{
 "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": [],
   "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": [],
   "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": [],
   "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": [
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:29:47 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2026-05-19 17:29:47 - 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": [
      "2026-05-19 17:30:01 - spxquery.core.query - INFO - Found 218 observations (6 bands, 225 days span)\n",
      "2026-05-19 17:30:01 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2026-05-19 17:30:01 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2026-05-19 17:30:01 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2026-05-19 17:30:01 - spxquery.core.download - INFO - Starting parallel download of 218 files\n",
      "2026-05-19 17:30:01 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=5\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: 2026-05-19 17:30:01\n",
      "\n",
      "Total observations found: 218\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  36 observations\n",
      "  D2 (1.10-1.62 μm):  36 observations\n",
      "  D3 (1.63-2.41 μm):  37 observations\n",
      "  D4 (2.42-3.82 μm):  36 observations\n",
      "  D5 (3.83-4.41 μm):  36 observations\n",
      "  D6 (4.42-5.00 μm):  37 observations\n",
      "\n",
      "Time span: 224.6 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "2026-05-19 17:35:20 - spxquery.core.download - INFO - Total size: 555.5 MB\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Downloaded 218 files\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.54 GB (actual)\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2026-05-19 17:35:20 - spxquery.core.pipeline - INFO - Processing 218 FITS files\n",
      "2026-05-19 17:35:20 - spxquery.processing.photometry - INFO - Processing photometry for 218 observations\n",
      "2026-05-19 17:35:20 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 218\n",
      "Successful: 218\n",
      "Failed: 0\n",
      "Total downloaded: 555.5 MB (0.54 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  37%|███▋      | 81/218 [00:01<00:01, 93.34files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations:  56%|█████▌    | 121/218 [00:01<00:00, 137.84files/s]Insufficient background pixels for zodiacal estimation (1621/3600 = 45.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Processing observations:  71%|███████   | 154/218 [00:01<00:00, 166.44files/s]Insufficient background pixels for zodiacal estimation (0/3600 = 0.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Insufficient usable pixels with strict masking: 0/10 required. Trying with relaxed masking (exclude_bad_only=False).\n",
      "Insufficient usable pixels in background window even with relaxed masking: 0/10 required (window: 50×50, aperture_radius: 1.1)\n",
      "Background estimation failed for 2026W03_2A_0316_4.fits - dropping observation\n",
      "Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations: 100%|██████████| 218/218 [00:01<00:00, 112.08files/s]\n",
      "2026-05-19 17:35:22 - spxquery.processing.photometry - INFO - Successfully processed 217 observations\n",
      "2026-05-19 17:35:22 - spxquery.processing.lightcurve - INFO - Generated light curve with 217 measurements\n",
      "2026-05-19 17:35:22 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2026-05-19 17:35:22 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2026-05-19 17:35:22 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2026-05-19 17:35:22 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2026-05-19 17:35:22 - spxquery.core.pipeline - INFO - Filtered photometry results by bands ['D1', 'D2', 'D3', 'D4', 'D5', 'D6']: 217 -> 217 measurements\n",
      "2026-05-19 17:35:22 - spxquery.visualization.plots - INFO - Quality filtering: 217 total points (206 good, 11 rejected - shown as crosses)\n",
      "2026-05-19 17:35:22 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 217\n",
      "Time span: 224.6 days\n",
      "MJD range: 60842.27 - 61066.92\n",
      "Wavelength range: 0.75 - 5.00 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 25.1\n",
      "\n",
      "Observations per band:\n",
      "  D1: 36\n",
      "  D2: 36\n",
      "  D3: 36\n",
      "  D4: 36\n",
      "  D5: 36\n",
      "  D6: 37\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2026-05-19 17:35:22 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n",
      "2026-05-19 17:35:23 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:35:23 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2026-05-19 17:35:23 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:35:23 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:35:23 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:35:23 - 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": "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": [
      "2026-05-19 17:41:21 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2026-05-19 17:41:21 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:21 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:21 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:41:21 - spxquery.core.pipeline - INFO - Loaded pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:21 - spxquery.core.pipeline - INFO - Resuming from saved state\n",
      "2026-05-19 17:41:21 - 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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N5K6s798WpqtdIJWPtSL3vb03ea0n4mP2HJ9EW7TNfx7LyPY/OOQITQgVZEWMLxAIrDdegwXm99tvv9S01VZb9er+5WxJnK4E692Th0LdEqw3s2bNSgXrLWP9kEMO0e67765hw4a5rHYbxMAy223QW5ss2/6BBx7Qsccem3Z7ti2rx291+M3gwYN1xhlnuBGLa2tr9dBDD+mpp55y5XxOPvlkl3l/1FFHtfuBYKWAbD+Tf5S2vcmTJ2vlypW699579eqrr7qMfdvOM8884/a/LVb737aXHJjB6jlNmzbNZe0vWrRId955p6sB9fHHH7v1Xn75ZXeFAAAAAAAAALJYYf/e3gP0JF/y45nbdrZ47rnn9MILL7jJ4pSW2GyTlU83lZWV2nfffVMB/F122cUF+fNRt2bY96ZvfetbLhh+0UUXuQC1nQzY0Lp161xw/R//+EfqbKoFvi1LfkP/93//px/96EfuttVLsgC6Zb+3ZgPnXnzxxe72kCFDXKZ7eXl52v37xje+odtvv93dTtZiar2uvQ3nn3++GwE5eYbt7bffVjAYTLs9OyHx9NNPu9t2eYgF/AsKClL3t7S0uKsD/va3v7n2YYcdpieeeEKdQYZ978j6s/wANhn9G8hN9G0gd9G/gdxF/0bWZdhHWrT1vzOTYf/hoUdoQjg7MuxbszioxT0teP/iiy+6yRKsjfdpFr6VON9rr71SAfwDDzxQ+aJbA/YLFy7cpMdZtvnmWrNmjRtNuDN17i2rPflHYPX2v/71r6+3jmXQW3De1jWW+b7HHnuk3d4RRxyhxx9/3N22mvZXXHHFRutYIN8u64jH467GvJ1YSHfMViLIzh69++67rm1Z8lbvf0MWqLeAffJqAtteuhMFdhx2smHFihWu/eyzz7ra/h0hYN87+NIA5C76N5Cb6NtA7qJ/A7mL/o1sC9jPjbRoq38lYovdIVZTq1htrbs992vTNKGoWB9++KGy3SeffOIC+M8//7z++9//unhnMnhvc4ub5otuva7ASq50dZowYUK3PHdngvXJszM2unCSnc3ZkA1cmwzW26UYbQXrjWX0J1mWezr33XefC9Ybq2Hf1gkKuyrAsuyTkpeEbKj18jPPPLPNrH5bbvd3tD0AAAAAAAAAfd+q2+/Uh/sd5KaW+QtUVVWlvsBixJa4/Ic//MHFUi+//HJVVFS4bPwcKRDTOzXsN+XF640XvHWAu6GhYaP7rVxNUkcD01rGup0EsAC/nfmxbHrL4N/U7VnGfpKV4WlsbHT18Tdne9dcc427/c9//rPddQEAAAAAAHKRJVK2RKsUj/t5Wxcb2Sse774BhitPO00VU6e62/O+Pk2VRUXKZs3Nza66SbI0zssvv+yqhljM2EqFWzUSKy+eT7o1YD9v3rx277cBWu0N+PnPf+4GS7VBYLfeemv1NBuANmncuHHt3t9edn0yK37nnXd2f1DJx7YO2Nsf13vvvdfp7Q0fPlyjRo3S4sWL3aUeNnDsrrvuut6lW8uXL3e37Y+29X3p2P32QWQfTDagrZ1Vs0EcAAAAAAAA8kFD8zItWfNPtUSrFVCZ+hdYuWDGj0NuCpaXu8l44VDWnaBau3atK3mTrF//xhtvuLE4LYZqSdZ77bWXC9DbtOeee7pE6XzTrQH7sWPHdrjODjvsoK997WuuBrsNxPrmm2+qJ3388cf617/+lWofddRR691vfxyWJZ9kZXs6YuskA/YfffTRevctWbJEdXV1qQD76NGjO7U9C9gnt9c6KN96+yNHjlQ4HG53WzYQra23aNGi1OPz7awUAAAAAADITxbnsWB9U2S1fD+quCKqaXlOw/2tUvWxgd7lKeZn6m8xe/7Gzz77bBc/tdhksnS4xZKnTp2aCtBvv/329MvuDth3VlFRkX7xi19o991317XXXqubb765R543FovpjDPOSP1R2B/ENttss946FlyPRCKp9qBBHZ9xbb1OdXX1RmeNkvr3799hgL0r2+vMviXXSwbsN9xeW+bMmeMGyk0neXIC3cuuQAGQm+jfQG6ibwO5i/4N5I6436TmSI0L1kth+X6LorF1WrV6iQJedpcKQc+w8SvbqiQyadIk3oZucuutt7pg/I477qjp06fr0EMP1YgRI3h90+i1ayIsa9wuaXj00Ud77DnPO++8VLB5yJAh7qTBhtatW7dee8P68em0XsdqLLW1vc5sq6e3BwAAAAAAkKs8FSrolcpTUFKL1T+QpxK3HMgGNrynH/cyM2XRWK1W7saueHnrrbf0zW9+U8cff7wuueQSFxvuKwPj5nSGvbEsd8t4X7ZsWY88309+8hP95je/SZWJ+ctf/sJZnHbYGcT333+/R94brK+zV04A6Hvo30Buom8DuYv+DeSG0uZjNqphP3jw4N7eLWSJDctbJ2277bY9tg/xLAqsZ4pVDXn33XdTtettbgPM3nDDDe7+LbbYwl3tsO+n08SJE5Wvei1g/8wzz6ipqUlDhw7N+HPddNNNuvTSS91tK0lz//3368ADD0y7br9+/dZrNzY2brRsQ7ZO67NFbW2v9XrZsj0AAAAAAIBcVlI4XBOHnq765gVqXFeadYNwAvnAyuHY2KY2fec730mVHbLg/fPPP+8Gor3tttvcZOtazNjq2icD+K3H+Mx1PR6wt/rwDz30kC688EL34h988MEZfT47S/Pd7343lVn/wAMPbDTQbGtlZWUKhUKKRq22mbR69eoOA/a2TlJFRcV697VuWx1E265tvzu213q9Td0eAAAAAABArrMYVFF4kJq8pt7eFWAjsXj2DA7bk8aPH++mr33ta6kY5osvvpjKwP/73/+uv/3tb67/JmO1+aBbA/YTJkxo937LqF+5cqWrV2STDcJ6xRVXKFOuu+46XXbZZe52YWGhO1Fw+OGHt/sY+wOwSzA++OCD1Jke+8Npj62TtOFAraNGjXInAWwwWysBtHDhwg5fp/a217q9ZMkSdwKkvYFs7X5br63tITdYf4pHahUIlzOaNgAAAAAAaQTicV4XIItZ0vSAAQPcNHDgQBUVFbmYar7p1oD9/PnzO72uXcrwy1/+0gXHM+Gqq67SlVdemRp09eGHH9aUKVM69Vi7NCMZsJ85c2a7VwHY2Z0333xzvcdueAJgu+220yuvvJLaXnsBe6vpv3jxYnc7GAxqm222We9+q7E2bNgwLV++3J0AeP3117XXXnu1ub3//e9/brwAYyMvV1ZWdnD06It8P65o8yqFQ2XyPBtIBwAAAAAAJMXjMTU2LlA8PtTFW4BsYQPDxjOUYZ9Ng86ms2bNGlcKJ1nX/o033nDJx8nk1OQ4m/vtt5/ySbcG7O+44472nywUcmdIdtxxR40cOVKZ8oMf/EA//vGP3e2SkhI32nBXSu8cccQRuu+++9ztxx57TN///vfbXPe5555TfX29uz158mQ3pdteMmBv2/vKV77S5vbs/qSDDjrInWxIt73bb789tX57AfvW27PHIfdEGharesEDirWsVbBggCrGflnhklG9vVsAAAAAAGSFSP1i1c6/X9GWKinYX36lxUcG9fZuAXnHkr1bl7z5+OOPU5VYjI0vseOOO7oAfXLqifFPczpgf+qpp6q3XXLJJbr++uvdbStF889//lP7779/l7Zx9NFHq7S01AXi7Y/HsuL32GOPtOveeOONqdsnn3xy2nVOPPFEl+1vme424O21116r0aNHp83Wv/nmm1PtU045Je327HmSAftbb73V1ehPV2e/trZWv//97zvcHvqOuB/XWq3TAPVTwAu4DIHqBX9RtHm1FI8q1tyimoUPqHLL8+R5DKIDAAAAAMhvdkX62vl/VqxppTw/Lj/eonjVo/JHbMPvZmQN38/9GvYWC126dKm7nQzQWwnz3XffPRWc33vvvVVeXq58l1MRvYsuuigVrLc398knn+xysN5Ybf3kQLXm61//euoPasNg/eOPP+5uDxo0SBdccEHa7VnZH9uGaW5udgF3C6a3Zn+otv/vvvuua2+99db66le/mnZ7hxxyiMu+NytWrNBpp52mlpaW9dax9umnn+7uN4ceeqgOPPDALr0OyC4r/bW6X0/rQT3n5taORxsVi9S4YL0XLJRvQfuWGvkxBtEBAAAAAMB+N0daqlywPhbw3Dweq3bLAXzGEpdtkNcLL7xQBxxwgIYPH+4C6pbUPHbsWB1zzDEuMXhTa8rbGJuWcHzYYYe5ZObnn39eNTU1bm7tL3zhCwTrM5Fh35t++MMf6qabbkq1v/Od77gBbq12fXss0G719Df0ve99T0888YQrZWOXZ+y0004688wzXT16C7bbALZ2QsBY7TP7g7VAf1vsRIJd7jFnzhw3t1r3Z5xxhqvDtGrVKt17772psjlWxsfKC1kJobbccsst7qyTjZ784IMPauedd3aBeztbtWjRIvf4ZB3+IUOG6He/+10nXkVseBJlWZOv4UVerw/kavvytN7QGq1TVDE3/bflBW1TtVLFiihkuxdrkhcIK1jQX16wqFf3FwAAAACAbGBB+ljQUzAmBeOJrN5oIOCWU8ke2aK3x0O2mKqVGG9q2jgB1JKCFy5c6KZHHnlEV1xxhYuDHnnkkV16DqtPb+VuejvGltMBe3uTusuYMWM2extWuqa16667rlOPszNGzz777EbLrXa8ldOxevP/+te/XFA9WRe/Ncvkt2D4scce2+7z2GCxTz31lI4//ng3UOyCBQvcSYYN2YCyd999t/bcc892t2e18u2EwQknnKC5c+e64HzrqwJar2dleCZOnNju9rCxuO9r1rqYhhYGFezlf0yaFVGdGhVTTAUKKeJHNGTNPDXFIoqUFam8rtF98SgoHKL+Y77MZX0AAAAAAFjgyytUS0GBQtGIPKuV7XlqKSxwywEkzJo1KxWst5rxVt3DStVYnDIWi+mdd97Rn/70Jy1btsxNlm3/wAMPdBgldNrZAABiKUlEQVQPbc2SoZHhgP348ePVHeysitVuz0YDBw50QXbLpr/nnnv02muvuRIzyUtBvvjFL+qss87q9AC69pq9+uqrLiD/l7/8xf2x24kAy8y3gLr9kX/zm990A/N2xi677OJK6Nx2220uy/6jjz5SVVWVKisrtdVWW2nq1Kn6xje+kXbgWrTvzbVRfeeNBi1siGtMSUC/3qVEOw/ovQtSChVWmYrVoohaFFVR3FNBLCrfjykeLtWa8qDCXoEmDv+GwgXU+gIAAAAAwKyKr1A04KmxqEBxz1PA9xX0wvL9ZqtxwIuEXmfl3OPxzCSKfloqvlPx2YMPPtiV654yZcpGVT9sXMzLL7/clfn+xz/+4YL4VonESna3V3EEm8bzk1X+u8hG7e0uNhgrsse2227r5u+//77ygXWBKj+qSi/k/oGyzPr9nl6nj9bF1BiTioPSVv2CeuFgG+g1c5n2Vt4oWaYpHatZ/7ReV60aVO4Xa/sV8xSNVsuLNaswElHAlwoLhmnIsGNVVDQiY/sJoPv7N4C+ib4N5C76N5A7v/f/7P9HWy94VaXNTQpa/XovoHBwkMZOOper09Hr8TF7jllNEQ1/6D8Z2f6y4w7RFkXhDo9hzZo1LnG5M3XurZqHZdmbu+66KzVuJ7rPJqcMz5s3rxt3A+g9FqBfFGvWgGCi9E11xNfSpriaYlJ5SFoXlWvb8oEFvVcaZ4g3QCf4B2uJVmukN0gLy2dq1dpn1M+C9fG4bM8iLau0avnDGjX2bL54AAAAAADympWXrfea9fawMdpx2UIVRlvUHCrQoJID+c2MLOIplqEMe9t2Z3QmWG+s6sjRRx/txtY0b7/99mbtHbo5YG8lYYC+bna0UT9vWKwV8YiGBsK6oGSUJoaLNKIooNpITLXRRIa9tSvCvT8ohidPA9RPftzX7OhbNtiC+jUmRraPep5CflTRaK3i8SYFg1zaBwAAAADIX1ZetlRFWhcu0pyhQ1QQjSoWLFBFM6WDgU1l43kmNTQ08EJmQPfVtUFOsTJF8+fPT03V1dXKxcx6C9YvjDVrnR9z8583LHH3/WqXEm3ZL+gy6m1u7UyWw+ksK9lT5hWrSesU96OKBwJudHuraxX0fXleUKFQuQKBot7eVQAAAAAAev039CH+zhrSUqewH5eCnsJ+TJ+E33TlcoANWfwrGQuLRCI9VsbbathnYsoEG5Mzady4cRl5jnxHwB5p2eC1NkhucpoxY0bOvVJ1fkxV8aha5KtEATevikfcchtg9oWDynT3nqVu3psDzqZT7JUr4IXs24dWlZerJRRSLBBQuGCIBg87lkv7AAAAAACQNMArUYkflKW6hVUgX3G1eI2KyAadBdZn8a9kLGz27NkuPobPfPzxx/rXv/6Vah911FG8PBmwWVFIG3h2+PDhWrIkkZXc2ocffujORO2www6b8xToJZWVlZo5c2aqXVFRkXPvxZJoROvicZedXq+4CjxPlYGwyrygu98y6rfoF8yKzPp0fW+b4oP0QeMzagl7WlY5VBOD22pU6T4KBBL7DwAAAABAvgurUEVeiSJ+syxlL6CgCvxitxzY0PTp0zVt2jR3e8qUKQoGMx9jsYs97AKQzbH6hIPTLo8tni9NnrR5G09uKxbTGWeckbrqYOrUqdpmm226ZdtY32anDbd1CdHBBx+sVatWKRqNbu5ToJcCwrl8WYuVw/lZ7Qo1xQJSyFfA8+X7ns4vHpEK0NulcyOKsy9YnzSyYEsNDUzUwui7Gh3cTp7XSGY9AAAAAACt2G/7HQsP0NvNz6kxbqVxijQxsotbDmzIElaTSavhcLjHXqCYn/1/j+edd55efPFFd3vIkCH6xS9+0du7lLMyWueDemDIVnV+XKviETX7nkoiYTUorqJAUMODhX3uxMrA0CgFA0EFAp8N+gEAAAAAABIqgoO1X9GXVO9Xq3FNVAEvfytEW6xueZOvYUUeJy1yyIC/PJN2+doTD+qW7f/kJz/Rb37zG3e7oKBAf/nLXzRixIhu2TY2ll2FuYEeUuYFNDgQVn08rgb5KlCibcv7WsC+IjC4t3cDAAAAAICsZhn1hX5YTYopn1nFgVm1MQ0pDCrIVQZZI1MDxHaHm266SZdeemnqqoP7779fBx54YG/vVk7rW9FJoJtY2ZtL+g/T2FCByr2gxoUK9P3+w7OyXj0AAAAAANh0VnO7KrZWdZHVeV0N4q01UR30r3qd+t8GN7c20J4bbrhBF110USqz/sEHH9QxxxzDi5ZhZNgjb20ZLtIfBo7VgliLxgYLFAxw/goAAAAAgFyy2l+jl1qeVb+6RQrHYipUmYb7+0sapHzLrD/vtUZ9XBtTY0xqjMVc+9kpZSQv9jI7hfTpOK4Z2famuu6663TZZZe524WFhXrooYd0+OGHd9u+oW1EKJHXLEg/IVxEsB4AAAAAgBxj2fTPx2aqrG6hwtEWBfyoWvwarYz9N+8y7atbfC1tjKspJpWF5ObWtuXAhq666qpUsL64uFiPPPIIwfoeRIY9AAAAAAAAck6zWtTk1ykUjyogXzHPU9D3FVWDon6Twl6x8kVFgacRxQHVRqJaF5WKg9KI4qBbjl7mS36mathvwvmYH/zgB/rxj3/sbpeUlOjRRx/VwQcf3P37hswF7FesWKFgMNjm/e3dlxz0IxqlZhbQ2bp7tapRufq7AWcBAAAAAEB6hSpQkVemaCCkQDzigvW+PIVUopBXlFcvm43Z952tCvTtN6KKBeQmazOWH1q75JJLdP3117vbZWVl+uc//6n997cSUuhTAft8u4QI6C1r4lV6NfqS6v06lXpl2jO0twZ4A9USr1dBoNSd/AIAAAAAAAn2O3n/4B56qaxB/dYtVChuNez7aUhgn7z7DW017H8xp1lKHrYn1z5+DEH7bBDPVIZ9F9jgsjfddJO7XV5erscff1x77713b+9WXtqsgP0VV1zRfXsCoN0TYxasr/GrFVNMUT/q2lOCR6gxWqVwuCTvvmwAAAAAANCRQd5A7RXcRy/0i8j3IyqIFWtQSzjvXrjqiK+lTZ/WsA9K9VbDvinulg+kLE7e++EPf5gK1pvvfOc7WrlypR5++OF2X5tBgwZp3333zfvXr7sRsAf6gBa1aOXiVVKllR/z1FjVoKKhcb2z7m61xNapMFiuSeWHqSw8tLd3FQAAAACArLE6tlpPx59SzIu5rPKIV6/3A+9ovD8hrxLfKsKeRhRZDfuY6mKf1rAvCrjl6F1WuyQWz9y2O+OFF15Yr33dddd16nEHHHCAnn322U3YM7SHIthAH7Bi8QpVz6tXzeu1qn29RvWfNEjzVqkpukZRv9Fl2c+pfZISVQAAAAAAtLpa/ZXYS+5K9WTgMq64mrwmlxiXT6xW/a92KdGW/YIuo97m1qaGPZCDNewBZF754Aq1zC1UKNaogI0b4QVUVmFfM2IKqlAx+6oRr8u7Ue4BAAAAAGiLBeXr/fpUsN7mlk9e6NtwtAV598LtPCCkFw4q0wurY9pvUFDBAHm8WcH3MlfD3u/cdsmSzy4E7JFWPB7X/PnzU+2Kigo3oXcUKqywV6iGgO+yAQJeULFAswKKKiabh1QQKMu7Ue4BAAAAAGhLWGE1W0w6/lmJCd/ztE3T9vJK8rMUjGXUb9EvSGZ9G6qrq91kIpGIgsFgT749gMOpNKRVVVWl8ePHp6YZM2bwSvWiqtVVmuQPVUmgSKFAWMV+gQa27K7iUKVCXrGbWw37fKq/BwAAAABAe5q9qGqD5YoEQoopoGYvqLWBASryy/L2hbO4wYjiAPGDNlj8KxkLmz17touP9QQ/5mVkQt9Ehj3Sqqys1MyZM1Ntsut7TkxxrVa9BqlUwU/PqY0aNcrNDx60vxZrjYpWxzVm1BjF43uoMbZGxcGBCnApGwAAAAAAKUUKqzjQTxZyjQWjCiioiliJCn3CYUhv+vTpmjZtmrs9ZcoUMuzRK/gXCmlZ8HfcuHG8Oj1sZbBeD+hjVatRFSrW0dpOI9Q/FbT35Wu4KlU2qij1PpUGBvE+AQAAAACwAU+ejtAOeizwjmrUoP4q0d41Y9xyIJ3WJaHD4XCPvEg2VGEsnrlto+8hYA+0M5r88kZfw4q9HrlUzILxT5fN11o1u8r0EcX1iN7TN7W3Ap9+mbAvFf3EoLIAAAAAAHTGcFXoNO2rharSGFVqTWwNLxyyTsYGnUWfRA17oA1x39es2pib94RmL6a6QMQF6wsUdPNaNatJEd4jAAAAAAA2kSW/VaofmfUA+gQy7IE03loT1fkzG7WwPq4xpQHdvEexdhqY2e5S6AdVFg8rEoyrRTGFFFS5Cl3NPQAAAAAAsGkSV6snSssC2SieoZI46JvIsAc2YBn1FqyfVRPT2mbfza2d6Ux7+wJxcN04DVapihV2c6thnyyHAwAAAAAAcqsU76pY1M0BIIkMe2AD1S2+ljXE1RSTysPSuohc25YPLMxs8HxIrFRn6nNaoDUaq4EKck4NAAAAAICcZImBC6LNGhguVrAHxs5DlvIlL0M17DkX1DcRsAc2UFHgaXhJQOsiMdVGpOKgXNuW9wTLqB+kMjLrAQAAAADoBbF4XCvUqKEqVjCQmeIUH0Wa9JPq5VoWi2p4MKTvVwzTVmHK9mDz+XU1Un1NohGLMKBtH0TAHthAwPNczfoNa9jb8p5gpXHKqa0HAAAAAECPW+iv073+bFWpSZUq0sn+ZI3x+nV5O1bmZmW9ryGlnrwN4gmWWf+TmuWaH2tRs++rORZ37dsrx/ZY7AHZJRjrvvc99vAt8v9yfapdFRncbdtGzyBgD6RhA8w+PaVUL66Mad8hwYydUW/rQ71WzW7A2Q0/1AEAAAAAQGZYIP3e+GwtV4MiiiuiBtf+XmDnLgfSbVtz18Q1qCSwUbmbdX7c1a5v8X2VegE1fNq25f29YDcfFfJN4KizpYNPcrdjV05VZf+C3t4ldBEBe6AN9mG8RXmwx89ux+VrlRpUpgIFGXAWAAAAAIAe0aioqtXigvVFCqpJMde25aUKd3o7762I6dJ/t2hJbVwjywO67tACbTf0s0B8Py+gwcGQ6v24mwo9z7VtOfKPRZ0C8W7cYEn/xGQxplBYgR5MQkX34B0D2mDZ7Va7viez3JcHG/RLzdSf9I6bL/ZreX8AAAAAAOgBxQqpQgUKK+CC9Ta3ti3vSmb9Zf9ucdn11U1yc2vb8iRLDPx+/2EaFyxQuRd0c2tTDgeAIcMeyBK+fD1ZtlBValbUXXoX04P6QOf6e/KhDQAAAABAhlnA/OTAZN0Tn6XVatIgq2EfmNyl3+S1zdLyeqtLL/UrlOpaEm1bXtFqTFkbYPa2yjF6M9KoncOZG9wWfYBvGfYZShb97DwR+hD+NQDaGRX+g9qom/eEJi+mdYGIC9YXKujmNWpWk6K8RwAAAAAA9ICAfBUqogJF3NzaXVFeKA0r9VQYlNY1y82tbcs3ei7P09hQIUl6ANZDhj3Sisfjmj9/fqpdUVHhpnzxRnVU33qrXgsa4xpbHNBvdyrVLhWZ7S5FflD94mG1BOJqVkwhBdRfhSqimwIAAAAAkHFWtuav+lArvQaXRLdSDa59vr9Hp4Pqtt6PDy1Yr4a9tdM93vu0dj2yR3V1tZtMJBJRMNgzgwB7sR55GvQRZNgjraqqKo0fPz41zZgxI68+oC1Y/1FdTGtbfDe3dut6c5lgmfzb1g7WEL9UxQpriEo1Vdtwph0AAAAAgB5gV7jble5Rb/OufLcBZh8+qVC/OrLQzVsPOIvsZvGvZCxs9uzZLj4G9DRO4yGtyspKzZw5M9XOp+z66oivpU1xNVm9uZC0LirXtuUDCzJTU+yTeL1uLl6qNV5UQ5pL9JWCidolUKkgI8QDAAAAANAj7Ap3u9LdAvRNfkyeAiq3K9+9rofPLKN+4sAASXh9zPTp0zVt2jR3e8qUKT2SYe/5noIZqmFv20bfQ8AeaQUCAY0bNy4vX52KsKcRRQHVRmMuWF8UlGvb8kywzP1fRD5Wc0mdyuSrXo26JxrVrgWDMvJ8AAAAAAAgfZD9eH9r3Rn/UHOivmIW7PQKtSDcoPFeaZdeMit3M7Qs+4KldnX/R/VxbVUaYKDbNFqXhA6Hwz399gAOJXGANB/QVrN+q7KgBhR4bv7bHUu0qt6Xn4GyODV+RM2hOjeQjX2U29zathwAAAAAAPScEeqnNdFi1UVDqo8FNT8a1S8jczNeJrcnvFET1V7/rdVBL9W6ubWRHQLxzEzomwjYI6/ZmeU5zc1u3poNMPvS/v10725lbr5j/6Dmroln5AO6RRF5n446n9y6tW05AAAAAADoOXV+VIujESWjBDa3ti3vyyzucfrbdfqwLqY1Ed/Nz3qnrs04h63/QV1ko3gJgMyjJA7y1gfNzbpi1SotjUY1IhTSVYMHa+uCAq1o8DW0xHOZ9pZd/8EqX5f9u0WLa2MaVOrphimF2nFY93WdShUrpIAbzCZ5sZy1bTkAAAAAAOg5i/x6xVLpdJ/pS/n1Vh1gdSymQcGgK81j1rTEtaQp5sbrKwtKdbG2x+t7c11E3/lonRY2xzSmMKhfb9VPO5WFUvGS5DbRfQIxXlN8hgx75CU7g3zlqlWaF4moJh53c2tH43HNrklk0kdiMb1W3axL/92sj9fGtML39X5DXF96tFFvr+q+M+uhQECneFsq5Ce6Y1jBRDtA9wQAAAAAoKdYLOCv8fkKeOuH54d5heq3CQPP9uZxzIs2p7Ln329q1pnLVqoxELNRSLUu5qsw6Kcdr88ec87H6/RxQ9Rl4tvc2q3jJehmvuTFvYxMfepME1L6zr82QDeqjce1IhZTs++rzPNU7/tasFY67LVGLavzFa6Ia0FJi1oi0uA1RYoGpU/j6WqMSxc916ynpga7bbT3PQNDNHJVVC8EV+uYii1VEizslu0CAAAAAIBE1nnNKsn3/DYzxBsUVY0iKglG1RgLK+ZLFs/+ZuHoTv/+txIyn1T5mlDp9cqgrh+2NOmaqpVaFotoeDCsywYO1uXL1+qTSERlFTE1rS6yF0FeULpgQtFGx1Ud9bW0Oa6muFQelNbFpMXVvg57pEnL6uIa1S+gG/ct0g6Dgj1+bEC+IGCPvFQeCGhoMKj6eFx1vq9CeVr9Yam7vKshGldtYYt8K9MWkKIhX36rDzA7Obmq0VdNszSgqHv2Z168Xr8rW6E1gajej8/SN+ITND7QtRHoAQAAAABAelaKffk8acA4KdhGrLlEIVV4BS4TPei1KChPI1WsbQLlnXpZ318e1+VPNmtJra+R5Z6uOaxQ2w7ruaC9Zb9fs2al5kVbXIJik9+iq6tWakU0oKa4r7p1BTZo3qeRDU8zFjTpKyMK1wvaV4Q8jSgMqNZiIzGp2JK0V4T0SSSupqjUGIvr4heb9MQxJd2WxJjv7FUMxjK3bfQ91NxAXlm8eLGamprU0tysc1taND4cVv9AQKNVoIJISM0xqSRxstmxz57aES2fVavzpMKgNKzEU//C7vtAvS06TyuDETV6cS3xm1y7M5eZWYZA9UrfzQEAAAAAwMYWfODrupOlWy6Wfvvt/loyK33E3gLQ04ITNVzFKvNCGu4Va1poYqcC0/Yb/vInWzS3yld1ozSnKq6LHmty5XZ7yrp4XKuiUbX4vko9z83XWC37UEAh31NL1JOFD0IBqTkuLWmOuRr2rdmx/mrLftqyJKSBYU+TCkMq9QMuXtKvQG6+rD6RxAggM8iwR14F6+fMmaO5c+e6tgW5b5gwQcuHDtUuBQU68p0mNUbiamhyJd1c0N4+tqIlvppHt2jr2iKtbfY1rMzT9fuvfwZ6czQoprV+iyLyVeR7avLirm3LyzrooskMgX6VbWcIAAAAAACQr+JxX3+6Slo2T4o0Sc1NIT10Y5m238tXILDx7/qxXpkuD26vWarVFirvdFmb2iZpRV3cBbQLin1VheNaHZUO+3uTZuzfMyVk+gUCGhwKqS4Sd6V/Cz1PQ8IhfX9QpX64fI0WhXw1xz3F4p6Kg9LIwuBGNezNzv3CemHXCr1QE9E+5SEduaJJjdG41rVIRSFpeGn3JTEikSMasHrzmUB+Z59Ehj3yxqBBg1ydOgvU22S3hwwe7LLsbYDXG/Yt0qRyT/3CniY3hlUUSGTY24fYr3Yu1V+PLNJvDy7Q1Yd52q6y+7pOiYKq8GyoWQvW+woroAFegVve2QwBm1sbAAAAAAB8pnGdVL1SijRLRWVStFmqXR1wy9tiCXrDvBJXTqSqqnNXtZcXSUPLAioI+loTjisWlCwG+0ltooRMZwdrteeqWrNpV9Lbfl8+cIjGhwpcNQGbW3v74iI9OHaYfrlNqXYsS2TOb10a1O+2LWszGdGWb1ESSsVLJlcENKBQbm5tu9/q9c9uanFzAN2HDHvkNRe0DyW6gWXUx8JSNCwNCoR0+3bFeqEhpnNGFygcDOq5NU26IbpGK5fHNDIc0jXDKrVt0eafUv4k3qjqSECRgH0gSpUq0DdC49vN4N8wQ6ClWa592Z/TZwgAAAAAAJCPivtJFUOkxnqpqU4KFUrlg+Iq7hdoN1YwQAUuEL1ksa+KCruqvf3f2vYb/prDCvS9J5q02irrfqoxKi1aF+/0OHj2e3/xEqmif8fPmc7WBUX649BRer2lUbsWFKeuELD9O7yySF8dVKzn18Z0wMBQu1cP2GswwmoCS+7qgCeOLtZLy+Pae1jAPe69xmb9YPkaLYlEXYzk2mEDtV0xafebwt7lADXs0QoZ9sgbq1evTmXWJzPtbZmxM90XvNyo2TVx1UXk5t+bGdEBAxJnk6PxuK5ds0YLo1FVx+Oa2xLR5curOn2GvC32+F82LdKyeFS1kbDqWwrUEi3UWK+kSxkCNrd2exkCAAAAAADkG0tq+9oV0vDxUml/aciYqI67qK7DZLe5c31992Jf11+fmFu7w+eKSWX2u7z1qr7UFLH67x0/fs5cXxdf4uv6nyXm1t4UFpwfH1q/lK/FQYaGEkH6rcqCXS7za+tP7h9wc4tlWLB+bnNE1bG4m1t7c2MkABLIsEfeGDVqVKo0jrFgfXJZTYu0rMFXU0wqD0vrItLyRl8TisN6f3VcFz/fqPlbRKWCxMAtjb6vFdGYauNxVQSDLvi/Zq00cEDiQ7Cz6hVTlR9Ri3wV+wE1er7W+FG3vF873XPDDIFwUaJtywEAAAAAwGfGbuPp+/f4evM/0ugdaxQKeR1muf/6V3EtWiRFIlJLi/TrX8d1ww2BNgP99pj/ezii+VWeQpVSpDBxJb+NkVfme1rX4rWbYe+e87dxLVqceL5me87fxnXj9W0/Z1ssLmG17Nu6b0RR1+vp2+OGlSb2oyYWczGRZt9XWcBTfXz9GAm6zstUDXv0SQTskVY8Htf8+fNT7YqKCjf1dckA/Ya3+xdIw0vsA9RXbSRRt35oibS4pUWXPBPTJ2t9xccGFQhFVR/wVRzwVOkF1e/T4Lx9sC7ahEvWShVUpRdWgx9zwfqwbLtht7zjDIFEWZyqpVLlCLmMAcrhAAAAAACQXl0nr0qvr5fWrEkE64tLpMYGaU1VYnm/NhLl1jVJq2p995iCmCe/yXe1TorD0uj+gQ4HabVtV61JBOtLSqSGhkS7vefMJEtMXN4S17CCwEaJieWBgIaGgqqLxVUX91XksveDbnlfV11d7SYTiUQU7IMnIOIN1Yo31rjbfjSieDzc27uELiJgj7Sqqqo0fvz4VPuKK67QlVdembOvll3S9fPPFWv6y41aVOersjyu+sEtOuqtRvlrixWPegq8X6bQtnUKFMY0pjSkr0cHukvbZs2O6ee/9rW2Rho6WDr3bE+TJnidft5zi0a7sjgrok2qVMi1O3NpmmUIXHqvr9n/kybt6qu2OlHmpysZ/gAAAAAA5Lr5H/m648fSqqXSgL/11/Hn1evTi+/TWrLa17pmXzaUakO9FC7wNLBSKi1t+zH9iqTB5Z7qmqSStUH5FTH5IWnyAE8/PWj98jTp2LaHDFqspqZBamqS+pevVuXAUe0+ZyZZeZtZDVENCYcV3GDf7VisZv2GNey7WmYnG82YMUNXXXVVqj148ODMP6kvBbuxhn3df36jdY9fl2pXqQeOAd3K8zdl2GnktG233dZl2D/++OM5l2HfERtQ5oXlMf1oea1mNUbd4DD93y2Rb9exOb5K49IekQItr5aGeJ4aZgXUHE2MElIQlsaMln7+k2CXst3teV9dtVgTA0UaOnhIpx9n3bdmlVQ20NeH70rb7GAZ/n3/jDaQa5LjZSRLcgHIDfRtIHfRv4HcYVfEXzVNWjrfd+O/hQqkoaNj+r+7Q2l/t9v6Z18X08IFvoJVnqtLX1Ak/eT/Apo8uf3f2x8uiev/HopoWbWvYRXS0fsEdfwOAdVWBzRgYPsldBcvXqyZM2dr5v88l1VfVhrXMUdP1l57jVZPe6suovNm12pRU0yji4L6xeRy7VgacqWDhxUnxgVMxTIamrVnSWG7A9j21Qz7KVOmuAz7Dz/8MKMxuFlr4hr2g9cykmG/+tfHaFJlOKPHgO5Hhj3SCgQCGjduXN69OnY2eGiZp2UtcTXFpXJJwYinmH3uBBI1xcqXhTQ/LrXYpXGfBBS1q6Pss8pPLLNL1urqfLXEpMqKztW0d8/rFSjgNtR5tu01Nb6uu1JatUIaPFQ66wJfEyb3/bPaAAAAAABsroZ10tpVUqRFKiiWWhqlmqqAW17Wf+P16xql1dW+miwpb0RckSZP/ftLQ0d0/Dt765EB/fHskP7zka+Dt5SqmgOWaacli3z1r2i/hK4l91RWztWUQ+NauUoaNjSgnXYa3CuZ9efPrnXZ9Y1xKwcUde1/71Ch2TW+hhQFUhn3FsuYWBjOicz6dAmr4XDPlJKxVy9gl3N0k0BRhWSTbTsYdjE+9C28Y8AGAfAt+wU1ojCgooBUawPEFPgqjEiFjZ7KWzx3mVJLVCoNSoEWC+K3erykAf2l4mJfC5f77sx8Z5+3fyDU5XI2tv1bfu5rycJELT6bW7uzzwsAAAAAQC4r6ScNGJzIrG9ulIIFUv/KuFueTlmxBfLj8kNxNbX4ihfEVV4Rd8s7w5ev6k/r1zcs83TpBdKNP/b1/em+Ppnd8W91CwuUl3cu+S8TqqO+ljZ/msQYlJsvrPF18OMNOu2FBh36eL3erkrUb7F9HBrueiwDQPsI2CPv2CVbHzdE3DwdOzN88+RybVES0sCwp8pxURV6lvueuOxrSIWngpCvdVFfflgqbEmcCbWPp8KQdMxxns65Lq4rfxvTt6+NadaCzAXP6+sSA9/YoDQ2EI7N3UA4dRl7SgAAAAAA+gwrezPlq76ihVKkSIoW+tpvakPbZWw9qXH7tWoOSc1FcnNrd+aC+PeXxfWVu6K64ZmovnJnVD+/Mb5egt3vfhFvM8HOSnFZ2VvLhi4tCbjbyfJcPaki5H2WxBiTCj2peVVIn9TGtbbZ16yauKa/0ugy8dFNfCkQ8zIy2bbR9xCwR155u75Fh31YpaM/Xu3m1k5np7KwntlxgG7fslxjlhcrHLPSOFIwLtUFfdXZB3eJtHx8TP0HeKqIS6NKpWt/JP31aV8Llvla15CY33hXLGMZ76VlcgPfFBQkRq23uRsIpywjT4cMsBNHH9a3fQIJAAAAALDp7Pf4Px+Q/ECy9oj09D+L2/ydXhONaMkL/eWGsrN4pyfXtuXtPo/v65K/t+jD5b7qWqSPF/tassx3iXVFxa0S7OrTP37UqFGaNGmS9txzTzfZbVvW05JJjJOLguoXlCYUBFXse2qKSeVhufmyxrhqWogEA5mSUwF7O/s4d+5c/fWvf9Vll12mww8/XMOGDXNZ0clpUzz88MM6/vjjNX78eBUXF7u6YrvuuquuvPJKLV26tEvbisVi+tOf/qQjjzxSo0ePVmFhoYYOHap99tlHP/vZz1IDW3RWU1OTfvOb3+jggw/WiBEj3PZsbm1bbvfjsw/Pi+bXaFZTRGujvptbu62zwvYhNSIQ0iqrRx/11K/QU0uLp6paKfbpB3cs4GtFc1wtIV/1NgBsg69la+JqiEuxsNzc2nUNmXkXLCPgrAs8jRwjlfWTm1u7KwPeovfYQD6HvLNGR763xs2tDQAAAADoPg110trVcgPO2uCxVsu+Zk3ALU9n3Zqg4u5Hvws0SXEpHvXc8vZUW9LeGt89xLKaY0GpOewrXOCrqbFVgl1p29uwAH1RUZGL7RSWj3Rxrk1hj1sZjW7y4y18ZvsdCvsqKvI1qDigoqBUG5GbDy8OqH+B5xLPZjW1kIDWDazcciYm9E05NejsxRdfrJtuuqnbtrd27VqddNJJevLJJ9dbbkHwqqoqvfHGG5oxY4ZuvfVWnXDCCR1ub8GCBS7w/9pr64/8vHLlSje99NJLbnt33323DjrooA6399Zbb7nnnT179nrLly1b5qZnnnlGv/jFL3T//fdrhx12UL6rifla1BJzg6bYh6fNrW3LB4Q2DnDbCZ7J/YMaUhZVXbOvuubEpWDx5Kq+NHhRUH5cqipLnHW/9Be+fLttp8LsczGQeJ6SImtkJohuA8z++Je+PnhH2maH9gexQfawE0XT59RoVmNiIJ+meNS1n96xMqcG7AEAAACA3lRSJg0YJDXWSy1NFoiW+g+Mq6QsfQB+RKWnwqDn1i2uCyaCnsHE4LUa2vbzeGkaa0fEVD4/nIgP+NIXj+1cgp1l/89b6WtgqbdJv/Ht9+a8SESVgc8GiO3KYy+YV6PZTYnfqnOaoxo5tFmTA4VaVO9rTKmnGXsV64OmiC5dUqXFkZhGhYO6bmSltisu6PK+QvJ8Gy/Ry9i20ffkVIa9Za+3ZmckLRN+U1hQ/otf/GIqWD948GBdeumluueee/Tb3/5WU6ZMcctramp08skn69FHH213e1Z3zB6TDNaPGTNGV199tf785z/r5ptvdpc7GcvYP+qoozYK6m9ozpw5bnvJYP0222yj66+/3m3P5tY2H3/8sVtv3rx5ynf9AlJDzHdnyO0/m1vblrfFAqdXHVGgCZWe+hdLYyqtkv2n98UkLyK1fBqsdzwpmvwz/HRZYYHU0JzZfyDtA7+klMz6vqQm6mtZy/oD+VjblgMAAAAAuu/38pkXexoxRioplYaMjOqks+vbDJyHQgFNOySo4rpA4ne/L4V9T7/4o99uudv+xZ7G9fcSgTarSe5LIxaHFGr5tMRui/T4XxPB+PZ8uCSur/86qu/fE3Vza3fFB83N+srSpbpwxQo3t3ZXWFLj8pbYp79VPTevDcX0wOeLdcd+Jfr34aXafmBAly5Z44L51bG4m1ubuvZA98ipDHsLUp9//vnaeeed3WTtUGjTRqu28jSW8W622GILl61upWaSzj77bN14440uq99OFJxxxhkueF5uQ3mncckll2jWrFnutpW/eeyxx9Zb99xzz3X7/stf/lL19fU67bTT9PbbbysYTH/G96yzztKqVavc7alTp+ree+9VgV1f9Snbll0d8Le//U0rVqzQt771LT3xxBPKZ+tiUsj3FAr57vIuuzIsFPPc8gHtBO23HR7QX04r0LwqaewAX8feENXiWl/xoBQLtQrWf8p9mIekiA3OEpaGVXqdHk1+cwwYmPnnQPfpH/I0vCCgdbG4G8inOCDXtuUAAAAAgO7jxaRwgxSqkwrKPNduiwXUn33DV6BVnDwW81W1xnPlbsvbGDPOTgD89LgCXfn3Fi1cm8hE76eA6iNScbFcWZw1qxMlesrK237uax6Muuz65qjUFEm0/3ROuHOZ+b6vK1etctn1Tb6v5kjEte8bObLTV3L3D3oaVhBUbSym2pjvBp+19oBQQJP7JxIba2JxrYhG1exbEqSnurjv2rWxuCpC7ZcOQnp2cgjIyQz7b37zm66kzKmnnupKwFiwflPU1tbqpz/9aaptNedbB+uTLrroIlcn31hJm5///Odpt2eB/DvvvDOV9W/B9Q0D+3ZSwcr5bL/99q79/vvvu9I46Tz99NNuMlb//vbbb18vWG+sfccdd7j7jV0p8Nxzzymf2WApXjjmgvXG5ta25R0JBgKaNDigcCioG74W1jZDpLKAVLZdzAXokyz/PtwijRsulZdIY4d5+u4pQWrKYyP2JWfGpP7aojjkSjLZ3NqUwwEAAACA7mNB8LuulZbPl1rqpVWLQnrw5rI2M93rGqWqOl/x1hEzTxrQXyoraf+5thkR0L3fDOvKY8K6+9thDRkiFRQmgvU2HzgoUaKnLeuapFW1No6eVFooN7e2Le+M2nhcK2IxF0gv8zw3t7Yt7yz7Tfrt4SUuETEc8t3c2hYXGV4ScPGr8mBAQ0MhFXqe1sV9N7e2LQew+ehJafz97393We5m33331R577NHmC2hB+yQLxKdz3333Kf7pP45Ww97K4aRjJxgsMz7Jyu+k03r5mWee2WZWvy23+zvaXr5YZ7Xkgzb4cKJajc2tbcu7YuuRAXd2e8ZpYd33w7BOO+azjmTz048J6tZLQrrqjKBu+V5QW47JfDezLxpLF7Z/eR6yz05lYf1nh4H653YD3dzaAAAAAIDuY7Xn165KDDZbUCxFbdDZqkCiJn0adoX8kApP6pe4st4CCOFC6YJvBDqVjGeB7V1GBxUOBXTmhZ5GjpHK+snNrd3eNvoVSYPLPRWEpHobJDeUaNvyzigPBDQ0GHQB9Dr/00B6MOiWd5Zl6f9+VV0qbmJza7cud2NB/etGDtSkwpAqggE3tzYJaJsuEPcyMqFvImCfhpWrSTryyCPbfQEPOOAAlX46xLeVvNlwANiubu+II45I3bYyPI2Njd22vX/+85/KZ3ZZ1+iCoIq9RNDe5ta25V0VCgW1+8Sgm58yNaxHficdvZ/c/JTjEhn1Y4d17sN8c82b5euHZ0szfiQ3tzb6Dvsyt3Vp2M0BAAAAAN2rpJ80YHBisNmWRilkg85Wxt3ydOx3/CUnBzV2lKeCIb4GTfB1ww8C2nJC536zWQb6kHKLO3iasIWna34tTb9Cbm7t9thzXz41pPFDEuPo2dzanY0tWMD8ysGDNT4cVv9AwM2t3ZVAerKGvSt3E0xk6VvblrdmA8w+PGGofj16kJsz4CzQfYgQpfHOO++kbreXXZ/Mird6+ekea3zf13vvvdfp7Q0fPlyjRo1yt6PRqD744IONBq9dvny5u2317TsaVNfuD3waCLQBbauqqpSv7APq+tEDNLkopAHBgJtbuzvOABcUBLTP7gE3N/bBPKgi8QGdSZZR//sbfC1ZmKiDZ3Nrk2kPAAAAAEAiCH7E2Ys1fGKTivs3aegWCzT1/Lp2g+Bbjg7oDxcH9X+nB/SLc4Laeuymh8/seUaMbj+zfsOr+v/4nZB+f3bYza3dFdsUFuq+ESN01/Dhbm7trkjWsC8M2Jh/vpsPayPZ0eIpEwtDZNZvLj8xzkImJts2+h4C9huwAHvrLPnx48d3+CK2Xuejjz5a774lS5aorq4uFWAfPXr0Zm2vdXvkyJEKh9svoWG17G29traXb7YvKdA/Jg/WA5MGu7m1u+NvpmZtQLvuEGhzkOBMsSD96uVSS1NiEF2bW9uWAwAAAACQ7xYvXqz66FztP22mdj52pvaY+oFC/ZZ0+DgLsI8bFtTgykTd9k1ljx04qGsJfcFgQBOHWoxh08J2bhy+wsJNupLbgvA/G1OhyYWfJjsWhlw7XbKjHdPQcCjjyYpAvtm0UVlzmAXXI5FIqj1o0KAOH9N6nerq6vXuW7t2bep2//79Owywd2V7ndm35HqLFi1Ku722zJkzR1tttVXa+1588UX1dZX2WiaGKdhsNlr8/Dmexk3yFdyE8jpJNTU1XX5MNCo1Nw5INOysqWdtqa5hjZpaNnlXAHSzTenfALIffRvIXfRvIHdYMHn5kma991pQjfWePpldqLIji7V62OqOHyspHwsVjJD0x0ppUcTT6LAUbKjV6gblLBu/Mp158+Zp0qRJGX9++zsLxjJz0oNTKX0TAfsNrFu3/qgjxcXFHb6Irdepra1tc3ud2VZPbw+bZ+EnQd17a6nWrgpowOC4Tv5mvcZMsGuOekZjnVQgXxEbSMROnMelooCv5kZPoX5c9wQAAAAAyG/xuPTezLDq11nCnRSLBPTYPZXadueoGEqsbZadP66QwhxAbyBgj7TsDOL777/Pq9MOqxN/4+W+Vi6VWpqlSCSgv97eX9f+pvO16dLp7JUT8z/ydce1vloapKAv+TErgSQNHeFp9NiBPTLgLYDM9G8AfQt9G8hd9G+g75v18SK1NHuKRT2FwnalelzNLTUqKRqjsnJ+N6Pt8tHbbrttz7w8vhTIVO4nuZx9EgH7DfTrt/4w4Y2NjRst25Ctk1ReXt7m9lqvly3bw6azOvFrVieC9cUlUmNDom3Ly8ozf7Lgjh9LyxZ4UtSXF7Q6c9LIcdLp39+8EwYAAAAAAOSKSZNHqdDztXrFIEWbpZKKVaroP1wlZb29ZwCQHte2bKCsrEyh0GfnMVav7rimWet1Kioq1ruvddvqIEat6Hg3ba8z+9bR9rDp7MN94CCpoDARrLe5tXviQ79hnbR2lRRpkQqLPDfyd0mRdNGN0rgtCdYDAAAAAGAsoe2080dpyNAiFZcWuWD9id+uJ9ENWcOiOIF4ZiYiRH0TAfs0g5FsscUW6w0w0ZHW62w4UOuoUaPcSQATi8W0cOHCzdpe6/aSJUvWGyA3Hbvf1mtre9i8D/0zL/Q0coxU1k9ubu2eyG4v6ScNGCyFCxKDzNrJgsqhnvpV8E8xAAAAAACtjZ3s6dQzpXOulC64vkajJ/bc2HMA0FUE7NPYYYcdUrdnzpzZ7gtoGfNvvvlm2scmTwBst912nd7esmXLtHjxYnc7GAxqm222We/+wYMHa9iwYakTAK+//nq72/vf//6nuI2wYqN8jxihysrKdtdH10zYwtM1v5aumCE3t3ZPsJMCu+8vRZsS9ciiTZ72Otj+ZgjYAwAAAACQtPA9Xz/7knTHBdJDl0vLZwV5cZBdfMmLed02xepr1LJmgZv8WCQVF0TfQcA+jSOOOCJ1+7HHHmv3BXzuuedUX1/vbk+ePNlNm7O91vcfdNBBKi4u7rbttX4cuk8wGNDocQE3zzTfl2qW25UTvv75e8lrkYItibm1o1FGEwEAAAAAIDn+259/IK2YK9VXS2sWS4/+pEzEL5HLVv3vl/rglq3c1Lx2jqqqqnp7l9BFBOzTOProo1VaWupuv/DCC+1mxd94442p2yeffHLadU488UQFAomX+v7779eiRYvazNa/+eabU+1TTjkl7Xqtn+fWW2/VunXr0q5XW1ur3//+9x1uD31HLCZ9MlNatThRv96zs7BeYm7tNUt7ew8BAAAAAMgOjbVS1RKppdEy4DxFmjzVLAuqaR1XpyO7BGPdNw3b+Vxtf8ZHbiqsmES1jT6IgH0a/fv313e/+91U++tf/7qWLl2aNlj/+OOPu9uDBg3SBRdckPZFtpr4tg3T3NzsAu4WTG/N931ddNFFevfdd11766231le/+tW02zvkkENc9r1ZsWKFTjvtNLW0tKy3jrVPP/10d7859NBDdeCBB7b3t4Ast/gd6RdfkP56oXTvNyQ3NrJ9x7Ckei9Rz37giN7eSwAAAAAAskNhmRRp+LTx6QXp0UZPhaVcnY7sYUmYgVj3TQXhChWXjXNTIBBOJRGj77CQX86orq7WDTfc0O46l19++UbLrrnmmo2Wfe9739MTTzyhV155RR9//LF22mknnXnmma4evQXbH3roIT355JOpWvOWyW6B/rZcf/31evHFFzVnzhw3t1r3Z5xxhiZNmqRVq1bp3nvvdc9lSkpKdMcddyjkIrLp3XLLLdp77721evVqPfjgg9p5551d4H706NEug98e/8EHH7h1hwwZot/97nftvi7Ibna53t3fkZbPT5TFaZjtqXKErzWFUqRZChdK035kQXyyBAAAAAAAMM3rPJUEfUWshLfFLONSUcBXSz2/nQFkL8+31O4cMX/+fI0fP77Lj2vrJVizZo2+8pWv6F//+lebjy0vL3fB8JNOOqnD55k3b56OP/74dgeKtQFl7777bpdF35E33nhDJ5xwgubOndvmOlZT38rw2AmHztp2223d/P333+/0Y7D57ORL8mqNDdVVST/aVYpZjfpPs+qDIU+Xv+zrg1ekPY6UCgr4wgH0xf4NoO+ibwO5i/4N5E7y28+PkJbP9hVpksJF0qDxUZ1+b40GD+G7OXo/PmbPMW+5rx1PeSsj23/7np00fphHjK+P4ZqIdgwcOFBPPfWU/va3v2nq1KkaM2aMCgsL3XLLaP/hD3/ostg7E6w3djLh1Vdf1Z133qnDDz9cI0eOVEFBgQYPHqy99tpLP/nJT9z2OhOsN7vssosrofPLX/7SlbuxYH84HHZza9vyt99+u0vBemQn32LxXmJu55eS7VCBtN0+Ujjc23sIAAAAAEB2sUogJ1wvDZ0kFZVKA0dJh19eJ49oGIAsllMlccaNG9dmtvzmOO6449zUHax8zqmnnuqm7lBcXKxzzjnHTchdpRVS+Qhfq5cmgvVW38zaZQM89wUEAAAAAABszPLdrI59Q0yqXyr97eoyfenqOg3al1cLWcKKKcQzt230PYT6gD7BV7DUzvh8+m0jqESbf3kBAAAAAGizJM79F/laukSK+VI8Jq1eGNQj15UpHieSCSA75VSGPZCrGmulhtpEsL6wRGppTLRtuWXfAwAAAACA9TXVSNXLJBeb/3Q8OCvMULsywO9pZA2XlxnL3LbR9xCwR1rxeNwN4ptUUVHhJvSO4nKpYqjUVCe1NCQGyrG2LQcAAAAAABsr6i8VD5DU8OkCKzErqXxIXMXlFJ3Axqqrq91kIpGIK20N9DT+dUJaVVVVbpDc5DRjxgxeqR4Si0nLP0rMkwIBTyddKw2dKJVUJObWtuUAAAAAACC9eKGnQKvqN8GwdNT369r9Pe2y8Jcl5sgvFv9KxsJmz57t4mMZ50uBmJeRiUrKfRMZ9kirsrJSM2fOTLXJru8Zy98P6u6rpbWLpAGjpS/fJI3aMXHfmO08ffdvvlZ8Ig2dYAMYE6wHAAAAAKCj8rKe56mw0FekSSou9TVwRLzD2vcrZ0ulQ+y3N69vPpk+fbqmTZvmbk+ZMoUMe/QKAvZIKxAIaNy4cbw6PciPS0/+qExV86Roo9wXiQcvlM79l70fyffFU2n5Z20AAAAAAJCelZHtb+Vl1yV+Y4cLE+Vwivq1nTq/5G3pwenS2oXSgDHS1BnSyE8T6ZD7WpeEDofDPfa8gQzVsEffRNgPyBJNtZ7WrQwo2iQVlsvNa5YnBslpfZZ/+dzEHAAAAAAAtM2S3U66Tho6ycrLeho22dNRP6iT10Y0zH5rW7B+5SypcW1ibm1+gwPoSWTYA1miqNxXvyFxtdQH1VwrhYql/sMSg+SYRe9Jf75UWrNYGjgq8aVj9Ha9vdcAAAAAAGQv+9180cPSnFelSXtKa9e2ncpsCXNWu95l4xcn5ta25SU2eC2QAZ6rYZ+5baPvIcMeyBJ2hv+wq+s0ZHJiFHubT70pkRFgZ/MtWL9ijtRQnZhbm7P8AAAAAAC0z35XD5vYcXlZS5grqpB8T2puTMytnUykA4CeQIY9kEWGbRvTuU9J8/4rjd/ns8FtbKCcmhVSpFkq7Cc11yXatrw0UVoNAAAAAACk4XmJWvadYb+7AxEbaM4emGgDmeUpEPMytm30PWTYA1kiHpOqPvHk+9Lgyeuf+U8OlGMD5DSvS8ytbcsBAAAAAMDms7r16xYmgvUuzOkn2rYcAHoKAXsgCyx5S7r3uP76ywkV+s1B0sJX1i93s/5AOYm5tTu6nA8AAAAAAHTOp0n1btrwNpAxn9awz8TEH2/fREkcoJdZYP6h86WquSE3oE1DrXTvmdLwm6WpN0sjd1x/oJyVc6UhEz8rlwMAAAAAADafDSxbOUFaNVvyLInOS7QZcBZATyI/F+hlTdVS7VIpanXxQpIfT5THWTlLenD6+pn2FqQfvgXBegAAAAAAuptdxX7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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": [
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       "    }\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>1089.093859</td>\n",
       "      <td>39.851227</td>\n",
       "      <td>16.307337</td>\n",
       "      <td>0.039728</td>\n",
       "      <td>1.941146</td>\n",
       "      <td>0.047597</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.239263</td>\n",
       "      <td>29.927626</td>\n",
       "      <td>False</td>\n",
       "      <td>27.328992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025W25_1B_0062_1</td>\n",
       "      <td>60842.269794</td>\n",
       "      <td>3452.445778</td>\n",
       "      <td>152.320799</td>\n",
       "      <td>15.054683</td>\n",
       "      <td>0.047902</td>\n",
       "      <td>4.660034</td>\n",
       "      <td>0.036682</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.577005</td>\n",
       "      <td>29.839928</td>\n",
       "      <td>False</td>\n",
       "      <td>22.665623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025W25_1B_0062_2</td>\n",
       "      <td>60842.271286</td>\n",
       "      <td>3328.733891</td>\n",
       "      <td>154.367277</td>\n",
       "      <td>15.094302</td>\n",
       "      <td>0.050350</td>\n",
       "      <td>4.694237</td>\n",
       "      <td>0.036818</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.436455</td>\n",
       "      <td>29.968734</td>\n",
       "      <td>False</td>\n",
       "      <td>21.563727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025W25_1B_0062_2</td>\n",
       "      <td>60842.271286</td>\n",
       "      <td>1111.192159</td>\n",
       "      <td>40.484140</td>\n",
       "      <td>16.285527</td>\n",
       "      <td>0.039557</td>\n",
       "      <td>1.986221</td>\n",
       "      <td>0.049049</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.239724</td>\n",
       "      <td>29.032751</td>\n",
       "      <td>False</td>\n",
       "      <td>27.447592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025W25_1B_0062_3</td>\n",
       "      <td>60842.272779</td>\n",
       "      <td>1059.285046</td>\n",
       "      <td>40.073555</td>\n",
       "      <td>16.337468</td>\n",
       "      <td>0.041074</td>\n",
       "      <td>2.031946</td>\n",
       "      <td>0.050662</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.789633</td>\n",
       "      <td>29.144533</td>\n",
       "      <td>False</td>\n",
       "      <td>26.433519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2025W25_1B_0062_3</td>\n",
       "      <td>60842.272779</td>\n",
       "      <td>3701.830277</td>\n",
       "      <td>167.186553</td>\n",
       "      <td>14.978959</td>\n",
       "      <td>0.049035</td>\n",
       "      <td>4.728453</td>\n",
       "      <td>0.036660</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.690867</td>\n",
       "      <td>29.258618</td>\n",
       "      <td>False</td>\n",
       "      <td>22.141914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2025W25_1B_0062_4</td>\n",
       "      <td>60842.274271</td>\n",
       "      <td>1254.803623</td>\n",
       "      <td>84.854982</td>\n",
       "      <td>16.153561</td>\n",
       "      <td>0.073422</td>\n",
       "      <td>2.079288</td>\n",
       "      <td>0.052247</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097157</td>\n",
       "      <td>1000000000000000000101</td>\n",
       "      <td>29.041269</td>\n",
       "      <td>29.242490</td>\n",
       "      <td>False</td>\n",
       "      <td>14.787625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2025W25_1B_0062_4</td>\n",
       "      <td>60842.274271</td>\n",
       "      <td>3599.542844</td>\n",
       "      <td>158.374631</td>\n",
       "      <td>15.009382</td>\n",
       "      <td>0.047771</td>\n",
       "      <td>4.762672</td>\n",
       "      <td>0.036502</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.758518</td>\n",
       "      <td>29.527838</td>\n",
       "      <td>False</td>\n",
       "      <td>22.728027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2025W25_1B_0178_1</td>\n",
       "      <td>60842.882044</td>\n",
       "      <td>1310.057482</td>\n",
       "      <td>43.035318</td>\n",
       "      <td>16.106774</td>\n",
