Stumpy-Forecast.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65c4ebe7-1ea5-476b-b5cf-93fc228b1808",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
       "  var reloading = false;\n",
       "  var Bokeh = root.Bokeh;\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\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, js_modules, js_exports, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "    if (js_exports == null) js_exports = {};\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "\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.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    if (!reloading) {\n",
       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    }\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",
       "    window._bokeh_on_load = on_load\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"jspanel\"], function(jsPanel) {\n",
       "\twindow.jsPanel = jsPanel\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-modal\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-tooltip\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-hint\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-layout\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-contextmenu\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-dock\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 9;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
       "    }\n",
       "\n",
       "    var existing_stylesheets = []\n",
       "    var links = document.getElementsByTagName('link')\n",
       "    for (var i = 0; i < links.length; i++) {\n",
       "      var link = links[i]\n",
       "      if (link.href != null) {\n",
       "\texisting_stylesheets.push(link.href)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
       "\ton_load()\n",
       "\tcontinue;\n",
       "      }\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\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",
       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\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",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\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",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "\ttry {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "\t} catch(e) {\n",
       "\t  if (!reloading) {\n",
       "\t    throw e;\n",
       "\t  }\n",
       "\t}\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\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",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      if (!reloading && !bokeh_loaded) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\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, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\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.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\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    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\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    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\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    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\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  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n\ttry {\n          inline_js[i].call(root, root.Bokeh);\n\t} catch(e) {\n\t  if (!reloading) {\n\t    throw e;\n\t  }\n\t}\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\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    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
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       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || 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      }
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     "output_type": "display_data"
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   ],
   "source": [
    "import pandas as pd\n",
    "import stumpy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as dates\n",
    "from matplotlib.patches import Rectangle\n",
    "from matplotlib import animation\n",
    "from matplotlib.figure import Figure\n",
    "import matplotlib.gridspec as gridspec\n",
    "from IPython.display import HTML\n",
    "import os\n",
    "import datetime as dt\n",
    "import panel as pn\n",
    "\n",
    "pn.extension()\n",
