OMM1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Урсов Эдуард, 314 группа"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Постановка задачи. 2 вариант\n",
    "Используя схему бегущего счета и итерационные методы, решить задачу для квазилинейного уравнением переноса:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\\begin{eqnarray}\n",
    " \\begin{cases}\n",
    "   \\frac{\\partial u}{\\partial t} - u \\frac{\\partial u}{\\partial x} = 0, ~~-1 \\leq x < 0\n",
    "   \\\\\n",
    "   u(x, 0) = 2 - \\frac{4}{\\pi} arctg(x+2)\n",
    "   \\\\\n",
    "   u(0, t) = (2 - \\frac{4}{\\pi} arctg(2)) e^{-t}\n",
    " \\end{cases}\n",
    "\\end{eqnarray}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Исследование характеристик\n",
    "Уравнение характеристик для данного уравнения будет иметь вид:\n",
    "\\begin{eqnarray}\n",
    "    \\frac{dt}{1} = \\frac{dx}{-u} = \\frac{du}{0} \\Longrightarrow u = u^{*} = const  \\Longrightarrow t - t^{*} = \\frac{x - x^{*}}{-u^{*}}\n",
    "\\end{eqnarray}\n",
    "НУ и ГУ:\n",
    "\\begin{equation}\n",
    "    1) t^{*} = 0 \\Longrightarrow t = (x - x^{*})\\frac{1}{-u^{*}} = \\frac{x - x^{*}}{-(2 - \\frac{4}{\\pi} arctg(x^{*}+2))}\n",
    "    \\\\\n",
    "    2) x^{*} = 0 \\Longrightarrow t = t^{*} - \\frac{x}{u^{*}} = t^{*} -\\frac{x}{(2 - {\\frac{4}{\\pi} arctg(2)) e^{-t^{*}}}}\n",
    "\\end{equation}\n",
    "В точках пересечения характеристик решение будет разрывным. Построим уравнения характеристик и узнаем, есть ли где-то пересечения."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from math import *\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "\n",
    "\n",
    "def IC(x):\n",
    "    return [((x0-x)/(2-4/pi*np.arctan(x0 + 2))) for x0 in np.arange(-10,0.1,0.1)]\n",
    "def BC(x):\n",
    "    return [(t0 - x*exp(t0)/(2-4/pi*np.arctan(2))) for t0 in np.arange(0,10,0.1)]         \n",
    "Xarr = np.arange(-5,0.1,0.1)\n",
    "t1arr = [IC(x) for x in Xarr]\n",
    "t2arr = [BC(x) for x in Xarr]\n",
    "%matplotlib notebook\n",
    "plt.plot(Xarr, t1arr, Xarr, t2arr) \n",
    "plt.ylim(0,5)\n",
    "plt.xlim(-5,0)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('t')\n",
    "\n",
    "\n",
    "plt.show()            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В области $-1 \\leq x < 0$ характеристики не пересекаются. Да и вообще при $x < 0$ характеристики не пересекаются"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Аналитическое решение\n",
    "Мы получили два семейства характеристик. Получим аналитическое (численно) решение задачи, составив и численно решив два неявных уравнения относительно $u^{*}$:\n",
    "\\begin{eqnarray}\n",
    " \\begin{cases}\n",
    "   \\ln{u^{*}} + t - \\ln{(2 - \\frac{4}{\\pi} \\arctan{2})} = -\\frac{x}{u*} ~~ t > -\\frac{x}{2 - \\frac{4}{\\pi} \\arctan{2}}\n",
    "   \\\\\n",
    "   -tu^{*} = 2 + x + \\tan{(\\frac{\\pi}{4}(u^{*} - 2))} ~~ t \\leq -\\frac{x}{2 - \\frac{4}{\\pi} \\arctan{2}}\n",
    " \\end{cases}\n",
    " \\\\\n",
    " 2 - \\frac{4}{\\pi} \\arctan{2} \\approx 0.59\n",
    "\\end{eqnarray}\n",
    "## Библиотеки\n",
    "Для построения численного и аналитического решения нам понадобятся следующие библиотеки:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from math import *\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "from matplotlib import animation\n",
