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    "# Custom Radius and Wavelength-Dependent Aerosol Layers\n",
    "\n",
    "In this tutorial you will learn: \n",
    "\n",
    "1. How to generate your own Mie coefficients for a given radius grid\n",
    "2. How to compute the optics of an aerosol for your custom radius grid\n",
    "3. How to inject this aerosol as a custom layer into an atmospheric model for PICASO\n",
    "\n",
    "You need to have downloaded PICASO, Virga, and the particle size distribution file to run this tutorial."
   ]
  },
  {
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   "id": "c8bbfed5",
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   "source": [
    "First, let's import all the necessary packages:"
   ]
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   "id": "c264e8ce",
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     "text": [
      "WARNING: Failed to load Vega spectrum from /Users/nbatalh1/Documents/data/grp/redcat/trds/calspec/alpha_lyr_stis_011.fits; Functionality involving Vega will be severely limited: FileNotFoundError(2, 'No such file or directory') [stsynphot.spectrum]\n",
      "/Users/nbatalh1/Documents/codes/PICASO/picaso/picaso/justdoit.py:77: UserWarning: Your code version is 5.0 but your reference data version is 4.0. For some functionality you may experience Keyword errors. Please download the newest ref version or update your code: https://github.com/natashabatalha/picaso/tree/master/reference\n",
      "  warnings.warn(msg)\n"
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   "source": [
    "#standards\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import astropy.units as u\n",
    "\n",
    "#main programs\n",
    "\n",
    "#radiative transfer and atmosphere code\n",
    "from picaso import justdoit as pdi\n",
    "\n",
    "#cloud code\n",
    "from virga import justdoit as vdi\n",
    "\n",
    "\n",
    "#plotting tools\n",
    "from picaso import justplotit as ppi\n",
    "from virga import justplotit as vpi\n",
    "ppi.output_notebook() \n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "024be42e",
   "metadata": {},
   "source": [
    "Now, let's load in a sample particle size distribution. \n",
    "This one comes from [He et al., 2018](https://iopscience.iop.org/article/10.3847/2041-8213/aab42b), on the sizes of hazes produced in a laboratory setting. Notice that these are given in particle diameter, so we have to convert them to radii."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc595c87",
   "metadata": {},
   "source": [
    "## Load Custom Particle Radius Distribution "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0736e204",
   "metadata": {},
   "outputs": [],
   "source": [
    "from inspect import getsourcefile\n",
    "import os  \n",
    "#if you haven't installed virga from github this file will exist in your libary package here\n",
    "particle_distribution_file = os.path.join(\n",
    "    str(os.path.abspath(getsourcefile(vpi)).replace('justplotit.py','')),'reference','particle_sizes.csv')\n",
    "#all this does is grab the code directory to get the reference data location of the code  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1a7058c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "particle_distribution = pd.read_csv(particle_distribution_file)\n",
    "\n",
    "n_400K, n_300K, size = particle_distribution['400 K'], particle_distribution['300 K'], particle_distribution['size (nm)'] \n",
    "\n",
    "#cut the range of sizes where there aren't any data points\n",
    "non_nans_400 = np.where(np.isfinite(n_400K))\n",
    "non_nans_300 = np.where(np.isfinite(n_300K))\n",
    "\n",
    "n4 = n_400K.iloc[non_nans_400]\n",
    "r4 = size.iloc[non_nans_400]\n",
    "\n",
    "n3 = n_300K.iloc[non_nans_300]\n",
    "r3 = size.iloc[non_nans_300]\n",
    "\n",
    "#turn them into arrays for handy plotting and convert the particle diameters into radii\n",
    "r4=np.array(r4/2)\n",
    "n4=np.array(n4)\n",
    "r3=np.array(r3/2)\n",
    "n3=np.array(n3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13b2b5de",
   "metadata": {},
   "source": [
    "Let's plot up the distribution so we can see what it looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "766ef06a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x30299b7d0>"
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(r4,n4,color='red',label='400 K haze')\n",
    "plt.plot(r3,n3,color='blue',label = '300 K haze')\n",
    "plt.xlim(5,60)\n",
    "\n",
    "plt.xlabel('particle radius (nm)',fontsize=15)\n",
