TD1_lotka_volterra.ipynb 233 KB
Newer Older
FAGES Francois's avatar
TD12  
FAGES Francois committed
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TD1: Lotka-Volterra's prey-predator enzymatic model\n",
    "- reaction network\n",
    "- differential, stochastic and boolean semantics\n",
    "- addition of immigration/emigration reactions\n",
    "\n",
    "F. Fages, 18 Jan. 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "clear_model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "present(A,a). present(B,b)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "k1*A*B for A+B => 2*B."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "k2*A for A => 2*A."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "k3*B for B => _."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameter(a=1, b=1, k1=2, k2=2, k3=1)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "k1*A*B for A=[B]=>B.\r\n",
       "k2*A for _=[A]=>A.\r\n",
       "k3*B for B=>_.\r\n",
       "present(A,a).\r\n",
       "present(B,b).\r\n",
       "parameter(\r\n",
       "  a = 1,\r\n",
       "  b = 1,\r\n",
       "  k1 = 2,\r\n",
       "  k2 = 2,\r\n",
       "  k3 = 1\r\n",
       ").\r\n"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_reactions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
124
      "image/png": "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"
FAGES Francois's avatar
TD12  
FAGES Francois committed
125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_influences."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Continuous semantics\n",
    "* One observes sustained oscillations and limit cycle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "\\begin{align*}\n",
       "B_0 &= 1\\\\\n",
       "A_0 &= 1\\\\\n",
       "a &= 1\\\\\n",
       "b &= 1\\\\\n",
       "k1 &= 2\\\\\n",
       "k2 &= 2\\\\\n",
       "k3 &= 1\\\\\n",
       "\\frac{dB}{dt} &= k1*A*B-k3*B\\\\\n",
       "\\frac{dA}{dt} &= k2*A-k1*A*B\\\\\n",
       "\\end{align*}\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "list_ode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No complex invariant found\r\n"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_conservations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "option(time:40)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var 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",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var 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",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\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",
       "      var cmd = \"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, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].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",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\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",
       "      var 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",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\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",
       "    var events = require('base/js/events');\n",
       "    var 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",
       "\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",
       "  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",
       "    var el = document.getElementById(null);\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",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._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",
       "    root._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",
       "        root._bokeh_is_loading--;\n",
       "        if (root._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",
       "  };\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.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",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._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",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var 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\n  \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  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    var el = document.getElementById(null);\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\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._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    root._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        root._bokeh_is_loading--;\n        if (root._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  };\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.14.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.14.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.14.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.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    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._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}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
479
       "    <div class=\"bk-plotdiv\" id=\"9d23cbe0-8f50-48c0-824e-069684295c86\"></div>\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
480 481 482 483 484 485 486 487 488 489 490 491
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
492 493
       "  var docs_json = {\"f8f758b3-0639-4adb-ac4b-3f97e634f0bf\":{\"roots\":{\"references\":[{\"attributes\":{},\"id\":\"0bbca3db-9e74-4072-b4ad-c2b4609b6cf4\",\"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\":\"622d9821-1052-49da-8081-8aa242e5c248\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"overlay\":{\"id\":\"622d9821-1052-49da-8081-8aa242e5c248\",\"type\":\"BoxAnnotation\"}},\"id\":\"9c6198fa-fc64-4769-95a0-3b97d0c57610\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"90655dce-81cc-4f6a-ac36-d747044a22ae\",\"type\":\"Line\"},{\"attributes\":{\"dimension\":1,\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"aab65d08-f16d-4b7c-9a99-87e1ea845937\",\"type\":\"BasicTicker\"}},\"id\":\"8b212799-01a1-4be0-92b3-31042837b6d3\",\"type\":\"Grid\"},{\"attributes\":{\"axis_label\":\"Time\",\"formatter\":{\"id\":\"37c36640-f754-40a1-9104-8bbe8fbba90e\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0bbca3db-9e74-4072-b4ad-c2b4609b6cf4\",\"type\":\"BasicTicker\"}},\"id\":\"2959a4ee-02bf-4f9b-ae95-a6878b76e11d\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"aab65d08-f16d-4b7c-9a99-87e1ea845937\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"dccf17b5-b67b-408f-93e2-6bb345919608\",\"type\":\"DataRange1d\"},{\"attributes\":{\"data_source\":{\"id\":\"d6d7941d-a957-498d-baa0-dba5294aabf3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"2d81d6d0-0f47-491f-82c0-65a919133580\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1184235a-1a8d-40ef-862d-de911adbf22f\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"efd36064-871c-4b6f-be31-93b37beec6f6\",\"type\":\"CDSView\"}},\"id\":\"2ffbf26e-a46f-43ce-80a8-dd3f2ca6fdfa\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"1184235a-1a8d-40ef-862d-de911adbf22f\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"64850b4d-4f72-4c6d-bea5-d62d3104a0bf\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"ec0df6b6-bd79-4407-b309-1a2eb41fd442\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"ae6b1b37-fa02-48d0-b911-58c95cf5debe\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"37c36640-f754-40a1-9104-8bbe8fbba90e\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"ffbed30f-195e-4b14-91e4-088e831247f9\",\"type\":\"LinearScale\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"A\",\"B\",\"Time\"],\"data\":{\"A\":[1.0,1.0,0.999985,0.839354,0.529653,0.32126,0.229338,0.203341,0.218549,0.271707,0.371873,0.532886,0.753127,0.959824,0.963109,0.694201,0.41557,0.267718,0.211259,0.205822,0.2381,0.311374,0.438156,0.629265,0.859696,0.999339,0.860478,0.550751,0.332061,0.233411,0.203709,0.216161,0.2663,0.36249,0.518627,0.735606,0.948675,0.973821,0.718248,0.431799,0.274872,0.21339,0.204885,0.2344,0.30427,0.426566,0.612966,0.843231,0.996975,0.880557,0.572519,0.343545,0.23785,0.2043,0.213976,0.261145,0.353442,0.504732,0.718134,0.936476,0.982724,0.742233,0.44884,0.282543,0.2158,0.204152,0.230918,0.297455,0.415343,0.596956,0.82641,0.992965,0.899442,0.594896,0.355736,0.242672,0.20512,0.211993,0.256236,0.344724,0.491205,0.700756,0.923333,0.989787,0.766006,0.466693,0.290758,0.2185,0.203623,0.227652,0.290922,0.404482,0.581254,0.809312,0.987387,0.916993,0.617807,0.368659,0.247895,0.206174,0.210209,0.251568,0.335249],\"B\":[1.0,1.00003,1.00391,1.43252,1.65848,1.54786,1.28564,1.02132,0.808483,0.657564,0.568142,0.544497,0.608727,0.814533,1.2025,1.58198,1.64019,1.43347,1.15873,0.915271,0.730928,0.608519,0.548274,0.560873,0.682021,0.974507,1.403,1.65453,1.56391,1.30635,1.03949,0.822191,0.666662,0.57265,0.543664,0.599943,0.792815,1.16944,1.56269,1.64766,1.45311,1.17873,0.931454,0.742487,0.615516,0.550486,0.556848,0.66791,0.946047,1.37241,1.64848,1.57908,1.32705,1.05796,0.836245,0.676099,0.577509,0.543287,0.591902,0.772212,1.13663,1.54143,1.65352,1.47236,1.19892,0.947971,0.754389,0.622851,0.553081,0.553383,0.654739,0.918592,1.34093,1.6403,1.59327,1.34772,1.0767,0.850645,0.685874,0.582718,0.543354,0.584574,0.752712,1.10422,1.51831,1.65769,1.49117,1.21926,0.964817,0.766636,0.630524,0.556054,0.550458,0.642475,0.892189,1.30876,1.62996,1.60639,1.3683,1.09572,0.86539,0.695989,0.589028],\"Time\":[0.0,3.1e-05,0.003906,0.403906,0.803906,1.20391,1.60391,2.00391,2.40391,2.80391,3.20391,3.60391,4.00391,4.40391,4.80391,5.20391,5.60391,6.00391,6.40391,6.80391,7.20391,7.60391,8.00391,8.40391,8.80391,9.20391,9.60391,10.0039,10.4039,10.8039,11.2039,11.6039,12.0039,12.4039,12.8039,13.2039,13.6039,14.0039,14.4039,14.8039,15.2039,15.6039,16.0039,16.4039,16.8039,17.2039,17.6039,18.0039,18.4039,18.8039,19.2039,19.6039,20.0039,20.4039,20.8039,21.2039,21.6039,22.0039,22.4039,22.8039,23.2039,23.6039,24.0039,24.4039,24.8039,25.2039,25.6039,26.0039,26.4039,26.8039,27.2039,27.6039,28.0039,28.4039,28.8039,29.2039,29.6039,30.0039,30.4039,30.8039,31.2039,31.6039,32.0039,32.4039,32.8039,33.2039,33.6039,34.0039,34.4039,34.8039,35.2039,35.6039,36.0039,36.4039,36.8039,37.2039,37.6039,38.0039,38.4039,38.8039,39.2039,39.6039,40.0]}},\"id\":\"d6d7941d-a957-498d-baa0-dba5294aabf3\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"6748e240-e8e7-40f5-a5a7-11b4712fccf3\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"label\":{\"value\":\"B\"},\"renderers\":[{\"id\":\"2ffbf26e-a46f-43ce-80a8-dd3f2ca6fdfa\",\"type\":\"GlyphRenderer\"}]},\"id\":\"3ccce4c6-3e1b-43f8-ac10-b9f6afc272c6\",\"type\":\"LegendItem\"},{\"attributes\":{\"active_drag\":{\"id\":\"9c6198fa-fc64-4769-95a0-3b97d0c57610\",\"type\":\"BoxZoomTool\"},\"active_inspect\":\"auto\",\"active_scroll\":null,\"active_tap\":\"auto\",\"tools\":[{\"id\":\"d51bffc8-863d-4aa0-a762-991a84bfa0c4\",\"type\":\"PanTool\"},{\"id\":\"6748e240-e8e7-40f5-a5a7-11b4712fccf3\",\"type\":\"WheelZoomTool\"},{\"id\":\"9c6198fa-fc64-4769-95a0-3b97d0c57610\",\"type\":\"BoxZoomTool\"},{\"id\":\"7bdc8c31-03de-47ec-ad7b-f27d1eada3a4\",\"type\":\"ResetTool\"},{\"id\":\"ae6b1b37-fa02-48d0-b911-58c95cf5debe\",\"type\":\"SaveTool\"},{\"id\":\"ceaf08c0-7348-4c24-97f8-6b9b031fec99\",\"type\":\"UndoTool\"},{\"id\":\"2bc9e458-83e4-4f43-9aa0-f95c811aeef9\",\"type\":\"HoverTool\"}]},\"id\":\"a3e7abec-917f-4af2-a9ee-84914da58cd1\",\"type\":\"Toolbar\"},{\"attributes\":{\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0bbca3db-9e74-4072-b4ad-c2b4609b6cf4\",\"type\":\"BasicTicker\"}},\"id\":\"a70c64af-9a83-4888-9a7