testBokeh.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook\n",
    "from bokeh.models import CustomJS, Spinner, ColumnDataSource, Arrow\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.layouts import column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"18505\">Loading BokehJS ...</span>\n",
       "    </div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\nconst JS_MIME_TYPE = 'application/javascript';\n  const HTML_MIME_TYPE = 'text/html';\n  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n  const CLASS_NAME = 'output_bokeh rendered_html';\n\n  /**\n   * Render data to the DOM node\n   */\n  function render(props, node) {\n    const script = document.createElement(\"script\");\n    node.appendChild(script);\n  }\n\n  /**\n   * Handle when an output is cleared or removed\n   */\n  function handleClearOutput(event, handle) {\n    const cell = handle.cell;\n\n    const id = cell.output_area._bokeh_element_id;\n    const server_id = cell.output_area._bokeh_server_id;\n    // Clean up Bokeh references\n    if (id != null && id in Bokeh.index) {\n      Bokeh.index[id].model.document.clear();\n      delete Bokeh.index[id];\n    }\n\n    if (server_id !== undefined) {\n      // Clean up Bokeh references\n      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n      cell.notebook.kernel.execute(cmd_clean, {\n        iopub: {\n          output: function(msg) {\n            const id = msg.content.text.trim();\n            if (id in Bokeh.index) {\n              Bokeh.index[id].model.document.clear();\n              delete Bokeh.index[id];\n            }\n          }\n        }\n      });\n      // Destroy server and session\n      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n      cell.notebook.kernel.execute(cmd_destroy);\n    }\n  }\n\n  /**\n   * Handle when a new output is added\n   */\n  function handleAddOutput(event, handle) {\n    const output_area = handle.output_area;\n    const output = handle.output;\n\n    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n      return\n    }\n\n    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n\n    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n      // store reference to embed id on output_area\n      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n    }\n    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n      const bk_div = document.createElement(\"div\");\n      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n      const script_attrs = bk_div.children[0].attributes;\n      for (let i = 0; i < script_attrs.length; i++) {\n        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n      }\n      // store reference to server id on output_area\n      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n    }\n  }\n\n  function register_renderer(events, OutputArea) {\n\n    function append_mime(data, metadata, element) {\n      // create a DOM node to render to\n      const toinsert = this.create_output_subarea(\n        metadata,\n        CLASS_NAME,\n        EXEC_MIME_TYPE\n      );\n      this.keyboard_manager.register_events(toinsert);\n      // Render to node\n      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n      render(props, toinsert[toinsert.length - 1]);\n      element.append(toinsert);\n      return toinsert\n    }\n\n    /* Handle when an output is cleared or removed */\n    events.on('clear_output.CodeCell', handleClearOutput);\n    events.on('delete.Cell', handleClearOutput);\n\n    /* Handle when a new output is added */\n    events.on('output_added.OutputArea', handleAddOutput);\n\n    /**\n     * Register the mime type and append_mime function with output_area\n     */\n    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n      /* Is output safe? */\n      safe: true,\n      /* Index of renderer in `output_area.display_order` */\n      index: 0\n    });\n  }\n\n  // register the mime type if in Jupyter Notebook environment and previously unregistered\n  if (root.Jupyter !== undefined) {\n    const events = require('base/js/events');\n    const OutputArea = require('notebook/js/outputarea').OutputArea;\n\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  }\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const 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    const el = document.getElementById(\"18505\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"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.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n          for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\nif (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(\"18505\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));",