    "import plotly\n",
    "import plotly.graph_objs as go\n",
    "import warnings\n",
    "\n",
    "from IPython.display import clear_output, HTML, display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Сетка\n",
    "Введем в области $\\Omega = \\{(x, t ): -1 \\leq x < 0, ~~0 < t < T \\}$ сетку с шагом $h$ по $x$ и с шагом $\\tau$ по $t$: \n",
    "\\begin{eqnarray}\n",
    " \\omega_{h, ~ \\tau}=\\begin{cases}\n",
    "x_n=n\\cdot h, ~~h=-\\frac{1}{N}, ~~n=\\overline{0, N}\\\\\n",
    "t_m=m\\cdot \\tau, ~~\\tau=\\frac{1}{M}, ~~m=\\overline{0, M}\n",
    "\\end{cases}\n",
    "\\end{eqnarray}\n",
    "Имеем сеточную функцию $y^m_{n}=u(x_n,t_m)$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Настройки\n",
    "Введем различные параметры, необходимые для численного решения:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "epsilon = 0.00001 # точность в методе Ньютона\n",
    "N = 20; M = 20 # количество шагов по x и t соответственно\n",
    "T_begin = 0; T_end = 5 # границы по x и t\n",
    "X_begin = 0; X_end = -1\n",
    "h = (X_end - X_begin)/(N-1)\n",
    "tau = (T_end - T_begin)/(M-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Определим функцию, которая будет строить графики:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotly.offline.init_notebook_mode(connected=True)\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib notebook\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "tm = np.linspace(T_begin,T_end, num=M)\n",
    "xn = np.linspace(X_begin, X_end, num=N)\n",
    "X, T = np.meshgrid(xn, tm)\n",
    "def plot_u(X1, T1, y1, filename='/home/eduard/Desktop/', online=True):\n",
    "        '''\n",
    "        Функция, который строит 3D график численного решения.\n",
    "        '''\n",
    "        X0 = X1\n",
    "        T0 = T1\n",
    "        u = y1\n",
    "        data = [go.Surface(x = X0, y = T0, z = u, colorscale = 'YlGnBu')]\n",
    "        # Наведем красоту\n",
    "        layout = go.Layout(\n",
    "                    scene = dict(\n",
    "                    xaxis = dict(\n",
    "                        title='x',\n",
    "                        gridcolor=\"rgb(255, 255, 255)\",\n",
    "                        zerolinecolor=\"rgb(255, 255, 255)\",\n",
    "                        showbackground=True,\n",
    "                        backgroundcolor=\"rgb(200, 200, 230)\"),\n",
    "                        \n",
    "                    yaxis = dict(\n",
    "                        title='t',\n",
    "                        gridcolor=\"rgb(255, 255, 255)\",\n",
    "                        zerolinecolor=\"rgb(255, 255, 255)\",\n",
    "                        showbackground=True,\n",
    "                        backgroundcolor=\"rgb(230, 200,230)\"),\n",
    "                        \n",
    "                    zaxis = dict(\n",
    "                        title='u(x, t)',\n",
    "                        gridcolor=\"rgb(255, 255, 255)\",\n",
    "                        zerolinecolor=\"rgb(255, 255, 255)\",\n",
    "                        showbackground=True,\n",
    "                        backgroundcolor=\"rgb(230, 230,200)\",),),\n",
