MagDipole.ipynb

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    "%matplotlib notebook\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
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    "### Define functions for calculation\n",
    "\n",
    "* MagneticMonopoleField(obsloc,poleloc=(0.,0.,0.),Q=1)\n",
    "* VerticalMagneticLongDipoleLine(radius,L,stepsize=0.1,nstepmax=1000,dist_tol=0.5)\n",
    "* MagneticLongDipoleLine(dipoleloc,dipoledec,dipoleinc,dipoleL,radii,Nazi=10)\n",
    "* MagneticLongDipoleField(dipoleloc,dipoledec,dipoleinc,dipoleL,obsloc,dipolemoment=1.)"
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    "def MagneticMonopoleField(obsloc,poleloc=(0.,0.,0.),Q=1):\n",
    "    # relative obs. loc. to pole, assuming pole at origin\n",
    "    dx, dy, dz = obsloc[0]-poleloc[0], obsloc[1]-poleloc[1], obsloc[2]-poleloc[2]\n",
    "    r = np.sqrt(dx**2+dy**2+dz**2)\n",
    "    Bx = Q * 1e-7 / r**2 * dx\n",
    "    By = Q * 1e-7 / r**2 * dy\n",
    "    Bz = Q * 1e-7 / r**2 * dz\n",
    "    return Bx, By, Bz\n",
    "\n",
    "\n",
    "def VerticalMagneticLongDipoleLine(radius,L,stepsize=0.1,nstepmax=1000,dist_tol=0.5):\n",
    "    yloc, zloc = [radius], [0.]\n",
    "    dist2pole = np.sqrt( yloc[0]**2 + (zloc[0]-L/2)**2 )\n",
    "    # loop to get the lower half\n",
    "    count = 1\n",
    "    while (dist2pole > dist_tol) & (count<nstepmax):\n",
    "        _, By1, Bz1 = MagneticMonopoleField((0.,yloc[-1],zloc[-1]),(0.,0.,L/2),Q=1)\n",
    "        _, By2, Bz2 = MagneticMonopoleField((0.,yloc[-1],zloc[-1]),(0.,0.,-L/2),Q=-1)\n",
    "        By, Bz = By1+By2, Bz1+Bz2\n",
    "        B = np.sqrt(By**2 + Bz**2)\n",
    "        By, Bz = By/B*stepsize, Bz/B*stepsize\n",
    "        yloc = np.append(yloc, yloc[-1]+By)\n",
    "        zloc = np.append(zloc, zloc[-1]+Bz)\n",
    "        dist2pole = np.sqrt( yloc[-1]**2 + (zloc[-1]-L/2)**2 )\n",
    "        count += 1\n",
    "    # mirror to get the upper half\n",
    "    yloc = np.append(yloc[-1:0:-1],yloc)\n",
    "    zloc = np.append(-zloc[-1:0:-1],zloc)\n",
    "    return yloc, zloc\n",
    "\n",
    "\n",
    "def MagneticLongDipoleLine(dipoleloc,dipoledec,dipoleinc,dipoleL,radii,Nazi=10):\n",
    "    x0, y0, z0 = dipoleloc[0], dipoleloc[1], dipoleloc[2]\n",
    "    \n",
    "    # rotation matrix\n",
    "    theta, alpha = -np.pi*(dipoleinc+90.)/180., -np.pi*dipoledec/180.\n",
    "    Rx = np.array([[1.,0.,0.],[0.,np.cos(theta),-np.sin(theta)],[0.,np.sin(theta),np.cos(theta)]])\n",
    "    Rz = np.array([[np.cos(alpha),-np.sin(alpha),0.],[np.sin(alpha),np.cos(alpha),0.],[0.,0.,1.]])\n",
    "    R = np.dot(Rz,Rx) # Rz @ Rx\n",
    "\n",
    "    azimuth = np.linspace(0.,2*np.pi,num=Nazi,endpoint=False)\n",
    "    xloc, yloc, zloc = [], [], []\n",
    "    for r in radii:\n",
    "        hloc, vloc = VerticalMagneticLongDipoleLine(r,dipoleL,stepsize=0.5)\n",
    "        for a in azimuth:\n",
    "            x, y, z = np.sin(a)*hloc, np.cos(a)*hloc, vloc\n",
    "            xyz = R @ np.vstack((x,y,z))\n",
    "            xloc.append(xyz[0]+x0)\n",
    "            yloc.append(xyz[1]+y0)\n",
    "            zloc.append(xyz[2]+z0)\n",
    "    return xloc, yloc, zloc\n",
    "\n",
    "\n",
    "def MagneticLongDipoleField(dipoleloc,dipoledec,dipoleinc,dipoleL,obsloc,dipolemoment=1.):\n",
    "    dec, inc, L = np.radians(dipoledec), np.radians(dipoleinc), dipoleL\n",
    "    x1 = L/2 * np.cos(inc) * np.sin(dec) \n",
    "    y1 = L/2 * np.cos(inc) * np.cos(dec) \n",
