2D_sed_local.ipynb

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    "# Sedimentation Experiments\n",
    "\n",
    "In this notebook, we perform sedimentation experiments to benchmark the pIBM for droplets and rigid bodies. Following Kim & Peskin (Phys. Fluids 28, 033603 (2016); https://doi.org/10.1063/1.4944565), we apply gravity as a body force and apply an updraft to keep the body in the computational domain. "
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    "#### Script for IBM simulation of a single droplet in incompressible, periodic fluid\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "from matplotlib import gridspec\n",
    "\n",
    "%matplotlib notebook \n",
    "\n",
    "from fluid2 import FLUID    #### Generic fluid solver\n",
    "from ib2 import IB2         #### 2D Immersed Boundary object (droplet membrane)\n",
    "from pib2 import PIB2       #### 2D penalty IB object (droplet interior)\n",
    "from rpib2 import RPIB2       #### 2D penalty IB object (rigid body)\n",
    "\n",
    "from util import *          #### General functions (iterate, geometry, force functions, etc)\n",
    "import warnings; warnings.simplefilter('ignore')"
   ]
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    "## Parameters\n",
    "\n",
    "We declare default values of many parameters up front, including\n",
    "- Fluid Parameters - Domain space/length scale and resolution; fluid density rho and viscosity mu\n",
    "- Solid Parameters - mass/elasticity, position/size, and spacial resolution of immersed bodies\n",
    "- Force Parameters - to tune gravity and updraft mechanism (see below)\n",
    "\n",
    "Note that we can use lists of parameters to later initialize several immersed bodies using list comprehension - see simulation code. "
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      "Traceback (most recent call last):\n",
      "  File \"/home/users6/zds241/.local/lib/python3.6/site-packages/matplotlib/cbook/__init__.py\", line 215, in process\n",
      "    func(*args, **kwargs)\n",
      "  File \"/home/users6/zds241/.local/lib/python3.6/site-packages/matplotlib/animation.py\", line 1478, in _stop\n",
      "    self.event_source.remove_callback(self._loop_delay)\n",
      "AttributeError: 'NoneType' object has no attribute 'remove_callback'\n"
     ]
    }
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   "source": [
    "global dt, nsteps, nmod\n",
    "# Fluid Parameters\n",
    "L = 1.0                 # Domain Length\n",
    "N = 128                 # Domain Points (NxN grid)\n",
    "mu = 0.1               # viscosity\n",
    "dt = 0.0005             # timestep\n",
    "nsteps = 250            # simulation time \n",
    "nmod = 10               # save every nmod frames\n",
    "\n",
    "%matplotlib notebook\n",
    "def RESOLVE(res):\n",
    "    global dt, nsteps, nmod\n",
    "    dt/=res\n",
    "    nsteps=int(nsteps*res)\n",
    "    nmod=int(nmod*res)\n",
    "\n",
    "RESOLVE(2)\n",
    "# Membrane Parameters\n",
    "K = 500\n",
    "Nb = 400\n",
    "rad = 0.05\n",
    "positions = [[0.5, 0.5]]    \n",
    "# rad = [0.05, 0.1]\n",
    "# positions = [[0.2, 0.2], [0.6, 0.6]]\n",
    "\n",
    "# Interior Parameters\n",
    "Kp = 7000\n",
    "M = 0.01\n",
    "Ni = 300\n",
    "    "
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    "## Gravity and Updraft\n",
    "Our sedimentation experiments follow Kim & Peskin's 2016 paper, \"A penalty immersed boundary method\n",
    "for a rigid body in fluid\". Following their procedure, we generate an updraft to keep the particle inside of the domain and to increase stability. "
   ]
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   "cell_type": "code",
   "execution_count": 12,
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   "source": [
    "# Body Force Parameters\n",
    "z0=0.5\n",
    "gamma=1e5\n",
    "sigma=1e4\n",
    "\n",
    "def GRAV(solid, Y, g=980.):\n",