    "plt.ylabel('Distribution (percent total)',fontsize=15)\n",
    "plt.minorticks_on()\n",
    "plt.tick_params(axis='y',which='major',length =10, width=2,direction='out',labelsize=15)\n",
    "plt.tick_params(axis='x',which='major',length =10, width=2,direction='out',labelsize=15)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86574233",
   "metadata": {},
   "source": [
    "Okay, looks good! Now we have to compute a custom set of Mie coefficients that correspond to these particle radii. Make sure you **stick these new Mie databases in a new folder so you don't overwrite your existing Virga databases!** We're going to use the refractive indices of Titan-like tholins from [Khare et al., 1984](https://www.sciencedirect.com/science/article/abs/pii/0019103584901428?via%3Dihub) just for example purposes. Make sure you have this set of Refractive Indices in your version of Virga."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec552d1b",
   "metadata": {},
   "source": [
    "## Compute Mie Parameters for Custom Radius Grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2d8ce9db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Computing optical properties for khare_tholins using MiePython...\n",
      "If this function seems to be running a really long time... Check that you gave your rmin (and r_mon if using aggregates) in centimeters and that you are not making tennis balls :)\n",
      "\n",
      "90 wavelengths of refractive index data found for khare_tholins. Grid of mean radii (in bins) to calculate extinction and scattering efficiencies for (in cm):\n",
      "\n",
      "\t       min             mean             max          bin width (dr) \n",
      "\t   1.336746e-06    1.350000e-06    1.363254e-06       2.650744e-08\n",
      "\t   1.363254e-06    1.376770e-06    1.390287e-06       2.703308e-08\n",
      "\t   1.390287e-06    1.404071e-06    1.417856e-06       2.756914e-08\n",
      "\t   1.417856e-06    1.431914e-06    1.445972e-06       2.811583e-08\n",
      "\t   1.445972e-06    1.460308e-06    1.474645e-06       2.867336e-08\n",
      "\t   1.474645e-06    1.489266e-06    1.503887e-06       2.924195e-08\n",
      "\t   1.503887e-06    1.518798e-06    1.533709e-06       2.982181e-08\n",
      "\t   1.533709e-06    1.548915e-06    1.564122e-06       3.041317e-08\n",
      "\t   1.564122e-06    1.579630e-06    1.595138e-06       3.101626e-08\n",
      "\t   1.595138e-06    1.610954e-06    1.626770e-06       3.163131e-08\n",
      "\t   1.626770e-06    1.642899e-06    1.659028e-06       3.225855e-08\n",
      "\t   1.659028e-06    1.675477e-06    1.691926e-06       3.289823e-08\n",
      "\t   1.691926e-06    1.708702e-06    1.725477e-06       3.355060e-08\n",
      "\t   1.725477e-06    1.742585e-06    1.759693e-06       3.421590e-08\n",
      "\t   1.759693e-06    1.777140e-06    1.794587e-06       3.489439e-08\n",
      "\t   1.794587e-06    1.812380e-06    1.830174e-06       3.558634e-08\n",
      "\t   1.830174e-06    1.848320e-06    1.866466e-06       3.629201e-08\n",
      "\t   1.866466e-06    1.884971e-06    1.903477e-06       3.701168e-08\n",
      "\t   1.903477e-06    1.922350e-06    1.941223e-06       3.774561e-08\n",
      "\t   1.941223e-06    1.960470e-06    1.979717e-06       3.849410e-08\n",
      "\t   1.979717e-06    1.999346e-06    2.018974e-06       3.925743e-08\n",
      "\t   2.018974e-06    2.038992e-06    2.059010e-06       4.003590e-08\n",
      "\t   2.059010e-06    2.079425e-06    2.099840e-06       4.082980e-08\n",
      "\t   2.099840e-06    2.120660e-06    2.141480e-06       4.163945e-08\n",
      "\t   2.141480e-06    2.162712e-06    2.183945e-06       4.246515e-08\n",
      "\t   2.183945e-06    2.205598e-06    2.227252e-06       4.330723e-08\n",
      "\t   2.227252e-06    2.249335e-06    2.271418e-06       4.416601e-08\n",
      "\t   2.271418e-06    2.293939e-06    2.316460e-06       4.504181e-08\n",
      "\t   2.316460e-06    2.339427e-06    2.362395e-06       4.593498e-08\n",
      "\t   2.362395e-06    2.385818e-06    2.409241e-06       4.684586e-08\n",
      "\t   2.409241e-06    2.433128e-06    2.457015e-06       4.777481e-08\n",
      "\t   2.457015e-06    2.481377e-06    2.505738e-06       4.872217e-08\n",
      "\t   2.505738e-06    2.530582e-06    2.555426e-06       4.968833e-08\n",
      "\t   2.555426e-06    2.580763e-06    2.606100e-06       5.067364e-08\n",
      "\t   2.606100e-06    2.631939e-06    2.657778e-06       5.167849e-08\n",
      "\t   2.657778e-06    2.684130e-06    2.710481e-06       5.270326e-08\n",