    "                    width=800, height=600, \n",
    "                    margin=dict(\n",
    "                    r=20, b=10,\n",
    "                    l=10, t=10)\n",
    "                  )\n",
    "\n",
    "        fig = go.Figure(data = data, layout = layout)\n",
    "        if  online:\n",
    "            return plotly.offline.iplot(fig, filename = filename)  # построение графика оффлайн влечет за собой\n",
    "                                        # большой вес ноутбука, но построение почти мгновенное"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Код, строящий аналитическое решение"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "responsive": true,
        "showLink": false
       },
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   "source": [
    "# создаем массив размером (M x N) из начальных приближений\n",
    "y0 = np.ones((M,N)) * 0.01\n",
    "for n in np.arange(N):\n",
    "        y0[0][n] = (2 - (4/np.pi)*np.arctan(h*n + 2))\n",
    "\n",
    "for m in np.arange(M):\n",
    "        y0[m][0] = (2 - (4/np.pi)*np.arctan(2))*exp(-tau * m)\n",
    "def F1(m, k):\n",
    "    return np.log(y0[m][k]) + tau*m - np.log(0.59) + h*k/y0[m][k]\n",
    "def dF1(m, k):\n",
    "    return 1/y0[m][k] - h*k/(y0[m][k])**2\n",
    "def F2(m, k):\n",
    "    return tau*m*y0[m][k] + 2 + h*k + np.tan((np.pi/4)*(y0[m][k] - 2))\n",
    "def dF2(m, k):\n",
    "    return tau*m + 1/(np.cos((np.pi/4)*(y0[m][k] - 2)))**2\n",
    "\n",
    "# метод Ньютона для каждой точки сетки\n",
    "eps = epsilon + 1\n",
    "while eps > epsilon:\n",
    "    eps = 0\n",
    "    for m in np.arange(M)[1:M]:\n",
    "        for n in np.arange(N)[1:N]:\n",
    "            r0 = y0[m][n]\n",
    "            if tau*m >= -h*n/(2 - (4/np.pi)*np.arctan(2)):\n",
    "                k = F1(m, n) / dF1( m, n)\n",
    "               # print(k)\n",
    "                y0[m][n] = y0[m][n] - k\n",
    "                while y0[m][n] <= 0:\n",
    "                    y0[m][n] = (r0 + y0[m][n])/2 # вилка на случай, если решение станет меньше или равно 0\n",
    "            else:\n",
    "                k = F2(m, n) / dF2( m, n)\n",
    "              #  print(k)\n",
    "                y0[m][n] = y0[m][n] - k\n",
    "                while np.abs((np.pi/4)*(y0[m][n]-2)) >= np.pi/2:\n",
    "                    y0[m][n] = (r0 + y0[m][n])/2 # вилка, ибо тангенс пи периодичен\n",
    "            if abs(k) > eps:\n",
    "                eps = abs(k)\n",
    "plot_u(X,T,y0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Численное решение"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Шаблон\n",
    "Перепишем исходное уравненение в дивергентном виде:\n",
    "\\begin{eqnarray}\n",
    "\\frac{\\partial u}{\\partial t} - \\frac{\\partial (\\frac{u^2}{2})}{\\partial x} = 0\n",
    "\\end{eqnarray}\n",
    "Воспользуемся шаблоном следующего вида (\"ящик\"):"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![alt text](Temp2.png \"Title\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Он безусловно устойчив и аппроксимирует задачу как $O(h^2+\\tau^2)$. Разностная схема будет выглядить следующим образом:\n",
    "\n",
    "\\begin{eqnarray}\n",
