85e0-7d7a1420e2da\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"0e3648a6-ca57-42ec-abea-5b669574df2c\",\"elementid\":\"3f338121-46c7-401e-8719-fb219436512c\",\"modelid\":\"b4a053c4-5068-497c-85e0-7d7a1420e2da\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"3f338121-46c7-401e-8719-fb219436512c\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 10 - Grados: 10 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"1c3037e7-2b0b-4cba-95c3-167e6d81f5f0\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"1c3037e7-2b0b-4cba-95c3-167e6d81f5f0\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"1c3037e7-2b0b-4cba-95c3-167e6d81f5f0\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '1c3037e7-2b0b-4cba-95c3-167e6d81f5f0' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"234ec526-9cb4-4175-ab71-9fbac255a8cd\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"718f89e2-b4a0-4151-84ec-722ec0fdac9d\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"bc3684f9-740c-4206-8cce-ec22afea8221\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"7a5ba992-40d3-4f59-b65b-9520acf45f69\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"3865699e-3201-4bf8-925d-1a00da23c5b2\",\"type\":\"GlyphRenderer\"}]},\"id\":\"7cec0e3d-2e0d-4b76-b069-43d61b44fb10\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"4ab36a43-f685-49e9-9c42-ea1001920078\",\"type\":\"ToolEvents\"},{\"attributes\":{\"items\":[{\"id\":\"7cec0e3d-2e0d-4b76-b069-43d61b44fb10\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"52d6eb02-7f8e-4dc3-9387-d9fbf5016b37\",\"type\":\"Legend\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"fe96ecd4-840b-44c5-916c-041652cdbe20\",\"type\":\"PanTool\"},{\"id\":\"e0c6b74f-663c-480b-8c4f-00c84f0b71d2\",\"type\":\"WheelZoomTool\"},{\"id\":\"e504444c-d204-410a-8ce2-448e1714eb90\",\"type\":\"BoxZoomTool\"},{\"id\":\"bc3684f9-740c-4206-8cce-ec22afea8221\",\"type\":\"SaveTool\"},{\"id\":\"718f89e2-b4a0-4151-84ec-722ec0fdac9d\",\"type\":\"ResetTool\"},{\"id\":\"7af74b88-15d9-49cb-b4c2-b8aafd123392\",\"type\":\"HelpTool\"}]},\"id\":\"39127d36-cd38-4d0e-95f5-7924db4d0999\",\"type\":\"Toolbar\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 42.35 \"},\"id\":\"a8d73ac1-90c0-487c-8fe6-d4ebef4a3776\",\"type\":\"Title\"},{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7af74b88-15d9-49cb-b4c2-b8aafd123392\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"cdbf5961-6822-4c94-9d1e-569cfe2205d7\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"0047f520-d152-41cd-9b2f-4eed7edd3068\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"56b0b6cb-0cda-4958-8ed6-69cad8751f9a\",\"type\":\"DataRange1d\"},{\"attributes\":{\"end\":{\"id\":\"1c3c5898-d303-40a1-a742-a867f8c69e25\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":42.35},\"x_start\":{\"value\":42.35},\"y_end\":{\"value\":0},\"y_start\":{\"value\":1.5191090545856403}},\"id\":\"2a60fcd0-4172-47fa-917c-2275adaf11ff\",\"type\":\"Arrow\"},{\"attributes\":{},\"id\":\"794c78bb-594b-4e08-bfd3-4c5e3d1f9e64\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"008073b5-1119-4450-86cb-8036d3ea36f5\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"1c3c5898-d303-40a1-a742-a867f8c69e25\",\"type\":\"OpenHead\"},{\"attributes\":{\"below\":[{\"id\":\"f0f4ebda-5026-4226-9042-664f5643fec9\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"4b0b1b95-aa2f-4609-9cf8-d47707796529\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"f0f4ebda-5026-4226-9042-664f5643fec9\",\"type\":\"LinearAxis\"},{\"id\":\"e312a743-b50d-4cc6-81c4-7819c28a9b92\",\"type\":\"Grid\"},{\"id\":\"4b0b1b95-aa2f-4609-9cf8-d47707796529\",\"type\":\"LinearAxis\"},{\"id\":\"05040197-808d-47ec-a77a-217953c4a388\",\"type\":\"Grid\"},{\"id\":\"dc24a831-1665-462a-845b-b597cfdceb40\",\"type\":\"BoxAnnotation\"},{\"id\":\"52d6eb02-7f8e-4dc3-9387-d9fbf5016b37\",\"type\":\"Legend\"},{\"id\":\"3865699e-3201-4bf8-925d-1a00da23c5b2\",\"type\":\"GlyphRenderer\"},{\"id\":\"2a60fcd0-4172-47fa-917c-2275adaf11ff\",\"type\":\"Arrow\"},{\"id\":\"de2fd1ed-925b-46fc-a54f-8fe40e63ac1e\",\"type\":\"Span\"}],\"title\":{\"id\":\"a8d73ac1-90c0-487c-8fe6-d4ebef4a3776\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"4ab36a43-f685-49e9-9c42-ea1001920078\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"39127d36-cd38-4d0e-95f5-7924db4d0999\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"56b0b6cb-0cda-4958-8ed6-69cad8751f9a\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"008073b5-1119-4450-86cb-8036d3ea36f5\",\"type\":\"DataRange1d\"}},\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"data_source\":{\"id\":\"8c78d55c-c547-4e1b-8dff-284fad9bb050\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"7c7749ed-ab87-4ee4-b1f6-cd01749718bd\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"12b6c8ab-4088-4024-a89d-3a9c663571be\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"3865699e-3201-4bf8-925d-1a00da23c5b2\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"cdbf5961-6822-4c94-9d1e-569cfe2205d7\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"794c78bb-594b-4e08-bfd3-4c5e3d1f9e64\",\"type\":\"BasicTicker\"}},\"id\":\"f0f4ebda-5026-4226-9042-664f5643fec9\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":3.0382181091712805,\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"de2fd1ed-925b-46fc-a54f-8fe40e63ac1e\",\"type\":\"Span\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"dc24a831-1665-462a-845b-b597cfdceb40\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"7c7749ed-ab87-4ee4-b1f6-cd01749718bd\",\"type\":\"Line\"},{\"attributes\":{\"overlay\":{\"id\":\"dc24a831-1665-462a-845b-b597cfdceb40\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e504444c-d204-410a-8ce2-448e1714eb90\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"7a5ba992-40d3-4f59-b65b-9520acf45f69\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0047f520-d152-41cd-9b2f-4eed7edd3068\",\"type\":\"BasicTicker\"}},\"id\":\"4b0b1b95-aa2f-4609-9cf8-d47707796529\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"794c78bb-594b-4e08-bfd3-4c5e3d1f9e64\",\"type\":\"BasicTicker\"}},\"id\":\"e312a743-b50d-4cc6-81c4-7819c28a9b92\",\"type\":\"Grid\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0047f520-d152-41cd-9b2f-4eed7edd3068\",\"type\":\"BasicTicker\"}},\"id\":\"05040197-808d-47ec-a77a-217953c4a388\",\"type\":\"Grid\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"12b6c8ab-4088-4024-a89d-3a9c663571be\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[87]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[87]}}},\"id\":\"8c78d55c-c547-4e1b-8dff-284fad9bb050\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fe96ecd4-840b-44c5-916c-041652cdbe20\",\"type\":\"PanTool\"},{\"attributes\":{\"plot\":{\"id\":\"6c8bfb87-9998-4732-8c06-5477cad59146\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e0c6b74f-663c-480b-8c4f-00c84f0b71d2\",\"type\":\"WheelZoomTool\"}],\"root_ids\":[\"6c8bfb87-9998-4732-8c06-5477cad59146\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"234ec526-9cb4-4175-ab71-9fbac255a8cd\",\"elementid\":\"1c3037e7-2b0b-4cba-95c3-167e6d81f5f0\",\"modelid\":\"6c8bfb87-9998-4732-8c06-5477cad59146\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"1c3037e7-2b0b-4cba-95c3-167e6d81f5f0\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 10 - Grados: 15 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"dc32b738-09f4-44ec-a075-e094e512b529\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"dc32b738-09f4-44ec-a075-e094e512b529\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"dc32b738-09f4-44ec-a075-e094e512b529\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'dc32b738-09f4-44ec-a075-e094e512b529' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"4343490a-f367-4421-ac68-19c149c99b8c\":{\"roots\":{\"references\":[{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"04647e64-fd00-4a0a-9081-faca8ca1410b\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"edc1f6a4-f83d-4de9-9f10-7a6473a32182\",\"type\":\"GlyphRenderer\"}]},\"id\":\"f76b3cfe-7a76-43a5-82dd-d04226303650\",\"type\":\"LegendItem\"},{\"attributes\":{\"end\":{\"id\":\"a33d0c6e-34a6-4296-a70a-4b0744a0c7b5\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":56.51},\"x_start\":{\"value\":56.51},\"y_end\":{\"value\":0},\"y_start\":{\"value\":2.4588398476083997}},\"id\":\"485a622c-8b0d-4b96-8837-b5a833699dbd\",\"type\":\"Arrow\"},{\"attributes\":{\"callback\":null},\"id\":\"bcd88607-7b1f-467a-b9ec-8a9c7633ec1a\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"c8f14160-747d-4088-a9aa-065e491b3691\",\"type\":\"ToolEvents\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":4.917679695216799,\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"58a71c5a-8edb-462f-82fe-a30157ec0628\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"81e2bcf0-a777-4557-9042-e7aedf9f6365\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"data_source\":{\"id\":\"4f7f32d9-47aa-4573-ab04-a693c3dbdd74\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"71e4d700-78e1-4b1c-abfa-a1a40739d12a\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"27275d66-2fd2-4d0a-b573-f0a295878711\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"edc1f6a4-f83d-4de9-9f10-7a6473a32182\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"0892b4d1-a1d1-496e-8ffc-4d319df0d7eb\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2ba6f364-8960-4dab-8b8b-b57dde907434\",\"type\":\"PanTool\"},{\"attributes\":{\"callback\":null},\"id\":\"79fa0f95-48e1-4278-a91b-247162cc3dda\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"88d9ab8e-10cd-49ef-b01d-959b8c26eee3\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6f69681d-0562-4242-b465-570c9caef0cb\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[118]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[118]}}},\"id\":\"4f7f32d9-47aa-4573-ab04-a693c3dbdd74\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"85abaeda-a338-4d7d-9402-4362e7463892\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0892b4d1-a1d1-496e-8ffc-4d319df0d7eb\",\"type\":\"BasicTicker\"}},\"id\":\"83c9bce9-be02-4a01-b804-d89acfd39716\",\"type\":\"LinearAxis\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0892b4d1-a1d1-496e-8ffc-4d319df0d7eb\",\"type\":\"BasicTicker\"}},\"id\":\"2d7610d3-15eb-4f20-8123-5146e1583b23\",\"type\":\"Grid\"},{\"attributes\":{\"overlay\":{\"id\":\"04647e64-fd00-4a0a-9081-faca8ca1410b\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"4a386c62-bec8-4e67-aa8a-478715fdb01d\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"70da4d1f-e963-4767-987d-64f05630e2ae\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"9989b9a7-d885-43ff-92cf-97041fb47109\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"85abaeda-a338-4d7d-9402-4362e7463892\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"a33d0c6e-34a6-4296-a70a-4b0744a0c7b5\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9989b9a7-d885-43ff-92cf-97041fb47109\",\"type\":\"BasicTicker\"}},\"id\":\"404969e1-ea6a-443d-893a-672f21ecd9e0\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 56.51 \"},\"id\":\"19d3f99e-8be3-40e3-bcb0-de6c06f5b506\",\"type\":\"Title\"},{\"attributes\":{\"items\":[{\"id\":\"f76b3cfe-7a76-43a5-82dd-d04226303650\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"da19343f-3d54-4823-b14f-31929ec4d284\",\"type\":\"Legend\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"71e4d700-78e1-4b1c-abfa-a1a40739d12a\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"70da4d1f-e963-4767-987d-64f05630e2ae\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9989b9a7-d885-43ff-92cf-97041fb47109\",\"type\":\"BasicTicker\"}},\"id\":\"dcf12628-1dd8-43e0-9174-784fbe4458ed\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"27275d66-2fd2-4d0a-b573-f0a295878711\",\"type\":\"Line\"},{\"attributes\":{\"below\":[{\"id\":\"dcf12628-1dd8-43e0-9174-784fbe4458ed\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"83c9bce9-be02-4a01-b804-d89acfd39716\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"dcf12628-1dd8-43e0-9174-784fbe4458ed\",\"type\":\"LinearAxis\"},{\"id\":\"404969e1-ea6a-443d-893a-672f21ecd9e0\",\"type\":\"Grid\"},{\"id\":\"83c9bce9-be02-4a01-b804-d89acfd39716\",\"type\":\"LinearAxis\"},{\"id\":\"2d7610d3-15eb-4f20-8123-5146e1583b23\",\"type\":\"Grid\"},{\"id\":\"04647e64-fd00-4a0a-9081-faca8ca1410b\",\"type\":\"BoxAnnotation\"},{\"id\":\"da19343f-3d54-4823-b14f-31929ec4d284\",\"type\":\"Legend\"},{\"id\":\"edc1f6a4-f83d-4de9-9f10-7a6473a32182\",\"type\":\"GlyphRenderer\"},{\"id\":\"485a622c-8b0d-4b96-8837-b5a833699dbd\",\"type\":\"Arrow\"},{\"id\":\"58a71c5a-8edb-462f-82fe-a30157ec0628\",\"type\":\"Span\"}],\"title\":{\"id\":\"19d3f99e-8be3-40e3-bcb0-de6c06f5b506\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"c8f14160-747d-4088-a9aa-065e491b3691\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"b7af22c1-5adc-4d5b-a950-13210fc14c08\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"79fa0f95-48e1-4278-a91b-247162cc3dda\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"bcd88607-7b1f-467a-b9ec-8a9c7633ec1a\",\"type\":\"DataRange1d\"}},\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"2ba6f364-8960-4dab-8b8b-b57dde907434\",\"type\":\"PanTool\"},{\"id\":\"81e2bcf0-a777-4557-9042-e7aedf9f6365\",\"type\":\"WheelZoomTool\"},{\"id\":\"4a386c62-bec8-4e67-aa8a-478715fdb01d\",\"type\":\"BoxZoomTool\"},{\"id\":\"6f69681d-0562-4242-b465-570c9caef0cb\",\"type\":\"SaveTool\"},{\"id\":\"29252419-c383-4471-b5df-c670d58e6d45\",\"type\":\"ResetTool\"},{\"id\":\"88d9ab8e-10cd-49ef-b01d-959b8c26eee3\",\"type\":\"HelpTool\"}]},\"id\":\"b7af22c1-5adc-4d5b-a950-13210fc14c08\",\"type\":\"Toolbar\"},{\"attributes\":{\"plot\":{\"id\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"29252419-c383-4471-b5df-c670d58e6d45\",\"type\":\"ResetTool\"}],\"root_ids\":[\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"4343490a-f367-4421-ac68-19c149c99b8c\",\"elementid\":\"dc32b738-09f4-44ec-a075-e094e512b529\",\"modelid\":\"9415ecbb-fdb0-4c17-a83e-a3fc7162860c\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"dc32b738-09f4-44ec-a075-e094e512b529\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 20 - Grados: 0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"8d741e61-829d-45b3-8356-d44153d6f216\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6f04b844-9fc4-4a9e-b79f-bb6a8bc47baf\",\"type\":\"BasicTicker\"}},\"id\":\"85054dc6-4459-4b68-8cda-3c822d24a977\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":1.5,\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"68c8b466-7694-4b66-b944-351e5ffbe064\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"9d7b2a0e-733c-41e6-aa76-18645d1c9764\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8bdf45f5-2da3-48c9-af1c-42aa7107af39\",\"type\":\"HelpTool\"},{\"attributes\":{\"overlay\":{\"id\":\"117e93aa-048b-494a-983b-361a2ce70d42\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"dc538e86-2b83-4a1e-8cd9-e7f203417ace\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c6fbbdb1-aa21-4376-afc4-4d112f6af39c\",\"type\":\"Line\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"4a46e44b-0b6e-4ec3-be3b-02dfce9f136b\",\"type\":\"OpenHead\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"a003b132-e197-43cd-a677-9b95e0b422e3\",\"type\":\"PanTool\"},{\"id\":\"392cd8a0-9b40-415e-b5b5-b6bdbb8e8ab6\",\"type\":\"WheelZoomTool\"},{\"id\":\"dc538e86-2b83-4a1e-8cd9-e7f203417ace\",\"type\":\"BoxZoomTool\"},{\"id\":\"9d7b2a0e-733c-41e6-aa76-18645d1c9764\",\"type\":\"SaveTool\"},{\"id\":\"4eebd29d-521c-4e54-8821-7f66e59ae7ac\",\"type\":\"ResetTool\"},{\"id\":\"8bdf45f5-2da3-48c9-af1c-42aa7107af39\",\"type\":\"HelpTool\"}]},\"id\":\"7f44f911-1cf0-420b-acfe-252074350885\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"baff639e-a5ee-4009-a0f9-4aacbf82ae33\",\"type\":\"DataRange1d\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"ab311d17-2b41-4dc0-86e3-0b834b301e63\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6f04b844-9fc4-4a9e-b79f-bb6a8bc47baf\",\"type\":\"BasicTicker\"}},\"id\":\"db7de100-a9d6-4dbc-9016-14756996a48d\",\"type\":\"LinearAxis\"},{\"attributes\":{\"data_source\":{\"id\":\"6c576573-23b0-4da1-af25-17d4508cf422\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c6fbbdb1-aa21-4376-afc4-4d112f6af39c\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"66087124-41cf-4fb9-8134-d83f6f286b60\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"382acb09-4a89-41ab-ac59-74f01c7e7e78\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"cfcbfb09-0d82-443f-83a7-2ea4d1bb1f8b\",\"type\":\"BasicTicker\"}},\"id\":\"101ab243-00b1-4874-a899-f09d00a7b31e\",\"type\":\"Grid\"},{\"attributes\":{\"items\":[{\"id\":\"79a4a6ba-6f17-449d-8db3-e573ad8d628e\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"99bd1710-b7c1-4a7c-8242-cf8d45cb18c2\",\"type\":\"Legend\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAADwPwAAAAAAAABAAQAAAAAACEAAAAAAAAAQQAAAAAAAABRAAAAAAAAAGEAAAAAAAAAcQP///////x9AAAAAAAAAIkD///////8jQP///////yVAAAAAAAAAKEAAAAAAAAAqQAEAAAAAACxAAQAAAAAALkABAAAAAAAwQAEAAAAAADFAAQAAAAAAMkACAAAAAAAzQAEAAAAAADRAAgAAAAAANUACAAAAAAA2QAIAAAAAADdAAgAAAAAAOEACAAAAAAA5QAMAAAAAADpAAwAAAAAAO0ADAAAAAAA8QAQAAAAAAD1ABAAAAAAAPkAEAAAAAAA/QAIAAAAAAEBAAgAAAACAQEACAAAAAABBQAIAAAAAgEFA\",\"dtype\":\"float64\",\"shape\":[36]},\"y\":{\"__ndarray__\":\"AAAAAAAA+D+X/5B++/r3P13+Q/rt6/c/UPwYc9fS9z9y+Q/pt6/3P8P1KFyPgvc/QfFjzF1L9z/u68A5Iwr3P8nlP6TfvvY/097gC5Np9j8K16NwPQr2P3DOiNLeoPU/BMWPMXct9T/HuriNBrD0P7ivA+eMKPQ/16NwPQqX8z8kl/+QfvvyP5+JsOHpVfI/SXuDL0ym8T8hbHh6pezwPyhcj8L1KPA/uZaQD3q27j9/c0aU9gbtP6BOQBNhQ+s/Hyh+jLlr6T/6/////3/nPzLWxW00gOU/x6rP1VZs4z+4fR04Z0ThPwieXinLEN4/YD0K16Nw2T9s2T15WKjUP2Dk8h/Sb88/WA96Nqs+xT+gZyJseHq1PwBQrkfhekS/\",\"dtype\":\"float64\",\"shape\":[36]}}},\"id\":\"6c576573-23b0-4da1-af25-17d4508cf422\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"382acb09-4a89-41ab-ac59-74f01c7e7e78\",\"type\":\"GlyphRenderer\"}]},\"id\":\"79a4a6ba-6f17-449d-8db3-e573ad8d628e\",\"type\":\"LegendItem\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"7235ea37-10af-4220-800e-81f937f0ab8c\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"cfcbfb09-0d82-443f-83a7-2ea4d1bb1f8b\",\"type\":\"BasicTicker\"}},\"id\":\"03703316-3fe1-4083-bb18-c5fd3d62644c\",\"type\":\"LinearAxis\"},{\"attributes\":{\"end\":{\"id\":\"4a46e44b-0b6e-4ec3-be3b-02dfce9f136b\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":35.0},\"x_start\":{\"value\":35.0},\"y_end\":{\"value\":0},\"y_start\":{\"value\":0.75}},\"id\":\"c22598d3-3732-45f6-bd19-59c96c8dafdf\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"392cd8a0-9b40-415e-b5b5-b6bdbb8e8ab6\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"ab311d17-2b41-4dc0-86e3-0b834b301e63\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 