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      "cell_type": "code",
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      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Gaussian spot centroid detection\n\nThis demo shows how the ``itom.algorithms`` can be used.\nIn this example a camera ``DummyGrabber`` is used to acquire a moving gaussian spot.\nFor the centroid detection the ``itom.algorithms.centroidxy`` function is used. \nFinally, this examples shows how a centroid position marker is added to the gaussian spot image.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>For older ``itom`` versions the ``itom.filter`` function is used for the centroidXY algorithm.\n    By using the itom.algorithms you will get the algorithms information by a pop-up during typing.</p></div>\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from itom import dataIO\nfrom itom import dataObject\nfrom itom import plot2\nfrom itom import timer\n\ntry:\n    from itom import algorithms\n\n    hasItomAlgo = True\nexcept ImportError:\n    from itom import filter\n\n    hasItomAlgo = False\n    print(\n        \"The itom.algorithms module cannot be used because\" \"of an older itom version. Use the itom.filter functions.\"\n    )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Constructor of the live gaussianSpot centroid detection.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "class GaussianSpotCentroidDetection:\n    def __init__(self):\n        \"\"\"Constructor function of the class.\"\"\"\n        # first initialize the DummyGrabber with a gaussianSpot as private member\n        self.__cam = dataIO(\"DummyGrabber\", imageType=\"gaussianSpot\")\n        self.__cam.startDevice()\n\n        # define a dataobject for the gaussienSpot image as a public member\n        self.dObj = dataObject()\n        self.__cam.acquire()\n        self.__cam.getVal(self.dObj)\n        self.dObj = self.__defineDObj(self.dObj)\n\n        # plot index and handle as private member\n        self.__plotHandle = None\n        self.__plotIndex = None\n\n        # define timer to update live image\n        self.__liveTimer = timer(50, self.__updateTimerCallBack, name=\"liveTimer\")\n\n        return\n\n    ###############################################################################\n    # Callback function to update the live image.\n\n    def __updateTimerCallBack(self):\n        \"\"\"Callback function to update the live image.\"\"\"\n        # stop live time if plot window is closed\n        if self.__plotHandle:\n            if not self.__plotHandle.exists():\n                self.__liveTimer.stop()\n                return\n\n        # acquire and get image\n        self.__cam.acquire()\n        self.__cam.getVal(self.dObj)\n\n        # calculate the centroid of the gaussianSpot\n        if hasItomAlgo:  # new itom.algorithms with auto completion and docstring in pop-up\n            [intensityX, intensityY, centroidX, centroidY] = algorithms.centroidXY(self.dObj)\n        else:  # old itom.filter\n            [intensityX, intensityY, centroidX, centroidY] = filter(\"centroidXY\", self.dObj)\n\n        print(\n            \"Centroid (x, y) position: {:.3f} {}, {:.3f} {}\".format(\n                centroidX, self.dObj.axisUnits[1], centroidY, self.dObj.axisUnits[0]\n            )\n        )\n\n        # create the centroid xy marker\n        centroidMarker = dataObject([2, 1], \"float32\")\n        centroidMarker[0, :] = centroidY\n        centroidMarker[1, :] = centroidX\n\n        # plot the camera image with marked centroid position\n        if not self.__plotHandle:  # open figure window by first time\n            [self.__plotIndex, self.__plotHandle] = plot2(\n                self.dObj, properties={\"keepAspectRatio\": True, \"colorBarVisible\": True, \"colorMap\": \"viridis\"}\n            )\n\n        else:  # replot the figure\n            self.__plotHandle.call(\"replot\")\n\n        # delete markers and plot the new one\n        if self.__plotHandle:\n            self.__plotHandle.call(\"deleteMarkers\")\n            self.__plotHandle.call(\"plotMarkers\", centroidMarker, \"r+25;2\", \"centroid\", 0)\n\n        return\n\n    ###############################################################################\n    # Function to defines the dataObject by meta information.\n\n    def __defineDObj(self, dObj: dataObject) -> dataObject:\n        \"\"\"Private function to define the meta information of the image dataObject.\n\n        Args:\n            image (dataObject): 2D image\n\n        Returns:\n            dataObject: 2D image with define meta information\n        \"\"\"\n        # define dataobject\n        dObj.setAxisDescription(0, \"y axis\")\n        dObj.setAxisDescription(1, \"x axis\")\n        dObj.setAxisUnit(0, \"\\xb5m\")\n        dObj.setAxisUnit(1, \"\\xb5m\")\n        dObj.setAxisScale(0, 10e-3)  # pixel pitch of 10 \\xb5m\n        dObj.setAxisScale(1, 10e-3)  # pixel pitch of 10 \\xb5m\n        dObj.valueDescription = \"intensity\"\n        dObj.valueUnit = \"counts\"\n\n        return dObj\n\n\nif __name__ == \"__main__\":\n    gaussianSpotCentroid = GaussianSpotCentroidDetection()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://../../_static/demoGaussianSpotCentroidDetection_1.png\" width=\"100%\">\n\n"
      ]
    }
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