GCR SpecGen.ipynb

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    "<h1><center> GCR SpecGen <a href=\"https://doi.org/10.5281/zenodo.2573359\"><img src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.2573359.svg\" alt=\"DOI\"></a></center></h1>\n",
    "\n",
    "Welcome to GCR SpecGen!  This is a Jupyter notebook for conveniently generating Galactic Cosmic Ray (GCR) spectra as a function of source ion and solar modulation (which is a function of time) using [Daniel Matthiä's model (linked here)](https://www.sciencedirect.com/science/article/pii/S0273117712005947?via%3Dihub).  The spectra can be copied or downloaded as text files in a raw tab-delimited format or as source cards ready to be copied into a MCNP or PHITS input file.\n",
    "\n",
    "\n",
    "### Setup instructions\n",
    "\n",
    "There are a few steps you need to take before using this tool if this is your first session of this Jupyter notebook.  Above and on the right side of this body of text should be a small box which either says 'Trusted' or 'Not Trusted' inside it.  If this notebook is already trusted, then great!  If not, click the 'Not Trusted' box and confirm that you trust this notebook in the menu that appears.  This Jupyter notebook uses HTML and JavaScript for a few things to make using this notebook as clean an experience as possible and to allow cells, the individual units containing all of the code and UI elements below, to update by just pressing the buttons on the page (rather than having to manually run the cells), making this page usable by anyone regardless of their proficiency in any of these languages.\n",
    "\n",
    "After the notebook is trusted, all of the following cells need to be initialized.  Either click the 'restart kernal and re-run whole notebook' button above ( &#9193; ) or run the first few cells manually by either clicking the 'Run' button above or pressing Shift+Enter a few times and then clicking the green \"Initialize code\" button below once it has been initialized.  This procedure will only need to be performed once for each time the Jupyter notebook is launched.\n",
    "\n",
    "### A few notes on usage\n",
    "\n",
    "The input source cards generated for PHITS and MCNP are designed for each GCR ion to be simulated independently.  While all source ions could be consolidated into a single input deck, the complexity in the reactions and cascades generated by each ion, the relative prominence of each ion, the significant difference in computational power required to simulate a complete history for each source ion, and differences in each use case in terms of desired results and available computational resources makes providing a universal solution to this nearly impossible.  To best optimize these factors, it is suggested to simulate each source GCR ion separately (for however many histories is deemed necessary for each) and to then combine tally results from each source ion in post, weighted by each source ion's relative fraction of the total GCR flux which is tabulated above the complete spectra.  \n",
    "\n",
    "Additionally, these source cards are designed around MCNP6 and PHITS ver. 3.0; additional changes may be necessary for older versions of these codes.\n",
    "\n",
    "#### W parameter\n",
    "The value of the solar modulation parameter W can be automatically calculated when provided with a date or range of dates.  However, the sources of data for these W values varies depending on the date and are listed below.\n",
    "* 1749/07-1964/04 -- W set equal to the [International Sunspot Number (ISSN)](http://www.sidc.be/silso/infosnmtot)\n",
    "* 1964/05-1997/07 -- derived from [Oulu Neutron Monitor count rates](https://cosmicrays.oulu.fi/) as specified in [Matthiä et al.](https://www.sciencedirect.com/science/article/pii/S0273117712005947?via%3Dihub)\n",
    "* 1997/08-2012/04 -- directly from [Matthiä et al.](https://www.sciencedirect.com/science/article/pii/S0273117712005947?via%3Dihub), derived from [ACE data](http://www.srl.caltech.edu/ACE/ASC/)\n",
    "* 2012/05-2019/01 -- derived from [Oulu Neutron Monitor count rates](https://cosmicrays.oulu.fi/) as specified in [Matthiä et al.](https://www.sciencedirect.com/science/article/pii/S0273117712005947?via%3Dihub)"
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    "%matplotlib notebook\n",
    "from IPython.display import HTML, display, Javascript, Math, clear_output\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import re\n",
    "import ipywidgets as w\n",
    "import unicodedata as ud\n",
    "import zipfile as zf\n",
    "import datetime as dt\n",
    "import time\n",
    "#import tabulate\n",
    "\n",
    "HTML('''<script>\n",
    "  function code_toggle() {\n",
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    "    code_shown = !code_shown\n",
    "  }\n",
    "\n",
    "  $( document ).ready(function(){\n",
    "    code_shown=false;\n",
    "    $('div.input').hide()\n",
    "  });\n",
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    "'''\n",
    "This code serves to quickly generate GCR spectra for ions with Z=1-28 using the Matthia model\n",
    "https://www.sciencedirect.com/science/article/pii/S0273117712005947?via%3Dihub\n",
    "'''\n",
    "\n",
    "def slugify(value):\n",
    "    \"\"\"\n",
    "    Normalizes string, converts to lowercase, removes non-alpha characters,\n",
    "    and converts spaces to hyphens.\n",
    "    \"\"\"\n",
    "    value = str(ud.normalize('NFKD', value).encode('ascii', 'ignore'))\n",
    "    value = str(re.sub('[^\\w\\s-]', '', value).strip().lower())\n",
    "    value = str(re.sub('[-\\s]+', '-', value))\n",
    "    return value\n",
    "\n",
    "def on_click(change):\n",
    "    #display(Javascript('IPython.notebook.execute_cells_below()'))  \n",
    "    #display(Javascript('IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, IPython.notebook.ncells())'))\n",
    "    #display(Javascript('IPython.notebook.execute_cell_range(IPython.notebook.get_selected_index()+1, 6)'))\n",
    "    display(Javascript('IPython.notebook.execute_cells'))\n",
    "\n",
    "def on_click_run_all(change):\n",
    "    display(Javascript('IPython.notebook.execute_cells_below()'))\n",
    "    \n",
    "def on_click_next(change):\n",
    "    display(Javascript('IPython.notebook.execute_cells([IPython.notebook.get_selected_index()+1])'))\n",
    "\n",
    "def on_click_calcs(change):\n",
    "    display(Javascript('IPython.notebook.execute_cells([8,9,10,11])'))\n",
    "\n",
    "def on_click_67(change):\n",
    "    display(Javascript('IPython.notebook.execute_cells([10,11])'))\n",
    "\n",
    "def gen_generic_save_file_button():\n",
    "    generic_save_file_button = w.Button(\n",
    "        description='Save file (txt)',\n",
    "        disabled=False,\n",
    "        button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "        tooltip='Save a text file with information of the this spectrum ('+plotted_spectra_names[i][j]+') in the local text_files/ folder',\n",
    "        icon='save' # pencil, rotate-right\n",
    "    )\n",
    "    return generic_save_file_button\n",
    "    \n",
    "def on_click_save_text_files(change):\n",
    "    arc_fname = r'text_files/' + window_title + '.zip'\n",
    "    zfile = zf.ZipFile(arc_fname, mode='w',compression=zf.ZIP_DEFLATED)\n",
    "    for i in range(len(plotted_spectra_names)):\n",
    "        for j in range(len(plotted_spectra_names[i])):\n",
    "            txtname = plotted_spectra_names[i][j] + '.txt'\n",
    "            zfile.writestr(txtname,plotted_spectra_text[i][j].replace('\\n','\\r\\n'))\n",
    "    zfile.close()\n",
    "    update_print_str = 'ZIP archive of text files saved to: '+arc_fname\n",
    "    print(update_print_str) # print saved note\n",
    "    \n",
    "def on_click_save_plot_pdf(change):\n",
    "    global fig, window_title, update_print_str\n",
    "    fname = r'images/'+window_title+'.pdf'\n",
    "    fig.patch.set_alpha(0.0)\n",
    "    fig.savefig(fname,facecolor=fig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note\n",
    "    \n",
    "def on_click_save_plot_png(change):\n",
    "    global fig, window_title, update_print_str\n",
    "    fname = r'images/'+window_title+'.png'\n",
    "    fig.patch.set_alpha(0.0)\n",
    "    fig.savefig(fname,facecolor=fig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note    \n",
    "    \n",
    "def on_click_save_plot_svg(change):\n",
    "    global fig, window_title, update_print_str\n",
    "    fname = r'images/'+window_title+'.svg'\n",
    "    fig.patch.set_alpha(0.0)\n",
    "    fig.savefig(fname,facecolor=fig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note\n",
    "    \n",
    "def on_click_save_plot_pdf2(change):\n",
    "    global Wfig, window_title2, update_print_str\n",
    "    fname = r'images/'+window_title2+'.pdf'\n",
    "    Wfig.patch.set_alpha(0.0)\n",
    "    Wfig.savefig(fname,facecolor=Wfig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note\n",
    "    \n",
    "def on_click_save_plot_png2(change):\n",
    "    global Wfig, window_title2, update_print_str\n",
    "    fname = r'images/'+window_title2+'.png'\n",
    "    Wfig.patch.set_alpha(0.0)\n",
    "    Wfig.savefig(fname,facecolor=Wfig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note    \n",
    "    \n",
    "def on_click_save_plot_svg2(change):\n",
    "    global Wfig, window_title2, update_print_str\n",
    "    fname = r'images/'+window_title2+'.svg'\n",
    "    Wfig.patch.set_alpha(0.0)\n",
    "    Wfig.savefig(fname,facecolor=Wfig.get_facecolor())\n",
    "    update_print_str = 'Plot saved to: '+fname\n",
    "    print(update_print_str) # print saved note\n",
    "\n",
    "def on_click_reset_sliders(change):\n",
    "    global fig_x_in, fig_y_in, default_fig_x_in, default_fig_y_in\n",
    "    fig_x_in, fig_y_in = default_fig_x_in, default_fig_y_in\n",
    "    display(Javascript('IPython.notebook.execute_cells([10])')) # refresh sliders\n",
    "    \n",
    "def on_click_zoom_out(change):\n",
    "    global zoom_mult\n",
    "    zoom_mult = 8\n",
    "    update_print_str = 'Zoomed out!'\n",
    "    display(Javascript('IPython.notebook.execute_cells([9])')) # redraw plot\n",
    "\n",
    "\n",
    "def on_click_refresh_plot(change):\n",
    "    global update_print_str, currently_updating_fig_dims\n",
    "    update_print_str = 'Plot has been updated/refreshed!'\n",
    "    display(Javascript('IPython.notebook.execute_cells([9])')) # update and redraw plot\n",
    "    \n",
    "def gen_all_none_buttons_v2():\n",
    "    # uses actual Buttons\n",
    "    global all_none_strings\n",
    "    select_all = w.Button(\n",
    "        description=all_none_strings[0],\n",
    "        disabled=False,\n",
    "        button_style='', # 'success', 'info', 'warning', 'danger' or ''\n",
    "        tooltips=all_none_strings,\n",
    "    #     icons=['check'] * 5\n",
    "    )\n",
    "    select_none = w.Button(\n",
    "        description=all_none_strings[1],\n",
    "        disabled=False,\n",
    "        button_style='', # 'success', 'info', 'warning', 'danger' or ''\n",
    "        tooltips=all_none_strings,\n",
    "    #     icons=['check'] * 5\n",
    "    )\n",
    "    select_all_none = [select_all,select_none]\n",
    "    return select_all_none\n",
    "\n",
    "def on_click_set_checkF(change):\n",
    "    global checkTF\n",
    "    checkTF = False\n",
    "    display(Javascript('IPython.notebook.execute_cells([IPython.notebook.get_selected_index()+1])'))\n",
    "\n",
    "def on_click_set_checkT(change):\n",
    "    global checkTF\n",
    "    checkTF = True\n",
    "    display(Javascript('IPython.notebook.execute_cells([IPython.notebook.get_selected_index()+1])'))\n",
    "    \n",
    "def on_click_sync_dates(change):\n",
    "    global date_start, date_end\n",
    "    date_end.value = date_start.value\n",
    "    \n",
    "def on_click_calc_W(change):\n",
    "    global W_slider\n",
    "    W_slider.value = calculate_W()\n",
    "    \n",
    "\n",
    "    \n",
    "    \n",
    "def toYearFraction(date):\n",
    "    if date==None: return None\n",
    "    \n",
    "    day_of_year = dt.datetime.today().timetuple().tm_yday\n",
    "    fraction = day_of_year/365\n",
    "\n",
    "    return date.year + fraction\n",
    "  \n",
    "    \n",
    "def calc_GCR_intensity(Z,W,E):\n",
    "    '''\n",
    "    Calculate GCR flux for a given ion at a given energy\n",
    "    Inputs:\n",
    "       - Z: GCR ion Z\n",
    "       - W: solar modulation parameter\n",
    "       - E: GCR ion energy (in MeV/n)\n",
    "    Outputs: \n",
    "       - IOSI: ion flux in (s*sr*cm^2*MeV/n)^-1\n",
    "    '''\n",
    "    \n",
    "    if Z<1 or Z>28 or W<0 or W>200:\n",
    "        return -99\n",
    "    if E<10:\n",
    "        return 0\n",
    "    \n",
    "    AI = [1.0 ,4.0,  6.9,  9.0, 10.8, 12.0, 14.0, 16.0, 19.0, 20.2, 23.0, 24.3, 27.0, 28.1, 31.0, 32.1, 35.4, 39.9, 39.1, 40.1, 44.9, 47.9, 50.9, 52.0, 54.9, 55.8, 58.9, 58.7]\n",
    "    CI = [1.85e4, 3.69e3, 19.5, 17.7, 49.2, 103.0, 36.7, 87.4, 3.19, 16.4, 4.4300, 19.300, 4.17, 13.4, 1.15, 3.060, 1.30, 2.33, 1.87, 2.17, 0.74, 2.63, 1.23, 2.12, 1.14, 9.32, 0.10, 0.48]\n",
    "    gammaI = [2.74, 2.77, 2.82, 3.05, 2.96, 2.76, 2.89, 2.70, 2.82, 2.76, 2.84, 2.70, 2.77, 2.66, 2.89, 2.71, 3.00, 2.93, 3.05, 2.77, 2.97, 2.99, 2.94, 2.89, 2.74, 2.63, 2.63, 2.63]\n",
    "    alphaI = [2.85, 3.12, 3.41, 4.30, 3.93, 3.18, 3.77, 3.11, 4.05, 3.11, 3.14, 3.65, 3.46, 3.00, 4.04, 3.30, 4.40, 4.33, 4.49, 2.93, 3.78, 3.79, 3.50, 3.28, 3.29, 3.01, 4.25, 3.52]\n",
    "    \n",
    "    P = [0.02,4.7]\n",
    "    \n",
    "    i = int(Z-1)\n",
    "    \n",
    "    E0S = 938.0 # rest mass in MeV/n\n",
    "    if Z>1: E0S = 939.0 # rest mass in MeV/n\n",
    "    E0SS = E0S/1000 # rest mass in GeV/n\n",
    "    ES = E/1000 # energy in GeV/n\n",
    "    RigS = (AI[i]/Z*np.sqrt(ES*(ES+2*E0SS))) #rigidity in GV\n",
    "    betaS2 = (np.sqrt(ES*(ES+2.*E0SS))/(ES+E0SS)) #convert kinetic energy per nucleon to beta=v/c\n",
    "    R0S = (0.37+0.0003*(W**1.45))\n",
    "    DELTAI = (P[1]+P[0]*W)\n",
    "    PHII = CI[i]*(betaS2**alphaI[i])/(RigS**gammaI[i])\n",
    "    PHII = PHII*((RigS/(RigS+R0S))**DELTAI)\n",
    "    IOSI = 0.0001*PHII*AI[i]/Z*0.001/betaS2\n",
    "    \n",
    "    return IOSI\n",
    "    \n",
    "def assemble_GCR_flux(W,nEbins=1000):\n",
    "    '''\n",
