{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# KPF Data Tutorial\n",
    "\n",
    "This tutorial demonstrates how to create and use RVData standard files for the Keck Planet Finder (KPF) instrument at all data levels:\n",
    "\n",
    "- **Level 2 (L2)**: Extracted, wavelength-calibrated echelle spectra\n",
    "- **Level 3 (L3)**: Stitched 1D spectrum on a common wavelength grid\n",
    "- **Level 4 (L4)**: Radial velocity measurements\n",
    "\n",
    "## Prerequisites\n",
    "\n",
    "Install the rvdata package:\n",
    "```bash\n",
    "pip install rv-data-standard\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup and Data Download\n",
    "\n",
    "First, we'll import the necessary modules and download sample KPF data files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:34.633277Z",
     "iopub.status.busy": "2026-02-11T05:21:34.633176Z",
     "iopub.status.idle": "2026-02-11T05:21:55.907082Z",
     "shell.execute_reply": "2026-02-11T05:21:55.906650Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from astropy.io import fits\n",
    "\n",
    "# RVData imports\n",
    "from rvdata.core.models.level2 import RV2\n",
    "from rvdata.core.models.level3 import RV3\n",
    "from rvdata.core.models.level4 import RV4\n",
    "\n",
    "def download_file(url, filename):\n",
    "    \"\"\"Download a file if it doesn't already exist.\"\"\"\n",
    "    if not os.path.exists(filename):\n",
    "        print(f\"Downloading {filename}...\")\n",
    "        response = requests.get(url)\n",
    "        response.raise_for_status()\n",
    "        with open(filename, \"wb\") as f:\n",
    "            f.write(response.content)\n",
    "        print(f\"Downloaded {filename}\")\n",
    "    else:\n",
    "        print(f\"{filename} already exists, skipping download.\")\n",
    "\n",
    "# KPF sample data URLs (hosted on project server)\n",
    "# L0 (raw) and L1 (extracted) files are needed to create L2\n",
    "# Native L2 files are needed to create L4\n",
    "file_urls = {\n",
    "    \"l0\": \"http://grinnell.as.arizona.edu/~rvdata/kpf/KP.20250208.17485.59.fits\",\n",
    "    \"l1\": \"http://grinnell.as.arizona.edu/~rvdata/kpf/KP.20250208.17485.59_L1.fits\",\n",
    "    \"native_l2\": \"http://grinnell.as.arizona.edu/~rvdata/kpf/KP.20241022.41656.30_L2.fits\",\n",
    "}\n",
    "\n",
    "# Download the files\n",
    "l0_file = \"KP.20250208.17485.59.fits\"\n",
    "l1_file = \"KP.20250208.17485.59_L1.fits\"\n",
    "native_l2_file = \"KP.20241022.41656.30_L2.fits\"\n",
    "\n",
    "download_file(file_urls[\"l0\"], l0_file)\n",
    "download_file(file_urls[\"l1\"], l1_file)\n",
    "download_file(file_urls[\"native_l2\"], native_l2_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Level 2: Extracted Echelle Spectra\n",
    "\n",
    "Level 2 data contains wavelength-calibrated, extracted echelle spectra organized by trace (fiber). Each trace contains flux, wavelength, variance, and blaze function arrays.\n",
    "\n",
    "## Creating L2 from Native KPF Files\n",
    "\n",
    "To create an RVData-standard L2 file from native KPF data, you need:\n",
    "- **L0 file**: Raw data with headers and telemetry\n",
    "- **L1 file**: Extracted spectra from the KPF pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:55.909208Z",
     "iopub.status.busy": "2026-02-11T05:21:55.908942Z",
     "iopub.status.idle": "2026-02-11T05:21:57.052919Z",
     "shell.execute_reply": "2026-02-11T05:21:57.052383Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create RVData-standard L2 from native KPF files\n",