    "    F = np.zeros(np.shape(Y))\n",
    "    F[:,1] -= g*solid.M\n",
    "    return F\n",
    "\n",
    "def UPDRAFT(z, w, z0=0.5, gamma=1e5, sigma=1e4): return gamma*(z0-z) - sigma*w\n"
   ]
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   "source": [
    "# PIBM Droplet Sedimentation\n",
    "\n",
    "Droplets can be modeled using a massive interior fluid surrounded by an external elastic membrane. The interior mass markers follow a penalty IBM scheme, and the membrane follows the conventional IBM for an immersed body.\n",
    "\n",
    "To set up a simulation, we define a method to instantiate an interior and exterior corresponding to given parameters, and a method to iterate the fluid and solids in time with the updraft described above.\n"
   ]
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   "cell_type": "code",
   "execution_count": 13,
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   "source": [
    "#### Define a pIBM droplet using geometry from util\n",
    "def pibDROPLET(fluid, RAD, POS, Nb=400, K=40, Ni=200, Kp=2500, M=None):\n",
    "#     X_in = FULL_CIRCLE(RAD-fluid.h/2, POS, Ni)\n",
    "    X_in = SUNFLOWER(RAD-fluid.h/2, POS, n=Ni)\n",
    "    X_out = CIRCLE(RAD, POS, Nb)\n",
    "    drop_in= PIB2(X_in, fluid.N, fluid.h, fluid.dt)\n",
    "    drop_in.Kp = Kp    \n",
    "    drop_in.M = M or drop_in.M\n",
    "    drop_out = IB2(X_out, fluid.N, fluid.h, fluid.dt)\n",
    "    drop_out.K = K\n",
    "    return [drop_in, drop_out]\n",
    "\n",
    "\n",
    "\n",
    "#### Iterate fluids and immersed solids using built-in functions\n",
    "def iterate(fluid, solids):\n",
    "    ff = 0. \n",
    "    ## Force density on fluid\n",
    "    for solid in solids:\n",
    "        solid.step_XX(fluid.u)\n",
    "        ff += solid.ff         # Force at midpoint\n",
    "    ff[1][:, -1] += UPDRAFT(np.mean(solids[0].Y, axis=0)[1], np.mean(solids[0].V, axis=0)[1], z0=z0, gamma=gamma, sigma=sigma)\n",
    "    uu=fluid.step_u(ff)        # Step Fluid Velocity\n",
    "    for solid in solids:\n",
    "        solid.step_X(uu)       # full step using midpoint velocity    \n"
   ]
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    "####################################\n",
    "  ########   Simulation   ########\n",
    "####################################\n",
    "\n",
    "#### Initialize Fluid+Droplets\n",
    "fluid = FLUID(N=N, L=L, mu=mu, dt=dt)\n",
    "droplets = [pibDROPLET(fluid, rad, positions[i], Nb=Nb, K=K, Ni=Ni, Kp=Kp, M=M) for i in range(len(positions))]\n",
    "# rad = [0.05, 0.1]\n",
    "# droplets = [pibDROPLET(fluid, rad[i], positions[i], h=fluid.h/2, K=K, Kp=Kp, Nb=Nb, M=M) for i in range(len(positions))]\n",
    "\n",
    "insides = [drop[0] for drop in droplets]\n",
    "outsides = [drop[1] for drop in droplets]\n",
    "\n",
    "solids = []\n",
    "trash = [solids.extend(drop) for drop in droplets]\n",
    "\n",
    "#### Declare Forces\n",
    "for inside in insides:\n",
    "    inside.bForce = lambda solid, Y:  GRAV(solid, Y)\n",
    "    \n",
    "    \n",
    "    \n",
    "#### Values that we're tracking\n",
    "delta = [[] for inside in insides]    ## Keep track of |X-Y|/h\n",
    "V = [[] for inside in insides]\n",
    "# THETA = [[] for outside in outsides]\n",
    "\n",
    "U = []\n",
    "Xout = [[] for outside in outsides]\n",
    "Xin = [[] for inside in insides]\n",
    "Y = [[] for inside in insides]\n",
    "for i in range(nsteps+1):\n",
    "    iterate(fluid, solids)\n",
    "    #### Keeping track of 'interior' properties\n",
    "    for j, iin in enumerate(insides):\n",
    "        delta[j].append(np.max(np.linalg.norm(iin.Y - iin.X, axis=1)))\n",
    "        V[j].append(np.mean(iin.V, axis=0))\n",
    "    if i%nmod==0:\n",
    "        print(i)\n",
    "        U.append(fluid.u.copy())\n",
    "        for j, iin in enumerate(insides):\n",
    "            Xin[j].append(iin.X.copy())\n",