    "    Composes a NumPy array containing GCR flux from 10 MeV/n to 1 TeV/n for each GCR ion with Z=1-28\n",
    "    Inputs:\n",
    "       - W: solar modulation parameter\n",
    "    Outputs:\n",
    "       - GCR_flux(28,4,1000) - array containing flux values in (s*sr*cm^2*MeV/n)^-1 ; [emin/emid/emax/flux]\n",
    "    '''\n",
    "    GCR_flux = np.zeros((28,4,nEbins))\n",
    "    \n",
    "    Emin = 10 # MeV\n",
    "    Emax = 1e6 # MeV\n",
    "    \n",
    "    logEmin = np.log10(Emin)\n",
    "    logEmax = np.log10(Emax)\n",
    "    logdE = (logEmax-logEmin)/nEbins\n",
    "    logE = logEmin\n",
    "    \n",
    "    for k in range(nEbins):\n",
    "        GCR_flux[:,0,k] = 10**(logE)\n",
    "        GCR_flux[:,1,k] = 10**(logE+0.5*logdE)\n",
    "        GCR_flux[:,2,k] = 10**(logE+logdE)\n",
    "        logE += logdE\n",
    "    \n",
    "    for j in range(28):\n",
    "        Z = j+1\n",
    "        for k in range(nEbins):\n",
    "            GCR_flux[j,3,k] = calc_GCR_intensity(Z,W,GCR_flux[j,1,k])\n",
    "            \n",
    "    return GCR_flux  \n",
    "\n",
    "\n",
    "def calculate_W():\n",
    "    global date_start, date_end, default_date, W_dates, W_values\n",
    "    d1 = date_start.value\n",
    "    d2 = date_end.value\n",
    "    if d1 == None: d1 = default_date\n",
    "    if d2 == None: d2 = d1\n",
    "    \n",
    "    d1_yr = toYearFraction(d1)\n",
    "    d2_yr = toYearFraction(d2)\n",
    "    \n",
    "    if d1==d2:\n",
    "        W_val = np.interp(d1_yr,W_dates,W_values)\n",
    "    else:\n",
    "        date_span = np.linspace(d1_yr,d2_yr,num=10)\n",
    "        W_span = np.interp(date_span,W_dates,W_values)\n",
    "        W_val = np.average(W_span)\n",
    "        \n",
    "    return W_val\n",
    "\n",
    "\n",
    "# read in W values\n",
    "W_dates = []\n",
    "W_values = []\n",
    "f = open('W_values.txt')\n",
    "for line in f:\n",
    "    vals = line.split()\n",
    "    W_dates.append(np.float(vals[0]))\n",
    "    W_values.append(np.float(vals[1]))\n",
    "f.close()\n",
    "\n",
    "\n",
    "# Source ion information\n",
    "all_iso_strs = ['1H','4He','7Li','9Be','11B','12C','14N','16O','19F','20Ne','23Na','24Mg','27Al','28Si','31P','32S','35Cl','40Ar','39K','40Ca','45Sc','48Ti','51V','52Cr','55Mn','56Fe','59Co','59Ni']\n",
    "all_iso_strs_TeX = [r'$^{1}_{1}$H',r'$^{4}_{2}$He',r'$^{7}_{3}$Li',r'$^{9}_{4}$Be',r'$^{11}_{5}$B',r'$^{12}_{6}$C',r'$^{14}_{7}$N',r'$^{16}_{8}$O',r'$^{19}_{9}$F',r'$^{20}_{10}$Ne',r'$^{23}_{11}$Na',r'$^{24}_{12}$Mg',r'$^{27}_{13}$Al',r'$^{28}_{14}$Si',r'$^{31}_{15}$P',r'$^{32}_{16}$S',r'$^{35}_{17}$Cl',r'$^{40}_{18}$Ar',r'$^{39}_{19}$K',r'$^{40}_{20}$Ca',r'$^{45}_{21}$Sc',r'$^{48}_{22}$Ti',r'$^{51}_{23}$V',r'$^{52}_{24}$Cr',r'$^{55}_{25}$Mn',r'$^{56}_{26}$Fe',r'$^{59}_{27}$Co',r'$^{59}_{28}$Ni']\n",
    "all_Z_strs = ['H','He','Li','Be','B','C','N','O','F','Ne','Na','Mg','Al','Si','P','S','Cl','Ar','K','Ca','Sc','Ti','V','Cr','Mn','Fe','Co','Ni']\n",
    "A_list = [1,4,7,9,11,12,14,16,19,20,23,24,27,28,31,32,35,40,39,40,45,48,51,52,55,56,59,59]\n",
    "Z_list = range(1,29)\n",
    "ZZZAAA = []\n",
    "for i in range(28):\n",
    "    ZZZAAA.append(\"%03d\" % Z_list[i] + \"%03d\" % A_list[i])\n",
    "\n",
    "    \n",
    "update_print_str = \"\"\n",
    "checkTF = False # sets wether checkbox default state is True or False\n",
    "currently_updating_fig_dims = False\n",
    "zoom_mult = 1 # default zoom level to reset to\n",
    "all_none_strings = ['Deselect All','Select All']\n",
    "setup_run = True # condition for very first running of all cells\n",
    "default_Z_on = [1,2,6,7,8,26]\n",
    "default_date = dt.date(year=2012,month=1,day=31)\n",
    "\n",
    "\n",
    "run_all_label = w.Label(value='(This button also resets everything in this code to its default state.)')\n",
    "\n",
    "run_all_cells_button = w.Button(\n",
    "    description='Initialize code',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to load all of the code cells if not already loaded.',\n",
    "    icon='play' # pencil, rotate-right, paint-brush\n",
    ")\n",
    "\n",
    "display(w.HBox([run_all_cells_button,run_all_label]))\n",
    "run_all_cells_button.on_click(on_click_run_all)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<hr>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h2>Input</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h3>GCR ion selection</h3>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67be655ea4d94891824a1e53646e69d6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(Label(value='Select GCR ion species of interest'), Button(description='Deselect All', style=ButtonStyle()), Button(description='Select All', style=ButtonStyle())))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML('<hr>'))\n",
    "display(HTML('<h2>Input</h2>'))\n",
    "display(HTML('<h3>GCR ion selection</h3>'))\n",
    "\n",
    "ion_label = w.Label(value=\"Select GCR ion species of interest\")\n",
    "ion_an = gen_all_none_buttons_v2()\n",
    "display(w.HBox([ion_label,ion_an[0],ion_an[1]]))\n",
    "ion_an[0].on_click(on_click_set_checkF)\n",
    "ion_an[1].on_click(on_click_set_checkT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "358c73f5c5134c1e9bf126e74c10bb07",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</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": [
       "VBox(children=(HBox(children=(Checkbox(value=True, description='Z=1 (H)', indent=False), Checkbox(value=True, description='Z=2 (He)', indent=False), Checkbox(value=False, description='Z=3 (Li)', indent=False), Checkbox(value=False, description='Z=4 (Be)', indent=False), Checkbox(value=False, description='Z=5 (B)', indent=False), Checkbox(value=True, description='Z=6 (C)', indent=False), Checkbox(value=True, description='Z=7 (N)', indent=False)), layout=Layout(width='130ex')), HBox(children=(Checkbox(value=True, description='Z=8 (O)', indent=False), Checkbox(value=False, description='Z=9 (F)', indent=False), Checkbox(value=False, description='Z=10 (Ne)', indent=False), Checkbox(value=False, description='Z=11 (Na)', indent=False), Checkbox(value=False, description='Z=12 (Mg)', indent=False), Checkbox(value=False, description='Z=13 (Al)', indent=False), Checkbox(value=False, description='Z=14 (Si)', indent=False)), layout=Layout(width='130ex')), HBox(children=(Checkbox(value=False, description='Z=15 (P)', indent=False), Checkbox(value=False, description='Z=16 (S)', indent=False), Checkbox(value=False, description='Z=17 (Cl)', indent=False), Checkbox(value=False, description='Z=18 (Ar)', indent=False), Checkbox(value=False, description='Z=19 (K)', indent=False), Checkbox(value=False, description='Z=20 (Ca)', indent=False), Checkbox(value=False, description='Z=21 (Sc)', indent=False)), layout=Layout(width='130ex')), HBox(children=(Checkbox(value=False, description='Z=22 (Ti)', indent=False), Checkbox(value=False, description='Z=23 (V)', indent=False), Checkbox(value=False, description='Z=24 (Cr)', indent=False), Checkbox(value=False, description='Z=25 (Mn)', indent=False), Checkbox(value=True, description='Z=26 (Fe)', indent=False), Checkbox(value=False, description='Z=27 (Co)', indent=False), Checkbox(value=False, description='Z=28 (Ni)', indent=False)), layout=Layout(width='130ex'))))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select ions of interest\n",
    "ion_anb = checkTF\n",
    "\n",
    "Z_strs= []\n",
    "\n",
    "for i in range(28):\n",
    "    Z_strs.append('Z='+str(i+1)+' ('+all_Z_strs[i]+')')\n",
    "\n",
    "ions = [w.Checkbox(description=Z_strs[i],indent=False,value=ion_anb) for i in range(len(Z_strs))]\n",
    "\n",
    "if setup_run: # set up default ions to be on\n",
    "    for i in range(28):\n",
    "        if (i+1) in default_Z_on:\n",
    "            ions[i].value = True\n",
    "\n",
    "ion_box1 = w.HBox((ions[0:7]),layout=w.Layout(width='130ex'))\n",
    "ion_box2 = w.HBox((ions[7:14]),layout=w.Layout(width='130ex'))\n",
    "ion_box3 = w.HBox((ions[14:21]),layout=w.Layout(width='130ex'))\n",
    "ion_box4 = w.HBox((ions[21:28]),layout=w.Layout(width='130ex'))\n",
    "\n",
    "display(w.VBox(([ion_box1, ion_box2, ion_box3, ion_box4])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d22084855b574ed5b6723421015ec548",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(Label(value='Select number of energy bins per spectrum'), IntText(value=100, layout=Layout(width='12%'))))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h3>Solar Modulation</h3>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9ba5d0110e4746318f141580e0e6cd6d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(DatePicker(value=None, description='Start date'), DatePicker(value=None, description='End date'), Button(description='Same as start date', style=ButtonStyle(), tooltip='Click to set end date equal to start date.'), Button(button_style='info', description='Calculate W', icon='calculator', style=ButtonStyle(), tooltip='Click to calculate W over given date(s).')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7671c457f63449c3bb15c72c61671336",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(Label(value='Select solar modulation parameter W'), FloatSlider(value=50.0, description='W', max=300.0, step=10.0), FloatText(value=0.0, layout=Layout(width='12%'), step=1.0)))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#W = 50\n",
    "#nEbins = 1000\n",
    "\n",
    "E_text = w.IntText(value=100,step=1,layout=w.Layout(width='12%'))\n",
    "E_label = w.Label(value='Select number of energy bins per spectrum')\n",
    "\n",
    "display(w.HBox([E_label,E_text]))\n",
    "\n",
    "\n",
    "\n",
    "display(HTML('<h3>Solar Modulation</h3>'))\n",
    "\n",
    "date_start = w.DatePicker(\n",
    "    description='Start date',\n",
    "    #value=default_date,\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "date_end = w.DatePicker(\n",
    "    description='End date',\n",
    "    disabled=False\n",
    ")\n",
    "\n",
    "date_same_button = w.Button(\n",
    "    description='Same as start date',\n",
    "    disabled=False,\n",
    "    button_style='', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to set end date equal to start date.',\n",
    "    icon='' # pencil, rotate-right, paint-brush\n",
    ")\n",
    "\n",
    "calc_W_button = w.Button(\n",
    "    description='Calculate W',\n",
    "    disabled=False,\n",
    "    button_style='info', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to calculate W over given date(s).',\n",
    "    icon='calculator' # pencil, rotate-right, paint-brush\n",
    ")\n",
    "\n",
    "\n",
    "display(w.HBox([date_start,date_end,date_same_button,calc_W_button]))\n",
    "date_same_button.on_click(on_click_sync_dates)\n",
    "calc_W_button.on_click(on_click_calc_W)\n",
    "\n",
    "W_slider = w.FloatSlider(\n",
    "    description='W',\n",
    "    min=0,\n",
    "    max=300,\n",
    "    step=10.0,\n",
    "    value = 50,\n",
    ")\n",
    "\n",
    "W_text = w.FloatText(step=1.0,layout=w.Layout(width='12%'))\n",
    "\n",
    "W_label = (w.Label(value=\"Select solar modulation parameter W\"))\n",
    "\n",
    "display(w.HBox([W_label,W_slider,W_text]))\n",
    "\n",
    "w_link = w.jslink((W_slider, 'value'), (W_text, 'value'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"950\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e7e1e6b855774abc88ac7cb66dbed36e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(Button(button_style='success', description='Save plot (PDF)', icon='save', style=ButtonStyle(), tooltip='Save plot as PDF in local images/ folder'), Button(button_style='success', description='Save plot (PNG)', icon='save', style=ButtonStyle(), tooltip='Save plot as PNG in local images/ folder'), Button(button_style='success', description='Save plot (SVG)', icon='save', style=ButtonStyle(), tooltip='Save plot as SVG in local images/ folder')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c_ISSN = '#41b6c4'\n",
    "c_Oulu = '#2c7fb8'\n",
    "c_ACE  = '#253494'\n",
    "\n",
    "xlim_vals = [1748,2020]\n",
    "ylim_vals = [0,300]\n",
    "\n",
    "Wfig, Wax = plt.subplots(nrows=1, ncols=1);\n",
    "Wfig.set_size_inches(9.5,3)\n",
    "Wax.plot(W_dates[:2578],W_values[:2578],c=c_ISSN,label=r'ISSN')\n",
    "Wax.plot(W_dates[2578:2977],W_values[2578:2977],c=c_Oulu,label=r'W$_{Oulu}$')\n",
    "Wax.plot(W_dates[2977:3175],W_values[2977:3175],c=c_ACE,label=r'W$_{ACE}$')\n",
    "Wax.plot(W_dates[3175:-1],W_values[3175:-1],c=c_Oulu)\n",
    "\n",
    "# W horizontal line\n",
    "line, = Wax.plot([W_dates[0],W_dates[-1]],[50,50],c='#F67521',linewidth=0.5) \n",
    "\n",
    "# date vertical line(s)\n",
    "d1_yr = toYearFraction(date_start.value)\n",
    "d2_yr = toYearFraction(date_end.value)\n",
    "d1_line, = Wax.plot([d1_yr,d1_yr],ylim_vals,c='#F67521',linewidth=0.5)\n",
    "d2_line, = Wax.plot([d2_yr,d2_yr],ylim_vals,c='#F67521',linewidth=0.5)\n",
    "\n",
    "Wax.set_xlabel('Year')\n",
    "Wax.set_ylabel('W')\n",
    "title_text = 'W values 1750-2019 (from varied sources)'\n",
    "window_title2 = 'W_values'\n",
    "plt.legend(loc='best',ncol=3)\n",
    "plt.title(title_text)\n",
    "plt.grid(b=True, which='major', linestyle='-', alpha=0.25)\n",
    "plt.grid(b=True, which='minor', linestyle='-', alpha=0.10)\n",
    "plt.xlim(xlim_vals)\n",
    "plt.ylim(ylim_vals)\n",
    "plt.tight_layout()\n",
    "\n",
    "out = w.Output()\n",
    "\n",
    "def myplot(n,d1,d2):\n",
    "    with out:\n",
    "        line.set_ydata(n)\n",
    "        d1_line.set_xdata(toYearFraction(d1))\n",
    "        d2_line.set_xdata(toYearFraction(d2))\n",
    "        plt.tight_layout()\n",
    "        display(Wfig)\n",
    "        clear_output(wait=True)\n",
    "\n",
    "\n",
    "def on_value_change(change):\n",
    "    myplot(n=W_slider.value,d1=date_start.value,d2=date_end.value)\n",
    "\n",
    "W_slider.observe(on_value_change)\n",
    "#display(W_slider)\n",
    "\n",
    "\n",
    "save_plot_button_pdf2 = w.Button(\n",
    "    description='Save plot (PDF)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as PDF in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "save_plot_button_png2 = w.Button(\n",
    "    description='Save plot (PNG)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as PNG in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "save_plot_button_svg2 = w.Button(\n",
