{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing Coincidence using a Na-22 Source"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Coincidence Filtering of Sodium-22 (Na-22)\n",
    "\n",
    "Sodium 22 (Na-22) is a radioactive isotope with one less neutron than the \\\"stable\\\" form of Sodium 23. With a half life of 2.60 years, it\\'s a relatively shelf stable isotype making it conveinent in labs as a calibration. \n",
    "\n",
    "In most cases, the Na-22 emits a positron and decays into an excited Ne-22 nucleus. The Ne-22 nucleus then falls to ground state and emits of *1.2745 MeV* gamma ray. \n",
    "\n",
    "\n",
    "![alt text](data/na22_images/equation.png \"Nuclear Reaction\")\n",
    "\n",
    "After this initial nuclear decay, the emitted positron generally annilihates with an electron and that reactions emits a pair of *.511 MeV* gamma rays. Importantly, these annhilitation gamma rays are emitted in opposite directions. \n",
    "\n",
    "![alt text](data/na22_images/equation2.png \"Positron Annhilation\")\n",
    "\n",
    "Taking advantage of this, we can set up detectors opposite of each other on either side of our Na-22 source and selectively save primarily annihilation events using the FemtoDAQ Vireo's coincidence filter. \n",
    "\n",
    "![alt text](data/na22_images/setup.png \"Coincidence Setup\")\n",
    "\n",
    "### Experimental Setup\n",
    "\n",
    "The Vireo's **coincidence filter** allows you to selectively trigger on events which create a certain hit pattern on your detectors. In the case of *Na-22*, we want to only measure events which create pulses on our two detectors simultaneously. This will screen out the vast majority of noise events caused by _Ne-22*_ excitation or ambient noises such as cosmic rays. These noise sources are statistically unlikely to interact with two detectors simultaneously. Unlike the annhiliation decay which emits two opposing gamma rays perfectly in line with our detectors.  \n",
    "\n",
    "![alt text](data/na22_images/pic_of_setup.jpeg \"Picture of Setup\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **In this experiment we will:**\n",
    "\n",
    "### 1) **Collect data using 2-hit coincidence** to show detection of only the .511 MeV beta decay peak\n",
    "### 2) **Collect data without coincidence** to show detection of all sodium lines - including the 1.2745 MeV Ne-22 excitation peak"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "___\n",
    "\n",
    "## **Collecting Data**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting up Environment\n",
    "\n",
    "We're going to define some variables up front so they are easier to change later. `TRIGGER_SENSITIVITY` defines how sensitive the trigger is to capture a pulse. `NUMBER_OF_EVENTS` indicates how many events we are going to capture before stopping data collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skutils is in beta, please contact support@skutek.com with bugs, issues, and questions\n"
     ]
    }
   ],
   "source": [
    "import skutils\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "VIREO_URL = \"vireo-000019.tek\" \n",
    "TRIGGER_SENSITIVITY = 40\n",
    "NUMBER_OF_EVENTS = 100_000\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **1) Connect to your FemtoDAQ Vireo**\n",
    "\n",
    "We can use the `FemtoDAQController` class to control our digitizer remotely in this python script. The FemtoDAQ Controller contains functions to control trigger, data capture, and recording configuration. We will use it here to configure our trigger parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vireo-000019 (http://vireo-000019.tek)\n",
      "Product Revision    : VIREO100_REV_B\n",
      "Number of Channels  : 2\n",
      "Sampling Frequency  : 100.0 MHz\n",
      "ADC Bitdepth        : 14 bits\n",
      "Maximum Wave Length : 81.92us\n",
      "Firmware Version    : 5.5.0-0\n",
      "Software Version    : 5.4.0\n",
      "Linux Image Version : 5.1.1\n"
     ]
    }
   ],
   "source": [
    "vireo = skutils.FemtoDAQController(VIREO_URL, skip_version_check=True)\n",
    "print( vireo.summary() )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **2) Configure Data Recording Parameters**\n",
    "\n",
    "Before capturing data, we need to configure the instrument to trigger at the appropriate levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring Trigger Settings\n",
    "vireo.setTriggerSensitivity(0, TRIGGER_SENSITIVITY)\n",
    "vireo.setTriggerSensitivity(1, TRIGGER_SENSITIVITY)\n",
    "vireo.setTriggerXPosition(128)\n",
    "vireo.setInvertADCSignal(0, True)\n",
    "vireo.setInvertADCSignal(1, True)\n",
    "vireo.setDigitalOffset(0, 640)\n",
    "vireo.setDigitalOffset(1, 640)\n",
    "\n",
    "# Enabling Triggers \n",
    "vireo.setEnableTrigger(0, True)\n",
    "vireo.setEnableTrigger(1, True)\n",
    "\n",
    "# Configuring Pulse Windows\n",
    "vireo.setPulseHeightAveragingWindow(8)\n",
    "vireo.setTriggerActiveWindow(32)\n",
    "vireo.setPulseHeightWindow(32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "\n",
    "### **3) Collect Coincidence data**\n",
    "#### i) **Set Coincidence**: Require at Least 2 Triggers for Saved Events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring Coincidence\n",
    "vireo.configureCoincidence(\"multiplicity\",  2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ii) **Recording**: Name files with appropriate prefix and define our file format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure Recording on CH0, CH1\n",
    "vireo.configureRecording(channels_to_record=[0,1],\n",
    "                            file_recording_name_prefix = \"Na-22_with_coincidence\",\n",
    "                            file_recording_format = \"igorph\",\n",
    "                        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### iii) **Start Data Collection**: Wait until complete or a maximum timeout is reached"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "vireo.start(NUMBER_OF_EVENTS)\n",
