VDP.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### モデルを作ってシミュレーションを実行する\n",
    "[JModelica Users Guid - Version 2.10](https://jmodelica.org/downloads/UsersGuide-2.10.pdf) の 5.2. A first example に簡単なモデルを作ってシミュレーションを実行し、結果をプロットする方法が書かれています。 これを実行してみます。\n",
    "\n",
    "Van der Pol oscillator の支配方程式を次に示します。\n",
    "$$\n",
    "\\frac{d^2 x}{dt^2} - \\mu (1-x^2) \\frac{d x}{d t} + x = 0\n",
    "$$\n",
    "$x=x_2, \\frac{dx}{dt} = x_1, \\mu = 1$ とおくと次のように変形できます。\n",
    "$$\n",
    "\\frac{d x_1}{d t} = (1-x_2^2) x_1 - x_2, \\  \\frac{d x_2}{dt} = x_1\n",
    "$$\n",
    "これは、ここで解く方程式 \n",
    "$$\n",
    "\\frac{d x_1}{d t} = (1-x_2^2) x_1 - x_2 + u, \\  \\frac{d x_2}{dt} = x_1\n",
    "$$\n",
    "の制御信号(control signal) を$u=0$としたものになります。初期条件を\n",
    "$$\n",
    "x_1(0)=0, \\  x_2(0)=1\n",
    "$$\n",
    "とします。\n",
    "\n",
    "モデルのソースコードを作成します。短いソースコードのモデルは Jupyter Notebook の Magicコマンド %%writefile で作成できます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting VDP.mo\n"
     ]
    }
   ],
   "source": [
    "%%writefile VDP.mo\n",
    "model VDP\n",
    "    // State start values\n",
    "    parameter Real x1_0 = 0;\n",
    "    parameter Real x2_0 = 1;\n",
    "    \n",
    "    // The states\n",
    "    Real x1(start = x1_0);\n",
    "    Real x2(start = x2_0);\n",
    "    \n",
    "    // The control signal\n",
    "    input Real u;\n",
    "    \n",
    "equation\n",
    "    der(x1) = (1 - x2^2) * x1 - x2 + u;\n",
    "    der(x2) = x1;\n",
    "end VDP;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "モデルをコンパイルして FMU を作成してロードします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the function for compilation of models and the load_fmu method\n",
    "from pymodelica import compile_fmu\n",
    "from pyfmi import load_fmu\n",
    "# Compile model\n",
    "fmu_name = compile_fmu(\"VDP\",\"VDP.mo\")\n",
    "# Load model\n",
    "vdp = load_fmu(fmu_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "シミュレーションを実行します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final Run Statistics: --- \n",
      "\n",
      " Number of steps                                 : 148\n",
      " Number of function evaluations                  : 208\n",
      " Number of Jacobian evaluations                  : 3\n",
      " Number of function eval. due to Jacobian eval.  : 6\n",
      " Number of error test failures                   : 11\n",
      " Number of nonlinear iterations                  : 204\n",
      " Number of nonlinear convergence failures        : 0\n",
      "\n",
      "Solver options:\n",
      "\n",
      " Solver                   : CVode\n",
      " Linear multistep method  : BDF\n",
      " Nonlinear solver         : Newton\n",
      " Linear solver type       : DENSE\n",
      " Maximal order            : 5\n",
      " Tolerances (absolute)    : 1e-06\n",
      " Tolerances (relative)    : 0.0001\n",
      "\n",
      "Simulation interval    : 0.0 - 10.0 seconds.\n",
      "Elapsed simulation time: 0.0104110240936 seconds.\n"
     ]
    }
   ],
   "source": [
    "res = vdp.simulate(final_time=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "シミュレーション結果をプロットします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
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       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "# Import the plotting library\n",
    "import matplotlib.pyplot as plt \n",
    "x1 = res['x1']\n",
    "x2 = res['x2']\n",
    "t = res['time']\n",
    "plt.figure(1)\n",
    "plt.plot(t, x1, t, x2)\n",
    "plt.legend(('x1','x2'))\n",
    "plt.title('Van der Pol oscillator.')\n",
    "plt.ylabel('Angle (rad)')\n",
    "plt.xlabel('Time (s)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "シミュレーション結果に含まれる変数や定数、パラメータは以下のようにして調べることができます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time\n",
      "x1_0\n",
      "x2_0\n",
      "_block_jacobian_check_tol\n",
      "_cs_rel_tol\n",
      "_cs_step_size\n",
      "_events_default_tol\n",
      "_events_tol_factor\n",
      "_nle_jacobian_finite_difference_delta\n",
      "_nle_solver_default_tol\n",
      "_nle_solver_max_residual_scaling_factor\n",
      "_nle_solver_min_residual_scaling_factor\n",
      "_nle_solver_min_tol\n",
      "_nle_solver_regularization_tolerance\n",
      "_nle_solver_step_limit_factor\n",
      "_nle_solver_tol_factor\n",
      "_time_events_default_tol\n",
      "der(x1)\n",
      "der(x2)\n",
      "x1\n",
      "x2\n",
      "u\n",
      "_block_solver_experimental_mode\n",
      "_cs_experimental_mode\n",
      "_cs_solver\n",
      "_iteration_variable_scaling\n",
      "_log_level\n",
      "_nle_active_bounds_mode\n",
      "_nle_jacobian_calculation_mode\n",
      "_nle_jacobian_update_mode\n",
      "_nle_solver_exit_criterion\n",
      "_nle_solver_max_iter\n",
      "_nle_solver_max_iter_no_jacobian\n",
      "_residual_equation_scaling\n",
      "_block_jacobian_check\n",
      "_block_solver_profiling\n",
      "_enforce_bounds\n",
      "_nle_brent_ignore_error\n",
      "_nle_solver_check_jac_cond\n",
      "_nle_solver_use_last_integrator_step\n",
      "_nle_solver_use_nominals_as_fallback\n",
      "_rescale_after_singular_jac\n",
      "_rescale_each_step\n",
      "_runtime_log_to_file\n",
      "_use_Brent_in_1d\n",
      "_use_jacobian_equilibration\n",
      "_use_newton_for_brent\n"
     ]
    }
   ],
   "source": [
    "for name in res.keys():\n",
    "    print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最初がアンダーバーで始まるものを除くと以下のようになります。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time\n",
      "x1_0\n",
      "x2_0\n",
      "der(x1)\n",
      "der(x2)\n",
      "x1\n",
      "x2\n",
      "u\n"
     ]
    }
   ],
   "source": [
    "for name in res.keys():\n",
    "    if name[0] != '_':\n",
    "        print (name)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.17"
  }
 },
 "nbformat": 4,
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}

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