       "      <td>0.035666</td>\n",
       "      <td>2.176754</td>\n",
       "      <td>0.054898</td>\n",
       "      <td>D3</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.427420</td>\n",
       "      <td>29.189553</td>\n",
       "      <td>False</td>\n",
       "      <td>30.441450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2025W25_1B_0178_1</td>\n",
       "      <td>60842.882044</td>\n",
       "      <td>3840.086981</td>\n",
       "      <td>171.008625</td>\n",
       "      <td>14.939147</td>\n",
       "      <td>0.048351</td>\n",
       "      <td>4.831608</td>\n",
       "      <td>0.037045</td>\n",
       "      <td>D6</td>\n",
       "      <td>2097152</td>\n",
       "      <td>1000000000000000000000</td>\n",
       "      <td>29.659934</td>\n",
       "      <td>29.756718</td>\n",
       "      <td>False</td>\n",
       "      <td>22.455516</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  1089.093859   39.851227  16.307337   \n",
       "1  2025W25_1B_0062_1  60842.269794  3452.445778  152.320799  15.054683   \n",
       "2  2025W25_1B_0062_2  60842.271286  3328.733891  154.367277  15.094302   \n",
       "3  2025W25_1B_0062_2  60842.271286  1111.192159   40.484140  16.285527   \n",
       "4  2025W25_1B_0062_3  60842.272779  1059.285046   40.073555  16.337468   \n",
       "5  2025W25_1B_0062_3  60842.272779  3701.830277  167.186553  14.978959   \n",
       "6  2025W25_1B_0062_4  60842.274271  1254.803623   84.854982  16.153561   \n",
       "7  2025W25_1B_0062_4  60842.274271  3599.542844  158.374631  15.009382   \n",
       "8  2025W25_1B_0178_1  60842.882044  1310.057482   43.035318  16.106774   \n",
       "9  2025W25_1B_0178_1  60842.882044  3840.086981  171.008625  14.939147   \n",
       "\n",
       "   mag_ab_error  wavelength  bandwidth band     flag             flag_binary  \\\n",
       "0      0.039728    1.941146   0.047597   D3  2097152  1000000000000000000000   \n",
       "1      0.047902    4.660034   0.036682   D6  2097152  1000000000000000000000   \n",
       "2      0.050350    4.694237   0.036818   D6  2097152  1000000000000000000000   \n",
       "3      0.039557    1.986221   0.049049   D3  2097152  1000000000000000000000   \n",
       "4      0.041074    2.031946   0.050662   D3  2097152  1000000000000000000000   \n",
       "5      0.049035    4.728453   0.036660   D6  2097152  1000000000000000000000   \n",
       "6      0.073422    2.079288   0.052247   D3  2097157  1000000000000000000101   \n",
       "7      0.047771    4.762672   0.036502   D6  2097152  1000000000000000000000   \n",
       "8      0.035666    2.176754   0.054898   D3  2097152  1000000000000000000000   \n",
       "9      0.048351    4.831608   0.037045   D6  2097152  1000000000000000000000   \n",
       "\n",
       "       pix_x      pix_y  is_upper_limit        snr  \n",
       "0  29.239263  29.927626           False  27.328992  \n",
       "1  29.577005  29.839928           False  22.665623  \n",
       "2  29.436455  29.968734           False  21.563727  \n",
       "3  29.239724  29.032751           False  27.447592  \n",
       "4  29.789633  29.144533           False  26.433519  \n",
       "5  29.690867  29.258618           False  22.141914  \n",
       "6  29.041269  29.242490           False  14.787625  \n",
       "7  29.758518  29.527838           False  22.728027  \n",
       "8  29.427420  29.189553           False  30.441450  \n",
       "9  29.659934  29.756718           False  22.455516  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total measurements: 217\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": [
      "2026-05-19 17:41:21 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2026-05-19 17:41:21 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'aperture_diameter', 'background_method', 'annulus_inner_offset']\n",
      "2026-05-19 17:41:22 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2026-05-19 17:41:22 - 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": [
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:22 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2026-05-19 17:41:22 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:27 - spxquery.core.query - INFO - Found 218 observations (6 bands, 225 days span)\n",
      "2026-05-19 17:41:27 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2026-05-19 17:41:27 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2026-05-19 17:41:27 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2026-05-19 17:41:27 - spxquery.core.download - INFO - Starting parallel download of 218 files\n",
      "2026-05-19 17:41:27 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=5\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: 2026-05-19 17:41:27\n",
      "\n",
      "Total observations found: 218\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  36 observations\n",
      "  D2 (1.10-1.62 μm):  36 observations\n",
      "  D3 (1.63-2.41 μm):  37 observations\n",
      "  D4 (2.42-3.82 μm):  36 observations\n",
      "  D5 (3.83-4.41 μm):  36 observations\n",
      "  D6 (4.42-5.00 μm):  37 observations\n",
      "\n",
      "Time span: 224.6 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "2026-05-19 17:41:27 - spxquery.core.pipeline - INFO - Processing 218 FITS files\n",
      "2026-05-19 17:41:27 - spxquery.processing.photometry - INFO - Processing photometry for 218 observations\n",
      "2026-05-19 17:41:27 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 218\n",
      "Successful: 218\n",
      "Failed: 0\n",
      "Total downloaded: 555.5 MB (0.54 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  51%|█████     | 111/218 [00:01<00:00, 118.64files/s]Insufficient background pixels for zodiacal estimation (1621/3600 = 45.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Processing observations:  69%|██████▉   | 151/218 [00:01<00:00, 153.26files/s]Insufficient background pixels for zodiacal estimation (0/3600 = 0.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Insufficient usable pixels with strict masking: 0/10 required. Trying with relaxed masking (exclude_bad_only=False).\n",
      "No usable pixels in background annulus\n",
      "Background estimation failed for 2026W03_2A_0316_4.fits - dropping observation\n",
      "Processing observations: 100%|██████████| 218/218 [00:01<00:00, 112.32files/s]\n",
      "2026-05-19 17:41:29 - spxquery.processing.photometry - INFO - Successfully processed 217 observations\n",
      "2026-05-19 17:41:29 - spxquery.processing.lightcurve - INFO - Generated light curve with 217 measurements\n",
      "2026-05-19 17:41:29 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2026-05-19 17:41:29 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2026-05-19 17:41:29 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2026-05-19 17:41:29 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2026-05-19 17:41:29 - spxquery.core.pipeline - INFO - Filtered photometry results by bands ['D1', 'D2', 'D3', 'D4', 'D5', 'D6']: 217 -> 217 measurements\n",
      "2026-05-19 17:41:29 - spxquery.visualization.plots - INFO - Quality filtering: 217 total points (209 good, 8 rejected - shown as crosses)\n",
      "2026-05-19 17:41:29 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 217\n",
      "Time span: 224.6 days\n",
      "MJD range: 60842.27 - 61066.92\n",
      "Wavelength range: 0.75 - 5.00 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 23.6\n",
      "\n",
      "Observations per band:\n",
      "  D1: 36\n",
      "  D2: 36\n",
      "  D3: 36\n",
      "  D4: 36\n",
      "  D5: 36\n",
      "  D6: 37\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2026-05-19 17:41:29 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n",
      "2026-05-19 17:41:30 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:30 - 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": [
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:30 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2026-05-19 17:41:30 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:38 - spxquery.core.query - INFO - Found 218 observations (6 bands, 225 days span)\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Starting parallel download of 218 files\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=5\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: 2026-05-19 17:41:38\n",
      "\n",
      "Total observations found: 218\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  36 observations\n",
      "  D2 (1.10-1.62 μm):  36 observations\n",
      "  D3 (1.63-2.41 μm):  37 observations\n",
      "  D4 (2.42-3.82 μm):  36 observations\n",
      "  D5 (3.83-4.41 μm):  36 observations\n",
      "  D6 (4.42-5.00 μm):  37 observations\n",
      "\n",
      "Time span: 224.6 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading:   0%|          | 0/218 [00:00<?, ?files/s]2026-05-19 17:41:38 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_1.fits - already exists\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_1.fits - already exists\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_2.fits - already exists\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Skipping 2025W25_1B_0062_2.fits - already exists\n",
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      "Downloading: 100%|██████████| 218/218 [00:00<00:00, 3445.71files/s]\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Download complete: 218 successful, 0 failed\n",
      "2026-05-19 17:41:38 - spxquery.core.download - INFO - Total size: 555.5 MB\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Downloaded 218 files\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.54 GB (actual)\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2026-05-19 17:41:38 - spxquery.core.pipeline - INFO - Processing 218 FITS files\n",
      "2026-05-19 17:41:38 - spxquery.processing.photometry - INFO - Processing photometry for 218 observations\n",
      "2026-05-19 17:41:38 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 218\n",
      "Successful: 218\n",
      "Failed: 0\n",
      "Total downloaded: 555.5 MB (0.54 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  28%|██▊       | 61/218 [00:00<00:01, 89.72files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations:  51%|█████▏    | 112/218 [00:01<00:00, 162.86files/s]Insufficient background pixels for zodiacal estimation (1621/3600 = 45.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Processing observations:  71%|███████   | 154/218 [00:01<00:00, 202.62files/s]Insufficient background pixels for zodiacal estimation (0/3600 = 0.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Insufficient usable pixels with strict masking: 0/10 required. Trying with relaxed masking (exclude_bad_only=False).\n",
      "Insufficient usable pixels in background window even with relaxed masking: 0/10 required (window: 50×50, aperture_radius: 1.0)\n",
      "Background estimation failed for 2026W03_2A_0316_4.fits - dropping observation\n",
      "Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations: 100%|██████████| 218/218 [00:01<00:00, 159.48files/s]\n",
      "2026-05-19 17:41:39 - spxquery.processing.photometry - INFO - Successfully processed 217 observations\n",
      "2026-05-19 17:41:39 - spxquery.processing.lightcurve - INFO - Generated light curve with 217 measurements\n",
      "2026-05-19 17:41:39 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2026-05-19 17:41:39 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2026-05-19 17:41:39 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2026-05-19 17:41:39 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2026-05-19 17:41:39 - spxquery.core.pipeline - INFO - Filtered photometry results by bands ['D1', 'D2', 'D3', 'D4', 'D5', 'D6']: 217 -> 217 measurements\n",
      "2026-05-19 17:41:39 - spxquery.visualization.plots - INFO - Quality filtering: 217 total points (209 good, 8 rejected - shown as crosses)\n",
      "2026-05-19 17:41:39 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 217\n",
      "Time span: 224.6 days\n",
      "MJD range: 60842.27 - 61066.92\n",
      "Wavelength range: 0.75 - 5.00 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 24.4\n",
      "\n",
      "Observations per band:\n",
      "  D1: 36\n",
      "  D2: 36\n",
      "  D3: 36\n",
      "  D4: 36\n",
      "  D5: 36\n",
      "  D6: 37\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2026-05-19 17:41:39 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 217 measurements (0 outliers removed)\n",
      "2026-05-19 17:41:40 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:40 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2026-05-19 17:41:40 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:40 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:40 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:40 - 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_73894/1917494619.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: 0.33%\n",
      "Std flux difference: 1.82%\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": [
      "2026-05-19 17:41:41 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2026-05-19 17:41:41 - spxquery.core.config - INFO - Updated parameters: ['aperture_method', 'aperture_diameter', 'background_method', 'window_size']\n",
      "2026-05-19 17:41:41 - spxquery.core.config - INFO - Loaded advanced parameters from demo_data/cloverleaf/cloverleaf.yaml\n",
      "2026-05-19 17:41:41 - 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": [
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:41 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2026-05-19 17:41:41 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:50 - spxquery.core.query - INFO - Found 218 observations (6 bands, 225 days span)\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2026-05-19 17:41:50 - spxquery.core.download - INFO - Starting parallel download of 218 files\n",
      "2026-05-19 17:41:50 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=5\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: 2026-05-19 17:41:50\n",
      "\n",
      "Total observations found: 218\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  36 observations\n",
      "  D2 (1.10-1.62 μm):  36 observations\n",
      "  D3 (1.63-2.41 μm):  37 observations\n",
      "  D4 (2.42-3.82 μm):  36 observations\n",
      "  D5 (3.83-4.41 μm):  36 observations\n",
      "  D6 (4.42-5.00 μm):  37 observations\n",
      "\n",
      "Time span: 224.6 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "Downloading: 100%|██████████| 218/218 [00:00<00:00, 4492.15files/s]\n",
      "2026-05-19 17:41:50 - spxquery.core.download - INFO - Download complete: 218 successful, 0 failed\n",
      "2026-05-19 17:41:50 - spxquery.core.download - INFO - Total size: 555.5 MB\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Downloaded 218 files\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.54 GB (actual)\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2026-05-19 17:41:50 - spxquery.core.pipeline - INFO - Processing 218 FITS files\n",
      "2026-05-19 17:41:50 - spxquery.processing.photometry - INFO - Processing photometry for 218 observations\n",
      "2026-05-19 17:41:50 - spxquery.processing.photometry - INFO - Using multiprocessing with 10 workers\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Download Summary\n",
      "============================================================\n",
      "Total files: 218\n",
      "Successful: 218\n",
      "Failed: 0\n",
      "Total downloaded: 555.5 MB (0.54 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:  30%|███       | 66/218 [00:00<00:01, 96.94files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Processing observations:  56%|█████▌    | 121/218 [00:01<00:00, 175.56files/s]Insufficient background pixels for zodiacal estimation (1621/3600 = 45.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Processing observations:  78%|███████▊  | 169/218 [00:01<00:00, 234.05files/s]Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "Insufficient background pixels for zodiacal estimation (0/3600 = 0.0% < 50.0%) - using fallback scale factor 1.0\n",
      "Insufficient usable pixels with strict masking: 0/10 required. Trying with relaxed masking (exclude_bad_only=False).\n",
      "Insufficient usable pixels in background window even with relaxed masking: 0/10 required (window: 50×50, aperture_radius: 1.5)\n",
      "Background estimation failed for 2026W03_2A_0316_4.fits - dropping observation\n",
      "Processing observations: 100%|██████████| 218/218 [00:01<00:00, 168.60files/s]\n",
      "2026-05-19 17:41:52 - spxquery.processing.photometry - INFO - Successfully processed 217 observations\n",
      "2026-05-19 17:41:52 - spxquery.processing.lightcurve - INFO - Generated light curve with 217 measurements\n",
      "2026-05-19 17:41:52 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Filtered photometry results by bands ['D1', 'D2', 'D3', 'D4', 'D5', 'D6']: 217 -> 217 measurements\n",
      "2026-05-19 17:41:52 - spxquery.visualization.plots - INFO - Quality filtering: 217 total points (203 good, 14 rejected - shown as crosses)\n",
      "2026-05-19 17:41:52 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 216 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 217\n",
      "Time span: 224.6 days\n",
      "MJD range: 60842.27 - 61066.92\n",
      "Wavelength range: 0.75 - 5.00 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 24.5\n",
      "\n",
      "Observations per band:\n",
      "  D1: 36\n",
      "  D2: 36\n",
      "  D3: 36\n",
      "  D4: 36\n",
      "  D5: 36\n",
      "  D6: 37\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2026-05-19 17:41:52 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 216 measurements (1 outliers removed)\n",
      "2026-05-19 17:41:52 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:41:52 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:52 - 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": [
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - Initialized pipeline for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - State file: cloverleaf.yaml\n",
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - Starting full pipeline execution\n",
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - Pipeline stages: ['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:41:53 - spxquery.core.pipeline - INFO - Running query stage\n",
      "2026-05-19 17:41:53 - spxquery.core.query - INFO - Querying SPHEREx observations for source at RA=213.942708, Dec=11.495389\n",
      "2026-05-19 17:42:08 - spxquery.core.query - INFO - Found 218 observations (6 bands, 225 days span)\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Marked stage 'query' as complete\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=download, completed=['query']\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Running download stage (skip_existing=True)\n",
      "2026-05-19 17:42:08 - spxquery.core.download - INFO - Starting parallel download of 218 files\n",
      "2026-05-19 17:42:08 - spxquery.core.download - INFO - Download settings: timeout=300s, retries=3, workers=5\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: 2026-05-19 17:42:08\n",
      "\n",
      "Total observations found: 218\n",
      "\n",
      "Observations by band:\n",
      "  D1 (0.75-1.09 μm):  36 observations\n",
      "  D2 (1.10-1.62 μm):  36 observations\n",
      "  D3 (1.63-2.41 μm):  37 observations\n",
      "  D4 (2.42-3.82 μm):  36 observations\n",
      "  D5 (3.83-4.41 μm):  36 observations\n",
      "  D6 (4.42-5.00 μm):  37 observations\n",
      "\n",
      "Time span: 224.6 days\n",
      "Total data volume: 0.00 GB\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "Downloading: 100%|██████████| 218/218 [00:00<00:00, 4558.00files/s]\n",
      "2026-05-19 17:42:08 - spxquery.core.download - INFO - Download complete: 218 successful, 0 failed\n",
      "2026-05-19 17:42:08 - spxquery.core.download - INFO - Total size: 555.5 MB\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Downloaded 218 files\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Total data size: 0.00 GB (estimated) → 0.54 GB (actual)\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Marked stage 'download' as complete\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=processing, completed=['query', 'download']\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Running processing stage\n",
      "2026-05-19 17:42:08 - spxquery.core.pipeline - INFO - Processing 218 FITS files\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Processing photometry for 218 observations\n",
      "2026-05-19 17:42:08 - 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: 218\n",
      "Successful: 218\n",
      "Failed: 0\n",
      "Total downloaded: 555.5 MB (0.54 GB)\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing observations:   0%|          | 0/218 [00:00<?, ?files/s]2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_1.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2679/3600 (74.4%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2157\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2157\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1959/2601 (75.3%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=1178.320±43.868 μJy (0.001178±0.000044 Jy) at λ=1.941 μm, mag_AB=16.222±0.040\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_1.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.080160e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3026/3600 (84.1%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2972\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2972\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2192/2601 (84.3%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_1.fits: flux=3795.616±168.787 μJy (0.003796±0.000169 Jy) at λ=4.660 μm, mag_AB=14.952±0.048\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_2.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.168054e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3048/3600 (84.7%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3028\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3028\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2210/2601 (85.0%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=3636.145±171.266 μJy (0.003636±0.000171 Jy) at λ=4.694 μm, mag_AB=14.998±0.051\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_2.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2664/3600 (74.0%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2165\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2165\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1951/2601 (75.0%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_2.fits: flux=1217.878±44.654 μJy (0.001218±0.000045 Jy) at λ=1.986 μm, mag_AB=16.186±0.040\n",
      "Processing observations:   2%|▏         | 4/218 [00:00<00:05, 38.82files/s]2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_3.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2659/3600 (73.9%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2536\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2536\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1935/2601 (74.4%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=1192.605±44.566 μJy (0.001193±0.000045 Jy) at λ=2.032 μm, mag_AB=16.209±0.041\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_3.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.286845e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3056/3600 (84.9%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2948\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2948\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2214/2601 (85.1%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_3.fits: flux=3967.095±184.111 μJy (0.003967±0.000184 Jy) at λ=4.728 μm, mag_AB=14.904±0.050\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0062_4.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2701\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2701\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1958/2601 (75.3%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=1466.761±99.908 μJy (0.001467±0.000100 Jy) at λ=2.079 μm, mag_AB=15.984±0.074\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0062_4.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0062_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.318814e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3045/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3063\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3063\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2210/2601 (85.0%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0062_4.fits: flux=3786.930±174.712 μJy (0.003787±0.000175 Jy) at λ=4.763 μm, mag_AB=14.954±0.050\n",
      "Processing observations:   4%|▎         | 8/218 [00:00<00:05, 39.03files/s]2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_1.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.078027e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2671/3600 (74.2%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2939\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2939\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1951/2601 (75.0%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=1458.633±47.254 μJy (0.001459±0.000047 Jy) at λ=2.177 μm, mag_AB=15.990±0.035\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_1.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.476675e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3044/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2953\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2953\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2214/2601 (85.1%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_1.fits: flux=4200.530±190.534 μJy (0.004201±0.000191 Jy) at λ=4.832 μm, mag_AB=14.842±0.049\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_2.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.517506e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3062/3600 (85.1%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2760\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2760\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2223/2601 (85.5%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_2.fits: flux=4345.619±194.889 μJy (0.004346±0.000195 Jy) at λ=4.867 μm, mag_AB=14.805±0.049\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_3.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 3050/3600 (84.7%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2872\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2872\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2216/2601 (85.2%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=4135.859±192.940 μJy (0.004136±0.000193 Jy) at λ=4.903 μm, mag_AB=14.859±0.051\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_3.fits\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.017840e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:08 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 2674/3600 (74.3%) pixels available\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3322\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3322\n",
      "2026-05-19 17:42:08 - spxquery.utils.spherex_mef - INFO - Background mask: 1937/2601 (74.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_3.fits: flux=1923.751±50.761 μJy (0.001924±0.000051 Jy) at λ=2.279 μm, mag_AB=15.690±0.029\n",
      "Processing observations:   6%|▌         | 13/218 [00:00<00:04, 43.85files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0178_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2984/3600 (82.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3227\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3227\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2172/2601 (83.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=4894.334±346.410 μJy (0.004894±0.000346 Jy) at λ=4.939 μm, mag_AB=14.676±0.077\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0178_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0178_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2629/3600 (73.0%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3390\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3390\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1928/2601 (74.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0178_4.fits: flux=4554.300±71.066 μJy (0.004554±0.000071 Jy) at λ=2.331 μm, mag_AB=14.754±0.017\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0202_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (2.185604e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3032/3600 (84.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3304\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3304\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/2601 (84.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=4313.004±219.673 μJy (0.004313±0.000220 Jy) at λ=4.974 μm, mag_AB=14.813±0.055\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0202_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0202_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2676/3600 (74.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3785\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3785\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1960/2601 (75.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0202_1.fits: flux=2050.439±60.703 μJy (0.002050±0.000061 Jy) at λ=2.383 μm, mag_AB=15.620±0.032\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.818707e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3071/3600 (85.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3753\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3753\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2226/2601 (85.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=3239.244±155.068 μJy (0.003239±0.000155 Jy) at λ=4.413 μm, mag_AB=15.124±0.052\n",
      "Processing observations:   8%|▊         | 18/218 [00:00<00:04, 44.62files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2698/3600 (74.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1978/2601 (76.0%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_3.fits: flux=1419.116±51.836 μJy (0.001419±0.000052 Jy) at λ=1.634 μm, mag_AB=16.020±0.040\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0329_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1153\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1153\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1958/2601 (75.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=1343.344±51.936 μJy (0.001343±0.000052 Jy) at λ=1.671 μm, mag_AB=16.080±0.042\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0329_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0329_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.682290e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3047/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3945\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3945\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2208/2601 (84.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0329_4.fits: flux=3980.118±168.766 μJy (0.003980±0.000169 Jy) at λ=4.445 μm, mag_AB=14.900±0.046\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (1.017489e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3047/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4428\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4428\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2222/2601 (85.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=3110.570±168.523 μJy (0.003111±0.000169 Jy) at λ=4.477 μm, mag_AB=15.168±0.059\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.448998e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2695/3600 (74.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1425\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1425\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1970/2601 (75.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_1.fits: flux=1541.299±80.702 μJy (0.001541±0.000081 Jy) at λ=1.710 μm, mag_AB=15.930±0.057\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2691/3600 (74.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1480\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1480\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1961/2601 (75.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=2039.079±55.922 μJy (0.002039±0.000056 Jy) at λ=1.749 μm, mag_AB=15.626±0.030\n",
      "Processing observations:  11%|█         | 24/218 [00:00<00:04, 47.17files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.571368e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3040/3600 (84.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3485\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3485\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2207/2601 (84.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_2.fits: flux=3879.996±165.546 μJy (0.003880±0.000166 Jy) at λ=4.509 μm, mag_AB=14.928±0.046\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2694/3600 (74.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1428\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1428\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1971/2601 (75.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=1533.813±50.390 μJy (0.001534±0.000050 Jy) at λ=1.790 μm, mag_AB=15.936±0.036\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3045/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2868\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2868\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2211/2601 (85.0%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_3.fits: flux=4695.879±171.230 μJy (0.004696±0.000171 Jy) at λ=4.542 μm, mag_AB=14.721±0.040\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0468_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2672/3600 (74.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1679\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1679\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1953/2601 (75.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=1428.635±48.917 μJy (0.001429±0.000049 Jy) at λ=1.832 μm, mag_AB=16.013±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0468_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0468_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.261420e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3028/3600 (84.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2418\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2418\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2188/2601 (84.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0468_4.fits: flux=4728.408±414.574 μJy (0.004728±0.000415 Jy) at λ=4.575 μm, mag_AB=14.713±0.095\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.955895e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2862\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2862\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2208/2601 (84.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=3794.159±164.030 μJy (0.003794±0.000164 Jy) at λ=4.608 μm, mag_AB=14.952±0.047\n",