      "\t   2.710481e-06    2.737356e-06    2.764230e-06       5.374836e-08\n",
      "\t   2.764230e-06    2.791637e-06    2.819044e-06       5.481418e-08\n",
      "\t   2.819044e-06    2.846994e-06    2.874945e-06       5.590113e-08\n",
      "\t   2.874945e-06    2.903450e-06    2.931955e-06       5.700964e-08\n",
      "\t   2.931955e-06    2.961025e-06    2.990095e-06       5.814013e-08\n",
      "\t   2.990095e-06    3.019741e-06    3.049388e-06       5.929304e-08\n",
      "\t   3.049388e-06    3.079622e-06    3.109857e-06       6.046881e-08\n",
      "\t   3.109857e-06    3.140691e-06    3.171525e-06       6.166790e-08\n",
      "\t   3.171525e-06    3.202970e-06    3.234415e-06       6.289076e-08\n",
      "\t   3.234415e-06    3.266484e-06    3.298553e-06       6.413787e-08\n",
      "\t   3.298553e-06    3.331258e-06    3.363963e-06       6.540971e-08\n",
      "\t   3.363963e-06    3.397316e-06    3.430670e-06       6.670678e-08\n",
      "\t   3.430670e-06    3.464684e-06    3.498699e-06       6.802956e-08\n",
      "\t   3.498699e-06    3.533388e-06    3.568078e-06       6.937857e-08\n",
      "\t   3.568078e-06    3.603455e-06    3.638832e-06       7.075434e-08\n",
      "\t   3.638832e-06    3.674911e-06    3.710990e-06       7.215739e-08\n",
      "\t   3.710990e-06    3.747784e-06    3.784578e-06       7.358825e-08\n",
      "\t   3.784578e-06    3.822102e-06    3.859625e-06       7.504749e-08\n",
      "\t   3.859625e-06    3.897893e-06    3.936161e-06       7.653567e-08\n",
      "\t   3.936161e-06    3.975188e-06    4.014214e-06       7.805336e-08\n",
      "\t   4.014214e-06    4.054015e-06    4.093815e-06       7.960115e-08\n",
      "\t   4.093815e-06    4.134405e-06    4.174995e-06       8.117962e-08\n",
      "\t   4.174995e-06    4.216390e-06    4.257784e-06       8.278940e-08\n",
      "\t   4.257784e-06    4.300000e-06    4.342216e-06       8.443110e-08\n",
      "\n",
      "Averages from 6 sub-bins will be used to calculate the properties that represent the mean radius in each bin above.\n",
      "Optical properties for khare_tholins have been calculated and saved as /Users/nbatalh1/Documents/data/virga//khare_tholins.mieff.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Remember to change these paths to where your refractive indices and Mie databases live\n",
    "mieff_dir = '/Users/nbatalh1/Documents/data/virga/'\n",
    "# here I am assuming the refractive indices are stored in the same place as I want the output\n",
    "refrind_dir = output_dir = mieff_dir \n",
    "\n",
    "#First, let's just assume our hazes follow the distribution of the 300 K haze above.\n",
    "\n",
    "#Note that this function wants the radii in centimeters, so we have to convert it from nanometers\n",
    "newmies=vdi.calc_mie_db('khare_tholins', os.path.join(refrind_dir,'virga_tholins'), \n",
    "                        output_dir, \n",
    "                        rmin = np.min(r3/1e7), rmax=np.max(r3/1e7), nradii = len(r3))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f61a3074",
   "metadata": {},
   "source": [
    "Okay, now let's grab those Mieff coefficients we just calculated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15478225",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "qext, qscat, cos_qscat, nwave, radius, wave_in = vdi.get_mie('khare_tholins',\n",
    "                                                             directory=os.path.join(mieff_dir,'virga_tholins'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "255bad1c",
   "metadata": {},
   "source": [
    "Next, we calculate our optical properties. Remember that **r3** here is your grid of radii bins and **n3** is the distribution of particles per radius bin.\n",
    "\n",
    "**ndz** is the total number of particles that make up our aerosol layer. Since we're setting our own slab, it's not really physical in this implementation because we're setting the particle number over many atmospheric layers. So we're going to set it fairly high."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "caa16cfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "ndz = 5e9 #that's particles/cm^2 but over the entire region of atmosphere where we're sticking aerosol\n",
    "\n",
    "opd,w0,g0,wavenumber_grid=vdi.calc_optics_user_r_dist(wave_in, ndz ,r3, u.nm, n3/100, \n",
    "                                                      qext, qscat, cos_qscat, )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e11ac2c",
   "metadata": {},
   "source": [