d-2f0c691a0984\",\"type\":\"Grid\"},{\"attributes\":{\"formatter\":{\"id\":\"ec0df6b6-bd79-4407-b309-1a2eb41fd442\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"aab65d08-f16d-4b7c-9a99-87e1ea845937\",\"type\":\"BasicTicker\"}},\"id\":\"c8eccaef-80e3-4a2b-b871-2e0d102c6d76\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"5ad8fd94-2026-44dc-b3e0-35ab15ee6ffb\",\"type\":\"Title\"},{\"attributes\":{\"label\":{\"value\":\"A\"},\"renderers\":[{\"id\":\"c3f01923-7dae-47b0-a80d-357ebdce7b21\",\"type\":\"GlyphRenderer\"}]},\"id\":\"44d86d11-6a13-42e7-bc45-425991710fdf\",\"type\":\"LegendItem\"},{\"attributes\":{\"background_fill_alpha\":{\"value\":0.3},\"background_fill_color\":{\"value\":\"oldlace\"},\"below\":[{\"id\":\"2959a4ee-02bf-4f9b-ae95-a6878b76e11d\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"c8eccaef-80e3-4a2b-b871-2e0d102c6d76\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":640,\"renderers\":[{\"id\":\"2959a4ee-02bf-4f9b-ae95-a6878b76e11d\",\"type\":\"LinearAxis\"},{\"id\":\"a70c64af-9a83-4888-9a7d-2f0c691a0984\",\"type\":\"Grid\"},{\"id\":\"c8eccaef-80e3-4a2b-b871-2e0d102c6d76\",\"type\":\"LinearAxis\"},{\"id\":\"8b212799-01a1-4be0-92b3-31042837b6d3\",\"type\":\"Grid\"},{\"id\":\"622d9821-1052-49da-8081-8aa242e5c248\",\"type\":\"BoxAnnotation\"},{\"id\":\"2ffbf26e-a46f-43ce-80a8-dd3f2ca6fdfa\",\"type\":\"GlyphRenderer\"},{\"id\":\"c3f01923-7dae-47b0-a80d-357ebdce7b21\",\"type\":\"GlyphRenderer\"},{\"id\":\"6db9326d-8354-47a8-aa6a-fd1c16c6a1d5\",\"type\":\"Legend\"}],\"right\":[{\"id\":\"6db9326d-8354-47a8-aa6a-fd1c16c6a1d5\",\"type\":\"Legend\"}],\"title\":{\"id\":\"5ad8fd94-2026-44dc-b3e0-35ab15ee6ffb\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"a3e7abec-917f-4af2-a9ee-84914da58cd1\",\"type\":\"Toolbar\"},\"toolbar_location\":\"below\",\"toolbar_sticky\":false,\"x_range\":{\"id\":\"4bc9725d-59fc-4c38-82d4-9b397e96c2b7\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"64850b4d-4f72-4c6d-bea5-d62d3104a0bf\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"dccf17b5-b67b-408f-93e2-6bb345919608\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"ffbed30f-195e-4b14-91e4-088e831247f9\",\"type\":\"LinearScale\"}},\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"ceaf08c0-7348-4c24-97f8-6b9b031fec99\",\"type\":\"UndoTool\"},{\"attributes\":{\"callback\":null},\"id\":\"4bc9725d-59fc-4c38-82d4-9b397e96c2b7\",\"type\":\"DataRange1d\"},{\"attributes\":{\"indices\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102]},\"id\":\"3190191e-d814-4d06-b087-ea0391b1fa3a\",\"type\":\"IndexFilter\"},{\"attributes\":{\"line_color\":\"#ff7f0e\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"22bdacaf-225a-4052-aa05-6bc86d47d566\",\"type\":\"Line\"},{\"attributes\":{\"border_line_color\":{\"value\":\"gray\"},\"click_policy\":\"hide\",\"items\":[{\"id\":\"3ccce4c6-3e1b-43f8-ac10-b9f6afc272c6\",\"type\":\"LegendItem\"},{\"id\":\"44d86d11-6a13-42e7-bc45-425991710fdf\",\"type\":\"LegendItem\"}],\"location\":[10,0],\"plot\":{\"id\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"6db9326d-8354-47a8-aa6a-fd1c16c6a1d5\",\"type\":\"Legend\"},{\"attributes\":{\"data_source\":{\"id\":\"d6d7941d-a957-498d-baa0-dba5294aabf3\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"22bdacaf-225a-4052-aa05-6bc86d47d566\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"90655dce-81cc-4f6a-ac36-d747044a22ae\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"efd36064-871c-4b6f-be31-93b37beec6f6\",\"type\":\"CDSView\"}},\"id\":\"c3f01923-7dae-47b0-a80d-357ebdce7b21\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"x,y\",\"$x, $y\"]]},\"id\":\"2bc9e458-83e4-4f43-9aa0-f95c811aeef9\",\"type\":\"HoverTool\"},{\"attributes\":{\"filters\":[{\"id\":\"3190191e-d814-4d06-b087-ea0391b1fa3a\",\"type\":\"IndexFilter\"}],\"source\":{\"id\":\"d6d7941d-a957-498d-baa0-dba5294aabf3\",\"type\":\"ColumnDataSource\"}},\"id\":\"efd36064-871c-4b6f-be31-93b37beec6f6\",\"type\":\"CDSView\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"2d81d6d0-0f47-491f-82c0-65a919133580\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"d51bffc8-863d-4aa0-a762-991a84bfa0c4\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"7bdc8c31-03de-47ec-ad7b-f27d1eada3a4\",\"type\":\"ResetTool\"}],\"root_ids\":[\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"f8f758b3-0639-4adb-ac4b-3f97e634f0bf\",\"elementid\":\"9d23cbe0-8f50-48c0-824e-069684295c86\",\"modelid\":\"e72a3f10-c9d9-4ad2-985b-b41cc9abd772\",\"notebook_comms_target\":\"cfa9935b-b25f-4df2-b95d-7dd936cb3f50\"}];\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
519
       "id": "e72a3f10-c9d9-4ad2-985b-b41cc9abd772"
FAGES Francois's avatar
TD12  
FAGES Francois committed
520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "numerical_simulation. plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
541
       "    <div class=\"bk-plotdiv\" id=\"16147933-1d69-4e64-9489-5d12e25d2b27\"></div>\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
542 543 544 545 546 547 548 549 550 551 552 553
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
554 555
       "  var docs_json = {\"8e1901ff-98c8-4591-9d3f-2404aa8c5f3f\":{\"roots\":{\"references\":[{\"attributes\":{\"indices\":[]},\"id\":\"e5c4d926-0317-4ebf-9121-ec376c977208\",\"type\":\"IndexFilter\"},{\"attributes\":{},\"id\":\"7bf53c15-06c7-4a48-a051-faf603e08628\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7bf53c15-06c7-4a48-a051-faf603e08628\",\"type\":\"BasicTicker\"}},\"id\":\"b8b94897-62a7-4122-b823-277f11df0c1e\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"5e96416e-5926-4acc-9154-dc50652f44de\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c2c47ca5-cfe5-42b1-a97b-81a1af3cfa8e\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"96d920bb-b3ec-42cf-a0b3-d71c4c4099ac\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"2f9c6871-d263-4ecd-b3f9-39eb660435aa\",\"type\":\"CDSView\"}},\"id\":\"e4e8a0a8-2d02-4913-8183-83d19fd986c7\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"68227258-adcc-4e6b-a3a4-4c86fee91d86\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"c23be242-fd48-4f59-91ea-5ee5e4ee417f\",\"type\":\"ResetTool\"},{\"attributes\":{\"formatter\":{\"id\":\"e9a745fa-9cd5-4e92-9797-d14ce5d6d4e9\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"7bf53c15-06c7-4a48-a051-faf603e08628\",\"type\":\"BasicTicker\"}},\"id\":\"de62e315-d9c9-4b50-b97a-3cbd302fc56c\",\"type\":\"LinearAxis\"},{\"attributes\":{\"background_fill_alpha\":{\"value\":0.3},\"background_fill_color\":{\"value\":\"oldlace\"},\"below\":[{\"id\":\"5c341183-af6a-4b30-a737-60c35dbfbdfc\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"de62e315-d9c9-4b50-b97a-3cbd302fc56c\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":640,\"renderers\":[{\"id\":\"5c341183-af6a-4b30-a737-60c35dbfbdfc\",\"type\":\"LinearAxis\"},{\"id\":\"c701e9b3-791d-49bf-82a1-17710f4a6aba\",\"type\":\"Grid\"},{\"id\":\"de62e315-d9c9-4b50-b97a-3cbd302fc56c\",\"type\":\"LinearAxis\"},{\"id\":\"b8b94897-62a7-4122-b823-277f11df0c1e\",\"type\":\"Grid\"},{\"id\":\"c82257d6-2f93-43c7-b049-7be0a3e67081\",\"type\":\"BoxAnnotation\"},{\"id\":\"e4e8a0a8-2d02-4913-8183-83d19fd986c7\",\"type\":\"GlyphRenderer\"},{\"id\":\"f724620f-c327-4c55-93be-415879d80320\",\"type\":\"Legend\"}],\"right\":[{\"id\":\"f724620f-c327-4c55-93be-415879d80320\",\"type\":\"Legend\"}],\"title\":{\"id\":\"f979a49f-6f7f-4d15-8e53-b609e31664df\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"6a548a6c-0968-49b6-b0e4-60a110289e07\",\"type\":\"Toolbar\"},\"toolbar_location\":\"below\",\"toolbar_sticky\":false,\"x_range\":{\"id\":\"7e64fa64-4af4-4308-a692-8a0e3cc6694e\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"f0976525-8a63-4d54-88e9-ceb5c2f84b9a\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1d6626d7-ca41-4422-81b3-340cf17cec02\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"d75457ea-c722-483c-a39b-ecf50a06daa7\",\"type\":\"LinearScale\"}},\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"overlay\":{\"id\":\"c82257d6-2f93-43c7-b049-7be0a3e67081\",\"type\":\"BoxAnnotation\"}},\"id\":\"2d4da0f6-f97a-4737-8af9-f093b8c92ea9\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"x,y\",\"$x, $y\"]]},\"id\":\"d7604d94-0579-4985-b289-2e5be418442c\",\"type\":\"HoverTool\"},{\"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\":\"c82257d6-2f93-43c7-b049-7be0a3e67081\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"axis_label\":\"A\",\"formatter\":{\"id\":\"68227258-adcc-4e6b-a3a4-4c86fee91d86\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6caabac9-89ca-477e-8114-67d074c8db29\",\"type\":\"BasicTicker\"}},\"id\":\"5c341183-af6a-4b30-a737-60c35dbfbdfc\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"e9a745fa-9cd5-4e92-9797-d14ce5d6d4e9\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"A\",\"B\",\"Time\"],\"data\":{\"A\":[1.0,1.0,0.999985,0.839354,0.529653,0.32126,0.229338,0.203341,0.218549,0.271707,0.371873,0.532886,0.753127,0.959824,0.963109,0.694201,0.41557,0.267718,0.211259,0.205822,0.2381,0.311374,0.438156,0.629265,0.859696,0.999339,0.860478,0.550751,0.332061,0.233411,0.203709,0.216161,0.2663,0.36249,0.518627,0.735606,0.948675,0.973821,0.718248,0.431799,0.274872,0.21339,0.204885,0.2344,0.30427,0.426566,0.612966,0.843231,0.996975,0.880557,0.572519,0.343545,0.23785,0.2043,0.213976,0.261145,0.353442,0.504732,0.718134,0.936476,0.982724,0.742233,0.44884,0.282543,0.2158,0.204152,0.230918,0.297455,0.415343,0.596956,0.82641,0.992965,0.899442,0.594896,0.355736,0.242672,0.20512,0.211993,0.256236,0.344724,0.491205,0.700756,0.923333,0.989787,0.766006,0.466693,0.290758,0.2185,0.203623,0.227652,0.290922,0.404482,0.581254,0.809312,0.987387,0.916993,0.617807,0.368659,0.247895,0.206174,0.210209,0.251568,0.335249],\"B\":[1.0,1.00003,1.00391,1.43252,1.65848,1.54786,1.28564,1.02132,0.808483,0.657564,0.568142,0.544497,0.608727,0.814533,1.2025,1.58198,1.64019,1.43347,1.15873,0.915271,0.730928,0.608519,0.548274,0.560873,0.682021,0.974507,1.403,1.65453,1.56391,1.30635,1.03949,0.822191,0.666662,0.57265,0.543664,0.599943,0.792815,1.16944,1.56269,1.64766,1.45311,1.17873,0.931454,0.742487,0.615516,0.550486,0.556848,0.66791,0.946047,1.37241,1.64848,1.57908,1.32705,1.05796,0.836245,0.676099,0.577509,0.543287,0.591902,0.772212,1.13663,1.54143,1.65352,1.47236,1.19892,0.947971,0.754389,0.622851,0.553081,0.553383,0.654739,0.918592,1.34093,1.6403,1.59327,1.34772,1.0767,0.850645,0.685874,0.582718,0.543354,0.584574,0.752712,1.10422,1.51831,1.65769,1.49117,1.21926,0.964817,0.766636,0.630524,0.556054,0.550458,0.642475,0.892189,1.30876,1.62996,1.60639,1.3683,1.09572,0.86539,0.695989,0.589028],\"Time\":[0.0,3.1e-05,0.003906,0.403906,0.803906,1.20391,1.60391,2.00391,2.40391,2.80391,3.20391,3.60391,4.00391,4.40391,4.80391,5.20391,5.60391,6.00391,6.40391,6.80391,7.20391,7.60391,8.00391,8.40391,8.80391,9.20391,9.60391,10.0039,10.4039,10.8039,11.2039,11.6039,12.0039,12.4039,12.8039,13.2039,13.6039,14.0039,14.4039,14.8039,15.2039,15.6039,16.0039,16.4039,16.8039,17.2039,17.6039,18.0039,18.4039,18.8039,19.2039,19.6039,20.0039,20.4039,20.8039,21.2039,21.6039,22.0039,22.4039,22.8039,23.2039,23.6039,24.0039,24.4039,24.8039,25.2039,25.6039,26.0039,26.4039,26.8039,27.2039,27.6039,28.0039,28.4039,28.8039,29.2039,29.6039,30.0039,30.4039,30.8039,31.2039,31.6039,32.0039,32.4039,32.8039,33.2039,33.6039,34.0039,34.4039,34.8039,35.2039,35.6039,36.0039,36.4039,36.8039,37.2039,37.6039,38.0039,38.4039,38.8039,39.2039,39.6039,40.0]}},\"id\":\"5e96416e-5926-4acc-9154-dc50652f44de\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"d75457ea-c722-