    "    description='Save plot (SVG)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as SVG in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "display(w.HBox([save_plot_button_pdf2,save_plot_button_png2,save_plot_button_svg2]))\n",
    "\n",
    "save_plot_button_pdf2.on_click(on_click_save_plot_pdf2)\n",
    "save_plot_button_png2.on_click(on_click_save_plot_png2)\n",
    "save_plot_button_svg2.on_click(on_click_save_plot_svg2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<hr>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<h3>Calculate spectra with updated parameters</h3>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6552d34ce3ad4d9c806a12125fc34b97",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Button</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": [
       "Button(button_style='success', description='Update values', icon='refresh', style=ButtonStyle(), tooltip='Click to redraw the plot below with updated options from above.')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<hr>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(HTML('<hr>'))\n",
    "display(HTML('<h3>Calculate spectra with updated parameters</h3>'))\n",
    "\n",
    "make_plot_button = w.Button(\n",
    "    description='Update values',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to redraw the plot below with updated options from above.',\n",
    "    icon='refresh' # pencil, rotate-right, paint-brush, refresh\n",
    ")\n",
    "\n",
    "display(make_plot_button)\n",
    "#display(make_plot_button)\n",
    "make_plot_button.on_click(on_click_calcs)\n",
    "\n",
    "display(HTML('<hr>'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Output</h2>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Collect and calculate values based on user input\n",
    "display(HTML('<h2>Output</h2>'))\n",
    "\n",
    "# Get number of energy bins\n",
    "nEbins = E_text.value\n",
    "\n",
    "# Determine ions of interest\n",
    "zi_list = []\n",
    "for i in range(28):\n",
    "    if ions[i].value: zi_list.append(i)\n",
    "\n",
    "# Get W\n",
    "W = (W_slider.value)\n",
    "W_text = ('{:g}'.format(W)).replace('.','p')\n",
    "\n",
    "# Calculate GCR flux\n",
    "GCR_flux = assemble_GCR_flux(W,nEbins)\n",
    "\n",
    "integral_flux = []\n",
    "for i in zi_list:\n",
    "    integral_flux.append(np.sum(GCR_flux[i,3,:]*(GCR_flux[i,2,:]-GCR_flux[i,0,:])))\n",
    "integral_flux = np.array(integral_flux)\n",
    "\n",
    "\n",
    "setup_run = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "Integral GCR ion fluxes for W = 50"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table><tr><td>Z</td><td>A$^*$</td><td>ID</td><td>$\\phi$ [#/(s$\\cdot$sr$\\cdot$cm$^2$)]</td><td>$\\phi$ [#/(d$\\cdot$sr$\\cdot$cm$^2$)]</td><td>$\\phi$ [#/(yr$\\cdot$sr$\\cdot$cm$^2$)]</td><td>Percent (%)</td></tr><tr><td>1</td><td>1</td><td>H</td><td>2.58577E-01</td><td>2.23411E+04</td><td>8.16008E+06</td><td>8.9952E+01</td></tr><tr><td>2</td><td>4</td><td>He</td><td>2.71427E-02</td><td>2.34513E+03</td><td>8.56559E+05</td><td>9.4422E+00</td></tr><tr><td>6</td><td>12</td><td>C</td><td>7.56739E-04</td><td>6.53822E+01</td><td>2.38809E+04</td><td>2.6325E-01</td></tr><tr><td>7</td><td>14</td><td>N</td><td>2.00612E-04</td><td>1.73329E+01</td><td>6.33084E+03</td><td>6.9788E-02</td></tr><tr><td>8</td><td>16</td><td>O</td><td>7.04545E-04</td><td>6.08727E+01</td><td>2.22337E+04</td><td>2.4509E-01</td></tr><tr><td>26</td><td>56</td><td>Fe</td><td>7.91415E-05</td><td>6.83782E+00</td><td>2.49752E+03</td><td>2.7531E-02</td></tr><tr><td></td><td></td><td>All</td><td>2.87461E-01</td><td>2.48366E+04</td><td>9.07158E+06</td><td>1.0000E+02</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "$^*$A = average atomic mass rounded to nearest integer"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Table\n",
    "\n",
    "# Useful meta information\n",
    "#   Total particle flux (by ion and total)\n",
    "\n",
    "s_per_d = 60*60*24\n",
    "s_per_y = 365.25*s_per_d\n",
    "\n",
    "table = [['Z',r'A$^*$','ID',r'$\\phi$ [#/(s$\\cdot$sr$\\cdot$cm$^2$)]',r'$\\phi$ [#/(d$\\cdot$sr$\\cdot$cm$^2$)]',r'$\\phi$ [#/(yr$\\cdot$sr$\\cdot$cm$^2$)]','Percent (%)']]\n",
    "for i in range(len(zi_list)):\n",
    "    zi = zi_list[i]\n",
    "    table.append([str(zi+1),\n",
    "                  str(A_list[zi]),\n",
    "                  all_Z_strs[zi],\n",
    "                  '{:.5E}'.format(integral_flux[i]),\n",
    "                  '{:.5E}'.format(integral_flux[i]*s_per_d),\n",
    "                  '{:.5E}'.format(integral_flux[i]*s_per_y),\n",
    "                  '{:.4E}'.format(100*integral_flux[i]/np.sum(integral_flux))])\n",
    "    \n",
    "table.append(['','','All',\n",
    "              '{:.5E}'.format(np.sum(integral_flux)),\n",
    "              '{:.5E}'.format(np.sum(integral_flux)*s_per_d),\n",
    "              '{:.5E}'.format(np.sum(integral_flux)*s_per_y),\n",
    "              '{:.4E}'.format(100*np.sum(integral_flux)/np.sum(integral_flux))])\n",
    "    \n",
    "display(HTML('Integral GCR ion fluxes for W = {:g}'.format(W))) # $W={{{:}}}$'.format(str(W)))) # fancy W=XX text\n",
    "\n",
    "display(HTML(\n",
    "   '<table><tr>{}</tr></table>'.format(\n",
    "       '</tr><tr>'.join(\n",
    "           '<td>{}</td>'.format('</td><td>'.join(str(_) for _ in row)) for row in table)\n",
    "       )\n",
    "))\n",
    "\n",
    "display(HTML(r'$^*$A = average atomic mass rounded to nearest integer'))\n",
    "\n",
    "\n",
    "#display(HTML(tabulate.tabulate(table, tablefmt='html')))\n",
    "#display(Math(all_iso_strs_TeX[7].replace('$','')))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "17438d275c744779b32767ab4ce5bfc7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Label</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": [
       "Label(value='For convenience, the GCR spectra can be viewed and saved in the tabs below.')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e46f7696641a4b3dbe692117af1f8c41",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Tab</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": [
       "Tab(children=(Accordion(children=(VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">Flux F in units of [#/(s*sr*cm^2*MeV/n)]<br>Emin [MeV/n]\\tEmid [MeV/n]\\tEmax [MeV/n]\\tF(Z=1/H)\\tF(Z=2/He)\\tF(Z=6/C)\\tF(Z=7/N)\\tF(Z=8/O)\\tF(Z=26/Fe)<br>1.00000000E+01\\t1.05925373E+01\\t1.12201845E+01\\t3.11230416E-06\\t1.79107161E-06\\t4.40374042E-08\\t6.01217275E-09\\t3.95803507E-08\\t5.32311078E-09<br>1.12201845E+01\\t1.18850223E+01\\t1.25892541E+01\\t3.78742143E-06\\t2.10420044E-06\\t5.19422577E-08\\t7.27696652E-09\\t4.66625657E-08\\t6.23071859E-09<br>1.25892541E+01\\t1.33352143E+01\\t1.41253754E+01\\t4.59188374E-06\\t2.46022152E-06\\t6.09719211E-08\\t8.76487180E-09\\t5.47485136E-08\\t7.25777328E-09<br>1.41253754E+01\\t1.49623566E+01\\t1.58489319E+01\\t5.54583448E-06\\t2.86243295E-06\\t7.12212475E-08\\t1.05044602E-08\\t6.39222511E-08\\t8.41253311E-09<br>1.58489319E+01\\t1.67880402E+01\\t1.77827941E+01\\t6.67135214E-06\\t3.31384616E-06\\t8.27792387E-08\\t1.25254107E-08\\t7.42625648E-08\\t9.70230463E-09<br>1.77827941E+01\\t1.88364909E+01\\t1.99526231E+01\\t7.99232213E-06\\t3.81705061E-06\\t9.57254993E-08\\t1.48579038E-08\\t8.58398391E-08\\t1.11330802E-08<br>1.99526231E+01\\t2.11348904E+01\\t2.23872114E+01\\t9.53420450E-06\\t4.37406543E-06\\t1.10126276E-07\\t1.75318482E-08\\t9.87125653E-08\\t1.27091489E-08<br>2.23872114E+01\\t2.37137371E+01\\t2.51188643E+01\\t1.13236770E-05\\t4.98618082E-06\\t1.26030144E-07\\t2.05759277E-08\\t1.12923548E-07\\t1.44326902E-08<br>2.51188643E+01\\t2.66072506E+01\\t2.81838293E+01\\t1.33881336E-05\\t5.65379308E-06\\t1.43463436E-07\\t2.40164666E-08\\t1.28495892E-07\\t1.63033604E-08<br>2.81838293E+01\\t2.98538262E+01\\t3.16227766E+01\\t1.57550197E-05\\t6.37623820E-06\\t1.62425523E-07\\t2.78761129E-08\\t1.45428872E-07\\t1.83178867E-08<br>3.16227766E+01\\t3.34965439E+01\\t3.54813389E+01\\t1.84509886E-05\\t7.15162947E-06\\t1.82884102E-07\\t3.21723543E-08\\t1.63693810E-07\\t2.04696818E-08<br>3.54813389E+01\\t3.75837404E+01\\t3.98107171E+01\\t2.15008690E-05\\t7.97670592E-06\\t2.04770651E-07\\t3.69158875E-08\\t1.83230124E-07\\t2.27484962E-08<br>3.98107171E+01\\t4.21696503E+01\\t4.46683592E+01\\t2.49264407E-05\\t8.84669860E-06\\t2.27976263E-07\\t4.21088766E-08\\t2.03941696E-07\\t2.51401268E-08<br>4.46683592E+01\\t4.73151259E+01\\t5.01187234E+01\\t2.87450241E-05\\t9.75522272E-06\\t2.52348060E-07\\t4.77431500E-08\\t2.25693768E-07\\t2.76261984E-08<br>5.01187234E+01\\t5.30884444E+01\\t5.62341325E+01\\t3.29679044E-05\\t1.06942038E-05\\t2.77686436E-07\\t5.37984018E-08\\t2.48310561E-07\\t3.01840376E-08<br>5.62341325E+01\\t5.95662144E+01\\t6.30957344E+01\\t3.75986215E-05\\t1.16538464E-05\\t3.03743375E-07\\t6.02404781E-08\\t2.71573832E-07\\t3.27866584E-08<br>6.30957344E+01\\t6.68343918E+01\\t7.07945784E+01\\t4.26311793E-05\\t1.26226535E-05\\t3.30222090E-07\\t6.70198486E-08\\t2.95222580E-07\\t3.54028764E-08<br>7.07945784E+01\\t7.49894209E+01\\t7.94328235E+01\\t4.80482424E-05\\t1.35875054E-05\\t3.56778257E-07\\t7.40703803E-08\\t3.18954128E-07\\t3.79975695E-08<br>7.94328235E+01\\t8.41395142E+01\\t8.91250938E+01\\t5.38194108E-05\\t1.45338044E-05\\t3.83023063E-07\\t8.13085418E-08\\t3.42426781E-07\\t4.05320995E-08<br>8.91250938E+01\\t9.44060876E+01\\t1.00000000E+02\\t5.98996836E-05\\t1.54456923E-05\\t4.08528302E-07\\t8.86331831E-08\\t3.65264231E-07\\t4.29649054E-08<br>1.00000000E+02\\t1.05925373E+02\\t1.12201845E+02\\t6.62282401E-05\\t1.63063447E-05\\t4.32833680E-07\\t9.59260368E-08\\t3.87061876E-07\\t4.52522791E-08<br>1.12201845E+02\\t1.18850223E+02\\t1.25892541E+02\\t7.27276826E-05\\t1.70983441E-05\\t4.55456447E-07\\t1.03053083E-07\\t4.07395124E-07\\t4.73493220E-08<br>1.25892541E+02\\t1.33352143E+02\\t1.41253754E+02\\t7.93038921E-05\\t1.78041307E-05\\t4.75903361E-07\\t1.09866907E-07\\t4.25829710E-07\\t4.92110807E-08<br>1.41253754E+02\\t1.49623566E+02\\t1.58489319E+02\\t8.58466508E-05\\t1.84065244E-05\\t4.93684898E-07\\t1.16210135E-07\\t4.41933939E-07\\t5.07938441E-08<br>1.58489319E+02\\t1.67880402E+02\\t1.77827941E+02\\t9.22311664E-05\\t1.88893082E-05\\t5.08331446E-07\\t1.21920002E-07\\t4.55292643E-07\\t5.20565777E-08<br>1.77827941E+02\\t1.88364909E+02\\t1.99526231E+02\\t9.83206103E-05\\t1.92378551E-05\\t5.19411048E-07\\t1.26833996E-07\\t4.65522494E-07\\t5.29624538E-08<br>1.99526231E+02\\t2.11348904E+02\\t2.23872114E+02\\t1.03969728E-04\\t1.94397757E-05\\t5.26548061E-07\\t1.30796471E-07\\t4.72288142E-07\\t5.34804217E-08<br>2.23872114E+02\\t2.37137371E+02\\t2.51188643E+02\\t1.09029515E-04\\t1.94855546E-05\\t5.29441885E-07\\t1.33665972E-07\\t4.75318452E-07\\t5.35867484E-08<br>2.51188643E+02\\t2.66072506E+02\\t2.81838293E+02\\t1.13352871E-04\\t1.93691390E-05\\t5.27884689E-07\\t1.35322904E-07\\t4.74421977E-07\\t5.32664412E-08<br>2.81838293E+02\\t2.98538262E+02\\t3.16227766E+02\\t1.16801027E-04\\t1.90884390E-05\\t5.21776932E-07\\t1.35677075E-07\\t4.69500605E-07\\t5.25144566E-08<br>3.16227766E+02\\t3.34965439E+02\\t3.54813389E+02\\t1.19250451E-04\\t1.86456922E-05\\t5.11139357E-07\\t1.34674514E-07\\t4.60560292E-07\\t5.13365911E-08<br>3.54813389E+02\\t3.75837404E+02\\t3.98107171E+02\\t1.20599824E-04\\t1.80476540E-05\\t4.96120169E-07\\t1.32302944E-07\\t4.47717759E-07\\t4.97499543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fit your usage.<br>c <br>c Source<br> SDEF PAR=001001 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    1.00000000E+01 0.0 <br>    1.25892541E+01 5.18524345E-06<br>    1.41253754E+01 7.05369055E-06<br>    1.58489319E+01 9.55855894E-06<br>    1.77827941E+01 1.29014756E-05<br>    1.99526231E+01 1.73419727E-05<br>    2.23872114E+01 2.32118621E-05<br>    2.51188643E+01 3.09323554E-05<br>    2.81838293E+01 4.10341609E-05<br>    3.16227766E+01 5.41806823E-05<br>    3.54813389E+01 7.11942894E-05<br>    3.98107171E+01 9.30853922E-05<br>    4.46683592E+01 1.21083729E-04<br>    5.01187234E+01 1.56670849E-04<br>    5.62341325E+01 2.01612224E-04<br>    6.30957344E+01 2.57986774E-04<br>    7.07945784E+01 3.28210799E-04<br>    7.94328235E+01 4.15052491E-04<br>    8.91250938E+01 5.21632279E-04<br>    1.00000000E+02 6.51403439E-04<br>    1.12201845E+02 8.08106749E-04<br>    1.25892541E+02 9.95692574E-04<br>    1.41253754E+02 1.21820400E-03<br>    1.58489319E+02 1.47961551E-03<br>    1.77827941E+02 1.78362364E-03<br>    1.99526231E+02 2.13338916E-03<br>    2.23872114E+02 2.53123476E-03<br>    2.51188643E+02 2.97830794E-03<br>    2.81838293E+02 3.47422581E-03<br>    3.16227766E+02 4.01672574E-03<br>    3.54813389E+02 4.60135299E-03<br>    3.98107171E+02 5.22122241E-03<br>    4.46683592E+02 5.86689379E-03<br>    5.01187234E+02 6.52639943E-03<br>    5.62341325E+02 7.18545551E-03<br>    6.30957344E+02 7.82787619E-03<br>    7.07945784E+02 8.43619081E-03<br>    7.94328235E+02 8.99244211E-03<br>    8.91250938E+02 9.47911915E-03<br>    1.00000000E+03 9.88015658E-03<br>    1.12201845E+03 1.01819160E-02<br>    1.25892541E+03 1.03740579E-02<br>    1.41253754E+03 1.04502186E-02<br>    1.58489319E+03 1.04084215E-02<br>    1.77827941E+03 1.02511808E-02<br>    1.99526231E+03 9.98528870E-03<br>    2.23872114E+03 9.62130909E-03<br>    2.51188643E+03 9.17283609E-03<br>    2.81838293E+03 8.65559343E-03<br>    3.16227766E+03 8.08646451E-03<br>    3.54813389E+03 7.48254097E-03<br>    3.98107171E+03 6.86026592E-03<br>    4.46683592E+03 6.23472903E-03<br>    5.01187234E+03 5.61914712E-03<br>    5.62341325E+03 5.02454062E-03<br>    6.30957344E+03 4.45959614E-03<br>    7.07945784E+03 3.93068987E-03<br>    7.94328235E+03 3.44203781E-03<br>    8.91250938E+03 2.99593487E-03<br>    1.00000000E+04 2.59304644E-03<br>    1.12201845E+04 2.23272069E-03<br>    1.25892541E+04 1.91329598E-03<br>    1.41253754E+04 1.63238540E-03<br>    1.58489319E+04 1.38712677E-03<br>    1.77827941E+04 1.17439243E-03<br>    1.99526231E+04 9.90957656E-04<br>    2.23872114E+04 8.33629775E-04<br>    2.51188643E+04 6.99341973E-04<br>    2.81838293E+04 5.85217011E-04<br>    3.16227766E+04 4.88606257E-04<br>    3.54813389E+04 4.07109329E-04<br>    3.98107171E+04 3.38579092E-04<br>    4.46683592E+04 2.81116114E-04<br>    5.01187234E+04 2.33055954E-04<br>    5.62341325E+04 1.92951969E-04<br>    6.30957344E+04 1.59555699E-04<br>    7.07945784E+04 1.31796353E-04<br>    7.94328235E+04 1.08760476E-04<br>    8.91250938E+04 8.96725142E-05<br>    1.00000000E+05 7.38767330E-05<br>    1.12201845E+05 6.08207398E-05<br>    1.25892541E+05 5.00407020E-05<br>    1.41253754E+05 4.11482627E-05<br>    1.58489319E+05 3.38190821E-05<br>    1.77827941E+05 2.77828924E-05<br>    1.99526231E+05 2.28149305E-05<br>    2.23872114E+05 1.87286060E-05<br>    2.51188643E+05 1.53692609E-05<br>    2.81838293E+05 1.26088827E-05<br>    3.16227766E+05 1.03416446E-05<br>    3.54813389E+05 8.48015688E-06<br>    3.98107171E+05 6.95232485E-06<br>    4.46683592E+05 5.69872383E-06<br>    5.01187234E+05 4.67041019E-06<br>    5.62341325E+05 3.82710053E-06<br>    6.30957344E+05 3.13565955E-06<br>    7.07945784E+05 2.56884654E-06<br>    7.94328235E+05 2.10427755E-06<br>    8.91250938E+05 1.72356750E-06<br>    1.00000000E+06 1.41162151E-06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-1-H_MCNP) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">c Notes:<br>c   The listed energy bins should be ready to use for your application.