    "            Y[j].append(iin.Y.copy())\n",
    "        for j, out in enumerate(outsides):\n",
    "            Xout[j].append(out.X.copy())"
   ]
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       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"717\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "500\n"
     ]
    }
   ],
   "source": [
    "#### Animation\n",
    "fig = plt.figure(constrained_layout=True)\n",
    "nfigs = len(Xin)\n",
    "gs = fig.add_gridspec(nfigs, nfigs+1)\n",
    "ax = fig.add_subplot(gs[:, :-1])\n",
    "ax.set_xlim([0, L])\n",
    "ax.set_ylim([0, L])\n",
    "\n",
    "axes_frame = [fig.add_subplot(gs[i, -1]) for i in range(nfigs)]\n",
    "for j, axj in enumerate(axes_frame):\n",
    "#     axj.set_title('$K={}, M={}, N_i={}$'.format(outsides[j].K, insides[j].M, len(insides[j].X)))\n",
    "    axj.set_title('$K={}, M={}, N_i={}$'.format(K, M, Nb))\n",
    "    \n",
    "#     axj.set_xlim([-1, 1])\n",
    "#     axj.set_ylim([-1, 1])\n",
    "cmap = plt.get_cmap('tab10')\n",
    "RED = plt.get_cmap('Reds')\n",
    "ims = []\n",
    "\n",
    "for i, u in enumerate(U):\n",
    "    print(i*nmod)\n",
    "    im = [show_vorticity(u, L, ax)]\n",
    "    out = show_streamlines(u, L, ax)\n",
    "    im.append(out.lines)\n",
    "    for k, X in enumerate([Xin, Xout]):\n",
    "        for j, x in enumerate(X): \n",
    "            im.append(ax.scatter(x[i][:,0]%L, x[i][:,1]%L, color=cmap(2*j+k)))\n",
    "            im.append(ax.text(0.5, 1.01, 'Time {}'.format(i*nmod*dt), horizontalalignment='center', verticalalignment='bottom', transform=ax.transAxes))\n",
    "    for j, axj in enumerate(axes_frame):\n",
    "        #### Plot Droplets in COM Frame\n",
    "        xin = Xin[j][i]\n",
    "        xout = Xout[j][i]\n",
    "        com = np.mean(xin, axis=0)\n",
    "        ins = xin - com\n",
    "        out = xout - com\n",
    "\n",
    "        im.append(axj.scatter(ins[:,0], ins[:,1], s=1000/Ni, color=cmap(0)))\n",
    "        im.append(axj.scatter(out[:,0], out[:,1], color=cmap(1)))\n",
    "        im.append(axj.scatter([out[0,0]], [out[0,1]], color='red'))  ## Mark theta=0\n",
    "        \n",
    "        ### DEBUG ####\n",
    "        yins = Y[j][i] - com\n",
    "        im.append(axj.scatter(yins[:,0], yins[:,1], s=1000/Ni, color=cmap(1)))\n",
    "#         TETHERS = np.array([[ins[i], yins[i]] for i in range(len(ins))])\n",
    "#         for tether in TETHERS:\n",
    "#             im.extend(axj.plot(tether[:,0], tether[:,1], color=RED(np.linalg.norm(tether[1]-tether[0])*N/L)))\n",
    "        \n",
    "        ## Record theta profile of each boundary\n",
    "#             THETA[j].append(np.arctan2(out[:,1], out[:,0]))\n",
    "\n",
    "\n",
    "    ims.append(im) \n",
    "        \n",
    "#### Credit: Stack Exchange  https://stackoverflow.com/questions/61932534/cannot-remove-streamplot-arrow-heads-from-matplotlib-axes\n",
    "from matplotlib import patches\n",
    "for art in ax.get_children():\n",
    "    if not isinstance(art, patches.FancyArrowPatch):\n",
    "        continue\n",
    "    art.remove()        # Method 1\n",
    "    # art.set_alpha(0)  # Method 2  \n",
    "\n",
    "\n",
    "    \n",
    "    \n",
    "# ani2 = animation.ArtistAnimation(fig, ims, interval=150, repeat_delay=1)\n",
    "# ani2.save('single_droplet.gif', writer='pillow')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "ani2 = animation.ArtistAnimation(fig, ims, interval=150, repeat_delay=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "MovieWriter ffmpeg unavailable. Trying to use pillow instead.\n"
     ]
    }
   ],
   "source": [
    "ani2.save('Droplet_sed_2.gif')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rigid Body Sedimentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0\n",
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      " 440\n",
      " 460\n",
      " 480\n",
      " 500\n"
     ]
    }