483c-a39b-ecf50a06daa7\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"f0976525-8a63-4d54-88e9-ceb5c2f84b9a\",\"type\":\"LinearScale\"},{\"attributes\":{\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"6caabac9-89ca-477e-8114-67d074c8db29\",\"type\":\"BasicTicker\"}},\"id\":\"c701e9b3-791d-49bf-82a1-17710f4a6aba\",\"type\":\"Grid\"},{\"attributes\":{\"border_line_color\":{\"value\":\"gray\"},\"click_policy\":\"hide\",\"items\":[{\"id\":\"7141ef96-cc32-41e8-8698-c4fb311d2d10\",\"type\":\"LegendItem\"}],\"location\":[10,0],\"plot\":{\"id\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"f724620f-c327-4c55-93be-415879d80320\",\"type\":\"Legend\"},{\"attributes\":{\"callback\":null,\"end\":1.7699993,\"start\":0.4317677},\"id\":\"1d6626d7-ca41-4422-81b3-340cf17cec02\",\"type\":\"Range1d\"},{\"attributes\":{\"filters\":[{\"id\":\"e5c4d926-0317-4ebf-9121-ec376c977208\",\"type\":\"IndexFilter\"}],\"source\":{\"id\":\"5e96416e-5926-4acc-9154-dc50652f44de\",\"type\":\"ColumnDataSource\"}},\"id\":\"2f9c6871-d263-4ecd-b3f9-39eb660435aa\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"81f63bcd-1999-4ed9-8c8d-a5e76f74359d\",\"type\":\"UndoTool\"},{\"attributes\":{\"label\":{\"value\":\"B\"},\"renderers\":[{\"id\":\"e4e8a0a8-2d02-4913-8183-83d19fd986c7\",\"type\":\"GlyphRenderer\"}]},\"id\":\"7141ef96-cc32-41e8-8698-c4fb311d2d10\",\"type\":\"LegendItem\"},{\"attributes\":{\"active_drag\":{\"id\":\"2d4da0f6-f97a-4737-8af9-f093b8c92ea9\",\"type\":\"BoxZoomTool\"},\"active_inspect\":\"auto\",\"active_scroll\":null,\"active_tap\":\"auto\",\"tools\":[{\"id\":\"5885864b-af0b-49bb-abc5-369c696e7324\",\"type\":\"PanTool\"},{\"id\":\"4f5da9b8-824a-485f-9e94-05240e6bf790\",\"type\":\"WheelZoomTool\"},{\"id\":\"2d4da0f6-f97a-4737-8af9-f093b8c92ea9\",\"type\":\"BoxZoomTool\"},{\"id\":\"c23be242-fd48-4f59-91ea-5ee5e4ee417f\",\"type\":\"ResetTool\"},{\"id\":\"66d53167-80c8-4fba-958b-fb39748728d2\",\"type\":\"SaveTool\"},{\"id\":\"81f63bcd-1999-4ed9-8c8d-a5e76f74359d\",\"type\":\"UndoTool\"},{\"id\":\"d7604d94-0579-4985-b289-2e5be418442c\",\"type\":\"HoverTool\"}]},\"id\":\"6a548a6c-0968-49b6-b0e4-60a110289e07\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"4f5da9b8-824a-485f-9e94-05240e6bf790\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"A\"},\"y\":{\"field\":\"B\"}},\"id\":\"96d920bb-b3ec-42cf-a0b3-d71c4c4099ac\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"7e64fa64-4af4-4308-a692-8a0e3cc6694e\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"6caabac9-89ca-477e-8114-67d074c8db29\",\"type\":\"BasicTicker\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"f979a49f-6f7f-4d15-8e53-b609e31664df\",\"type\":\"Title\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"A\"},\"y\":{\"field\":\"B\"}},\"id\":\"c2c47ca5-cfe5-42b1-a97b-81a1af3cfa8e\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"66d53167-80c8-4fba-958b-fb39748728d2\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"5885864b-af0b-49bb-abc5-369c696e7324\",\"type\":\"PanTool\"}],\"root_ids\":[\"319d26df-d58e-4bac-b239-3942aa960d6d\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"8e1901ff-98c8-4591-9d3f-2404aa8c5f3f\",\"elementid\":\"16147933-1d69-4e64-9489-5d12e25d2b27\",\"modelid\":\"319d26df-d58e-4bac-b239-3942aa960d6d\",\"notebook_comms_target\":\"e95c6ac3-edd3-4f02-a277-1a2872701a20\"}];\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
581
       "id": "319d26df-d58e-4bac-b239-3942aa960d6d"
FAGES Francois's avatar
TD12  
FAGES Francois committed
582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(show:B, against:A)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stochastic semantics\n",
    "* With this parameter set, the prey and predator extend almost surely\n",
    "* The intuitive explanation is that low concentrations become almost surely 0 at some time point in the stochastic simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
610
       "    <div class=\"bk-plotdiv\" id=\"61a1e3f6-9a34-4232-8252-8c633603a22b\"></div>\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
611 612 613 614 615 616 617 618 619 620 621 622
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
623 624
       "  var docs_json = {\"30fee2a1-b758-4a91-a28a-4fa671540fa1\":{\"roots\":{\"references\":[{\"attributes\":{\"indices\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218]},\"id\":\"6ab7d1ea-5f73-4fc0-9505-b95bee90235f\",\"type\":\"IndexFilter\"},{\"attributes\":{\"data_source\":{\"id\":\"8e14dd7c-b23f-4b73-8878-3d2fad41a8b1\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"a68b3f8e-41b3-4d57-aa67-22996d604900\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"9dc594ab-a8a8-4780-b7ae-cd0b6ba2706f\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"3328e5b5-1115-47fb-b8e0-7e29ce9d259c\",\"type\":\"CDSView\"}},\"id\":\"061bc021-d9c8-4e50-990c-e6b9cc5e4d35\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"81eeceec-05ee-4b26-90ca-aaf9199dad71\",\"type\":\"LinearScale\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"9dc594ab-a8a8-4780-b7ae-cd0b6ba2706f\",\"type\":\"Line\"},{\"attributes\":{\"overlay\":{\"id\":\"4c74acec-9985-494b-9458-7a33710024c4\",\"type\":\"BoxAnnotation\"}},\"id\":\"3dfb603e-75ce-49ff-8404-694e56b2076b\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"dimension\":1,\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3ddb6b6d-bc06-4a29-ab2b-7c70a2c0cd41\",\"type\":\"BasicTicker\"}},\"id\":\"ec596bde-a76e-4621-9576-266a8f8b3450\",\"type\":\"Grid\"},{\"attributes\":{\"label\":{\"value\":\"B\"},\"renderers\":[{\"id\":\"44cc01a9-f804-4c2b-ab1a-941abcc3009b\",\"type\":\"GlyphRenderer\"}]},\"id\":\"a8276435-4230-4ea1-99b0-65f91d0fe54b\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"7d8d65f9-48fe-4507-ba9f-ad4ad8d0b5dc\",\"type\":\"ResetTool\"},{\"attributes\":{\"label\":{\"value\":\"A\"},\"renderers\":[{\"id\":\"061bc021-d9c8-4e50-990c-e6b9cc5e4d35\",\"type\":\"GlyphRenderer\"}]},\"id\":\"acea540a-067a-43b9-9be6-18317da07e49\",\"type\":\"LegendItem\"},{\"attributes\":{\"callback\":null},\"id\":\"3ade8706-ff6f-4139-8780-02193dda79a4\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"ae4621b7-5bc8-4101-8b0b-c8e66eab5d7e\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"B\",\"A\",\"Time\"],\"data\":{\"A\":[100.0,99.0,105.0,101.0,101.0,105.0,106.0,103.0,95.0,89.0,79.0,75.0,75.0,68.0,61.0,59.0,60.0,62.0,61.0,55.0,47.0,50.0,46.0,42.0,35.0,33.0,27.0,24.0,20.0,17.0,14.0,15.0,14.0,14.0,14.0,16.0,15.0,14.0,14.0,15.0,11.0,12.0,12.0,13.0,12.0,13.0,14.0,14.0,14.0,13.0,11.0,9.0,7.0,8.0,8.0,6.0,7.0,7.0,5.0,5.0,5.0,5.0,5.0,5.0,4.0,4.0,4.0,5.0,6.0,6.0,5.0,5.0,6.0,7.0,7.0,7.0,6.0,6.0,6.0,7.0,8.0,8.0,8.0,9.0,8.0,8.0,9.0,10.0,13.0,16.0,18.0,19.0,19.0,22.0,25.0,29.0,33.0,36.0,43.0,47.0,53.0,58.0,62.0,70.0,78.0,84.0,86.0,93.0,104.0,110.0,123.0,132.0,140.0,159.0,171.0,180.0,200.0,222.0,238.0,253.0,273.0,291.0,312.0,332.0,349.0,376.0,398.0,414.0,413.0,399.0,388.0,331.0,295.0,241.0,204.0,152.0,115.0,84.0,55.0,39.0,28.0,31.0,19.0,14.0,8.0,7.0,4.0,4.0,4.0,3.0,4.0,3.0,2.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],\"B\":[100.0,106.0,107.0,107.0,114.0,120.0,124.0,132.0,143.0,148.0,158.0,163.0,162.0,163.0,168.0,166.0,166.0,165.0,173.0,176.0,183.0,177.0,179.0,181.0,186.0,184.0,187.0,181.0,178.0,176.0,173.0,168.0,160.0,154.0,153.0,151.0,150.0,148.0,142.0,132.0,130.0,127.0,120.0,115.0,110.0,105.0,103.0,100.0,95.0,92.0,90.0,92.0,89.0,85.0,83.0,79.0,78.0,73.0,72.0,70.0,66.0,62.0,59.0,53.0,49.0,45.0,43.0,43.0,42.0,39.0,38.0,36.0,36.0,34.0,32.0,29.0,29.0,26.0,25.0,23.0,22.0,20.0,18.0,17.0,17.0,16.0,15.0,15.0,15.0,14.0,14.0,13.0,14.0,12.0,11.0,11.0,10.0,9.0,8.0,8.0,8.0,8.0,8.0,8.0,7.0,6.0,8.0,10.0,12.0,11.0,10.0,8.0,9.0,8.0,8.0,8.0,7.0,8.0,9.0,13.0,17.0,20.0,23.0,28.0,37.0,46.0,57.0,76.0,104.0,146.0,184.0,256.0,307.0,356.0,395.0,443.0,477.0,500.0,522.0,517.0,519.0,502.0,500.0,484.0,476.0,462.0,436.0,424.0,418.0,395.0,378.0,361.0,348.0,336.0,318.0,302.0,286.0,274.0,266.0,258.0,242.0,233.0,220.0,208.0,196.0,187.0,174.0,168.0,162.0,149.0,140.0,129.0,126.0,120.0,115.0,108.0,103.0,100.0,95.0,92.0,89.0,83.0,77.0,73.0,69.0,67.0,62.0,56.0,54.0,51.0,48.0,45.0,42.0,38.0,36.0,35.0,33.0,32.0,29.0,26.0,24.0,22.0,21.0,20.0,17.0,16.0,14.0,13.0,12.0,10.0,9.0,8.0,7.0,5.0,3.0,2.0,1.0,0.0,0.0],\"Time\":[0.0,0.0400359985445974,0.08145255083720931,0.12317668600384774,0.16332186262839976,0.20334077455314054,0.2469333873920436,0.28713771140956895,0.3279363491382488,0.36863881728802655,0.40934376094722014,0.45148138714239483,0.49183389221671747,0.5328442739822793,0.5752122197626396,0.6388863860584918,0.6833186405436193,0.7258351980605862,0.7660545685680962,0.8096508343578392,0.8510125385793297,0.8919175828395187,0.932921814538824,0.9751701238406658,1.016405193742034,1.0629667297988847,1.1033829289833594,1.1464316582450662,1.1873763736706544,1.2343301391064416,1.274891656567059,1.315436411683894,1.3581081858287865,1.3992809470620664,1.447911347196082,1.488471697539021,1.5291736285548627,1.5702809204764918,1.6139533861632038,1.6571990918445956,1.705939111654279,1.7523112624893404,1.7928837506739137,1.836296744290599,1.878231335756673,1.9196698015131701,1.9686683716589302,2.0160939801028066,2.06551076215993,2.108872746925114,2.158536548832477,2.201613031292431,2.2428403227686835,2.2900655423726,2.338504965231361,2.3821182169217576,2.437304673090977,2.504965505514344,2.549112635474689,2.5963427007355118,2.639404938646551,2.680273610838007,2.7502717014667937,2.7975659401939263,2.8547235019700463,2.9062140261518024,2.9471045513125604,3.0059613999904933,3.0522890279291386,3.1310595904685723,3.185026772800433,3.2299394734846607,3.2910736780018897,3.3412918451146583,3.4049073090774065,3.446502887666085,3.498090542648599,3.5592511922106573,3.6233332455414202,3.6688129483215937,3.740961426033741,3.8423184758971005,3.957390099406925,4.03809823606079,4.091607004314039,4.147013578236524,4.206192806203972,4.3030443176644,4.3647841488667245,4.407868987727099,4.475431814370238,4.51970323805272,4.562748697984685,4.6059304758435085,4.650472652571026,4.693280387163547,4.744007344503794,4.785207696445642,4.831109452595536,4.887207527107414,4.931752792130138,4.972562762223781,5.014862757281701,5.061295754950194,5.103944410682383,5.147289197550972,5.189801695122156,5.230265169130304,5.273295733648928,5.31540548969697,5.362220633414314,5.402400778814609,5.450380009387233,5.492417896979264,5.533784788634675,5.573881009972379,5.614731584918084,5.657534239999992,5.697683160634004,5.738806923319024,5.779080611022558,5.8203107795220115,5.86119003677963,5.902265403054742,5.942637934671833,5.984016942092992,6.024958623818848,6.066392907550334,6.1086936351100745,6.149599464194887,6.1898014884816375,6.2300455469077,6.2703807812256205,6.3110730270850315,6.3521001476447365,6.392117627884677,6.432476065714841,6.47320897500449,6.51335800345607,6.5537992487959995,6.594862851861638,6.635803919298715,6.67683336561045,6.718531160921211,6.758587570449445,6.799040844473917,6.841298825506195,6.88173441079602,6.921971947367163,6.965553855274469,7.009660227117509,7.0499786941937295,7.090255986630856,7.131213663371943,7.1720574922991105,7.220902158136783,7.2625310767106805,7.304860098333161,7.347328760282252,7.3961774935497475,7.436982168326693,7.479270975690839,7.525454681029805,7.566016432658887,7.6093161513511625,7.649452204798534,7.691121922056621,7.744271056820239,7.796900013813918,7.838614532393019,7.885316372899439,7.941649387846778,7.982197871153491,8.036741831759429,8.080411484451444,8.122494282880014,8.174591821008523,8.223527905640582,8.26359959541336,8.32320170863728,8.424989968958432,8.467976374855496,8.55816723405702,8.600115967681274,8.659099019846483,8.699646794861488,8.758532000198182,8.823926520682834,8.899531971144109,8.952476191129206,9.014203756187833,9.117303884041645,9.165466542347188,9.226583072826969,9.289934395979339,9.388811149605784,9.56615602517557,9.606388721577511,9.65105772983676,9.694093102181563,9.748376960775488,9.801155099666232,9.860225639552755,9.990603105885791,10.184138011730605,10.29368935233564,10.333712436626595,10.38733622361642,10.463623628533282,10.647484783042602,10.73129036050474,10.794263451979225,10.954794689102506,11.201039947874026,11.393298833073409,12.237957238811328,12.638338330751832,13.423728415728995,40.0]}},\"id\":\"8e14dd7c-b23f-4b73-8878-3d2fad41a8b1\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_color\":\"#ff7f0e\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"6344f97c-96f7-47c3-9883-f6584fac532a\",\"type\":\"Line\"},{\"attributes\":{\"filters\":[{\"id\":\"6ab7d1ea-5f73-4fc0-9505-b95bee90235f\",\"type\":\"IndexFilter\"}],\"source\":{\"id\":\"8e14dd7c-b23f-4b73-8878-3d2fad41a8b1\",\"type\":\"ColumnDataSource\"}},\"id\":\"3328e5b5-1115-47fb-b8e0-7e29ce9d259c\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"11e91d72-ccdf-425c-bc21-9d6811ea1fba\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"background_fill_alpha\":{\"value\":0.3},\"background_fill_color\":{\"value\":\"oldlace\"},\"below\":[{\"id\":\"15886b04-70ed-4144-ae3d-98e11086fe7d\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"797f0999-0624-4501-912e-e0024c784936\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":640,\"renderers\":[{\"id\":\"15886b04-70ed-4144-ae3d-98e11086fe7d\",\"type\":\"LinearAxis\"},{\"id\":\"b0b230b4-f330-4a56-9309-548581803eff\",\"type\":\"Grid\"},{\"id\":\"797f0999-0624-4501-912e-e0024c784936\",\"type\":\"LinearAxis\"},{\"id\":\"ec596bde-a76e-4621-9576-266a8f8b3450\",\"type\":\"Grid\"},{\"id\":\"4c74acec-9985-494b-9458-7a33710024c4\",\"type\":\"BoxAnnotation\"},{\"id\":\"061bc021-d9c8-4e50-990c-e6b9cc5e4d35\",\"type\":\"GlyphRenderer\"},{\"id\":\"44cc01a9-f804-4c2b-ab1a-941abcc3009b\",\"type\":\"GlyphRenderer\"},{\"id\":\"ca1d9696-0c81-403e-aab2-1a8582e6b537\",\"type\":\"Legend\"}],\"right\":[{\"id\":\"ca1d9696-0c81-403e-aab2-1a8582e6b537\",\"type\":\"Legend\"}],\"title\":{\"id\":\"6eff9b57-c059-43dc-9e40-3ed2f13f0a80\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"87d5b86f-122a-4209-8028-edd084d408b8\",\"type\":\"Toolbar\"},\"toolbar_location\":\"below\",\"toolbar_sticky\":false,\"x_range\":{\"id\":\"3ade8706-ff6f-4139-8780-02193dda79a4\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"1e57afb0-6c04-40e5-a92a-be38161c5a89\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"0c97a7a5-6503-4821-9f24-36c8c864f1b1\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"81eeceec-05ee-4b26-90ca-aaf9199dad71\",\"type\":\"LinearScale\"}},\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"b5a63db7-eeb0-4ab0-b98d-74cdeb084265\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"6eff9b57-c059-43dc-9e40-3ed2f13f0a80\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null},\"id\":\"0c97a7a5-6503-4821-9f24-36c8c864f1b1\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"b77520c4-8886-4227-8542-12da4fd2c724\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"d11fba17-326d-4c2f-860e-2f5181b6f8df\",\"type\":\"Line\"},{\"attributes\":{\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"ae4621b7-5bc8-4101-8b0b-c8e66eab5d7e\",\"type\":\"BasicTicker\"}},\"id\":\"b0b230b4-f330-4a56-9309-548581803eff\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"a68b3f8e-41b3-4d57-aa67-22996d604900\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1e57afb0-6c04-40e5-a92a-be38161c5a89\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"5701960c-0999-46eb-af7e-92865c7c1f28\",\"type\":\"PanTool\"},{\"attributes\":{\"data_source\":{\"id\":\"8e14dd7c-b23f-4b73-8878-3d2fad41a8b1\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"6344f97c-96f7-47c3-9883-f6584fac532a\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"d11fba17-326d-4c2f-860e-2f5181b6f8df\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"3328e5b5-1115-47fb-b8e0-7e29ce9d259c\",\"type\":\"CDSView\"}},\"id\":\"44cc01a9-f804-4c2b-ab1a-941abcc3009b\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"border_line_color\":{\"value\":\"gray\"},\"click_policy\":\"hide\",\"items\":[{\"id\":\"acea540a-067a-43b9-9be6-18317da07e49\",\"type\":\"LegendItem\"},{\"id\":\"a8276435-4230-4ea1-99b0-65f91d0fe54b\",\"type\":\"LegendItem\"}],\"location\":[10,0],\"plot\":{\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ca1d9696-0c81-403e-aab2-1a8582e6b537\",\"type\":\"Legend\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"x,y\",\"$x, $y\"]]},\"id\":\"8edc1a0d-2268-4f5b-a7f9-421f775b3dcc\",\"type\":\"HoverTool\"},{\"attributes\":{\"axis_label\":\"Time\",\"formatter\":{\"id\":\"11e91d72-ccdf-425c-bc21-9d6811ea1fba\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"ae4621b7-5bc8-4101-8b0b-c8e66eab5d7e\",\"type\":\"BasicTicker\"}},\"id\":\"15886b04-70ed-4144-ae3d-98e11086fe7d\",\"type\":\"LinearAxis\"},{\"attributes\":{\"formatter\":{\"id\":\"b5a63db7-eeb0-4ab0-b98d-74cdeb084265\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3ddb6b6d-bc06-4a29-ab2b-7c70a2c0cd41\",\"type\":\"BasicTicker\"}},\"id\":\"797f0999-0624-4501-912e-e0024c784936\",\"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\":\"4c74acec-9985-494b-9458-7a33710024c4\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"9c266a62-2cf4-420c-8a9c-4ec7e22131d0\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"3ddb6b6d-bc06-4a29-ab2b-7c70a2c0cd41\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"175f467f-1152-448d-b2d2-6e118902fb9a\",\"type\":\"UndoTool\"},{\"attributes\":{\"active_drag\":{\"id\":\"3dfb603e-75ce-49ff-8404-694e56b2076b\",\"type\":\"BoxZoomTool\"},\"active_inspect\":\"auto\",\"active_scroll\":null,\"active_tap\":\"auto\",\"tools\":[{\"id\":\"5701960c-0999-46eb-af7e-92865c7c1f28\",\"type\":\"PanTool\"},{\"id\":\"b77520c4-8886-4227-8542-12da4fd2c724\",\"type\":\"WheelZoomTool\"},{\"id\":\"3dfb603e-75ce-49ff-8404-694e56b2076b\",\"type\":\"BoxZoomTool\"},{\"id\":\"7d8d65f9-48fe-4507-ba9f-ad4ad8d0b5dc\",\"type\":\"ResetTool\"},{\"id\":\"9c266a62-2cf4-420c-8a9c-4ec7e22131d0\",\"type\":\"SaveTool\"},{\"id\":\"175f467f-1152-448d-b2d2-6e118902fb9a\",\"type\":\"UndoTool\"},{\"id\":\"8edc1a0d-2268-4f5b-a7f9-421f775b3dcc\",\"type\":\"HoverTool\"}]},\"id\":\"87d5b86f-122a-4209-8028-edd084d408b8\",\"type\":\"Toolbar\"}],\"root_ids\":[\"16200e6b-5025-4de8-98cd-2d7a6abed93c\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"30fee2a1-b758-4a91-a28a-4fa671540fa1\",\"elementid\":\"61a1e3f6-9a34-4232-8252-8c633603a22b\",\"modelid\":\"16200e6b-5025-4de8-98cd-2d7a6abed93c\",\"notebook_comms_target\":\"6f57aedd-94d0-461d-936e-6efa3ee1d94c\"}];\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
650
       "id": "16200e6b-5025-4de8-98cd-2d7a6abed93c"
FAGES Francois's avatar
TD12  
FAGES Francois committed
651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seed(0). numerical_simulation(method:ssa). plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
670
       "    <div class=\"bk-plotdiv\" id=\"b96d089c-fac7-40eb-b054-bd585a76727e\"></div>\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
671 672 673 674 675 676 677 678 679 680 681 682
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
683 684
       "  var docs_json = {\"3a06f898-152b-4df3-8c72-c27a05c69ad4\":{\"roots\":{\"references\":[{\"attributes\":{\"callback\":null},\"id\":\"e7b5c4c3-72e3-444f-bf9a-d8b99a43cbe2\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"a7b9b296-eac7-4bcd-b1ec-9e2e3506dca4\",\"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\":\"a52d1518-4760-4078-8e30-9397274ddac0\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"B\",\"A\",\"Time\"],\"data\":{\"A\":[100.0,99.0,105.0,101.0,101.0,105.0,106.0,103.0,95.0,89.0,79.0,75.0,75.0,68.0,61.0,59.0,60.0,62.0,61.0,55.0,47.0,50.0,46.0,42.0,35.0,33.0,27.0,24.0,20.0,17.0,14.0,15.0,14.0,14.0,14.0,16.0,15.0,14.0,14.0,15.0,11.0,12.0,12.0,13.0,12.0,13.0,14.0,14.0,14.0,13.0,11.0,9.0,7.0,8.0,8.0,6.0,7.0,7.0,5.0,5.0,5.0,5.0,5.0,5.0,4.0,4.0,4.0,5.0,6.0,6.0,5.0,5.0,6.0,7.0,7.0,7.0,6.0,6.0,6.0,7.0,8.0,8.0,8.0,9.0,8.0,8.0,9.0,10.0,13.0,16.0,18.0,19.0,19.0,22.0,25.0,29.0,33.0,36.0,43.0,47.0,53.0,58.0,62.0,70.0,78.0,84.0,86.0,93.0,104.0,110.0,123.0,132.0,140.0,159.0,171.0,180.0,200.0,222.0,238.0,253.0,273.0,291.0,312.0,332.0,349.0,376.0,398.0,414.0,413.0,399.0,388.0,331.0,295.0,241.0,204.0,152.0,115.0,84.0,55.0,39.0,28.0,31.0,19.0,14.0,8.0,7.0,4.0,4.0,4.0,3.0,4.0,3.0,2.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],\"B\":[100.0,106.0,107.0,107.0,114.0,120.0,124.0,132.0,143.0,148.0,158.0,163.0,162.0,163.0,168.0,166.0,166.0,165.0,173.0,176.0,183.0,177.0,179.0,181.0,186.0,184.0,187.0,181.0,178.0,176.0,173.0,168.0,160.0,154.0,153.0,151.0,150.0,148.0,142.0,132.0,130.0,127.0,120.0,115.0,110.0,105.0,103.0,100.0,95.0,92.0,90.0,92.0,89.0,85.0,83.0,79.0,78.0,73.0,72.0,70.0,66.0,62.0,59.0,53.0,49.0,45.0,43.0,43.0,42.0,39.0,38.0,36.0,36.0,34.0,32.0,29.0,29.0,26.0,25.0,23.0,22.0,20.0,18.0,17.0,17.0,16.0,15.0,15.0,15.0,14.0,14.0,13.0,14.0,12.0,11.0,11.0,10.0,9.0,8.0,8.0,8.0,8.0,8.0,8.0,7.0,6.0,8.0,10.0,12.0,11.0,10.0,8.0,9.0,8.0,8.0,8.0,7.0,8.0,9.0,13.0,17.0,20.0,23.0,28.0,37.0,46.0,57.0,76.0,104.0,146.0,184.0,256.0,307.0,356.0,395.0,443.0,477.0,500.0,522.0,517.0,519.0,502.0,500.0,484.0,476.0,462.0,436.0,424.0,418.0,395.0,378.0,361.0,348.0,336.0,318.0,302.0,286.0,274.0,266.0,258.0,242.0,233.0,220.0,208.0,196.0,187.0,174.0,168.0,162.0,149.0,140.0,129.0,126.0,120.0,115.0,108.0,103.0,100.0,95.0,92.0,89.0,83.0,77.0,73.0,69.0,67.0,62.0,56.0,54.0,51.0,48.0,45.0,42.0,38.0,36.0,35.0,33.0,32.0,29.0,26.0,24.0,22.0,21.0,20.0,17.0,16.0,14.0,13.0,12.0,10.0,9.0,8.0,7.0,5.0,3.0,2.0,1.0,0.0,0.0],\"Time\":[0.0,0.0400359985445974,0.08145255083720931,0.12317668600384774,0.16332186262839976,0.20334077455314054,0.2469333873920436,0.28713771140956895,0.3279363491382488,0.36863881728802655,0.40934376094722014,0.45148138714239483,0.49183389221671747,0.5328442739822793,0.5752122197626396,0.6388863860584918,0.6833186405436193,0.7258351980605862,0.7660545685680962,0.8096508343578392,0.8510125385793297,0.8919175828395187,0.932921814538824,0.9751701238406658,1.016405193742034,1.0629667297988847,1.1033829289833594,1.1464316582450662,1.1873763736706544,1.2343301391064416,1.274891656567059,1.315436411683894,1.3581081858287865,1.3992809470620664,1.447911347196082,1.488471697539021,1.5291736285548627,1.5702809204764918,1.6139533861632038,1.6571990918445956,1.705939111654279,1.7523112624893404,1.7928837506739137,1.836296744290599,1.878231335756673,1.9196698015131701,1.9686683716589302,2.0160939801028066,2.06551076215993,2.108872746925114,2.158536548832477,2.201613031292431,2.2428403227686835,2.2900655423726,2.338504965231361,2.3821182169217576,2.437304673090977,2.504965505514344,2.549112635474689,2.5963427007355118,2.639404938646551,2.680273610838007,2.7502717014667937,2.7975659401939263,2.8547235019700463,2.9062140261518024,2.9471045513125604,3.0059613999904933,3.0522890279291386,3.1310595904685723,3.185026772800433,3.2299394734846607,3.2910736780018897,3.3412918451146583,3.4049073090774065,3.446502887666085,3.498090542648599,3.5592511922106573,3.6233332455414202,3.6688129483215937,3.740961426033741,3.8423184758971005,3.957390099406925,4.03809823606079,4.091607004314039,4.147013578236524,4.206192806203972,4.3030443176644,4.3647841488667245,4.407868987727099,4.475431814370238,4.51970323805272,4.562748697984685,4.6059304