    "\\frac{y^{m+1}_n - y^m_{n} + y^{m+1}_{n+1} - y^m_{n+1}}{\\tau} - \\frac{(y^{m+1}_{n+1})^2 - (y^{m+1}_{n})^2 + (y^{m}_{n+1})^2 - (y^{m}_{n})^2}{2h}=0 ~~(*)\n",
    "\\end{eqnarray}\n",
    "\n",
    "НУ и ГУ:\n",
    "\n",
    "\\begin{aligned} \n",
    "   y^0_n = 2 - \\frac{4}{\\pi} arctg(nh+2)\n",
    "   \\\\\n",
    "   y^j_0 = (2 - \\frac{4}{\\pi} arctg(2)) e^{-j\\tau}\n",
    "\\end{aligned}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Подробнее об аппроксимации и устойчивости\n",
    "### Устойчивость\n",
    "Зафиксируем коэффициент перед $\\frac{\\partial u}{\\partial x}$. Выберем произвольную точку $(x_0,t_0)$ исследуемой обасти $\\Omega$ и обозначим $-u(x_0, t_0)$  за $С$. Теперь исследуемая схема приобретет вид:\n",
    "\\begin{eqnarray}\n",
    "\\frac{y^{m+1}_{n+1}-y^{m}_{n+1}+y^{m+1}_{n}-y^{m}_{n}}{\\tau}+C\\frac{y^{m+1}_{n+1}-y^{m+1}_{n}+y^{m}_{n+1}-y^{m}_{n}}{h}=0\n",
    "\\end{eqnarray}\n",
    "Ищем решение в виде $y^{j}_{n}=q^j e^{i\\alpha n}$:\n",
    "\\begin{eqnarray}\n",
    "\\frac{y^{j+1}_{n+1} - y^{j}_{n+1}}{\\tau} + C \\frac{{y^{j+1}_{n+1}} - {y^{j+1}_{n}}}{h} = 0\n",
    "\\end{eqnarray}\n",
    "Выразим отсюда q:\n",
    "\\begin{eqnarray}\n",
    "q = \\frac{e^{i\\alpha} + 1 + r(1 - e^{i\\alpha})}{e^{i\\alpha} + 1 + r(e^{i\\alpha} -1)}, где ~r = \\frac{C\\tau}{h}\n",
    "\\end{eqnarray}\n",
    "$|q| \\leq 1$ для любых $C, \\tau $ и $h$, следовательно выполнен спектральный критерий Неймана для любого размера сетки.\n",
    "### Порядок аппроксимации\n",
    "Вычислим порядок аппроксимации данной схемы, разложив сначала каждую точку шаблона в ряд Тейлора до третьего члена включительно в точке $(x_n+h/2,t_m+\\tau/2)$:\n",
    "\\begin{aligned}\n",
    "y^{m+1} = y^{m+0.5}+\\frac{\\tau}{2}y'~^{m+0.5} + \\frac{1}{2}\\frac{\\tau^{2}}{4} y''~^{m+0.5}+\\frac{1}{6}\\frac{\\tau^{3}}{8}y'''~^{m+0.5} + O(\\tau^{4})\\\\\n",
    "y^{m} = y^{m+0.5}-\\frac{\\tau}{2}y'~^{m+0.5}+\\frac{1}{2}\\frac{\\tau^{2}}{4} y''~^{m+0.5}-\\frac{1}{6}\\frac{\\tau^{3}}{8}y'''~^{m+0.5} + O(\\tau^{4})\\\\\n",
    "y_{n+1} = y_{n+0.5}+\\frac{h}{2}y'_{n+0.5}+\\frac{1}{2}\\frac{h^{2}}{4} y''_{n+0.5}+\\frac{1}{6}\\frac{h^{3}}{8}y'''_{n+0.5} + O(h^{4})\\\\\n",
    "y_{n} = y_{n+0.5}-\\frac{h}{2}y'_{n+0.5}+\\frac{1}{2}\\frac{h^{2}}{4} y''_{n+0.5}-\\frac{1}{6}\\frac{h^{3}}{8}y'''_{n+0.5} + O(h^{4})\n",
    "\\end{aligned}\n",
    "Следовательно:\n",
    "\\begin{aligned}\n",
    "\\frac{y^{m+1}_{n+1}-y^{m}_{n+1}+y^{m+1}_n-y^{m}_n}{2\\tau} +C\\frac{y^{m+1}_{n+1}-y^{m+1}_{n}+y^{m}_{n+1}-y^{m}_{n}}{2h} -\\frac{\\partial y}{\\partial t} -C\\frac{\\partial y}{\\partial x}=O(\\tau^{2} + h^{2}) \\end{aligned}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Схема бегущего счета\n",
    "Будем решать задачу с помощью схемы бегущего счета. Из разностной схемы видно, что неизвестную сеточную функцию $y^{j+1}_{n+1}$ можно найти численно, решив уравнение (*) относительно этой функции, так как нам известны массивы $y^0_n$ и $y^j_0$. Таким образом, мы найдем значения сеточной функции на всей области определения, заполняя двумерный массив по горизонтали снизу вверх: находим сначала $y^1_1$, потом $y^1_2$ и т. д. вплоть до $y^1_n$; далее $y^2_1$ и т. д.\n",
    "\n",
    "Будем решать уравнение с помощью метода Ньютона. Будем приближенно искать корень корень уравнения (*) - $y^{j+1}_{n+1}$.\n",