    "\n",
    "plt.style.use('https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/stumpy.mplstyle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b50096d9-c003-405e-9001-c5e9d4e19985",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ed6f7ccf-f727-4cf5-80ee-7597890636a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/u1/Apps/anaconda3/envs/stumpy/lib/python3.10/site-packages/pandas/core/arraylike.py:396: RuntimeWarning: divide by zero encountered in log\n",
      "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "ticker= (\n",
    "    'BTCUSD' \n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "res = 'Day'\n",
    "# res = 'Week'\n",
    "# res = 'Month'\n",
    "# res = 'Quarter'\n",
    "# res = 'Year'\n",
    "\n",
    "exportPath = './'\n",
    "marketPath = './'\n",
    "imgPath = './'\n",
    "tmpPath = './'\n",
    "\n",
    "\n",
    "_df = pd.read_csv(marketPath + ticker + '.csv',parse_dates = True,index_col=0)\n",
    "\n",
    "if res == 'Day':\n",
    "    _df = _df.resample('D').mean() \n",
    "elif res == 'Week':\n",
    "    _df = _df.resample('W-MON').mean()    \n",
    "elif res == 'Month':\n",
    "    _df = _df.resample('MS').first()\n",
    "elif res == 'Quarter':\n",
    "    _df = _df.resample('Q').mean()    \n",
    "elif res == 'Year':\n",
    "    _df = _df.resample('Y').mean() \n",
    "\n",
    "\n",
    "_df['y'] = _df['close']\n",
    "\n",
    "\n",
    "def log_transform(df):\n",
    "    # copy the dataframe\n",
    "    tdf = df.copy()\n",
    "    # apply log scaling\n",
    "    for column in tdf.columns:\n",
    "        tdf[column] = np.log(tdf[column])\n",
    "\n",
    "    tdf.replace([np.inf, -np.inf], np.nan, inplace=True)\n",
    "    tdf = tdf.astype(float)\n",
    "    tdf = tdf.interpolate(method='linear', axis=0).ffill().bfill()\n",
    "#     tdf = tdf.dropna(axis='columns')\n",
    "    tdf = tdf.fillna(0)\n",
    "\n",
    "    return tdf\n",
    "\n",
    "def min_max_scaling(df):\n",
    "    # copy the dataframe\n",
    "    tdf = df.copy()\n",
    "    # apply min-max scaling\n",
    "    for column in tdf.columns:\n",
    "        tdf[column] = (tdf[column] - tdf[column].min()) / (tdf[column].max() - tdf[column].min())\n",
    "#     tdf = tdf.dropna(axis='columns')\n",
    "    tdf = tdf.fillna(0)\n",
    "    return tdf\n",
    "\n",
    "    \n",
    "_df = log_transform(_df)\n",
    "\n",
    "df_index = _df.index\n",
    "\n",
    "df = _df.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cff74cb0-2ab8-4eab-b3d0-1513e9f04629",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPX\n"
     ]
    }
   ],
   "source": [
    "def get_value(dictionary, key, default_value):\n",
    "    return dictionary.get(key, default_value)\n",
    "\n",
    "ticker_dict = {\n",
    "    # 'BTCUSD': 'GOLD', \n",
    "    # 'BTCUSD': 'NDX',\n",
    "    'BTCUSD': 'SPX',    \n",
    "}\n",
    "\n",
    "ticker1 = get_value(ticker_dict, ticker, None)\n",
    "print(ticker1)  # Output: 1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bc39c72d-62eb-45c1-bc2b-e18b8133704c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/u1/Apps/anaconda3/envs/stumpy/lib/python3.10/site-packages/pandas/core/arraylike.py:396: RuntimeWarning: divide by zero encountered in log\n",
      "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "res = 'Day'\n",
    "# res = 'Week'\n",
    "# res = 'Month'\n",
    "# res = 'Quarter'\n",
    "# res = 'Year'\n",
    "\n",
    "exportPath = './'\n",
    "marketPath = './'\n",
    "imgPath = './'\n",
    "tmpPath = './'\n",
    "\n",
    "\n",
    "# --------------------------------------------------------------------------------------------------------------------------------------------\n",
    "_df1 = pd.read_csv(marketPath + ticker1 + '.csv',parse_dates = True,index_col=0)\n",
    "    \n",
    "_df1 = log_transform(_df1)\n",
    "\n",
    "df1_index = _df1.index\n",
    "\n",
    "df1 = _df1.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e0eb8367-1882-44f5-b74c-41bcb480f74d",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.suptitle(ticker, fontsize='30')\n",
    "plt.xlabel('Time', fontsize ='20')\n",
    "plt.ylabel('Scale', fontsize='20')\n",
    "plt.plot(df['close'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d0af4007-299f-4e3e-a39c-944ca2af288c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/u1/Apps/anaconda3/envs/stumpy/lib/python3.10/site-packages/numba/cuda/dispatcher.py:536: NumbaPerformanceWarning: Grid size 11 will likely result in GPU under-utilization due to low occupancy.\n",