    "kpf_l2 = RV2.from_fits(l1_file, l0file=l0_file, instrument=\"KPF\")\n",
    "\n",
    "# Save to FITS file\n",
    "l2_standard_file = \"kpf_L2_standard.fits\"\n",
    "kpf_l2.to_fits(l2_standard_file)\n",
    "print(f\"Created {l2_standard_file}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using L2 Data\n",
    "\n",
    "### Reading the L2 File\n",
    "\n",
    "You can read L2 files using either astropy's `fits.open()` or the RVData `RV2.from_fits()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:57.054390Z",
     "iopub.status.busy": "2026-02-11T05:21:57.054288Z",
     "iopub.status.idle": "2026-02-11T05:21:57.057301Z",
     "shell.execute_reply": "2026-02-11T05:21:57.057125Z"
    }
   },
   "outputs": [],
   "source": [
    "# Open using astropy\n",
    "l2 = fits.open(l2_standard_file)\n",
    "\n",
    "# Examine the primary header - same keywords regardless of instrument!\n",
    "hdr = l2[0].header\n",
    "print(f\"Telescope: {hdr['TELESCOP']}\")\n",
    "print(f\"Instrument: {hdr['INSTRUME']}\")\n",
    "print(f\"Object: {hdr['OBJECT']}\")\n",
    "print(f\"Number of traces: {hdr['NUMTRACE']}\")\n",
    "print(\"\\nTrace contents:\")\n",
    "for i in range(1, hdr['NUMTRACE'] + 1):\n",
    "    print(f\"  TRACE{i}: {hdr[f'TRACE{i}']}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examining L2 Extensions\n",
    "\n",
    "The `EXT_DESCRIPT` extension lists all FITS extensions in the file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:57.058667Z",
     "iopub.status.busy": "2026-02-11T05:21:57.058585Z",
     "iopub.status.idle": "2026-02-11T05:21:57.069504Z",
     "shell.execute_reply": "2026-02-11T05:21:57.069303Z"
    }
   },
   "outputs": [],
   "source": [
    "# List all extensions\n",
    "ext_descript = pd.DataFrame(l2['EXT_DESCRIPT'].data)\n",
    "print(ext_descript[['Name', 'Description']].to_string())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examining the Order Table\n",
    "\n",
    "The `ORDER_TABLE` extension describes the wavelength coverage of each echelle order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:57.070782Z",
     "iopub.status.busy": "2026-02-11T05:21:57.070690Z",
     "iopub.status.idle": "2026-02-11T05:21:57.074689Z",
     "shell.execute_reply": "2026-02-11T05:21:57.074486Z"
    }
   },
   "outputs": [],
   "source": [
    "order_table = pd.DataFrame(l2['ORDER_TABLE'].data)\n",
    "print(f\"Number of orders: {len(order_table)}\")\n",
    "print(f\"\\nWavelength coverage: {order_table['WAVE_START'].min():.1f} - {order_table['WAVE_END'].max():.1f} Angstroms\")\n",
    "print(\"\\nFirst 5 orders:\")\n",
    "print(order_table.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting L2 Spectra\n",
    "\n",
    "KPF has 5 traces:\n",
    "- TRACE1: Calibration fiber (etalon)\n",
    "- TRACE2, TRACE3, TRACE4: Science fibers\n",
    "- TRACE5: Sky fiber\n",
    "\n",
    "Let's plot one order from the science traces."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:57.075986Z",
     "iopub.status.busy": "2026-02-11T05:21:57.075904Z",
     "iopub.status.idle": "2026-02-11T05:21:57.396971Z",
     "shell.execute_reply": "2026-02-11T05:21:57.393762Z"
    }
   },
   "outputs": [],
   "source": [
    "# Plot a single order from the three science traces\n",
    "order = 30  # Choose an order to plot\n",
    "\n",
    "fig, axes = plt.subplots(3, 1, figsize=(12, 8), sharex=True)\n",
    "\n",
    "for i, (ax, trace_num) in enumerate(zip(axes, [2, 3, 4])):\n",
    "    wave = l2[f'TRACE{trace_num}_WAVE'].data[order]\n",
    "    flux = l2[f'TRACE{trace_num}_FLUX'].data[order]\n",