35.0 \"},\"id\":\"a990eb30-af7a-444b-8950-e5df8f167fe3\",\"type\":\"Title\"},{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"4eebd29d-521c-4e54-8821-7f66e59ae7ac\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"101eb507-b2b9-4f0f-9684-62af5133396b\",\"type\":\"ToolEvents\"},{\"attributes\":{},\"id\":\"6f04b844-9fc4-4a9e-b79f-bb6a8bc47baf\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"66087124-41cf-4fb9-8134-d83f6f286b60\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"8848fc55-7243-42ff-9968-67447be52c5f\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"cfcbfb09-0d82-443f-83a7-2ea4d1bb1f8b\",\"type\":\"BasicTicker\"},{\"attributes\":{\"below\":[{\"id\":\"db7de100-a9d6-4dbc-9016-14756996a48d\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"03703316-3fe1-4083-bb18-c5fd3d62644c\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"db7de100-a9d6-4dbc-9016-14756996a48d\",\"type\":\"LinearAxis\"},{\"id\":\"85054dc6-4459-4b68-8cda-3c822d24a977\",\"type\":\"Grid\"},{\"id\":\"03703316-3fe1-4083-bb18-c5fd3d62644c\",\"type\":\"LinearAxis\"},{\"id\":\"101ab243-00b1-4874-a899-f09d00a7b31e\",\"type\":\"Grid\"},{\"id\":\"117e93aa-048b-494a-983b-361a2ce70d42\",\"type\":\"BoxAnnotation\"},{\"id\":\"99bd1710-b7c1-4a7c-8242-cf8d45cb18c2\",\"type\":\"Legend\"},{\"id\":\"382acb09-4a89-41ab-ac59-74f01c7e7e78\",\"type\":\"GlyphRenderer\"},{\"id\":\"c22598d3-3732-45f6-bd19-59c96c8dafdf\",\"type\":\"Arrow\"},{\"id\":\"68c8b466-7694-4b66-b944-351e5ffbe064\",\"type\":\"Span\"}],\"title\":{\"id\":\"a990eb30-af7a-444b-8950-e5df8f167fe3\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"101eb507-b2b9-4f0f-9684-62af5133396b\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"7f44f911-1cf0-420b-acfe-252074350885\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"baff639e-a5ee-4009-a0f9-4aacbf82ae33\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"8848fc55-7243-42ff-9968-67447be52c5f\",\"type\":\"DataRange1d\"}},\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"7235ea37-10af-4220-800e-81f937f0ab8c\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"117e93aa-048b-494a-983b-361a2ce70d42\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"a003b132-e197-43cd-a677-9b95e0b422e3\",\"type\":\"PanTool\"}],\"root_ids\":[\"3c03dfeb-d781-422f-baef-fcb843fe11ac\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"8d741e61-829d-45b3-8356-d44153d6f216\",\"elementid\":\"b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513\",\"modelid\":\"3c03dfeb-d781-422f-baef-fcb843fe11ac\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"b9195f45-dd1a-4e79-8ba9-8e4fe8ed3513\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 20 - Grados: 10 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"02610bed-1238-4d98-9522-37a36aaee926\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"02610bed-1238-4d98-9522-37a36aaee926\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"02610bed-1238-4d98-9522-37a36aaee926\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '02610bed-1238-4d98-9522-37a36aaee926' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"8aba927e-8048-48e8-926b-d4090ebcb04c\":{\"roots\":{\"references\":[{\"attributes\":{\"end\":{\"id\":\"2bfe3879-003f-4bb0-a36f-1d9d1e2d8a66\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":147.72},\"x_start\":{\"value\":147.72},\"y_end\":{\"value\":0},\"y_start\":{\"value\":3.8268978071760267}},\"id\":\"fad9619b-b936-4da4-92e8-b710cbce61e9\",\"type\":\"Arrow\"},{\"attributes\":{},\"id\":\"d15770fd-2318-4176-bcac-96565149d262\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2057b19c-121b-4a4a-85ea-9aeee336626b\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"2bfe3879-003f-4bb0-a36f-1d9d1e2d8a66\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"c49252ee-f089-4e6f-8022-b90a67d7d3e5\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 147.72 \"},\"id\":\"bb0c8c1c-61a2-4fea-864d-6fcd49d19e26\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"540506b7-1ec9-4129-81eb-22c454b0f853\",\"type\":\"ToolEvents\"},{\"attributes\":{\"overlay\":{\"id\":\"7207239c-bc31-42b5-9dfd-f22951975169\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"df3e57bc-4bc3-48d4-8809-3ded9401c2a8\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"c5b715d2-35e2-472f-a95e-5c20a1f89589\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"60f1bfbe-82eb-42c0-8b8b-6ce2c498061b\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"721c1221-7cbf-4df9-b3d1-a33278ed895f\",\"type\":\"PanTool\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":7.653795614352053,\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"05d5879f-0386-4f25-a590-cace2c904df3\",\"type\":\"Span\"},{\"attributes\":{\"data_source\":{\"id\":\"b2324b4a-56c5-4c26-ab25-34fc2f7db54d\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"01416a4a-2f72-4f18-b160-8d1c0f39ca43\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"77c1dec3-001b-40b3-a5af-327247bb56a0\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"8ffc9f7e-b1e1-419f-9f86-9e3b6ca68402\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"d15770fd-2318-4176-bcac-96565149d262\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"30ace1d6-07de-41c7-a560-adfa753d4955\",\"type\":\"BasicTicker\"}},\"id\":\"59b06951-beec-4570-a917-a485c1744b40\",\"type\":\"LinearAxis\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"8ffc9f7e-b1e1-419f-9f86-9e3b6ca68402\",\"type\":\"GlyphRenderer\"}]},\"id\":\"e7e9af83-e701-4749-82ff-a20f8516a296\",\"type\":\"LegendItem\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[151]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[151]}}},\"id\":\"b2324b4a-56c5-4c26-ab25-34fc2f7db54d\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"below\":[{\"id\":\"59b06951-beec-4570-a917-a485c1744b40\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"209ad086-3cf5-4886-9a17-0e833759b365\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"59b06951-beec-4570-a917-a485c1744b40\",\"type\":\"LinearAxis\"},{\"id\":\"34c27411-4b5b-403c-994b-d624cea038d6\",\"type\":\"Grid\"},{\"id\":\"209ad086-3cf5-4886-9a17-0e833759b365\",\"type\":\"LinearAxis\"},{\"id\":\"40eb43ae-350a-41d8-931d-ff16fc97bcd6\",\"type\":\"Grid\"},{\"id\":\"7207239c-bc31-42b5-9dfd-f22951975169\",\"type\":\"BoxAnnotation\"},{\"id\":\"e4b62fe8-a861-4c85-b2bb-0b7a8e3bceaf\",\"type\":\"Legend\"},{\"id\":\"8ffc9f7e-b1e1-419f-9f86-9e3b6ca68402\",\"type\":\"GlyphRenderer\"},{\"id\":\"fad9619b-b936-4da4-92e8-b710cbce61e9\",\"type\":\"Arrow\"},{\"id\":\"05d5879f-0386-4f25-a590-cace2c904df3\",\"type\":\"Span\"}],\"title\":{\"id\":\"bb0c8c1c-61a2-4fea-864d-6fcd49d19e26\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"540506b7-1ec9-4129-81eb-22c454b0f853\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"b403f3fd-239d-4d2a-961c-df97fc0c9355\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"23654fb4-7146-4977-af02-443c67bda916\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"1677a087-abc9-4dc6-97f2-57f974bc69a2\",\"type\":\"DataRange1d\"}},\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"77c1dec3-001b-40b3-a5af-327247bb56a0\",\"type\":\"Line\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"721c1221-7cbf-4df9-b3d1-a33278ed895f\",\"type\":\"PanTool\"},{\"id\":\"62fc35a9-0124-408d-88a4-6185ce69dfbf\",\"type\":\"WheelZoomTool\"},{\"id\":\"df3e57bc-4bc3-48d4-8809-3ded9401c2a8\",\"type\":\"BoxZoomTool\"},{\"id\":\"c5b715d2-35e2-472f-a95e-5c20a1f89589\",\"type\":\"SaveTool\"},{\"id\":\"c49252ee-f089-4e6f-8022-b90a67d7d3e5\",\"type\":\"ResetTool\"},{\"id\":\"2057b19c-121b-4a4a-85ea-9aeee336626b\",\"type\":\"HelpTool\"}]},\"id\":\"b403f3fd-239d-4d2a-961c-df97fc0c9355\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"1677a087-abc9-4dc6-97f2-57f974bc69a2\",\"type\":\"DataRange1d\"},{\"attributes\":{\"callback\":null},\"id\":\"23654fb4-7146-4977-af02-443c67bda916\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"30ace1d6-07de-41c7-a560-adfa753d4955\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"352c46d3-d1bd-424e-9cdb-a5eab59c6e5c\",\"type\":\"BasicTicker\"}},\"id\":\"40eb43ae-350a-41d8-931d-ff16fc97bcd6\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"01416a4a-2f72-4f18-b160-8d1c0f39ca43\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"352c46d3-d1bd-424e-9cdb-a5eab59c6e5c\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"60f1bfbe-82eb-42c0-8b8b-6ce2c498061b\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"352c46d3-d1bd-424e-9cdb-a5eab59c6e5c\",\"type\":\"BasicTicker\"}},\"id\":\"209ad086-3cf5-4886-9a17-0e833759b365\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"62fc35a9-0124-408d-88a4-6185ce69dfbf\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"items\":[{\"id\":\"e7e9af83-e701-4749-82ff-a20f8516a296\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e4b62fe8-a861-4c85-b2bb-0b7a8e3bceaf\",\"type\":\"Legend\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"7207239c-bc31-42b5-9dfd-f22951975169\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"30ace1d6-07de-41c7-a560-adfa753d4955\",\"type\":\"BasicTicker\"}},\"id\":\"34c27411-4b5b-403c-994b-d624cea038d6\",\"type\":\"Grid\"}],\"root_ids\":[\"52f4ed25-2f15-4a16-a884-f4b486db1136\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"8aba927e-8048-48e8-926b-d4090ebcb04c\",\"elementid\":\"02610bed-1238-4d98-9522-37a36aaee926\",\"modelid\":\"52f4ed25-2f15-4a16-a884-f4b486db1136\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"02610bed-1238-4d98-9522-37a36aaee926\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 20 - Grados: 15 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"e4c310c0-6225-4f31-9e36-288660057d1f\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"e4c310c0-6225-4f31-9e36-288660057d1f\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"e4c310c0-6225-4f31-9e36-288660057d1f\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e4c310c0-6225-4f31-9e36-288660057d1f' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"88bc7c84-d985-46f4-b607-78456a633f63\":{\"roots\":{\"references\":[{\"attributes\":{},\"id\":\"e32cebb7-08b8-4197-a4ad-40453195ed08\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"56b22db2-a69d-42ec-8e32-4671d894f1ed\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"56b22db2-a69d-42ec-8e32-4671d894f1ed\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"e32cebb7-08b8-4197-a4ad-40453195ed08\",\"type\":\"BasicTicker\"}},\"id\":\"e88b4f49-1e34-4bcf-bd19-2889b940761b\",\"type\":\"LinearAxis\"},{\"attributes\":{\"below\":[{\"id\":\"106b9f20-0672-47d6-918b-05fd112e876e\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"e88b4f49-1e34-4bcf-bd19-2889b940761b\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"106b9f20-0672-47d6-918b-05fd112e876e\",\"type\":\"LinearAxis\"},{\"id\":\"ee762071-5f8c-444a-a1a0-f6d703090a05\",\"type\":\"Grid\"},{\"id\":\"e88b4f49-1e34-4bcf-bd19-2889b940761b\",\"type\":\"LinearAxis\"},{\"id\":\"37a33c88-ac58-425f-b982-81280f2901d1\",\"type\":\"Grid\"},{\"id\":\"19ae5254-d680-4d5e-b3f4-f49788030815\",\"type\":\"BoxAnnotation\"},{\"id\":\"80ef084d-1060-48a9-a22f-86f289e489e2\",\"type\":\"Legend\"},{\"id\":\"6f35fc62-fbbc-480a-9e8c-85ed04d459b2\",\"type\":\"GlyphRenderer\"},{\"id\":\"fc6eb325-38c2-4383-a3f5-3e3f010a5ff4\",\"type\":\"Arrow\"},{\"id\":\"9301c2be-7cb7-458e-b0e5-c033d991d5cd\",\"type\":\"Span\"}],\"title\":{\"id\":\"3dee5d05-5beb-455b-afcb-dfdb8108e98d\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"cc198dc2-3425-4c23-bdc0-816d91babe4f\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"643cb629-24b2-48e7-9e33-fe7abbe8f270\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"4c9c9b1a-d0d1-4383-acfe-cd71288d2018\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"6aeec7c9-62bf-4232-a82e-d1f483b28709\",\"type\":\"DataRange1d\"}},\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f1d953ae-924c-431e-859d-4b1c3f808eaf\",\"type\":\"BasicTicker\"}},\"id\":\"ee762071-5f8c-444a-a1a0-f6d703090a05\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null},\"id\":\"4c9c9b1a-d0d1-4383-acfe-cd71288d2018\",\"type\":\"DataRange1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1747acd2-9c9b-465a-862c-cf3fccd887fa\",\"type\":\"PanTool\"},{\"id\":\"b549673a-121e-43c3-bc2d-2bba5685f57b\",\"type\":\"WheelZoomTool\"},{\"id\":\"8213dd26-c405-43e6-bde5-2ea04a243125\",\"type\":\"BoxZoomTool\"},{\"id\":\"63779711-1c15-4408-99d5-89f598b49f29\",\"type\":\"SaveTool\"},{\"id\":\"c0af8bb9-fd7f-4983-9a68-398163304292\",\"type\":\"ResetTool\"},{\"id\":\"05e07c0e-459c-4ae5-9431-2e37f903b0a3\",\"type\":\"HelpTool\"}]},\"id\":\"643cb629-24b2-48e7-9e33-fe7abbe8f270\",\"type\":\"Toolbar\"},{\"attributes\":{\"end\":{\"id\":\"4eef0b9f-20a3-458c-bde1-5177abbcf174\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":209.61},\"x_start\":{\"value\":209.61},\"y_end\":{\"value\":0},\"y_start\":{\"value\":7.585359390433599}},\"id\":\"fc6eb325-38c2-4383-a3f5-3e3f010a5ff4\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 209.61 \"},\"id\":\"3dee5d05-5beb-455b-afcb-dfdb8108e98d\",\"type\":\"Title\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"ce09616c-cf7c-4745-b20a-92ecebd02d6a\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f1d953ae-924c-431e-859d-4b1c3f808eaf\",\"type\":\"BasicTicker\"}},\"id\":\"106b9f20-0672-47d6-918b-05fd112e876e\",\"type\":\"LinearAxis\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"6f35fc62-fbbc-480a-9e8c-85ed04d459b2\",\"type\":\"GlyphRenderer\"}]},\"id\":\"1b14d368-8947-467a-b6e8-23616f5c09a8\",\"type\":\"LegendItem\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"a4216f82-755a-4ff0-9b26-136d1ae171b3\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b549673a-121e-43c3-bc2d-2bba5685f57b\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"e32cebb7-08b8-4197-a4ad-40453195ed08\",\"type\":\"BasicTicker\"}},\"id\":\"37a33c88-ac58-425f-b982-81280f2901d1\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null},\"id\":\"6aeec7c9-62bf-4232-a82e-d1f483b28709\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"cc198dc2-3425-4c23-bdc0-816d91babe4f\",\"type\":\"ToolEvents\"},{\"attributes\":{},\"id\":\"f1d953ae-924c-431e-859d-4b1c3f808eaf\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":15.170718780867197,\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"9301c2be-7cb7-458e-b0e5-c033d991d5cd\",\"type\":\"Span\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[218]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[218]}}},\"id\":\"c5ed1538-af2d-426b-b47b-b6e268604aa0\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"fb8a4726-40cc-4f57-baae-ec5f9b2b0d17\",\"type\":\"Line\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"19ae5254-d680-4d5e-b3f4-f49788030815\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"1747acd2-9c9b-465a-862c-cf3fccd887fa\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"ce09616c-cf7c-4745-b20a-92ecebd02d6a\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data_source\":{\"id\":\"c5ed1538-af2d-426b-b47b-b6e268604aa0\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"fb8a4726-40cc-4f57-baae-ec5f9b2b0d17\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"a4216f82-755a-4ff0-9b26-136d1ae171b3\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"6f35fc62-fbbc-480a-9e8c-85ed04d459b2\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"4eef0b9f-20a3-458c-bde1-5177abbcf174\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"05e07c0e-459c-4ae5-9431-2e37f903b0a3\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"c0af8bb9-fd7f-4983-9a68-398163304292\",\"type\":\"ResetTool\"},{\"attributes\":{\"items\":[{\"id\":\"1b14d368-8947-467a-b6e8-23616f5c09a8\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"80ef084d-1060-48a9-a22f-86f289e489e2\",\"type\":\"Legend\"},{\"attributes\":{\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"63779711-1c15-4408-99d5-89f598b49f29\",\"type\":\"SaveTool\"},{\"attributes\":{\"overlay\":{\"id\":\"19ae5254-d680-4d5e-b3f4-f49788030815\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8213dd26-c405-43e6-bde5-2ea04a243125\",\"type\":\"BoxZoomTool\"}],\"root_ids\":[\"8a727eba-2e3c-4403-9da2-19ccdba137cf\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"88bc7c84-d985-46f4-b607-78456a633f63\",\"elementid\":\"e4c310c0-6225-4f31-9e36-288660057d1f\",\"modelid\":\"8a727eba-2e3c-4403-9da2-19ccdba137cf\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"e4c310c0-6225-4f31-9e36-288660057d1f\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 30 - Grados: 0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"dc37d600-0914-449d-9c97-4d15d6c496fb\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"dc37d600-0914-449d-9c97-4d15d6c496fb\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"dc37d600-0914-449d-9c97-4d15d6c496fb\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'dc37d600-0914-449d-9c97-4d15d6c496fb' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"04b86649-98da-4515-bb07-48c658f19cdd\":{\"roots\":{\"references\":[{\"attributes\":{\"callback\":null},\"id\":\"3cb22ca0-cce6-413d-a5a5-34db77cc99ed\",\"type\":\"DataRange1d\"},{\"attributes\":{\"end\":{\"id\":\"741c51c0-3a58-4127-bd8f-fc3029e3a6fe\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":52.5},\"x_start\":{\"value\":52.5},\"y_end\":{\"value\":0},\"y_start\":{\"value\":0.75}},\"id\":\"997e9ab8-4847-4e8d-92b0-562d8afdbf79\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 