      "Processing observations:  14%|█▍        | 30/218 [00:00<00:03, 48.28files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2672/3600 (74.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2354\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2354\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1949/2601 (74.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_1.fits: flux=1462.765±49.545 μJy (0.001463±0.000050 Jy) at λ=1.874 μm, mag_AB=15.987±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0503_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.069117e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3031/3600 (84.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2640\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2640\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2215/2601 (85.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=3662.059±165.687 μJy (0.003662±0.000166 Jy) at λ=4.643 μm, mag_AB=14.991±0.049\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0503_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0503_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2334\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2334\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1958/2601 (75.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0503_2.fits: flux=1345.617±46.710 μJy (0.001346±0.000047 Jy) at λ=1.918 μm, mag_AB=16.078±0.038\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2878/3600 (79.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2272\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2272\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2144/2601 (82.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=1249.009±49.258 μJy (0.001249±0.000049 Jy) at λ=1.481 μm, mag_AB=16.159±0.043\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (5.752662e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2216/3600 (61.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4372\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4372\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1683/2601 (64.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_1.fits: flux=2968.763±121.265 μJy (0.002969±0.000121 Jy) at λ=4.253 μm, mag_AB=15.219±0.044\n",
      "Processing observations:  16%|█▌        | 35/218 [00:00<00:03, 48.76files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2888/3600 (80.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1963\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1963\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2145/2601 (82.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=1316.198±47.939 μJy (0.001316±0.000048 Jy) at λ=1.516 μm, mag_AB=16.102±0.040\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (5.870905e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2175/3600 (60.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3829\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3829\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1663/2601 (63.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_2.fits: flux=3159.580±125.333 μJy (0.003160±0.000125 Jy) at λ=4.289 μm, mag_AB=15.151±0.043\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (6.027371e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.97px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2219/3600 (61.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3511\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3511\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1685/2601 (64.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=3127.450±125.724 μJy (0.003127±0.000126 Jy) at λ=4.326 μm, mag_AB=15.162±0.044\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2877/3600 (79.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1677\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1677\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2143/2601 (82.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_3.fits: flux=1480.483±49.805 μJy (0.001480±0.000050 Jy) at λ=1.553 μm, mag_AB=15.974±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0616_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2837/3600 (78.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1331\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1331\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2110/2601 (81.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=1366.444±48.874 μJy (0.001366±0.000049 Jy) at λ=1.591 μm, mag_AB=16.061±0.039\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0616_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0616_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2160/3600 (60.0%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3287\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3287\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1648/2601 (63.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0616_4.fits: flux=3434.933±131.572 μJy (0.003435±0.000132 Jy) at λ=4.363 μm, mag_AB=15.060±0.042\n",
      "Processing observations:  19%|█▉        | 41/218 [00:00<00:03, 49.67files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_1B_0679_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2208/3600 (61.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4398\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4398\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1684/2601 (64.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=3265.288±132.424 μJy (0.003265±0.000132 Jy) at λ=4.400 μm, mag_AB=15.115±0.044\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_1B_0679_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0679_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2897/3600 (80.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1505\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1505\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2163/2601 (83.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0679_1.fits: flux=1418.873±47.779 μJy (0.001419±0.000048 Jy) at λ=1.628 μm, mag_AB=16.020±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2025W25_1B_0746_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 3035/3600 (84.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3086\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3086\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2214/2601 (85.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=3943.713±184.762 μJy (0.003944±0.000185 Jy) at λ=4.797 μm, mag_AB=14.910±0.051\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W25_1B_0746_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_1B_0746_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2699/3600 (75.0%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2627\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2627\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1956/2601 (75.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_1B_0746_1.fits: flux=1328.373±45.679 μJy (0.001328±0.000046 Jy) at λ=2.127 μm, mag_AB=16.092±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (4.696401e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2158/3600 (59.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3952\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3952\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1643/2601 (63.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=2489.474±291.238 μJy (0.002489±0.000291 Jy) at λ=4.110 μm, mag_AB=15.410±0.127\n",
      "Processing observations:  21%|██        | 46/218 [00:00<00:03, 48.56files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2876/3600 (79.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2446\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2446\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2142/2601 (82.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_1.fits: flux=1229.067±48.064 μJy (0.001229±0.000048 Jy) at λ=1.347 μm, mag_AB=16.176±0.042\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2904/3600 (80.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2403\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2403\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2151/2601 (82.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=1290.831±50.333 μJy (0.001291±0.000050 Jy) at λ=1.379 μm, mag_AB=16.123±0.042\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2220/3600 (61.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3917\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3917\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1689/2601 (64.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_2.fits: flux=2727.435±118.167 μJy (0.002727±0.000118 Jy) at λ=4.145 μm, mag_AB=15.311±0.047\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2889/3600 (80.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2218\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2218\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2149/2601 (82.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=1208.975±47.677 μJy (0.001209±0.000048 Jy) at λ=1.412 μm, mag_AB=16.194±0.043\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.145005e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2212/3600 (61.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3816\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3816\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1682/2601 (64.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_3.fits: flux=2842.580±118.798 μJy (0.002843±0.000119 Jy) at λ=4.181 μm, mag_AB=15.266±0.045\n",
      "Processing observations:  23%|██▎       | 51/218 [00:01<00:03, 47.57files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0075_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.417434e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2200/3600 (61.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3849\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3849\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1678/2601 (64.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=2896.453±121.598 μJy (0.002896±0.000122 Jy) at λ=4.217 μm, mag_AB=15.245±0.046\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0075_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0075_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2164\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2164\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2139/2601 (82.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0075_4.fits: flux=1255.917±50.672 μJy (0.001256±0.000051 Jy) at λ=1.446 μm, mag_AB=16.153±0.044\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (3.813377e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2194/3600 (60.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.5431\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.5431\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1673/2601 (64.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=2850.733±164.158 μJy (0.002851±0.000164 Jy) at λ=3.817 μm, mag_AB=15.263±0.063\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_2.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2882/3600 (80.1%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2212\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2212\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2148/2601 (82.6%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_2.fits: flux=1074.991±48.967 μJy (0.001075±0.000049 Jy) at λ=1.103 μm, mag_AB=16.321±0.049\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2863/3600 (79.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1949\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1949\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2118/2601 (81.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=1267.285±50.104 μJy (0.001267±0.000050 Jy) at λ=1.128 μm, mag_AB=16.143±0.043\n",
      "Processing observations:  26%|██▌       | 56/218 [00:01<00:03, 47.38files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_3.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (3.905322e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2190/3600 (60.8%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4890\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4890\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1673/2601 (64.3%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_3.fits: flux=3515.909±119.192 μJy (0.003516±0.000119 Jy) at λ=3.850 μm, mag_AB=15.035±0.037\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0206_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2192/3600 (60.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4632\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4632\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1671/2601 (64.2%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=2964.433±114.166 μJy (0.002964±0.000114 Jy) at λ=3.884 μm, mag_AB=15.220±0.042\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0206_4.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0206_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2905/3600 (80.7%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1604\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1604\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2171/2601 (83.5%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0206_4.fits: flux=1207.903±49.305 μJy (0.001208±0.000049 Jy) at λ=1.156 μm, mag_AB=16.195±0.044\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (4.052316e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2191/3600 (60.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4667\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4667\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 1676/2601 (64.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=2616.971±111.297 μJy (0.002617±0.000111 Jy) at λ=3.917 μm, mag_AB=15.356±0.046\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_1.fits\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2896/3600 (80.4%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1751\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1751\n",
      "2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/2601 (82.9%) pixels available\n",
      "2026-05-19 17:42:09 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_1.fits: flux=1267.507±51.243 μJy (0.001268±0.000051 Jy) at λ=1.183 μm, mag_AB=16.143±0.044\n",
      "Processing observations:  28%|██▊       | 61/218 [00:01<00:03, 47.48files/s]2026-05-19 17:42:09 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2875/3600 (79.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1698\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1698\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2139/2601 (82.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=1341.112±53.815 μJy (0.001341±0.000054 Jy) at λ=1.211 μm, mag_AB=16.081±0.044\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (4.114605e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2168/3600 (60.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4649\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4649\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1662/2601 (63.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_2.fits: flux=2732.212±111.813 μJy (0.002732±0.000112 Jy) at λ=3.951 μm, mag_AB=15.309±0.044\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (4.212143e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2160/3600 (60.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4410\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4410\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1655/2601 (63.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=2659.775±108.998 μJy (0.002660±0.000109 Jy) at λ=3.986 μm, mag_AB=15.338±0.044\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.672673e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2892/3600 (80.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1910\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1910\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/2601 (82.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_3.fits: flux=1237.373±51.541 μJy (0.001237±0.000052 Jy) at λ=1.240 μm, mag_AB=16.169±0.045\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0241_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (4.476950e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2200/3600 (61.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4197\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4197\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1680/2601 (64.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=2971.164±117.977 μJy (0.002971±0.000118 Jy) at λ=4.021 μm, mag_AB=15.218±0.043\n",
      "Processing observations:  30%|███       | 66/218 [00:01<00:03, 46.84files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0241_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0241_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2889/3600 (80.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2018\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2018\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2149/2601 (82.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0241_4.fits: flux=1285.306±51.293 μJy (0.001285±0.000051 Jy) at λ=1.270 μm, mag_AB=16.127±0.043\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2885/3600 (80.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2118\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2118\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2150/2601 (82.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=1253.049±49.470 μJy (0.001253±0.000049 Jy) at λ=1.286 μm, mag_AB=16.155±0.043\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (4.498141e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2213/3600 (61.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4342\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4342\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1681/2601 (64.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_1.fits: flux=2824.587±111.777 μJy (0.002825±0.000112 Jy) at λ=4.039 μm, mag_AB=15.273±0.043\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2025W25_2A_0366_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2888/3600 (80.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2465\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2465\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2158/2601 (83.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=1197.947±49.210 μJy (0.001198±0.000049 Jy) at λ=1.316 μm, mag_AB=16.204±0.045\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2025W25_2A_0366_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W25_2A_0366_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (4.861885e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2224/3600 (61.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.5171\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.5171\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1686/2601 (64.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W25_2A_0366_2.fits: flux=2486.968±196.896 μJy (0.002487±0.000197 Jy) at λ=4.075 μm, mag_AB=15.411±0.086\n",
      "Processing observations:  33%|███▎      | 71/218 [00:01<00:03, 46.73files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0204_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.347740e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2684/3600 (74.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4317\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4317\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1992/2601 (76.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=1407.786±55.346 μJy (0.001408±0.000055 Jy) at λ=2.441 μm, mag_AB=16.029±0.043\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0204_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0204_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2965/3600 (82.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2056\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2056\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2193/2601 (84.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0204_4.fits: flux=546.690±45.227 μJy (0.000547±0.000045 Jy) at λ=0.750 μm, mag_AB=17.056±0.090\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3054/3600 (84.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2028\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2028\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2255/2601 (86.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=682.702±45.682 μJy (0.000683±0.000046 Jy) at λ=0.767 μm, mag_AB=16.814±0.073\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (7.822022e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2650/3600 (73.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3584\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3584\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_1.fits: flux=1448.970±45.017 μJy (0.001449±0.000045 Jy) at λ=2.499 μm, mag_AB=15.997±0.034\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (7.223686e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2661/3600 (73.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3411\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3411\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1983/2601 (76.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=1456.665±43.326 μJy (0.001457±0.000043 Jy) at λ=2.567 μm, mag_AB=15.992±0.032\n",
      "Processing observations:  35%|███▍      | 76/218 [00:01<00:03, 47.01files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3035/3600 (84.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1916\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1916\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2247/2601 (86.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_2.fits: flux=605.347±43.904 μJy (0.000605±0.000044 Jy) at λ=0.785 μm, mag_AB=16.945±0.079\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3059/3600 (85.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1896\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1896\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2254/2601 (86.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=618.616±44.292 μJy (0.000619±0.000044 Jy) at λ=0.804 μm, mag_AB=16.921±0.078\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (7.053709e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2666/3600 (74.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3568\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3568\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1992/2601 (76.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_3.fits: flux=1528.272±44.604 μJy (0.001528±0.000045 Jy) at λ=2.636 μm, mag_AB=15.939±0.032\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0240_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3050/3600 (84.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1904\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1904\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2250/2601 (86.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=778.940±46.245 μJy (0.000779±0.000046 Jy) at λ=0.823 μm, mag_AB=16.671±0.064\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0240_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0240_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (7.201919e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.98px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2681/3600 (74.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3940\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3940\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1999/2601 (76.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0240_4.fits: flux=1539.682±44.831 μJy (0.001540±0.000045 Jy) at λ=2.707 μm, mag_AB=15.931±0.032\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (7.648971e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.98px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2652/3600 (73.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4473\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4473\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=1647.086±46.491 μJy (0.001647±0.000046 Jy) at λ=2.780 μm, mag_AB=15.858±0.031\n",
      "Processing observations:  38%|███▊      | 82/218 [00:01<00:02, 47.61files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3058/3600 (84.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2182\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2182\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2269/2601 (87.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_1.fits: flux=725.446±45.271 μJy (0.000725±0.000045 Jy) at λ=0.842 μm, mag_AB=16.748±0.068\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0298_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (7.206540e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2653/3600 (73.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4437\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4437\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1970/2601 (75.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=1757.885±47.203 μJy (0.001758±0.000047 Jy) at λ=2.856 μm, mag_AB=15.788±0.029\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0298_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0298_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3061/3600 (85.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1765\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1765\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2270/2601 (87.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0298_2.fits: flux=822.573±45.689 μJy (0.000823±0.000046 Jy) at λ=0.862 μm, mag_AB=16.612±0.060\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.55px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3035/3600 (84.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1858\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1858\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2249/2601 (86.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=949.856±47.480 μJy (0.000950±0.000047 Jy) at λ=0.882 μm, mag_AB=16.456±0.054\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (6.502416e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2636/3600 (73.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4902\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4902\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1961/2601 (75.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_1.fits: flux=1771.789±45.945 μJy (0.001772±0.000046 Jy) at λ=2.934 μm, mag_AB=15.779±0.028\n",
      "Processing observations:  40%|███▉      | 87/218 [00:01<00:02, 47.07files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (6.146542e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2630/3600 (73.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4312\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4312\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1958/2601 (75.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=2051.454±47.773 μJy (0.002051±0.000048 Jy) at λ=3.013 μm, mag_AB=15.620±0.025\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3038/3600 (84.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2030\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2030\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2261/2601 (86.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_2.fits: flux=984.955±48.598 μJy (0.000985±0.000049 Jy) at λ=0.903 μm, mag_AB=16.416±0.054\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.677693e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3042/3600 (84.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2279\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2279\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2256/2601 (86.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=826.022±46.983 μJy (0.000826±0.000047 Jy) at λ=0.925 μm, mag_AB=16.608±0.062\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.896560e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2640/3600 (73.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4470\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4470\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1963/2601 (75.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_3.fits: flux=1809.017±87.946 μJy (0.001809±0.000088 Jy) at λ=3.097 μm, mag_AB=15.756±0.053\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_1A_0553_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.800812e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2662/3600 (73.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4633\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4633\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1988/2601 (76.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=1869.821±46.000 μJy (0.001870±0.000046 Jy) at λ=3.182 μm, mag_AB=15.720±0.027\n",
      "Processing observations:  42%|████▏     | 92/218 [00:01<00:02, 47.78files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_1A_0553_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_1A_0553_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3025/3600 (84.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2653\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2653\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2239/2601 (86.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_1A_0553_4.fits: flux=944.086±48.616 μJy (0.000944±0.000049 Jy) at λ=0.947 μm, mag_AB=16.462±0.056\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3048/3600 (84.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2399\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2399\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2265/2601 (87.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=983.024±56.680 μJy (0.000983±0.000057 Jy) at λ=0.969 μm, mag_AB=16.419±0.063\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (6.036169e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.48px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2663/3600 (74.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.5222\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.5222\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1984/2601 (76.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_1.fits: flux=1943.599±46.780 μJy (0.001944±0.000047 Jy) at λ=3.268 μm, mag_AB=15.678±0.026\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (5.794674e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2669/3600 (74.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4600\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4600\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1995/2601 (76.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=1939.999±45.926 μJy (0.001940±0.000046 Jy) at λ=3.356 μm, mag_AB=15.680±0.026\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3044/3600 (84.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2353\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2353\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2267/2601 (87.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_2.fits: flux=1364.514±52.581 μJy (0.001365±0.000053 Jy) at λ=0.992 μm, mag_AB=16.063±0.042\n",
      "Processing observations:  44%|████▍     | 97/218 [00:02<00:02, 47.31files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2664/3600 (74.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4348\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4348\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1983/2601 (76.2%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=1833.077±45.467 μJy (0.001833±0.000045 Jy) at λ=3.446 μm, mag_AB=15.742±0.027\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.747464e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.86px) → diameter=2.57px (radius=1.29px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3055/3600 (84.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2268\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2268\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2274/2601 (87.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_3.fits: flux=1028.139±48.842 μJy (0.001028±0.000049 Jy) at λ=1.016 μm, mag_AB=16.370±0.052\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0026_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2682/3600 (74.5%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4620\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4620\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2004/2601 (77.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=2165.391±48.053 μJy (0.002165±0.000048 Jy) at λ=3.539 μm, mag_AB=15.561±0.024\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0026_4.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0026_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3015/3600 (83.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2185\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2185\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2231/2601 (85.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0026_4.fits: flux=1111.770±50.065 μJy (0.001112±0.000050 Jy) at λ=1.040 μm, mag_AB=16.285±0.049\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (6.433695e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.98px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2640/3600 (73.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.5136\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.5136\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1974/2601 (75.9%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=2024.261±47.522 μJy (0.002024±0.000048 Jy) at λ=3.634 μm, mag_AB=15.634±0.025\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3029/3600 (84.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.6038\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.6038\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2244/2601 (86.3%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_1.fits: flux=1133.164±53.317 μJy (0.001133±0.000053 Jy) at λ=1.064 μm, mag_AB=16.264±0.051\n",