    "    blaze = l2[f'TRACE{trace_num}_BLAZE'].data[order]\n",
    "    \n",
    "    # Scale blaze for visualization\n",
    "    blaze_scaled = blaze * (np.nanmax(flux) / np.nanmax(blaze))\n",
    "    \n",
    "    ax.plot(wave, flux, 'b-', lw=0.5, label='Flux')\n",
    "    ax.plot(wave, blaze_scaled, 'orange', lw=1, label='Blaze (scaled)')\n",
    "    ax.set_ylabel(f'TRACE{trace_num}\\nCounts')\n",
    "    ax.legend(loc='upper right')\n",
    "    ax.set_ylim(0, np.nanmax(flux) * 1.1)\n",
    "\n",
    "axes[-1].set_xlabel('Wavelength (Angstroms)')\n",
    "fig.suptitle(f'KPF L2 Spectra - Order {order}', fontsize=14, fontweight='bold')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Level 3: Stitched 1D Spectrum\n",
    "\n",
    "Level 3 data contains a stitched 1D spectrum on a common wavelength grid with constant velocity spacing. The stitching process:\n",
    "1. Divides out the blaze function\n",
    "2. Resamples each order onto a common wavelength grid\n",
    "3. Combines overlapping regions using inverse-variance weighting\n",
    "\n",
    "## Creating L3 from L2\n",
    "\n",
    "L3 is created from an RVData-standard L2 file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:21:57.400984Z",
     "iopub.status.busy": "2026-02-11T05:21:57.400802Z",
     "iopub.status.idle": "2026-02-11T05:22:00.563685Z",
     "shell.execute_reply": "2026-02-11T05:22:00.563335Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create L3 from the standard L2 file\n",
    "kpf_l3 = RV3.from_fits(l2_standard_file, instrument=\"KPF\")\n",
    "\n",
    "# Save to FITS file\n",
    "l3_standard_file = \"kpf_L3_standard.fits\"\n",
    "kpf_l3.to_fits(l3_standard_file)\n",
    "print(f\"Created {l3_standard_file}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using L3 Data\n",
    "\n",
    "### Reading the L3 File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:00.565421Z",
     "iopub.status.busy": "2026-02-11T05:22:00.565295Z",
     "iopub.status.idle": "2026-02-11T05:22:00.572235Z",
     "shell.execute_reply": "2026-02-11T05:22:00.572033Z"
    }
   },
   "outputs": [],
   "source": [
    "# Open the L3 file\n",
    "l3 = fits.open(l3_standard_file)\n",
    "\n",
    "# List extensions\n",
    "print(\"L3 Extensions:\")\n",
    "for hdu in l3:\n",
    "    print(f\"  {hdu.name}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Understanding L3 Extensions\n",
    "\n",
    "For KPF with multiple science fibers, the stitched spectra are stored in `STITCHED_CORR_TRACE{n}_*` extensions:\n",
    "- `STITCHED_CORR_TRACE2_WAVE/FLUX/VAR`: Science fiber 1\n",
    "- `STITCHED_CORR_TRACE3_WAVE/FLUX/VAR`: Science fiber 2  \n",
    "- `STITCHED_CORR_TRACE4_WAVE/FLUX/VAR`: Science fiber 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:00.573442Z",
     "iopub.status.busy": "2026-02-11T05:22:00.573358Z",
     "iopub.status.idle": "2026-02-11T05:22:00.575327Z",
     "shell.execute_reply": "2026-02-11T05:22:00.575108Z"
    }
   },
   "outputs": [],
   "source": [
    "# Check which STITCHED extensions are present\n",
    "stitched_exts = [hdu.name for hdu in l3 if 'STITCHED' in hdu.name]\n",
    "print(\"Stitched spectrum extensions:\")\n",
    "for ext in stitched_exts:\n",
    "    print(f\"  {ext}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting the Stitched Spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:00.576640Z",
     "iopub.status.busy": "2026-02-11T05:22:00.576561Z",
     "iopub.status.idle": "2026-02-11T05:22:00.743617Z",
     "shell.execute_reply": "2026-02-11T05:22:00.742646Z"