    "Now, we need to turn the above variables into something that PICASO can read. Choose where to set your aerosol layer pressure limits. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8ac93062",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x500 with 6 Axes>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nlayer = 30\n",
    "base_pressure = 1e-1 # let's start by setting the haze layer base at 0.1 bars\n",
    "haze_top_pressure = 1e-7 #and set the top of the haze layer at 0.1 microbar. Not unreasonble for a haze that forms fairly high!\n",
    "\n",
    "#just set an arbitrary pressure grid from 1000 bars to a nanobar\n",
    "pressure =  np.logspace(-9,3,nlayer)\n",
    "\n",
    "#here's where we shove all the variables into a dataframe PICASO can read\n",
    "df_haze = vdi.picaso_format_slab(base_pressure,opd, w0, g0, wavenumber_grid, pressure,p_top=haze_top_pressure)\n",
    "\n",
    "\n",
    "nwno = len(wavenumber_grid) #this will depend on the refractive indices you have. Khare's tholin have wide coverage but low resolution\n",
    "ppi.plot_cld_input(nwno, nlayer,df=df_haze)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92464e9a",
   "metadata": {},
   "source": [
    "We can see that lovely slab of haze and how it's changing according to wavelength! The above plots aren't in physical units though. Let's change the axes to be real numbers and not gridpoints. The wavelength grid covers a lot, so you'll probably have to zoom in to see the wavelength units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "62bef42a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 6 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ppi.plot_cld_input(nwno, nlayer,df=df_haze,pressure=pressure, wavelength=1e4/wavenumber_grid)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb8730f4",
   "metadata": {},
   "source": [
    "Now let's see how that would look in a spectrum. First, let's load a couple basic planet parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b9a3b03a",
   "metadata": {},
   "outputs": [],
   "source": [
    "nlevel = nlayer+1\n",
    "opa = pdi.opannection(wave_range=[0.3,14])\n",
    "case1 = pdi.inputs()\n",
    "\n",
    "case1.phase_angle(0)\n",
    "\n",
    "\n",
    "#here we are going to have to specify gravity through R and M since we need it in the Flux calc\n",
    "case1.gravity(mass=1, mass_unit=pdi.u.Unit('M_jup'),\n",
    "              radius=1.2, radius_unit=pdi.u.Unit('R_jup'))\n",
    "\n",
    "#here we are going to have to specify R as well\n",
    "case1.star(opa, 4000,0.0122,4.437,radius=0.7, radius_unit = pdi.u.Unit('R_sun') )\n",
    "\n",
    "#atmo -- make sure your pressure grid matches the one you computed your haze on!\n",
    "case1.atmosphere( df = pdi.pd.DataFrame({'pressure':np.logspace(-9,3,nlevel),\n",
    "                                                 'temperature':np.logspace(-9,3,nlevel)*0+600, #just an isothermal one for simplicity\n",
    "                                                 \"H2\":np.logspace(-9,3,nlevel)*0+0.837,\n",
    "                                                 \"He\":np.logspace(-9,3,nlevel)*0+0.163,\n",
    "                                                 \"H2O\":np.logspace(-9,3,nlevel)*0+0.00034,\n",
    "                                                 \"CH4\":np.logspace(-9,3,nlevel)*0+0.000466}))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "414674fd",
   "metadata": {},
   "source": [
    "And compute and plot our clear transmission spectrum, without our haze:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "01f59184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"cb883e9f-fee4-4575-9f6b-dc5b0292f45b\" data-root-id=\"p1008\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\"},\"shape\":[1153],\"dtype\":\"float64\",\"order\":\"little\"}],[\"y\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"H4sIAAEAAAAC/xWadzyWXRjHZZeSSAtJZWZGVsP9ZkRRhEplZqYkW9mJIrIVIZLslTIyQ5GRHdL92GSXkFG9P399P9eZ9znXPA8z/NufFaWSxFPlZfUfaSRh6aQoI/2SJBT5pc+fzieJKEEipxSyc01eDzP6VW+FmTu/JYl/C+ovmTJI4kzm8os9oBTvr88DWKfB1pVtWxZJXE+XPdZfQhKM5fcfz4D+QrV6lUkkwa7tVpD6iiQe5gaWh70hiVkbDun3OSTxtajQQBrrOKc8VOZHv/jJCO1xrKfgy0b9+gVJtHgY9XzPxncp+OWnpZNErfSH2jf4rkGJgKhQjBdOOmLghfkHGaarU1JIoj7wIf802oeqLzKXYPzeoa6qrRivfkdRahTrmVmw/WvHvpMR9M9Pov/8ym5zXpyr03pH6MFkkphWqub+lUsSPqc8Oq3AEdNzZ+7j/JmeT7TscI7FMLrTcZivWbzvpjL2+2/x0zUdrFtzUu6xMGS7IOPQn9i/7mXdRvVMkqBey0zoxLojt9tuLGNc63T+0jT2bYuWyopBP6+f4KYcjK+3zLqrhvnCk0+Tq7DPl2tLF5hx7lDbPyrMxSRBSNSI1KBfUX/S8AnaqUNDV1Rxrvw+im455PTrT3hDMI+3QevII4yTF2VfnEH/5LaSrC/Yd07Q50M82sdW1Qp4cZ5sXdE5Q3xXwcXVXdb4ntjkedcb+A62ljvBdJjXH9ZuehnyDbrZ2Hmsm2d/Vfwz2lcaNc/NYb9rci6a/4pIoulljMUq1m1NsOpWxTotda+KBcBbjZVxsRg32aAzGo19VJb7