      "Processing observations:  47%|████▋     | 103/218 [00:02<00:02, 48.44files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3026/3600 (84.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 2.8322\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 2.8322\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2236/2601 (86.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=1150.701±63.468 μJy (0.001151±0.000063 Jy) at λ=1.090 μm, mag_AB=16.248±0.060\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_2.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2655/3600 (73.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.4378\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.4378\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1979/2601 (76.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_2.fits: flux=2150.735±49.043 μJy (0.002151±0.000049 Jy) at λ=3.732 μm, mag_AB=15.569±0.025\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2025W26_2A_0142_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 3009/3600 (83.6%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3142\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3142\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2222/2601 (85.4%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=1340.145±71.541 μJy (0.001340±0.000072 Jy) at λ=1.115 μm, mag_AB=16.082±0.058\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2025W26_2A_0142_3.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W26_2A_0142_3: detector 4, shape (54, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2429/3240 (75.0%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3694\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3694\n",
      "2026-05-19 17:42:10 - spxquery.processing.background - WARNING - Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1919/2499 (76.8%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W26_2A_0142_3.fits: flux=2892.327±55.237 μJy (0.002892±0.000055 Jy) at λ=3.834 μm, mag_AB=15.247±0.021\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2025W29_2A_0482_1.fits\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Loaded 2025W29_2A_0482_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 2705/3600 (75.1%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1713\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1713\n",
      "2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Background mask: 1970/2601 (75.7%) pixels available\n",
      "2026-05-19 17:42:10 - spxquery.processing.photometry - INFO - Extracted photometry from 2025W29_2A_0482_1.fits: flux=1194.361±45.618 μJy (0.001194±0.000046 Jy) at λ=1.941 μm, mag_AB=16.207±0.041\n",
      "Processing observations:  50%|████▉     | 108/218 [00:02<00:02, 47.90files/s]2026-05-19 17:42:10 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0220_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2910/3600 (80.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2140\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2140\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2167/2601 (83.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_1.fits: flux=944.186±52.315 μJy (0.000944±0.000052 Jy) at λ=0.878 μm, mag_AB=16.462±0.060\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0220_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (9.327552e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2489/3600 (69.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1867/2601 (71.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_1.fits: flux=1765.301±48.943 μJy (0.001765±0.000049 Jy) at λ=2.915 μm, mag_AB=15.783±0.030\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0220_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2920/3600 (81.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2311\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2311\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2175/2601 (83.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_2.fits: flux=1005.164±54.939 μJy (0.001005±0.000055 Jy) at λ=0.899 μm, mag_AB=16.394±0.059\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0220_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (9.076173e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2515/3600 (69.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3031\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3031\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1907/2601 (73.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_2.fits: flux=2011.550±66.631 μJy (0.002012±0.000067 Jy) at λ=2.995 μm, mag_AB=15.641±0.036\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0220_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.879545e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2548/3600 (70.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3350\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3350\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1927/2601 (74.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_3.fits: flux=1874.131±49.584 μJy (0.001874±0.000050 Jy) at λ=3.079 μm, mag_AB=15.718±0.029\n",
      "Processing observations:  52%|█████▏    | 113/218 [00:02<00:02, 39.89files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0220_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2899/3600 (80.5%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2470\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2470\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2156/2601 (82.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_3.fits: flux=871.215±52.082 μJy (0.000871±0.000052 Jy) at λ=0.920 μm, mag_AB=16.550±0.065\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0220_4.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2951/3600 (82.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2614\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2614\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2203/2601 (84.7%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_4.fits: flux=1000.422±53.895 μJy (0.001000±0.000054 Jy) at λ=0.942 μm, mag_AB=16.400±0.058\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0220_4.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0220_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (8.779163e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2529/3600 (70.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3140\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3140\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1905/2601 (73.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0220_4.fits: flux=1797.884±47.939 μJy (0.001798±0.000048 Jy) at λ=3.163 μm, mag_AB=15.763±0.029\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0238_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.697320e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2532/3600 (70.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3515\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3515\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1923/2601 (73.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_1.fits: flux=1800.706±51.464 μJy (0.001801±0.000051 Jy) at λ=3.189 μm, mag_AB=15.761±0.031\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0238_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2939/3600 (81.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2588\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2588\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2185/2601 (84.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_1.fits: flux=944.437±52.993 μJy (0.000944±0.000053 Jy) at λ=0.949 μm, mag_AB=16.462±0.061\n",
      "Processing observations:  54%|█████▍    | 118/218 [00:02<00:02, 41.09files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0238_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (8.821747e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2542/3600 (70.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3513\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3513\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1927/2601 (74.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_2.fits: flux=1968.890±49.185 μJy (0.001969±0.000049 Jy) at λ=3.277 μm, mag_AB=15.664±0.027\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0238_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2929/3600 (81.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2558\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2558\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2179/2601 (83.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_2.fits: flux=1150.933±137.921 μJy (0.001151±0.000138 Jy) at λ=0.972 μm, mag_AB=16.247±0.130\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0238_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.881748e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2542/3600 (70.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3129\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3129\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1925/2601 (74.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_3.fits: flux=2048.186±50.681 μJy (0.002048±0.000051 Jy) at λ=3.366 μm, mag_AB=15.622±0.027\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0238_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2946/3600 (81.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2492\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2492\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2191/2601 (84.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_3.fits: flux=1425.975±57.989 μJy (0.001426±0.000058 Jy) at λ=0.995 μm, mag_AB=16.015±0.044\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0238_4.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_4: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 5 pixels with NaN variance using median variance (9.263569e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2530/3600 (70.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1921/2601 (73.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_4.fits: flux=1857.524±48.432 μJy (0.001858±0.000048 Jy) at λ=3.457 μm, mag_AB=15.728±0.028\n",
      "Processing observations:  56%|█████▋    | 123/218 [00:02<00:02, 42.05files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0238_4.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0238_4: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2950/3600 (81.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2362\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2362\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2192/2601 (84.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0238_4.fits: flux=1141.545±54.912 μJy (0.001142±0.000055 Jy) at λ=1.019 μm, mag_AB=16.256±0.052\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0255_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2935/3600 (81.5%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2285\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2285\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2176/2601 (83.7%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_1.fits: flux=1336.669±57.809 μJy (0.001337±0.000058 Jy) at λ=1.043 μm, mag_AB=16.085±0.047\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0255_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (9.974161e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2518/3600 (69.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3296\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3296\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1896/2601 (72.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_1.fits: flux=2224.747±51.935 μJy (0.002225±0.000052 Jy) at λ=3.550 μm, mag_AB=15.532±0.025\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0255_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (1.048660e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2535/3600 (70.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2942\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2942\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1903/2601 (73.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_2.fits: flux=2069.844±52.080 μJy (0.002070±0.000052 Jy) at λ=3.646 μm, mag_AB=15.610±0.027\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0255_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2914/3600 (80.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 2.4939\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 2.4939\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2165/2601 (83.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_2.fits: flux=1043.547±74.868 μJy (0.001044±0.000075 Jy) at λ=1.068 μm, mag_AB=16.354±0.078\n",
      "Processing observations:  59%|█████▊    | 128/218 [00:02<00:02, 43.37files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0255_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_3: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2918/3600 (81.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 2.9842\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 2.9842\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2187/2601 (84.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_3.fits: flux=1291.598±81.120 μJy (0.001292±0.000081 Jy) at λ=1.093 μm, mag_AB=16.122±0.068\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0255_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0255_3: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2532/3600 (70.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3065\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3065\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1916/2601 (73.7%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0255_3.fits: flux=2140.071±53.264 μJy (0.002140±0.000053 Jy) at λ=3.744 μm, mag_AB=15.574±0.027\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0803_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0803_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (9.747738e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2538/3600 (70.5%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3039\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3039\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1905/2601 (73.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0803_1.fits: flux=1577.118±48.239 μJy (0.001577±0.000048 Jy) at λ=2.763 μm, mag_AB=15.905±0.033\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0803_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0803_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2929/3600 (81.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2294\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2294\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2188/2601 (84.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0803_1.fits: flux=848.163±50.985 μJy (0.000848±0.000051 Jy) at λ=0.838 μm, mag_AB=16.579±0.065\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0803_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0803_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2933/3600 (81.5%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2128\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2170/2601 (83.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0803_2.fits: flux=818.600±51.105 μJy (0.000819±0.000051 Jy) at λ=0.857 μm, mag_AB=16.617±0.068\n",
      "Processing observations:  61%|██████    | 133/218 [00:02<00:01, 43.97files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0803_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0803_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2529/3600 (70.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3026\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3026\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1896/2601 (72.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0803_2.fits: flux=14355.420±1138.777 μJy (0.014355±0.001139 Jy) at λ=2.838 μm, mag_AB=13.507±0.086\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0804_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0804_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2939/3600 (81.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2288\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2288\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2184/2601 (84.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0804_1.fits: flux=743.164±56.829 μJy (0.000743±0.000057 Jy) at λ=0.799 μm, mag_AB=16.722±0.083\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0804_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0804_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (9.511875e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2526/3600 (70.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2504\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2504\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1910/2601 (73.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0804_1.fits: flux=1459.365±46.025 μJy (0.001459±0.000046 Jy) at λ=2.618 μm, mag_AB=15.990±0.034\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W02_2A_0804_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0804_2: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.620286e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2523/3600 (70.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2924\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2924\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1907/2601 (73.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0804_2.fits: flux=1560.586±47.531 μJy (0.001561±0.000048 Jy) at λ=2.690 μm, mag_AB=15.917±0.033\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W02_2A_0804_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W02_2A_0804_2: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2934/3600 (81.5%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2240\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2240\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2186/2601 (84.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W02_2A_0804_2.fits: flux=796.559±50.332 μJy (0.000797±0.000050 Jy) at λ=0.818 μm, mag_AB=16.647±0.069\n",
      "Processing observations:  63%|██████▎   | 138/218 [00:03<00:01, 43.29files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W03_1A_0013_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0013_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2924/3600 (81.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2261\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2261\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2167/2601 (83.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0013_1.fits: flux=694.081±52.676 μJy (0.000694±0.000053 Jy) at λ=0.781 μm, mag_AB=16.796±0.082\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W03_1A_0013_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0013_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (9.882953e-02). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2518/3600 (69.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2437\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2437\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1892/2601 (72.7%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0013_1.fits: flux=1443.251±46.928 μJy (0.001443±0.000047 Jy) at λ=2.549 μm, mag_AB=16.002±0.035\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W03_1A_0014_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0014_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2927/3600 (81.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2362\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2362\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2189/2601 (84.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0014_1.fits: flux=659.956±51.037 μJy (0.000660±0.000051 Jy) at λ=0.763 μm, mag_AB=16.851±0.084\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W03_1A_0014_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0014_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.97px (radius=1.48px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2532/3600 (70.3%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2422\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2422\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1919/2601 (73.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0014_1.fits: flux=1454.207±48.495 μJy (0.001454±0.000048 Jy) at λ=2.482 μm, mag_AB=15.993±0.036\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D4/2026W03_1A_0030_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0030_1: detector 4, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (2.184365e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.104\" (0.99px) → diameter=2.98px (radius=1.49px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1621/3600 (45.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - WARNING - Insufficient background pixels for zodiacal estimation (1621/3600 = 45.0% < 50.0%) - using fallback scale factor 1.0\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0000\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 1298/2601 (49.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0030_1.fits: flux=1262.530±64.941 μJy (0.001263±0.000065 Jy) at λ=2.431 μm, mag_AB=16.147±0.056\n",
      "Processing observations:  66%|██████▌   | 143/218 [00:03<00:01, 44.30files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D1/2026W03_1A_0030_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0030_1: detector 1, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.254\" (0.85px) → diameter=2.56px (radius=1.28px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2919/3600 (81.1%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2485\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2485\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2182/2601 (83.9%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0030_1.fits: flux=554.868±50.937 μJy (0.000555±0.000051 Jy) at λ=0.746 μm, mag_AB=17.040±0.100\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0050_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (7.096026e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2809/3600 (78.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2213\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2213\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2080/2601 (80.0%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_1.fits: flux=2737.161±127.862 μJy (0.002737±0.000128 Jy) at λ=4.035 μm, mag_AB=15.307±0.051\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0050_1.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2778/3600 (77.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2033\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2033\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2112/2601 (81.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_1.fits: flux=1260.898±54.529 μJy (0.001261±0.000055 Jy) at λ=1.282 μm, mag_AB=16.148±0.047\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0050_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2779/3600 (77.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2210\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2210\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2096/2601 (80.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_2.fits: flux=1271.140±53.966 μJy (0.001271±0.000054 Jy) at λ=1.313 μm, mag_AB=16.140±0.046\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0050_2.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.98px) → diameter=2.95px (radius=1.48px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2838/3600 (78.8%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2088\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2088\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2097/2601 (80.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_2.fits: flux=2702.203±126.961 μJy (0.002702±0.000127 Jy) at λ=4.070 μm, mag_AB=15.321±0.051\n",
      "Processing observations:  68%|██████▊   | 148/218 [00:03<00:01, 45.11files/s]2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0050_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (7.711303e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2829/3600 (78.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2045\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2045\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2091/2601 (80.4%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_3.fits: flux=2888.991±132.192 μJy (0.002889±0.000132 Jy) at λ=4.106 μm, mag_AB=15.248±0.050\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0050_3.fits\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2778/3600 (77.2%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2246\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2246\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/2601 (81.6%) pixels available\n",
      "2026-05-19 17:42:11 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_3.fits: flux=1190.671±54.385 μJy (0.001191±0.000054 Jy) at λ=1.343 μm, mag_AB=16.211±0.050\n",
      "2026-05-19 17:42:11 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0050_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2796/3600 (77.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2216\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2216\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2118/2601 (81.4%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_4.fits: flux=1316.112±54.604 μJy (0.001316±0.000055 Jy) at λ=1.376 μm, mag_AB=16.102±0.045\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0050_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0050_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.101148e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2805/3600 (77.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2001\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2001\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2083/2601 (80.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0050_4.fits: flux=2768.397±127.684 μJy (0.002768±0.000128 Jy) at λ=4.141 μm, mag_AB=15.294±0.050\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0066_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0066_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2812/3600 (78.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2418\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2418\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2094/2601 (80.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0066_1.fits: flux=2927.368±126.216 μJy (0.002927±0.000126 Jy) at λ=4.000 μm, mag_AB=15.234±0.047\n",
      "Processing observations:  70%|███████   | 153/218 [00:03<00:01, 43.76files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0066_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0066_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2793/3600 (77.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1906\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1906\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2132/2601 (82.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0066_1.fits: flux=1216.649±54.806 μJy (0.001217±0.000055 Jy) at λ=1.252 μm, mag_AB=16.187±0.049\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0100_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0100_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.993776e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2756/3600 (76.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2553\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2553\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2034/2601 (78.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0100_2.fits: flux=3006.505±121.072 μJy (0.003007±0.000121 Jy) at λ=3.898 μm, mag_AB=15.205±0.044\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0100_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0100_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2699/3600 (75.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1618\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1618\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2067/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0100_2.fits: flux=1277.320±55.780 μJy (0.001277±0.000056 Jy) at λ=1.167 μm, mag_AB=16.134±0.047\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0574_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (8.144151e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2793/3600 (77.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1980\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1980\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2075/2601 (79.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_1.fits: flux=2935.308±130.514 μJy (0.002935±0.000131 Jy) at λ=4.184 μm, mag_AB=15.231±0.048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0574_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2789/3600 (77.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1955\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1955\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2123/2601 (81.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_1.fits: flux=1324.581±54.758 μJy (0.001325±0.000055 Jy) at λ=1.415 μm, mag_AB=16.095±0.045\n",
      "Processing observations:  72%|███████▏  | 158/218 [00:03<00:01, 44.77files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0574_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2772/3600 (77.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1844\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1844\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2089/2601 (80.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_2.fits: flux=1238.732±52.707 μJy (0.001239±0.000053 Jy) at λ=1.449 μm, mag_AB=16.168±0.046\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0574_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2826/3600 (78.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1969\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1969\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2095/2601 (80.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_2.fits: flux=2971.608±132.743 μJy (0.002972±0.000133 Jy) at λ=4.220 μm, mag_AB=15.218±0.049\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0574_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2772/3600 (77.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1954\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1954\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2106/2601 (81.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_3.fits: flux=1277.807±52.378 μJy (0.001278±0.000052 Jy) at λ=1.484 μm, mag_AB=16.134±0.045\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0574_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 5 pixels with NaN variance using median variance (8.992914e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2823/3600 (78.4%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1842\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1842\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2087/2601 (80.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_3.fits: flux=2878.931±1539.052 μJy (0.002879±0.001539 Jy) at λ=4.257 μm, mag_AB=15.252±0.580\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0574_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.426852e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2817/3600 (78.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1742\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1742\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2076/2601 (79.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_4.fits: flux=3088.206±140.257 μJy (0.003088±0.000140 Jy) at λ=4.293 μm, mag_AB=15.176±0.049\n",
      "Processing observations:  75%|███████▍  | 163/218 [00:03<00:01, 43.98files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0574_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0574_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2784/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1607\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1607\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2120/2601 (81.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0574_4.fits: flux=1421.860±54.910 μJy (0.001422±0.000055 Jy) at λ=1.520 μm, mag_AB=16.018±0.042\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0634_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2799/3600 (77.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1188\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1188\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2112/2601 (81.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_1.fits: flux=1579.049±55.096 μJy (0.001579±0.000055 Jy) at λ=1.557 μm, mag_AB=15.904±0.038\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0634_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (9.724593e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2820/3600 (78.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1599\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1599\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2087/2601 (80.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_1.fits: flux=3114.009±140.755 μJy (0.003114±0.000141 Jy) at λ=4.330 μm, mag_AB=15.167±0.049\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0634_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.025065e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2832/3600 (78.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1639\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1639\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2095/2601 (80.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_2.fits: flux=2873.847±140.594 μJy (0.002874±0.000141 Jy) at λ=4.367 μm, mag_AB=15.254±0.053\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0634_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2793/3600 (77.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0865\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0865\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2111/2601 (81.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_2.fits: flux=1353.058±50.419 μJy (0.001353±0.000050 Jy) at λ=1.595 μm, mag_AB=16.072±0.040\n",