<br>c   This source term assumes a large spherical shell geometry for GCRs<br>c     isotropically impingent on a planet\\'s atmosphere.<br>c   Change the geometric and angular portions of the source card to fit your usage.<br>c <br>c Source<br> SDEF PAR=002004 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    4.00000000E+01 0.0 <br>    5.03570165E+01 1.15231872E-05<br>    5.65015018E+01 1.51167950E-05<br>    6.33957277E+01 1.97342594E-05<br>    7.11311764E+01 2.56340870E-05<br>    7.98104926E+01 3.31293892E-05<br>    8.95488455E+01 4.25961930E-05<br>    1.00475457E+02 5.44820617E-05<br>    1.12735317E+02 6.93147116E-05<br>    1.26491106E+02 8.77101883E-05<br>    1.41925356E+02 1.10380032E-04<br>    1.59242868E+02 1.38136705E-04<br>    1.78673437E+02 1.71896384E-04<br>    2.00474893E+02 2.12678065E-04<br>    2.24936530E+02 2.61597727E-04<br>    2.52382938E+02 3.19856219E-04<br>    2.83178314E+02 3.88719360E-04<br>    3.17731294E+02 4.69488805E-04<br>    3.56500375E+02 5.63462247E-04<br>    4.00000000E+02 6.71881820E-04<br>    4.48807382E+02 7.95869990E-04<br>    5.03570165E+02 9.36352910E-04<br>    5.65015018E+02 1.09397220E-03<br>    6.33957277E+02 1.26898738E-03<br>    7.11311764E+02 1.46117274E-03<br>    7.98104926E+02 1.66971427E-03<br>    8.95488455E+02 1.89311397E-03<br>    1.00475457E+03 2.12911089E-03<br>    1.12735317E+03 2.37462933E-03<br>    1.26491106E+03 2.62576542E-03<br>    1.41925356E+03 2.87782262E-03<br>    1.59242868E+03 3.12540475E-03<br>    1.78673437E+03 3.36257159E-03<br>    2.00474893E+03 3.58305656E-03<br>    2.24936530E+03 3.78053957E-03<br>    2.52382938E+03 3.94896071E-03<br>    2.83178314E+03 4.08285369E-03<br>    3.17731294E+03 4.17767233E-03<br>    3.56500375E+03 4.23008067E-03<br>    4.00000000E+03 4.23817838E-03<br>    4.48807382E+03 4.20163740E-03<br>    5.03570165E+03 4.12173425E-03<br>    5.65015018E+03 4.00127326E-03<br>    6.33957277E+03 3.84440752E-03<br>    7.11311764E+03 3.65637525E-03<br>    7.98104926E+03 3.44317775E-03<br>    8.95488455E+03 3.21122963E-03<br>    1.00475457E+04 2.96701249E-03<br>    1.12735317E+04 2.71675999E-03<br>    1.26491106E+04 2.46619571E-03<br>    1.41925356E+04 2.22033729E-03<br>    1.59242868E+04 1.98337189E-03<br>    1.78673437E+04 1.75860052E-03<br>    2.00474893E+04 1.54844293E-03<br>    2.24936530E+04 1.35449108E-03<br>    2.52382938E+04 1.17759738E-03<br>    2.83178314E+04 1.01798424E-03<br>    3.17731294E+04 8.75362757E-04<br>    3.56500375E+04 7.49050736E-04<br>    4.00000000E+04 6.38082730E-04<br>    4.48807382E+04 5.41307438E-04<br>    5.03570165E+04 4.57469932E-04<br>    5.65015018E+04 3.85278028E-04<br>    6.33957277E+04 3.23453380E-04<br>    7.11311764E+04 2.70768772E-04<br>    7.98104926E+04 2.26073515E-04<br>    8.95488455E+04 1.88309037E-04<br>    1.00475457E+05 1.56516733E-04<br>    1.12735317E+05 1.29839934E-04<br>    1.26491106E+05 1.07521636E-04<br>    1.41925356E+05 8.88993381E-05<br>    1.59242868E+05 7.33980597E-05<br>    1.78673437E+05 6.05223927E-05<br>    2.00474893E+05 4.98481838E-05<br>    2.24936530E+05 4.10142975E-05<br>    2.52382938E+05 3.37147499E-05<br>    2.83178314E+05 2.76913981E-05<br>    3.17731294E+05 2.27272841E-05<br>    3.56500375E+05 1.86406743E-05<br>    4.00000000E+05 1.52797914E-05<br>    4.48807382E+05 1.25182087E-05<br>    5.03570165E+05 1.02508609E-05<br>    5.65015018E+05 8.39061521E-06<br>    6.33957277E+05 6.86534279E-06<br>    7.11311764E+05 5.61543241E-06<br>    7.98104926E+05 4.59168929E-06<br>    8.95488455E+05 3.75356716E-06<br>    1.00475457E+06 3.06768603E-06<br>    1.12735317E+06 2.50659358E-06<br>    1.26491106E+06 2.04773291E-06<br>    1.41925356E+06 1.67258452E-06<br>    1.59242868E+06 1.36595459E-06<br>    1.78673437E+06 1.11538565E-06<br>    2.00474893E+06 9.10669651E-07<br>    2.24936530E+06 7.43445984E-07<br>    2.52382938E+06 6.06870228E-07<br>    2.83178314E+06 4.95341437E-07<br>    3.17731294E+06 4.04277874E-07<br>    3.56500375E+06 3.29932731E-07<br>    4.00000000E+06 2.69242853E-07<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-2-He_MCNP) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">c Notes:<br>c   The listed energy bins should be ready to use for your application.<br>c   This source term assumes a large spherical shell geometry for GCRs<br>c     isotropically impingent on a planet\\'s atmosphere.<br>c   Change the geometric and angular portions of the source card to fit your usage.<br>c <br>c Source<br> SDEF PAR=006012 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    1.20000000E+02 0.0 <br>    1.51071049E+02 8.53350776E-07<br>    1.69504505E+02 1.12392322E-06<br>    1.90187183E+02 1.47304611E-06<br>    2.13393529E+02 1.92100366E-06<br>    2.39431478E+02 2.49249563E-06<br>    2.68646537E+02 3.21734562E-06<br>    3.01426372E+02 4.13124734E-06<br>    3.38205952E+02 5.27652491E-06<br>    3.79473319E+02 6.70287375E-06<br>    4.25776067E+02 8.46803644E-06<br>    4.77728605E+02 1.06383549E-05<br>    5.36020311E+02 1.32891253E-05<br>    6.01424680E+02 1.65046658E-05<br>    6.74809590E+02 2.03779941E-05<br>    7.57148813E+02 2.50099935E-05<br>    8.49534941E+02 3.05079403E-05<br>    9.53193882E+02 3.69832561E-05<br>    1.06950113E+03 4.45483569E-05<br>    1.20000000E+03 5.33124835E-05<br>    1.34642215E+03 6.33764360E-05<br>    1.51071049E+03 7.48261877E-05<br>    1.69504505E+03 8.77254363E-05<br>    1.90187183E+03 1.02107257E-04<br>    2.13393529E+03 1.17965155E-04<br>    2.39431478E+03 1.35243982E-04<br>    2.68646537E+03 1.53831326E-04<br>    3.01426372E+03 1.73550177E-04<br>    3.38205952E+03 1.94153771E-04<br>    3.79473319E+03 2.15323604E-04<br>    4.25776067E+03 2.36671568E-04<br>    4.77728605E+03 2.57747017E-04<br>    5.36020311E+03 2.78049261E-04<br>    6.01424680E+03 2.97045532E-04<br>    6.74809590E+03 3.14193914E-04<br>    7.57148813E+03 3.28970059E-04<br>    8.49534941E+03 3.40895917E-04<br>    9.53193882E+03 3.49568198E-04<br>    1.06950113E+04 3.54684010E-04<br>    1.20000000E+04 3.56061163E-04<br>    1.34642215E+04 3.53651005E-04<br>    1.51071049E+04 3.47542334E-04<br>    1.69504505E+04 3.37955894E-04<br>    1.90187183E+04 3.25229934E-04<br>    2.13393529E+04 3.09798310E-04<br>    2.39431478E+04 2.92163315E-04<br>    2.68646537E+04 2.72865891E-04<br>    3.01426372E+04 2.52455908E-04<br>    3.38205952E+04 2.31464937E-04<br>    3.79473319E+04 2.10383422E-04<br>    4.25776067E+04 1.89643448E-04<br>    4.77728605E+04 1.69607578E-04<br>    5.36020311E+04 1.50563605E-04<br>    6.01424680E+04 1.32724534E-04<br>    6.74809590E+04 1.16232771E-04<br>    7.57148813E+04 1.01167372E-04<br>    8.49534941E+04 8.75531884E-05<br>    9.53193882E+04 7.53708528E-05<br>    1.06950113E+05 6.45667829E-05<br>    1.20000000E+05 5.50625476E-05<br>    1.34642215E+05 4.67631929E-05<br>    1.51071049E+05 3.95643009E-05<br>    1.69504505E+05 3.33577122E-05<br>    1.90187183E+05 2.80359548E-05<br>    2.13393529E+05 2.34954973E-05<br>    2.39431478E+05 1.96389861E-05<br>    2.68646537E+05 1.63766412E-05<br>    3.01426372E+05 1.36269848E-05<br>    3.38205952E+05 1.13170608E-05<br>    3.79473319E+05 9.38228526E-06<br>    4.25776067E+05 7.76604144E-06<br>    4.77728605E+05 6.41911462E-06<br>    5.36020311E+05 5.29903676E-06<br>    6.01424680E+05 4.36939533E-06<br>    6.74809590E+05 3.59914416E-06<br>    7.57148813E+05 2.96194249E-06<br>    8.49534941E+05 2.43553834E-06<br>    9.53193882E+05 2.00120543E-06<br>    1.06950113E+06 1.64323766E-06<br>    1.20000000E+06 1.34850123E-06<br>    1.34642215E+06 1.10604235E-06<br>    1.51071049E+06 9.06746728E-07<br>    1.69504505E+06 7.43046425E-07<br>    1.90187183E+06 6.08669050E-07<br>    2.13393529E+06 4.98424487E-07<br>    2.39431478E+06 4.08024394E-07<br>    2.68646537E+06 3.33930094E-07<br>    3.01426372E+06 2.73224883E-07<br>    3.38205952E+06 2.23507164E-07<br>    3.79473319E+06 1.82801271E-07<br>    4.25776067E+06 1.49483248E-07<br>    4.77728605E+06 1.22219194E-07<br>    5.36020311E+06 9.99141620E-08<br>    6.01424680E+06 8.16698631E-08<br>    6.74809590E+06 6.67497219E-08<br>    7.57148813E+06 5.45500369E-08<br>    8.49534941E+06 4.45762100E-08<br>    9.53193882E+06 3.64231747E-08<br>    1.06950113E+07 2.97592951E-08<br>    1.20000000E+07 2.43131316E-08<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-6-C_MCNP) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">c Notes:<br>c   The listed energy bins should be ready to use for your application.<br>c   This source term assumes a large spherical shell geometry for GCRs<br>c     isotropically impingent on a planet\\'s atmosphere.<br>c   Change the geometric and angular portions of the source card to fit your usage.<br>c <br>c Source<br> SDEF PAR=007014 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    1.40000000E+02 0.0 <br>    1.76249558E+02 1.39477429E-07<br>    1.97755256E+02 1.88494691E-07<br>    2.21885047E+02 2.53470427E-07<br>    2.48959117E+02 3.39113852E-07<br>    2.79336724E+02 4.51347559E-07<br>    3.13420959E+02 5.97559638E-07<br>    3.51664100E+02 7.86888105E-07<br>    3.94573610E+02 1.03053481E-06<br>    4.42718872E+02 1.34210276E-06<br>    4.96738745E+02 1.73794648E-06<br>    5.57350039E+02 2.23751971E-06<br>    6.25357029E+02 2.86369796E-06<br>    7.01662127E+02 3.64304575E-06<br>    7.87277855E+02 4.60598935E-06<br>    8.83340282E+02 5.78684653E-06<br>    9.91124098E+02 7.22365502E-06<br>    1.11205953E+03 8.95773333E-06<br>    1.24775131E+03 1.10329012E-05<br>    1.40000000E+03 1.34942857E-05<br>    1.57082584E+03 1.63866454E-05<br>    1.76249558E+03 1.97521577E-05<br>    1.97755256E+03 2.36276458E-05<br>    2.21885047E+03 2.80412624E-05<br>    2.48959117E+03 3.30087072E-05<br>    2.79336724E+03 3.85291324E-05<br>    3.13420959E+03 4.45809770E-05<br>    3.51664100E+03 5.11180660E-05<br>    3.94573610E+03 5.80663949E-05<br>    4.42718872E+03 6.53220831E-05<br>    4.96738745E+03 7.27510007E-05<br>    5.57350039E+03 8.01905260E-05<br>    6.25357029E+03 8.74537722E-05<br>    7.01662127E+03 9.43364148E-05<br>    7.87277855E+03 1.00625971E-04<br>    8.83340282E+03 1.06113063E-04<br>    9.91124098E+03 1.10603852E-04<br>    1.11205953E+04 1.13932601E-04<br>    1.24775131E+04 1.15973108E-04<br>    1.40000000E+04 1.16647821E-04<br>    1.57082584E+04 1.15933592E-04<br>    1.76249558E+04 1.13863383E-04<br>    1.97755256E+04 1.10523730E-04<br>    2.21885047E+04 1.06048224E-04<br>    2.48959117E+04 1.00607800E-04<br>    2.79336724E+04 9.43988823E-05<br>    3.13420959E+04 8.76306617E-05<br>    3.51664100E+04 8.05127309E-05<br>    3.94573610E+04 7.32441304E-05<br>    4.42718872E+04 6.60045681E-05<br>    4.96738745E+04 5.89482252E-05<br>    5.57350039E+04 5.22002283E-05<br>    6.25357029E+04 4.58555848E-05<br>    7.01662127E+04 3.99801795E-05<br>    7.87277855E+04 3.46133228E-05<br>    8.83340282E+04 2.97713159E-05<br>    9.91124098E+04 2.54515370E-05<br>    1.11205953E+05 2.16366333E-05<br>    1.24775131E+05 1.82985061E-05<br>    1.40000000E+05 1.54018770E-05<br>    1.57082584E+05 1.29073184E-05<br>    1.76249558E+05 1.07737052E-05<br>    1.97755256E+05 8.96010310E-06<br>    2.21885047E+05 7.42714173E-06<br>    2.48959117E+05 6.13794514E-06<br>    2.79336724E+05 5.05869835E-06<br>    3.13420959E+05 4.15892792E-06<br>    3.51664100E+05 3.41156784E-06<br>    3.94573610E+05 2.79287256E-06<br>    4.42718872E+05 2.28222781E-06<br>    4.96738745E+05 1.86189948E-06<br>    5.57350039E+05 1.51675090E-06<br>    6.25357029E+05 1.23395091E-06<br>    7.01662127E+05 1.00268787E-06<br>    7.87277855E+05 8.13899758E-07<br>    8.83340282E+05 6.60026278E-07<br>    9.91124098E+05 5.34785748E-07<br>    1.11205953E+06 4.32977727E-07<br>    1.24775131E+06 3.50310661E-07<br>    1.40000000E+06 2.83253058E-07<br>    1.57082584E+06 2.28906166E-07<br>    1.76249558E+06 1.84895900E-07<br>    1.97755256E+06 1.49281722E-07<br>    2.21885047E+06 1.20480248E-07<br>    2.48959117E+06 9.72015307E-08<br>    2.79336724E+06 7.83961354E-08<br>    3.13420959E+06 6.32113481E-08<br>    3.51664100E+06 5.09550587E-08<br>    3.94573610E+06 4.10660607E-08<br>    4.42718872E+06 3.30896869E-08<br>    4.96738745E+06 2.66578689E-08<br>    5.57350039E+06 2.14728477E-08<br>    6.25357029E+06 1.72938907E-08<br>    7.01662127E+06 1.39264759E-08<br>    7.87277855E+06 1.12134979E-08<br>    8.83340282E+06 9.02812576E-09<br>    9.91124098E+06 7.26800818E-09<br>    1.11205953E+07 5.85057727E-09<br>    1.24775131E+07 4.70924487E-09<br>    1.40000000E+07 3.79032459E-09<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-7-N_MCNP) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">c Notes:<br>c   The listed energy bins should be ready to use for your application.<br>c   This source term assumes a large spherical shell geometry for GCRs<br>c     isotropically impingent on a planet\\'s atmosphere.<br>c   Change the geometric and angular portions of the source card to fit your usage.