    "    z1 = L/2 * -np.sin(inc)\n",
    "    x2, y2, z2 = -x1, -y1, -z1\n",
    "    Q = dipolemoment * 4e-7 * np.pi / L \n",
    "    Bx1, By1, Bz1 = MagneticMonopoleField(obsloc,(x1+dipoleloc[0],y1+dipoleloc[1],z1+dipoleloc[2]),Q=Q)\n",
    "    Bx2, By2, Bz2 = MagneticMonopoleField(obsloc,(x2+dipoleloc[0],y2+dipoleloc[1],z2+dipoleloc[2]),Q=-Q)\n",
    "    return Bx1+Bx2, By1+By2, Bz1+Bz2"
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   "source": [
    "### Define a magnetic dipole\n",
    "\n",
    "A dipole is defined in the section below using\n",
    "* dipoleloc: x, y, z location of the dipole center\n",
    "* dipoledec: declination of the dipole's direction in degree; north = 0; positive clockwise\n",
    "* dipoleinc: declination of the dipole's direction in degree; horizontal = 0; positive down\n",
    "* dipoleL: length of the dipole *L* or the distance between two opposite charges *Q* that make the dipole\n",
    "* dipolemoement: $m=\\frac{QL}{\\mu_0}$\n"
   ]
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   "execution_count": 17,
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   "source": [
    "# define a dipole\n",
    "dipoleloc = (0.,0.,-1.)\n",
    "dipoleL = 2.\n",
    "dipoledec, dipoleinc = 0., 90.\n",
    "dipolemoment = 1e13"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the Earth's magnetic field $B_0$\n",
    "$B_0$ is used to calcualte the total field anomaly, which is the projection of the anomalous vector field onto the earth's field (inner product).\n",
    "* B0: the magnitude of the earth's field\n",
    "* Binc: inclination of the earth's field\n",
    "* Bdec: declination of the earth's field"
   ]
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   "source": [
    "# geomagnetic field\n",
    "B0, Binc, Bdec = 53600e-9, 90., 0. # in Tesla, degree, degree\n",
    "B0x = B0*np.cos(np.radians(Binc))*np.sin(np.radians(Bdec))\n",
    "B0y = B0*np.cos(np.radians(Binc))*np.cos(np.radians(Bdec))\n",
    "B0z = -B0*np.sin(np.radians(Binc))"
   ]
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   "cell_type": "markdown",
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   "source": [
    "### Define the observations\n",
    "Four data plots will be generated in the figure: magnetic anomalous field map (contour) at a certain elevation, magnetic anomalous field data (curve) along a x-profile and a y-profile, and the magnetic field lines of the dipole. \n",
    "* xmin, xmax, ymin, ymax: the outer bounds of the survey grid\n",
    "* z: elevation at which the data map is measured\n",
    "* profile_x, profile_y: x-coordinate of y-profile, y-coordinate of x-profile\n",
    "* h: grid interval\n",
    "* radii: how far the field lines expand; can plot multiple layers if given (r1, r2, ...)\n",
    "* Nazi: number of azimuth angles for the field line"
   ]
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   "execution_count": 19,
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   "source": [
    "# set observation grid\n",
    "xmin, xmax, ymin, ymax, z = -5., 5., -5., 5., 1. # x, y bounds and elevation\n",
    "profile_x = 0. # x-coordinate of y-profile\n",
    "profile_y = 0. # y-coordinate of x-profile\n",
    "h = 0.2 # grid interval\n",
    "radii = (2., 5.) # how many layers of field lines for plotting\n",
    "Nazi = 10 # number of azimuth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate data for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
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   "source": [