      "Processing observations:  77%|███████▋  | 168/218 [00:03<00:01, 44.50files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_1A_0634_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2780/3600 (77.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0984\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0984\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2109/2601 (81.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_3.fits: flux=1431.963±51.806 μJy (0.001432±0.000052 Jy) at λ=1.633 μm, mag_AB=16.010±0.039\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_1A_0634_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_1A_0634_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2827/3600 (78.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1687\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1687\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2091/2601 (80.4%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_1A_0634_3.fits: flux=3394.389±148.781 μJy (0.003394±0.000149 Jy) at λ=4.404 μm, mag_AB=15.073±0.048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_2A_0061_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0061_3: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2767/3600 (76.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1334\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1334\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2097/2601 (80.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0061_3.fits: flux=1199.604±54.314 μJy (0.001200±0.000054 Jy) at λ=1.113 μm, mag_AB=16.202±0.049\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_2A_0061_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0061_3: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 4 pixels with NaN variance using median variance (5.323153e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2817/3600 (78.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2821\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2821\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2098/2601 (80.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0061_3.fits: flux=3363.706±125.364 μJy (0.003364±0.000125 Jy) at λ=3.831 μm, mag_AB=15.083±0.040\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_2A_0061_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0061_4: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2810/3600 (78.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1456\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1456\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2134/2601 (82.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0061_4.fits: flux=1268.168±54.640 μJy (0.001268±0.000055 Jy) at λ=1.139 μm, mag_AB=16.142±0.047\n",
      "Processing observations:  79%|███████▉  | 173/218 [00:03<00:01, 43.89files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_2A_0061_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0061_4: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.506469e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2800/3600 (77.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2493\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2493\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2067/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0061_4.fits: flux=4530.713±1549.718 μJy (0.004531±0.001550 Jy) at λ=3.864 μm, mag_AB=14.760±0.371\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W03_2A_0316_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (2.873659e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2956/3600 (82.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1671\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1671\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2164/2601 (83.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_1.fits: flux=4040.897±228.516 μJy (0.004041±0.000229 Jy) at λ=4.895 μm, mag_AB=14.884±0.061\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W03_2A_0316_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2787/3600 (77.4%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3056\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3056\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2053/2601 (78.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_1.fits: flux=1664.426±52.621 μJy (0.001664±0.000053 Jy) at λ=2.267 μm, mag_AB=15.847±0.034\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W03_2A_0316_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2784/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3050\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3050\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2059/2601 (79.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_2.fits: flux=4733.751±73.507 μJy (0.004734±0.000074 Jy) at λ=2.319 μm, mag_AB=14.712±0.017\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W03_2A_0316_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (3.178692e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2945/3600 (81.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2157/2601 (82.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_2.fits: flux=4061.055±236.790 μJy (0.004061±0.000237 Jy) at λ=4.931 μm, mag_AB=14.878±0.063\n",
      "Processing observations:  82%|████████▏ | 178/218 [00:03<00:00, 44.47files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W03_2A_0316_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2791/3600 (77.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2799\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2799\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2069/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_3.fits: flux=2540.374±62.562 μJy (0.002540±0.000063 Jy) at λ=2.372 μm, mag_AB=15.388±0.027\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W03_2A_0316_3.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2962/3600 (82.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2138\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2138\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2172/2601 (83.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_3.fits: flux=4402.804±256.699 μJy (0.004403±0.000257 Jy) at λ=4.967 μm, mag_AB=14.791±0.063\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W03_2A_0316_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_4: detector 6, shape (54, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (3.952930e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2647/3240 (81.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2014\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2014\n",
      "2026-05-19 17:42:12 - spxquery.processing.background - WARNING - Background window [4:55, -2:49] exceeds image boundaries, clipped to [4:55, 0:49]\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2054/2499 (82.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0316_4.fits: flux=3859.532±263.560 μJy (0.003860±0.000264 Jy) at λ=5.003 μm, mag_AB=14.934±0.074\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W03_2A_0316_4.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0316_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 0/3600 (0.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - WARNING - Insufficient background pixels for zodiacal estimation (0/3600 = 0.0% < 50.0%) - using fallback scale factor 1.0\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0000\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 0/2601 (0.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.background - WARNING - Insufficient usable pixels with strict masking: 0/10 required. Trying with relaxed masking (exclude_bad_only=False).\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 0/2601 (0.0%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.background - ERROR - Insufficient usable pixels in background window even with relaxed masking: 0/10 required (window: 50×50, aperture_radius: 1.3)\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - ERROR - Background estimation failed for 2026W03_2A_0316_4.fits - dropping observation\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_2A_0544_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0544_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2800/3600 (77.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2530\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2530\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2079/2601 (79.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0544_1.fits: flux=2407.628±115.856 μJy (0.002408±0.000116 Jy) at λ=3.931 μm, mag_AB=15.446±0.052\n",
      "Processing observations:  84%|████████▍ | 183/218 [00:04<00:00, 44.26files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_2A_0544_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0544_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2786/3600 (77.4%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1568\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1568\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2122/2601 (81.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0544_1.fits: flux=1341.547±54.640 μJy (0.001342±0.000055 Jy) at λ=1.195 μm, mag_AB=16.081±0.044\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_2A_0544_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0544_2: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2805/3600 (77.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1693\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1693\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2146/2601 (82.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0544_2.fits: flux=1253.825±59.453 μJy (0.001254±0.000059 Jy) at λ=1.223 μm, mag_AB=16.154±0.051\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_2A_0544_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0544_2: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (5.839788e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2803/3600 (77.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2508\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2508\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2085/2601 (80.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0544_2.fits: flux=2598.990±198.152 μJy (0.002599±0.000198 Jy) at λ=3.966 μm, mag_AB=15.363±0.083\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D5/2026W03_2A_0570_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0570_1: detector 5, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.059\" (0.99px) → diameter=2.96px (radius=1.48px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2812/3600 (78.1%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2048\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2078/2601 (79.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0570_1.fits: flux=2872.747±153.672 μJy (0.002873±0.000154 Jy) at λ=4.177 μm, mag_AB=15.254±0.058\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D2/2026W03_2A_0570_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W03_2A_0570_1: detector 2, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.154\" (0.84px) → diameter=2.52px (radius=1.26px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2765/3600 (76.8%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2094\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2094\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2097/2601 (80.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W03_2A_0570_1.fits: flux=1221.272±51.941 μJy (0.001221±0.000052 Jy) at λ=1.408 μm, mag_AB=16.183±0.046\n",
      "Processing observations:  86%|████████▌ | 188/218 [00:04<00:00, 45.37files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_1A_0529_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_1A_0529_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2959/3600 (82.2%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1659\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1659\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2176/2601 (83.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_1A_0529_1.fits: flux=4271.620±218.537 μJy (0.004272±0.000219 Jy) at λ=4.824 μm, mag_AB=14.824±0.056\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_1A_0529_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_1A_0529_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2769/3600 (76.9%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2445\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2445\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2063/2601 (79.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_1A_0529_1.fits: flux=1256.694±48.331 μJy (0.001257±0.000048 Jy) at λ=2.165 μm, mag_AB=16.152±0.042\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_1A_0529_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_1A_0529_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (2.364245e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2939/3600 (81.6%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1725\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1725\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2147/2601 (82.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_1A_0529_2.fits: flux=4412.825±223.012 μJy (0.004413±0.000223 Jy) at λ=4.859 μm, mag_AB=14.788±0.055\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_1A_0529_2.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_1A_0529_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2784/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2740\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2740\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2069/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_1A_0529_2.fits: flux=1421.801±50.528 μJy (0.001422±0.000051 Jy) at λ=2.216 μm, mag_AB=16.018±0.039\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0029_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0029_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2976/3600 (82.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1995\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1995\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2178/2601 (83.7%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0029_1.fits: flux=4172.013±213.417 μJy (0.004172±0.000213 Jy) at λ=4.790 μm, mag_AB=14.849±0.056\n",
      "Processing observations:  89%|████████▊ | 193/218 [00:04<00:00, 43.90files/s]2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0029_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0029_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2790/3600 (77.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.3674\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.3674\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2069/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0029_1.fits: flux=1455.525±49.687 μJy (0.001456±0.000050 Jy) at λ=2.116 μm, mag_AB=15.992±0.037\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0108_1.fits\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2782/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1278\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1278\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Background mask: 2062/2601 (79.3%) pixels available\n",
      "2026-05-19 17:42:12 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_1.fits: flux=1903.037±58.075 μJy (0.001903±0.000058 Jy) at λ=1.719 μm, mag_AB=15.701±0.033\n",
      "2026-05-19 17:42:12 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0108_1.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2960/3600 (82.2%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2335\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2335\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2165/2601 (83.2%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_1.fits: flux=4110.344±186.182 μJy (0.004110±0.000186 Jy) at λ=4.484 μm, mag_AB=14.865±0.049\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0108_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.394919e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2976/3600 (82.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1831\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1831\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2173/2601 (83.5%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_2.fits: flux=4000.791±333.600 μJy (0.004001±0.000334 Jy) at λ=4.516 μm, mag_AB=14.895±0.091\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0108_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2795/3600 (77.6%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1381\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1381\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2058/2601 (79.1%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_2.fits: flux=1944.547±57.079 μJy (0.001945±0.000057 Jy) at λ=1.759 μm, mag_AB=15.678±0.032\n",
      "Processing observations:  91%|█████████ | 198/218 [00:04<00:00, 44.80files/s]2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0108_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.355133e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2981/3600 (82.8%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1438\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1438\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2175/2601 (83.6%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_3.fits: flux=4121.781±178.481 μJy (0.004122±0.000178 Jy) at λ=4.549 μm, mag_AB=14.862±0.047\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0108_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2817/3600 (78.2%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1214\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1214\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2073/2601 (79.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_3.fits: flux=1506.202±51.169 μJy (0.001506±0.000051 Jy) at λ=1.799 μm, mag_AB=15.955±0.037\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0108_4.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2782/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1370\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1370\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2048/2601 (78.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_4.fits: flux=1419.670±53.001 μJy (0.001420±0.000053 Jy) at λ=1.842 μm, mag_AB=16.020±0.041\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0108_4.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0108_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.382208e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2951/3600 (82.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1228\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1228\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2155/2601 (82.9%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0108_4.fits: flux=4070.757±175.531 μJy (0.004071±0.000176 Jy) at λ=4.582 μm, mag_AB=14.876±0.047\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0476_1.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.447094e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2938/3600 (81.6%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1355\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1355\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2154/2601 (82.8%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_1.fits: flux=3590.541±175.023 μJy (0.003591±0.000175 Jy) at λ=4.615 μm, mag_AB=15.012±0.053\n",
      "Processing observations:  93%|█████████▎| 203/218 [00:04<00:00, 40.65files/s]2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0476_1.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2797/3600 (77.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2045\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2045\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2054/2601 (79.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_1.fits: flux=1447.522±51.679 μJy (0.001448±0.000052 Jy) at λ=1.884 μm, mag_AB=15.998±0.039\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0476_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2810/3600 (78.1%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1784\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1784\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2077/2601 (79.9%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_2.fits: flux=1269.104±49.920 μJy (0.001269±0.000050 Jy) at λ=1.927 μm, mag_AB=16.141±0.043\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0476_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 2 pixels with NaN variance using median variance (1.573436e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2990/3600 (83.1%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1544\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1544\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2170/2601 (83.4%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_2.fits: flux=3581.874±186.217 μJy (0.003582±0.000186 Jy) at λ=4.649 μm, mag_AB=15.015±0.056\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0476_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.702935e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2978/3600 (82.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1726\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1726\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2173/2601 (83.5%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_3.fits: flux=3388.990±183.087 μJy (0.003389±0.000183 Jy) at λ=4.683 μm, mag_AB=15.075±0.059\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0476_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.371398e-01). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2784/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1620\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1620\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2052/2601 (78.9%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_3.fits: flux=1205.924±47.937 μJy (0.001206±0.000048 Jy) at λ=1.971 μm, mag_AB=16.197±0.043\n",
      "Processing observations:  95%|█████████▌| 208/218 [00:04<00:00, 42.14files/s]2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0476_4.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_4: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2808/3600 (78.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1969\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1969\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2076/2601 (79.8%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_4.fits: flux=1197.188±47.797 μJy (0.001197±0.000048 Jy) at λ=2.017 μm, mag_AB=16.205±0.043\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0476_4.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0476_4: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.863742e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2943/3600 (81.8%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1900\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1900\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2138/2601 (82.2%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0476_4.fits: flux=4050.658±195.962 μJy (0.004051±0.000196 Jy) at λ=4.717 μm, mag_AB=14.881±0.053\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0657_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0657_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2796/3600 (77.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.0732\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.0732\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2062/2601 (79.3%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0657_2.fits: flux=1423.298±54.720 μJy (0.001423±0.000055 Jy) at λ=1.643 μm, mag_AB=16.017±0.042\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0657_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0657_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (1.308375e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2968/3600 (82.4%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2537\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2537\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2165/2601 (83.2%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0657_2.fits: flux=3691.484±178.734 μJy (0.003691±0.000179 Jy) at λ=4.421 μm, mag_AB=14.982±0.053\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W04_2A_0657_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0657_3: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.433077e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2945/3600 (81.8%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2804\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2804\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2146/2601 (82.5%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0657_3.fits: flux=3858.379±183.096 μJy (0.003858±0.000183 Jy) at λ=4.453 μm, mag_AB=14.934±0.052\n",
      "Processing observations:  98%|█████████▊| 213/218 [00:04<00:00, 41.81files/s]2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W04_2A_0657_3.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W04_2A_0657_3: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2809/3600 (78.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.1040\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.1040\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2068/2601 (79.5%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W04_2A_0657_3.fits: flux=1233.037±51.930 μJy (0.001233±0.000052 Jy) at λ=1.681 μm, mag_AB=16.173±0.046\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W05_1A_0196_1.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W05_1A_0196_1: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.54px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2783/3600 (77.3%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2223\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2223\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2055/2601 (79.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W05_1A_0196_1.fits: flux=1270.802±46.637 μJy (0.001271±0.000047 Jy) at λ=2.063 μm, mag_AB=16.140±0.040\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W05_1A_0196_1.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W05_1A_0196_1: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 3 pixels with NaN variance using median variance (1.970570e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2965/3600 (82.4%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 0.7969\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 0.7969\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2160/2601 (83.0%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W05_1A_0196_1.fits: flux=4046.226±206.278 μJy (0.004046±0.000206 Jy) at λ=4.751 μm, mag_AB=14.882±0.055\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D3/2026W05_1A_0196_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W05_1A_0196_2: detector 3, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=5.223\" (0.85px) → diameter=2.55px (radius=1.27px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2798/3600 (77.7%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2115\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2115\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2071/2601 (79.6%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W05_1A_0196_2.fits: flux=1389.922±46.762 μJy (0.001390±0.000047 Jy) at λ=2.111 μm, mag_AB=16.043±0.037\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Reading SPHEREx MEF: demo_data/cloverleaf/data/D6/2026W05_1A_0196_2.fits\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Converted units: MJy/sr → μJy/arcsec² (factor: 2.350443e+01)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Loaded 2026W05_1A_0196_2: detector 6, shape (60, 60), units μJy/arcsec²\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Repaired 1 pixels with NaN variance using median variance (2.078181e+00). All repaired pixels have non-zero flags.\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - FWHM-based aperture: FWHM=6.615\" (1.07px) → diameter=3.22px (radius=1.61px)\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2968/3600 (82.4%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Zodiacal scaling factor: 1.2040\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Subtracted zodiacal background with scaling factor 1.2040\n",
      "2026-05-19 17:42:13 - spxquery.utils.spherex_mef - INFO - Background mask: 2162/2601 (83.1%) pixels available\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Extracted photometry from 2026W05_1A_0196_2.fits: flux=4214.819±207.682 μJy (0.004215±0.000208 Jy) at λ=4.785 μm, mag_AB=14.838±0.053\n",
      "Processing observations: 100%|██████████| 218/218 [00:04<00:00, 44.87files/s]\n",
      "2026-05-19 17:42:13 - spxquery.processing.photometry - INFO - Successfully processed 217 observations\n",
      "2026-05-19 17:42:13 - spxquery.processing.lightcurve - INFO - Generated light curve with 217 measurements\n",
      "2026-05-19 17:42:13 - spxquery.processing.lightcurve - INFO - Saved light curve to demo_data/cloverleaf/results/lightcurve.csv\n",
      "2026-05-19 17:42:13 - spxquery.core.pipeline - INFO - Marked stage 'processing' as complete\n",
      "2026-05-19 17:42:13 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=visualization, completed=['query', 'download', 'processing']\n",
      "2026-05-19 17:42:13 - spxquery.core.pipeline - INFO - Running visualization stage\n",
      "2026-05-19 17:42:13 - spxquery.core.pipeline - INFO - Filtered photometry results by bands ['D1', 'D2', 'D3', 'D4', 'D5', 'D6']: 217 -> 217 measurements\n",
      "2026-05-19 17:42:13 - spxquery.visualization.plots - INFO - Quality filtering: 217 total points (204 good, 13 rejected - shown as crosses)\n",
      "2026-05-19 17:42:13 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 216 measurements (1 outliers removed)\n",
      "2026-05-19 17:42:13 - spxquery.visualization.plots - INFO - Sigma clipping: 217 -> 216 measurements (1 outliers removed)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Light Curve Summary\n",
      "============================================================\n",
      "Total observations: 217\n",
      "Time span: 224.6 days\n",
      "MJD range: 60842.27 - 61066.92\n",
      "Wavelength range: 0.75 - 5.00 μm\n",
      "Number of bands: 6\n",
      "Upper limits: 0\n",
      "Mean SNR: 25.0\n",
      "\n",
      "Observations per band:\n",
      "  D1: 36\n",
      "  D2: 36\n",
      "  D3: 36\n",
      "  D4: 36\n",
      "  D5: 36\n",
      "  D6: 37\n",
      "============================================================\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2026-05-19 17:42:14 - spxquery.visualization.plots - INFO - Saved combined plot to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:42:14 - spxquery.core.pipeline - INFO - Marked stage 'visualization' as complete\n",
      "2026-05-19 17:42:14 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:42:14 - spxquery.core.pipeline - INFO - Visualization saved to demo_data/cloverleaf/results/combined_plot.png\n",
      "2026-05-19 17:42:14 - spxquery.core.pipeline - INFO - Saved pipeline state: stage=complete, completed=['query', 'download', 'processing', 'visualization']\n",