<br>c <br>c Source<br> SDEF PAR=008016 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    1.60000000E+02 0.0 <br>    2.01428066E+02 1.02214878E-06<br>    2.26006007E+02 1.34560575E-06<br>    2.53582911E+02 1.76277776E-06<br>    2.84524706E+02 2.29781704E-06<br>    3.19241970E+02 2.98012442E-06<br>    3.58195382E+02 3.84519120E-06<br>    4.01901829E+02 4.93548706E-06<br>    4.50941269E+02 6.30136659E-06<br>    5.05964426E+02 8.00195558E-06<br>    5.67701423E+02 1.01059643E-05<br>    6.36971473E+02 1.26923599E-05<br>    7.14693747E+02 1.58508125E-05<br>    8.01899574E+02 1.96818115E-05<br>    8.99746120E+02 2.42963309E-05<br>    1.00953175E+03 2.98149045E-05<br>    1.13271326E+03 3.63659613E-05<br>    1.27092518E+03 4.40832626E-05<br>    1.42600150E+03 5.31022869E-05<br>    1.60000000E+03 6.35554280E-05<br>    1.79522953E+03 7.55659070E-05<br>    2.01428066E+03 8.92403631E-05<br>    2.26006007E+03 1.04660176E-04<br>    2.53582911E+03 1.21871696E-04<br>    2.84524706E+03 1.40875715E-04<br>    3.19241970E+03 1.61616677E-04<br>    3.58195382E+03 1.83972345E-04<br>    4.01901829E+03 2.07744807E-04<br>    4.50941269E+03 2.32653880E-04<br>    5.05964426E+03 2.58334053E-04<br>    5.67701423E+03 2.84336095E-04<br>    6.36971473E+03 3.10134316E-04<br>    7.14693747E+03 3.35140124E-04<br>    8.01899574E+03 3.58722032E-04<br>    8.99746120E+03 3.80231643E-04<br>    1.00953175E+04 3.99034374E-04<br>    1.13271326E+04 4.14542989E-04<br>    1.27092518E+04 4.26251374E-04<br>    1.42600150E+04 4.33765633E-04<br>    1.60000000E+04 4.36829565E-04<br>    1.79522953E+04 4.35341909E-04<br>    2.01428066E+04 4.29363520E-04<br>    2.26006007E+04 4.19113620E-04<br>    2.53582911E+04 4.04955450E-04<br>    2.84524706E+04 3.87372769E-04<br>    3.19241970E+04 3.66939545E-04<br>    3.58195382E+04 3.44285799E-04<br>    4.01901829E+04 3.20062689E-04<br>    4.50941269E+04 2.94909756E-04<br>    5.05964426E+04 2.69426657E-04<br>    5.67701423E+04 2.44151011E-04<br>    6.36971473E+04 2.19543133E-04<br>    7.14693747E+04 1.95977670E-04<br>    8.01899574E+04 1.73741541E-04<br>    8.99746120E+04 1.53037111E-04<br>    1.00953175E+05 1.33989345E-04<br>    1.13271326E+05 1.16655590E-04<br>    1.27092518E+05 1.01036763E-04<br>    1.42600150E+05 8.70889012E-05<br>    1.60000000E+05 7.47342619E-05<br>    1.79522953E+05 6.38714211E-05<br>    2.01428066E+05 5.43840278E-05<br>    2.26006007E+05 4.61480709E-05<br>    2.53582911E+05 3.90376558E-05<br>    2.84524706E+05 3.29293882E-05<br>    3.19241970E+05 2.77055225E-05<br>    3.58195382E+05 2.32560657E-05<br>    4.01901829E+05 1.94800280E-05<br>    4.50941269E+05 1.62860089E-05<br>    5.05964426E+05 1.35922818E-05<br>    5.67701423E+05 1.13265196E-05<br>    6.36971473E+05 9.42527859E-06<br>    7.14693747E+05 7.83333271E-06<br>    8.01899574E+05 6.50292842E-06<br>    8.99746120E+05 5.39301351E-06<br>    1.00953175E+06 4.46847629E-06<br>    1.13271326E+06 3.69942038E-06<br>    1.27092518E+06 3.06049033E-06<br>    1.42600150E+06 2.53025669E-06<br>    1.60000000E+06 2.09066381E-06<br>    1.79522953E+06 1.72654000E-06<br>    2.01428066E+06 1.42516760E-06<br>    2.26006007E+06 1.17590880E-06<br>    2.53582911E+06 9.69882377E-07<br>    2.84524706E+06 7.99686057E-07<br>    3.19241970E+06 6.59159477E-07<br>    3.58195382E+06 5.43182614E-07<br>    4.01901829E+06 4.47505116E-07<br>    4.50941269E+06 3.68602280E-07<br>    5.05964426E+06 3.03553894E-07<br>    5.67701423E+06 2.49942570E-07<br>    6.36971473E+06 2.05768644E-07<br>    7.14693747E+06 1.69379078E-07<br>    8.01899574E+06 1.39408175E-07<br>    8.99746120E+06 1.14728221E-07<br>    1.00953175E+07 9.44084447E-08<br>    1.13271326E+07 7.76809402E-08<br>    1.27092518E+07 6.39124040E-08<br>    1.42600150E+07 5.25807106E-08<br>    1.60000000E+07 4.32555214E-08<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-8-O_MCNP) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">c Notes:<br>c   The listed energy bins should be ready to use for your application.<br>c   This source term assumes a large spherical shell geometry for GCRs<br>c     isotropically impingent on a planet\\'s atmosphere.<br>c   Change the geometric and angular portions of the source card to fit your usage.<br>c <br>c Source<br> SDEF PAR=026056 ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90<br> SI90      -1 0 1           <br> SP90      0 0.5 0.5        <br> #  SI1      SP1<br>    5.60000000E+02 0.0 <br>    7.04998231E+02 4.77696086E-07<br>    7.91021025E+02 6.24333939E-07<br>    8.87540188E+02 8.11970653E-07<br>    9.95836470E+02 1.05072352E-06<br>    1.11734690E+03 1.35278532E-06<br>    1.25368384E+03 1.73272649E-06<br>    1.40665640E+03 2.20780562E-06<br>    1.57829444E+03 2.79827682E-06<br>    1.77087549E+03 3.52767783E-06<br>    1.98695498E+03 4.42307839E-06<br>    2.22940016E+03 5.51526314E-06<br>    2.50142812E+03 6.83881744E-06<br>    2.80664851E+03 8.43207912E-06<br>    3.14911142E+03 1.03369134E-05<br>    3.53336113E+03 1.25982639E-05<br>    3.96449639E+03 1.52634284E-05<br>    4.44823811E+03 1.83810097E-05<br>    4.99100525E+03 2.19994917E-05<br>    5.60000000E+03 2.61654017E-05<br>    6.28330334E+03 3.09210336E-05<br>    7.04998231E+03 3.63017290E-05<br>    7.91021025E+03 4.23327468E-05<br>    8.87540188E+03 4.90257931E-05<br>    9.95836470E+03 5.63753382E-05<br>    1.11734690E+04 6.43549036E-05<br>    1.25368384E+04 7.29135711E-05<br>    1.40665640E+04 8.19730230E-05<br>    1.57829444E+04 9.14254756E-05<br>    1.77087549E+04 1.01132891E-04<br>    1.98695498E+04 1.10927844E-04<br>    2.22940016E+04 1.20616364E-04<br>    2.50142812E+04 1.29982950E-04<br>    2.80664851E+04 1.38797801E-04<br>    3.14911142E+04 1.46826070E-04<br>    3.53336113E+04 1.53838715E-04<br>    3.96449639E+04 1.59624266E-04<br>    4.44823811E+04 1.64000642E-04<br>    4.99100525E+04 1.66826009E-04<br>    5.60000000E+04 1.68007679E-04<br>    6.28330334E+04 1.67508176E-04<br>    7.04998231E+04 1.65347811E-04<br>    7.91021025E+04 1.61603487E-04<br>    8.87540188E+04 1.56403827E-04<br>    9.95836470E+04 1.49921092E-04<br>    1.11734690E+05 1.42360688E-04<br>    1.25368384E+05 1.33949255E-04<br>    1.40665640E+05 1.24922391E-04<br>    1.57829444E+05 1.15513030E-04<br>    1.77087549E+05 1.05941283E-04<br>    1.98695498E+05 9.64063329E-05<br>    2.22940016E+05 8.70806846E-05<br>    2.50142812E+05 7.81068140E-05<br>    2.80664851E+05 6.95960373E-05<br>    3.14911142E+05 6.16292655E-05<br>    3.53336113E+05 5.42592196E-05<br>    3.96449639E+05 4.75136539E-05<br>    4.44823811E+05 4.13991588E-05<br>    4.99100525E+05 3.59051742E-05<br>    5.60000000E+05 3.10079168E-05<br>    6.28330334E+05 2.66740137E-05<br>    7.04998231E+05 2.28637056E-05<br>    7.91021025E+05 1.95335544E-05<br>    8.87540188E+05 1.66386388E-05<br>    9.95836470E+05 1.41342613E-05<br>    1.11734690E+06 1.19772129E-05<br>    1.25368384E+06 1.01266566E-05<br>    1.40665640E+06 8.54469282E-06<br>    1.57829444E+06 7.19667191E-06<br>    1.77087549E+06 6.05131089E-06<br>    1.98695498E+06 5.08066545E-06<br>    2.22940016E+06 4.26000026E-06<br>    2.50142812E+06 3.56759188E-06<br>    2.80664851E+06 2.98449167E-06<br>    3.14911142E+06 2.49426935E-06<br>    3.53336113E+06 2.08275207E-06<br>    3.96449639E+06 1.73776990E-06<br>    4.44823811E+06 1.44891459E-06<br>    4.99100525E+06 1.20731596E-06<br>    5.60000000E+06 1.00543811E-06<br>    6.28330334E+06 8.36896386E-07<br>    7.04998231E+06 6.96294648E-07<br>    7.91021025E+06 5.79082081E-07<br>    8.87540188E+06 4.81428107E-07<br>    9.95836470E+06 4.00113877E-07<br>    1.11734690E+07 3.32438651E-07<br>    1.25368384E+07 2.76139441E-07<br>    1.40665640E+07 2.29322309E-07<br>    1.57829444E+07 1.90403858E-07<br>    1.77087549E+07 1.58061561E-07<br>    1.98695498E+07 1.31191704E-07<br>    2.22940016E+07 1.08873868E-07<br>    2.50142812E+07 9.03409982E-08<br>    2.80664851E+07 7.49542259E-08<br>    3.14911142E+07 6.21817257E-08<br>    3.53336113E+07 5.15809871E-08<br>    3.96449639E+07 4.27839681E-08<br>    4.44823811E+07 3.54846765E-08<br>    4.99100525E+07 2.94287922E-08<br>    5.60000000E+07 2.44050040E-08<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-26-Fe_MCNP) in the local text_files/ folder')))), selected_index=None, _titles={'0': 'GCR-flux_W-50_Z-1-H_MCNP', '1': 'GCR-flux_W-50_Z-2-He_MCNP', '2': 'GCR-flux_W-50_Z-6-C_MCNP', '3': 'GCR-flux_W-50_Z-7-N_MCNP', '4': 'GCR-flux_W-50_Z-8-O_MCNP', '5': 'GCR-flux_W-50_Z-26-Fe_MCNP'}), Accordion(children=(VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   1H       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 3.11230416E-06<br>       1.12201845E+01 3.78742143E-06<br>       1.25892541E+01 4.59188374E-06<br>       1.41253754E+01 5.54583448E-06<br>       1.58489319E+01 6.67135214E-06<br>       1.77827941E+01 7.99232213E-06<br>       1.99526231E+01 9.53420450E-06<br>       2.23872114E+01 1.13236770E-05<br>       2.51188643E+01 1.33881336E-05<br>       2.81838293E+01 1.57550197E-05<br>       3.16227766E+01 1.84509886E-05<br>       3.54813389E+01 2.15008690E-05<br>       3.98107171E+01 2.49264407E-05<br>       4.46683592E+01 2.87450241E-05<br>       5.01187234E+01 3.29679044E-05<br>       5.62341325E+01 3.75986215E-05<br>       6.30957344E+01 4.26311793E-05<br>       7.07945784E+01 4.80482424E-05<br>       7.94328235E+01 5.38194108E-05<br>       8.91250938E+01 5.98996836E-05<br>       1.00000000E+02 6.62282401E-05<br>       1.12201845E+02 7.27276826E-05<br>       1.25892541E+02 7.93038921E-05<br>       1.41253754E+02 8.58466508E-05<br>       1.58489319E+02 9.22311664E-05<br>       1.77827941E+02 9.83206103E-05<br>       1.99526231E+02 1.03969728E-04<br>       2.23872114E+02 1.09029515E-04<br>       2.51188643E+02 1.13352871E-04<br>       2.81838293E+02 1.16801027E-04<br>       3.16227766E+02 1.19250451E-04<br>       3.54813389E+02 1.20599824E-04<br>       3.98107171E+02 1.20776574E-04<br>       4.46683592E+02 1.19742448E-04<br>       5.01187234E+02 1.17497543E-04<br>       5.62341325E+02 1.14082342E-04<br>       6.30957344E+02 1.09577371E-04<br>       7.07945784E+02 1.04100336E-04<br>       7.94328235E+02 9.78008126E-05<br>       8.91250938E+02 9.08527983E-05<br>       1.00000000E+03 8.34457053E-05<br>       1.12201845E+03 7.57745123E-05<br>       1.25892541E+03 6.80299039E-05<br>       1.41253754E+03 6.03892103E-05<br>       1.58489319E+03 5.30088492E-05<br>       1.77827941E+03 4.60187806E-05<br>       1.99526231E+03 3.95192458E-05<br>       2.23872114E+03 3.35798007E-05<br>       2.51188643E+03 2.82404316E-05<br>       2.81838293E+03 2.35143602E-05<br>       3.16227766E+03 1.93920439E-05<br>       3.54813389E+03 1.58458460E-05<br>       3.98107171E+03 1.28348874E-05<br>       4.46683592E+03 1.03096728E-05<br>       5.01187234E+03 8.21619698E-06<br>       5.62341325E+03 6.49935129E-06<br>       6.30957344E+03 5.10555854E-06<br>       7.07945784E+03 3.98464943E-06<br>       7.94328235E+03 3.09105582E-06<br>       8.91250938E+03 2.38443109E-06<br>       1.00000000E+04 1.82982214E-06<br>       1.12201845E+04 1.39751552E-06<br>       1.25892541E+04 1.06266697E-06<br>       1.41253754E+04 8.04804944E-07<br>       1.58489319E+04 6.07278246E-07<br>       1.77827941E+04 4.56698493E-07<br>       1.99526231E+04 3.42410993E-07<br>       2.23872114E+04 2.56014212E-07<br>       2.51188643E+04 1.90937584E-07<br>       2.81838293E+04 1.42080182E-07<br>       3.16227766E+04 1.05508035E-07<br>       3.54813389E+04 7.82050173E-08<br>       3.98107171E+04 5.78708980E-08<br>       4.46683592E+04 4.27597034E-08<br>       5.01187234E+04 3.15517677E-08<br>       5.62341325E+04 2.32534181E-08<br>       6.30957344E+04 1.71189796E-08<br>       7.07945784E+04 1.25905755E-08<br>       7.94328235E+04 9.25196172E-09<br>       8.91250938E+04 6.79332141E-09<br>       1.00000000E+05 4.98455256E-09<br>       1.12201845E+05 3.65508831E-09<br>       1.25892541E+05 2.67871176E-09<br>       1.41253754E+05 1.96216849E-09<br>       1.58489319E+05 1.43665318E-09<br>       1.77827941E+05 1.05146212E-09<br>       1.99526231E+05 7.69272016E-10<br>       2.23872114E+05 5.62635931E-10<br>       2.51188643E+05 4.11387493E-10<br>       2.81838293E+05 3.00721231E-10<br>       3.16227766E+05 2.19775040E-10<br>       3.54813389E+05 1.60584838E-10<br>       3.98107171E+05 1.17314607E-10<br>       4.46683592E+05 8.56898743E-11<br>       5.01187234E+05 6.25812669E-11<br>       5.62341325E+05 4.56986515E-11<br>       6.30957344E+05 3.33666527E-11<br>       7.07945784E+05 2.43600123E-11<br>       7.94328235E+05 1.77829078E-11<br>       8.91250938E+05 1.29805396E-11<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-1-H_PHITS) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   4He       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 1.79107161E-06<br>       1.12201845E+01 2.10420044E-06<br>       1.25892541E+01 2.46022152E-06<br>       1.41253754E+01 2.86243295E-06<br>       1.58489319E+01 3.31384616E-06<br>       1.77827941E+01 3.81705061E-06<br>       1.99526231E+01 4.37406543E-06<br>       2.23872114E+01 4.98618082E-06<br>       2.51188643E+01 5.65379308E-06<br>       2.81838293E+01 6.37623820E-06<br>       3.16227766E+01 7.15162947E-06<br>       3.54813389E+01 7.97670592E-06<br>       3.98107171E+01 8.84669860E-06<br>       4.46683592E+01 9.75522272E-06<br>       5.01187234E+01 1.06942038E-05<br>       5.62341325E+01 1.16538464E-05<br>       6.30957344E+01 1.26226535E-05<br>       7.07945784E+01 1.35875054E-05<br>       7.94328235E+01 1.45338044E-05<br>       8.91250938E+01 1.54456923E-05<br>       1.00000000E+02 1.63063447E-05<br>       1.12201845E+02 1.70983441E-05<br>       1.25892541E+02 1.78041307E-05<br>       1.41253754E+02 1.84065244E-05<br>       1.58489319E+02 1.88893082E-05<br>       1.77827941E+02 1.92378551E-05<br>       1.99526231E+02 1.94397757E-05<br>       2.23872114E+02 1.94855546E-05<br>       2.51188643E+02 1.93691390E-05<br>       2.81838293E+02 1.90884390E-05<br>       3.16227766E+02 1.86456922E-05<br>       3.54813389E+02 1.80476540E-05<br>       3.98107171E+02 1.73055748E-05<br>       4.46683592E+02 1.64349412E-05<br>       5.01187234E+02 1.54549739E-05<br>       5.62341325E+02 1.43878964E-05<br>       6.30957344E+02 1.32580089E-05<br>       7.07945784E+02 1.20906281E-05<br>       7.94328235E+02 1.09109644E-05<br>       8.91250938E+02 9.74302285E-06<br>       1.00000000E+03 8.60861052E-06<br>       1.12201845E+03 7.52652444E-06<br>       1.25892541E+03 6.51197465E-06<br>       1.41253754E+03 5.57627147E-06<br>       1.58489319E+03 4.72677849E-06<br>       1.77827941E+03 3.96710717E-06<br>       1.99526231E+03 3.29750796E-06<br>       2.23872114E+03 2.71540032E-06<br>       2.51188643E+03 2.21597962E-06<br>       2.81838293E+03 1.79284204E-06<br>       3.16227766E+03 1.43857809E-06<br>       3.54813389E+03 1.14529837E-06<br>       3.98107171E+03 9.05068993E-07<br>       4.46683592E+03 7.10247468E-07<br>       5.01187234E+03 5.53720548E-07<br>       5.62341325E+03 4.29053373E-07<br>       6.30957344E+03 3.30563991E-07<br>       7.07945784E+03 2.53339293E-07<br>       7.94328235E+03 1.93208276E-07<br>       8.91250938E+03 1.46686951E-07<br>       1.00000000E+04 1.10906879E-07<br>       1.12201845E+04 8.35366479E-08<br>       1.25892541E+04 6.27030594E-08<br>       1.41253754E+04 4.69165623E-08<br>       1.58489319E+04 3.50036285E-08<br>       1.77827941E+04 2.60473879E-08<br>       1.99526231E+04 1.93368466E-08<br>       2.23872114E+04 1.43243612E-08<br>       2.51188643E+04 1.05906539E-08<br>       2.81838293E+04 7.81646441E-09<br>       3.16227766E+04 5.75987445E-09<br>       3.54813389E+04 4.23837197E-09<br>       3.98107171E+04 3.11480296E-09<br>       4.46683592E+04 2.28646116E-09<br>       5.01187234E+04 