    "# Код, строящий численное решение"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
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   "source": [
    "# создаем массив размером (M x N) из единиц (положим единицу за начальное приближение метода Ньютона)\n",
    "y = np.ones((M,N)) \n",
    "\n",
    "# заполняем ячейки, соответствующие НУ и ГУ\n",
    "for n in np.arange(N):\n",
    "        y[0][n] = (2 - (4/np.pi)*np.arctan(h*n + 2))\n",
    "\n",
    "for m in np.arange(M):\n",
    "        y[m][0] = (2 - (4/np.pi)*np.arctan(2))*exp(-tau * m)\n",
    "\n",
    "# определяем функцию (и ее производную), корень которой нам нужно численно найти\n",
    "def F(mp1, np1):\n",
    "    n = np1-1\n",
    "    m = mp1-1\n",
    "    return (y[mp1][n]- y[m][n] + y[mp1][np1]-y[m][np1]) / (2.*tau) - (y[mp1][np1]**2-y[mp1][n]**2 + y[m][np1]**2-y[m][n]**2) / (4.*h)\n",
    "\n",
    "#(y[m][k] - y[m-1][k])/tau - (y[m][k]**2 - y[m][k-1]**2)/(2.* h)\n",
    "\n",
    "def dF(m, k):\n",
    "    return  1/(2*tau) - y[m][k]/(2*h)\n",
    "\n",
    "#1/tau - y[m][k]/h\n",
    "\n",
    "# метод Ньютона для каждой точки сетки\n",
    "eps = epsilon + 1\n",
    "while eps > epsilon:\n",
    "    eps = 0\n",
    "    for m in np.arange(M)[0:M-1]:\n",
    "        for n in np.arange(N)[0:N-1]:\n",
    "            k = F(m+1, n+1) / dF( m+1, n+1)\n",
    "            y[m+1][n+1] = y[m+1][n+1] - k\n",
    "            if abs(k) > eps:\n",
    "                eps = abs(k)\n",
    "\n",
    "\n",
    "plot_u(X,T,y)"
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   "source": [
    "# Погрешность\n",
    "Зная аналитическое решение (хотя оно то же как бы численное), можно вычислить погрешность численного решения:\n",
    "\\begin{eqnarray}\n",
    "|z_{h,\\tau}(x_n, t_j)| = |y(x_n, t_j) - y_0(x_n, t_j)|\n",
    "\\end{eqnarray}\n",
    "Построим график зависмости погрешности от x и t и вычислим среднее значение и максимум погрешности в заданных областях x и t:"
   ]
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   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
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     "text": [
      "Максимальное значение погрешности: 0.024707902505659907 \n",
      "Среднее значение погрешности: 0.005055798249805755\n"
     ]
    }
   ],
   "source": [
    "S = np.zeros((M,N))\n",
    "S = np.abs(y0 - y)\n",
    "plot_u(X,T,S)\n",
    "print(\"Максимальное значение погрешности:\", np.max(S), \"\\nСреднее значение погрешности:\", np.mean(S))"
   ]
  },
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   "source": [
    "# Измелечение сетки\n",
    "Рассмотрим три варианта размера сетки.\n",
    "## N = 10, M = 10\n",
    "![alt text](1010.png \"Title\")\n",
    "При этом максимальный модуль погрешности и средний модуль погрешности равны: 0.06 и 0.012\n",
    "## N = 75, M = 75\n",
    "![alt text](7575.png \"Title\")\n",
    "При этом максимальный модуль погрешности и средний модуль погрешности равны: 0.007 и 0.0008\n",
    "## N = 150, M = 150\n",
    "![alt text](150150.png \"Title\")\n",
    "При этом максимальный модуль погрешности и средний модуль погрешности равны: 0.004 и 0.0003"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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