758435085,4.650472652571026,4.693280387163547,4.744007344503794,4.785207696445642,4.831109452595536,4.887207527107414,4.931752792130138,4.972562762223781,5.014862757281701,5.061295754950194,5.103944410682383,5.147289197550972,5.189801695122156,5.230265169130304,5.273295733648928,5.31540548969697,5.362220633414314,5.402400778814609,5.450380009387233,5.492417896979264,5.533784788634675,5.573881009972379,5.614731584918084,5.657534239999992,5.697683160634004,5.738806923319024,5.779080611022558,5.8203107795220115,5.86119003677963,5.902265403054742,5.942637934671833,5.984016942092992,6.024958623818848,6.066392907550334,6.1086936351100745,6.149599464194887,6.1898014884816375,6.2300455469077,6.2703807812256205,6.3110730270850315,6.3521001476447365,6.392117627884677,6.432476065714841,6.47320897500449,6.51335800345607,6.5537992487959995,6.594862851861638,6.635803919298715,6.67683336561045,6.718531160921211,6.758587570449445,6.799040844473917,6.841298825506195,6.88173441079602,6.921971947367163,6.965553855274469,7.009660227117509,7.0499786941937295,7.090255986630856,7.131213663371943,7.1720574922991105,7.220902158136783,7.2625310767106805,7.304860098333161,7.347328760282252,7.3961774935497475,7.436982168326693,7.479270975690839,7.525454681029805,7.566016432658887,7.6093161513511625,7.649452204798534,7.691121922056621,7.744271056820239,7.796900013813918,7.838614532393019,7.885316372899439,7.941649387846778,7.982197871153491,8.036741831759429,8.080411484451444,8.122494282880014,8.174591821008523,8.223527905640582,8.26359959541336,8.32320170863728,8.424989968958432,8.467976374855496,8.55816723405702,8.600115967681274,8.659099019846483,8.699646794861488,8.758532000198182,8.823926520682834,8.899531971144109,8.952476191129206,9.014203756187833,9.117303884041645,9.165466542347188,9.226583072826969,9.289934395979339,9.388811149605784,9.56615602517557,9.606388721577511,9.65105772983676,9.694093102181563,9.748376960775488,9.801155099666232,9.860225639552755,9.990603105885791,10.184138011730605,10.29368935233564,10.333712436626595,10.38733622361642,10.463623628533282,10.647484783042602,10.73129036050474,10.794263451979225,10.954794689102506,11.201039947874026,11.393298833073409,12.237957238811328,12.638338330751832,13.423728415728995,40.0]}},\"id\":\"f709418f-0868-4acb-badd-064368d44a1b\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"eaf12eaf-6f34-4890-bda1-13228fb751b8\",\"type\":\"BasicTicker\"}},\"id\":\"fc705d9f-9fa3-4db9-a0fb-c8de66a9b3f1\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"b9b2b610-5748-42a7-adbf-2468c7da6e85\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_drag\":{\"id\":\"91baed84-9592-4a2f-ab99-7229585627ed\",\"type\":\"BoxZoomTool\"},\"active_inspect\":\"auto\",\"active_scroll\":null,\"active_tap\":\"auto\",\"tools\":[{\"id\":\"b3a5f487-0275-4de8-8252-e11daf2ad169\",\"type\":\"PanTool\"},{\"id\":\"f116c8e7-3ff3-41de-90e5-b8cd1663120e\",\"type\":\"WheelZoomTool\"},{\"id\":\"91baed84-9592-4a2f-ab99-7229585627ed\",\"type\":\"BoxZoomTool\"},{\"id\":\"f0b6e7b5-8d65-4155-bd10-504d47b325b8\",\"type\":\"ResetTool\"},{\"id\":\"27db86c5-8db1-471f-9e49-c9021ded6411\",\"type\":\"SaveTool\"},{\"id\":\"64738ea7-f26d-4005-9245-76a49a147c2c\",\"type\":\"UndoTool\"},{\"id\":\"10acb2b8-6cc2-48fd-894b-ed0455aa3989\",\"type\":\"HoverTool\"}]},\"id\":\"a3aa0fe5-7e8a-4ebd-8081-fa24860a3865\",\"type\":\"Toolbar\"},{\"attributes\":{\"overlay\":{\"id\":\"a52d1518-4760-4078-8e30-9397274ddac0\",\"type\":\"BoxAnnotation\"}},\"id\":\"91baed84-9592-4a2f-ab99-7229585627ed\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"filters\":[{\"id\":\"bd913e23-bd0c-4daf-821c-6cf94b55d64d\",\"type\":\"IndexFilter\"}],\"source\":{\"id\":\"f709418f-0868-4acb-badd-064368d44a1b\",\"type\":\"ColumnDataSource\"}},\"id\":\"c416c889-d61c-4d51-84e1-81a5b224d06a\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"64738ea7-f26d-4005-9245-76a49a147c2c\",\"type\":\"UndoTool\"},{\"attributes\":{\"callback\":null,\"end\":574.2,\"start\":-52.2},\"id\":\"9832a420-c153-48f5-b2a7-cfbb17f7e7c8\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"08954a5a-0a8b-4480-8489-7a87d73f73d2\",\"type\":\"LinearScale\"},{\"attributes\":{\"border_line_color\":{\"value\":\"gray\"},\"click_policy\":\"hide\",\"items\":[{\"id\":\"de6150ec-25db-4df2-aff2-f0dcd2218d8b\",\"type\":\"LegendItem\"}],\"location\":[10,0],\"plot\":{\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b82af70f-a04c-42ff-b34b-703802940aa1\",\"type\":\"Legend\"},{\"attributes\":{\"axis_label\":\"A\",\"formatter\":{\"id\":\"a7b9b296-eac7-4bcd-b1ec-9e2e3506dca4\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"eaf12eaf-6f34-4890-bda1-13228fb751b8\",\"type\":\"BasicTicker\"}},\"id\":\"d86d0d89-567a-423d-bdfa-71dc27c6cd9e\",\"type\":\"LinearAxis\"},{\"attributes\":{\"formatter\":{\"id\":\"3e9aa63f-28ac-4add-84e1-7283e2e19d55\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b9b2b610-5748-42a7-adbf-2468c7da6e85\",\"type\":\"BasicTicker\"}},\"id\":\"ad987850-a27d-43aa-8e1e-7f3ee3f2e716\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"f0b6e7b5-8d65-4155-bd10-504d47b325b8\",\"type\":\"ResetTool\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"A\"},\"y\":{\"field\":\"B\"}},\"id\":\"8dcc74d3-0990-4b76-b8bb-1c349745e117\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"eaf12eaf-6f34-4890-bda1-13228fb751b8\",\"type\":\"BasicTicker\"},{\"attributes\":{\"background_fill_alpha\":{\"value\":0.3},\"background_fill_color\":{\"value\":\"oldlace\"},\"below\":[{\"id\":\"d86d0d89-567a-423d-bdfa-71dc27c6cd9e\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"ad987850-a27d-43aa-8e1e-7f3ee3f2e716\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":640,\"renderers\":[{\"id\":\"d86d0d89-567a-423d-bdfa-71dc27c6cd9e\",\"type\":\"LinearAxis\"},{\"id\":\"fc705d9f-9fa3-4db9-a0fb-c8de66a9b3f1\",\"type\":\"Grid\"},{\"id\":\"ad987850-a27d-43aa-8e1e-7f3ee3f2e716\",\"type\":\"LinearAxis\"},{\"id\":\"82e479f0-23a4-4a10-955b-3a25e52e1e64\",\"type\":\"Grid\"},{\"id\":\"a52d1518-4760-4078-8e30-9397274ddac0\",\"type\":\"BoxAnnotation\"},{\"id\":\"fcf0e427-3506-46d5-a0d7-4e0b238be067\",\"type\":\"GlyphRenderer\"},{\"id\":\"b82af70f-a04c-42ff-b34b-703802940aa1\",\"type\":\"Legend\"}],\"right\":[{\"id\":\"b82af70f-a04c-42ff-b34b-703802940aa1\",\"type\":\"Legend\"}],\"title\":{\"id\":\"e28ea4b4-5646-47fd-935e-530556d63ae6\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"a3aa0fe5-7e8a-4ebd-8081-fa24860a3865\",\"type\":\"Toolbar\"},\"toolbar_location\":\"below\",\"toolbar_sticky\":false,\"x_range\":{\"id\":\"e7b5c4c3-72e3-444f-bf9a-d8b99a43cbe2\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"264b1520-6bd1-41b7-a219-15f875fc7f1b\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"9832a420-c153-48f5-b2a7-cfbb17f7e7c8\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"08954a5a-0a8b-4480-8489-7a87d73f73d2\",\"type\":\"LinearScale\"}},\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"x,y\",\"$x, $y\"]]},\"id\":\"10acb2b8-6cc2-48fd-894b-ed0455aa3989\",\"type\":\"HoverTool\"},{\"attributes\":{\"data_source\":{\"id\":\"f709418f-0868-4acb-badd-064368d44a1b\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"8dcc74d3-0990-4b76-b8bb-1c349745e117\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"22eb7990-d45c-4c6a-94d9-e1d3258708e9\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"c416c889-d61c-4d51-84e1-81a5b224d06a\",\"type\":\"CDSView\"}},\"id\":\"fcf0e427-3506-46d5-a0d7-4e0b238be067\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"3e9aa63f-28ac-4add-84e1-7283e2e19d55\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"27db86c5-8db1-471f-9e49-c9021ded6411\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"f116c8e7-3ff3-41de-90e5-b8cd1663120e\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"A\"},\"y\":{\"field\":\"B\"}},\"id\":\"22eb7990-d45c-4c6a-94d9-e1d3258708e9\",\"type\":\"Line\"},{\"attributes\":{\"indices\":[]},\"id\":\"bd913e23-bd0c-4daf-821c-6cf94b55d64d\",\"type\":\"IndexFilter\"},{\"attributes\":{\"label\":{\"value\":\"B\"},\"renderers\":[{\"id\":\"fcf0e427-3506-46d5-a0d7-4e0b238be067\",\"type\":\"GlyphRenderer\"}]},\"id\":\"de6150ec-25db-4df2-aff2-f0dcd2218d8b\",\"type\":\"LegendItem\"},{\"attributes\":{\"dimension\":1,\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"b9b2b610-5748-42a7-adbf-2468c7da6e85\",\"type\":\"BasicTicker\"}},\"id\":\"82e479f0-23a4-4a10-955b-3a25e52e1e64\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"b3a5f487-0275-4de8-8252-e11daf2ad169\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"264b1520-6bd1-41b7-a219-15f875fc7f1b\",\"type\":\"LinearScale\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"e28ea4b4-5646-47fd-935e-530556d63ae6\",\"type\":\"Title\"}],\"root_ids\":[\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"3a06f898-152b-4df3-8c72-c27a05c69ad4\",\"elementid\":\"b96d089c-fac7-40eb-b054-bd585a76727e\",\"modelid\":\"21b5837a-f72c-4ee0-98ee-edec5f715e4d\",\"notebook_comms_target\":\"388a5051-9f61-4670-9ed9-1e03c70552de\"}];\n",
FAGES Francois's avatar
TD12  
FAGES Francois committed
685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
710
       "id": "21b5837a-f72c-4ee0-98ee-edec5f715e4d"
FAGES Francois's avatar
TD12  
FAGES Francois committed
711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(show:B, against:A)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Boolean semantics\n",
    "* reason just on the presence or absence of molecular species\n",
    "* asynchronous Boolean transition system ignoring reaction rates\n",
    "* SAT algorithm for enumerating all stable states, here: \n",
    " * either both A, B absent is a stable state\n",
    " * or B absent A present\n",
    " * yet both A and B present is not stable since A and B may disappear in this case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[A-0,B-0]\r\n",
       "[A-1,B-0]\r\n"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_stable_states."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Computation Tree Logic (CTL) symbolic model-checking algorithm for enumerating possible qualitative behaviors of interest, here:\n",
    " * both A and B may extinguish\n",
    " * species A may survive with no possibility of disappearing (reachability of stable state A present)\n",
    " * B may survive but with always the possibility of disappearing (reachability of non stable steady state B present)\n",
    " * no Boolean oscillation possible (0 is stable)\n",
    " * checkpoints are possibly non causal phenomenological properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reachable(stable('A'))\r\n",
       "reachable(stable(not'A'))\r\n",
       "reachable(stable(not'B'))\r\n",
       "reachable(steady('B'))\r\n",
       "checkpoint2('B',not'A')\r\n",
       "checkpoint2('A',not'B')\r\n"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generate_ctl_not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AG(f)\r\n"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expand_ctl(stable(f))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EG(f)\r\n"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expand_ctl(steady(f))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EF(EG(s))\r\n"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expand_ctl(reachable(steady(s)))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "not EU(not x,y)\r\n"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expand_ctl(checkpoint(x,y))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EF(y)/\\not EU(not x,y)\r\n"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expand_ctl(checkpoint2(x,y))."