      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div class=\"bk-root\" id=\"5bd38a77-8441-40d1-bb40-a238e2231d6a\" data-root-id=\"18552\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "(function(root) {\n  function embed_document(root) {\n  const docs_json = {\"3c0824ff-349b-43f2-b292-b1eb4d8376c6\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"18544\"},{\"id\":\"18545\"},{\"id\":\"18507\"}]},\"id\":\"18552\",\"type\":\"Column\"},{\"attributes\":{\"below\":[{\"id\":\"18516\"}],\"center\":[{\"id\":\"18519\"},{\"id\":\"18523\"},{\"id\":\"18548\"},{\"id\":\"18549\"},{\"id\":\"18550\"}],\"height\":400,\"left\":[{\"id\":\"18520\"}],\"renderers\":[{\"id\":\"18542\"}],\"title\":{\"id\":\"19298\"},\"toolbar\":{\"id\":\"18531\"},\"width\":400,\"x_range\":{\"id\":\"18508\"},\"x_scale\":{\"id\":\"18512\"},\"y_range\":{\"id\":\"18510\"},\"y_scale\":{\"id\":\"18514\"}},\"id\":\"18507\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"coordinates\":null,\"group\":null},\"id\":\"19298\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"19315\",\"type\":\"Selection\"},{\"attributes\":{\"args\":{\"source\":{\"id\":\"18506\"},\"spinner1\":{\"id\":\"18544\"},\"spinner2\":{\"id\":\"18545\"}},\"code\":\"\\n    source.data['x'] = [spinner1.value, 0, spinner1.value]\\n    source.data['y'] = [0, spinner2.value, spinner2.value]\\n    source.change.emit()\\n\"},\"id\":\"18546\",\"type\":\"CustomJS\"},{\"attributes\":{\"coordinates\":null,\"end\":{\"id\":\"19306\"},\"group\":null,\"source\":{\"id\":\"19307\"},\"start\":null,\"x_end\":{\"value\":1},\"x_start\":{\"value\":0},\"y_end\":{\"value\":0},\"y_start\":{\"value\":0}},\"id\":\"18548\",\"type\":\"Arrow\"},{\"attributes\":{\"coordinates\":null,\"end\":{\"id\":\"19308\"},\"group\":null,\"source\":{\"id\":\"19309\"},\"start\":null,\"x_end\":{\"value\":0},\"x_start\":{\"value\":0},\"y_end\":{\"value\":1},\"y_start\":{\"value\":0}},\"id\":\"18549\",\"type\":\"Arrow\"},{\"attributes\":{\"data\":{\"x\":[1,0,1],\"y\":[0,1,1]},\"selected\":{\"id\":\"19313\"},\"selection_policy\":{\"id\":\"19312\"}},\"id\":\"18506\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.6},\"line_color\":{\"value\":\"#1f77b4\"},\"line_width\":{\"value\":3},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"18539\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"18512\",\"type\":\"LinearScale\"},{\"attributes\":{\"source\":{\"id\":\"18506\"}},\"id\":\"18543\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"19301\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"19317\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"tools\":[{\"id\":\"18524\"},{\"id\":\"18525\"},{\"id\":\"18526\"},{\"id\":\"18527\"},{\"id\":\"18528\"},{\"id\":\"18529\"}]},\"id\":\"18531\",\"type\":\"Toolbar\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"19301\"},\"group\":null,\"major_label_policy\":{\"id\":\"19302\"},\"ticker\":{\"id\":\"18521\"}},\"id\":\"18520\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"18508\",\"type\":\"DataRange1d\"},{\"attributes\":{\"coordinates\":null,\"end\":{\"id\":\"19310\"},\"group\":null,\"source\":{\"id\":\"19311\"},\"start\":null,\"x_end\":{\"value\":1},\"x_start\":{\"value\":0},\"y_end\":{\"value\":1},\"y_start\":{\"value\":0}},\"id\":\"18550\",\"type\":\"Arrow\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"19304\"},\"group\":null,\"major_label_policy\":{\"id\":\"19305\"},\"ticker\":{\"id\":\"18517\"}},\"id\":\"18516\",\"type\":\"LinearAxis\"},{\"attributes\":{\"bottom_units\":\"screen\",\"coordinates\":null,\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"group\":null,\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"18530\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"19318\",\"type\":\"Selection\"},{\"attributes\":{\"js_property_callbacks\":{\"change:value\":[{\"id\":\"18546\"},{\"id\":\"18551\"}]},\"title\":\"Escalar 1\",\"value\":1,\"value_throttled\":1,\"width\":80},\"id\":\"18544\",\"type\":\"Spinner\"},{\"attributes\":{},\"id\":\"19304\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data\":{},\"selected\":{\"id\":\"19318\"},\"selection_policy\":{\"id\":\"19317\"}},\"id\":\"19307\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"18510\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"18514\",\"type\":\"LinearScale\"},{\"attributes\":{\"data\":{\"x_end\":[1],\"y_end\":[1]},\"selected\":{\"id\":\"19315\"},\"selection_policy\":{\"id\":\"19314\"}},\"id\":\"18547\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"18528\",\"type\":\"ResetTool\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"18506\"},\"glyph\":{\"id\":\"18539\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"18541\"},\"nonselection_glyph\":{\"id\":\"18540\"},\"view\":{\"id\":\"18543\"}},\"id\":\"18542\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"18517\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"19319\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"axis\":{\"id\":\"18516\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"18519\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"19310\",\"type\":\"OpenHead\"},{\"attributes\":{},\"id\":\"19320\",\"type\":\"Selection\"},{\"attributes\":{\"axis\":{\"id\":\"18520\"},\"coordinates\":null,\"dimension\":1,\"group\":null,\"ticker\":null},\"id\":\"18523\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"18521\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"19302\",\"type\":\"AllLabels\"},{\"attributes\":{\"js_property_callbacks\":{\"change:value\":[{\"id\":\"18546\"},{\"id\":\"18551\"}]},\"title\":\"Escalar 