B19Cr+8+cjcfwnjWWzW3LkCOzeb89Aj0UvK2NMF+w+oeb9fvj9r1uulprKP2464sFWS3k1r1LJAPPL7P4ALZRXH/2l7o4dMjh9Q9oOeoZqw+zuVQ0q2uDXswiJY/Uw0aazwaTUL7qYsm9gXr9jPNeozAfvFGu+iFwERbDtb1/S62LQbEwn5nn19O1sO85riv8/mgWIjMr1rQdYDgKMJ8JZuc/d15WDfpmeZJ2I1ZseCueNhJwPUXb8bRLhiwtUgc6/ju2x7YWgD/6nN3dgD5vxZIamAcr0YKuySo7ayYcgT3F3eKhl4M/haxcHJLKvyiMuSrFwvGp5Gmp3rRn+P193PZO9iBTd2+x+DCj9JiJbSftDhV9BmyqLGoIl0pSRSbDY8IVZPEgPCFuOAqjFOakhp9TxI2330KpiEzd7HZ3/4E+xaTK9H7gHWtHw66Qr7D2HLPC9yeztCe00gSsgbOvRe7SSK5JohgaoHdbJM42NAGvfQcbDzXC7u9YDLq0kcS346K9s50Qt9LTEd0vsK/NrwLvt4PP9z0UFJ9gCSOiJ5miBwkiXAtZzuOMZLYV789qGeSJBhGG59OzpPEMTvrsT2/oP/MUzxUcyTh4Uoj+n2WJB6d3BOgTkUh1O7R2Bj8w32aU3Uq0lII37uKvCF0FOLLXdfv9AwUQmVc7LjJRjBgeGs5qLlIJpcyUohPm7x3sm2hEPQ5Mn7kdgphGc/eXc5MIQ5TlQb3s1KIlm23yqJ2UIiGxjOG/hwUYuyU0AOdXRRCuczXNXA3hRilH+b4t5NCFJZf7RHBuL3lziO22yiEtlr4jB7ay3Z2uu7aRyGOx9MWMWK+9ep7i4a9oHcaRXI/hTjqyv75lSCFeG6UXRfERyGoeB2efBGmEIb2maFuMhQi5F9igZAihZDioAzaqlIIGa5M+Qh1ClEu5HuLFe3Grju4tqN9q4Smva4QhRjkSQgfwb5rkguNPJsphJCrs2ozvoct78L2AOwfLbHl1RQ3BXpRi/jJRSEKGijmr/AdetNv38tLQBYuX9QXoxD7DRLCJI/gHK1c5XQiWD86NkpTGudIFjB+inGm501aGQ5RiKwXDbz14hRCcStfbgf2Dzz93+QQ1tVrTA6244QskHGJG/cSsRict4B23/9WzaT3UAgftyNMKdCTPZe05XXog/ZFH10xDYUYakp+y0xNIT7rbpto/4N8YVJqSb8B+ztWfWiC3quWXlVcX0I8MvRViYR8L+G0jxjoubLifHSGJHYEaInvWyaJv/l5J37Cbto/Smlar8Kv5vxH3WA/bTSdQX1/Mf7LUVYZzFugNltc/AE/4H88fhbUtdUp95giCXPTjHEX2GP+9R8qqdMkMbMQzhS7iUJsDNfRE8P6msrekV8wjibZXbQH677lp+v0gR3e+FgU4k1PIeSmZRpnYE9XxULOaLLgvirSm9OZKMSWnVWs/3DetU0+Zr6wT6nCgZ2Vi/C7iOeeUSvw+5w6jWycz8WpP94R6z8O01BinkD8qHl+sWAYdl9rWJ+H767++VutDv0/rhStaaJfPltY8y/Yozpo64J7EFsc6L4K/6HV/Wo+hPHHsx7vfA1/2XVWtoxE+4TNk6iKBZLIWnlNkcU9NWQXHDkEmerfsUvbcN7briY7lDBPRotydRF0j/4ws35PdJtpL3/BPlm8rszc8FMZo43h7qPw+60Vn2Qx/9dh7or3+P7A8UmD32skEZbHXkqP9uNRjmE933GfN2kcHmKeiC7rLSusly9+okoY7fahtMzjoMC/mKfbsF76hfnixCHEWemuLmWc88E/443r/r+1I/17wgjiUq0nUyy+I92HMX4a8YOLoObwwrmk8sa6z6C95awDDYH5zZZCykOIM1y84d8Mv5FEb3zM9HfEq65Xj3aroD/02B/L9B6SOJE2lcKBdc8c+tnQgH5y8VkSXTvsQjm9sB5xay3bXMYNcYzr19h9oXqSYLn/nDP1I0kkmcxQ8SHO0WRftIlB/BMSydjHhfg3VHrUWLcO8ZmXEpD+GXmYcbJIDeuJVapnqGA+wxUB9zeIo0shDgGyiMMRYzmhMR3I629sE/VRB4kaKi7YoP2d6CtZlRrUCWNTIa/LYXeOkTL70X45+k3uKuJ61/s8/i+Iw5a3BKbeIL7X6CZx/ENeyK83c91TiDwWZfnABfNCfdI+1KMusCip2FGC/EeTtm2XDPKIa+XL6Cjkj86C+bhm5N/BVY60n+hfe60dYIZ85asaP6OD/Hvx8h6xm8h7Ct8lyRHkx6y8Wjn71yTBneVebYT+Oq3UaLE4kjj9s8utFPmv3K9nWwDG99cu8/9GHTCRL8ZxAPnzRP+TpUiMH2KyDLRDnh8bs2Hpfo58foetpRn58owMre47rNMlzi8w/Ywkgkel3vxCPfHxfbJTTgzqyYvaCodBm4XsgHdYL8bnxsOdqIv+6LzUL8R61a/T58qw/qrvhzsXkV8tD6w+kIoliRC2MlZPyJ0rc30CONdDbTvzg09gp3R/lN/inmwL5M9+wzqzn11vdmDdhGnnTBWcbxtZdfMD7vP1SvlbFrSv6VC52GP8xd2VbhnoP6U7rbh+D3tyexeOYF1OY/rh/dAL4/bX3A8hH2aokJutQN7mvH5YBvecHZzLYAr9HmPZaLkd4ywlOyy7Kklio5RFWCHG1d8wsXaFnKC1dsUF+fiFjECgdC3q6U+3c28jD4cVRXEww37C3xZspgMHdvZ+fAb9Pyuw55BrRtyord7g2Aq/nAm1DAO9BieSDsJuow5xlyvD/kiriyaH4C8CuoPiTfCHWOfOwL1g0OTaEhvinYKVTpoW/E/K2/RB6Dj8yIdvtB1ymrpgitq63Ju74xvig4jPiGY+4gJzi2ZSLeJKpO5Zj3j43f6MMa9P8GNy94SmE/xxfnHchPYn7H7QntMM8Xw3ZWJZGfFOhf3TpXxwkNawrQHx1HF0rekROFyiLZeFuPHjg0rkWcgJd27rGCD+O3h6PIlBXuAeCdR1Q/xMn/49L4F8MXPu7CVv5G8j7xdcbYiv3rpfAwMRb90NhhR0kadPKO4e12KnEMdkaOxUIL+QOyCmDu6K7QspQHtckojEHA+FIO/NjeUhL2fWPG/adZBCeFx/aHoSeZH2whJ1ND+F+M9+riEN+W3KcoreFfn6DF/5jVo5CuGcp+Opjfw3e2uoZhh5e2/VPock5O0rXZcM3NHuztLdLCVJIZj76B9txrodSeHdIsirNIFyt6axTrHsUocW5qnUPRNXPUwhho981+tQoRAlXm5/2E0phLhd7J+DjljvnCOtynkK8S9d6gPLAdQVkUm0z5DHbW0tw2RAXzEfqkUB5BVt6Upp1BFbOPpXy7DeXmmVa1TI5zk73Ca/H8W5Vmd1NuB7Mgjm0mJ8J1fONQllfOdturaoRoxjOhfBj5hFZP0996UQ55a8zGKWhTyvmZHPpYT7aFxsVM5HfSE4FrNfFPf9T7tEYwr5TjRhaJUa+k1u56GMQn8SGx82dyC+96+e1tJB3Ja819R2CfF1h9OznkjY3wNDr1xBxF36PWceSsIuj2YyBxQijiYKqUoloV2mvMDdAPE0JfqTcgnsuIb+12gv4ujHmL/nEyAzpChkCjTgnXElQicFdv/l1rXZjfAHhfiz4p8Ql8VdwpuMMH7DHYfpyS7I/sdHv0FOOs8sko14/oLM3VQGitrR8sRg/m1VEX0LjNP//ejHD+z/3MKXLwT9B7p/vW3Ad3DK7v1hgfYPXSz71pA3BFaaWocgU1eIdPTge+o3/a7Zh7wWY3DIhJ5CEhlFrPmzyDudE27UYfAvEyNP2kbsHzbAMOkBfxSesm1NaULebS50e06ShNHr366zyNu7GhaZajCPKVbBYQPs35fFvK8Afnf1I5v7L/jXsp5wQCfuNZ5lbWsU7vHTtuM5z1EXpIldoNuI76pb0yqwwz2/f9ee8ns9z6aLqzUg/7IosrVVIM930JTZ+UE/PqrhjqzQ37kHfrbr+pEODfR8DP0diuWJnkH+lk+/SbxEexWTZJAe/PfbRyGRWPi5JKvG3BziASXWYnY7/F/KX7l9FixPuPhABeN5fF6LjWC/wqp9YeNY5wAvGfIV66r5aq4woT6qv/1M6CS472rc3hv06zSRSEKd6i/qF+OJutvST+jpS9RZrmPUwVzwU7PKuxrq8OdK79qicIzL89Mf+oh6dm3Y8nYV7FDZSrf1LOyypLjkY6Ao1vN5HraCukv/goeWE+rMjJEI/0Pw24Rn5/ZS4B9dREpqOPyj66hYUzXmUR5c5z0LmV67+uYy3gmSU0rllWwUIldD4nMAxrd7pQ6KIy70Dhpdisd+Yn/lsvxQx9pd3plJgJO1jYVDqHONPP8Se1BfB41S2friu3nnq+I48J2TxntN+hGnDm1NUVUBadQNPK9jny1eiT32GNfVXuC7EeeWoJzrk8L9Tf8a696AemfNK1tivf5UVp+d+gM9Ovk8ZTCHvgcis7WFYXdX1OdsbqNOIRqsnnej3pC/VFpTB3tqq2LSmATbi4uoneEHb0ZmVZ+WkUQmzVfVAlDrWot9KuqAw2nVgp7IYyt6fVwCeF8m59VKiiP/vftL83oQedi/5ia/DfL4vc32