Tried_to_solve_phys.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Преамбула\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy.optimize import minimize\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Решение задачи сложной подгонки\n",
    "\n",
    "В этом блокноте предпринята попытка решения следующей задачи.\n",
    "\n",
    "В результате физического эксперимента были получены несколько файлов с данными по распределению температуры в пассивной части исследуемой пластины при разных значениях силы тока. Была предложена модель теплообмена с внешней средой, из которой было получено теоретической распределение температуры в пластине:\n",
    "\\begin{equation}\\label{solve_in}\n",
    "T = A e^{\\beta x} + B e^{-\\beta x} + \\tau\n",
    "\\end{equation},\n",
    "где наибольший интерес представляет коэффициент $\\beta$, характеризующий пластину и окружающую среду.\n",
    "$\\tau$ по смыслу отвечает за \"рабочую\" температуру среды.\n",
    "### Проблема\n",
    "\n",
    "Заключалась в чрезмерно большом поле свободных параметров для подгонки, при очень маленьком числе точек(~20).\n",
    "\n",
    "### Возможное решение\n",
    "\n",
    "* Построить функцию на интересующим коэффициенте $\\beta$, которая была бы нормой результата подгонки по оставшимся параметрам для каждой выборки.\n",
    "* Произвести минимизацию функции по корректному диапозону\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Для подгонки необходи передать функцию в терминах python, так что объявим её как функцию для каждого $\\beta$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "## для каждой беты своя функция\n",
    "def fit_b(b):\n",
    "    def func(x, a_1, a_2, t_out):\n",
    "        return a_1*np.exp(b*x) + a_2*np.exp(-b*x) + t_out\n",
    "    return func"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Основная функция\n",
    "\n",
    "Функция получает на вход кортеж данных, текущую функцию подгонки, имя файла для ведения лога, диапозон значений для подгонки.\n",
    "Далее производится процедура подгонки и запись в файл оптимальных коэффициентов и их относительные погрешности(при необходимости).\n",
    "Возвращается норма текущей подгонки.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def podgon_and(data_lol, funct, name='testing_fit', rang=(-np.inf, np.inf),log=0):\n",
    "    try:\n",
    "        popt, pcov = curve_fit(funct, data_lol[0], data_lol[1], bounds=rang)\n",
    "        perr = np.sqrt(np.diag(pcov))\n",
    "        mod = perr/popt\n",
    "    except RuntimeError:\n",
    "         mod = np.inf\n",
    "    if (log == 1) and (np.linalg.norm(mod) < 10000):\n",
    "        f = open(name, 'a')\n",
    "        f.write(np.array2string(popt, separator='\\t', prefix='optium')  +'\\t' + np.array2string(mod, separator = '\\t', prefix='error') + '\\n')\n",
    "        f.close()\n",
    "    \n",
    "    return(np.linalg.norm(mod)**2)\n",
    "                                           "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Процедура извлечения данных эксперимента.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_hot=[]\n",
    "for i in range(17):\n",
    "    d_in = np.loadtxt(f\"profil_0_{i}.txt\",  dtype=np.float)\n",
    "    list_hot.append((np.arange(len(d_in)), d_in))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Построение функции от $\\beta$ и данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main_fit(b, data_full,record=0):\n",
    "    f_now = fit_b(b)\n",
    "    namem = f\"fit_b_{b}\"\n",
    "    mass = 0\n",
    "    for data in data_full:\n",
    "        mass += podgon_and(data, f_now, namem, log=record)\n",
    "    return np.sqrt(mass)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Визуальная оценка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0.005, 0.6, 0.0001)\n",
    "y = [main_fit(_, list_hot) for _ in x]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
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       "    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=\"642.7272587965346\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "plt.plot(x, y)\n",
    "plt.title('Подгон только по '+ r'$\\beta $')\n",
    "plt.ylabel('Масса вектора ошибок')\n",
    "plt.xlabel(r'$\\beta$')\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Запуск минимизации средствами Scimpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#определение функции для оптимизации\n",
    "def func_to_b(b):\n",
    "    return(main_fit(b, list_hot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 4.681366\n",
      "         Iterations: 22\n",
      "         Function evaluations: 50\n",
      "[0.07482178]\n"
     ]
    }
   ],
   "source": [
    "## Минимизация первой ямы\n",
    "x0 = [0.05]\n",
    "res = minimize(func_to_b, x0, method='Nelder-Mead',options={'xtol': 1e-7, 'disp': True})\n",
    "print(res.x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.837267\n",
      "         Iterations: 22\n",
      "         Function evaluations: 50\n",
      "[0.25549095]\n"
     ]
    }
   ],
   "source": [
    "x0 = [0.3]\n",
    "res = minimize(func_to_b, x0, method='Nelder-Mead',options={'xtol': 1e-7, 'disp': True})\n",
    "print(res.x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.07482178\n",
      "Масса в локальном оптиуме =  4.68142391199281\n"
     ]
    }
   ],
   "source": [
    "### Подстановка различных значений для получения лога\n",
    "b_ = float(input())\n",
    "res = main_fit(b_,list_hot, record=1)\n",
    "print(f'Масса в локальном оптиуме =  {res}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.25549095\n",
      "Масса в локальном оптиуме =  0.8372677032941243\n"
     ]
    }
   ],
   "source": [
    "### Подстановка различных значений для получения лога\n",
    "b_ = float(input())\n",
    "res = main_fit(b_,list_hot, record=1)\n",
    "print(f'Масса в локальном оптиуме =  {res}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Подгон в границах по температуре среды\n",
    "\n",