    }
   },
   "outputs": [],
   "source": [
    "# Plot the stitched spectrum for one trace\n",
    "# Check which trace extensions exist\n",
    "trace_num = 2  # Try TRACE2 first\n",
    "wave_ext = f'STITCHED_CORR_TRACE{trace_num}_WAVE'\n",
    "flux_ext = f'STITCHED_CORR_TRACE{trace_num}_FLUX'\n",
    "\n",
    "if wave_ext in [hdu.name for hdu in l3]:\n",
    "    wave_l3 = l3[wave_ext].data\n",
    "    flux_l3 = l3[flux_ext].data\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(14, 5))\n",
    "    ax.plot(wave_l3, flux_l3, 'b-', lw=0.3)\n",
    "    ax.set_xlabel('Wavelength (Angstroms)', fontsize=12)\n",
    "    ax.set_ylabel('Flux (normalized)', fontsize=12)\n",
    "    ax.set_title(f'KPF L3 Stitched Spectrum - TRACE{trace_num}', fontsize=14, fontweight='bold')\n",
    "    \n",
    "    # Zoom inset\n",
    "    ax.set_xlim(wave_l3[np.isfinite(wave_l3)].min(), wave_l3[np.isfinite(wave_l3)].max())\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "    \n",
    "    print(f\"\\nWavelength range: {np.nanmin(wave_l3):.1f} - {np.nanmax(wave_l3):.1f} Angstroms\")\n",
    "    print(f\"Number of pixels: {len(wave_l3)}\")\n",
    "else:\n",
    "    print(f\"Extension {wave_ext} not found. Available: {stitched_exts}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Zoomed View of Spectral Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:00.750903Z",
     "iopub.status.busy": "2026-02-11T05:22:00.750652Z",
     "iopub.status.idle": "2026-02-11T05:22:00.876451Z",
     "shell.execute_reply": "2026-02-11T05:22:00.876196Z"
    }
   },
   "outputs": [],
   "source": [
    "# Zoom in on H-alpha region\n",
    "if wave_ext in [hdu.name for hdu in l3]:\n",
    "    fig, ax = plt.subplots(figsize=(12, 4))\n",
    "    \n",
    "    # H-alpha region\n",
    "    mask = (wave_l3 > 6550) & (wave_l3 < 6580)\n",
    "    ax.plot(wave_l3[mask], flux_l3[mask], 'b-', lw=0.5)\n",
    "    ax.axvline(6562.8, color='red', ls='--', alpha=0.7, label='H-alpha (6562.8 A)')\n",
    "    ax.set_xlabel('Wavelength (Angstroms)')\n",
    "    ax.set_ylabel('Flux')\n",
    "    ax.set_title('H-alpha Region', fontsize=12)\n",
    "    ax.legend()\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Level 4: Radial Velocity Measurements\n",
    "\n",
    "Level 4 data contains radial velocity (RV) measurements derived from the spectra. These can include:\n",
    "- Per-order RVs\n",
    "- Combined RV with uncertainty\n",
    "- Activity indicators\n",
    "\n",
    "## Creating L4 from Native KPF L2\n",
    "\n",
    "L4 is typically created from native pipeline outputs that contain RV measurements. For KPF, the native L2 file includes CCF-derived RVs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:00.877885Z",
     "iopub.status.busy": "2026-02-11T05:22:00.877800Z",
     "iopub.status.idle": "2026-02-11T05:22:01.036284Z",
     "shell.execute_reply": "2026-02-11T05:22:01.035888Z"
    }
   },
   "outputs": [],
   "source": [
    "# Create L4 from native KPF L2 file (which contains RV measurements)\n",
    "kpf_l4 = RV4.from_fits(native_l2_file, instrument=\"KPF\")\n",
    "\n",
    "# Save to FITS file\n",
    "l4_standard_file = \"kpf_L4_standard.fits\"\n",
    "kpf_l4.to_fits(l4_standard_file)\n",
    "print(f\"Created {l4_standard_file}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using L4 Data\n",
    "\n",
    "### Reading the L4 File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:01.037819Z",
     "iopub.status.busy": "2026-02-11T05:22:01.037713Z",
     "iopub.status.idle": "2026-02-11T05:22:01.043681Z",