52.5 \"},\"id\":\"c7c09ab3-8404-4ee4-bc47-73d00c3b6947\",\"type\":\"Title\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":1.5,\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"257203dc-8be8-4857-a12a-93931f33e7c3\",\"type\":\"Span\"},{\"attributes\":{\"below\":[{\"id\":\"0f92eaa4-3858-4f45-b2a6-b78e5d407f42\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"8d07598e-a16e-47bf-ace1-9880b7a8b777\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"0f92eaa4-3858-4f45-b2a6-b78e5d407f42\",\"type\":\"LinearAxis\"},{\"id\":\"97e0816f-d367-4a53-8416-171124a2d069\",\"type\":\"Grid\"},{\"id\":\"8d07598e-a16e-47bf-ace1-9880b7a8b777\",\"type\":\"LinearAxis\"},{\"id\":\"e525658b-3b00-4ec1-86c4-a7fc8ad4bb39\",\"type\":\"Grid\"},{\"id\":\"0b8af557-cf52-483f-ab61-4d09f3abfc51\",\"type\":\"BoxAnnotation\"},{\"id\":\"7b1ec822-1967-44bf-9bfd-00e84be0d1c9\",\"type\":\"Legend\"},{\"id\":\"73a5d6e3-e331-405f-9a4f-a055918d0c66\",\"type\":\"GlyphRenderer\"},{\"id\":\"997e9ab8-4847-4e8d-92b0-562d8afdbf79\",\"type\":\"Arrow\"},{\"id\":\"257203dc-8be8-4857-a12a-93931f33e7c3\",\"type\":\"Span\"}],\"title\":{\"id\":\"c7c09ab3-8404-4ee4-bc47-73d00c3b6947\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"9c1dd2e0-51ce-4c42-bf6a-e0911479332c\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"810c3bcc-81be-49f0-90be-3b06d8b05779\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"3cb22ca0-cce6-413d-a5a5-34db77cc99ed\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"4cd21d5a-f545-4807-a1ea-cfb8138a7388\",\"type\":\"DataRange1d\"}},\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"9da3bba5-58f3-4369-8bd5-b828e8c5806e\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"9e8f4d3a-a2de-422c-bc01-efce076beff0\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"fa79897c-5aea-439b-8615-939d59b8d472\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"16b1d36e-02e8-4229-998b-dc3bcace26f2\",\"type\":\"PanTool\"},{\"id\":\"9da3bba5-58f3-4369-8bd5-b828e8c5806e\",\"type\":\"WheelZoomTool\"},{\"id\":\"f1aff516-bdd1-429c-81b3-5d351ed9402b\",\"type\":\"BoxZoomTool\"},{\"id\":\"6d592388-ff4b-4bed-be19-f18e294eccc2\",\"type\":\"SaveTool\"},{\"id\":\"7035c31c-7ce4-409a-88ee-540d0f122a47\",\"type\":\"ResetTool\"},{\"id\":\"76332ec4-42f2-44cf-8408-336b8145b211\",\"type\":\"HelpTool\"}]},\"id\":\"810c3bcc-81be-49f0-90be-3b06d8b05779\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"4cd21d5a-f545-4807-a1ea-cfb8138a7388\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"9c1dd2e0-51ce-4c42-bf6a-e0911479332c\",\"type\":\"ToolEvents\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"9e8f4d3a-a2de-422c-bc01-efce076beff0\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"fa79897c-5aea-439b-8615-939d59b8d472\",\"type\":\"BasicTicker\"}},\"id\":\"0f92eaa4-3858-4f45-b2a6-b78e5d407f42\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"5aca645c-5a05-4f27-9c02-44b4f6ea8c4e\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"AAAAAAAAAAAAAAAAAAD4PwAAAAAAAAhAAQAAAAAAEkAAAAAAAAAYQAAAAAAAAB5AAAAAAAAAIkAAAAAAAAAlQP///////ydA////////KkD///////8tQP//////fzBAAAAAAAAAMkAAAAAAAIAzQAEAAAAAADVAAQAAAACANkABAAAAAAA4QAIAAAAAgDlAAgAAAAAAO0ACAAAAAIA8QAIAAAAAAD5AAgAAAACAP0ABAAAAAIBAQAIAAAAAQEFAAgAAAAAAQkACAAAAAMBCQAIAAAAAgENAAgAAAABAREACAAAAAABFQAMAAAAAwEVAAwAAAACARkADAAAAAEBHQAMAAAAAAEhAAwAAAADASEAEAAAAAIBJQAQAAAAAQEpA\",\"dtype\":\"float64\",\"shape\":[36]},\"y\":{\"__ndarray__\":\"AAAAAAAA+D+X/5B++/r3P13+Q/rt6/c/UPwYc9fS9z9y+Q/pt6/3P8P1KFyPgvc/QfFjzF1L9z/u68A5Iwr3P8nlP6TfvvY/097gC5Np9j8K16NwPQr2P3DOiNLeoPU/BMWPMXct9T/HuriNBrD0P7ivA+eMKPQ/16NwPQqX8z8kl/+QfvvyP5+JsOHpVfI/SXuDL0ym8T8hbHh6pezwPyhcj8L1KPA/uZaQD3q27j9/c0aU9gbtP6BOQBNhQ+s/Hyh+jLlr6T/6/////3/nPzLWxW00gOU/x6rP1VZs4z+4fR04Z0ThPwieXinLEN4/YD0K16Nw2T9s2T15WKjUP2Dk8h/Sb88/WA96Nqs+xT+gZyJseHq1PwBQrkfhekS/\",\"dtype\":\"float64\",\"shape\":[36]}}},\"id\":\"fce084f7-351f-4f6b-af51-9619d70b1621\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"5eb5f3b8-247a-4c2a-9388-0ac1003f9a1f\",\"type\":\"Line\"},{\"attributes\":{\"data_source\":{\"id\":\"fce084f7-351f-4f6b-af51-9619d70b1621\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"5eb5f3b8-247a-4c2a-9388-0ac1003f9a1f\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"770b407c-c63e-4b7f-885b-fc0d80301c86\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"73a5d6e3-e331-405f-9a4f-a055918d0c66\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"770b407c-c63e-4b7f-885b-fc0d80301c86\",\"type\":\"Line\"},{\"attributes\":{\"items\":[{\"id\":\"27fea0c2-2ecf-42aa-ab9e-7709d435204b\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7b1ec822-1967-44bf-9bfd-00e84be0d1c9\",\"type\":\"Legend\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"b0499748-2417-40b5-ba74-62b34ba298f7\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"5aca645c-5a05-4f27-9c02-44b4f6ea8c4e\",\"type\":\"BasicTicker\"}},\"id\":\"8d07598e-a16e-47bf-ace1-9880b7a8b777\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"76332ec4-42f2-44cf-8408-336b8145b211\",\"type\":\"HelpTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"0b8af557-cf52-483f-ab61-4d09f3abfc51\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"overlay\":{\"id\":\"0b8af557-cf52-483f-ab61-4d09f3abfc51\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f1aff516-bdd1-429c-81b3-5d351ed9402b\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"741c51c0-3a58-4127-bd8f-fc3029e3a6fe\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7035c31c-7ce4-409a-88ee-540d0f122a47\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"16b1d36e-02e8-4229-998b-dc3bcace26f2\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"b0499748-2417-40b5-ba74-62b34ba298f7\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"73a5d6e3-e331-405f-9a4f-a055918d0c66\",\"type\":\"GlyphRenderer\"}]},\"id\":\"27fea0c2-2ecf-42aa-ab9e-7709d435204b\",\"type\":\"LegendItem\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"fa79897c-5aea-439b-8615-939d59b8d472\",\"type\":\"BasicTicker\"}},\"id\":\"97e0816f-d367-4a53-8416-171124a2d069\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6d592388-ff4b-4bed-be19-f18e294eccc2\",\"type\":\"SaveTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"5aca645c-5a05-4f27-9c02-44b4f6ea8c4e\",\"type\":\"BasicTicker\"}},\"id\":\"e525658b-3b00-4ec1-86c4-a7fc8ad4bb39\",\"type\":\"Grid\"}],\"root_ids\":[\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"04b86649-98da-4515-bb07-48c658f19cdd\",\"elementid\":\"dc37d600-0914-449d-9c97-4d15d6c496fb\",\"modelid\":\"dd59d217-3914-4ae1-b16b-d18b6c0f4a5a\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"dc37d600-0914-449d-9c97-4d15d6c496fb\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 30 - Grados: 10 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"8e649e2d-11d9-4c13-8e52-9394297b4946\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"8e649e2d-11d9-4c13-8e52-9394297b4946\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"8e649e2d-11d9-4c13-8e52-9394297b4946\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '8e649e2d-11d9-4c13-8e52-9394297b4946' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"f088bf24-4933-4f88-999c-3fa68edb282a\":{\"roots\":{\"references\":[{\"attributes\":{\"callback\":null},\"id\":\"ded00055-dcd6-4e88-8136-68f120bf9304\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 323.51 \"},\"id\":\"85298789-2344-46f1-ad80-836419073149\",\"type\":\"Title\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"fe4a8fc8-3d5e-4581-86b6-ca1940bdfecb\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"e6c6085f-55dc-4dc3-a8ba-d6b56ec0110b\",\"type\":\"BasicTicker\"}},\"id\":\"271bb2ef-9116-4749-9345-9603e9bb6e20\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":15.34596024904192,\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"df187385-2d72-435d-94c8-2ac90df052c7\",\"type\":\"Span\"},{\"attributes\":{},\"id\":\"e6c6085f-55dc-4dc3-a8ba-d6b56ec0110b\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"e044a186-b80e-4606-940c-1e9fe9cd1352\",\"type\":\"Line\"},{\"attributes\":{\"items\":[{\"id\":\"8ea70647-98c3-4ba3-b69e-bb2dce9a0115\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ecfd005f-2a47-47ca-a990-24b1edea7f67\",\"type\":\"Legend\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"15c460be-20f5-4fd1-ab68-05b15c337db5\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2b24bc72-a100-44f7-8169-609f5c43b3e6\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"a89bd62c-eadf-4c38-8ba9-ab5397af6aac\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"148d3379-9b9f-4a6c-ad08-54b966b92bbd\",\"type\":\"PanTool\"},{\"id\":\"bfd93d7a-6566-4b1a-9c89-fad8a46b9b5a\",\"type\":\"WheelZoomTool\"},{\"id\":\"103c0194-c706-469f-8c1d-ec356f36d07d\",\"type\":\"BoxZoomTool\"},{\"id\":\"40bfdc94-3ae9-4a45-ac7f-a29b58561a83\",\"type\":\"SaveTool\"},{\"id\":\"5b2e5ed9-263e-4d4c-8e28-c0b6cb0d4b9a\",\"type\":\"ResetTool\"},{\"id\":\"2b24bc72-a100-44f7-8169-609f5c43b3e6\",\"type\":\"HelpTool\"}]},\"id\":\"4acaba24-c9f8-44eb-b148-01d510ccc41b\",\"type\":\"Toolbar\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"40bfdc94-3ae9-4a45-ac7f-a29b58561a83\",\"type\":\"SaveTool\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"a89bd62c-eadf-4c38-8ba9-ab5397af6aac\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3b71a4c5-ee2d-4078-9744-a0c6a4e39ba6\",\"type\":\"BasicTicker\"}},\"id\":\"29f75755-6e30-4e98-a664-f5b0de064583\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"3b71a4c5-ee2d-4078-9744-a0c6a4e39ba6\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"7997b9ac-38df-4245-9eb3-199f957890cc\",\"type\":\"OpenHead\"},{\"attributes\":{\"callback\":null},\"id\":\"d5943084-9fa6-4bc8-83a5-c0f86c78055d\",\"type\":\"DataRange1d\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[220]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[220]}}},\"id\":\"4805a0ce-9164-473c-81c2-ae5c693e872a\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3b71a4c5-ee2d-4078-9744-a0c6a4e39ba6\",\"type\":\"BasicTicker\"}},\"id\":\"ec40dc1c-423e-4b4e-a31d-f93628799fbb\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"148d3379-9b9f-4a6c-ad08-54b966b92bbd\",\"type\":\"PanTool\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"5b2e5ed9-263e-4d4c-8e28-c0b6cb0d4b9a\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"fe4a8fc8-3d5e-4581-86b6-ca1940bdfecb\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data_source\":{\"id\":\"4805a0ce-9164-473c-81c2-ae5c693e872a\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"15c460be-20f5-4fd1-ab68-05b15c337db5\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"e044a186-b80e-4606-940c-1e9fe9cd1352\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"a25eae8e-3925-4213-94c9-3bb59c15cf06\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"end\":{\"id\":\"7997b9ac-38df-4245-9eb3-199f957890cc\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":323.51},\"x_start\":{\"value\":323.51},\"y_end\":{\"value\":0},\"y_start\":{\"value\":7.67298012452096}},\"id\":\"c5194d52-821d-42ef-80d2-ecbadcd310db\",\"type\":\"Arrow\"},{\"attributes\":{},\"id\":\"da7313a2-dab1-4938-882b-617c193dab83\",\"type\":\"ToolEvents\"},{\"attributes\":{\"overlay\":{\"id\":\"20ab537f-9340-4e22-8846-ff349c6b5469\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"103c0194-c706-469f-8c1d-ec356f36d07d\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"below\":[{\"id\":\"29f75755-6e30-4e98-a664-f5b0de064583\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"271bb2ef-9116-4749-9345-9603e9bb6e20\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"29f75755-6e30-4e98-a664-f5b0de064583\",\"type\":\"LinearAxis\"},{\"id\":\"ec40dc1c-423e-4b4e-a31d-f93628799fbb\",\"type\":\"Grid\"},{\"id\":\"271bb2ef-9116-4749-9345-9603e9bb6e20\",\"type\":\"LinearAxis\"},{\"id\":\"87c3043c-e96e-44b2-8d67-47ffcc6726ef\",\"type\":\"Grid\"},{\"id\":\"20ab537f-9340-4e22-8846-ff349c6b5469\",\"type\":\"BoxAnnotation\"},{\"id\":\"ecfd005f-2a47-47ca-a990-24b1edea7f67\",\"type\":\"Legend\"},{\"id\":\"a25eae8e-3925-4213-94c9-3bb59c15cf06\",\"type\":\"GlyphRenderer\"},{\"id\":\"c5194d52-821d-42ef-80d2-ecbadcd310db\",\"type\":\"Arrow\"},{\"id\":\"df187385-2d72-435d-94c8-2ac90df052c7\",\"type\":\"Span\"}],\"title\":{\"id\":\"85298789-2344-46f1-ad80-836419073149\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"da7313a2-dab1-4938-882b-617c193dab83\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"4acaba24-c9f8-44eb-b148-01d510ccc41b\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"ded00055-dcd6-4e88-8136-68f120bf9304\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"d5943084-9fa6-4bc8-83a5-c0f86c78055d\",\"type\":\"DataRange1d\"}},\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"e6c6085f-55dc-4dc3-a8ba-d6b56ec0110b\",\"type\":\"BasicTicker\"}},\"id\":\"87c3043c-e96e-44b2-8d67-47ffcc6726ef\",\"type\":\"Grid\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"20ab537f-9340-4e22-8846-ff349c6b5469\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"a25eae8e-3925-4213-94c9-3bb59c15cf06\",\"type\":\"GlyphRenderer\"}]},\"id\":\"8ea70647-98c3-4ba3-b69e-bb2dce9a0115\",\"type\":\"LegendItem\"},{\"attributes\":{\"plot\":{\"id\":\"8427d440-d5ad-4c58-a963-235f63470d76\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"bfd93d7a-6566-4b1a-9c89-fad8a46b9b5a\",\"type\":\"WheelZoomTool\"}],\"root_ids\":[\"8427d440-d5ad-4c58-a963-235f63470d76\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"f088bf24-4933-4f88-999c-3fa68edb282a\",\"elementid\":\"8e649e2d-11d9-4c13-8e52-9394297b4946\",\"modelid\":\"8427d440-d5ad-4c58-a963-235f63470d76\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"8e649e2d-11d9-4c13-8e52-9394297b4946\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 30 - Grados: 15 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"7ed16d2d-1fd7-465f-9283-7f5a4a2e3704\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"7ed16d2d-1fd7-465f-9283-7f5a4a2e3704\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"7ed16d2d-1fd7-465f-9283-7f5a4a2e3704\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '7ed16d2d-1fd7-465f-9283-7f5a4a2e3704' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"3cdad555-27cf-4ce0-8ed9-7bd4eaf5d775\":{\"roots\":{\"references\":[{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"7e10ff02-7b80-43bd-becc-2faaaef16428\",\"type\":\"Line\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 465.09 \"},\"id\":\"abba59fd-af70-42f7-a391-c983243aebf2\",\"type\":\"Title\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"36d54fae-cb3a-4434-b968-136b33d0855b\",\"type\":\"BasicTicker\"}},\"id\":\"544f322d-b6f1-4c10-9b7c-b18669e3e8f4\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"36d54fae-cb3a-4434-b968-136b33d0855b\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"3ed98f59-345f-4d34-9f6c-2a69a933d6ad\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"36d54fae-cb3a-4434-b968-136b33d0855b\",\"type\":\"BasicTicker\"}},\"id\":\"82083229-c0d8-4488-9310-cc280a4385e2\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7fce5e66-8737-4ef4-8296-7b9d30f67993\",\"type\":\"BasicTicker\"}},\"id\":\"26607499-474d-4d45-9091-4894479e5e40\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"7fce5e66-8737-4ef4-8296-7b9d30f67993\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"2304e7eb-4577-4367-b5dc-66508347bb70\",\"type\":\"DataRange1d\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"5465d617-6bf1-4cf2-82b3-453222245bab\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7fce5e66-8737-4ef4-8296-7b9d30f67993\",\"type\":\"BasicTicker\"}},\"id\":\"5345c2d7-9582-4d27-9fed-159fe0ed59bd\",\"type\":\"LinearAxis\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"0c3c9c25-1219-479d-92a4-e347fe165156\",\"type\":\"PanTool\"},{\"id\":\"6d3600ed-9c0c-4577-8999-bf0ba4a10769\",\"type\":\"WheelZoomTool\"},{\"id\":\"13ef1e99-d8ca-4cca-b65b-2e3411a5357a\",\"type\":\"BoxZoomTool\"},{\"id\":\"b192a11b-59a3-4468-a7ce-54fd2589cd8d\",\"type\":\"SaveTool\"},{\"id\":\"b7e0bdf2-b67c-468d-af40-cdc7721fe440\",\"type\":\"ResetTool\"},{\"id\":\"3e36980f-9f13-43f5-b814-21a3dd8c8ead\",\"type\":\"HelpTool\"}]},\"id\":\"2dfccd55-e41d-4150-92ce-2f1bb89aa628\",\"type\":\"Toolbar\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"74f0aab2-cbfd-471f-9b42-9cbdaf2a97ef\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[322]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[322]}}},\"id\":\"91746ed7-9a8c-4c73-bcf3-e255b8725b56\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"5b1358d9-96fc-4a89-8baf-d1c549fbfe34\",\"type\":\"OpenHead\"},{\"attributes\":{\"data_source\":{\"id\":\"91746ed7-9a8c-4c73-bcf3-e255b8725b56\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"7e10ff02-7b80-43bd-becc-2faaaef16428\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"74f0aab2-cbfd-471f-9b42-9cbdaf2a97ef\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"66ef5ffb-6892-45b4-adfe-e5a26aeb6c3e\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"below\":[{\"id\":\"5345c2d7-9582-4d27-9fed-159fe0ed59bd\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"82083229-c0d8-4488-9310-cc280a4385e2\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"5345c2d7-9582-4d27-9fed-159fe0ed59bd\",\"type\":\"LinearAxis\"},{\"id\":\"26607499-474d-4d45-9091-4894479e5e40\",\"type\":\"Grid\"},{\"id\":\"82083229-c0d8-4488-9310-cc280a4385e2\",\"type\":\"LinearAxis\"},{\"id\":\"544f322d-b6f1-4c10-9b7c-b18669e3e8f4\",\"type\":\"Grid\"},{\"id\":\"6a591b4d-c878-41eb-9a89-51803172b60c\",\"type\":\"BoxAnnotation\"},{\"id\":\"0907f84a-21a5-4f40-9f0e-2a3dc9125dc3\",\"type\":\"Legend\"},{\"id\":\"66ef5ffb-6892-45b4-adfe-e5a26aeb6c3e\",\"type\":\"GlyphRenderer\"},{\"id\":\"5fa218ef-cc13-4821-b77c-706660426935\",\"type\":\"Arrow\"},{\"id\":\"fe0bde37-1119-473a-ba93-41637252bc5b\",\"type\":\"Span\"}],\"title\":{\"id\":\"abba59fd-af