h/+Bup5k8ivk1fhfKxW8qBP8JjUrqpDXXfqiX4+jXjDZalGch/7gN6c2RkFWlf6ZH4x3rZNj5t0TkI/NJFBqsf5jvZntash7PvaHE6aQD3mPBt8RxHuUoWdSRRX5srj6xr541CsaPcXsqch3gV5+z45Bzth3Z6kG/i31Ji1QBv4arGB1yAD11cxL+1/6GHeLnut3FWQx01eMYqDcDpopebRv9kqt1Eed5WMUT1QhXnx//zREdj0/drzdRI978h4q7cjB/X3TDeINgd8+aJQZS8E9Z+25+F0DfijQbNcpCr+Kd/XcugF+nHe7NvEb9DHoEfsrA+9Y2Stuc4wYv7bPnZ0L48w3JAYNwV8rp3WS5aG/vHLGN5Xw173xWgZN0O9ZG83Wg8ifis9ajMrgt11fE/bTwu8tiuZTHyAfDs2p+9Wi/+/vmdOh2Kf25GZPf/Bumm2BBqhg69rZj34e03vUxlhvjsPz7wX454jYq5+70M77t3JzCPxUbe1nJDvWYyo9spEP43QDmmsZ8O6Rrq42F4JfKkVn8vBj35p3aY4HEVeSTnuVE4gbpNxHrreIOxeiFnexwk/FXzjzdSMuS37wl83GeZ4p1sfV4pxWjraPeiFbJgTtsMN3aS7sb+TB/POdWRo5sN+8R3XSXzBus1z+Ex7MF8io6DiOOMpO5XYnHnVO9U4xOlfUn6//O5r8PgH1maGy5JYIkjB0G9gQEoh4mLxj+EAA6iL6E5Gsj5AHyjZ+fPEY8S+C7u+NcNT1bP3itmgPqK9S/IlxiQvmPT8fksTJ5KMsfpAb2xp+jWM854njL36A+hy5l3hQN/7oF5g2jIK+je/l1qO+nHoQ1KGCejOYxUC/C3Vm4yT5dBPsNvds6Aw17LxJQ5vjG+xy7OlZlmyQ498BvmzUb0WSbqPx8KdNSWw3hFGfNew/aKsEu7SufHvDAPWY5GU2vzuwv6Q1/6EQtB/o716+/gV2lRN55T7yjK26k/4KqHLp2P4B2AHbcKkjP/QgPWGdIQ45xvCEXT7u99OhKF8p2M8pEUdGefQLrSVf3Q/9hptQmXCtv9t2LAW5/8Y7ovaunw/0zSj+o1gE7VFMXtyPIO/Wa6paj9Omke3jr2EfzUwr4yaY737VfMQJeopY5S+8hvFFmvkH/qCdVXAxbjf06Ht8Is4Q/bwZNZ+L8S4xlOzm0APXcg6aVIM8/a0pffAr48nHtGWIJyF/fDllUScH6fX1mqDOrhC8dT4YcWPuSMyBn4gTrqvnTz2Cnue+yfdEo+6unVer54AevKMqT7MF4X1YtKx51Q/vz1ozr2pf3M8yOa/khn1P10ZOukJ/YRJ3W12gPyknZhrQ/1hI6ntQyXfzcUd3kuh7acF0HjymwUG17IX3ZKd4K/99vJdHCv5WYd32i3t0y2AXimW2AXWgd9FVE0PY2xVONwOzSPhLn46XOt4JjTp9LTOJyNNWeaGP1n8H/OQsIYDzHKs06guHvkuEj5c9gF7fStGUaSB+XJBj1LiFeJL2drQlAvei2PqJQwT1zObNTArr9UR0TKc6BfrrNSMp7xBfUnLYWUIQb873OcyaQb/cfPXV0dBr8YH5418g81lzRKhi3oR4TXk64l3pUakX7xDHWa3uHzaGnd2uHv44jfllcmfS3uJdeEmgim8B7d8ML0Q2YlxIb6fvB9QZ1IIKz4Ih26Xv3kyDd+EzIc976++f08mGSyHQB6NPTXEx7N6FXsndFH5w5Ir/x4JQnOsmT5Qa7sWdd4/DVdzTnUWvvf0eWE+hsd4c+shqTs9fuwO7rlpiFwebBHLiVaGH0QWzQiXIpbWO/RXQF8meQvUJtJFNVBvHPN+mrwUr0M8kF7d47j2sn8ngZ/UA7y1u0ZtGwbinlYwjhfBryqkGlo6n+F6X1nwX6EG+pEZ8FHllQO9ybOQLxOHzw+ZV8fAD/fqvO3COE58nQuKgp3spQ5m38P5rv1sxGY580xvWyu0H/91baWPwEO9Qj/vDRw6BMV42N5eQ3yKsxDUu4d1pN2n3hBu8YPTjGyf831Mue/s/7LPxleWmX7DXwcXSiLOIG4KSlhuGYB95f+5MvcX+WZbuL9oxb7VQz3sVjBMcYj+z/neNVbU/wVinXZwq7ej6e5V7IK4M33mAPZH6Eu57p7x57Dmsf6zrdKAnmDLX6EGN85Udqtq8G/7ysnVI+Sfy5PGdNbzx6I+6trG5B3HuCZNPWRvuJ0Lhbcl8zPrvAv5+Ezi3xpeYM+u/LxNBTBuKEE+T34eIrv/enlFgoaMDv2QU69+5H3Y5bppwJxF5NzD1x5IX3pXU+VJ8q7CbzT2Orzfh/Xo425DVAusOm87eOg6/rDPdYd0egvFOtyzE4Z9elvKZxYijOQdzJz0gi8tRbXZFvN02rFO0zR/5ZzezFD30+bkhNK0OMlm9pq8Lee/Kys4dGMfckfhtJ+xJO3NLz2HIBoPD5VKI8xzX5sMr0R5Qs92VD3ZAnaXgFo71k0Nlf3xDHDCsCTyZB7vhLRrh1IEd/epN/HjSE/Hk0YFCfW/YkZXHxG3YJ315sNMWyNptU4M92P+e03LHOOQp8uLA87skoadwpbbECfWw7aenDs6I70O1TAUgSb3d5zHajcuvCvM4QB9aWU069lhHukT/K+z3PRkaFop+v2PVv1kcEY/f+IVKov+/5SsXftmh3ophc98A+fUF5+fi4KpogYQj+KLg80QFmCFwausi+MaEN04V6z8csTHOBXfd9kulxXqJy518XuBjde/X27GPqVjqy234rihVvlgO+JW3wvyJNvjVAt23V7I4P31VDGU/7uOapl6OMO6nbjnv+kH4E011m7omeDDDz3cZlBxNM0zH/RetWd94jPjH/ZDJywL3wqkkyJSIuMjnzHmsFHrYGCP6gg16zap9edMK85KFw+ue4377L91ssAXb7s2KcyCeXt6mrCkIfrbiSV3vn9Jw5NfxIQl+SakmQcicOgM+V9Df/S3tky/aWX6Xv26EXMhAI3Ic38t8OIy6Giy/wnigGGSJ4fDY6LFe17UGXwO/vMyp8gAD9bRP1K3zQ7YjP9Y1KuWLdgadjfRa/oBl9FnCblj3gla3RSZYIGZAkYCeF5miHC+BWiGtx6NxL04Vnm1B4HZZk4veOBfv0yzZB7iH/UdcTiei3Z75fmcKZNPp3oh5yKqv+FnbMS7405wlNeTFRzNnLoMicYbDD8GXo2ecRHBvm3JTJQXAGxnCh+6Bglqh1hvX75dNx/Mv5Nr+x6ubILM7/WdzEeT5KB6TCGY/adRcAJ/6qsSoQg8HKq8+jge3hY+dWwKtf3PX34a+uriE5RdAE+WSCH/o503ETcaXINEjFjoKP6FXNU2oQjzQ7pi/1g//afpex7QEv7lge5fxJPyml39/Mj/ksWT9FzLwX9cg+oscaGdqan10E/POKVIMktfrKer6zz/Brjx/qlVQPN7M5TzGWduJdUeA9998192GdXZRK1jqgP72sxNhoDL3NrYzsJcHfm1Fs5AP7v1TdwKyM4vLvRBwtDT/7zfw3hU+emHsv2iW0H0XTDwXY/QVPNFycEgJeUb6Q8uaMzjwYEr5K6h+LH9SOAz5QvedcBxInZB3tx+85qajz464txg0M2wIbm1bpX4CbpC0C+oHbZ/cMxNHvqIPi6O4gSfHr9E1gm/NJWu4kNeFOTPprcH9C9pyxeAVvTy7TYhv/nvzqS+Bj6zdkl+Bm3gkzVbBlp7rTzSikd/Mn0bEg4M9N88tg4qRVe6XULd41SZEVoNS11xEDiNPpa6eNE4GJ+W35U6AUk+oyoMQR5mYX9FJggGWY8l24IDxMNU7MGmwP5wKeWQ4b9VQCyz/c9YjCfR1SVeYB5PF0jlPIh87+hZnhoGsFxpHhkA5E3VjceQPxbZFJU/QWW9pQzP43VWngQv5qDyGXskGfH98NLMcHHfWtN6K/KXG+VXNCPymmPszD1zwkFTagHwVRFoP6YA1p37yJoD+wy1KM6C54WPWE8i7S5NlX4LAZtnzv76BGTrGAqLIay0Jyfc9QCEn9tZmsP5omjL3+t+LS+9x2IIUjhGTSlC4myLFinycVqZ/3xRkOnJCqwSkWuV8xYh8uJu2tMoYXPurNpb6ct1efzOugR2yfT5KyIeXAqQ8138n3tshKDcC5o6PbZdG/r5n+NLVDxxrYtL+AsbdzWQQQN714G1qdAG7N+sU1IOUtqN+e5Afv2T/umMNnsh6ol0K7mcpPL4F+d/FWlfCAJQ62SWYA5pK99tTIf9abfWu0QL5emtOvgB9S2w85sH78pT7SsjL3VczHkeCVWlCRaPgA/830zJ4LzwLZhR/CPKepvfuBXcoNA8cQh7O5yk45w7SjabVr/++rvT9uSQP6hP5oa8FdqC76uGhGvAGfRfzDrzDWcJPm5mDWdqnQwpBN+rhZUbkd0kPh/uXQXpNHYlM8Kk0w/Af0E2pNPIc8n7qwiG9RNCGT1RwHlS5P0StjLzeyak+FAXaV4t+HQcdpkRq5PHu/phD+/7R+vv7zlodCQayP5sQR/1u/pl7yQc0vibP2QnWhihq8OPd087p5OMKZoaG1jWA9a9ouPcW4t0iE+pgC5o8Ke57D77SZ/ZlR50