   ]
  },
  {
   "cell_type": "code",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
893
   "execution_count": 24,
FAGES Francois's avatar
TD12  
FAGES Francois committed
894 895 896 897 898 899 900 901
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reachable(checkpoint2(not A,not B)) is true\r\n"
      ]
     },
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
902
     "execution_count": 24,
FAGES Francois's avatar
TD12  
FAGES Francois committed
903 904 905 906 907 908 909 910 911 912
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_ctl(query: reachable(checkpoint2(not A, not B)))."
   ]
  },
  {
   "cell_type": "code",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
913
   "execution_count": 25,
FAGES Francois's avatar
TD12  
FAGES Francois committed
914 915 916 917 918 919 920 921
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reachable(checkpoint2(not B,not A)) is false\r\n"
      ]
     },
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
922
     "execution_count": 25,
FAGES Francois's avatar
TD12  
FAGES Francois committed
923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_ctl(query: reachable(checkpoint2(not B, not A)))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Questions on the continuous semantics\n",
    "\n",
    "\n",
    "### 1) play with the sliders below to change the parameter values "
   ]
  },
  {
   "cell_type": "code",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
943
   "execution_count": 26,
FAGES Francois's avatar
TD12  
FAGES Francois committed
944
   "metadata": {},
FAGES Francois's avatar
cours2  
FAGES Francois committed
945 946 947 948
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
949
       "model_id": "c61af34506c14d1285933e1f0bda2214",
FAGES Francois's avatar
cours2  
FAGES Francois committed
950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Box</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Box(children=(SelectionSlider(continuous_update=False, description='k1', index=10, layout=Layout(min_width='300px'), options=(('0', 0.0), ('0.2', 0.2), ('0.4', 0.4), ('0.6', 0.6000000000000001), ('0.8', 0.8), ('1', 1.0), ('1.2', 1.2000000000000002), ('1.4', 1.4000000000000001), ('1.6', 1.6), ('1.8', 1.8), ('2', 2.0), ('2.2', 2.2), ('2.4', 2.4000000000000004), ('2.6', 2.6), ('2.8', 2.8000000000000003), ('3', 3.0), ('3.2', 3.2), ('3.4', 3.4000000000000004), ('3.6', 3.6), ('3.8', 3.8000000000000003), ('4', 4.0), ('4.2', 4.2), ('4.4', 4.4), ('4.6', 4.6000000000000005), ('4.8', 4.800000000000001), ('5', 5.0), ('5.2', 5.2), ('5.4', 5.4), ('5.6', 5.6000000000000005), ('5.8', 5.800000000000001), ('6', 6.0), ('6.2', 6.2), ('6.4', 6.4), ('6.6', 6.6000000000000005), ('6.8', 6.800000000000001), ('7', 7.0), ('7.2', 7.2), ('7.4', 7.4), ('7.6', 7.6000000000000005), ('7.8', 7.800000000000001), ('8', 8.0), ('8.2', 8.200000000000001), ('8.4', 8.4), ('8.6', 8.6), ('8.8', 8.8), ('9', 9.0), ('9.2', 9.200000000000001), ('9.4', 9.4), ('9.6', 9.600000000000001), ('9.8', 9.8), ('10', 10.0), ('10.2', 10.200000000000001), ('10.4', 10.4), ('10.6', 10.600000000000001), ('10.8', 10.8), ('11', 11.0), ('11.2', 11.200000000000001), ('11.4', 11.4), ('11.6', 11.600000000000001), ('11.8', 11.8), ('12', 12.0), ('12.2', 12.200000000000001), ('12.4', 12.4), ('12.6', 12.600000000000001), ('12.8', 12.8), ('13', 13.0), ('13.2', 13.200000000000001), ('13.4', 13.4), ('13.6', 13.600000000000001), ('13.8', 13.8), ('14', 14.0), ('14.2', 14.200000000000001), ('14.4', 14.4), ('14.6', 14.600000000000001), ('14.8', 14.8), ('15', 15.0), ('15.2', 15.200000000000001), ('15.4', 15.4), ('15.6', 15.600000000000001), ('15.8', 15.8), ('16', 16.0), ('16.2', 16.2), ('16.4', 16.400000000000002), ('16.6', 16.6), ('16.8', 16.8), ('17', 17.0), ('17.2', 17.2), ('17.4', 17.400000000000002), ('17.6', 17.6), ('17.8', 17.8), ('18', 18.0), ('18.2', 18.2), ('18.4', 18.400000000000002), ('18.6', 18.6), ('18.8', 18.8), ('19', 19.0), ('19.2', 19.200000000000003), ('19.4', 19.400000000000002), ('19.6', 19.6), ('19.8', 19.8), ('20', 20.0)), value=2.0), SelectionSlider(continuous_update=False, description='k2', index=10, layout=Layout(min_width='300px'), options=(('0', 0.0), ('0.2', 0.2), ('0.4', 0.4), ('0.6', 0.6000000000000001), ('0.8', 0.8), ('1', 1.0), ('1.2', 1.2000000000000002), ('1.4', 1.4000000000000001), ('1.6', 1.6), ('1.8', 1.8), ('2', 2.0), ('2.2', 2.2), ('2.4', 2.4000000000000004), ('2.6', 2.6), ('2.8', 2.8000000000000003), ('3', 3.0), ('3.2', 3.2), ('3.4', 3.4000000000000004), ('3.6', 3.6), ('3.8', 3.8000000000000003), ('4', 4.0), ('4.2', 4.2), ('4.4', 4.4), ('4.6', 4.6000000000000005), ('4.8', 4.800000000000001), ('5', 5.0), ('5.2', 5.2), ('5.4', 5.4), ('5.6', 5.6000000000000005), ('5.8', 5.800000000000001), ('6', 6.0), ('6.2', 6.2), ('6.4', 6.4), ('6.6', 6.6000000000000005), ('6.8', 6.800000000000001), ('7', 7.0), ('7.2', 7.2), ('7.4', 7.4), ('7.6', 7.6000000000000005), ('7.8', 7.800000000000001), ('8', 8.0), ('8.2', 8.200000000000001), ('8.4', 8.4), ('8.6', 8.6), ('8.8', 8.8), ('9', 9.0), ('9.2', 9.200000000000001), ('9.4', 9.4), ('9.6', 9.600000000000001), ('9.8', 9.8), ('10', 10.0), ('10.2', 10.200000000000001), ('10.4', 10.4), ('10.6', 10.600000000000001), ('10.8', 10.8), ('11', 11.0), ('11.2', 11.200000000000001), ('11.4', 11.4), ('11.6', 11.600000000000001), ('11.8', 11.8), ('12', 12.0), ('12.2', 12.200000000000001), ('12.4', 12.4), ('12.6', 12.600000000000001), ('12.8', 12.8), ('13', 13.0), ('13.2', 13.200000000000001), ('13.4', 13.4), ('13.6', 13.600000000000001), ('13.8', 13.8), ('14', 14.0), ('14.2', 14.200000000000001), ('14.4', 14.4), ('14.6', 14.600000000000001), ('14.8', 14.8), ('15', 15.0), ('15.2', 15.200000000000001), ('15.4', 15.4), ('15.6', 15.600000000000001), ('15.8', 15.8), ('16', 16.0), ('16.2', 16.2), ('16.4', 16.400000000000002), ('16.6', 16.6), ('16.8', 16.8), ('17', 17.0), ('17.2', 17.2), ('17.4', 17.400000000000002), ('17.6', 17.6), ('17.8', 17.8), ('18', 18.0), ('18.2', 18.2), ('18.4', 18.400000000000002), ('18.6', 18.6), ('18.8', 18.8), ('19', 19.0), ('19.2', 19.200000000000003), ('19.4', 19.400000000000002), ('19.6', 19.6), ('19.8', 19.8), ('20', 20.0)), value=2.0), SelectionSlider(continuous_update=False, description='k3', index=10, layout=Layout(min_width='300px'), options=(('0', 0.0), ('0.1', 0.1), ('0.2', 0.2), ('0.3', 0.30000000000000004), ('0.4', 0.4), ('0.5', 0.5), ('0.6', 0.6000000000000001), ('0.7', 0.7000000000000001), ('0.8', 0.8), ('0.9', 0.9), ('1', 1.0), ('1.1', 1.1), ('1.2', 1.2000000000000002), ('1.3', 1.3), ('1.4', 1.4000000000000001), ('1.5', 1.5), ('1.6', 1.6), ('1.7', 1.7000000000000002), ('1.8', 1.8), ('1.9', 1.9000000000000001), ('2', 2.0), ('2.1', 2.1), ('2.2', 2.2), ('2.3', 2.3000000000000003), ('2.4', 2.4000000000000004), ('2.5', 2.5), ('2.6', 2.6), ('2.7', 2.7), ('2.8', 2.8000000000000003), ('2.9', 2.9000000000000004), ('3', 3.0), ('3.1', 3.1), ('3.2', 3.2), ('3.3', 3.3000000000000003), ('3.4', 3.4000000000000004), ('3.5', 3.5), ('3.6', 3.6), ('3.7', 3.7), ('3.8', 3.8000000000000003), ('3.9', 3.9000000000000004), ('4', 4.0), ('4.1', 4.1000000000000005), ('4.2', 4.2), ('4.3', 4.3), ('4.4', 4.4), ('4.5', 4.5), ('4.6', 4.6000000000000005), ('4.7', 4.7), ('4.8', 4.800000000000001), ('4.9', 4.9), ('5', 5.0), ('5.1', 5.1000000000000005), ('5.2', 5.2), ('5.3', 5.300000000000001), ('5.4', 5.4), ('5.5', 5.5), ('5.6', 5.6000000000000005), ('5.7', 5.7), ('5.8', 5.800000000000001), ('5.9', 5.9), ('6', 6.0), ('6.1', 6.1000000000000005), ('6.2', 6.2), ('6.3', 6.300000000000001), ('6.4', 6.4), ('6.5', 6.5), ('6.6', 6.6000000000000005), ('6.7', 6.7), ('6.8', 6.800000000000001), ('6.9', 6.9), ('7', 7.0), ('7.1', 7.1000000000000005), ('7.2', 7.2), ('7.3', 7.300000000000001), ('7.4', 7.4), ('7.5', 7.5), ('7.6', 7.6000000000000005), ('7.7', 7.7), ('7.8', 7.800000000000001), ('7.9', 7.9), ('8', 8.0), ('8.1', 8.1), ('8.2', 8.200000000000001), ('8.3', 8.3), ('8.4', 8.4), ('8.5', 8.5), ('8.6', 8.6), ('8.7', 8.700000000000001), ('8.8', 8.8), ('8.9', 8.9), ('9', 9.0), ('9.1', 9.1), ('9.2', 9.200000000000001), ('9.3', 9.3), ('9.4', 9.4), ('9.5', 9.5), ('9.6', 9.600000000000001), ('9.7', 9.700000000000001), ('9.8', 9.8), ('9.9', 9.9), ('10', 10.0)), value=1.0), SelectionSlider(continuous_update=False, description='a', index=10, layout=Layout(min_width='300px'), options=(('0', 0.0), ('0.1', 0.1), ('0.2', 0.2), ('0.3', 0.30000000000000004), ('0.4', 0.4), ('0.5', 0.5), ('0.6', 0.6000000000000001), ('0.7', 0.7000000000000001), ('0.8', 0.8), ('0.9', 0.9), ('1', 1.0), ('1.1', 1.1), ('1.2', 1.2000000000000002), ('1.3', 1.3), ('1.4', 1.4000000000000001), ('1.5', 1.5), ('1.6', 1.6), ('1.7', 1.7000000000000002), ('1.8', 1.8), ('1.9', 1.9000000000000001), ('2', 2.0), ('2.1', 2.1), ('2.2', 2.2), ('2.3', 2.3000000000000003), ('2.4', 2.4000000000000004), ('2.5', 2.5), ('2.6', 2.6), ('2.7', 2.7), ('2.8', 2.8000000000000003), ('2.9', 2.9000000000000004), ('3', 3.0), ('3.1', 3.1), ('3.2', 3.2), ('3.3', 3.3000000000000003), ('3.4', 3.4000000000000004), ('3.5', 3.5), ('3.6', 3.6), ('3.7', 3.7), ('3.8', 3.8000000000000003), ('3.9', 3.9000000000000004), ('4', 4.0), ('4.1', 4.1000000000000005), ('4.2', 4.2), ('4.3', 4.3), ('4.4', 4.4), ('4.5', 4.5), ('4.6', 4.6000000000000005), ('4.7', 4.7), ('4.8', 4.800000000000001), ('4.9', 4.9), ('5', 5.0), ('5.1', 5.1000000000000005), ('5.2', 5.2), ('5.3', 5.300000000000001), ('5.4', 5.4), ('5.5', 5.5), ('5.6', 5.6000000000000005), ('5.7', 