70-42f7-a391-c983243aebf2\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"cea473c6-6ff3-4df0-b36b-a29ad00ab269\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"2dfccd55-e41d-4150-92ce-2f1bb89aa628\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"648e4748-824f-4974-815b-a0bb472b1de8\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"2304e7eb-4577-4367-b5dc-66508347bb70\",\"type\":\"DataRange1d\"}},\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":32.25921368929741,\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fe0bde37-1119-473a-ba93-41637252bc5b\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0c3c9c25-1219-479d-92a4-e347fe165156\",\"type\":\"PanTool\"},{\"attributes\":{\"callback\":null},\"id\":\"648e4748-824f-4974-815b-a0bb472b1de8\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"cea473c6-6ff3-4df0-b36b-a29ad00ab269\",\"type\":\"ToolEvents\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"6a591b4d-c878-41eb-9a89-51803172b60c\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"5465d617-6bf1-4cf2-82b3-453222245bab\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b192a11b-59a3-4468-a7ce-54fd2589cd8d\",\"type\":\"SaveTool\"},{\"attributes\":{\"end\":{\"id\":\"5b1358d9-96fc-4a89-8baf-d1c549fbfe34\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":465.09},\"x_start\":{\"value\":465.09},\"y_end\":{\"value\":0},\"y_start\":{\"value\":16.129606844648706}},\"id\":\"5fa218ef-cc13-4821-b77c-706660426935\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6d3600ed-9c0c-4577-8999-bf0ba4a10769\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"6a591b4d-c878-41eb-9a89-51803172b60c\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"13ef1e99-d8ca-4cca-b65b-2e3411a5357a\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b7e0bdf2-b67c-468d-af40-cdc7721fe440\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"3e36980f-9f13-43f5-b814-21a3dd8c8ead\",\"type\":\"HelpTool\"},{\"attributes\":{\"items\":[{\"id\":\"9390a930-f6eb-4a18-8ee8-56e5bfcf8bac\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0907f84a-21a5-4f40-9f0e-2a3dc9125dc3\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"3ed98f59-345f-4d34-9f6c-2a69a933d6ad\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"66ef5ffb-6892-45b4-adfe-e5a26aeb6c3e\",\"type\":\"GlyphRenderer\"}]},\"id\":\"9390a930-f6eb-4a18-8ee8-56e5bfcf8bac\",\"type\":\"LegendItem\"}],\"root_ids\":[\"076a3299-9b30-470a-8332-1cb2a3f178ec\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"3cdad555-27cf-4ce0-8ed9-7bd4eaf5d775\",\"elementid\":\"7ed16d2d-1fd7-465f-9283-7f5a4a2e3704\",\"modelid\":\"076a3299-9b30-470a-8332-1cb2a3f178ec\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"7ed16d2d-1fd7-465f-9283-7f5a4a2e3704\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for vel in [10, 20, 30]:\n",
    "    for grds in [0, 10, 15]:\n",
    "        trayectoria, impacto = lanza_proyectil(altura=1.5, velocidad=vel, grados=grds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creamos un dataset de entreno"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>altura</th>\n",
       "      <th>grados</th>\n",
       "      <th>gravedad</th>\n",
       "      <th>impacto</th>\n",
       "      <th>velocidad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1.45</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2.05</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2.90</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   altura  grados  gravedad  impacto  velocidad\n",
       "0     1.0       1       9.8     1.45          1\n",
       "1     1.5       1       9.8     1.80          1\n",
       "2     2.0       1       9.8     2.05          1\n",
       "3     3.0       1       9.8     2.50          1\n",
       "4     4.0       1       9.8     2.90          1"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = []\n",
    "\n",
    "gravedad = 9.8\n",
    "altura=[1, 1.5, 2, 3, 4, 5]\n",
    "velocidad=range(1,50)\n",
    "grados=range(1,89)\n",
    "\n",
    "for vel in velocidad:\n",
    "    for grds in grados:\n",
    "        for alt in altura:\n",
    "            trayectoria, impacto = lanza_proyectil(\n",
    "                altura=alt,\n",
    "                velocidad=vel,\n",
    "                grados=grds,\n",
    "                gravedad=gravedad,\n",
    "                with_plot=False\n",
    "            )\n",
    "            data.append({\n",
    "                \"altura\": alt,\n",
    "                \"velocidad\": vel,\n",
    "                \"grados\": grds,\n",
    "                \"gravedad\": gravedad,\n",
    "                \"impacto\": impacto\n",
    "            })\n",
    "data = pd.DataFrame(data)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25872"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>altura</th>\n",
       "      <th>grados</th>\n",
       "      <th>gravedad</th>\n",
       "      <th>impacto</th>\n",
       "      <th>velocidad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>25872.000000</td>\n",
       "      <td>25872.000000</td>\n",
       "      <td>25872.0</td>\n",
       "      <td>25872.000000</td>\n",
       "      <td>25872.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.750000</td>\n",
       "      <td>44.500000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>553.635589</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.406856</td>\n",
       "      <td>25.402263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>586.828285</td>\n",
       "      <td>14.142409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.500000</td>\n",
       "      <td>22.750000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>85.995000</td>\n",
       "      <td>13.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>44.500000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>327.405000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>66.250000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>860.080000</td>\n",
       "      <td>37.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2456.560000</td>\n",
       "      <td>49.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             altura        grados  gravedad       impacto     velocidad\n",
       "count  25872.000000  25872.000000   25872.0  25872.000000  25872.000000\n",
       "mean       2.750000     44.500000       9.8    553.635589     25.000000\n",
       "std        1.406856     25.402263       0.0    586.828285     14.142409\n",
       "min        1.000000      1.000000       9.8      0.100000      1.000000\n",
       "25%        1.500000     22.750000       9.8     85.995000     13.000000\n",
       "50%        2.500000     44.500000       9.8    327.405000     25.000000\n",
       "75%        4.000000     66.250000       9.8    860.080000     37.000000\n",
       "max        5.000000     88.000000       9.8   2456.560000     49.000000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creamos un modelo y lo entrenoamos con nuestro set de datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    data[[\"altura\", \"velocidad\", \"grados\", \"gravedad\"]],\n",
    "    data[\"impacto\"],\n",
    "    test_size=20,\n",
    "    random_state=42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1988.68,  1398.21,   219.08, ...,     4.86,   284.4 ,  1273.13])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.get_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1, loss = 320236.55259037\n",
      "Iteration 2, loss = 316608.08002914\n",
      "Iteration 3, loss = 312014.00818322\n",
      "Iteration 4, loss = 306124.04914904\n",
      "Iteration 5, loss = 298432.50233086\n",
      "Iteration 6, loss = 288429.10761998\n",
      "Iteration 7, loss = 275773.58875100\n",
      "Iteration 8, loss = 260882.31034638\n",
      "Iteration 9, loss = 244362.54987717\n",
      "Iteration 10, loss = 226649.77513741\n",
      "Iteration 11, loss = 208468.54456190\n",
      "Iteration 12, loss = 190526.16502439\n",
      "Iteration 13, loss = 173662.03387878\n",
      "Iteration 14, loss = 158515.38478224\n",
      "Iteration 15, loss = 145326.94944201\n",
      "Iteration 16, loss = 133968.31218664\n",
      "Iteration 17, loss = 124061.94404266\n",
      "Iteration 18, loss = 115101.91013793\n",
      "Iteration 19, loss = 106847.41642386\n",
      "Iteration 20, loss = 99028.44889985\n",
      "Iteration 21, loss = 91477.42653363\n",
      "Iteration 22, loss = 84307.63481652\n",
      "Iteration 23, loss = 77795.88405130\n",
      "Iteration 24, loss = 71836.91835233\n",
      "Iteration 25, loss = 66488.97226471\n",
      "Iteration 26, loss = 61873.08335134\n",
      "Iteration 27, loss = 57844.43396485\n",
      "Iteration 28, loss = 54385.52214501\n",
      "Iteration 29, loss = 51660.99901142\n",
      "Iteration 30, loss = 49454.08226456\n",
      "Iteration 31, loss = 47649.79805608\n",
      "Iteration 32, loss = 46132.90179356\n",
      "Iteration 33, loss = 44852.44320594\n",
      "Iteration 34, loss = 43737.26722427\n",
      "Iteration 35, loss = 42721.14531863\n",
      "Iteration 36, loss = 41789.35429842\n",
      "Iteration 37, loss = 40912.09424615\n",
      "Iteration 38, loss = 40046.29174535\n",
      "Iteration 39, loss = 39203.82773462\n",
      "Iteration 40, loss = 38388.10865338\n",
      "Iteration 41, loss = 37576.09762483\n",
      "Iteration 42, loss = 36762.80755370\n",
      "Iteration 43, loss = 35962.18182345\n",
      "Iteration 44, loss = 35159.84541039\n",
      "Iteration 45, loss = 34356.67105676\n",
      "Iteration 46, loss = 33554.16693118\n",
      "Iteration 47, loss = 32747.17522528\n",
      "Iteration 48, loss = 31932.43748350\n",
      "Iteration 49, loss = 31123.26976252\n",
      "Iteration 50, loss = 30301.37871015\n",
      "Iteration 51, loss = 29468.07501685\n",
      "Iteration 52, loss = 28621.54812270\n",
      "Iteration 53, loss = 27778.99112700\n",
      "Iteration 54, loss = 26951.31876527\n",
      "Iteration 55, loss = 26116.52748636\n",
      "Iteration 56, loss = 25278.04348129\n",
      "Iteration 57, loss = 24431.52560858\n",
      "Iteration 58, loss = 23598.92230921\n",
      "Iteration 59, loss = 22779.61855854\n",
      "Iteration 60, loss = 21969.73455089\n",
      "Iteration 61, loss = 21171.96730356\n",
      "Iteration 62, loss = 20403.59804488\n",
      "Iteration 63, loss = 19640.48484606\n",
      "Iteration 64, loss = 18901.26636790\n",
      "Iteration 65, loss = 18183.29662731\n",
      "Iteration 66, loss = 17489.99815295\n",
      "Iteration 67, loss = 16830.18385650\n",
      "Iteration 68, loss = 16192.98204204\n",
      "Iteration 69, loss = 15616.36234130\n",
      "Iteration 70, loss = 15028.69206447\n",
      "Iteration 71, loss = 14497.55082186\n",
      "Iteration 72, loss = 13991.25463043\n",
      "Iteration 73, loss = 13530.90302739\n",
      "Iteration 74, loss = 13090.21274376\n",
      "Iteration 75, loss = 12683.50097988\n",
      "Iteration 76, loss = 12300.65417263\n",
      "Iteration 77, loss = 11949.26832557\n",
      "Iteration 78, loss = 11624.07970553\n",
      "Iteration 79, loss = 11319.44704316\n",
      "Iteration 80, loss = 11037.37726035\n",
      "Iteration 81, loss = 10770.64383761\n",
      "Iteration 82, loss = 10517.72357714\n",
      "Iteration 83, loss = 10281.64032071\n",
      "Iteration 84, loss = 10071.15611346\n",
      "Iteration 85, loss = 9858.52989406\n",
      "Iteration 86, loss = 9650.01991363\n",
      "Iteration 87, loss = 9465.90414961\n",
      "Iteration 88, loss = 9284.17590826\n",
      "Iteration 89, loss = 9113.05256929\n",
      "Iteration 90, loss = 8948.82426657\n",
      "Iteration 91, loss = 8789.13407009\n",
      "Iteration 92, loss = 8633.92969147\n",
      "Iteration 93, loss = 8487.66167413\n",
      "Iteration 94, loss = 8341.96379183\n",
      "Iteration 95, loss = 8204.10270873\n",
      "Iteration 96, loss = 8067.90722010\n",
      "Iteration 97, loss = 7941.26271847\n",
      "Iteration 98, loss = 7811.27805407\n",
      "Iteration 99, loss = 7690.60458221\n",
      "Iteration 100, loss = 7571.39170491\n",
      "Iteration 101, loss = 7455.06204970\n",
      "Iteration 102, loss = 7343.58749125\n",
      "Iteration 103, loss = 7232.52855278\n",
      "Iteration 104, loss = 7128.60746592\n",
      "Iteration 105, loss = 7023.85042967\n",
      "Iteration 106, loss = 6924.15041528\n",
      "Iteration 107, loss = 6823.65733061\n",
      "Iteration 108, loss = 6726.33728647\n",
      "Iteration 109, loss = 6628.36447381\n",
      "Iteration 110, loss = 6536.81289675\n",
      "Iteration 111, loss = 6447.51717207\n",
      "Iteration 112, loss = 6352.74581907\n",
      "Iteration 113, loss = 6266.54636259\n",
      "Iteration 114, loss = 6176.99885193\n",
      "Iteration 115, loss = 6098.11952829\n",
      "Iteration 116, loss = 6017.76946803\n",
      "Iteration 117, loss = 5937.64435251\n",
      "Iteration 118, loss = 5859.62672690\n",
      "Iteration 119, loss = 5784.52945966\n",
      "Iteration 120, loss = 5706.09766534\n",
      "Iteration 121, loss = 5633.13514176\n",
      "Iteration 122, loss = 5566.62924590\n",
      "Iteration 123, loss = 5496.06326349\n",
      "Iteration 124, loss = 5429.03831663\n",
      "Iteration 125, loss = 5362.91214552\n",
      "Iteration 126, loss = 5296.77859005\n",
      "Iteration 127, loss = 5236.55032335\n",
      "Iteration 128, loss = 5179.89075573\n",
      "Iteration 129, loss = 5117.37457356\n",
      "Iteration 130, loss = 5054.83199847\n",
      "Iteration 131, loss = 4996.36770676\n",
      "Iteration 132, loss = 4940.37438039\n",
      "Iteration 133, loss = 4886.41793521\n",
      "Iteration 134, loss = 4833.37098670\n",
      "Iteration 135, loss = 4783.61385638\n",
      "Iteration 136, loss = 4727.29978400\n",
      "Iteration 137, loss = 4673.75661932\n",
      "Iteration 138, loss = 4631.03757528\n",
      "Iteration 139, loss = 4578.33318052\n",
      "Iteration 140, loss = 4530.72745066\n",
      "Iteration 141, loss = 4485.41515704\n",
      "Iteration 142, loss = 4436.85901116\n",
      "Iteration 143, loss = 4391.01046584\n",
      "Iteration 144, loss = 4346.16328644\n",
      "Iteration 145, loss = 4299.52360668\n",
      "Iteration 146, loss = 4257.42263282\n",
      "Iteration 147, loss = 4213.57137040\n",
      "Iteration 148, loss = 4173.28359316\n",
      "Iteration 149, loss = 4131.29113036\n",
      "Iteration 150, loss = 4088.91705748\n",
      "Iteration 151, loss = 4046.55640292\n",
      "Iteration 152, loss = 4007.02374145\n",
      "Iteration 153, loss = 3964.59643778\n",
      "Iteration 154, loss = 3933.45664842\n",
      "Iteration 155, loss = 3891.32854185\n",
      "Iteration 156, loss = 3852.11393560\n",
      "Iteration 157, loss = 3813.70636221\n",
      "Iteration 158, loss = 3774.31387210\n",
      "Iteration 159, loss = 3742.46532104\n",
      "Iteration 160, loss = 3702.69113150\n",
      "Iteration 161, loss = 3674.52637695\n",
      "Iteration 162, loss = 3633.02994223\n",
      "Iteration 163, loss = 3597.42249651\n",
      "Iteration 164, loss = 3568.06404093\n",
      "Iteration 165, loss = 3530.83213179\n",
      "Iteration 166, loss = 3510.36252410\n",
      "Iteration 167, loss = 3462.98349508\n",
      "Iteration 168, loss = 3433.74498970\n",
      "Iteration 169, loss = 3395.43168028\n",
      "Iteration 170, loss = 3365.76137456\n",
      "Iteration 171, loss = 3334.10249977\n",
      "Iteration 172, loss = 3301.95259427\n",
      "Iteration 173, loss = 3267.11924244\n",
      "Iteration 174, loss = 3235.61292970\n",
      "Iteration 175, loss = 3201.66441494\n",
      "Iteration 176, loss = 3167.24360427\n",
      "Iteration 177, loss = 3137.32335982\n",
      "Iteration 178, loss = 3098.98151050\n",
      "Iteration 179, loss = 3074.41430364\n",
      "Iteration 180, loss = 3034.34953480\n",
      "Iteration 181, loss = 3002.28158736\n",
      "Iteration 182, loss = 2965.15748856\n",
      "Iteration 183, loss = 2935.41909067\n",
      "Iteration 184, loss = 2897.77693255\n",
      "Iteration 185, loss = 2873.02503897\n",
      "Iteration 186, loss = 2837.56682134\n",
      "Iteration 187, loss = 2805.06803484\n",
      "Iteration 188, loss = 2777.60216236\n",
      "Iteration 189, loss = 2747.83255544\n",
      "Iteration 190, loss = 2718.25628697\n",
      "Iteration 191, loss = 2683.65905091\n",
      "Iteration 192, loss = 2659.53805498\n",
      "Iteration 193, loss = 2625.12383443\n",
      "Iteration 194, loss = 2593.07403807\n",
      "Iteration 195, loss = 2565.28836650\n",
      "Iteration 196, loss = 2531.68740142\n",
      "Iteration 197, loss = 2500.28282775\n",
      "Iteration 198, loss = 2472.55482234\n",
      "Iteration 199, loss = 2440.51653964\n",
      "Iteration 200, loss = 2414.13741118\n",
      "Iteration 201, loss = 2382.19673310\n",
      "Iteration 202, loss = 2355.32807611\n",
      "Iteration 203, loss = 2327.41892943\n",
      "Iteration 204, loss = 2296.73047324\n",
      "Iteration 205, loss = 2268.19696349\n",
      "Iteration 206, loss = 2239.80236823\n",
      "Iteration 207, loss = 2209.56836763\n",
      "Iteration 208, loss = 2181.18488895\n",
      "Iteration 209, loss = 2152.35103485\n",
      "Iteration 210, loss = 2124.07454930\n",
      "Iteration 211, loss = 2100.01427370\n",
      "Iteration 212, loss = 2068.52841383\n",
      "Iteration 213, loss = 2041.29032048\n",
      "Iteration 214, loss = 2011.68823703\n",
      "Iteration 215, loss = 1988.45700042\n",
      "Iteration 216, loss = 1958.81145172\n",
      "Iteration 217, loss = 1933.97819656\n",
      "Iteration 218, loss = 1904.82312510\n",
      "Iteration 219, loss = 1878.48946805\n",
      "Iteration 220, loss = 1852.89948342\n",
      "Iteration 221, loss = 1827.13905332\n",
      "Iteration 222, loss = 1800.30330081\n",
      "Iteration 223, loss = 1772.79082891\n",
      "Iteration 224, loss = 1746.66944355\n",
      "Iteration 225, loss = 1721.31533378\n",
