too_depth.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fc678569-c4b8-47d6-9ef6-a76079aa8cb7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from rubin_scheduler.utils import m5_flat_sed\n",
    "from rubin_scheduler.utils import SysEngVals\n",
    "from rubin_scheduler.site_models import SeeingModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "278fcedb-17ca-4633-ac0b-2f7165992fc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'u': 23.051983,\n",
       " 'g': 22.253839,\n",
       " 'r': 21.197579,\n",
       " 'i': 20.462795,\n",
       " 'z': 19.606305,\n",
       " 'y': 18.601512}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dark sky (per filter)\n",
    "se_vals = SysEngVals()\n",
    "dark_sky = se_vals.sky_mag\n",
    "dark_sky"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0d1c7c68-ef24-4e54-bd6f-42f6ba4781a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'u': 0.9028135724330592,\n",
       " 'g': 0.8541995456912611,\n",
       " 'r': 0.8097465599661966,\n",
       " 'i': 0.7790786082834846,\n",
       " 'z': 0.7587285808106591,\n",
       " 'y': 0.742436066986218}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fiducial seeing (per filter)\n",
    "seeing_model = SeeingModel()\n",
    "fwhm_500 = 0.6\n",
    "airmass = 1.0\n",
    "fwhm_eff = seeing_model(fwhm_z=fwhm_500, airmass=airmass)['fwhmEff']\n",
    "filterlist = ['u', 'g', 'r', 'i', 'z', 'y']\n",
    "fwhm_eff = dict(zip(filterlist, fwhm_eff))\n",
    "fwhm_eff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb29c745-a233-45ad-a4d1-250c10c9001a",
   "metadata": {},
   "outputs": [],
   "source": [
    "exptimes = np.arange(30, 240, 1)\n",
    "m5 = {}\n",
    "for f in 'ugrizy':\n",
    "    m5[f] = np.zeros(len(exptimes))\n",
    "    for i, exp_time in enumerate(exptimes):\n",
    "        m5[f][i] = m5_flat_sed(visit_filter=f, \n",
    "                               musky=dark_sky[f], \n",
    "                               fwhm_eff=fwhm_eff[f], \n",
    "                               exp_time=exp_time, \n",
    "                               airmass=airmass, \n",
    "                               nexp=1, tau_cloud=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1ccf8c3a-2fdb-466f-90d8-aa7a8268021f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Depth with variable exposure time, \\n dark sky, fiducial seeing, X=1.0')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = {\"u\": \"cyan\", \"g\": \"g\", \"r\": \"orange\", \"i\": \"r\", \"z\": \"m\", \"y\": \"b\"}\n",
    "filter_rgb_map = {\n",
    "    \"u\": (74 / 256, 125 / 256, 179 / 256),\n",
    "    \"g\": (104 / 256, 173 / 256, 87 / 256),\n",
    "    \"r\": (238 / 256, 134 / 256, 50 / 256),\n",
    "    \"i\": (232 / 256, 135 / 256, 189 / 256),\n",
    "    \"z\": (209 / 256, 53 / 256, 43 / 256),\n",
    "    \"y\": (142 / 256, 82 / 256, 159 / 256),\n",
    "}\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "for f in filterlist:\n",
    "    plt.plot(exptimes, m5[f], color=filter_rgb_map[f], label=f)\n",
    "plt.legend(loc=(1.0, 0.5))\n",
    "plt.grid(True, alpha=0.5)\n",
    "plt.xlabel(\"Exposure time (seconds)\", fontsize='x-large')\n",
    "plt.ylabel(\"Point Source m5 depth (mag)\", fontsize='x-large')\n",
    "plt.title(\"Depth with variable exposure time, \\n dark sky, fiducial seeing, X=1.0\", fontsize='x-large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "08a58ac2-3962-4d71-a783-e64efb4bac95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "    <style>\n",
       "        .bk-notebook-logo {\n",
       "            display: block;\n",
       "            width: 20px;\n",
       "            height: 20px;\n",
       "            background-image: url(data:image/png;base64,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);\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-notebook-logo\"></a>\n",
       "        <span id=\"da987ca2-84da-418b-ad0e-4f8df8436129\">Loading BokehJS ...</span>\n",
       "    </div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  const force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "const JS_MIME_TYPE = 'application/javascript';\n",
       "  const HTML_MIME_TYPE = 'text/html';\n",
       "  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  const CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    const script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    function drop(id) {\n",
       "      const view = Bokeh.index.get_by_id(id)\n",
       "      if (view != null) {\n",
       "        view.model.document.clear()\n",
       "        Bokeh.index.delete(view)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    const cell = handle.cell;\n",