5.7), ('5.8', 5.800000000000001), ('5.9', 5.9), ('6', 6.0), ('6.1', 6.1000000000000005), ('6.2', 6.2), ('6.3', 6.300000000000001), ('6.4', 6.4), ('6.5', 6.5), ('6.6', 6.6000000000000005), ('6.7', 6.7), ('6.8', 6.800000000000001), ('6.9', 6.9), ('7', 7.0), ('7.1', 7.1000000000000005), ('7.2', 7.2), ('7.3', 7.300000000000001), ('7.4', 7.4), ('7.5', 7.5), ('7.6', 7.6000000000000005), ('7.7', 7.7), ('7.8', 7.800000000000001), ('7.9', 7.9), ('8', 8.0), ('8.1', 8.1), ('8.2', 8.200000000000001), ('8.3', 8.3), ('8.4', 8.4), ('8.5', 8.5), ('8.6', 8.6), ('8.7', 8.700000000000001), ('8.8', 8.8), ('8.9', 8.9), ('9', 9.0), ('9.1', 9.1), ('9.2', 9.200000000000001), ('9.3', 9.3), ('9.4', 9.4), ('9.5', 9.5), ('9.6', 9.600000000000001), ('9.7', 9.700000000000001), ('9.8', 9.8), ('9.9', 9.9), ('10', 10.0)), value=1.0), SelectionSlider(continuous_update=False, description='b', index=10, layout=Layout(min_width='300px'), options=(('0', 0.0), ('0.1', 0.1), ('0.2', 0.2), ('0.3', 0.30000000000000004), ('0.4', 0.4), ('0.5', 0.5), ('0.6', 0.6000000000000001), ('0.7', 0.7000000000000001), ('0.8', 0.8), ('0.9', 0.9), ('1', 1.0), ('1.1', 1.1), ('1.2', 1.2000000000000002), ('1.3', 1.3), ('1.4', 1.4000000000000001), ('1.5', 1.5), ('1.6', 1.6), ('1.7', 1.7000000000000002), ('1.8', 1.8), ('1.9', 1.9000000000000001), ('2', 2.0), ('2.1', 2.1), ('2.2', 2.2), ('2.3', 2.3000000000000003), ('2.4', 2.4000000000000004), ('2.5', 2.5), ('2.6', 2.6), ('2.7', 2.7), ('2.8', 2.8000000000000003), ('2.9', 2.9000000000000004), ('3', 3.0), ('3.1', 3.1), ('3.2', 3.2), ('3.3', 3.3000000000000003), ('3.4', 3.4000000000000004), ('3.5', 3.5), ('3.6', 3.6), ('3.7', 3.7), ('3.8', 3.8000000000000003), ('3.9', 3.9000000000000004), ('4', 4.0), ('4.1', 4.1000000000000005), ('4.2', 4.2), ('4.3', 4.3), ('4.4', 4.4), ('4.5', 4.5), ('4.6', 4.6000000000000005), ('4.7', 4.7), ('4.8', 4.800000000000001), ('4.9', 4.9), ('5', 5.0), ('5.1', 5.1000000000000005), ('5.2', 5.2), ('5.3', 5.300000000000001), ('5.4', 5.4), ('5.5', 5.5), ('5.6', 5.6000000000000005), ('5.7', 5.7), ('5.8', 5.800000000000001), ('5.9', 5.9), ('6', 6.0), ('6.1', 6.1000000000000005), ('6.2', 6.2), ('6.3', 6.300000000000001), ('6.4', 6.4), ('6.5', 6.5), ('6.6', 6.6000000000000005), ('6.7', 6.7), ('6.8', 6.800000000000001), ('6.9', 6.9), ('7', 7.0), ('7.1', 7.1000000000000005), ('7.2', 7.2), ('7.3', 7.300000000000001), ('7.4', 7.4), ('7.5', 7.5), ('7.6', 7.6000000000000005), ('7.7', 7.7), ('7.8', 7.800000000000001), ('7.9', 7.9), ('8', 8.0), ('8.1', 8.1), ('8.2', 8.200000000000001), ('8.3', 8.3), ('8.4', 8.4), ('8.5', 8.5), ('8.6', 8.6), ('8.7', 8.700000000000001), ('8.8', 8.8), ('8.9', 8.9), ('9', 9.0), ('9.1', 9.1), ('9.2', 9.200000000000001), ('9.3', 9.3), ('9.4', 9.4), ('9.5', 9.5), ('9.6', 9.600000000000001), ('9.7', 9.700000000000001), ('9.8', 9.8), ('9.9', 9.9), ('10', 10.0)), value=1.0)), layout=Layout(display='flex', flex_flow='row wrap'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
980
       "    <div class=\"bk-plotdiv\" id=\"218016a4-04e7-415a-a8a3-df1e51705b04\"></div>\n",
FAGES Francois's avatar
cours2  
FAGES Francois committed
981 982 983 984 985 986 987 988 989 990 991 992
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
993 994
       "  var docs_json = {\"0f478da3-e90a-48d5-a71b-d0a362a3e7c5\":{\"roots\":{\"references\":[{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"0750c847-3378-4aad-b873-356fdaaea3e3\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Time\",\"formatter\":{\"id\":\"a59955df-7145-42b0-bd61-f7e6f9d57564\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d03a938e-5125-4c4c-9401-766a78bbb83d\",\"type\":\"BasicTicker\"}},\"id\":\"ca7bc28a-9866-4c14-a4b2-1093ce41cd25\",\"type\":\"LinearAxis\"},{\"attributes\":{\"data_source\":{\"id\":\"e08ad2b4-0f06-4f7d-821e-2550a0134bd7\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"45f066f7-f179-4ace-805b-1131c72b866b\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"578d2b63-98a4-47a5-b4c3-b7bb03a6a8a7\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"bb3ebbd9-5ff6-469a-b74a-355e44fa7228\",\"type\":\"CDSView\"}},\"id\":\"1d37bc38-7738-40bd-b332-4fb6b0d7cad4\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"e307b716-00a6-464b-818c-13f1fc006d96\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"A\",\"B\",\"Time\"],\"data\":{\"A\":[1.0,1.0,0.999985,0.839354,0.529653,0.32126,0.229338,0.203341,0.218549,0.271707,0.371873,0.532886,0.753127,0.959824,0.963109,0.694201,0.41557,0.267718,0.211259,0.205822,0.2381,0.311374,0.438156,0.629265,0.859696,0.999339,0.860478,0.550751,0.332061,0.233411,0.203709,0.216161,0.2663,0.36249,0.518627,0.735606,0.948675,0.973821,0.718248,0.431799,0.274872,0.21339,0.204885,0.2344,0.30427,0.426566,0.612966,0.843231,0.996975,0.880557,0.572519,0.343545,0.23785,0.2043,0.213976,0.261145,0.353442,0.504732,0.718134,0.936476,0.982724,0.742233,0.44884,0.282543,0.2158,0.204152,0.230918,0.297455,0.415343,0.596956,0.82641,0.992965,0.899442,0.594896,0.355736,0.242672,0.20512,0.211993,0.256236,0.344724,0.491205,0.700756,0.923333,0.989787,0.766006,0.466693,0.290758,0.2185,0.203623,0.227652,0.290922,0.404482,0.581254,0.809312,0.987387,0.916993,0.617807,0.368659,0.247895,0.206174,0.210209,0.251568,0.335249],\"B\":[1.0,1.00003,1.00391,1.43252,1.65848,1.54786,1.28564,1.02132,0.808483,0.657564,0.568142,0.544497,0.608727,0.814533,1.2025,1.58198,1.64019,1.43347,1.15873,0.915271,0.730928,0.608519,0.548274,0.560873,0.682021,0.974507,1.403,1.65453,1.56391,1.30635,1.03949,0.822191,0.666662,0.57265,0.543664,0.599943,0.792815,1.16944,1.56269,1.64766,1.45311,1.17873,0.931454,0.742487,0.615516,0.550486,0.556848,0.66791,0.946047,1.37241,1.64848,1.57908,1.32705,1.05796,0.836245,0.676099,0.577509,0.543287,0.591902,0.772212,1.13663,1.54143,1.65352,1.47236,1.19892,0.947971,0.754389,0.622851,0.553081,0.553383,0.654739,0.918592,1.34093,1.6403,1.59327,1.34772,1.0767,0.850645,0.685874,0.582718,0.543354,0.584574,0.752712,1.10422,1.51831,1.65769,1.49117,1.21926,0.964817,0.766636,0.630524,0.556054,0.550458,0.642475,0.892189,1.30876,1.62996,1.60639,1.3683,1.09572,0.86539,0.695989,0.589028],\"Time\":[0.0,3.1e-05,0.003906,0.403906,0.803906,1.20391,1.60391,2.00391,2.40391,2.80391,3.20391,3.60391,4.00391,4.40391,4.80391,5.20391,5.60391,6.00391,6.40391,6.80391,7.20391,7.60391,8.00391,8.40391,8.80391,9.20391,9.60391,10.0039,10.4039,10.8039,11.2039,11.6039,12.0039,12.4039,12.8039,13.2039,13.6039,14.0039,14.4039,14.8039,15.2039,15.6039,16.0039,16.4039,16.8039,17.2039,17.6039,18.0039,18.4039,18.8039,19.2039,19.6039,20.0039,20.4039,20.8039,21.2039,21.6039,22.0039,22.4039,22.8039,23.2039,23.6039,24.0039,24.4039,24.8039,25.2039,25.6039,26.0039,26.4039,26.8039,27.2039,27.6039,28.0039,28.4039,28.8039,29.2039,29.6039,30.0039,30.4039,30.8039,31.2039,31.6039,32.0039,32.4039,32.8039,33.2039,33.6039,34.0039,34.4039,34.8039,35.2039,35.6039,36.0039,36.4039,36.8039,37.2039,37.6039,38.0039,38.4039,38.8039,39.2039,39.6039,40.0]}},\"id\":\"e08ad2b4-0f06-4f7d-821e-2550a0134bd7\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"0ad1bac3-aada-49f7-9943-30a6f4436ffc\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"d03a938e-5125-4c4c-9401-766a78bbb83d\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"5b021159-7b38-476f-992e-14314f3e4d00\",\"type\":\"LinearScale\"},{\"attributes\":{\"line_color\":\"#ff7f0e\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"A\"}},\"id\":\"054ede72-9148-4560-84ac-cf4767f773cc\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"f25d7984-fe48-4634-a547-310e43c7fc77\",\"type\":\"LinearScale\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"45f066f7-f179-4ace-805b-1131c72b866b\",\"type\":\"Line\"},{\"attributes\":{\"label\":{\"value\":\"A\"},\"renderers\":[{\"id\":\"19d65ad1-62ac-4159-ae08-a93b1a809cbf\",\"type\":\"GlyphRenderer\"}]},\"id\":\"26381a6d-7851-43b7-96f3-96ee3028445f\",\"type\":\"LegendItem\"},{\"attributes\":{\"dimension\":1,\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d387a5ff-4b7d-4c7c-b903-751894ef7aac\",\"type\":\"BasicTicker\"}},\"id\":\"d8beaea3-e341-455d-8e06-444e311ca100\",\"type\":\"Grid\"},{\"attributes\":{\"formatter\":{\"id\":\"e4f80cb4-d8cf-40c1-9a52-4585a555f2b0\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d387a5ff-4b7d-4c7c-b903-751894ef7aac\",\"type\":\"BasicTicker\"}},\"id\":\"d7732ebd-8bfa-4714-a400-887d56903695\",\"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\":\"98ed70bb-fc19-4937-b7f8-06e482384b9a\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"x,y\",\"$x, $y\"]]},\"id\":\"279efda7-6a7c-467c-9d7c-d919fec4f062\",\"type\":\"HoverTool\"},{\"attributes\":{\"border_line_color\":{\"value\":\"gray\"},\"click_policy\":\"hide\",\"items\":[{\"id\":\"a1da6100-431c-4fe6-9021-babdddde26cd\",\"type\":\"LegendItem\"},{\"id\":\"26381a6d-7851-43b7-96f3-96ee3028445f\",\"type\":\"LegendItem\"}],\"location\":[10,0],\"plot\":{\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"63c1bbea-45db-4c5e-abb8-23dd14344a04\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"e4f80cb4-d8cf-40c1-9a52-4585a555f2b0\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"indices\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102]},\"id\":\"4c044b3f-86aa-450a-8665-6ba5c57317c8\",\"type\":\"IndexFilter\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"bf316a7e-e4d1-4b8c-950d-5c56fb4f2d21\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"d387a5ff-4b7d-