{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8f84b965",
   "metadata": {},
   "outputs": [],
   "source": [
    "# this example requires that ENDFtk and ACEtk be installed as well\n",
    "import ENDFtk\n",
    "import ACEtk\n",
    "import scion\n",
    "\n",
    "import matplotlib.pyplot as plot\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b44313bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# the files we want to look at\n",
    "endffile = 'resources/n-001_H_001-endf80.endf'\n",
    "acefile = 'resources/n-001_H_001-endf80.ace'    # Lib80x at 0.1 K (1001.805c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "baebe2f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# a few functions we need (these will be integrated into scion when from_endf(...) becomes available)\n",
    "\n",
    "# convert to the proper Legendre coefficients\n",
    "def convert( coefficients ) :\n",
    "    \n",
    "    converted = [ 0.5 ]\n",
    "    for i in range( 1, len( coefficients ) + 1 ) :\n",
    "        \n",
    "        converted.append( ( 2 * i + 1 ) / 2 * coefficients[i - 1] )\n",
    "    \n",
    "    return converted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e1038229",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number incident energies:  153\n"
     ]
    }
   ],
   "source": [
    "# open the ENDF file and retrieve the capture cross section\n",
    "tape = ENDFtk.tree.Tape.from_file( endffile )\n",
    "endf_elastic = tape.materials.front().file( 4 ).section( 2 ).parse()\n",
    "\n",
    "print( 'number incident energies: ', len( endf_elastic.angular_distributions ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5301f234",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "order:  6\n",
      "coefficients:  [0.5, -0.02419452, 0.0195173075, -0.0027194370000000003, 0.0016944974999999998, 5.2521997e-05, 4.48370065e-05]\n"
     ]
    }
   ],
   "source": [
    "# retrieve the ENDF data for 20 MeV\n",
    "index = -1\n",
    "\n",
    "incident_energy = endf_elastic.incident_energies[index]\n",
    "endf_legendre = scion.math.LegendreSeries( convert( endf_elastic.angular_distributions[index].coefficients ) )\n",
    "\n",
    "print( 'order: ', endf_legendre.order )\n",
    "print( 'coefficients: ', endf_legendre.coefficients )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "43b81161",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "zaid:  1001.805nc\n",
      "temperature:  8.6174e-12\n",
      "number points:  8\n"
     ]
    }
   ],
   "source": [
    "# open the ACE file and retrieve the elastic angular distribution data\n",
    "ace = ACEtk.ContinuousEnergyTable.from_file( acefile )\n",
    "\n",
    "# reaction index = 0 for elastic (it's an ACE things)\n",
    "ace_elastic = ace.angular_distribution_block.angular_distribution_data( 0 ).distributions[index]\n",
    "\n",
    "print( 'zaid: ', ace.header.zaid )\n",
    "print( 'temperature: ', ace.header.temperature )\n",
    "print( 'number points: ', len( ace_elastic.cosines ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b138247b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# linearise the pdf at different tolerances\n",
    "plot1 = endf_legendre.linearise( scion.linearisation.ToleranceConvergence( .0025 ) )\n",
    "plot2 = endf_legendre.linearise( scion.linearisation.ToleranceConvergence( .0001 ) )\n",
    "\n",
    "# plot the data\n",
    "plot.figure()\n",
    "plot.plot( ace_elastic.cosines, ace_elastic.pdf, label = 'Lib80x', color = 'red', linewidth = 1.5 )\n",
    "plot.plot( plot1.x, plot1.y, label = 'scion - 0.25 % tolerance', color = 'blue', linewidth = 1.5 )\n",
    "plot.plot( plot2.x, plot2.y, label = 'scion - 0.01 % tolerance', color = 'orange', linewidth = 1.5 )\n",
    "plot.xlabel( 'Cosine' )\n",
    "plot.ylabel( 'Angular distribution pdf' )\n",
    "plot.title( 'ENDF/B-VIII.0 H1 elastic angular distribution at $E_{in}$ = 20 MeV' )\n",
    "plot.yscale( 'log' )\n",
    "plot.legend()\n",
    "plot.show()\n",
    "plot.savefig('test.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6246c705",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "9\n",
      "37\n"
     ]
    }
   ],
   "source": [
    "print( len( ace_elastic.cosines ) )\n",
    "print( len( plot1.x ) )\n",
    "print( len( plot2.x ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fa32a13e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can linearise the cdf directly based on the primitive of the pdf as a Legendre series\n",
