{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b0a12025-2961-432c-ab19-16f219698574",
   "metadata": {},
   "source": [
    "# Histogramming Pulse Summary (DSP) Quantities on FemtoDAQ Vireo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "424d2e32-e203-4c45-9326-a83617f89023",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import skutils"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbe38a58-37b4-4d5f-8a7d-fa1bf6714417",
   "metadata": {},
   "source": [
    "## Put your file paths here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d411f695-00da-4c1f-8c19-234b800cf417",
   "metadata": {},
   "outputs": [],
   "source": [
    "FILENAMES = [r\"C:\\Users\\SkuTek\\Downloads\\cs137_relative_timestamp_test_03.07.06PM_Dec05_2025_seq000001.itx\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d0200f3-3c2a-4f3e-8ae7-ff667d6b633f",
   "metadata": {},
   "source": [
    "## Predefine Quantity lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "da6b7532-4cdd-4646-9543-2f7e218910ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Channel 0 Data\n",
    "ch0_pulse_heights       = []\n",
    "ch0_trigger_heights     = []\n",
    "ch0_relative_timestamps = []\n",
    "# Channel 1 Data\n",
    "ch1_pulse_heights       = []\n",
    "ch1_trigger_heights     = []\n",
    "ch1_relative_timestamps = []\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97f47ba9-1b8a-4d0d-abdc-9feef2a5a1a9",
   "metadata": {},
   "source": [
    "## Iterate through events and append to the quantity lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "95a10b43-ecb7-4be5-9ee2-f91a62b64008",
   "metadata": {},
   "outputs": [],
   "source": [
    "for event in skutils.quickLoad(FILENAMES):\n",
    "    # Channel0\n",
    "    ch0_pulse_heights.append      ( event[0].pulse_height               )\n",
    "    ch0_trigger_heights.append    ( event[0].trigger_height             )\n",
    "    ch0_relative_timestamps.append( event[0].relative_channel_timestamp )\n",
    "    \n",
    "    # Channel1\n",
    "    ch1_pulse_heights.append      ( event[1].pulse_height               )\n",
    "    ch1_trigger_heights.append    ( event[1].trigger_height             )\n",
    "    ch1_relative_timestamps.append( event[1].relative_channel_timestamp )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5633d9e4-c1d2-4594-91ac-d38a832373e9",
   "metadata": {},
   "source": [
    "## Example 2D histogram of Pulse Heights "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5b5faccf-9ba4-47c8-9eee-6cf35281e67f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax1.set_xlabel(\"Channel1 Scionx\")\n",
    "ax1.set_ylabel(\"Channel1 Scionx with 80ns wire delay\")\n",
    "ax1.set_title(\"Relative Timestamps between channels with Na22 Source multiplicity=2 coincidence\")\n",
    "res = ax1.hist2d(ch0_relative_timestamps, ch1_relative_timestamps, bins=[range(0,16,2),range(0,16,2)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "09fd3e20-089c-4c5f-ba83-213c637ac893",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot:\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.set_xlabel(\"channel0 pulse heights\")\n",
    "ax.set_ylabel(\"channel1 pulse heights\")\n",
    "ax.set_title(\"Channel Pulse Heights\")\n",
    "res = ax.hist2d(ch0_pulse_heights, ch1_pulse_heights, bins=[range(-64,64,1),range(-64,64,1)])\n"
   ]
  }
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