1.67667839E-09<br>       5.62341325E+04 1.22838479E-09<br>       6.30957344E+04 8.99206365E-10<br>       7.07945784E+04 6.57751777E-10<br>       7.94328235E+04 4.80812898E-10<br>       8.91250938E+04 3.51262603E-10<br>       1.00000000E+05 2.56481873E-10<br>       1.12201845E+05 1.87186632E-10<br>       1.25892541E+05 1.36555216E-10<br>       1.41253754E+05 9.95810535E-11<br>       1.58489319E+05 7.25934930E-11<br>       1.77827941E+05 5.29038140E-11<br>       1.99526231E+05 3.85441684E-11<br>       2.23872114E+05 2.80753642E-11<br>       2.51188643E+05 2.04455318E-11<br>       2.81838293E+05 1.48863354E-11<br>       3.16227766E+05 1.08368376E-11<br>       3.54813389E+05 7.88770664E-12<br>       3.98107171E+05 5.74036545E-12<br>       4.46683592E+05 4.17710462E-12<br>       5.01187234E+05 3.03923239E-12<br>       5.62341325E+05 2.21110986E-12<br>       6.30957344E+05 1.60849290E-12<br>       7.07945784E+05 1.17002317E-12<br>       7.94328235E+05 8.51020244E-13<br>       8.91250938E+05 6.18954427E-13<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-2-He_PHITS) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   12C       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 4.40374042E-08<br>       1.12201845E+01 5.19422577E-08<br>       1.25892541E+01 6.09719211E-08<br>       1.41253754E+01 7.12212475E-08<br>       1.58489319E+01 8.27792387E-08<br>       1.77827941E+01 9.57254993E-08<br>       1.99526231E+01 1.10126276E-07<br>       2.23872114E+01 1.26030144E-07<br>       2.51188643E+01 1.43463436E-07<br>       2.81838293E+01 1.62425523E-07<br>       3.16227766E+01 1.82884102E-07<br>       3.54813389E+01 2.04770651E-07<br>       3.98107171E+01 2.27976263E-07<br>       4.46683592E+01 2.52348060E-07<br>       5.01187234E+01 2.77686436E-07<br>       5.62341325E+01 3.03743375E-07<br>       6.30957344E+01 3.30222090E-07<br>       7.07945784E+01 3.56778257E-07<br>       7.94328235E+01 3.83023063E-07<br>       8.91250938E+01 4.08528302E-07<br>       1.00000000E+02 4.32833680E-07<br>       1.12201845E+02 4.55456447E-07<br>       1.25892541E+02 4.75903361E-07<br>       1.41253754E+02 4.93684898E-07<br>       1.58489319E+02 5.08331446E-07<br>       1.77827941E+02 5.19411048E-07<br>       1.99526231E+02 5.26548061E-07<br>       2.23872114E+02 5.29441885E-07<br>       2.51188643E+02 5.27884689E-07<br>       2.81838293E+02 5.21776932E-07<br>       3.16227766E+02 5.11139357E-07<br>       3.54813389E+02 4.96120169E-07<br>       3.98107171E+02 4.76996266E-07<br>       4.46683592E+02 4.54167716E-07<br>       5.01187234E+02 4.28145125E-07<br>       5.62341325E+02 3.99530195E-07<br>       6.30957344E+02 3.68990372E-07<br>       7.07945784E+02 3.37229183E-07<br>       7.94328235E+02 3.04954358E-07<br>       8.91250938E+02 2.72846157E-07<br>       1.00000000E+03 2.41528359E-07<br>       1.12201845E+03 2.11544115E-07<br>       1.25892541E+03 1.83338325E-07<br>       1.41253754E+03 1.57247499E-07<br>       1.58489319E+03 1.33497237E-07<br>       1.77827941E+03 1.12206733E-07<br>       1.99526231E+03 9.33990560E-08<br>       2.23872114E+03 7.70156125E-08<br>       2.51188643E+03 6.29330017E-08<br>       2.81838293E+03 5.09805775E-08<br>       3.16227766E+03 4.09572773E-08<br>       3.54813389E+03 3.26466397E-08<br>       3.98107171E+03 2.58293359E-08<br>       4.46683592E+03 2.02929153E-08<br>       5.01187234E+03 1.58387836E-08<br>       5.62341325E+03 1.22866562E-08<br>       6.30957344E+03 9.47687606E-09<br>       7.07945784E+03 7.27104218E-09<br>       7.94328235E+03 5.55139823E-09<br>       8.91250938E+03 4.21938871E-09<br>       1.00000000E+04 3.19372407E-09<br>       1.12201845E+04 2.40822317E-09<br>       1.25892541E+04 1.80962877E-09<br>       1.41253754E+04 1.35552829E-09<br>       1.58489319E+04 1.01246001E-09<br>       1.77827941E+04 7.54244754E-10<br>       1.99526231E+04 5.60554792E-10<br>       2.23872114E+04 4.15712425E-10<br>       2.51188643E+04 3.07699567E-10<br>       2.81838293E+04 2.27353617E-10<br>       3.16227766E+04 1.67723122E-10<br>       3.54813389E+04 1.23557287E-10<br>       3.98107171E+04 9.09055016E-11<br>       4.46683592E+04 6.68058624E-11<br>       5.01187234E+04 4.90447446E-11<br>       5.62341325E+04 3.59724367E-11<br>       6.30957344E+04 2.63625979E-11<br>       7.07945784E+04 1.93056713E-11<br>       7.94328235E+04 1.41284206E-11<br>       8.91250938E+04 1.03334319E-11<br>       1.00000000E+05 7.55379146E-12<br>       1.12201845E+05 5.51923940E-12<br>       1.25892541E+05 4.03096645E-12<br>       1.41253754E+05 2.94289288E-12<br>       1.58489319E+05 2.14779391E-12<br>       1.77827941E+05 1.56703740E-12<br>       1.99526231E+05 1.14300675E-12<br>       2.23872114E+05 8.33515122E-13<br>       2.51188643E+05 6.07693628E-13<br>       2.81838293E+05 4.42968094E-13<br>       3.16227766E+05 3.22838827E-13<br>       3.54813389E+05 2.35251635E-13<br>       3.98107171E+05 1.71403736E-13<br>       4.46683592E+05 1.24869123E-13<br>       5.01187234E+05 9.09583755E-14<br>       5.62341325E+05 6.62503662E-14<br>       6.30957344E+05 4.82498953E-14<br>       7.07945784E+05 3.51375140E-14<br>       7.94328235E+05 2.55867941E-14<br>       8.91250938E+05 1.86309129E-14<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-6-C_PHITS) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   14N       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 6.01217275E-09<br>       1.12201845E+01 7.27696652E-09<br>       1.25892541E+01 8.76487180E-09<br>       1.41253754E+01 1.05044602E-08<br>       1.58489319E+01 1.25254107E-08<br>       1.77827941E+01 1.48579038E-08<br>       1.99526231E+01 1.75318482E-08<br>       2.23872114E+01 2.05759277E-08<br>       2.51188643E+01 2.40164666E-08<br>       2.81838293E+01 2.78761129E-08<br>       3.16227766E+01 3.21723543E-08<br>       3.54813389E+01 3.69158875E-08<br>       3.98107171E+01 4.21088766E-08<br>       4.46683592E+01 4.77431500E-08<br>       5.01187234E+01 5.37984018E-08<br>       5.62341325E+01 6.02404781E-08<br>       6.30957344E+01 6.70198486E-08<br>       7.07945784E+01 7.40703803E-08<br>       7.94328235E+01 8.13085418E-08<br>       8.91250938E+01 8.86331831E-08<br>       1.00000000E+02 9.59260368E-08<br>       1.12201845E+02 1.03053083E-07<br>       1.25892541E+02 1.09866907E-07<br>       1.41253754E+02 1.16210135E-07<br>       1.58489319E+02 1.21920002E-07<br>       1.77827941E+02 1.26833996E-07<br>       1.99526231E+02 1.30796471E-07<br>       2.23872114E+02 1.33665972E-07<br>       2.51188643E+02 1.35322904E-07<br>       2.81838293E+02 1.35677075E-07<br>       3.16227766E+02 1.34674514E-07<br>       3.54813389E+02 1.32302944E-07<br>       3.98107171E+02 1.28595269E-07<br>       4.46683592E+02 1.23630553E-07<br>       5.01187234E+02 1.17532110E-07<br>       5.62341325E+02 1.10462609E-07<br>       6.30957344E+02 1.02616382E-07<br>       7.07945784E+02 9.42094479E-08<br>       7.94328235E+02 8.54680393E-08<br>       8.91250938E+02 7.66166354E-08<br>       1.00000000E+03 6.78665442E-08<br>       1.12201845E+03 5.94060300E-08<br>       1.25892541E+03 5.13927641E-08<br>       1.41253754E+03 4.39490857E-08<br>       1.58489319E+03 3.71602047E-08<br>       1.77827941E+03 3.10751545E-08<br>       1.99526231E+03 2.57100272E-08<br>       2.23872114E+03 2.10528552E-08<br>       2.51188643E+03 1.70694400E-08<br>       2.81838293E+03 1.37094628E-08<br>       3.16227766E+03 1.09123222E-08<br>       3.54813389E+03 8.61229401E-09<br>       3.98107171E+03 6.74277522E-09<br>       4.46683592E+03 5.23951617E-09<br>       5.01187234E+03 4.04286964E-09<br>       5.62341325E+03 3.09916341E-09<br>       6.30957344E+03 2.36135052E-09<br>       7.07945784E+03 1.78910623E-09<br>       7.94328235E+03 1.34853456E-09<br>       8.91250938E+03 1.01162627E-09<br>       1.00000000E+04 7.55583503E-10<br>       1.12201845E+04 5.62097342E-10<br>       1.25892541E+04 4.16638551E-10<br>       1.41253754E+04 3.07799675E-10<br>       1.58489319E+04 2.26709358E-10<br>       1.77827941E+04 1.66527219E-10<br>       1.99526231E+04 1.22019106E-10<br>       2.23872114E+04 8.92073126E-11<br>       2.51188643E+04 6.50874959E-11<br>       2.81838293E+04 4.74029575E-11<br>       3.16227766E+04 3.44669358E-11<br>       3.54813389E+04 2.50242290E-11<br>       3.98107171E+04 1.81444717E-11<br>       4.46683592E+04 1.31405095E-11<br>       5.01187234E+04 9.50642803E-12<br>       5.62341325E+04 6.87080577E-12<br>       6.30957344E+04 4.96165165E-12<br>       7.07945784E+04 3.58023886E-12<br>       7.94328235E+04 2.58166448E-12<br>       8.91250938E+04 1.86046306E-12<br>       1.00000000E+05 1.33999734E-12<br>       1.12201845E+05 9.64658792E-13<br>       1.25892541E+05 6.94149606E-13<br>       1.41253754E+05 4.99300841E-13<br>       1.58489319E+05 3.59020749E-13<br>       1.77827941E+05 2.58072126E-13<br>       1.99526231E+05 1.85456260E-13<br>       2.23872114E+05 1.33239732E-13<br>       2.51188643E+05 9.57038679E-14<br>       2.81838293E+05 6.87288541E-14<br>       3.16227766E+05 4.93482633E-14<br>       3.54813389E+05 3.54271397E-14<br>       3.98107171E+05 2.54295781E-14<br>       4.46683592E+05 1.82510425E-14<br>       5.01187234E+05 1.30974742E-14<br>       5.62341325E+05 9.39818620E-15<br>       6.30957344E+05 6.74313497E-15<br>       7.07945784E+05 4.83776941E-15<br>       7.94328235E+05 3.47054531E-15<br>       8.91250938E+05 2.48956144E-15<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-7-N_PHITS) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   16O       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 3.95803507E-08<br>       1.12201845E+01 4.66625657E-08<br>       1.25892541E+01 5.47485136E-08<br>       1.41253754E+01 6.39222511E-08<br>       1.58489319E+01 7.42625648E-08<br>       1.77827941E+01 8.58398391E-08<br>       1.99526231E+01 9.87125653E-08<br>       2.23872114E+01 1.12923548E-07<br>       2.51188643E+01 1.28495892E-07<br>       2.81838293E+01 1.45428872E-07<br>       3.16227766E+01 1.63693810E-07<br>       3.54813389E+01 1.83230124E-07<br>       3.98107171E+01 2.03941696E-07<br>       4.46683592E+01 2.25693768E-07<br>       5.01187234E+01 2.48310561E-07<br>       5.62341325E+01 2.71573832E-07<br>       6.30957344E+01 2.95222580E-07<br>       7.07945784E+01 3.18954128E-07<br>       7.94328235E+01 3.42426781E-07<br>       8.91250938E+01 3.65264231E-07<br>       1.00000000E+02 3.87061876E-07<br>       1.12201845E+02 4.07395124E-07<br>       1.25892541E+02 4.25829710E-07<br>       1.41253754E+02 4.41933939E-07<br>       1.58489319E+02 4.55292643E-07<br>       1.77827941E+02 4.65522494E-07<br>       1.99526231E+02 4.72288142E-07<br>       2.23872114E+02 4.75318452E-07<br>       2.51188643E+02 4.74421977E-07<br>       2.81838293E+02 4.69500605E-07<br>       3.16227766E+02 4.60560292E-07<br>       3.54813389E+02 4.47717759E-07<br>       3.98107171E+02 4.31202156E-07<br>       4.46683592E+02 4.11350992E-07<br>       5.01187234E+02 3.88599963E-07<br>       5.62341325E+02 3.63466850E-07<br>       6.30957344E+02 3.36530223E-07<br>       7.07945784E+02 3.08404204E-07<br>       7.94328235E+02 2.79711060E-07<br>       8.91250938E+02 2.51053640E-07<br>       1.00000000E+03 2.22989789E-07<br>       1.12201845E+03 1.96010638E-07<br>       1.25892541E+03 1.70524299E-07<br>       1.41253754E+03 1.46845873E-07<br>       1.58489319E+03 1.25194020E-07<br>       1.77827941E+03 1.05693679E-07<br>       1.99526231E+03 8.83839908E-08<br>       2.23872114E+03 7.32300867E-08<br>       2.51188643E+03 6.01372602E-08<br>       2.81838293E+03 4.89660487E-08<br>       3.16227766E+03 3.95469528E-08<br>       3.54813389E+03 3.16938031E-08<br>       3.98107171E+03 2.52151229E-08<br>       4.46683592E+03 1.99231574E-08<br>       5.01187234E+03 1.56405224E-08<br>       5.62341325E+03 1.22046340E-08<br>       6.30957344E+03 9.47021966E-09<br>       7.07945784E+03 7.31027851E-09<br>       7.94328235E+03 5.61587341E-09<br>       8.91250938E+03 4.29510957E-09<br>       1.00000000E+04 3.27160661E-09<br>       1.12201845E+04 2.48270928E-09<br>       1.25892541E+04 1.87762150E-09<br>       1.41253754E+04 1.41559242E-09<br>       1.58489319E+04 1.06423652E-09<br>       1.77827941E+04 7.98032988E-10<br>       1.99526231E+04 5.97022561E-10<br>       2.23872114E+04 4.45701478E-10<br>       2.51188643E+04 3.32100223E-10<br>       2.81838293E+04 2.47028390E-10<br>       3.16227766E+04 1.83464051E-10<br>       3.54813389E+04 1.36065711E-10<br>       3.98107171E+04 1.00786200E-10<br>       4.46683592E+04 7.45698848E-11<br>       5.01187234E+04 5.51170552E-11<br>       5.62341325E+04 4.07018319E-11<br>       6.30957344E+04 3.00322716E-11<br>       7.07945784E+04 2.21434614E-11<br>       7.94328235E+04 1.63162023E-11<br>       8.91250938E+04 1.20154129E-11<br>       1.00000000E+05 8.84364178E-12<br>       1.12201845E+05 6.50609556E-12<br>       1.25892541E+05 4.78440725E-12<br>       1.41253754E+05 3.51700970E-12<br>       1.58489319E+05 2.58448504E-12<br>       1.77827941E+05 1.89865037E-12<br>       1.99526231E+05 1.39444169E-12<br>       2.23872114E+05 1.02388812E-12<br>       2.51188643E+05 7.51644554E-13<br>       2.81838293E+05 5.51683896E-13<br>       3.16227766E+05 4.04850546E-13<br>       3.54813389E+05 2.97052830E-13<br>       3.98107171E+05 2.17928617E-13<br>       4.46683592E+05 1.59861079E-13<br>       5.01187234E+05 1.17253215E-13<br>       5.62341325E+05 8.59934437E-14<br>       6.30957344E+05 6.30621788E-14<br>       7.07945784E+05 4.62423239E-14<br>       7.94328235E+05 3.39063429E-14<br>       8.91250938E+05 2.48597095E-14<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-8-O_PHITS) in the local text_files/ folder'))), VBox(children=(HBox(children=(HTML(value='<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\"># Notes:<br>#   The entry \\'iMeVperu = 1\\' must be set in your [PARAMETERS] card.<br>#   The listed energy bins should be ready to use for your application.<br>#   This source term assumes a large spherical shell geometry for GCRs<br>#     isotropically impingent on a planet\\'s atmosphere.<br>#   Change the geometric and angular portions of the source card to fit your usage.