    "# get field lines\n",
    "linex, liney, linez = MagneticLongDipoleLine(dipoleloc,dipoledec,dipoleinc,dipoleL,radii,Nazi)\n",
    "\n",
    "# get map\n",
    "xi, yi = np.meshgrid(np.r_[xmin:xmax+h:h], np.r_[ymin:ymax+h:h])\n",
    "x1, y1 = xi.flatten(), yi.flatten()\n",
    "z1 = np.full(x1.shape,z)\n",
    "Bx, By, Bz = np.zeros(len(x1)), np.zeros(len(x1)), np.zeros(len(x1))\n",
    "for i in np.arange(len(x1)):\n",
    "    Bx[i], By[i], Bz[i] = MagneticLongDipoleField(dipoleloc,dipoledec,dipoleinc,dipoleL,(x1[i],y1[i],z1[i]),dipolemoment)\n",
    "Ba1 = np.dot(np.r_[B0x,B0y,B0z], np.vstack((Bx,By,Bz)) )\n",
    "\n",
    "# get x-profile\n",
    "x2 = np.r_[xmin:xmax+h:h]\n",
    "y2, z2 = np.full(x2.shape,profile_y), np.full(x2.shape,z)\n",
    "Bx, By, Bz = np.zeros(len(x2)), np.zeros(len(x2)), np.zeros(len(x2))\n",
    "for i in np.arange(len(x2)):\n",
    "    Bx[i], By[i], Bz[i] = MagneticLongDipoleField(dipoleloc,dipoledec,dipoleinc,dipoleL,(x2[i],y2[i],z2[i]),dipolemoment)\n",
    "Ba2 = np.dot( np.r_[B0x,B0y,B0z], np.vstack((Bx,By,Bz)) )\n",
    "\n",
    "# get y-profile\n",
    "y3 = np.r_[ymin:ymax+h:h]\n",
    "x3, z3 = np.full(y3.shape,profile_x), np.full(y3.shape,z)\n",
    "Bx, By, Bz = np.zeros(len(x3)), np.zeros(len(x3)), np.zeros(len(x3))\n",
    "for i in np.arange(len(x3)):\n",
    "    Bx[i], By[i], Bz[i] = MagneticLongDipoleField(dipoleloc,dipoledec,dipoleinc,dipoleL,(x3[i],y3[i],z3[i]),dipolemoment)\n",
    "Ba3 = np.dot( np.r_[B0x,B0y,B0z] , np.vstack((Bx,By,Bz)) )"
   ]
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   "cell_type": "markdown",
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   "source": [
    "### 3D plot of field lines and data\n",
    "* Color bar in nT\n",
    "* Spatial distance in meter\n",
    "* Profile data only reflects shape of anomaly and positivity"
   ]
  },
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   "cell_type": "code",
   "execution_count": 21,
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       "        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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // 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",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-9.0, 7.5)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca(projection='3d')\n",
    "\n",
    "# plot field lines\n",
    "for lx,ly,lz in zip(linex,liney,linez):\n",
    "    ax.plot(lx,ly,lz,'-',markersize=1)\n",
    "\n",
    "# plot map\n",
    "ax.scatter(x1,y1,z1,s=2,alpha=0.3)\n",
    "Bt = Ba1.reshape(xi.shape)*1e9 # contour and color scale in nT \n",
    "c = ax.contourf(xi,yi,Bt,alpha=1,zdir='z',offset=z-max(radii)*2,cmap='jet',\n",
    "                  levels=np.linspace(Bt.min(),Bt.max(),50,endpoint=True))\n",
    "fig.colorbar(c)\n",
    "\n",
    "# auto-scaling for profile plot\n",
    "ptpmax = np.max((Ba2.ptp(),Ba3.ptp())) # dynamic range\n",
    "autoscaling = np.max(radii) / ptpmax\n",
    "\n",
    "# plot x-profile\n",
    "ax.scatter(x2,y2,z2,s=2,c='black',alpha=0.3)\n",
    "ax.plot(x2,Ba2*autoscaling,zs=ymax,c='black',zdir='y')\n",
    "\n",
    "# plot y-profile\n",
    "ax.scatter(x3,y3,z3,s=2,c='black',alpha=0.3)\n",
    "ax.plot(y3,Ba3*autoscaling,zs=xmin,c='black',zdir='x')\n",
    "\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "\n",
    "ax.set_xlim(xmin, xmax)\n",
    "ax.set_ylim(ymin, ymax)\n",
    "ax.set_zlim(z-max(radii)*2, max(radii)*1.5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}