xKNI+bAE25I9alRSt/z9DwI/NqEc2TMrdMAQVlQdo88G8qg+vafGeUlwKMr8Ilv73kTcdLNyp9WMNnH3//sM51K+Rc5MpSaAPY2DoAth3fO8D1VLEvWMOAbFgRVj4kxlQilEx4z/U6dIehY0R4L/Gt8tjYLq3vvjRctgTW4hdMEh/4kTVAOj4jmrXEbxHf35ecXsAMnztmfgK8nmYW4lVksSfA+SMDyhR3eC8/jv9LkZVdqEq1NG/y9+5g4Sih00ryLgpS5QXdZVlquLv9d/tV865NTeCTh1v8/dVw/76Vp47gA89NaPrQCHmtkhO1O9P2549twXrmCKLasDt3S19u1CXbaSqZb4JFm6yP1sFzltJxrLj3bFBNn7BCnzHcsWgHDzhJ9nBijp/PtHisgVoIOk1sf5euHEjJoClDu+MjCY5MzB9f89SMajcVlSz/vcDiaSG59fAlynnA4vAHFuO+1vwnqvYmhFsAr6hU3tVCMYm5Xze3IB6NHDnoAn4P+OFsqgIJAAA\"},\"shape\":[1153],\"dtype\":\"float64\",\"order\":\"little\"}]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1049\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1050\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1045\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#0072B2\",\"line_width\":3}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1046\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#0072B2\",\"line_alpha\":0.1,\"line_width\":3}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1047\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#0072B2\",\"line_alpha\":0.2,\"line_width\":3}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1016\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"PanTool\",\"id\":\"p1029\"},{\"type\":\"object\",\"name\":\"WheelZoomTool\",\"id\":\"p1030\",\"attributes\":{\"renderers\":\"auto\"}},{\"type\":\"object\",\"name\":\"BoxZoomTool\",\"id\":\"p1031\",\"attributes\":{\"dimensions\":\"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[\\u03bcm]\",\"axis_label_text_font\":\"times\",\"axis_label_text_font_size\":\"14pt\",\"axis_label_text_font_style\":\"bold\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1022\"},\"major_label_text_font\":\"times\",\"major_label_text_font_size\":\"14pt\"}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1023\",\"attributes\":{\"axis\":{\"id\":\"p1019\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1028\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1024\"}}}]}}]}};\n  const render_items = [{\"docid\":\"5f104e8e-58d5-455e-9d9e-3f27444e14ae\",\"roots\":{\"p1008\":\"cb883e9f-fee4-4575-9f6b-dc5b0292f45b\"},\"root_ids\":[\"p1008\"]}];\n  void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    let attempts = 0;\n    const timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1008"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "df= case1.spectrum(opa, full_output=True,calculation='transmission')\n",
    "\n",
    "wno, rprs2  = df['wavenumber'] , df['transit_depth']\n",
    "wno, rprs2 = pdi.mean_regrid(wno, rprs2, R=300)\n",
    "full_output = df['full_output']\n",
    "\n",
    "ppi.show(ppi.spectrum(wno,rprs2*1e6,plot_width=500))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25c50292",
   "metadata": {},
   "source": [
    "Now, let's add in that hazy information. We need to make sure the pressure grids match (by reducing the layers by one because of PICASO's idiosyncrasies)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8b8381fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "case1.clouds(df=df_haze.astype(float))\n",
    "hazy= case1.spectrum(opa, full_output=True,calculation='transmission')\n",
    "hazyx,hazyy =hazy['wavenumber'] , hazy['transit_depth']\n",
    "hazyx,hazyy = pdi.mean_regrid(hazyx,hazyy, R=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b09f7a85",
   "metadata": {},
   "source": [
    "Let's compare our hazy spectrum to our clear spectrum!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "22253f07",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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\"},\"shape\":[1153],\"dtype\":\"float64\",\"order\":\"little\"}],[\"y\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"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\"},\"shape\":[1153],\"dtype\":\"float64\",\"order\":\"little\"}],[\"y\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"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\"},\"shape\":[1153],\"dtype\":\"float64\",\"order\":\"little\"}]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1105\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1106\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1101\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#E69F00\",\"line_width\":3}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1102\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#E69F00\",\"line_alpha\":0.1,\"line_width\":3}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1103\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#E69F00\