      "  warn(NumbaPerformanceWarning(msg))\n"
     ]
    }
   ],
   "source": [
    "mps = {}\n",
    "m = 119\n",
    "\n",
    "for colname in df.columns:\n",
    "    mps[colname] = stumpy.gpu_stump(\n",
    "    T_A = df['close'],\n",
    "    m = m,\n",
    "        \n",
    "    T_B = df1['close'],\n",
    "    ignore_trivial = False\n",
    ")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "44776bca-b84c-483f-a31f-0dd75f875bc0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5146\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
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1152px;&quot;&gt;&lt;/img&gt;\"}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"11771ffc-868f-4b02-ab83-fea00e898378\",\"attributes\":{\"plot_id\":\"18006acb-6da3-48a0-aaeb-24ef18457b27\",\"comm_id\":\"45fa93e0e33644be9ffa0f13c477ea1a\",\"client_comm_id\":\"4e4428f453d740238130df7c7e3cd67f\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"deed15a6-fbee-4887-931f-a0033d97f96a\",\"roots\":{\"18006acb-6da3-48a0-aaeb-24ef18457b27\":\"a2eee8cc-44ca-436e-b78a-ae612990a565\"},\"root_ids\":[\"18006acb-6da3-48a0-aaeb-24ef18457b27\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "Column\n",
       "    [0] Row\n",
       "        [0] Select(options=['close', 'high', ...], value='close', width=100)\n",
       "        [1] CheckButtonGroup(name='Normalize', options=['Z-Normalize'], value=['Z-Normalize'], width=100)\n",
       "        [2] TextInput(value='5146', width=100)\n",
       "        [3] IntSlider(end=10264, value=5146, width=800)\n",
       "    [1] Row\n",
       "        [0] Matplotlib(Figure)"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "18006acb-6da3-48a0-aaeb-24ef18457b27"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_idx_start = len(df)-m\n",
    "print(current_idx_start)\n",
    "subset_start_idx = []\n",
    "\n",
    "\n",
    "select_plot = pn.widgets.Select(name='', options=sorted(list(df1.columns)), width=100)\n",
    "normalize_btn = pn.widgets.CheckButtonGroup(name='Normalize', value=['Z-Normalize'], options=['Z-Normalize'], width=100)\n",
    "idx_slider = pn.widgets.IntSlider(value=0, start=0, end=len(df1), width=800)\n",
    "txt_input = pn.widgets.TextInput(value=\"0\", width=100)\n",
    "\n",
    "def display_raw(df1, mps, colname, m=m, idx=None):\n",
    "    fig = Figure(figsize=(18,8))\n",
    "    shared_spec = gridspec.GridSpec(3, 1, hspace=0)\n",
    "    unshared_spec = gridspec.GridSpec(3, 1)\n",
    "    raw_ax = fig.add_subplot(shared_spec[0, :])\n",
    "    mp_ax = fig.add_subplot(shared_spec[1, :], sharex=raw_ax)\n",
    "    overlap_ax = fig.add_subplot(unshared_spec[2, :])\n",
    "    \n",
    "    raw_ax.plot(df1[colname])\n",
    "    \n",
    "    mp = mps[colname]\n",
    "    mp_ax.plot(mp[:, 0])\n",
    "    \n",
    "    if idx is None:\n",
    "        # idx = int(np.argsort(mp[:, 0])[0])\n",
    "        idx = current_idx_start\n",
    "    nn_idx = mp[:, 1][idx]\n",
    "    distance = mp[idx, 0]\n",
    "    subset_start_idx.append(nn_idx)\n",
    "    \n",
    "    idx_slider.value = idx\n",
    "    txt_input.value = str(idx)\n",
    "    \n",
    "    y_midpoint = (raw_ax.get_ylim()[1] + raw_ax.get_ylim()[0]) / 2\n",
    "\n",
    "    raw_ax.text(idx, y_midpoint, str(idx), color=\"black\", fontsize=20, ha='center')\n",
    "    raw_ax.text(nn_idx, y_midpoint, str(nn_idx), color=\"black\", fontsize=20, ha='center')\n",
    "    \n",
    "    raw_ax.axvline(x=idx, color=\"C1\")\n",
    "    raw_ax.axvline(x=nn_idx, linestyle=\"dashed\", color=\"C1\")\n",
    "    \n",
    "    rect = Rectangle((idx, 0), m, 40, facecolor='lightgrey')\n",
    "    raw_ax.add_patch(rect)\n",
    "    rect = Rectangle((nn_idx, 0), m, 40, facecolor='lightgrey')\n",
    "    raw_ax.add_patch(rect)\n",
    "    \n",
    "    mp_ax.axvline(x=idx, linestyle=\"dashed\", color=\"C1\")\n",
    "    mp_ax.hlines(distance, 0, len(df1), linestyle=\"dashed\", color=\"C1\")\n",
    "    ymin, ymax = mp_ax.get_ylim()\n",
    "    xmin, xmax = mp_ax.get_xlim()\n",
    "    mp_ax.text(xmax * 0.95, ymin+(ymax-ymin)/2, f'{np.round(distance,1)}', color=\"black\", fontsize=20)\n",
    "\n",
    "    # Need to z-normalize\n",
