{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SPXQuery Quickstart Demo\n",
    "\n",
    "This notebook demonstrates the flexible, resumable pipeline features of the `spxquery` package.\n",
    "\n",
    "**Point Source:** Cloverleaf quasar (RA=213.9427080°, Dec=+11.4953890°, z=2.56)\n",
    "\n",
    "**Package Version:** v0.2.2\n",
    "\n",
    "## Features Demonstrated\n",
    "\n",
    "1. **Advanced Configuration** (v0.2.2) - FWHM-based apertures and window background\n",
    "2. **One-click pipeline execution** - Run everything with a single function call\n",
    "3. **Smart resume with YAML** - Human-readable state files with automatic loading\n",
    "4. **Manual step execution** - Run individual stages with dependency checking\n",
    "5. **Method comparisons** (v0.2.2) - Compare background and aperture methods\n",
    "6. **Parameter tuning** (v0.2.2) - Interactive exploration of optimal settings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SPHEREx Bad Pixel Flags Reference\n",
    "\n",
    "The `bad_flags` parameter specifies which pixel quality flags to reject during visualization.\n",
    "\n",
    "**Default bad_flags: [0, 1, 2, 6, 7, 9, 10, 11, 14, 15, 17, 19]**\n",
    "\n",
    "| Flag Name    | Bit | Flag Name    | Bit |\n",
    "|--------------|-----|--------------|-----|\n",
    "| TRANSIENT    | 0   | COLD         | 11  |\n",
    "| OVERFLOW     | 1   | FULLSAMPLE   | 12  |\n",
    "| SUR_ERROR    | 2   | PHANMISS     | 14  |\n",
    "| NONFUNC      | 6   | NONLINEAR    | 15  |\n",
    "| DICHROIC     | 7   | PERSIST      | 17  |\n",
    "| MISSING_DATA | 9   | OUTLIER      | 19  |\n",
    "| HOT          | 10  | SOURCE       | 21  |\n",
    "\n",
    "**Note:** The FLAGS extension in SPHEREx FITS files uses a bitmap where multiple flags can be set for a single pixel. The pipeline marks measurements as \"bad\" if ANY of the specified flag bits are set.\n",
    "\n",
    "**Usage examples:**\n",
    "```python\n",
    "bad_flags=[0, 1, 2, 6, 7, 9, 10, 11, 14, 15, 17, 19]  # Default: comprehensive quality control\n",
    "bad_flags=[]                      # No flag filtering (use all data)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### Automatic Variance Repair (NEW in v0.2.2)\n",
    "\n",
    "**Problem**: Some SPHEREx images contain pixels with NaN variance but valid flux values, typically due to flagged conditions.\n",
    "\n",
    "**Solution**: The pipeline automatically repairs variance for flagged pixels:\n",
    "- **Validates assumption**: Checks that NaN variance correlates with non-zero flags\n",
    "- **Estimates variance**: Uses median of valid variance values across the image\n",
    "- **Fails safely**: Raises error if NaN variance found without flags (unexpected data quality issue)\n",
    "\n",
    "**Benefits:**\n",
    "- Preserves observations that would otherwise fail photometry\n",
    "- Provides reasonable error estimates for flagged pixels\n",
    "- Maintains SNR-based quality control\n",
    "- No manual intervention required\n",
    "\n",
    "**Log message example:**\n",
    "```\n",
    "INFO - Repaired 23 pixels with NaN variance using median variance (1.234e-06). \n",
    "       All repaired pixels have non-zero flags.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import required modules\n",
    "from pathlib import Path\n",
    "\n",
    "from spxquery import QueryConfig, Source, SPXQueryPipeline\n",
    "from spxquery.core.pipeline import run_pipeline\n",
    "from spxquery.utils.helpers import setup_logging\n",
    "\n",
    "# Set up logging\n",
    "setup_logging(\"INFO\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Spectrophotometry for a Single Source\n",
    "\n",
    "**NEW IN v0.2.2**: Enhanced photometry with adaptive apertures and flexible background estimation!\n",
    "\n",
    "The advanced parameter system allows you to customize photometry, visualization, and download parameters beyond the basic pipeline settings.\n",
    "\n",
    "### What's New in v0.2.2\n",
    "\n",
    "**Adaptive Aperture Sizing:**\n",
    "- **FWHM-based apertures**: Automatically size apertures based on PSF FWHM\n",
    "- **Automatic fallback**: Falls back to fixed aperture if FWHM estimation fails\n",
    "- Parameters: `aperture_method` ('fixed' or 'fwhm'), `fwhm_multiplier`\n",
    "\n",
    "**Flexible Background Estimation:**\n",
    "- **Window method**: Rectangular background region (alternative to annulus)\n",
    "- **Automatic aperture exclusion**: Pixels intersecting the aperture are automatically excluded\n",
    "- Parameters: `background_method` ('annulus' or 'window'), `window_size`\n",
    "\n",
    "**Key features:**\n",
    "- Export default parameters to YAML template with inline comments\n",
    "- Edit parameters manually for fine-tuning\n",
    "- Load custom parameters into pipeline\n",
    "- Priority system: explicit params > YAML file > defaults"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parameter Setting (v0.2.2 Features)\n",
    "\n",
    "Here's how to use the new photometry features directly in your pipeline:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# FWHM-based adaptive apertures\n",
    "from spxquery.core.config import (\n",
    "    PhotometryConfig,\n",
    "    QueryConfig,\n",
    "    Source,\n",
    "    AdvancedConfig,\n",
    "    DownloadConfig,\n",
    "    VisualizationConfig,\n",
    ")\n",
    "\n",
    "# Define our target source\n",
    "source = Source(\n",
    "    name=\"cloverleaf\",\n",
    "    ra=213.9427080,  # Right ascension in degrees\n",
    "    dec=11.4953890,  # Declination in degrees\n",
    ")\n",
    "\n",
    "# Define the output directory\n",
    "output_dir = Path(\"./demo_data/cloverleaf\")\n",
    "\n",
    "\n",
    "config_all = AdvancedConfig(\n",
    "    # === Query Configuration ===\n",
    "    query=QueryConfig(\n",
    "        source=source,\n",
    "        output_dir=output_dir,\n",
    "        bands=[\"D1\", \"D2\", \"D3\", \"D4\", \"D5\", \"D6\"],  # SPHEREx bands to query\n",
    "    ),\n",
    "    # === Download Configuration ===\n",
    "    download=DownloadConfig(\n",
    "        # === Image settings ===\n",
    "        cutout_size=\"60px\",  # Size of cutout images; None for full image (e.g., \"200px\", \"3arcmin\")\n",
    "        cutout_center=None,  # Center of cutout; defaults to source coordinates (e.g., \"70,20\", \"300.5,120px\")\n",
    "        # === Download Settings ===\n",
    "        max_retries=3,  # Number of retry attempts for failed downloads\n",
    "        max_download_workers=5,  # Number of parallel download workers\n",
    "        # === Advanced Users Only ===\n",
    "        chunk_size=8192,  # Only for advanced users: size of data chunks to read (bytes)\n",
    "        timeout=300,  # Only for advanced users: HTTP timeout (seconds)\n",
    "        user_agent=\"SPXQuery/0.2.2\",  # Only for advanced users: User agent string for HTTP requests\n",
    "    ),\n",
    "    # === Photometry Configuration ===\n",
    "    photometry=PhotometryConfig(\n",
    "        # === Aperture Configuration ===\n",
    "        aperture_method=\"fwhm\",  # \"fixed\" or \"fwhm\" - aperture sizing method\n",
    "        fwhm_multiplier=2.5,  # Multiplier for FWHM-based apertures (aperture = FWHM × multiplier)\n",
    "        aperture_diameter=3.0,  # Aperture diameter in pixels (fixed method OR fallback)\n",
    "        # === Background Configuration ===\n",
    "        background_method=\"window\",  # \"annulus\" or \"window\" - background estimation method\n",
    "        window_size=50,  # Window size for window method (int for square, tuple for rectangular)\n",
    "        # === Annulus Parameters (Only valid if aperture_method=\"annulus\") ===\n",
    "        annulus_inner_offset=1.414,  # Gap between aperture and annulus inner radius (pixels)\n",
    "        min_annulus_area=10,  # Minimum annulus area (pixels)\n",
    "        max_outer_radius=5.0,  # Maximum outer annulus radius (pixels)\n",
    "        max_annulus_attempts=5,  # Max attempts to expand annulus if insufficient pixels\n",
    "        annulus_expansion_step=0.5,  # Step size for annulus expansion (pixels)\n",
    "        # === Background Statistics ===\n",
    "        min_usable_pixels=10,  # Minimum unflagged pixels required for background estimation\n",
    "        bg_sigma_clip_sigma=3.0,  # Sigma threshold for background sigma clipping\n",
    "        bg_sigma_clip_maxiters=3,  # Maximum iterations for background sigma clipping\n",
    "        # === Other Photometry Parameters ===\n",
    "        subtract_zodi=True,  # Whether to subtract zodiacal light background from images\n",
    "        zodi_scale_min=0.0,  # Minimum allowed zodiacal scaling factor\n",
    "        zodi_scale_max=10.0,  # Maximum allowed zodiacal scaling factor\n",
    "        pixel_scale_fallback=6.2,  # Fallback pixel scale (arcsec/pixel) when WCS fails\n",
    "        # === Processing & Quality Control ===\n",
    "        max_processing_workers=10,  # Parallel processing\n",
    "        bad_flags=[0, 1, 2, 6, 7, 9, 10, 11, 15],  # Photometry fails if aperture contains flagged pixels\n",
    "    ),\n",
    "    # === Visualization Configuration ===\n",
    "    visualization=VisualizationConfig(\n",
    "        # === Quality Control ===\n",
    "        sigma_threshold=5.0,  # Minimum SNR (flux/flux_err) for quality control filtering\n",
    "        # === Plot Type ===\n",
    "        use_magnitude=False,  # If True, plot AB magnitude instead of flux\n",
    "        show_errorbars=True,  # If True, show error bars on plots\n",
    "        # === Color Maps ===\n",
    "        wavelength_cmap=\"rainbow\",  # Colormap for wavelength coding in light curves\n",
    "        date_cmap=\"viridis\",  # Colormap for date coding in spectra\n",
    "        # === Outlier Removal ===\n",
    "        sigma_clip_sigma=5.0,  # Sigma threshold for outlier removal in plots\n",
    "        sigma_clip_maxiters=10,  # Maximum iterations for sigma clipping\n",
    "        # === Y-axis Limits ===\n",
    "        ylim_percentile_min=1.0,  # Lower percentile for smart y-axis limits (0-100)\n",
    "        ylim_percentile_max=99.0,  # Upper percentile for smart y-axis limits (0-100)\n",
    "        ylim_padding_fraction=0.1,  # Padding fraction added to y-axis range\n",
    "        # === Marker Sizes ===\n",
    "        marker_size_good=1.5,  # Marker size for good measurements\n",
    "        marker_size_rejected=2.0,  # Marker size for rejected measurements\n",
    "        marker_size_upper_limit=3.0,  # Marker size for upper limit arrows\n",
    "        # === Transparency ===\n",
    "        errorbar_alpha=0.2,  # Transparency for error bars (0-1)\n",
    "        marker_alpha=0.9,  # Transparency for markers (0-1)\n",
    "        # === Line Widths ===\n",
    "        errorbar_linewidth=0.5,  # Line width for error bars in points\n",
    "        # === Figure Settings ===\n",
    "        figsize=(10, 8),  # Figure size in inches (width, height)\n",
    "        dpi=150,  # Resolution in dots per inch for saved figures\n",
    "    ),\n",
    ")\n",
    "\n",
    "# Save these settings for future use\n",
    "config_all.to_yaml_file(output_dir / \"config_params.yaml\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Or use a YAML template and Edit outside**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:00 - spxquery.utils.params - INFO - Default parameters exported to demo_data/cloverleaf/config_params.yaml\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "======================================================================\n",
      "Advanced Parameters Template Exported\n",
      "======================================================================\n",
      "File location: demo_data/cloverleaf/config_params.yaml\n",
      "\n",
      "This template contains customizable parameters for:\n",
      "  • Photometry (aperture, background annulus, sigma clipping)\n",
      "  • Visualization (colormaps, marker sizes, figure settings)\n",
      "  • Downloads (chunk size, timeouts, retries)\n",
      "\n",
      "NOTE: This template does NOT include source information (ra/dec).\n",
      "      You must provide source coordinates when running the pipeline.\n",
      "\n",
      "Next steps:\n",
      "  1. Edit config_params.yaml to customize parameters (YAML format with comments)\n",
      "  2. Use the file in your pipeline with:\n",
      "     • QueryConfig(source=..., advanced_params_file='demo_data/cloverleaf/config_params.yaml')\n",
      "     • run_pipeline(ra=..., dec=..., advanced_params_file='demo_data/cloverleaf/config_params.yaml')\n",
      "======================================================================\n",
      "\n",
      "\n",
      "Parameter template created at: demo_data/cloverleaf/config_params.yaml\n"
     ]
    }
   ],
   "source": [
    "# Export default parameters to a JSON template\n",
    "from spxquery.utils.params import export_default_parameters\n",
    "\n",
    "# Export to custom directory\n",
    "params_file = export_default_parameters(output_dir, filename=\"config_params.yaml\")\n",
    "\n",
    "print(f\"\\nParameter template created at: {params_file}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:00 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/config_params.yaml\n"
     ]
    }
   ],
   "source": [
    "# Load the file back into a QueryConfig object\n",
    "config_all = AdvancedConfig.from_yaml_file(params_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**You can also update your parameters after build up the config**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:00 - spxquery.core.config - INFO - Updated parameters: ['source', 'output_dir', 'max_processing_workers']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MySource\n",
      "cloverleaf\n"
     ]
    }
   ],
   "source": [
    "# Only name of the parameter is needed. Package will identify which category it belongs to.\n",
    "print(config_all.query.source.name)\n",
    "config_all.update(source=source, output_dir=output_dir, max_processing_workers=1)\n",
    "print(config_all.query.source.name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use Custom Parameters in Pipeline\n",
    "\n",
    "There are two ways to use custom parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:00 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:33:00 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Method 1: Using SPXQueryPipeline with advanced_params_file\n",
      "======================================================================\n",
      "\n",
      "✓ Custom parameters loaded!\n",
      "  Visualization DPI: 150\n",
      "  Figure size: (10, 8)\n",
      "  Wavelength colormap: rainbow\n",
      "  BG sigma clipping: 3.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:04 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:33:04 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:33:04 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:33:04\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "2025-11-13 00:33:04 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.51 GB (actual)\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2025-11-13 00:33:04 - spxquery.core.pipeline - INFO - Processing 108 FITS files\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Processing photometry for 108 observations\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Using sequential processing (max_workers=1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:   0%|          | 0/108 [00:00<?, ?files/s]2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_1.fits\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Repaired 12 pixels with NaN variance using median variance (9.499758e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.017\" (0.82px) → diameter=2.04px (radius=1.02px)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1757\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1757\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=1038.191±38.595 μJy (0.001038±0.000039 Jy) at λ=1.940 μm, mag_AB=16.359±0.040\n",
      "Processing observations:   1%|          | 1/108 [00:00<00:22,  4.69files/s]2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_1.fits\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.811026e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.625\" (0.91px) → diameter=2.28px (radius=1.14px)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0426\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0426\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=2436.807±110.307 μJy (0.002437±0.000110 Jy) at λ=4.658 μm, mag_AB=15.433±0.049\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_2.fits\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (9.150388e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.643\" (0.75px) → diameter=1.89px (radius=0.94px)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1734\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1734\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=1023.154±37.410 μJy (0.001023±0.000037 Jy) at λ=1.985 μm, mag_AB=16.375±0.040\n",
      "Processing observations:   3%|▎         | 3/108 [00:00<00:09, 10.75files/s]2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_2.fits\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (6.164463e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.250\" (0.69px) → diameter=1.72px (radius=0.86px)\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0365\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0365\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:04 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=1933.091±93.696 μJy (0.001933±0.000094 Jy) at λ=4.692 μm, mag_AB=15.684±0.053\n",
      "2025-11-13 00:33:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (8.889740e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.495\" (0.73px) → diameter=1.83px (radius=0.91px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1805\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1805\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=886.621±35.335 μJy (0.000887±0.000035 Jy) at λ=2.032 μm, mag_AB=16.531±0.043\n",
      "Processing observations:   5%|▍         | 5/108 [00:00<00:07, 14.02files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (6.721239e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=7.940\" (1.29px) → diameter=3.22px (radius=1.61px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0259\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0259\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=3041.467±146.377 μJy (0.003041±0.000146 Jy) at λ=4.726 μm, mag_AB=15.192±0.052\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (8.557443e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.490\" (0.73px) → diameter=1.83px (radius=0.91px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1888\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1888\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=1035.729±35.128 μJy (0.001036±0.000035 Jy) at λ=2.078 μm, mag_AB=16.362±0.037\n",
      "Processing observations:   6%|▋         | 7/108 [00:00<00:06, 15.78files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (7.100530e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=7.936\" (1.29px) → diameter=3.22px (radius=1.61px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0445\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0445\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=2935.772±149.228 μJy (0.002936±0.000149 Jy) at λ=4.761 μm, mag_AB=15.231±0.055\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (8.644567e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.551\" (0.90px) → diameter=2.25px (radius=1.13px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0760\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0760\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=2720.236±127.554 μJy (0.002720±0.000128 Jy) at λ=4.830 μm, mag_AB=15.313±0.051\n",
      "Processing observations:   8%|▊         | 9/108 [00:00<00:05, 16.68files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (7.728661e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.629\" (0.75px) → diameter=1.88px (radius=0.94px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1792\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1792\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=1065.493±36.852 μJy (0.001065±0.000037 Jy) at λ=2.176 μm, mag_AB=16.331±0.038\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_2.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (9.236660e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.553\" (0.90px) → diameter=2.25px (radius=1.13px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0621\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0621\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_2.fits: flux=2996.135±133.733 μJy (0.002996±0.000134 Jy) at λ=4.866 μm, mag_AB=15.209±0.048\n",
      "Processing observations:  10%|█         | 11/108 [00:00<00:05, 17.25files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (9.960690e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.567\" (0.74px) → diameter=1.85px (radius=0.93px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0838\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0838\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=2216.766±113.886 μJy (0.002217±0.000114 Jy) at λ=4.901 μm, mag_AB=15.536±0.056\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (6.856603e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.714\" (0.77px) → diameter=1.91px (radius=0.96px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1851\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1851\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=1518.666±40.899 μJy (0.001519±0.000041 Jy) at λ=2.277 μm, mag_AB=15.946±0.029\n",
      "Processing observations:  12%|█▏        | 13/108 [00:00<00:05, 17.56files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (1.096818e+00). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.570\" (0.74px) → diameter=1.85px (radius=0.93px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0908\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0908\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=2417.426±121.911 μJy (0.002417±0.000122 Jy) at λ=4.937 μm, mag_AB=15.442±0.055\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (6.745640e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.713\" (0.77px) → diameter=1.91px (radius=0.96px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2239\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2239\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=3445.029±58.752 μJy (0.003445±0.000059 Jy) at λ=2.329 μm, mag_AB=15.057±0.019\n",
      "Processing observations:  14%|█▍        | 15/108 [00:00<00:05, 18.17files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0202_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (1.186982e+00). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.12px (radius=1.06px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0572\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0572\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=2556.301±135.873 μJy (0.002556±0.000136 Jy) at λ=4.973 μm, mag_AB=15.381±0.058\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0202_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 26 pixels with NaN variance using median variance (1.020734e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.415\" (0.72px) → diameter=1.79px (radius=0.90px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3655\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3655\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=1505.321±50.051 μJy (0.001505±0.000050 Jy) at λ=2.382 μm, mag_AB=15.956±0.036\n",
      "Processing observations:  16%|█▌        | 17/108 [00:01<00:05, 17.65files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.231259e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.646\" (0.76px) → diameter=1.89px (radius=0.94px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0272\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0272\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=1041.454±41.376 μJy (0.001041±0.000041 Jy) at λ=1.633 μm, mag_AB=16.356±0.043\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_3.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (3.707438e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.581\" (0.91px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 0.9897\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 0.9897\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=1770.649±91.207 μJy (0.001771±0.000091 Jy) at λ=4.411 μm, mag_AB=15.780±0.056\n",
      "Processing observations:  18%|█▊        | 19/108 [00:01<00:04, 17.94files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.203764e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.662\" (0.76px) → diameter=1.89px (radius=0.94px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0526\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0526\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=1071.033±42.147 μJy (0.001071±0.000042 Jy) at λ=1.671 μm, mag_AB=16.325±0.043\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_4.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (3.862086e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.584\" (0.91px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 0.9603\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 0.9603\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=2347.701±99.688 μJy (0.002348±0.000100 Jy) at λ=4.443 μm, mag_AB=15.473±0.046\n",
      "Processing observations:  19%|█▉        | 21/108 [00:01<00:04, 18.18files/s]2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.169509e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.704\" (0.76px) → diameter=1.91px (radius=0.96px)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0774\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0774\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=1225.838±42.605 μJy (0.001226±0.000043 Jy) at λ=1.709 μm, mag_AB=16.179±0.038\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_1.fits\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:05 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.453817e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.645\" (0.92px) → diameter=2.29px (radius=1.15px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0566\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0566\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=1786.397±100.958 μJy (0.001786±0.000101 Jy) at λ=4.475 μm, mag_AB=15.770±0.061\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.113934e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.558\" (0.74px) → diameter=1.85px (radius=0.93px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0940\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0940\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=1611.082±46.411 μJy (0.001611±0.000046 Jy) at λ=1.749 μm, mag_AB=15.882±0.031\n",
      "Processing observations:  22%|██▏       | 24/108 [00:01<00:04, 18.89files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (4.604722e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.405\" (0.71px) → diameter=1.79px (radius=0.89px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0315\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0315\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=1943.829±90.072 μJy (0.001944±0.000090 Jy) at λ=4.508 μm, mag_AB=15.678±0.050\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_3.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.078577e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.561\" (0.74px) → diameter=1.85px (radius=0.93px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1140\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1140\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=1243.893±41.996 μJy (0.001244±0.000042 Jy) at λ=1.789 μm, mag_AB=16.163±0.037\n",
      "Processing observations:  24%|██▍       | 26/108 [00:01<00:04, 19.02files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_3.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (4.797451e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.406\" (0.71px) → diameter=1.79px (radius=0.89px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0258\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0258\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=2453.452±101.397 μJy (0.002453±0.000101 Jy) at λ=4.540 μm, mag_AB=15.426±0.045\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_4.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (4.988441e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.677\" (0.92px) → diameter=2.30px (radius=1.15px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0101\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0101\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=3044.509±113.623 μJy (0.003045±0.000114 Jy) at λ=4.573 μm, mag_AB=15.191±0.041\n",
      "Processing observations:  26%|██▌       | 28/108 [00:01<00:04, 19.01files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_4.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (1.039659e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.362\" (0.71px) → diameter=1.77px (radius=0.89px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1364\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1364\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=983.200±38.791 μJy (0.000983±0.000039 Jy) at λ=1.831 μm, mag_AB=16.418±0.043\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_1.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (5.483860e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.637\" (0.91px) → diameter=2.28px (radius=1.14px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0489\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0489\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=2544.291±118.549 μJy (0.002544±0.000119 Jy) at λ=4.607 μm, mag_AB=15.386±0.051\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_1.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (1.003989e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.361\" (0.71px) → diameter=1.77px (radius=0.89px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1580\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1580\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=913.576±37.143 μJy (0.000914±0.000037 Jy) at λ=1.873 μm, mag_AB=16.498±0.044\n",
      "Processing observations:  29%|██▊       | 31/108 [00:01<00:03, 19.40files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (5.778874e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.634\" (0.91px) → diameter=2.28px (radius=1.14px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0207\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0207\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=2290.276±111.149 μJy (0.002290±0.000111 Jy) at λ=4.640 μm, mag_AB=15.500±0.053\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (9.719857e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.438\" (0.72px) → diameter=1.80px (radius=0.90px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1714\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1714\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=940.792±35.942 μJy (0.000941±0.000036 Jy) at λ=1.917 μm, mag_AB=16.466±0.041\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_1.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (3.814502e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.566\" (0.91px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3159\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3159\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=2357.584±97.139 μJy (0.002358±0.000097 Jy) at λ=4.251 μm, mag_AB=15.469±0.045\n",
      "Processing observations:  31%|███▏      | 34/108 [00:01<00:03, 19.51files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_1.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.311397e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.541\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1742\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1742\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=986.890±40.346 μJy (0.000987±0.000040 Jy) at λ=1.480 μm, mag_AB=16.414±0.044\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.271930e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.542\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1367\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1367\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=1024.023±39.575 μJy (0.001024±0.000040 Jy) at λ=1.516 μm, mag_AB=16.374±0.042\n",
      "Processing observations:  33%|███▎      | 36/108 [00:02<00:03, 19.33files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_2.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (3.952595e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.565\" (0.91px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2754\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2754\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=2375.139±101.912 μJy (0.002375±0.000102 Jy) at λ=4.287 μm, mag_AB=15.461±0.047\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_3.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (4.147240e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.928\" (0.97px) → diameter=2.42px (radius=1.21px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2534\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2534\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=2531.522±107.528 μJy (0.002532±0.000108 Jy) at λ=4.324 μm, mag_AB=15.392±0.046\n",
      "Processing observations:  35%|███▌      | 38/108 [00:02<00:03, 19.21files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_3.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.213519e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.574\" (0.75px) → diameter=1.86px (radius=0.93px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1006\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1006\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=1147.682±41.158 μJy (0.001148±0.000041 Jy) at λ=1.552 μm, mag_AB=16.250±0.039\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_4.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.322733e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.949\" (0.97px) → diameter=2.42px (radius=1.21px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2312\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2312\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=2807.264±113.975 μJy (0.002807±0.000114 Jy) at λ=4.361 μm, mag_AB=15.279±0.044\n",
      "Processing observations:  37%|███▋      | 40/108 [00:02<00:03, 19.31files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_4.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.164446e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.574\" (0.75px) → diameter=1.86px (radius=0.93px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0617\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0617\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=1017.127±40.294 μJy (0.001017±0.000040 Jy) at λ=1.589 μm, mag_AB=16.382±0.043\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0679_1.fits\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (4.967668e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.709\" (0.93px) → diameter=2.33px (radius=1.16px)\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3352\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3352\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=2770.542±111.917 μJy (0.002771±0.000112 Jy) at λ=4.398 μm, mag_AB=15.294±0.044\n",