<br># <br>[ S o u r c e ]<br>   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)<br>     proj =   56Fe       <br>       r1 =   3.48707700e+08   # inner radius [cm]<br>       r2 =   3.48707700e+08   # outer radius [cm]<br>       x0 =   0.0000        # center position of x-axis [cm]<br>       y0 =   0.0000        # center position of y-axis [cm]<br>       z0 =   0.0000        # center position of z-axis [cm]<br>      dir =   iso           # inward isotropic distribution<br>   e-type =   21            # differential probability, dphi/dE<br>       ne =   100          # number of energy bins<br>       1.00000000E+01 5.32311078E-09<br>       1.12201845E+01 6.23071859E-09<br>       1.25892541E+01 7.25777328E-09<br>       1.41253754E+01 8.41253311E-09<br>       1.58489319E+01 9.70230463E-09<br>       1.77827941E+01 1.11330802E-08<br>       1.99526231E+01 1.27091489E-08<br>       2.23872114E+01 1.44326902E-08<br>       2.51188643E+01 1.63033604E-08<br>       2.81838293E+01 1.83178867E-08<br>       3.16227766E+01 2.04696818E-08<br>       3.54813389E+01 2.27484962E-08<br>       3.98107171E+01 2.51401268E-08<br>       4.46683592E+01 2.76261984E-08<br>       5.01187234E+01 3.01840376E-08<br>       5.62341325E+01 3.27866584E-08<br>       6.30957344E+01 3.54028764E-08<br>       7.07945784E+01 3.79975695E-08<br>       7.94328235E+01 4.05320995E-08<br>       8.91250938E+01 4.29649054E-08<br>       1.00000000E+02 4.52522791E-08<br>       1.12201845E+02 4.73493220E-08<br>       1.25892541E+02 4.92110807E-08<br>       1.41253754E+02 5.07938441E-08<br>       1.58489319E+02 5.20565777E-08<br>       1.77827941E+02 5.29624538E-08<br>       1.99526231E+02 5.34804217E-08<br>       2.23872114E+02 5.35867484E-08<br>       2.51188643E+02 5.32664412E-08<br>       2.81838293E+02 5.25144566E-08<br>       3.16227766E+02 5.13365911E-08<br>       3.54813389E+02 4.97499543E-08<br>       3.98107171E+02 4.77829372E-08<br>       4.46683592E+02 4.54746158E-08<br>       5.01187234E+02 4.28735680E-08<br>       5.62341325E+02 4.00361305E-08<br>       6.30957344E+02 3.70241731E-08<br>       7.07945784E+02 3.39025217E-08<br>       7.94328235E+02 3.07362028E-08<br>       8.91250938E+02 2.75877058E-08<br>       1.00000000E+03 2.45144675E-08<br>       1.12201845E+03 2.15667599E-08<br>       1.25892541E+03 1.87861238E-08<br>       1.41253754E+03 1.62044326E-08<br>       1.58489319E+03 1.38436047E-08<br>       1.77827941E+03 1.17159237E-08<br>       1.99526231E+03 9.82486874E-09<br>       2.23872114E+03 8.16632656E-09<br>       2.51188643E+03 6.73003667E-09<br>       2.81838293E+03 5.50112714E-09<br>       3.16227766E+03 4.46161424E-09<br>       3.54813389E+03 3.59176809E-09<br>       3.98107171E+03 2.87127888E-09<br>       4.46683592E+03 2.28018963E-09<br>       5.01187234E+03 1.79958948E-09<br>       5.62341325E+03 1.41208226E-09<br>       6.30957344E+03 1.10205910E-09<br>       7.07945784E+03 8.55811210E-10<br>       7.94328235E+03 6.61520781E-10<br>       8.91250938E+03 5.09165588E-10<br>       1.00000000E+04 3.90368552E-10<br>       1.12201845E+04 2.98217464E-10<br>       1.25892541E+04 2.27074167E-10<br>       1.41253754E+04 1.72386895E-10<br>       1.58489319E+04 1.30514742E-10<br>       1.77827941E+04 9.85694253E-11<br>       1.99526231E+04 7.42766892E-11<br>       2.23872114E+04 5.58576819E-11<br>       2.51188643E+04 4.19293527E-11<br>       2.81838293E+04 3.14221516E-11<br>       3.16227766E+04 2.35129463E-11<br>       3.54813389E+04 1.75709839E-11<br>       3.98107171E+04 1.31147984E-11<br>       4.46683592E+04 9.77815294E-12<br>       5.01187234E+04 7.28332692E-12<br>       5.62341325E+04 5.42030879E-12<br>       6.30957344E+04 4.03068374E-12<br>       7.07945784E+04 2.99522354E-12<br>       7.94328235E+04 2.22437187E-12<br>       8.91250938E+04 1.65097994E-12<br>       1.00000000E+05 1.22478017E-12<br>       1.12201845E+05 9.08195846E-13<br>       1.25892541E+05 6.73172831E-13<br>       1.41253754E+05 4.98790181E-13<br>       1.58489319E+05 3.69462247E-13<br>       1.77827941E+05 2.73588580E-13<br>       1.99526231E+05 2.02541908E-13<br>       2.23872114E+05 1.49910744E-13<br>       2.51188643E+05 1.10933368E-13<br>       2.81838293E+05 8.20753457E-14<br>       3.16227766E+05 6.07145564E-14<br>       3.54813389E+05 4.49065929E-14<br>       3.98107171E+05 3.32101884E-14<br>       4.46683592E+05 2.45574109E-14<br>       5.01187234E+05 1.81572145E-14<br>       5.62341325E+05 1.34238195E-14<br>       6.30957344E+05 9.92356037E-15<br>       7.07945784E+05 7.33545917E-15<br>       7.94328235E+05 5.42199225E-15<br>       8.91250938E+05 4.00742439E-15<br>       1.00000000E+06<br></p></font>'),), layout=Layout(height='400px', overflow_x='auto', overflow_y='auto', width='1800px')), Button(button_style='success', description='Save file (txt)', icon='save', style=ButtonStyle(), tooltip='Save a text file with information of the this spectrum (GCR-flux_W-50_Z-26-Fe_PHITS) in the local text_files/ folder')))), selected_index=None, _titles={'0': 'GCR-flux_W-50_Z-1-H_PHITS', '1': 'GCR-flux_W-50_Z-2-He_PHITS', '2': 'GCR-flux_W-50_Z-6-C_PHITS', '3': 'GCR-flux_W-50_Z-7-N_PHITS', '4': 'GCR-flux_W-50_Z-8-O_PHITS', '5': 'GCR-flux_W-50_Z-26-Fe_PHITS'})), _titles={'0': 'Experiment', '1': 'MCNP', '2': 'PHITS'})"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f709a2af3195494cabca68ffb33acf0f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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": [
       "HBox(children=(Button(button_style='success', description='Save text (ZIP)', icon='save', style=ButtonStyle(), tooltip='Save text files of all GCR spectra in a ZIP archive in the local text_files/ folder'), Label(value='(All above text files are archived into a single ZIP file when saved.)')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Expandable menu with spectra (raw/PHITS/MCNP)\n",
    "\n",
    "spectra_text_label = w.Label(value='For convenience, the GCR spectra can be viewed and saved in the tabs below.')\n",
    "display(spectra_text_label)\n",
    "\n",
    "plotted_spectra_text = [[],[],[]]\n",
    "plotted_spectra_names = [[],[],[]]\n",
    "\n",
    "ion_names = []\n",
    "for i in zi_list:\n",
    "    ion_names.append('Z-'+str(i+1)+'-'+all_Z_strs[i]+'_')\n",
    "name_bases = ['All-Z-1-28_'] + ion_names\n",
    "\n",
    "name_suffixes = ['raw','MCNP','PHITS']\n",
    "\n",
    "column_headers = ['Emin [MeV/n]','Emid [MeV/n]','Emax [MeV/n]','Flux [#/(s*sr*cm^2*MeV/n)]']\n",
    "\n",
    "for i in range(3):\n",
    "    for j in range(len(zi_list)+1):\n",
    "        if j!=0: zi = zi_list[j-1]\n",
    "            \n",
    "        if j==0 and i!=0: continue # skip combined files for MCNP and PHITS\n",
    "        \n",
    "        plotted_spectra_names[i].append('GCR-flux_W-' + W_text +'_'+ name_bases[j] + name_suffixes[i])\n",
    "        \n",
    "        if i==0: # raw spectra\n",
    "            if j==0: # All ions\n",
    "                text = \"Flux F in units of [#/(s*sr*cm^2*MeV/n)]\\n\"\n",
    "                text += column_headers[0]+'\\t'+column_headers[1]+'\\t'+column_headers[2]+'\\t'\n",
    "                for zii in zi_list:\n",
    "                    text += 'F(Z={0}/{1})\\t'.format(str(zii+1),all_Z_strs[zii])\n",
    "                text = text[:-1]+'\\n' # replace last tab with newline\n",
    "                \n",
    "                for ei in range(nEbins):\n",
    "                    text += '{0:.8E}\\t{1:.8E}\\t{2:.8E}\\t'.format(GCR_flux[0,0,ei],GCR_flux[0,1,ei],GCR_flux[0,2,ei])\n",
    "                    for zii in zi_list:\n",
    "                        text += '{0:.8E}\\t'.format(GCR_flux[zii,3,ei])\n",
    "                    text = text[:-1]+'\\n' # replace last tab with newline\n",
    "        \n",
    "            if j!=0: # Individual ions\n",
    "                text = \"\"\n",
    "                text += column_headers[0]+'\\t'+column_headers[1]+'\\t'+column_headers[2]+'\\t'+column_headers[3]+'\\n'\n",
    "                for ei in range(nEbins):\n",
    "                    text += '{0:.8E}\\t{1:.8E}\\t{2:.8E}\\t{3:.8E}\\n'.format(GCR_flux[zi,0,ei],GCR_flux[zi,1,ei],GCR_flux[zi,2,ei],GCR_flux[zi,3,ei])\n",
    "        \n",
    "        if i==1: # MCNP spectra\n",
    "            MCNP6_str =  'c Notes:' +  '\\n'\n",
    "            MCNP6_str += 'c   The listed energy bins should be ready to use for your application.' +  '\\n'\n",
    "            MCNP6_str += \"c   This source term assumes a large spherical shell geometry for GCRs\" + '\\n'\n",
    "            MCNP6_str += \"c     isotropically impingent on a planet's atmosphere.\" + '\\n'\n",
    "            MCNP6_str += 'c   Change the geometric and angular portions of the source card to fit your usage.' + '\\n'\n",
    "            MCNP6_str += 'c ' +  '\\n'\n",
    "            MCNP6_str += 'c Source' +  '\\n'\n",
    "            MCNP6_str += ' SDEF PAR='+ZZZAAA[zi]+' ERG=D1 SUR=999 NRM = -1  AXS = 0 0 1  EXT = D90\\n'\n",
    "            MCNP6_str += ' SI90      -1 0 1           ' +  '\\n'\n",
    "            MCNP6_str += ' SP90      0 0.5 0.5        ' +  '\\n'\n",
    "            MCNP6_str += ' #  SI1      SP1' +  '\\n'\n",
    "            MCNP6_str += \"    %.8E\" % (GCR_flux[zi,0,0]*A_list[zi])+\" 0.0 \\n\"\n",
    "            for ei in range(nEbins):\n",
    "                if ei==0: continue\n",
    "                de = (GCR_flux[zi,2,ei]-GCR_flux[zi,2,ei-1])*A_list[zi]\n",
    "                MCNP6_str += \"    %.8E\" % (GCR_flux[zi,2,ei]*A_list[zi]) +\" %.8E\" % (GCR_flux[zi,3,ei]*de) +'\\n'\n",
    "            text = MCNP6_str\n",
    "        \n",
    "        if i==2: # PHITS spectra\n",
    "            PHITS_str =  '# Notes:' +  '\\n'\n",
    "            PHITS_str += \"#   The entry 'iMeVperu = 1' must be set in your [PARAMETERS] card.\" + \"\\n\"\n",
    "            PHITS_str += '#   The listed energy bins should be ready to use for your application.' +  '\\n'\n",
    "            PHITS_str += \"#   This source term assumes a large spherical shell geometry for GCRs\" + '\\n'\n",
    "            PHITS_str += \"#     isotropically impingent on a planet's atmosphere.\" + '\\n'\n",
    "            PHITS_str += '#   Change the geometric and angular portions of the source card to fit your usage.' + '\\n'\n",
    "            PHITS_str += '# ' +  '\\n'\n",
    "            PHITS_str += \"[ S o u r c e ]\" + \"\\n\"\n",
    "            PHITS_str += \"   s-type =   9             # sperical shell source with energy distribution (should be =10 if using version before 2.94)\" + \"\\n\"\n",
    "            PHITS_str += \"     proj =   \"+all_iso_strs[zi]+\"       \" + \"\\n\"\n",
    "            PHITS_str += \"       r1 =   {:.8e}\".format(3.48707700e8)+\"   # inner radius [cm]\" + \"\\n\"\n",
    "            PHITS_str += \"       r2 =   {:.8e}\".format(3.48707700e8)+\"   # outer radius [cm]\" + \"\\n\"\n",
    "            PHITS_str += \"       x0 =   0.0000        # center position of x-axis [cm]\" + \"\\n\"\n",
    "            PHITS_str += \"       y0 =   0.0000        # center position of y-axis [cm]\" + \"\\n\"\n",
    "            PHITS_str += \"       z0 =   0.0000        # center position of z-axis [cm]\" + \"\\n\"\n",
    "            PHITS_str += \"      dir =   iso           # inward isotropic distribution\" + \"\\n\"\n",
    "            PHITS_str += \"   e-type =   21            # differential probability, dphi/dE\" + \"\\n\"\n",
    "            PHITS_str += \"       ne =   \"+str(nEbins)+\"          # number of energy bins\" + \"\\n\"\n",
    "     \n",
    "            for ei in range(nEbins):\n",
    "                PHITS_str += \"       %.8E\" % (GCR_flux[zi,0,ei]) +' %.8E' % (GCR_flux[zi,3,ei]) +'\\n'\n",
    "            PHITS_str += \"       %.8E\" % (GCR_flux[zi,2,-1]) +'\\n'\n",
    "            text = PHITS_str\n",
    "        \n",
    "        \n",
    "        plotted_spectra_text[i].append(text)\n",
    "        \n",
    "        \n",
    "#print(mm_raw_text[0,2,0,0,0,0,0])\n",
    "\n",
    "tab_names = ['Experiment','MCNP','PHITS']\n",
    "tab_accordions = [[],[],[]]\n",
    "accordions_list = []\n",
    "\n",
    "\n",
    "save_file_buttons_list = [[],[],[]]\n",
    "\n",
    "for i in range(len(plotted_spectra_names)):\n",
    "    for j in range(len(plotted_spectra_names[i])):\n",
    "        text = '<font size=\"2\"><p style=\"line-height:1.4; font-family: monospace\">' + plotted_spectra_text[i][j].replace('\\n','<br>') + '</p></font>'\n",
    "        textbox = w.HBox([w.HTML(value=text)], layout=w.Layout(height='400px', overflow_y='auto',width='1800px', overflow_x='auto'))\n",
    "        \n",
    "        save_file_buttons_list[i].append(gen_generic_save_file_button())\n",
    "        #save_file_buttons_list[i][j].on_click(on_click_save_a_text_file)\n",
    "        \n",
    "        tab_accordions[i].append(w.VBox([textbox,save_file_buttons_list[i][j]]))\n",
    "        \n",
    "        \n",
    "        \n",
    "    temp_acc = w.Accordion(children=tab_accordions[i],selected_index=None) # ,layout=w.Layout(collapsed=True)\n",
    "    for j in range(len(plotted_spectra_names[i])):\n",
    "        temp_acc.set_title(j, plotted_spectra_names[i][j])\n",
    "        \n",
    "    accordions_list.append(temp_acc)\n",
    "\n",
    "\n",
    "tab_nest = w.Tab()\n",
    "tab_nest.children = accordions_list\n",
    "tab_nest.set_title(0, tab_names[0])\n",
    "tab_nest.set_title(1, tab_names[1])\n",
    "tab_nest.set_title(2, tab_names[2])\n",
    "\n",
    "display(tab_nest)\n",
    "\n",
    "# Save individual files\n",
    "\n",
    "# make individual save functions\n",
    "save_funcions_array = [[],[],[]]\n",
    "for i in range(len(plotted_spectra_names)):\n",
    "    for j in range(len(plotted_spectra_names[i])):\n",
    "        fname = r'text_files/' + plotted_spectra_names[i][j] + '.txt'\n",
    "        fcontents = plotted_spectra_text[i][j]\n",
    "        update_print_str = 'Text file saved to: '+ fname\n",
    "        def function_builder(fname,fcontents,update_print_str):\n",
    "            def on_click_save_a_text_file(change):\n",
    "                f = open(fname,'w')\n",
    "                f.write(fcontents)\n",
    "                f.close()\n",
    "                print(update_print_str) # print saved note\n",
    "            return on_click_save_a_text_file\n",
    "        save_funcions_array[i].append(function_builder(fname,fcontents,update_print_str))\n",
    "        \n",
    "        save_file_buttons_list[i][j].on_click(save_funcions_array[i][j])\n",
    "\n",
    "# Save files in a ZIP archive\n",
    "\n",
    "window_title = 'All_GCR_spectra_files'\n",
    "\n",
    "save_text_button = w.Button(\n",
    "    description='Save text (ZIP)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save text files of all GCR spectra in a ZIP archive in the local text_files/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "save_text_button.on_click(on_click_save_text_files)\n",
    "save_text_extra_label = w.Label(value='(All above text files are archived into a single ZIP file when saved.)')\n",
