dedalus_1d_momentum.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solve zero pressure gradient viscous 1D momentum problem\n",
    "\n",
    "$$\n",
    "\\frac{\\partial u}{\\partial t} + 0 - 0 - \\nu \\frac{\\partial^2 u}{\\partial z^2}  = \\frac{\\partial u_{\\infty}}{\\partial t}\n",
    "$$\n",
    "\n",
    "with boundary conditions\n",
    "\n",
    "$$\n",
    "u(z=H) = 0\n",
    "$$\n",
    "\n",
    "$$\n",
    "u(z=0) = 0\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Gotta find my FFTW_PATH\n",
    "!export FFTW_PATH=/path/to/your/fftw_prefix "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[sudo] password for suntans: \n"
     ]
    }
   ],
   "source": [
    "!sudo pip install dedalus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Bad key \"backend.qt5\" on line 8 in\n",
      "/home/suntans/.config/matplotlib/matplotlibrc.\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "http://github.com/matplotlib/matplotlib/blob/master/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import numpy as np\n",
    "import dedalus.public as de\n",
    "from dedalus.tools  import post\n",
    "\n",
    "from dedalus.extras.plot_tools import quad_mesh, pad_limits\n",
    "\n",
    "\n",
    "import logging\n",
    "import matplotlib.pyplot as plt\n",
    "logger = logging.getLogger(__name__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "\n",
    "H = 1. # Depth\n",
    "\n",
    "nz = 64\n",
    "nz = 200\n",
    "\n",
    "nu = 1e-2 \n",
    "\n",
    "u_top  =0\n",
    "u_bottom = 0\n",
    "\n",
    "k_ramp = -1/(2*np.pi)\n",
    "\n",
    "uniform_diffusion = True\n",
    "hot_start = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CReate the domain\n",
    "\n",
    "z = de.Chebyshev('z',nz,interval=[0.,H])\n",
    "domain = de.Domain([z],grid_dtype='float')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the problem\n",
    "problem = de.IVP(domain, variables=['u', 'uz', 'uzz']) # u and viscous stress\n",
    "problem.parameters['nu'] = nu\n",
    "problem.parameters['u_top'] = u_top\n",
    "problem.parameters['u_bottom'] = u_bottom\n",
    "problem.parameters['k_ramp'] = k_ramp\n",
    "problem.parameters['a0'] = 1\n",
    "T = 2*np.pi\n",
    "problem.parameters['omega'] = 2*np.pi/T\n",
    "\n",
    "\n",
    "\n",
    "# Add an acceleration term\n",
    "#ncc = domain.new_field(name = 'duinf_dt')\n",
    "\n",
    "\n",
    "# if uniform_diffusion:\n",
    "#     problem.parameters['K'] = K_0\n",
    "# else:\n",
    "#     # Add vertically varying diffusion\n",
    "#     ncc = domain.new_field(name = 'K')\n",
    "#     ncc['g'] = (H-z)*K_0\n",
    "#     problem.parameters['K'] = ncc\n",
    "\n",
    "problem.add_equation('dt(u) - nu*uzz  = a0*cos(omega*t)')\n",
    "problem.add_equation('uzz - dz(uz) = 0')\n",
    "problem.add_equation('uz - dz(u) = 0')\n",
    "\n",
    "# Add the time varying boundary conditions\n",
    "problem.add_bc('left(u) = 0')\n",
    "problem.add_bc('right(uz) = 0')\n",
    "# else:    \n",
    "#     problem.add_bc('left(u) = u_top*(1-exp(k_ramp*t))')\n",
    "#     problem.add_bc('right(u) = u_bottom')\n",
    "\n",
    "# y = 1-exp(-t)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-11-07 15:55:36,205 pencil 0/1 INFO :: Building pencil matrix 1/1 (~100%) Elapsed: 0s, Remaining: 0s, Rate: 7.3e+01/s\n",
      "2019-11-07 15:55:40,051 solvers 0/1 INFO :: Simulation stop time reached.\n",
      "2019-11-07 15:55:40,053 __main__ 0/1 INFO :: Total time: 3.842908\n",
      "2019-11-07 15:55:40,053 __main__ 0/1 INFO :: Iterations: 1257\n",
      "2019-11-07 15:55:40,054 __main__ 0/1 INFO :: Average timestep: 0.010000\n"
     ]
    }
   ],
   "source": [
    "solver = problem.build_solver(de.timesteppers.RK443)\n",
    "\n",
    "solver.stop_sim_time = 4*np.pi\n",
    "solver.stop_wall_time = 1000.\n",
    "solver.stop_iteration = np.inf\n",
    "dt = 0.01\n",
    "\n",
    "# Store data for final plot\n",
    "# Initial conditions\n",
    "z = domain.grid(0)\n",
    "u = solver.state['u']\n",
    "\n",
    "u.set_scales(1, keep_data=True)\n",
    "u_list = [np.copy(u['g'])]\n",
    "t_list = [solver.sim_time]\n",
    "\n",
    "start_time = time.time()\n",
    "while solver.ok:\n",
    "    solver.step(dt)\n",
    "    if solver.iteration % 20 == 0:\n",
    "        #logger.info(\"Time step {}\".format(solver.iteration))\n",
    "        u.set_scales(1, keep_data=True)\n",
    "        u_list.append(np.copy(u['g']))\n",
    "        t_list.append(solver.sim_time)\n",
    "        \n",
    "end_time = time.time()\n",
    "\n",
    "# Print statistics\n",
    "logger.info('Total time: %f' %(end_time-start_time))\n",
    "logger.info('Iterations: %i' %solver.iteration)\n",
    "logger.info('Average timestep: %f' %(solver.sim_time/solver.iteration))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "u_array = np.array(u_list)\n",
    "t_array = np.array(t_list)\n",
    "zmesh, tmesh = quad_mesh(x=z, y=t_array)\n",
    "\n",
    "delta = np.sqrt(2*nu) # assumes zero freq\n",
    "\n",
    "zmesh = zmesh/delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
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       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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=\"639.4833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.pcolormesh(tmesh.T, zmesh.T, u_array.T, cmap='RdBu_r',vmin=-1, vmax=1)\n",
    "plt.axis(pad_limits(tmesh, zmesh))\n",
    "plt.colorbar()\n",
    "plt.ylabel('z')\n",
    "plt.xlabel('t')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((63, 200), (200,), 63)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "u_array.shape, z.shape, len(t_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": {
      "text/html": [
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\" width=\"639.4833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_ind(t_array, val):\n",
    "    \n",
    "    dt = np.abs(t_array-val)\n",
    "    return np.where(dt==np.min(dt))[0][0]\n",
    "\n",
    "z_ = z/delta\n",
    "\n",
    "plt.figure()\n",
    "# plt.plot(u_array[0,:], z, 'k:')\n",
    "plt.plot(u_array[get_ind(t_array, 1.00*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 1.25*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 1.50*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 1.75*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 2.00*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 2.25*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 2.50*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 2.75*np.pi),:], z_)\n",
    "plt.plot(u_array[get_ind(t_array, 3.00*np.pi),:], z_)\n",
    "# plt.plot(u_array[-1,:],z, 'k')\n",
    "\n",
    "plt.plot([-1, 1], [delta, delta], 'k--')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}