      "Iteration 226, loss = 1694.77744044\n",
      "Iteration 227, loss = 1669.03630049\n",
      "Iteration 228, loss = 1644.11828650\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 229, loss = 1618.49575868\n",
      "Iteration 230, loss = 1593.88521162\n",
      "Iteration 231, loss = 1569.60544575\n",
      "Iteration 232, loss = 1543.90490701\n",
      "Iteration 233, loss = 1523.28799403\n",
      "Iteration 234, loss = 1494.36855170\n",
      "Iteration 235, loss = 1477.75945278\n",
      "Iteration 236, loss = 1451.42581539\n",
      "Iteration 237, loss = 1422.95735820\n",
      "Iteration 238, loss = 1401.35686529\n",
      "Iteration 239, loss = 1380.24892324\n",
      "Iteration 240, loss = 1361.18911175\n",
      "Iteration 241, loss = 1338.44805316\n",
      "Iteration 242, loss = 1315.81216130\n",
      "Iteration 243, loss = 1290.85394454\n",
      "Iteration 244, loss = 1270.77333939\n",
      "Iteration 245, loss = 1248.37406203\n",
      "Iteration 246, loss = 1227.53690420\n",
      "Iteration 247, loss = 1207.88446114\n",
      "Iteration 248, loss = 1186.63046204\n",
      "Iteration 249, loss = 1166.57403596\n",
      "Iteration 250, loss = 1152.53934580\n",
      "Iteration 251, loss = 1127.30042193\n",
      "Iteration 252, loss = 1106.35648996\n",
      "Iteration 253, loss = 1086.77172000\n",
      "Iteration 254, loss = 1071.66762569\n",
      "Iteration 255, loss = 1054.10316475\n",
      "Iteration 256, loss = 1031.03947439\n",
      "Iteration 257, loss = 1015.27892558\n",
      "Iteration 258, loss = 998.97795211\n",
      "Iteration 259, loss = 978.99842500\n",
      "Iteration 260, loss = 961.57762379\n",
      "Iteration 261, loss = 946.88320852\n",
      "Iteration 262, loss = 928.65427998\n",
      "Iteration 263, loss = 914.12348595\n",
      "Iteration 264, loss = 896.86257605\n",
      "Iteration 265, loss = 881.63563122\n",
      "Iteration 266, loss = 862.05870740\n",
      "Iteration 267, loss = 849.92965616\n",
      "Iteration 268, loss = 833.65731497\n",
      "Iteration 269, loss = 817.45309836\n",
      "Iteration 270, loss = 804.59337839\n",
      "Iteration 271, loss = 789.74206023\n",
      "Iteration 272, loss = 774.60997765\n",
      "Iteration 273, loss = 762.81609751\n",
      "Iteration 274, loss = 747.15803632\n",
      "Iteration 275, loss = 733.29595502\n",
      "Iteration 276, loss = 723.88340781\n",
      "Iteration 277, loss = 705.63958855\n",
      "Iteration 278, loss = 693.50517183\n",
      "Iteration 279, loss = 684.41524981\n",
      "Iteration 280, loss = 669.46227549\n",
      "Iteration 281, loss = 659.52875816\n",
      "Iteration 282, loss = 647.35095530\n",
      "Iteration 283, loss = 633.68374490\n",
      "Iteration 284, loss = 622.72056773\n",
      "Iteration 285, loss = 610.63485426\n",
      "Iteration 286, loss = 599.89517405\n",
      "Iteration 287, loss = 590.48865279\n",
      "Iteration 288, loss = 579.07076350\n",
      "Iteration 289, loss = 566.98290080\n",
      "Iteration 290, loss = 556.69268404\n",
      "Iteration 291, loss = 547.65929146\n",
      "Iteration 292, loss = 535.88596531\n",
      "Iteration 293, loss = 526.46354819\n",
      "Iteration 294, loss = 516.01850935\n",
      "Iteration 295, loss = 506.08968093\n",
      "Iteration 296, loss = 498.56029702\n",
      "Iteration 297, loss = 488.86188261\n",
      "Iteration 298, loss = 478.52669324\n",
      "Iteration 299, loss = 469.88587455\n",
      "Iteration 300, loss = 463.01230883\n",
      "Iteration 301, loss = 454.48500763\n",
      "Iteration 302, loss = 446.67846310\n",
      "Iteration 303, loss = 441.04704123\n",
      "Iteration 304, loss = 429.44076099\n",
      "Iteration 305, loss = 420.74642300\n",
      "Iteration 306, loss = 415.43014114\n",
      "Iteration 307, loss = 407.83268405\n",
      "Iteration 308, loss = 400.85460011\n",
      "Iteration 309, loss = 392.58544983\n",
      "Iteration 310, loss = 386.20754200\n",
      "Iteration 311, loss = 379.43947369\n",
      "Iteration 312, loss = 373.35050830\n",
      "Iteration 313, loss = 364.98230061\n",
      "Iteration 314, loss = 360.04424799\n",
      "Iteration 315, loss = 351.34473416\n",
      "Iteration 316, loss = 346.11246057\n",
      "Iteration 317, loss = 341.30599069\n",
      "Iteration 318, loss = 336.20056708\n",
      "Iteration 319, loss = 327.06212389\n",
      "Iteration 320, loss = 321.58398152\n",
      "Iteration 321, loss = 319.44669407\n",
      "Iteration 322, loss = 311.82952061\n",
      "Iteration 323, loss = 306.51000425\n",
      "Iteration 324, loss = 299.11043606\n",
      "Iteration 325, loss = 294.35606660\n",
      "Iteration 326, loss = 288.73598580\n",
      "Iteration 327, loss = 282.95811406\n",
      "Iteration 328, loss = 279.39151645\n",
      "Iteration 329, loss = 275.02143303\n",
      "Iteration 330, loss = 268.92393353\n",
      "Iteration 331, loss = 263.86109647\n",
      "Iteration 332, loss = 259.97648511\n",
      "Iteration 333, loss = 253.68944978\n",
      "Iteration 334, loss = 250.20232857\n",
      "Iteration 335, loss = 246.35270591\n",
      "Iteration 336, loss = 242.04415077\n",
      "Iteration 337, loss = 237.45678890\n",
      "Iteration 338, loss = 232.89889497\n",
      "Iteration 339, loss = 228.44703627\n",
      "Iteration 340, loss = 223.68561261\n",
      "Iteration 341, loss = 221.27990419\n",
      "Iteration 342, loss = 217.39882480\n",
      "Iteration 343, loss = 212.15424328\n",
      "Iteration 344, loss = 209.21145056\n",
      "Iteration 345, loss = 205.10919575\n",
      "Iteration 346, loss = 202.44921489\n",
      "Iteration 347, loss = 197.91045036\n",
      "Iteration 348, loss = 195.77439153\n",
      "Iteration 349, loss = 192.36588744\n",
      "Iteration 350, loss = 189.70722034\n",
      "Iteration 351, loss = 184.79428115\n",
      "Iteration 352, loss = 181.41583255\n",
      "Iteration 353, loss = 179.75660145\n",
      "Iteration 354, loss = 176.93987983\n",
      "Iteration 355, loss = 172.58770291\n",
      "Iteration 356, loss = 169.59873799\n",
      "Iteration 357, loss = 167.17098522\n",
      "Iteration 358, loss = 164.66192044\n",
      "Iteration 359, loss = 161.19927895\n",
      "Iteration 360, loss = 158.79496448\n",
      "Iteration 361, loss = 156.12410345\n",
      "Iteration 362, loss = 152.86994869\n",
      "Iteration 363, loss = 150.56247743\n",
      "Iteration 364, loss = 149.07139947\n",
      "Iteration 365, loss = 145.31411745\n",
      "Iteration 366, loss = 143.76385035\n",
      "Iteration 367, loss = 141.23822553\n",
      "Iteration 368, loss = 139.25079857\n",
      "Iteration 369, loss = 135.56954935\n",
      "Iteration 370, loss = 133.58393561\n",
      "Iteration 371, loss = 131.61989449\n",
      "Iteration 372, loss = 129.19647211\n",
      "Iteration 373, loss = 127.59096489\n",
      "Iteration 374, loss = 126.12661121\n",
      "Iteration 375, loss = 123.06346383\n",
      "Iteration 376, loss = 121.25268632\n",
      "Iteration 377, loss = 119.69906573\n",
      "Iteration 378, loss = 117.22090656\n",
      "Iteration 379, loss = 115.84133969\n",
      "Iteration 380, loss = 113.27213953\n",
      "Iteration 381, loss = 112.34108331\n",
      "Iteration 382, loss = 112.63229363\n",
      "Iteration 383, loss = 109.22932659\n",
      "Iteration 384, loss = 107.26541439\n",
      "Iteration 385, loss = 104.63877453\n",
      "Iteration 386, loss = 104.51714864\n",
      "Iteration 387, loss = 103.21266116\n",
      "Iteration 388, loss = 101.20072426\n",
      "Iteration 389, loss = 98.98586535\n",
      "Iteration 390, loss = 99.49147847\n",
      "Iteration 391, loss = 96.82057453\n",
      "Iteration 392, loss = 95.51372337\n",
      "Iteration 393, loss = 93.83101389\n",
      "Iteration 394, loss = 93.15895905\n",
      "Iteration 395, loss = 91.64653346\n",
      "Iteration 396, loss = 90.61508921\n",
      "Iteration 397, loss = 88.39070643\n",
      "Iteration 398, loss = 87.76816663\n",
      "Iteration 399, loss = 86.23010652\n",
      "Iteration 400, loss = 84.93223475\n",
      "Iteration 401, loss = 84.54690008\n",
      "Iteration 402, loss = 82.81545453\n",
      "Iteration 403, loss = 81.80617968\n",
      "Iteration 404, loss = 80.88142541\n",
      "Iteration 405, loss = 79.95833250\n",
      "Iteration 406, loss = 78.35390810\n",
      "Iteration 407, loss = 77.40676631\n",
      "Iteration 408, loss = 76.11776098\n",
      "Iteration 409, loss = 75.50879934\n",
      "Iteration 410, loss = 74.93150392\n",
      "Iteration 411, loss = 73.30934551\n",
      "Iteration 412, loss = 73.20754864\n",
      "Iteration 413, loss = 73.20019202\n",
      "Iteration 414, loss = 71.10911164\n",
      "Iteration 415, loss = 70.91084423\n",
      "Iteration 416, loss = 69.55439009\n",
      "Iteration 417, loss = 67.83779788\n",
      "Iteration 418, loss = 67.22581803\n",
      "Iteration 419, loss = 66.38445709\n",
      "Iteration 420, loss = 65.26669726\n",
      "Iteration 421, loss = 65.05878404\n",
      "Iteration 422, loss = 65.21038565\n",
      "Iteration 423, loss = 63.09540092\n",
      "Iteration 424, loss = 63.62315309\n",
      "Iteration 425, loss = 61.99135947\n",
      "Iteration 426, loss = 61.16871796\n",
      "Iteration 427, loss = 60.49145661\n",
      "Iteration 428, loss = 60.33009133\n",
      "Iteration 429, loss = 59.90325868\n",
      "Iteration 430, loss = 58.55244241\n",
      "Iteration 431, loss = 58.47814648\n",
      "Iteration 432, loss = 57.22649045\n",
      "Iteration 433, loss = 57.17654154\n",
      "Iteration 434, loss = 57.06347144\n",
      "Iteration 435, loss = 55.29502565\n",
      "Iteration 436, loss = 54.85624555\n",
      "Iteration 437, loss = 53.99140536\n",
      "Iteration 438, loss = 53.38949880\n",
      "Iteration 439, loss = 52.94008512\n",
      "Iteration 440, loss = 52.56724028\n",
      "Iteration 441, loss = 52.13477322\n",
      "Iteration 442, loss = 51.93249023\n",
      "Iteration 443, loss = 50.45589670\n",
      "Iteration 444, loss = 50.51475651\n",
      "Iteration 445, loss = 50.16101207\n",
      "Iteration 446, loss = 49.26044300\n",
      "Iteration 447, loss = 48.86536727\n",
      "Iteration 448, loss = 48.53459299\n",
      "Iteration 449, loss = 47.56048589\n",
      "Iteration 450, loss = 47.40608244\n",
      "Iteration 451, loss = 46.46806505\n",
      "Iteration 452, loss = 46.11099110\n",
      "Iteration 453, loss = 45.80206076\n",
      "Iteration 454, loss = 45.67574083\n",
      "Iteration 455, loss = 44.82662943\n",
      "Iteration 456, loss = 45.06279178\n",
      "Iteration 457, loss = 44.26289873\n",
      "Iteration 458, loss = 43.98526422\n",
      "Iteration 459, loss = 44.40530385\n",
      "Iteration 460, loss = 42.55166882\n",
      "Iteration 461, loss = 42.16702795\n",
      "Iteration 462, loss = 41.64308806\n",
      "Iteration 463, loss = 41.90250993\n",
      "Iteration 464, loss = 41.47156774\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 465, loss = 40.90612787\n",
      "Iteration 466, loss = 41.59533843\n",
      "Iteration 467, loss = 40.05117475\n",
      "Iteration 468, loss = 40.47149539\n",
      "Iteration 469, loss = 39.34964395\n",
      "Iteration 470, loss = 40.01628642\n",
      "Iteration 471, loss = 38.90270262\n",
      "Iteration 472, loss = 38.45942546\n",
      "Iteration 473, loss = 37.69972090\n",
      "Iteration 474, loss = 37.53793845\n",
      "Iteration 475, loss = 37.56711624\n",
      "Iteration 476, loss = 37.65805188\n",
      "Iteration 477, loss = 37.02322889\n",
      "Iteration 478, loss = 36.83227297\n",
      "Iteration 479, loss = 36.55476977\n",
      "Iteration 480, loss = 36.09523699\n",
      "Iteration 481, loss = 35.60319782\n",
      "Iteration 482, loss = 35.83014033\n",
      "Iteration 483, loss = 35.80227202\n",
      "Iteration 484, loss = 34.69988615\n",
      "Iteration 485, loss = 35.63524672\n",
      "Iteration 486, loss = 34.67621098\n",
      "Iteration 487, loss = 33.93599478\n",
      "Iteration 488, loss = 34.04650755\n",
      "Iteration 489, loss = 34.41066714\n",
      "Iteration 490, loss = 33.99328734\n",
      "Training loss did not improve more than tol=0.000001 for two consecutive epochs. Stopping.\n"
     ]
    }
   ],
   "source": [
    "mlp = MLPRegressor(\n",
    "    hidden_layer_sizes=(100,100,100,100),\n",
    "    learning_rate_init=0.00001,\n",
    "    tol=0.000001,\n",
    "    max_iter=1000,\n",
    "    verbose=True,)\n",
    "model = mlp.fit(X_train.get_values(), y_train.get_values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mse: 81.6659676671\n",
      "mae: 6.41344152901\n",
      "evs: 0.999857631482\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn.metrics import explained_variance_score\n",
    "\n",
    "y_pred = model.predict(X_test.get_values())\n",
    "\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "mae = mean_absolute_error(y_test, y_pred)\n",
    "evs = explained_variance_score(y_test, y_pred)\n",
    "\n",
    "print(\"mse: %s\" % mse)\n",
    "print(\"mae: %s\" % mae)\n",
    "print(\"evs: %s\" % evs)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Probamos el algoritmo\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_test(rows=5, with_plot=False):\n",
    "    test_data = []\n",
    "    for r in range(0, rows):\n",
    "        \n",
    "        velocidad=random.randint(1,50)\n",
    "        grados=random.randint(10,80)\n",
    "        gravedad=9.8\n",
    "        altura=random.choice([1, 1.5, 2, 3, 4, 5])\n",
    "        \n",
    "        test_data.append({\n",
    "            \"altura\": altura,\n",
    "            \"velocidad\": velocidad, \n",
    "            \"grados\": grados,\n",
    "            \"gravedad\": gravedad,\n",
    "        })\n",
    "        \n",
    "    test_data = pd.DataFrame(test_data)\n",
    "    test_data[\"predict\"] = model.predict(\n",
    "        test_data[[\"altura\", \"velocidad\", \"grados\", \"gravedad\"]]\n",
    "    )\n",
    "    \n",
    "    impactos = []\n",
    "    for row in test_data.iterrows():\n",
    "        \n",
    "        trayectoria, impacto = lanza_proyectil(\n",
    "            altura=row[1][\"altura\"],\n",
    "            velocidad=row[1][\"velocidad\"],\n",
    "            grados=row[1][\"grados\"],\n",
    "            gravedad=row[1][\"gravedad\"],\n",
    "            with_plot=with_plot,\n",
    "            predict=row[1][\"predict\"],\n",
    "        )\n",
    "        impactos.append(impacto)\n",
    "    \n",
    "    test_data[\"impacto\"]=impactos\n",
    "    test_data[\"predict_error\"]=test_data[\"impacto\"]-test_data[\"predict\"]\n",
    "    \n",
    "    return test_data\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 46.0 - Grados: 55.0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"3085c291-ea1a-43fe-bee7-bd90904b1eac\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"3085c291-ea1a-43fe-bee7-bd90904b1eac\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"3085c291-ea1a-43fe-bee7-bd90904b1eac\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3085c291-ea1a-43fe-bee7-bd90904b1eac' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"22794440-b6ba-4719-be10-9884bcbe7e3b\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"3b01a389-f14c-43b5-ac01-d5de8d1ac194\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"below\":[{\"id\":\"eb9edf77-0914-4b5c-ae94-321700702348\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"91ccd8bc-b810-441b-8788-a0f6d2e75fe7\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"eb9edf77-0914-4b5c-ae94-321700702348\",\"type\":\"LinearAxis\"},{\"id\":\"3e58c992-2533-4f75-b5be-b7b240de829a\",\"type\":\"Grid\"},{\"id\":\"91ccd8bc-b810-441b-8788-a0f6d2e75fe7\",\"type\":\"LinearAxis\"},{\"id\":\"d07d8d05-5f8c-4a79-9353-fd4a74075fd3\",\"type\":\"Grid\"},{\"id\":\"4d787337-11f7-4ed7-b26f-2f96384ddd9a\",\"type\":\"BoxAnnotation\"},{\"id\":\"88f30a0f-741d-423a-9052-ccd675adb518\",\"type\":\"Legend\"},{\"id\":\"684cddb7-08fd-4aca-9d31-f3ddcfb87427\",\"type\":\"GlyphRenderer\"},{\"id\":\"d73b9528-f55a-470d-a51b-e12403445239\",\"type\":\"Arrow\"},{\"id\":\"18d61147-e553-436f-8cfc-c7166d3a1545\",\"type\":\"Span\"},{\"id\":\"4ae914a5-af13-4801-a7c2-e40eeb4f1291\",\"type\":\"Arrow\"}],\"title\":{\"id\":\"63759f78-c293-48f3-93ff-6efb09dc95d9\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"9bb507aa-ea74-4009-8eb7-0ca1e52561d4\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"ba4ceaef-b343-4a5f-be33-b03216ee8465\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"1f5ac9de-37b3-4bf0-bf16-a2f1c98eaf21\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"f5192c10-dd66-4b7e-9b9d-ade4482f5229\",\"type\":\"DataRange1d\"}},\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"b2708a13-c475-456d-a0c3-737627218b76\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"3010e4f1-1c6f-4d59-af6d-160326615854\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"80123238-a2e3-45ea-8178-65b7a42d123e\",\"type\":\"BasicTicker\"}},\"id\":\"eb9edf77-0914-4b5c-ae94-321700702348\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 2031.61 \"},\"id\":\"63759f78-c293-48f3-93ff-6efb09dc95d9\",\"type\":\"Title\"},{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"15340389-925e-4d6e-96a2-93519175ee40\",\"type\":\"SaveTool\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"243a2b77-8818-4e5d-a341-bbcd22425281\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9df61517-bc7e-4a30-b71f-1c57b173e1d2\",\"type\":\"BasicTicker\"}},\"id\":\"91ccd8bc-b810-441b-8788-a0f6d2e75fe7\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"9bb507aa-ea74-4009-8eb7-0ca1e52561d4\",\"type\":\"ToolEvents\"},{\"attributes\":{\"callback\":null},\"id\":\"1f5ac9de-37b3-4bf0-bf16-a2f1c98eaf21\",\"type\":\"DataRange1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"bdbd04bc-ea2a-4d6e-9580-45d80fc89182\",\"type\":\"PanTool\"},{\"id\":\"3b01a389-f14c-43b5-ac01-d5de8d1ac194\",\"type\":\"WheelZoomTool\"},{\"id\":\"090f104b-38c9-4254-8c23-ed598d5f7537\",\"type\":\"BoxZoomTool\"},{\"id\":\"15340389-925e-4d6e-96a2-93519175ee40\",\"type\":\"SaveTool\"},{\"id\":\"f7c8ca58-46e7-4263-a73b-6eb0abd9f1ad\",\"type\":\"ResetTool\"},{\"id\":\"f0a722f2-d643-489f-be03-66aa1375bd7b\",\"type\":\"HelpTool\"}]},\"id\":\"ba4ceaef-b343-4a5f-be33-b03216ee8465\",\"type\":\"Toolbar\"},{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"80123238-a2e3-45ea-8178-65b7a42d123e\",\"type\":\"BasicTicker\"}},\"id\":\"3e58c992-2533-4f75-b5be-b7b240de829a\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null},\"id\":\"f5192c10-dd66-4b7e-9b9d-ade4482f5229\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"80123238-a2e3-45ea-8178-65b7a42d123e\",\"type\":\"BasicTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"2f5b22ec-f28e-48b0-9a58-e02c5d50840a\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"b2708a13-c475-456d-a0c3-737627218b76\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"ecd590fb-6223-4b4d-b4fa-451a0c5b0c82\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"684cddb7-08fd-4aca-9d31-f3ddcfb87427\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9df61517-bc7e-4a30-b71f-1c57b173e1d2\",\"type\":\"BasicTicker\"}},\"id\":\"d07d8d05-5f8c-4a79-9353-fd4a74075fd3\",\"type\":\"Grid\"},{\"attributes\":{\"overlay\":{\"id\":\"4d787337-11f7-4ed7-b26f-2f96384ddd9a\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"090f104b-38c9-4254-8c23-ed598d5f7537\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"ecd590fb-6223-4b4d-b4fa-451a0c5b0c82\",\"type\":\"Line\"},{\"attributes\":{\"items\":[{\"id\":\"74673ba6-4d43-4a02-9f90-49f81c93758d\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"88f30a0f-741d-423a-9052-ccd675adb518\",\"type\":\"Legend\"},{\"attributes\":{\"plot\":null,\"size\":5},\"id\":\"86ddd102-bbf6-4c1f-8dba-f21c2b4af53d\",\"type\":\"VeeHead\"},{\"attributes\":{},\"id\":\"243a2b77-8818-4e5d-a341-bbcd22425281\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"2ed237a3-cbd7-4a79-82e4-73f31d4fbf32\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":2031.61},\"x_start\":{\"value\":2031.61},\"y_end\":{\"value\":0},\"y_start\":{\"value\":363.2084978669698}},\"id\":\"d73b9528-f55a-470d-a51b-e12403445239\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"2ed237a3-cbd7-4a79-82e4-73f31d4fbf32\",\"type\":\"OpenHead\"},{\"attributes\":{\"end\":{\"id\":\"86ddd102-bbf6-4c1f-8dba-f21c2b4af53d\",\"type\":\"VeeHead\"},\"line_color\":{\"value\":\"blue\"},\"line_dash\":[2,4,6,4],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":2025.5127268313963},\"x_start\":{\"value\":2025.5127268313963},\"y_end\":{\"value\":0},\"y_start\":{\"value\":363.2084978669698}},\"id\":\"4ae914a5-af13-4801-a7c2-e40eeb4f1291\",\"type\":\"Arrow\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":726.4169957339396,\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"18d61147-e553-436f-8cfc-c7166d3a1545\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f0a722f2-d643-489f-be03-66aa1375bd7b\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f7c8ca58-46e7-4263-a73b-6eb0abd9f1ad\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"3010e4f1-1c6f-4d59-af6d-160326615854\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"bdbd04bc-ea2a-4d6e-9580-45d80fc89182\",\"type\":\"PanTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"4d787337-11f7-4ed7-b26f-2f96384ddd9a\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"AAAAAAAAAACyhyiEjBv1P7KHKISMGwVAjMs8xlKpD0CyhyiEjBsVQJ6pMqVvYhpAiss8xlKpH0C7dqPzGngiQLGHKISMGyVAp5itFP6+J0CdqTKlb2IqQJO6tzXhBS1Aiss8xlKpL0BA7mArYiYxQLx2o/MaeDJAN//lu9PJM0CzhyiEjBs1QC4Qa0xFbTZAqpitFP6+N0AlIfDcthA5QKCpMqVvYjpAGzJ1bSi0O0CXurc14QU9QBJD+v2ZVz5Ajcs8xlKpP0AEqj/HhX1AQELuYCtiJkFAgDKCjz7PQUC+dqPzGnhCQPu6xFf3IENAOf/lu9PJQ0B3QwcgsHJEQLSHKISMG0VA8stJ6GjERUAwEGtMRW1GQG5UjLAhFkdAq5itFP6+R0Dp3M542mdIQCch8Ny2EElAZGURQZO5SUChqTKlb2JKQN7tUwlMC0tAGzJ1bSi0S0BYdpbRBF1MQJW6tzXhBU1A0v7Ymb2uTUAPQ/r9mVdOQEyHG2J2AE9AiMs8xlKpT0DjBy+VFylQQAGqP8eFfVBAIExQ+fPRUEA+7mArYiZRQFyQcV3QelFAezKCjz7PUUCZ1JLBrCNSQLh2o/MaeFJA1hi0JYnMUkD1usRX9yBTQBNd1YlldVNAMv/lu9PJU0BQofbtQR5UQG5DByCwclRAjeUXUh7HVECrhyiEjBtVQMopObb6b1VA6MtJ6GjEVUAHbloa1xhWQCUQa0xFbVZARLJ7frPBVkBiVIywIRZXQID2nOKPaldAn5itFP6+V0C9Or5GbBNYQNzcznjaZ1hA+n7fqki8WEAZIfDcthBZQDfDAA8lZVlAVmURQZO5WUB0ByJzAQ5aQJKpMqVvYlpAsUtD1922WkDP7VMJTAtbQO6PZDu6X1tADDJ1bSi0W0Ar1IWflghcQEl2ltEEXVxAaBinA3OxXECGurc14QVdQKRcyGdPWl1Aw/7Ymb2uXUDhoOnLKwNeQABD+v2ZV15AHuUKMAisXkA9hxtidgBfQFspLJTkVF9Aess8xlKpX0CYbU34wP1fQNsHL5UXKWBA6lg3rk5TYED6qT/HhX1gQAn7R+C8p2BAGExQ+fPRYEAnnVgSK/xgQDfuYCtiJmFARj9pRJlQYUBVkHFd0HphQGTheXYHpWFAczKCjz7PYUCDg4qodflhQJLUksGsI2JAoSWb2uNNYkCwdqPzGnhiQMDHqwxSomJAzxi0JYnMYkDeabw+wPZiQO26xFf3IGNA/AvNcC5LY0AMXdWJZXVjQBuu3aKcn2NAKv/lu9PJY0A5UO7UCvRjQEmh9u1BHmRAWPL+BnlIZEBnQwcgsHJkQHaUDznnnGRAheUXUh7HZECVNiBrVfFkQKSHKISMG2VAs9gwncNFZUDCKTm2+m9lQNJ6Qc8xmmVA4ctJ6GjEZUDwHFIBoO5lQP9tWhrXGGZADr9iMw5DZkAeEGtMRW1mQC1hc2V8l2ZAPLJ7frPBZkBLA4SX6utmQFtUjLAhFmdAaqWUyVhAZ0B59pzij2pnQIhHpfvGlGdAl5itFP6+Z0Cn6bUtNelnQLY6vkZsE2hAxYvGX6M9aEDU3M542mdoQOQt15ERkmhA837fqki8aEAC0OfDf+ZoQBEh8Ny2EGlAIHL49e06aUAwwwAPJWVpQD8UCShcj2lATmURQZO5aUBdthlayuNpQG0HInMBDmpAfFgqjDg4akCLqTKlb2JqQJr6Or6mjGpAqktD1922akC6nEvwFOFqQMrtUwlMC2tA2j5cIoM1a0Dqj2Q7ul9rQPvgbFTxiWtACzJ1bSi0a0Abg32GX95rQCvUhZ+WCGxAOyWOuM0ybEBLdpbRBF1sQFvHnuo7h2xAaxinA3OxbEB7aa8cqttsQIu6tzXhBW1AmwvAThgwbUCrXMhnT1ptQLut0ICGhG1Ay/7Ymb2ubUDbT+Gy9NhtQOug6csrA25A+/Hx5GItbkALQ/r9mVduQBuUAhfRgW5AK+UKMAisbkA7NhNJP9ZuQEyHG2J2AG9AXNgje60qb0BsKSyU5FRvQHx6NK0bf29AjMs8xlKpb0CcHEXfidNvQKxtTfjA/W9AXt+qCPwTcEDmBy+VFylwQG4wsyEzPnBA9lg3rk5TcEB+gbs6amhwQAaqP8eFfXBAjtLDU6GScEAW+0fgvKdwQJ4jzGzYvHBAJkxQ+fPRcECudNSFD+dwQDadWBIr/HBAvsXcnkYRcUBG7mArYiZxQM4W5bd9O3FAVj9pRJlQcUDeZ+3QtGVxQGaQcV3QenFA7rj16euPcUB24Xl2B6VxQP4J/gIjunFAhjKCjz7PcUAOWwYcWuRxQJaDiqh1+XFAHqwONZEOckCn1JLBrCNyQC/9Fk7IOHJAtyWb2uNNckA/Th9n/2JyQMd2o/MaeHJAT58ngDaNckDXx6sMUqJyQF/wL5ltt3JA5xi0JYnMckBvQTiypOFyQPdpvD7A9nJAf5JAy9sLc0AHu8RX9yBzQI/jSOQSNnNAFwzNcC5Lc0CfNFH9SWBzQCdd1YlldXNAr4VZFoGKc0A3rt2inJ9zQL/WYS+4tHNAR//lu9PJc0DPJ2pI795zQFdQ7tQK9HNA33hyYSYJdEBnofbtQR50QO/JenpdM3RAd/L+BnlIdED/GoOTlF10QIdDByCwcnRAD2yLrMuHdECXlA8555x0QB+9k8UCsnRAp+UXUh7HdEAvDpzeOdx0QLc2IGtV8XRAP1+k93AGdUDHhyiEjBt1QE+wrBCoMHVA19gwncNFdUBfAbUp31p1QOcpObb6b3VAb1K9QhaFdUD4ekHPMZp1QICjxVtNr3VACMxJ6GjEdUCQ9M10hNl1QBgdUgGg7nVAoEXWjbsDdkAobloa1xh2QLCW3qbyLXZAOL9iMw5DdkDA5+a/KVh2QEgQa0xFbXZA0Djv2GCCdkBYYXNlfJd2QOCJ9/GXrHZAaLJ7frPBdkDw2v8Kz9Z2QHgDhJfq63ZAACwIJAYBd0CIVIywIRZ3QBB9ED09K3dAmKWUyVhAd0AgzhhWdFV3QKj2nOKPandAMB8hb6t/d0C4R6X7xpR3QEBwKYjiqXdAyJitFP6+d0BQwTGhGdR3QNjptS016XdAYBI6ulD+d0DoOr5GbBN4QHBjQtOHKHhA+IvGX6M9eECAtErsvlJ4QAjdznjaZ3hAkAVTBfZ8eEAYLteREZJ4QKBWWx4tp3hAKH/fqki8eECwp2M3ZNF4QDjQ58N/5nhAwPhrUJv7eEBIIfDcthB5QNFJdGnSJXlAWXL49e06eUDhmnyCCVB5QGnDAA8lZXlA8euEm0B6eUB5FAkoXI95QAE9jbR3pHlAiWURQZO5eUARjpXNrs55QJm2GVrK43lAId+d5uX4eUCpByJzAQ56QDEwpv8cI3pAuVgqjDg4ekBBga4YVE16QMmpMqVvYnpAUdK2MYt3ekDZ+jq+pox6QGEjv0rCoXpA6UtD1922ekBxdMdj+ct6QPmcS/AU4XpAgcXPfDD2ekAJ7lMJTAt7QJEW2JVnIHtAGT9cIoM1e0ChZ+Cunkp7QCmQZDu6X3tAsbjox9V0e0A54WxU8Yl7QMEJ8eAMn3tASTJ1bSi0e0DRWvn5Q8l7QFmDfYZf3ntA4asBE3vze0Bp1IWflgh8QPH8CSyyHXxAeSWOuM0yfEABThJF6Ud8QIl2ltEEXXxAEZ8aXiByfECZx57qO4d8QCLwIndXnHxAqhinA3OxfEAyQSuQjsZ8QLpprxyq23xAQpIzqcXwfEDKurc14QV9QFLjO8L8Gn1A2gvAThgwfUBiNETbM0V9QOpcyGdPWn1AcoVM9GpvfUD6rdCAhoR9QILWVA2imX1ACv/Ymb2ufUCSJ10m2cN9QBpQ4bL02H1AonhlPxDufUAqoenLKwN+QLLJbVhHGH5AOvLx5GItfkDCGnZxfkJ+QEpD+v2ZV35A0mt+irVsfkBalAIX0YF+QOK8hqPsln5AauUKMAisfkDyDY+8I8F+QHo2E0k/1n5AAl+X1VrrfkCKhxtidgB/QBKwn+6RFX9Amtgje60qf0AiAagHyT9/QKopLJTkVH9AMlKwIABqf0C6ejStG39/QEKjuDk3lH9Ayss8xlKpf0BS9MBSbr5/QNocRd+J039AYkXJa6Xof0DqbU34wP1/QDnLaEJuCYBAfd+qCPwTgEDB8+zOiR6AQAUIL5UXKYBASRxxW6UzgECNMLMhMz6AQNFE9efASIBAFVk3rk5TgEBZbXl03F2AQJ2BuzpqaIBA4ZX9APhygEAlqj/HhX2AQGm+gY0TiIBArdLDU6GSgEDx5gUaL52AQDX7R+C8p4BAeQ+KpkqygEC9I8xs2LyAQAE4DjNmx4BARUxQ+fPRgECJYJK/gdyAQM101IUP54BAEokWTJ3xgEBWnVgSK/yAQJqxmti4BoFA3sXcnkYRgUAi2h5l1BuBQGbuYCtiJoFAqgKj8e8wgUDuFuW3fTuBQDIrJ34LRoFAdj9pRJlQgUC6U6sKJ1uBQP5n7dC0ZYFAQnwvl0JwgUCGkHFd0HqBQMqksyNehYFADrn16euPgUBSzTeweZqBQJbheXYHpYFA2vW7PJWvgUAeCv4CI7qBQGIeQMmwxIFApjKCjz7PgUDqRsRVzNmBQC5bBhxa5IFAcm9I4ufugUC2g4qodfmBQPqXzG4DBIJAPqwONZEOgkCCwFD7HhmCQMbUksGsI4JACunUhzougkBO/RZOyDiCQJIRWRRWQ4JA1iWb2uNNgkAaOt2gcViCQF5OH2f/YoJAomJhLY1tgkDmdqPzGniCQCqL5bmogoJAbp8ngDaNgkCys2lGxJeCQPbHqwxSooJAOtzt0t+sgkB+8C+ZbbeCQMIEcl/7wYJABhm0JYnMgkBKLfbrFteCQI5BOLKk4YJA0lV6eDLsgkAWarw+wPaCQFp+/gROAYNAnpJAy9sLg0DipoKRaRaDQCa7xFf3IINAas8GHoUrg0Cu40jkEjaDQPL3iqqgQINANgzNcC5Lg0B6IA83vFWDQL40Uf1JYINAAkmTw9dqg0BGXdWJZXWDQIpxF1Dzf4NAzoVZFoGKg0ASmpvcDpWDQFau3aKcn4NAmsIfaSqqg0De1mEvuLSDQCLro/VFv4NAZv/lu9PJg0CqEyiCYdSDQO4nakjv3oNAMjysDn3pg0B2UO7UCvSDQLpkMJuY/oNA/nhyYSYJhEBCjbQntBOEQIah9u1BHoRAyrU4tM8ohEAOynp6XTOEQFLevEDrPYRAlvL+BnlIhEDaBkHNBlOEQB4bg5OUXYRAYi/FWSJohECnQwcgsHKEQOtXSeY9fYRAL2yLrMuHhEBzgM1yWZKEQLeUDznnnIRA+6hR/3SnhEA/vZPFArKEQIPR1YuQvIRAx+UXUh7HhEAL+lkYrNGEQE8OnN453IRAkyLepMfmhEDXNiBrVfGEQBtLYjHj+4RAX1+k93AGhUCjc+a9/hCFQOeHKISMG4VAK5xqShomhUBvsKwQqDCFQLPE7tY1O4VA99gwncNFhUA77XJjUVCFQH8BtSnfWoVAwxX372xlhUAHKjm2+m+FQEs+e3yIeoVAj1K9QhaFhUDTZv8IpI+FQBd7Qc8xmoVAW4+Dlb+khUCfo8VbTa+FQOO3ByLbuYVAJ8xJ6GjEhUBr4Iuu9s6FQK/0zXSE2YVA8wgQOxLkhUA3HVIBoO6FQHsxlMct+YVAv0XWjbsDhkADWhhUSQ6GQEduWhrXGIZAi4Kc4GQjhkDPlt6m8i2GQBOrIG2AOIZAV79iMw5DhkCb06T5m02GQN/n5r8pWIZAI/wohrdihkBnEGtMRW2GQKskrRLTd4ZA7zjv2GCChkAzTTGf7oyGQHdhc2V8l4ZAu3W1KwqihkD/iffxl6yGQEOeObglt4ZAh7J7frPBhkDLxr1EQcyGQA/b/wrP1oZAU+9B0VzhhkCXA4SX6uuGQNsXxl149oZAHywIJAYBh0BjQErqkwuHQKdUjLAhFodA62jOdq8gh0AvfRA9PSuHQHORUgPLNYdAt6WUyVhAh0D7udaP5kqHQD/OGFZ0VYdAg+JaHAJgh0DH9pzij2qHQAsL36gddYdATx8hb6t/h0CTM2M1OYqHQNdHpfvGlIdAG1znwVSfh0BfcCmI4qmHQKOEa05wtIdA55itFP6+h0Arre/ai8mHQG/BMaEZ1IdAs9VzZ6feh0D36bUtNemHQDz+9/PC84dAgBI6ulD+h0DEJnyA3giIQAg7vkZsE4hATE8ADfodiECQY0LThyiIQNR3hJkVM4hAGIzGX6M9iEBcoAgmMUiIQKC0Suy+UohA5MiMskxdiEAo3c542meIQGzxED9ocohAsAVTBfZ8iED0GZXLg4eIQDgu15ERkohAfEIZWJ+ciEDAVlseLaeIQARrneS6sYhASH/fqki8iECMkyFx1saIQNCnYzdk0YhAFLyl/fHbiEBY0OfDf+aIQJzkKYoN8YhA4PhrUJv7iEAkDa4WKQaJQGgh8Ny2EIlArDUyo0QbiUDwSXRp0iWJQDReti9gMIlAeHL49e06iUC8hjq8e0WJQACbfIIJUIlARK++SJdaiUCIwwAPJWWJQMzXQtWyb4lAEOyEm0B6iUBUAMdhzoSJQJgUCShcj4lA3ChL7umZiUAgPY20d6SJQGRRz3oFr4lAqGURQZO5iUDseVMHIcSJQDCOlc2uzolAdKLXkzzZiUC4thlayuOJQPzKWyBY7olAQN+d5uX4iUCE89+scwOKQMgHInMBDopADBxkOY8YikBQMKb/HCOKQJRE6MWqLYpA2FgqjDg4ikAcbWxSxkKKQGCBrhhUTYpApJXw3uFXikDoqTKlb2KKQCu+dGv9bIpAb9K2MYt3ikCy5vj3GIKKQPX6Or6mjIpAOA99hDSXikB7I79KwqGKQL83ARFQrIpAAkxD1922ikBFYIWda8GKQIh0x2P5y4pAy4gJKofWikAOnUvwFOGKQFKxjbai64pAlcXPfDD2ikDY2RFDvgCLQBvuUwlMC4tAXgKWz9kVi0CiFtiVZyCLQOUqGlz1KotAKD9cIoM1i0BrU57oEECLQK5n4K6eSotA8nsidSxVi0A1kGQ7ul+LQHikpgFIaotAu7jox9V0i0D+zCqOY3+LQEHhbFTxiYtAhfWuGn+Ui0DICfHgDJ+LQAseM6eaqYtATjJ1bSi0i0CRRrcztr6LQNVa+flDyYtAGG87wNHTi0Bbg32GX96LQJ6Xv0zt6ItA4asBE3vzi0AlwEPZCP6LQGjUhZ+WCIxAq+jHZSQTjEDu/Akssh2MQDERTPI/KIxAdCWOuM0yjEC4OdB+Wz2MQPtNEkXpR4xAPmJUC3dSjECBdpbRBF2MQMSK2JeSZ4xACJ8aXiByjEBLs1wkrnyMQI7Hnuo7h4xA0dvgsMmRjEAU8CJ3V5yMQFgEZT3lpoxAmxinA3OxjEDeLOnJALyMQCFBK5COxoxAZFVtVhzRjECnaa8cqtuMQOt98eI35oxALpIzqcXwjEBxpnVvU/uMQLS6tzXhBY1A9875+24QjUA74zvC/BqNQH73fYiKJY1AwQvAThgwjUAEIAIVpjqNQEc0RNszRY1Ai0iGocFPjUDOXMhnT1qNQBFxCi7dZI1AVIVM9GpvjUCXmY66+HmNQNqt0ICGhI1AHsISRxSPjUBh1lQNopmNQKTqltMvpI1A5/7Ymb2ujUAqExtgS7mNQG4nXSbZw41AsTuf7GbOjUD0T+Gy9NiNQDdkI3mC441AenhlPxDujUC9jKcFnviNQAGh6csrA45ARLUrkrkNjkCHyW1YRxiOQMrdrx7VIo5ADfLx5GItjkBRBjSr8DeOQJQadnF+Qo5A1y64NwxNjkAaQ/r9mVeOQF1XPMQnYo5AoWt+irVsjkDkf8BQQ3eOQCeUAhfRgY5AaqhE3V6MjkCtvIaj7JaOQPDQyGl6oY5ANOUKMAisjkB3+Uz2lbaOQLoNj7wjwY5A/SHRgrHLjkBANhNJP9aOQIRKVQ/N4I5Ax16X1VrrjkAKc9mb6PWOQE2HG2J2AI9AkJtdKAQLj0DUr5/ukRWPQBfE4bQfII9AWtgje60qj0Cd7GVBOzWPQOAAqAfJP49AIxXqzVZKj0BnKSyU5FSPQKo9blpyX49A7VGwIABqj0AwZvLmjXSPQHN6NK0bf49At452c6mJj0D6org5N5SPQD23+v/Eno9AgMs8xlKpj0DD336M4LOPQAf0wFJuvo9ASggDGfzIj0CNHEXfidOPQNAwh6UX3o9AE0XJa6Xoj0BWWQsyM/OPQJptTfjA/Y9A7sBHXycEkEAQy2hCbgmQQDLViSW1DpBAU9+qCPwTkEB16cvrQhmQQJbz7M6JHpBAuP0NstAjkEDaBy+VFymQQPsRUHheLpBAHRxxW6UzkEA+JpI+7DiQQGAwsyEzPpBAgjrUBHpDkECjRPXnwEiQQMVOFssHTpBA5lg3rk5TkEAIY1iRlViQQCpteXTcXZBAS3eaVyNjkEBtgbs6amiQQI6L3B2xbZBAsJX9APhykEDRnx7kPniQQPOpP8eFfZBAFbRgqsyCkEA2voGNE4iQQFjIonBajZBAedLDU6GSkECb3OQ26JeQQL3mBRovnZBA3vAm/XWikEAA+0fgvKeQQCEFacMDrZBAQw+KpkqykEBlGauJkbeQQIYjzGzYvJBAqC3tTx/CkEDJNw4zZseQQOtBLxatzJBADUxQ+fPRkEAuVnHcOteQQFBgkr+B3JBAcWqzosjhkECTdNSFD+eQQLV+9WhW7JBA1ogWTJ3xkED4kjcv5PaQQBmdWBIr/JBAO6d59XEBkUBdsZrYuAaRQH67u7v/C5FAoMXcnkYRkUDBz/2BjRaRQOPZHmXUG5FABOQ/SBshkUAm7mArYiaRQEj4gQ6pK5FAaQKj8e8wkUCLDMTUNjaRQKwW5bd9O5FAziAGm8RAkUDwKid+C0aRQBE1SGFSS5FAMz9pRJlQkUBUSYon4FWRQHZTqwonW5FAmF3M7W1gkUC5Z+3QtGWRQNtxDrT7apFA/Hsvl0JwkUAehlB6iXWRQECQcV3QepFAYZqSQBeAkUCDpLMjXoWRQKSu1AalipFAxrj16euPkUDowhbNMpWRQAnNN7B5mpFAK9dYk8CfkUBM4Xl2B6WRQG7rmllOqpFAkPW7PJWvkUCx/9wf3LSRQNMJ/gIjupFA9BMf5mm/kUAWHkDJsMSRQDcoYaz3yZFAWTKCjz7PkUB7PKNyhdSRQJxGxFXM2ZFAvlDlOBPfkUDfWgYcWuSRQAFlJ/+g6ZFAI29I4ufukUBEeWnFLvSRQGaDiqh1+ZFAh42ri7z+kUCpl8xuAwSSQMuh7VFKCZJA7KsONZEOkkAOti8Y2BOSQC/AUPseGZJAUcpx3mUekkBz1JLBrCOSQJTes6TzKJJAtujUhzoukkDX8vVqgTOSQPn8Fk7IOJJAGwc4MQ8+kkA8EVkUVkOSQF4bevecSJJAfyWb2uNNkkChL7y9KlOSQMM53aBxWJJA5EP+g7hdkkAGTh9n/2KSQCdYQEpGaJJASWJhLY1tkkBqbIIQ1HKSQIx2o/MaeJJAroDE1mF9kkDPiuW5qIKSQPGUBp3vh5JAEp8ngDaNkkA0qUhjfZKSQFazaUbEl5JAd72KKQudkkCZx6sMUqKSQLrRzO+Yp5JA3Nvt0t+skkD+5Q62JrKSQB/wL5ltt5JAQfpQfLS8kkBiBHJf+8GSQIQOk0JCx5JAphi0JYnMkkDHItUI0NGSQOks9usW15JACjcXz13ckkAsQTiypOGSQE5LWZXr5pJAb1V6eDLskkCRX5tbefGSQLJpvD7A9pJA1HPdIQf8kkD2ff4ETgGTQBeIH+iUBpNAOZJAy9sLk0BanGGuIhGTQHymgpFpFpNAnbCjdLAbk0C/usRX9yCTQOHE5To+JpNAAs8GHoUrk0Ak2ScBzDCTQEXjSOQSNpNAZ+1px1k7k0CJ94qqoECTQKoBrI3nRZNAzAvNcC5Lk0DtFe5TdVCTQA8gDze8VZNAMSowGgNbk0BSNFH9SWCTQHQ+cuCQZZNAlUiTw9dqk0C3UrSmHnCTQNlc1YlldZNA+mb2bKx6k0AccRdQ83+TQD17ODM6hZNAX4VZFoGKk0CBj3r5x4+TQKKZm9wOlZNAxKO8v1Wak0Dlrd2inJ+TQAe4/oXjpJNAKcIfaSqqk0BKzEBMca+TQGzWYS+4tJNAjeCCEv+5k0Cv6qP1Rb+TQND0xNiMxJNA8v7lu9PJk0AUCQefGs+TQDUTKIJh1JNAVx1JZajZk0B4J2pI796TQJoxiys25JNAvDusDn3pk0DdRc3xw+6TQP9P7tQK9JNAIFoPuFH5k0BCZDCbmP6TQGRuUX7fA5RAhXhyYSYJlECngpNEbQ6UQMiMtCe0E5RA6pbVCvsYlEAMofbtQR6UQC2rF9GII5RAT7U4tM8olEBwv1mXFi6UQJLJenpdM5RAtNObXaQ4lEDV3bxA6z2UQPfn3SMyQ5RAGPL+BnlIlEA6/B/qv02UQFsGQc0GU5RAfRBisE1YlECfGoOTlF2UQMAkpHbbYpRA4i7FWSJolEADOeY8aW2UQCVDByCwcpRAR00oA/d3lEBoV0nmPX2UQIphasmEgpRAq2uLrMuHlEDNdayPEo2UQO9/zXJZkpRAEIruVaCXlEAylA8555yUQFOeMBwuopRAdahR/3SnlECXsnLiu6yUQLi8k8UCspRA2sa0qEm3lED70NWLkLyUQB3b9m7XwZRAP+UXUh7HlEBg7zg1ZcyUQIL5WRis0ZRAowN7+/LWlEDFDZzeOdyUQOcXvcGA4ZRACCLepMfmlEAqLP+HDuyUQEs2IGtV8ZRAbUBBTpz2lECOSmIx4/uUQLBUgxQqAZVA0l6k93AGlUDzaMXatwuVQBVz5r3+EJVANn0HoUUWlUBYhyiEjBuVQHqRSWfTIJVAm5tqShomlUC9pYstYSuVQN6vrBCoMJVAALrN8+41lUAixO7WNTuVQEPOD7p8QJVAZdgwncNFlUCG4lGACkuVQKjscmNRUJVAyvaTRphVlUDrALUp31qVQA0L1gwmYJVALhX372xllUBQHxjTs2qVQHIpObb6b5VAkzNamUF1lUC1PXt8iHqVQNZHnF/Pf5VA+FG9QhaFlUAaXN4lXYqVQDtm/wikj5VAXXAg7OqUlUB+ekHPMZqVQKCEYrJ4n5VAwY6Dlb+klUDjmKR4BqqVQAWjxVtNr5VAJq3mPpS0lUBItwci27mVQGnBKAUiv5VAi8tJ6GjElUCt1WrLr8mVQM7fi672zpVA8OmskT3UlUAR9M10hNmVQDP+7lfL3pVAVQgQOxLklUB2EjEeWemVQJgcUgGg7pVAuSZz5ObzlUDbMJTHLfmVQP06tap0/pVAHkXWjbsDlkBAT/dwAgmWQGFZGFRJDpZAg2M5N5ATlkClbVoa1xiWQMZ3e/0dHpZA6IGc4GQjlkAJjL3DqyiWQCuW3qbyLZZATaD/iTkzlkBuqiBtgDiWQJC0QVDHPZZAsb5iMw5DlkDTyIMWVUiWQPTSpPmbTZZAFt3F3OJSlkA45+a/KViWQFnxB6NwXZZAe/sohrdilkCcBUpp/meWQL4Pa0xFbZZA4BmML4xylkABJK0S03eWQCMuzvUZfZZARDjv2GCClkBmQhC8p4eWQIhMMZ/ujJZAqVZSgjWSlkDLYHNlfJeWQOxqlEjDnJZADnW1KwqilkAwf9YOUaeWQFGJ9/GXrJZAc5MY1d6xlkCUnTm4JbeWQLanWptsvJZA2LF7frPBlkD5u5xh+saWQBvGvURBzJZAPNDeJ4jRlkBe2v8Kz9aWQIDkIO4V3JZAoe5B0VzhlkDD+GK0o+aWQOQChJfq65ZABg2lejHxlkAnF8ZdePaWQEkh50C/+5ZAaysIJAYBl0CMNSkHTQaXQK4/SuqTC5dAz0lrzdoQl0DxU4ywIRaXQBNerZNoG5dANGjOdq8gl0BWcu9Z9iWXQHd8ED09K5dAmYYxIIQwl0C7kFIDyzWXQNyac+YRO5dA/qSUyVhAl0Afr7Wsn0WXQEG51o/mSpdAY8P3ci1Ql0CEzRhWdFWXQKbXOTm7WpdAx+FaHAJgl0Dp63v/SGWXQAv2nOKPapdALAC+xdZvl0BOCt+oHXWXQG8UAIxkepdAkR4hb6t/l0CzKEJS8oSXQNQyYzU5ipdA9jyEGICPl0AXR6X7xpSXQDlRxt4NmpdAWlvnwVSfl0B8ZQilm6SXQJ5vKYjiqZdAv3lKaymvl0Dhg2tOcLSXQAKOjDG3uZdAJJitFP6+l0BGos73RMSXQGes79qLyZdAibYQvtLOl0CqwDGhGdSXQMzKUoRg2ZdA7tRzZ6fel0AP35RK7uOXQDHptS016ZdAUvPWEHzul0B0/ffzwvOXQJYHGdcJ+ZdAtxE6ulD+l0DZG1udlwOYQPolfIDeCJhAHDCdYyUOmEA+Or5GbBOYQF9E3ymzGJhAgU4ADfodmECiWCHwQCOYQMRiQtOHKJhA5mxjts4tmEAHd4SZFTOYQCmBpXxcOJhASovGX6M9mEBsledC6kKYQI2fCCYxSJhAr6kpCXhNmEDRs0rsvlKYQPK9a88FWJhAFMiMskxdmEA10q2Vk2KYQFfcznjaZ5hAeebvWyFtmECa8BA/aHKYQLz6MSKvd5hA3QRTBfZ8mED/DnToPIKYQCEZlcuDh5hAQiO2rsqMmEBkLdeREZKYQIU3+HRYl5hAp0EZWJ+cmEDJSzo75qGYQOpVWx4tp5hADGB8AXSsmEAtap3kurGYQE90vscBt5hAcX7fqki8mECSiACOj8GYQLSSIXHWxphA1ZxCVB3MmED3pmM3ZNGYQBmxhBqr1phAOrul/fHbmEBcxcbgOOGYQH3P58N/5phAn9kIp8brmEDA4ymKDfGYQOLtSm1U9phABPhrUJv7mEAlAo0z4gCZQEcMrhYpBplAaBbP+W8LmUCKIPDcthCZQKwqEcD9FZlAzTQyo0QbmUDvPlOGiyCZQBBJdGnSJZlAMlOVTBkrmUBUXbYvYDCZQHVn1xKnNZlAl3H49e06mUC4exnZNECZQNqFOrx7RZlA/I9bn8JKmUAdmnyCCVCZQD+knWVQVZlAYK6+SJdamUCCuN8r3l+ZQKTCAA8lZZlAxcwh8mtqmUDn1kLVsm+ZQAjhY7j5dJlAKuuEm0B6mUBM9aV+h3+ZQG3/xmHOhJlAjwnoRBWKmUCwEwkoXI+ZQNIdKgujlJlA8ydL7umZmUAVMmzRMJ+ZQDc8jbR3pJlAWEaul76pmUB6UM96Ba+ZQJta8F1MtJlAvWQRQZO5mUDfbjIk2r6ZQAB5UwchxJlAIoN06mfJmUBDjZXNrs6ZQGWXtrD105lAh6HXkzzZmUCoq/h2g96ZQMq1GVrK45lA6786PRHpmUANylsgWO6ZQC/UfAOf85lAUN6d5uX4mUBy6L7JLP6ZQJPy36xzA5pAtfwAkLoImkDXBiJzAQ6aQPgQQ1ZIE5pAGhtkOY8YmkA7JYUc1h2aQF0vpv8cI5pAfjnH4mMomkCgQ+jFqi2aQMJNCanxMppA41cqjDg4mkAFYktvfz2aQCZsbFLGQppASHaNNQ1ImkBqgK4YVE2aQIuKz/uaUppArZTw3uFXmkDOnhHCKF2aQPCoMqVvYppAErNTiLZnmkA0vXRr/WyaQFbHlU5EcppAd9G2MYt3mkCZ29cU0nyaQLrl+PcYgppA3O8Z21+HmkD++Tq+poyaQB8EXKHtkZpAQQ59hDSXmkBiGJ5ne5yaQIQiv0rCoZpApizgLQmnmkDHNgERUKyaQOlAIvSWsZpACktD1922mkAsVWS6JLyaQE5fhZ1rwZpAb2mmgLLGmkCRc8dj+cuaQLJ96EZA0ZpA1IcJKofWmkD2kSoNztuaQBecS/AU4ZpAOaZs01vmmkBasI22ouuaQHy6rpnp8JpAncTPfDD2mkC/zvBfd/uaQOHYEUO+AJtAAuMyJgUGm0Ak7VMJTAubQEX3dOySEJtAZwGWz9kVm0CJC7eyIBubQKoV2JVnIJtAzB/5eK4lm0DtKRpc9SqbQA80Oz88MJtAMT5cIoM1m0BSSH0FyjqbQHRSnugQQJtAlVy/y1dFm0C3ZuCunkqbQNlwAZLlT5tA+noidSxVm0AchUNYc1qbQD2PZDu6X5tAX5mFHgFlm0CBo6YBSGqbQKKtx+SOb5tAxLfox9V0m0DlwQmrHHqbQAfMKo5jf5tAKdZLcaqEm0BK4GxU8YmbQGzqjTc4j5tAjfSuGn+Um0Cv/s/9xZmbQNAI8eAMn5tA8hISxFOkm0AUHTOnmqmbQDUnVIrhrptAVzF1bSi0m0B4O5ZQb7mbQJpFtzO2vptAvE/YFv3Dm0DdWfn5Q8mbQP9jGt2KzptAIG47wNHTm0BCeFyjGNmbQGSCfYZf3ptAhYyeaabjm0Cnlr9M7eibQMig4C807ptA6qoBE3vzm0AMtSL2wfibQC2/Q9kI/ptAT8lkvE8DnEBw04WflgicQJLdpoLdDZxAtOfHZSQTnEDV8ehIaxicQPf7CSyyHZxAGAYrD/kinEA6EEzyPyicQFsabdWGLZxAfSSOuM0ynECfLq+bFDicQMA40H5bPZxA4kLxYaJCnEADTRJF6UecQCVXMygwTZxAR2FUC3dSnEBoa3XuvVecQIp1ltEEXZxAq3+3tEtinEDNidiXkmecQO+T+XrZbJxAEJ4aXiBynEAyqDtBZ3ecQFOyXCSufJxAdbx9B/WBnECXxp7qO4ecQLjQv82CjJxA2trgsMmRnED75AGUEJecQB3vIndXnJxAP/lDWp6hnEBgA2U95aacQIINhiAsrJxAoxenA3OxnEDFIcjmubacQOcr6ckAvJxACDYKrUfBnEAqQCuQjsacQEtKTHPVy5xAbVRtVhzRnECOXo45Y9acQLBorxyq25xA0nLQ//DgnEDzfPHiN+acQBWHEsZ+65xANpEzqcXwnEBYm1SMDPacQHqldW9T+5xAm6+WUpoAnUC9ubc14QWdQN7D2BgoC51AAM75+24QnUAi2BrftRWdQEPiO8L8Gp1AZexcpUMgnUCG9n2IiiWdQKgAn2vRKp1AygrAThgwnUDrFOExXzWdQA0fAhWmOp1ALikj+Ow/nUBQM0TbM0WdQHI9Zb56Sp1Ak0eGocFPnUC1UaeECFWdQNZbyGdPWp1A+GXpSpZfnUAacAou3WSdQDt6KxEkap1AXYRM9GpvnUB+jm3XsXSdQKCYjrr4eZ1AwaKvnT9/nUDjrNCAhoSdQAW38WPNiZ1AJsESRxSPnUBIyzMqW5SdQGnVVA2imZ1Ai9918OienUCt6ZbTL6SdQM7zt7Z2qZ1A8P3Ymb2unUARCPp8BLSdQDMSG2BLuZ1AVRw8Q5K+nUB2Jl0m2cOdQJgwfgkgyZ1AuTqf7GbOnUDbRMDPrdOdQP1O4bL02J1AHlkCljvenUBAYyN5guOdQGFtRFzJ6J1Ag3dlPxDunUClgYYiV/OdQMaLpwWe+J1A6JXI6OT9nUAJoOnLKwOeQCuqCq9yCJ5ATbQrkrkNnkBuvkx1ABOeQJDIbVhHGJ5AsdKOO44dnkDT3K8e1SKeQPTm0AEcKJ5AFvHx5GItnkA4+xLIqTKeQFkFNKvwN55Aew9Vjjc9nkCcGXZxfkKeQL4jl1TFR55A4C24NwxNnkABONkaU1KeQCNC+v2ZV55AREwb4eBcnkBmVjzEJ2KeQIhgXaduZ55AqWp+irVsnkDLdJ9t/HGeQOx+wFBDd55ADonhM4p8nkAwkwIX0YGeQFGdI/oXh55Ac6dE3V6MnkCUsWXApZGeQLa7hqPslp5A2MWnhjOcnkD5z8hpeqGeQBva6UzBpp5APOQKMAisnkBe7isTT7GeQID4TPaVtp5AoQJu2dy7nkDDDI+8I8GeQOQWsJ9qxp5ABiHRgrHLnkAnK/Jl+NCeQEk1E0k/1p5Aaz80LIbbnkCMSVUPzeCeQK5TdvIT5p5Az12X1VrrnkDxZ7i4ofCeQBNy2Zvo9Z5ANHz6fi/7nkBWhhtidgCfQHeQPEW9BZ9AmZpdKAQLn0C7pH4LSxCfQNyun+6RFZ9A/rjA0dgan0Afw+G0HyCfQEHNAphmJZ9AY9cje60qn0CE4URe9C+fQKbrZUE7NZ9Ax/WGJII6n0Dp/6cHyT+fQAsKyeoPRZ9ALBTqzVZKn0BOHguxnU+fQG8oLJTkVJ9AkTJNdytan0CzPG5acl+fQNRGjz25ZJ9A9lCwIABqn0AXW9EDR2+fQDll8uaNdJ9AWm8TytR5n0B8eTStG3+fQJ6DVZBihJ9Av412c6mJn0Dhl5dW8I6fQAKiuDk3lJ9AJKzZHH6Zn0BGtvr/xJ6fQGfAG+MLpJ9Aico8xlKpn0Cq1F2pma6fQMzefozgs59A7uifbye5n0AP88BSbr6fQA==\",\"dtype\":\"float64\",\"shape\":[1541]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1541]}}},\"id\":\"2f5b22ec-f28e-48b0-9a58-e02c5d50840a\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"684cddb7-08fd-4aca-9d31-f3ddcfb87427\",\"type\":\"GlyphRenderer\"}]},\"id\":\"74673ba6-4d43-4a02-9f90-49f81c93758d\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"9df61517-bc7e-4a30-b71f-1c57b173e1d2\",\"type\":\"BasicTicker\"}],\"root_ids\":[\"bb4351f0-e69f-4fd1-8a05-06b756766faa\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"22794440-b6ba-4719-be10-9884bcbe7e3b\",\"elementid\":\"3085c291-ea1a-43fe-bee7-bd90904b1eac\",\"modelid\":\"bb4351f0-e69f-4fd1-8a05-06b756766faa\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"3085c291-ea1a-43fe-bee7-bd90904b1eac\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 50.0 - Grados: 16.0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"7af7ea14-036d-4293-9bb3-20ac91a4e5cb\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"7af7ea14-036d-4293-9bb3-20ac91a4e5cb\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"7af7ea14-036d-4293-9bb3-20ac91a4e5cb\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '7af7ea14-036d-4293-9bb3-20ac91a4e5cb' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"eadeb3c9-3e37-4234-a0cd-ded823cfc331\":{\"roots\":{\"references\":[{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"3938cc9f-9533-4ed1-9939-c16fa0850ece\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"2eea090d-489e-4757-80e9-99785c6a93a9\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d369d8fa-b702-4815-b1e5-abe4e0db731f\",\"type\":\"BasicTicker\"}},\"id\":\"fff21edd-5909-4f9f-889e-f8c10053cbf3\",\"type\":\"LinearAxis\"},{\"attributes\":{\"callback\":null},\"id\":\"b73bf044-2e2a-485c-9168-4d19ec875f7e\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"068c9c6b-78ff-4f1c-8a1a-15107ce7bec5\",\"type\":\"SaveTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"ba0eb0f0-17ec-4865-a50b-53e7e40104da\",\"type\":\"BasicTicker\"}},\"id\":\"585258ff-ff70-4c53-83f8-b75b19157392\",\"type\":\"Grid\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"2efa713d-db44-4ace-9f59-61841e3632c9\",\"type\":\"GlyphRenderer\"}]},\"id\":\"68eebb20-16ad-4e3c-aadf-96a6c690c08c\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"cb2867cc-5e11-45f7-83c1-c529ed347c6c\",\"type\":\"ToolEvents\"},{\"attributes\":{\"data_source\":{\"id\":\"f8ff9696-9ac6-4743-8c48-977ce17ca3e8\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"7cec5d6f-928b-4957-bea1-b8fbb9cffe4f\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"e4f78a84-0b69-44e6-bbeb-147ffc6278a6\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"2efa713d-db44-4ace-9f59-61841e3632c9\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"ba0eb0f0-17ec-4865-a50b-53e7e40104da\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"1b631193-529b-4422-9673-142444b6b1ae\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e9285b20-43ef-4173-bc51-2cb48b0f1c31\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"2eea090d-489e-4757-80e9-99785c6a93a9\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"40de8d83-88ca-4565-8075-d05775d0ac5d\",\"type\":\"VeeHead\"},\"line_color\":{\"value\":\"blue\"},\"line_dash\":[2,4,6,4],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":1375.3305737562068},\"x_start\":{\"value\":1375.3305737562068},\"y_end\":{\"value\":0},\"y_start\":{\"value\":50.95400873072095}},\"id\":\"a071a66b-e241-4104-8d68-f59a90174bf9\",\"type\":\"Arrow\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":101.9080174614419,\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"d0742324-4c6e-4f6c-afa5-7b74c03826c9\",\"type\":\"Span\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"e4f78a84-0b69-44e6-bbeb-147ffc6278a6\",\"type\":\"Line\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"6e0efd22-219e-49d7-a46f-403ff7293d2b\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"items\":[{\"id\":\"68eebb20-16ad-4e3c-aadf-96a6c690c08c\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2d9819db-7f64-434d-89d6-d0ed9d20f590\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"d369d8fa-b702-4815-b1e5-abe4e0db731f\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7db2437c-365d-45c8-a1e3-bc22bac6241d\",\"type\":\"PanTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[571]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[571]}}},\"id\":\"f8ff9696-9ac6-4743-8c48-977ce17ca3e8\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"below\":[{\"id\":\"fff21edd-5909-4f9f-889e-f8c10053cbf3\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"99ec9e02-a86e-4d75-a256-e0f4cdf84953\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"fff21edd-5909-4f9f-889e-f8c10053cbf3\",\"type\":\"LinearAxis\"},{\"id\":\"143738ae-2913-4a70-b26f-df5175476f34\",\"type\":\"Grid\"},{\"id\":\"99ec9e02-a86e-4d75-a256-e0f4cdf84953\",\"type\":\"LinearAxis\"},{\"id\":\"585258ff-ff70-4c53-83f8-b75b19157392\",\"type\":\"Grid\"},{\"id\":\"6e0efd22-219e-49d7-a46f-403ff7293d2b\",\"type\":\"BoxAnnotation\"},{\"id\":\"2d9819db-7f64-434d-89d6-d0ed9d20f590\",\"type\":\"Legend\"},{\"id\":\"2efa713d-db44-4ace-9f59-61841e3632c9\",\"type\":\"GlyphRenderer\"},{\"id\":\"4d646b11-de0f-4df9-b929-f94b9bcbb04c\",\"type\":\"Arrow\"},{\"id\":\"d0742324-4c6e-4f6c-afa5-7b74c03826c9\",\"type\":\"Span\"},{\"id\":\"a071a66b-e241-4104-8d68-f59a90174bf9\",\"type\":\"Arrow\"}],\"title\":{\"id\":\"1015af39-294a-4ea4-85fe-b811ebdf6e20\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"cb2867cc-5e11-45f7-83c1-c529ed347c6c\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"367a24d3-6b58-4b5a-b32a-d0f3e0f56584\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"b73bf044-2e2a-485c-9168-4d19ec875f7e\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"0e9d4f28-f7a0-47f3-a787-01d0a825dd9e\",\"type\":\"DataRange1d\"}},\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"callback\":null},\"id\":\"0e9d4f28-f7a0-47f3-a787-01d0a825dd9e\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"0ce736ed-63d2-4153-a87e-77a53fdad90e\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"7cec5d6f-928b-4957-bea1-b8fbb9cffe4f\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"0ce736ed-63d2-4153-a87e-77a53fdad90e\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"ba0eb0f0-17ec-4865-a50b-53e7e40104da\",\"type\":\"BasicTicker\"}},\"id\":\"99ec9e02-a86e-4d75-a256-e0f4cdf84953\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d369d8fa-b702-4815-b1e5-abe4e0db731f\",\"type\":\"BasicTicker\"}},\"id\":\"143738ae-2913-4a70-b26f-df5175476f34\",\"type\":\"Grid\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"7db2437c-365d-45c8-a1e3-bc22bac6241d\",\"type\":\"PanTool\"},{\"id\":\"3938cc9f-9533-4ed1-9939-c16fa0850ece\",\"type\":\"WheelZoomTool\"},{\"id\":\"b3f5d80e-8f41-4cce-9094-e65c6dd7b306\",\"type\":\"BoxZoomTool\"},{\"id\":\"068c9c6b-78ff-4f1c-8a1a-15107ce7bec5\",\"type\":\"SaveTool\"},{\"id\":\"e9285b20-43ef-4173-bc51-2cb48b0f1c31\",\"type\":\"ResetTool\"},{\"id\":\"1b631193-529b-4422-9673-142444b6b1ae\",\"type\":\"HelpTool\"}]},\"id\":\"367a24d3-6b58-4b5a-b32a-d0f3e0f56584\",\"type\":\"Toolbar\"},{\"attributes\":{\"plot\":null,\"size\":5},\"id\":\"40de8d83-88ca-4565-8075-d05775d0ac5d\",\"type\":\"VeeHead\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"0e090b60-7886-4fae-96b7-8dfc525a5cc3\",\"type\":\"OpenHead\"},{\"attributes\":{\"overlay\":{\"id\":\"6e0efd22-219e-49d7-a46f-403ff7293d2b\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b3f5d80e-8f41-4cce-9094-e65c6dd7b306\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"end\":{\"id\":\"0e090b60-7886-4fae-96b7-8dfc525a5cc3\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":1369.8},\"x_start\":{\"value\":1369.8},\"y_end\":{\"value\":0},\"y_start\":{\"value\":50.95400873072095}},\"id\":\"4d646b11-de0f-4df9-b929-f94b9bcbb04c\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 1369.8 \"},\"id\":\"1015af39-294a-4ea4-85fe-b811ebdf6e20\",\"type\":\"Title\"}],\"root_ids\":[\"d1a5e4bc-232b-4498-a27e-dc100b98a284\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"eadeb3c9-3e37-4234-a0cd-ded823cfc331\",\"elementid\":\"7af7ea14-036d-4293-9bb3-20ac91a4e5cb\",\"modelid\":\"d1a5e4bc-232b-4498-a27e-dc100b98a284\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"7af7ea14-036d-4293-9bb3-20ac91a4e5cb\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 21.0 - Grados: 71.0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"56c2e36c-75bf-4a03-8cdf-344307fb76c5\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"56c2e36c-75bf-4a03-8cdf-344307fb76c5\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"56c2e36c-75bf-4a03-8cdf-344307fb76c5\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '56c2e36c-75bf-4a03-8cdf-344307fb76c5' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"3f64b4e8-8a51-4954-b767-666e6c4942df\":{\"roots\":{\"references\":[{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"7d3e9dd5-d38f-4bbb-aefa-b68a85d87bab\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"3f1340c6-4f8e-4f21-8b28-b35aa8f8c713\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1eed620a-de42-4796-b995-93dcf752a28b\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"542dad70-46e1-48b7-8df8-69a7a7474e0b\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fb5ea035-0aa7-4e78-ba26-88894e77da81\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"bbc38de2-aa13-4972-b014-d0e4a1095e8d\",\"type\":\"BasicTicker\"}},\"id\":\"ca196172-a4d2-49c9-b77a-5bd981d37205\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b683e110-c99a-401f-9ce8-06037d534021\",\"type\":\"SaveTool\"},{\"attributes\":{\"data_source\":{\"id\":\"41542e8a-abdb-40a4-97ec-a3de2c0057c7\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"7d3e9dd5-d38f-4bbb-aefa-b68a85d87bab\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"89fbaaa9-314e-4391-a06e-4103909de757\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"eb77b1b7-e7bd-43fc-bb1e-2934596215fd\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 277.58 \"},\"id\":\"e861dcda-512c-42b0-8c67-6ca611761bc0\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"89e68423-d1dd-407b-a474-8a10184b5413\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"1eed620a-de42-4796-b995-93dcf752a28b\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"89e68423-d1dd-407b-a474-8a10184b5413\",\"type\":\"BasicTicker\"}},\"id\":\"76d23b43-3826-4e1b-8dfe-761ab65379d4\",\"type\":\"LinearAxis\"},{\"attributes\":{\"callback\":null},\"id\":\"f369ebae-b20b-433d-9334-f5966ae4142d\",\"type\":\"DataRange1d\"},{\"attributes\":{\"overlay\":{\"id\":\"9cf6c8e9-fbee-42f1-b96e-d8a8c799fffe\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0a4ab05a-3216-4c9c-a634-3d5f6cbb7192\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"800ef325-951a-489f-8b6a-ea9b77cf8617\",\"type\":\"PanTool\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"89e68423-d1dd-407b-a474-8a10184b5413\",\"type\":\"BasicTicker\"}},\"id\":\"d0a1b8c6-1861-44c9-9c2e-b2f72b722942\",\"type\":\"Grid\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"800ef325-951a-489f-8b6a-ea9b77cf8617\",\"type\":\"PanTool\"},{\"id\":\"fb5ea035-0aa7-4e78-ba26-88894e77da81\",\"type\":\"WheelZoomTool\"},{\"id\":\"0a4ab05a-3216-4c9c-a634-3d5f6cbb7192\",\"type\":\"BoxZoomTool\"},{\"id\":\"b683e110-c99a-401f-9ce8-06037d534021\",\"type\":\"SaveTool\"},{\"id\":\"542dad70-46e1-48b7-8df8-69a7a7474e0b\",\"type\":\"ResetTool\"},{\"id\":\"ad4864cd-1803-4600-8e33-7e61b287cd1b\",\"type\":\"HelpTool\"}]},\"id\":\"16d85ee7-2bc4-4286-8dc0-deb6e573ca09\",\"type\":\"Toolbar\"},{\"attributes\":{\"below\":[{\"id\":\"76d23b43-3826-4e1b-8dfe-761ab65379d4\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"b2c07350-1453-45f8-a23c-2bde74a2e220\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"76d23b43-3826-4e1b-8dfe-761ab65379d4\",\"type\":\"LinearAxis\"},{\"id\":\"d0a1b8c6-1861-44c9-9c2e-b2f72b722942\",\"type\":\"Grid\"},{\"id\":\"b2c07350-1453-45f8-a23c-2bde74a2e220\",\"type\":\"LinearAxis\"},{\"id\":\"ca196172-a4d2-49c9-b77a-5bd981d37205\",\"type\":\"Grid\"},{\"id\":\"9cf6c8e9-fbee-42f1-b96e-d8a8c799fffe\",\"type\":\"BoxAnnotation\"},{\"id\":\"fdcd1abb-a9a0-4aa6-935e-33a9bd874b90\",\"type\":\"Legend\"},{\"id\":\"eb77b1b7-e7bd-43fc-bb1e-2934596215fd\",\"type\":\"GlyphRenderer\"},{\"id\":\"100ea974-e02a-4931-98a9-27f85a3a89f8\",\"type\":\"Arrow\"},{\"id\":\"7fa7f22b-8585-4e18-b0db-82dde77099f7\",\"type\":\"Span\"},{\"id\":\"a6c0a771-5643-4109-b432-9689396c3ca2\",\"type\":\"Arrow\"}],\"title\":{\"id\":\"e861dcda-512c-42b0-8c67-6ca611761bc0\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"ca4277c1-2d5c-4120-ac26-27ddc57d2418\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"16d85ee7-2bc4-4286-8dc0-deb6e573ca09\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"f369ebae-b20b-433d-9334-f5966ae4142d\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"3f1340c6-4f8e-4f21-8b28-b35aa8f8c713\",\"type\":\"DataRange1d\"}},\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"6736198d-ad34-4e41-8fcf-65a5078ef7c0\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"bbc38de2-aa13-4972-b014-d0e4a1095e8d\",\"type\":\"BasicTicker\"}},\"id\":\"b2c07350-1453-45f8-a23c-2bde74a2e220\",\"type\":\"LinearAxis\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"9cf6c8e9-fbee-42f1-b96e-d8a8c799fffe\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[813]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[813]}}},\"id\":\"41542e8a-abdb-40a4-97ec-a3de2c0057c7\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"89fbaaa9-314e-4391-a06e-4103909de757\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"bbc38de2-aa13-4972-b014-d0e4a1095e8d\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ad4864cd-1803-4600-8e33-7e61b287cd1b\",\"type\":\"HelpTool\"},{\"attributes\":{\"items\":[{\"id\":\"49772f2b-4ed7-48b2-a175-46f59bf77e9d\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fdcd1abb-a9a0-4aa6-935e-33a9bd874b90\",\"type\":\"Legend\"},{\"attributes\":{\"end\":{\"id\":\"204e575b-5d6d-47b9-9f73-f59a6ebe849b\",\"type\":\"VeeHead\"},\"line_color\":{\"value\":\"blue\"},\"line_dash\":[2,4,6,4],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":271.86701789844454},\"x_start\":{\"value\":271.86701789844454},\"y_end\":{\"value\":0},\"y_start\":{\"value\":101.07557463680472}},\"id\":\"a6c0a771-5643-4109-b432-9689396c3ca2\",\"type\":\"Arrow\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"eb77b1b7-e7bd-43fc-bb1e-2934596215fd\",\"type\":\"GlyphRenderer\"}]},\"id\":\"49772f2b-4ed7-48b2-a175-46f59bf77e9d\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"6736198d-ad34-4e41-8fcf-65a5078ef7c0\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"f1fa89e3-d1a4-45e3-adab-7f8e42f08b59\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":277.58},\"x_start\":{\"value\":277.58},\"y_end\":{\"value\":0},\"y_start\":{\"value\":101.07557463680472}},\"id\":\"100ea974-e02a-4931-98a9-27f85a3a89f8\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"f1fa89e3-d1a4-45e3-adab-7f8e42f08b59\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":null,\"size\":5},\"id\":\"204e575b-5d6d-47b9-9f73-f59a6ebe849b\",\"type\":\"VeeHead\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":202.15114927360943,\"plot\":{\"id\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7fa7f22b-8585-4e18-b0db-82dde77099f7\",\"type\":\"Span\"},{\"attributes\":{},\"id\":\"ca4277c1-2d5c-4120-ac26-27ddc57d2418\",\"type\":\"ToolEvents\"}],\"root_ids\":[\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"3f64b4e8-8a51-4954-b767-666e6c4942df\",\"elementid\":\"56c2e36c-75bf-4a03-8cdf-344307fb76c5\",\"modelid\":\"31a1ac9b-26b2-40df-8b63-4be86685c0c2\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"56c2e36c-75bf-4a03-8cdf-344307fb76c5\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 11.0 - Grados: 