    "    if 'Z-Normalize' in normalize_btn.value:\n",
    "        overlap_ax.plot(stumpy.core.z_norm(df[colname].values[idx:idx+m]))\n",
    "        overlap_ax.plot(stumpy.core.z_norm(df1[colname].values[nn_idx:nn_idx+m]))  \n",
    "    else:\n",
    "        overlap_ax.plot(df[colname].values[idx:idx+m])\n",
    "        overlap_ax.plot(df1[colname].values[nn_idx:nn_idx+m])\n",
    "\n",
    "    return fig\n",
    " \n",
    "\n",
    "plot = pn.Row(display_raw(df1, mps, \"close\"), align='start')\n",
    "\n",
    "\n",
    "def replace_plot(event):\n",
    "    colname = event.new\n",
    "    plot[0] = display_raw(df1, mps, colname=colname)\n",
    "\n",
    "    \n",
    "def update_plot(event):\n",
    "    colname = select_plot.value\n",
    "    plot[0] = display_raw(df1, mps, colname=colname)\n",
    "\n",
    "\n",
    "def move_idx(event):\n",
    "    idx = event.new\n",
    "    txt_input.value = str(idx)\n",
    "    colname = select_plot.value\n",
    "    plot[0] = display_raw(df1, mps, colname=colname, idx=idx)\n",
    "\n",
    "\n",
    "def update_slider(event):\n",
    "    idx = int(event.new)\n",
    "    idx_slider.value = idx\n",
    "    colname = select_plot.value\n",
    "    plot[0] = display_raw(df1, mps, colname=colname, idx=idx)\n",
    "    \n",
    "\n",
    "select_plot.param.watch(replace_plot, 'value')\n",
    "normalize_btn.param.watch(update_plot, 'value')\n",
    "txt_input.param.watch(update_slider, 'value' )\n",
    "idx_slider.param.watch(move_idx, 'value')\n",
    "\n",
    "p = pn.Column(\n",
    "        pn.Row(select_plot, normalize_btn, txt_input, idx_slider),\n",
    "        plot,\n",
    "    )\n",
    "\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d50a38e1-deac-4197-b269-67b74249e98b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5146\n"
     ]
    }
   ],
   "source": [
    "print(len(df)-m)\n",
    "\n",
    "current_idx_start = len(df)-m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bbf85b19-c3ff-4c6d-ba89-977e3d22136c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "p.save(\"test.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "10c45c46-39b3-469e-a60a-ecb3c2824b47",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 open       high        low      close     volume          y\n",
      "timestamp                                                                   \n",
      "2009-10-05  -7.177047  -7.177047  -7.177047  -7.177047   2.995732  -7.177047\n",
      "2009-10-06  -7.030443  -7.030443  -7.030443  -7.030443   2.995732  -7.030443\n",
      "2009-10-07  -6.858584  -6.858584  -6.858584  -6.858584   2.995732  -6.858584\n",
      "2009-10-08  -6.826839  -6.826839  -6.826839  -6.826839   2.995732  -6.826839\n",
      "2009-10-09  -6.725059  -6.725059  -6.725059  -6.725059   2.995732  -6.725059\n",
      "...               ...        ...        ...        ...        ...        ...\n",
      "2024-02-29  11.042505  11.060844  11.006384  11.021346  10.854646  11.021346\n",
      "2024-03-01  11.021277  11.053704  11.014067  11.041573  10.399320  11.041573\n",
      "2024-03-02  11.041469  11.042498  11.028887  11.035224   9.334431  11.035224\n",
      "2024-03-03  11.033827  11.054898  11.024921  11.053251   9.367573  11.053251\n",
      "2024-03-04  11.053217  11.058909  11.051714  11.058069   6.380939  11.058069\n",
      "\n",
      "[5265 rows x 6 columns]\n",
      "                         open      high       low     close     volume\n",
      "timestamp                                                             \n",
      "1983-07-15 13:30:00  5.112048  5.112229  5.100049  5.101633  17.961182\n",
      "1983-07-18 13:30:00  5.101572  5.101633  5.095589  5.099562  18.051210\n",
      "1983-07-19 13:30:00  5.099562  5.107036  5.099562  5.104854  18.119981\n",
      "1983-07-20 13:30:00  5.105279  5.131613  5.105279  5.131613  18.509698\n",
      "1983-07-21 13:30:00  5.131613  5.134621  5.125926  5.130254  18.438815\n",
      "...                       ...       ...       ...       ...        ...\n",
      "2024-02-26 14:30:00  8.535622  8.536537  8.530881  8.531005  21.492911\n",
      "2024-02-27 14:30:00  8.532003  8.533202  8.528586  8.532706  21.467106\n",
      "2024-02-28 14:30:00  8.530544  8.532549  8.528796  8.531051  21.431302\n",
      "2024-02-29 14:30:00  8.534121  8.537974  8.529495  8.536266  21.831498\n",
