camera-maps-illustration-01.ipynb

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    "# Demonstration of the PYME camera map infrastructure\n",
    "\n",
    "## With applications to test CMOS image algorithms"
   ]
  },
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   "source": [
    "# some useful imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
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    "# import our io and map handling routines\n",
    "from PYME.localization.remFitBuf import CameraInfoManager\n",
    "ci = CameraInfoManager()\n",
    "\n",
    "import PYME.Analysis.gen_sCMOS_maps as gmaps\n",
    "from PYME.IO.MetaDataHandler import NestedClassMDHandler\n",
    "\n",
    "md = NestedClassMDHandler()"
   ]
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    "### Making a test metadata structure\n",
    "\n",
    "Here we make a metadata structure from scratch to test the infrastructure of reading maps which matches in terms of camera data and ROI size etc.\n",
    "\n",
    "For actual data this metadata should be directly supplied by the metadata stored with the acquired data."
   ]
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     "text": [
      "ROI half size is 7\n"
     ]
    }
   ],
   "source": [
    "def ROISZscale(md,refsize=7,refscale=0.1,minsize=5):\n",
    "    roisize = max(int(refsize*refscale/md['voxelsize.x']+0.9),minsize)\n",
    "    print 'ROI half size is %d' % roisize\n",
    "    return roisize\n",
    "\n",
    "md['voxelsize.x'] = 0.1\n",
    "md['voxelsize.y'] = 0.1\n",
    "md['voxelsize.z'] = 0.05\n",
    "\n",
    "#what ROI size should we use\n",
    "ROI_HALF_SIZE = ROISZscale(md)\n",
    "ROI_SIZE = 2*ROI_HALF_SIZE + 1\n",
    "\n",
    "md['Camera.ADOffset'] = 100.0\n",
    "md['Camera.EMGain'] = 1.0\n",
    "md['Camera.ElectronsPerCount'] = 0.5\n",
    "md['Camera.NoiseFactor'] = 1.0 #ignored / calculated de-novo for simulation\n",
    "md['Camera.ReadNoise'] = 1.4 #ignored for sCMOS\n",
    "md['Camera.TrueEMGain'] = 1.0\n",
    "\n",
    "#NB ROI width and height in metadata must match the simulation ROI size\n",
    "md['Camera.ROIHeight'] = ROI_SIZE\n",
    "md['Camera.ROIPosX'] = 1024\n",
    "md['Camera.ROIPosY'] = 1024\n",
    "md['Camera.ROIWidth'] = ROI_SIZE\n",
    "\n",
    "md['Camera.SerialNumber'] = 'VSC-02858'\n",
    "\n",
    "md['Camera.IntegrationTime'] = 0.1"
   ]
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     "text": [
      "Dark map path is /Users/csoe002/PYMEData/CALIBRATION/VSC-02858/dark_100ms.tif\n",
      "Variance map path is /Users/csoe002/PYMEData/CALIBRATION/VSC-02858/variance_100ms.tif\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    darkname = gmaps.mkDefaultPath('dark',md,create=False)\n",
    "except ValueError:\n",
    "    print 'calibration dir for camera does not exist'\n",
    "try:\n",
    "    varname = gmaps.mkDefaultPath('variance',md,create=False)\n",
    "except ValueError:\n",
    "    print 'calibration dir for camera does not exist'\n",
    "\n",
    "print('Dark map path is %s' % darkname)\n",
    "print('Variance map path is %s' % varname)\n",
    "md['Camera.DarkMapID'] = darkname\n",
    "md['Camera.VarianceMapID'] = varname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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     "text": [
      "filename == /Users/csoe002/PYMEData/CALIBRATION/VSC-02858/variance_100ms.tif\n",
      "/Users/csoe002/PYMEData/CALIBRATION/VSC-02858/variance_100ms.tif\n",
      "[2048, 2048, 1, 1]\n",
      "[2048, 2048, 1, 1]\n",
      "filename == /Users/csoe002/PYMEData/CALIBRATION/VSC-02858/dark_100ms.tif\n",
      "/Users/csoe002/PYMEData/CALIBRATION/VSC-02858/dark_100ms.tif\n",
      "[2048, 2048, 1, 1]\n",
      "[2048, 2048, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "# based on all of this, the 'gain' according to the *** paper\n",
    "# should be\n",
    "#     gain = 1.0/(flat*mdh['Camera.ElectronsPerCount'])\n",
    "\n",
    "# we need to figure out what we actually need, in terms of units\n",
    "gain = 1.0/(ci.getFlatfieldMap(md)*md['Camera.ElectronsPerCount']) # in units of ADUperElectron\n",
    "var = ci.getVarianceMap(md) # in electron^2\n",
    "offset = ci.getDarkMap(md) # in ADUs\n"
   ]
  },
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   "source": [
    "# this one we only need for interactive checks in a separate window - very convenient as we share the kernal and namespace for quick code evaluations\n",
    "# %qtconsole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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       "    this.format_dropdown = fmt_picker[0];\n",
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       "\n",
       "\n",
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       "    fig.ondownload(fig, format);\n",
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       "\n",
       "\n",
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       "\n",
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       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
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       "    // Request the server to send over a new figure.\n",
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       "}\n",
       "\n",
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       "    fig.image_mode = msg['mode'];\n",
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       "\n",
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       "\n",
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       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
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       "             * 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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar instance at 0x114739ea8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.subplot(1,2,1)\n",
    "plt.imshow(np.sqrt(var),cmap='hot') # dark noise in units of e-\n",
    "plt.colorbar()\n",
    "plt.subplot(1,2,2)\n",
    "plt.imshow(offset,cmap='hot')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}