    "endf_cdf = endf_legendre.primitive( -1.0 ) # the integral[-1,x] of the endf_legendre series\n",
    "\n",
    "plot1 = endf_cdf.linearise( scion.linearisation.ToleranceConvergence( .0025 ) )\n",
    "plot2 = endf_cdf.linearise( scion.linearisation.ToleranceConvergence( .0001 ) )\n",
    "\n",
    "# plot the data\n",
    "plot.figure()\n",
    "plot.plot( ace_elastic.cosines, ace_elastic.cdf, label = 'Lib80x', color = 'red', linewidth = 1.5 )\n",
    "plot.plot( plot1.x, plot1.y, label = 'scion - 0.25 % tolerance', color = 'blue', linewidth = 1.5 )\n",
    "plot.plot( plot2.x, plot2.y, label = 'scion - 0.01 % tolerance', color = 'orange', linewidth = 1.5 )\n",
    "plot.xlabel( 'Cosine' )\n",
    "plot.ylabel( 'Angular distribution cdf' )\n",
    "plot.title( 'ENDF/B-VIII.0 H1 elastic angular distribution at $E_{in}$ = 20 MeV' )\n",
    "plot.yscale( 'log' )\n",
    "plot.legend()\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "75b1c512",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "9\n",
      "44\n"
     ]
    }
   ],
   "source": [
    "print( len( ace_elastic.cosines ) )\n",
    "print( len( plot1.x ) )\n",
    "print( len( plot2.x ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4a1fdcd4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "roots:  []\n"
     ]
    }
   ],
   "source": [
    "# we can verify that the pdf never goes below zero in [-1,1] by calculating the roots of the pdf on the real axis\n",
    "print( 'roots: ', endf_legendre.roots() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "57d3c6e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "roots:  []\n"
     ]
    }
   ],
   "source": [
    "# we can verify that the cdf is monotonically increasing in [-1,1] by calculating the roots of the \n",
    "# first derivative of the cdf on the real axis and showing that the derivative is always above zero\n",
    "# and yes: I know that boils down to calculating the roots of the pdf but I'm flexing the interface here :-)\n",
    "print( 'roots: ', endf_legendre.primitive( -1 ).derivative().roots() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "71c89e73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min and max distance points:  [-0.13715028896666442]\n"
     ]
    }
   ],
   "source": [
    "# more fun: calculate the point where the distance between the pdf and the linear approximation is highest\n",
    "x = [ -1, 1 ]\n",
    "y = [ endf_legendre(-1), endf_legendre(1) ]\n",
    "\n",
    "slope = ( y[1] - y[0] ) / ( x[1] - x[0] )\n",
    "\n",
    "# the distance between the line and the actual pdf is maximum where d/dx( f(x) - slope * x + b ) = 0\n",
    "# or df/dx = slope\n",
    "cosines = endf_legendre.derivative().roots( a = slope )\n",
    "print( 'min and max distance points: ', cosines )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "41befb64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cosines += [ -1., 1. ]\n",
    "cosines.sort()\n",
    "values = [ endf_legendre( cosine ) for cosine in cosines ]\n",
    "\n",
    "plot2 = endf_legendre.linearise( scion.linearisation.ToleranceConvergence( .0001 ) )\n",
    "\n",
    "# plot the data\n",
    "plot.figure()\n",
    "plot.plot( plot2.x, plot2.y, label = 'scion - 0.01 % tolerance', color = 'red', linewidth = 1.5 )\n",
    "plot.plot( x, y, label = 'two points', color = 'blue', linewidth = 1.5 )\n",
    "plot.plot( cosines, values, label = 'three points', color = 'orange', linewidth = 1.5 )\n",
    "plot.xlabel( 'Cosine' )\n",
    "plot.ylabel( 'Angular distribution pdf' )\n",
    "plot.title( 'ENDF/B-VIII.0 H1 elastic angular distribution at $E_{in}$ = 20 MeV' )\n",
    "plot.yscale( 'linear' )\n",
    "plot.legend()\n",
    "plot.show()\n",
    "plot.savefig('test.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5eafd935",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.0003293997516063407\n",
      "-0.026861435003000006\n",
      "-0.02686143500299989\n"
     ]
    }
   ],
   "source": [
    "distance = endf_legendre( cosines[1] ) - ( slope * ( x[1] - x[0] ) + y[0] )\n",
    "\n",
    "print( distance )\n",
    "print( slope )\n",
    "print( endf_legendre.derivative()( cosines[1] ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "976efe88",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