     "shell.execute_reply": "2026-02-11T05:22:01.043406Z"
    }
   },
   "outputs": [],
   "source": [
    "# Open the L4 file\n",
    "l4 = fits.open(l4_standard_file)\n",
    "\n",
    "# Examine primary header for RV info\n",
    "hdr4 = l4[0].header\n",
    "print(f\"Object: {hdr4['OBJECT']}\")\n",
    "print(f\"Observation time (BJD): {hdr4.get('BJD_TDB', 'N/A')}\")\n",
    "\n",
    "# List extensions\n",
    "print(\"\\nL4 Extensions:\")\n",
    "for hdu in l4:\n",
    "    print(f\"  {hdu.name}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examining the RV1 Extension\n",
    "\n",
    "The `RV1` extension contains per-order radial velocity measurements with standardized column names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:01.044998Z",
     "iopub.status.busy": "2026-02-11T05:22:01.044908Z",
     "iopub.status.idle": "2026-02-11T05:22:01.054282Z",
     "shell.execute_reply": "2026-02-11T05:22:01.054075Z"
    }
   },
   "outputs": [],
   "source": [
    "# Examine the RV1 extension\n",
    "rv1 = pd.DataFrame(l4['RV1'].data)\n",
    "print(\"RV1 columns:\")\n",
    "print(rv1.columns.tolist())\n",
    "print(f\"\\nNumber of orders: {len(rv1)}\")\n",
    "print(\"\\nFirst 5 rows:\")\n",
    "print(rv1.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Per-Order RVs\n",
    "\n",
    "The `RV1` extension contains one row per echelle order. The `RV` column holds the combined RV measurement for each order, and `ORDER_INDEX` identifies which order each row corresponds to. Additional columns include `BERV` (barycentric earth radial velocity), `WAVE_START`/`WAVE_END` (wavelength range), and `WEIGHT` (RV weight)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:01.055491Z",
     "iopub.status.busy": "2026-02-11T05:22:01.055405Z",
     "iopub.status.idle": "2026-02-11T05:22:01.220368Z",
     "shell.execute_reply": "2026-02-11T05:22:01.218874Z"
    }
   },
   "outputs": [],
   "source": [
    "# Plot per-order RVs from the RV1 extension\n",
    "rv1 = pd.DataFrame(l4['RV1'].data)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "valid = np.isfinite(rv1['RV'])\n",
    "ax.scatter(rv1.loc[valid, 'ORDER_INDEX'], rv1.loc[valid, 'RV'], s=20, alpha=0.7)\n",
    "median_rv = np.nanmedian(rv1['RV'])\n",
    "ax.axhline(median_rv, color='red', ls='--', label=f'Median: {median_rv:.2f} m/s')\n",
    "ax.set_xlabel('Order Index')\n",
    "ax.set_ylabel('RV (m/s)')\n",
    "ax.set_title('Per-Order Radial Velocities (RV1)')\n",
    "ax.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# Summary\n",
    "\n",
    "This tutorial demonstrated how to:\n",
    "\n",
    "1. **Create L2** from native KPF L0+L1 files using `RV2.from_fits()`\n",
    "2. **Use L2** data: access headers, examine extensions, plot spectra\n",
    "3. **Create L3** from standard L2 using `RV3.from_fits()`\n",
    "4. **Use L3** data: access stitched spectra, examine spectral features\n",
    "5. **Create L4** from native KPF L2 using `RV4.from_fits()`\n",
    "6. **Use L4** data: access RV measurements and per-order RVs\n",
    "\n",
    "The standardized data format allows consistent access patterns across all EPRV instruments!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-11T05:22:01.223273Z",
     "iopub.status.busy": "2026-02-11T05:22:01.223086Z",
     "iopub.status.idle": "2026-02-11T05:22:01.226535Z",
     "shell.execute_reply": "2026-02-11T05:22:01.225796Z"
    }
   },
   "outputs": [],
   "source": [
    "# Clean up - close FITS files\n",
    "l2.close()\n",
    "l3.close()\n",
    "l4.close()"
   ]
  }
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