45.0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"4fea5662-68c7-49c3-b741-834ac34d5162\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"4fea5662-68c7-49c3-b741-834ac34d5162\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"4fea5662-68c7-49c3-b741-834ac34d5162\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '4fea5662-68c7-49c3-b741-834ac34d5162' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"83b03a03-1c8c-4b55-b2a3-88a6d28aa171\":{\"roots\":{\"references\":[{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6e065a4c-0193-404e-bcfa-f6ca4707ff9e\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"bd92c6a3-1edc-45a4-842e-2b7dc421c4e0\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"end\":{\"id\":\"2038bd88-75ff-45c7-904d-452b7862dbf5\",\"type\":\"VeeHead\"},\"line_color\":{\"value\":\"blue\"},\"line_dash\":[2,4,6,4],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":117.33587173511205},\"x_start\":{\"value\":117.33587173511205},\"y_end\":{\"value\":0},\"y_start\":{\"value\":16.433631507381783}},\"id\":\"5800704c-3a41-464c-af6c-634b0daa0308\",\"type\":\"Arrow\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"7af84105-a588-4b7d-8267-0e04803448aa\",\"type\":\"PanTool\"},{\"id\":\"f56d2adb-ad0c-4984-9b7f-cfa78d3c7e2a\",\"type\":\"WheelZoomTool\"},{\"id\":\"e1b123bc-5edb-4e24-b7f0-cf1aa98b49c3\",\"type\":\"BoxZoomTool\"},{\"id\":\"5270c289-2f3f-42d4-bd88-1c88fd517a2b\",\"type\":\"SaveTool\"},{\"id\":\"74e8d1f2-94f1-4bbf-8b07-b05e4d472051\",\"type\":\"ResetTool\"},{\"id\":\"8945ff80-9ac8-41db-ac11-778ad1cb3343\",\"type\":\"HelpTool\"}]},\"id\":\"df3eefd1-83c0-4b61-bc90-ed8b0431db47\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"72313420-faad-4dfe-9c9d-d6b7cc37b992\",\"type\":\"ToolEvents\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6a17d715-c9ee-4d8d-93d4-777676d63cd5\",\"type\":\"BasicTicker\"}},\"id\":\"55ae4b34-7e37-4ebc-b686-00ad6376b593\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 125.62 \"},\"id\":\"ec8c791c-763e-47fa-913f-0cc8c9e2b44c\",\"type\":\"Title\"},{\"attributes\":{\"end\":{\"id\":\"8cd2b671-65a2-4b3d-b6b3-30ec4a4c5b91\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":125.62},\"x_start\":{\"value\":125.62},\"y_end\":{\"value\":0},\"y_start\":{\"value\":16.433631507381783}},\"id\":\"11043236-b4ee-483a-ab66-568f80d403d8\",\"type\":\"Arrow\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"1fb3f7df-f1f8-4b61-b977-304245c8565e\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b714a70a-c175-41bb-ab79-f8fb60cada8d\",\"type\":\"BasicTicker\"}},\"id\":\"a9d2f9c2-6ae4-4777-89a0-10ecf7f4cf6d\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8945ff80-9ac8-41db-ac11-778ad1cb3343\",\"type\":\"HelpTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[324]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[324]}}},\"id\":\"18324f8b-aec2-4764-9e91-99947d7eedda\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"49011c96-3306-404e-8d41-1d901702c34f\",\"type\":\"GlyphRenderer\"}]},\"id\":\"aaa02f30-1f30-4bae-92c2-19740ee646b5\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"b714a70a-c175-41bb-ab79-f8fb60cada8d\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b714a70a-c175-41bb-ab79-f8fb60cada8d\",\"type\":\"BasicTicker\"}},\"id\":\"49340f10-6064-4d72-87ae-a28dd440a47e\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"6a17d715-c9ee-4d8d-93d4-777676d63cd5\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"b0b104e0-42c9-44e0-a59c-6d1deac860ff\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1fb3f7df-f1f8-4b61-b977-304245c8565e\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":32.867263014763566,\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f7a83014-adb3-413e-b3c0-99df641a49b1\",\"type\":\"Span\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"5270c289-2f3f-42d4-bd88-1c88fd517a2b\",\"type\":\"SaveTool\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"bd92c6a3-1edc-45a4-842e-2b7dc421c4e0\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6a17d715-c9ee-4d8d-93d4-777676d63cd5\",\"type\":\"BasicTicker\"}},\"id\":\"06166bad-3020-4c4c-9c13-b84552cd9d59\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":null,\"size\":5},\"id\":\"2038bd88-75ff-45c7-904d-452b7862dbf5\",\"type\":\"VeeHead\"},{\"attributes\":{\"below\":[{\"id\":\"a9d2f9c2-6ae4-4777-89a0-10ecf7f4cf6d\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"06166bad-3020-4c4c-9c13-b84552cd9d59\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"a9d2f9c2-6ae4-4777-89a0-10ecf7f4cf6d\",\"type\":\"LinearAxis\"},{\"id\":\"49340f10-6064-4d72-87ae-a28dd440a47e\",\"type\":\"Grid\"},{\"id\":\"06166bad-3020-4c4c-9c13-b84552cd9d59\",\"type\":\"LinearAxis\"},{\"id\":\"55ae4b34-7e37-4ebc-b686-00ad6376b593\",\"type\":\"Grid\"},{\"id\":\"85375f0f-b99e-4b76-ad91-0fd68b81ccd1\",\"type\":\"BoxAnnotation\"},{\"id\":\"196a68b5-fd9e-4bd9-9943-9df353f44377\",\"type\":\"Legend\"},{\"id\":\"49011c96-3306-404e-8d41-1d901702c34f\",\"type\":\"GlyphRenderer\"},{\"id\":\"11043236-b4ee-483a-ab66-568f80d403d8\",\"type\":\"Arrow\"},{\"id\":\"f7a83014-adb3-413e-b3c0-99df641a49b1\",\"type\":\"Span\"},{\"id\":\"5800704c-3a41-464c-af6c-634b0daa0308\",\"type\":\"Arrow\"}],\"title\":{\"id\":\"ec8c791c-763e-47fa-913f-0cc8c9e2b44c\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"72313420-faad-4dfe-9c9d-d6b7cc37b992\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"df3eefd1-83c0-4b61-bc90-ed8b0431db47\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"ca8e3fe6-9c56-4e37-b0c8-c76c544471a1\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"b0b104e0-42c9-44e0-a59c-6d1deac860ff\",\"type\":\"DataRange1d\"}},\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"74e8d1f2-94f1-4bbf-8b07-b05e4d472051\",\"type\":\"ResetTool\"},{\"attributes\":{\"data_source\":{\"id\":\"18324f8b-aec2-4764-9e91-99947d7eedda\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"945e2c65-0fb8-4fad-b0f2-878d70386c76\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"6e065a4c-0193-404e-bcfa-f6ca4707ff9e\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"49011c96-3306-404e-8d41-1d901702c34f\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"overlay\":{\"id\":\"85375f0f-b99e-4b76-ad91-0fd68b81ccd1\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e1b123bc-5edb-4e24-b7f0-cf1aa98b49c3\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"85375f0f-b99e-4b76-ad91-0fd68b81ccd1\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"8cd2b671-65a2-4b3d-b6b3-30ec4a4c5b91\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f56d2adb-ad0c-4984-9b7f-cfa78d3c7e2a\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"7af84105-a588-4b7d-8267-0e04803448aa\",\"type\":\"PanTool\"},{\"attributes\":{\"callback\":null},\"id\":\"ca8e3fe6-9c56-4e37-b0c8-c76c544471a1\",\"type\":\"DataRange1d\"},{\"attributes\":{\"items\":[{\"id\":\"aaa02f30-1f30-4bae-92c2-19740ee646b5\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"196a68b5-fd9e-4bd9-9943-9df353f44377\",\"type\":\"Legend\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"945e2c65-0fb8-4fad-b0f2-878d70386c76\",\"type\":\"Line\"}],\"root_ids\":[\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"83b03a03-1c8c-4b55-b2a3-88a6d28aa171\",\"elementid\":\"4fea5662-68c7-49c3-b741-834ac34d5162\",\"modelid\":\"fa96ada1-96a5-4b9c-9d75-0de0f1b52822\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"4fea5662-68c7-49c3-b741-834ac34d5162\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Velocidad: 36.0 - Grados: 20.0 - Gravedad: 9.8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"d2501f9a-d6f4-48c0-8e1c-2ef7efb7164f\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"d2501f9a-d6f4-48c0-8e1c-2ef7efb7164f\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"d2501f9a-d6f4-48c0-8e1c-2ef7efb7164f\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'd2501f9a-d6f4-48c0-8e1c-2ef7efb7164f' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"afa9de5d-6a73-4540-8169-bf755fc96124\":{\"roots\":{\"references\":[{\"attributes\":{\"items\":[{\"id\":\"13fc9d6b-7008-4787-ab80-10e6003309d3\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e48030ed-d337-4a58-ad4a-78916fffa1e8\",\"type\":\"Legend\"},{\"attributes\":{\"end\":{\"id\":\"d0ccc52e-8860-4241-8988-9787da275cde\",\"type\":\"OpenHead\"},\"line_color\":{\"value\":\"green\"},\"line_dash\":[6],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":860.95},\"x_start\":{\"value\":860.95},\"y_end\":{\"value\":0},\"y_start\":{\"value\":40.67423787726856}},\"id\":\"cf1919f0-9efe-4e96-8953-5ead87accd2a\",\"type\":\"Arrow\"},{\"attributes\":{\"line_color\":{\"value\":\"orange\"},\"line_dash\":[2,4],\"line_width\":{\"value\":1.5},\"location\":81.34847575453712,\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ba9a4858-409c-4253-9025-5d98667caf5b\",\"type\":\"Span\"},{\"attributes\":{\"axis_label\":\"Distancia - Metros\",\"formatter\":{\"id\":\"b5b86e54-c0c9-4b02-8e33-5e019428b487\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6997d72b-fdc6-4caa-9ca9-3b25d3d561f0\",\"type\":\"BasicTicker\"}},\"id\":\"cfa409cc-c11d-4579-b00f-fc0cbe0dc986\",\"type\":\"LinearAxis\"},{\"attributes\":{\"end\":{\"id\":\"63c84056-a341-49cc-8628-9d78258a048d\",\"type\":\"VeeHead\"},\"line_color\":{\"value\":\"blue\"},\"line_dash\":[2,4,6,4],\"line_width\":{\"value\":2},\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"source\":null,\"start\":null,\"x_end\":{\"value\":856.939226265276},\"x_start\":{\"value\":856.939226265276},\"y_end\":{\"value\":0},\"y_start\":{\"value\":40.67423787726856}},\"id\":\"ef8f7c1f-f2cc-4e8d-a7cc-3f93e3dcf081\",\"type\":\"Arrow\"},{\"attributes\":{\"plot\":null,\"size\":10},\"id\":\"d0ccc52e-8860-4241-8988-9787da275cde\",\"type\":\"OpenHead\"},{\"attributes\":{\"plot\":null,\"size\":5},\"id\":\"63c84056-a341-49cc-8628-9d78258a048d\",\"type\":\"VeeHead\"},{\"attributes\":{},\"id\":\"b5fe27bf-13e8-4a57-ae08-c8511d092a70\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"callback\":null},\"id\":\"e4c5f56b-1eae-4078-ae85-65eb22492cfc\",\"type\":\"DataRange1d\"},{\"attributes\":{\"label\":{\"value\":\"Trayectoria\"},\"renderers\":[{\"id\":\"53aceed1-28df-4a9a-b6dd-7d5855de895e\",\"type\":\"GlyphRenderer\"}]},\"id\":\"13fc9d6b-7008-4787-ab80-10e6003309d3\",\"type\":\"LegendItem\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[510]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[510]}}},\"id\":\"9b444216-9f34-4ef1-a73f-ff4173d97be4\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":null,\"text\":\"Impacto: 860.95 \"},\"id\":\"2574256c-fc87-4be1-a82e-84abd59d0d62\",\"type\":\"Title\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"9dc42bdc-1934-4fdb-ab0c-efaf959524e9\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"dd7fc51a-5966-41ce-9440-8888bdf0143c\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6997d72b-fdc6-4caa-9ca9-3b25d3d561f0\",\"type\":\"BasicTicker\"}},\"id\":\"fe0afbf4-345c-4b04-849f-fbed71f26e1c\",\"type\":\"Grid\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e189f199-8818-4ef5-a31a-8a2570bbd74c\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"6997d72b-fdc6-4caa-9ca9-3b25d3d561f0\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"Altura - Metros\",\"formatter\":{\"id\":\"b5fe27bf-13e8-4a57-ae08-c8511d092a70\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f7e2d629-6620-4800-b42d-e91a560938c3\",\"type\":\"BasicTicker\"}},\"id\":\"1151a2a6-ac4d-4c46-aa7b-91ce8ac2be80\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8a23f95b-1574-4e5d-9270-9157b9840f0d\",\"type\":\"ResetTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"f7e2d629-6620-4800-b42d-e91a560938c3\",\"type\":\"BasicTicker\"}},\"id\":\"59255283-087e-4749-b5d2-6ded48aea965\",\"type\":\"Grid\"},{\"attributes\":{\"below\":[{\"id\":\"cfa409cc-c11d-4579-b00f-fc0cbe0dc986\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"1151a2a6-ac4d-4c46-aa7b-91ce8ac2be80\",\"type\":\"LinearAxis\"}],\"plot_height\":200,\"plot_width\":750,\"renderers\":[{\"id\":\"cfa409cc-c11d-4579-b00f-fc0cbe0dc986\",\"type\":\"LinearAxis\"},{\"id\":\"fe0afbf4-345c-4b04-849f-fbed71f26e1c\",\"type\":\"Grid\"},{\"id\":\"1151a2a6-ac4d-4c46-aa7b-91ce8ac2be80\",\"type\":\"LinearAxis\"},{\"id\":\"59255283-087e-4749-b5d2-6ded48aea965\",\"type\":\"Grid\"},{\"id\":\"a7bd97b2-6b10-4268-ac5c-485808e2c46c\",\"type\":\"BoxAnnotation\"},{\"id\":\"e48030ed-d337-4a58-ad4a-78916fffa1e8\",\"type\":\"Legend\"},{\"id\":\"53aceed1-28df-4a9a-b6dd-7d5855de895e\",\"type\":\"GlyphRenderer\"},{\"id\":\"cf1919f0-9efe-4e96-8953-5ead87accd2a\",\"type\":\"Arrow\"},{\"id\":\"ba9a4858-409c-4253-9025-5d98667caf5b\",\"type\":\"Span\"},{\"id\":\"ef8f7c1f-f2cc-4e8d-a7cc-3f93e3dcf081\",\"type\":\"Arrow\"}],\"title\":{\"id\":\"2574256c-fc87-4be1-a82e-84abd59d0d62\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"c5265b92-dc36-41ea-9731-9d4683a69d01\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"92110b22-f01e-47cf-b2f0-27fe968355c1\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"2c15cd5d-a267-4283-8f29-f0600e5ad0ec\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"e4c5f56b-1eae-4078-ae85-65eb22492cfc\",\"type\":\"DataRange1d\"}},\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_color\":{\"value\":\"darkred\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"a65732f7-3b42-4050-8c84-3aa028b43dab\",\"type\":\"Line\"},{\"attributes\":{\"overlay\":{\"id\":\"a7bd97b2-6b10-4268-ac5c-485808e2c46c\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"d7cb9cd6-d135-45c2-8009-8a827ca0b558\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"f7e2d629-6620-4800-b42d-e91a560938c3\",\"type\":\"BasicTicker\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"a7bd97b2-6b10-4268-ac5c-485808e2c46c\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"c5265b92-dc36-41ea-9731-9d4683a69d01\",\"type\":\"ToolEvents\"},{\"attributes\":{\"data_source\":{\"id\":\"9b444216-9f34-4ef1-a73f-ff4173d97be4\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"a65732f7-3b42-4050-8c84-3aa028b43dab\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"9dc42bdc-1934-4fdb-ab0c-efaf959524e9\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"53aceed1-28df-4a9a-b6dd-7d5855de895e\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"125b3813-92b4-4034-ab21-79ed9183e43c\",\"type\":\"PanTool\"},{\"id\":\"e189f199-8818-4ef5-a31a-8a2570bbd74c\",\"type\":\"WheelZoomTool\"},{\"id\":\"d7cb9cd6-d135-45c2-8009-8a827ca0b558\",\"type\":\"BoxZoomTool\"},{\"id\":\"dd7fc51a-5966-41ce-9440-8888bdf0143c\",\"type\":\"SaveTool\"},{\"id\":\"8a23f95b-1574-4e5d-9270-9157b9840f0d\",\"type\":\"ResetTool\"},{\"id\":\"5396a809-a184-4ff2-a244-b8c2cdd64099\",\"type\":\"HelpTool\"}]},\"id\":\"92110b22-f01e-47cf-b2f0-27fe968355c1\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"2c15cd5d-a267-4283-8f29-f0600e5ad0ec\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"b5b86e54-c0c9-4b02-8e33-5e019428b487\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"5396a809-a184-4ff2-a244-b8c2cdd64099\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"5461e7f4-418a-4016-ab9d-25680449c483\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"125b3813-92b4-4034-ab21-79ed9183e43c\",\"type\":\"PanTool\"}],\"root_ids\":[\"5461e7f4-418a-4016-ab9d-25680449c483\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.5\"}};\n",
       "            var render_items = [{\"docid\":\"afa9de5d-6a73-4540-8169-bf755fc96124\",\"elementid\":\"d2501f9a-d6f4-48c0-8e1c-2ef7efb7164f\",\"modelid\":\"5461e7f4-418a-4016-ab9d-25680449c483\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"d2501f9a-d6f4-48c0-8e1c-2ef7efb7164f\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>altura</th>\n",
       "      <th>grados</th>\n",
       "      <th>gravedad</th>\n",
       "      <th>velocidad</th>\n",
       "      <th>predict</th>\n",
       "      <th>impacto</th>\n",
       "      <th>predict_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>55</td>\n",
       "      <td>9.8</td>\n",
       "      <td>46</td>\n",
       "      <td>2025.512727</td>\n",
       "      <td>2031.61</td>\n",
       "      <td>6.097273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>9.8</td>\n",
       "      <td>50</td>\n",
       "      <td>1375.330574</td>\n",
       "      <td>1369.80</td>\n",
       "      <td>-5.530574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>9.8</td>\n",
       "      <td>21</td>\n",
       "      <td>271.867018</td>\n",
       "      <td>277.58</td>\n",
       "      <td>5.712982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>9.8</td>\n",
       "      <td>11</td>\n",
       "      <td>117.335872</td>\n",
       "      <td>125.62</td>\n",
       "      <td>8.284128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>9.8</td>\n",
       "      <td>36</td>\n",
       "      <td>856.939226</td>\n",
       "      <td>860.95</td>\n",
       "      <td>4.010774</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   altura  grados  gravedad  velocidad      predict  impacto  predict_error\n",
       "0       2      55       9.8         46  2025.512727  2031.61       6.097273\n",
       "1       5      16       9.8         50  1375.330574  1369.80      -5.530574\n",
       "2       1      71       9.8         21   271.867018   277.58       5.712982\n",
       "3       2      45       9.8         11   117.335872   125.62       8.284128\n",
       "4       4      20       9.8         36   856.939226   860.95       4.010774"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gen_test(with_plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = gen_test(rows=10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mostramos los resultados de la calidad del moldelo en gráficas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112cdf978>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105c18f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(test_data[\"predict_error\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x112d9a198>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112d9a240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(test_data, vars=[\"predict_error\", \"impacto\", \"altura\", \"grados\", \"velocidad\",])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}