      "Processing observations:  39%|███▉      | 42/108 [00:02<00:03, 19.41files/s]2025-11-13 00:33:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0679_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.141730e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.439\" (0.72px) → diameter=1.81px (radius=0.90px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0796\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0796\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=1132.340±38.347 μJy (0.001132±0.000038 Jy) at λ=1.627 μm, mag_AB=16.265±0.037\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0746_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (8.280554e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.752\" (0.93px) → diameter=2.33px (radius=1.17px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0637\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0637\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=2834.850±135.527 μJy (0.002835±0.000136 Jy) at λ=4.795 μm, mag_AB=15.269±0.052\n",
      "Processing observations:  41%|████      | 44/108 [00:02<00:03, 19.09files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0746_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (8.186452e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.560\" (0.74px) → diameter=1.85px (radius=0.93px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1785\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1785\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=1101.919±37.666 μJy (0.001102±0.000038 Jy) at λ=2.127 μm, mag_AB=16.295±0.037\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 27 pixels with NaN variance using median variance (2.792472e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.099\" (0.83px) → diameter=2.07px (radius=1.04px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2205\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2205\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=1801.026±67.128 μJy (0.001801±0.000067 Jy) at λ=4.107 μm, mag_AB=15.761±0.040\n",
      "Processing observations:  43%|████▎     | 46/108 [00:02<00:03, 19.34files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.412864e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.929\" (0.80px) → diameter=2.01px (radius=1.00px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2326\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2326\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=1062.394±43.543 μJy (0.001062±0.000044 Jy) at λ=1.346 μm, mag_AB=16.334±0.044\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_2.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.392585e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.833\" (0.79px) → diameter=1.97px (radius=0.98px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2170\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2170\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=1105.652±44.017 μJy (0.001106±0.000044 Jy) at λ=1.379 μm, mag_AB=16.291±0.043\n",
      "Processing observations:  44%|████▍     | 48/108 [00:02<00:03, 18.88files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_2.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (2.996648e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.574\" (0.91px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2300\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2300\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=2024.953±91.798 μJy (0.002025±0.000092 Jy) at λ=4.143 μm, mag_AB=15.634±0.049\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_3.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.339184e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.830\" (0.79px) → diameter=1.97px (radius=0.98px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1844\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1844\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=1017.162±40.772 μJy (0.001017±0.000041 Jy) at λ=1.412 μm, mag_AB=16.382±0.044\n",
      "Processing observations:  46%|████▋     | 50/108 [00:02<00:03, 19.17files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_3.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (3.166565e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.571\" (0.91px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2336\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2336\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=2095.266±94.111 μJy (0.002095±0.000094 Jy) at λ=4.179 μm, mag_AB=15.597±0.049\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_4.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.324254e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.792\" (0.78px) → diameter=1.95px (radius=0.98px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1701\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1701\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=1006.390±42.360 μJy (0.001006±0.000042 Jy) at λ=1.446 μm, mag_AB=16.393±0.046\n",
      "Processing observations:  48%|████▊     | 52/108 [00:02<00:02, 19.09files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_4.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (3.447359e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.504\" (0.90px) → diameter=2.24px (radius=1.12px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2517\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2517\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=2179.995±98.121 μJy (0.002180±0.000098 Jy) at λ=4.215 μm, mag_AB=15.554±0.049\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_2.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.581823e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.504\" (0.73px) → diameter=1.84px (radius=0.92px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2306\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2306\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=950.834±41.364 μJy (0.000951±0.000041 Jy) at λ=1.102 μm, mag_AB=16.455±0.047\n",
      "Processing observations:  50%|█████     | 54/108 [00:02<00:02, 19.06files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_2.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (2.212814e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.550\" (0.90px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3802\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3802\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=2330.662±89.843 μJy (0.002331±0.000090 Jy) at λ=3.815 μm, mag_AB=15.481±0.042\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_3.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (2.206441e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.588\" (0.91px) → diameter=2.27px (radius=1.14px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3323\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3323\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=2725.853±98.194 μJy (0.002726±0.000098 Jy) at λ=3.848 μm, mag_AB=15.311±0.039\n",
      "Processing observations:  52%|█████▏    | 56/108 [00:03<00:02, 18.20files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_3.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.528159e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.506\" (0.73px) → diameter=1.84px (radius=0.92px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1931\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1931\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=1082.146±44.309 μJy (0.001082±0.000044 Jy) at λ=1.128 μm, mag_AB=16.314±0.044\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_4.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (1.480095e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.188\" (0.68px) → diameter=1.71px (radius=0.85px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1456\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1456\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=1026.325±39.947 μJy (0.001026±0.000040 Jy) at λ=1.154 μm, mag_AB=16.372±0.042\n",
      "Processing observations:  54%|█████▎    | 58/108 [00:03<00:02, 18.35files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_4.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (2.241896e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.588\" (0.91px) → diameter=2.27px (radius=1.14px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2988\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2988\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=2358.564±94.382 μJy (0.002359±0.000094 Jy) at λ=3.882 μm, mag_AB=15.468±0.043\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.471404e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.478\" (0.73px) → diameter=1.82px (radius=0.91px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1484\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1484\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=867.443±40.227 μJy (0.000867±0.000040 Jy) at λ=1.182 μm, mag_AB=16.554±0.050\n",
      "Processing observations:  56%|█████▌    | 60/108 [00:03<00:02, 18.71files/s]2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_1.fits\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (2.329182e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.527\" (0.90px) → diameter=2.25px (radius=1.12px)\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3030\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3030\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=2045.221±87.366 μJy (0.002045±0.000087 Jy) at λ=3.916 μm, mag_AB=15.623±0.046\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.441440e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.480\" (0.73px) → diameter=1.82px (radius=0.91px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1353\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1353\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=963.083±42.628 μJy (0.000963±0.000043 Jy) at λ=1.209 μm, mag_AB=16.441±0.048\n",
      "Processing observations:  57%|█████▋    | 62/108 [00:03<00:02, 19.04files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 28 pixels with NaN variance using median variance (2.362807e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.525\" (0.90px) → diameter=2.25px (radius=1.12px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1901\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1901\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=2032.974±86.873 μJy (0.002033±0.000087 Jy) at λ=3.950 μm, mag_AB=15.630±0.046\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_3.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.451720e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.756\" (0.77px) → diameter=1.94px (radius=0.97px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1532\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1532\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=966.438±44.684 μJy (0.000966±0.000045 Jy) at λ=1.239 μm, mag_AB=16.437±0.050\n",
      "Processing observations:  59%|█████▉    | 64/108 [00:03<00:02, 19.04files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_3.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (2.401630e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.605\" (0.91px) → diameter=2.28px (radius=1.14px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2596\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2596\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=1990.659±86.711 μJy (0.001991±0.000087 Jy) at λ=3.984 μm, mag_AB=15.653±0.047\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_4.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.448073e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.684\" (0.76px) → diameter=1.91px (radius=0.95px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1694\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1694\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=942.211±41.840 μJy (0.000942±0.000042 Jy) at λ=1.268 μm, mag_AB=16.465±0.048\n",
      "Processing observations:  61%|██████    | 66/108 [00:03<00:02, 19.01files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_4.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (2.518859e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.569\" (0.74px) → diameter=1.86px (radius=0.93px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2444\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2444\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=1820.615±80.044 μJy (0.001821±0.000080 Jy) at λ=4.019 μm, mag_AB=15.749±0.048\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_1.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (2.634656e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.496\" (0.89px) → diameter=2.23px (radius=1.12px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2615\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2615\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=2055.672±86.719 μJy (0.002056±0.000087 Jy) at λ=4.037 μm, mag_AB=15.618±0.046\n",
      "Processing observations:  63%|██████▎   | 68/108 [00:03<00:02, 19.21files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_1.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.435891e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.538\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1846\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1846\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=1041.061±40.612 μJy (0.001041±0.000041 Jy) at λ=1.284 μm, mag_AB=16.356±0.042\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.447795e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.536\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2307\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2307\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=1015.715±41.439 μJy (0.001016±0.000041 Jy) at λ=1.315 μm, mag_AB=16.383±0.044\n",
      "Processing observations:  65%|██████▍   | 70/108 [00:03<00:02, 18.92files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (2.910928e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.099\" (0.83px) → diameter=2.07px (radius=1.04px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3046\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3046\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=1738.574±80.805 μJy (0.001739±0.000081 Jy) at λ=4.072 μm, mag_AB=15.800±0.050\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0204_4.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (8.066626e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.608\" (0.91px) → diameter=2.28px (radius=1.14px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2096\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2096\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=962.074±40.974 μJy (0.000962±0.000041 Jy) at λ=2.438 μm, mag_AB=16.442±0.046\n",
      "Processing observations:  67%|██████▋   | 72/108 [00:03<00:01, 18.65files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0204_4.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.516588e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.820\" (0.78px) → diameter=1.96px (radius=0.98px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2944/3600 (81.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1701\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1701\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2944/3600 (81.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2944/3600 (81.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=445.904±37.093 μJy (0.000446±0.000037 Jy) at λ=0.751 μm, mag_AB=17.277±0.090\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_1.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (6.193488e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.958\" (0.80px) → diameter=2.01px (radius=1.01px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2945\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2945\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=1053.824±34.742 μJy (0.001054±0.000035 Jy) at λ=2.501 μm, mag_AB=16.343±0.036\n",
      "Processing observations:  69%|██████▊   | 74/108 [00:04<00:01, 18.72files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_1.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (1.562245e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.822\" (0.78px) → diameter=1.96px (radius=0.98px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2093\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2093\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=597.272±39.962 μJy (0.000597±0.000040 Jy) at λ=0.768 μm, mag_AB=16.960±0.073\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (5.939406e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.960\" (0.80px) → diameter=2.01px (radius=1.01px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3071\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3071\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=1073.086±34.625 μJy (0.001073±0.000035 Jy) at λ=2.567 μm, mag_AB=16.323±0.035\n",
      "Processing observations:  70%|███████   | 76/108 [00:04<00:01, 18.53files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_2.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.550666e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.992\" (0.81px) → diameter=2.03px (radius=1.02px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2133\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2133\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=535.552±39.404 μJy (0.000536±0.000039 Jy) at λ=0.786 μm, mag_AB=17.078±0.080\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_3.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.576395e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.647\" (0.76px) → diameter=1.89px (radius=0.94px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2171\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2171\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=492.086±38.042 μJy (0.000492±0.000038 Jy) at λ=0.805 μm, mag_AB=17.170±0.084\n",
      "Processing observations:  72%|███████▏  | 78/108 [00:04<00:01, 18.89files/s]2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_3.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (5.790259e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.314\" (0.86px) → diameter=2.16px (radius=1.08px)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3242\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3242\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=1189.216±37.498 μJy (0.001189±0.000037 Jy) at λ=2.636 μm, mag_AB=16.212±0.034\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_4.fits\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:08 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (5.448314e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.302\" (0.86px) → diameter=2.16px (radius=1.08px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3125\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3125\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=1102.399±36.971 μJy (0.001102±0.000037 Jy) at λ=2.706 μm, mag_AB=16.294±0.036\n",
      "Processing observations:  74%|███████▍  | 80/108 [00:04<00:01, 18.90files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_4.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (1.576505e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.647\" (0.76px) → diameter=1.89px (radius=0.94px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3039/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2252\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2252\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3039/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3039/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=582.431±39.542 μJy (0.000582±0.000040 Jy) at λ=0.824 μm, mag_AB=16.987±0.074\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.584829e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.838\" (0.79px) → diameter=1.97px (radius=0.98px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3037/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2557\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2557\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3037/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3037/3600 (84.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=690.974±39.301 μJy (0.000691±0.000039 Jy) at λ=0.843 μm, mag_AB=16.801±0.062\n",
      "Processing observations:  76%|███████▌  | 82/108 [00:04<00:01, 19.03files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.298661e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.589\" (0.91px) → diameter=2.27px (radius=1.14px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3188\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3188\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=1196.569±36.788 μJy (0.001197±0.000037 Jy) at λ=2.779 μm, mag_AB=16.205±0.033\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (5.243953e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.575\" (0.91px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3461\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3461\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=1350.574±38.946 μJy (0.001351±0.000039 Jy) at λ=2.854 μm, mag_AB=16.074±0.031\n",
      "Processing observations:  78%|███████▊  | 84/108 [00:04<00:01, 19.06files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.500622e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.549\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2080\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2080\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=754.124±39.575 μJy (0.000754±0.000040 Jy) at λ=0.863 μm, mag_AB=16.706±0.057\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.501274e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.687\" (0.76px) → diameter=1.90px (radius=0.95px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2063\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2063\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=807.865±41.964 μJy (0.000808±0.000042 Jy) at λ=0.883 μm, mag_AB=16.632±0.056\n",
      "Processing observations:  80%|███████▉  | 86/108 [00:04<00:01, 19.16files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (5.287452e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.383\" (0.71px) → diameter=1.78px (radius=0.89px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4092\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4092\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=1063.322±33.050 μJy (0.001063±0.000033 Jy) at λ=2.931 μm, mag_AB=16.333±0.034\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (1.481494e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.403\" (0.72px) → diameter=1.79px (radius=0.89px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2080\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2080\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=719.661±39.111 μJy (0.000720±0.000039 Jy) at λ=0.904 μm, mag_AB=16.757±0.059\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (4.931199e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=3.079\" (0.50px) → diameter=1.25px (radius=0.63px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3528\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3528\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=751.148±26.300 μJy (0.000751±0.000026 Jy) at λ=3.011 μm, mag_AB=16.711±0.038\n",
      "Processing observations:  82%|████████▏ | 89/108 [00:04<00:00, 19.51files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_3.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (4.747215e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=3.080\" (0.50px) → diameter=1.25px (radius=0.63px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3728\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3728\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=643.977±35.197 μJy (0.000644±0.000035 Jy) at λ=3.094 μm, mag_AB=16.878±0.059\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_3.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (1.460178e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.399\" (0.72px) → diameter=1.79px (radius=0.89px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2154\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2154\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=558.906±35.738 μJy (0.000559±0.000036 Jy) at λ=0.925 μm, mag_AB=17.032±0.069\n",
      "Processing observations:  84%|████████▍ | 91/108 [00:04<00:00, 19.30files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_4.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (4.723504e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.255\" (0.85px) → diameter=2.13px (radius=1.07px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3956\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3956\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=1423.584±38.378 μJy (0.001424±0.000038 Jy) at λ=3.178 μm, mag_AB=16.017±0.029\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_4.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (1.457800e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.449\" (0.72px) → diameter=1.81px (radius=0.90px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3007/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2347\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2347\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3007/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3007/3600 (83.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=711.734±37.958 μJy (0.000712±0.000038 Jy) at λ=0.948 μm, mag_AB=16.769±0.058\n",
      "Processing observations:  86%|████████▌ | 93/108 [00:05<00:00, 19.28files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (4.935230e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.284\" (0.86px) → diameter=2.14px (radius=1.07px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4528\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4528\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=1520.030±39.160 μJy (0.001520±0.000039 Jy) at λ=3.265 μm, mag_AB=15.945±0.028\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_1.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (1.411780e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.573\" (0.74px) → diameter=1.86px (radius=0.93px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3027/3600 (84.1%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1951\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1951\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3027/3600 (84.1%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3027/3600 (84.1%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=753.487±38.104 μJy (0.000753±0.000038 Jy) at λ=0.970 μm, mag_AB=16.707±0.055\n",
      "Processing observations:  88%|████████▊ | 95/108 [00:05<00:00, 18.40files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (1.393711e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.576\" (0.74px) → diameter=1.86px (radius=0.93px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3032/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1769\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1769\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3032/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3032/3600 (84.2%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=988.743±41.599 μJy (0.000989±0.000042 Jy) at λ=0.993 μm, mag_AB=16.412±0.046\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_2.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.739665e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.277\" (0.86px) → diameter=2.14px (radius=1.07px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3908\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3908\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=1482.157±40.189 μJy (0.001482±0.000040 Jy) at λ=3.354 μm, mag_AB=15.973±0.029\n",
      "Processing observations:  90%|████████▉ | 97/108 [00:05<00:00, 18.76files/s]2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_3.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (4.657418e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.495\" (0.89px) → diameter=2.23px (radius=1.11px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3628\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3628\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=1414.463±38.439 μJy (0.001414±0.000038 Jy) at λ=3.445 μm, mag_AB=16.024±0.030\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_3.fits\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (1.373315e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.521\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1554\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1554\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=789.735±37.811 μJy (0.000790±0.000038 Jy) at λ=1.017 μm, mag_AB=16.656±0.052\n",
      "Processing observations:  92%|█████████▏| 99/108 [00:05<00:00, 19.07files/s]2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_4.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (4.719877e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.836\" (0.95px) → diameter=2.37px (radius=1.18px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3709\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3709\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=1667.974±40.322 μJy (0.001668±0.000040 Jy) at λ=3.538 μm, mag_AB=15.845±0.026\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_4.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (1.343486e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.542\" (0.74px) → diameter=1.85px (radius=0.92px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3003/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1348\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1348\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3003/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3003/3600 (83.4%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=748.293±37.514 μJy (0.000748±0.000038 Jy) at λ=1.041 μm, mag_AB=16.715±0.054\n",
      "Processing observations:  94%|█████████▎| 101/108 [00:05<00:00, 19.10files/s]2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_1.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.108546e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.832\" (0.95px) → diameter=2.37px (radius=1.18px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4118\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4118\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=1657.464±40.785 μJy (0.001657±0.000041 Jy) at λ=3.634 μm, mag_AB=15.851±0.027\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_1.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 12 pixels with NaN variance using median variance (1.690161e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.949\" (0.80px) → diameter=2.01px (radius=1.00px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3012/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4808\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4808\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3012/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3012/3600 (83.7%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=897.737±42.041 μJy (0.000898±0.000042 Jy) at λ=1.065 μm, mag_AB=16.517±0.051\n",
      "Processing observations:  95%|█████████▌| 103/108 [00:05<00:00, 19.07files/s]2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_2.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (3.226726e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.055\" (0.82px) → diameter=2.05px (radius=1.03px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3017/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 2.6388\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 2.6388\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3017/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3017/3600 (83.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=927.186±52.357 μJy (0.000927±0.000052 Jy) at λ=1.091 μm, mag_AB=16.482±0.061\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_2.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (5.286015e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.639\" (0.92px) → diameter=2.29px (radius=1.14px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3300\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3300\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=1644.076±41.040 μJy (0.001644±0.000041 Jy) at λ=3.731 μm, mag_AB=15.860±0.027\n",
      "Processing observations:  97%|█████████▋| 105/108 [00:05<00:00, 19.12files/s]2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_3.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (1.359724e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.054\" (0.82px) → diameter=2.05px (radius=1.03px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1747\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1747\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=990.997±42.160 μJy (0.000991±0.000042 Jy) at λ=1.116 μm, mag_AB=16.410±0.046\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_3.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 4, shape (54, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (5.430989e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.641\" (0.92px) → diameter=2.29px (radius=1.14px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2421\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2421\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=2274.172±45.958 μJy (0.002274±0.000046 Jy) at λ=3.832 μm, mag_AB=15.508±0.022\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W29_2A_0482_1.fits\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W29_2A_0482_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.133680e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.018\" (0.82px) → diameter=2.04px (radius=1.02px)\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1333\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1333\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W29_2A_0482_1.fits: flux=1050.897±40.417 μJy (0.001051±0.000040 Jy) at λ=1.940 μm, mag_AB=16.346±0.042\n",
      "Processing observations: 100%|██████████| 108/108 [00:05<00:00, 18.50files/s]\n",
      "2025-11-13 00:33:10 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:33:10 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:33:10 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:33:10 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (104 good, 4 rejected - shown as crosses)\n",
      "2025-11-13 00:33:10 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:33:10 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 25.3\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:10 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:10 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "To run pipeline, uncomment the last two lines above.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Method 1: Using SPXQueryPipeline with advanced_params_file\n",
    "print(\"\\nMethod 1: Using SPXQueryPipeline with advanced_params_file\")\n",
    "print(\"=\" * 70)\n",
    "\n",
    "# Create source\n",
    "pipeline_custom = SPXQueryPipeline(config_all)\n",
    "\n",
    "# Verify parameters were loaded\n",