2\",\"value\":1,\"value_throttled\":1,\"width\":80},\"id\":\"18545\",\"type\":\"Spinner\"},{\"attributes\":{},\"id\":\"18529\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"19314\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"18525\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"19321\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"#1f77b4\"},\"hatch_alpha\":{\"value\":0.2},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"#1f77b4\"},\"line_width\":{\"value\":3},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"18541\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"18524\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"19305\",\"type\":\"AllLabels\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"hatch_alpha\":{\"value\":0.1},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"line_width\":{\"value\":3},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"18540\",\"type\":\"Circle\"},{\"attributes\":{\"data\":{},\"selected\":{\"id\":\"19322\"},\"selection_policy\":{\"id\":\"19321\"}},\"id\":\"19311\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"19322\",\"type\":\"Selection\"},{\"attributes\":{\"args\":{\"source\":{\"id\":\"18547\"},\"spinner1\":{\"id\":\"18544\"},\"spinner2\":{\"id\":\"18545\"}},\"code\":\"\\n    arrowSource.data['x_end'] = [spinner1.value]\\n    arrowSource.data['y_end'] = [spinner2.value]\\n    arrowSource.change.emit()\\n\"},\"id\":\"18551\",\"type\":\"CustomJS\"},{\"attributes\":{},\"id\":\"19306\",\"type\":\"OpenHead\"},{\"attributes\":{\"data\":{},\"selected\":{\"id\":\"19320\"},\"selection_policy\":{\"id\":\"19319\"}},\"id\":\"19309\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"19308\",\"type\":\"OpenHead\"},{\"attributes\":{},\"id\":\"19312\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"19313\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"18527\",\"type\":\"SaveTool\"},{\"attributes\":{\"overlay\":{\"id\":\"18530\"}},\"id\":\"18526\",\"type\":\"BoxZoomTool\"}],\"root_ids\":[\"18552\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.3\"}};\n  const render_items = [{\"docid\":\"3c0824ff-349b-43f2-b292-b1eb4d8376c6\",\"root_ids\":[\"18552\"],\"roots\":{\"18552\":\"5bd38a77-8441-40d1-bb40-a238e2231d6a\"}}];\n  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    let attempts = 0;\n    const timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "18552"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "source = ColumnDataSource(data=dict(x=[1,0,1], y=[0,1,1]))\n",
    "\n",
    "plot = figure(width=400, height=400)\n",
    "plot.circle('x', 'y', source=source, line_width=3, line_alpha=0.6)\n",
    "\n",
    "spinner1 = Spinner(value=1, step = 1, width=80, title=\"Escalar 1\")\n",
    "spinner2 = Spinner(value=1, step = 1, width=80, title=\"Escalar 2\")\n",
    "\n",
    "update_tamanho = CustomJS(args=dict(source=source, spinner1=spinner1, spinner2=spinner2), code=\"\"\"\n",
    "    source.data['x'] = [spinner1.value, 0, spinner1.value]\n",
    "    source.data['y'] = [0, spinner2.value, spinner2.value]\n",
    "    source.change.emit()\n",
    "\"\"\")\n",
    "\n",
    "arrowSource = ColumnDataSource(data=dict(x_end = [1], y_end = [1]))\n",
    "plot.add_layout(Arrow(x_start = 0, x_end = spinner1.value, y_start = 0, y_end = 0 ))\n",
    "plot.add_layout(Arrow(x_start = 0, x_end = 0, y_start = 0, y_end = spinner2.value))\n",
    "plot.add_layout(Arrow(x_start = 0, x_end = spinner1.value, y_start = 0, y_end = spinner2.value))\n",
    "\n",
    "update_arrow = CustomJS(args=dict(source=arrowSource, spinner1=spinner1, spinner2=spinner2), code=\"\"\"\n",
    "    arrowSource.data['x_end'] = [spinner1.value]\n",
    "    arrowSource.data['y_end'] = [spinner2.value]\n",
    "    arrowSource.change.emit()\n",
    "\"\"\")\n",
    "\n",
    "spinner2.js_on_change('value', update_tamanho)\n",
    "spinner1.js_on_change('value', update_tamanho)\n",
    "spinner2.js_on_change('value', update_arrow)\n",
    "spinner1.js_on_change('value', update_arrow)\n",
    "\n",
    "show(column(spinner1, spinner2, plot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "input1 = input(\"Escalar 1: \")\n",
    "input2 = input(\"Escalar 2: \")\n",
    "escalar1 = float(input1)\n",
    "escalar2 = float(input2)\n",
    "plt.arrow(0, 0, escalar1, 0, width = 0.04, color = 'red')\n",
    "plt.arrow(0, 0, 0, escalar2, width = 0.04, color = 'black')\n",
    "plt.arrow(0, 0, escalar1, escalar2, width = 0.04)\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}