    "\n",
    "display(w.HBox([save_text_button,save_text_extra_label]))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"950\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting\n",
    "\n",
    "fig = plt.figure()\n",
    "bg_color = '#E1E4E6'\n",
    "fig.patch.set_facecolor(bg_color)\n",
    "fig.patch.set_alpha(1.0)\n",
    "l_corner_logo_text = 'plot generated by GCR SpecGen'\n",
    "l_corner_logo_fs = 8\n",
    "r_corner_logo_text = 'github.com/Lindt8/GCR_SpecGen'\n",
    "r_corner_logo_fs = 6\n",
    "fig.text(0.005,0.005,l_corner_logo_text,fontsize=l_corner_logo_fs,horizontalalignment='left',verticalalignment='bottom')\n",
    "fig.text(0.995,0.005,r_corner_logo_text,fontsize=r_corner_logo_fs,horizontalalignment='right',verticalalignment='bottom')\n",
    "ax = plt.subplot(111)\n",
    "for i in range(28):\n",
    "    if i not in zi_list: continue\n",
    "    Z = i+1\n",
    "    legstr = 'Z='+str(Z)+' (' + all_Z_strs[i] + ')' # all_iso_strs_TeX[i]\n",
    "    plt.plot(GCR_flux[i,1,:],GCR_flux[i,3,:],label=legstr)\n",
    "\n",
    "\n",
    "# hangle figure/legend positioning/sizing\n",
    "# First, figure size\n",
    "default_fig_x_in = 9.5\n",
    "default_fig_y_in = 6.5\n",
    "\n",
    "# first, try getting widget widths from below; otherwise, use defaults\n",
    "if currently_updating_fig_dims:\n",
    "    fig_x_in = adjust_w_slider.value\n",
    "    fig_y_in = adjust_h_slider.value\n",
    "else:\n",
    "    fig_x_in = default_fig_x_in\n",
    "    fig_y_in = default_fig_y_in\n",
    "\n",
    "fig.set_size_inches(fig_x_in,fig_y_in)\n",
    "    \n",
    "legend_type = 'outside_right'\n",
    "if legend_type == 'outside_right':\n",
    "    # Add primary legend\n",
    "    leg1_anchor = (1.0, 1.05) # varied items \n",
    "    handles_l1, labels_l1 = ax.get_legend_handles_labels()\n",
    "    # remove the errorbars\n",
    "    if len(handles_l1)>0:\n",
    "        handles_l1 = [h for h in handles_l1]\n",
    "        legend1 = ax.legend(handles_l1, labels_l1,loc='upper left',bbox_to_anchor=leg1_anchor,ncol=1)\n",
    "        ax.add_artist(legend1)\n",
    "        # Change marker in legend\n",
    "        #for l in legend1.get_lines():\n",
    "        #    #l.set_alpha(1)\n",
    "        #    l._legmarker.set_marker('s')\n",
    "        #    l._legmarker.set_markersize(12)\n",
    "    \n",
    "\n",
    "good_to_go = True\n",
    "if good_to_go: # stuff that will error out code on first initialization\n",
    "    fig.canvas.draw()\n",
    "    f1 = legend1.get_frame()\n",
    "    l1_w0_px, l1_h0_px = f1.get_width(), f1.get_height()\n",
    "    l_w0_in, l_h0_in = l1_w0_px/fig.dpi, l1_h0_px/fig.dpi # max legend dimensions in inches\n",
    "    \n",
    "    # Determine relative dimensions of plot\n",
    "    x0bar = 0.8075 # inches, horizontal space needed for ylabel\n",
    "    y0bar = 0.6500 # inches, vertical space needed for xlabel alone\n",
    "    t0bar = 0.4000 # inches, vertical space needed for title\n",
    "    del_l_in = 0.15 # inches, extra horizontal padding right of legend\n",
    "\n",
    "    x0 = x0bar/fig_x_in\n",
    "    y0 = y0bar/fig_y_in\n",
    "    h0 = 1 - (y0bar+t0bar)/fig_y_in\n",
    "    w0 = 1 - x0 - (l_w0_in/fig_x_in) - (del_l_in/fig_x_in)\n",
    "    \n",
    "    # Set size and location of the plot on the canvas\n",
    "    box = ax.get_position()\n",
    "    # all vals in [0,1]: left, bottom, width, height\n",
    "    ax.set_position([x0, y0, w0, h0])\n",
    "    \n",
    "    \n",
    "plt.xlabel('Energy [MeV/n]')\n",
    "plt.ylabel(r'Flux [(s$\\cdot$sr$\\cdot$cm$^2\\cdot$MeV/n)$^{-1}$]')\n",
    "title_text = 'GCR flux for W={:g}'.format(W)\n",
    "plt.title(title_text)\n",
    "#plt.legend(loc='best')\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "plt.grid(b=True, which='major', linestyle='-', alpha=0.25)\n",
    "plt.grid(b=True, which='minor', linestyle='-', alpha=0.10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "  Widgets Documentation</a> for setup instructions.\n",
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       "</p>\n"
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       "HBox(children=(Label(value='Zooming in can be freely done within the interactive plot.  This button zooms out the default view.'), Button(description='Zoom out', icon='search-minus', style=ButtonStyle(), tooltip='While you can freely zoom in to any rectangle on the interactive plot, there is no way to zoom out from the starting view.  This solves that issue.')))"
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      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Label</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"
      ],
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       "Label(value='Adjust figure dimensions via sliders or text boxes (all units in inches, minimum dimension = 1\", maximum dimension = 10\").')"
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     },
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      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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",
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       "</p>\n"
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       "HBox(children=(FloatSlider(value=9.5, description='width (in.)', max=10.0, min=1.0), FloatSlider(value=6.5, description='height (in.)', max=10.0, min=1.0), Button(button_style='info', description='Reset sliders', icon='exclamation', style=ButtonStyle(), tooltip='Click to reset sliders to default values.'), Button(button_style='success', description='Refresh plot', icon='refresh', style=ButtonStyle(), tooltip='Click to redraw the plot with updated dimensions.')))"
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      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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",
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       "HBox(children=(FloatText(value=0.0, step=0.1), FloatText(value=0.0, step=0.1)))"
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      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</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"
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      "text/plain": [
       "HBox(children=(Button(button_style='success', description='Save plot (PDF)', icon='save', style=ButtonStyle(), tooltip='Save plot as PDF in local images/ folder'), Button(button_style='success', description='Save plot (PNG)', icon='save', style=ButtonStyle(), tooltip='Save plot as PNG in local images/ folder'), Button(button_style='success', description='Save plot (SVG)', icon='save', style=ButtonStyle(), tooltip='Save plot as SVG in local images/ folder')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "save_plot_button_pdf = w.Button(\n",
    "    description='Save plot (PDF)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as PDF in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "save_plot_button_png = w.Button(\n",
    "    description='Save plot (PNG)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as PNG in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "save_plot_button_svg = w.Button(\n",
    "    description='Save plot (SVG)',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Save plot as SVG in local images/ folder',\n",
    "    icon='save' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "\n",
    "currently_updating_fig_dims = True\n",
    "adjust_label = w.Label(value=\"Adjust figure dimensions via sliders or text boxes (all units in inches, minimum dimension = 1\\\", maximum dimension = 10\\\").\")\n",
    "\n",
    "adjust_w_slider = w.FloatSlider(\n",
    "    description='width (in.)',\n",
    "    min=1,\n",
    "    max=10,\n",
    "    value = fig_x_in,\n",
    ")\n",
    "adjust_w_text = w.FloatText(step=0.1)\n",
    "\n",
    "adjust_h_slider = w.FloatSlider(\n",
    "    description='height (in.)',\n",
    "    min=1,\n",
    "    max=10,\n",
    "    value = fig_y_in,\n",
    ")\n",
    "\n",
    "reset_sliders_button = w.Button(\n",
    "    description='Reset sliders',\n",
    "    disabled=False,\n",
    "    button_style='info', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to reset sliders to default values.',\n",
    "    icon='exclamation' # pencil, rotate-right, paint-brush\n",
    ")\n",
    "adjust_h_text = w.FloatText(step=0.1)\n",
    "\n",
    "refresh_plot_button2 = w.Button(\n",
    "    description='Refresh plot',\n",
    "    disabled=False,\n",
    "    button_style='success', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='Click to redraw the plot with updated dimensions.',\n",
    "    icon='refresh' # pencil, rotate-right, paint-brush\n",
    ")\n",
    "\n",
    "zoom_mult = 1 # reset zoom value\n",
    "zoom_out_label = w.Label(value='Zooming in can be freely done within the interactive plot.  This button zooms out the default view.')\n",
    "zoom_out_button = w.Button(\n",
    "    description='Zoom out',\n",
    "    disabled=False,\n",
    "    button_style='', # 'success', 'info', 'warning', 'danger' or ''\n",
    "    tooltip='While you can freely zoom in to any rectangle on the interactive plot, there is no way to zoom out from the starting view.  This solves that issue.',\n",
    "    icon='search-minus' # pencil, rotate-right\n",
    ")\n",
    "\n",
    "display(w.HBox([zoom_out_label,zoom_out_button]))\n",
    "zoom_out_button.on_click(on_click_zoom_out)\n",
    "\n",
    "display(adjust_label)\n",
    "display(w.HBox([adjust_w_slider,adjust_h_slider,reset_sliders_button,refresh_plot_button2]))\n",
    "display(w.HBox([adjust_w_text,adjust_h_text]))\n",
    "w_link = w.jslink((adjust_w_slider, 'value'), (adjust_w_text, 'value'))\n",
    "h_link = w.jslink((adjust_h_slider, 'value'), (adjust_h_text, 'value'))\n",
    "reset_sliders_button.on_click(on_click_reset_sliders)\n",
    "refresh_plot_button2.on_click(on_click_refresh_plot)\n",
    "\n",
    "#PDF_box = w.HBox([PDF_label,save_plot_button,save_plot_button_wbg],layout=w.Layout(width='380px')) \n",
    "#PNG_box = w.HBox([PNG_label,save_plot_button_png,save_plot_button_wbg_png])\n",
    "#save_buttons_box = w.Box([PDF_box,PNG_box])\n",
    "#save_buttons_box.layout.justify_content='space-around'\n",
    "display(w.HBox([save_plot_button_pdf,save_plot_button_png,save_plot_button_svg]))\n",
    "\n",
    "save_plot_button_pdf.on_click(on_click_save_plot_pdf)\n",
    "save_plot_button_png.on_click(on_click_save_plot_png)\n",
    "save_plot_button_svg.on_click(on_click_save_plot_svg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Special notes on saving plots and text files\n",
    "\n",
    "##### For users online on the Binder build of this notebook:\n",
    "\n",
    "The save buttons will generate the PDFs/PNGs/SVGs in the [``images``](images/) folder of the repository window (the page on which you clicked the ``SHAEDIT.ipynb`` link to arrive here), but you must download them locally yourself before you leave the site because they will be erased once your Binder session is ended.  \n",
    "\n",
    "The plots can also be saved directly to your computer as a PNGs (regardless of where you are viewing the data from), by clicking the little power button ( &#9211; ) in the top right of the figure, right clicking the image, and then clicking \"Save image as...\" to save it to a local folder. \n",
    "\n",
    "Any saved text files or ZIP archives will be stored in the [``text_files``](text_files/) folder of the repository window, and you must manually download any files from that folder before leaving the site if you wish to keep them since they will otherwise be deleted automatically once the session is ended. \n",
    "\n",
    "Files can be downloaded from the repository window (and its folders) by checking the checkbox(es) to the left of the file(s) you wish to download and then clicking the Download button above the files interface.\n",
    "\n",
    "##### For users viewing this notebook locally:\n",
    "You will know if you are viewing this locally since it would had required downloading this whole repository and installing python, jupyter, and all libraries this notebook depends on.  Additionally, your URL should look something like ``localhost:8888/notebooks/GCR%20SpecGen.ipynb`` if viewing locally.\n",
    "\n",
    "If you wish to save a plot with the above buttons, you must create a folder titled [``images``](images/) within the main directory which holds this notebook and the data files it relies on; plots will be saved in that [``images``](images/) folder with descriptive filenames resembling the plot title.   \n",
    "\n",
    "Likewise, for saving individual text files or ZIP archives of all plotted files, you must generate a [``text_files``](text_files/) folder within the main directory containing this notebook.\n",
    "\n",
    "\n",
    "### Binder session duration information (relevant to online viewing only)\n",
    "\n",
    "Binder sessions will automatically close (deleting all extra files generated by this code) if it detects 10 minutes of inactivity, though [the Binder FAQ](https://mybinder.readthedocs.io/en/latest/faq.html#how-long-will-my-binder-session-last) states that keeping the window open serves as staying active.  Since a lost connection can cause Binder to believe this notebook is no longer active, resulting in it being closed, it is advisable that any files generated with the Save buttons ( &#128190; ) are downloaded from their subdirectories ([``images``](images/) and/or [``text_files``](text_files/)) of the main repository window in the same sitting in which they were generated.  \n",
    "\n",
    "Additionally, while it may be possible for a Binder session to remain open for a long time, it is suggested to close the notebook tabs when done and then reload the notebook at the start of each sitting by visiting https://mybinder.org/v2/gh/Lindt8/GCR_SpecGen/master, allowing Binder to build the most up-to-date version of this code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>GCR SpecGen was written by Hunter Ratliff at the University of Tennessee, Knoxville, Department of Nuclear Engineering. <br />\n",
    "    Copyright &#169; 2018 Hunter Ratliff (Lindt8)  [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2573359.svg)](https://doi.org/10.5281/zenodo.2573359)</center> \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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