    "Поэтому поступим немного иначе: физически ограничим температуру подгонки и повысим её вес"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Организуем принудительно подгонку в границах для температуры"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "# функция для подгонки с обрезанным диапозоном температуры\n",
    "def fit_cut_t(b, data_full,record=0,t=100):\n",
    "    f_now = fit_b(b)\n",
    "    namem = f\"fit_cut_t_{t}_b_{b}\"\n",
    "    mass = 0\n",
    "    rang = ([-np.inf, -np.inf, 20], [np.inf, np.inf, t])\n",
    "    for data in data_full:\n",
    "        mass += podgon_and(data, f_now, namem,rang, log=record)\n",
    "    return mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_cut =[fit_cut_t(_, list_hot, t=40) for _ in x] # получение точек то тем же x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"623.6363501194098\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "plt.plot(x, y_cut)\n",
    "plt.title('Подгон с ограничение t = 40 C')\n",
    "plt.ylabel('Масса вектора ошибок')\n",
    "plt.xlabel(r'T_{out},C')\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.06\n"
     ]
    }
   ],
   "source": [
    "b_ = float(input())\n",
    "res = fit_cut_t(b_,list_hot, record=1,t=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Простая срезка не помогла, температура подгонки просто упирается в предел.\n",
    "#### Пути debug'а\n",
    "* поменять вес для подгонтки по температуре\n",
    "* смотреть 2d распределение"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Модель постоянной температуры среды"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Объявление функции\n",
    "def func_to_fit_t(t_):\n",
    "    def func(x, a_1, a_2, b):\n",
    "        return a_1*np.exp(b*x) + a_2*np.exp(-b*x) + t_\n",
    "    return func"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_t(t, data_full, record=0):\n",
    "    f_now = func_to_fit_t(t)\n",
    "    namem = f\"fit_t_{t}\"\n",
    "    mass = 0\n",
    "    \n",
    "    for data in data_full:\n",
    "        mass += podgon_and(data, f_now, namem, log=record)\n",
    "    return np.sqrt(mass)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Визуально"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.arange(20, 50 , 0.01)\n",
    "k = [fit_t(_, list_hot) for _ in t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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"
    },
    {
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\" width=\"672.7272581463021\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "plt.plot(t, k)\n",
    "plt.title('Подгон t')\n",
    "plt.ylabel('Масса вектора ошибок')\n",
    "plt.xlabel(r't,C')\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Минимизация по t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#определение функции для оптимизации\n",
    "def func_to_t(t):\n",
    "    return fit_t(t, list_hot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 689.879030\n",
      "         Iterations: 51\n",
      "         Function evaluations: 128\n",
      "[35.68125157]\n"
     ]
    }
   ],
   "source": [
    "t0 = 33\n",
    "res = minimize(func_to_t, t0, method='Nelder-Mead',options={'xtol': 1e-7, 'disp': True})\n",
    "print(res.x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Как видно из картинки, получилась совсем не глаткая зависимость связано это со сложнастями при подгонке таких функция как экспонента"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35.5\n",
      "Масса в локальном оптиуме =  26.2957851701939\n"
     ]
    }
   ],
   "source": [
    "### Подстановка различных значений для получения лога\n",
    "t = float(input())\n",
    "\n",
    "res = fit_t(t, list_hot, record=1)\n",
    "\n",
    "print(f'Масса в локальном оптиуме =  {res}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Модель постоянных $T_{out}$ и $\\beta$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "# строим функцию\n",
    "def func_to_fit_both(v):\n",
    "    def func(x, a_1, a_2):\n",
    "        return a_1*np.exp(v[0]*x) + a_2*np.exp(-v[0]*x) + v[1]\n",
    "    return func"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "# основа\n",
    "def fit_both (b_t, data_full, record=0):\n",
    "    f_now = func_to_fit_both(b_t)\n",
    "    #namem = f\"fit_t_{b_t[0]}_{b_t[1]}\"\n",
    "    mass = 0\n",
    "    for data in data_full:\n",
    "        mass += podgon_and(data, f_now, log=record)\n",
    "    return mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def func_to_Z(b_t):\n",
    "    return fit_both(b_t, list_hot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "# получение точек\n",
    "b = np.arange(0.15, 0.25, 0.001)\n",
    "t = np.arange(25, 100, 1)\n",
    "Z,k = np.meshgrid(b, t)\n",
    "B, T = np.meshgrid(b, t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "# обсчёт\n",
    "for bi in b:\n",
    "    i = 0\n",
    "    for tau in t:\n",
    "        j=0\n",
    "        a = func_to_Z((bi, tau))\n",
    "        if (a < 1.0):\n",
    "            Z[i][j] = a\n",
    "        else:\n",
    "            Z[i][j] = 1\n",
    "        j+=1\n",
    "    i+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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"
    },
    {
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\" width=\"1498.8889285958853\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Построение графика\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n",
    "%matplotlib notebook\n",
    "# Настраиваем 3D график\n",
    "fig = plt.figure(figsize=[15, 10])\n",
    "ax = fig.gca(projection='3d')\n",
    "\n",
    "# Задаем угол обзора\n",
    "ax.view_init(45, 30)\n",
    "\n",
    "# Рисуем поверхность\n",
    "surf = ax.plot_surface(B, T, Z, cmap=cm.coolwarm)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В общем всего, что хотелось бы достичь не удалось, ну и ладно.\n",
    "\n",
    "![alt-текст](https://hsto.org/webt/_i/vd/cj/_ivdcjv0itamifffxs0i1i-mqh4.jpeg \"Кривые, да\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}