   ],
   "source": [
    "def iterate(fluid, solids):\n",
    "    ff = 0. ## Force density on fluid\n",
    "    for solid in solids:\n",
    "        solid.step_XX(fluid.u)\n",
    "        ff += solid.ff         # Force at midpoint\n",
    "#     ff += fluid.ff             # External force on fluid. NOTE: add this after solid.ff to keep numpy happy\n",
    "    ff[1][:, -1] += UPDRAFT(solids[0].YCM[1], solids[0].VCM[1], z0=z0, gamma=gamma, sigma=sigma)\n",
    "    uu=fluid.step_u(ff)        # Step Fluid Velocity\n",
    "    for solid in solids:\n",
    "        solid.step_X(uu)       # full step using midpoint velocity    \n",
    "\n",
    "# Kp = 20000\n",
    "# rad = 0.05\n",
    "# Ni = 100\n",
    "\n",
    "####################################\n",
    "  ########   Simulation   ########\n",
    "####################################\n",
    "\n",
    "#### Initialize Fluid+Droplets\n",
    "fluid = FLUID(N=N, L=L, mu=mu, dt=dt)\n",
    "insides = [RPIB2(SUNFLOWER(rad-fluid.h/2, positions[i], n=Ni), fluid.N, fluid.h, fluid.dt) for i in range(len(positions))]\n",
    "solids = insides\n",
    "\n",
    "#### Declare Forces\n",
    "for inside in insides:\n",
    "    inside.Kp = Kp    \n",
    "    inside.M = M \n",
    "#     inside.dtheta = 1.\n",
    "    inside.bForce = lambda solid, Y:  GRAV(solid, Y)\n",
    "    \n",
    "## Values that we're tracking\n",
    "delta = [[] for inside in insides]    ## Keep track of |X-Y|/h\n",
    "YCM = [[] for inside in insides]\n",
    "VCM = [[] for inside in insides]\n",
    "LL = [[] for inside in insides]\n",
    "\n",
    "U = []\n",
    "Xin = [[] for inside in insides]\n",
    "Y = [[] for inside in insides]\n",
    "for i in range(nsteps+1):\n",
    "    iterate(fluid, solids)\n",
    "    #### Keeping track of 'interior' properties\n",
    "    for j, iin in enumerate(insides):\n",
    "        delta[j].append(np.max(np.linalg.norm(iin.Y - iin.X, axis=1)))\n",
    "        YCM[j].append(iin.YCM.copy())\n",
    "        VCM[j].append(iin.VCM.copy())\n",
    "        LL[j].append(iin.L)\n",
    "        Xin[j].append(iin.X.copy())\n",
    "        Y[j].append(iin.Y.copy())\n",
    "    if i%nmod==0:\n",
    "        print('\\r {}'.format(i))\n",
    "        U.append(fluid.u.copy())\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plt.figure()\n",
    "ax1 = fig2.add_subplot(3, 2, 1)\n",
    "ax1.set_ylim([-1, 3])\n",
    "ax1.set_title('Mass Marker Convergence')\n",
    "ax1.set_ylabel('||X-Y||/h')\n",
    "ax1.set_xlabel('Timestep')\n",
    "for d in delta: ax1.plot(np.array(d)/fluid.h)\n",
    "    \n",
    "ax2 = fig2.add_subplot(3, 2, 2)       \n",
    "ax2.set_title('Angular Velocity')\n",
    "ax2.set_ylabel('$\\omega$')\n",
    "ax2.set_xlabel('Timestep')\n",
    "for i in range(len(insides)): ax2.plot(0.5*dt*np.array(LL[i])/insides[i].I0)\n",
    "    \n",
    "ax3 = fig2.add_subplot(3, 2, 3)       \n",
    "ax3.set_title('$Vx_{cm}$')\n",
    "ax3.set_xlabel('Timestep')\n",
    "for i in range(len(insides)): ax3.plot(np.array(VCM)[i][:, 0])\n",
    "\n",
    "ax3 = fig2.add_subplot(3, 2, 4)       \n",
    "ax3.set_title('$Vy_{cm}$')\n",
    "ax3.set_xlabel('Timestep')\n",
    "for i in range(len(insides)): ax3.plot(np.array(VCM)[i][:, 1])\n",
    "    \n",
    "ax3 = fig2.add_subplot(3, 2, 5)       \n",
    "ax3.set_title('$X_{cm}$')\n",
    "ax3.set_xlabel('Timestep')\n",
    "for i in range(len(insides)): ax3.plot(np.array(YCM)[i][:, 0])\n",
    "\n",
    "ax3 = fig2.add_subplot(3, 2, 6)       \n",
    "ax3.set_title('$Y_{cm}$')\n",
    "ax3.set_xlabel('Timestep')\n",
    "for i in range(len(insides)): ax3.plot(np.array(YCM)[i][:, 1])\n",
    "    \n",
    "fig2.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "#### Animation\n",
    "fig = plt.figure(constrained_layout=True)\n",
    "nfigs = len(Xin)\n",
    "gs = fig.add_gridspec(nfigs, nfigs+1)\n",
    "ax = fig.add_subplot(gs[:, :-1])\n",
    "ax.set_xlim([0, L])\n",