    "print(\"\\n✓ Custom parameters loaded!\")\n",
    "print(f\"  Visualization DPI: {pipeline_custom.config.visualization.dpi}\")\n",
    "print(f\"  Figure size: {pipeline_custom.config.visualization.figsize}\")\n",
    "print(f\"  Wavelength colormap: {pipeline_custom.config.visualization.wavelength_cmap}\")\n",
    "print(f\"  BG sigma clipping: {pipeline_custom.config.photometry.bg_sigma_clip_sigma}\")\n",
    "\n",
    "# Create and run pipeline\n",
    "# Uncomment to run:\n",
    "pipeline_custom.run_full_pipeline()\n",
    "\n",
    "print(\"\\nTo run pipeline, uncomment the last two lines above.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:11 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/config_params.yaml\n",
      "2025-11-13 00:33:11 - spxquery.utils.params - INFO - Loaded advanced parameters from demo_data/cloverleaf/config_params.yaml\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:11 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:33:11 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Method 2: Using run_pipeline() with advanced_params_file\n",
      "======================================================================\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:37 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:33:37 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:33:37 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:33:37\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Downloading: 100%|██████████| 108/108 [00:00<00:00, 5660.90files/s]\n",
      "2025-11-13 00:33:37 - spxquery.core.download - INFO - Download complete: 108 successful, 0 failed\n",
      "2025-11-13 00:33:37 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.51 GB (actual)\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2025-11-13 00:33:37 - spxquery.core.pipeline - INFO - Processing 108 FITS files\n",
      "2025-11-13 00:33:37 - spxquery.processing.photometry - INFO - Processing photometry for 108 observations\n",
      "2025-11-13 00:33:37 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations: 100%|██████████| 108/108 [00:02<00:00, 47.21files/s]\n",
      "2025-11-13 00:33:39 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:33:39 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:33:39 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:33:39 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:33:39 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:33:39 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:33:39 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (104 good, 4 rejected - shown as crosses)\n",
      "2025-11-13 00:33:39 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:33:39 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 25.3\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:39 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:39 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "To run pipeline with custom parameters, uncomment the code above.\n",
      "Custom parameters will be loaded from: demo_data/cloverleaf/config_params.yaml\n"
     ]
    },
    {
     "data": {
      "image/png": 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KeL5z3EOJO893d2Xm9/1Tx+XMfL3zDgR1rGULM/N+qqCgQPLy8iTQfiHgmLG0BIP5sqlYsaI2NyEiIiIiChWcM+8cBvN+xmQyyeHDh3UOSyAeOwL6jIyMMneyJNG5S1gvk2NJRERERKESzBewAZ7DGMz7GSOQR7lLlSpVAiqQQzCfn58vFSpUCKjj9sdxPHv2rJY9Qa1atXx9SERERERE5GcYzHtZx44dtXwaS3kUXc4DpfVGIJ+QkCCBhsG8+0REROitMY+JJfdERERE5G/mzJmjG+IYX5TZvz3/jMybf0YKCkJzaToG8162bt26EpsyGHPkkZEnMs4DnBcM5omIiIjI3xgJSqOBXVkVmEy6OWrwoCq6ZWQUStPmRyTUsOW4H2KJOvE8ICIiIvJP6SczfH0IQauwDFsoYmaeiIiIiIjIQRknMyU6Porj5QEFLjbAK3Bhn2DAzDwRERERERFRgGEwTwHr559/1ikJuA00gwcPluTkZF8fBhERERGR30AfO1e3UMRgnrxm/vz5GnwbG5awq1Onjga2Bw4c8LufxN9//y1TpkyRlJQUXx8KEREREVHQ45x553DOPHnd1KlTpUGDBpKdnS1r1qzRIP/XX3+VLVu2SOXKlR1+ne7du0tWVpaEh4d7LJh/8sknpUePHsyiExERERF5WKGUkwIp59J+oYjBPHndlVdeKRdccIF+PWzYMKlWrZo899xz8t///lcGDhzo8OuUL1/eqeCfiIiIiChQpGujvUgJJYWmc5sr+4UiltmTz1188cV6u2vXLvN9//zzjwwYMEDi4+M1YEfwj2DfkTnza9eulSuuuELXusRa7ZdccomsXLmy2PuitH/o0KFSu3ZtqVSpklYLDB8+XHJzc7Va4MYbb9TnXXrppeapAZbvtWjRIj32qlWrSlRUlFx99dXy119/FXufr776Slq1aqWfA7dffvmlG0aNiIiIiIJZxqlMXx8C+Tlm5snnjDnpcXFxeouAuFu3bjqffsKECRosf/rpp9K3b1/5/PPP5YYbbijxtX788UfN/Hfo0EGeeOIJzd7PmzdPevbsKStWrJALL7xQn3fw4EH9+vTp03LPPffIeeedp8H9ggUL5OzZs1rCP2rUKHnllVdk4sSJ0rx5c93PuH3//fdl0KBB0qdPH60qwD6vvfaaXHTRRfL777+by/J/+OEH6d+/v7Ro0UKeffZZOXHihAwZMkTq1q3r8XElIiIiIgokBU6W2X/47hn56N0zUhiiqXkG817WsWNHCQsLk5EjR+rmLQg2kaU2bn0pLS1Njh8/rnPmkUXHvHRkxq+55hp9fPTo0VK/fn1Zt26d3g8jRozQQHn8+PElBvMmk0nuu+8+zaQja45MOtx7773SsmVLefzxxzW4hkcffVQOHz6s72+U/Bvz+fE6sbGxmnVHMH/55ZfrvHlDZmamBvqYIvDGG2+Y70dw36xZM3nmmWfM9+N4a9SooT0BUCkAqBTo3bu3JCUleWB0iYiIiIi8Y86cOboVFBT4JJi/aVCkbpkZhdK15SEJNSyz9zIEqGis5u1AHu+7fPlyvcX3vtSrVy+pXr261KtXT0vpkXlHCT2y1SdPntTsOubOZ2RkaNCPDRltZMF37NhRYuf7P/74Qx+/9dZb9fnGvmfOnJHLLrtMP39hYaFuKH2/9tprrQJ5g3ERoCRLlizRjP4tt9xifg9suEjTqVMn+emnn/R5hw4d0mNCkG8E8oCLA8jUExEREVHwSD+ZIaEGMQ1iG8QY7lBoKufyVpoXX3xR+vXrJ02aNNG/zZE0RHLtzjvvlD///LPE/TD9FhW9kZGROgX4qquuklWrVok/YGY+iBw5ckSOHj1q8zHcjyAWZeeWc9MtJSYmahbZ03D1rmnTppqhf+eddzTINjLwO3fu1Mz4pEmTdCvps6AEvygE8oDguSR4T8yJT09P1/nrrjDeB6X7tkRHR+ttamqq3uIXRlHI4G/cuNGl9yciIiIi/5OhDeuifH0YAc3ZzLzBkX1QPYsk3/nnny+tW7c2T+/F9NmPP/5YvvjiC3OlsOHBBx+UWbNmSUREhFbWorIYiT1U+2J6LqYB+5LfBfO4YoKSZFwdQdCGAatZs6aWJj/yyCPmgbd1xeTVV1/VK0NYqqxz585aVt21a9cS3wtN0Z5++mldHg0BHrKl999/v16dKcn+/fs1yPz+++81i4xycGRoUbbt687qCMRtBePIxONYkXFGoNyoUSOfltrjypaREcf/ACifRzZ927ZtesEBHn74Yc3E29K4cWOb9xv7Pv/889K2bVubz8EVNYxFWRjvg//xcW4WVaGC3/1vRURERBR0/GkaKfm/hQsXal+tojEbYkhUGGAKLWI942/5pUuXaiCfkJAgq1evNifo8DWm4KIPFm4xPddX/C7q8NYVEzRSu+mmmzQwQ7MzLI+2bNkyzepu3rxZXnjhhWL7IGvcpUsXLalGVhdzqtevX6/zrLEvNiPD7E/wyw1z9f3xlx1K09EYDvPcZ8+eLXfddZfeX7FiRS3HdwYuUhiZcXv7osQfz8G69vaUVG5vvA8qGey9jzEn3sjkW8KFCyIiIiIq2zRSI1ll/K3raTlZOZL69z6pVideKkX439/9ga5Ayuvm/H6lQ4NtW9CbCwllVC8jMYw4FHAfIEFsWWmLeBB9utBb6+2335axY8eKr5T3xysmp06d0sZkCNyxIfBBaXZeXp5eMcnPzzc/3/KKyaZNm3Qu9OLFi7V0G4EirphgfrMlZGYRNKJRA4J9LDeGWyyHhqzvzJkziy13BoMHD9ZAHs3PUDnwySef6LGhIRuy/AhK/ZXxy82fAnkDrmghW//yyy9rkI3v586dq3POizp27FiJr4MrbQi0cSEGTepK2hdTDXCB5+uvv9aLMUXhHwTAXH4oev6gYgDHiQtPOCdLep9atWpphcC7776r5f0GXGjCLwoiIiIicmwqKf72ttwQeKGKF38v4hbfF30O9nN3IP/IZVPl2dtf0Vt8T+5lcnG+vMmBOfP2IJEIqPCGrKws7eMF6PFVlHEf4glf8rvMvDeumLz11ls6Z/r666/XJggGlKjPmDFD70NAb9nB/LffftOAHdlYPMeAMgwsSfbNN9/oe+E4WGbtPEyhwLrumC6BCzcovUdlxt133y0NGzbUX8YoaUHpCy7a2IIgHT9bLE2H7vW4kIO59WiYh6Z0CMCN/+EQiKNyA9M3sDQdlpzDPwafffaZTvNAuQwCcVwQwtJzCMZRdYF58jgH8DO/4447pH379nLzzTdrtn/v3r3y7bff6jmMKgPABR6sP4/PgwtIuJD0f//3f3p8ti44EBEREVHpU0k9PY0UzewwB94SMvJ7tqRKfm6B3m5YskmSWtQzP34k9ZhExUdy3ryfzpkvCSrAkaBFLGnEk/g+JydH/8a3taQ0YgBARbcv+V0w7+4rJgiwEcBZBvMIuEraB4EX5lEg449yfWNOhbEPOqAXLaXHLxeU3ONYEAhaXgQgx+ACipFVRwCPjDmWrENwj870CKDbtWsnkydPtvs6GHsE/U899ZQG1AiYMa8dXeaxRJ0BQT6qP9D/4IMPPtCLO7gPFwKMfwiw3+uvv64B+dChQ7WSAxcFcCyY41+7dm2ZPn26ztHH/+zYH+cBLiIYrrjiCr1AgIs86KuAz4h171GBYqv6g4iIiIh8P40UjeyKNrNDaX2DVkkayOO2w+VtipXaswFe2RSYyuvm/H7iMPztjmncmNq9detW/Rp/13/00UeayAMk6cBWIG9U8CL5h4pyrMAVFeWbxocBE8y784qJkdk1HreECwWYD49gcvv27eYKAHv7GPcjmMd7MZi3DdMUsJWUVUdPAgOy8ShPt8dYz7JoJQQy6uiJUBo0LyztPTCtA5st+Dk78rPGhQrLChDA1AwiIiIiCpxppAjcn182WTPytgJ5d8rJypXUrfulWm3MzT+XyKR/5eaYJC/33wj+TOa5BtWOQCNz9Dqz7HP13nvv6ZRdg1FBa+/cQkCP6bgM5r14xQQZWGP+ckn74X4E81hazAjmS3sv435jObKS4AdudEMHZPmNTD/uR5mQsQUi47i9cfwHDx7UW/RLCNTxssc4D3BeWJ4zRRnnjb3nkPtx3H2D484xDxU81znuoSSQzveKlSpK/eZ19bbo8brrMyCQn3Dls5Ly1z5JbllPpi961CMBfVnGHQlVbAbEWG45JiknhQ60dXv/tRPy7izXVqhCBbYRl6G3ApqZY+rttGnT5LHHHpNA4reZeU9dMbGcp1zSfkbjM+zj6HvZ2sdeh3MDyv+xDBugmRr+Z0KDP8smf4ECvwyMbHlJneDdARd4cFEHc89xEQVZ/EAcr9LgM+F8wDQDY4qJLXgOLlBh/FHhQN7BcfcNjjvHPFTwXOe4h5JAO9/TMk9LhaPlHb7fnrMZWZKVmW113/5th2XPlr1SkF+ot8u/Xi11m1kvhxwRWVmqREWIr8YdU2PRY8xXc+ZvHh4v/YfGmb8/m1koN3fd49R7IemLKbLfffed9lvD9FusjIbpG1jOWl/37Fm7MQn4qsTer4P5YLpiYgmZezRis5WZxxx9XAxA2XggN9GzF3i6AyotsBwhGuRh/rnRQyHY4BzAL1ZUHhRdD7PoL2JcPMF0k0D4BzBYcNw57qGC5zrHPZTwfOe4OyI/o1B7KDl6v102nt6waQP57tWfzZn57td28Vhm3tW/IdGfCj2hLDPzRZOWnpwzHxZeXsIshqTA5MjidCXHLliyfMOGDdprDcE8puMCmm+XFMgjTo2Li2Mw780rJsY+xn6WgXVJ+1juV9J7OXplBp/H1nsC/ifC/1DGFmhwVc84bk8ef4MGDazKeoKVcR7gvCjtF6yjzyP34rj7BsedYx4qeK5z3ENJIJ3vxrE6er+zIqpWlhnfPyYblm2WDped79E5866Oe0REhG4Gd/3czpXZOx9HFJahmz1Uq1bNaonpZs2aacIV32NlLDS6trRx40a9NaZk+4r//99S5IoJAkZjeTFXrpggkI6JibG7n3G/5dWl0t7L1j5EREREREQZp0tOPtqCAD6peV02v/OSX375RW+x8hTgQgWWpAasTFXUggULzCud+VLABPOOXDEpqqQrJm3atLF63BLmrW/ZskXLmps2berQPvbei4iIiIiIgltOVo6uQ49bdwTzoQrN7wpc2ApLCWtXrlwpixcvLtbsD7Ef+nBh5TQE8EgeG8aMGaO3mOa9Y8cO8/1YBnvu3LlacY3lq32pfCheMcFa8paPW/rmm2907nqvXr2s5ikb+6AqoGiJ95EjR2TFihVaAdCtW7cyf85g7MxOzuN5QEREROT/EMA/ctlUefb2V/S2pICeHJ8z78pmD4LxK6+8UmrUqCFXXHGF3HbbbdKnTx+tqh41apT24Jo/f77Uq1fPvA/iwdGjR2szaix93bdvX7nqqquke/fu2qgavbsQ0PuSXwXz3rpignXDUW6/cOFC+eKLL8z3Hz16VMaNG2fuMm/pwgsv1EAdzxk/frz5fvwgR4wYoceIE6Eszd+Mfe31AKDQYZwHnm4oSERERESOST+ZIUdSj8mBnYfMG9ad37MlVfJzC/QW31s+ji0z7Vx/LbIPGXZXN3vQSH3ixIla2b1582ZNBCP2jI+PlwceeEAbrg8cOLDYfi+//LIG7c2bN5clS5ZojIkgf/ny5Rrc+5pftUxHMD5kyBAtp8cSdOjiffz4cR3cQ4cOaaa8pCsms2bN0isml19+ueTm5upgI7Np64oJfmjvvPOO/sAGDBggPXr00PdCB33MsccFAtxXFF4LTfjwXj/++KO0aNFC1q1bJ7t375auXbvKo48+WqbPHxYWpseKCwbGMniB1AgP442LG+jCHkjH7Y/jiEAe5wHOB5wXREREROR70fFRUiOputRpXMt8X7U68dKgVZIG8rjtcHkbqRRxbrUqw8GU4z442sBTYCqnmyv7ldZA++mnnxZXDB48WDd/5FfBvHHFBOX0uGKCQB4lD8nJyRp0I/PduHFjm1dMEMjPnj1bg3jsgyAfne8RZNvSv39/vaKCjP6aNWv0AgCC8/vvv18GDRpkc58mTZrI77//LpMnT9YKgi+//FIb4+F9cNzGEnNlUbPmuTUkjYA+0IJQVFUYXfmpbBDIG+cDERERkS9knD4jUbFVOfh2IHB/ftlkzcjbCuTJcxa9f0wW/+e4FBaG5jRlvwrmvX3FBGXzixYtcmofVAUgQ+8pCIJr1aqla1SidD+QIJDHnBJUOQTCsiL+DKX1zMgTERGRr6FxG4P50iGAT2pRj4F8GRkN7RzV+44aup3NKJDB7TZJqPGrYD4UdOzYUYO0kSNH6lYSPCfQgjkE8whCMR2CwTwRERERUXCbM2eObgUFBW55vUJTed2c388koYjBvJdhjj2a7xERERERUeCJio/09SH4DSNBmZ6eLjExMV7PzBsKhME8ERERERGRQ0J1Pj2a4JFnYE0zVxrgFUpo4sRmIiIiIiJyaT49EfkOy+yJiIiIiIj8TFRc6JXzO7JmfEn7hSIG80RERERERB6Sk50nqTuOSELNGKlUuaLD+0WH4Nz8AlN53VzZLxQxmCciIiIiIvJQID/hjtclZdthSW5WU6a/f59VQJ9+MjMkg/aSFEo53VzZLxQxmCciIiIiIiqjzIwsOZhy3Oo+ZOQRyOfnFejtxhXbJalJDfPjh/cekybnJ0lUbBWOPzPzTmMwT0RERER+KyPtrETFMNDxhZzsXEndfvh/5eHhPjmGQBIZFSG1k6tZ3YexQ0beyMy3v7ipVWbeVJDPQL4Mfv7goPz84UEpLOTSdEREREREfiUjLYvBvI8C+Qk3vyop/xyU5PNqy/SPRzCgdwECd5TWIyNfNJCnsq8zf/FtdXXLysyXhy/4NeSGlJl5L+vYsaOEhYXJyJEjdSMiIiIi8vV68UWXmUNGHoG8lof/c1A2Lt8mSU1rWj3nTHqWl480MCGAR2l9MAbyc+bM0a2goMAtr1doKqebK/uFIgbzXrZu3TqJjo729tsSEREREdkUFVtVt2Ll4efVNmfm23dvZpWZ1xL8HYelfnYuM/YhzEhQpqenS0xMTJlfr9DJzLyBS9MRERERERFpNjlcS+uRkbcVyE+49TVJ2XZIkpvVkukfDmdAj4si7EpfZoWm8rq5sl8oYmaeiIiIiIiKQQCPDP2Jw2lW9yMjj0D+XIf2Q7JxxTZJamJdgo/u7EWz/cEuOj7K14dAIYbBPBERERER2RQZjQ7t1W10aK9lzsy3v9g6c0/kqgIpp5sr+4UiBvNERERERORcCf6HwzUjz0Ce3Ill9s4JzckFREREROT3crLzJHXXUb0l/wvoUVrPjDy5U4FFdt65LTQxM09EREREfgcB/Pihb0vKjiOS3KSGPPf20KBc2otCV05WrqRu3S/VasdLpQhOUwBm5p3DYJ6IiIiIfCoj7axkpFmvWY6MPAL5/PwCvd24eqckNUo0Px4VEyFRMVV8cLRE7gnkx1/xtOzZsk8atKonzy1+jAG9C9Z8lCJrP0qVwkJTSJ6WDOaJiIiIyKcQlBcNzBMSozUjb2Tm23dpzMw8BaT0k5lyeO8xMRXkm+9DRh6BPFYEwO2GZZslqXldq/2i4iIlOsSWuyswldfNUR1vbqhbdmaePNtlsYQaBvNERERE5HdQUo/SemTkGchTIENAXrN+damdXM18H0rrkZE3MvMdLjufmXkRMUk5KXShM72J3ezJGzp27ChhYWEycuRI3YiIiIio5IAepfWcK+87WC+e3D+OmCOP0npk5AM5kJ8zZ45uBQUFPsnMG1zZJxgwM+9l69atk+joaG+/LRERERGR06Jiq3LUPHRRBAE8Suu9Fcij3N/dZftGgjI9PV1iYmLK/HqFpnK6ubJfKArNSxhEREREREQhJOPUGV8fArkZM/NERERERETkcwVSXjdX9gtFDOaJiIiIiCio5tMjCx0VxykCgYZl9s5hME9EREREREE1nz7jNIP5QFQo5XVzZb9QxGCeiIiIiCiEMYtN/qLAVE43R236ZIds+mSnmApNEooYzBMRERGR34qKifD1IQS9jNNnWZJOAanNTU10y8nMk9cu/kJCDYN5IiIiIvJbUTH+Oy+biNyLc+adE5qTC4iIiIiIiMivmEzlpdCFzWSyH9aePXtWvvrqKxk6dKg0a9ZMKleuLFWrVpU2bdrI1KlTJTMzs9g+U6ZMkXLlypW4TZgwQXyNmXkv69ixo4SFhcnIkSN1IyIiIiIiCkRz5szRraCgwC2vVyDldHNlP3s+/PBDufvuu/Xr5s2by3XXXSfp6emyatUqeeKJJ+Sjjz6SX375RRITE4vt261bN2ncuHGx+zt06CC+xmDey9atWyfR0dHeflsiIiIiIvIzUXGREsiMBCUC45iYmDK/HvrYodTelf3sqVixotxzzz3y4IMPajBvOHTokFx99dXy+++/62MI+osaNmyYDB48WPwRy+yJiIiIiIh8IDreO8F8TlaupG49oLehaNCgQTJ37lyrQB5q1aqllQXwxRdfSG5uYI2PXwXz3p7LsHLlSrnqqqskPj5eIiMj5cILL5T33nvP7jHu379fhgwZIrVr19bja9q0qZZmZGdnu2UMiIiIiIiI3AUB/PgrnpXnBr+qt/4c0LsyX77wf5urEGtCTk6OnDhxQgKJX5XZe3Muw+effy433XSTFBYWSvfu3aVatWqybNkyvWqzefNmeeGFF4rts3PnTunSpYscP35cWrVqJRdffLGsX79eLzRgX2yVKlVyy1gQEREREZGLWehthyShZqxUiggPqSFMP5kpGafOWN2HjPyev/ZJfl6B3m5YtkWSmtcRk8kkaRmnJT/zXIWAt6oE7CmUcrq5sp+rdu/ebS7FR5K3qB9//FH++OMPTd7WrVtXrrzySr+YL+93wby35jKcPHlS7rrrLm3UgKC+X79+ev+RI0fkoosukpkzZ8o111wjPXr0sNoPr49AftSoUTJr1iy9Lz8/XwYOHChffvmlPPvss1opQEREREQUMIHv9sOSUDPGrwNfBKhRcVUd+jwTbnxFUrYekOTmdWT6Z6Psfq70kxkSHR8lwcJWUF6tdpw0aFlPA3ncdrislY4JkpoVjoomSsuX94+C7QJTOd1KfV5ugW6GvDP5Lr+nEdddccUVNhOz77//vtX3kyZNkv79+8v8+fO1utuX/CqYR1YcW1HGXIauXbua5zKEh7v+y+att97SjP/1119vDuShRo0aMmPGDL0PAb1lMP/bb79pWT5OdjzHUKFCBXnttdfkm2++kVdeeUUef/xxvY+IiIiIyJ9p4HvzHEn556Akn1dbpn880m8D+ozTxYN5BPi43xIy8gjk8/ML9XbjL1slqVktq+dExVY1v1bGycygCuaRmS8azONn+tziRzUjbwTy/srRkvlN8/+QzW/9Ueb3++677+Ttt9/WpPJTTz1l9RiqvlGtjUx8UlKSnDp1SpYvXy7jxo3ThDASw0jo+lLARJ1F5zIgwHfVt99+q7cDBgwo9hgqADAXfunSpVpKga8t97n22muLXbHBRQCU3KME49dffy2W0SciIiIi8qVzge9Zq/uQkUcgj/Jr3G5cvk2Smta0ek5UbBWHMuK+gOMqemworUdG3sjMt7+kuV8Hr+6Wcap4MA8YA5TWB8tYtB7URlrc0sr8fd6ZXPn8uk+deo1//vlHbr/9dp1u8Pzzz5vjTQMes4Rebrfeeqtceuml0rp1a+31tmbNGuncubP4SsAE8+6cy7Bp0ya9bd++fbHHkPHHfHjMhd++fbucf/75pe5j3I9jwHx7BvNERERE5P+Bb4xm5I3MfPvuzQI+2MPxo7QeGflQC+SDgc6Zd6DMvlzFClKhYgWX58wfOHBAy+qRbR8zZoyMHj3a4X2RVEZDdGTtFy9ezGDem3MZUF6flpamXyPotwX3I5hPTU01B/N79+4tdR/APvacPn1a56cY8FmCpWkePheubFl+PuK4Byue7xz3UMFzneMeSkLtfK9YqYI889Fw+WP5dmnbval+74vP7si4O/Nzweeo37SmQ58n2H7e9j5P0cfKcr6jWhqbZYzlDiYXG+CZnNgH/dN69+6tcZsRlDurSZMm5t5uvhQQmXl3zmWwXN6uSpUqNt8PJRSQkZFRbD9n9rEFx2hp7Nix8vDDD0swwC8CXCjBLwV/aaIRCjjuHPdQwvOdYx4qeK5z3L0pplYlSUs/LeKeeMwj5zu6rocdNTn8mo4+Py3ztFQ4Gjx/t+JzVzhazs5j7vk9g/gLPcbcDVl5RzLztvZzBGI6xI1///239kl78803dTlzZyHmtIwBfcXvg/lgmMtgCVeAoqOjgzYzj/8ZqlevzmCe4x70eL5z3EMFz3WOeygJ1fO94Gx5SUys5tfjXnC2nCQmVnf4NR19fn5Goc1lrwNVfqapxM+DJegsHyvL+Y4EKxp/W2bmiyYtXeHqmvGFDuyDSgI0QEdj8z59+uiy52FhYU6/F+JSI1lc0hRsb/HrYN4TcxksS+7Pnj1rFVgbzpw51xUzKurfzpbGftjHFlv72BIbG2vzPYMFfiHgl0Eo/QPoDzjuHPdQwvOdYx4qeK5z3L19rvnz+e7sMTr6fH/47O5k7/PYeszV3zMRERG6Gfx9DAsKCuSWW27RHmdoXI4V0uytjnbs2DH59NNP5c4777SK75DZR1X12rVrpWbNmlYro/mC3wbznprLgEA6JiZGS0r2798vLVq0KLYf7gfLq0v169fXde6NxxzZh4iIiIgokNZp99cl9LDkHDrVs6FdcPNUmf3s2bPN2fRq1arJiBEjbD4PMSceR6L2/vvvlwkTJkjHjh01UYwAf+PGjbqyGhK0CxYsKHEKdkgH856ey4BSfcyrxw+jaDCfl5cnW7Zs0SXpmjZtarXPwoULdR9bjPuNhnlERERERP4Cy9IFYjCPQH7CgFnmpeamLxjNgD7Yu9m70ACvsJR9jLgQ7K0NP2XKFA3mExISZPz48TpdGyucrVq1SkvyGzRoIIMHD5aHHnpI6tSpI77md8G8N+YyYC15BPO4mlJ0zv0333yjy9tdc8015jXmjX2mTp0qX3/9tR6j5Tz3I0eOyIoVKyQuLk66devmwqcmIiIiImdkpJ2VqBjfZsX8TSBn3yHj9Bk5k5ZldR8y8gjk8/ML9RZLziU1q2V+PCq2+JJ7jsrJypHUv/dJtTrxUikiOHpYBTpPZeanTJmim6NQWj99+nTxd+UDfS7DnDlzinWQR2Z/+PDhJc5lGDZsmJbbI9OO9zAcPXpUu+AbXeYtXXjhhRqo4zm4SmPIz8/XMg1k9EeNGqUd94mIiIjIszKKBH10LvvubxcXnIHAvHaDRKsNa8UjI1+hQnm9xfeWj5clkH/ksqny7O2v6C2+J/8J5h3ddn2+RZbe9pH8PGyBhKIyZ+aRxUYJvDs6sntrLkN8fLy88847MnDgQBkwYID06NFDSymWLl2q68Cj2R7uK2revHnSpUsXXfMeFxxQor9u3TrZvXu3dO3aVR599NEyjwERERERUTBwR6UA5sijtB4ZeQTyrsyZTz+ZIRkn/12eGpCR37MlVfJzC/R2w5JNktSintVzouIjJTrefnNrv+stsHW/VKsd79I4BaIG/VrrlncmVxZd8aaEGqeD+Z9//lkz2itXrtQ57VlZ566KImBu3ry5BrV9+/a1GQyXxptzGfr376+l9tOmTdP9c3NzNTjHxYFBgwaV2FAPTfAmT56sHfJxjGiMN2nSJJk4cWLQLDFHRERE5E0smfetqFj/nq6AwBSl9c4EqMjyGxCQFw3KUVrfoFWSBvK47XB5m4AutUcgP/6Kp2XPln3SoFU9eW7xY8XGKxCmYHh6nfmQDOZRQj537lx58cUXJSUlRTPbmIeO+eaYJ4756QjE9+zZI//5z3/klVde0a7uKFW/9957HS499/ZcBpTNL1q0yKl96tWrpxl6IiIiInJfyTznv/tOIAR57v5MCNyfXzZZM/KBFsinn8yUjFNFKg227tdAPj8PlQb7ZMOyzZLUvK7N/aPj/12q298wmPdAMN+4cWPNXCNjjdL0og3litqwYYN89tln8swzz2hJPC4AEBERERER+Uv5PwJ4lNYHUiBvBONFA3KU1iMjb2TmO1x2fkCW2psc6Exf0n6hyKFgHiXkKFt3tIy8Q4cOuqH7O7PY1jC3H1MBRo4cqRsRERERkcfnUm8/LAk1YwIywPNE1/xgq0bAzxWl9cjIezOQRzNybGhk7g7MzHsgmEepvCvQid7VfYMVGuahkz4RERERkVfWab95jqT8c1CSz6st0z8eyYA+SGlvgeZ1vfrzNRKU6enpEhMT47X3DTSLFy+WyMhIueiii/R7XAB58803tWcbvsbUda8tTffJJ59oF3siIiIiIm/Lyc6T1F1H9Zb+NyZZufLP7ykatB/cc8y8bVy+Te/DXGrc4nvLx7E5u4Qckb8sTVdosfmzRx55RC94wJ9//qm95a666irtOYeV1Ly6NB3Wgkd2GR3h0QTv0ksvdfkAiIiIiIgchQB+/NC3JWXHEUluUkOee3uoVKrsWLPlUMy+o7Qe9xmPte/ezCuZWy3t/+egJNSKZSUASaiX2e/Zs0ez8PD555/LNddco/3lsKQ6gnqvBvO//vqrfPDBB9rkbv78+br826233qqBfatWrVw+GCIiIiKiosvWodu9ARl5BPL5+QV6u3H1TklqlGi1T1RMRNB2x0cWPeP0Wav7MB++aPY9qWlN8+Ojn7tJ/lq3Wzr3auW1QH789TMlZesBSW5eR55bOLbM72u51BwFL2eD+QNf/SEHFv4hpkL/boGH6ednz577/3bp0qVy55136tdYJc7I2HstmMda8thmzZql9f8I7GfPni3PP/+8tG7dWu644w4N7mvVquXygRERERFR6JTMJyRG28ywIyi3DMzxPGTkjcx8+y6NQyozj8ZtRZu3OZJ9D69UUbPkHrvAYFGqj4w8Anm9uLD1gGz86W9JOq92qZ/DnmBrWEe2mUzldHNU7evb6ZZ/JkdWXj/bb4cVc+VRTo+l0X/77Tedtg7bt2+XunVtLyHosWDevHOFCloigC0zM1O+/PJLzdSPGzdOJkyYID169DAvZ4erEUREREREZSmZx+N4HjLyoRbIlwSBO0rrkZH3Vhm9vcAcFw2QkTcy8+0vbcFSewpps2fPlhEjRsiCBQvktdde08p2WLRokVxxxRW+CeYtbdmyRa8yYEK/yWSS8847T06cOKElBI8++qh89NFH5u59RERERBR63FUyjwAez2MgX6STedOafhE06zJpC8dqRt7fA/moIuu1B4r0k5nF1poPBlhj3pV15gtd2Meb6tevL998802x+1966aUyvW6ZgnmUBaDE/sMPP5Tdu3dLtWrVtLweAXz79u31OevXr5ehQ4fKfffdpwE/EREREYUmR0vm085kS0zVyj49VnLDxYXzavt1IA/R8VESiDJOBWkwH6QN8KCgoEAr2bdu3arfN2/eXPr27avV7q5yaU/MlUcQv2HDBqlUqZJce+218vLLL2uJQFhYmNVzL7jgAp0fgICeiIiIiKi0knkG8+TRLvvbDklCTXbZD4Y58wZX9vGmv/76S2PmI0eOSLNmzfS+5557TqpXry5ff/21y03kXVpn/qGHHtIg/vXXX5dDhw7pBP6rr766WCBvGdBPmjTJpQMMNh07dtRlCebMmePrQyEiIiLyuaIl89m5+bL74Am9JXL7En43viIzRs7XW3wfbKLivJutR0yD2AYxjjsE6zrzw4YN04B9//79uhwdtn379sn5558v99xzj3cz87t27ZIGDRo4/PyWLVvqRiLr1q2T6OhoDgURERFREQjg731pgew8cFwa16kmcx8aIJXD3dbiiULIuSX8/u2wD8jIa5f9/MJzXfZ/2SpJzWpZLX8X6F3zvV16P3LkSN2wvFpMTIxX3zuQ/PHHHzr9PC4uznwfvn766afLdCHEpd+OzgTyRERERBS8UBKPrSyOnkyX/MphmpFHIJ9fUKC3a/5OlYa1E+zu4wjMvw+mOfhYZz4q1ropIDmyhF+RLvuXNPf7Of2hJljL7Js2baol9kUT3EePHpXGjRt7Pph/8cUXnXphlNwjA42yi06dOrlybERERETk59wRKFfILpDaibGSGBupGXkjM9+5RVKJmXljn1BdFcDZYJ7B//+W8PtslGbkGcj7J5OLJfMmPwzmUa1gePbZZ2XUqFEyZcoU6dy5s963Zs0amTp1qs6d93gw//DDD7v0BuXKldNl6v773/9Ko0aNXHoNIiIiIgp+CNxRWo+MvL1A3liyjoqMiZ0AP9DLx93aZb9ZLWbk/ZRJA3PHn3/06w1y9JsNYiosFH8TGxursbABy7cPHDjQfB++BzTGQ6d7jwbze/bsceqFcXAZGRm69jwuBOBKxLfffuvKMRIRERFRiEAAj9L60ubKF117nvwvYPe34yH/h/Xi8Z+jql17gW4FZ3Nk04CZ4k9++uknj7+Hw8F8UlKSS2/QunVrnR+A0gIiIiIioqKYZQ9ODOY9uLze1v1SrXY8Kwz82CWXXOLx9/BIe9A33nhDvvzyS1m0aJF+37NnT9mxY4cn3oqIiIiIAlzRLHswNasjcncgP/6Kp2XPln3SoFU9eW7xY0EV0AdrAzw4ffq0vP3227J161b9Hs3w7rrrrjKtAuBSMI/g3F55/Z9//in5+f+uDYpJ/sZEfyIiIiIiexjMU6hLP5kpGacyi92PjDwC+fy8Ar3dsGyzJDWvW2yteW8vUecuaH5XzoXAvNDPg3ksS9enTx+JiIiQCy+80NxgHkvT/fDDD9K+fXvvBfOFhYVWk/mNIB7l9MjAo4v9Bx984NIBERERERERhTIE47YCcpTWIyNvZOY7XHZ+kGXmnWuAZ3BlH2966KGH5LrrrpM333xTKlQ4F4Ij+T1s2DB58MEHZfny5d4L5n/++ecSH/vrr7+kd+/esm7dOrn66qtdOqhg1rFjR122b+TIkboRERERETkqJztPUncekYQaMVKpckUOXIhB4I7SemTk/SGQnzNnjm6udmMPlTL79evXWwXygK/HjRsnF1xwgcuvW17cDLX/999/v/5QqThc5Pj7778ZyBMRERFRiTJOn7UZyE8Y9KbMePgTvcX3FKLL6zWv6/NAHpCcRGyDGIdKhsr1vXv3Frt/3759EhUVJX7VAA+T+PPy+MuFiIiIiMgVh/adkIw064AeGfmU7Yd1vjRuN67cLkmNaxRrJmhvvXkSiYrlknn+Klgz8zfddJMMHTpUXnjhBenatavet3LlSnnkkUfklltu8Z9gPjc3V+fL33bbbe5+aSIiIiKikBAZHSG1k6pZ3YfS+uSmNTWQx237bk1Zau8CLpnnv4K1Ad4LL7ygPefuvPNOc6P4ihUryvDhw2X69OneDebRQt+WjIwMWb16tbbdb9SokdXzcPBoxU9ERERERM7DHPnp796tGXkG8hSMnG2Ad/K73+TUonViKiwUfxYeHi6zZs2SZ599Vnbt2qX3IV6uUqVsVTQuBfM//vhjsW72BlxhqF69uqxYscLq/pKeT0REREREjgf0KK1n8zsK3mDe8bgx7spOuhWczZYdt7ue4fYWBO+tW7d22+u5FMynpKS47QCIiIiIiAJBelqWRMdE+PowiMhJZ8+e1fXcv/76a/n1118lNTVVVxhr3Lix9O/fX8aMGSORkcWXAoT58+fLq6++qo3+kGHv3LmzPP744+a5777k9m72RERERES+UrRpnFtfOz3LY69NRP82wHNls+fDDz+UG264Qd555x0N4rHm+8UXXyx79uyRJ554QpcPP3r0aLH9sAb8kCFDZMuWLdKrVy+58MILZcmSJdK9e3f56quvJCCCecyDd1VZ9iUiIiIickZGWpZPAn0iKjtTGTZ7MBX8nnvu0ew6tk8//VQWL14s27Ztk3bt2sk///yjgbulpUuX6jz3hIQE2bRpkwbv2Gf58uV6QQBBPnrF+X0w37NnT7n00kv1Q6NEoTSZmZl69QNXLC677DJ3HCcRERERkccCfX9ZSx6wfjyWoeM68hRqPJWZHzRokMydO1eaN29udX+tWrVkzpw5+vUXX3yhK7MZXnzxRb1FSX2TJk3M93fp0kXuu+8+DeQdbfCOCwBGF3tLuA+PeXTO/Pbt22Xq1Klyxx136FWNTp06Sfv27aVBgwYSFxcnJpNJTp06pWUK69evl99++00PDK33sUwd/QslHLiSM3LkSN2IiIiIKDShUqDomvAI4CcMetO8/By617PZHRUVFWd7fre3IRDGVlBQ4J4XdCTNXtJ+LmrTpo3e5uTkyIkTJzTAz8rK0qbvMGDAgGL74L5XXnlF5+CPHTu21PdAYvzQoUOSmJhodX9aWpo+5ur4ORTM16tXT958801tpf/+++/LwoULtQkAPqSliIgIueCCC2TatGka+KOrPVlbt26dREdHc1iIiIiIQlxmepYcTD1udR8y8gjk8/MK9BbL0KF7vaUz6dlePlLyN9Hx/hHMGwnK9PR0iYmJkUC0e/duvUXSOj4+Xr9G+T2Ce8SzdevWLbYPEtuwefNmh94DyW9bq7vh4kHVqlW9082+WrVq8tBDD+mGzPvevXv1AABzCerXry8VKrjUIJ+IiIiIKKRERkdI7aRqVvcl1IjRjLyRmbe1nnxJ5flEAc+Bknl9Wl6+bobCrH/L452FefFwxRVXSKVKlfRrxLlgK5AHBOCxsbFanZ6RkSFRUVE2n9evXz+9RSA/ePBg8+sDsvG4GFCWrvgud7NH0N6wYUMtG8eGr8sayGM+PhoLDB06VJo1ayaVK1fWgULpA8r8MRe/JFgyAN0FsaQArqhcddVVsmrVKrvvt3LlSn0eno/9sP97771nd5/9+/drs4PatWvr8TVt2lQ7IGZn8wopERERUSBypDGezmPffczj89gRuKO0ftwLN5VYYl+0NJ8ouNaZL307+eVy2T34afOWMvwFl97vu+++03nvyMo/9dRT5vuNuBPrwpfEyKgjmC8JqhWwITOPgN/4HlvNmjW1Kd9//vMfcZVfpdHRNO/uu+/Wr9GcAEsGoGQDQTkC5o8++kh++eWXYnMN0HkQV1RQ5t+7d28NrLFkANYSXLBggfTt27fYe33++edy0003SWFhoTbqQ9XBsmXLtDkCrpC88ELxE2Lnzp3a8OD48ePSqlUrXc4APQJwoQH7YrO82kJERERE3qMB966jkpAY7dQ8czTGi4qpYvd1x494T/bsPCINGteQ516906Pz2PHaKK3nXHkKNY40s4PY6y+RmKu6mb8vzMqRvSOfd+q90MH+9ttv10D7+eefN8+dd6d58+bpbXJysjz88MNlKqn3+2DeWDIAwbllp0E0C7j66qvl999/18cQ9NtaMgDL4BmdBvF1jx49NIuOW5RBGE6ePCl33XWXljYgqDfKH44cOSIXXXSRzJw5U6655hrdzxJKIxDIjxo1ylyOgekGAwcOlC+//FJ7CkyZMsXj40RERERENgLuu+dJyo4jktykhjz35hCrYNiZQD89LUvOZOaYv0dGHoF8fn6h3m5Yu1uSGlr3hoqKjpDomAj+WIjKAoG8A8F8uQoVdbPazwkHDhzQsnqUyY8ZM0ZGjx5t9TiqtsHeSm5nzpzR25JK7C2NGzdOLxoYUlNTNX5s0aKFJqO9XmbvCd5aMuCtt97SjP/1119vDuShRo0aMmPGDP0aAb0ldOhHWT6qAoznAKYWvPbaa3ohAh0NbS05QERERETuL40/uPeEedu4eqcG8vn5BXqL743H8P2YO9+Q6Y9+pgF/aaXyCMrr1Is3bx06NdSMfIUK5fUW31s+js3ZQJ7LzxH5xsmTJzWARkCNxK+timz0gjOmWJcUyCPOxMpujgTziDuN6dzYD9O7EW/ifsSSQRHMO7NkADiyZABgyQBL3377bYn7oAIAc+GR8becB2/sc+211xYrpcdFAJTc48rOr7/+WubPSkRERET2oSy+dv0E89a+S2PNyIdVKC916sdLrbrnulLDof0n5cDek1KQX1gs0Md25OBpu/PmkclHaf34p/q7pcTeWH5uxsOf6C3Xk/9Xxqlz2U4KTY7Ombe1OQJz4a+88kr5+++/NamLFdtsdZlH/zbEfMeOHdMsflEbN27U2/PPP9+h98XzES8CpoFjvjwuJiDAR0I4KMrsvbVkwKZNm6wetxQeHq7z4TEXfvv27eYfkL19jPtxYQHvVbQ8n4iIiIg8SwPuN4dooI7A3jLgRmk9An2jBL/o48bFAfRSsvf6KK13NpBH5/miFwq4/Jy98TojUXHunVfsivSTGRIdX3rGldzMg+vM5+TkaCYcFdd9+vTRfmxhYWE2n4tebD179pRFixbJZ599plO9LSEgNxK9jkC5vpHBR183XEgoX768dO7cWYN6r2bmn3vuOZtXKDzJHUsGAMrr09LS7O5n3G85sKW9l619iIiIiMh7NOBulFgs4DYC/fHPDig2l97T0Hkey89ZblhuDsvOVagYZl5+ruhzqkZX9toxUnEZJ0teRYs83wDPlc0e9Eq75ZZbNPmKDDmmbiOJaw/m0sO0adNkx44d5vvRmw1TwxFnYhU2RzRu3FhXbdu3b598//335nnyR48elejoaPFqZv6xxx7TDV3g77jjDi1Xd2SugKvKumQA5iUY6/9ZLm9X0n62lhko7b0cWZoAcCyWV31xYSJYOuDjc6Gxg72r2sRxDxY83znuoYLnOsc90JT0t0jF8DCp37C63lo+jhL3lJ1HJK5apD5m728Zd/2dg/d5Zt5Q+WPVDmnbtUmxY3LnewXa7xl/+dz+chyeVJbxRpYbmwEJU7dxJTNfitmzZ2vDOcAqZiNGjLD5PMyfx+PQq1cvbYyHpHLbtm3l8ssv195tWDUN44ZO9ZZN1u2ZPHmy3HrrrfLQQw/JZZddpv3djCx9u3btxKvBPLLP6Cj/wQcf6NWI+++/X0sMENgjc15SuYIrvLFkgDclJSVZfT927FhdpiAY4BcBqh7ws0LZCHHcgxnPd457qOC5znEPNGnp6RJ2NN+hx3Jz8uW58V/J/pSTUjc5Xh559jrJyj5T4t8yaWkZUiHcfevMxySGS1r6KREbcVBufo4cPVogofZ7Ji0DPyMPRHNOSss8LRWOBvffs2X5/Y6gt2jDcH926tQp89dGUG8LViYzgnl4+eWXNZDHxQAE8cjmI8ifNGmSdO3a1eH3R/Ibq6ZhlTbLeBaB/Q033CBeDebr1KkjjzzyiG5btmzRoB5zDj799FP98Fi/HQF4p06dpCw8sWSAsY+xn62yBlvLDJT2Xo4uTYALIZbvGWyZeTSQQA8DBvMc92DH853jHip4rnPcA01BTgVJTPy3+Z2ltOP5+rhh/66TciDllDbGw+3BPRkSU62CFOZWFNP/mmJFRlc2r0Gfn1tREhPj3Hes2WGSmJhg+8FECcnfMyYdE+tl/3whP6NQV7EKZmX5/Y5qaawmZpmZL5q09OQ687b2swdBuqtLiGN5cmyuysvL0zn4f/zxR7EsPLral0WZG+ChWRzWV8e2YsUKvXrx6quv6taoUSO58847de14Z/9n8NSSAQikY2Ji9CoU9sPafkUZr2d5QuK9sM59Se9lax9bUIpRlnkR/g6/EPDLgME8xz0U8HznuIcKnusc90A8X23BWvDofG+oViPGqjFeu86NNVOOANvWa9h7bXcfa6gxxsJfxsRfjsNff78jOMVmcNtYOdkAL2PpaslYtkZMfjwlAlPFEUti3r67uWXUsYTbxx9/rOuvYxk4lNmj5T8CfVy1QVBvr5zB20sGGKUNxuNFr5yg2gDL0zVt2tShfey9FxERERH5J2cb4+FiAHlOTlaupG47pLcUqso5tUX16iq1nx0jtabcL/4M/eYmTpyoCWu/COYxtwIT9gcNGqTrrGNC/8GDBzWgR5b6m2++0S6BKSkp0qFDB50b7ghXlgwALBlQVElLBmAtecvHLeG4cXECcyEQ0BfdBxcrLJs9wJEjR7QqARUA3bp1c+hzEhEREZH7RcVEuKUDvi3RTr42OS43O08mDnxFZoyYJxMGzGJAH6pMZdj8GObcL1++XGrXrq0JaSxrbrl5tcweXfg++eQTDWJr1aol9913n5bTt2zZsthz8fiwYcP08dK4umQA1v/DkgEIuJs0aVLqkgE4nqeffloWLlyo74Hsv7E0wLhx4/TrohcfMJ8BgfrKlStl/PjxOp0A8vPztRsiMvqjRo3SMgoiIiIi8g1jfrvtxxiM+4OMU2d0PXnLJOE/v++RlK0HJT+/UFK2HpCNv2yVpGa1zM+Jiq3qtfXnc7JyJPXvfVKtTrxUigiO3lbkW3379vXI67oUzKPsHV33EKAjg22rBN4SOvehdb+/LBkQHx8v77zzjgwcOFA7C/bo0UMSEhJk6dKlOsceFwhwX1F4LSwjgPfCBQfMt1+3bp3s3r1buxk++uijpX5GIiIiIvK/QJ+8B0G5ZWCORmwF5XMluXltDeiTm9eR9pc0l0oR9pN6ngrkH7lsquzZkioNWiXJ88smM6D3Jlez7Cbxa0888YT/BPPIyBvrqjsiOTlZN39aMqB///5a6oCM/po1a/QCAIJzLLOHqQO2IOuPJnhYJ3Dx4sV6jGhmgPfBHIhg6UpPRERERJ7Hiwv/Cq9cUZ75dJT8sWKb1wL59JMZknEy0+o+ZOQRyOfnFujthiWbJKlFPeufW3ykRMfbX8GKXISu9C50sxdX9gkCLgXzrVu31gD6uuuus/k45p2j5BwZa2d4e8kAlM2jRN8Z9erVc6jKgIiIiIjInqhYVgpYQgCP0npvZeQRkBcNylFaj4y8kZnvcHkbZua9yGQ6t7myn79BNfj27ds1CY3eavaq2V1tjOdSMI+mdug4XxI8hiXliIiIiIiIAgXmyKO0Hhl5BvI+EERl9i+99JJ5eXSj35q7ubzOvL0rC5hHXnSeOp3TsWNH7c4/cuRI3YiIiIjIt+w1xstIO8ty+BAM6FFaz+Z3pZszZ45unlhDPdBt2rRJ+7NhKnaDBg10+neFCi6H3zY5/Gpo+obNCOQffPBBXS+vqLS0NG0ih6XqyPaFjujoaA4NERERUQDMXc9Iy2Iw74Fu9t7qTE+eZSQo09PTJSYmpuwvGERz5v/v//5PV0FDr7lLL71UDh06JImJib4J5vHGxtJzKLOvU6eObpYQ5ONgsa58SZ3oiYiIiIgodGFZOgbzZEs507nN4XPpp1WS8fMqMRUW+t2AogH8K6+8Ir1799ZV1rB0OubO29K9e3fPBvNY/x0b4MrC448/LpdddplLb0pERERERERUljnzUT266laYlS37HpzsV4P5/PPPy3333SfPPvusJr2xtLsteMzVaQouFe3/9NNPLr0ZEREREREFF5bNk9sEUZl93759dUNzeEyz3rZtm2/K7LEeu2X63/i+NK6WCxARERERUegF81GxnEtPwSUyMlKT4WiC55MGeD169ND0f1ZWloSHh5u/LwnmBJSlXICIiIiIyNdysvMkdddRSUiMlkqVK/r6cEKCv8ylj4qP9PUhhKYgWprO0iWXXCKeUMGZsnoE8pbfExEREREFayA//u55krLjiCQ3qSHPvTmEAX0IiY4/tz44eVmQBvOeUsGVKwmeurJARERERORtWEseS9ChujQtPV0KcirI3t3HNJDPzy/Q242rd0pSo8Ri69PbW9bu7NmzUqVKFfMtEZWCwbxT3Fq0v3v3bsnJyZHmzZu782WJiIiIiDwGATm2wsJCCTuaL4mJ8VKtRoxm5I3MfPsujZ3KzCOAX7dunU49xUWCjh07MqAnCqEGeH4bzGO9vFWrVsnHH39svm/IkCHy3nvv6dft2rWT7777zu3d+oIBfpGHhYXJyJEjdSMiIiIi/4PAHaX1yMg7EsgfOXJEjh49anUfvscFgvLly8uuXbuK7YO/lWvUqCGhJCcrV1K3HZKEmrFSKeLcFF4KXHPmzNGNvdIcs3PnTv1dgEbxERER5l5zXg3m33rrLV1r3vD999/Lu+++K/fee6+0bt1a16B/8skn9QdL1nCFFksTEBEREZF/QwCP0npHMvIIyi0Dc2TmT548ac7MN2rUKCgz8xqc/3NQEmqVHpzjuRMGzJKUrQckuXkdmb5gNAP6AGckKNPT0yUmJqbMr1fOdG5zVPrylZKxYqWYCgvFn504cUJuuukm+fHHH/V3wo4dO6Rhw4YydOhQiYuLk5kzZ3ovmE9NTbUqpf/000+11f5rr72m3x8+fFjef/99lw6IiIiIiCjQIXA3SuuDdc48gvPx1880B+fPLRxrFZxjybqM02fM3yMjj+fm5xfq7cZftkpSs1rnehVknJaCs+UkOi7Sbzrak//PmY++uJtuhVnZsnf84+KvHnroIV2Wbu/evVZxNAL8MWPGeDeYx/9wln744Qe5/vrrzd8nJydrQE9EREREFKqMAD5YAnkNzk9ZBOf/HDwXnOcVnAvOf/pbks6rbbUPAnMjOEdpPYJ+I/hvf0lzDf7P9SowSWJidZ2SQBRsfvjhB61mr1u3rtX9TZo00US5q1wK5ps2bSpffvml3HfffXpQBw8elCuvvNL8+P79+yU2NtblgyIiIiIiIv9iGZgDSuutgvNLW9gtm8djKK1HRt4I5IksYfa4M2X2Bn9vf3fmzBmbF/UwFadSpUreDeYffvhhufXWW7W+HweGUoE+ffqYH8dcgLZt27p8UEREREREgSJUl6BDMI7SemTkSwvkLfdBaT0DeQolF198sTaLf+qpp/R7zJtHRcqMGTOsetF5JZi/+eabJSEhQTvWIwM/YsQInQNgXF2Ij4+XO+64w+WDIiIiIiLyB1hL3p5QX4JOg/PzajM4J/cI0qXpZsyYIZdddpmsX79ecnNzZdy4cfLXX39p7Lxy5UrvrzN/+eWX61YUAvkvvvjC5QMiIiIiIvIXWH/e3vJzwCXoiHzTAM/MlX28qFWrVrJ9+3aZPXu2REVFSWZmpvTr109XAqhVq5b3g3kiIiIiolBSdPm5UFqCjsgrgjSYByzd99hjj4k7udzN/o033pC3335bdu/eLadOnSr2HPxCy8/Pd8cxEhERERH5pVBYgo7IW5xdZ97gyj7eNG/ePImMjJQbb7zR6v7PPvtMf28MGjTIe8E8avxffPFFbXJ3++23ayM8IiIiIvKetMwsiYm0P5+bvCPYlqAjIvd69tlnZe7cucXuT0xMlHvuuce7wfy7774r/fv3l08//dSlNw1luHIbFham8yOwEREREbki/Ux2mYP5NLxG1cr8ARCRS+bMmaNbQUGBT8rs01b+KukrV4mpsFD82d69e6VBgwbF7k9KStLHXOVSMJ+VlSW9evVy+U1DGbqdRkdH+/owiIiIKIBl5+bJ7oMnpHpcpFQOr+gXwTwvDJCjomL/XaueApuRoExPT9c54d4O5mO6XqRbYXa2pExy73x0d0IGfvPmzZKcnGx1/6ZNm3SVOFeVd2UntNVHUEpERERE3g/khz+/QB5/c5He4nvXXidfLwjg1l3BPIWmqLiqHn0+hd6ceVe20mzYsEGmT5+uXeTr1q2rPd6wlWTKlCnm59jaJkyYII665ZZbZNSoUfLTTz9pFQO2H3/8UUaPHq3Lvns1M//qq69Knz595JlnnpF77723TFcTiIiIiEJljjtK4x1tNpx2OlNyJbzYH5sIwHceOC75BQV6u/avVGlY27m/xXLy8mXSvO8l9egpSUqMk1n3Xy+JcVHiKuPCQGIsKgW4WFKoYXBOgbDO/FNPPSULFy50+qW7desmjRs3LnZ/hw4dHH4NvHdKSoomxStUOPc7srCwUO68806NqV3l0m/bZs2a6ZtPmjRJt8qVK+s8cEv4hyctLc3lAyOi4Jdx6gz/ACCikIH57Y7OccffWeGSK4mJsVK+vHUhZaXwilIvMVb2Hjmlt7UTY8VkJ7tky/7j6bL32GkpKCzU279Tj0p2nmtzXnFhYPK8xZJ65JQ0rJUgbz08kAE9EfmdLl26yPnnn689zLCh5D0nJ6fU/YYNGyaDBw8u03uHh4fLJ598okE9SusjIiKkdevWOme+LFwK5tH8zl5JAhGRIzJOM5gnInJWYlykvDPxZs3Id2qZ5NKceWTQG9SMl92HTkj9xFipU931ua4HjqXJ3qPnLgzsOXxS1vztfKWALZjLz+Z8RCHGg+vMjx8/XnytadOmurmLS8H8/Pnz3XYAREREROQcBPAImF1tfodSeGTQEXh3bpFUptJ4XBhoXKealvzjtqyvR0ShK1jXmS8oKNAYetmyZXL06FGtvrKE+fOu4G9aIvKJnKxcSd12SBJqxkqliHD+FIiInBRdxi70CLjPXRAo25+D2H/uQwPccmGAiEKcBzPzrkKg/ccff0h2drY2zrvyyiudmi8PaHSHYP7qq6+WVq1aua3K3eXftlgPD5P10ZEPVxfQTKB79+5y/PhxmTp1qgwZMkTatWvnloMkouAL5CcMmCUpWw9IcvM6Mn3BaAb0REROKusa8/oablqWzl0XBogoxLmYmRcPBvPvv/++1ffoGYdp5wjOIyMjHXqNjz/+WD799FO56qqr3HpsLv3G/fvvv+Xiiy/W8oBOnTrJzp07JT//3LIm1apVk19//VXOnDkjb7/9tlsPlogCr8Ed5sUXhYw8Avn8/EK93fjLVklqVsvmOrTskEtE5DnunJPO+e1E5C2F+fli+l/8qd/nuH9pTHSwf+GFFzQTj0Z1p06dkuXLl8u4cePk888/19L5L7/80uEGeLY64vskmMcHiI2NlTVr1miJQGJiotXjKB9Atz4qDp0T0fl/5MiRuhEFMwTitoJxlNYjI29k5ttf0pyZeSKiAMdgnij0zJkzRzcEtt4ssz/181I5+dMP4km333671fdVq1aVW2+9VS699FLtRP/VV19pPNy5c+dSX2vs2LEya9YsmT17tlsbybsUzOOKxOTJk6V69epy4sSJYo/Xr19fDhw44I7jCzrr1q2T6OhoXx8GkU9hjjxK65GRZyBPREREFJiMBGV6errExLi+KoazwXxc914S27WHVWY+5YWp4g21atXSKeXI2i9evNihYB6V65ievmjRImnZsqVUrGjdvPSLL77wXjCP8voqVaqU+PixY8ekUqVKLh0QEYVOQI/Seja/IyIiIiJnutmHhVUQwfY/BV7uZt+kSRO9PXTokEPPR1X7DTfc4PbjcCmYb9++vXz77bcyYsSIYo9h7jwm+DtyhcKWDRs2yJIlS+S3337Tzcjwm0y2f0JTpkyRJ5980u56gtOnT7f52MqVK+Xpp5/W8ojc3Fxp0aKF3H///XLnnXeW+Hr79+/Xpgfff/+9nDx5UqsQbrnlFnn00UelcmX3zTsjCgWYE09EREREFEhOnTplLr13xLx58zxyHC4F8whcr7nmGhk+fLjcfPPNet+RI0dk6dKl2uF+69atOh/AFU899ZR2xndWt27dbDYVKGnZADQtuOmmm7TKAF340bgP6/4NGjRINm/erGUTRaHRX5cuXbRjP5YUQBPA9evXa/d+7IuNFQlEjmNzO/+SfjJTouMj/e61iNwlLTPLLR3giYgodJlMJnPjOyS5fcmlYB4d/dCKH+vlvfHGG+YGAfhgmA/+3nvvaYDsCgTL559/vjaKw5acnCw5OTml7jds2DAZPHiwQ++BjPpdd92ljRoQ1Pfr1898QeKiiy6SmTNn6sWKHj3+nYcBeH0E8qNGjdIGBkYlwsCBA/UH+uyzz2qlABFRIMo45b4AHCsZMJgnf5N+JpvBPBGRP/OTdeaPHTumS8mhYjsqKsp8f2Zmpjz88MOydu1aqVmzpjmOtAWBPpK9cXFxumS7vcZ3GzdudOk4XV4M9I477tCD/+GHHzRjjQx3o0aNpE+fPlYf2Fkoi/e0t956S5s0XH/99VY/gBo1asiMGTP0PgT0lsE8Sv5Rlo/O/XiOoUKFCvLaa6/JN998I6+88oo8/vjjeh8RUSDJycqV1K37pVrtePYxoKCUnZsnuw+ekOpxkVI53LrxEBERBdaceVv7lQbTxFEFbsA0a7CcHo7p1FiZDcusY/r1hAkTNMGMpncI8BF0owE85sAvWLDAbh85xJpG1Xbfvn3FE8oUdWKOgCcm8nsafpAwYMCAYo/hh4e575gykJ2dbZ4Hb+xz7bXXFiulx0UAlNz/+OOP2qmwaEafiMjfA/nxVzwte7bskwat6slzix9jQE9BF8gPf36B7DxwXBrXqSavPTKAAT0Rkb/yUDO7Y8eOaUa9KMv78BxISEjQJDN6q23fvl1WrVqly4s3aNBAq7UfeughqVOnjt33e+KJJ2x+7fNgHpl4NKnbtWuXZGRkaCYe89Uvv/xyzc77AgLpP/74QwPwunXr6lSAkubLb9q0qcQ5DuHh4TofHnPh8YNDyX9p+xj34xgw357BPBH5C8xdR/m8PcjII5DPzyvQ2w3LNktS87olPj8qLtJuCf25LP8BqVY7jhcFyK3z3VEm7wpk5BHI5xcU6O3av1KlYe0El14r42yO1Kkew3J9IqIAK7MfPHiww9OyEd+W1ETdFfv27dMye8SpRtX3hx9+qA3Y77nnHu8E85gjcPfdd8tnn32mZfVFlS9fXhvizZ071+HOfu7y/vvvW32PEon+/fvr3P7IyH//6ER5fVpamn5tDGZRuB/BfGpqqjmY37t3b6n7APax5/Tp01Zjhyx/sDTNw+dC3wRb5wZx3INNoJzvkbFVdLMnvmasJLesJyl/7dPbdpe2KjUIL+lzI5CfcNV0SflrvyS3rCvTv5vg1oA+UMY9mPjLmEdVqaSbKxJiqkqjOgmy68AJve3YvL5UDnetOHH/0dN6HJ4eD38Z91DDcee4h5KynO/oaWbZ1wwxli+cWvernF63Ukx+/rvy1ltv1aAdU9UPHz4svXr10gTyBx98oN9PnjzZpdd1+F8y/KCvu+46+fnnn6V37956IDgABMoI8rds2aKN73CFAY3kkLn3BlQEoPM8MvFJSUm6TMDy5ctl3Lhx2twOTe6MboOAYzWUNMfBuBCBqoOi+zmzjy04Rktjx47VJgrBAL8IcKEE5wou7BDHPZgF2/k+9r1hsnXNTmneubGkZZwWsfGr7GxGlmRl2m9Iun/bYc3uF+QX6u3yr9dI3WY17e4TEVlJqkRFhOS4B4JgGfMn7+wuf+4+Iq0b1pD00yfFlT87c/Ly9TVMeTWkUkXP9scJlnEPNBx3jnsoKcv5jvgLPcZ8PWc+/oKLdCvIyZYdMyaKv0KsfOGFF+rXaKzXunVr7ceG/nP33Xef54N5BMQI5FFugEC5qDZt2shtt92mjz/22GPy1VdfeWyivyV00S8aVOPKx6WXXqqDhOPAXAdX1713N2Tu0fE/WDPzKB+pXr06//DguAe9YDzfy+dXkNr1a5T8hMTSX6Nh02T57rWfzZn57td2dntmPtjG3d8F05iXq1hF6ibGurRvdm6+jJi5wJzdf3Us5t17LqAPpnEPJBx3jnsoKcv5jkZyaPxtmZkvmrQM5G727paXl2eO+dCbDUlyOO+88+TQoUMuv67D/wp99NFHGrDbCuQtoePfxx9/rBl6bwTzJUHHwSFDhuhVo8WLF5uDecuS+7Nnz1oF1gZ0LwTLrvzGftjHFlv72ILOh7beM1jgFwJ+GfAPD457KAi28z06PqrMnyWiamWZsXiibFi2RTpcVnq5viuCbdwDQTCMOebcZ2blyoFj56bauTLvHoE85t3jdt3WvS7Pu4foqpVLnXcfDOMeiDjuHPdQ4ur5HhERoZvBXb+nPNnN3pdatmwpr7/+ujZbRwW70VX/4MGD2mzP48E82vAj8+4IXGlA/b+vNWnSRG8tr3YgkI6JidGSkv3792vTgaJwP1heXapfv778/vvv5scc2YeIKJC4a114BPBJzeuw+R35FQTOpQXP9mBJO3TCNzrid2qZxI74RETuFqSZ+eeee05XgXv++edl0KBBmiSH//73v+bye48G80ePHnU4UMXz8Hxfw/x5KNqMD4OHefW4QFE0mEcJBOY0YEm6pk2bWu2zcOFC3ccW436jYR4RERG5P7teloC8LLA2PZa0Qyd8BvJEROQMrHZ2/PhxnY4QFxdnvh9N8eytVV8ah+shUEZuWUphDwLhksrRvQWNHIzGd0WXk0N5AyxYsKDYft98840ub4cOg8Ya85b7fP3111adGwEN/1asWKE/mG7dunnk8xARBZKoOO+uaEKhwdWl6dwZ0KO0HrdlvShBRER2MvOubH4O69RbBvKQnJwsiYkONCUqQXln51T4k2PHjsmcOXOKdZBH5/nhw4fL2rVrpWbNmtKvXz+rx4cNG6bl9si0f/HFF+b7UU1g9ARAl3lLKH9AoI7njB8/3nx/fn6+jBgxQjP6o0aNkooVy/YPPBFRMHBXyT6RITs3T3YfOKG3voS57oF+UYKIyF8Zc+Zd2UKRU21Yhw4dKvfee2+pz0OA66pvv/3W3BAAcnNz9dayGz3WkEemHNUC999/vzbd69ixoza9Q4CPkvcTJ05oszlk34uWLsTHx8s777wjAwcOlAEDBmjZAxoPoLMg1oEfM2aM3lfUvHnzpEuXLjJr1iz58ccftUR/3bp1snv3bunatas8+uijLn9uIiIisg0B/MjpC2TXvuPSqF41mTMBneR9c/G8rGX+elHi4Amdg++rz0BE5LeCdM68z4N5TNT3BgTjyKgXZXkfngMIwJElx9Jz27dvl1WrVmn5QoMGDWTw4MHy0EMPSZ06dWy+T//+/XXe/LRp03R/XDRAcI6LAyV9VjTUQxM8rAOIDvko40djPFxcmDhxYtAsMUdERORuKC13NSONjDwCee0kv++4rN2SKg3rJHisi7ynIJAf/vwCcxM9zMFnQE9EZIHBvGeCeWSlvQFBODZHYBk4rGvvKpTNL1q0yKl96tWr57WxICIiChZl6SaPLDYy8kZmvlMr73eSL8vFCAMy8gjkcVECt2imV9Lyduj9k3Y6U3IlvMRpjr68MEFE5A9ObvxVTv6+UkyFhRJoUBGOSnKvldlT2WE6AKoHRo4cqRsRERHZh8AdpfXIyPsikHfH0nbOLm9XWFgo4ZIriYmxXGeeiPwW+pdhKygocMvrOTv/PaHdRboV5GTLP69MFH9emg7N7m666Sb9HtO9P//8c+3v9t1335mXqnMWg3kvwxx7NN8jIiIqi/SMLImOCp2srHaSr1P2TvK+xOXtiCjYGAlKLLkWExNT9hcM0jL7119/XT744AP9esmSJbqhQvzTTz+VRx55RH744QeXXpfBPBERUQBKz8wOqWDeXZ3kfc1dy9sREQUjVzvTl/PzYP7w4cM6XdtYCh2Z+d69e2u2vlOnTt5Zmo6IiIh8LycnT/bsO663oSRY5ocHw0UJIiKPCNJ15uPi4mTfvn36NRqp9+rVy9wfpSxTFJiZJyIiCiAI4Ec/8ansTj0uDZOqyawnB0qlSszyBpJguShBRESO6devn9x66626OhqWUL/yyiv1fqyU1rhxY3EVg3kiIiIfzntHubwzkJFHIJ+fX6C3v21KkQb1qjn1GtGRlUOuRJ+IiAJAkM6Zf+mll7SkHtn5GTNmSGRkpN5/6NAhGTFihHeD+blz58q9995b4uNZWVk6kX/27NkuHxgREVGwQ0DtbFBdPT5SM/JGZv7CNsnMzBMRUVDAQpzlXNzPn+Xm5srDDz9c7P6HHnqoTK/r0pz54cOHyxVXXCEHDhwo9tiKFSukdevW8uabb5bpwIiIiKg4lNSjtH7SQ1exxJ6IiIJLkM6Zr1Gjhtx1113y66+/uvV1XQrm//Of/8j69eulVatW8u677+p92dnZ8uCDD8qll14qERERsnr1arceKBEREf0b0KO0nnPliYgoGLvZu7L5M8TPJ0+elJ49e0rTpk1l+vTpcvDgQd8E85i8/+eff0q3bt30CsNVV12lC93PmTNHxo0bJxs3bpT27duX+eCIiIio5HnvREREoez4pl9l2/vPyY5PXhJ/1rdvX/nqq6+0sv2+++6TDz/8UJKSkuSaa66RL774QvLz8727NF2tWrX0jTt27Kjt9Xfu3KmT+Z955hmpWJFddYmIiDyJDeyIiCjoOFlaX+38i6TZ7eOlycCyzT33lurVq8uYMWNk8+bN8uKLL8rSpUtlwIABUrt2bZk8ebKcPXvWO8H8H3/8IRdccIFs2LBBRo4cKS1atNCsPDZM8CfbcPEDY4UqBiIiIiIiokCFmAaxDWIctwmy+fKWjhw5oglwjNmECRM0kF+2bJnMnDlTE+XI4Hu8m/2UKVPk2Wef1dKAX375Rbp27aoBPK4m4EC+++47nUvfoUMHV14+qK1bt06io6N9fRhEASHj1BmJiqvq68MgIiIiIhuQ1MWWnp4uMTExZR4jV+e/l/PzgB6B+rx58+T777/XQB7L0d1+++0SGxtrfg5i6ubNm3s+M//UU0/JPffcI5s2bdI3hfDwcJ3Ijw59qPnv0qWLKy9NRGSWcfoMR4OIiIgoVARpN/shQ4ZoKf3KlSu1wv3++++3CuQBjz/22GOez8yjth9d623p1KmTBvkTJ0505aWJKMi4ml3PycqV1G2HJKFmrFSKCPfIsRERERERedqhQ4ekSpUqdp+DFeGeeOIJzwfzJQXyhkqVKmm5PRERsuvOBvMI5CcMmCUpWw9IcvM6Mn3BaAb0REREREEuWMvsq1gE8ljSvWiPOVenYbsUzO/du9eh59WvX9+VlyeiIFFadh1Ze1ul9NgHgXx+fqHebvxlqyQ1q1XseVGxVTmnnoiIiChYuFoybxK/dubMGRk/frx8+umncuLEiWKPFxQUeC+YT05OlnLlypX6PFcPiogCnyPZdWTsbWXtEfxjH2Pf9pc0Z2aeglZ6RhaXmSMiIgrizPy4cePkp59+ktdee03uuOMOXQUAa87PnTtX+865yqVg/p133ikWzCNwT0lJkffee08SExO1qyERBT9PZNcR9CP4xz4M5CnYA+z0zGwG80RERC5k5o9t+VWO/7VSTKZCvx6/r7/+WuPkHj16aDO8iy++WBo3bqyrw33wwQdy2223eS+YHzx4cImPoXwATfDS0tJcOiAiCiyeyq7juQj+2fyOfCE9wzsBdk5OnuzZd1yqx0dKpUoVPf5+REREwaR6q4t0K8jNls3z/LcB+8mTJ6Vhw4bm+fH4Hi666CIZPny4y6/r0tJ09lStWlWvNrz00kvufmkiCiBGdn3cq0PYwI4CCgLslL3H9dbT7zP6iU/lqZe+01tPvx8REZHfC9Kl6Ro2bCh79uzRr8877zydO29k7IsuUefxzHxpCgsL5fDhw5546YDXsWNHCQsL02kInIpAwa6s2XWU4BN5EwLqBx//VHanHpOGSdXl5WkDHcqYoywf5fLOQEZ+d+pxyc8v0NvfNqVIg3rVnHqN6MjKLNEnIiKfwdxvbO7qlebJOfMbNmyQJUuWyG+//aYb5qyDyWR/5/nz58urr74qf//9t4SHh0vnzp3l8ccfl65duzp8fEh2Y/n2Sy65RCZMmCDXXnutzJ49W/Ly8uTFF18Uvwjm09PTZfny5fL8889Lu3bt3PnSQWPdunUuLz1A5Ks1330lkI6V/JMG2RmOB9nIyCOQPxdgH5N1v6dIcn3HA+zoKMeDa5TWN0yqpoE8bi9sk8xSeyIiCihGghJxYExMjF93s3/qqadk4cKFTr3sgw8+KLNmzdI14Hv37q3LyuGCwA8//CALFiyQvn37OvQ6Dz30kPnrXr16yT///KMXFzBv/vzzzxevBvPly5cvsZs9rmxgSTpcvSAi/5Jx+qzXA2Rm18mXEFg7M/e9egIC7OrmzHzHdp4LsPG6s54cqBl5BvJERETIsJt0c1Y5B/bp0qWLBs6olMaGFdpycnJKfP7SpUs1kE9ISJDVq1dLkyZN9H58bTSyw60rZfJofIetrFwK5idPnlwsmMf3cXFx0qhRI71qUaGCRyr4iagsa75vPywJNWOcLntHt3pXg3Jm1ymQIMBGaT0y8p4M5C3fD6X1bH5HRETkWePHj3fq+Ub5O0rqjUDeuChw3333ySuvvCJvv/22jB07ttQp6CjV/+KLL3T1N8TNDRo0kAEDBugydY4s+V4SlyLuKVOmuPyGROSjNd9vniMp/xyU5PNqy/SPRzoV0GtGn/PXKUQgsEZpvbcCbMx7JyIiIs+W2TsjKytLfvzxR/0aQXdRuA/BPBrY2QvmUbV+3XXXyXfffSdt2rSR1q1b631bt27VFeIQ4H/11VfiKqbPibzkXEBcxQtrvp8tdj8y8gjk8/MK9Hbj8m2S1LSm1XNwbLay6DnZuZK6438Z/cquNbIjCjSY++699/LOevZERET+zpMN8Jyxbds2LcGvXr261K1bt9jj7du319vNmzfbfR1k5NFTbtmyZXLppZdaPYaLBZhzj/Xn77zzTvFYMH/XXXc5/cIoF0DZARGdk5Hm+WC+5DXfYzQjb2Tm23dv5lBmHoH8hFtfk5RthyS5WS2Z/uFwBvRBdPGH3Btgo9keA3MiIiLPZ+YLC/LFVJBv/r4gz7kVZUqzd+9evbUVyBvLsWOu/KlTpyQjI0OioqJsPu+jjz6SiRMnFgvkoWfPntrZ/oMPPvBsMI+rBs7W8pel9p/IbkAcwwDHpTXfPx6pGXlbgTzmxNvM6O84rIG8ZvS3HZKNK7ZJUhMbGX2W4Lsdg/nAg675DOaJiIg8n5k/vHmZHNz0g8eGOjMzU2+rVCk57kBAf/r0abvBPDL3M2bMKPE1rrzySi3Xd5VDwTwm6hP5g4y0rIAM5nOy8yR15xFJqIFSde/Mw7W55nvTmjYz8gjGbQXkmtFvVsucmW9/cTNm5r11vuw48r+pDb45X8j59emxrB264bOZHRERkWfVan2Z1GxxiVVmftOCp/xu2E+ePCk1atQo8XE8huy+qzhnnsgLgdmEQW9KyvbDkty0pkx/9+6ACdAwRx6l9cjI2wvkA239er8/X+54XVK2HZbkZjVl+vv3Bcz54q88Xf6OQP7Bxz81L2eHbvgM6ImIiDxXZl++fAURbJb7uVFkZKTenj1bvHLVcObMGb0tKSsPBQUFdld5CwsLk/z8f6cLeCyYR63/zTffXKZF7Ul0TUP80EaOHKkbOU6zlbuOSkJitF8HN4dST4jJ4jcKMvII5LVUffth2bhyuyQ1/vcKHSoNvDU32pX3QQCP0np7ze8YzDtfQm9rWgMgI49A/tzUhsOyccV2SWpS8hVdMZmkdoPqTh5BaHG2/B3BP/ZxFDLyCOTz8wv0FsvaoRu+sw33WKJPRESBZs6cObohaA2mBnj169fX2/3795cYyKPEHkuz2wvm0bkeXesrVapk83F769y7NZifPn26tGrVyhzMnzhxQhITE2XJkiU6eZ8cs27dOomOjuZwuRDIjx/6tqTsOCLJTWrIc28P9duAHoF87aR//5BHaT0y8kZmvn23pj47dlez5/YuAuj69f8clIRasU6vX+9vTIWnpVz5WI+/z7k+A7bH9NzUhprmzHz7i+2fLwd2HZZQczYrx6Pl7wiqnQms8drIyBuZeW+sT19WaZlZEhPJLvpERFQ2RoIyPT1dYmJigmZpumbNmmkAfuzYMTlw4IDUqVPH6vGNGzfqbWmJ7kGDBpX6Xq42vytzmT2uNBB5stkd5sgDMvII5JH5wu3G1TslqVGiPhYVE+HRefTpaVkSHRPh8tx43KK0Hhl5XwbyZYH59Lay7wjkx18/U1K2HpDk5nXkuYVjAzugL0wT8UIwb4+eL+/fpxn50gJ5vZCydb9Uqx0f2OPupLNZeX5V/o7XxGsjIx8IgXx2bp78sf2AdGqVJJXD/ftYiYgo9Lg7y+6KiIgITVgvWrRIPvvsM3nwwQetHl+wYIHeXnvttXZfZ968eeJJfjdnfsOGDZrt/+2333TDlRBHLhxgDb9XX31V/v77bwkPD5fOnTvL448/Ll27di1xn5UrV8rTTz8ta9askdzcXGnRooXcf//9dq+OoNRi0qRJ8v3332tDA5Rg3HLLLfLoo49K5creW5c4FGj5+f+CdJTWIyNvZObbd2nstaA4I92xYN7e3HjcorQ+EAN5QCC/c/NeqVEvwep+ZOQRyGtJ+NYDsvGnvyXpvNoOLZfnb0ymbDl7+k+pklBDypXz7P/L6SczJDq+5JIsPV+a2D9f9ELKFU/Lni37pEGrevLc4seCPqBH+fux4xny1z+HJCIiutSguazl786UvuNY8NqBEMiPnL5Adu07Lo3qVZM5EwYwoCciIrJhzJgxGsxPmzZNrr76amnSpInev3r1apk7d64uTTd06FDxJb8L5p966ilZuHChU/vgSsmsWbP0Ckrv3r0lOztbLwj88MMPetWkb9++xfb5/PPP5aabbpLCwkLp3r27VKtWTZYtW6alEFhC4IUXXii2z86dO6VLly5y/PhxnXJw8cUXy/r162Xq1Km6L7aS5kNQ2SCoQWk9MvJFA3lPLlenmfbdx6Ra9ahigZXOe0476/Dc+HLineUaPTF/PbxyRck+k1OslB7fIyNvZObbX9oiIANKBPKmk3dKpbxtYjr5nkj8eyUG9KUF4o7IOJlZ+muYTHZL6JGRRyCP8w23G5ZtlqTmttdChai4SImOP9fMJVBVCq8gz7/6g+xOOSY/rU6VWdNushs8e7v8HcG/N8vk0884v6bu7gMnNJDPLyjQ27VbUqVhHeuLdEXhYnra6UzJlXBddja6amWW6BMRkWcggetK9bep9H2+/fZbjTUNSOYCksAGJG0RuEOvXr1k9OjRGme2bdtWLr/8ct0HcSb+bUTWHQF9wATzWKLOmB+Qlpamtzt27CjxQ7Rv397pA0KwjLkHaBSHLTk52W5jgKVLl+oAJyQk6FUSyysmPXr0kCFDhuit5TEio37XXXdpowYE9f369dP7jxw5IhdddJHMnDlTrrnmGt3PEpoXIJAfNWqUvieg++DAgQPlyy+/lGeffVamTJni9Gcmx2i2slFi8aDaQ8vV6Tz9Ee/Jnp1HpEHjGvLcq3davbepXDm3zI23t564K2uN6z5OBvNYZ76kteLtldLjFt8jI+/vgTzmw2sZva3H8neKKW+7mArz9FZyVopUaGzzuZknsyU6vpnLx5GTlSOpf++TanVQGl/yxb/SmtqhtB4ZeSMz3+Gy8/16/N3VaG5PKgLRQr11JNP+yMjesnnrful2YWOPZ8292cAO891dmfNePS5SM/JGZt6RUntc9A6XXElMjJXy5cuX4aiJiIh81wDv2LFjsnbt2mL3W96H51h6+eWXNZCfPXu2BvGoAEeQj6DfXgW4t5QzOTjxHf+A44q8Jexa9D7L+93R1RCl6wjmSzrMq666SssfXnrppWJzGXAl5ZVXXtEs+9ixY833z5gxQ8aPHy/XX3+9fPXVV1b7IChHcI9g/uuvvzbfj5L/Tp06adO/vXv3WmXgcRGgXr16uoTB0aNHbS4/YDSFwEWQYG2Ahz/48PkxRp76g+/g3hNSu36CVcBtK1vv6tx4lNQbkJF/btLnkp9fKBUqlJfxT/WXpIb/BliZGdnSrIV1Sbkej5Nz4w+mHre6KODoY7bGPS8nXzYu3ybtuzdzKrA7mHJML4ggq18USumfu/ctzQBXqBgm4+cOK1ZKn5l2Vpq2S5ZAlXM2Tfb/1kdq1DktRw7ESt0Lv5dKVWJsBuIblmySDpe3kYqVKjp9vmP/Ry6bKnu2pEqDVkny/LLJdgP60l8vVzPygRjIuwJz4Ec//olm5hsmVy81M2/Yf/CU1K0d55VjDAQotUdG3tE589743U4cd3/B853jHkrceb6XNdYx9r+g/zSpUNH5Srf8vGxZ//njQR1rlSkz7+nJ+67IysqSH3/8Ub8eMGBAscdxH4J5BOWWwTxKLEraB2UVuICAjD/K9Y158MY+aHJQtJS+Ro0aWnKPY/n111+LZfRDAUo+o6p4bopB2plsialaWZvdearDPebFW86NR2k9MvJGZr5Dp4bm1zfK73Fr+Z7Ozo231TDPVTnZuTLxltck5Z+DknxebZn+8UiHAjzsl7r9sF4AqB13rqmgJUdK6W1dBPA3KI9HebstyJTPHNpQatXPlEN7I2Xs29skqUU9q+fkZufKc3fOlgM7DkmD1kny3JJJLr0PAvn8XJTGp+qFgaLvYykqPtL+3PqIcC2tD4VAHhC4vzT1Rvn51z+lx0WtnehOz34mlhDAt21ah3PliYjI75QrPLc56vCOlXJ410oxmZzYKRSDeUfa6nvbtm3bNGtfvXp1qVu3boll/pgDb2nTpk1Wj1tC6QTmw2Mu/Pbt283LDdjbx7gfwTzeKxSDeczd9EYwb2TnvdHhXufpv3qnbFi7u1ggb6/83lH2GuaVFugfSjlmnhqk81kz0mTPH0c1kNc5+/8c1Ax9UtOaxZdEsyjBRyA/4eZXLS4AjCi2nrwjpfS+anDnTH8ABMUlBcYoea/TpIHs+XOP1GlSR2o1LL6u+6HdR+TAzkP/m6OeKhuXbpbY+pGSn1FYrEKppCAc74OMvJGZR4a/LJl5fa+4wJ4H7ywE8PXqxDpVMs/124vjsnRERBQMajbpphsy8+u+fFxCjd81wHMGyt3BViAPVatW1bnyp06dkoyMDImKitISDmO+f0n74X4E86mpqeZgvrT3Mu7HPvacPn1aS1oMyPIHQ9M8BJT4XMatO2Xn5suug8elWnQVqRpVWTeIqxZp1eG+rUXADY4eh70GehXDwyS+WqQcO5puvg8ZeQTyKL/H7fo1u6zK78uV8N54n8z/LbUHe4s2zPt1m9T/X8O83Jw8eWH8Z3Ig5bg0aFpTnpk/rMhnM0mt5HPl93iv8scKJKlRrCSfV0tS/jmkt20vbmIVmGeknZH00+c28zFsP2x9AeCXf6R+kQsAEBkbIfWb1ZKKlSq4/edbFumnMqWqg8sG2oOSeWTaf1+6Str16mrzgkV8rThp0Kq+7Plzr9627dlK0jPT9GKirdI0W+NkvA8uBLTvdb5+X9bxjIyt4lc/E0/DZ42o7F/nYbDz1O924rj7I57vHPdQUpbzHQlVy75miLHcwk/WmQ8UAR3MZ2aeK2WtUqXkDCwCegTQRjBv7GNvP+wD2MfR97K1jy1JSUlW36P8/+GHH5ZAlpOXL3/uPiIFOdUl++wZ/aXgrnmVeO1H5/8oKUfTJDkxRp4d3FMqVfz3tB3zzDXyz+Z9ct759SQt/ZSInd8jWWdyJKJq8QsnJ4+lS3xOyXNrwivnS4Xwf9e1rtcgUurUj5P9qSf1Ft9bPg6Yf2RLmEW1b50msVInOV727z4uNerGSJWY8uc+A+b47jmhgXxBfoHs2X5YVizZKHUbnOsVgHnxuBDQpnxj7TKPX8C4QIVxf2jWjfLPxlQ5r32SpKWfLjYeYUXi3jrN4qROw2qyf9cxvcX3YZWL/0LPyjkjuabsEj+XL+Rm58k/v++RgvK5Og7uEFO/pqRlnBYp4X/jhz+4T7au2SHNOzfR5xnj7uz5XqtFdbvvE2rOZuVIFQcrFHC+5+Zk6bnI+dveYfk7hmPuPRx33+C4c9xDSVnOd/QkQ9PwQGqAF4wCOpgPRMjcWzZlCPTMPLLmI2YukF0HTkijOgky5Y6Ly9REA+X06WfPXeU7k5ElRzKzJfVYuhQUFurt7hPZ0rDWuaA2ukolSUysLGFSWWrViy/1tQ/tOymJicWfV5BTweb99sx84y7Z+NseaX9hgzLNdX/+g+Hyx6od0rZrE6vXadA4SRZ9sNFcdXDx5e318XPz4l81Z9+f+WiEVAyvoGXeRoY4rLCS1HJiLe3nF4ySP1Zsl7YXo2mfnbnXxafT+wwav00c+oqkbD0oyc1ryzOfjnLLvPHKFSMkOs7+knHl8ytI7aSa+g+g5bg7xY/G0h8cOHRaO6U7okzjTi7hmPsGx53jHkp4vgfeuGOJt8cff9wqM180aelvS9MFo4AO5tE9Hs6e/Xet76LOnDlXUoysvOU+xn62uh0W3ceR97K1jy0o+w+GDovGGse7D57QQF7XLD5wQrbsOSrlw6u6vBZxXFQV3eBgTqE0bJEojetUk50HjuttlxbJUjnc+rSNjq1S6i8gzD/fi/Xii8w/L+n+0tauj6hSSZIbJeptWWD/pCY1i70Ovn981m2y5qet0rJ9kpw6ci7FjkZ1COTPlcUfkj9W7JD6TWpIWka6FGaF6biXL1/OqV/IEVUqS1KzWnrrTzAfHkvm2ZK67ZAG8pjqgNs/VmzTz1AUlttzZj5/bELxDvZFRSdEmcf33HiXZ1BZxg71qftOSGK1KIfnwXPcvY9j7hscd457KOH5HljjHhERoZvBXRfYmZkPoWC+fv36ert///4SA2yU2MfFxZmDbATSxrIJ2K9FixbF9jNez/LqEt7r999/L/G9bO0TzIw1jrFmsRFsIzPfumENqVvGtYgtm90hcJ/70ABZ83eqdG6BZZSKn7KlNbrThnV3z/u36/2bQ/6X5bZ9v6Nr10dFu2dN6ZLeB13k23VrYr2Wfc0YbVRnNKxDB3rMYw87WiiJidVcHndn17L3BgThJQXiCTWLdNi/pLlLmXlnGugZ7HWXJ+cD+Qcf+1T2pB6TBknV5eWnB3p8LXgiIiKiYBHQwXyzZs20RP3YsWNy4MABqVOnjtXjGzdu1FujiZ2hTZs2snz5cn28aDCfl5cnW7Zs0SXpmjZtarXPwoULza9ZVEnvFQpLHL32yABZ+1eqdGxeX9JPnyzzayKYrxwWpt3qExKjpXLlitKwdoLNQL4kyKwjIC/a9R7zz5f+93ddqx5d8fF9QYF1N/zcnHzZtf2Qvre9EnrLZezKwl4gXTTQR8CKJecs15J3R1MqZLADiY7DgtGy8ZetLgfygMy/rzrxB6v0jCxJz8h26Lkpe49rIK//b6Yek3W/p0hyKVNEdPWGtEypHBElsTH82REREQUVNsALnWAepR09e/aURYsWyWeffSYPPvig1eMLFiwwrw1fdC15BPN4/Pbbb7d67JtvvtH15a+55hrzGvPGPlOnTtU169G50XKe+5EjR2TFihVaAdCtWzcJNQjojWDbHX0s0cm96PrxzkIQbATCCMotu973uq6dBukt2taXJV//Yb6/fZfG+nwjW//1x79ZZet9wVagr2uLN60ZMmuLl0THoVktl8cB8+5Rro8sf6iPpTthGThHl4KrnhCpGXkjM9+xXXKpmXlcvKoYlsvl5oiIiIIQy+xDKJiHMWPGaDA/bdo0DbibNGmi969evVrmzp2rc9SHDrUOBocNGyZPP/20Ztq/+OIL6devn96P7sjjxo0zd5m3dOGFF2qgvnLlShk/fry8/PLLen9+fr6MGDFCM/qjRo2SihVDs0QU8+PLwsiko3v9sl//lt07j0ihxfrx8bVj5GB2gUvrx+t68W8O0ddBwG4E57h9fOZNsvbnbdKyXZKcOJpud+16d61f7w7+WBbvC6VVFJRURo9AfsKNr5jL9Kd/5p4GeuQcBO4orUdG3pFAnoiIiIKckw3wDu5eJYf2rBKTKTSXT/W7YP7bb7/V7oiG3Nxcve3cubP5vkmTJmngDr169ZLRo0fLrFmzpG3btnL55ZfrPkuWLNFyzHnz5mlAbyk+Pl7eeecdGThwoAwYMEB69OghCQkJsnTpUp1jjwsEuK8ovFaXLl30vX788Uct0V+3bp3s3r1bunbtKo8++qiEKsyfd6Xc25gfjwC5YkS43PvSAtm5/7hUaB0jMX+mSXLjcxnzsmbHsT+C8qKvUy0xRtp1bqRl97ay+O54b09gaXjp43Di0GlZs+RPaXlhQwkvEiSea6B34H8N9A5oub6tBnquNNEj5yCAR2k9A3kiIiJyNjNfp0FX3fLzsmX1oskhN4B+F8xj/vvatWuL3W95H55jCVlyBPKzZ8/WID48PFyDfAT9CLJt6d+/v5baI6O/Zs0avQCA4Pz++++XQYMG2dwHWX80wZs8ebIsXrxYvvzyS22Mh/eZOHFiQC8x5yv7j6VpQA/ojI9GevmFBSIRFeTqEd3lsp6t5Ej6GYkpqGxuiudJJWXxKbAg8z7t7rdKzLy7q4FeSdJPZrBRHhERERGFVjA/ePBg3byxH8rmUaLvjHr16mmGntyzRv2x05nS6H/z7RNj/+2Mj9veF7WQBvWqu22oUSLvyP0lZfFJAmzpOvuZ99Ev3CK7txyQble3dXuJfcbJTAbzToiO8q9lEYmIiMhH2AAvsIN5Cp1AXkvq/xe4Y/m5osvQ5WWdm2LhClvrxJc0190f5sCTb5auS6jh/uZ3OVk5kvr3PqlWJ14qRbBaxxGONswjIiKi4MYGeM5hMO9lHTt2lLCwMBk5cqRuoQTl9MVK6gsK9BYBPDriAzL0COydWYquKEfWiXcli08BtHTdZ6NKXbrO3XPhEcg/ctlU2bMlVRq0SpLnl01mQE9ERERBa86cObphqWe3KDSd21zZLwQxmPcyNMyLjo6WUIQ578a896Il9cjEG8H73qOny/Q+Odl55jXqXS2VZ7Y+8JV16bqS5sKjhN683nnmacnPKJRy5crpfcjII5DPzy3Q2w1LNklSi3o2XysqPpKl+ERERBTQjARlenq6xMTElP0FWWbvFAbz5BNFS+ots/BlaXSHQN5YJ17XqPfxOvHk30vXOSs6PsocgGP1hgpHy0tiYqKUL19e70NpPTLyRma+w+VtmJknIiIiIo9gME8+gwAepfVFy+mdDeaNNerB3jrx/rJGPHmPt5eUwxx5lNYjI89AnoiIiMg5qHV0Zmk6w7kaydDDYJ58yh3LzSFAN4L0QFknnoIXAnqU1rP5HREREZGTTKZzmyv7hSAG8yEqLTNLYiJ93+TN3WvHc5148geYD09EREREnu1mf2Dvajmwb7WYTIUhOdQM5kNU+plsvwjmPYHrxJOvGfPqiYiIiMhzDfDq1OuiW35+tvz605SQG+pzXZsopGTn5snuAyf01tPZf1/h0nJERERERBTMmJkPMQjgR05fILv2HZdG9arJnAkDpHJ4xaDL/rPRHRERERFRYClnMunmyn6hiMF8iECWHME1MvII5PMLCvR27ZZUaVgnQaKxBrwbA2/N/h88IdXjIj12sYCIiIiIiIIIpr67Mv29UEISg3kv69ixo4SFhcnIkSN18xYE6tgQXCMjb2TmO7VKcnuwnZ2bLyNnfi47DxyXxnWqyWuPeC77T0REREREvjFnzhzdCgoK3PJ6zMw7h8G8l61bt06io6O9/baSnpEl0VERGlSjtB4Z+bIE8kW74eN73U5nyj8HMzSQR/Yft2v/StX15DPO5kid6jFB23iPiIiIiCiUGAnK9PR0iYmJ8XoDPLPQrLJnA7xQkZ6Zbf4aATxK68uSLUfJviUE6HUTY6V6bKRc2CJJM/IVwsL0tlPLJKlXI06iqlRiIE9EFOB82dyUiIiI/sXMfAjIycmTPfuOS/X4SKlUqaLH58NXDq+gpfXIyCOQx3M4h56IKPDhd/kf2w94ZIoWERGRoJGdK83sTKGZmmcwHwKB/OgnPpXdqcelYVI1mfXkQA3o0fDOXtm8vT/khj+/oNT58Jr9r30u++/oPkRE5L/QD+WBGZ97ZTUUIiIKTeVM5zZX9gtFDOaDFObIo7QeGXkE8vn5BXr726YUaVCvmkRHVnZ4GTkE+geOpWmZPDLytubDQ2REuNU+mCO/78gpu/u4u4s+ERGVvrKJM0wmk/ZD2XYgw+ZqKM7i730iIrLzj45TWfZ9B9fI/oNrxWQKzXb2DOaDFJrdYUNpPTLyRmb+wjbJxUrttQT+QMll8wi28ccf5r3jOciuG1l2o4weCgsL5ejZDPM+RpBubx8iIvIey9/NjsLv9nDJlUbJ8R5fDYWIiEJbucJzm6Pq1+ysW35+tvy8dpqEGgbzQcroXo/AHaX1yMiXFMiPnL7Abtlk0WC/6Hz40riyDxER+Rf0Q3HHaihERES+0KNHD/nll19KfHzRokVyxRVXSCBhMB+kUGKPYB4QwKO03gjkLcssEaTbKps0yiBLCvaN+fCOcmUfIiLyL/gd3rZpHf4uJyKigG2A179/f4mMjCx2f506dSTQMJgPke71lnPki5bAFy2bzMnN12AfW0nBviuKNt0jIqLAwz4nRETkMV5YZ/6FF16Q5ORkCQYM5r2sY8eOEhYWJiNHjtTNa93r/5elt5VlKVo2ic1esO9qdp1/ABIRERERBY85c+boVlBQ4JbXK2cy6ebKfqGIwbyXrVu3TqKjo33Svd5eQI9se0lLzHGOJBERERERFWUkKNPT0yUmJqbsA8R15p3CYD4Eu9c7WwJvL9gnIiIiIiIKFG+//bacOHFCypcvL02bNpW+fftK/fr1JRAxmA8ypXWvd7UEnvPdiYiIiIjIo1At78DSdIWF+VJoyjd/n1+Q4/BbTJtmvYTdww8/LJMmTdIt0DCYD0JFu9e7A+e7ExFRWZw9e1aqVKliviUiInJ1zvyeg8tl96GSl5mzpXv37jJs2DDp2rWr1KpVS/bt2ycLFizQ4H7y5Mk6FXr06NEB9UNhMB+kLLvXExER+RICePSMKVeunJhMJm0Gy4CeiIhsd7MvPZhvWPMiSa7RxSozv/zPl+zuM3XqVKvvUWI/ceJEueCCC6RPnz4yZcoUueeeeyQiwn7Fsj9hMB+kSmp2R0RE5IojR47I8ePHXR68o0ePSmFhoc5R3LVrl8uvk5iYKDVq1HB5fyIi8mMONsArXy5MN6v9XNS7d28N6NevXy9r166VHj16SKBgMO/n0KWegTkREfkaAmiUJbqamT958qQ5M9+oUSNm5omIyG80adJEg/lDhw5JIGEw7+fSM7IdDuYZ+BMRkT9CSb1RWs8580REVCI0vyvnwvgUlm1MT506pbdVq1aVQFLe1wdAJcvJyZOUvcf11tHAn4iIyB8Zc+Q5V56IiEprgOfK5qpjx47JihUr9Ov27dtLIGFm3k8hgH/w8U9ld+oxaZhUXV6eNtBud3oj8K+eEOnWLvZERERERET+NGfe5n52rFq1Snu3XHvttRIW9u9c+5SUFLn99tvlzJkzct1110ndunUlkDCY9zKUGeIEGjlypG4llctv/mu/BvL5+QV6u+73FEmuX02ioyoXK7t3NvB3RFpmFpejIyIiIiKiEs2ZM0e3goICvw7mt2/fLkOGDJGaNWtq9j02NlZSU1Nlw4YNkp2dLS1btpQ333xTAg2DeS/D0jxYw9AeBOsd2yVrYG4E6Pi+aICOoB+l9cjIOxr4Oyr9TDaDeSIiIiIiKpGRoExPT5eYmBi/HalOnTrJ8OHDtVs94jHMkcf8+LZt28qNN96ojwXSknQGBvN+CoE7MuwIzC0Decsmd7jFhtL60gJ/Z2Tn5snuAyekelykVA5nyT4REREREXmBhzLzzZs3l1dffVWCTVA0wMNagFjupqRt8eLFNvebP3++XHjhhRIZGSnx8fFy1VVX6XwKe1auXKnPw/OxH/Z/7733PPK5EJAjw24ZmNtqcmcE/pPGXF3mEnsE8iOnL5AnXlukt/ieiIiIiIjI4wqd2/YeXy+/bp8rq3e+E5I/nKDKzPfv318D7KLq1KlT7L4HH3xQZs2apeUUvXv31rkSS5YskR9++EEWLFggffv2LbbP559/LjfddJMUFhZK9+7dpVq1arJs2TIZNGiQbN68WV544QW3fyaUyjvS5M5W4O/M/HiU1QMy8rv2HZf8ggK9XbslVRrWSZDoqpVZdk9ERERERB7jbGf6pLgOuuUX5MjS7S+G3E8mqIJ5BNPJycmlPm/p0qUayCckJMjq1aulSZMmej++RpYfzRFwi8YIhpMnT8pdd92lzR0Q1Pfr10/vP3LkiFx00UUyc+ZMueaaa3Q/dzJK6h1pcmcZ+DsjJjLCHKijtL5RvWoayOO2U6skltoTEREREVHAltkHq6Aos3fWiy+eu2rz+OOPmwN56NKli9x3331y+vRpefvtt632eeutt7Sxw/XXX28O5KFGjRoyY8YM/RoBvbthjvz+g6d07nzRJnd4zJKrze4sYY78nAkD5MnhV+ot58wTERERERH5n5AL5rOysuTHH3/UrwcMGFDsceO+r7/+2ur+b7/9tsR9rr76aqlcubJm/FGu704I0OvWjjN3t69QIczc5M5TEMC3bVqHgTwREREREXlPocn1LQQFVZk9suknTpyQ8uXLS9OmTXXee/369a2es23bNsnJyZHq1atL3bp1i70G1h0EzIG3tGnTJqvHLYWHh0urVq1k/fr1uobh+eef75Xu9sdOZLolG2+LUXZPRERERETkFSyzD91gftq0aVbfP/zwwzJp0iTdDHv37tVbW4E8YL1BzJXH2oMZGRkSFRWl5fVpaWl298P9COZTU1PtBvMo4UcDPUOlSpV0c0TFimGSVC9Bb7OycmTP3mOSEFelTN3r3Qmfy2QyWX0+4rgHK57vHPdQwXOd4x5KeL5z3ENJWc53JEexGRAvuYeLc+aFmfmAhc7yw4YNk65du0qtWrVk37592pEewf3kyZMlOjpaRo8erc/NzMzU2ypVqpT4egjoEXQbwbyxj739sA9gH3uSkpKsvh87dqxedHBUXm6O7N9/Vp58cYnsO3Ba6tWJlSfGXC7h4b6/LoNfBLjogV8KqI4gjnsw4/nOcQ8VPNc57qGE5zvHPZSU5XxH43FP9AtjZt45vo8A3WDq1KlW36PEfuLEiXLBBRdInz59ZMqUKXLPPffoMnS+hsw9Li64kplHw7u8gnBJ2Xdc9h9Mk4KCQr1NPXhWkutVk6jISh4ru3f0F0K5cuV0CgODeY57sOP5znEPFTzXOe6hhOc7xz2UlOV8f+qpp7SZuGVmvmjSkjwvKIL5kmD9eAT0KH9fu3atLhtnrEN/9uzZEvc7c+aM3iIrD5Zr12M/y2C8pH1KghJ+W/sXDdptBeWxMVV1S6wWpU3wjGXqLmzXwG9K7fELAb8MGMxz3EMBz3eOe6jguc5xDyU83znuocTV8x1JUstEqdv+9tdGdi6UzBeyzD4oYek5BPOHDh3S742GePv377f5fATlKLGPi4szB+YIvmNiYrQMBfu1aNGi2H7G65X1ihTWk9/8135zkztHm+EREREREREFNFPhuc1Bqel/yN6MTTpVIBQF/cRmNLKznNPerFkzLWs/duyYHDhwoNjzN27cqLdFm9i1adPG6nFLeXl5smXLFl2eDiX+ZQnkH3zsU5k281u9xfclQQCfXL8aA3kiIiIiIgqubvYObklRbeTi2ndK11o3SygK6mAeAfuKFSuslpRDOUjPnj31688++6zYPmicB9dee22xteQtH7f0zTff6PryvXr10oDeWSir33/wlGba96Qek/z8Ar3F97gfj9sSHeX8exEREREREfklrjMfWsH8qlWr5KuvvpKCggKr+1NSUuSGG27QsvnrrrvOakm5MWPG6C263e/YscN8/+rVq2Xu3Lk6r33o0KFWr4du+Si3X7hwoXzxxRfm+48ePSrjxo0zd6Z3BebH160dpyXzDZKqS4UKYXqL73F/SU3tfNnsjoiIiIiIiHwn4Bvgbd++XYYMGSI1a9bU7DsCcXSM37Bhg2bLW7ZsKW+++abVPsigY6m6WbNmSdu2beXyyy+X3NxcWbJkic63mDdvnr6Opfj4eHnnnXdk4MCBMmDAAG2ml5CQIEuXLtU59rhAgPvKQufCP8258EREREREFIKMEnpX9gtBAR/Md+rUSYYPH67d6tetW6dz5DE/HkH6jTfeqI/ZWpLu5Zdf1ufMnj1bg/jw8HAN8idNmqTr1dvSv39/Wb58uWb016xZoxcA0Azv/vvvl0GDBrnl83AuPBERERERhSRtZu9KMC8hKeCD+ebNm8urr77q0r6DBw/WzRndunWTRYsWiSdxLjwREREREYUcZuZDa858oOnYsaNm8+fMmVPiczgXnoiIiIiI/B1iGsQ2iHHcorDQ9S0EBXxmPtBgKgAa6REREREREQWykSNH6paeni4xMTG+PpyQw2CeiIiIiIiIAq7MPvXsFtl7dos2MQ9FDOaJiIiIiIgo4IL5pIiWuuUX5srS4+9IqGEwT0RERERERL5XqO3sXdwv9DCYJyIiIiIiIp8zmQp1c2W/UMRu9kREREREREQBhpl5IiIiIiIi8j3Ml3elZN7EMnsiIiIiIiIi39CgnMG8o5iZJyIiIiIiIt8rLBQp58L8dxPnzJMXdOzYUVq0aCFz5szheBMRERERUcBCTIPYBjGOW5emc2ULQczMe9m6deskOjra229LRERERETkViNHjtQtPT1dYmJiOLpexmCeiIiIiIiIfM5UWCgmJ8rs9+b9I/vytomJmXkiIiIiIiKiwGiAV79CM93yTbnyY9YnEmq4zjwRERERERH5Hpalc3VzQFZWlkyePFmaNm0qlStXltq1a8tdd90lBw4ckEDEYJ6IiIiIiIh8T5vZFbqwmUp96ezsbOnZs6c89dRTkpmZKddff73Uq1dP5s2bJ+3atZPdu3dLoGEwT0REREREREFt2rRpsmbNGunSpYts375dPvnkE1m7dq3MnDlTjh07phn6QMNgntwmJydHXnjhBb0l7+G4+wbHneMeKniuc9xDCc93jnso8cfz3VRocnmzJzc3V2bPnm1eTi8yMtL82JgxY+T888+XX375RTZs2CCBhME8uQ1+EeDKlj/9QggFHHeOeyjh+c4xDxU81znuoYTnO8fdzKUS+8Jzmx0rV66UtLQ0adSokZbUFzVgwAC9/frrryWQMJgPULii5I+v5U7uOi5/HSt/HHd//Xz++lrB/vn89bWC/fP562sF++fz19cK9s/nj//Wu5M/jpU7X4vjznEPlMz8pk2b9LZ9+/Y2Hzfu37x5swQSBvMByh9/obubP/5D46+vFeyfz19fK9g/n7++VrB/Pn99rWD/fP76WsH++fzx33p38sexcudrcdw57oGSmd+7d6/e1q1b1+bjxv2pqakSSCr4+gBChel/HRZx1ScsLEzuvvtuueeee1x+vYKCAklPT3fLsbnrtYzXwG358uX95rj8caz8ddz98fP562tx3DnuofJa/vq7Pdhfi+Pu/THnuDuP4+6b8fKncX/jjTfkzTff1GOyjHlclS95Di0zXygFUij/BvD5km/3+eheD1WqVLH5eNWqVfU2IyNDAkk5U1lHnByyf/9+XfqAiIiIiIgoGO3bt6/E7Hdpy8Y1aNBADh8+7PJ7R0ZGald6rB9fFJKouOjw2GOPaVf7onbu3ClNmjTRDZ3uAwUz815Su3ZtPbmjoqKkXLly3npbIiIiIiIij0J+GFltxDyuQAC+Z88e7TrvaNPEnCJNtxFn2Qrkwehef/bsWZuPnzlzxvwagYTBvJegdMWVq1RERERERET+LiYmpkz7IxAvKRgvq/r165urpW0x7k9KSpJAwgZ4REREREREFLTatGmjtxs3brT5uHE/1psPJAzmiYiIiIiIKGh169ZNKwd27dolf/zxR7HHFyxYoLfXXnutBBIG82TThg0bZPr06dKvXz+dHoB5/mWZ63/q1CkZPXq0lq5UqlRJbx988EE5ffo0fwIeGPPk5GTz/ra2f/75h+P+P5g79dVXX8nQoUOlWbNmWt6Fjqa4gjt16lRz91Oe7/475jzfHffiiy/q7xg0+MEfNcbv4zvvvFP+/PNPp3+W/N3u/XHn+e66EydOSGJiov472LhxY5deg+e898ed57xjevToYfdvv8WLF4f0uR4eHi7333+/fj1y5EjzHHnjdzTWl7/kkkukQ4cOEkjYzZ5s6tu3ryxcuLDY/a4sfnD8+HHp0qWLdols2LChXHDBBfLXX3/p1rRpU1m9erXEx8eH/E/CnWOOf/iwTuagQYNsPv7ss89KrVq1Qn7M4a233tKlIqF58+bSqlUrXaJl1apV2sjlvPPOk19++UX/EOH57p9jzvPdcdWqVdM/YFBGWKdOHb0Pv4vRubdixYryxRdfyDXXXOPQa/F3u2/Gnee76wYPHizvvfee/rvaqFEj/bvEGTznfTPuPOcdD+bxb2f//v3Nzd4sjR07Vlq3bh3S53p2draO09q1a/Xv4Isvvlj/Xsb31atXlzVr1ujnDShYmo6oqOnTp5smTZpk+u9//2s6dOiQqVKlSogoXRqo2267Tfft16+fKS8vz3z/Aw88oPcPGjSIPwA3j3lSUpLL+4aa+fPnm+655x7T33//bXX/wYMHTe3atdNxvOWWWxx+PZ7v3h9znu+O+/XXX01ZWVnF7p8zZ46Oe40aNax+T9vDc903487z3TVLly7VscbvHtw2atTI6dfgOe+bcec575hLLrlEx3jPnj2msgrmc/3s2bP69zbOxfDwcFPNmjVNgwcPNu3bt88UiJiZJ4egDBbLPzibJT506JCWjFeoUEH27t0rNWrUMD+G16tXr56cPHlSDh486HAWLlS4OuaWV7Fd2Zf+hSvPXbt21fIyZI5RomUPz3fvjznwfHcPlL9iLuGmTZtKbQDEc9034w48352XlZWlGUn8XsEUH2QWnc0Q85z3zbgDz3nnMvNY3g1j5iqe64GFc+bJozA/p7CwUMtYLAN5wC93NJkoKCiQ7777jj8J8tvOp7iogjl/peH57v0xJ/dBuTc4cgGF57pvxp1c8+STT8ru3bvl9ddfN4+3s3jO+2bcyft4rgcWrjNPHoVMA7Rv397m47j/nXfe0aYT5H7PP/+8Znxw4aRly5Zyww036Jwgcgz+CAH8EeLI3DCe794fc0s83133/vvvy7Zt27RBG7bS8Fz3zbhb4vnuGPx9MXPmTBkyZIgmFlJSUlz6WfGc9824W+I575i3335bL4aXL19eqyHQk8lYY90RPNcDC4N58iiU1gNK7W0x7kdJOLnfuHHjrL5/6KGH5P/+7//krrvu4nA7YNasWXp7xRVX6AWR0vB89/6YW+L57twfxWhkhKZsW7du1a9r164tH330kYSFhZW6P89134y7JZ7vpUNl4LBhwyQ2NlZmzJghZcFz3jfjbonnvGOmTZtm9f3DDz8skyZN0s0RPNcDC8vsyaOMJaaqVKli83EsRwXoYE3uc91112l3ZFwkwTJgW7ZskTFjxmjpMv6BtdU1n6xh6geubiND/NRTTzk0PDzfvT/mwPPded9//728++67uq4uAkosOYSA0tEleXiu+2bcgee743Dxet26dXoRJSEhQcqC57xvxh14zjume/fuWu2Dikz87Yeqn6efflr7Vk2ePNl8sbw0PNcDjK878FFgcLWz+uWXX677vfnmmzYfX7JkiT6O55F7xtyeN954Q1+zWbNmHG47tm7daoqLi9Oxevnllx0eK57v3h9ze3i+l+7UqVOm5cuXm3r16qVjP23aNIfGlue6b8bdHp7v1lJTU02RkZHa4dsSOn270lWd57xvxt0envOO+f7773XsY2NjtZN7aXiuBxZm5smjjHUucYXQFpQaQlRUFH8SXjB06FBdNQBXa90xfy0YHThwQEu8T506pdUMo0ePdnhfnu/eH3N7eL6XDmWwmM+Kqghkh1GGiYxaaXiu+2bc7eH5bm3kyJGSm5urzdfcgee8b8bdHp7zjundu7euE3/69GldT700PNcDC+fMk0cZDTf2799v83HjfpQakuehGQqWhTl69KguPVKWpUuCEZZJxD96mJ6Apj0vvPCCU/vzfPf+mNvD891xmNpw0003yYYNG+Trr7+Wjh072n0+z3XfjLs9PN+tffPNN3rR5L777rO6Pzs723wREUt5wccffyw1a9a0O748530z7vbwnHccGmyuX79e//YrDc/1wMJgnryyzNTGjRttPm7c78jauuQeyH5a9iugf+eIXXnllfL3339Lv3795M0335Ry5co5NTw8370/5qXh+e64atWq6e2xY8dKfS7Pdd+Me2l4vltDJhLrbtuC4NJ4zAg07eE575txLw3PefePE8/1AOPrOn8K7vnbBw8eNJUvX94UHh5uOnLkiNVj2dnZpurVq5vCwsKKPUaemTO/ZcsWU7ly5UxVqlQx5eTkcJgtzsWePXvqePfp08flseH57v0xt4fnu3MGDRqkP4/nn3++1OfyXPfNuNvD890xrs7d5jlfNp6YM89z3jFHjx41Va1aVcd/3759pT6f53pg4Zx5covZs2fLeeedJ48++qjV/bVq1ZJbbrlF50+NGDFC8vPzrZYYQSbi9ttv13nc5J4xxxzMH3/80eaarzfeeCOuDmhH+/DwcA65iBQUFOg5ijHDHFasAlDa2PB8958x5/nuuJUrV8rixYt12ShLeXl52n0aXZAjIiK07Lu0cefvdt+MO893z+M57xs858tm1apV8tVXX+m/r5bQH+mGG27QHlVYFcByqWie68GBZfZk07fffmu1NBSCcejcubP5PjTsufrqq/Xr48ePa1M1W3NxXn75ZVmzZo18/vnn+scJmnBgSR4sl4Y5PC+++CJ/Cm4c899++02efPJJ7UOAUiksC7h7926d0oCLKZirNn36dI65xT9mX375pbncFRedbMFcbqMclue7/4w5z3fH7dixQ/sSYEzRdA1LRmFc//zzTx3XypUry/z586VevXrmfXiu+9e483z3PJ7zvsFzvmy2b9+uv2fQg6B9+/batwC9aNCPA9MZWrZsqVPZHBlz4N/ugYPBPNmEjLmtjpeW9zk6vw9/wOAPkClTpuhVQ/wRX6NGDRk1apQGnfiFQ+4b8z59+si+ffu0MzIyQmlpaRIdHS0XXXSR3HbbbfrLPiwsjENeZB4ZGAGmLTh/jcCS57v/jDnPd8ddcsklMnHiRJ2vikod/CGHigg0whwwYID+Tm7cuLHDr8ff7d4fd57vvsVz3vt4zjumU6dOMnz4cP2bEX//4d9ZzI9v27atVmXiMVQAOYrneuAoh1p7Xx8EERERERERETmOc+aJiIiIiIiIAgyDeSIiIiIiIqIAw2CeiIiIiIiIKMAwmCciIiIiIiIKMAzmiYiIiIiIiAIMg3kiIiIiIiKiAMNgnoiIiIiIiCjAMJgnIiIiIiIiCjAM5omIiIiIiIgCDIN5IiIiHxg8eLAkJyf7/djPnz9fypUrJ+vXry/T64wYMUIuv/xy8YXXX39d6tevLzk5OT55fyIiIk9gME9ERAHr008/1UDzyy+/LPZYmzZt9LGffvqp2GMI7Lp27eqlowwMr776qgbunrBnzx556623ZOLEieKrCye5ubkyd+5cn7w/ERGRJzCYJyKigHXRRRfp7a+//mp1f3p6umzZskUqVKggK1eutHps3759uhn7kueD+VmzZkmDBg3k0ksv9clwV65cWQYNGiQvvviimEwmnxwDERGRuzGYJyKigFW7dm0NEosG86tXr9ag7cYbbyz2mPE9g3nvyMvLkw8++EAGDhwovoT3T01NtVmpQUREFIgYzBMRUUBDUP77779LVlaW+T5k41u2bClXXnmlrFmzRgoLC60eQ/l9t27d9Pt58+ZJz549JTExUSpVqiQtWrSQ1157zeo9rrnmGmnYsKHN9+/SpYtccMEFVvf95z//kQ4dOkhERITEx8fLzTffrNUApcFxvvzyy3rsyCbXqFFD7r33Xjl16pTV8zDXHseECxMXXnihPhfH99577xV7zc2bN8sll1yix1K3bl2ZNm2afmaMQUpKivn1/vrrL/nll1/0fmw9evSweh3MNx8zZoxUr15dqlatKjfccIMcO3as1M+EYzx+/Lj06tXL5lx84xgMP//8s96PWwOOpVWrVubPUqVKFWncuLEsWLBAH8dxd+rUST9js2bNZOnSpcWOAz8P/CwWLlxY6jETEREFAgbzREQU8ME8sr9r1661CtgxJx5bWlqaltxbPnbeeedJQkKCfo/APSkpSedzz5w5U+rVq6fN2ubMmWPe56abbtJ53+vWrbN6b2R6cbEAwbrh6aefljvvvFOaNGmiZd0PPvigLFu2TLp37y6nT5+2+1kQuD/yyCN6oQGl6UOGDNGsdp8+ffQzWtq5c6cMGDBAm8rhuOPi4nRuOIJyw4EDB7S0Hfc9+uij8tBDD+nr4bUt4QICAn2My/vvv6/bY489ZvWcBx54QDZt2iRPPPGEDB8+XL7++mu5//77S/35rFq1SoPzdu3aSVngggYuYCBonzFjhl54wbh/8sknenvVVVfJ9OnT5cyZMzouGRkZxV6jffv2xaZdEBERBSwTERFRAPvrr78wCdr01FNP6fd5eXmmqlWrmt599139vkaNGqY5c+bo1+np6aawsDDT3Xffbd7/7NmzxV6zT58+poYNG5q/T0tLM1WqVMk0duxYq+fNmDHDVK5cOVNqaqp+n5KSoq//9NNPWz3vzz//NFWoUMHq/kGDBpmSkpLM369YsUI/xwcffGC17+LFi4vdj/1w3/Lly833HT16tNgxPvDAA3p8v//+u/m+EydOmOLj43X/PXv2mO9v2bKl6ZJLLik2FvPmzdPn9urVy1RYWGi+/6GHHtLPevr0aZM9t99+uykhIaHE17U8Bvjpp5/0ftwacFy478MPPzTf988//+h95cuXN61Zs8Z8//fff6/34/WLuueee0wRERF2j5eIiChQMDNPREQBrXnz5pplN+bCI3uM7KzRrR63RjYWc+kLCgqs5sujNNuALD5KwlHKvXv3bv0eoqOjtWQf3fMtG6ghK9y5c2ftjg9ffPGFlspjfjZex9hq1qypmXp787U/++wziYmJ0Uy75b4oD4+MjCy2L6YDXHzxxebvUf6OEnMct2Hx4sU6DaBt27bm+1Bqfttttzk9zvfcc49m2A14b4wlqhPsOXHihFYNlBXGwLICAp81NjZWf/7I1huMry3HwYDjwHSMs2fPlvl4iIiIfK2Crw+AiIioLBBgImBfvny5BtII3DH/HXOqAY/Nnj1bvzaCestgHvehdByBftEgD8E8Amyj1P6rr77S5+E1d+3aJRs2bNASdcOOHTs02EfgbkvFihVL/BzYF++HY7fl6NGjVt8bFxCKBquW8+sRaCOYL8oYG2cUfT8jQC86n98Wd3SQxzQAy4sJgJ8NpkUUva+k4zKOo+jrEBERBSIG80REFPAQnGMO959//mmeL2/A15iHjvnjyN6jA77RzA4B+WWXXaZzxTG/HYFheHi4fPfdd/LSSy9ZNc679tprtfEasvN4TdyWL19eO+Yb8HwEiosWLZKwsDCb2eWSYF8E8pjTbgsy75ZsvT54auk1V98PVROOBPylvV5J7+/MceE48DO0rMYgIiIKVAzmiYgoqNabRzCPpnMGlKmjWRq6o6NJHhqlGXABAF3a//vf/1plnm2Vw6ODOxqwoRwegT9K7FFqjosDhkaNGmkQieXymjZt6tRnwL7owo7md+4KNtHYD43yirJ1n6ey1bhQggsUllUOloo2qjty5Ih4CpoYoiyfiIgoGHDOPBERBTwsDYfl2RA0IgNvmZlHII8u5uhOj7n0liX2RlbXMouLoBNLt9mCUvuDBw/KW2+9pXPz8b2lfv366Ws++eSTxTLD+B7zx0uCefaYg/7UU08Veyw/P7/UTvi2oAs+pgX88ccf5vtOnjxpM/uPixWuvEdpUOaPz44pCbYUvXDy5ZdfeqzCYOPGjVbnBhERUSBjZp6IiAIeSuM7duwoK1as0OAd2XhLCOCwfBtYBvO9e/fWfVFCj2XhMjMz5c0339Ry90OHDhV7H2T1o6Ki5OGHH9agvX///sWy61jHHcvAYf30vn376vOREUaQiiZy2NcWNN3DMTz77LMafOPYMMcec+lRDYDl5LDkmjPGjRuna96jqR6WlkPAjgsRqEJAUG+ZjceYYZk+HD/m1GMMevbsKWWF8UapPaoObL0eLnzgAgymPvz444/yww8/6P3vvvuujh0u1LgDLibgM19//fVueT0iIiJfY2aeiIiCghGkG2X1llC6DggO27RpY9URfcGCBRrUIsh+/fXXNeAePXq0zfdA9v+6667T0nCs326rWd2ECRPk888/1/n0CFTxuijjR3COfe3B+7/xxhva7A7r3uOiAALc22+/3fwZnIEeAMh8o7T8mWee0WZ9gwYNkrvuusv8eQyTJ0/WixVYw/2WW26RqVOnijvgYgm65+OChC24SPHNN9/IqFGj9AIIGhn26NFDFi5caLeSwVl4f1zEcMcFCiIiIn9QDuvT+fogiIiIyHvQU2Du3LlaiVBSAzl3wjJxmDuPxoBoOAjz58+XIUOGaNVCcnKyR98ffRHwHrjQUtKFGiIiokDDzDwREVEQw7rqlpDtfv/997WSwRuBPKCEfujQoTJ9+nTxBfRAwJSF++67zyfvT0RE5AnMzBMREQWxtm3batk6Su3RKf7tt9/WJn7Lli2T7t27++y4vJmZJyIiCkZsgEdERBTEMA8efQEwFx+9AdDZHwG9LwN5IiIiKjtm5omIiIiIiIgCDOfMExEREREREQUYBvNEREREREREAYbBPBEREREREVGAYTBPREREREREFGAYzBMREREREREFGAbzRERERERERAGGwTwRERERERFRgGEwT0REFALKlSsnPXr0KNNr/Pzzz/o6U6ZMcdtxERERkWsYzBMRUZmdOXNGnnnmGWnfvr1ERkZKpUqVpG7dunLxxRfLo48+Krt27bJ6PoJKBIXGVr58eYmLi9Pnz58/X0wmk/m5KSkp+pwrrrii1CDzvvvus7p/8ODBVu9ja8P7GfB10ccjIiKkadOm8sADD8jhw4dtvn9ycnKp74PP4W5438qVK0swX0TYvn27jn3Lli0lOjpaz6169erJgAED5PPPP5fCwkK3Hi8REVGgqODrAyAiosCWkZEhF110kWzevFkaN24st99+uyQkJMjx48flt99+k+nTp0ujRo10K2rs2LEa/BcUFMju3bvliy++kF9//VU2bNgg//d//+e2Yxw6dKheXLClbdu2xe677LLL9DPBiRMnZNmyZTJ79mz56quvZOPGjVK9evVi+4SFhcnjjz9e4jHExsaKL23dulWqVKkigWTmzJkyfvx4Ddjx87j88sv1M+zbt0+WLl2qwfxdd90lb7/9tq8PlYiIyOsYzBMRUZm8/PLLGsgPGzZM3njjDc3EWtqzZ4/k5OTY3Pfhhx+WmjVrmr//888/pVOnTjJnzhwZM2aMNGjQwC0/HRxb586dHX5+r169ZMKECebvEUxee+218t1332lQ/+STTxbbp0KFCn5dfn7eeedJIMG5hPMD1QcI2lH1YSk/P1/effddWbFihc+OkYiIyJdYZk9ERGWyevVqvR05cmSxQB4QkDsaSLZu3VouueQSLbNfv3693/xkMA0AJfuAqoGyWLlypQb+qAgoepHD3mOeKndH+f9NN90k8fHxWiWB8V++fLlemMA+mMJgC34+yJRHRUVJTEyM3HDDDVZTCYypD/DLL7+UOLXBltOnT8sjjzwi4eHh8u233xYL5AHjhIqLuXPnFptWYWtKg63PY9kDYNWqVdK7d2+toMB9qamp+nPv2bOnzWPMy8uTatWqacm/Zal/bm6uvPjii3rMVatW1fHB9JH//ve/dj8zERGRsxjMExFRmaCk3pjb7E62Lgz4AwSRZdGtWzctx9+0aZOWkFsGsLfddpvOCf/oo4/01tMOHDggXbt2lU8//VQrIkaNGqUBKoL0tWvXlrjfunXrpHv37hps33vvvXLBBRfoFARUNGRnZ+tzkFF/4okn9OukpCT92thsTW2wtGDBAklPT9d58S1atLD7XHeMEwJ5o4/DPffcoxc3cMz4jLgQsX///mL7oEoDUzDwM0PQD7gA06dPH50+ggtSuNiAaSe4MHD99ddrVQcREZG7sMyeiIjK5MYbb5T//Oc/WsqOOfLIbnbo0MEc5Dvjr7/+MmdxESBa2rlzZ4ll7KU1l3vrrbdk8eLFNh9DOX1pTeSQeZ03b55+bcylLwpl3yUdH6YSWDbnmzRpks75fuWVVzT4u/LKKzUoRtCHTHPz5s3FG/DZDx06JE8//bRMnDjRfP8777yjgWhJEMh+/PHHGvQa7rzzTnn//fc1qL/55ps1mMd4YEqC8bWjUKEAJWXF3W3JkiX6mYcMGWJ1/x133KHn44cffijjxo2zegyf1XiOYerUqZrtx88Xn9u4IIW+EvgsCPL79esntWvX9srnIiKiIGei/2/vPuCbqto/gP+S7kEXUPbeZSkKCqigIio4gRe3TGcVFByvKMhfcaH4iloXIjh5VYYKKK8MleVgKSIyZO+yOuhucv+f58TUtE3bJE2T3Jvf18/1cG9ybm5z2rTPPec8h4iIqmnatGlabGyspKAv2Vq1aqWlpqZqO3bsKPf8Pn36qOeMHz9ee/LJJ7UnnnhCu+WWW7SoqCh1fMyYMSXP3bNnT6nzVrbdddddpV5n2LBhVdY5ffp0yfNnzZqljl166aXqumS7//77tQ4dOqjjvXr10s6cOVPu62nWrFmlr9G1a9dydfbu3aslJCRoycnJ2rPPPqueN2jQILfed3ndiIgIl54r55f33S4/P1/VldeXfzuyWq1au3btVJ3vvvuu5Lj8W45ddNFF5c5vf2zcuHGVvq4rrrjiClVvyZIlbtWzt7d8z5QlbVnR19OtWzen58vIyNAiIyO1zp07lzou3zPy3p111lklxywWi5aYmKi+7+X9K+urr75Sr/Xaa6+59TURERFVhD3zRERUbZKs7o477lC93zJkWeZTyzBtSWQnmcY//fRTXHPNNU6zlQvpwZRlx6Q3XnqEpZe3LOnBrqh3XXpDL7744krn9buTAE+y18tWdni8HKtoWLcctw8xd4UM437rrbdUL7b0iku2/RkzZsBXtm/froaFy3te9muS9pDh9/IcZ2TkRVn21QJkuoDedO/e3elxyQUg37cyDUGmRXTt2lUd//zzz9V759grL+/V6dOnVa+7swSJx48fV+W2bdtq7OsgIqLgwmCeiIi8QhJ9yZB72URmZqYKUt944w0VoMv8bJlj7UiGeDtmsw8Uzz33nBqCLsPrZQi/DBGXYdVyw+KDDz7w2uvIEnhyE0Pmh998880qCZ2vyGuK5ORkp4/Xq1evwrpyzRXlEpBlBqvL/j0h3zO+UNnXKgG7BPMylcQezMv3gixFKG1md+rUqZKpIrJVJCcnx6vXTkREwYsJ8IiIqEZIr6Yk/JIeaFlzXpad0xtJbNayZUu1BJokQ7PPCfcWWSNdgmrJLyBL/P3666/wFXtAnp6e7vTxY8eOwV9kFIQoOzqiKvZEdJK/oCy5ueRJssUrrrgCdevWVUkJ7Td3Vq9erZL9Od6Isr+fgwcPVsnvKtrsuReIiIiqi8E8ERHVGAmSZHkuI3wd06dPV+Vjjz1WaikyT8kUhIULF6ps599++606dtNNNyE3Nxe+0K5dOzW8XpbaK7sMngSd9iUHq0sCbHd76yWLvQTHsr58VcPSHa89MTGxwh79TZs2wRMy4kCmQsg5v/vuO3z88cfq/ZF2cyRJC+WaZYqJLFtHRERU0xjMExFRtUj2dVmqzBnpxf7zzz/V2t2dOnXS9Tsty6ldd911KriUgK46tmzZgoceekj1+ss0BFmTXDLKy7kfeOAB+IIE8hI0Sw+8jApwJFMJvDW3W6YOOFvarTLy/fLiiy+qQH3gwIFORyzIDQIZMeG4SoB97nvZdexlqTvJSu8p+9x4GZkhm9yguv7668sF/ffcc49akUDa1llAL+1e0UgIIiIid3HOPBERVcs333yjAqrWrVur4dGSAEzmBUtP6KpVq1TPrASsvlg33ZOl6SQxngyldoWskS43KGQJMulFd1xzvrKl6YT07rZv314lyZO68nxZ8kxyDQhZtkx66CUJniT7k+HarpCgcfjw4RU+XjawLZsbQJbIk/wAEuyeffbZKpHbokWL1Hsi75l96LqnZEk2mXMuN0Lk/DLXXJLKdenSpdJ6st67TEGQa5ObHTLNQepHRUWpXnIZgi+lLIloJ2u5t2rVSn3NBw4cUM+Xm0krVqzAgAED1JJ6npCbBDKSQdpL3m8J7p2NOJHEdxs3blRLDi5evFhds+QkkOuUaSaSRE9GPFSUp4CIiMgdDOaJiKhaXnjhBRXEy1rdK1euVEntRKNGjTBs2DDcf//9TrOf+5Jk1K/I2LFjXQ7mJQGarBMuw7+l91rmvDv2FDvLYu7Ysy/BvPTaSg/tlClTcN5555U8LkP4padZglxJtNejRw80adKkymuSIf9Sz5NgXs4vweWjjz6qbiRIQC9tJf+WjO0VJbtzh0xPEBJQy7QCuV7JfF9VMC/kvbr66qtV7gWpLzdlpLdegmEJsOXc0h52EujLzYkHH3xQBfs//fSTulkj35dyg8LTYF5IAP/EE0+of5cdYm8nN6zk5pZ8v8n3h3yfyPVKgr2UlBR106tz584eXwMREZEjk6xPV+oIERERBb0LLrhABfqSOC42Njbo3w8iItK3vn37VjrlSm7GunpzP1CwZ56IiCiIyUiKBg0alDomy7CtWbMG/fv3ZyBPRESGMnjwYKe/22REod4wmCciIgpikphQ5pbLMHCZzy7J5r7//ns1l/+ll17y9+URERF51UsvvYTmzZsb4l1lME9ERBTEZB63zGWXJdUkcaGsqX7zzTdj4sSJao4/ERERBSbOmSciIiIiIqKgmDO/Z88e9swTERERERER6cnMmTNx8uRJtfRq27Zt1dKpTZs2hR6xZ56IiIiIiIiCMpt9WFiYmlomm94wmPcRWVf38OHDKqGQrCVMRERERERkBLLaeXZ2Nho2bKh6vD2Rn5+PwsJCl55bUFCgNkcSZ8XHx1dYZ9KkSaonvlevXmoVlwMHDmDu3LmYMmUK8vLy8Morr2Ds2LHQEwbzPnLw4EE0adLEVy9HRERERETkUxIgN27c2KNAvkVUFI5W47VjY2Nx/PhxREZGulXv22+/xeWXX46EhATV+RoVFQW9YDZ7H5E7RfZv8Li4uAqf1717d6xbt65GrkGP566p82ZkZKBZs2bYt2+f+sEN9vdDj+fWaxvq9dz8WfTN+6HXc9fkz6Me34+aPLce21CP74dez82fRd+913psw5q87m7dumHXrl0lMY+7pEdeAvkDZhMqjpT+UaBpcOyXzwaQcuaMOo+7wXz//v1x7rnnqlVdfv75ZzUcXy8YzPuIfWi9BPKVBfOyxm9lj1eHHs9dU+eVaQ+utEewvB96PLde21Cv5+bPom/eD72euyZ/HvX4ftTkufXYhnp8P/R6bv4s+u691mMb1vT7Iao7nTguxIQ4D86RpWlAke2980SbNm1UMH/kyBHoiWcTGqjGpKam8tw+ej9qUk1dN78/fIfvte/ej5rEn0XfvB81iT+Lvns/ahJ/Fn3zftQk/iz67v2oSTV13XfccYd3ThRi9nyrhtOnT6syJiYGesI58z6SlZWlEjJkZmbW2F1ecm8IU2JiovrBrYkhTFTz2IbGwHY0Braj/rENjYHtqH96bcPqxjol9SNDPe6Zj88v9uj1ZZ59ixYtkJOT4/Gcf39hzzwFpYiICIwfP16VpE9sQ2NgOxoD21H/2IbGwHbUv6Bvw1ATPN4qsXbtWnzxxRewWCylju/duxfXX3+9CuSvueYaXQXygj3zPsKe+cAi85HS09ORnJzs8fIZ5F9sQ2NgOxoD21H/2IbGwHbUP722odd65uMjPO+Zzyyo8PVnz56NESNGoH79+ipZn4x6kCSDGzZsUJn0O3bsiBUrVqj3XU+YAI+IiIiIiIj8z2yybe6yVv7weeedh3vuuUdlq5ds/jKNQebHn3XWWfjXv/6lHtPTknR2DOaJiIiIiIjI/ySRnSfBvEmr9OEOHTrgjTfegNHoZ+wGERERERERESkM5n2se/fuSElJQVpamq9fmoiIiIiIyGskppHYRmIcPS9Np1ccZu9jMkeDS9MREREREZHeybr1stkT2FVbiIdz5k0ISgzmCcg8DcQn8p0gIiIiIiLDzZk3KgbzBGRlMJgnIiIiIiL/Ys+8W4JzcgERERERERGRjrFnnoiIiIiIiAKjZ96NZHZpGflqs2gcZk9ERERERETkx2De9TnzqbWj1JZlsSJ+xykEG/bMExERERERkf8F8TJznmAwT547fQpITOI7SERERERE1cdg3i287UGeyzjNd4+IiIiIiMgP2DNPREREREREupsz/w9P6ugfe+Z9rHv37khJSUFaWpqvX5qIiIiIiMhrJKaR2EZiHK8Os/dkC0LsmfexdevWIS4uDgElO9PfV0BERERERDqTmpqqtqysLMTHx1f/hGYPe+a14OyZZzBPQHYW3wUiIiIiIvIvT3vZNQSlgBuP8PLLL2PQoEFo06aNursTERGBZs2a4fbbb8fvv/9eYb3Zs2ejR48eiI2NRVJSEgYMGIC1a9dW+lpr1qxRz5PnSz2p/8EHH1Ra5+DBgxgxYgQaNmyIyMhItG3bFk8++STy8/M9/prJPbm5uaVKIiIiIiKiYBNwwfyzzz6Lb775RgXYl156KQYOHKiC5g8//BDnnHMOFi1aVK7OAw88oALsLVu2oF+/fiooX7p0KS666CJ88cUXTl9n3rx56NOnD5YsWYIuXbrgiiuuwM6dOzFs2DA89NBDTuv89ddfOPvss9WNg9q1a+Paa6+FxWLBU089pV63oKAAupOfBxzYYyt1QAJ4maqwcuVKVTKgJyIiIiIyWAI8T7YgFHDB/JdffonTp0/j559/xvz589W2fft2lVyhqKgIo0ePRnFxccnzly1bhunTp6vg+rffflPBuwToEuyFhISoID8jI6PUa5w6dQojR45UgfjcuXPx/fffq3Lbtm1o3bo1pk2bpo6VNXz4cJw4cQJjxoxRowQ+/fRTdW3XX3+96uV/7rnnoCsSwN89FPjPU7ZSBwF9dHQ0TCYTrFarKmWfiIiIiIgMgAnw9B3M9+7dW/XEl3XvvfeiVatWOHbsGLZu3VpqWL544okn1NB8u549e+Luu+9WgfzMmTNLnevdd99VSRqkZ12G9NvVq1cPU6dOVf+WgN7RL7/8ogL25OTkkueI0NBQvPnmmwgLC8Orr75a6kZDwNv7F7B7O2Cx2ErZD3DSE69pGsxmsyrZM09EREREZBDsmdd3MF8ZCZhFeHi4KvPy8rBixQr17yFDhpR7vv3YwoULSx1fvHhxhXXsw/qlx99xHry9ztVXX63m8TuSmwAXXnihGlGwevVq6Ebz1kDLdkBIiK2U/QAnPfGy9IVMoZCSPfNERERERAbBnnljBvMyZ16GtEvvu70HXvZlnnrdunXRuHHjcnW6deumys2bN5c6LsPxHR93JDcKOnXqpAL5HTt2uFSnstcKaJFRwFufAQ9OspWy76q8PGDHNlvpY/YAnoE8EREREREFq4Bdmu7FF1/EH3/8gZycHPz555/q35JBfs6cOWouvNi/f78qnQXyIiYmBgkJCarHPDs7G7Vq1VLD6zMzMyutJ8fXr1+Pffv2qeR4rryW/bjUqYwM+5f53nbSy1+2p9+nwiOAxs1tpcN1VSovD6YbrgG2bQXap0D79Csgyo0bAQFA2kCG6Tu2BekL29AY2I7GwHbUP7ahMbAd9U8vbSgdqo7JvyXG8gq1zrzr/c1pezOQtj8DFi0416YL2GD+f//7H5YvX16yL8vTybJxktHe7syZM1X20EpALwG0PZi316msntQRUsfV13JWxxn5OhyNHz++wuz5PlNQBKSnu/z00G1bkbT9T6C4CNj+J06t+xnF7VOgJ/IBKTd17PPvSX/YhsbAdjQGtqP+sQ2Nge2of3ppw5deeqlcjjGvcDMzfWqrRLVlFVkQvyTw838FTTAvc9aFBOKSOV6Wf5Ol5KZMmYLHH38ceiU993FxcYHTMy/2hgHJya4/v1YtmNp1sPXMt+uApO7n6bJnXrLhyxSNQP6gpIqxDY2B7WgMbEf9YxsaA9tR//TShk8//bRKQO7YM1+207Jac+bdZWXPfECSYfKSXO7rr79WGeonTpyI/v37q+RnsbGx6jmVZTSXYfpCeuWFvY69nmNgXVEdx3oVvZazOhV9Pc5e069MJsCdDwsZhfD5ImDlCuCiS2DSWSBvJx+U8iEZyB+UVDm2oTGwHY2B7ah/bENjYDvqnx7aMCoqSm12XrtWT9eMt3Kd+YDPZH/DDTeoISf27PRNmzZV5cGDBysMsKVnPzExsSTIlkA6Pj6+0nr24453l6p6LWd1DE1+eNu2112PvNsyTvv7CoiIiIiIiMoJ3Ns9TtSpU0eVx48fV2W7du3UEHXZP3ToULnnb9y4UZX2JHZ2Xbt2LfW4o6KiImzZskUtT9e2bVuX6lT2WgEvPw/Yv8dWUnmZDOaJiIiIiHyCS9MZN5j/4YcfVNmqVStVytCOSy65RP37888/L/f8uXPnlqwNX3YtecfHHS1atEgtS9evXz8V0JetI6MCHDM3imPHjmHVqlVqBEDv3r2hGxLAjxoMTH3SVjKgJyIiIiIif7EPs/dkC0IBFcyvWbMGS5YsKbcUg/SWv/baa2qteQngZbi93bhx41QpifF27txZcvzHH3/E22+/reaojxo1qtT5Ro8erYbbf/nll5g/f37J8fT0dDzyyCMlWeYd9ejRQwXq8pxHH3205HhxcTHuvfdedY1jxoxR0wF0Y89fwK7tgMViK2WfiIiIiIjIH2TuvSe98+aACmuDM5u9BOMjRoxQw+llCbratWvjxIkTKpv9kSNHVE/57Nmz0aRJk5I60oM+duxYTJ8+HWeddRYuu+wyFBYWYunSpWp+/axZs1RA7ygpKQnvvfcehg4diiFDhqBv377qtSSDvsyxlxsEcqwsOZck4ZPXWrFiBVJSUrBu3Trs3r0bvXr1wmOPPQZdadEaaNUO2LHVVso+ERERERGRP3jayx7Cnnm/k6XnJkyYoObCb968WQ2dl956Cb7vv/9+FdRLAF7WK6+8ogLtDh06qCBeeuUlyF+5ciWuu+46p681ePBg9fjll1+OTZs2qWz5rVu3VjcLKlozsU2bNuq5w4cPV/P0FyxYoDI3Sob95cuX+3+JOXdFRgEz5wGP/J+tlH2jy83y9xUQEREREREZq2e+RYsWeOaZZzyqKwG2bO6QYfPffPONW3VkVIDcODAMCeCbtgiOQN4ezEcH2NKARERERETk+TrzIcG5znxwTi7wo+7du6vh+Wlpaf6+FCIiIiIiIo9JTCOxjcQ4XsEEePrtmQ8GMsdeku8FlNgAux4iIiIiIgp4qampasvKykJ8fHz1T8ieebcwmCeglhd+8PQuJxOI4ftAREREROQ3qmfek2H2VgQjDrMnEkyMR0REREREOsKeefJcQiLfPSIiIiIi8g6zyba5KG3zUaRtPgaLxgR4RO5JTDL2O5afB/y13VYSEREREVHNMv+dzd7FLfXshtg67Gysu6lLULYMe+bJcxmnjds7LwH8sOuBHX8CbTsA7y8InuX7iIiIiIj8wZ7N3pN6QYhz5ql6wbxR7d4J7NwGFBfbStknIiIiIqKa40avPMpuQSg4v2oKTkUFwNE9trIqLdsAbdoDoaG2Uva9SCvK8er5iIiIiIgouHCYPQUHCeDfGgMc2Q00aAnc+Urlz5ch9TK0fs33QO++Xh9irxXnwBQW49VzEhERERHpGofZu4U98z7WvXt3pKSkIC0tzdcvHdzS99l65a0WWyn7VZEAvnU7zpUnIiIiInJCYhqJbSTG8VoCPE+3IMSeeR9bt24d4uLifP2ylNwMqN/C1jMvpeyfzrS9L4X5wJE9QHxdIDyS7xURERERkQtSU1PVlpWVhfj4+Oq/Z+yZdwuDeQLiE4z/LoRFAHe/Cmz/BWjXAwgJsx0vLADeGAMc3gU0bAXc9xoDeiIiIiIify5N50m9IBScXzWVFm/Q5eWcBfTSKy+lnQy3l956GX4v5TEXht8TERERERH5GYN5Cm4y3F4S4plDbGW9Zv6+IiIiIiKi4GQfZu/JFoQ4zJ6CW3iEbWj9tl+A9j04xJ6IiIiIyF88TWZnDs4+agbzRJL0rkELnwXymqUQ1pwjMIUnwBQSzvefiIiIiEgwAZ5bGMyTZ/LzgJ3bgPoNuHSbm4F8/m/TYc05BHNMI0R2HcuAnoiIiIioJJj3oJc9hMPsiVwP5G+6Fti+FWiXAsz5kgG9i6y5x2DNPQJoVlXKfkitJvzOIyIiIiIit7Bnntz3105br3xxsa2U/U5d+E66wBxdD+boBrae+egGap+IiIiIiOSPZZNtc1Ha6r1IW7MfFqsWlG8fg3lyX+s2QJv2tp55KWWfXCJz5GVoveX0nwhJ7MAh9kREREREdjLE3o1h9ql9WqotK78I8Y/+L+jex+BM++dH3bt3R0pKCtLS0qBbkVG2ofXT39HfEPvoOPeeH59YIwG9OaYBA3kiIiIi0jWJaSS2kRjHK0x/98y7u5k4Z558YN26dYiLczOgDEQSwEuvvD2QP3UKSEqC4YL5BO8H80RERERERpCamqq2rKwsxMfH+7xnvoQndQwgOL9q8j4J5omIiIiIiMgnOGeeiIiIiIiIdJcAr4QndQyAwTzpX3YGUCvBt8PviYiIiIjIuzjM3i0M5kn/sjOrH8zHeGGODxEREREReY49827hnHkKLrlZ/r4CIiIiIiKqrGfek80NJ0+eRHJyMkwmE1q3bg29YjBPwSUvMIJ5U2iMvy+BiIiIiCgojR8/HidOnIDeMZgn8gNTGIN5IiIiIqJSPFlj3uxe0rzly5fj/fffxx133KH7N5/BPBEREREREfmf2cMh9mbXwtq8vDzcddddSElJwUMPPQS9YzDvY927d1ffPGlpab5+aSIiIiIiIq+RmEZiG4lx9NAz/3//93/YvXs33nrrLYSFhUHvmM3ex9atW4e4OIMsg5aQ6O8rICIiIiIiP0lNTVVbVlYW4uO9sDqU2fVe9lJcqLN582ZMmzYNI0aMwIUXXoi9e/dC7xjMU/WD+bw8YOtWoFEjICqK7ygREREREdWYgiILCoqsJftZeUWVPt9qtWL06NFISEjA1KlTDdMyATXMPjc3F1988QVGjRqFdu3aITIyEjExMejatSueeuopnDlzplydyZMnqyUFKtr+/e9/V/h6a9aswYABA5CUlITY2Fj06NEDH3zwQaXXePDgQXU3p2HDhur62rZtiyeffBL5+fkIShLIX9YPuO1WWyn7RERERERE7gqRzVTl9tyXfyB+xGclW5N7F1R62tdee02NkH7xxRdRu3Ztw7RLQPXMf/LJJyVZBTt06IBrrrlGDdlYu3atCpjnzJmDH374Qa0JWFbv3r2drhF4zjnnOH2tefPm4YYbblB3aS666CLUqVNHZTYcNmyYGoLx0ksvlavz119/oWfPnmoZg06dOqnhGevXr1c3GqSubBEREQgq27YBf/wBFBfbStk/+2zfvX5BPrBvJ1C7HhAR6bvXJSIiIiIi73JxmP1jQ7pg3LUdS/azcovQ5M55Tp+7f/9+PPHEE+jTpw+GDx8OIwmoYF6SENx555144IEHVDBvd+TIEQwcOBCbNm1Sj0nQX5YMm3C1cU6dOoWRI0fCYrGooH7QoEHq+LFjx3DBBReouRRXXXUV+vbtW6qenF8C+TFjxmD69OnqWHFxMYYOHYoFCxbgueeeUyMFdCcrA4hL8Kxu+/ZAx47A77/bStn3hewMIDwSePQ2YO8OoHlb4IUPKw/oiwqAY3uBuLpAiP4TXhARERERGYqLyewiIkLVVqpeBWROf2FhoUp6ZzQBNcxeesXffvvtUoG8aNCgQUn29/nz56vGqI53331X9fhfe+21JYG8qFevXskcCgnoHf3yyy9qWL6MCnCcZxEaGoo333xT3Yh49dVXVXCvy2DeE6dO2ebIL10GfPiRrfTVnPkzmcCBXcD+vwBLsa2U/coC+XcfAD6bYitln4iIiIiIAocLQ+wr3CqwaNEiREdH4+6771adtfbtxhtvVI8fOnSo5NjRo0ehJwHVM18ZmTcvCgoKcPLkSRXge2rx4sWqHDJkSLnHZASAzIVftmyZmgcv/3asc/XVV5cbSi83AWTI/YoVK7B69epyPfqGdfoUkJRkC+BTUnyf/K5JK6Bpa1vPvJSyX5Hj+4D0vYC12FYe3w+EeiHjJhERERERBbSMjAw1XdsZifnsj+ktD1pA9cxXRtYDFNIDLgnrypJAWobgyx2XKVOmYMOGDRWe67ffflNlt27dyj0WHh6u5sNLQ+7YscOlOo7HZb49+YgMqZeh9Y9Oq3qIfd1mQHJzwBxqK+s2ZTMREREREQXinHlPtgpomuZ027Nnj3q8VatWJceaN28OPdFNz7x9jvoVV1zhNMnchx9+WGp/4sSJGDx4MGbPnq0y1dvJ8PrMzEz178aNGzt9LTkuie327duHLl26lCROqKqOkDpV3RWSpHt28rX4PWmepsl6DdWr5+k5PGV/vbBwW6+8lJW9vsyRH/kysGs90OpcWEPC1A+sY1uQvkjbsQ31j+1oDGxH/WMbGgPbUf/00oYyWlo2xxjLG6wmE6wuzJl3Vi8Y6SKY//rrrzFz5kzVK//000+Xekwy2Evm+SuvvBLNmjXD6dOnsXLlSjzyyCMquZ0kuZPkdHaOy9vJ3AlnZDk8kZ2dXa6eO3WckWt0NH78eDz00EPwq8wsICzd/XrZZ4D0v+udcfi3L2RkAeb0f64/xMXXDk0ETmeqD0i5qSMflmYXMmZS4GEbGgPb0RjYjvrHNjQGtqP+6aUNJf4qm2PMG6xms9o8qReMAj6Y37ZtG2699Vb1DS3rAtrnztvJY2WD6ptvvhkXX3wxOnfurNat/+mnn3D++ecjEEjPfVxcXGD1zBflAU6W+6vSmex/6slNDE/O4Slr/j+vZ3H4d1VCi4CkZPVBaTKZULdu3YD+oKSKsQ2Nge1oDGxH/WMbGgPbUf/00obSwSrLvTn2zJfttPSE9Mp71DNvZs98wJHMgjKsXnrbx40bh7Fjx7pcVxLkjRgxQt01WrJkSUkw7zjkPjc3t1RgbZeTk6PKWrVqlRyz15M6zjir40xCQoLT1/QrGZbiyYeFYz1Pz+EpT1/b4bnyQSkfkoH8QUmVYxsaA9vRGNiO+sc2NAa2o/7poQ2joqLUZhfI11oRmR8vHcZ6FrDvuqwF379/f9WTbQ/K3dWmTZuSdertJJCOj7dlMT948KDTevbjjneXmjZt6nYdqiEF+bZl6KR0V94/0yyIiIiIiChwWELMHm/BKCC/apmfLnPgt27dqtaBnzFjhrpD5S7p0Xecz25nH6q/cePGcnWKioqwZcsWtSRd27ZtXarjeNyeMI9qiATw/zcSePVRW+luQJ9vG0FBRERERESBxT7M3pMtGAVcMC9ZEa+99lr88ssvuPzyyzFnzhyEhIS4fR4ZMmFPfFd2OTlZS17MnTu3XL1FixapZen69etXssa8Y52FCxeWytwojh07hlWrViExMRG9e/eGrkgwvHenZ73c/nBoD3DgL8BSbCtl3x2FzqdJ+JpWxJsKRERERESl/kY2mz3eglFAfdWSef6mm25Sa8ZfeOGFmD9/vlr3vSLHjx9HWlpauQzy0rN/zz334Oeff0b9+vVV776j0aNHq+H2X375pXoNu/T0dJUF355l3lGPHj1UoC7PefTRR0uOFxcX495771U9+mPGjFEZ93VDAvgHbgKmjLWV/groc2xLBbqkUQugSWsgJNRWyr47CgIjmAeDeSIiIiKiUtgz7+Ns9tKLLUPgvZGR/fXXXy/pTa9Tp44Kkp2R+fPyuCSdu++++/Dvf/8b3bt3V0nvJMCXIe8nT55Uyeak973scnJJSUl47733MHToUAwZMgR9+/ZF7dq1sWzZMrUOvCTbk2NlzZo1Cz179lRr3ssNh5SUFKxbtw67d+9Gr1698Nhjj0FX9v1l65UvLraVst+2k2t18/KAP7cCDRtJBozqXUdOFhBjy2NQpYhI4Mn3gN/WAl172faJiIiIiIiCjNvB/Pfff696tNesWaPmtOdJUPf3+usdOnRQQe11113nNBh2dY67cFwbvqzJkyerYF4CcOkll6XnduzYgbVr16oh+S1atMDw4cPx4IMPolGjRk7PMXjwYLUe/ZQpU1T9wsJCFZzLzYFhw4ZVmFBv06ZNmDRpksqQL9coifEmTpyICRMm+H+JOXc1aw00bwPs2W4rZd8V0uZX9gf+2AJ07AR8863cIYHPSADfpNU/gXyteDfqlr6x4y9acS6Cc2YPEREREZFz7s5/nzFvM2bO2wyLVd9Z6T1l0lzIxy9DyN9++228/PLL2Lt3r+rZlnnoLVu2VPPE5RQSiO/Zs0f1iksmesnqLkPV77rrLn0NPa8hsvaiZNHPzMwMrKXpZGj9ulVA9wtd7+X+dRNweT+gsBCQaRD/Wwacdbbn15B+AEhu4l6dI/uABh6sHLB7I9Cym1rDU6ZMJCcn+2UpDcupbQhJau/z1zUSf7cheQfb0RjYjvrHNjQGtqP+6bUNqxvr2OvvWX434mLc7yDNyilAi0vfCrxYKxB65lu3bq16rqXHWoaml00oV9aGDRvw+eef49lnn1VD4uUGAAUoCeClV96d4ert2gMdUmw981LKvj9lZQBxCf69BiIiIiIiqhbN5Flmes2Dlc+CJpiXIeQybN3VYeTnnHOO2p566ik1z5z+IXP7ZSpAamqq2nRJ5sjL0PrlS4FLL6v+nPnqynYxmC8qAE4eApp0BEI4WoSIiIiIqDokGblsksjcGywms9o8qReMXArmZai8JyQTvad1jUoS5hli6IcE8NIr7+9A3lUSyM8eDxzbBfz6P+D2F/19RUREREREumbvoLQPkyff8ugWxqeffqqy2BPpxon9QPpeWf/QVsq+n2iWQmi56aokIiIiIiIbLk3ng2Be1oKX9dtHjRqF7777zpNTENkU5gOHd9vKmhRfDyp9vLXYVsq+H0gAX7zhP7Du+FyVDOiJiIiIiGwYzPsgmF+9ejVuueUWLFy4EP369VPLs8la71u2bPHkdBSsJIB/+R5g5hO20p2APtbNYTxZ6UB4KBAZYSuz0+EPWs5RaDmHAc2qStknIiIiIiJAM5s93oKRR1+1rCUviQ4OHz6s1pzv3bs3Xn/9dXTt2hVnnXUWpk2bhiNHjnj/aslYju619crL0HcpZd9VtdzMXl+7CVC3ORAaZiuT3FwKz0tMMfUB2STjZkx92z4REREREbFn3k3VuoURGhqKq666CnPmzMHRo0cxe/Zs1K5dG4888ojqrb/sssvw0UcfqWXtiMqp3xxo2BIICbGVsl9TwiKAm18ALrnTVsq+nxRGhKIgPESVREREREREnvDaeAQZYv/LL7/g999/h6ZpaN++PU6ePInbb78drVq1UkPzKUB5ukZ7Zmb1Xjc8Ehj3JjBqiq2U/ZokAXxiQ78G8ta8Y7DmpUMzm1Qp+0REREREJD3zZo+3YFStr3rHjh148skn0aZNGzXU/rPPPsPNN9+M9evXq6B+48aNKsBPSkrC3Xff7b2rpsAI5rOqGcwLCeClV76mA/kAYY6qB3O0DLM3q1L2ibxNK8rhm0pERES6YzWZPN6CkUfjfKdPn46PP/4YGzZsQEREBK6++mq88soruOKKKxAiQ6YdnHvuuRg3bpzKfE/kdQX5wN6dQJ36QETg3xAwhYQjpuP9KDr2M8Lqnaf2ibxNK86FKSyGbywRERHpMpu9J/V8ISMjAwsWLMCqVauwb98+5Obmom7dujj77LNx+eWXq9xyAd8z/+CDD6og/q233lKJ7mTd+YEDB5YL5B0D+okTJ1b3Wg2he/fuSElJUQkEdS/ezYzyNRHIj78FeOZBWyn7OiABfEhkXQbyVCNkuUNr7hEue0hEREQ1TmIaiW0kxvEGzcMh9loND7OXxO+jR49GgwYNMGXKFOTl5anE75deeikaN26slmuXfHHyXkhsHNA987t27UKLFi1cfn7Hjh3VRsC6desQFxdnjLci3sPh+d6yf5etV95SbCtlvw2/zyi4A/m831+FNecwzDENEdV5DG8aERERUY1JTU1VW1ZWFuL93dFXg6TnfdiwYWpkugTszkiA/8UXX6gR6wcOHMBDDz2EgAzm3QnkiWpM01ZA8zbA7u22Uvb9IS8biKrln9cmKptgMfcooFlVKfshsf5ZhpGIiIjIXRaYYHFj/vsnH61Tm9VqrdE3e+vWrWrVtspERUXhpptuUpskgvcFl4P5l19+2a0Ty5B76YGWOxfnnXeeJ9dGVDmZIz/tY2D9KuDcC12bMx9ZA/OI8xnMU2AlWFQ980ywSERERLqcM+/6kPkbbz9PbWey83H+Wc/X2HVVFchX9/k1Hsx7OkzAZDKpZeq++uortUQdkVdJAC+98q4mv0tsEBgNEBrl7ysgA5J8DDK03pKxDSEJ7TnEnoiIiHRFM5nU5kk9X5I59LL0enp6erlRAWPGjPHZdbgczO/Zs8etE8ta89nZ2WppOrkRIF/U4sWLPblGMroYH+YQiAqMfAWmsGh/XwIZOKA3RzdgIE9ERES6E+jZ7MXs2bNx1113ITw8XPXAS+e1nfw7IIP5Zs2aefQCnTt3xrFjx/Dcc895VJ8CVF4esO1PoEFDmSBSvXPFGDdZRkVMoQzmiYiIiIj0ZuLEiZg0aRIee+wxmGs4i35VauTV33nnHVx55ZUl+5dccgmGDBlSEy9F/grkr70CuHO4rZR9cgvXAKeaxJtFREREpEdWk9njzVdkbfkbb7zR74G8x9nsJTivbHj977//juLi4pJj559/vtrIIHZut/XKSxtLKftdzvL3VRHR33iziIiIiPRID8PsR40ahc8//xz//ve/octgXib5O84NsAfxMpx+586dKov9xx9/7K1rpEDTph3QvgOw9Q9bKftERERERETVYDWZ1OZJPV+R6eNXXXUVlixZoqaUh4WFVWsVOJ8H899//32Fj/3xxx/o378/1q1bh4EDB1bn2gype/fuatm+1NRUtemSzJH/cgnw3XLg4kurP2dez4oKgJP7gdjaQFiEv6+GiIiIiMhn0tLS1GaxWLxyPlmWzuLB8HWrD4e8SzD/v//9D+3a2To0yybA8yWPgvnKdOzYEffdd5+6IzF58mRvn1735CaHjFzQPQngpVc+2AP5zx8Dju8B6rYA/vUcA3oiIiIiChr2DsqsrCzExwdHUutp06bhvffew/Dhw/19KTWTAE8asqioqCZOTVRerQT/vCunDtp65a0WWyn7RERERERUrWH2nmy+EhERgd69eyMQeD2YLywsVPPlb7nlFm+fmsi5OD8F80mNgdpNAXOIrZR9IiIiIiIybDA/duxYvPbaawgEHg2zHzlypNPj2dnZ+PHHH5GRkYFWrVqVep7MH5g5c6bnV0oUaGSOvAyt37oMSOnHIfZERERERNWgmc1q86Ser/zyyy9YsWIFFi1apKaYl02AN3/+/MAO5uXiK5rcL19M3bp1sWrVqlLHfZ0MgMhnAX1iQwbyRERERERBkM0+ISEBgwYNQiDwKJjfu3ev96+EiKqn4AwQEct3kYiIiIiohsyaNQuBwnfjEYioQlrhmeq/O944BxERERGRn7g7T37ee2twe++puOuyV/zeZjt27MA111wTeD3zMg++Z8+eHr1AdeoSBY3c40A4e9WJiIiIKHhZ4d4w+2tHX6i2nKx8XNPiMfhCixYtnE4hP336NMLDwxFwwfwll1yC888/H/fccw+uuuoqREdHV/r8M2fO4KuvvsJbb72F9evXIzc311vXSxRYigts68w3TAFCIzw/TxF/RoiIiIgouFlNZrV5Us9XHnjggVL7FosFu3btwkcffYS0tDQEXDAvQwaeeuop3HbbbSrB3XnnnYdu3bqpuxKJiYnQNE3didizZ48K3iXDX3FxMW6//Xa1TB39o3v37ggJCUFqaqradC0xEQj2QH7+47ZgftdaYNAz1QvoiYiIiIh0RIJX2SSg9QarybNkdlYf5lqXpekq6gB/8sknMWTIkMAK5ps0aYIZM2bgueeew4cffogvv/wSb7zxBvLy8ko9LyoqCueeey6mTJmiAn/Jak+lrVu3DnFxccZ4WxKTENROHQRO7Qc0q62U/eRW/r4qIiIiIiKfsHdQZmVlIT4+Pqjf9W7dumH37t2Bm82+Tp06ePDBB9UmPe/79+/HyZMn1WO1a9dG06ZNERrqUYJ8Iv1JagwkNQVO7LGVsk9ERERERB6xmk2wmD3omTf7fxl0GZHuy1554fHkAgnaW7ZsqYaNyyb/rm4gL3Prv/jiC4waNQrt2rVDZGQkYmJi0LVrVzXMX+biV2T27Nno0aMHYmNjkZSUhAEDBmDt2rWVvt6aNWvU8+T5Uk/qf/DBB5XWOXjwIEaMGIGGDRuq62vbtq0aTpGfn+/x1006JUPqZWj9haOrP8S+qPQoF7cVFwKZB20lEREREZGO58x7svnK2WefrXrhHbdGjRqpmPC3334rdbymBVQ3+ieffII77rhD/btDhw4qtb8M2ZCgXN6cOXPm4IcffkBycnK5JATTp09Xw/z79++vAuulS5fi22+/xdy5c3HdddeVe6158+bhhhtugNVqxUUXXaRGHSxfvhzDhg3D5s2b8dJLL5Wr89dff6nM/CdOnECnTp1w4YUXqhwBcqNB6soWEcE500FFAviEhtUK5DVLIbTsQ4ClC0whHmTAlAB++RQgcz8Q3xS49Akg1LeZNImIiIiIqkszmdTmST1fcRZb+ktABfOSXO/OO+9UwbkE83ZHjhzBwIEDsWnTJvWYBP12y5YtU4G8DPOXZfDatGmjjsu/+/btq3rRpUxISCipc+rUKYwcOVIlapCgftCgQer4sWPHcMEFF2DatGkqa7/UczR8+HAVyI8ZM0a9ppDpBkOHDsWCBQtUToHJkyfX+PtExqEC+Z+nAlkHoJ38HTjvEfcD+qxDtl55q9VWyn5Si5q6ZCIiIiKimluaDh4Ms4fvgnnpZA4UvhuP4ALpFX/77bdLBfKiQYMGJWn+58+fj8LCf4YSv/zyy6p84oknSgJ5IT3od999NzIyMjBz5sxS53v33XdVj/+1115bEsiLevXqYerUqerfEtA7kgz9MixfRgXYnyNkasGbb76pbkS8+uqrKrinIMton3nEVnoi6wBMp/fAVFyoStl3W1wjIL4xYDbbStknIiIiIiKvyMnJqdHnGyKYr4zMmxcFBQUlSfckm/6KFSvUv50lG7AfW7hwYanjixcvrrCOjACQufDS4+84D95e5+qrry43lF5uAsiQe1meb/Xq1dX+WskFZzL9/zZJAP/VJODHWbbSk4Be0yrfd4UMqZeh9b3u4xB7IiIiItItWZbO060mtW7dGs8//7waMV4RWa5dpnpfeeWVqpM36IbZV8ae5l96wCVhndi+fbsK7mUJvMaNy2cStycdkDnwjiQxgePjjsLDw9V8eJkLv2PHDnTp0qXKOvbjcmNBXqvs8PyAl3kaiE/UXzAf6+flL04fsi1JZ7XYStmv29KtU5jim0KLbw5k7Qfimqp9j0hAL73ynCtPRERERDrlaTI7aw0nwPv+++8xYcIENaVaOpllOXZ7QnTp0N26daua5i2jth977DHcdddd8AWPvuoXXngBhw4dgi/Z56hfccUVJT3jsjSecBbIC8mEL3Pl5Q3Ozs5Wx2R4fWZmZqX17Mf37dtXcqyq13JWRzeyMvx9BfqU2Mi2JJ05xFbKvrtCwmHq+SjQaqCt9CQBHhERERGRAQRqz3y7du1UrjXp7JV8aRILS6L1GTNmqEBfstnLv/fu3Yt7770XISEhCNie+ccff1xtkgX+tttuU8PVa9WqhZry9ddfq3nv0iv/9NNPlxy3L1UXHR1dYV0J6GXevATzco2Oy9tVVE/qCPsNAFdey1kdZ+RaJIO+ndyY8HsGfBna7XBNulDNa5Y2kKEwjm3hNnMYcNVkYPv3QLu+tn1PzifXYtVgkrqmalyPVYftWA1eaUPyO7ajMbAd9Y9taAxsR/3TSxvK6GjZ7KTD1BssJpPaPKnnC02bNsX48ePVFgg8Cual91kyyn/88cdqTfj77rtPzSWXwF56zr15J2Lbtm249dZb1Tf1iy++WDJ3Xq+aNWtWal++ER566CH4VWY2EJ4OXcnIAkyeX7N8QMoIDfm+MkviuOoIqw+c8nAOv6UISVvfQWjOERQf3IhTKXcCIWGenSsvA8jzXSZPf/NqG5LfsB2Nge2of2xDY2A76p9e2lCW8S6bMJx0EszLMIKHH35YbVu2bFFBvawB/9lnn6n12mX9dgnAzzvvvGpdnAxfkJsDMkx+3LhxGDt2bKnHY2NjVZmbm1tlJkH7yAF7HXu9uLi4Kuu48lrO6lR0I8TxNQOiZ74wF0hOhq5oBdW6ZvmgNJlMKt9CtT8oI6xAvIfXkrEPpny5KWFFWH46kqOKgQQPs9Fna0AtnbVjNXi1Dclv2I7GwHbUP7ahMbAd9U8vbSijpWU1Mcee+bKdlp5wd8j8t2+twNK3VsBqCeyRDAGbAE+Sxcn66rKtWrUKr7zyCt544w21tWrVCrfffrtaO16WdHOHrAXfv39/FfzKWvFy98fZMAdx8ODBCgNsGdaemJhYEmRLIB0fH6/ueEm9lJSUcvXs53P8hpTXknXuK3otZ3WckTn8zm4g+JX8wATwh0VNXbN8UMqHZLU/KM3VuJb4RkCtRtAy98NUqxFMsu/puapzHTrltTYkv2I7GgPbUf/YhsbAdtQ/PbRhVFSU2uy8da1WmNXmqn5391NbblYe7ky+F8HGK++6LOH23//+V62/LsvAyTB7Sckvgb7ctZGgfsGCBS6fT+anS33JCijrwEsyAfmmdpaIQHq1jx8/7jQh38aNG1Vpz0hvZx+qb3/cUVFRkRptIJkJ27Zt61Kdyl6LakBhPnBwl63UO0l4d+G/gXZX2crqJMAL/2fUCRERERGR7phM0DzY4KM584YJ5mUex7fffothw4apddZvvvlmHD58WAX00ku9aNEizJ8/X2X0O+ecc1xOEiCJFK699lr88ssvuPzyy9Xw/Yrm4MvdoEsuuUT9+/PPPy/3uGQYFDKfv+xa8o6PO5LrlpsT/fr1UwF92Tpys8Ix2YM4duyYGpUgIwB69+7t0tdJHpIA/pnRQNq/baVRAvq4xtXPZB/BYJ6IiIiI9CtQs9kbKph/8MEH1bx56T1fvnw57r77bvz+++/YsGEDHnjggVJD6hs0aIDRo0eroL4qFosFN910k1qv/cILL1Q3A2Td98rIXHoxZcoU7Ny5s+S4rPP39ttvq2HtkqTPkVyPDHX/8ssv1WvYpaen45FHHlH/LnvzoUePHipQl+c8+uijJceLi4vV8gPSoz9mzBiVcV9X8vOAPTtspR4c3mPrlZe13aWUfQMwRSX5+xKIiIiIiMgFMpVbOrY/+ugjfPDBB6W2gJ8zL8Per7/+ejUfXnqwnQ2Bd3TBBRdg1qxZVZ739ddfLxmOL4n0JEh2RubPy+NCXl8S48k69GeddRYuu+wyFBYWYunSpWr0gLyuBPSOkpKS8N5776k1AmVZvb59+6J27dpYtmyZahi5QSDHypJz9ezZU72W3HCQ+fbr1q3D7t270atXLzz22GPQFQng778R2LUNaNUeeO2/QOQ/c18CUsMWQONWwP6dtlL2jSDMtrQhEREREVGwssKkNk/q+YqM1L7lllvU1HDpIHaMheXfEiMHdDAvw8rt66q7onnz5mqrimStt6tsjv3kyZNLgnkhSfckkJebARLES2++BPkTJ05UQbYzgwcPxsqVK1WP/k8//aRuAEhwLsvsydQBZ9q0aaOS4E2aNAlLlixR1yiJ8eR1JkyY4P+s9O7atwvYvQOwFNtK2W/XCQEtPBJ4/F1g849Al562fX/j8HYiIiIiomqzDZl3f/C41YfD7GUE98iRI/Hss88iOjoa/uRRMN+5c2cVQF9zzTVOH5d55zLkXHqs3SFBumyeGD58uNrcIcPmv/nmG7fqNGnSxKVRBrrQrBXQsq2tZ15K2dcDCeClVz4QAnkRWflyhEREREREZIye+UOHDqlY19+BvMdz5mX+uwwrqIg8JkvKUYCTIfUytH7yq/oYYk9ERERERIZVkwnwXn75ZbVSmoy2lqXKZVS1LCsuw+Il/5urJEn7+vXroet15iubJy/zyMvOUyeb7t27q+z8qampavM7CeBbtGUgT0REREREbklLS1ObJDIPdM8++yxycnLUUuIy0lz88ccf+PDDD9Uy65IY/aqrrnJa96uvviq1ytnDDz+sllGX85RNgF7R6HW/BvOS9E02eyAvWesff/zxcs/LzMxUSeRkqTpyfqNDEiVQNeVmG+st1DR/XwERERERkVvsHZRZWVmqt7u6LDCpzZN6VZGVzGTJdMflx8Ubb7yhvgZZ8UyWWA8NLR8iX3fddeWOPfXUU+WOSZzsyxsbLgfzstxcx44dS4bZy9J0spW9eEmMJ29SRZnoibzCaME8EREREVGQ83TNeKsLdSRfmjMSt8oQ/F27dqnedum5L3d+qxWByOVgXtZ/l01cfPHFeOKJJ3DppZfW5LURERERERFRkNBgUpsn9arDPlReVkWriqwlf8MNN5RbyUxWR5Ph+r5cms6jBHjfffcdA3nynpxMvptEREREREFOM5nV0nTubpoHy9nZyZz57du3q8R4slVlxIgRamp5WdnZ2eqxgOuZl/XYxUUXXVRqvyr25xNVKjcLiHFzjk00l4MjIiIiIgpGxQVFarPLz8pzue6LL76oEt9JMrw///xT/bthw4aYM2eOSlReFU3TnCaDl/n23sgb4PVgvm/fvuqC8/Ly1NAD+35VX6AeshoSgDgdrjwQY6BgvrgQyDwERCUBoVUP7SEiIiIiCuZ15r99bgH+99TnHr3G//73PyxfvrxkX5ank6HzkvetMmeffbaKcWWT6eaOifIk7t2zZw+uuOIKBFwwL8PqHecQ2PfJIOIT/X0FwUsC+R+eBTIOAAlNgD4TGNATERERUVByNZi/5LHBuGjcNaV65p9ueqdLr7Fs2TJVygpssr68ZKXv06cPpkyZ4nS1trIZ7X/99Ve11nxsbGzJYxInN2/eHIMHD0bABfPyxVW2TxSscnNzER0dXVK6LfuwrVdes9pK2U9sXhOXSkRERERkiGDeHBGO8Ih/RrS6UqeshIQEXHjhhfj666/Rs2dPTJw4Ef3790f37t2dPv/JJ59UpQTtkgCv7BJ3/uB5pgAndu/ereYdEAUDCeDXrVunckhIKftuq9UQiG8ESNIOKWWfiIiIiCgIWWSqtodbdTLZS3AuU8UXLlxY5fOHDRsWEIG8x8H8q6++ihtvvLHUMcncJ9n/OnXqhHPPPRfp6eneukZDkTs9KSkpSEtL8/el6FdhPnBot630I+mJlzkzsu6klB71zMsceRlaf969HGJPRERERLoiMY3ENhX1ZutFnTp1VHn8+PEqn5uYmIikpKRyW+3atdGoUSM1in3WrFmBG8y/++67qFevXqkkAu+//z7uvPNOvPbaa6qH/v/+7/+8eZ2GIT24W7duRWpqqr8vJTBIQH5kj+uBuTzvhbuAtyfYSj8G9NITL3fwzGazKj3qmbcH9NIrz+R3RERERKQjEtNIbCMxjjeH2XuyVccPP/ygylatWlX53EmTJqm//wcOHKhiXtnk33JM3o+2bdvinnvuwYwZMxAQc+bL2rdvHzp06FCy/9lnn6FFixZ488031f7Ro0fVen1ElZJA/NX7gMO7gIatgDGvA+FVDFk5shc4tEtSRtpK2W/W3i9vtPTEy13Ias2ZJyIiIiIixQqz2txlraLOmjVr1DrwMidegm67oqIivPXWWyp2jYqKUsPtq7J69WqVLO/uu+8udfztt9/Gt99+i3nz5qFLly5qNPsdd9wReD3z0gvpSC76yiuvLNmXpAAS0BNV6tg+4OgewGqxlbJflQbNgUatAFkDUkrZ9yN7AM9AnoiIiIioejSYPN4qs3PnThWvyuhyWT7ulltuURnpZVm6MWPGqGz0s2fPRpMmTVAVGZXer1+/csdluTp5TAwYMECNVq9pHgXzMnRgwYIF6t9ywYcPHy4VzB88eFBlBySqVL1mQP0WgDnEVsp+VaTn/tG3gbuetZVV9eQTEREREZEu1NQw+z59+mDChAlo164dNm/ejM8//1z11stc9/vvv18tUTd06FCXrlHqOEuUJ8fkMZGTk4NatWohIIfZP/TQQ7j55pvV5H+5UBlyL3c27FasWIGzzjrLm9dJRiSBuAyt3/YL0L6H64G5PK9RSwby3lwij4iIiIjIoFq0aIFnnnnGK+eSJexkTvx3332HHj16qGOSM0CWuJMh+2Lp0qU+Wc7do2BeMtlLtj65YOmBv/feexEaajvVqVOn1B2J2267zdvXSkYkgXmDFgzMw2OrvUSeZNSXKTD2efxERERERHqieZjMTqtmAjx3yDx4yeD/+uuvY/78+eqY9PhLEr1evXqp/fHjx/vkWjwK5sVll12mtrIkkLd/UUTkoohYryyRJwk9GMgTERERkR55mpne6sNgXvTu3Vtt/uZxME9EgcHZEnkM6ImIiIhIbyxqM3lUz5ekE+2vv/5Cenq6+rejiy66KLCDeQkY3nnnHcycOVNl6Tt9+nS550hPYXFxsTeukYgqwSXyiIiIiMgIXMlMX1E9X/npp59U/jhZrr3sKm8SA1tkCe1ADuYfeeQRvPzyyyrJ3a233qoS4RGR/3CJvOBQbMlDaEiUvy+DiIiIKGjdfffdOPfcc7F48WI0aNBABfD+4lEw//7772Pw4MH47LPPvH9FBifJyUJCQpCamqo2IiJXWayuBfMWSy5CQpgEkYiIiGpWWlqa2rzVG+3unPmNaV9hY9pCWC2lh7rXJFmzfu7cuWjdujX8zaNgPi8vD/369fP+1QQByToeFxfn78vQv5h4f18BkU9ZrUXILzqOsJBaMJvDKn1uUcEphHBFAyIiIqph9g7KrKwsxMdX/+9zi2ZSm6u63nut2gqycvBawvXwhfPOO0/Nl9dtMH/ppZeqoPTOO+/0/hVR8In24OZGLIN5Cq5A/q/0j5FflI7IsGS0Tr6lwoBenluQfxDhkfWqDPqJiIiIAokestnff//9aum5o0ePonPnzggLK/33VpcuXQI7mH/jjTdw+eWX49lnn8Vdd92l1pwn8hh72YkqlV98UvXKa5pVlbIfHV7faSB/aP+7KMo7gqysTWjUdDQDeiIiItINPSTAGzx4sCpHjhxZckzmzUsyPF0kwGvXrp1KwT9x4kS1RUZGqnngjuQLyczM9NZ1EpVyqtCKpHAz3xUKCpGhtREZVvfvnvm6at+ZwvzDMGXsRaTVAmvBXhQmH0ZkdDOfXy8RERGRUe3ZsweBItTTuxH+zNpHdLpQQ1I43wcKDjJcXobWZ+fvRq3IlhX2tpusgPnvJVKklH0iIiIivbDCrDZP6vlKs2bN9B3Mz5492/tXQkREFZIAXnrlK5sHHx7dEGFRjVCcdwShUQ3UPhEREZFeaJoJVjcS4DnW86UPP/wQb731luql//HHH1WA/8orr6BFixa49tprfXYdHKdMupNn0fBnlkWVRMEkxFz5snQmcxjqtL0XsY2vVaXsExEREemFBSaPN1958803MW7cOAwYMAAZGRklc+QTEhJUQO9LHgfz+/fvx913363mzycmJmLlypXq+IkTJzBmzBhs2rTJm9dJpEgAf8XKbAz/JUeVDOgpmLiyxrwE8OExjRnIExERke5ID7unm6+89tprmDFjBh5//PFSeePOPfdc/P777wj4YfZbt27FhRdeqJLg2dfZKy4uVo/VqVMHq1evRk5ODmbOnOnt66Ugtz3bonrlizWoUvbPSvDo25jIsMLCucIIERERUU2QofVnn312ueMREREqBg74nvlHHnlEDSPYsWMHPvroI5WG39HAgQOxatUqb12joXTv3h0pKSlIS0vz96XoUrtaIegQF4JQE1Qp+0RUmjk0mm8JERER1TiJaSS2kRjHm+vMe7L5isyL//XXX8sdX7JkCTp06ABf8qhLU4bUT5o0CXXr1sXJkyfLPd60aVMcOnTIG9dnOOvWrUNcXJy/L0O3okJMWHJRLSw/VoRL64WpfSIiIiIi8r3U1FS1ZWVlIT4+vtrns2gmtXlSz1dkvrx8zfn5+apT+5dffsGcOXPw3HPP4d1330XAB/MyvD46uuKen+PHj6thBkQ1QQJ46ZVnIE9EREREZBye9rJbfdgzP3r0aERFReGJJ55Abm4ubr75ZjRs2BDTp0/HjTfeiIAfZt+tWzcsXrzY6WMyd/6///0vzj//fI8uaMOGDXj++ecxaNAgNG7cWK1nX9ma9pMnTy55jrPt3//+d4V116xZo7IQJiUlITY2Fj169MAHH3xQ6fUdPHgQI0aMUA0WGRmJtm3b4sknn1R3Zsh3EsPZI09EREREZCR6SIAnbrnlFuzcuRNnzpzB0aNHVYw4atQo+JpHPfOPPfYYrrrqKtxzzz0ldx+OHTuGZcuW4dlnn8Wff/6J119/3aMLevrpp/Hll1+6Xa93795o3bp1uePnnHOO0+fPmzcPN9xwgxplcNFFF6nEfcuXL8ewYcOwefNmvPTSS+XqSKK/nj17qoz9nTp1UkkA169fj6eeekrVlS2YRiRkWi2IN9vmrGdZixFn9l0iuqRwrqpIwaVQy0e4KdLfl0FEREREf5PR6pWNWK9pHkVfV155JWbPno2xY8finXfeUcduvfVWNWdA5oNL77YEyJ6QYLlLly4qiYJszZs3R0FBgUvDHYYPH+7Sa5w6dQojR45UawJKUC+jAOw3JC644AJMmzZN3azo27dvqXpyfvvSezKMwj4SYejQoViwYIGaJyEjBYJFlkMwn61ZEOfZtxMRuaBQK2AwT0RERIbm7jD7bW/OU5tmsdbodUn2+spGizvauHEjfMXj6Ou2225TQfC3336reqylh7tVq1a4/PLLUatWLY8v6NFHH0VNk8QEkqTh2muvLQnkRb169TB16lR1TAJ6x2BeEhvIsPzk5GT1HLvQ0FC8+eabWLRoEV599VU1d0KOGV2+ZsWeogLUDQlFpIm95EQ1yaIVI8t6GlGmGISYjP/5QkRERMHJqpnU5qq2dw9RW2FWDj6t26/Gruu6665DIKrWX4UxMTG4/vrroTf2+f5Dhgwp95gsqydz4WXKgMyDl3871rn66qvLDaWXmwAy5H7FihVYvXp1uR59Iwby9508gF3FBWiVE4HXazfx9yURGTqQX52/EFnWU4gzJ+GCyKsZ0BMREZEhSSDvSWZ6aw3PmZccaYYJ5qUnfunSpdi1axeys7NVT7zMV7/ssstU77w/SCAt6/1JAC6J82QqQEXz5X/77beSRH5lhYeHq/nwMhd+x44dash/VXXsx+UaZL690YP5fcWF2FNcCIsGVe4sykc2ilDHHIYI9tITeVW2NQPZ1tPQYFWl7CeE1OG7TERERIajqc3kUT1fysjIwNy5c1U8/PDDD6uE6jK8Xjp5GzVqFJjBvGTru+OOO/D555+rYfVlmc1mlRDv7bffVr32vvThhx+W2p84cSIGDx6s5vZLpno7GV6fmZmp/i1BvzNyXIL5ffv2lQTz+/fvr7KOkDpVNbzjeye9/HpLmtfUHIoWIeHYZSlAs5AwvJ13GPus+WgREokXYprrIqCXNpAcD86+j0kfgqUNYxCHWqZEZGknVSn7Rvqag6UdjY7tqH9sQ2NgO+qfXtpQcpo55jWTGCtYbN68Gf369UN8fDz27t2r4mMJ5ufPn69ixqpWR/NLMC/fVNdccw2+//579O/fX82Zlx5sCZQlyN+yZYu68E8++UQlkpOee1+QEQGSeV564ps1a4bTp09j5cqVeOSRR1RyO0lyJ8np7ORa7SrKPGi/ESGjDsrWc6eOM3KNjsaPH4+HHnoIejNRC8cWKxAHM6ZazsACDXuK8/HbiSNoroUh0MkHpNzUke9ruQlF+hNMbdgK5+CoaSfqa21wEqdgJMHUjkbGdtQ/tqExsB31Ty9tKPGX5Bjz95x5Xw2zdzRu3DiVGF3yqDnmipMlz2XNeV9yOZiXgFgCeVkDXgLlsrp27arW25PHH3/8cXzxxRc+SRQgWfTLBtXyJl588cXo3Lmzuo6ffvrJ43XvvU167iXjv5575u1MxYUqAV6LnALssdh65rvGN9BNz7xkpKxbt25Af1BSxYKlDWXO/IacL3DGehLF5pM4J+Y6Q82ZD5Z2NDq2o/6xDY2B7ah/emlDWU5cEn879syX7bT0hMyXN3sQmFt8GMyvW7dOjUQvS4bXy5rzvuTyX4Rz5sxRAbuzQN7Rv//9b/z3v/9VPfT+zPrXoEEDjBgxQt01WrJkSUkw7zjkPjc3t1RgbZeTk6NKxzst9npSxxlndZxJSEhw+pp6FB8ahihzCF6s1RIbirJxTlgtXQTydvJBKR+SgfxBSZULhjY8U5yJHOspNWdeyjwtE3EhdWEkwdCOwYDtqH9sQ2NgO+qfHtowKipKbXbeuiQxKFMAAERuSURBVFarZts8qecr0hHrbFqB5FuTmzC+5PK7LhP6JZO7K2Q4/oYNG+Bvbdq0UeWRI0dKjkkgLfMbxMGDB53Wsx93vLvUtGlTt+sYnX2NeQngm4VE6iqQJ9KLmJBExIbUhhkhqpR9IiIiIiPSNJPHm69IrPvUU0+hqKio5OaLzJWXJdYlZ5svuRx9paenuxyoyvPk+f4m8+dF2WR8MsLAfoOiLGkUmf8vS9K1bdvWpTqOx+0J84iIHBVo/ySJcYcMqT839np0ju6vSiMNsSciIiLSm2nTpql8asnJycjLy0OfPn1UHjcZof3MM88EZjAvw8gdh1JURgLhioaj+4okjbAnviu7nJysJS9kOYGyFi1apJa3kwyF9jXmHessXLiwVOZGIQn/Vq1ahcTERPTu3RvBqJbJ1ktPRM4VwrNgXkgAH2mKZiBPREREhmZPgOfJ5isyyluSvUtc+Oqrr+K+++7D119/jR9++MHnK7q5NS5ahhAEkuPHjyMtLa1cBnm5U3LPPffg559/Rv369TFo0KBSj48ePVoNt//yyy/VEgJ2MprAnhNAssw76tGjhwrU5TkyhMKuuLgY9957r+rRHzNmDMLCAj+Te02IM7O3kKgixVoxMq0ZqvRUYH36EhEREXmfFSaPN185cOCAKi+44AIVB0r8KB3B/uBWBDZq1CjcddddVT5PAlxPLV68WGVHtCssLFSlYzZ6WUNeespltIDcCZGke927d1dJ7yTAlyHvJ0+eVMnmpPe97HJysg7ge++9h6FDh2LIkCHo27cvateujWXLlql14GW5ATlW1qxZs9CzZ09Mnz4dK1asQEpKispmuHv3bvTq1QuPPfaYx183ERmTBPDLi/6HDO00EkyJuDTscoS6OVTeohWh0JINS2hthJiC84YhERERGZ8estk3b95cBfKyqprEkjI6219c/oty2LBh8AUJxqVHvSzHY/IcIQG49JLL0nOSPXDt2rUICQlBixYt1Np/Dz74oFoiwBlJTiDr0U+ZMkXVl5sGEpzLzYGKvlZJqLdp0yZMmjRJZciXYfySGE9uLkyYMEG3S8wRUc3J0jKRoWXACqsqZT/JVNutQP6PU58hx3IcMSF10TFpKAN6IiIiMiRPk9lpPgzm169fr1ZukyR4999/P6644goV2EuyeF/HgyZNJpdTjZPlC2R+RWZmpmGWptP7Gp4yZUISVwTysh+k/zasbs/8maJj2HL6v7BqFphNIeiUeCNiw+rBKPTSjlQ5tqP+sQ2Nge2of3ptw+rGOvb6/Q6sRljcP0uJu6oo6wyWNbnAp7GWhNHff/+9CuznzZun2k6md8sIcF/Rz3eIQch0ABkBIHP9icj4JHCXAL536EUeDbGPCk1CdEgdmExmVco+ERERUSCQmEZiG4lxvEGzmmB1Y9v79qdY2WMQ1l58K3xN8sldfPHFmDFjhpquLaPD33//fZ9eA7OW+ZjMsWfPPJHv5KIQ0Qj361suAXy8OcHtQF7IHHkZWp9RsBcJEc05xJ6IiIgCRmpqqtrsPevVJXPfTW4MmW80+ia1FWedwffNe8GXDh48qHrlZZOlzSW3mq87bBnME5Gh5aHI78G8CIfnc6gkoI8OrcNAnoiIiAzN02XmrD6cM//222+rAH7NmjVo3749brnlFrVKWrNmzeBrDOaJyLCKYEE6ziAOkQhDiF+vJcJUvYQooeZIr10LERERUSDS4GECPPgumJcE6jfddJNaY75r167wJwbzRGTYQH4WfkE6spGMWhiBHn4P6KsjzBzl70sgIiIiCnr79+9X8+UDAYN5IjKkEziD48iGFZoqZb8Bqj+Xi4iIiIiCd5i96e9APjc3VwX2ssS5oy5dugR2NnuZJ1CZvLw8tV47EZG/1EEs6qIWzDCpUvaJiIiIKHBZNc83Xzl+/DgGDhyIWrVqoWPHjjj77LNLbb7kUTB/zz334IorrsChQ4fKPbZq1Sp07txZpegnIvIXGVIvQ+sHo6vuh9gTERERBQOL1eTx5isPPPCAWs/+559/RlRUFJYsWaKWpGvTpg2++uorBHww/9FHH2H9+vXo1KlTyVp6+fn56guTtfbki/rxxx+9fa1ERG6RAD4ZsQzkiYiIiHRAkt95uvnKihUr8PLLL+Pcc8+F2WxWWexvvfVWTJ06Fc899xwCPpi/+eab8fvvv6N3794YOXIkBgwYoDL5ybp6jzzyCDZu3Ihu3bp5/2qJiNwUhTC+Z0RERETkFTk5OUhOTlb/TkxMVMPuhYxOlzhYFwnwGjRogPnz5+Oiiy5SQwskEcBLL72EBx980LtXSERUDYGwxjwRERERGSMBXrt27bB9+3Y0b95cdWhLPjn591tvvaVi5IDvmRe//vqrGlqwYcMGpKamIiUlRfXKy1Y2ox/9o3v37uq9klEMREREREREeiUxjcQ2EuN4g9XD+fJWH86ZHzt2LI4cOaL+/eSTT+Kbb75B06ZN1brzzz77LAK+Z37y5MlqPoDMD/jhhx/Qq1cvFcBPmjQJ06ZNw9dff63m0p9zzjnev2KdW7duHeLi4vx9Gbp3qtCKpHCP70UREREREVE1SaeubFlZWYiPr/4SwNLDbgrQnvk9e/agRYsWan68ncS7+/btw7Zt21RAX6dOHfiSR9HQ008/jTvvvBO//fabCuRFeHg4nn/+eaxevRrFxcXo2bOnt6+VqMSpQh+uP0FERERERDVOs3q+1bRWrVqpYF5yxklC+IMHD6rj0dHRKl+crwN5j3vmly1bprLWO3PeeeepIH/ChAnVvTYip/IsGn45VYRGUWZEhfhuSA0REREREQWnFStW4Pvvv1fbnDlz1Mj0li1b4pJLLlGxsWz16tUL/GC+okDeLiIiQg23J6qJQP6yNVn4PcuCN/YWYGnvOAb0REREREQGYNXg1jD7Ex98pDbNWvNd83379lWbfVn2tWvXlgT3MsW8qKgI7du3xx9//IGADub379/v0vNk3gCRN23LtmBrtgVFVqhS9s9O8HhRBiIiIiIiChCSyM7kRjK7pFtvU5slOxtbu54NX4mMjFQ98hdccIHq6JYkeJLVXubO+5JHUZCk3pel6KpisVg8OT1RhZpFmQELUGx12CeqRK5WhGgT15onIiIiCnQW6ZX3IJmdxUdL08nQ+p9++gnfffed6pH/+eef0aRJE7Vc++uvv44+ffog4IP59957r1wwL4H73r178cEHHyA5OVllNSTytgM5VkTlm6BpQJTJtp8UwYA+mJ3RihCHiAofz0URosFgnoiIiCjQaVaT2jypV9OkJ16Cd0mCJ0H7XXfdhU8++cTna8tXO5gfPnx4hY89+uijKgleZmZmda6LyKm2cSHoEB+KLRkWdIgPUfsU3HJRXGEwX6RZcAxnEK9FIMzE7xUiIiIi8syqVatU4C5Bvcydl4C+du3a8Cevd2nGxMRgxIgR+M9//uPtUxMhKtSEhZfGYso5kaqUfQpeRbDisJaLQs3iNJB/CxvwCbaoUvaJiIiIKHBZ/06C5/aGmpeRkYF33nlHLUX3wgsvoGHDhujcuTPuu+8+zJ07F8ePH4ev1cj4ZKvViqNHj9bEqXWve/fuSElJQVpamr8vRbckgD87KYSBfJCTAH5m/GG8i7/wouWPcgF9OnJUr7wVVlXKPhERERF5j8Q0EttIjOOtBHgWDzarD4bZS6f1FVdcgeeff14Ntz9x4gSmTp2qgnspGzdujE6dOsGXvJoGPCsrCytXrsSLL76Is8/2XTZBPVm3bh3i4uL8fRm6lxDm2X2ojHwNCZHszTeCo8hHekih5EPEYeTiCPLQDLEljycjBvUQi6M4o0rZJyIiIiLvkTxpskkcGB8fX+3zqaDcg8Dc6oNg3llwn5SUpLbExESEhobizz//DPxg3mw2V5jNXtM0tSTdG2+8Ud1rI6pQYrhnP7AM5o2jPiKRbAlHurkIDRGNBogq9bjMkb9bOwc7cBJtUZtz5omIiIgCnKZJomsPEuBpldfJzc3Ft99+i4ULF2L16tXYt28fQkJC0Lp1awwePBjjxo1DbOw/nUIVjT5fv369ymIv2ezXrFmDnJwcNGrUSC1PJ6MUpAz4YH7SpEnlgnnZlzsSrVq1Qv/+/dWdCaKa4kkG+/xiDTtPWlE/1oTwMtVP52tIZI+9roSbQjAqsyGO1wlDp5AktV+WBPT1tFgG8kRERERB7JNPPsEdd9yh/t2hQwdcc801ajTB2rVr8eSTT2LOnDn44Ycf1KpsFUlISFDBe/369VXQLjniJBGexL/+4lHEPXnyZO9fCVENkkD+5rn52H7CinZ1zPhoUHipxzMKGMzrURjMaGiKdhrI23FZOiIiIiJ9sKoMeB7Wq0RYWBjuvPNOPPDAAyqYtzty5AgGDhyITZs2qcck6K+ITCWXIL5t27YIFOw+p6Cw65RV9coXW6HKXac01P37sbxiDdtPW1A/xuRRUr3MHA3xMZyH7y/RVXyMRZu4xjwRERGRHtTUnPlhw4aprSxZak6Gx/fq1Qvz589HYWEhwsNLd/rZybrygcalYH7kyJFun1iG3c+cOdOTayLyulZJZrSpbVY981K2SjIh65QtkL9hcR7+PGVFhyQzPr86ulRAn2GxICGk8vXJs3KBeOZW8xveRiEiIiIyBslMr/k4AV7Xrl1VWVBQgJMnT6oAXy9cCuZXrFhRYcK7irj7fKKaFBlqwidDIrFqnwUXNgtBuFlDlvTYZ1ix/bQVFitU+VeGFZ3r/BO8Z1qsVQbznsjO0lArjj8j3pCLYtRChFfORURERET+449s9rt37y4Zii+Z6fXEpWB+7969NX8lRD4I6KVXXkqrVVPHWiWY0S7RrHrmpWyd8E9mvHyrFTsLClEvNASRZucJ9/ILNew+akXdeDMi3ciwfyYbqMUVCqutCFacRC4StchK580TERERkXFohQXQCgtL9q05Zzw+1/Tp01Upa8hHROirg4hz5snvTkvyuQj/9FLLkHoZWv/DwWL0aRxaMsReAvnbDhzDjoJCtI0Ix4dN6pUL6CWQT32jCLuOaGjVwIS0e8PcCuipemSF+Q8TDuA4CtFIi8EYdGVAT0RERKRjmtW2VeXMe68jZ8Z/qv16X3/9tZoaLr3yTz/9NPTG5fW9JkyYgM2bN9fs1QSB7t27IyUlRSVa0DuZT+6tYN5XEpwsPycBfLvEkFJz5XcVFuGvwkIUQ1Ol7Je1L13DnqOaSqonpey7oqBAw4F9mirJc8eQh+OhEtJrOIJcHEMu304iIiIiH5KYRmIbiXG8waKZXNoih92PpBXbSrbEhevdfq1t27bh1ltvhaZpKlO9fe68IYP5559/Hlu2bCnZl+QAISEhaj49uW7dunXYunUrUlNTdf+2ZVa1BoQLJAHdtgyLKv0VzKvjZUYGtAoPQ+vwcITCpErZL6tZsgkt6psQYoIqZb8qEsA/9bCGV5+DKhnQe64eolCnOFwlwKuHaLUFqjz8MwyMiIiIqDpOF1X/b3BvkZhGYhuJcbxB02Q6bNWbFhoJRMc5bLXcep1Dhw6pYfWnT5/GuHHjMHbsWOhRtYbZy10MCk4yDH1XYSHqhVQ8n7wqEsBf+20Otp62IiXRjC/7x3i0NJw3JJYJ8uVrkqH1q3PycEFMlNOvUYbU/+eOUHz8nRW3XOzanPnDB4AD+wCrxVbKfovW3vkass5oiIsNomH+mglnLGHINmk4YwoHwgLzay+CBQdwEi2QjDBwXj8RERFVz+liKxLDPPv7O9BJX6HJg3sVmht1Tp06hf79+2Pfvn0YMWIEXnrpJehVwH0XbNiwQY0CGDRoEBo3bqyy4ruSGX/27Nno0aMHYmNjVRbCAQMGYO3atZXWWbNmjXqePF/qSf0PPvig0joHDx5Ujd6wYUNERkaibdu2ePLJJ5Gfnw+92ptf7HYgP/LIETyanq5K2ffEzkwrtmfY1n6XUvYDiQTwbSLCK7xZUVCo4aE3LfhsuVWVsl+Vhk2AJs0Ac4itlH1vyc5BUDmMPBwzF6MIJhzS8nBYy0MgBvKfYA2+wgZVyj4RERGRp/IsGrblFquS3HfmzBlceeWVajSBxJszZszQ9SpsAZcATxIPfPnll27VeeCBB1QWwqioKHWXRQLrpUuX4ttvv8XcuXNx3XXXlaszb9483HDDDbBarbjoootQp04dLF++HMOGDVO5AZzdofnrr7/Qs2dPnDhxAp06dcKFF16I9evX46mnnlJ1ZdNbBkSxNbcQzSNd/1bYU/T3fHLNNp9c9jt48HW3iTejbbwZW05ZVSn7NS0jT0NClOs/sPEhFV/T3mOSyV6DJMaXUvbbNan83BERJkx6Efh5tYbzLjCpfW+QGwl7D2uokwhEBEkSvtpaBOT2j/wuk7J2AC5PdxLZOIFsWKGpUvbrI8Hfl0VEREQ6JAH8NX+cwtacYqTEhOKrjkmIkvmeBqLWmPdgmTnNhTqyjvy1116LX375BZdffjnmzJmjpo3rmVvBvCxRt3HjRvXvzMxMVe7cuRMJCc7/OO3WrZvbFyTBcpcuXVQSBdmaN2+u3viKLFu2TAXytWvXxo8//og2bdqo4/Lvvn37ql50KR2vUYZWjBw5EhaLRQX1cldGHDt2DBdccAGmTZuGq666StVzNHz4cBXIjxkzpmQJg+LiYgwdOhQLFizAc889h8mTJ0NPThdZ8EN2PnrWikBimGvfzC3CbPPJdxYWqlL2PRVSDIQW20pfOJBpRUKU6z+0la0x37yeCS3rm7DzsKZK2XeFBPDxSZpXA/lxLxZj90GgZWPg5YdDgyKgP4FCFFnNsJgks71JZbWvFWD3J2ujFuqgFo4jS5WyT0REROSJHXnFqldeOtSklP2usZ7/HR6IZD68qQaCeYvFgptuuknle5MO2fnz5yM8PBx6Z9JcnPhuNpvLDUGQqs6GJdiPy5tWXTKUXYL5ii5Thsl/8803+M9//qN66B1JIoNXX31V9bKPHz++5PjUqVPx6KOPqjszX3zxRak6EpRLcC/B/MKFC0uOyx2c8847D8nJydi/f3+pHni5CdCkSRM1VD89PR2hoeUDiqysLMTHx6ubIHFxcQETyPfafgT5JisiNTPWtmvgckAvQ+vX5uWhV5Tz+eSu+P2EBdctzkWhBQgPAb4YGI3OdWru7lh+kYb5W4swKCUM4SGaaitpT/nerk4g/eF3Ftx2cYjLAbQkvftumRUX9zN7JaDfuU/DA1OLUVQMhIUCrzwSijbNjB/M51mKMTFnKw6FFqG5ORqTI9ohwhRwM4fU0Po9SOec+QrI6Chv/CySf7Ed9Y9taAxsR2O3YSD3zFc31rHXj1q8E6YY9zs/tJxs5A1sU+HrS0esPVa8/vrrK7xGiRtlxLZeuNyNNWvWLASavLy8kmz6Q4YMKfe4HJNgXoJyx2B+8eLFFdYZOHCguoEgPf4yXF/+7Vjn6quvLjeUvl69euoOj1zL6tWry/XoB6pvM/NVIC+klP0b6sS4VFcC+FbhFc8nd0XrBDPaJZrx5ymrKmW/JgP5W/6bj60nrJi32YIPh3rnTpxmAjSzrXQ1kH9yghV79wDfr7Di/56tfkDftIFsGv46ZP83goIE7mNy62JPUgjOD6sTkIG8kKR3TVC72snvcjI1xMS79r2SnaWhVlxg/HInIiIi75DAXQL47zIKcHFCRMAE8nromT99+nSpztuKyChrQwbzMpc80Gzfvl312tetW1cly6tomL/MgXf022+/lXrckQy3kPnwMhd+x44dash/VXXsxyWYl9fSSzDfOCxUZYyUeFxK2XdHfDV70SRz/bwB0fjhYDH6NA51K5P9qUIrksJdf/2tx63YmGFBcShU+edxKxqFVv8GwR1vF2LHEQ0rt1sw465wRFaRUf3QQWC/ZLO32krZb9kK1WYJA6yhtjKYyMJ0bcyxARvI20Wh+jePcjKBmHjXnnsmG6gVGAOAiIiIyIskgG8fHWrIQL4mTZ48WXfToV0RWBNM3STD3YWzQF7ExMSoufJyJyY7Oxu1atVSQzjs8/0rqifHJZiX5QrswXxVr2U/LnUqk5GRoYbP2Ekvv7+S5p0VE4o25ghsyy9G+8hQte94bVWJM8k6j9XLQB9hBtrGmxBh1mCVTHIuOllgQYIb371WzWrrPddsvegW2de0al3/tkNWbJEEeIAqtx2yoEvTyoPKBg01NGlqC+SlbNDQqu5AVmdZuT1HNOw7KtNboMo9R6xoW0UiPiOQtpM2jNLM1f4+1APb92vV7VpYABzYqyExyYTwwMsJWGE7BkMbGhnbUf/YhsbAdgyONpTBrP7+vSkdqo55zSTG8gZNkiHJ5km9IBSq96UFRHR0dIXPkYBeAmh7MG+vU1k9qSOkjquv5ayOM82aNSu1L8P/H3roIfjLu4kaFmUW46p4M7JPHEflV18zrIUa0gtc/wHMswLrszSExpkQ5WKHrAyWaZsQhb8yzWgdb0UdZCEjI1N9WHo6T/dURghgilU3CGCS/dNIj6w6T0TqA8CO7SFo286Cv+8r4dARKxo18Ow65D1oXKcW9h0LQeM6FkSZTyE9HYaUp1kQZbINV5dfYnJjLl7TUGDwudZFBcDuzSEohAVhlQTohYXAa88l4MiBUDRoUoT7H8tAoOd2sbdjdX4Wyf/YjvrHNjQGtmPwtKG//9STueWSNNzbLD5YZ95IdB3M65H03DsmXPBnz7xd79hCNI3131/8yW48VxJ/DFqfhS1nLOgUG4Kl58a5NMxIhsQn5BciJltDQkQokutEIzvUpKZoeBpAxCVqSGlYhB3HgLb1gPM7JFU5zN6uMM+Kxo3/ed3D6VYkJ3seyLw+XsP6bRrObR+GiPAoGNURawGSzRElv+wk0WZ12lAPCvOB/9wBHNoJNGoDPDgDCLel8ihnz1/AscPy3mg4djgcRfnJqGAwUcAIlnY0Oraj/rENjYHtqH96aUNZTvyJJ54o1TNfttMykObMG5Wug3nJHi9yc3MrfE5OTo4qpVfesY69nrNMhmXruPJazuo4I8P+AyWbvV3z6PCA/rBwtONMMbaesaJYgyp35Gk4O67qxGJ7T1mx5wRgLjapct9pE2qbTerr9vRrj44AZo4246uNFlzTLcTlQF7IIhD2183KtmLdJqB1CyCuloe985FAi4YaoiKN+0FWoFlxQCtEHVNEyRx5+WVXnTbUg/R9Gg7vkiVVoMr0fUDTDs7buXEzDU2aadi3x4QmzWRf3p/A/54IhnYMBmxH/WMbGgPbUf/00IZRUVFqs/PWtcq0UY962TUEpcD9DnFB06ZNVXnw4MEKA2wZYp+YmFgSZEsgLcseVFbPftzx7lJVr+Wsjl4khurn26B9TAg6xoZAcuVJKfuniqr+iW9Zx4TWdU0IDYEqW9T2ToAjAXzHRma3AnkRE2MqCeRvH2PF/P9BlbLvqTjXFiLQbSA/IfcvvJi/T5WyHyzqtwAatgJCQmyl7FdEVkaY9KIJd46FKr2x9CERERERBSb9RHFOtGvXTg1RP378OA4dOlTu8Y0bN6rSnsTOrmvXrqUed1RUVIQtW7aoJenatm3rUp3KXou8S4bUL+sRj4+61FKl7J8urjqwk2B71u0RmDooTJXuBt+VaZzk3rkKCzQc3KupcuNvQG6BBvkv9+99T8X9fYPAiA5a87HPmg8LNFXKfrAIjzRh/Exg9AtQpexXRgL4xERbSURERKQrfw+zd3dDkA6z13UwL0M7LrnkEvXvzz//vNzjc+fOLVkbvuxa8o6PO1q0aJFaX75fv34la8w71pE16x0zN4pjx45h1apVagRA7969vfK1UcUkgE+JtS3JIXPot+UWq7IqEsC3rut+L3pV4qNdP58E8E+N1/DqM1Bl29ZWaOG2JeWk7NghSMcIVaGxORLNzJEIgUmVsh9MJICXXvmqAnkiIiIiPQuxyGZyeTMtnAntnl7Ag/0QjHQdzItx48apcsqUKdi5c2fJ8R9//BFvv/22mqM+atSoUnVGjx6thtt/+eWXmD9/fsnx9PR0PPLIIyVZ5h316NFDBerynEcffbTkeHFxMe69917Voz9mzBiEhQXZQt9+khRmC+Sv+v0URm3LVKUrAX18lH+DoUP7gYN7AavFVu7caUZEJGAOgSozzuj+R7JGyBz5Z6Nb4+HIZqoM9HXla4Kra8zLDaOMk7aSiIiISE/MVve20CtGI/zVHxE2dRmCUcD9Rbx48WKcf/75JVuhrLUElDomz7GTHvSxY8fi5MmTOOuss3DddddhwIABuOiii1SgPWvWLBXQO0pKSsJ7772nEjUMGTJE9e7/61//UsP2//rrL3WDoG/fvuWuTc5Vu3ZtTJ8+XQ2nv/HGG1UduSHQq1cvPPbYYz54h0i1YbgZO/KK8WeuBUUaVCn7VUnwczDfqCnQuLkteJey21lA80ZQc/mlbNrAr5cX0CSAbxoSGZSBvIiJd2WNeQ1THtAwcxpUyYCeiIiI9MRsNXm8BaOAy2Yv899//vnncscdj8lzHL3yyisqkH/99dexdOlShIeHqyB/4sSJKsh2ZvDgwVi5cqXq0f/pp5/UTYOUlBTcd999GDZsmNM6bdq0waZNmzBp0iQsWbIECxYsUInx5HUmTJjg9yXmPCVzzvWUBM+uSXgIrFZA8t+F/b0f6MIlQdk0YPN6DV3ONan9aY+a8NliC4YODEFEeHB+EJF3HNpnG/Ehme+llP0W/6T+ICIiIiIDCbhgfvjw4WrzRT0ZNv/NN9+4VadJkyaqh95IMiz6DOb351tQXGRSS1EUm0xqX3rsA50E8NIrL6WQAL5TGxMDeRfUMgX+DRt/atQMaNgM2L/LVso+ERERkV6YLLbNbRYEpcCPfKhG5Vk17MgvUqXetIsJRceYUITCpErZ14tY20qJJWLcSKIXzGqZ9NPGfqEBIUVASKGtDNY1V4mIiEifQqwmj7dgxGDex7p3766G86elpcHfJIC/4a/juG/fKVXqLaCXbPZLzknAB53iVCn7ehEbV+Za9fXWU4A6vA84vNf2/SSl7BMRERHVFIlpJLaRGMcfCfDMDlswYjeXj61bt05l0g8Eu/KLsD2/CMWapkrZ7xQdDj2RAL7D38vU6VVBgYZTJ4GCxhrXBqdqkaH1jVsC+3faStknIiIiqimpqalqy8rKQny8i0vvVEIS2Zks7v9drwVpzzyD+SDWKjIM7SLD8Gd+kSplX48SvbxuvK8D+ceftGLfPqBZMw3P/J+ZAT15TNahf+w1YN33Grr3NXFdeiIiIiIDYzAfxKLMJnzaui5WZufjolqRal+PksL0O1vk4CFg/35b9nEpZb9VS39fFek9oG/d0VYSERER6YlJeuY96WW3BuffPQzmg5wE8G0jw3QbyOtdY1lbvilUz7yUsk9UXTGBMZOHiIiIyC1mi21zlzVIs9kzmCckhOi3Z1vvIiJMamj9pt80nN3VxCH2BpVzGohJ9N3rxcbz5hwRERHpj8yZl81t1uD824fBPOlyjXmjBfRNm9hKMqbcDN8G80RERETB1DOPIO2ZZxRHFABqxfr7CqimFOYBR3fYyuo4k8n1C4mIiIjoH+yZJwoAtWqxV96IJIB/Yyhw5E+gQQfg3s+A8CjPzpWTJcPnvX2FRERERPpPgGfiMHsiIvKm9L+Ao9sBa7GtlP3Gnd0/T2G+hkO7gcS6GrPUExERkWGFuDnM/szKd3Bm1TvQgjQDHofZ+1j37t2RkpKCtLQ0X780EflYcmugfjvAHGorZd+TQH7q3cA7j0OVsk9EREQUCCSmkdhGYhxvMGuSBM/1Le6CO9HwsfVoMP4HBCMOs/exdevWIS6O60YR+UruaSDaT8nnZEi9DK3fvhJod5FnQ+yP7IXqlbcUA4d22fabta+JqyUiIiJyT2pqqtqysrIQH1/9+YBmi0ltbrME55RV9swTkeGDeX+SAD6xfaHHc+UbNAcatQTMIUByE9s+ERERERF75onIsIrygGPbgfgGQJiHwXR1FWsWHI84gfpaPYSaQtyuHx5pwgPTNXw9E2jcoUYukYiIiCggmKy2zZN6wYjBPBEZNpB/63rg6J9A/Q7A3Qt8H9BLID8fP+BE3UzsRDwGaX3cDuhljvxrdwI7dgOaGVj6GfDYm0yER0RERMYT4uEwexOH2RMRGUf6TuDYNlsmeSll39dOIUttVmg4qdn+7a6ju4GDuwG54axZ/543v69GLpeIiIjIr0x/Z7N3dzMFZzJ7zpknImNKbgPUa2/LJC+l7PtaEuKQaI0DrGbUyo9T++6q3xJo3BKQ/nyTGWjUCmjQrEYul4iIiMivzFaTx1sw4jB7IjIkGVIvQ+s3LwK6XOWfOfPW/BAcvr0P0guykJFXC/mfmRGb6P6c+fHva9j8PWANBc66wHaMiIiIiIIbg3kiMiwJ4OOS/Zf8Ln0XcPh3M/KKEtQA++m3AA/Pd3++uzy/aQdNzZlnIE9ERERGZfJwyLyJw+yJiIyXBC/7mK30h+RWQO2mgCa/ZEzAyYPAsV2enSsmHohxf5Q+ERERkW6EWE0qCZ7bmzU4Ry1ynXkf6969O1JSUpCWlubrlyYKKhLAv3MtsGCcrfRHQC9ry9/3KVCvhW10QMO2QL1Wnp0rJsGE2Pjg/EVFREREgUliGoltJMbxBk+S35n/3oIRh9n72Lp16xAXx+41In9ks2/Uxffve2yiCaNf13D8ANDhQg6TJyIiIuNITU1VW1ZWFuLj46t9PrPVtrlLC9J15tkzT0SGFAjZ7O3i65nQoA0DeSIiIiLyHvbME5EhybD2O78EdnwHtL3Yf0nwRIxksOcIeSIiIqJKmSwmtbnL5EEdI2AwT0SGJQG89Mr7M5AXubm5iEmIVmV0dLR/L4aIiIgoQIVYbJur0je9hfRf34KmBeekeQbzRGRo0W6u6+5tEsBLrgyTyQRN01SCGAb0REREROW5m8yufpe71WYpyMKGN5OD7i1lME9EhubvYF4CdwnkrVYrzGYzA3kiIiKiCpisJpg9GDJv5dJ0RET6k3saAU165qVHXgJ5KWWfiIiIiKi62DNPRLp2eg8QWxsBS3rm7UPrOWeeiIiIqGImq21zlylIl6ZjME9EulWcBxzeANTv6P8kd5Wxz5HnXHkiIiIi7yXAswvS/HcM5olIn4rygC/+lYSTO0z49X1g5PLADuiJiIiIqHIyX96TOfPmIF2azuzvCwg2Mtw2JSUFaWlp/r4UIl07+htwZEcY8jVg/xbbfiDLyfD3FRARERF5l8Q0EttIjOPNbPaebMGIw+x9TJaoiouL8/XLEhmOZrZtsDr8O4DlZgAxCf6+CiIiIiLvSU1NVVtWVhbi4+P51vpYgP/5S0TkXIPOQHKnIoRGAI3Otu0HqsJ84MhOW0lEREREzrFnPgiD+b59+6p1nCvalixZ4rTe7Nmz0aNHD8TGxiIpKQkDBgzA2rVrK32tNWvWqOfJ86We1P/ggw9q6CsjoorI/PghH51Cn3Ea7vw6cOfLSwD/2k3A+2NtJQN6IiIiosrnzHuyBSNDDbMfPHiwCrDLatSoUbljDzzwAKZPn46oqCj0798f+fn5WLp0Kb799lvMnTsX1113Xbk68+bNww033ACr1YqLLroIderUwfLlyzFs2DBs3rwZL730Uo19bUTkXHiABvF2x/4Cju4ErMW2UvabdPL3VREREREFHrPVs/nvZi5Np38STDdv3rzK5y1btkwF8rVr18aPP/6INm3aqOPyb+nlHzFihCoTEv6Z4Hrq1CmMHDkSFotFBfWDBg1Sx48dO4YLLrgA06ZNw1VXXaXqEZGPstnflIRT20zYNh8Y8b/A7J2v1xqo3wY4vN1Wyj4RERERVTDM3oOx4+YgTYBniGH27nr55ZdV+cQTT5QE8qJnz564++67kZGRgZkzZ5aq8+6776rEDtdee21JIC/q1auHqVOnqn9LQE9EvnFiO3BqR6haVzR9K3B8e2C+8+GRwP1zgGHTbaXsExERERFVV9AF83l5eVixYoX695AhQ8o9bj+2cOHCUscXL15cYZ2BAwciMjJS9fjLcH0iqnl12gFJbYthCgGSU4C67QL3XZcAvlV3BvJERERElTF5uCydKUh75g01Z15600+ePAmz2Yy2bduqee9NmzYt9Zzt27ejoKAAdevWRePGjcudo1u3bqqUOfCOfvvtt1KPOwoPD0enTp2wfv167NixA126dPHyV0ZEZcmQ+uvmnMLBb5Nxzm2mgBxi74jL0hERERFVTiWzM7uezG7v7jewd8+b0GSoZhAyVDA/ZcqUUvsPPfQQJk6cqDa7/fv3q9JZIC9iYmLUXPnTp08jOzsbtWrVUsPrMzMzK60nxyWY37dvX6XBvAzhlwR6dhEREWoj35I20DStVFuQPttQ06yQZmRT6hN/Fo2B7ah/bENjYDvqn17aUDpHZbOTeMkb3J0z37LZvWorKsrCN0uSEGwMEcxLZvnRo0ejV69eaNCgAQ4cOKAy0ktwP2nSJMTFxWHs2LHquWfOnFFldHR0heeTgF6Cbnswb69TWT2pI6ROZZo1a1Zqf/z48eqmA/mWfEDKDRr5sJSRHKQ/hblWzLspARm7zFj/QTGu//gUQjkfXXf4s2gMbEf9YxsaA9tR//TShpJ4vCbyhTEBXhAG80899VSpfRliP2HCBJx77rm4/PLLMXnyZNx5551qGTp/k557ublgx555/31QmkwmNd0ikD8oqWKHNlmRuccMWEw4/VcYcDoZyV35jukNfxaNge2of2xDY2A76p9e2vDpp59WycQde+bLdlpSzTNEMF8RWT9eAnoZ/v7zzz+rZePs69Dn5uZWWC8nJ0eV0isvHNeul3qOwXhFdSoiQ/id1Sffkw9K+ZAM5A9KKi3vFBD19wiq5PZA7TbFOLUjDMkdTKjXXtqT75ge8WfRGNiO+sc2NAa2o/7poQ2lk9Sxo9Rb18p15t0TuN8hXmJfeu7IkSOqtCfEO3jwoNPnS1AuQ+wTExNLAnMJvuPj4yutZz/OO1JENbeu/P5VtlJIwjsZWv+v9zSM+iYw15gnIiIiIjcT4Hm4BSPDB/OSyM5xTnu7du3U0Pbjx4/j0KFD5Z6/ceNGVZZNYte1a9dSjzsqKirCli1b1PJ0MsSfiLxLAvgPLgHm3Wor7QG9zJFP7sBAnoiIiMgIPFmWzvz3FowMHcxLwL5q1apSS8rJcJBLLrlE/fvzzz8vV0cS54mrr7663Fryjo87WrRokVpfvl+/fiqgJyLvOrENSN8KaMW2UvbtIhP5bhMREREZQU0G8xs2bMDzzz+PQYMGqZXIZDqDbHqm+2B+7dq1+OKLL2CxlG7BvXv34vrrr1fD5q+55ppSS8qNGzdOlZLtfufOnSXHf/zxR7z99ttqXvuoUaNKnU+y5ctw+y+//BLz588vOZ6eno5HHnmkJDM9EXlfnfZAcgpgCrWVsm8XzWCeiIiIiFxI2vfYY49hwYIFTkdo65HuE+Dt2LEDI0aMQP369VXvuwTikjFe7rxIb3nHjh0xY8aMUnWkB12Wqps+fTrOOussXHbZZSgsLMTSpUvVMhCzZs1S53GUlJSE9957D0OHDsWQIUNUMr3atWtj2bJlao693CCQY0TkfTIf/vYVwO5vgZb9bfsBvvwqEREREblJ9bJ70FludqFnvmfPnmoqdffu3dXWvHlzFBQU6LqNdB/Mn3feebjnnntUtvp169apOfIyP16C9H/961/qMWdL0r3yyivqOa+//roK4sPDw1WQP3HiRLVevTODBw/GypUrVY/+Tz/9pG4ApKSk4L777sOwYcN88NUSBS8J4Ot25Px4IiIiIqMyeRjMm1wI5h999FEYje6D+Q4dOuCNN97wqO7w4cPV5o7evXvjm2++8ej1iKh67MvSEREREZHxmK2eZaY3W/U99z1o58zrjQzpkN78tLQ0f18Kke4wmCciIiIKHBLTSGwjMY43MJt9kPXM641MBZBEekRERERERHqWmpqqtqysLMTHx/v7coIOg3kiIiIiIiLyO9Uz78LzLNYCWLR/ktcVW7IQjBjMExERERERkW6C+U3HnsOm408h2DGYJyIiIiIiIt0E892SHkPXxHEl+4WWLHyyqymCDYN5IiIiIiIi0k0wb0YEwhDhsB+cgvXrJiIiIiIiItIt9swTERERERFRYPTMax7UsyIoMZgnIiIiIiIivzNbTDBrJvfrWd2vYwQM5omIiIiIiMjvTB72zJtc6JlfvHgxnn766ZL9wsJCVZ5//vklxyZOnIiBAwdCLxjM+1j37t0REhKC1NRUtREREREREelRWlqa2iwWS8APsz9+/Dh+/vnncscdj8lz9ITBvI+tW7cOcXFxvn5ZIiIiIiIir7J3UGZlZSE+Pj6g393hw4erzUgYzBMREREREZHfMQGeexjMExERERERkd8xmHcPg3kiIiIiIiLyO5n77tGceQ1BicE8ERERERERBUbPvAerzJmDNJg3+/sCiIiIiIiIiMg9DOYpKBUUFOCll15SJekT29AY2I7GwHbUP7ahMbAd9S/Y29Bc7PkWjEyapgXpoATfsi/XkJmZyaXpAkBGRgYSExNx+vRpJCQk+PtyyANsQ2NgOxoD21H/2IbGwHbUP722YXVjHXv9h8MyEWFyvf56S5rarLDgFHYEXazFnvkAk5aWxnP76P2oSTV13fz+8B2+1757P2oSfxZ9837UJP4s+u79qEn8WfTN+1GT+LPou/ejJtXUdb/zzjvemzPvxtYDqbg3ZCvuMK9DMGLPfIDdrUpJScHWrVtr5Br0eO6aOm9N3/XU2/uhx3PrtQ31em7+LPrm/dDruWvy51GP70dNnluPbajH90Ov5+bPou/eaz22YU1ed7t27bBjh+c94/ZY6d/IRCTcr5+PLDyP4BsFzWz2PmKfzdCtWzeEhITgjjvuwJ133lnueRaLRX0z1wQ9nrumzms/p5Rms/cHqOjt/dDjufXahno9N38WffN+6PXcNfnzqMf3oybPrcc21OP7oddz82fRd++1HtuwJq5beuRnzJiB3bt3q/3qzuAuQJZP6+kde+Z95ODBg2jSpImvXo6IiIiIiMinDhw4gMaNG7tdLz8/Hy1atMDRo0c9fu369etjz549iIyMRLBgMO8jVqsVhw8fRq1atWAyebB4IhERERERUQCSHvns7Gw0bNjQ4xEFEtAXFhZ6fA3h4eFBFcgLBvNEREREREREOsNs9kREREREREQ6w2CeiIiIiIiISGcYzFNAOH78OB566CG1rEVUVBSSkpJU5v+HH37Y6fMXLlyIPn36qKUnZOvbty8WL15cac6Ct99+Gz179lTPlzk1kpzj5ptvxq+//urSNa5cuVLNAZKcB6NHj3b6HLkOebyibcmSJTCyQGzHytpDNpmf5UxeXh4mTZqEtm3bqvlXMgds5MiROHToEIzMKG3In8XAa0e73377Dbfddpt6fkREBOrVq6deb9asWRVmXv7Pf/6Dzp07q6+lbt26GDp0KP78808YWSD+LHrShsOHD6/05/ett96CkQVaO06ePLnKz1TZ5G+esvh7Ud9tGOy/F42Kc+bJ7zZs2IDLL78cJ0+eRMeOHdGpUye1ZIasgSmrABQXF5d6/iuvvIIHH3wQoaGh6Nevn/pD4ttvv1W/ZF577TXcd9995RJyDB48GAsWLFAfwhdeeKFax3LLli3qj8GwsDB88cUXGDBgQIXXWFBQgK5du6r1M+V8o0aNwrvvvlvuefJB+cMPP6jXi42NLff4+PHj1R+kRhSo7Si/oGJiYjBkyBCn1y3LqUhdRxIcXnzxxfjpp5/QoEED9Vp79+7FL7/8ogIJOd6yZUsYjZHakD+LgdeOQj4377nnHnWO888/X63ycuzYMfUHq/xxvGzZsnJ/5Eq7y2vJesuXXnopTpw4of5Ildf+7rvv0KNHDxhNoP4setKGEsy///776uuRTNNlDRs2TH3eGlEgtqPsy+aM3KyW9ouOjlZt6vh3DH8v6r8Ng/n3oqFpRH6Unp6u1alTR4uOjta+/PLLco///PPPpfa3bdumhYSEaBEREdratWtLjm/fvl2rXbu2Fhoaqu3cubNUHTmvfKs3b95cO3ToUKnHXnjhhZLHKvPEE09oJpNJGz16tHr+qFGjnD6vT58+6vE9e/ZowSSQ21GON2vWzK2v5/HHH1f1evbsqWVnZ5ccnzZtmjou7Ww0RmtD/iwGXjsuX75cfY62bt1a27p1a6nHCgoKtI0bN5arM2PGDHW+Nm3aaEePHi05PnfuXHVczlVUVKQZidHacNiwYep83333nRZMArkdK/LII4+oOrfccku5x/h7Uf9tGKy/F42OwTz51T333KM+WNLS0tx6/tixY8s99vLLL6vH7rvvvlLHx48fr44/99xz5epYrVYtPj5ePX7s2DGnr7llyxYtPDxcBfKzZs1iMK+zdnQ3EJQ/SO3ncvaHaZcuXdRj69ev14zESG0YzH+0BHI7pqSkaGazWdu8ebPLX0+HDh3UuRYsWFDusWuuuUY9JoG9kRitDYM1mA/kdnRGnt+kSRP1/CVLlpR6jL8X9d+Gwfx70eg4Z578RoYcffTRR2r47IgRI1yqY59z5Gy4rf2YzFVyJEOcKmKfJxQSEqKGNZUlccSdd96pHnvhhRdcusZgo4d2dMeaNWuQmZmJVq1a4eyzz3b5+vTMaG0YrAK5HeXnSoalyjBPV4dx7tmzRw0zlaGnAwcOdPn69MxobRisArkdK/L999/jwIEDaiqEDA93xN+L+m9DMq5Qf18ABa/169cjOzsbF1xwgfpj7ZtvvsHSpUvVvCxJOiYJjiTpmF1GRgb279+v/u0syJJ5e3Xq1MG+ffvUfCZJIiL69++PZ599ViUXuf3220udc+rUqeq8MmfP2Qfqm2++ibVr1+KDDz5QCU9cNXPmTDVHThLmyddy3XXXoWnTpjAiPbRjTk4OnnnmGfW6Mo9MXnfQoEFO54xJYichcz+dsR/fvHkzjMJobeiIP4uB0Y4rVqxQZa9evVSg89///lfNJ5Y/Us855xz861//Ut97zn4WZY5q2ZwIgj+Lgd+GjubPn4958+aphIYtWrTA1Vdfjfbt28OI9PCZWpbcfBA33XSTalNH/L2o/zYM1t+LQcHfQwMoeL311ltquM+gQYO0a6+9Vv3bcYuKitI++eSTkuf/9ttv6nhiYmKF5zzrrLPUc8oOAXz44YdLznn55Zdr//rXv9TwzbCwMG348OFabm5uuXMdPHhQi4uL0y6++OKSY64Osy+7yes89dRTmhEFejs6aw/ZZP7aokWLyj3/wQcfVI9L6cyvv/6qHu/WrZtmFEZrQ8GfxcBqxxtvvFE9f8KECVq7du3KXVvTpk3Lvcb06dPVY9dff73Ta8vIyFCPJyUlaUZhtDZ0HGZfdpO59/fee6/hch4Eejs6k5eXV+n0Mv5e1H8bBuvvxWDAYJ78RuYHyYeIJASRZCEyr0wSxuzdu1d76KGHSj5gNm3apJ6/Zs0adaxRo0YVnrN3797qOfLcsl555RX1Wo4fYJLE5+OPP3Z6ruuuu07NlZeEJq4G8xMnTtQ+/PBDbdeuXerDV5KePPPMM+oDWurJNRhNoLfj7bffruaOSWKZM2fOqOu47bbbVD1p319++aXU8++44w71mCT7cUaS19gTchmF0dpQ8GcxsNpR/kC1f481btxY+/rrr7XMzEzt999/1y677LKSvAg5OTkldeSzs6JETkKCQPvXZBRGa0P7a0hwu2PHDvV7cffu3errkqBH6jzwwAOa0QRyOzrz6aefqjodO3Z0+jh/L+q/DYP192IwYDBPfmP/Q002ydhZltyZlMduvvnman1Q5ufna0OHDlUZRidNmqQSf2RlZWkrVqzQOnXqpJ4/derUUueZN2+eOi7Pd1RVMF+R//3vf6peQkKCS3dY9SSQ27Ey0rskdfr3768F+x8tRmvDyvBn0T/taA/2ZCubAVrOJ8GhPPbOO+8EdTBvtDasjD25rAQw+/fv14wkkNvRmauvvlo99/nnn3f6OH8v6r8Ng/X3YjBgME9+Yx9CKZvc7SxL7vo7fjB6OoTpySefrDC76L59+7SYmBi1dMzx48fVMelpaNiwoQrW5EPWG8G8OPfccw2Z0TdQ27EqMkRXfnnKH5OSqTeYhxMarQ2rwp9F37ejDJWXOpIN3dXllIJxmL3R2rAqQ4YMUXXkd6uRBHI7lnXixAl1Q0xWKThw4IDT5/D3ov7bMFh/LwYDZrMnv2nWrJkqJZlV3bp1yz3evHlzVaanp6vSnpzj9OnTKhmWMwcPHix1bvHhhx9WmF1UznneeechNzdXJfIRGzduxOHDh1FUVITLL79cZe61b88//3xJxlLZv/HGG13+etu0aaPKI0eOwEgCtR2rIplhk5OTUVhYqBLBOJ7L8RpcuTa9M1obVoU/i75vR3t9+/dSVd9jjtfHn0X9tmFV+LPo/8/UTz/9VP2906dPHzRu3Njpc/izqP82DNafxWDAYJ78xp7tU7LiFhQUlHv81KlTqrRnq05ISCj5sNy0aVO558tyHCdOnFAfkvYsoY4fnhUt62E/Lh/Ajvbu3Ysffvih1LZ9+3b12NGjR9X+Tz/95PLXaz+/LFVjJIHejhWxWq0qo2zZNunatWvJTR1n7Me7dOkCozBaG1aFP4u+b0f791hFbVv2e8zxZ3HLli3qD9Wy+LMY+G1YFf4s+v8z1Z4B/bbbbqvwOfy9qP82DNafxWDAYJ78Rj705BeETPeQwLgs+zHHJT7saw3PnTu33PPtx2S5G0ey3qZ9qZiyZIkc+4eu/S6r9Lj/PQWl3DZr1iz1nFGjRql9Cfhdcfz4caxatarSJc/0KlDbsSpLlixRd89lPXnHX6y9e/dWvzx37dqFX3/91eXr0zOjtWFl+LPon3YcMGAAQkND8fvvv5f8EVzV95gsX9ahQwd1k8m+frMr16dnRmvDysiNQ3u78veifz5Td+/ejR9//FEtnzd48OAK24q/F/XfhsH6ezEo+HucPwU3ydIp34adO3fWDh8+XHJcsoPKPEh57LPPPis5LpnlZY6sZIf98ccfS45LllxZpkoS6UiCMkdjxoxR55HkPJK50664uLhkjp9k4HVleZzK5sxLQpMFCxao8zqSZCb2pCfXXHONZkSB2o5z5sxxmun8+++/V3kRpM7LL79c7nFJfieP9erVS2VPt5s2bZo6Lsu7GI2R2pA/i4HXjo5JtGROtWOOg9mzZ6vjkZGR5RKhzZgxoyTh5LFjx8olKZVsz0Zb2ixQfxY9acM///xT++CDD8rln5F55LJijNTp2rWrZrVaNaMJ5Ha0+7//+z/1HFl2sCr8vajvNgzm34tGx2Ce/M6+Bq1k0RwwYIBa110+COWY/OFQlvzhLo/Jh+KVV16p1nC1L6vx6quvOk0MYl8TV84r5x88eLDWsmVLdUzqLl++3KVrrSyYtz9Wv3599XVIhlP5gJQ/buzLhTj+MWo0gdiO9mtq27atSt4kGWPtCWjsv/wsFovT9VrPO+889ZwGDRqoevb9unXrqmVdjMgobcifxcBrR3vCOgls7GuSyxrc9qRL8gewBH1lSdvaE69JYilJmNa3b1+1Rrm8zk8//aQZUSD+LHrShpJMy952kg1ffi9K+9WqVctpAGM0gdqOdvK5Ks9bvHhxlV8Lfy/quw2D/feikTGYJ7+TO/KylM0555yjMnZK5s6ePXuqO/0V+eqrr7QLL7xQi42NVZv8e+HChRU+X5b5kIyhXbp0UeeXrJ/yh4j8ot26davL11pZMC/nueeee1SWcwn45IM8Pj5eO//881WPrtGX+wjEdpRss9KD1L59e/XHlLRJcnKy+gX7+eefV/r1SHvJmqytWrVS2dLlF+Dw4cM9zhSrB0ZpQ/4sBl472slIF1lSUHrU5edKereuuuoqbfXq1RXWkZ4k+QyVPzblD0/p4ZKg/o8//tCMKhB/Fj1pw0OHDql15OX3oHyGymvItcnvSXntU6dOaUYWyO0oywvK3zPyeerq6Bb+XtRvGwb770UjM8n//D3Un4iIiIiIiIhcxwR4RERERERERDrDYJ6IiIiIiIhIZxjMExEREREREekMg3kiIiIiIiIinWEwT0RERERERKQzDOaJiIiIiIiIdIbBPBEREREREZHOMJgnIiIiIiIi0hkG80REREREREQ6w2CeiIiIiIiISGcYzBMREQWw2bNnw2QyqW316tXlHtc0DU2aNFGPX3XVVSXHZf++++4r2d+7d2/JeWQLCwtDnTp10KtXL0yYMAH79+/32ddERERE1cdgnoiISAciIyPxySeflDv+ww8/4ODBg4iIiHDpPDfddBM+/PBDzJw5ExMnTkTLli3xyiuvoEOHDvjvf/9bA1dORERENSG0Rs5KREREXjVgwAB8/vnnePXVVxEa+s+vbwnwzznnHJw4ccKl83Tr1g233nprqWP79u1D//79MWzYMBXUd+3ala1HREQU4NgzT0REpAPSo37y5EksXbq05FhhYSHmzp2Lm2++uVrnbtasmRrOL+ebOnWqF66WiIiIahqDeSIiIh1o3rw5evbsiTlz5pQc++abb5CZmYkbb7yx2ueXc7dq1arUzQIiIiIKXAzmiYiIdEJ64L/44gvk5eWp/Y8//hh9+vRBw4YNvXL+Tp064fjx48jKyvLK+YiIiKjmMJgnIiLSiaFDh6pAftGiRcjOzlZldYfYO4qNjVWlnJuIiIgCGxPgERER6UTdunXRr18/lfQuNzcXFosFQ4YM8dr5z5w5o8patWp57ZxERERUMxjMExER6Yj0xN9xxx04evQorrzySiQkJHjt3Fu2bEFycjLi4uK8dk4iIiKqGRxmT0REpCPXX389zGYzfvrpJ68Osf/xxx+xa9cutUQdERERBT72zBMREemIzGt/8803sXfvXlx99dVeOaesMz98+HCEh4fj4Ycf9so5iYiIqGYxmCciItKZYcOGeVx348aN+Oijj2C1WpGRkYF169Zh3rx5MJlM+PDDD9GlSxevXisRERHVDAbzREREBqNpmipDQkLKPSbr1MsWGhqq5sa3adMGDzzwAO6++240bdrUD1dLREREnjBp9t/4REREZAiyTnx8fDyeeOIJPP300/6+HCIiIqoBTIBHRERkMDJ0XqSkpPj7UoiIiKiGsGeeiIjIIDZv3oxly5bh5ZdfRn5+Pnbv3s1l5oiIiAyKPfNEREQGMX/+fEyYMAHNmzfHN998w0CeiIjIwNgzT0RERERERKQz7JknIiIiIiIi0hkG80REREREREQ6w2CeiIiIiIiISGcYzBMRERERERHpDIN5IiIiIiIiIp1hME9ERERERESkMwzmiYiIiIiIiHSGwTwRERERERER9OX/AbRPs8/1rRsrAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Method 2: Using run_pipeline() function\n",
