326 lines
9.6 KiB
Plaintext
326 lines
9.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Experimental Data Calibration Pipeline\n",
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"\n",
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"Interactive workflow for processing raw CAMAC MCA binary spectra:\n",
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"read -> subtract -> calibrate -> livetime -> validate -> export\n",
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"\n",
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"## Prerequisites\n",
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"- Raw binary spectrum files (A*.DAT format)\n",
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"- Am-241 calibration file (CAM1.DAT)\n",
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"- Pulser frequency and real time (from calibration run metadata)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib\n",
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"# Use non-interactive backend only when no display is available (e.g. jupyter execute)\n",
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"import matplotlib as mpl\n",
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"try:\n",
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" import matplotlib.pyplot as plt\n",
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" # Check if we're in a headless environment\n",
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" import os\n",
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" if not os.environ.get(\"DISPLAY\") and not os.environ.get(\"WAYLAND_DISPLAY\"):\n",
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" mpl.use(\"Agg\")\n",
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"except ImportError:\n",
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" mpl.use(\"Agg\")\n",
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" import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
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"from exp_data.pipeline import process_spectrum, process_run_sequence\n",
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"from exp_data.root_io import write_spectrum, read_spectrum\n",
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"from exp_data.livetime import LivetimeDetermination\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Configuration"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Paths\n",
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"RAW_FILE = \"../data/raw/A1\"\n",
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"CALIBRATION_FILE = \"../data/raw/CAM1.DAT\"\n",
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"RUN_DIR = \"../data/raw/\"\n",
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"\n",
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"# Pulser parameters (from calibration run metadata)\n",
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"PULSER_FREQUENCY_HZ = 100.0\n",
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"REAL_TIME_SEC = 3600.0"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Raw Spectrum Visualization\n",
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"Visualize raw spectra before calibration to identify peaks and verify calibration source."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Visualize raw spectra before calibration\n",
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"# This helps identify what calibration source is actually present\n",
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"\n",
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"# Detect header size from file\n",
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"def detect_header_size(filepath):\n",
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" \"\"\"Detect MCA header size by checking for binary pattern.\"\"\"\n",
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" with open(filepath, 'rb') as f:\n",
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" header = f.read(128)\n",
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" # Check if first 32 bytes look like a header (small ints)\n",
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" # and bytes 32-128 also look like header\n",
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" # Simple heuristic: if file is exactly 32 + 4096*4 = 16412, header=32\n",
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" # If file is 128 + 4096*4 = 16512, header=128\n",
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" import os\n",
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" size = os.path.getsize(filepath)\n",
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" expected_32 = 32 + 4096 * 4\n",
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" expected_128 = 128 + 4096 * 4\n",
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" if size == expected_32:\n",
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" return 32\n",
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" elif size == expected_128:\n",
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" return 128\n",
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" else:\n",
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" # Try to detect by checking if byte 32 looks like an int\n",
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" with open(filepath, 'rb') as f:\n",
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" f.seek(32)\n",
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" test = f.read(4)\n",
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" return 32 # default\n",
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"\n",
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"# --- Raw run spectrum ---\n",
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"header_size = detect_header_size(RAW_FILE)\n",
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"with open(RAW_FILE, 'rb') as f:\n",
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" f.read(header_size)\n",
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" raw_counts = np.fromfile(f, dtype=np.int32, count=4096)\n",
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"\n",
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"fig, axes = plt.subplots(2, 2, figsize=(14, 8))\n",
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"\n",
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"ax = axes[0, 0]\n",
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"ax.plot(raw_counts, 'b-', linewidth=0.5)\n",
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"ax.set_title('Raw Run Spectrum (counts vs channel)')\n",
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"ax.set_xlabel('Channel')\n",
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"ax.set_ylabel('Counts')\n",
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"ax.set_xlim(0, min(200, len(raw_counts)))\n",
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"\n",
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"ax = axes[0, 1]\n",
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"ax.plot(raw_counts, 'b-', linewidth=0.5)\n",
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"ax.set_title('Raw Run Spectrum (full range)')\n",
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"ax.set_xlabel('Channel')\n",
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"ax.set_ylabel('Counts')\n",
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"\n",
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"# --- Calibration spectrum ---\n",
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"with open(CALIBRATION_FILE, 'rb') as f:\n",
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" f.read(128) # CAM files have 128-byte header\n",
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" cal_counts = np.fromfile(f, dtype=np.int32, count=4096)\n",