    "ax.set_ylim([0, L])\n",
    "\n",
    "axes_frame = [fig.add_subplot(gs[i, -1]) for i in range(nfigs)]\n",
    "for j, axj in enumerate(axes_frame):\n",
    "#     axj.set_title('$K={}, M={}, N_i={}$'.format(outsides[j].K, insides[j].M, len(insides[j].X)))\n",
    "    axj.set_title('$K={}, M={}, N_i={}$'.format(K, M, Nb))\n",
    "    \n",
    "#     axj.set_xlim([-1, 1])\n",
    "#     axj.set_ylim([-1, 1])\n",
    "cmap = plt.get_cmap('tab10')\n",
    "RED = plt.get_cmap('Reds')\n",
    "ims = []\n",
    "\n",
    "for i, u in enumerate(U):\n",
    "    ii = i*nmod\n",
    "    print(ii)\n",
    "    im = [show_vorticity(u, L, ax)]\n",
    "    out = show_streamlines(u, L, ax)\n",
    "    im.append(out.lines)\n",
    "    for k, X in enumerate([Xin]):\n",
    "        for j, x in enumerate(X): \n",
    "            im.append(ax.scatter(x[ii][:,0]%L, x[ii][:,1]%L, color=cmap(2*j+k)))\n",
    "            im.append(ax.text(0.5, 1.01, 'Time {}'.format(i*nmod*dt), horizontalalignment='center', verticalalignment='bottom', transform=ax.transAxes))\n",
    "    for j, axj in enumerate(axes_frame):\n",
    "        #### Plot Droplets in COM Frame\n",
    "        xin = Xin[j][ii]\n",
    "        com = np.mean(xin, axis=0)\n",
    "        ins = xin - com\n",
    "\n",
    "        im.append(axj.scatter(ins[:,0], ins[:,1], s=1000/Ni, color=cmap(0)))\n",
    "#         im.append(axj.scatter([ins[-1,0]], [ins[-1,1]], color='red'))  ## Mark theta=0\n",
    "        \n",
    "        ### DEBUG ####\n",
    "        yins = Y[j][i] - com\n",
    "        im.append(axj.scatter(yins[:,0], yins[:,1], s=1000/Ni, color=cmap(1)))\n",
    "        im.append(axj.scatter([yins[-1,0]], [yins[-1,1]], color='red'))  ## Mark theta=0\n",
    "        \n",
    "#         TETHERS = np.array([[ins[i], yins[i]] for i in range(len(ins))])\n",
    "#         for tether in TETHERS:\n",
    "#             im.extend(axj.plot(tether[:,0], tether[:,1], color=RED(np.linalg.norm(tether[1]-tether[0])*N/L)))\n",
    "        \n",
    "#         im.append(ax.set_title('t={}'.format(1*fluid.t)))\n",
    "\n",
    "        ## Record theta profile of each boundary\n",
    "#             THETA[j].append(np.arctan2(out[:,1], out[:,0]))\n",
    "\n",
    "\n",
    "    ims.append(im) \n",
    "        \n",
    "#### Credit: Stack Exchange  https://stackoverflow.com/questions/61932534/cannot-remove-streamplot-arrow-heads-from-matplotlib-axes\n",
    "from matplotlib import patches\n",
    "for art in ax.get_children():\n",
    "    if not isinstance(art, patches.FancyArrowPatch):\n",
    "        continue\n",
    "    art.remove()        # Method 1\n",
    "    # art.set_alpha(0)  # Method 2  \n",
    "\n",
    "\n",
    "    \n",
    "    \n",
    "# ani2 = animation.ArtistAnimation(fig, ims, interval=150, repeat_delay=1)\n",
    "# ani2.save('single_droplet.gif', writer='pillow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ani3 = animation.ArtistAnimation(fig, ims, interval=150, repeat_delay=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ani3.save('rtex_shedding.gif')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* 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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// 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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plt.figure()\n",
    "ax1 = fig2.add_subplot(2, 1, 1)\n",
    "ax1.set_ylim([-1, 3])\n",
    "for d in delta: ax1.plot(np.array(d)/fluid.h)\n",
    "    \n",
    "ax2 = fig2.add_subplot(2, 1, 2)       \n",
    "for i in range(len(insides)): ax2.plot(0.5*dt*np.array(LL[i])/insides[i].I0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# An Extension: Poisseuille Flow\n",
    "\n",
    "We can also use a \"control flow\" to try and simulate a flow through a channel. This follows the same principle as the sedimentation experiment: we "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}