    "\n",
    "# ======================================\n",
    "# === Old way and will be deprecated ===\n",
    "# ======================================\n",
    "\n",
    "print(\"Method 2: Using run_pipeline() with advanced_params_file\")\n",
    "print(\"=\" * 70)\n",
    "\n",
    "run_pipeline(\n",
    "    ra=213.9427080,\n",
    "    dec=11.4953890,\n",
    "    source_name=\"cloverleaf\",\n",
    "    output_dir=Path(\"demo_data/cloverleaf\"),\n",
    "    advanced_params_file=params_file,  # <-- Load custom parameters\n",
    ")\n",
    "\n",
    "print(\"To run pipeline with custom parameters, uncomment the code above.\")\n",
    "print(f\"Custom parameters will be loaded from: {params_file}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Option A: One-Click Resume\n",
    "\n",
    "The simplest way - let the pipeline automatically run all remaining stages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:40 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Loaded pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Resuming from saved state\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - All stages already complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Pipeline Status:\n",
      "  Completed stages: ['query', 'download', 'processing', 'visualization']\n",
      "  Pending stages: None\n",
      "  Current stage: complete\n",
      "\n",
      "\n",
      "Final status after resume:\n",
      "\n",
      "Pipeline Status:\n",
      "  Completed stages: ['query', 'download', 'processing', 'visualization']\n",
      "  Pending stages: None\n",
      "  Current stage: complete\n",
      "\n",
      "To use one-click resume, uncomment the lines above.\n",
      "This will automatically complete all remaining stages.\n"
     ]
    }
   ],
   "source": [
    "# Uncomment to run one-click resume:\n",
    "pipeline_resumed = SPXQueryPipeline(AdvancedConfig.from_yaml_file(output_dir / \"cloverleaf.yaml\"))\n",
    "pipeline_resumed.resume(skip_existing_downloads=True)\n",
    "print(\"\\nFinal status after resume:\")\n",
    "pipeline_resumed.print_status()\n",
    "\n",
    "print(\"To use one-click resume, uncomment the lines above.\")\n",
    "print(\"This will automatically complete all remaining stages.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Option B: Step-by-Step Manual Execution\n",
    "\n",
    "Run each remaining stage manually for more control."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking which stages remain...\n",
      "\n",
      "Completed stages: ['query', 'download', 'processing', 'visualization']\n",
      "Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "\n",
      "Remaining stages: None - all complete!\n",
      "\n",
      "✓ Pipeline stages now in AdvancedConfig (not PipelineState)\n",
      "  - No duplicate entries in YAML file\n",
      "  - Accessible via: pipeline.config.pipeline_stages\n"
     ]
    }
   ],
   "source": [
    "# Check what stages still need to be run\n",
    "print(\"Checking which stages remain...\")\n",
    "print(f\"\\nCompleted stages: {pipeline_resumed.state.completed_stages}\")\n",
    "print(f\"Pipeline stages: {pipeline_resumed.config.pipeline_stages}\")\n",
    "\n",
    "remaining = [s for s in pipeline_resumed.config.pipeline_stages if s not in pipeline_resumed.state.completed_stages]\n",
    "print(f\"\\nRemaining stages: {remaining if remaining else 'None - all complete!'}\")\n",
    "\n",
    "print(\"\\n✓ Pipeline stages now in AdvancedConfig (not PipelineState)\")\n",
    "print(\"  - No duplicate entries in YAML file\")\n",
    "print(\"  - Accessible via: pipeline.config.pipeline_stages\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Download stage already completed. Skipping.\n"
     ]
    }
   ],
   "source": [
    "# Step 1: Download (if not already completed)\n",
    "if \"download\" in pipeline_resumed.state.completed_stages:\n",
    "    print(\"✓ Download stage already completed. Skipping.\")\n",
    "else:\n",
    "    print(\"\\nRunning download stage...\")\n",
    "    pipeline_resumed.run_download(skip_existing=True)\n",
    "    print(\"\\n✓ Download complete!\")\n",
    "    pipeline_resumed.print_status()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Processing stage already completed. Skipping.\n"
     ]
    }
   ],
   "source": [
    "# Step 2: Processing (if not already completed)\n",
    "if \"processing\" in pipeline_resumed.state.completed_stages:\n",
    "    print(\"✓ Processing stage already completed. Skipping.\")\n",
    "else:\n",
    "    print(\"\\nRunning processing stage...\")\n",
    "    pipeline_resumed.run_processing()\n",
    "    print(\"\\n✓ Processing complete!\")\n",
    "    pipeline_resumed.print_status()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Visualization stage already completed. Skipping.\n",
      "\n",
      "======================================================================\n",
      "ALL STAGES COMPLETE!\n",
      "======================================================================\n"
     ]
    }
   ],
   "source": [
    "# Step 3: Visualization (if not already completed)\n",
    "if \"visualization\" in pipeline_resumed.state.completed_stages:\n",
    "    print(\"✓ Visualization stage already completed. Skipping.\")\n",
    "else:\n",
    "    print(\"\\nRunning visualization stage...\")\n",
    "    pipeline_resumed.run_visualization()\n",
    "    print(\"\\n✓ Visualization complete!\")\n",
    "    pipeline_resumed.print_status()\n",
    "\n",
    "print(\"\\n\" + \"=\" * 70)\n",
    "print(\"ALL STAGES COMPLETE!\")\n",
    "print(\"=\" * 70)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View Results\n",
    "\n",
    "After running the pipeline, results are saved in the output directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Light curve plot:\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Display the light curve plot\n",
    "import pandas as pd\n",
    "from IPython.display import Image, display\n",
    "\n",
    "# Show plot from the one-click example\n",
    "plot_path = output_dir / \"results\" / \"combined_plot.png\"\n",
    "if plot_path.exists():\n",
    "    print(\"\\nLight curve plot:\")\n",
    "    display(Image(filename=str(plot_path)))\n",
    "else:\n",
    "    print(f\"Plot not found at {plot_path}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background and Aperture Method Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Light curve data (first 10 rows):\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>obs_id</th>\n",
       "      <th>mjd</th>\n",
       "      <th>flux</th>\n",
       "      <th>flux_error</th>\n",
       "      <th>mag_ab</th>\n",
       "      <th>mag_ab_error</th>\n",
       "      <th>wavelength</th>\n",
       "      <th>bandwidth</th>\n",
       "      <th>band</th>\n",
       "      <th>flag</th>\n",
       "      <th>flag_binary</th>\n",
       "      <th>pix_x</th>\n",
       "      <th>pix_y</th>\n",
       "      <th>is_upper_limit</th>\n",
       "      <th>snr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025W25_1B_0062_1</td>\n",
       "      <td>60842.269794</td>\n",
       "      <td>1038.190806</td>\n",
       "      <td>38.594902</td>\n",
       "      <td>16.359307</td>\n",
       "      <td>0.040362</td>\n",
       "      <td>1.940270</td>\n",
       "      <td>0.047790</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.226040</td>\n",
       "      <td>29.946309</td>\n",
       "      <td>False</td>\n",
       "      <td>26.899687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025W25_1B_0062_1</td>\n",
       "      <td>60842.269794</td>\n",
       "      <td>2436.806596</td>\n",
       "      <td>110.306551</td>\n",
       "      <td>15.432947</td>\n",
       "      <td>0.049148</td>\n",
       "      <td>4.658078</td>\n",
       "      <td>0.036448</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.557889</td>\n",
       "      <td>29.859574</td>\n",
       "      <td>False</td>\n",
       "      <td>22.091223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025W25_1B_0062_2</td>\n",
       "      <td>60842.271286</td>\n",
       "      <td>1023.153740</td>\n",
       "      <td>37.410014</td>\n",
       "      <td>16.375148</td>\n",
       "      <td>0.039698</td>\n",
       "      <td>1.984936</td>\n",
       "      <td>0.048890</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.228793</td>\n",
       "      <td>29.049005</td>\n",
       "      <td>False</td>\n",
       "      <td>27.349729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025W25_1B_0062_2</td>\n",
       "      <td>60842.271286</td>\n",
       "      <td>1933.090874</td>\n",
       "      <td>93.695601</td>\n",
       "      <td>15.684369</td>\n",
       "      <td>0.052625</td>\n",
       "      <td>4.691950</td>\n",
       "      <td>0.036713</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.420567</td>\n",
       "      <td>29.979960</td>\n",
       "      <td>False</td>\n",
       "      <td>20.631608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025W25_1B_0062_3</td>\n",
       "      <td>60842.272779</td>\n",
       "      <td>886.621010</td>\n",
       "      <td>35.335209</td>\n",
       "      <td>16.530655</td>\n",
       "      <td>0.043271</td>\n",
       "      <td>2.031681</td>\n",
       "      <td>0.050041</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.779715</td>\n",
       "      <td>29.163495</td>\n",
       "      <td>False</td>\n",
       "      <td>25.091716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2025W25_1B_0062_3</td>\n",
       "      <td>60842.272779</td>\n",
       "      <td>3041.467188</td>\n",
       "      <td>146.377337</td>\n",
       "      <td>15.192292</td>\n",
       "      <td>0.052253</td>\n",
       "      <td>4.726364</td>\n",
       "      <td>0.036983</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.694355</td>\n",
       "      <td>29.330708</td>\n",
       "      <td>False</td>\n",
       "      <td>20.778266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2025W25_1B_0062_4</td>\n",
       "      <td>60842.274271</td>\n",
       "      <td>1035.728823</td>\n",
       "      <td>35.127564</td>\n",
       "      <td>16.361885</td>\n",
       "      <td>0.036824</td>\n",
       "      <td>2.078427</td>\n",
       "      <td>0.051193</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.027695</td>\n",
       "      <td>29.260076</td>\n",
       "      <td>False</td>\n",
       "      <td>29.484789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2025W25_1B_0062_4</td>\n",
       "      <td>60842.274271</td>\n",
       "      <td>2935.771804</td>\n",
       "      <td>149.228218</td>\n",
       "      <td>15.230694</td>\n",
       "      <td>0.055189</td>\n",
       "      <td>4.760819</td>\n",
       "      <td>0.037252</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.752959</td>\n",
       "      <td>29.544355</td>\n",
       "      <td>False</td>\n",
       "      <td>19.673034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2025W25_1B_0178_1</td>\n",
       "      <td>60842.882044</td>\n",
       "      <td>2720.236164</td>\n",
       "      <td>127.554061</td>\n",
       "      <td>15.313483</td>\n",
       "      <td>0.050911</td>\n",
       "      <td>4.830310</td>\n",
       "      <td>0.037796</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.663109</td>\n",
       "      <td>29.794504</td>\n",
       "      <td>False</td>\n",
       "      <td>21.326143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2025W25_1B_0178_1</td>\n",
       "      <td>60842.882044</td>\n",
       "      <td>1065.492761</td>\n",
       "      <td>36.851711</td>\n",
       "      <td>16.331124</td>\n",
       "      <td>0.037552</td>\n",
       "      <td>2.175510</td>\n",
       "      <td>0.053584</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.418622</td>\n",
       "      <td>29.210586</td>\n",
       "      <td>False</td>\n",
       "      <td>28.912979</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              obs_id           mjd         flux  flux_error     mag_ab  \\\n",
       "0  2025W25_1B_0062_1  60842.269794  1038.190806   38.594902  16.359307   \n",
       "1  2025W25_1B_0062_1  60842.269794  2436.806596  110.306551  15.432947   \n",
       "2  2025W25_1B_0062_2  60842.271286  1023.153740   37.410014  16.375148   \n",
       "3  2025W25_1B_0062_2  60842.271286  1933.090874   93.695601  15.684369   \n",
       "4  2025W25_1B_0062_3  60842.272779   886.621010   35.335209  16.530655   \n",
       "5  2025W25_1B_0062_3  60842.272779  3041.467188  146.377337  15.192292   \n",
       "6  2025W25_1B_0062_4  60842.274271  1035.728823   35.127564  16.361885   \n",
       "7  2025W25_1B_0062_4  60842.274271  2935.771804  149.228218  15.230694   \n",
       "8  2025W25_1B_0178_1  60842.882044  2720.236164  127.554061  15.313483   \n",
       "9  2025W25_1B_0178_1  60842.882044  1065.492761   36.851711  16.331124   \n",
       "\n",
       "   mag_ab_error  wavelength  bandwidth band     flag             flag_binary  \\\n",
       "0      0.040362    1.940270   0.047790   D3  2097152  1000000000000000000000   \n",
       "1      0.049148    4.658078   0.036448   D6  2097152  1000000000000000000000   \n",
       "2      0.039698    1.984936   0.048890   D3  2097152  1000000000000000000000   \n",
       "3      0.052625    4.691950   0.036713   D6  2097152  1000000000000000000000   \n",
       "4      0.043271    2.031681   0.050041   D3  2097152  1000000000000000000000   \n",
       "5      0.052253    4.726364   0.036983   D6  2097152  1000000000000000000000   \n",
       "6      0.036824    2.078427   0.051193   D3  2097152  1000000000000000000000   \n",
       "7      0.055189    4.760819   0.037252   D6  2097152  1000000000000000000000   \n",
       "8      0.050911    4.830310   0.037796   D6  2097152  1000000000000000000000   \n",
       "9      0.037552    2.175510   0.053584   D3  2097152  1000000000000000000000   \n",
       "\n",
       "       pix_x      pix_y  is_upper_limit        snr  \n",
       "0  29.226040  29.946309           False  26.899687  \n",
       "1  29.557889  29.859574           False  22.091223  \n",
       "2  29.228793  29.049005           False  27.349729  \n",
       "3  29.420567  29.979960           False  20.631608  \n",
       "4  29.779715  29.163495           False  25.091716  \n",
       "5  29.694355  29.330708           False  20.778266  \n",
       "6  29.027695  29.260076           False  29.484789  \n",
       "7  29.752959  29.544355           False  19.673034  \n",
       "8  29.663109  29.794504           False  21.326143  \n",
       "9  29.418622  29.210586           False  28.912979  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total measurements: 108\n"
     ]
    }
   ],
   "source": [
    "# Display the light curve data\n",
    "csv_path = output_dir / \"results\" / \"lightcurve.csv\"\n",
    "if csv_path.exists():\n",
    "    df = pd.read_csv(csv_path, comment=\"#\")\n",
    "    print(\"\\nLight curve data (first 10 rows):\")\n",
    "    display(df.head(10))\n",
    "    print(f\"\\nTotal measurements: {len(df)}\")\n",
    "else:\n",
    "    print(f\"CSV not found at {csv_path}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Background Method Comparison (NEW in v0.2.1)\n",
    "\n",
    "SPXQuery v0.2.1 introduces two methods for local background estimation:\n",
    "\n",
    "### Annulus Method (Traditional)\n",
    "- Uses an annular region around the source aperture\n",
    "- Inner radius offset from aperture edge\n",
    "- Outer radius determined by minimum area requirement\n",
    "- Best for isolated sources in sparse fields\n",
    "\n",
    "### Window Method (NEW)\n",
    "- Uses a rectangular window centered on the source\n",
    "- Automatically excludes pixels intersecting the aperture\n",
    "- Simpler geometry, easier to visualize\n",
    "- More robust in crowded fields or near image edges\n",
    "\n",
    "Below we demonstrate both methods and compare their results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recommendations\n",
    "\n",
    "**When to use Annulus method:**\n",
    "- Isolated point sources in sparse fields\n",
    "- When local background varies smoothly\n",
    "- Traditional aperture photometry workflows\n",
    "\n",
    "**When to use Window method:**\n",
    "- Crowded fields with nearby sources\n",
    "- Sources near image edges or defects\n",
    "- When you want simpler background geometry\n",
    "- Faster computation (simpler geometry)\n",
    "\n",
    "**Configuration tip:** Save your preferred method in a YAML template for consistent analysis!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cell-bg-setup",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:40 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2025-11-13 00:33:40 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'aperture_diameter', 'background_method', 'annulus_inner_offset']\n",
      "2025-11-13 00:33:40 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2025-11-13 00:33:40 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'aperture_diameter', 'background_method', 'window_size']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Configurations created:\n",
      "  Annulus: method=annulus\n",
      "  Window: method=window, size=50\n"
     ]
    }
   ],
   "source": [
    "# Setup: Create configurations for both background methods\n",
    "from spxquery.core.config import PhotometryConfig, AdvancedConfig\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Configuration with annulus background (default)\n",
    "advanced_annulus = AdvancedConfig.from_yaml_file(output_dir / \"cloverleaf.yaml\")\n",
    "advanced_annulus.update(\n",
    "    aperture_method=\"fixed\", aperture_diameter=2.0, background_method=\"annulus\", annulus_inner_offset=1.414\n",
    ")\n",
    "\n",
    "# Configuration with window background (NEW)\n",
    "advanced_window = AdvancedConfig.from_yaml_file(output_dir / \"cloverleaf.yaml\")\n",
    "advanced_window.update(aperture_method=\"fixed\", aperture_diameter=2.0, background_method=\"window\", window_size=50)\n",
    "\n",
    "print(\"✓ Configurations created:\")\n",
    "print(f\"  Annulus: method={advanced_annulus.photometry.background_method}\")\n",
    "print(f\"  Window: method={advanced_window.photometry.background_method}, size={advanced_window.photometry.window_size}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cell-bg-annulus",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:40 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:33:40 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:46 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:33:46 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:33:46 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:33:46\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Downloading: 100%|██████████| 108/108 [00:00<00:00, 4835.66files/s]\n",
      "2025-11-13 00:33:46 - spxquery.core.download - INFO - Download complete: 108 successful, 0 failed\n",
      "2025-11-13 00:33:46 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.51 GB (actual)\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2025-11-13 00:33:46 - spxquery.core.pipeline - INFO - Processing 108 FITS files\n",
      "2025-11-13 00:33:46 - spxquery.processing.photometry - INFO - Processing photometry for 108 observations\n",
      "2025-11-13 00:33:46 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations: 100%|██████████| 108/108 [00:01<00:00, 104.66files/s]\n",
      "2025-11-13 00:33:47 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:33:47 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:33:47 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:33:47 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (105 good, 3 rejected - shown as crosses)\n",
      "2025-11-13 00:33:47 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:33:47 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 25.4\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:47 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:47 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Annulus method configuration ready.\n",
      "Uncomment the code above to run the pipeline.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demo 1: Run pipeline with annulus background\n",
    "config_annulus = SPXQueryPipeline(advanced_annulus)\n",
    "config_annulus.run_full_pipeline(skip_existing_downloads=True)\n",
    "df_annulus = pd.read_csv(output_dir / \"results/lightcurve.csv\", comment=\"#\")\n",
    "print(\"Annulus method configuration ready.\")\n",
    "print(\"Uncomment the code above to run the pipeline.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cell-bg-window",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:48 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:33:48 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:52 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:33:52 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:33:52 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:33:52\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Downloading: 100%|██████████| 108/108 [00:00<00:00, 4743.25files/s]\n",
      "2025-11-13 00:33:52 - spxquery.core.download - INFO - Download complete: 108 successful, 0 failed\n",
      "2025-11-13 00:33:52 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.51 GB (actual)\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2025-11-13 00:33:52 - spxquery.core.pipeline - INFO - Processing 108 FITS files\n",
      "2025-11-13 00:33:52 - spxquery.processing.photometry - INFO - Processing photometry for 108 observations\n",
      "2025-11-13 00:33:52 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  88%|████████▊ | 95/108 [00:00<00:00, 158.77files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations: 100%|██████████| 108/108 [00:00<00:00, 111.76files/s]\n",
      "2025-11-13 00:33:53 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:33:53 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:33:53 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:33:53 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (105 good, 3 rejected - shown as crosses)\n",
      "2025-11-13 00:33:53 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:33:53 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 26.2\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:53 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:53 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Window method configuration ready.\n",
      "Uncomment the code above to run the pipeline.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demo 2: Run pipeline with window background\n",
    "config_window = SPXQueryPipeline(advanced_window)\n",
    "config_window.run_full_pipeline(skip_existing_downloads=True)\n",
    "df_window = pd.read_csv(output_dir / \"results/lightcurve.csv\", comment=\"#\")\n",
    "print(\"Window method configuration ready.\")\n",
    "print(\"Uncomment the code above to run the pipeline.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cell-bg-compare",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z5/qygyj_xj7dq109c9rzqq2wv40000gn/T/ipykernel_78266/1917494619.py:19: UserWarning: The figure layout has changed to tight\n",
      "  plt.tight_layout()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean flux difference: 0.22%\n",
      "Std flux difference: 1.57%\n"
     ]
    }
   ],
   "source": [
    "# Compare flux measurements\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "# Plot 1: Flux comparison\n",
    "axes[0].scatter(df_annulus[\"flux\"], df_window[\"flux\"], alpha=0.6)\n",
    "axes[0].plot([0, max(df_annulus[\"flux\"])], [0, max(df_annulus[\"flux\"])], \"k--\", alpha=0.3)\n",
    "axes[0].set_xlabel(\"Annulus Flux (MJy/sr)\")\n",
    "axes[0].set_ylabel(\"Window Flux (MJy/sr)\")\n",
    "axes[0].set_title(\"Flux Comparison\")\n",
    "\n",
    "# Plot 2: Difference\n",
    "flux_diff = (df_window[\"flux\"] - df_annulus[\"flux\"]) / df_annulus[\"flux\"] * 100\n",
    "axes[1].hist(flux_diff, bins=20, alpha=0.7)\n",
    "axes[1].set_xlabel(\"Relative Difference (%)\")\n",
    "axes[1].set_ylabel(\"Count\")\n",
    "axes[1].set_title(\"Flux Difference Distribution\")\n",
    "axes[1].axvline(0, color=\"k\", linestyle=\"--\", alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"Mean flux difference: {flux_diff.mean():.2f}%\")\n",
    "print(f\"Std flux difference: {flux_diff.std():.2f}%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-ap-intro",
   "metadata": {},
   "source": [
    "## Aperture Sizing Comparison (NEW in v0.2.1)\n",
    "\n",
    "SPXQuery v0.2.1 introduces adaptive aperture sizing based on PSF FWHM:\n",
    "\n",
    "### Fixed Aperture (Traditional)\n",
    "- User specifies aperture diameter in pixels\n",
    "- Same aperture size for all observations\n",
    "- Simple, predictable, widely used\n",
    "- May be suboptimal when seeing varies\n",
    "\n",
    "### FWHM-Based Aperture (NEW)\n",
    "- Aperture size adapts to PSF FWHM for each observation\n",
    "- `aperture_diameter = FWHM × fwhm_multiplier`\n",
    "- Optimizes signal-to-noise ratio\n",
    "- Automatically falls back to fixed aperture if FWHM estimation fails\n",
    "\n",
    "Below we demonstrate both methods and compare their photometric results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cell-ap-setup",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:54 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2025-11-13 00:33:54 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'aperture_diameter', 'background_method', 'window_size']\n",
      "2025-11-13 00:33:54 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2025-11-13 00:33:54 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'fwhm_multiplier', 'aperture_diameter', 'background_method', 'window_size', 'max_processing_workers']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Configurations created:\n",
      "  Fixed: method=fixed, diameter=3.0\n",
      "  FWHM: method=fwhm, multiplier=3.0\n"
     ]
    }
   ],
   "source": [
    "# Setup: Create configurations for both aperture methods\n",
    "\n",
    "# Configuration with fixed aperture (traditional)\n",
    "advanced_fixed = AdvancedConfig.from_yaml_file(output_dir / \"cloverleaf.yaml\")\n",
    "advanced_fixed.update(aperture_method=\"fixed\", aperture_diameter=3.0, background_method=\"window\", window_size=50)\n",
    "\n",
    "# Configuration with FWHM-based aperture (NEW)\n",
    "advanced_fwhm = AdvancedConfig.from_yaml_file(output_dir / \"cloverleaf.yaml\")\n",
    "advanced_fwhm.update(\n",
    "    aperture_method=\"fwhm\",\n",
    "    fwhm_multiplier=3.0,\n",
    "    aperture_diameter=3.0,\n",
    "    background_method=\"window\",\n",
    "    window_size=50,\n",
    "    max_processing_workers=1,\n",
    ")\n",
    "\n",
    "\n",
    "print(\"✓ Configurations created:\")\n",
    "print(\n",
    "    f\"  Fixed: method={advanced_fixed.photometry.aperture_method}, diameter={advanced_fixed.photometry.aperture_diameter}\"\n",
    ")\n",
    "print(\n",
    "    f\"  FWHM: method={advanced_fwhm.photometry.aperture_method}, multiplier={advanced_fwhm.photometry.fwhm_multiplier}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cell-ap-fixed",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:33:54 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:33:54 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:33:58 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:33:58 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:33:58 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:33:58\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "2025-11-13 00:33:58 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.51 GB (actual)\n",
      "2025-11-13 00:33:58 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
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      "2025-11-13 00:33:58 - spxquery.processing.photometry - INFO - Processing photometry for 108 observations\n",
      "2025-11-13 00:33:58 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  92%|█████████▏| 99/108 [00:00<00:00, 158.24files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations: 100%|██████████| 108/108 [00:00<00:00, 110.79files/s]\n",
      "2025-11-13 00:33:59 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:33:59 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:33:59 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:33:59 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:33:59 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:33:59 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:33:59 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (101 good, 7 rejected - shown as crosses)\n",
      "2025-11-13 00:33:59 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:33:59 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 27.0\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:34:00 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fixed aperture configuration ready.\n",
      "  Aperture diameter: 3.0 pixels (constant)\n",
      "Uncomment the code above to run the pipeline.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demo 1: Run pipeline with fixed aperture\n",
    "config_fixed = SPXQueryPipeline(advanced_fixed)\n",
    "config_fixed.run_full_pipeline(skip_existing_downloads=True)\n",
    "df_fixed = pd.read_csv(output_dir / \"results/lightcurve.csv\", comment=\"#\")\n",
    "\n",
    "print(\"Fixed aperture configuration ready.\")\n",
    "print(f\"  Aperture diameter: {advanced_fixed.photometry.aperture_diameter} pixels (constant)\")\n",
    "print(\"Uncomment the code above to run the pipeline.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cell-ap-fwhm",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:00 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2025-11-13 00:34:00 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2025-11-13 00:34:04 - spxquery.core.query - INFO - Found 108 observations spanning 33.1 days\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Starting parallel download of 108 files\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "SPHEREx Archive Search Results\n",
      "============================================================\n",
      "Source: RA=213.942708, Dec=11.495389\n",
      "        Name: cloverleaf\n",
      "Query time: 2025-11-13 00:34:04\n",
      "\n",
      "Total observations found: 108\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  18 observations\n",
      "  D2 (1.10-1.62 μm):  18 observations\n",
      "  D3 (1.63-2.41 μm):  18 observations\n",
      "  D4 (2.42-3.82 μm):  18 observations\n",
      "  D5 (3.83-4.41 μm):  18 observations\n",
      "  D6 (4.42-5.00 μm):  18 observations\n",
      "\n",
      "Time span: 33.1 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading:   0%|          | 0/108 [00:00<?, ?files/s]2025-11-13 00:34:04 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_1.fits - already exists\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_1.fits - already exists\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_2.fits - already exists\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_2.fits - already exists\n",
      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_3.fits - already exists\n",
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      "2025-11-13 00:34:04 - spxquery.core.download - INFO - Total size: 525.9 MB\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Downloaded 108 files\n",
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      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2025-11-13 00:34:04 - spxquery.core.pipeline - INFO - Processing 108 FITS files\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 108\n",
      "Successful: 108\n",
      "Failed: 0\n",
      "Total downloaded: 525.9 MB (0.51 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:   0%|          | 0/108 [00:00<?, ?files/s]2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_1.fits\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:04 - spxquery.processing.photometry - INFO - Repaired 12 pixels with NaN variance using median variance (9.499758e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:04 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.017\" (0.82px) → diameter=2.45px (radius=1.22px)\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1757\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1757\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Background mask: 1945/2601 (74.8%) pixels available\n",
      "2025-11-13 00:34:04 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=1121.937±41.018 μJy (0.001122±0.000041 Jy) at λ=1.940 μm, mag_AB=16.275±0.040\n",
      "2025-11-13 00:34:04 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_1.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.811026e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.625\" (0.91px) → diameter=2.74px (radius=1.37px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2995/3600 (83.2%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0426\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0426\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2172/2601 (83.5%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=2825.502±119.947 μJy (0.002826±0.000120 Jy) at λ=4.658 μm, mag_AB=15.272±0.046\n",