       "\n",
       "    const id = cell.output_area._bokeh_element_id;\n",
       "    const server_id = cell.output_area._bokeh_server_id;\n",
       "\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null) {\n",
       "      drop(id)\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd_clean, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            const id = msg.content.text.trim()\n",
       "            drop(id)\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd_destroy);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    const output_area = handle.output_area;\n",
       "    const output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      const bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      const script_attrs = bk_div.children[0].attributes;\n",
       "      for (let i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      const toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    const events = require('base/js/events');\n",
       "    const OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  const NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    const el = document.getElementById(\"da987ca2-84da-418b-ad0e-4f8df8436129\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error(url) {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < css_urls.length; i++) {\n",
       "      const url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < js_urls.length; i++) {\n",
       "      const url = js_urls[i];\n",
       "      const element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.3.4.min.js\"];\n",
       "  const css_urls = [];\n",
       "\n",
       "  const inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "          for (let i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      const cell = $(document.getElementById(\"da987ca2-84da-418b-ad0e-4f8df8436129\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    const el = document.getElementById(\"da987ca2-84da-418b-ad0e-4f8df8436129\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.3.4.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n          for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\nif (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(\"da987ca2-84da-418b-ad0e-4f8df8436129\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"b79bbc75-f626-4911-94de-a96b7e9d9b31\" data-root-id=\"p1001\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
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       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
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       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
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       "    }, 10, root)\n",
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      ],
      "application/vnd.bokehjs_exec.v0+json": ""
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      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1001"
      }
     },
     "output_type": "display_data"
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   ],
   "source": [
    "from bokeh.io import output_notebook, output_file, show\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.models import ColumnDataSource, HoverTool\n",
    "\n",
    "# Create plot\n",
    "BAND_COLORS = dict(u=\"#56b4e9\", g=\"#008060\", r=\"#ff4000\", i=\"#850000\", z=\"#6600cc\", y=\"#222222\")\n",
    "plot = figure(width=600, height=500, \n",
    "              title=\"Depth with variable exposure time - Dark sky, fiducial seeing, X=1.0\", \n",
    "              x_axis_label=\"Exposure Time (seconds)\", \n",
    "              y_axis_label=\"Point Source m5 depth (mags)\")\n",
    "\n",
    "\n",
    "depths = pd.DataFrame(m5)\n",
    "depths['exposure time'] = exptimes\n",
    "data = ColumnDataSource(depths)\n",
    "\n",
    "for f in 'ugrizy':\n",
    "    plot.line(x='exposure time', y=f, source=data, line_width=2, \n",
    "                           line_color=BAND_COLORS[f], \n",
    "                            name=f, legend_label=f)\n",
    "\n",
    "plot.legend.location = 'bottom_right'\n",
    "plot.legend.orientation = 'horizontal'\n",
    "plot.legend.nrows = 2\n",
    "\n",
    "hover_tool = HoverTool()\n",
    "hover_tool.tooltips = [\n",
    "    (\"(band, exptime, m5)\", \"($name, $x{(0.0)}, $y{(0.00)})\"),\n",
    "]\n",
    "plot.add_tools(hover_tool)\n",
    "\n",
    "plot.title.text_font_size = '15px'\n",
    "\n",
    "#Show plot\n",
    "output_notebook()\n",
    "#output_file('depth_plot.html')\n",
    "show(plot)"
   ]
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