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"\n",
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"ax = axes[1, 0]\n",
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"ax.plot(cal_counts, 'r-', linewidth=0.5)\n",
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"ax.set_title('Calibration Spectrum (counts vs channel)')\n",
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"ax.set_xlabel('Channel')\n",
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"ax.set_ylabel('Counts')\n",
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"ax.set_xlim(0, min(200, len(cal_counts)))\n",
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"\n",
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"ax = axes[1, 1]\n",
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"ax.plot(cal_counts, 'r-', linewidth=0.5)\n",
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"ax.set_title('Calibration Spectrum (full range)')\n",
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"ax.set_xlabel('Channel')\n",
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"ax.set_ylabel('Counts')\n",
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"\n",
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"plt.tight_layout()\n",
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"plt.show()\n",
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"\n",
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"# Print some stats\n",
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"print(f'Raw run: {len(raw_counts)} channels, max={raw_counts.max()} at ch {np.argmax(raw_counts)}')\n",
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"print(f'Calibration: {len(cal_counts)} channels, max={cal_counts.max()} at ch {np.argmax(cal_counts)}')\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Process Single Spectrum"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"result = process_spectrum(\n",
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" raw_path=RAW_FILE,\n",
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" calibration_path=CALIBRATION_FILE,\n",
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" pulser_frequency_hz=PULSER_FREQUENCY_HZ,\n",
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" real_time_sec=REAL_TIME_SEC,\n",
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")\n",
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"\n",
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"print(f\"Validation: {'PASSED' if result.validation_passed else 'FAILED'}\")\n",
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"print(f\"Calibration chi2/dof: {result.calibration.chi2_per_dof:.4f}\")\n",
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"for msg in result.validation_messages:\n",
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" print(f\" {msg}\")\n",
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"if result.livetime:\n",
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" print(f\"Live-time fraction: {result.livetime.live_time_fraction:.4f}\")\n",
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" print(f\"Pulser peak: {result.livetime.pulser_peak_center_keV:.1f} keV\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot Calibrated Spectrum"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.figure(figsize=(10, 6))\n",
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"plt.plot(result.spectrum.energies, result.spectrum.counts, 'b-', label='Counts')\n",
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"plt.xlabel('Energy (keV)')\n",
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"plt.ylabel('Counts')\n",
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"plt.title('Calibrated Beta Spectrum')\n",
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"plt.legend()\n",
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"plt.tight_layout()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Process Run Sequence"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"results = process_run_sequence(\n",
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" run_dir=RUN_DIR,\n",
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" calibration_path=CALIBRATION_FILE,\n",
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" prefix=\"A\",\n",
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" pulser_frequency_hz=PULSER_FREQUENCY_HZ,\n",
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" real_time_sec=REAL_TIME_SEC,\n",
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")\n",
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"\n",
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"print(f\"Processed {len(results)} runs\")\n",
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"for i, r in enumerate(results):\n",
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" print(f\" Run {i+1}: {'PASSED' if r.validation_passed else 'FAILED'} \"\n",
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" f\"(chi2/dof={r.calibration.chi2_per_dof:.4f})\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Export to ROOT"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"write_spectrum(\"output.root\", result.spectrum)\n",
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"print(\"Exported to output.root\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Read Back from ROOT"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"read_back = read_spectrum(\"output.root\")\n",
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"print(f\"Read {len(read_back.energies)} channels\")\n",
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"print(f\"Source: {read_back.source}\")\n",
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"print(f\"Run ID: {read_back.run_id}\")\n",
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"print(f\"Calibration: {read_back.metadata.get('calibration', {})}\")\n",
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"\n",
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"# Verify round-trip\n",
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"assert np.allclose(read_back.energies, result.spectrum.energies)\n",
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"assert np.allclose(read_back.counts, result.spectrum.counts)\n",
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"print(\"Round-trip verified\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Livetime Determination"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Direct livetime determination from calibration file\n",
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"livetime_result = LivetimeDetermination.from_file(\n",
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" filepath=CALIBRATION_FILE,\n",
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" pulser_frequency_hz=PULSER_FREQUENCY_HZ,\n",
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" real_time_sec=REAL_TIME_SEC,\n",
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" source=\"pulser\",\n",
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")\n",
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"\n",
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"print(f\"Live-time fraction: {livetime_result.live_time_fraction:.4f}\")\n",
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"print(f\"Observed pulser rate: {livetime_result.observed_pulser_rate:.1f} Hz\")\n",
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"print(f\"Pulser peak: {livetime_result.pulser_peak_center_keV:.1f} keV \"\n",
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" f\"(sigma={livetime_result.pulser_peak_sigma_keV:.2f} keV, \"\n",
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" f\"chi2/dof={livetime_result.pulser_peak_chi2:.2f})\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.14.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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