4c7c-b903-751894ef7aac\",\"type\":\"BasicTicker\"},{\"attributes\":{\"filters\":[{\"id\":\"4c044b3f-86aa-450a-8665-6ba5c57317c8\",\"type\":\"IndexFilter\"}],\"source\":{\"id\":\"e08ad2b4-0f06-4f7d-821e-2550a0134bd7\",\"type\":\"ColumnDataSource\"}},\"id\":\"bb3ebbd9-5ff6-469a-b74a-355e44fa7228\",\"type\":\"CDSView\"},{\"attributes\":{\"data_source\":{\"id\":\"e08ad2b4-0f06-4f7d-821e-2550a0134bd7\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"054ede72-9148-4560-84ac-cf4767f773cc\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"0750c847-3378-4aad-b873-356fdaaea3e3\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"bb3ebbd9-5ff6-469a-b74a-355e44fa7228\",\"type\":\"CDSView\"}},\"id\":\"19d65ad1-62ac-4159-ae08-a93b1a809cbf\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null},\"id\":\"27049ce2-f049-4a16-817c-0a42d4d60523\",\"type\":\"DataRange1d\"},{\"attributes\":{\"grid_line_dash\":[6,4],\"plot\":{\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"d03a938e-5125-4c4c-9401-766a78bbb83d\",\"type\":\"BasicTicker\"}},\"id\":\"092670b3-88e7-4ef9-af9d-fa391ef6fa8c\",\"type\":\"Grid\"},{\"attributes\":{\"active_drag\":{\"id\":\"5ba7e320-4b54-49cd-b336-047e264eab9a\",\"type\":\"BoxZoomTool\"},\"active_inspect\":\"auto\",\"active_scroll\":null,\"active_tap\":\"auto\",\"tools\":[{\"id\":\"23a75e0d-9db3-4ff4-8433-15d8bf2fb8f7\",\"type\":\"PanTool\"},{\"id\":\"8308518a-8e03-4f19-abd0-2c0578fe71bf\",\"type\":\"WheelZoomTool\"},{\"id\":\"5ba7e320-4b54-49cd-b336-047e264eab9a\",\"type\":\"BoxZoomTool\"},{\"id\":\"0ad1bac3-aada-49f7-9943-30a6f4436ffc\",\"type\":\"ResetTool\"},{\"id\":\"e307b716-00a6-464b-818c-13f1fc006d96\",\"type\":\"SaveTool\"},{\"id\":\"5f4e32d3-66b2-4f6b-8090-d26ff2e14187\",\"type\":\"UndoTool\"},{\"id\":\"279efda7-6a7c-467c-9d7c-d919fec4f062\",\"type\":\"HoverTool\"}]},\"id\":\"74563446-a110-4bf9-a41f-5586c852244e\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"5f4e32d3-66b2-4f6b-8090-d26ff2e14187\",\"type\":\"UndoTool\"},{\"attributes\":{},\"id\":\"8308518a-8e03-4f19-abd0-2c0578fe71bf\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"Time\"},\"y\":{\"field\":\"B\"}},\"id\":\"578d2b63-98a4-47a5-b4c3-b7bb03a6a8a7\",\"type\":\"Line\"},{\"attributes\":{\"overlay\":{\"id\":\"98ed70bb-fc19-4937-b7f8-06e482384b9a\",\"type\":\"BoxAnnotation\"}},\"id\":\"5ba7e320-4b54-49cd-b336-047e264eab9a\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"a59955df-7145-42b0-bd61-f7e6f9d57564\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"23a75e0d-9db3-4ff4-8433-15d8bf2fb8f7\",\"type\":\"PanTool\"},{\"attributes\":{\"background_fill_alpha\":{\"value\":0.3},\"background_fill_color\":{\"value\":\"oldlace\"},\"below\":[{\"id\":\"ca7bc28a-9866-4c14-a4b2-1093ce41cd25\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"d7732ebd-8bfa-4714-a400-887d56903695\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":640,\"renderers\":[{\"id\":\"ca7bc28a-9866-4c14-a4b2-1093ce41cd25\",\"type\":\"LinearAxis\"},{\"id\":\"092670b3-88e7-4ef9-af9d-fa391ef6fa8c\",\"type\":\"Grid\"},{\"id\":\"d7732ebd-8bfa-4714-a400-887d56903695\",\"type\":\"LinearAxis\"},{\"id\":\"d8beaea3-e341-455d-8e06-444e311ca100\",\"type\":\"Grid\"},{\"id\":\"98ed70bb-fc19-4937-b7f8-06e482384b9a\",\"type\":\"BoxAnnotation\"},{\"id\":\"1d37bc38-7738-40bd-b332-4fb6b0d7cad4\",\"type\":\"GlyphRenderer\"},{\"id\":\"19d65ad1-62ac-4159-ae08-a93b1a809cbf\",\"type\":\"GlyphRenderer\"},{\"id\":\"63c1bbea-45db-4c5e-abb8-23dd14344a04\",\"type\":\"Legend\"}],\"right\":[{\"id\":\"63c1bbea-45db-4c5e-abb8-23dd14344a04\",\"type\":\"Legend\"}],\"title\":{\"id\":\"bf316a7e-e4d1-4b8c-950d-5c56fb4f2d21\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"74563446-a110-4bf9-a41f-5586c852244e\",\"type\":\"Toolbar\"},\"toolbar_location\":\"below\",\"toolbar_sticky\":false,\"x_range\":{\"id\":\"27049ce2-f049-4a16-817c-0a42d4d60523\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"5b021159-7b38-476f-992e-14314f3e4d00\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"372f9e0d-1f67-4404-aef6-db4e839819c0\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"f25d7984-fe48-4634-a547-310e43c7fc77\",\"type\":\"LinearScale\"}},\"id\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"label\":{\"value\":\"B\"},\"renderers\":[{\"id\":\"1d37bc38-7738-40bd-b332-4fb6b0d7cad4\",\"type\":\"GlyphRenderer\"}]},\"id\":\"a1da6100-431c-4fe6-9021-babdddde26cd\",\"type\":\"LegendItem\"},{\"attributes\":{\"callback\":null},\"id\":\"372f9e0d-1f67-4404-aef6-db4e839819c0\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"ced640d0-726b-4493-931c-80c2438efabe\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.14\"}};\n",
       "  var render_items = [{\"docid\":\"0f478da3-e90a-48d5-a71b-d0a362a3e7c5\",\"elementid\":\"218016a4-04e7-415a-a8a3-df1e51705b04\",\"modelid\":\"ced640d0-726b-4493-931c-80c2438efabe\",\"notebook_comms_target\":\"2558b48a-fdec-401a-910c-1428fce005db\"}];\n",
FAGES Francois's avatar
cours2  
FAGES Francois committed
995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
FAGES Francois's avatar
TD6et7  
FAGES Francois committed
1020
       "id": "ced640d0-726b-4493-931c-80c2438efabe"
FAGES Francois's avatar
cours2  
FAGES Francois committed
1021 1022 1023 1024 1025
      }
     },
     "output_type": "display_data"
    }
   ],
FAGES Francois's avatar
TD12  
FAGES Francois committed
1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279
   "source": [
    "%slider k1 k2 k3 a b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### 2) enumerate the possible qualitative behaviors that you could obtain in the continuous semantics\n",
    "\n",
    "*write your answer here*\n",
    "\n",
    "...\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3)  add immigration and emigration reactions for the prey (with parameters k4 k5)\n",
    "\n",
    "*write your commands in the cells below*\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%slider k4 k5 k1 k2 k3 a b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4) enumerate the qualitative behaviors that can now be obtained in the continuous semantics\n",
    "\n",
    "*write your answer here*\n",
    "\n",
    "\n",
    "...\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5) can you make a general conjecture about the existence of sustained oscillations in the stochastic semantics in presence of synthesis and degradation reactions ?\n",
    "\n",
    "*write your answer here* (to my knowledge there is no known theorem ensuring that property)\n",
    "\n",
    " \n",
    " \n",
    " ...\n",
    " "
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Biocham",
   "language": "",
   "name": "biocham"
  },
  "language_info": {
   "codemirror_mode": "biocham",
   "file_extension": ".bc",
   "mimetype": "text/plain",
   "name": "biocham",
   "pygments_lexer": "prolog"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "1767921c752e4e119f7bce35f40f066b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "k1",
       "layout": "IPY_MODEL_569d3923c4c54833a163b4fc27900467",
       "max": 20,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_92c14cd58a974887909a6a84a73cafa0",
       "value": 2
      }
     },
     "486b3d549fe945bc908652fddb5bf80b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "569d3923c4c54833a163b4fc27900467": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "56a51429487d457290a1b9e41464106d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "5f0367a185a2417291af7a5a01691ea2": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "k2",
       "layout": "IPY_MODEL_6e4e10f7333e48b3b0281ef1cdac21fe",
       "max": 20,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_6ef2c16d0eda489f9732dd7167b11cfe",
       "value": 2
      }
     },
     "6e4e10f7333e48b3b0281ef1cdac21fe": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "6ef2c16d0eda489f9732dd7167b11cfe": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "7e85b2e1d33e454a84cc022c25c7e5d8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "92c14cd58a974887909a6a84a73cafa0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "9ba4dd1e44a94ce79f65c49296ce1e48": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "cd9d6c48b14d4c4cb62014ff8a2947ae": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "dd571a0e525846ebb1a2676fc454da65": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "k3",
       "layout": "IPY_MODEL_ffa2b4668ad54cd2a1d5fed7046a18cd",
       "max": 10,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_486b3d549fe945bc908652fddb5bf80b",
       "value": 1
      }
     },
     "decfcf83840844d392c6ad37aa359b16": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "b",
       "layout": "IPY_MODEL_56a51429487d457290a1b9e41464106d",
       "max": 10,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_7e85b2e1d33e454a84cc022c25c7e5d8",
       "value": 1
      }
     },
     "e42159a5921c4105b0c7f4e4bf64ab7e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.1.0",
      "model_name": "FloatSliderModel",
      "state": {
       "continuous_update": false,
       "description": "a",
       "layout": "IPY_MODEL_cd9d6c48b14d4c4cb62014ff8a2947ae",
       "max": 10,
       "readout_format": ".1f",
       "step": 0.1,
       "style": "IPY_MODEL_9ba4dd1e44a94ce79f65c49296ce1e48",
       "value": 1
      }
     },
     "ffa2b4668ad54cd2a1d5fed7046a18cd": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}