      "Processing observations:   2%|▏         | 2/108 [00:00<00:06, 16.15files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_2.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (9.150388e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.643\" (0.75px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1734\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1734\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1942/2601 (74.7%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=1106.323±39.931 μJy (0.001106±0.000040 Jy) at λ=1.985 μm, mag_AB=16.290±0.039\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_2.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (6.164463e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.250\" (0.69px) → diameter=2.07px (radius=1.03px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0365\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0365\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2192/2601 (84.3%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=2312.551±103.936 μJy (0.002313±0.000104 Jy) at λ=4.692 μm, mag_AB=15.490±0.049\n",
      "Processing observations:   4%|▎         | 4/108 [00:00<00:05, 18.16files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (8.889740e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.495\" (0.73px) → diameter=2.19px (radius=1.10px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2635/3600 (73.2%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1805\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1805\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1917/2601 (73.7%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=1024.168±37.980 μJy (0.001024±0.000038 Jy) at λ=2.032 μm, mag_AB=16.374±0.040\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (6.721239e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=7.940\" (1.29px) → diameter=3.87px (radius=1.93px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3023/3600 (84.0%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0259\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0259\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2192/2601 (84.3%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=3330.851±154.565 μJy (0.003331±0.000155 Jy) at λ=4.726 μm, mag_AB=15.094±0.050\n",
      "Processing observations:   6%|▌         | 6/108 [00:00<00:05, 18.82files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_4.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (8.557443e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.490\" (0.73px) → diameter=2.19px (radius=1.10px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2667/3600 (74.1%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1888\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1888\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1945/2601 (74.8%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=1208.118±37.310 μJy (0.001208±0.000037 Jy) at λ=2.078 μm, mag_AB=16.195±0.034\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_4.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (7.100530e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=7.936\" (1.29px) → diameter=3.87px (radius=1.93px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3021/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0445\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0445\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2191/2601 (84.2%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=3114.435±150.008 μJy (0.003114±0.000150 Jy) at λ=4.761 μm, mag_AB=15.167±0.052\n",
      "Processing observations:   7%|▋         | 8/108 [00:00<00:05, 18.99files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_1.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (8.644567e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.551\" (0.90px) → diameter=2.70px (radius=1.35px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3022/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0760\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0760\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2199/2601 (84.5%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=3209.757±139.790 μJy (0.003210±0.000140 Jy) at λ=4.830 μm, mag_AB=15.134±0.047\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_1.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (7.728661e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.629\" (0.75px) → diameter=2.26px (radius=1.13px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1792\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1792\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1935/2601 (74.4%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=1255.156±40.227 μJy (0.001255±0.000040 Jy) at λ=2.176 μm, mag_AB=16.153±0.035\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_2.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (9.236660e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.553\" (0.90px) → diameter=2.70px (radius=1.35px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3034/3600 (84.3%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0621\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0621\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2201/2601 (84.6%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_2.fits: flux=3468.647±144.604 μJy (0.003469±0.000145 Jy) at λ=4.866 μm, mag_AB=15.050±0.045\n",
      "Processing observations:  10%|█         | 11/108 [00:00<00:05, 19.30files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (9.960690e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.567\" (0.74px) → diameter=2.23px (radius=1.11px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3024/3600 (84.0%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0838\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0838\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2196/2601 (84.4%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=2750.664±127.283 μJy (0.002751±0.000127 Jy) at λ=4.901 μm, mag_AB=15.301±0.050\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (6.856603e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.714\" (0.77px) → diameter=2.30px (radius=1.15px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1851\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1851\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1915/2601 (73.6%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=1633.109±43.013 μJy (0.001633±0.000043 Jy) at λ=2.277 μm, mag_AB=15.867±0.029\n",
      "Processing observations:  12%|█▏        | 13/108 [00:00<00:05, 18.64files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_4.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (1.096818e+00). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.570\" (0.74px) → diameter=2.23px (radius=1.11px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2966/3600 (82.4%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0908\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0908\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/2601 (82.9%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=3023.937±157.861 μJy (0.003024±0.000158 Jy) at λ=4.937 μm, mag_AB=15.199±0.057\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_4.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (6.745640e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.713\" (0.77px) → diameter=2.30px (radius=1.15px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2603/3600 (72.3%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2239\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2239\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1908/2601 (73.4%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=3873.840±62.466 μJy (0.003874±0.000062 Jy) at λ=2.329 μm, mag_AB=14.930±0.018\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0202_1.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (1.186982e+00). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0572\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0572\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2191/2601 (84.2%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=3014.348±148.454 μJy (0.003014±0.000148 Jy) at λ=4.973 μm, mag_AB=15.202±0.053\n",
      "Processing observations:  15%|█▍        | 16/108 [00:00<00:04, 19.01files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0202_1.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 26 pixels with NaN variance using median variance (1.020734e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.415\" (0.72px) → diameter=2.15px (radius=1.08px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3655\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3655\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1945/2601 (74.8%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=1829.841±55.316 μJy (0.001830±0.000055 Jy) at λ=2.382 μm, mag_AB=15.744±0.033\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.231259e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.646\" (0.76px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0272\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0272\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1967/2601 (75.6%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=1253.936±45.043 μJy (0.001254±0.000045 Jy) at λ=1.633 μm, mag_AB=16.154±0.039\n",
      "Processing observations:  17%|█▋        | 18/108 [00:00<00:04, 18.19files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_3.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (3.707438e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.581\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 0.9897\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 0.9897\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/2601 (84.7%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=2134.900±98.292 μJy (0.002135±0.000098 Jy) at λ=4.411 μm, mag_AB=15.577±0.050\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_4.fits\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.203764e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.662\" (0.76px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 2677/3600 (74.4%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0526\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0526\n",
      "2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Background mask: 1954/2601 (75.1%) pixels available\n",
      "2025-11-13 00:34:05 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=1207.572±45.054 μJy (0.001208±0.000045 Jy) at λ=1.671 μm, mag_AB=16.195±0.041\n",
      "Processing observations:  19%|█▊        | 20/108 [00:01<00:04, 18.61files/s]2025-11-13 00:34:05 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_4.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (3.862086e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.584\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 0.9603\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 0.9603\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2173/2601 (83.5%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=2620.783±107.760 μJy (0.002621±0.000108 Jy) at λ=4.443 μm, mag_AB=15.354±0.045\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.169509e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.704\" (0.76px) → diameter=2.29px (radius=1.15px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0774\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0774\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1963/2601 (75.5%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=1521.356±47.269 μJy (0.001521±0.000047 Jy) at λ=1.709 μm, mag_AB=15.944±0.034\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.453817e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.645\" (0.92px) → diameter=2.75px (radius=1.37px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3000/3600 (83.3%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0566\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0566\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2186/2601 (84.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=2102.276±108.125 μJy (0.002102±0.000108 Jy) at λ=4.475 μm, mag_AB=15.593±0.056\n",
      "Processing observations:  21%|██▏       | 23/108 [00:01<00:04, 19.28files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.113934e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.558\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0940\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0940\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1951/2601 (75.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=1788.948±49.582 μJy (0.001789±0.000050 Jy) at λ=1.749 μm, mag_AB=15.769±0.030\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (4.604722e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.405\" (0.71px) → diameter=2.14px (radius=1.07px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3004/3600 (83.4%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0315\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0315\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2183/2601 (83.9%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=2280.462±98.781 μJy (0.002280±0.000099 Jy) at λ=4.508 μm, mag_AB=15.505±0.047\n",
      "Processing observations:  23%|██▎       | 25/108 [00:01<00:04, 19.35files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_3.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.078577e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.561\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2678/3600 (74.4%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1140\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1140\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1961/2601 (75.4%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=1392.935±45.493 μJy (0.001393±0.000045 Jy) at λ=1.789 μm, mag_AB=16.040±0.035\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_3.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (4.797451e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.406\" (0.71px) → diameter=2.14px (radius=1.07px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3014/3600 (83.7%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0258\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0258\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2186/2601 (84.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=2818.990±108.006 μJy (0.002819±0.000108 Jy) at λ=4.540 μm, mag_AB=15.275±0.042\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_4.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (4.988441e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.677\" (0.92px) → diameter=2.76px (radius=1.38px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2987/3600 (83.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0101\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0101\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/2601 (83.1%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=3517.963±119.892 μJy (0.003518±0.000120 Jy) at λ=4.573 μm, mag_AB=15.034±0.037\n",
      "Processing observations:  26%|██▌       | 28/108 [00:01<00:04, 19.53files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_4.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (1.039659e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.362\" (0.71px) → diameter=2.13px (radius=1.06px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2658/3600 (73.8%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1364\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1364\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1944/2601 (74.7%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=1253.689±42.934 μJy (0.001254±0.000043 Jy) at λ=1.831 μm, mag_AB=16.155±0.037\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (5.483860e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.637\" (0.91px) → diameter=2.74px (radius=1.37px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 3008/3600 (83.6%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0489\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0489\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2193/2601 (84.3%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=2919.277±119.140 μJy (0.002919±0.000119 Jy) at λ=4.607 μm, mag_AB=15.237±0.044\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (1.003989e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.361\" (0.71px) → diameter=2.13px (radius=1.06px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2649/3600 (73.6%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1580\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1580\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1936/2601 (74.4%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=1207.048±41.556 μJy (0.001207±0.000042 Jy) at λ=1.873 μm, mag_AB=16.196±0.037\n",
      "Processing observations:  29%|██▊       | 31/108 [00:01<00:03, 19.82files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 23 pixels with NaN variance using median variance (5.778874e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.634\" (0.91px) → diameter=2.74px (radius=1.37px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0207\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0207\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/2601 (84.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=2682.458±118.442 μJy (0.002682±0.000118 Jy) at λ=4.640 μm, mag_AB=15.329±0.048\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (9.719857e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.438\" (0.72px) → diameter=2.16px (radius=1.08px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2654/3600 (73.7%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1714\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1714\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1940/2601 (74.6%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=1134.037±39.745 μJy (0.001134±0.000040 Jy) at λ=1.917 μm, mag_AB=16.263±0.038\n",
      "Processing observations:  31%|███       | 33/108 [00:01<00:03, 19.61files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (3.814502e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.566\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3159\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3159\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1666/2601 (64.1%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=2652.838±104.667 μJy (0.002653±0.000105 Jy) at λ=4.251 μm, mag_AB=15.341±0.043\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_1.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.311397e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.541\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2866/3600 (79.6%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1742\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1742\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2136/2601 (82.1%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=1124.569±43.783 μJy (0.001125±0.000044 Jy) at λ=1.480 μm, mag_AB=16.273±0.042\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.271930e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.542\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1367\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1367\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2141/2601 (82.3%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=1153.277±41.911 μJy (0.001153±0.000042 Jy) at λ=1.516 μm, mag_AB=16.245±0.039\n",
      "Processing observations:  33%|███▎      | 36/108 [00:01<00:03, 19.60files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_2.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (3.952595e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.565\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/3600 (59.5%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2754\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2754\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1633/2601 (62.8%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=2802.135±107.660 μJy (0.002802±0.000108 Jy) at λ=4.287 μm, mag_AB=15.281±0.042\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_3.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (4.147240e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.928\" (0.97px) → diameter=2.90px (radius=1.45px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2195/3600 (61.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2534\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2534\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1668/2601 (64.1%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=2894.202±112.163 μJy (0.002894±0.000112 Jy) at λ=4.324 μm, mag_AB=15.246±0.042\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_3.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.213519e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.574\" (0.75px) → diameter=2.24px (radius=1.12px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2865/3600 (79.6%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1006\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1006\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2134/2601 (82.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=1297.317±43.575 μJy (0.001297±0.000044 Jy) at λ=1.552 μm, mag_AB=16.117±0.036\n",
      "Processing observations:  36%|███▌      | 39/108 [00:02<00:03, 19.81files/s]2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_4.fits\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.322733e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.949\" (0.97px) → diameter=2.90px (radius=1.45px)\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/3600 (59.0%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2312\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2312\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Background mask: 1620/2601 (62.3%) pixels available\n",
      "2025-11-13 00:34:06 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=3197.984±118.941 μJy (0.003198±0.000119 Jy) at λ=4.361 μm, mag_AB=15.138±0.040\n",
      "2025-11-13 00:34:06 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_4.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.164446e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.574\" (0.75px) → diameter=2.24px (radius=1.12px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2824/3600 (78.4%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0617\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0617\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2101/2601 (80.8%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=1174.522±42.245 μJy (0.001175±0.000042 Jy) at λ=1.589 μm, mag_AB=16.225±0.039\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0679_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (4.967668e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.709\" (0.93px) → diameter=2.79px (radius=1.40px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/3600 (60.7%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3352\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3352\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1668/2601 (64.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=2963.480±117.091 μJy (0.002963±0.000117 Jy) at λ=4.398 μm, mag_AB=15.220±0.043\n",
      "Processing observations:  39%|███▉      | 42/108 [00:02<00:03, 19.96files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0679_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.141730e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.439\" (0.72px) → diameter=2.17px (radius=1.09px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2886/3600 (80.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0796\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0796\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2156/2601 (82.9%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=1233.630±41.307 μJy (0.001234±0.000041 Jy) at λ=1.627 μm, mag_AB=16.172±0.036\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0746_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (8.280554e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.752\" (0.93px) → diameter=2.80px (radius=1.40px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 3005/3600 (83.5%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0637\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0637\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2193/2601 (84.3%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=3082.004±136.653 μJy (0.003082±0.000137 Jy) at λ=4.795 μm, mag_AB=15.178±0.048\n",
      "Processing observations:  41%|████      | 44/108 [00:02<00:03, 19.89files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0746_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (8.186452e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.560\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2683/3600 (74.5%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1785\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1785\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1947/2601 (74.9%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=1175.484±39.542 μJy (0.001175±0.000040 Jy) at λ=2.127 μm, mag_AB=16.224±0.037\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 27 pixels with NaN variance using median variance (2.792472e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.099\" (0.83px) → diameter=2.49px (radius=1.24px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2129/3600 (59.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2205\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2205\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1617/2601 (62.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=2030.394±71.666 μJy (0.002030±0.000072 Jy) at λ=4.107 μm, mag_AB=15.631±0.038\n",
      "Processing observations:  43%|████▎     | 46/108 [00:02<00:03, 19.44files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_1.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.412864e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.929\" (0.80px) → diameter=2.41px (radius=1.20px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2864/3600 (79.6%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2326\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2326\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2132/2601 (82.0%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=1191.820±46.193 μJy (0.001192±0.000046 Jy) at λ=1.346 μm, mag_AB=16.209±0.042\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_2.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.392585e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.833\" (0.79px) → diameter=2.36px (radius=1.18px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2170\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2170\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2142/2601 (82.4%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=1224.834±47.185 μJy (0.001225±0.000047 Jy) at λ=1.379 μm, mag_AB=16.180±0.042\n",
      "Processing observations:  44%|████▍     | 48/108 [00:02<00:03, 19.37files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_2.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (2.996648e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.574\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/3600 (61.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2300\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2300\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1678/2601 (64.5%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=2339.555±96.875 μJy (0.002340±0.000097 Jy) at λ=4.143 μm, mag_AB=15.477±0.045\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_3.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.339184e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.830\" (0.79px) → diameter=2.36px (radius=1.18px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2873/3600 (79.8%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1844\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1844\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2138/2601 (82.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=1145.978±44.401 μJy (0.001146±0.000044 Jy) at λ=1.412 μm, mag_AB=16.252±0.042\n",
      "Processing observations:  46%|████▋     | 50/108 [00:02<00:02, 19.38files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_3.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (3.166565e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.571\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/3600 (60.7%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2336\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2336\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1668/2601 (64.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=2467.138±100.419 μJy (0.002467±0.000100 Jy) at λ=4.179 μm, mag_AB=15.420±0.044\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_4.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.324254e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.792\" (0.78px) → diameter=2.34px (radius=1.17px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2860/3600 (79.4%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1701\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1701\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/2601 (81.7%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=1153.586±46.299 μJy (0.001154±0.000046 Jy) at λ=1.446 μm, mag_AB=16.245±0.044\n",
      "Processing observations:  48%|████▊     | 52/108 [00:02<00:02, 19.50files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_4.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (3.447359e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.504\" (0.90px) → diameter=2.69px (radius=1.34px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/3600 (60.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2517\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2517\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1647/2601 (63.3%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=2489.013±102.615 μJy (0.002489±0.000103 Jy) at λ=4.215 μm, mag_AB=15.410±0.045\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_2.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.581823e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.504\" (0.73px) → diameter=2.20px (radius=1.10px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2872/3600 (79.8%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2306\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2306\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2140/2601 (82.3%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=1006.959±45.064 μJy (0.001007±0.000045 Jy) at λ=1.102 μm, mag_AB=16.392±0.049\n",
      "Processing observations:  50%|█████     | 54/108 [00:02<00:02, 18.92files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_2.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (2.212814e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.550\" (0.90px) → diameter=2.71px (radius=1.36px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/3600 (59.8%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3802\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3802\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1643/2601 (63.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=2526.442±95.536 μJy (0.002526±0.000096 Jy) at λ=3.815 μm, mag_AB=15.394±0.041\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_3.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (2.206441e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.588\" (0.91px) → diameter=2.73px (radius=1.36px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/3600 (59.7%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3323\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3323\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1642/2601 (63.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=3094.978±103.156 μJy (0.003095±0.000103 Jy) at λ=3.848 μm, mag_AB=15.173±0.036\n",
      "Processing observations:  52%|█████▏    | 56/108 [00:02<00:02, 19.01files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_3.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.528159e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.506\" (0.73px) → diameter=2.20px (radius=1.10px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2853/3600 (79.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1931\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1931\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2109/2601 (81.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=1185.612±45.997 μJy (0.001186±0.000046 Jy) at λ=1.128 μm, mag_AB=16.215±0.042\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_4.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (1.480095e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.188\" (0.68px) → diameter=2.05px (radius=1.02px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2891/3600 (80.3%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1456\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1456\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2161/2601 (83.1%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=1073.604±42.865 μJy (0.001074±0.000043 Jy) at λ=1.154 μm, mag_AB=16.323±0.043\n",
      "Processing observations:  54%|█████▎    | 58/108 [00:03<00:02, 19.28files/s]2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_4.fits\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (2.241896e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.588\" (0.91px) → diameter=2.73px (radius=1.36px)\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 2153/3600 (59.8%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2988\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2988\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Background mask: 1644/2601 (63.2%) pixels available\n",
      "2025-11-13 00:34:07 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=2641.889±96.582 μJy (0.002642±0.000097 Jy) at λ=3.882 μm, mag_AB=15.345±0.040\n",
      "2025-11-13 00:34:07 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.471404e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.478\" (0.73px) → diameter=2.19px (radius=1.09px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2883/3600 (80.1%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1484\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1484\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/2601 (82.4%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=1111.059±45.280 μJy (0.001111±0.000045 Jy) at λ=1.182 μm, mag_AB=16.286±0.044\n",
      "Processing observations:  56%|█████▌    | 60/108 [00:03<00:02, 18.76files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (2.329182e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.527\" (0.90px) → diameter=2.70px (radius=1.35px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/3600 (59.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3030\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3030\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1652/2601 (63.5%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=2274.227±91.826 μJy (0.002274±0.000092 Jy) at λ=3.916 μm, mag_AB=15.508±0.044\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (1.441440e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.480\" (0.73px) → diameter=2.19px (radius=1.09px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2859/3600 (79.4%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1353\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1353\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2128/2601 (81.8%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=1191.300±47.707 μJy (0.001191±0.000048 Jy) at λ=1.209 μm, mag_AB=16.210±0.043\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 28 pixels with NaN variance using median variance (2.362807e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.525\" (0.90px) → diameter=2.70px (radius=1.35px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2126/3600 (59.1%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1901\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1901\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1628/2601 (62.6%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=2348.428±92.304 μJy (0.002348±0.000092 Jy) at λ=3.950 μm, mag_AB=15.473±0.043\n",