",\"line_alpha\":0.2,\"line_width\":3}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1063\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"PanTool\",\"id\":\"p1076\"},{\"type\":\"object\",\"name\":\"WheelZoomTool\",\"id\":\"p1077\",\"attributes\":{\"renderers\":\"auto\"}},{\"type\":\"object\",\"name\":\"BoxZoomTool\",\"id\":\"p1078\",\"attributes\":{\"dimensions\":\"both\",\"overlay\":{\"type\":\"object\",\"name\":\"BoxAnnotation\",\"id\":\"p1079\",\"attributes\":{\"syncable\":false,\"line_color\":\"black\",\"line_alpha\":1.0,\"line_width\":2,\"line_dash\":[4,4],\"fill_color\":\"lightgrey\",\"fill_alpha\":0.5,\"level\":\"overlay\",\"visible\":false,\"left\":{\"type\":\"number\",\"value\":\"nan\"},\"right\":{\"type\":\"number\",\"value\":\"nan\"},\"top\":{\"type\":\"number\",\"value\":\"nan\"},\"bottom\":{\"type\":\"number\",\"value\":\"nan\"},\"left_units\":\"canvas\",\"right_units\":\"canvas\",\"top_units\":\"canvas\",\"bottom_units\":\"canvas\",\"handles\":{\"type\":\"object\",\"name\":\"BoxInteractionHandles\",\"id\":\"p1085\",\"attributes\":{\"all\":{\"type\":\"object\",\"name\":\"AreaVisuals\",\"id\":\"p1084\",\"attributes\":{\"fill_color\":\"white\",\"hover_fill_color\":\"lightgray\"}}}}}}}},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1086\"},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"p1087\"},{\"type\":\"object\",\"name\":\"HelpTool\",\"id\":\"p1088\"}]}},\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1071\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1072\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1073\"},\"axis_label\":\"Spectrum\",\"axis_label_text_font\":\"times\",\"axis_label_text_font_size\":\"14pt\",\"axis_label_text_font_style\":\"bold\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1074\"},\"major_label_text_font\":\"times\",\"major_label_text_font_size\":\"14pt\"}},{\"type\":\"object\",\"name\":\"Legend\",\"id\":\"p1107\",\"attributes\":{\"location\":[0,0],\"click_policy\":\"mute\",\"items\":[{\"type\":\"object\",\"name\":\"LegendItem\",\"id\":\"p1108\",\"attributes\":{\"label\":{\"type\":\"value\",\"value\":\"clear\"},\"renderers\":[{\"id\":\"p1095\"}]}},{\"type\":\"object\",\"name\":\"LegendItem\",\"id\":\"p1109\",\"attributes\":{\"label\":{\"type\":\"value\",\"value\":\"hazy\"},\"renderers\":[{\"id\":\"p1104\"}]}}]}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1066\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1067\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1068\"},\"axis_label\":\"Wavelength [\\u03bcm]\",\"axis_label_text_font\":\"times\",\"axis_label_text_font_size\":\"14pt\",\"axis_label_text_font_style\":\"bold\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1069\"},\"major_label_text_font\":\"times\",\"major_label_text_font_size\":\"14pt\"}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1070\",\"attributes\":{\"axis\":{\"id\":\"p1066\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1075\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1071\"}}}]}}]}};\n  const render_items = [{\"docid\":\"976d37f2-afab-4653-ac7a-1ffbddeab5a7\",\"roots\":{\"p1055\":\"d2a6ad96-0351-4425-9eb6-a75a9c8e39f9\"},\"root_ids\":[\"p1055\"]}];\n  void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n  }\n  if (root.Bokeh !== undefined) {\n    embed_document(root);\n  } else {\n    let attempts = 0;\n    const timer = setInterval(function(root) {\n      if (root.Bokeh !== undefined) {\n        clearInterval(timer);\n        embed_document(root);\n      } else {\n        attempts++;\n        if (attempts > 100) {\n          clearInterval(timer);\n          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n        }\n      }\n    }, 10, root)\n  }\n})(window);",
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1055"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ppi.show(ppi.spectrum([wno,hazyx],[(rprs2*1e6),(hazyy*1e6)],\n",
    "                  legend=['clear','hazy'],plot_width=900,plot_height=300))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2010c3b",
   "metadata": {},
   "source": [
    "This is a very hazy run, wow! In the visibile and NIR, the haze creates a bigger scattering slope and mutes the water features at Hubble WFC3/IR wavelengths.\n",
    "\n",
    "With this amount of haze, we can actually see IR features in the spectrum that are due to the haze itself. At 4.6 microns, we see absorption due to nitrile functional groups (C=N bonds) and from 2.8 to almost 4 microns we see a large, broad amine (N-H) feature. "
   ]
  }
 ],
 "metadata": {
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