      "2024-03-01 14:30:00  8.536704  8.544873  8.535850  8.544238  21.601647\n",
      "\n",
      "[10264 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "# zdf = pd.DataFrame({'timestamp': df_index})\n",
    "zdf = df\n",
    "zdf['timestamp'] = df_index\n",
    "zdf = zdf.set_index('timestamp')\n",
    "print(zdf)\n",
    "\n",
    "\n",
    "zdf1 = df1\n",
    "zdf1['timestamp'] = df1_index\n",
    "zdf1 = zdf1.set_index('timestamp')\n",
    "print(zdf1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "62e8c3bc-a7f6-4c6b-9dd3-5b26dc27c8ea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x722d7df18910>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_idx = subset_start_idx[0]\n",
    "\n",
    "# start_idx = 5771\n",
    "end_idx = round(start_idx+m*1.5)\n",
    "\n",
    "# Extract the range of values using iloc\n",
    "subset1 = zdf1.iloc[start_idx:end_idx+1]\n",
    "\n",
    "\n",
    "start_idx = current_idx_start\n",
    "# start_idx = 4869\n",
    "end_idx = start_idx+m\n",
    "\n",
    "# Extract the range of values using iloc\n",
    "subset2 = zdf.iloc[start_idx:end_idx+1]\n",
    "\n",
    "subset1 = min_max_scaling(subset1)\n",
    "subset2 = min_max_scaling(subset2)\n",
    "\n",
    "plt.plot(subset1['close'].reset_index(drop=True))\n",
    "plt.plot(subset2['close'].reset_index(drop=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0b840067-5b9f-4831-89b8-c7f09991adb7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(facecolor='black')\n",
    "fig.set_edgecolor('black')\n",
    "\n",
    "ax = fig.add_subplot(label=\"1\", facecolor='black')\n",
    "ax2 = ax.twinx()  # create a twin of ax that shares the x-axis\n",
    "\n",
    "color_ax = '#C0C0C0'\n",
    "color_ax2 = '#00FF00'\n",
    "\n",
    "subset1_reset = subset1['close'].reset_index(drop=True)\n",
    "subset2_reset = subset2['close'].reset_index(drop=True)\n",
    "\n",
    "\n",
    "ax.plot(subset1_reset, color=color_ax)\n",
    "ax2.plot(subset2_reset, color=color_ax2)\n",
    "\n",
    "# ax.tick_params(axis='both', colors=color_ax, which='major', labelsize=15)\n",
    "# ax2.tick_params(axis='both', colors=color_ax2, which='major', labelsize=15)\n",
    "\n",
    "# Find the index in subset2 that matches the last index of subset1\n",
    "match_index = len(subset2) - 1\n",
    "match_index_sub1 = len(subset1) - 1\n",
    "\n",
    "import datetime\n",
    "\n",
    "# Label the matching index with text annotation\n",
    "start_date = subset2.index[match_index].strftime('%Y-%m-%d')\n",
    "date_1 = datetime.datetime.strptime(start_date, \"%Y-%m-%d\")\n",
    "date_2 = date_1 + datetime.timedelta(days=len(subset1)-len(subset2))\n",
    "\n",
    "ax.annotate('Fractal: ' + subset1.index[match_index].strftime('%Y-%m-%d'), \n",
    "            xy=(match_index, subset1_reset.iloc[match_index]), \n",
    "            xytext=(match_index, subset1_reset.iloc[match_index] - subset1_reset.std()/2), \n",
    "            color='red', ha='left', va='top')\n",
    "\n",
    "ax2.annotate('Current: ' + subset2.index[match_index].strftime('%Y-%m-%d'), \n",
    "             xy=(match_index, subset2_reset.iloc[match_index]), \n",
    "             xytext=(match_index, subset2_reset.iloc[match_index] + subset2_reset.std() /4), \n",
    "             color=color_ax2, ha='left', va='bottom')\n",
    "\n",
    "ax.annotate('Projection: ' + date_2.strftime('%Y-%m-%d'), \n",
    "            xy=(match_index_sub1, subset1_reset.iloc[match_index_sub1]), \n",
    "            xytext=(match_index_sub1, subset1_reset.iloc[match_index_sub1] - subset1_reset.std()/2), \n",
    "            color=color_ax2, ha='left', va='bottom')\n",
    "\n",
    "\n",
    "\n",
    "title = ticker + ':' + ticker1 + ' ' + str(m) + ' Fractal'\n",
    "# title = ticker +  ' Fractal'\n",
    "fig.suptitle(title, fontsize=24, fontweight='regular', color='#C0C0C0')\n",
    "\n",
    "fig.subplots_adjust(top=0.8)\n",
    "\n",
    "grid_style = {'linewidth': 0.5, 'color': '#999999', 'linestyle': '--'}\n",
    "ax.grid(True, **grid_style)\n",
    "ax2.grid(True, **grid_style)\n",
    "\n",
    "plt.savefig(imgPath + title + '.png', dpi=300, bbox_inches='tight', facecolor='black')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "244d519f-7a0a-4df8-9589-b48e76bedb99",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c543e5c-6143-4832-9db6-a7475bc5ea6e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}