    "# Wait for data to be collected up to a maximum of 20 minutes\n",
    "timed_out = vireo.waitUntil(timeout_time=20*60)\n",
    "vireo.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### iiii) **Download Data Files** for later analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vireo-000019 (http://vireo-000019.tek) Controller : downloaded `Na-22_with_coincidence_03.45.26PM_May16_2025_seq000001.itx` to 'C:\\Users\\Jeff\\Documents\\projects\\skutils\\docs\\examples\\Na-22_with_coincidence_03.45.26PM_May16_2025_seq000001.itx'\n"
     ]
    }
   ],
   "source": [
    "coincidence_data_files = vireo.downloadLastRunDataFiles()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "\n",
    "### **4) Collect No-Coincidence data**\n",
    "#### i) **Set No Coincidence**: Disable coincidence by setting a multiplicity of 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring Coincidence\n",
    "vireo.configureCoincidence(\"multiplicity\",  1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ii) **Recording**: Name files with appropriate prefix and define our file format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure Recording on CH0, CH1\n",
    "vireo.configureRecording(channels_to_record=[0,1],\n",
    "                            file_recording_name_prefix = \"Na-22_with_no_coincidence\",\n",
    "                            file_recording_format = \"igorph\",\n",
    "                        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### iii) **Start Data Collection**: Wait until complete or a maximum timeout is reached"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "vireo.start(NUMBER_OF_EVENTS)\n",
    "# Wait for data to be collected up to a maximum of 20 minutes\n",
    "timed_out = vireo.waitUntil(timeout_time=20*60)\n",
    "vireo.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### iiii) **Download Data Files** for later analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vireo-000019 (http://vireo-000019.tek) Controller : downloaded `Na-22_with_no_coincidence_04.05.28PM_May16_2025_seq000001.itx` to 'C:\\Users\\Jeff\\Documents\\projects\\skutils\\docs\\examples\\Na-22_with_no_coincidence_04.05.28PM_May16_2025_seq000001.itx'\n"
     ]
    }
   ],
   "source": [
    "no_coincidence_data_files = vireo.downloadLastRunDataFiles()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_____\n",
    "_____\n",
    "\n",
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **5) Loading Data**: Grab Pulse Heights for every Event"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading in coincidence data\n",
    "ch0_coincidence_pulse_heights = []\n",
    "ch1_coincidence_pulse_heights = []\n",
    "for event in skutils.quickLoad(coincidence_data_files):\n",
    "    ch0_coincidence_pulse_heights.append(event.pulse_heights[0])\n",
    "    ch1_coincidence_pulse_heights.append(event.pulse_heights[1])\n",
    "\n",
    "\n",
    "# loading in no coincidence data\n",
    "ch0_no_coincidence_pulse_heights = []\n",
    "ch1_no_coincidence_pulse_heights = []\n",
    "for event in skutils.quickLoad(no_coincidence_data_files):\n",
    "    ch0_no_coincidence_pulse_heights.append(event.pulse_heights[0])\n",
    "    ch1_no_coincidence_pulse_heights.append(event.pulse_heights[1])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **6) Histogramming**: Calculate a Pulse Height Histogram\n",
    "\n",
    "Pulse Heights here refer to the DSP Pulse Height quantity calculated in firmware, which is subject to filtering/averaging \n",
    "and configured in your data collection setup. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bin_width = 5\n",
    "num_bins = int((x_max - x_min) / bin_width)\n",
    "\n",
    "coincidence_hist0, edges = np.histogram(ch0_coincidence_pulse_heights, bins=num_bins, range=(0, x_max))\n",
    "coincidence_hist1, _     = np.histogram(ch1_coincidence_pulse_heights, bins=num_bins, range=(0, x_max))\n",
    "no_coincidence_hist0, _  = np.histogram(ch0_no_coincidence_pulse_heights, bins=num_bins, range=(0, x_max))\n",
    "no_coincidence_hist1, _  = np.histogram(ch1_no_coincidence_pulse_heights, bins=num_bins, range=(0, x_max))\n",
    "\n",
    "bin_centers = (edges[1:] + edges[:-1]) / 2\n",
    "\n",
    "fig,axes = plt.subplots(2,1)\n",
    "fig.suptitle(\"Comparison of histograms between coincidence and no-coincidence for Na-22\")\n",
    "axes[0].set_title(\"Channel 0\")\n",
    "axes[0].set_xlabel(\"Pulse Height\")\n",
    "axes[0].set_ylabel(\"Counts\")\n",
    "axes[0].set_yscale('log')\n",
    "axes[0].plot(bin_centers,no_coincidence_hist0, label=\"No Coincidence\")\n",
    "axes[0].plot(bin_centers,coincidence_hist0,    label=\"Coincidence\")\n",
    "axes[0].legend()\n",
    "\n",
    "axes[1].set_title(\"Channel 1\")\n",
    "axes[1].set_xlabel(\"Pulse Height\")\n",
    "axes[1].set_yscale('log')\n",
    "axes[1].set_ylabel(\"Counts\")\n",
    "axes[1].plot(bin_centers,no_coincidence_hist1, label=\"No Coincidence\")\n",
    "axes[1].plot(bin_centers,coincidence_hist1,    label=\"Coincidence\")\n",
    "axes[1].legend()\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "We can see the obvious difference between coincidence (orange) and no-coincidence (blue) histograms. No-Coincidence has a much more prominent noise peak near bin0. Without coincidence suppression, pulse heights are saved for all channels whether or the channel triggered. This results in large \"noise\" peaks more or less equal to the channel baseline. \n",
    "\n",
    "Coincidence histograms also notably only have 1 major signal peak - the 0.511MeV line beta decay line produced by positron and which creates a pair of photons. No-Coincidence histograms see a secondary peak produced by the single photon released by Ne*-22 excitation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}