      "Processing observations:  58%|█████▊    | 63/108 [00:03<00:02, 19.14files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_3.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.451720e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.756\" (0.77px) → diameter=2.32px (radius=1.16px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1532\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1532\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2138/2601 (82.2%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=1143.269±46.915 μJy (0.001143±0.000047 Jy) at λ=1.239 μm, mag_AB=16.255±0.045\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_3.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (2.401630e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.605\" (0.91px) → diameter=2.74px (radius=1.37px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2125/3600 (59.0%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2596\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2596\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1626/2601 (62.5%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=2302.212±90.589 μJy (0.002302±0.000091 Jy) at λ=3.984 μm, mag_AB=15.495±0.043\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_4.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.448073e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.684\" (0.76px) → diameter=2.29px (radius=1.14px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1694\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1694\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2148/2601 (82.6%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=1172.464±46.689 μJy (0.001172±0.000047 Jy) at λ=1.268 μm, mag_AB=16.227±0.043\n",
      "Processing observations:  61%|██████    | 66/108 [00:03<00:02, 19.60files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_4.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (2.518859e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.569\" (0.74px) → diameter=2.23px (radius=1.12px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/3600 (59.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2444\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2444\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1639/2601 (63.0%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=2242.229±88.374 μJy (0.002242±0.000088 Jy) at λ=4.019 μm, mag_AB=15.523±0.043\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (2.634656e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.496\" (0.89px) → diameter=2.68px (radius=1.34px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/3600 (60.8%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2615\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2615\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1661/2601 (63.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=2379.442±92.328 μJy (0.002379±0.000092 Jy) at λ=4.037 μm, mag_AB=15.459±0.042\n",
      "Processing observations:  63%|██████▎   | 68/108 [00:03<00:02, 19.32files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.435891e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.538\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1846\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1846\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2142/2601 (82.4%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=1143.112±44.632 μJy (0.001143±0.000045 Jy) at λ=1.284 μm, mag_AB=16.255±0.042\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.447795e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.536\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2870/3600 (79.7%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2307\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2307\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2144/2601 (82.4%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=1120.550±44.975 μJy (0.001121±0.000045 Jy) at λ=1.315 μm, mag_AB=16.276±0.044\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 17 pixels with NaN variance using median variance (2.910928e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.099\" (0.83px) → diameter=2.49px (radius=1.24px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2204/3600 (61.2%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3046\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3046\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1667/2601 (64.1%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=2031.299±88.358 μJy (0.002031±0.000088 Jy) at λ=4.072 μm, mag_AB=15.631±0.047\n",
      "Processing observations:  66%|██████▌   | 71/108 [00:03<00:01, 19.38files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0204_4.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (8.066626e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.608\" (0.91px) → diameter=2.73px (radius=1.37px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2096\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2096\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1969/2601 (75.7%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=1139.536±44.124 μJy (0.001140±0.000044 Jy) at λ=2.438 μm, mag_AB=16.258±0.042\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0204_4.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.516588e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.820\" (0.78px) → diameter=2.35px (radius=1.18px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2944/3600 (81.8%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1701\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1701\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2177/2601 (83.7%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=513.560±39.912 μJy (0.000514±0.000040 Jy) at λ=0.751 μm, mag_AB=17.124±0.084\n",
      "Processing observations:  68%|██████▊   | 73/108 [00:03<00:01, 19.13files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (6.193488e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.958\" (0.80px) → diameter=2.41px (radius=1.21px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2627/3600 (73.0%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2945\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2945\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1958/2601 (75.3%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=1274.580±38.202 μJy (0.001275±0.000038 Jy) at λ=2.501 μm, mag_AB=16.137±0.033\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_1.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (1.562245e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.822\" (0.78px) → diameter=2.35px (radius=1.18px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2093\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2093\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2250/2601 (86.5%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=668.962±42.221 μJy (0.000669±0.000042 Jy) at λ=0.768 μm, mag_AB=16.836±0.069\n",
      "Processing observations:  69%|██████▉   | 75/108 [00:03<00:01, 18.92files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (5.939406e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.960\" (0.80px) → diameter=2.41px (radius=1.21px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3071\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3071\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1967/2601 (75.6%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=1221.012±37.075 μJy (0.001221±0.000037 Jy) at λ=2.567 μm, mag_AB=16.183±0.033\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_2.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 8 pixels with NaN variance using median variance (1.550666e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.992\" (0.81px) → diameter=2.44px (radius=1.22px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2133\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2133\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2238/2601 (86.0%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=609.424±41.783 μJy (0.000609±0.000042 Jy) at λ=0.786 μm, mag_AB=16.938±0.074\n",
      "Processing observations:  71%|███████▏  | 77/108 [00:04<00:01, 19.08files/s]2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_3.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.576395e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.647\" (0.76px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2171\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2171\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2235/2601 (85.9%) pixels available\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=595.003±40.460 μJy (0.000595±0.000040 Jy) at λ=0.805 μm, mag_AB=16.964±0.074\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_3.fits\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:08 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (5.790259e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.314\" (0.86px) → diameter=2.59px (radius=1.29px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3242\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3242\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=1370.767±39.484 μJy (0.001371±0.000039 Jy) at λ=2.636 μm, mag_AB=16.058±0.031\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_4.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (5.448314e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.302\" (0.86px) → diameter=2.59px (radius=1.29px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3125\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3125\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1966/2601 (75.6%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=1315.342±38.577 μJy (0.001315±0.000039 Jy) at λ=2.706 μm, mag_AB=16.102±0.032\n",
      "Processing observations:  74%|███████▍  | 80/108 [00:04<00:01, 19.62files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_4.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (1.576505e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.647\" (0.76px) → diameter=2.27px (radius=1.13px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3039/3600 (84.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2252\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2252\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2241/2601 (86.2%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=735.192±42.276 μJy (0.000735±0.000042 Jy) at λ=0.824 μm, mag_AB=16.734±0.062\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.584829e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.838\" (0.79px) → diameter=2.36px (radius=1.18px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3037/3600 (84.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2557\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2557\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2253/2601 (86.6%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=721.219±43.073 μJy (0.000721±0.000043 Jy) at λ=0.843 μm, mag_AB=16.755±0.065\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.298661e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.589\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2641/3600 (73.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3188\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3188\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1966/2601 (75.6%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=1405.195±39.617 μJy (0.001405±0.000040 Jy) at λ=2.779 μm, mag_AB=16.031±0.031\n",
      "Processing observations:  77%|███████▋  | 83/108 [00:04<00:01, 19.73files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (5.243953e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.575\" (0.91px) → diameter=2.72px (radius=1.36px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2615/3600 (72.6%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3461\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3461\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1946/2601 (74.8%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=1557.544±41.189 μJy (0.001558±0.000041 Jy) at λ=2.854 μm, mag_AB=15.919±0.029\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (1.500622e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.549\" (0.74px) → diameter=2.22px (radius=1.11px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2080\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2080\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2255/2601 (86.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=793.754±41.839 μJy (0.000794±0.000042 Jy) at λ=0.863 μm, mag_AB=16.651±0.057\n",
      "Processing observations:  79%|███████▊  | 85/108 [00:04<00:01, 19.66files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (1.501274e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.687\" (0.76px) → diameter=2.29px (radius=1.14px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3018/3600 (83.8%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2063\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2063\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2234/2601 (85.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=924.035±44.099 μJy (0.000924±0.000044 Jy) at λ=0.883 μm, mag_AB=16.486±0.052\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (5.287452e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.383\" (0.71px) → diameter=2.14px (radius=1.07px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4092\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4092\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1950/2601 (75.0%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=1349.474±36.817 μJy (0.001349±0.000037 Jy) at λ=2.931 μm, mag_AB=16.075±0.030\n",
      "Processing observations:  81%|████████  | 87/108 [00:04<00:01, 19.58files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (1.481494e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.403\" (0.72px) → diameter=2.15px (radius=1.07px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3020/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2080\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2080\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2249/2601 (86.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=878.668±42.619 μJy (0.000879±0.000043 Jy) at λ=0.904 μm, mag_AB=16.540±0.053\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (4.931199e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=3.079\" (0.50px) → diameter=1.50px (radius=0.75px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2617/3600 (72.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3528\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3528\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1946/2601 (74.8%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=1015.837±30.529 μJy (0.001016±0.000031 Jy) at λ=3.011 μm, mag_AB=16.383±0.033\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_3.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 7 pixels with NaN variance using median variance (4.747215e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=3.080\" (0.50px) → diameter=1.50px (radius=0.75px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2624/3600 (72.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3728\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3728\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1951/2601 (75.0%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=854.004±40.411 μJy (0.000854±0.000040 Jy) at λ=3.094 μm, mag_AB=16.571±0.051\n",
      "Processing observations:  83%|████████▎ | 90/108 [00:04<00:00, 19.91files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_3.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (1.460178e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.399\" (0.72px) → diameter=2.15px (radius=1.07px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3019/3600 (83.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2154\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2154\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2240/2601 (86.1%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=727.004±40.411 μJy (0.000727±0.000040 Jy) at λ=0.925 μm, mag_AB=16.746±0.060\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_4.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 21 pixels with NaN variance using median variance (4.723504e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.255\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2644/3600 (73.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3956\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3956\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1976/2601 (76.0%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=1609.867±40.756 μJy (0.001610±0.000041 Jy) at λ=3.178 μm, mag_AB=15.883±0.027\n",
      "Processing observations:  85%|████████▌ | 92/108 [00:04<00:00, 19.85files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_4.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 22 pixels with NaN variance using median variance (1.457800e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.449\" (0.72px) → diameter=2.17px (radius=1.09px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3007/3600 (83.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2347\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2347\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2224/2601 (85.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=819.873±41.351 μJy (0.000820±0.000041 Jy) at λ=0.948 μm, mag_AB=16.616±0.055\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 14 pixels with NaN variance using median variance (4.935230e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.284\" (0.86px) → diameter=2.57px (radius=1.29px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3600 (73.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4528\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4528\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=1771.316±42.095 μJy (0.001771±0.000042 Jy) at λ=3.265 μm, mag_AB=15.779±0.026\n",
      "Processing observations:  87%|████████▋ | 94/108 [00:04<00:00, 19.71files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_1.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 11 pixels with NaN variance using median variance (1.411780e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.573\" (0.74px) → diameter=2.23px (radius=1.12px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3027/3600 (84.1%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1951\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1951\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2248/2601 (86.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=898.901±42.105 μJy (0.000899±0.000042 Jy) at λ=0.970 μm, mag_AB=16.516±0.051\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (1.393711e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.576\" (0.74px) → diameter=2.23px (radius=1.12px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3032/3600 (84.2%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1769\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1769\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2255/2601 (86.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=1218.523±45.826 μJy (0.001219±0.000046 Jy) at λ=0.993 μm, mag_AB=16.185±0.041\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_2.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 20 pixels with NaN variance using median variance (4.739665e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.277\" (0.86px) → diameter=2.57px (radius=1.29px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2645/3600 (73.5%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3908\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3908\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=1762.516±41.424 μJy (0.001763±0.000041 Jy) at λ=3.354 μm, mag_AB=15.785±0.026\n",
      "Processing observations:  90%|████████▉ | 97/108 [00:05<00:00, 19.88files/s]2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_3.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 10 pixels with NaN variance using median variance (4.657418e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.495\" (0.89px) → diameter=2.68px (radius=1.34px)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2643/3600 (73.4%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3628\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3628\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1970/2601 (75.7%) pixels available\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=1649.648±41.213 μJy (0.001650±0.000041 Jy) at λ=3.445 μm, mag_AB=15.857±0.027\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_3.fits\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:09 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (1.373315e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.521\" (0.74px) → diameter=2.21px (radius=1.11px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3041/3600 (84.5%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1554\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1554\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2260/2601 (86.9%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=885.334±40.874 μJy (0.000885±0.000041 Jy) at λ=1.017 μm, mag_AB=16.532±0.050\n",
      "Processing observations:  92%|█████████▏| 99/108 [00:05<00:00, 19.86files/s]2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_4.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (4.719877e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.836\" (0.95px) → diameter=2.84px (radius=1.42px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2665/3600 (74.0%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3709\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3709\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1989/2601 (76.5%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=1971.830±43.879 μJy (0.001972±0.000044 Jy) at λ=3.538 μm, mag_AB=15.663±0.024\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_4.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 15 pixels with NaN variance using median variance (1.343486e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.542\" (0.74px) → diameter=2.21px (radius=1.11px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3003/3600 (83.4%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1348\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1348\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2222/2601 (85.4%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=938.222±41.548 μJy (0.000938±0.000042 Jy) at λ=1.041 μm, mag_AB=16.469±0.048\n",
      "Processing observations:  94%|█████████▎| 101/108 [00:05<00:00, 19.11files/s]2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_1.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 19 pixels with NaN variance using median variance (5.108546e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.832\" (0.95px) → diameter=2.84px (radius=1.42px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2626/3600 (72.9%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4118\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4118\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1964/2601 (75.5%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=1844.657±43.295 μJy (0.001845±0.000043 Jy) at λ=3.634 μm, mag_AB=15.735±0.025\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_1.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 12 pixels with NaN variance using median variance (1.690161e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=4.949\" (0.80px) → diameter=2.41px (radius=1.21px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3012/3600 (83.7%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4808\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4808\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2232/2601 (85.8%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=1012.836±46.497 μJy (0.001013±0.000046 Jy) at λ=1.065 μm, mag_AB=16.386±0.050\n",
      "Processing observations:  95%|█████████▌| 103/108 [00:05<00:00, 19.21files/s]2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_2.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 13 pixels with NaN variance using median variance (3.226726e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.055\" (0.82px) → diameter=2.46px (radius=1.23px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3017/3600 (83.8%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 2.6388\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 2.6388\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2231/2601 (85.8%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=1045.197±57.026 μJy (0.001045±0.000057 Jy) at λ=1.091 μm, mag_AB=16.352±0.059\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_2.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 18 pixels with NaN variance using median variance (5.286015e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.639\" (0.92px) → diameter=2.75px (radius=1.37px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2637/3600 (73.2%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3300\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3300\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1969/2601 (75.7%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=1889.274±43.481 μJy (0.001889±0.000043 Jy) at λ=3.731 μm, mag_AB=15.709±0.025\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_3.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 16 pixels with NaN variance using median variance (1.359724e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.054\" (0.82px) → diameter=2.46px (radius=1.23px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2997/3600 (83.2%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1747\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1747\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2211/2601 (85.0%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=1160.069±45.452 μJy (0.001160±0.000045 Jy) at λ=1.116 μm, mag_AB=16.239±0.043\n",
      "Processing observations:  98%|█████████▊| 106/108 [00:05<00:00, 19.38files/s]2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_3.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 4, shape (54, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 6 pixels with NaN variance using median variance (5.430989e-02). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.641\" (0.92px) → diameter=2.75px (radius=1.37px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2415/3240 (74.5%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2421\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2421\n",
      "2025-11-13 00:34:10 - spxquery.processing.background - WARNING - Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1910/2499 (76.4%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=2550.316±48.841 μJy (0.002550±0.000049 Jy) at λ=3.832 μm, mag_AB=15.384±0.021\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W29_2A_0482_1.fits\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W29_2A_0482_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Repaired 9 pixels with NaN variance using median variance (1.133680e-01). All repaired pixels have non-zero flags.\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.018\" (0.82px) → diameter=2.45px (radius=1.22px)\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2693/3600 (74.8%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1333\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1333\n",
      "2025-11-13 00:34:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1964/2601 (75.5%) pixels available\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W29_2A_0482_1.fits: flux=1138.217±42.638 μJy (0.001138±0.000043 Jy) at λ=1.940 μm, mag_AB=16.259±0.041\n",
      "Processing observations: 100%|██████████| 108/108 [00:05<00:00, 19.35files/s]\n",
      "2025-11-13 00:34:10 - spxquery.processing.photometry - INFO - Successfully processed 108 observations\n",
      "2025-11-13 00:34:10 - spxquery.processing.lightcurve - INFO - Generated light curve with 108 measurements\n",
      "2025-11-13 00:34:10 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2025-11-13 00:34:10 - spxquery.visualization.plots - INFO - Quality filtering: 108 total points (103 good, 5 rejected - shown as crosses)\n",
      "2025-11-13 00:34:10 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n",
      "2025-11-13 00:34:10 - spxquery.visualization.plots - INFO - Sigma clipping: 108 -> 107 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 108\n",
      "Time span: 33.1 days\n",
      "MJD range: 60842.27 - 60875.36\n",
      "Wavelength range: 0.75 - 4.97 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 27.2\n",
      "\n",
      "Observations per band:\n",
      "  D1: 18\n",
      "  D2: 18\n",
      "  D3: 18\n",
      "  D4: 18\n",
      "  D5: 18\n",
      "  D6: 18\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-13 00:34:10 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2025-11-13 00:34:10 - spxquery.core.pipeline - INFO - Pipeline execution complete\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM-based aperture configuration ready.\n",
      "  Aperture = FWHM × 3.0 (adaptive per observation)\n",
      "  Fallback diameter: 3.0 pixels\n",
      "Uncomment the code above to run the pipeline.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demo 2: Run pipeline with FWHM-based aperture\n",
    "config_fwhm = SPXQueryPipeline(advanced_fwhm)\n",
    "config_fwhm.run_full_pipeline(skip_existing_downloads=True)\n",
    "df_fwhm = pd.read_csv(output_dir / \"results/lightcurve.csv\", comment=\"#\")\n",
    "\n",
    "print(\"FWHM-based aperture configuration ready.\")\n",
    "print(f\"  Aperture = FWHM × {advanced_fwhm.photometry.fwhm_multiplier} (adaptive per observation)\")\n",
    "print(f\"  Fallback diameter: {advanced_fwhm.photometry.aperture_diameter} pixels\")\n",
    "print(\"Uncomment the code above to run the pipeline.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cell-ap-compare",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z5/qygyj_xj7dq109c9rzqq2wv40000gn/T/ipykernel_78266/2193692466.py:19: UserWarning: The figure layout has changed to tight\n",
      "  plt.tight_layout()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean flux difference: -9.35%\n",
      "Std flux difference: 14.48%\n"
     ]
    }
   ],
   "source": [
    "# Compare flux measurements\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "# Plot 1: Flux comparison\n",
    "axes[0].scatter(df_fixed[\"flux\"], df_fwhm[\"flux\"], alpha=0.6)\n",
    "axes[0].plot([0, max(df_fixed[\"flux\"])], [0, max(df_fwhm[\"flux\"])], \"k--\", alpha=0.3)\n",
    "axes[0].set_xlabel(\"Fixed Aperture Flux (MJy/sr)\")\n",
    "axes[0].set_ylabel(\"PSF FWHM-based Flux (MJy/sr)\")\n",
    "axes[0].set_title(\"Flux Comparison\")\n",
    "\n",
    "# Plot 2: Difference\n",
    "flux_diff = (df_fwhm[\"flux\"] - df_fixed[\"flux\"]) / df_fixed[\"flux\"] * 100\n",
    "axes[1].hist(flux_diff, bins=20, alpha=0.7)\n",
    "axes[1].set_xlabel(\"Relative Difference (%)\")\n",
    "axes[1].set_ylabel(\"Count\")\n",
    "axes[1].set_title(\"Flux Difference Distribution\")\n",
    "axes[1].axvline(0, color=\"k\", linestyle=\"--\", alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"Mean flux difference: {flux_diff.mean():.2f}%\")\n",
    "print(f\"Std flux difference: {flux_diff.std():.2f}%\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/z5/qygyj_xj7dq109c9rzqq2wv40000gn/T/ipykernel_78266/3065869908.py:30: UserWarning: The figure layout has changed to tight\n",
      "  plt.tight_layout()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irsa = pd.read_csv(output_dir / \"cloverleaf_irsa.csv\")\n",
    "fig, ax = plt.subplots(1, 1, figsize=(8, 6))\n",
    "ax.errorbar(\n",
    "    df_fixed[\"wavelength\"],\n",
    "    df_fixed[\"flux\"],\n",
    "    yerr=df_fixed[\"flux_error\"],\n",
    "    xerr=df_fixed[\"bandwidth\"] / 2,\n",
    "    fmt=\"o\",\n",
    "    alpha=0.7,\n",
    "    markersize=4,\n",
    "    label=\"Fixed Aperture\",\n",
    ")\n",
    "\n",
    "ax.errorbar(\n",
    "    irsa[\"lambda\"],\n",
    "    irsa[\"flux\"],\n",
    "    yerr=irsa[\"flux_err\"],\n",
    "    xerr=irsa[\"lambda_width\"] / 2,\n",
    "    fmt=\"o\",\n",
    "    alpha=0.7,\n",
    "    markersize=4,\n",
    "    label=\"IRSA PSF Model\",\n",
    ")\n",
    "\n",
    "ax.set_xlabel(\"Wavelength (μm)\")\n",
    "ax.set_ylabel(\"Flux (uJy)\")\n",
    "ax.set_title(\"Fixed Aperture vs. IRSA PSF Model SED\")\n",
    "ax.legend(ncol=6, fontsize=8)\n",
    "ax.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# # Create spectral comparison plot with shared y-axis limits\n",
    "# fig, axes = plt.subplots(2, 1, figsize=(10, 8), sharex=True, sharey=True)\n",
    "\n",
    "# # Calculate shared y-axis limits based on both datasets\n",
    "# all_flux = pd.concat([df_fixed[\"flux\"], df_fwhm[\"flux\"]])\n",
    "# all_flux_err = pd.concat([df_fixed[\"flux_error\"], df_fwhm[\"flux_error\"]])\n",
    "# ymin = (all_flux - all_flux_err).min() * 0.9\n",
    "# ymax = (all_flux + all_flux_err).max() * 1.1\n",
    "\n",
    "# # Plot 1: Fixed aperture SED\n",
    "# axes[0].errorbar(\n",
    "#     df_fixed[\"wavelength\"],\n",
    "#     df_fixed[\"flux\"],\n",
    "#     yerr=df_fixed[\"flux_error\"],\n",
    "#     xerr=df_fixed[\"bandwidth\"] / 2,\n",
    "#     fmt=\"o\",\n",
    "#     alpha=0.7,\n",
    "#     markersize=4,\n",
    "# )\n",
    "# axes[0].set_ylabel(\"Flux (uJy)\")\n",
    "# axes[0].set_title(\"Fixed Aperture SED\")\n",
    "# axes[0].legend(ncol=6, fontsize=8)\n",
    "# axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# # Plot 2: FWHM-based aperture SED\n",
    "# irsa = pd.read_csv(output_dir / \"cloverleaf_irsa.csv\")\n",
    "# axes[1].errorbar(\n",
    "#     irsa[\"lambda\"],\n",
    "#     irsa[\"flux\"],\n",
    "#     yerr=irsa[\"flux_err\"],\n",
    "#     xerr=irsa[\"lambda_width\"] / 2,\n",
    "#     fmt=\"o\",\n",
    "#     alpha=0.7,\n",
    "#     markersize=4,\n",
    "# )\n",
    "# axes[1].set_xlabel(\"Wavelength (μm)\")\n",
    "# axes[1].set_ylabel(\"Flux (uJy)\")\n",
    "# axes[1].set_title(\"FWHM-based Aperture SED\")\n",
    "# axes[1].legend(ncol=6, fontsize=8)\n",
    "# axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "# plt.tight_layout()\n",
    "# plt.show()\n",
    "\n",
    "# print(f\"Shared y-axis range: [{ymin:.2f}, {ymax:.2f}] MJy/sr\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "spxquery-py3.14",
   "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": "3.14.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}