OceanOpticsSpectrum.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# dynamic OceanOptics measurements in python\n",
    "### you have to install the library first: https://github.com/ap--/python-seabreeze\n",
    "for OSX:\n",
    "wget https://github.com/ap--/python-seabreeze/releases/download/python-seabreeze-v0.5.3/seabreeze-0.5.3-cp27-cp27m-macosx_10_6_intel.whl\n",
    "pip install seabreeze-0.5.3-cp27-cp27m-macosx_10_6_intel.whl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import seabreeze.spectrometers as sb\n",
    "import numpy as np\n",
    "import time\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show connected Spectrometers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<SeaBreezeDevice USB4000:USB4F06783>]\n"
     ]
    }
   ],
   "source": [
    "devices = sb.list_devices()\n",
    "print(devices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Open Spectrometer and set integration time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "int_time = 10000 # integration time in microseconds\n",
    "spec = sb.Spectrometer(devices[0])\n",
    "spec.integration_time_micros(30000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "define funtion that updates the plot with spectrometer data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def pltspectrum(ax, spec):\n",
    "    x = spec.wavelengths()\n",
    "    y = spec.intensities()\n",
    "    if ax.lines:\n",
    "        for line in ax.lines:\n",
    "            line.set_xdata(x)\n",
    "            line.set_ydata(y)\n",
    "    fig.canvas.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "random numbers for demonstration purposes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def pltrandom(ax):\n",
    "    x = range(0,100)\n",
    "    y = np.random.randint(0,100,100)\n",
    "    if ax.lines:\n",
    "        for line in ax.lines:\n",
    "            line.set_xdata(x)\n",
    "            line.set_ydata(y)\n",
    "    fig.canvas.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "generate plot and populate it with inital measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
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       "            return;\n",
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       "}\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",
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       "        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",
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       "    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;\n",
       "    var y = canvas_pos.y;\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",
       "    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 + '\">');\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 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 = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.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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     },
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     "output_type": "display_data"
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1084edbd0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,1)\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_xlim(380,800)\n",
    "ax.set_ylim(1000,10000)\n",
    "plt.plot(spec.wavelengths(),spec.intensities())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "start measurement for n measurements an wait in between each measurement 3 times the integration time (only good for fast updates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for f in range(50):\n",
    "    #pltrandom(ax)\n",
    "    pltspectrum(ax, spec)\n",
    "    time.sleep(int_time*3)"
   ]
  }
 ],
 "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": 0
}