      "2026-05-19 17:42:14 - 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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zw1Y3BRK2pqtnpCamW7dumDlzJsKJyMhITJw4Ue0J5zsc4Wec8x3u8DPO+Q53+BnnfIczgfh8iz4RnSJ6JRDYavEf8Q1G5uuJcI/MS51OTk4OUlNT/W5hQTjfwQw/45zvcIefcc53uMPPOOc7nAnk5ztQkfk9m1vXKDL/5qwCvDmrEFarHdt3WsNWNwUS1swHKVarFWazGaH0C0SeV1pRUMzXHpPJpMxQCCGEEEIIaQw18zdcG6M2SbNP77K/Tp8tXKCYDzLsdjsOHjyo6l5C7blF0BcUFNTa+ZJUIPVO0mOT80kIIYQQQkINEfJWGuDVKRTzQYYm5CVFpkmTJiEj5ETMWywWGI3GkHnmYJ7L4uJilSoltGzZsqEfiRBCCCGEEBJkBJ2YHzJkCH766Sev5+fNm4dzzjmn0vFZs2bh1VdfxcaNGxEREYHTTz8dDz/8MAYMGOD1WsuXL8dTTz2FlStXory8XBk+3H777bjmmmu8jtm7dy8mT56MH374AceOHUNaWhquuOIKPPDAA4iKikJtU+s1IZ+cnIxQgmI+sERHR6u9VvvElHtCCCGEEBJKsDVdIxTzGqNHj0ZMTEyl461bt650bMKECZgxY4YSQCNHjlR12wsWLMD8+fMxe/ZsjBo1qtKYL774ApdddplKDR88eDCaNWuGRYsWYdy4cVi/fj2ef/75SmO2b9+O/v3748iRI+jevTsGDRqE3377DVOmTFFjZauNg6RWIy8ReUK0z4F8LijmCSGEEEJIKGG129XmzzgS4mJexHS7du2qfd3ChQuVkJdI9ooVK9CpUyd1XL6WKP91112n9s79FiWifv3116tIuIj6Sy+9VB0/dOgQBg4ciBdeeAEXXHCBGufMtddeq4T8HXfcoe4pSGr52LFjMXfuXEydOhWPPfZYrd8709QJPweEEEIIISSUkQZz/jSZY2M63wn5HmLTp09Xe0mp14S8IBH0W265RaWtv/322y5j3nrrLdUy4eKLL3YIeaF58+aYNm2a+loEvTOrVq1SafmS8qy9RpAa8ddee025j7/00ktK3BNCCCGEEEJIY0bM7/zdSCMQ8yUlJVi8eLH6esyYMZXOa8e+/vprl+Pffvut1zHnn3++qn2XiL+k67uPufDCCyul0ssigKTc5+bm4ueffw7IeyOEEEIIIYQQQkJOzEs0/bbbblOGdBLxzs7OrvSaLVu2oKysDCkpKWjTpk2l871791Z7qYF3Zt26dS7nnRHzPKmHFyG/detWn8ZUdS9SdyxZskSVJMg+1JCSDV/KSAghhBBCCAlFrHb/NxLiYv7JJ59U6eszZ87EnXfeiY4dO+KJJ55weY0m8D0JeaFp06aqVl4i5tL/XJD0+ry8vCrHacezsrJ8vpenMaRyxwER39omJQpiaCjCdt++fUE3XdIZQTwQdu/e3dCPQgghhBBCSEjWzPuzkRA1wBNn+RtvvFG1lJP+2nv27FGO9CLuH3nkEcTFxSlxLxQWFlbr/i6CXurmRczHxsY6xlQ1TsYI2gKAL/fyNMYT8izioK8hKfta2r4clxZv2hZqaM/s7dm1448//jgyMjJU9oO0BXzvvfdUecKff/5Zo/Z+Utog/dglm6Iu5uuvv/5Sz3rmmWciPT0ddUFVz619DuRz4fyZcf6suB8ndQfnvH7hfNc/nHPOd7jDzzjnO5ypzedbMp1l05DgZ0CeCTpYofNrHAlRMS9t3pzp3LkzHnzwQZx66qk4++yzVaT0pptucvThDjXcReHEiRNxzz33OFqQyT9AMdELNSM9+eUh3QGqcuPXfrlI+8A+ffqoryUqn5SUpLoXSEeAf/zjHzW6r0T3PYndQKC9H9kH+uehPW9V15Vz8rqjR48qg0X38ZJhIvOu1wdtgk1YwTnnfIc7/IxzvsMdfsY53+FMbT7f8ne4u/l3QJ7JXrH5M46EqJj3hghAEfTS1/3XX39VbeO0PvQSnfVGUVGR2ktUXnDuXS/jJNJf3Rjncd7u5WmMJyQN3/mezpF5iVRLZF8EqmyhiLvodEb7xSI9053fn0S+5ZeIpLNrxzdv3ozJkycrg0OZc/ExkO8vuugixziplR82bJh6jXMbQfl8yKKPtCeUBZK+ffviqaeewhlnnOHyPJLaL9ke33//vRLMrVq1UgtG0nbwo48+Uu0LhREjRjjGON9r3rx5qh3h2rVr1XuTrJJnn30WJ510kst9vvzyS/Xs27dvV+UismClzUVVP2c5J6+TtovuGQvyC1sWTcQvgmK+fuCc1y+c7/qHc875Dnf4Ged8hzO1+XxLKbN0BnOOzNdVVioJLCGlGKX1nIj5AwcOqO/T0tLUfu/evV4FtqS1JyYmOkS2COn4+Hi1ciXjunXrVmmcdj3nD7Hc6/fff/d6L09jPCE1/J4WEAT5h+dcUx5KyCqg9szent35vPNrNJ8BidDLcUlvF+Et9fT333+/KmH47LPPcMkll+CLL75Qe2/XE7F97rnnqsj/o48+qub03XffxVlnnYVly5ahX79+6nX79+/Haaedpj4fkunRpUsXJe6lpEO6JMgCwx133KHMFyUzpGvXrmqcfF7kXh988AHGjRunxL8IeFlwEI8HSf2Xz4lmbjd//nzVNUHGifCXRQNZJNA8Fqr6OWvvS96Dp1/KVZ0jdQPnvH7hfNc/nHPOd7jDzzjnO5zx9/MtGc/OWc+B+tvS6meavT9jGishJebFyM65Pj0zM1NFtQ8fPqyEmIg/ZyRiKvTo0cPleM+ePbF06VJ13l3MSyR3w4YNKhIqKf7OY7766ivHNd3xdq9gQcSm1Ptr+4ZEFlKOHDmiMhEkii516fJzvOCCC9R58USQxZPVq1c7shaks8HAgQMxadIkh5j3tKBwyy23YOjQoSpqrgnlm2++WUXLZcVRxLXwwAMP4ODBg+r+kvGhIVFzuY4suogwFzEvkXnnyL/4J4jQF2+HN954w3FcxL18Jp9++mnHcXleaV0ongCyiCTIQoFkmnDFkxBCCCGEhCs1FfOfvFeIT94rgo159j4TMiE9EewSWXVuAycrSJJmLXz++eeVxkiUVesN795L3vm8M998840SmcOHD3dJbdbGSM96Z4MI4dChQ+rZJAPAPZU7GBABL8JYFjBkX1VZQn0gcyspQG3btlVRa1mc+b//+z8VrT527JiKro8dO1aVHIjol00i2hIF37Ztm1fn+z/++EOdv/LKK9XrtbGSoSGReXn/Wn29pL7L58JZyGtUlxWxYMECFdG/4oorHPeQTcoHJNr/448/qtdJBok8k4h8TcgLsjjgKSOEEEIIIYQQDe1v9ob+291fbHZdjbax18RizqIW+N//NW/oRw8Zgioy/8svvyAnJ0eJLBFGGlJLffXVVytRJjXTzu3h7r77bhWFFbd7EdySii9IvfTrr7+uIqw33HCDy30koio11BJpnzNnDi699FJ1XO593333OYzpnJH0bBHqy5cvV9HWF1980WFSJlFjiehLtLaqmvG6RhYV5D14Qo6LiJW0mR07dnh8TWpqqooi1zXSblCyHiRC/8477yiRrUXgpa5cIuNSYy6bt/finoUhiJAXRDx7Q+5ZXl6uaoGkDt8ftPtoC0nuaGUUWvmA9pl0RiL43rI8CCGEEEJI40YLxkmQSf42Fg+ohs6urSlMs29kYn7r1q247rrr0KJFCxV9FyEugmjNmjUqWi6p0m+++WalKK+kZYtpWa9evVTUU8SaRE/lgy/10nIdZ6Q2W0SkRH8lMiwp1GIytnDhQhVxlQUC57RqDblW//791b0keizRVflHtnPnTtVKT1K3GxIR4p7EuPwykIi39sugQ4cODfrLQBZGtIj4qFGjVPq8RNO3bNnicHkXh3+JxHtCTOQ8oY197rnn1GfBE2JkKHNRG7T7SN28fFbdCVXzQkIIIYQQEjwBueqCcfUViCPBS1CpDklRvvXWW1Uds4hkqZGXFGwRZtKyTM55akknUXJ5zSuvvKJEvPQdF5EvkV0R2Z4YPXq0ighLRF96ncsCgIjz22+/3WtkVyKsYm6mOaBLKzWp7Zb7iEmaFl0ONkS4a6t5wVAz74xkYIgxnNS5y89Pc5CXDAf5GdYEWaTQIuNVjZUUf3mNeCNUhbd0e+0+8gu0qvtoNfFaJN8ZWbgghBBCCCHEU0Au2IJx/mCFXm01H0dCUsyLY/irr77q11jpVy5bTZC0eUnRrwlS5y0R+lBD+8cfjL8EJAtCovWyKDNhwgT1vZRI/Pvf/0bLli0reSeIGPeEONjLLzppcyeRfuc2hM5jZXVTMgL+97//qe4I7nXzmjO/ZrQo2RrOSMaALAaI0Z0sQriXVmj3kWeXRab33ntPufJrdfOy4LRx40Ya4BFCCCGkUZN/rBBxSa5/r5HgD8b5iv3vWnh/xpEQFPOk8XLvvfeq7ItZs2apmnpJvT/55JPxr3/9C+3bt1fpR+KDIC0A161b5/EaItLfeust1ZpOSjKkZENq68UwT0zpRICLgaEgQlyc7cVZXlrTyUKSGNaJkaI4z0tphghxyRyQ1nNSay+ZF1InLxF5aUP3z3/+U5WDXH755Uq8Z2dn49tvv1WLRJJlIEjWgXg5yPuRrANZYX355ZfV84krPiGEEEJIY6WAYj5kg3ENWTMvixvyd/zXX3+t/m6Xsmz5m11KcSX7Wkqm3YN6GqI1JHgsgTXJ5j799NNVxytv2dyCeKaJ35p7Nvc111yDhoZingQFYkKoRdVFwEvEXFrWyT84caYXAX3KKaeoEoeqkKi+iP4nnnhCCWoRzFLXLiUc0qJOQ0S+lHNIicSHH36oDPHkmCwEaL8wZdx///tfJcjFRNFqtapFAXkWify3atUKzzzzjKrRlw4HMl7a2ckigsY555yjFgjkl4R4Ksh7lMwOMV9csmRJHc4oIYQQQgghDYfVrldbzcdVff6jjz5SekGQgJwYpMvf8mKm/uijj+Ljjz/GTz/9pP5md0YygMX7TMq2pU20eLJJxqwsDEiXM8ncdeeLL77AZZddprwLBg8ejGbNmmHRokWqLHv9+vVKuzQkOrvkFJM6Rz5gkmYtEV7N7dwd+UDt2rULGRkZLm3xQgH5GImzv5i/VdfaLVDIPySpWZe2gBL5Djeq+jzILxQxRZFfUpKRQOoeznn9wvmufzjnnO9wh5/x4JvvfdsPonXHymbCpG7mO5C6xZfx89ZnoGlszZ+lqMCGc3vs8np/KWEV4T5hwgQl5jUky1YyYsXjTFpIi+jXEKNzMUoX03MJ/Dl3QJNgoATz5O9uZ+N0yaiVv8Pl/Yio1zqgScawaA/pwiWBPk/G6fUFVUA9I7UvkpohqeSkdsg/WEFWyAghgcVqy+WUEkIIIY0I0SeiU0SvBAIbdLBB78dWdWBQouLir9XVScgL4lelaSxpPy4p8RrTp09Xe8mWdW4bLZ3KbrnlFuWR9fbbb7tcT8p3RchffPHFDiEviFnhtGnT1NcvvPACGhKK+XpGXPqlRmP8+PH1feuwoaioCG+88YZKf2/Tpo3qWU8ICSw2m6vxIyGEEELCG9EnolNErwSyZt6fzV969uyp9lICK6W6QklJiWorLkhbcne0Y5q3loZ4YXkbIxkAkjkrEX/Jpm0oKOZJyCFu8eJ0L/UukvLCNHNCAovNXgKzeYvaE0IIIfWJmJs570no18z7s/nLzp071V66TSUlJTlaQou4F8NqCQS6I4bWgtTAO6OZbmvnnRHzvO7duyshv3XrVjQUNMAjIUe7du3UP0hCSOARAX/48D9gtmyCydgVKSmfQ6+L5lQTQgipc0TAS1RY662utWYjoUlFmn3No+z+jNEQgzvNhFo6UQnScUrwJOQFaUcttfK5ubkoKChAbGysSq+Xmv2qxslxMe0WN/0ePXqgIaCYJ4SQRlQHX136vETkRcjb7Ra1Ly39CSZTptfX6/UJMOgT6+BpCSGEhDN7svdi1c9r0D4vDcaIE5JETNzEzE0yL3fs2FFpnBi8Sc0yCR/Ky2wwl5/wZC8utPp1ne+++07VvUtUXjpbaWjtoKtaGBJBL3Xzmph3biHtbZyMEWRMQ0ExTwghjQQR3dUJb4OhhYrIa5H5qKgzGZknhBASUMpKyvH8la9j14ZsZHRPw7QFkxEZHaEi8+IgrkXmpaUvI/Ohi5jZWX2o6v7ktSP46KXDtbrX5s2bcfXVV6vPjbSN1mrnwx2K+SCE3QIJPwekoZCUekmtl4g8hTwhhJDakp9biKJc1/r3rI17lZC3mK1qv2bBeqR3q0hlbtMsHSktm8EYpaeQD3F8rX8ffUsqLro+xSUyf/3ALT7fZ9++fSqtXtLk7777btx5550u52NiYqr1YRCDbUGi8s5jtHGeWuS5j2kIKOaDCEkJ0T4wYu5GGjfaLxztc0FIfQp6Sa1nrTwhhJDaEpcYg4RkVyHUrHWSishrkfk+I3qoyDwJL7RWc9VhiNTDEOk6zleOHTuGkSNHqrr16667Ds8//3yl16Slpan93r17PV5DRLmk2CcmJjqEuYj3+Ph4VTcv46Rlnzva9dLT09FQUMwHEQaDQZkvSK2QIGlFkmYUKtkEFosFRqMxZJ45mOdShLx8DuTzIJ8LQgghhJBwQYS7pNZLRJ5CPnyx2nVq82ecLxQWFuLcc89V7fSkD/ybb77pUYdkZmYqMzzpiCVR/NatW7ucX7t2rdq7m9hJqv7SpUvVeXcxbzabsWHDBtWeriHbZFPMBxktWrRQe03Qh5IA1cxKKOYDgwh57fNASH0jxnaEEEJIXQp6Sa1nRN4/Q9vGbj4rna0uvvhirFq1CmeffTY+/vhjrwEwyXgeNmwY5s2bh88//xwTJkxwOT979my1v/DCCyv1khcxL+elHt+Zb775RrWlu+CCC5Sgbygo5oMMEcItW7ZUTp2y4hMqiJA/evQokpOT2fc9AEhqPSPypCFp7H8kEEIIIYHCZsuFPoD/X5XONKHw/2mrjwZ4lcfZqz5vteKKK67A4sWLMWjQIMyZM0f1fa8KqaUXMf/kk08qkd6pUyd1fMWKFXj99ddVEO2GG25wGXPjjTfiqaeewldffaXuIdF/Leh63333qa8nTpyIhoRiPkgRIRdKYk7EvAhQWZmS6DwhJDzIP1aAuKSGM3YhhBBCQh27tIUNAfEdaGx2vdpqPq5qMf/KK69g7ty56utmzZrhtttu8/g6qZ+X88Lw4cOVMZ70oe/VqxdGjBiB8vJyLFiwQGUYv/vuu0rQO5OUlIR33nkHY8eOxZgxYzBkyBAVuFy4cKGqsZcFAjnWkFDM1zN9+/ZVIn38+PFqI4SQYKbgWCHFPCGEENIImDlzptok8h3MkXlxrdeY+7eo98Rjjz3mEPPCiy++qIS8LAaIiJdovoj8yZMnY8CAAR6vMXr0aJVqLxH9lStXqgUAqZ+//fbbMW7cODQ0FPP1zOrVqz22NiCEkGCjrKQMWRv3KNfhyGgnm1lCCCGEhB1asDE/P185udcWWw3M7NzHVYWIdNn84dprr1VbTTjjjDNUin4wQjFPCCHEo5C/96wp2LUhCxnd0/Hcokco6AkhhBBCggiKeUIIaYR18JI+XxUSkRchbym3qv2aBeuQ3q1tlWNik2KYkk8IqTHSjlXa8Wp7Qkjj6jPvaRzxDYp5QghpZIihXXWmdpJaLxF5LTLfZ0RPRuYJIQFHBLyUIEo3HzGhEm8hCnoSrjQ2U1mrXa82f8YR36CYJ4QQUgmpkZfUeonIU8gTQgLFoUOHVFsnZ+R76Yoj3XB27NhRaYy0623evDl/CGGIZHQ1JgJtKhvsiwM26NTmzzjiGxTzhBBCvAp6Sa2n+R0hJFCIKHcW5hKZP3bsmCMy36FDB0bmGxFxjUzMN7aOM4zM1z0U84QQQgghpEGQlHottZ418yTUsdlyoW+E/eQDxZIP92PJR/ths1Xdmo6cgGKeEEKIVxpbCiQhpP7RauRZK09CHbvtOEAx73ef+UFXtVFbSaEF95z6c938kMIMinlCCCFeCeb0PUIIIYQELza7Tm3+jCO+QTFPCCGEEEIIIXWA3V4Cq3kr9IYWjW5+bTWMzDuPI75BMU8IIYQQQgghPqbS6/QJPgv5wiOXw2rZDIOxC4AXaz3HNnsJzOYtMITA4oDNrlebP+OIb1DME0IIIYQQQogv2PIAD2JezO9slr0uxyQiL0IedrPa6/W/wmpxHScLA76a5omQP3z4HzBbNsFk7Ao7XubPrJFDMV/PiGOrwWDA+PHj1UYIIYQQQggJbUSQ241tUJTfzOE3I6n1EpHXIvM222kwGDN8up5VFgfEUM8JiciLkLfbLRV7/UqY/14cEAd4i7UAVlsE9Pokv97DzJkz1Wa1WhEIrNCpzZ9xxDco5uuZ1atXIy4urr5vSwghhBBCCKnjVHvn3u86XTRimn0Cc+lS2OynI2vFFjRr3QqR0ZHV3sOgT1SbyzFDCxWR1yLzZtvpMP29OGCz2WA05MDgYwmAJ7RgY35+PuLj41FbmGZf91DME0IIIYQQQkgd1M2LoLdYMnD/2dOwa0MWMrqn47lFj/gk6N3R66KRkvI5Skt/QlTUmTiQ7xq5DzYkvu9fZJ74CsU8IYQQQgghhASAwuNF2Lf9gMux7I1blJC3lFvVfs2CdUjv1tblNbFJMT61gxVBbzJlwlyqR9bGPWjWOsmvhYH6gJH5uodinhBCCCGEEEICQExCU7Tu2NLlWGLzTBWR1yLzfUb0dBHg+ccKfBLyGmUlZjx49hSXSL8p0sSfXyOEYp4QQgghhBBC6ojIaJMS3BKRdxfy7nX27ojQl/PO7N64uVKkP61rG+QVHoelwAadTudzpL8usdr1avNnHPENinlCCCGEEEJIvdeT+/P6YEV6yksrOqCzx/Mi4CW1viYp8eJoH5eUWEmUxzfvUinSL5F5Y44eqamp0OuDQwzboYPNj5p5GUd8g2KeEEIIIYQQEhAao5gXIV945HLVgi4qsj3s9jnK+K62SGs6d0d7b5F+cbMPNhiZr3so5gkhhBBCCCHEB+y2PFjtebDD7jgmEXkR8rCbodfvUK3oDKYTEXqbZa/XBQuJvvuDP5H++sZm16nNV377ZCfWfLoTNtuJuSVVQzFPCCGEEEIICSrqI2Lv7R5ej9tLAdthGAxtoP+7v7ugN7SAwdhFCXqbtT1MUYMrReb1KsLu6nKvRd+BqIC9p1Dm1Mvbq62s0IwXzvimoR8nJKCYJ4QQQgghhAQV9ZJ+L0La0z1seZWOi5C3H7sGsGwFDOmwJ38Kna5ChItwj2n2CYryFmPTsjj0bqZHZO2z7EMeK/Rq82cc8Q2KeUIIIYQQQgj5G7stH7BkucyH3bK9QsjbzYBlF+xlywFjR5d2cQ+cuwC7/zqCjO7fq5r2YE6BD8Y0e+dxxDco5uuZvn37wmAwYPz48WojhBBCCCGEBA86fRx0xnTXg4bmsBs7A5YtsNpTkbO3NYAIx+msjYew+6/DsJTbHO3ipKZdXU93GHZ7FAqPFyGYmTlzptqsVmtArmeDXm3+jCO+QTFfz6xevRpxcXH1fVtCCCGEEEKIn0hKvT3xDZQfGQ2rfQ+SEh5AVPLHjlT7Zq2T0O6kFtj91yFHuzgtMm+zRama+X3bK9fMBxNasDE/Px/x8fG1vp7VrlObP+OIb1DME0IIIYQQQohbzb5sztjEtd66D4AFNstmWEuXQv+3a73JBDzz/RVY95PNRcifML/zjKTnZ208rBYDGntaPqk5FPOEEEIIIYQQn8k/Voi4pJhaz5iYyolA1hlaOCLcDUH+sQLEJcW6HBPzPXcDPnlOvbE9bNZd0Bu7wKBc6088d1RTO9K7RXkV5bFuc1ZWUoYHRr7uiOb7Wmevr2tjwADBmvm6h2KeEEIIIYQQ4jMFXsS8szh3rif3hLy29OgVKsKtL+rikrLeMO/HVcx7Qp4vMuFF2Cy7Kwl5X3FOtc/auAe7/zrosc5esOtyEJfYrNKzGaqI9AcTdrseNrver3HEN4J+po4ePYrU1FTodDp07HjCMdITs2bNQr9+/RATE4OkpCScd955+OWXX6ocs3z5cvU6eb2Mk/Hvv/9+lWP27t2L6667Dq1atUJUVBQ6d+6MRx99FKWlpX69R0IIIYQQQkIZTZyX5d2p9qonu3bOdlwJYOdNUtRFyIs7vJay7vIa695Kae7BgE4XqVLrC3ItNR4rorx1x5aOTdLxpc7eGGFw1Nk7n2+enurTIoMz1iCaMyt0fm8kTCLzEydOxJEjR6p93YQJEzBjxgxER0dj5MiRSlgvWLAA8+fPx+zZszFq1KhKY7744gtcdtllsNlsGDx4MJo1a4ZFixZh3LhxWL9+PZ5//vlKY7Zv347+/furZ+revTsGDRqE3377DVOmTFFjZYuMZL0LIYQQQggJT3TIg83iGsSSiLyLOC/7GTZrc9gsJdDrdZVS11XKelGXisi8W8q6WggwbwUaMPXe3+yEmiAp9VPn34z1Px6vVGfvLzYl5pMQDNjs/rWZk3EkDCLzIozfe+89/Otf/6rydQsXLlRCPjk5GevWrcOXX36J77//HkuXLlVt4CSKfvy46yrVsWPHcP3116vWCyL2lyxZovabN29WGQAvvPCCOubOtddeq4T8HXfcgT///BOffvoptmzZgksuuURF+adOnRrweSCEEEIIISRYsCMeemM7l03EuIhy6EwV4jxyIPSG5tAb0x2vca5BF+EuqfWR8TNcUuyrivAH9D2okoBtdXZ9X4mMNqnUenchb7OXwGzeovbecK/BJ42PoBXzJSUluPnmm9GtWzfcc889Vb52+vTpav/www+jU6dOjuMSQb/llluUkH/77bddxrz11luq7cLFF1+MSy+91HG8efPmmDZtmvpaBL0zq1atUoJd0v611whGoxGvvfYaTCYTXnrpJVgsNU+7IYQQQgghJFTxJs6rRIS0vgns1oO+p99bdtc6/V4EvPnoVbDk3aX2QJnLObtle72IfE2w2+GW5WAvweHD/8Cx3PFq703Q1zQFv76Renl/N+IbQTtTjz/+OHbu3In//ve/SiRXJfoXL16svh4zZkyl89qxr7/+2uX4t99+63XM+eefr2rhJeLvXAevjbnwwgsrpdLLIoCk3Ofm5uLnn3+u4bslhBBCCCEktBEBL/XkvhrDSaReb2hTdYRffe+aBeDuMl9tizlZAHDabKXLYLdsUQsGsjfpV1UcF2F99DLg+F2wH72yxoK+Js/lLNjtkdeh3LwZZssutZWW/gSzZRPsdovaV3y/y2Wz2nIR7Nig83sjIVwzL/XqEhWX9HgRyLt37/b6WklxLysrQ0pKCtq0aVPpfO/evR3XdEbS8Z3POxMREaHq4aUWfuvWrejRo0e1Y7TjsrAg9xoyZEiN3jMhhBBCCCGhgohkX8XroX2H0bx1CoqLi9GkSROfIvwSkffXMd7levKMbs+pl1Z4RZmwWzZDZ2gHm721cgKAdS9gzVLWbbDuhL1sOWB0NeC22/IBveeIeEU/+RNu9RoivCtq2U8gEXlNsEOXDYtlN0ymTHXOaGwHo6E9LNadMBm7IirqTOh10Qg1rHad2nxl0+ebsHn2ZthZNB+6Yl7M6G688UYkJCS4pLJ7Izs7W+09CXmhadOm6loSMS8oKEBsbKxKr8/Ly6tynBwXMZ+VleUQ89XdSzsuY7whKf/yHjUkwh8Ohnnynux2u8t7I5zvcIKfcc53uMPPOOc73OFnPHCov/ksudAZ4zzMs7ie2RzzXVhYiFW/rkJccoz6/tRTT3UR9NrrXYkADJ1gt0fAbq+Lvy0jYEj8APayn6GLHAjL8eOw61sAphTA0Bl2i7TX6wyY+sPutphgt2Ursent715Px3WIh0Ef73JMH5EKo7ErLCLorR0QGTEIOifBntLsS5SULkN01CDAHglbNfNw4vNd87/HJTAqm4ZopUBQ05T5zDEnqa28sByfnPW/gDxDuBN0Yv7ll1/G6tWr8e677ypDu+qQXxBCVat8IuhFRGtiXhtT1TgZI8gYX+/laYw76enpldz6q/MECAXkl4YskMgvEb0+aKs3wgbON+c83OFnnHMe7vAzzjkPVcpLyrHpt+2w6uMQ2TS6Ukvpo0d3Q6/fpz7jUg4rnaYOHTmI3EKTajUtXlPO2Gx5SE4urvR3v82aD70hp07fi93aHDpDPvIKj8OYo/39+hwM1t9hxSnAYRG1rsLWbrPAbi9CXmEpjDmVo87lKENOjm/Pbbe/Art9DfKPtocpQvSDq4awWFui0FD5eFW/UyyWMphMNZs36eDl7hVGQoOgEvMS+RYTuzPPPFO5xocjErWPi4sLy8i8/IKWcgeKec53OMLPOOc73OFnnPMd7vAzXnvKSsox6dInsWtDNtqd1BzTFj6ByOgIx3kxibZZmigHe5nvw4cPq2BX3pECR2S+V69erpF5S5Z6faWfl7S0M6aiLrFbSlBuTsCOX7PRvnN7x3uxW+zQGdt6GSXvMQu24ij1fj2crhFmiw06L9cyW4ph8nEOtM93QmIxIiNq9hBPPPGE0mDOkXn3AKQ/qPp3f1rTsWY+NMX8+PHjUV5erkzvfCUmpqIlg9TgeKOoqEjtJSrvPEYb5yyuvY3x5V6exrgjKf+e7hcOyC8QEfIU85zvcIWfcc53uMPPOOc73OFn3HfyjxWqXurOZG3cq4S8xWzF7o0H8fuiDUjv5lp+GptYjLhkvWO+5e/nbpknocNJ7TzXzOsr/n6shLfjAaS0zIJJZz+BXRuykNE9Hc8tekS1iLPrddBVce+yMguyN+1DSptkl8UMf9DLvf7+G9rTuZrMQcV1aj5vkj0h24n7Bmbe7X6a2ck4EoJi/ptvvlFiV9rJOaM5yu/bt89hLPfJJ5+gRYsWSEtLU9/v3bvXq8CWFPvExESHyBYxHR8fr1JRZJy0v3NHu57zqpTc6/fff/d6L09jCCGEEEIICTXikmLU5kyz1knIODkNu/7MRsZJzdFnRI9KYtZmqewAHxVZUXdenfmdLwsM7s/k+XUFldq2yTH3xYnsjVuUkLeUW9V+zYJ1que7QZcDq/3v96UDWndo6ZKdcP95s7Brw35kdE/DtPkP1VrQhysSlfcrMu/HmMZKUIl5QYT3Tz/95PGciHrtnCbwMzMzVZq6pPGI2G/dWtwoT7B27Vq110zsNHr27ImlS5eq8+5i3mw2Y8OGDao9XefOnV3GfPXVV45ruuPtXoQQQgghhIQ6IlqfW/gI1ixYj95D4wMiYmvSzq3ARzFf8TpXMS/fux9Lbp6pIvJaZL7PiJ4VkXlLOXTGlmrxYPvvuwAncVmRnbBfZSdIloLMRaXsBA8LIVUhrw9H/O0Zzz7zvhNUTmVSR+Np27VrlzrfoUMHx7F27dqpY5ISMmzYMPX1559/Xumas2fPdvSGd+8l73zePUNAFguGDx+uBL37GOlZ7+z4KBw6dAjLli1TGQBnnHFGreeCEEIIIYSQYEMEvIjXyGhTrcW5P68PJPIeJLX+gf/d4Uixd0YEefP0ZmjdsYVjk2wEicgbTQa1l++dz8tWEyFfcR/vJbqEhIyY95e7775b7Z988kls27bNcXzFihV4/fXXVer+DTfc4DJG2t9Jur1E2ufMmeM4Lu6T9913n8Np3pl+/fopoS6vmTRpkuO4xWLBbbfdpiL6d9xxB0wmz7/cCCGEEEIICWfcxbmkpUs0W/bBiAh4Sa13F/LeXx+hUuvvf288U+x9TLP3ZyMhmmbvDxJBv/POOzFjxgzlkDlixAhlpLdgwQIVxZc2dyLonUlKSsI777yDsWPHYsyYMaoWX1piLFy4UKX6ywKBVp/vjFyrf//+6l6LFy9WKfrSSm/nzp0YMGAAHnjggXp854QQQgghhNQ3ZbBbtgGGFtC59WF3b2M3acxT2L0hu6K+fMFkn1PzGzJi73t2QnDVytvtpTCbt8Jkagm9U8/6hkK52fthZkc3+0Ym5oUXX3xRCflXXnlFifiIiAgl8idPnqxEtidGjx6t6uYlor9y5Uq1ACDi/Pbbb8e4ceM8junUqZMywXvkkUfw/fffY+7cucoYT+7z4IMPhkWbOUIIIYQQQrwJxsToO2DL2wUYM2FI+kAJenf3ewmobVqzXQl5b/XlVdWWB7OYD0bs9hJYbDfjeN52FBV1RUrK5w0u6GmAV/eEhJiX+nj5hVAd0pu+pv3pJW1+3rx5NRrTtm1bFaEnhBBCCCEknJGe6jqc+DtcIvJG/U75ArBsgb1sGWDshNg4qE2hT4AdcbAZzWjXPc0Rmffkft+ghOiCgdWWC5vtuMuxsrItALbDbrfAbNmE0tKfYDJlurxGr0+AQZ9Yb89JMR8CYl6M4qSnISPShBBCCCGEhBci5HXGCuNphaEFLLb2iDBWROZ1kYM8ptrbbTZEREfg2R8eUv3og07IVxX918cjmBFB7i7K9bpU5KIjdLrtMBm7IirqzAaPzJMgFPNLlixRpnHLly/Hxo0bUVJS4ugb2bVrV5XSPmrUKI/15oQQQgghhJDQRYR7bslLaNlmq1chXxf15ZqRnvS6d7+Wc//5spIyZG3c8/fr/Ct/DZYUf4mk+4pOFw2j/nXExm1GkybBIeQZmQ8SMS8u7eIKP336dOzevVuZx/Xu3RtXX321asUmKfC5ubmqhdz//vc/vPTSS0hPT1du8DfffDPd3QkhhBBCCAkTYpOSoTN2qlbIBwoR8veNeELV3Xsy0tP6z4uQv/esKY6+8e7t5vKPFdSoDVwgFgZqI9hrmhIvPw+TqXNQCHmBYj5IxHzHjh2VOZyYwon7uwj5qlizZo3q+f7000/j+eefVwsApIK+ffvCYDBg/PjxaiOEEEIIISSUEOFstxypk2u7G+kJEpHf5Wakl9w6EUXHi9T5I/uPofB4IY7uP6aEvKVcXpeFNQvWqbZzGoXHi3wW89UtDASK+qxhr46ZM2eqzWq1BuR69ho602fNXYfsuetht1XvlUZqIObFpV2M5Xyti+/Tp4/apkyZQqM4N6SNnfS3J4QQQgghhFReKHB3uJfIuETktci8e/39vu0H0bpjCyXARXhrArzPiJ4uAnzf9gOep1tX+ZxE5KtcGMgrDrsfnRZszM/PR3x8fL1H5tuO6qU2S1EZFp//31rfvzHgk5iXVHl/kPZw/o4lhBBCCCGEEBHuklovEfneZ6V5rb+PiCxREXQR3u5Cvipad2hZ6VjFAoL3hQHJICDEV6SleUxMDAYOHKi+lwyIN998U7VFl6+ldN0f9P4M+vTTT5WLPSGEEEIIIYTUNQ4jvcgqIuK240pwSwS9tinxMl4WBh743x0eU+zdsweI98i8P1u4ce+996qMB+HPP/9U3nLnnXee8py7++6767c13RVXXKFSxUePHq1M8IYOHer3AxBCCCGEEEJIsBGohYHGCg3wTiCiXaLwwhdffIELLrhA+cutXbtWiXp/8Ssy//PPP+Oqq67C119/jeHDhyMtLQ33338/NmzY4PeDEEIIIYQQQoIHu70Udss2ta8NsYxiN0oYmXctPy8ursgqWbhwIUaOHKm+li5xWsS+3sS89JKX3P79+/ernvNnnHEGXnnlFfTs2RO9evXCCy+8gAMHvBhMEEIIIYQQQoIaEfDWY/+ELW+i2tdG0NdlSrrWf172JLiw23V+b+HGwIEDVTr9E088gVWrVuH8889Xx7du3Yo2bdrUr5jXMBqNKkXg448/xsGDBzFr1iwkJyfjvvvuU9H6ESNGqL7z0taOEEIIIYQQEpzYbcdht+w+sZUtAyxbALtZ7eV7l/PWfWpMQ6L1n3/mmpfVvqzE3KDPQ+oHaYP+zDPP4NJLL1VCWKfTqc0bjz32mOM1njbJMPfG8uXLVRq8RNDFwK5fv354//33a/zMEvgW7Tx79my89tpraN26tTo+b948nHPOOajXmnlPSIq9rDJIQb/dbkeXLl1w9OhRXHPNNXjggQeU4Nfc+wghhBBCCCHBg06fAMimYWgBGDMrBL0xE7rIQdDpok6c1ydUjKlHpE/8waxc2OxRHvvP/7FkK9p2jcWhrMMV/eb+TvGXzABpWyft5sSlnjXw9YP0mK9Jn3nncVUh0W3JDq8pkk3esWPHSselpbonpLb9sssug81mw+DBg9GsWTMsWrQI48aNw/r16/H888/7fG8JdH/zzTeVjv/nP/9BbaiVmJe0gA8//BAfffQRdu7cqd7glVdeqQR879691Wt+++033HDDDbjllltYU08IIYQQQkgIIMLdkPSBishXEvKa+K9nYhKaokW6ATpjC4/953sN6YyoWDlnV33nNUTI33vWFEebOU/u9CR0DPD69++PHj16oG/fvmpr164dysrKqr3ujTfeiGuvvdanZzh27Biuv/56WK1WJeolC0A4dOiQClBLWblkqA8ZMsTHdwV1rblz52LTpk3q+65du2LUqFEqYu8vfo2cMWOGEvGS4hAZGYkLL7wQL774okoRMBgMLq899dRTVX2ACHpCCCGEEEKce3WzxVfwogS8sVMlId9QVBjplXrsP99nRA9EmPYj/1jB35H5E0hEXoS8pVwi+FmqD7241LtfOy4ptt7eS2PA3/r36sZMmjQJdc1bb72ljOkuvvhih5AXmjdvjmnTpqljIuh9FfN//fWX0syyGJCZmamOPfvss0hJSVGm8t27d68/MX/XXXepNIX//ve/GDt2LOLj46t8vQj6yZMn+/WAhBBCCCEkPCnIpZgnvhObaIStdBv0hhaOBQat/3xElE2di01sgY6nZLgI84oIfrojMt9nRE+fI/N04m+crem+/fZbtR8zZkylc2JeFxUVpVzpS0tL1de+ZAWIYJdgeGJiojqWm5urMgVuuukm/PLLL/Un5nfs2IGMjAyfX3/SSSepjUClgkj2wvjx49VGCCGEEEIIqRpx0zcfvQp2yxboijJhSv7QKWOgzOVcbPKHLmNFuEtqvUTkayLkhVCL1utrUf4g3cpkk3TwcGTx4sX4448/lAAX47xzzz3Xa738unXr1F4rHXdvMyfCXMrJpexcUv6rQ+4rr9eEvCBfP/XUU0of+otfYr4mQp64snr1asTFxXFaCCGEEEII8YJyyndyy7eZtymxLu76dvMm2Iq/gM7YTp2LNKxXxwCreo2tdBn0pk4nLqZPQGR0gkqtD/daeUMtxLwWbJT08uoyrwOZZm8rt8BmPrGAYC2um05oH3zwgcv3kjk+evRo1ZFNnOo15P3n5eWpr721jZPjIs6zsrJ8EvOdO3dWKfbuAe6cnByPpnwBF/PTp0+v0YUl+iyitVu3bjjttNP8eTZCCCGEEEJII/QrcHfXV6n1RZkV0XdjJvRNRjsi82XWNogzLTxxLsrVsK+hW+g1VkTI+5Iyv+/Tldj/4c919hwdO3ZUzvMSiU9PT1fp7UuXLlXt1MXcTjOm0ygsLHR83aRJE4/XbNq0qdoXFBR4va8sCmhMnToVd9xxh2qTd/rpp6tjK1euxJQpU1TtfJ2L+XvuucevG0jvPmlT93//93/o0KGDX9cghBBCCCHhhfQIz9q0F81aSauwiIZ+nEZHQZCLeXdEnEtqvYq6u4l1ILKKcxL6Pe7ado/UC3Yl6Kt/XYux/dH8kn6O763FZVh/zcyAPcfVV19dSYhLB7ahQ4fi5JNPxpdffqmEtSayA0VCQoLSwhrSvl385rRj8r0gxnj+ljb4LOZ37dpVowvLw8lKhfSel4UAWYnQjAQIIYQQQkjjFvKTznkKuzbsQUb3tnj2+4co6IMIqy0XBv2J2t5gQUS6pM97ctev6hxpGKRfvPxXLSYTdCaT41ufxgSAli1b4rrrrlNR+++//94h5p1T7ouLiz2WSBcVFal9bKx3T4Uff/wRdY3PYl5SEvxBVjukPkBSCwghhBBCSONL5xbXemckIi9C3mKWVmF7sGbReqR3PVGbGpsYE1JR43DDZjselGKekEDTqVOFt8KBAwccx0S8i2eA1M3v3btXlY27I8er08hnnnlmnf/A/O9QXwVvvPGGqjuYN2+e+n7YsGHYtm1bXdyKEEIIIYQEMSLK3YW5pNZLRF6LzPc5qwcj88EK09NJkPWZDyS5ubkuNfAaPXv2VHX1a9eurSTmzWYzNmzYoFrSibGdrxw/fhxvv/02Nm3a5Oj4dv3119fKbNAvMS/ivKr0+j///BMWi8VxTFIWAl2DQAghhBBCQjN9W2rkJbVeIvIU8sGNMqILctgLPjgR8ztdEPeZt9vtDuM79xZ00ktexPzs2bMr1dx/8803qr3dBRdc4FOPeUGc788++2xER0ejX79+DoN5aU03f/58jy3wfEHvzyCbzabevPMmxyQ9YdmyZerrDz907e9ICCGEEEIaN5K+rSGCXlLraX5X/yjzwY171T4cYElGcCL+bv5ugeLw4cOYOXNmJdd5cay/9dZb8euvv6JFixa49NJLXc7feOONKt3+q6++wpw5c1xayYkLvjBx4kSfn+Ouu+7CRRddhN27d6vrySaedLIgMGHChPqNzC9ZssTrub/++gsjR45U/dRlRYMQQgghhBASHIiAv2/EE9i1IRsZ3dMwbcHkRrOgwgh+eKTZi6n6E0884fi+vLxiUco5E1x6yIsWFaO622+/Hffffz/69u2rTO9E4Ev6/NGjR5XjvETf3VvQJSUl4Z133lHu82PGjMGQIUOQnJyMhQsXqnT5u+++Wx3zFYnMv/nmmzAaT8hv+VoWBk499VQETc285P7LhEnagPTRI4QQQgghhDSQ+eAxN/PBjWI+mP23+WA21ixYj/RuJ8wHhSYJxUhshrAjLsm78zgJHUSMS0TdHedj8hpBBPikSZNU67mtW7fil19+gcFgQEZGBq699loVMW/dujU8MXr0aJVq/+STT6rxsmgg9fOidceNG4eaIFH+7Oxs1bLdmT179lTpiN8gBnhSxC/GAIQQQgghhJAgMh9sLeaDaY7IfJ8RruaDNnsJSkr/gM3eHnpdNEIdu70UNvM26A0t2LYuTCLzIsJl8wURys888wz85YwzznCYuteGyy67DDfccINqgzdgwAB1bPny5bj33ntxxRVXBI+YlxULqZe/6qqrAn1pQgghhBBCSC0Q4S6p9RKR9yTkDxz+B8rNmxBh6oqWKZ8Hn6CvgSGfCHnz0atgt2yBrigTpuQPKejrkWA3wKtPRMTrdDpcc801DqN4k8mk6vZrs9jgl5gXC31PiLHAihUrVB1Bhw4dXF4nDy9W/I0dqdWQ1I7x48erjRBCCCGkMSBCsdy8BQZDC4dAlH7ypP4RAZ/WLRZ60z6YTzSgUj8fEfJ2u1ntjx7+AQlJPV3G6vUJDdqD3pu7vt12HHZbPmDZ7TgmEXkR8rCb1d5Wugx6U0VfcQf6hJBw7K8PxChONqvVGpDr+WtmF0gDvGAhIiICM2bMwNSpU7Fjxw51TPSye61+vYj5xYsXK3HuCVlhSElJUa72znh7fWNDjAGlZoIQQgghpDEJ+UNOEd/mf0d86ULecOgQD5OxhcsxWWiRn09Z2UZERHRFWX4vmFLbIRQQQa6LcBXlKrW+KLMiMm/MhD5qECPzVaAFG/Pz82vV+9xVzPuTZo+wpUmTJjj55JMDdj2/xLxY6hNCCCGEEOKtn7xzG7oTEV+L2peU/oQIU2ZQRXwJ1AKLpNbv3fUVWra5GAfy80J6WnS6KJVaryLyFPIkDKkTAzxCCCGEENJ4EVHuLMy1iK8WmY+OOjP4arGJQn4ueof5XWiLeU3QS2q97ElwG+DlzvsVx79fDbvNVqfPFU7ofXmR1MH7S23GEkIIIYSQ0EeEoaTWN0ua6UixJ4SEN/YabgnnnoZ2M25H2rM3NfSjh5eYHzZsGIYOHYrPPvsMxcXF1b6+sLAQH330EQYPHoyzzjorEM9JCCGEEEJCGBHwklpPIU9I44rM+7OFG0uXLnW42Dsjx+RcnabZb926FVOmTME///lPZXB32mmnoXfv3sjIyEBiYiLsdjtyc3Oxa9cu/Pbbb1i1apV6MLHelzZ1hBBCCCGEkOAh1q3/vEZZSTmyNuYgpVV5vT8TCTO0kLs/48KMoUOH4sCBA0hNTXU5npeXp87520HAJzHftm1bvPnmm8pK/4MPPsBXX32FV199FSUlJS6vi46Oxqmnnoonn3xSCX9xtSeEEEIIIYTUDfnHCv3qCuBpjAj5+0Y+hV0bspDRfTUmvHZDvTwLIeGO3W732N3t6NGjaNq0af0Y4DVr1gx33XWX2iTynp2drR5ASE5ORlpaGoxGeuoRQgghhBBSHxT4IaBFdMs4d7I27sWuDdmwmK1q/+MnvwCXAxFRES4RfW/38+dZSBjjb8p8GKXZX3rppWovQv7aa69FZGSk45xE49evX48BAwb4fX2/lbeI9vbt26uNEEIIIYQQElyIaG+aYK7U8k8EtyfR3ax1EjK6p6nIvDBnxrf448cNeG7hI4iMPiHoCfG9zzwadZ/5+Ph4R2Q+NjZWZbJrRERE4PTTT8e//vUvv6/PMDohhBBCCKkXpJc8CTxWW24lwa5FyqPjSjye8xall9R6iciLkLdabNj1ZzbWLFiP9G5tXMZVFaEnRPDXzC6cDPDeffddtW/Xrh3uueeeWqXUe4JinhBCCCGE1AtViUriPzbbcb/n1mOU/nKoiLwI+YyT09BnRA9G5knNEVHeyNPsNe677z4VndfIysrC3Llz0a1bN4wcObJuW9ORwNG3b1/1Q5s5cyanlRBCCCGE+E2F8/xelJWYAzqLUiMvqfUP/O+O8EixZ0aIT4g+EZ0ieoUElosvvhjvv/+++vr48ePo168fXnjhBXX8tdde8/u6FPP1zOrVq7Fx40aMHz++vm9NCCGEEELCBOU8P+IJPHPNy3jwnDfV94FEBLyk1oe8kBfzMYp5nxB9IjpF9Eoga+b92cKNtWvXYtCgQerr2bNno0WLFio6LwL/pZde8vu6TLMnhBBCCCEkiPHkPu/sPL/7r0OV6trLS8uxY30W4ps3hym2AR6aEPaZd1BcXKwM8IT58+crl3u9Xq8M8ETU16uYf/bZZ3H11VejdevWft+YEEIIIYQQ4l9d+wnn+Wy0OynVpa5di9rv3bYLK76NxL1v/gdRTeLqJeVfniscovmk9tAA7wQdO3bEl19+iUsuuQQ//PCDavUu5OTkIC4urn7F/EMPPaS2wYMH45///CfGjBnjWGkghBBCCCEkUFituTAYaJznjgjmaQsmY9mcX9G+lx5H9h1znBNRLUL+1rdWo1WnIuzOvggxxlnQIconN3o5VxO0xQNZWJAFBnkuUyQTgIkoes6C8Mgjj+DKK69UIv6ss85C//79HVH6U045BfVaMy+pAFOnTsWxY8dwww03qJz/yy+/HN9++y2sVitqw/Tp01XaQadOnVRfvsjISKSnp+Oaa67Bn3/+6XXcrFmzlJFATEwMkpKScN555+GXX36p8l7Lly9Xr5PXyzgZrxkTeGPv3r247rrr0KpVK0RFRaFz58549NFHUVpa6vd7JoQQQgghnrHajnNqqhD0XU5ri5R2B9Es/ThS25WorcfQOPQaHqmEvMFkR2TMHiS23uw4L1t03GHV0s4TVbWck5T/fdsPumyS4q+l/Mtevt+/4xCOHshVexlDSHXkL1iBfZP+g/2PhJ9R+JgxY5CdnY3ffvsN33//veO4CPv//Oc/fl9XZ3f2yPeDDRs24MMPP8THH3+sHrBZs2a47LLLVBr+aaedVuPryfiioiL06NHDkcb/119/YevWrTCZTJgzZw4uuOAClzETJkzAjBkzEB0draz9RVgvWrRI2f+LwcCoUaMq3eeLL75Qz2mz2VSGgdxXxoi74MSJE/H8889XGrN9+3a1inLkyBF0795duT3KD2Tnzp0444wz1HhZfPBEfn6+WpzIy8urVSpFsCLzKGkiqampqv6DcL7DDX7GOd/hDj/jnO9gpdy8CxGmjEbxGffWL94bNnsJsvaMAgzbEWHqipYpn0Ovi1bnSovzVURehHxEhOs5XxGh3rpjC78j88E+3+FEID/ftdUt2vi2rz8KffSJbBBfsZWUYs/Nj4eNbjKbzUqn/vHHH0pDBpJa/8uSB5Io/e7du/HTTz8pl75XX30VAwYMUFHrJ598Un2wfOWrr75Cbm4ufv31VyXcZduyZYtqlSATceONN8JisThev3DhQiXkk5OTsW7dOlWLIKsdS5cuhcFgUFF0EejOSEbB9ddfr7IIROwvWbJE7Tdv3qzqGaRNgBxz59prr1VC/o477lBZAp9++ql6Nql9kCi/zAMhhBBCCKkd9RHJDcZosfSL9/asIvTNll0uW0npT7DrtsFut6DcvEl9r50zRBxFU9MTaJb4rF9Cvibp9lrK//3v/1vtWTNPXAzw/NnCCJPJhLS0tFpnsHsiIMtkEgn/5JNPMG3aNHz99ddKRJ977rlK6D/xxBPo0KED5s6d69O1JMIt6evu3Hbbbeo6hw4dUi0TnNPyhYcfflil5mtIBP2WW25RQv7tt992udZbb72lVoykr5+k9Gs0b95cvQdBBL0zq1atUoJdVru01whGo1H1BpQfkrQVcF5oIIQQQgghNacgtzAs7uENb+nt3hAne4nYm4wZLlt01JnQ2TtBpzOqyLx873xeb++EqMg+fgn56tLtw7mVHQkUulps4cVDDz2EBx98UAWVg0LMSwq7FOyPGzdOiWAp6N+/f78SulJX/s0336ioukTs+/Tpo1LXa4sIZiEiouKXRElJCRYvXuyoQ3BHOyYLDM5Ibb+3Meeff75aTJCIv3MdvDbmwgsvrJRKL+9fMhIko+Dnn3+u9fskhBBCCCGBx2YrDOoIfE0RkW4qfx2pSTP9jr4TUmcwMu/glVdeUZnj4ruWmZmJ3r17u2z+4pfNpLjwSYq5RMlbtmypIuBiUHfSSSdVeq2cl9R4OV8bPvjgA5XSLtF3LQIv35eVlSElJQVt2pzoq6mhTcz69etdjks6vvN5Z2ShQDIKpBZe6vSldr+6MdpxWViQew0ZMqRW75UQQgghhIjoLUGZeSuMhhbQ62svVK22orCb1rikZogwZVLIExLEePJwCwR+ifk333xT1YmLQB8+fDh0uqpTIQYOHIh33323Rvd47rnnlPGdmOFt2rRJfS0rGWK0J2n8ghjuCZ6EvNC0aVMkJCSoiHlBQYFqnyfp9WKmUNU4OS5iXlz7NTFf3b204zKmKiTtXwwqNCTK7800L5SQ9yTZGs7vjXC+wwl+xjnf4Q4/45zvYEL+prBYi5B9+HKUWTYj0tgFaSmf1Eqwun/Ga/t3i9V6HAZDQg2f4Tj0+gTYbJ7vXZBbhITkyseretaYhCYwWzyfrxjn+Zx0CTDoa/b81eH8nPydUr/UZr4lOCqbhuilgOBv/XuY1cwL0v0saMS8RORFKPtKu3bt1FYTfvjhB+UOryHt6aRtnKTsaxQWVqRKNWnSxOt15DlFQGtiXhtT1TjtvckYX+/laYwn5H04I+UH99xzD0Id+cUhiyTyS4SOpZzvcISfcc53uMPPOOe7YT9/hS5R8+MF+bDsP4xSbAbsZpSaN2Pv/h9g0HVwvMagbwq9PqaGn/ESGA05sJRbsem37bAZLYiIqijjrClmyyGYjOU1GmO1HoLBUA6LtUA9hzN2eymOHVmDMksMdLoT/lHlJeXYtEae1YwIL/Xonq6nxqIUhw97PmexHoLRULPnr468wuMw5lQE+fg7pX6pzXxLFy93v7CAYNdVbP6MI3Un5k8++WS8+OKLuOiiizyel3p5cXyXlm3+IjXrgghxcY6fMmUKzjzzTOWOLwYCoYpE7p1bLIRTZF4yNKTkgWKe8x2O8DPO+Q53+BnnfDcsqS5tzrJ/34D2nYbhUGEXR2S+TcrZtY7MW6w5iI9NwIPnP4vdf+1Bu5Pa4pl5D/hl2lZuLkaE6cRz+4LFUgyjMRVmSzFMxlSXFnOHjtyI6ISNsOm7oXmzT9V7lbmYNOYp7N6QjXbd0/DsDw95fFb36zlIlXO7PZ7zOqYWWArsyixavSf+bViv1Ga+xbBczMSdI/PuAUh/kAbo/jRBr13j9OAhKSlJlW1LC/TExMQqs9n9NcbzS8yLqZ1zhNsdOVddurmvSJq8mMt99913yqF+8uTJqpd83759ERNTsRpbXFzsdbyk6QsSlRe0Mdo4T70L3cc4j/N2L09jvL2fcOiX6An5gMovD4p5zne4ws845zvc4Wec893QiHh94Lyp2LVhDzK6t8XUeR/CghVoGjXY75p5aesmzvUSscwrKMCePzYqIW8xW9X+9x83IL2raxllbGJMtU7uen3F3z01QcZAV4Zy8++Arhx6XUVAp9y8BeWWTbDDgrLyjdif9TX09vbI2piD3RuyKp51QzZ+X7RBOca7PGtSDKLjvD+L0Zjo8Zw/z+/r7xD37/m3Yf3g73xLD3TZNAL282rkafb/+c9/HNpQAuF1gV9iXqhqZWH16tVKtAYScbK/7LLLsGbNGuVOL2Je+vUJ4p7vTWBLZF9WQrSJFCEdHx+v0lBkXLdu3SqN067nvCIl9/r999+93svTGEIIIYQQUrXIdiZr014l5EW8yv73xVvRpmsS8iF+R3k+C21n5LWySQ2+pO5LxF8WCrQFgz5n9ai3dmo2exn2H7gUVvtW1UpOc6A3GFqo78vKNiIyshtatrlYHU9pVY6M7r9i14ZsZHRPQ58Rnp/VbDns9Z7S0o4QUv+Igbp0T5Ms7IyMDAwYMEC1NQ8kPl9txowZatOE/IQJEzymu4tIFgEtreoCjaQoCIcPV/zCElt/mRz5ft++fWjdurXL69euXav2momdRs+ePVVrADnvLubNZjM2bNig2tN17tzZZcxXX33luKY73u5FCCGEEEJcTd5iE5s6RLbL33qtkioJbZ1xHyJMLWrtii9melKDL6n7EvGXhQJnIS+LCzVZJPCll7x7C7qyslWwWLcAOivKzZtQUvqTcqIXmiU+j0N7lqNlmysd5QTybNMWTMaaBeu9CnlBTPWCAckSIMRBI6+Zf/nllzFp0iTlrTZ06FAcOHDAUYZS72Jebqy1npM0exHO7uJZRL48rJjU3XbbbQg0P/30k9p36FBhfiLpIMOGDcO8efPw+eefqwUGZ2bPnu3oDe/eS17EvJy/+uqrK9X7S3/5Cy64QAl65zFSty9ZAeL26FznLoaAy5YtUxkAZ5xxRsDfNyGEEEJIuKTRb1i5Db2HdPMoTOXYs98/hDWL1juEdrm5ZvewWnOVU7vLfc1bVe29mOnJXlL3JeIvCwVyfXF1L8gt91nM+9IyTyLi7lFxe2QZdPZOgH67isRHR53pEO4yN3s2bkfzlgZEOl1S5kBS66vKHgiW6HsgF0NI6KOzV2z+jAsH2rVrh5deekmViEuZz4oVK5Re9MTgwYPrVsxfccUVahNkZUFMEs466ywEkuXLlys3eHnDzrUaEi3/73//q3rNi4CXdHuNu+++W4l5McYTwa31oJfJev3111W6/w033OByH+l7/9RTT6lI+5w5c3DppZeq4zk5ObjvvvscLvPO9OvXTwl1eUZZYdHqHiwWi1q4kGcU0z8pByCEEEIIIa4oM7dLpmP3pn1o17U1np17t1dBLzXs/qa+GwyJanNGRLeY6IkrvuylBl9S910j/od8FvJZhy9DqXkTokxdkZ7yqU/1/HZ7CWyWLJjMLyExZVclIT/pnKf+TqdfrRY0nN9/aVmpw7upqi5OviKGe1KnL+n9tTEVJKRKGnnN/HPPPYdbbrkFU6dOVUFvae3uCTlntVr9uodfSfs//vgj6oJt27bhuuuuU+n0Et1PTk7GkSNHlJu9pCVIpHzWrFlo27atY4z0ub/zzjtVCUCvXr0wYsQIlJeXY8GCBWoFRPrbu9fvi7PgO++8g7Fjx6o6hiFDhqh7iYO+lAjIAoEcc0euJSZ8cq/FixerFH3xBxDXfqmBeOCBB+pkXgghhBBCGjo1XrbakLVlvxLyysxt0z6sXbIR6ZmtPL720J6j0OkqAjs2WKBH5dZqkqovmy+I2JY+9dLeTrniK/FdUYPvT5RfhDzsFrUvKl2KSNOJ0swKdIgwtXMR8scOj4XFsgnQZyB3/yM47uQD4O4VIJkJmimfCPk/1v+BfUez1d+24htVG0EvQv7A4X+oNH/nun1CAk4jT7MfNWqU2sQcXnzbtmzZ0jBp9pKS7hz+176vjpqmC0jruQcffFCl069fv14J+YiICJWiIKJbIt8dO3asNE6i5CLkX3nlFSXiZYyIfHG+F5HtidGjR6v3IRH9lStXqgUAEee33347xo0b53GMRP3FBO+RRx7B999/j7lz5ypjPLmPPHc4tJgjhBBCCKmNcHZHiyY3SYhQEXktMu8t1V6w221o1V77ozcwf/wqozldhxoJV29RfonIa5F5d6d9my0XZWUbYHHKFbaYtyohb7eboTfsQHTcdsTGn3ClT0iNQ7uTWuLgwcNI69US0S0NOFZ8wtSuqLQAlgNlKnN1x44dlZ5TBELz5s19qttXzvlmeRZLpbp9x1zpE4ImdZ80HgqWLEfBkl9gt9kQTsTExKhguJjgBdoAT2eXJb5qkF8cEv4vKSlRQln73htyydqkC4Qj0q9Rc9EPx9Z00ttSyhTkfyZsP8L5Dkf4Ged8hzv8jHO+6wIR8pLFKH8Xyt+HPU/uiU2/7q5SyAv7dhxE6w61M73z9Bnft/9PtG51svpbxdnwrrjwEP5Ysg99zuruU3q/pNpLRN5by7xy8y5EmDJcIvNHDo1BccEG7N3aBF9MPx9Tv3na5V6Sav/bovk49ayRLsdlDhf/8CPikmNDKjLP3yn1SyDnu7a6RRvfdvoT0Eef8CDzFVtJKfbcPTlsdVMgMdYkrV6EvPP3hBBCCCGEaIbAIibckWMiNERg7Nm3B8ZEC7Zu31JlRFnaz9WUmrrRa68VEX3/eS8ia+NhZJzUFs9+/0C1gl4EvKTWe6uVP5h9BAa4nsve/CA+fHo69m6Nht121CWVXqNZq8peASLc+/brh+atUwJSMy/CXQS8ROSd6/YJCTiNvGY+aMS8pL9X9T0hhBBCCGnciCh3F+YiPo8dO+aIzEtHIl/EqD+u6NKzvrpxpcVl2L8zxyXDNGvTPmRtzIHFbMOuv6RefQPSu57o2GRDHuITW9X4mdwzC6Tt3ifPdoLdloP0k1I99rffVzmDXiFCXgiE+Z0gAl5S6ynkSZ1CMV/nBDRpX4zgpG1b165dA3lZQgghhBASgqio8t9p4YFyYq8NUU0i0aqVaxpys1aJSO+W6ojMu6fal5uLEWGqfcs1uebT316PdT/lo9fQtn679RMSMjRyA7z6wK+CCumXd/nll7scExd6MYjr3r07Tj31VI9pVgTqf2hitDdz5kxOByGEEELCHk3AN7SQFwz6yiZ+Iqqf+uY6TJp1m08p9r7U01t1O9W+8r1MKrW+SdPKpQWENDSiT0SniF4hdcP27dvxww8/KC86wQf7usCL+bfeessljUoe6L333sNNN92El19+WUXoH3/88Vo9WLgiJjAbN27E+PHjG/pRCCGEEEIaFXq95wh7hchuHRAhLz3oS4wPqb0nQV8V/ngFEBIoRJ+IThG9EgikoYO/W7hx9OhR1W2tc+fOOO+881TbdeGGG27AxIkT6zfNPisryyWV/rPPPlNW+6+99pr6/uDBg/jggw/8fihCCCGEEEJ8RUzspFe71KW7C/LqjPFEcEvveDu61HDCdcq1vlIP+vJNsNnNal+pB71N+spHB9QrgJCghTXzDu666y7Vli47O9tFR1922WW4++678cILL6DexLx7OsD8+fNx8cUXO76XvvAi6AkhhBBCCKlrIT/pnKewa8MeZHQXN/qHXAR9VcZ4WiRdesbrjR1gs8316lDvToSpXaVjVnMyDm6LQXzLo8g7EIN2yf0RYTrRWsticRX/hJDGwfz581U2e5s2rh0spExdAuX+4peYl/SAuXPn4pZbblEPtX//fpx77rmO83v37kVCQoLfD0UIIYQQQog7+3YcqtS3SiLyIuQtZqvau7d8KzxerPZW63GYLYeUoZ1erzsRSTdvAuwWWHXbK0XSbfYylJZvhNHQwqPIl6i/LBY4P8srN/VAUpt8HNsbh8g3trq2n9MdBpAeFD9YvZ5/q5O6Rf6V+ZMyH472d0VFRR59Q6TbR2RkZP2K+XvuuQdXXnklEhMT1YNJqsDZZ5/tOL948WL06tXL74cihBBCCCGkMnaPLd8kIq9F5t1bvu3bUZEtajAkwGQsR4TphJu9iPQoU1cl6CP0ndE0arBDtDtH7XOLZiE95dNKgl4i/s5Rf3mWtp3aYdeGbGR0T6v0LDZbJPT6xKD4wRqC5DkIaQwMGjQI77//Pp544gn1vbTHtNlsmDZtGoYOHVq/Yl6c7JOTk/Hdd9+pCPxtt92magC01YWkpCT885//9PuhCCGEEEII8QURy5JaLxF5d/HsXEtviqz8Z6+IcxHp+cXzEBXRDRbrQcCKSlF72btH7Q36BBgMiR6fZfWiBeh71ohK9fvBIuQJqRfYms6BiPazzjoLv/32G8rLy3Hffffhr7/+Utp5+fLlqPc+8yNGjFCbOyLk58yZ4/cDEUIIIYQQUhNENEs6u7uQd66ln/rdAx7HiqBvEnkKIkwZLsedo/ayd47aV/csaV1T2UeeEBrgOZD27Vu3bsUrr7yC2NhYFBYW4tJLL1UdBFq2bIl6F/OEEEIIIYQEA1K7fijrSJW19GsXb0BCm6awFNpViqvWCs6bOZ4WtZeIvK9CnhDiBMW8C/Hx8XjooYcQSPx2s3/jjTfw9ttvq57yubm5lV4jvyQtFksgnpEQQgghhDRyqmo/J4K8eXozl3p691r63sO6I6/gOFJTT9TMV4cIeEmtp5AnpObUtGd83s8/I/+XX2C32cJuut99913ExMTgH//4h8vxzz//HMXFxRg3blz9iXnJ8Z8+fboyubv66quVER4hhBBCCCEN0X5OQ/4oFsdobe9cS69q5gvq5+ejw4l2dIQQ34gfOFBtttJS7A5wBLuhmTp1Kl5//fVKx2Vx8aabbqpfMf/ee+9h9OjR+Oyzz/y6KSGEEEIIId7w1PKtqvZzQmlZGVavXq2yQyWLtG/fvkrQa7X04hztDTGzCyTxia0Dej1CQhKm2TvIzs5GRoarL4eQnp6uzvmLX2K+pKQEw4cP9/umjRn5H4vBYFBmB7IRQkgoY7Xlsr0RISTgeGr55pwy37ZHCxzLk57truTk5CjRLmn0O3bsUMdyD+XhWPFhJfDlbzCJhLnj7kofiOcnJNSYOXOm2qzWv1s61BaKeQfye2f9+vVo167diYMA1q1bp7rE1auYF1t9WfmUlABSM2Te4uKYekUICQ9stuMU84SQBmk/1xaukXlJrZc2T1pkvkOHDioyv6/JQVVLLyJfxD4hxDNasDE/P1+ZtdV3zbzzuHDjiiuuwB133KGc7AcPHqyO/fTTT7jzzjtV2/d6FfOvvvoqzj77bDz99NO4+eaba7WaQAghJDSx2UtgNm+BwdACeh1dngkh9d9+zhkR7lpqvVYzHwgCnYJPSKOBfeYdPPHEE9i9e7cKihuNFRJcFhivueYapanrVcxnZmaqm0+ePFltUVFRKm3JGVkVzcvL8/vBCCGEBLeQP3z4HzBbNsFk7IqUlM8p6AkhDY4m4J2FvLSfqw2BTsEnhDQ+IiIi8OmnnypRL6n10dHROPnkk1XNfG3wS8yL+Z3Wn5MQQkj41cFL+nxVSERehLzdblH70tKfYDJlen29Xp/AdHxCSIPA+nVCGog6qplfs2YNFixYgFWrVqlt3759FcPsVQ+cNWuWyjDfuHGjEtenn346Hn74YQwYMMDrmOXLl+Opp57CypUrUV5ejm7duuH2229XEXV/6Ny5s9oChV9iXiaCEEJIeGLQJ1YrvCW1XiLyWmQ+KupMRuYJIfWKzZYLfTW/q2qLe6s7X88RQuquZl6i21999VWNrjlhwgTMmDFDRcRHjhyJ0tJStSAwf/58zJ49G6NGjao05osvvsBll12mMtKlzr1Zs2ZYtGiRaiMnZnbPP/+8z/cXU0HR0DJeM+p0ZvHixag3MU8IIaRxIzXyklovEXkKeUJIfeGcMi8ZRHUp5kWke2p1V905QkjdRub79++PHj16qH93solDfFlZmdfXL1y4UAl58XlbsWIFOnXqpI7L10OGDMF1112n9gkJJ/wxxEzz+uuvVyJcRP2ll16qjh86dAgDBw7ECy+8gAsuuECN8wUxuhMxf/7556N79+4By3L3W8xLPzwp1v/xxx/V6oKsjsiKxZEjRzBlyhQ1KaecckpAHpIQQkhwCnpJraf5HSEkHFLm5Y90d7d7+V5aMkt6bVFRkcu5/fv3q1RdifRpbfDcW1E1b968zp6XkKDHz8h8dWJ+0qRJNbrc9OnT1V5S6jUhry0K3HLLLXjppZfw9ttvY+LEiY5zb731lnL1v/jiix1CXpB/09OmTVPHRND7KuY/+eQTfPbZZzjvvPMQSPwS81JnMGjQIJUecNppp2H79u2wWCzqnKQf/Pzzz+oXnkwKIYSQ8EVq4QkhJByQP9Kdxbd7q7uqIvNaGzxCSHBRUlLiSGEfM2ZMpfNyTMT8119/7SLmv/32W69jJLouBvAS8Zd0ffm6OmThr2PHjgg0fon5++67T6UhiBGA/BKTlUf3NyhufYQQQsKb6mrrCSEkVKmq1V1dtcEjJKyoozT7mrBlyxaVgp+SkoI2bdpUOt+7d2+1lxp4Z8Rx3vm8uzCXVPnffvsNW7duVSn/1SELBZLq/8orrwTUSN4vMb906VI88sgjalKOHj1a6XxaWprDVZAQQgghhJBAYreXwGLeqsw4dbroem1158s5QojvYt5mscD+d5a3+r6sNGDTl52drfaehLzQtGlTFaTOzc1FQUEBYmNjVXq91mLd2zg5LmI+KyvLJzEvmetSnj5v3jycdNJJMJlMLufnzJlTf2Je0uur+sV1+PBhREZG+vVAhBBCCCGEVCXkjx0eC4tlE4zGrkhK+axOBT0hpG7d7HN/WohjS+bXyTQXFhaqfVXaVQT98ePHHWJeG1PVOBkjyBhfkAWDSy65BIHGLzEv6QZSR3DbbbdVOie181LgL337SGUkJctgMGD8+PFqI4QQQggh3tvPiWu9y9+a5q1KyNvtFrUvK10Ko6lzJT+Pum5bR0i4MXPmTLWJg3t9kjR4OBIHDHGJzO96YQrCiXfffbdOruuXmH/ggQeUFf+tt96Kyy+/3OEAKiYA4nC/adMmVQ9AKiNmKXFxcZwaQgghhJBqEEHuLsoltV4i8lpkPjJqMCPzhAQALdgoaebx8fH1Nqd6oxGQrQ6IianogCHeFt7QOlVIVN55jDbOk3ZzH9NQ+DVr5557ruqTJ/3y3njjDXXs6quvVm6e8mbff/991aaOEEIIIYSQQCIp9ZJaLxF5CnlCgpggMMBLS0tT+71793o8L6JcUuwTExMdwlz0rCxmSN28jOvWrVulcdr10tPTq8xmX7Rokbq2tGyvyvhu7dq18Ae/l0D++c9/qv568+fPV63ppI5e2nKcffbZDb5CQQghhBBCwlvQS2o9a+UJCf2aeU/jAkVmZqbychNPNzFob926tUcR7W5i17NnT2X6LufdxbzZbMaGDRtUS7rOnV1LfJyRHvWaj9yoUaNQF9Qqn0EK/+uikJ8QQgghhBBCSIgTQGHuD9HR0Rg2bJhykf/8888xYcIEl/OzZ89W+wsvvLBSq3UR83JeMtCd+eabb1R/eSk7r6rH/KOPPurx60Ci92eQROJfe+013HPPPbj55pvV/r///S927NgR+CckhBBCCCGEEBKaafb+bAHk7rvvVvsnn3wS27ZtcxxfsWIFXn/9deU0f8MNN7iMufHGG1W6/VdffeXSNi4nJwf33Xefo3e8r+zZs8cl1X/VqlVqYUErWa+XyLzY9P/rX/9SqxqSVu+OXq9XhngyKZpdPyGEEEIIIYQQEgikq9oTTzzh+L68vFztnbupTZ48WUXXheHDhyuvtxkzZqBXr14YMWKEGrNgwQLl+SZO8yLonUlKSsI777yDsWPHYsyYMRgyZAiSk5OV4bvU2MsCgRzzlSuvvBI33XSTKlU/ePCgeqbu3bvjww8/VN8/8sgjdSvm5Y1edNFFWLJkCUaOHKkeRB5A3P5E5EvdgBjfffTRR8rZXiaHEEIIIYSQukDazxFCGl/NvNS///rrr5WOOx+T1zjz4osvKiEvHddEp0ZERChBLaJ/wIABHu8zevRolWovEf2VK1eqBQCpn7/99tsxbty4Gr0n0cr9+vVTX3/22Wc4+eSTsXz5cuU/d8stt9S9mJ87d64S8s8884wjtcDdJOCqq65S5x966CF8+eWXdVboTwghhBDSGLBYj8NooGj1BPvIE9I43eyvvfZatdUUf8adccYZqt6+tohpnmaGJ9F9CZILXbp0wYEDB+q+Zv7jjz9Wgt2TkHfm/vvvVysNEqEnhBBCCCH+YbOVoqBsldoTQkioRub92cKNk046SXnMLVu2TGUGnHPOOer4/v37Vfp+nYt5seV3d/nzhqw0rFmzxu+HIoQQQghpzIiA35ZzObKO3qH2FPSEkJAjSAzwgoFnn31W+cpJnf0VV1yhguTC//3f/znS7+s0zV6c+9LT0316rbxOXk8IIYQQ0ljT4y22417P22x2lFvyUWougV6vq3S+xLwVJebNsNvNap9XuhTRJu/9jKvDqE9guj4hhDQQIuKPHDmC/Px8JCYmOo6LKV6TJk3qXswXFRWpPn2+IP32iouL/X4oQgghhJBQRurcq6p1l65AEcYcRJlSVTcgd8oKYhFt6qKEvOzjowZDr/fez5gQQhpLzXyoYjAYXIS80K5du/prTafTVV45JjWjb9++6gc5fvx4tRFCCCGEOFNWUo6NK/eg15D3UYqVQSHkC3KLEJvYlIZ8hIQxM2fOVJvVag3I9Wpa/35szc84tnY57B5aoJMAiPkbbrgBN998c7Wvs1gsNblso2L16tWIi4tr6McghBBCSJAK+UkXv4Ddm/ahXdfWeGrOjQ0u5OWZNqzcht5DusFupLs+IeGKFmyUVPD4+Ph6j8wn9R6oNmtZKba8+GDt798I8FnM17SXHiGEEEJIY0Mi2LJVh91uR17BcViLdC6Zj1mb9yshbzFb1X790n1I71K7nFOJqMvm9+LCJdPVs3To0RyT3uuNiIQWDb7AQAgJAZhmHzxi/t13363bJyGEEEIICXF8Fc5SM2/IsSM1NcWlZj65ZYKKyGuR+d5DuyEyOqJWCwu+LjB4ImtLxeIC9OUYfOvn2JP3Pg4VdEKS9TXoEFXviwuEEBIuHD9+HAkJ3r1VAp5mTwghhBBC6g4R7s9+NRFrf9xYKyHvLJqrc9aviqbNmiK9SzLKrNvRvEMh9AbAqtuBJimba+GuX4xS82E67BMS5vjbM14Xpq3p2rVrh8suu0x9P3bsWHzxxRdo0aIFvvvuO0erujrrM18fiAP+l19+qWrzMzMzlSt+06ZN1ZubMmUKCgsLvY6dNWuW6tEXExODpKQknHfeefjll1+qvN/y5cvV6+T1Mk7Gv//++1WO2bt3L6677jq0atVKPV/nzp3x6KOPorS01O/3TQghoU7+sYKGfgRCwgYR8N37d6qVkK/krK9PQJSpXY23+LhOmPblgxh3z78RH9sdOp3J4a7vz/Wct6rc/gkhYQD7zDv473//i7Zt26qvFyxYoLZ58+bh3HPPxb333gt/CSox/9FHH+GSSy7BO++8oxzfL7roIgwaNAi7du1Sglmc4D31r58wYYIS2Bs2bMDw4cOVKJcJGjx4sFoc8ISshJx55pn4/vvv0aNHD5xzzjnYtm2b8ga45557PI7Zvn07TjnlFLVwkJycjIsvvli5PcpCg9y3rKws4HNCSLiRf8z7ohwJXQr4cw0rCnL571Si2Q1JINPQbbZSFJStUnu/FxdO647MFp8iPfkldEr9hDXzhBCfI/P+bOHGwYMHHWL+m2++UZH5kSNH4r777lMG6WEh5k0mE2666SZs3LhRbZ999pkS21u2bFEievPmzUq4O7Nw4ULMmDFDiet169Yp8S5jli5dqhYERORLPYIzx44dw/XXX6+E+OzZs7FkyRK1l+t37NgRL7zwgjrmzrXXXosjR47gjjvuwJ9//olPP/1UPZssQEiUf+rUqXU+R4SEOhR94UdZSRmyNu5RexK6WKx5J5zLV2xT+8ZKbcVvMCHvYVvO5cg6eofa+/ueZHFBTO9iI/tRyBNCfIOReQfSX37Pnj3qa9GqEgjWzFBr0wowqMS8RMVff/11dO3a1eV4y5YtVc9DYc6cOSgvP/EHxvTp09X+4YcfRqdOnRzH+/fvj1tuuUUJ+bffftvlem+99ZZquSCR9UsvvdRxvHnz5pg2bZr6WgS9M6tWrVKCPTU11fEawWg04rXXXlMLES+99BLb8hFSBSIOsjbubdQiIdwQAX/vWVMw9eqX1J6CPnSRmuryUjMeGDUdz970FiZd/Hyj/LcaKPEbyAyBUvNuv7dDR+ajxLwZdrtZ7fNKl9bqeoQQQmqOaM4rr7wSI0aMwNGjR1V6vfD777+rYHLYG+BppgCSyi4TIAK/pKQEixcvVsfHjBlTaYwcE4H99ddfY+LEiY7j3377rdcx559/vqqFl4i/1MHL185jLrzwQkRGRrqMkUUAKQeQZ/n5558xZMiQgL53QsIBEQX3jXgCuzZkI6N7GqYtmBywelBSd3Xw1WVSSER+14YsWMqtar9mwTqkd6tII/NGbFIM4pJiA/y0xD1Nvibu5XaUotS+Cjt+TzrRFm3jPqz98S+kd2nlp/FaTIP9UGpj+FZi3lpJ/Ppv9IZam7ypenc/x8vv3d1rDyGhRybKrFscte5sK0cIqRfYms7Bf/7zH2WAJ9F5CQyLX5tw4MAB3HbbbahXMS/R85tvvtnreRHZUsj/yiuvIFDs3LlT7SUCLoZ1gqS4i7hPSUlBmzZtKo3p3bu32q9fv97luKTjO593JiIiAt27d8dvv/2GrVu3qnr66sZox0XMy70o5kljR+ri3UWgRORFyItIkP2aBeuR3q2NF6HXcCKAnEAEd3Wiu1nrJGR0T1dCXvZ9RvREZLTrgiepf0RI+yqmKyLRNyvh2qJvBjr06I8d6w+hXTdpi3ZSSC661UYARxhaKNEr8xHK4te1P3xfTHrvZjRLGBaS74UQEpro/t78GRdulJeXe/Rlu+uuu2p1Xb/E/K233oq5c+eq9PXWrVu7nFu2bJmqU5dVh0CKeamLF8SoTouMZ2dnq70nIS+IE7707svNzUVBQQFiY2NVen1eXl6V4+S4iPmsrCyHmK/uXtpxGVMVkvYvvWU15L24R/pDEXlPUvPh/N5I453vmIQmanMmSXond0/D7g3Zan/KWd29ioRgfF/BPucNhSnShGcXTMbahevRe3gP9X0g5ojz7V/Nuz/R6FKnSLRVtxP3vHc7tq/So/sZHWDV70Nxma/R53gE23z490wR6JDyEfJLliEuepD6vi7+3Vf1GS84XoTC3OJaXV/rDy8LqLI4s21lLMyZ8vdPxd9A/hCT2ASxCaHbH56/Vzjf4UxtPt8SHHU28ha9FBAYmXfJ5BbTO/FtGzhwIAKFX2L+f//7nzKBkwj2iy++qGrdJSX9/vvvVwJeat5XrFgRsIeU3nuycCBR+SeeeMJxXGtV16SJq2hwF/QioDUx79zezts4GSPIGF/v5WmMJ9LT012+l/R/b+75oYT84pBFEvklotcHlRVDWBKq833PB//Cpl+3o+tpHXE8by90BaETgQ/VOa8vEtJikFdwHAhQhzrOt79E13iE3Z4JA9rDgh2AtR1s5V3RJlOHstJolPlcLi5/BFbuNtNQ2O2lKLGsRbSxN3Q6/yLRVlsHlBfKH7QB+qO2hp9xQy01c5tuzdC6Ywr2bstR+7bd2sEQVTuL6JLyIpTk+F6+EWzw9wrnO5ypzef7+eefr+QXFgjYZ95VP0tHtGHDhql0exH111xzjWp3Xu9iXor3hw4din/961/qQcTVfceOHSoVXuz1H3/8cSW8A4E4zF999dXqg/ncc885audDFYncx8XFhWVkXqfTqZIHCh3Od1XExSUgLjEGNksW9MZUhAr8jFdNlCkacYmBq4PnfNcvKfbZOF60DOWFnZGa2jakf4/n5R7FIfOdKMUWlOsy0THlY+hrKOglMh6bULe/n+rjM/78/92H33/ahFPO7BqS5RKBhr9XON/hTG0+3xIsFTNx58i8ewCS1I5Ro0ap7fDhw/jggw+UsJ88eTLOPvtspaelJbsYq9ebAZ4Y0ImzvPRyF3t9+fDIqk5t8/6d2bdvn0qrlzT5u+++G3feeafLec04oLjYeypaUVHFCrJE5Z3HaOOchbW3Mb7cy9MYT0jav6d7hgPyGZBfHqH8R2AoEarznZAcp6JmsG6DztTS76hZQxCqc+7N3C6QJnQJyYFPsQ6n+Q529GiCJpGdYSmODoo599fArqzEjI3rlqBJxy0AzCg1b0FB2c81MrCTa/y5cidOHtgeTZum1Mq8rqE/49FNo3By/85qT+pnzokrnO/QmO/o6Gi1aQTs3wfT7Cshiy2ia2V7+eWXlc+cZKE3a9ZMdWKTTPeqss4DJub/+OMPlRqwadMmjB8/XvVll6i8OPI9+eSTykiuNkgv+JEjR6pIttTgy0KBO2lpaWq/d+9erwJbUuylr58mskVIx8fHqzQUGdetW7dK47TrOa9Iyb2kdYC3e3kaQ0hjx247Dp3e9Q9hEfKlR6+AzbIZ+qIuiEr+OKQEfTgg7eM2/LyJZnUkrAzsxPDt0TEvYO+ObNz4ViyadyiosYGddg2pNW/XtTWe/WoijDWvXAgqpLMAIYQ0GDWo7jmy/mccXb8cdnv4+hMdOnQI7733norMi86V7mo33HCD0pLPPvssVq5cifnz59etmH/ssccwdepUJVx/+uknDBgwQDn0PfLII6reQlYX5CH79Onjz+VVfbr03tu4caPqyffmm2+qlSZ3MjMzVYq6pCtIFN/djG/t2rVqr5nYaUiq/tKlS9V5dzFvNpuxYcMG1ZKuc+fOLmO++uorxzXd8XYvQhorNutBWEoXwhDRFzrdiVISm3mrEvKwm9XeWroUeg9RM1kEcF8IIIHrC6+5zz+36BG6zxOHiV1F7XvDIe30atJSz5mszfuxa+NeWM12vHlDH/zr+UykNhuKdVt2+XyN/TtzsOuvvbBarOpaa3/c6FdrPtcWfRTThJDGSU1r5lNOHqg2a3kpNrzxIMKJOXPm4N1338UPP/yg9Ke0o5NScsna1hBNLd5zNcEvMS91FfIA0iNPS8mQSPwzzzyDSy65RBni9e/fXwn8miJOihdffDFWrVqlagg+/vhjGAwGj6+Ve4uJwLx58/D5559jwoQJLudnz57t6A3v3ktexLycl0l05ptvvlFmfhdccIGjx7w2ZsqUKapnvTyjc527rLCIi79kAJxxxhk1fs+EhBsSfS/LvbVCrBtdo+86QwsVkVeReWMXGKIGMzJfj73h2ReeeKPC+T3H77T4QKSjVwhfu1896pNbJiCjWxsVVW/bsTUGjbwaTWNSanSNbv06YMHHvzgi872HdmOtOSGE+AvT7B1Ipvnll1+O5cuXo2/fvvCEmOE99NBDqHMxv3DhQmWA54nTTjtN9WR/8MGar6ZYrVZcccUVql/7oEGD1ApGden6Um8gYl5S+0Vwd+rUSR0XN/3XX39drXZI6oIzN954I5566ikVaZd7SPRfyMnJUaUCmsu8M/369VNCXX4AkyZNUi7+gsViUQsbEtEXh/9AGf8REipp9LK5U130PSL+GVjLV8MYNZxCvp57w7MvPAk00qe+oGxVQPqxS5r7hhXb/OpvL6+XtHiJpvsrwgNxjbpY5CCEEBLaSCl6dbXwEqh+9NFH617MexPyGhK19qe9gbS1k/71gpgAiEj2hNTPy3lh+PDhyhhP+tD36tULI0aMUBkBCxYsUA74ks7gnL4gJCUl4Z133lG9/qROYciQIUhOTlaLFFJjLwsEcswduZZkHMi9ZMFBUiRWr16tXPwlLeKBBx6o8XsmJJTxlgrvS/Rdb2jONPoGIDI6UqXWr1mwjjXzJCBCflvO5apPvdSnd0r9xG9BL0J+0sXPY/fGfWjXTerV7/FL0Hfv36lWIjwQ1wj0IgchhIQibE13AmchL1ng7hns/hqk+yXms7OzfXqdZlDnK+Jar6GJem81+5qYFyRKLkJeFgNExEs0X0S+2P2LyPbE6NGjVaq9RPTFaEAmVMT57bffrsoEPCFRfzHBE28AcfCXZ5T3KPeRTIRwaDFHSCAQ4S6p9RKR95ZGz3r4hhX03QdKqyr+ziInIsjlllyUW/JRai6BXl/Zp8YTJeatSsjb7Wa1P3TkB5gLXf1rfGXv5hIl5C1mq9qv/fEvv+vVC3IL/65Xr3m6vlCbOndZlNi8djMiMiajzLql1oschBASsjDN3sWYXbK7P/vsMxw9ehSeMtTrTcxLo3tPhnS1fSgR6bL5w7XXXqu2miBp85KiXxPatm2rIvSEkKoRAS+p9XSqD04C2ZaOhD6SCq7XxSHCmIMoU6rPbYkiDC2UWNUi882bnQ19qn+itXnLcrTrtswRme8xuE2Na96DoTXeI6M/RJl1G659bQMio2XBYzPySpdWao9ns9l9XjwRc0Km6xNCQg1G5k8gpdw//vgjXnvtNfzzn//EzJkzlYG7lIWL75y/+CXmJUXdXcyLcN+9ezfef/99pKamqnZ1hJDGDaPvhIQ3Em2WqLOIVS2dvLi4WKUTantfxXNkdIJKrZeIfK8hHVCKlYi21W+Kuqubvu99fp0d9bM2HwH0TXFoewzadCtBhL4Dig92QQlc34eUAhYWlMFQ1sRrgIRu+ISQkIaReQdioi46WUq5xQxP/OE6duyousN9+OGHuOqqq1BvYr6qCLikD4gJnvRxJ4Q0bijmCWk4KlLN/UszrwkitmMj+zmEvHjJiDgVsSqOvdUJeufa8sjoKHQ7vS2y868JSB1+TamteBZHfXHBFzf8pa+OwaQP+qBZwjCPz2+z2WDIsSM1NcXnTAhCCCGhybFjx9C+fXtHfbx8LwwcOBC33nqr39f1S8xXRdOmTdVqw3/+8x/l7k4IIYQQ/5FWg7FJMTVyT6+NK7y0Wz1y5IgfT7rn7/H7YLWVKUG/eWvV5XZ2uwVHCt9HuTUHEYb30SzmGphtR1BuPIDYRLPXFHVfqe/0dHc3fENEMWvlCSGNF0bmHYiQ37Vrl/Jb69Kli6qdl25pErF3N2tvUDGvrTYfPHiwLi4d8kiUwmAwqDIEliIQQgipCocoH1a9KNci3FE4HQ+MesVvV/jmzZujZcuWftWXlxSXIudIU+jQVP0Nl5HRCtFNoqo00DMc/U0Z6Ol02UhPvgaRxj7IOpqEUstxRBozEGlM9+k5gqWu3NUNv3aO+IQQUp9IHbds/pqxucOa+RNIsFvat5955pm4//77ceGFFyrzdmlvPn36dASFmM/Pz1cO8c899xxOOeWUQF46bJD0Q39bDxBCCGk8HDlwDI+OnYG92w6hTafmuPf1fyEiyuTxtXaU4pjhNliwHdbiNOzd3gEWM2rkCi9p8XkFx2EtEgNLnc9u8CKgNREdFQ/0Py3N55p5dwM9re4+s/lclzr8UKM2qfqEENJQaMFG0XTx8fG1vyAj8w7uuusux9fSdW3z5s1Ys2aNqpvv0aMH6lXMS22XN7MW+WNA0gdeffVVvx+KEEIICbdU+RPGat6xIQ825Kuvszcfxr4dB2G12tR+764/kdbFs7u7BTuVkLfDAn2TbHQ9oyPWL7KjVfsEtOuhR2LzkurvbbMDR41o2cJ3N3tPaALeF/M7TwZ62nFJrQ9FIU8IIaQCnd2utpriz5hQQ4zvZKstfol56bPuLubl+8TERHTo0AEjR46E0VgnGfyEEEJIyCE1777VvTc/8VUradW2Frs37kW7bm3Qd9hZXtPlbbbu2JbzkSPC/eDrz+KPJTtqVDOvDNn0OahvnA303NPmCSGEkFDHZrNh1qxZmDNnjur+Jro5IyMDY8aMUW3qfGn57g2/FLe/veAJIYQQUgMzta/vxdrFf1VbM+8pwn2ibjv48VTrHgz174QQQuovzT5n4884vPkX2O22sJl2u92Oiy66CN999x169uyJk08+WR3btGmT6hAnAv/LL7/0+/oMnxNCSCPCasuFQZ/Y0I9B/DJTq1mEuz7a0hFCCCGBMsBr3nWg2qzlpfj9w4fCYmJnzZqlPOUWLVqEoUOHupxbvHgxRo0apfrPX3PNNXUn5q+//voaX1jSBd5++21/nokQQkgdYLOXoKzsV0RFnQm9LppzHMQt5pypyRhGswkhhAQNNMDDxx9/jAcffLCSkBeGDRumnO0//PDDuhXzsmpQ01z+2uT+E0IICbyQP3z4HzBbNsFk7IqUlM8p6IO0xRwhhBASDrA1HbB+/XpMmzbN6xyde+65eOmll/yeY5/EvBTqE0IICe70edvfvb49YTZvUULebreofWnpTzCZMqu8pl6fwJT8AAn5SRc+5zCykzp4CnpCCCEk/Dl27BiaNz9hbuuOnMvNzfX7+qyZJ4SQMEDq4KuqhTcYWqiIvBaZZ6p93baYcyZr834l5C1mq9qLoZ0vfd+dUT3f/UjRJ4QQQhoMptnDarVW2eXNYDDAYrHUvZiXXP/LL7+8Vk3tCSENA03PiNTIS2q9ROQp5OujxVwFFmsukludpCLyWmSeqfaEEEIaA0yzh3KuF9f6yMhIj3NUVlZWqzn2Wcw/88wz6N69u0PMHz16FKmpqViwYIEq3ieEBG+tdGnZr4iuR9Oz/GOFiGMUMeiQn39k5GmslfcDEeVGQ826ANhsJSgqW4XYqME+t5gjhBBCwgZG5jFu3Lhqp8lf87tap9nLSgOpGX379lXpFOPHj1cbIXUt5A8c/gfKzZsQYeqKlvVkeiapyBTzwQnb0tUcZ1Gu10f7PGbn4ctQZt6MSFMXtE/5NKT6vhNCCGl8zJw5U22SGh4oatKaLhx599136/T6rJmvZ1avXo24uLj6vi1ppAZo5eYtSsiL6ZnsS0p/QoSb6VmwmZwxqk+CCSXKc0aj1LINkcb2aJM0AyX5VjSNb1LluFLzViXk7Xaz2heULkVUbGeUmQ/7dF+DPqHGmQCEEEJIbdCCjfn5+YiPj+dkhgAU84SEsQGamJ5JRF6LzNdHqr04d2dt3ItmrZNqHIVU7bt+3ow+I3owgknqLF3e+veiV1mJGdt/34uOp7RBZLTJuyi3bAdkQcyyC0VFO7DlVz1OHtTB6xghwpiOCGMGyiw7VWS+JlF9QgghJCyQLG5/MrmZ/V03Yl5a1K1du1Z9nZeXp/bbtm1DQkKCx9f37t27JpcnhAQYEe6SWi8R+foS8veNeAK7NmQjo3sapi2Y7LModx/77A//RlTT1Dp9XtL4kGi3bPJ5e+SSaSfaxX1zn8fPqsnQQolxia5HGDIx9YrV2LHuYJVjNDqkfqki8hTyhBBCGiM0wAsyMT958mS1OXPbbbd5rKXX6XQBrbcghPhHYa4V0XGZARXykgovdfHuSERexLi04JL9mgXrkd6tjevzHC8CdEBMfFOvY/du24XNK75ASrtzAUS5vE6cxFmPT2rbMi5r8z7s+msPrOqzugcLP/oZrdp76QOrewyIXoOsjW2x/fe5sFqsauzaxRuQ3qV1lfexIQNFyJd/NRWfX7aYI4QQ0ligAV7wiPm6Lt4nhAQeLW2911ltYQpgUU2cF0EtqfUSVdei6zVJl9fGipB/8tNNSMtcA71pPqKSP4ZO5yroq4I1942TmraMS26ViIyT2joi88OvHFjlZ9VizUC3Hk0x/3+/ObWY6+7D59vLAgEhhBAS5uhsFZs/44hvGANpq08ICR5qk/LuL3J9uY9E5KsS8nbbcbU5YzIBz8y7Blt+XaiEPGCGzbIZ1tKl0Js6V7qGTp+gNk+LF73PSguaFP3i4mI0adLEsXdH5sH9fXgj/1gB4pJiEc5Yrbkw/G38VlJQAqTWPEJfnaiXuvnI6ESVJi/RdV9EuUrPj4Yas2X1DmT2lZp5OtMTQgghgeLgtuU4uGM57HaqeV+hAR4JCBZrhYcCaRg8pb37kvJeXcq6OOSLqV5NBKcIHLlPVULHkxAXomOB9qckQm+fr4S83tgFhqjBLpF5b5F3bfFi37Zd6DsiGhPeeAGRTRq2c4QIeOlgIWVHUn4krSmdBb3dXgpr2apK79ETZSVl2PDzJvQZ0ROR0ZEIV+f44rJVaBo1GGUlOmxbm40WrVoiummUT+JfLeas2FqlOHduMxcZHY3u/TvXSJTLa3sM7urHuyOEEEIaGTVMs2/R8Qy1WcylWP3lw3X5ZGEDxTwJCBYVZaVTc0Mh4rZpgtnFzb42Ke9C3tEjKLf+jOSUs6GTn6+PYr62xCU3g93+sYrIu4vcw/uOYeU3a3DyGS1himpWafFChPzkd9YjrXMJCvf+A0f0b4j8qtOa+0OHDiEnJ8freTlns9mg1+uxY8cOpzNmlBe8DLttP3T6jxER+2+kprZG8+bNPQr5e8+agl0bspDRPR3PLXrEo6C32XKhD6I2gzWJnIvIzjp8GUql84IhE69e1wfb/ziI795Yime/meTxs+ss/s1lBky6oGpDO0+932uSmk8IIYQQ36EBXt1DMU9qjc1Wqto32e2u/ctJ/WGzl6C07FcXx3pfU949UVqcj/05o2GKzkbpoS5oGX+7anPna+16bQWS3McQ2c/lfhJ1ffKy/6ia+lNHRGDCq3cjqsmJ+yQ3j1cReRHyRpMdpsh9SEjYCr2pk/u7g91yRC1O+JptUBUivj0JcMlmKCo8iKNHIqDTVXRZyUg3oUmTivdkk5ZneSsBuxl2ZKOo5BzYCi04UJhV6Vq7/zqkhLylXLIssrBmwTqkd2tb6X3p9b/CZjtNmQZWLFo0XEq+1akFXGFeMYryitXXRw7kolnLygsOVt1OlBg3ytIgSiybUFTcFFZzjFqMWvjZHLTqkOQ6QFcOU/Op0Jn2w25uhewVt2DXX1mwWmzYvTEbvy1ehLQuKS5DLOoemyruUbYJWbu/htHeHk3jo6vtGy+w9zshhBBSA9iars6hmCe1FvLbci5HiXkzDGiPFPts6FH9H8UksEL+wOF/OHrJSys6Z0HffWCXKoW8pNLbnOrXpff2CzdPw5jJO2A125Fg3AJ73r2wFHUA4p8DdBURYb0+oVJfew1/I9+VywUOukTeRcg/9M4faNu5GAUH9+CY/k0nt/sojL3/PlisuxEdcwB6Uyb0UYNqZJ4XSGShICYuAf1OS/NYM68ztIC+sCNs1u0wGLsgtcXFXp81qVUZMrqvdETm3VPt7fYSFB65HFbLZnWtmGafQFfHbQirQ1LftfT3pGYVmyzI7N28Aal9KqfB22zdsTvnPZRZtiLKmIEm0RkwmI6hXbdUDL6kd6We7mXmrdh7LKcifS8qB6ddkIQf3m2OrE05SO+aih4e+sDb7DHYc6y96v0eZeyE9DYXsvc7IYQQUkcwMl/3UMyTGmOxHv87rR4oMW9FcflmlTJswQ7klyxDk8iKCL1RnwCjoX5SsxsLmvC22eywWAtgthTDYt2qhLzdblF76SkfYTqRJREdJ+NcU/A19u04pFrFFR0vgsFQAIOhEHu3HcUfC0ow4PKmyOhSDJNOD5u0mbTuQvbvy1FW1hbRMVFITStBTHxewCLczi75ngzykprH49QR0UrIS+Q9InIvIlXk3dkcz4TC48/CGL0J+qizGkzIO6MJeE/md5Ext8Fmt8IQPdzrs0rqvNF0HM/8MA7rftyCnkMzYTTth9Vy4jVW81Yl5CXKL3uzlCh4MA3UkJ9Xfafji5CvKg1er49Gu9QvUFS6VKXNPzVHh2Xf/IpBF5zmsWbeaGiBKFNXlZYv+8T4YZj27Yhqzemk93tx+e9oEnEKhTwhhBBCQhqK+XpGDLAMBgPGjx+vtlBEBLom0u3mJFiL2sLQdA+MuvaIix4EoyFwkXnpGy19mUkFIshlkxpsoyEHJmMqTKaWKiKvReadU+2rE1dZf+1RbeuaNG3vON7p1HJ8+/ZGzPinFW26FOCe5w4jvXMpdKZMdOx7Vb0IZE8GeWKOd9cbLyB/72gl5PWmyuZ4QlyzdrBbklTkO1gR4zv7sWsAy1boDe2B6OFeX6tEtz4RTWKBkwa2RJPYyqnzekMLFZHXIvMmNS/RQdXnXfq6i5AXQ0bZe+vRLn3ZC5CPpgnR6NQ7zasoF/GfnvIpSsp/R/TfwjwyGtWa08nrYqIG+PEOCSGEkPBm5syZarNKECcQsM98nUMxX8+Is3VcXMM6bAcKEYMPjJqJvTs6ovuQTFw3eQL0VQg9iejXNFJfGzHvbAYWzr3HRbhLar1E5Gsi5MX5XdLWew2PxL1v/gdRfzu/i3h6fuFkrPx2Dez2IrQ9tR8M+l+hi3RNWW+IOZVnPKp/U0Xkq3SAryJToL6eW2UW2Dx3ebBbtishL5F0WHfCXrYcMHb0fjF9vFrc8FYDL8JdUuslIt8QQt6XPu/S110i8tX3aK/wH5AFqxJzRZ19VcK8KYU5IYQQEhC0YGN+fj7i4+ODOs1+yJAh+Omnn7yenzdvHs4555xKx2fNmoVXX30VGzduREREBE4//XQ8/PDDGDAgNBf6KeZJjRGBLVvW5v3YvWkfLGbgj/l2bDlnH4zWWNWGSwS4swiX2vqCslWIjxoMvd43wa8ix1v2I7llQo37OUsNcXnZKkRGDUZ5qQEbftmMPmfVzAQuEDi3zaqq9VttKcy1omnCaR6FvLe2dSLkb31rNVp1KsLu7IsQY5wFnaP+HOh4Snv1M4xsImnvfSuZ0Uk/95oa6wWC2KRmMEQmVJkh4C3tvz6fWz2Dt0UFQ3PYjZ0rBL2xM3SRZ6Ag11KrRQYR8EZlGhicXSVkvmvS150QQgghIU49GOCNHj0aMTGV/35q3bpy9t+ECRMwY8YMREdHY+TIkSgtLcWCBQswf/58zJ49G6NGjUKoQTFPaowm1EVkt+vaWgl62Xfp2x4t01JUCy5vJnnRpi7olPqJV0Evtfgi5lV97SXTHdd+du7dPv/xL0L+2OGxsFg2Qa/PxLNX98K23w8go3tbPPv9Q/UmIpzbZkkE0RcHen9wFqiGaO9t65xN7uKbx6mIvAh5g6o/34PE5M0utfaCXh9RSRzL/e4dPgW7/sxGxslpeG7hI/UqzPwVvFo2gtaqT5z+G0pQqoWIpPdVRF6EfHmpPiCLDMHelk4ZMtawrzshhBBCQpP6MMB7/vnn0a5du2pft3DhQiXkk5OTsWLFCnTqVNHtSL6WKP91112n9gkJoeX3RTFPahdp+2oi1v64Eb3O7IK8guNeTfJEyNvtZrXPK12K6L/NuZxN8iTan5t7FEY0URH5iqi/Ve3XLtmI9MxWjuu7R/7N5l2q/ZeQf2w9yssrWlxZLZtQWhIFi7mpEnFrFv2C9K5d/r6G537jgUjDdu6ZbdJ1RvuWs10EfVUO9DUVqPef/VS1AlWrtdcwxUKl1ktEXoR8RITnWvuKqP4JR3ktqi9CXn42spfWd+nd2tRpL3df8ZSF4PLcG/5+7g2en7s+n10J+og+SsjfN9LpZzi//hacGgL2dSeEEEJIfTN9+nS1l5R6TcgL/fv3xy233IKXXnoJb7/9NiZOnBhSPxyKeVIrRHSkd2lVIT4KPJvkRRhaqIi8Fpn3lmrfNN4AS+RRxEedVCnq33tINyVcRWRVpKa71tHLAp7JmKG+NhhiERHRrSIyb8xEVHQXGE0Vkfk+Zw2oUiipKPffKfnGCHF4T/Qpdd65p7a6jnmrEvKygFFq2YQjRz9BTMyJmmir9VCVDvTe2r4dP7oXRblG2O125BUex45f91QrUL2JU6k/b5kyG8Ymv3nNDtDc5Z1p1jpJReS1yHxDpNp7w9Pzujx397S/RXOrOn9uqZmXjIaqFhiErI3bfVpkaOiFkrouOSGEEEJImBEkBnglJSVYvHix+nrMmDGVzssxEfNff/01xTxpfFRnUCfCXVLrJSLvTch7SsWX1HqJyIuQF0Rk9x7WGVada2q6RMFFPEurKnOZAX+t2I3ewz4EdCtUzfxTXxuwZtH6amvmVWr/ORIh3aOE/xNfXwW7xeQinLylzjv31BbkWSIMmSjI34AD26Lw7ovb8fTXVznuL5H5/OJZHh3ovWUGyBhTkw1omXQmYI+EMUeH9p0znARqzYV1fHIzWG2ea+29IdeX1HoRncEk5KtDnlMyF9Yu/A2nDMpDRJStbt3qy9cAkWdUucBQeZHB88/Q2cwxVJHFLop5QgghpPFQH2n2b7/9No4eParKfDt37qzq3tPS0lxes2XLFpSVlSElJQVt2lQOmPTu3Vvt169fj1CDkXkSEDEvztNVIQJeUuudhbwvqfitM60oNWfhkQvew77te3D3//5A686FKi28ecrnauVOS2cX8fzqP3ti+9/18VO/u02ZgUm7qu4DusBql8bcESguLlY9v6XHuvPSX9YmScPeoyKke7btxh/L5yP/QAd0O607klsmIibB4LiX9LWWtljOgl5FYHNPRGAPbX4A7z81HQe2RQO2A2pBIb3riV8gMQmzYIx1jYprmQG9hkq7uApXb+e0/LLyTYiU9578qYtArY2w9seAT9U+D+yi9loEOhQQAd+r7zToSrfDbMmEKfnDgLfac247p0zukt6v8h7qZzj/Ia8/Q/GAsJStajCX+kDgvODmyT+CEEIIIWGIzV6xVfcyqwU2m/ydXoHFUurzLZ588kmX7++55x5MnjxZbRrZ2dlq70nIC02bNlW18rm5uSgoKECshzbAwQrFPKm/D5ub4KsqFV9X0htHD1hQkm/Ano1bsPuvfWjRMQ+JrY7CatOhrOwvbN/4GmQJwRb7l8T9UGLZhKLiSEd9/NofN6Fd14pfIMYoAzb/uVE57UuKes+TeyJr0x5HtF5SgJu16qEWAUTIj/9gHWLbLEGhtSleuuN8TJn7LxSV7lJCHnaL2heVLkXk37X/BvXeTGjd4URv82atkvDJs50AW87fKf4nhJoWaXWOimuZAXu37UbPs4yYMHMCoppURHTLzVtQXr4JNlu52peULoPF2hJmSzH0Jh26DhAnc+nx3QBGdLIgE2RivqIt3ImyBw2beRv02K5awtktW2ArXQa96UTdlAseet3XuO2cCHof2s5FRic4FkdcrmUvQeGRyx3946X9XKgJemf/CE+LYIQQQghp3Gn22Tt+RPb2hTW69ODBg3HjjTeqlnItW7bEnj17lCO9iPtHHnlEtQK/88471WsLCyuCbRLM84YI+uPHj1PME+KNqnrMe0rFT0iW1NxItOvSDRndV2PvNhty9yc7IvNp3W5FwbEiHLMsUUIh2pSJpk1O1Men9eiIY3mHK25QDOTk5FRkENiBb2YuxuE9R5HyfjIuv3cEmsQcRtOINrj91XOwc9PPSG3/MywWG5p3KERJ6W6sW7oNbbvGQ2dsC7s+W4kS51T7ioi6ayq/7J/57i78seTEooFz27yj+8WILxLAQUdmgAj5W9/4FS07FmLfgR2OdnFlpe2x70BTJLcpQ+7+GDTvdzqMhlKYjKkqrSixWcN87lQU2rINMLQIeIS7LtrC6eU5izKVkNcZM6GPGuTxuZ2zDfKPFVTq717TtnPe5kYWdey2XMCWi6ZxgNXy9+f1b6zmrUrIy8KA7KWPvOHvBSRv77uh0vHdfSPc/SM8LYK5I4tiTMUnhBBCGhdp7YeiTbtBLpH5VUumVjlmypQpLt9Liv2DDz6IU089FWeffTYee+wx3HTTTaoNXTjDyDwJGjyl4ks7tcjoRNVSTtLUe58uNfO/qNR0c2lFffwpw/4HC1Yocf20W318W1Sk0xzadxhZxmyxEMfxw3nYsXwfygrMyN1ajLJxOiQll0NvT0F0VBTSMhJgivpJ1bsf2tEUTaO7oO9ZI9T1bLZvcfjIfKQ0G+ki5O87+3Hs/qty+7smMc3RfUBTFyEvbfPM5k0wW1ojueUrjuh7fGocep4VoYS8tIszRWTDZl4Jvb09DuzMwYs3noxmbfNxZE887n5jGxLSYmApsKtsg4YwRRMhbz32T8CyBTBmwpD0QVAJek/I80lqvYrI/y3k8/OKERffxOV92cpWq/PlpTps+HkT+ozoCVOkySfB7952rqo5UcK7CvEtiw8Skdci88Gcau/uG6EhqfWy+KVF5r21aiSEEEJIeKHzsf7doDeqzXmcv4wcOVIJ+t9++w2//vqrajen9aGXUltvFBVJhitCKsVeoJgnQYvUiUt6ucHQApHR0areXBzYpdZZhLyzWd3T396mBILUx8vr3NOVm7dOwbCzh6r0muPHjuO3/21WYzue0hLNe09FqXUL8HcKcOzxGMQkfI7cqMUo3p6Ep7/u47ieGOz9+aMVHbofQURUhbjL2rwDZRI91Uera7rWxuehabwFFkuFWLSYt1YI+bJS2LETL9/+Eu6ceS8io02Iijbhrpl3YO+BLYiI3KeyD1q2uVil4ae0KkebTr86TNJ6Dz9ZtQJMTa2IzDdEyrqKyIuQV+nkW2AvWwYYO/mcqt5QiLjWR/ZV+7JSM1Yt24JBw7sjMsqkhLz5qBgfbgEKOuGBsZ2xbe0+ZHRPx7MLJlcr+COjI13aztV2cUOEu6TWS0Q+mIV8Vci/S/l3JRF5CnlCCCGkEWG3V2z+jKsFnTp1UmL+wIED6nvNEG/v3r1ehbyk2CcmJlLME+Iv0mc+Oi7BIeQPOfVhV2Z30GHfjoOwoxzZm9Y7zOpkL6ns6X/Xx3tbzxMhL6nATWKPK6d6SZ3vegaQU/SZSwpwVGxnWKxAbMxJ6N6/mUPIV9S0T8Wuv7KRcdKfePb7B2CKtKK0yVTc8q641jfBwhcvcXPNb6GM8Q5lacZ4mTBb2sKO7di3LQZrF5Zj3U/5TuI/GjHGD5CYvMnFGM/d6M4UaXRpBViXeE0pN7RQEXktMq+L9JyyHqyUFm7HxJu/RdaO4/jigyW4/7H+iI7MRmzUZuhggc2yGZYSO6zlUdi1YTf+WLQA8W0TYCvcjrioJ2DQ74HF0h4Pju2M3X/lIOPkdDy36JETgj5Aixgi4I2R/UJSyGuohTaVdRO674EQQgghwedm7wkxstPq4IXMzExERkbi8OHD2LdvH1q3bu3y+rVr16p9jx49EGowMl/P9O3bFwaDAePHj1dbuCJO9VXVyGvi3bmtXX7ufkTFGmG25FYYvrn1YU9Nr+jDrtenIqWVtGRr64jMV9d2zj0VOMIEZHSNQ2J8PPLLvacAl6Lwb9d7qWnfp4S8WkD4KxurFy1A626FKDNuRkQ00PakMjz4+QDojPtQbv77fvoExCUluqTAlxZ/hem3TFRCvk2ndh6f3WqLq9QuztlBvrruAfWBCHdJrZeIfLAKeUmhL8gv8Xhu+6YS7NhyDHabHbt2HMfuPU3RsesZsKIjDNgGK9rCam8NneEYWrZPUlux2QaDfh8M+r3QwQqDfgd0diOs5grBv3bBArQ76UQXArs9DnbEqa8rSiH8S90K9bZ0J0wiCSGEEBKszJw5U21WqzVk+8wfPnwYy5Ytc2k5J3Xzw4YNw7x58/D5559jwoQJLmPEOE+48MILEWpQzNczq1evVu6KoYzW2k3be+oZX1C2ymtPeU9iXqLe2VuK0KxlNyVWJbVeIvKe+rALhmg46uh9FfLuxCbGVJsC7NwjvFmrRGSclIZdf+1BxkltVR29ROazDn9YsRhg6IzE+GHVRh+lVEBS6yUi7+3ZvbWLq++6+OqoSCevSFkPSuR/RmXlns8VFAIlpUBEBFBSVvF9WTPkYQZM+lUw2/rhnnd02LEuCz2HnKTaE4qJYrOUPrDmfqZS8Q3GTjBGd4YhoiIVv/eIEY7IPHGFxnaEEEJIcKMFG/Pz8xEfH49g5ZdfflF/k1144YUqSKqxe/duXH311Spt/qKLLnJpRXf33XcrMS9u9+eff75KxRdWrFiB119/XbWmu+GGGxBqUMyTGiECXhYktBZvkmngLOht9lLsOHylo8WcONSLoHePwot4z9qyH8ktK6J1ky6Zjt2b9qFd19Z4du7dqkZeUuslIu8u5F0i1QMqt/PyFU0Yi/huEtmvWhEu95HU+jWLNqDPWd0d9/WnHji6aQq6D2jl97MHE8FWE++MRMK9RcObtU5Cx+e/wa6t+5DRuSVOP6+3Q4jbbSdq/UWkC1o2hLuJ3tR5OqxZsM6lZp4QQgghpLGjs9vV5s+4qti6dSuuu+46tGjRQkXfRYhnZWVhzZo1KC0txUknnYQ333zTZczw4cNVq7oZM2agV69eGDFiBMrLy7FgwQKlad599111nVCDYp5Uy6FDh9Tql4bW4k2M13bs2AGbrRgJSSbodAbkl6xTQt5uN6u9tJrTWzLw54qdOGVwbzSNSVFC/t4Ln0PWlgNo06E5LptwrhLykr4u+7VLNiI9s5W6lx0dYEu0IdZLlnGgItW+Rg0rFhA6u4hwf+qBJW06LsmvRyUBQoT3C4sfwbKvVmPQxX1dhHh1CxTOJnpiuth9YFcKeUIIIYQQZyQO4k9laDVjTjvtNNx6663KrV6CjFIjL/XxItL/8Y9/qHOeWtK9+OKL6jWvvPKKEvERERFK5E+ePFn1qw9FKOZJtTRv3lxtWmT+2LFjjsh8hw4dVGRexL2I/LjoTogu7OKIzEfhdDwwZiZ2bdyLNh1+xb2v3YADWYeRve0grFYb9u3KUX51rTNSsXfHIaR1aoHeQ7opwV8h1FOD7ifkaQGB9cChiQj4fiP9i6g7C35/a+EJIYQQQsKVuorMd+3aFa+++qpfz3TttdeqLVyo255WfiDpEc888wwuvfRSVecgolG26pg1axb69eun+ggmJSXhvPPOU/UUVbF8+XL1Onm9jJPx77//fpVjpKWBpHW0atUKUVFR6Ny5Mx599FGV0tEYEOEuqfWDBw+ulGIv6HVRaBHxNuLMTyCm+CX8sWSnirZbLTbs25mDA7sPo2V6ihLvBqNOpdWfNrIHps+bhPvfuBHPfX2vus6GXzYrQR8qsB44dKEQJ4QQQgipA+y12EhoRuafeOIJfPXVVzUaI46EUv8g6RQjR45UwlpSJ+bPn6/cCUeNGlVpzBdffIHLLrtMRZRFmDZr1gyLFi3CuHHjsH79ejz//POVxmzfvh39+/fHkSNH0L17dwwaNEj1MJwyZYoaK5u0PQh3NAHvyfxOiE9KRmRsX0SZ0tCsZQsl2LV6+N5DKwzuRLyvXvIj+g4ZeqL2/O/Ueuf+8WJyFw515YQQQgghhBAS1mJexLL0+JOor2zt2rVDWVmZ19cvXLhQCfnk5GTlRujsTDhkyBAVRZe9s6GBpIlff/31qu2CiHrJAtBqwwcOHIgXXngBF1xwgRrnjKRkiJC/44471D0Fi8WCsWPHYu7cuZg6dSoee+yxOpqZ0KK0wISopL9N476aiLU/bnQIecEUaUOHPmVqL33YC3ILUZhXjN0bs136x4tbvdaDXdzng83NnRBCCCGEEOIBSZf3I83erzGNlKBLs580aZKKdEurAXEorI7p06er/cMPP+wQ8tqiwC233ILjx4/j7bffdhnz1ltvqZYLF198sUPIC1IXPm3aNPW1CHpnVq1apdLyU1NTHa8RjEYjXnvtNZhMJrz00ktK3IdaP/hAI+nxm1YedqTJK9O4/p0cQl5a123LuRyHyu5T+5gEI1p3aIHM3u1VqzaJyBtNBkf/eDknG4U8IYQQQgghoYHO7v9GQlTM14SSkhIsXrxYfT1mzJhK57VjX3/9tcvxb7/91usY6TsotfAS8Xeug9fGyCKDeyq9LAJIyr04Kf78888IJSy24wEV+yLgJ138Ap69+S211wR9dJwZpebdahOHe3fHe+2c3bgfT307HpPeu40p9oQQQgghhIR6ZN6fjYS/mN+yZYtKwU9JSVFmee5I30FBauCdWbdunct5Z6RFgdTDi5CXHoa+jKnqXsGMRMhLzFuRd+yI1/MFZavU3hnpGe/+/YFdh3Hs4HH8/tMm1zZzP27E/p05yMkqh7kwBVGmdoiPGqyc7nU6k9rL93Jc25rGpNaqfzwhhBBCCCGkYdHZarbt3bcSK3+bgdW/v8YfXajWzNeE7Oxstfck5AXpNyi18hIxLygoQGxsrEqvz8vLq3KcHBdju6ysLFW/78u9tOMypiok7V9M9zQkyt8Qpnk2eym2H74CJeVbYC1qi64RnyO6SVyl86XmLYgyZaJjysfKqV4i7X+u2IpTzuzqENtN46MRHRsJ/WEb0jukuRje9TrTVZRXvPcIdEj5CPklyxAXPUh97zwnQkxCRbs74uXnZ7Op1oCco/qDc16/cL7rH8455zvc4Wec8x3O1ObzLcFRZ48y0UsNQduWp6vNYinFkl+fbJBnCDVCWswXFhZW6aquCXoR0JqY18ZUNU7GCDLG13t5GuOJ9PR0l+8nTpyIe+65B/VFuSUHpcWlMEbvRbFtM8zl5bDad+CZ2x7AuEduRESUSfWDsNh3oMQuqfAWFJdtQvb+72ErS8f0G7/Evu1H0aZTC0x697q/X1/xC0QWSeSXyN1vXI3Nq3eiS9/2yCs4DniZknJLC5QXyi+LhvmFEco4z7deH9IJNiED55zzHe7wM875Dnf4Ged8hzO1+XxLFy93v7CAQAO8OiekxXwoIpH7uLi4BonMS7T9yPE12LaiKTK69YBNnwabfQdydsZg08925GzRIb1LKmISm6BpfCdsP/weiss3obwgEXZ0QU5WGfbvyIXVYse+7TnYu/GIo51ck4Sm0CXoVMmD/AKJj0tAbELFAoc3Ss0liDKl1st7D8df2DrdifkmnPNwg59xznm4w8845zzc4Wc8dOZbWoOLmbhzZN49AOkX/vaMZ8l84xDzMTEVbcqKi4u9vqaoqKK+W6LyzmO0cc7C2tsYX+7laYwnJO3f0z3rGuUgf+gK5BVsQGGTGMy8bzQmv/8xZtz3GP780YI2HdPQZ1h3l5T4trFvYsUfI9A0KQfbDo7D6afNc0mh7zP0JCeHehvKckrULw8l5pOqngchwphIIVoL5Be2Nt+kfuCc1y+c7/qHc875Dnf4Ged8hzP+fr6jo6PVphGovy11drva/BlHGoGYT0tLU/u9e/d6FdiSYp+YmOgQ2SKk4+PjVRqKjOvWrVulcdr1nFek5F6///6713t5GhMMiBt93vF9yMv7C8W6TdDprEjJyEdRyWZs+PU3XDXxamSdbcfAC/soYS793vNy98OGfOzZvRZNWxRAZ7AjvvlR/LVuDm5/cSg2/7YH/YafWmuDOqMhIWDvkxBCCCGEEBJEMM2+zgnpkF5mZqZKUT98+DD27dtX6fzatWvVXjOx0+jZs6fLeWfMZjM2bNig2tN17tzZpzFV3auhEcGcnHwS2rW7CE0iu8JuN+Dwrjg0je6CvkOHoWO309FvxMkOYR6bGIM27Tsjrf2p6H365cg7lAy7Ra/28r28vvfAM5HaKqOh3xohhBBCCCGENFpCWsxLOsiwYcPU159//nml87Nnz3b0hnfvJe983plvvvlGtaUbPny4EvTuY6RnvbPbo3Do0CEsW7ZMZQCcccYZCEb0+ihktvgU7VNeRqr+dTw9+34XAe+pr7y425952iLYDt6v9prbfWxi1bXwhBBCCCGEkEaOZMvb/NiYZd84xLxw9913q/2TTz6Jbdu2OY6vWLECr7/+uqpRv+GGG1zG3HjjjSrd/quvvsKcOXMcx3NycnDfffc5XOad6devnxLq8ppJkyY5jlssFtx2220qon/HHXfAZKpwd29ILNZcr4I+LrYbup/uWhtfVV95EfBdep7h0raOYp4QQgghhBDiS828PxsJ0Zr5b7/9VjkqapSXl6v96aef7jg2efJkR6RcIuh33nknZsyYgV69emHEiBFqzIIFC1RrhnfffVcJemeSkpLwzjvvYOzYsRgzZgyGDBmC5ORkLFy4UNXYywKBHHNHrtW/f391r8WLF6t6+9WrV2Pnzp0YMGAAHnjgATQ0NlsJispWITZqMPT6E0YWGkZ9AqKcIvEnxpViW87lKDFvRrSpCzqlfqLEvxCf0Lpenp0QQgghhBASJig3ez+EObV86Ip5qX//9ddfKx13PiavcebFF19UQv6VV15RIj4iIkKJfBH9IrI9MXr0aCxdulRF9FeuXKkWAESc33777Rg3bpzHMZ06dVImeI888gi+//57zJ07VxnjyX0efPDBemsxV5WQ33n4MpSZNyPS1AXtUz5Vgv740b1ISG7j0XRO0uottuMoMW9VQt5uN6O4fDPySpci2tRZiX8a1RFCCCGEEEJqBA3wGp+Yv/baa9VWH+MkbX7evHk1GtO2bVsVoQ8mysy71RJWqXmrEvIiyGVfULoUdnMrbPxjMU7pf51LqryGCHXZIgwtVERehLy1qC2imp2OKFP9t9AjhBBCCCGEENIIauaJYEekKUOl1ktEXqczqb3Rfgp+W3stTK3+g+W/DkVJcb7X6ZKU+rS49/F/jw/HM+d3wAOjXkFZSUWJAyGEEEIIIYTUCFstNhKakXlS89R6iciX5sciPrmZSq0/dHguzIXpWL9hLuJbHYXeaEN8i6P4Y8XHaNtuKOITWyE26UTdvPSWL8gtQtbm/fj9BxssZmD3xn1Y++NfSO/SShneOTveE0IIIYQQQkhV+GtmRwM836GYr2f69u0Lg8GA8ePHq602jvV6XZSqkS8t3wxLUVtkRs9VqfRJSf0R2TwDKS1PxvJf31BCPu9gMs7of4XHVHsR6rIlt0xEu25tlJBv1631/7N3H+BNlW0fwP8Z3Rto2ZQ9CshQQEBQEcSNjNf9CogiggKCWxEHbvETFReiOF4nglsURGUIspQhG0qhrDK6d5LzXfcTU9I2bdM0TTP+v+s61+k5yUlOTh9K7vPcz/2g54WdHVa9JyIiIiIi/zJ37ly1mM3mOhkzf/DkBhw8tQGaxq55ZzGY9zCpfi/T4tWEBPL5Rdtg0fJUIF9UWAiztg8vTLwfU1+5uyQAl8C9f59fVY98RYG8PTnuua/vUT3yDOSJiIiIiAKHrbMxKysLMTExHg/mW9Q/Wy0mcyF+2f5izd8/AHDMvA+SHvnc7NPIPtpK9cibi3U4vi8SW34z4Z+VOTh1MAxH9h9Xz5UAvlP3y6sM5O0D+i5927FHnoiIiIiIyIuxZ97HlJp+LrIj2kV+gtmTZqpAvlmbRPQc1EU9b9Pyf1TavATntmnpnMXx8UREREREVCOcmq7WMZj3ERVNP2fS/YWpr0zDPyuzSwL5+698AQe2p6rx7899ey972YmIiIiIyLNk6LvOxePIKQzmvVz26RxExBpQVLwLEaEDEWRopKadUz3zQR3VdHR6fRgSOx3HqSPpqiK9BPKmYrNaSw99SUV6uwr2REREREREtYXV7Gsfg3kvlpdzHNvW7kdCj6dQZN6F0KBOSIz/TE0/l12woiSQF01aN1Tr+k1sFemtPfM9B7EiPREREREReRjT7Gsdg3kvlZ+XhRfvnIG01NO49fVtCA4DCop3ILdgBUKC2iM0qENJIF+uIv2396oeeQbyRERERERE/onBvBfKPHUSKSeuwRX370NacgSO741A06QChAa1V6n2joJ4e6xIT0REREREdcqiSa69a8eRUzg1nZcxm9OhD9uIoIhDMARpSGiViw2L+qNh1DNo3XhhqUBextNXhOPjiYiIiIioztPsXVnIKQzmvYzBEKd630ODOyE4JAQhxnaY9sqLiAg5H9tWHUBhfpF6nqy3rdldsk1EREREROQ9XA3kGcw7i2n2XkhVp4//TI2Pl8C+uNCA+4e9UlLU7okvpuLR/7x8Zvq57+7j9HNEREREROQ9WACv1rFn3gvT7G0BfXhIb+RmmLFp+TbrdHNFJiRvO4RFry5Ra9m2Tj+3rdKUeyIiIiIiIvIvDOY9rFevXkhKSsLcuXMdPm62ZJQE5pJyL2Pfew7qonrgjcFGtOrSHCPuukStZds6/VwXjpEnIiIiIiKXSXwicYrEK24hhexcXcgpTLP3sPXr1yM6OtrhYxZLPrJztmP32nroeeHZJanzarq57+5TPfASuNu2d63fhw692jDFnoiIiIiIamTSpElqycrKQkxMTM2vpmaxLk5KyfobB7M3Q2MBPKexZ95LSCCffPw/OHRiEjK12/DQ8KdLFbezTjfXvlSAf9bATgzkiYiIiIjI+1Sz8F1iVDcMaHIz+jW+rq7P3GcwmPeScfInTv6M/MIdgM6MhNZZyMvfgY3L15YaC8/p5oiIiIiIyCcwzb7WMZj3AjI2Pr7BxQgL6QRoBqTtj0Z4WCecPehcBvBERERERERUDsfMewmpXt+q4RdID12O/L318PTiM2PmiYiIiIiIfAqnpqt1DOa9LKCPje6HLucGMZAnIiIiIiLfJUXpXSlmx2L2TmMw72Ws09HV9VkQERERERHVAHvmax2DeSIiIiIiInIvi0xLZ3HxOHIGC+ARERERERER+Rj2zBMREREREZF7Mc2+1jGYJyIiIiIiIvdiMF/rmGbvYb169UJSUhLmzp3r6bcmIiIiIiJySOITiVMkXnELi+b6Qk5hz7yHrV+/HtHR0Z5+WyIiIiIiogpNmjRJLVlZWYiJianxldI0i1pcOY6cw555IiIiIiIiIh/DnnkiIiIiIiJy/5j5aqTMHyzYjoOF26HJceQUBvNERERERETkXioodz4wbxHSSS0mrQi/ZH7I34YTGMwTERERERGRe1ksgM6F8e8cM+80BvNERERERERUpz3zpY8jZ7AAHhEREREREZGPYc88ERERERERuZVmsUBzIc2eU9M5j8E8ERERERERuRfT7Gsd0+yJiIiIiIjIvWRaOleXKuTn5+PRRx9F+/btERoaiiZNmuCWW27B4cOHA+q3yGCeiIiIiIiI3N8zL5Xpq71UHswXFBRg0KBBePLJJ5GTk4Nhw4ahefPmeO+999CjRw/s378/YH6TDOY9rFevXkhKSsLcuXM9/dZEREREREQOSXwicYrEK95s1qxZWLt2Lfr27Yvdu3fjs88+w59//onZs2fjxIkTqoc+UDCY97D169dj+/btmDRpEvxJYWEhXnzxRbUmXm9/xDbO6+3v2MZ5vf0d2zivtz9zR/uW+ETiFIlX3EGzaC4vFSkqKsJrr71WcvMhMjKy5LFp06bhrLPOwu+//46NGzciEDCYJ7eQPxxyN4zBvGfwenserzmvt79jG+f19nds47ze/swr27dLKfb/LhVYvXo1MjMz0aZNG5VSX9aoUaPU+ttvv0UgYDDvo9yVpu+N6f7uPCdvvE7+fM298Tr58/V252t54zm5kz9fJ3++3u58LW88J3fy5+vkz9fbna/lba/jTv58vd39Wt6kNnrmN2/erNY9e/Z0+Lht/5YtWxAIGMz7KG/8Q+Qu3vjH0RvPyZ38+Tr58/V252t54zm5kz9fJ3++3u58LW88J3fy5+vkz9fbna/lba/jTv58vd39Wl6lFnrmDx48qNbNmjVz+Lhtf0pKCgIB55n3EO3fqoxZWVlueT2z2eyW13LX69heQ9Z6vd4rzsmdr+Vt5+TO6+2uc3Ln63jjObGNe/aas4179nq7+5r7898Cd70W27hnr7e7r7m3tSdvfB1eb89ec3deb9tr2eIXV5lQDDjxEhaYYcGZAN4EU4XPler1Ijw83OHjERERap2dnY1AoNNq+lsip6SmpqopE4iIiIiIiLzdoUOHKuwBr2rquFatWuHYsWMuv7cUtpPK9DKHvL3x48dj3rx5ePjhh1VV+7L27t2Ldu3aqUUq3fs79sx7SJMmTdQ/iKioKOh0Ok+9LRERERERkdOkr1d6tiV+cYUE4MnJyaryvDOkaF/Zwn0SM5UN5IWten1eXp7D18rNzS05PhAwmPcQSXdx5c4WERERERGRJ8XExNToeAnEHQXjNdWiRYuSrGdHbPsTExMRCFgAj4iIiIiIiLxet27d1HrTpk0OH7ftl/nmAwGDeSIiIiIiIvJ6/fv3V1kD+/btw99//13u8YULF6r1lVdeiUDAYJ7K2bhxI5599lmMGDFCDQ2QMf41Geefnp6OKVOmqHSXkJAQtZ46dSoyMjJ49d18vVu2bFlyvKNl586dAX/NZYzVV199hXHjxqFDhw4qBUwqn8qd3ieeeKKkSirbuHdeb7Zx57z00kvqb4oUAJIvPba/vTfffDO2bt1a7d8j/4577nqzjVffqVOnkJCQoP6fa9u2rQuvwDbuyevNNl61Cy64oNLvc0uWLAnYv+HBwcG488471c+TJk0qGSNv+1ss88uff/75OPvssxEIWM2eyrn66qvx9ddfl9vvysQHJ0+eRN++fVVlydatW+Occ87BP//8o5b27dtjzZo1qFevXkD/Ftx5veU/SJlXc/To0Q4ff+aZZ9C4cWMEsnfeeQe33Xab+rlTp07o0qWLmoLljz/+UMVeOnbsiN9//119UXEG27hnrzfbuHMaNGigvuBImmHTpk3VPvm7K5V9g4KCsGjRIlxxxRVOvRbbuGevN9t49Y0ZMwYffPCB+n+zTZs26jtHdbCNe/Z6s407F8zL/40jR44sKfhmb/r06ejatWvAtm+pli/X6M8//1TfawcMGKC+/8p2fHw81q5dqz5rQJCp6YjsPfvss9qMGTO0b775Rjt69KgWEhIiUaVLF+nGG29Ux44YMUIrLi4u2X/XXXep/aNHjw74i+/O652YmOjysYFiwYIF2vjx47Xt27eX2n/kyBGtR48e6vpdf/31Tr8e27hnrzfbuHNWrVql5efnl9s/d+5cdc0bNmxY6m9yZdjGPXu92carZ9myZeoay98ZWbdp06aar8A27unrzTZetfPPP19d3+TkZK2m/PVveF5envr+LG0wODhYa9SokTZmzBjt0KFDWiBhzzxVSdJiZbqI6vYUHz16VKWNG41GHDx4EA0bNix5TF6vefPmOH36NI4cOeJ0r1wgcPV629/tduVYgro73a9fP5WCJr3HkspVGbZxz15vwTZec5IWK2MNN2/eXGWBILZxz15vwTbuvPz8fNU7KX9DZDiP9DJWt6eYbdyz11uwjTvfMy/Tu8n1chXbt//jmHmqNTKex2KxqNQX+0BeyH8EUpjCbDbjhx9+4G+BvKpCqtxMkTGBVWEb9+z1JveQtG/hzM0TtnHPXm+qnscffxz79+/Hm2++WXKdq4tt3LPXmzyL7dv/cZ55qjXSCyF69uzp8HHZ/+6776pCFeReL7zwguoJkpsmnTt3xvDhw9UYIqqcfEkR8iXFmfFjbOOevd722MZd8+GHH2LXrl2qUJssVWEb9+z1tsc2Xjn57jB79myMHTtWdRocOHDApd8R27hnr7c9tvGqzZ8/X93s1uv1KhNC6izZ5ll3Btu3/2MwT7VGUuuFpNo7YtsvaeHkXvfdd1+p7bvvvhuvvvoqbrnlFl7qSsyZM0etL7nkEnUjpCps45693vbYxp3/sixFjqQ4244dO9TPTZo0wSeffAKDwVDl8Wzjnr3e9tjGKyZZf7feeitiY2Px/PPPoybYxj17ve2xjVdt1qxZpbbvuecezJgxQy3OYPv2f0yzp1pjm3IqPDzc4eMyPZWQitbkHldddZWqmiw3SGRKsG3btmHatGkqjVn+I3ZUNZ+sZLiH3AGXXuInn3zSqcvCNu7Z6y3Yxqvnp59+wvvvv6/m3ZXAUqYjksDS2Sl72MY9e70F23jV5Ob0+vXr1c2T+vXroybYxj17vQXbeNUGDhyoMnsky1K+z0mGz1NPPaXqUD366KMlN8OrwvYdAOq6Ah95P1erqw8ZMkQdN2/ePIePL126VD0uz6OaX+/KvP322+o1O3TowEvtwI4dO7S4uDh1jV5++WWnrxHbuGevd2XYxiuXnp6urVixQhs8eLC67rNmzXLqurKNe/Z6V4Zt3ColJUWLjIxU1b7tSdVvV6qrs4179npXhm28aj/99JO67rGxsaqae1XYvv0fe+ap1tjmxZQ7io5IGqKIiorib6GWjRs3Ts0YIHd23THOzZ8cPnxYpXmnp6erLIYpU6Y4fSzbuGevd2XYxisn6bEyzlUyIqSXWFI0paetKmzjnr3elWEbt5o0aRKKiopUETZ3YBv37PWuDNt41S6++GI1T3xGRoaaU70qbN/+j2PmqdbYCnSkpqY6fNy2X9IQqXZJ4RSZPiYtLU1NU1KTaU78iUyNKP8xyrAEKerz4osvVut4tnHPXu/KsI07R4Y1XHvttdi4cSO+/fZb9OrVq9Lns4179npXhm3c6rvvvlM3SyZMmFDq+hQUFJTcMJRpvcSnn36KRo0aVXpd2cY9e70rwzbuHCmmuWHDBvV9rips3/6PwTzV+rRTmzZtcvi4bb8z8+5SzUlPqH2tgkAn48guvfRSbN++HSNGjMC8efOg0+mq9Rps45693lVhG3dOgwYN1PrEiRNVPpdt3LPXuyps41bSKylzcDsiQabtMVvAWRm2cc9e76qwjbv3GrF9B4C6zvMn/x3DfeTIEU2v12vBwcHa8ePHSz1WUFCgxcfHawaDodxjga42xsxv27ZN0+l0Wnh4uFZYWKgFOml/gwYNUtd56NChLl8TtnHPXu/KsI07b/To0ep38cILL1T5XLZxz17vyrCNV87VMdxs466pjTHzbONVS0tL0yIiItS1P3ToUJXPZ/v2fxwzTzX22muvoWPHjnjwwQdL7W/cuDGuv/56NdZq4sSJMJlMpaYjkV6Km266SY3lpppfbxmbuXz5codzw/7nP/+RuwOqon1wcHBAX26z2azapVwrGdMq1f+ruiZs495xvdnGnbN69WosWbJETSdlr7i4WFWllgrJYWFhKv27qmvOv+Oevd5s47WHbdyz2MZd98cff+Crr75S/3/ak5pHw4cPVzWnZEYA+6mf2b4DF9PsqZzvv/++1FRREoyLc889t2SfFPO5/PLL1c8nT55UhdUcjd15+eWXsXbtWnz55Zfqi4sU7ZDpemTKNBnz89JLLwX8b8Bd13vdunV4/PHHVQ0CSauSKQH379+vhjPIjRQZ0/bss88G/PWW//AWL15ckv4qN5ockfHctvRYtnHvuN5s487Zs2ePqkkg11OKr8lUUnJNt27dqq5paGgoFixYgObNm5ccwzbuOndeb7bx2sM27lls467bvXu3+psi9Qd69uypahZIrRmpvSFDGTp37qyGqjlzvQW/i/s3BvNUjvSYO6qQab/P2bF/8uVGvpw89thj6i6jfKlv2LAhJk+erAJP+QMV6Nx1vYcOHYpDhw6pisnSU5SZmYno6Gicd955uPHGG9V/DAaDAYHONtZM2IJMR6TN2oLLyrCNe+56s4075/zzz8dDDz2kxrFKZo58yZNsCCl8OWrUKPX3t23btk6+Gtu4J68323jd4N9xz2Ebr1qfPn1wxx13qO+B8p1O/h+V8fHdu3dXmZbymGT7OIvt27/pJNe+rk+CiIiIiIiIiJzHMfNEREREREREPobBPBEREREREZGPYTBPRERERERE5GMYzBMRERERERH5GAbzRERERERERD6GwTwRERERERGRj2EwT0RERERERORjGMwTERERERER+RgG80REREREREQ+hsE8ERFRLRkzZgxatmzp9dd3wYIF0Ol02LBhQ41eZ+LEiRgyZAjqwptvvokWLVqgsLCwTt6fiIjI0xjMExGRV/v8889VoLl48eJyj3Xr1k099uuvv5Z7TAK7fv36eegsfcPrr7+uAvfakJycjHfeeQcPPfQQ6urGSVFREd566606eX8iIiJPYzBPRERe7bzzzlPrVatWldqflZWFbdu2wWg0YvXq1aUeO3TokFpsx1LtB/Nz5sxBq1atcOGFF9bJ5Q4NDcXo0aPx0ksvQdO0OjkHIiIiT2IwT0REXq1JkyYqSCwbzK9Zs0YFbf/5z3/KPWbbZjDvGcXFxfjf//6Ha665BnVJ3j8lJcVhpgYREZG/YTBPREReT4Lyv/76C/n5+SX7pDe+c+fOuPTSS7F27VpYLJZSj0n6ff/+/dX2e++9h0GDBiEhIQEhISFISkrCG2+8Ueo9rrjiCrRu3drh+/ft2xfnnHNOqX0fffQRzj77bISFhaFevXq47rrrVDZAVeQ8X375ZXXu0pvcsGFD3H777UhPTy/1PBlrL+ckNyZ69+6tnivn98EHH5R7zS1btuD8889X59KsWTPMmjVLfWa5BgcOHCh5vX/++Qe///672i/LBRdcUOp1ZLz5tGnTEB8fj4iICAwfPhwnTpyo8jPJOZ48eRKDBw92OBbfdg42v/32m9ovaxs5ly5dupR8lvDwcLRt2xYLFy5Uj8t59+nTR33GDh06YNmyZeXOQ34f8rv4+uuvqzxnIiIiX8dgnoiIfCKYl97fP//8s1TALmPiZcnMzFQp9/aPdezYEfXr11fbErgnJiaq8dyzZ89G8+bNVbG2uXPnlhxz7bXXqnHf69evL/Xe0tMrNwskWLd56qmncPPNN6Ndu3YqrXvq1Kn45ZdfMHDgQGRkZFT6WSRwv/fee9WNBklNHzt2rOrVHjp0qPqM9vbu3YtRo0aponJy3nFxcWpsuATlNocPH1ap7bLvwQcfxN13361eT17bntxAkEBfrsuHH36olocffrjUc+666y5s3rwZM2fOxB133IFvv/0Wd955Z5W/nz/++EMF5z169EBNyA0NuYEhQfvzzz+vbrzIdf/ss8/U+rLLLsOzzz6L3NxcdV2ys7PLvUbPnj3LDbsgIiLySxoREZGX++eff2QQtPbkk0+q7eLiYi0iIkJ7//331XbDhg21uXPnqp+zsrI0g8Gg3XbbbSXH5+XllXvNoUOHaq1bty7ZzszM1EJCQrTp06eXet7zzz+v6XQ6LSUlRW0fOHBAvf5TTz1V6nlbt27VjEZjqf2jR4/WEhMTS7ZXrlypPsf//ve/UscuWbKk3H45TvatWLGiZF9aWlq5c7zrrrvU+f31118l+06dOqXVq1dPHZ+cnFyyv3Pnztr5559f7lq899576rmDBw/WLBZLyf67775bfdaMjAytMjfddJNWv379Cl/X/hzEr7/+qvbL2kbOS/Z9/PHHJft27typ9un1em3t2rUl+3/66Se1X16/rPHjx2thYWGVni8REZE/YM88ERF5vU6dOqledttYeOk9lt5ZW7V6Wdt6Y2UsvdlsLjVeXlKzbaQXX1LCJZV7//79altER0erlH2pnm9fQE16hc8991xVHV8sWrRIpcrL+Gx5HdvSqFEj1VNf2XjtL774AjExMaqn3f5YSQ+PjIwsd6wMBxgwYEDJtqS/S4q5nLfNkiVL1DCA7t27l+yTVPMbb7yx2td5/PjxqofdRt5brqVkJ1Tm1KlTKmugpuQa2GdAyGeNjY1Vv3/prbex/Wx/HWzkPGQ4Rl5eXo3Ph4iIyJsZ6/oEiIiIqiIBpgTsK1asUIG0BO4y/l3GVAt57LXXXlM/24J6+2Be9knquAT6ZYM8CeYlwLal2n/11VfqefKa+/btw8aNG1WKus2ePXtUsC+BuyNBQUEVfg45Vt5Pzt2RtLS0Utu2Gwhlg1X78fUSaEswX5bt2lRH2fezBehlx/M74o4K8jIMwP5mgpDfjQyLKLuvovOynUfZ1yEiIvI3DOaJiMgnSHAuY7i3bt1aMl7eRn6Wcegyflx676UCvq2YnQTkF110kRorLuPbJTAMDg7GDz/8gP/7v/8rVTjvyiuvVIXXpHdeXlPWer1eVcy3kedLoPjjjz/CYDA47F2uiBwrgbyMaXdEet7tOXp9UVtTr7n6fpI14UzAX9XrVfT+1TkvOQ/5HdpnYxAREfkjBvNERORz881LMC9F52wkTV2KpUl1dCmSJ4XSbOQGgFRp/+abb0r1PDtKh5cK7lKATdLhJfCXFHtJNZebAzZt2rRRQaRMl9e+fftqfQY5VqqwS/E7dwWbUthPCuWV5WhfbfVWy40SuUFhn+Vgr2yhuuPHj6O2SBFDScsnIiLydxwzT0REPkGmhpPp2SRolB54+555CeSlirlUp5ex9PYp9rZeXfteXAk6Zeo2RyTV/siRI3jnnXfU2HzZtjdixAj1mo8//ni5nmHZlvHjFZFx9jIG/cknnyz3mMlkqrISviNSBV+GBfz9998l+06fPu2w919uVrjyHlWRNH/57DIkwZGyN04WL15caxkGmzZtKtU2iIiI/BV75omIyCdIanyvXr2wcuVKFbxLb7w9CeBk+jZhH8xffPHF6lhJoZdp4XJycjBv3jyV7n706NFy7yO9+lFRUbjnnntU0D5y5Mhyvesyj7tMAyfzp1999dXq+dIjLEGqFJGTYx2RontyDs8884wKvuXcZIy9jKWXbACZTk6mXKuO++67T815L0X1ZGo5CdjlRoRkIUhQb98bL9dMpumT85cx9XINBg0ahJqS6y2p9pJ14Oj15MaH3ICRoQ/Lly/Hzz//rPa///776trJjRp3kJsJ8pmHDRvmltcjIiLyZuyZJyIin2EL0m1p9fYkdV1IcNitW7dSFdEXLlyogloJst98800VcE+ZMsXhe0jv/1VXXaVSw2X+dkfF6h544AF8+eWXajy9BKryupLGL8G5HFsZef+3335bFbuTee/lpoAEuDfddFPJZ6gOqQEgPd+SWv7000+rYn2jR4/GLbfcUvJ5bB599FF1s0LmcL/++uvxxBNPwB3kZolUz5cbEo7ITYrvvvsOkydPVjdApJDhBRdcgK+//rrSTIbqkveXmxjuuEFBRETk7XQyP11dnwQRERG5l9QUeOutt1QmQkUF5NxJpomTsfNSGFAKDooFCxZg7NixKmuhZcuWtfr+UhdB3kNutFR0o4aIiMifsGeeiIjIx8m86vakt/vDDz9UmQyeCOSFpNCPGzcOzz77LOqC1ECQIQsTJkyok/cnIiLyNPbMExER+bju3burtHVJtZdK8fPnz1dF/H755RcMHDiwzs7Lkz3zREREgYYF8IiIiHycjIOXugAyFl9qA0hlfwno6zKQJyIiotrFnnkiIiIiIiIiH8Mx80REREREREQ+hsE8ERERERERkY9hME9ERERERETkYxjMExEREREREfkYBvNEREREREREPobBPBEREREREZGPYTBPRERERERE5GMYzBMREfkRnU6HCy64oEav8dtvv6nXeeyxx9x2XkREROReDOaJiMhpubm5ePrpp9GzZ09ERkYiJCQEzZo1w4ABA/Dggw9i3759pZ4vQaUEhbZFr9cjLi5OPX/BggXQNK3kuQcOHFDPueSSS6oMMidMmFBq/5gxY0q9j6NF3s9Gfi77eFhYGNq3b4+77roLx44dc/j+LVu2rPJ95HO4m7xvaGgo/Pkmwu7du9W179y5M6Kjo1Xbat68OUaNGoUvv/wSFovFredLRETk64x1fQJEROQbsrOzcd5552HLli1o27YtbrrpJtSvXx8nT57EunXr8Oyzz6JNmzZqKWv69Okq+Debzdi/fz8WLVqEVatWYePGjXj11Vfddo7jxo1TNxcc6d69e7l9F110kfpM4tSpU/jll1/w2muv4auvvsKmTZsQHx9f7hiDwYBHHnmkwnOIjY1FXdqxYwfCw8PhS2bPno37779fBezy+xgyZIj6DIcOHcKyZctUMH/LLbdg/vz5dX2qREREXoPBPBEROeXll19Wgfytt96Kt99+W/XE2ktOTkZhYaHDY++55x40atSoZHvr1q3o06cP5s6di2nTpqFVq1Zu+S3IuZ177rlOP3/w4MF44IEHSrYlmLzyyivxww8/qKD+8ccfL3eM0Wj06vTzjh07wpdIW5L2IdkHErRL1oc9k8mE999/HytXrqyzcyQiIvJGTLMnIiKnrFmzRq0nTZpULpAXEpA7G0h27doV559/vkqz37Bhg9f8BmQYgKTsC8kaqInVq1erwF8yAsre5KjssdpKd5f0/2uvvRb16tVTWRJy/VesWKFuTMgxMoTBEfn9SE95VFQUYmJiMHz48FJDCWxDH8Tvv/9e4dAGRzIyMnDvvfciODgY33//fblAXsh1koyLt956q9ywCkdDGhx9HvsaAH/88QcuvvhilUEh+1JSUtTvfdCgQQ7Psbi4GA0aNFAp//ap/kVFRXjppZfUOUdERKjrI8NHvvnmm0o/MxERkbswmCciIqdISr1tbLM7Obox4A0kiKyJ/v37q3T8zZs3qxRy+wD2xhtvVGPCP/nkE7WubYcPH0a/fv3w+eefq4yIyZMnqwBVgvQ///yzwuPWr1+PgQMHqmD79ttvxznnnKOGIEhGQ0FBgXqO9KjPnDlT/ZyYmKh+ti2OhjbYW7hwIbKystS4+KSkpEqf647rJIG8rY7D+PHj1c0NOWf5jHIjIjU1tdwxkqUhQzDkdyZBv5AbMEOHDlXDR+SGlNxskGEncmNg2LBhKquDiIiotjHNnoiInPKf//wHH330kUpllzHy0rt59tlnlwT51fHPP/+U9OJKgGhv7969FaaxV1Vc7p133sGSJUscPibp9FUVkZOe1/fee0/9bBtLX5akfVd0fjKUwL4434wZM9SY71deeUUFf5deeqkKiiXok57mTp06wRPksx89ehRPPfUUHnrooZL97777rgpEKyKB7KeffqqCXpubb74ZH374oQrqr7vuOhXMy/WQIQm2n50lGQqiol5xd1u6dKn6zGPHji21/7///a9qjx9//DHuu+++Uo/JZ7U9x+aJJ55Qvf3y+5XPbbshJXUl5LNIkD9ixAg0adLEI5+LiIgClEZEROSk2bNna5GRkVKCvmRp06aNNmnSJG337t3lnn/++eer50yfPl2bOXOm9sgjj2g33nijFhYWpvZPnjy55LnJycmlXrey5fbbby/1PqNHj67ymPT09JLnv/fee2rfRRddpM5Llrvuukvr1KmT2t+vXz8tJyen3OdJTEys9D26detW7pgDBw5osbGxWkJCgvb000+r540YMaJabU7eNyQkxKnnyuvLdbcpKChQx8r7y8/2LBaL1qFDB3XMr7/+WrJffpZ9AwcOLPf6tsemTZtW6fs645JLLlHHLVmypFrH2X7f0mbKkt9lRZ+nZ8+eDl8vIyNDCw0N1bp27Vpqv7QZuXbdu3cv2Wc2m7W4uDjV7uX6lfXNN9+o93r11Ver9ZmIiIiqiz3zRETkNClWd9ttt6neb0lZlvHUkqYtheyk0vhnn32Gq666ymG1ciE9mDLtmPTGS4+w9PKWJT3YFfWuS2/ohRdeWOm4/uoUwJPq9bKUTY+XfRWldct+W4q5MySN+80331S92NIrLtX2582bB0/ZtWuXSguXa172M8nvQ9Lv5TmOSOZFWbbZAmS4gK/p1auXw/1SC0DarQxDkGER3bp1U/u/+OILde3se+XlWqWnp6ted0cFEk+cOKHWO3furLXPQUREJBjMExFRtUihL0m5l0VkZmaqIPX1119XAbqMz5Yx1vYkxdu+mr23eOaZZ1QKuqTXSwq/pIhLWrXcsPjggw/c9j4yBZ7cxJDx4TfccIMqQucp8p4iISHB4eMNGzas8Fg554pqCcg0gzVlaxPSZjyhss8qAbsE8zKUxBbMS1uQqQjld2Zz+vTpkqEislQkNzfXredORERUFgvgERFRjUivphT8kh5omXNepp3zNVLYrHXr1moKNCmGZhsT7i4yR7oE1VJfQKb4+/vvv+EptoA8LS3N4ePHjx9HXZEsCFE2O6IqtkJ0Ur+gLLm55EqxxUsuuQTx8fGqKKHt5s6qVatUsT/7G1G26zly5EhV/K6ixVZ7gYiIqLYwmCciohqTIEmm5/KHzzFnzhy1fvDBB0tNReYqGYLw7bffqmrnP//8s9p3/fXXIy8vD57QoUMHlV4vU+2VnQZPgk7blIM1JQF2dXvrpYq9BMcyv3xVaen25x4XF1dhj/5ff/0FV0jGgQyFkNf89ddf8b///U9dH/m92ZOihXLOMsREpq0jIiKqKwzmiYjIKVJ9XaYqc0R6sXfs2KHm7u7SpYtPX1GZTu3qq69WwaUEdDWxbds23HPPParXX4YhyJzkUlFeXnvq1KnwBAnkJWiWHnjJCrAnQwncNbZbhg44mtqtMtJeXnjhBRWoX3755Q4zFuQGgWRM2M8SYBv7XnYee5nqTqrSu8o2Nl4yM2SRG1TDhw8vF/TfcccdakYC+d06Cujl915RJgQREZG7cMw8ERE55ccff1QBVdu2bVV6tBQAk3HB0hO6cuVK1TMrAasn5k13ZWo6KYwnqdTOkDnS5QaFTEEmvej2c85XNjWdkN7djh07qiJ5cqw8X6Y8k1oDQqYtkx56KYInxf4kXdsZEjSOGTOmwsfLBrZlawPIFHlSH0CC3R49eqhCbt999526JnLNbKnrrpIp2WTMudwIkdeXseZSVO6ss86q9DiZ712GIMi5yc0OGeYgx4eFhalecknBl7VMiWgjc7m3adNGfeZDhw6p58vNpOXLl+Oyyy5TU+q5Qm4SSCaD/L7kektw7yjjRArfbdq0SU05+P3336tzlpoEcp4yzESK6EnGQ0V1CoiIiNyBwTwRETnlueeeU0G8zNW9YsUKVdRONG3aFKNHj8Zdd93lsPq5J0lF/YpMmTLF6WBeCqDJPOGS/i291zLm3b6n2FEVc/uefQnmpddWemhnzZqFPn36lDwuKfzS0yxBrhTa6927N5o3b17lOUnKvxznSjAvry/B5f33369uJEhAL78r+VkqtldU7K46ZHiCkIBahhXI+Url+6qCeSHX6sorr1S1F+R4uSkjvfUSDEuALa8tvw8bCfTl5sTdd9+tgv21a9eqmzXSLuUGhavBvJAA/pFHHlE/l02xt5EbVnJzS9qbtA9pJ3K+UmAvKSlJ3fTq2rWry+dARETkDJ3MT+fUM4mIiMjvnHfeeSrQl8JxkZGRdX06REREVbrgggsqHVYlN1ydvYHvy9gzT0REFAAkk6Jx48al9sk0bKtXr8bFF1/MQJ6IiHzOyJEjHf7/JVmDgYDBPBERUQCQwoQytlzSwGU8uxSb++2339RY/hdffLGuT4+IiKjaXnzxRbRs2TJgrxyDeSIiogAg47hlLLtMqSaFC2VO9RtuuAEzZsxQY/yJiIjIt3DMPBEREREREfncmPnk5GT2zBMRERERERH5kvnz5+PUqVNqetX27dur6VFbtGiBQMGeeSIiIiIiIvL5avZBQUFq+JgsgYDBvIfIfLtHjhxRhYZkjmEiIiIiIiJvIzOXZ2dno0mTJqrH2xUFBQUoKipy6rmFhYVqsScxU0xMTIXHPProo6onvl+/fmqmlkOHDmHhwoWYNWsW8vPz8fLLL2PKlCnwdwzmPSQ1NRXNmzf31NsRERERERG5TALkZs2auRTItwoLw7EaXHuZbu7EiRMIDQ2t1nE///wzhg4ditjYWNWRGhYWBn/GavYeIneXbP8ooqOj4Um9evXC+vXrUVcyMjKQmJiIlJQU9Q+rrtT1deA5eMd1YHv0jt8Dz+EMtkm2B2/7d8E26R2/B56DFduj59tDVlaW6oS0xS/VJT3yEsgf0uvgTNRTqGmw75fPBpCUk6Nep7rB/MUXX4xzzjlHzdzy559/qnR8f8Zg3kNsqfUSyHs6mJf5hD39nmWHGNTVZ/em68Bz8I7rwPboHb8HnsMZbJNsD97274Jt0jt+DzwHK7bHumsPNR0aHG3QIdqF18jSNKDYGj+4ol27diqYP3r0KPwdg/kAMGnSpLo+Ba/gDdeB5+A916GuecM14Dl4z3XwBt5wHXgO3nMdvEFdX4e6fn+eg3dhe3CBQS93BKp/XA2D+fT0dLWOiIiAv+OYeQ+RdBUp4pCZmVnnd3nrIj0qLi5O/cOqyzR7IrZH8kb8G0nehm2SvAnbo+/FLSXHhxpd7pmPKTC59P4nTpxAq1atkJub6/KYf1/iWnlCqtFYl6SkJMydOzdgrmJISAimT5+u1kR1je2RvA3bJHkbtknyJmyPniPxicQpEq+4hVHn+lKJP/74A1999RXMZnOp/QcOHMDw4cNVIH/VVVf5fSAv2DPvIYHcMy9jndLS0pCQkODy9BZEbI/kr/g3krwN2yR5E7ZHH+6ZjwlxvWc+s7DC91+wYAHGjh2LRo0aoWfPnirzVwptb9y4UVXS79y5M5YvX65iD3/HMfNERERERETkXnqddamuKobL9+nTB3fccYeqVi/V/WUor4yP7969O/7zn/+ox/x9SjobBvNERERERETk/gJ4rgTzOq3Shzt16oTXX3/d9fPyI8x5JiIiIiIiIvIxXhfMX3DBBWpOw4qWJUuWODxOxk707t0bkZGRqFevHi677DJVHKEyq1evVs+T58txcvwHH3xQ6TGpqalqjEaTJk0QGhqK9u3bY+bMmWp8BhEREREREf3bM+/qQr6dZj9y5EgVYJfVtGnTcvumTp2KOXPmqLERF198sQqsly5dip9//hkLFy7E1VdfXe6YL7/8Etdee60qqjFw4EA0aNAAv/zyC0aPHo0tW7bgxRdfLHfM3r170bdvX5w8eRJdunTBgAEDsGHDBjzxxBPqWFlYsZ2IiIiIiAKewcUx8y4cEqi8NpiXYLply5ZVPm/ZsmUqkK9fvz7WrFmDdu3aqf3ys/TySy+6rO3nNz99+jRuueUWNZ2BBPUjRoxQ+48fP47zzjsPs2fPxhVXXKGOszdmzBgVyE+ePFm9pzCZTLjmmmuwePFiPPPMM3jsscfcfCWIiIiIiIh8TC2NmaczfD6H4aWXXlLrRx55pCSQF9KDPmHCBGRkZGD+/PmljnnnnXfUlAnDhg0rCeRFw4YN8fzzz6ufJaC3t27dOpWWL1Mc2J4jjEYj3njjDQQFBeGVV15RwT0RERERERECvWfe1YX8P5jPz89XcwiKUaNGlXvctu/bb78ttf/777+v8JjLL79cjYWXHn/7cfC2Y6688spyqfRyE0BS7mVahFWrVrnlsxERERERERH5XDAvvekTJ07EnXfeqXq8Dx48WO45u3btQmFhIeLj49GsWbNyj/fs2VOtZQy8vc2bN5d63F5wcLAaDy+B/O7du506prL3IiIiIiIiCjjSw27UO73MzSlCUmoWeh3Oqusz9xleO2Z+1qxZpbbvuecezJgxQy02tgDfUSAvIiIi1Fh56THPzs5GVFSUSq/PzMys9DjZL4XtUlJScNZZZzn1Xrb9cgwREREREVFAq2bK/KT6YWrJMlsQs/t0rZ6av/C6YF4qy996663o168fGjdujEOHDqmK9BLcP/roo4iOjsaUKVPUc3NyctQ6PDy8wteTgF7GzduCedsxlR0nxwg5xqaq93J0jCNyLlJB30ZS9v29Ar58Xk3TSn1uorrC9kjehm2SvA3bJHkTtsfaJ5nOsthI56dbcJq5wAvmZZo3ezKP+0MPPYRzzjkHQ4cOVdXix48fr6ah80WJiYmltqdPn66yDvz9j7BkQ0hAr9d77cgOChBsj+Rt2CbJ27BNkjdhe/TMLGJli3+7BYP5wAvmKyLzx0tAL+nvf/75p5o2zjYPfV5eXoXH5ebmqrX0ygv7uevlOOnpr+oY++Mqei9Hxzgiafj27xkoPfM6nU7VNmAwT3WN7ZG8DdskeRu2SfImbI+178knn1Qzg9n3zJftgCTv5DPBvJCp5ySYP3r0qNpu0aKFWqemplYYYEtae1xcXEmQLYF0TEyM6imW45KSksodZ3s9+0Ys7/XXX39V+F6OjnFExvA7uoHg7ySYl0CewTx5A7ZH8jZsk+Rt2CbJm7A91i7JeLbPenbb93WXp5nj1HTO8qmcZylkZz8+vUOHDqpX+8SJEzh8+HC552/atEmtbUXsbLp161bqcXvFxcXYtm2bmp5OUvydOaay9yIiIiIiIgo4tjR7VxZyis9cKQnYV65cWWoaOLmDNGjQIPXzF198Ue4YKZxnmxu+7Fzy9o/b++6779S0dIMHD1YBfdljZM56+wIR4vjx4+rcJAOgf//+8DW2oQOVDVcgIiIiIiJymv7fnvnqLnIc+V4w/8cff+Crr76C2Wwutf/AgQMYPny4Spu/6qqrSk0PN23aNLWWavd79uwp2b9mzRq89dZbKq193LhxpV5PquVLqvvXX3+NRYsWlexPS0vDfffdV1KYzl7v3r1VoC7Puf/++0v2m0wmTJw4UfXoT548GUFBQfAlEsCvX78eK1asUGsG9EREREREVGPsmQ+sMfO7d+/G2LFj0ahRI9X7LoG4FIzbuHGj6i3v3Lkz5s2bV+oY6UGXqermzJmD7t27Y8iQISgqKsLSpUtV9fT33ntPvY69evXq4d1338U111yDUaNGqWJ69evXx7Jly9QYe7lBIPvKktfq27eveq/ly5er8fYSAO/fv19Npffggw/C18hUezIOSYqLyPiYyqb5IyIiIiIiIu/gVT3zffr0wR133IEmTZqoIPnzzz9X49clSJfpEmRfQkJCueNefvllFWh36tRJBfHSKy9BvvQ2X3311Q7fa+TIkepxme5OCtv98MMPaNu2LRYsWFDh1AxSgE+eO2bMGJX2v3jxYhUAz5gxA7/88otPVqWXnnjblHGyZs88ERERERHVmCsp9i4XzQtMOk0iOKp1MsWDrYq+t1WzlwBeeuRt6xLZGUBU6awGV0ivvwxPkBsxrGZPdY3tkbwN2yR5G7ZJ8iZsj74Xt5QcPyAR0cbq9x1nmSyIWZnilXGTt/GqNHuqG7YAvlyKfU6mW4J5IiIiIiIKMK72smvsmXcWg3kiIiIiIiJyL1enmWPeuG+OmSciIiIiIiKiqjGY97BevXqpKvhz58719FsTEREREVEZWZbS02IHKolPJE6ReMV988zrnV7mHspC0uqD6LX2kHvePwAwzd7DpCI/CzkQEREREXmHLM2MaBgQ6CZNmqQWWwE7T4+Zn9QmTi1ZxWbELNlb8/cPAOyZJ4dsU9RxqjoiIiIi8leFmgUHTIVqTW5WjV75cgs5hT3zVI4E8JJBoMvJhBYZo1JtylW6JyIiIiLyYRLAT81IwX5TAVobQ/FybCJCdAwk67yavYXV7J3F1krlSOCuM5thyTil1gzkiYiIiMjfpJgKkWwuhAlQa9km8iXsmady8jLSof26GPqMk9BiGyCvZw+Ex8bxShERERGR30g0hqCVIUT1zMtatsmNXE2Zt3BuOmcxmKdywk8fQ6+DmxBelIe8rHC1DQbzRERERORHJKVeUuvXF+WiV3AEU+zdjWn2tY5p9lRe01YIb5oIGIzWddNWvEpERERE5JcBfUtjCAP52qB3sfidHEdOYc88lRcSCsx8F9j8B9Ctn3WbiIiIiIiotnvmXTkmQPG2BzkmAXzzNgzkiYiIiMivRadn1vUpELmEwTwREREREQWs6AwXg/n00+4+Ff/CeeZrHYN5UrIsZl4JIiIiIiJnZaTzWjmTZu/KQk5hMO9hvXr1QlJSEubOnQtvkqUxmCciIiIiClQSn0icIvGKW7BnvtaxAJ6HrV+/HtHR0fAmhZoFB0yFiNcbWcmTiIiIiCgATZo0SS1ZWVmIiYmp+QuqXnYX+o4Nlpq/d4BgMB/gJJC/OzMFyaYCtDKG4v9iEhnQExEREREReTkG8wHuoLkQB8yFMAFqLdvtjGF1fVpERERERG6Vl5eH8PDwkjXVMr3Oujhp7pZjmLvlOMyaVqun5U8YzAe4FoYQtDSEqJ55Wcs2EREREZE/kQBehrvqdDpomqbGhTOgr2V6fbXS7Cf1aKKWrEITYt5YV6un5i8YzAe4EJ1epdavP7QXvSKiS6fYR7phrAwRERERUR2TwF0CeYvFAr1ez0DeE1ytTM9q9k5jNXtSAXxLix4h6WWm14iK5dUhIiIiIr/omZceeQnkZS3bVMtYzb7WsWeeiIiIiIj8vmfellrvtjHzWVnuODUilzGYJyWadSaIiIiIyI/ZAni3jZXPznTP6/grptnXOgbzpERDxrMwoiciIiIiIjcVwJPFlePIKbxSRERERERE1ZGfDyTvs66p8p55VxZiME9ERERERFRpUL59e/WCcnnuNVcAjz1kXdc0oM8oU4Ta36amq+7CnnmnsWeeiIiIiIgCjwThQwYD/73JunY2KN+7G9i1EzCbrWvZrolMPw3mqdYxmPcwqaKZlJSEuXPnwquwGicRERERBZKdO4F//gFMJutatp3Rtj3QoSNgMFjXsu0HJD6ROEXiFbdgmn2tYwE8D1u/fj2io6PhVeQu5JZNQM8+dX0mRERERESe0bEj0LkzsHWrdS3bzggLAz7/Dlj4MTDqBuu2LV0+Ng6+atKkSWrJyspCTExMzV+QBfBqHYP5QGcb87N9G9C6LfDNsjN/kIiIiIiI/JV85126DFi6FBgypHrfgeW5rdqUPibTt4N5t+PUdLWOafaBzjbmR9KLdu4Ctm2p6zMiIiIiIvIMCcaTktiZVWvBvCtF8FjN3lkM5gOdjPFp2w44kQOkZQFTpnKKDSIiIiIiIi/HNPtAJ3cjH30W+H2QtTXs2GEt/tGjR12fGRERERER+Sq9zro4ae6qA5i7+iDMFq1WT8ufsGeegG7dgBbNAaOxesU/iIiIiIh8XUZG9Y8pyAcO7Leu7R075LbT8nnVTK+fdH5rbH/oAqy/57y6PnOfwZ55svbOP/wgEF2v+sU/iIiIiIh8WVZm9Z4vAfz1w4Cd24AvPwU++RoI/ff784nDQKPmtXKaPkdXvZ75UseRU9gzT1bBwSz+QURERESBJye7es/fuwfYIwWkzda1bFN5LhW/+3chp/BKERERERFR4MquZjAvxaPbdQSMButatm3ychwfI9PWVdTLv3lj+XR9IicwmCfrH4/Dh4DCAl4NIiIiIqLKSEq9pNY/PKt0ir3Iz3V8TFaG4+/go4cDM6ZZ1/4W0NsK4LmykFM4Zj7Q2cb8bN8K/Pw9sPin0n+QiIiIiIioNPm+3LJ1zb437/83Xd/8b7q+bCed5T9X2tWUeabZO4098x7Wq1cvJCUlYe7cufAKe+3+iKTs55gfIiIiIiJXOsj27gKKipw/pvW/6fqGf9P1ZbsOSXwicYrEK27Bnvlax555D1u/fj2io6PhNWxjfqRnPrF16TE/RERERETkWHRM6XT53TuARg2BgVc412Mvz3l/MfDVZ8DV19Z5duykSZPUkpWVhZiYfz+bD/TMnzp1Cp06dcKJEyfQpk0b7N27F4GCPfOBTv5ovPspMOxa4KmX6vyPCBERERGRTwXztnR5kwk4csS67Sz57i0davwO7rLp06fj5MmTCEQM5gPd8SPAtcOBjz4Apk4C8vOB3GrOtUlERERE5Kuiomp2vC1dPsgINGsINOM8855Ks//ll1/w/vvv47bbbkMgYjAf6Db/BezcYR0zv38fsGcXkJtV12dFREREROQZNR0CK73q8z4Bzu0ERJmBZ+7gLFFC7+Ic83KcE/Lz83H77bercf733HMPApHXB/MyBiIhIQE6nQ5t27at9LkLFixA7969ERkZiXr16uGyyy7DH3/8Uekxq1evVs+T58txcvwHH3xQ6TGpqakYO3YsmjRpgtDQULRv3x4zZ85EQYEPTu3WqjXQsRNgMAKt2wDtOlT83IwK5sckIiIiIvJVWW7oyDqWApw8DJiKgX3/ACk73XFmvq2We+Yff/xx7N+/H2+++SaCgoIQiPT+MgZi6tSpKsDetm0bBg8erILypUuXYuDAgfjqq68cHvPll1/i/PPPx5IlS3DWWWfhkksuwZ49ezB69OgK7+5IQYUePXqoGwf169fHsGHDYDab8cQTT6j3LSwshE8JDQW+XgI8/Rzw+nwgrJIx85kM5omIiIjIz2Rn1/w1JACVGNSiWdecK93aw+7qUoUtW7Zg9uzZKv4bMGAAApVXB/POjoFYtmwZ5syZo4LrzZs3q+BdAvQVK1bAYDCoX3JGRkapY06fPo1bbrlFBeILFy7Eb7/9ptY7d+5UGQDSOGRfWWPGjFE3FyZPnoytW7fis88+w65duzB8+HDVy//MM8/A50gAL73yTZrU9ZkQEREREXmO1Is6dNC6romGidaJwswWQB/87zbOVLvfv9u6pnIKi83Iyis+s+QXV3qVLBYLbr31VsTGxuL5558P6CvqtcF8dcZAvPTSS2r9yCOPoF27M1Or9e3bFxMmTFCB/Pz580sd884776hpF6RnfcSIESX7GzZsWNIoJKC3t27dOhWwS9q/fcMxGo144403VHrHK6+8ApNUsvRF9erV9RkQEREREXmGBPCXDQFefNa6rklAn3YEsEh0ZbSuZVtIAD/xWuDRu6zrsgG9bB9M9s9A3yCLrsrlma//QczYz0uW5hMXV/qyr776qpru+4UXXlCduYHMa4N5Z8dASNC/fPly9fOoUaPKPW7b9+2335ba//3331d4zOWXX67GwkuPv/04eNsxV155JUJCQkodIzcBJMUjPT0dq1atquanJSIiIiIij9q6Gfh7E1BUZF3LdnXExp35uVlroHEiYDAALdpZt0XKPiB5N2A2WdeybSMB/LiRwIszrWt/C+idTKl/cNRZyPzoupLl0NsjK3zJgwcPqg5cGSo9ZswYBDqvDOarMwZCUtxlnHp8fDyaNWtW7vGePXuWvKY9Sce3f9xecHAwunTpogL53bt3O3VMZe/ls3I4RR0RERER+amyddacnxGtfDAfEoq88Y8B19yOvIffUNtKYhugVXtrsWlZy7bte3byXmDfLuusUrKWbX/iZLG7kBAjoiND7JbgCl9y0qRJKCoqUh2+pAZ2eJfqjoGQuzPCUSAvIiIi1GtJj3l2djaioqJUen1mZmalx8n+DRs2ICUlRRXHc+a9bPvlmIpIyr98Rhvp4S/by+9RmiYX/czafl92BhBuN++m/XOqQT6vpmmlPjdRXWF7JG/DNknehm2SAqY9JnWF7pyzga1bgK5nQUvq6tJ3XZGXl4cN+5KhyzNA+3szzjnnHISHhwPBIcBrnwLrVgC9B1q35T0kmE9sDV2bDsDu7UCbDtASW7v8/jUhHaP2RbwlVnILWyq9K8dV4LvvvlOxnQyltmfLpj58+DAuuOAC9fOnn36KRo0awZ95XTBvGwPx3nvvOTUGIicnR63VP5YKSEAvQbQtmLcdU9lxcoyQY5x9L0fHlJWYmFiuWn+dzouYmQ0EpwFBIUBaGlBcCGPyVpiKNCAnC9ClnXluVrb1OdUkf3zl5on8IdY7OW8kUW1heyRvwzZJ3oZtkgKqPc77EMYvPoXpP9dZq9rXoLJ9XmERLGYN+rw8FTfYxxyo39g6BZ4tUM6QjsVg4OnXYVy3Cqbe51m/a8viYS+++GK5WmHeTOK633//3eFjEtTbHvPJacN9OZgPhDEQ0msfHR3tHT3zMi5n599Am7Yy6B+IjYbu/yYCR/YBTdpAu/EhICHB7vm5pber8UdYp9OpoRAM5qmusT2St2GbJG/DNkkB1x6bNAVatKjRS0jPfHhIMHR5Omjh4YiMjCzdAViUV+Z7dJHddj+gec3evyaefPJJFYPZ98yX7YB0iZPTzDk8rgJyU8eRAwcOoFWrVmjTpo2aSjxQeFUw78oYCPmHYvsHVJHc3Fy1ll55+2Nsx9kH1xUd48x7OTqmLEkLcfR+Hqcqa14H7N0BtO0E3P8ckHYQOJpsHbdzNBm6U0eAFu3PPH/fbqBREyC0krnoKyB/hOUPMIN58gZsj+Rt2CbJ27BNUsC1xxq+tsQJvTt2RPhRPfJ69y6fyavTlX4P++2yj3lYWFiYWmzcdZ0tOh0sMi7ehePIB4N5V8ZAtPj3LlpqamqFAbakYsTFxZUE2RJMx8TEqJQdOU6mvyvL9nr2d6Xkvf76668K38vRMV7rwF5g/y5AptGT9ZEUYMCFQJPWwOG91nVo9JlAfvRwYPcOoH0n4P3FLgX0RERERET+KrxhI+Do7kqH/wYSi16vFleOIx8M5l0ZA9GhQweVpn7ixAkV7Ddt2rTUMZs2bVJrWxE7m27dumHFihXq8bLBfHFxMbZt26amp2vfvn2pY77++uuS1yyrovfySi3bAq2l4MY267pzNyA4FJj2BrD9TyCpD7DjL+tz9+8B9uy0Bv6ylu0kH/iMRERERESeItXtw6w1tEiCchd75l04JlB51W0PGQPhaElOTlaPyxgI276WLVuqfZISMmjQIPXzF198Ue41Fy5cWDI3fNm55O0fL5shIDcLBg8erAL6ssfInPX2FR/F8ePHsXLlSpUB0L9/f3g96Vl/83Ng7GTrWtLnhQT00isva5vW7YB2HQGj0bqWbSIiIiIiKq2+f1dP91YtW7ZUMWIgjZf3umDeVdOmTVPrWbNmYc+ePSX716xZg7feekul7o8bN67UMTL9naTbS0/7okWLSvanpaXhvvvuK6k0b693794qUJfn3H///SX7TSYTJk6cqHr0J0+ejKCgIPgECegbN3OcMl9UABw/aF3L45Ja/+KbTLEnIiIiIqqI/bTOAc5s0Lu8kHP84kpJD/qUKVNw6tQpdO/eHVdffTUuu+wyDBw4UAXaMs2dBPT26tWrh3fffVcVeBg1apTq3f/Pf/6j0vbljo7cILCNz7dnmzJvzpw5Kp3+uuuuU8fIDYF+/frhwQcfhM8rKgSeuhX4eLZ1bQvo23bgWHkiIiIi8h/5+VIK3bp2h6iYqp8j362P7LeuAyDN3pWFAiiYFy+//LIKtDt16oSlS5eqXnkJ8mVcvAT3jowcOVI9PnToUFXY7ocffkDbtm2xYMGCCudabNeunXquTJ0n4/QXL16sbgjMmDEDv/zyS91NM+dOaalA6j7AYrauj1iHORARERER+Q0J4GW47lNPW9fuCOijSncgliMB/AsTgHkPW9d+HNBrer3LC/loAbzKxkBURQLs6s5PL2nzP/74Y7WOad68ubpx4LcSmgHN2gApu63rJq3q+oyIiIiIiNxr505g+3bAZLauZbtHj9q5ytH/BvlHD1h75c0m61q2dX7QGegAC+D5QDAvheJk7ke/6JEmq+AQ4OF3gN++Bi4YVroYHhERERGRP+jYEZBZrTb/bV3Ldm2JibOuG7e0FptO3WNdy7a7Uvwp4FQ7mP/tt99U0bjVq1dj+/btyP+38cl8ipLiLuPGJa3d0Xhz8jKFUuTusHUdUiZgl0SI7FzrmoiIiIjI34SFAcuXA2++AUy4w7pd26ST7N43gdXfA/0vt277acdZdXvm5325BfO/3AKzhQGIW4N5qdIuVeFfeuklHDhwQBWP69mzJ2666SY1FZukwKenp6sp5D766CO88sorSExMVNXgb7/9dt+p7h5IJIC/6xpg1z/An8uBVz8/E9Abg4H7/wvs3wGs/BF47sPywT4RERERka+TAH7gQM8E8jYSvDds7rdBfOlg3vnx7+P+010tWbmFaHXRm7V6bgEVzEtRuKKiIowePRrXXHONCuQrs3HjRjXn+9NPP40XX3xR3QAgq169esFgMGDSpElqqTO7/5FfFFBssq5lu+vZ1sdOnwQO7rUWwJP1oX1A2878FRIRERGR/4mpomhdgJg7d65azGazW15P07lWmV6OIzcG8w899JAqLOfsuPizzz5bLU888YR/F4pzwfr169X89nVO0lfMmjWNXtb26SzN2wAt2lp75mUt20RERERE5LdsnY1ZWVmIiXFiir0qmHV6tbhyHDnHqSslqfKuFLgLDg5Wx5IX6tAZSOomvyTrWrZtJKVeUuuvnVA6xd5WuIOIiIiIiJx3JIVXi9zOpdsen332mapiTz4sNAx4dxFw+93WtWzbkwC+YdPSY+VjGcwTEREREVXbscMBd9FsBfBcWagWg/nrr78ejRo1wrhx4/Drr7+68hLkDSSAb9K8fCBPRERERERUAwzmvTSYX7VqFW688UZ8++23GDx4MFq0aIEHHngA27Ztc/8ZUt0Ji+DVJyIiIiJyp6IC4MQh69qPaXq9yws5x6UrJXPJS6XDI0eOqDnn+/fvj9deew3dunVD9+7dMXv2bBw9etSVlyZvmrpOqtrLmoiIiIiIak4C+JcnAl/Osa79OKBnz3ztq9FtD6PRiCuuuAKffPIJjh07hgULFqB+/fq47777VG/9kCFD1LzzMq0d+RAJ4KffCLz+lHXNgJ6IiIiIqOaOpwBHkwHNbF3LNpGL3JbDICn269atw9atW6FpGjp27IhTp07h5ptvRps2bVRqPnmZgnzgWKp1be/gPuDAHsBisq5lm4iIiIiIaqZhItC4FaA3WNey7acser3LC7lxnvmK7N69G//73//w8ccfY//+/WjQoAFuuOEGFcD37NlTPWfDhg2qUN6ECRM4pt6bSAB/13XA7n+AP38DXv30TCG8Fm2Alu2AfTuta9kmIiIiIqKaCQ4Fpr4O7PgT6NTHuu2nLDqdWlw5jmoxmJ8zZ44K4jdu3Kjmn7/yyivx8ssv45JLLoHBYCj13HPOOQfTpk1TAT15kZR9wP7dgMViXct2hy7Wx2Q6utn/A1YuAQZcUnp6un9pxbnQBbFAHhERERFRtUgA37i1XwfywtVp5jw1NV1GRgYWL16MlStXIiUlBXl5eYiPj0ePHj0wdOhQVSfO27mUw3D33XerIP7NN99Uhe5k3vnLL7+8XCBvH9DPmDGjpudK7pTYBmjdHjAYrWvZticBfKfuDgN5oZly+fsgIiIiIqpKVgbw9xrrOoBoLqbY13Y1+yNHjuDWW29F48aNMWvWLOTn56si7hdddBGaNWumpl6X2m9JSUkqzvW7nvl9+/ahVatWTj+/c+fOaiGgV69e6qbHpEmT1FJnJKVeUuvXrQB6D+Rc80REREQUmOrVq73XlgD+hgFAXi6waAHw8UogOhbeSGYrk8VsNsOf9ejRA6NHj1ZZ5hKwOyIB/ldffaWyzw8dOoR77rkHfhPMVyeQp9LWr1+P6Oho77gsEtC3as9AnoiIiIgCV20G8xtWWAN5IWvZHnQVvJGtszErKwsxMTE1fj0zdDBXY/z7xx+tV4tFhgHXou3bt6sZ2CoTFhaG66+/Xi1S1N1bOR3Mv/TSS9V6Yel9lqBV7nb06dPHlXMjb5GXBYR7yQ0IIiIiIiJfcc5AIDzCGsjLWrYDhHXMvPMp89fd3EctOdkFOLf7s7V2XvWrCORr+nyvDOZdTS3Q6XRqmrpvvvlGTVFHvh/Ma+YiWHKPQhccC50huE5PjYiIiIjIa0lKvaTWvzsbuGW616bY1wZNp1OLK8d50pEjR9Q06mlpaeWyAiZPngxv5nQwn5ycXK0Xlrnms7Oz1dzzciNALsT333/vyjmSF5FAvmDzHFhyD0Mf0RSh3aYwoCciIiIi75abCUTUPHXcJRLAd+oRUIG8L1SzFwsWLMDtt9+O4OBg1QMvHdE28rPfBPOJiYkuvUHXrl1x/PhxPPPMMy4dT97FkncclryjgGZRa9k2RDWv69MiIiIiIqo807SugnnyWjNmzMCjjz6KBx98EPparqJfG2rljN9++21ceumlJduDBg3CqFGjauOtyMP04Q2hD28M6PRqLdtERERERFQNEf5fj8qi07u8eEpeXh6uu+46nwzkXa5mL8F5Zen1W7duhclkKtl37rnnqoV8TFT5VCAZIy+p9eb0HTDEdWKKPRERERH5DK04F7qgiLo+jYDIEvCFNPtx48bhiy++wAMPPICACealMID9eAJbEC/p9Hv27FFV7P/3v/+56xyprsi4nuJC4FgyEBMPBIWUBPT6iMYM5ImIiIjIp2imPO8I5gOARadTiyvHecozzzyDK664AkuWLFHDw4OCgmo0o5tPBPO//fZbhY/9888/uPjii9V86pdffnlNzo08obJCHBLIvzkZOLofaNwamPBKSUBPRERERERUEZmWzuxC+np1prNzRzD/008/oUOHDmq7bAE8b+dSMF+Zzp07484771R3MR577DF3vzy5W0xcxY+lpVh75S1m61q2m7bn74CIiIiIiHze7Nmz8e6772LMmDHwRbVy2yMmJgbFxcW18dLkSQmJQKNWgN5gXcs2EREREZEvKSoAjiZb13WhUN4/1boOwDR7VxZPCQkJQf/+/eGr3N4zX1RUpMbL33jjje5+afI0SamX1Ppd64AOvZliT0RERES+RQL4V+4EjuwDmrQBxj8GhHnw/SWAn3w9sHc7sOZX4JVPgJBQBAJfGDM/ZcoUvPrqq3jllVcQMMH8Lbfc4nB/dnY21qxZg4yMDLRp06bU82TMwfz58xHoevXqBYPBgEmTJqnFK+VmnqmwKQG99MrLH0K78fI6IwuHEBEREZGXO35m2KiWdgCWw1ugi0jwXCHnlL1A8m6pIG5dy3b7LvBGc+fOVYvZbHbL62l6vVpcOc5T1q1bh+XLl+O7775Tw8XLFsBbtGgR/C6Ylw9cUUEAuQDx8fFYuXJlqf2+UEDAE6QwoFT792p5WeWnyyizj1VAiYiIiMjrNbQOG9WO7Uf+Be1hOb0M+q3bEdZ1smcC+sS2QKv2wP6d1rVseylbZ3lIUG0AAG4gSURBVGNWVpYaNh0IPfOxsbEYMWIEfJVLwfyBAwfcfyZERERERETuFBwKTH4Nln9+giV/heqht+QdgyX/OAyRzWv/WktKvaTWr1sB9B4YMCn2vuK9996DL/NcDgMREREREZGnBYdC36Qr9OGNAZ0e+vBG0Ic19Nz7SwAvvfIBFshXt+jdl++uxs39n8ftQ16u61PH7t27cdVVV8EveuZlHHzfvn1deoOaHEtERERERFRTOn2QSq03Z+yEIbaj58bMBzALqpdmP+zWAWrJzSrAVa0ehCe0atXK4XDw9PR0BAcH+0cwP2jQIJx77rm44447cMUVVyA8PLzS5+fk5OCbb77Bm2++iQ0bNiAvL89d50tERERERFRtEsBL7zwDec+w6PRqceU4T5k6dWqpbSn+t2/fPnz00UeqGKBfBPOSZvDEE0/gv//9rypw16dPH/Ts2VPdyYiLi4OmaeruRXJysgrepSqgyWTCzTffrKapIx8nVexTdgAx8dZxR0RERERERJWw6FwrZifHeXJquoo6s2fOnIlRo0bB54P55s2bY968eXjmmWfw4Ycf4uuvv8brr7+O/Pz8Us8LCwvDOeecg1mzZqnAX6rakw/LyQSCQ4B59wPHDljn5rzzVQb0RERERETkt3r27In9+/fDr6rZN2jQAHfffbdapOf94MGDOHXqlHqsfv36aNGiBYxGlwrkk7eQ+eSPJlt74WW++fR8ayBvMQNH91vn6mzeoa7PkoiIiIiIvJhFr4NZ70LPvAvHuJtkl3t7r7xwOfKWoL1169ZqIT8K5F+5Eziyz9oLf90D1rk5GzQBTh4BGre2bhMRERER+RIPzl1OvjNmvkePHuUK4B0/fhzHjh1Dly5dVA+9zaZNm+Bt2I1OZ0iv+7Fkay+8rE8eBpq1Ba6eBBQVAx17M8WeiIiIiHxLXhbwb7ymM1ZeyJvcR9Pp1OLKcZ5y9dVXw5cxmKczpNe9UStrz7ysGzT9t5UEA/WbMZAnIiIiIt+Tn13yoy4ook5PJeCmprPdRanmcZ4yc+ZM+DLP5TCQ0qtXLyQlJXnnVAdSqX7ya8CYx63roGCguBA4fRgwFdX12RERERER+aboWHg7iU8kTpF4xZ/l5ubW6vM9icG8h61fvx7bt2/HpEmT4JUkoG/cyrqWAH7BdODnN4CvnrUG9kRERERE5HfBvMQnEqdIvOIOMi2dq0ttatu2LZ599lkcPXq0wufI1OtLly7FpZdeildeeQXeimn2VLH0o0BaMmAyASdTgZMHgcbteMWIiIiIiMgnC+D99ttveOihh/DYY4+hW7duamr1Jk2aIDQ0FOnp6eqGxpo1a1TB9wcffBC33347/CqYf+6553DTTTehadN/x1STf1a2z8kGTGagqAgI1gMxDev6rIiIiIiIqqe4yDpsNDoeCArh1fMQV3vZa7tnvkOHDvjyyy/VNOtffPEFVq5ciT/++AP5+flqKnapcD9v3jzVK28wGODNXArmH374YbUMHDgQ//3vf9UcfFFRUe4/O6obkk7/3O3A0T1AbDCgl2aiAzKOAeHR/K0QERERkdfQinMrLmwn32u/eAo4lQo0bAXc+jIDeg8x63RqceU4T2jRogWmT5+uFl/lUg5DSkoKnnnmGZw+fRrjxo1Do0aNcN111+H777+H2Wyu0Qm99NJLGDFiBNq1a4eYmBiEhIQgMTERN998M7Zu3VrhcQsWLEDv3r0RGRmJevXq4bLLLlN3WCqzevVq9Tx5vhwnx3/wwQeVHpOamoqxY8eWpGK0b99eVUEsKCiA30hLBQ7vA4rMQLEF0Outf/ziOcc8EREREXmZ4koKlB3dax0qajEBaQeAEymePDMi7wvmJb3+3nvvxd9//40tW7Zg8uTJWLt2La688ko0btwYd911F/7880+XTujpp5/Gjz/+qALsiy66CJdffrkKmj/88EOcffbZ+O6778odM3XqVBVgb9u2DYMHD1ZBuRQskMyBr776yuH7SGrF+eefjyVLluCss87CJZdcgj179mD06NG45557HB6zd+9elXYhNw7q16+PYcOGqZsXTzzxhHrfwkI/KRCX0Axo2gaQtJKoRGDo7byLSURERES+RXrlf5wLmIsB6XCUjil2TnlMdYveLXnrV0zvMQMPnzfLcyfp43SalOpzExlv8PLLL5cE0G3atFE96uPHj0dCQoJTryG95RK0SwBv7/XXX1cVFhs2bKh6x6UggVi2bBmGDBmigmspVCA9+kJ+vuCCCxAeHo7k5GTExp6pICkZBa1atUJWVpYK6iUTQBw/fhznnXeeCtp//fVXdbw9eUzOT25ezJkzR+0zmUy45pprsHjxYtVDL4UUHJH3kkyDzMxMREd7eap6bqY1/WjbWqDLucDe9UDSgFJP0XLToItw7ndqsViQlpam2oBeevmJ6hDbI3kbtknyNmyT5GvtUctLgy7cwfdSGTL63t3WMfOSuj32JaB559o/aR9X07jFdvzbaa8jPDqs2sfnZeVjfMJE34ib6phbIitJMf/000/x/PPP49tvv1WFAqRgQJcuXfDkk0+qoF6CXWf079+/XCAvJk6cqF5HAm6pMGifli8eeeSRkkBe9O3bFxMmTEBGRgbmz59f6rXeeecd1cikZ90WyAu5USCfQcyePbvUMevWrVOBvPwhsT1HyE2FN954A0FBQWraAgnufV5EjHVquqatrevCvPLPyT1RF2dGREREROScBi2A+JaA3mDtkW/UllfOk3Q6aC4s6sYL1W4wLx36P//8s0pLlyD4hhtuwJEjR1SgKz3nkg6/aNEiHDhwQPW0u6OwgATMIjg4WK2l4uDy5cvVz1KEryzbPrnBYE/G9ld0jC2tX3r87cfB246RoQQyjt+efP4BAwaoqQxWrVpV489JREREREROKqpgzLxkmo6ZDZx/AzDiARa+8zBvnWfen7hUzf7uu+/GZ599pnrJZYy89IBLOn3nzuXTVuTxW2+9VT1eEzJmfteuXar33dYDL9syTj0+Ph7NmjUrd0zPnj3VWsb129u8eXOpx+3JjQLJKNiwYQN2796txtNXdYxtv9xYkPcqm57v80LC6/oMiIiIiIjK0cxF0DJTgKim0BmsHX7lAvq4RoDRwWNEgMrklixsGc4hwzrs1TSG9cpgXubdGz58uPpwUvhNV8XdExlr/t5771XrPV544QX8888/yM3NxY4dO9TPUkH+k08+KZnvT+YGFI4CeREREaHGykuPeXZ2tpo+T9LrZfxFZcfJfgnmpWq/LZiv6r1s++WYqhqLfSORXv6yPf1eQ8opyLkGh1nXIj8bCItSmRm6Mo29IvJ55fll/3EQ1QW2R/I2bJPkbdgmyVfaowrkN7wI5B4Djq6B7uy7HQf08p02LxuIc/K7aEE2EBo4025L56h9IW+Jl9zBAp1aXDnOU7799lvceOONyMnJUePz7eNa+dkvg3npkZdA2VktW7ZUS3X89NNP+OWXX0q2ZXo6mTZOUvZt5KILKXJXETlPCaBtwbztmMqOs302OcbZ93J0jCPyOezJ8IOKqufXuYwswJQK4/EjMIUmWO9o5pwGwiJhOH4AZlM04OgPZhnyx1duoMgfYhbAo7rG9kjehm2SvA3bJPlKezTkH0VMzjGZmRzIOYLM1B0whzUu/QKmIhjTjsJUaASC4px7U/m+G1kPgeLFF18sVy/MHawp89Uf1e3JNPvp06fjlltuUTOqVRZT+lUw37VrV1W1/qqrrnL4uIyXl4rv+/fvd/nEZMy6kEBc5peX6d9kKrlZs2bh4Ycfhq+Snnv7qoxe3TNvyoZu6YvAiWRgdytoNzwHGAqg+2sekHkQOPkntAserjJtSf4Iy50tGQ7BYJ7qGtsjeRu2SfI2bJPkK+1RM8dCO5IA5KcBkU1Qr1mn0j3zxYXQff4gkLYfiG4I7axXnBs3H2IGYpybtckfSMFyKSZu3zNftgPSX3vmDx8+rOJWXwzkXQ7mpaidfQ93WfJYVenmzpI0eSku98MPP6gK9TNmzMDFF1+MXr16ITIyUj0nL89BtfV/SZq+kF55YTvGdpyj6Q7KHmN/XEXv5eiYij6Pz0yxkHkMOJkCWMxqrUs/DC3/BJCeDGgWtdZlHYKuwZlZBCoif4TlDzCDefIGbI/kbdgmyduwTZJPtEd9KLSkMdCy9kPXrF/5FPuMw8CpFIn6gew06GS7oRMV7aVnOICmUw4LC1OLjbu+r7tazM6ZY2RGs1WrVqlOXxnrLoXLGzVqpDp/7733XtX57IyhQ4eq4dWtW7dGwATzorJx8uvXry81r7s7SCX7a6+9Fhs3blRjGySYb9GihXpMqudXFGBLz35cXFxJkC2BtG3eRDkuKSmp3HG217O/IyXv9ddff1X4Xo6O8Xmxja3TeKQlW9f1m0M7mAoY9NCZLdAMeuvPdX2eRERERBSQdJrqvnf8fTQ6AeoB6ZgyBFm3yS9IWnxubq6qb2YL3KXGmhRNlynTZVa1K664wuGx33zzTamZzCT4l6nP5XVss6fZVJSJ7nPB/Jw5c9RiC+SnTp3qMN1dgmQJoGWqOndr0KCBWp84YZ3jvEOHDipFXbYlRaJp06alnr9p0ya1thWxs+nWrRtWrFihHi8bzBcXF2Pbtm1qerr27duXOubrr78uec2yKnovnxYTD9z4ArB/I9D6bJWWpDNEwNSskzXNPqYFjNHNgcIcIORMxkNNaMW50AU5X4+BiIiIiAKUuQjY+Ja1AN6BlcDAB0vXc8o+AQQbAV0IYDBat8N8JEPWD5ihU4srx1VF4rKzzz5bxWz2Xn/9dUyaNEnNpiadrUZj+XD36quvLrdPhnSXJTGv2WyGN3M6hyIhIUFNPSeLFKCQwNm2bVtkSjdJgX/uuefw1ltvuf1kf//9d7Vu06aNWks6yKBBg9TPX3zxRbnnL1y4sGRueHtyB8b+8bLj/SVNQ6r02zcO2zGSFWBf7dFWEHDlypUqA6B///7wG5Ex1nFF0isvaxl3lJkGY/c7Yeh4DYy9plvTmYoqHnJRHVKR1Jy1T62JiIiIiCqVngLkHLXOupSVCmQfKf14vWZA/UTAGATENrFuk1/MMy8xV2iZQF5MnDhRxYoSn0lvu8PzslicWrw9kK9Wz/z111+vFnHhhReqIgkXXXSRW09m9erVqhq83BCwH6shveVvvvmmSpuQAF7S7W2mTZuGH3/8URXGk4DbNgf9mjVr1A0FSfcfN25cqfeROzVPPfWUuqMjKRgjRoxQ+2W8xX333VdS2dBe7969VaORc7z//vtVAUBhMplUo5FzlOIJZVMz/EZxIfDFg6oYnu6fX4ALbnY89YeLJIDP3/oKLLlHoI9ogrCuk936+kRERETkR0yFwOr5QHGRGvaJqBZAVJPSzzGGIO+SRxC+53fkWUIRrjn5uqcOApH11fHkOg06tbhyXE0E/RuPBQdXHUvIbGkSW5YtSF5UVKTS9f1yarpff/3V/WcCYM+ePRg7dqxKp5e0ifr16+PkyZOqsMHRo0fV3ZcFCxagefPmJcdID/qUKVPUEIDu3btjyJAh6uIvXbpUZRDI/PZlx+/Xq1cP7777Lq655hqMGjUKF1xwgXovqaAvQwTkBoHsK0teS4rwyXstX75cpehLfQCp2t+vXz88+OCD8FunU61/2GTMkayz0oAyfy9rwpJ/HJa8Y6qwnqxl2xB55vdMRERERFRCitllpALmYsBoAM67odyUyVK4ev3GTdCtWQYtPxe9/liM8IlzKq5oL4H8ooetRfOkR3/EUwzoa0DT6V2amk6Oc9WHH36IXbt2qQ5eWydvZST2vOSSS1QWuj3pYJbH/CKYl/HlYuDAgaW2q2J7vrOk+uBDDz2k0um3bNmiAnm5oyJz1EvQLT3fbduWr0ApveQSyL/22msqiJdjJMiXyvcSZDsycuRI9TmkR3/t2rXqBoAE53feeSdGjx7t8BhpEFIE79FHH8WSJUuwePFiVRhP3kfO22unmHMHSUuq1xw4sR95MS0QFp2g/kC6axoHfVhD6MMbWXvmwxupbSIiIiIih2KbAnHNgVMHoJMe+fotyz1FvqfqcjNgyc+FXrMgXKaoS0sBmp6pi1Wu8+r0v51XspbtBOvwXqo9psJitdgUZOU7fewLL7ygCt9JMbwdO3aon5s0aYJPPvkEBoOhyuOl89dRYXcZby9F072dU8G89FLLh8zPz1eBsm27qotS3XEGrVq1UunvrhgzZoxaqkPS5iVFvzokK0B66AOO/LoNOuTpg7E+KwTYsh8Iy0SvHt0QLmOUwupVOd98pS9vCFap9eaMnTDEdmSKPRERERFVTFLgL3sM2P4T0KKHwx506XjSImKhD4tQPfN58a0RnpBYRedVC2vPvKw5xt4j88z//Mxi/PRE+fpnzvjpp5/wyy+/lGzLzGKSOi9Z3pXp0aOHildlkaHj9oXyJIZNTk5WPfZ+Eczb0upt4w5qK82evFRYlPXOZEYqwvUm6AoyYS7IhyHUgvA1L5VUtsdFj9Q4oDdEt2EgT0RERERVkwA+NKrC75/SM9+rz7kIb5uAvLQ0hJ/Vv+IUe9vrSWp9yl9AouMbBOT+YH7QgyMxcNpVpXrmn2wx3qn3WLZsmVrLUGkZmi1V6SXbW7KvHc28Vrai/d9//63mmo+MPDMzly0zXDK5/SKYlwtS2Tb5OZnCQ/7w1WuBvOMHoYXFwhAeDa0gC3mnjyBcbwEyU4Gsw0C9VjV6K05LR0REREROMxVU+rAaElpUD+FhsZUH8jYSwNdvwUDeg8G8PiQYwSFnbsg4c0xZsbGxGDBgAH744QdV40yGQUtR9V69ejl8/syZM9VagnYpgOeoMr4vcKkAXkWkEJxM29apUyd3vix5g3/vVIZvWIReSZci3FCIPHMIwtds/LdnvhkQ3bSuz5KIiIiIAokUrauK9N7nZHribMiOWYZdOzHNXFmuHGNfyV6C840bN6opxSsK5m0qqpXmK1wqFfjKK6/guuuuK7VPqv1JgTiZa/6cc85R07xRedKgpNDe3LlzfTOgj05AeLR1dgC1ltT6fnfWOMWeiIiIiKjagXzOKUAfVHUwT1WS+ETilKoCYG/XoEEDtT5x4kSVz42Li1MznZVdZKazpk2bqox0b66X5lIw/84776Bhw4alCg+8//77GD9+PF599VXVQ//444+78zz9hkxlt337dkyaNAk+KbhM9XoJ4KVXnoE8EREREXkykP/mUWDbEmDJc8710FOlJD6ROEXiFXem2buy1MTvv/+u1m3aVD0TgcxSptfrcfnll6v4VRb5WfbJ9Wjfvj3uuOMOzJs3D36TZp+SklIqlf7zzz9XlejfeOMNtX3s2DE1xx/5GfkjWZAJFGYD6fuA0Lhy83kSEREREdW69MOlp5GT7fjWvPBexAK9Wlw5rjKrV69W88BffPHFKui2KS4uxptvvqni0LCwMJVuX5VVq1apYnkTJkwotf+tt97Czz//jC+//BJnnXWWyky/7bbb4BfBvEw9Z08+6LBhw0q2pZCABPTkh3c/Tx0A9n8JGPXAgeVA3/vq+syIiIiIKNBEJQB66cG1WNeyTV5Fg04trhxXmT179qgh3g0aNFBT0ElK/MmTJ1U1+6NHj6pidgsWLFBTildFMsyfe+65cvtlurrp06erny+77DI88MAD8Js0e0k3WLx4cckFOHLkCC699NKSx1NTU1VFQfLDu58G2SiGppmAnMNAztG6PjMiIiIiCjT5J4HIECAi1LqW7cqER3vqzKiW0+xlHPtDDz2EDh06YMuWLfjiiy9Ub72Mdb/rrrtUUH/NNdc49XuQY6RQXlmyTx4Tubm5iIryzroLLvXM33PPPbjhhhtUwQD5cJJyL/Pz2Sxfvhzdu3d353lSXYtrqqamw6kUqRMJSJXJyKZAZGPAVFTXZ0dEREREgSSsAWCyABaLdS3b7grmWTDPq8nw7qeeesotryVT2MmY+F9//RW9e/dW+6RmgExxJyn7YunSpV47NbtLwbxUspd0BvmQ0gM/ceJEGI3Wlzp9+rS6i/Hf//7X3edKdV3J/qongEObgYZtgN3fAkmjrGPmOW6eiIiIiDwp94TkYwM6vXUt26GR7nltBvNuoblYzM6V1HxXyTh4qeD/2muvYdGiRWqf9PhLEb1+/fqpbVu6vV/NMz9kyBC1lCWBvO1CkB8G9DGNgHVzrXPLZxwEBjzAYJ6IiIiIPCumKRDXDDh9wLqWbfIqrlamr2k1++rq37+/WnyRy8E8Bai8NCD7MKBZrOvso0BsYl2fFREREREFEpkW+eKZwNavga7DOE2yFzKrRefScZ5ksViwd+9epKWlqZ/tDRw4EN7M5Wr2b7/9NubPn6/mlE9PTy/3HJ1OB5PJ5I5zJG8SngAtqonqmZe1LqpxXZ8REREREQVqQB8Zz0A+wKrZu9PatWtVLTiZer3sjG0Sz5rNnr614IFg/r777sNLL72kitzddNNNqhAeBQZp4lqwAQg2ArKWhl7XJ0VEREREgSk4zG0vlZeXh/Dw8JI1+b8JEybgnHPOwffff4/GjRurAN6XuBTMv//++xg5ciQ+//xz958ReTdzLpB7zDqpoaxliW5R12dFRERERIEooooq9k6SAF6qmEswJz20vXr1YkDv4THzm+Z+g01zv4XFXDrVvTbt2bMHCxcuRNu2beGLXJpnPj8/H4MHD3b/2QQA+cMgFRPnzp0Ln1SvDRDZBNAZrOuIRnV9RkREREQUqIIjavwSWRaTCtwlkJcx07IOxJ55iU8kTpF4xR3Mmq5aS7eJwzD2n3dw07pX4Sl9+vRR4+V9lUs98xdddJG6czV+/Hj3n5Gfk+sWHV2NeS69jE6moet9D7TU1dA162/dJiIiIiLyUdmaGca8ItUjr9fr1ToQU+0nTZqklqysLMTExARENfu77rpLTT137NgxdO3aFUFBQaUeP+uss+B3wfzrr7+OoUOH4umnn8btt9+u5pynwKEC+PAEBvJEREREVLdCaja3fKFmwQFzARqERZWk1gdiIB+oBfBGjhyp1rfcckvJPttQC78tgNehQweVgjJjxgy1hIaGwmCwFkOzkQ+fmZnprvMkbxPEP3BERERE5LvBvATy07OSkWwuRCtDCGZHt1L7GcgHjuTkZPgyo6t3MHyt0h+5GYN5IiIiIvJhB82FSDEXwgxNrWW7ndF91fEDnQV6tbhynKckJiYi4IL5BQsWuP9MyOvZT9dh+zPHKTyIiIiIyBe1MIQg0RCieuZlLdsoygGCa5a6T1aapoNFcyHN3oVjauLDDz/Em2++qXrp16xZowL8l19+Ga1atcKwYcPgzTx324N8mm26jhUrVqh1XrG+/L68vLo+TSIiIiIip4To9Cq1/qHIpmot2yjO5dVzEzN0Li+e8sYbb2DatGm47LLLkJGRUTJGPjY2VgX03s7lYP7gwYOYMGGCGj8fFxenAjpx8uRJTJ48GX/99Zc7z5PqWNnpOiJi4zmFBxERERH5NAngWxpCrYE8uZX0sLu6eMqrr76KefPm4eGHHy5VA+6cc87B1q1b4Zdp9tu3b8eAAQNUYGebm89kMqnHGjRogFWrViE3Nxfz58939/lSHZFe97LTdYhAn8KDiIiIiHxblK50IW8KHMnJyejRo0e5/SEhISqe9ctg/r777lOpB2vXrlW9tAkJCaUev/zyy/HZZ5+56xzJC0iQ7mi6Dk7hQURERES+LFrvUkhEfjDPfKtWrfD333+XK4S3ZMkSdOrUCd7OpZYrKfWPPvoo4uPjcerUqXKPt2jRAocPH3bH+ZEXsQXw9r3vjvYREREREfkccxGQfQQIjQMMwXV9Nj7PrOnU4spxnjJt2jRMmjQJBQUFKtN43bp1+OSTT/DMM8/gnXfegV8G85JeX1nwduLECZWaQERERERE5BOB/J8vANmHgaimQJ97GdAHQM/8rbfeirCwMDzyyCMq+/iGG25AkyZNMGfOHFx33XXwdi5VeujZsye+//57h4/J2PlPP/0U5557bk3PzS9JWnpSUhLmzp1b16dCREREREQi5yiQcwTQzNa1bAcYiU8kTpF4JVAK4Ikbb7wRe/bsQU5ODo4dO4bU1FSMGzcOvsClnvkHH3wQV1xxBe64446SOxbHjx/HsmXL8PTTT2PHjh147bXX3H2ufkGmcIuOjq7r0yAiIiIiIpvIxkBkE2vPvKxlO8BIurksWVlZiImJQaAJDw/3uaHDLgXzl156KRYsWIApU6bg7bffVvtuuukmNc5AAtUPPvgAAwcOdPe5EhERERERuZ+MkZfU+hP/APGdmWJfB2n2O9/4Ui2a2YLa1KNHD1XE3RmbNm2CN3O5dON///tfjBgxAj///LOamk7G0bdp0wZDhw5FVFSUe8+SiIiIiIiotgP6qCYM5N3EounU4qz2E0appSgrF5/FD0Ztufrqq+EvajQPQ0REBIYPH+6+syEiIiIiIiKfJ4G8K5Xpq3MDwBUzZ85EQAfz0hO/dOlS7Nu3D9nZ2aonvm3bthgyZIjqnSciIiIiIqLApalF59JxnpSRkYGFCxeq2Pbee+9FvXr1VHp9w4YN0bRpU/hNMC8V/m677TZ88cUXKq2+LL1erwrivfXWW6rXnoiIiIiIiMgbbdmyBYMHD1YF/w4cOKBiXQnmFy1ahIMHD6pacH4xNZ0Ut7vqqqvw2WefqQ/84Ycf4q+//lJl/GUt2xdddBE+/vhjvxqHQEREREREASKIHZLuHjPvyuIp06ZNw5gxY1RMGxoaWrL/sssuw4oVK+DtnO6ZX7x4MX777Tc8++yzuO+++8o93q1bNzVHnzz+8MMP46uvvmJQT0RERERELjOZ8z179YIjPft+fkzGy+tdCMxdGWdfk2nDJau8LEmvlznnvZ3TPfOffPKJCtgdBfL2HnjgAXTt2lX10BMREREREbnCYilGbuEhaJqJF9AHWTTXF08JCQlBVlZWuf27d+9GfHw8/CaYlyIAV155pVPPlXT8jRs31uS8iIiIiIgogAP5/cc/xOHTXyG9+Hu1Tb5F03QuL55y1VVX4YknnkBxsbV9yfzzMlb+/vvvx8iRI+E3wXxaWhoSExOdeq48T55PRERERERUXYWmkygoPgFNs8CspaPQdIoXkdxu9uzZqsh7QkIC8vPzcf7556tZ2mS2tqeeesp/xszn5uYiLCzMqedK8YC8vLyanBcF4Hgoo8G59kVERERE/i3E2AChQfEoKE6DHnEIMdav61OianK1mJ0nC+DFxMSoKddXrVqlKttLYN+zZ09V8N0XVGtqOkk7oJrp1asXDAYDJk2apBayjYc6iKjQ1oClGHpjOC8LERERUQDT64PQuuF/kZG9HYV59dU21a65c+eqxWw2u+X1LNCpxZXjPOXQoUNo3rw5zjvvPLX4mmoF8+PGjcPtt99e5fNMJhapqKxiYnR0dHUuu98H8nvT/qfuuoYaG6BZ6NkIi0mCjn+wiYiIiAKaBPBhhnoo0lUrZCEX2TobpSCc9FgHQjX7li1bqiD+pptuwqhRoxAXFwdf4vS/jNGjR9fumVBAKjCdso6HspgRemI3Mi17kBfWBPXbTWBAT0RERBTANEsxtMIMQIut61MhF7hazM6TBfA2bNigZmGTInh33XUXLrnkEhXYS+F3qXTvN8H8e++9V7tnQgEp1FhfjYcy5R2G0WxRNRlN+cdgKkhDUHjTuj49IiIiIqqjQP70rjdgyj8KGBtAi78T0Ht/cEW+pUePHmp5/vnn8dtvv6nAfvz48bBYLBgxYgTeffdd+EU1e6JaaYD6ILRNuBFNEq5GUFhT6HR6GMMawRiawAtOREREFKBMBcdhzj8mUT1QfFJ19JBv0Sw6WKqxHHjrM6zoPQJ/XHiTx89Vp9PhwgsvxLx587Bs2TK0atUK77//PrydVwXzUgH/q6++UmPzO3TooKriR0REoFu3bir1QaoLVmTBggXo3bs3IiMjUa9ePVx22WX4448/Kn2/1atXq+fJ8+U4Of6DDz6o9JjU1FSMHTsWTZo0UefXvn17zJw5EwUFBfB1WRZTnQX0kWGt0aD9RMQk3sAUeyIiIqIAZwxtCENYI0CnB4IasKPHB8nY9+osTW+9Hn3XfIXeyz72+Lmmpqaq3vnu3buXxJRSDNDbeVUwL2kNw4cPV+kMUvH9qquuwoABA5CcnKwCZqkE72j++qlTp6oAe9u2bWoaAfkFyBQDAwcOVDcHHPnyyy/VPIJLlizBWWedpcZH7NmzR9UGuOeeexwes3fvXpWGITcO6tevj2HDhqlqj3KjQd63sLAQvixbK1258nSRpL3XrgKtSK1lWjopehcS1Zpj5YmIiIgCnHwvjG13K4wJfaE1GMnvhz48NZ0ri6e89dZbKiaUQnjSqXvttddi3759WLlyJSZMmABv51XBfFBQkBqjsH37drV8/vnnKtjetWuXCqJ37typAnd7kgYxZ84cFVxv3rxZBe9yzIoVK9QNAQnyMzIySh1z+vRp3HLLLSoQX7hwoRofIWt5/bZt22L27NlqX1ljxozByZMnMXnyZGzduhWfffaZOje5ASG9/M888wx8VaFmQYq5QK1t0ou0Wn1Pk2bGYZxUaxtOS0dEREREMuPR0UPvIzNnIwpyvlHb5Fs0WAvgVXvx4NR0s2bNQp8+fbBx40bVMfzggw8iMTERvsKrgnnpFZe7I506dSq1v3HjxiVpDosWLUJRkbU3V7z00ktq/cgjj6Bdu3Yl+/v27avupkggP3/+/FKv984776gpF6RnXQob2DRs2FClVwgJ6O2tW7dOBewJCQklzxFGoxFvvPGGuhHxyiuv+OS0fBLA35u9H8/kpqq1bOebNezIMqt1bZAAfhF+x8/4U61tAb3ZnFcr70dEREREvqOw8BgKCo/AoplgtpxQ20TudvDgQRXbybBuX+RVwXxlbBdYUtlPnTqlfs7Pz8fy5cvVzzIvYFm2fd9++22p/d9//32Fx1x++eVqLLz0+NuPg7cd42iaArkJIMMB0tPTsWrVKviaQ+ZCpJgLYYam1nuKCnDJimyMWZer1rUR0J9Gllos0M78bClGfl4K77wSERERBbgigwFFRqNUJlM/F8vP5FN8Ic1ep9OV1G6TLO0tW7aUWvwymJfe88pIkH3nnXfCnfbv36/W0gMuBeuEpLhLcB8fH49mzZqVO6Znz55qXfYXIen49o/bCw4ORpcuXVQgv3v3bqeOqey9fEFzQwgSDSEwQKfWeXlBqlfepEGtd2WXHkvvDvUQrRY9dGodawnD4UPv4vjRL9SaqVREREREgT198cH4RkitVw8p8Y0QYrR+/yffYdFcXzzlxIkTqjM3KioKnTt3LpmqzrZ4O5ducd1xxx1YvHixSl9v2rT0XOBSLEDGqR86dAivvfaau85TjYsXUqjO1jMuaRHCUSAvpBJ+bGys6jHPzs5WvyRJr8/MzKz0ONm/YcMGpKSkqOJ4zryXbb8cUxlJ+5d5C23ks5Tt6fe0IADPRbTEpuIc9AyKVFNDdIoy4J8ss1q3i5DpIlwvhifHappW6jUkiL8aA3BIO47muoYwF6ahqCgNGixqXViQhpDQxm76hESVt0eiusQ2Sd6GbZK8QTpykRyZAEN4IYp1weiu5SLEwnnma4N0jtoX8pZ4yR3MFh10Fp1Lx3nK1KlTVWz4559/4oILLlAx7vHjx9VY+rLDrv0mmP/oo49UETjpwX755ZfVWHfpyX7ggQdUAC9j3tesWeO2k/zhhx/UjQPplX/yySdL9tumqgsPD6/wWAnoJYC2BfP209tVdJwcI+QYZ9/L0TGOlC2oMH369Aqr53tarKUYmXrr0IL3OwBrMzScG6tD9qk8VP6pqv5SIP9IJIDS60sngwRpGk7rTqnHdLo4aJZT0OnjkJGpQZfF+UTJ/Sprj0R1gW2SvA3bJHkDE8yIjA1DrqEI4QXBKM7KR5re+78bZhdbEBXkW98vXnzxxVoJXG0F7Vw5zlOWL1+Or7/+Guecc476Xiix2pAhQxAdHa2Km0uvvd8F8zfccAMuvPBC3HbbbaoqvFR1lxL+kgp/33334fHHH1eBtzvI2IWbbrpJffF+4YUXfLY4gY303Evj8KaeeZtQiwnR+jNNIqq+BXHBerd8KZDxKDIcoqLgKdecifj425CXtw/h4W3U3PNEtcGZ9kjkSWyT5G3YJskbmDUTWhTmIcuUhTCzhobx8QgyBMPb5eSYkRBpgC+RzlIpJm7fM+9LFd1rIjc3VxU4F3FxcSrtvn379ujatSs2bdoEb+dyJQmpMC+V5WUud5kKTr4cy12du+++220nd/jwYZVWL2ny06ZNw5QpU0o9HhkZWVKwoLJfkJBeeftjbMfZB9YVHePMezk6xhFJ+3f0nnUty2JGrLH0H8j6oe4LdKR9SODkKHgqshQg1bwTbYJ7ICKiJQwG77i5Qf6rsvZIVBfYJsnbsE1SXcs2ZyHXkq4mOCvQ5yBPl4U4vTXo8lZSNHpnjoamETqEGTzXu1xTYWFharFx1/cjV4vZebIAXocOHVQdNplnXjqNpTac/Pzmm2+qeNfbufyb+vvvv1U6gszJN2nSJCQlJaleeVnsp45zlcwFf/HFF6uebBmDLzcKymrRooVap6amVhhgS4q93GWxBdkSSMfExFR6nG2//R2pqt7L0TG+Qqai21yUV2qOeU+RQP737PdxsGCDWpt1DK6IiIiIAl2kPhZR+nrQQY9wSxQidbHw9kBeZoEaXYuzQfkaqcNldmGR4zxlypQpOHr0qPp55syZ+PHHH1XcJ1OOP/300/B2LkVOjz32GPr06aPGyf/+++949dVXVVAv47//7//+T1V2l21Xyfj0Sy+9FNu3b1fzwM+bN69k2oCyd1IkRV3SIaQXvyxbaoStiJ2NLVXfUepEcXExtm3bpqankxQLZ46p7L28nQTwd50+iMcyj6i1pwP6E6aDsGjWmz+ylm0iIiIiCmwGnRH9wq5E16Dz0TH/PLXtzWT2J5kFqthSe7NB+RpvnpouOTlZrWU495gxY9TPZ599tupIXr9+vSrmfu2118Ivg3kZVzF+/Hg1XVu/fv1KpnR79tln1TzrJpMJffv2demEpJLisGHDsG7dOgwdOhSffPIJDAbH404kHWTQoEHq5y+++KLc4wsXLiyZG96erZCB7XF73333nbpJMXjwYBXQlz1G5qy3r/YopOKhVPGXDID+/fvDlxwwFWG/qQhy81DWsu1J0YaG0Ous6f2yjjdaMyCIiIiIKLBJAB9riIce3j8GvUWYHtInJsG8rGU70Ml1cHWpbW3atEGrVq1U/Tcp7m7LspZi59Ix3aBBA/gCl1rZsmXLVG+8/dgKG+mxlyD/rrvuqvbrms1mXH/99aqq4IABA9SYfLlJUBkZSy9k+oA9e/aU7Jdq+jLmQcaojxs3rtQxt956q0q3l8qF8h42aWlpapiAkCwDe71791aBujzn/vvvL9kvNy4mTpyoevSlwr+7Cv95SktjMFobgyHDemQt255i0kzIRCb6R96IFqHn4Pyo0QjWn7mBQkRERESBS74rntROwQzv7+U+lGeB0SwFpaHWsk3ea/ny5WpGNingLkXdZah0u3btcPvtt+PTTz9VnbW+QKdJmXgvIXPJy1x/Yvjw4RUWipPx8/Z3S+QYOVbupMhUAjJmf+nSpaoCvvS+X3311eVe48svv8Q111yjniNzCtavX1/dpJAx9nKDwNH0DHKzQDIOTp06pSocSp0AScOQRiAZCtIoKqpML1UhZay+TInlbQXwJLV+XWEueodEIKQWxqxLVVy5CSKVIm0FNeSP8y/FPyFDS0esLg599eci2ljf7e9N5Ex7JKpLbJPkbdgmyRvId8XvzMuQazqBYC0Ww4KHItiLq9nnmzRc8WsOtmWY0SXWgO8ujESY0XeK4LkzbrEd32XrJhiqKA5u7+QHH6lFs1hQtD/ZY3FTQUEB/vjjD/z2229qkQxx6ajt2LEj/vnnH/hdMH/woHPjmm1F46ozFl+mtXNmjINUGbS3YMECNcf9jh07VG/+ueeeixkzZpQMA3Bk9erVqkd/7dq16gaABOd33nmnuktTERk/8eijj6oK/lKkTz6jZBM89NBDpdLyfSmYt1Wzj9YbPPal4LTlFJYWL4EFZug1PfrquqNpcAcYdL6V2UC+h19SyduwTZK3YZskb5BmScPW058gxFyEQkMwOsdeh0bGhvBmEtAvP1aMQY2CfDaQd2cwn7T5r2oF8zbm7Gxs79bD43FTUVGRig+lCJ5keEsdN8kc97tgXgIyRwXpyvL2D+9J3h7M16ZKe+Ytp9E4JxNBZhMijPHoXO8aBvTk8fZIVJfYJsnbsE2SN8gsOoJt6R8DKlTRqWA+NrQZvN2+bDPaRHn/GH9PBPMd/v7b5WB+V/futR43FRUVqU7dX3/9VfXI//nnn2jevLmael2W888/v9qd057mUlnId999t1wwL4H7gQMH8MEHH6gvyTJdHVGFDU9nRN/iAThpTEZq3nJoIRryzCeRbzqNyCDvvutKRERERLUrMigekYYEa5o9YtW2L4gL9t0eeXfTLDq1uHJcbRs0aJAK3qUIngTtMlb+448/9om55WsczNvK9zsixeGkCJ7cSSGqSF5eHv7a8BcKUIDMfCMaJhUjLqIBwoz1eNGIiIiIApwGHY5GxSK3uFgF82fBN4LkeiHM+vMFK1euVIG7BPVSP00Ceqmh5mvc3toiIiIwduxYNd88kb08nJn2TooVWnQacrQiNAjrjC4JVzLFnoiIiIiUdMtpnEY6CoIMyDJmI107zSvjY6Sev0VzYfHAuWVkZODtt99WMclzzz2HJk2aqALnUj9NCqifOHECvkBfW2Otjh07Vhsv7fN69eqlCu3NnTsXgcQECw4iHcX/Ti2SmZeNLdpB7NIfw1akAqZYjpUnIiIiohKlC3v5Rs+8L5P4ROIUiVfcwWLRwezCIsfVtoiICFxyySV49tlnVbr9yZMn8fzzz6vgXtbNmjVDly5d4Jdp9pUVO1ixYgVeeOEF9OjRw50v7TdkKrtAK4AnAfzX9fYgXVeIBERhLHojP9yM4l4xMIbrUZxnQXE4q9gTERERkVWkPgYWXTA0rQiaLghRusD6/lwXpOaZLLYCdjWlgnIXAnNPBPOOgvt69eqpJS4uDkajUc2S5pfBfGXV7KU4vlT9e/3112t6buQnTiIXp40F6u7qCWTjJHLQAFGID4/DCWSpdX1Uv9IlEREREfmnTF0BjgXFQKcVwaIZkaErQDjC6vq0qBo0TaeW6qrqGKm99fPPP+Pbb7/FqlWrkJKSAoPBgLZt22LkyJGYNm0aIiMjq8wk37Bhg6piL9XsZUq63NxcNG3aFBdeeKHKUpC1XwbzMs962WBetuUuRps2bXDxxReruxlEogEiUM8UivSgQsQjCg0QiSAYcAP6IxlpaIUEtU1EREREJOojEvG6aKQhE3GmMNQ3Vh6cUeCQqvO33Xab+rlTp0646qqrVDbBH3/8gZkzZ+KTTz7B77//rmZYq0hsbKwK3hs1aqSCdqn3JoXwJJb1JS5F3I899pj7z4T8lgTqw063Q1aCDu10ZwJ3WTdHfQbyRERERFTu++ON6Iv92nFEnAaCEtjx42ssqgKei8dVIigoCOPHj8fUqVNVMG9z9OhRXH755fjrr7/UYxL0V0SGhUsQ3759e/gydp+ThxqaHi0QWy5wD0MwfwNEREREVI58b2yGeshGRq1enUyLGTF63ixwt9oaMz969Gi1lCVTzUl6fL9+/bBo0SIUFRUhONhxrCHzyvsDp4L5W265pdovLGn38+fPd+WcyF+5MGaGiIiIiAKXdPxk1+LrF2gWbC7MQ+/QCITqOEe8O0lles3DBfC6deum1oWFhTh16pQK8P2ZU8H88uXLKyx4V5HqPp/8WzEsOIAMdNAaIEjHO59EREREVLckkL/z1CHsMxWiTW4IXqvfnAG9G9VFNfv9+/eXpOJLZXp/51Qwf+DAgdo/E/Lrqem+iNuPU7oiNEIkJmhnM6AnIiIiojqVYipCsqkIZg1qLdsdgkL5W/EwragQWlFRybYlN8fl15ozZ45ayxzyISEh8HccM0+1Lg15OGUshAUajiMHachFU3CuUCIiIiKqO4nGYLQyBqueeVnLNrmPZrEuVcl59zXkzvu/Gr/fDz/8oIZ5S6/8k08+iUDgdDD/0EMP4brrrsNZZ51Vu2dEficB4ahvCsGpoCI0RCQSEFHXp0REREREfiBPK0a4LqjK52UUaIgNLZ2+LWPkJbV+XUEux8zXArOT88yHjr4LIdefKUin5eYg/cpzqvVeO3fuxE033QRN01SletvYeX/ndJWHZ599Ftu2bSvZloICBoNBjacn/3S60IW5JCqoRPqf9Na4XuuMCWCKPRERERHVXLFmxnbtpFpXpsCkYf1hs1qXJQF9t5BwjpWvBRLIy/j3qhbNGAqER9stUdV6n8OHD6u0+vT0dEybNg1TpkxBoKhRyUa580HV06tXLyQlJalpE7xdepH7fr9B0KOlTE3H4ndEREREVEMSwM/VNuAzbYdaVxTQSwB/w8ICTP2xUK0dBfScls5K4hOJUyRecQeZL97VxVmnT5/GxRdfjJSUFIwdOxYvvvgiAgnHzHvY+vXrER3tG+PFM4rlX5J7Ks8XaCYkOJECRURERERUlVQtG/u0AphhUOtUZKOVLrbc8/adtmDPKQtMFqi1bHdO4MxKjkyaNEktWVlZiImJ8fpGmJOTg0svvRTbt2/HiBEjMG/evICbUY2TKVKFKfbfHC52S6p9rlaE9cEZak1EREREVHM6aLAGbta14yCuTT092tXXw6iHWss2eYbMMe/qUhWZR37YsGFYt24dhg4dik8++UQNAQ801eqZlynqNm3apH7OzMxU6z179iA2tvxdMNGzZ093nCN5mATwbX/KQI4FeDW5AHuHxqJeiGt/+HIsRZiBDSiKNWM1MjDL0huRelYKJSIiIiLXNdVFooUWhVTkoBki1bYjoUYdPh4VipUpZgxINKjt2nS6yIJ6wbxhIGQ8vM6FOeOrCubNZjOuv/56VbttwIABWLRoEYKDAzO+qFYwP2PGDLXYmzhxosOx9JLiIBeafM/S48UqkJcRRbL+OrUYY9u4Nk/jdmSoeeaFrGW7NxLcfMZEREREFEiCdQZM1Z+Fvy0n0F0fr7YrIgG89MrXdiCfb9aw6nQxhsQHI8wQWOnejpgtgM6FJN+qprN77bXXsHjxYvVzgwYNHMajQsbPy+P+zOlg/r333qvdMyGvMaRhECL1QLYFkHucMcU6VSzElT+ASVL0DgYUwazWsk1EREREVFMSwHfW1680kLcpOy1dbQTyF63JwrZsE7pEGfFL3+iAD+hrq2deqtbbLP43qHfkscce8/tgXqexJL1H2ApJyPAEbymAl5eXh/DwcLUuCglBrN04k8N5ZkzbnIPc/UFITtfQoYFepSi5EtBnmwvwVcYuXB3bAVGGUDd/CqLqsVgsSEtLQ0JCAvR6psFR3WObJG/DNkm+1B6PWfLRSB+GuvZXpgkX/JGJYg0I0uvwW99o9Ig50296utiCekH6gIhbbMeHfLsXuojqTTMntNxsFF7Z1qviJm/lGy2K3E4CeKmsv2LFCqxZtw5/pqej4N95IOTO4g3bsrDsVDG2l6n+6QqLpkeRxaDWRERERETOys2seKrkHEsxfi4+rtZVSS+o3Sm1W4br0CxcB8mu7xxpQMfIM51k8t36j4witfbU+XgDzaxzeSHnMLoKUNIjL3UNisxmLM7JwSPZ2bjl6FEV0K9PN2F7rhmFIRpMIRbodUCrONeqf2ZbTJhi2oxfonIx1bRZbRMREREROSMvy/F+CeAn5G/BV6aTal1ZQH8s24I/j5mQ72CO+ZrI/Lc+mHx/Hn8kDfqG2ejWohDf94ksSbGXAP6Sv9MxZkeWWtsC+oxCLSDGzLu6kHMYzAdwz7yMsMjUNJw2m6ErKMDeoiLszC/C8QwLzJoGCbtz2xRi5mAjbuttVAXxqmuzlokiWP9Fylq2iYiIiIiqUlSg4cg+oLiw/GMbLenI+/fbqaxl25GMfAtG/pCHO34rUGt3BfQSwP9VmK/W+4qK1fdoEzQct5ixv+jMjYVdeSbsyDWrTFdZy7acw650s9tvLnjjmHlXF6qFavbkXz3zvXr1gj40FIuTk6Hp9WhtCMaDy8zYmm1CTn1AhiWZoMPr24pxOEtDp616fHFlOMKqMW6+E6JghB4mWBAMPbrpYmr1cxERERGRfwTys8cBh/fokNAyDvctAELDzzwejxDVKyldRvp/t8sqKNZw/ReF2Ce94DpgV7oFezMs6NqgZvORSwB/e9ph7C0uRNugEMxp0BitjMH4OVWP4mI97szJx/LeIap3vkO4EZ0iDPgn16TWicEGdVNh52kLOtbT48vLwlGos5SqXeUvNK3qyvSOD6yFk/FT7JkP8IA+VK/HO61a4bmEBNwbloDdGRboinQwFuth1OnQLsiII9maSnex/QF0VqFmwdMFB5BbHISQomA8b+iKKL2x2uOhiIiIiCiwHEuG6pWXTPa0FKPattfWEIUOxlCEGzS1lu2y9p3WcPS0BQbJhteAFpF6tI2tefhzwFSE/cVFkIx5WR+zmHBfXH3oTAYYoMOOHAt25lpT8CWgX9I9Dgs6Rat1arb0yltrUsn6n3Qz1ucVltSuIqoOBvMeJr3hSUlJmDt3LryFBPQ9Q0PROc6IDnF6VYFzAEKwoEskvu0ThUZSzEMP9Vh1/gCmWgqQYimAGTpkQY+Mf+ebd3Tndc8m6zo7i0E9ERERUaBr1Apo0gaQDuuERJPathes02NmcBKmBrVVa9kuq009Hdo1MKB+vh6dDAYsviysWhmmFWlpDEbroGBV7E7Wst0tKghJkQYYbQXwIs70tEtA3ynCqNbyXVq+Uxv1QLt6OjydcwLTDp/ETQeP13lAL/GJxCkSr7jFv1PTVXeR48g5nJougKemc0TG7nyfbMLlrYz4K7MYz/1qwo5TZjSK1OPrkWGIC7X+oczO1hAVpauyZ/6hvL04YClAE7MBz0d1QJjBWEEKFdC0HXDjk0CL1vwHTLWHUy6Rt2GbJG/DNkneQr4nblxqQbOzTqBpc9emlJVU++X7TMi0aLi6fVCVwbwz33HV61osWFuQh3NDrZmuQorbLT1ZhCENgsvNMW8/NZ183/491YSEBhaMPXwcRZqGYJ0OHyc2QufQYPjL1HSGj5OhC3f+eMsP78Dyw3zAYlZpGd4eN3kD9sxTORadpv4YrU0zYfcpC8xmHdJyNOzMsPasFxZq+GeHptaVCdHp8XR4W9wT0hz3FtRT25WlUB3ep2Hb+qpfl4iIiIgCQ15R5d8LM3Mrf1zTAa/8VYzHVhbhuq/yKy065+x3XCEBfI+QsJJAXkgAf15cULlAXtjPMS83FPo0MiIpPAjtQoJghE6t2wT7VzkzvaV6i/GSWxH8yhoEPb+srk/dZ/hXi6EakT9uw37OxfYMMyypRbAYLIgMCYMuX6al0yEjtAiZBXo88YSGAweBli2Ap2caEBJS8d1LCeCTDBHIR2GlKVSpezTkxAEffwSsXq3h0RdQ6esSERERkX/3yj87ETi0V49GiXF4+K3SBfBEQZGGv/db0KeDHqHBjr83bj9hxr4MCywaVCfVvnQLusSXLzYnAfzDMy1ISQESEzU89bi+yu+iMQ6K1tULdq6vNC5UXluHj1o0xMrcAgyICC11Y8Af6G1p89WkMc3eaf7VYqhG9mRasCvDgiKDhhydtTCHOU8HQxGQ2iod96edxOgNp5ByCDCboNaph6t+3ShdxfeMgkN1mD4fuPJuwBJkzao5lAIcOcRfJhEREVGgOpoCHE62fjc8ftCotssG8pNeL8bMj0yY8Gqx2naUYv9/i02wFFjnLm8bp0ebOMfhj3ynPXjQmi0qa2e+47qDBPC9wkP8LpAnz2CroRLtYvToEKtHsFmHSE2P4AI9gvL10IebkRdqhqlYwwFzMeo11mDRa2jeTEOzpjW/gBLQd+kFNG8J6A1A80SgSXP+YoiIiIgCVeNEWTRoBiC+mUlt20tJ05B8TIPJDBxI09R2WQdOaDhwAqh32oAG6QbM6hsCU77j95PvtC1aWAvuydod33HLjpmvkJ+OMNWZXV/IOUyzp1Ljd76+OAK/HjHh3IZR+D2jEB+lAXtOGxGcY0TQb9EwnjLiYLYGS4gO+VKfQwdk5WiIjqxZSnxcvE6l1m/eqKHb2Tqm2BMREREFMh1gCgVMIRpModZ54u0lJujQsqEOuw5paBwGNI4p/xIt43VoFQ/sTAPaxenQKk6HHVs1dOtZfjinbEtq/V+bNfTo5tx30Qyz2an54aUW1ZqsIgyKtc49X7aQ3vrcQgyI8r80ewPT7Gudf7UYcktA37ehEfVC9Di/Xgj+d10onhwcjPkJDRGWEQR9gQ7F+TqVqrT3ALB5hxlb92gorKI4SVUiYqx/NJsnMpAnIiIiCnSHZdhlCqBpwPHDRhw5WPpxNeI8B4g9aEDeVgOeeNxx4bqiMKAoFDCHAE89rGHOcxoeu9/i8Llmcz46d9KpdVUkCN9UUFDldHISyF+x9TRu3Zml1rIt0gst6tjrk9Mw5fApta7rqenqugCe/ULOYc88lRP3751IqbopY410FqBFfZ26O6rL1KnUF0l50szAK//TcDrHjFZNgZfuNSKkguIjzoqM4i+EiIiIKNA1TQSatQQO7gcaNTOhSYvSU7ZtP2hGcjIQWWwN+FNSNBxOBVq3OfOc/ac07DupqeJ3hw4BxpR/6zMdBA4fAlq3PfPcvLw8rF+/HjqdTo2/P69fL4SHl6m49y8Jum85ehR7iorQLjgY7zZuXGGv+u58E3bmmWHSNLWW7W6RQUgv1HDYYsaewmL1mKz3FprQJazup6ZzawE8Mwvg1SYG8wEu3WRBnNHxHx8J5Mf8rxB70jQ0j9GpPI6CaA1Rp6XKpPWO6OkcWMcqHQEOHgXalRnPVF1R0axgT0RERBTogkN0eORlYPM6DQ0TMxAcklDq8ROWIpgNRpiNgMEExDXS0LRZ6ddoIlOUW6zfVSVVv2kLa49/8xZA0zL1mSRwl0C+qNiMoxk66IPCKjy35OJi7C0qUkG4rGW7U0iIw+e2DzOiY7gB/+Sa1Fq2ZQYpmfK5byODmpJuV2GxWrcNYWhG1cMWE8DyLRp+ySjA5fXCEKYvH0TL3cy9JzRV1f5QuoYg07+98kZAr8nYIqBBA+DICaBlE6BF4zr5GAEnvdiCOLu5SomIiIj8NaCX3nldUPnHzk0MQWSzPOTqgxAaZsbMGSHlxrkfzbQG+iGSuq0D/jsdOLoVuGBI+WnnpGe+2Kzh203A6WwLfjuaiTcmxCA0qPx35FZBQWgbHKx65mUt2xWRMfJfdI7D7EPZmN48ShW7G7bUOhV0UqwBn10Ujw35/jlmXufi1HTg1HRO868WQ9UK5K/ecQJTD6SrtWyX1bq+Dm3jdZCO++aROpgKrMU2VUCv6VTqzOMTdRgxRIdnphhqnGJPcLqAim28FREREVEgig4x4O27whATooMxOxjPvYZyNZxaNdChbYIewXrrumV9HXSarmwtvZKe+QYtzsam7H44YO6JvSfCVJV8RyToltT65xISKk2xF/Id+9pdp/DeyVy13pphxs5Ms+osk/WhHKBXhH9OTac3AwYXFjmOnMOe+QC1LbcY/xQVwWKAWst2r6jSY3TkTuSCG0Ower8ZMQYdJrxjQlA+EJKrU1PIhRRreORtDYdPARv3apgzVVfjgD4nS0MkU+0dkgD+qn9OY3uuCUkRRnzTuV65iqhERERE/iQiCsgrKL9fAveHXtOQm6FXwfmBVODQEaBty9LfZeePCcaavWac3VyP5x+wjsFf8ZOGR2dbe/7tdWgRgdYNi7H3WBjaNtShZULF37Mk+O4ZWnVvuvrOXVik6k3JushoRscYg+qZl3W7aL0qQO2PpONPlmpjz7zT/O8WkJfr1asXkpKSMHfu3Do9j2JNK5nSUvt32xH5I3h2CwO6JOqR1EwHXSQQFA2E6HVo0FyHo6ehKtsnH9WQcrzmvcVph9njXBFrARXTvwVUTGqbiIiIyK9V8NXwwHENhzOt89DLUxrGA82bOP4u2zPRgFNHdUg9YC2AJ+vDBx0/963xQXjqOqNaO0qxt+fMtHQ6nXWx/RwqU0EPicDb/cPU2psCeYlPJE6ReMUdpIfd1YWcw555D5MqmdHRUo2jbhnlHqbKmbf+kVTbFYgNsz729u1BWL7VgvPa67Bpg4aeZ+tx3xsa9h/R0KqxDokNa/bHqKhQw/5dQLPWWrk7pWQroGJUPfOylm0iIiIif5WRnov9m0MR1bgACaXr36k55ls31mGfRUNCFDD7voqHfMaE6xDWQiupji9rKYbniATwrRvqqwzkndU5PAjdwoOwPb8YSWFBaltqVclU0N4UyItJkyapJSsrCzExMXV9OuQERgMBqmtEEDoaQtUflk5hQWq7KvJHrX9HPaLDdTj7bA1RUTqVWr9uh4benWqWYn86zYKXHgUO7gN+W6Lh0TnlU58CnaTUS2r9rxmFuDA2hCn2RERE5NeB/CuPb0DWKSAi1oypjzVAXP3Iksfle+erk41Yt1NDx+ZAdGTlCcfyvVJS67ds0HDWObpKv2fGOJ6RziUSuH/ZPh7fp+fh8rjwkqLTcSH+nyDtagE8l4rmBSgG8wEcGH7XpT6+O5WPK+qHOR0Yyp1NIYG87Q9pt7bWtauKCjT88ROQvBNqHtDkXUDKHg3tuvAfsqPfW9/oYAbyRERE5Ncyj4cjS6ZDhkWNi89IC0dc/dLPke+frRoD8XHOfWeUAL5j16o7jGzfd91FAviLYhzPHuXPqlvMLmfF28hZ+TY0GQtBTmEwH+CB4eC4UJcCQ/tCddERNQvkn50owTug2V7GUvH4KAKnpSMiIiK/F9MwD9H1gKxTetUzH5uQB+BMz7xNdDV70euq0HKcTA8VYGQqa718r3dS9Hnj1WIpyELq/U1r89T8hte1qo0bN+LZZ5/FiBEj0KxZM+h0OrVUZcGCBejduzciIyNRr149XHbZZfjjjz8qPWb16tXqefJ8OU6O/+CDDyo9JjU1FWPHjkWTJk0QGhqK9u3bY+bMmSgocFBm0we4Ml+5jG3fuVVT65o6mgIcTgY0C2CUeUB1QNu2QGK7wLpzSURERERnxMZFYPLMczD8+v646c7WiIlzHLXXpFOJapferHN5IR/tmX/yySfx9ddfV+uYqVOnYs6cOQgLC8PFF1+sAuulS5fi559/xsKFC3H11VeXO+bLL7/EtddeC4vFgoEDB6JBgwb45ZdfMHr0aGzZsgUvvvhiuWP27t2Lvn374uTJk+jSpQsGDBiADRs24IknnlDHyhISEgJ/JgH8E9M1VTykRWvH03pUR+NEoGkrIHWfDi1aaeh7GXDhVToEh/IfMREREVGgB/TRDUyIigmt61Mh8kpe1zMvwfKMGTPwzTff4OjRo1UGx8uWLVOBfP369bF582Z89dVXWLJkCVasWAGDwaB60TMyMkodc/r0adxyyy0wm80q2P/tt9/UeufOnWjbti1mz56t9pU1ZswYFchPnjwZW7duxWeffYZdu3Zh+PDhqpf/mWeegb+TaTyqmtajOiRof+B1YPQDwENv6tC9n3UfEREREQU26UTKPA0UF9b1mZArdBbXF/LRYP7+++9XPd1XXnklGjVqVOXzX3rpJbV+5JFH0K5du1I3BSZMmKAC+fnz55c65p133lFTLgwbNkyl89s0bNgQzz//vPpZAnp769atUwF7QkJCyXOE0WjEG2+8gaCgILzyyiswmfx77m+ZxkOm89AbKp/Wo7ps42kaNvO6JklEREREdRDIPzVZw7sv6vDG47EoYkDvcwxmncsLOcenI6f8/HwsX75c/Txq1Khyj9v2ffvtt6X2f//99xUec/nll6ux8NLjbz8O3naM3GQomy0gNwEk5T49PR2rVq2CP7NO66HD5Ieh1jWdPk4K4L0wHvhwFtRatomIiIgosB35t66S2QQcO2RU2+RbdP9Ws6/uIsdRAATzkuJeWFiI+Ph4VSyvrJ49e6q1jIG3J+n49o/bCw4OVuPhJZDfvXu3U8dU9l7+yDqtR80DebF/C3Bkn/UPtayPHnDLKRIRERGRD2uSCDRubp3hKKGxSW2Tb9FbdC4v5KMF8Krj4EHrgG1HgbyIiIhAbGys6jHPzs5GVFSUSq/PzMys9DjZL4XtUlJScNZZZzn1Xrb9ckxlJO1fiu7ZSC+/LxbNC48ELDIpvBPk82qaVupzi6ICIO840DAROLIXaNwKaNjC+dclckVF7ZGorrBNkrdhmyRvUJgD5P4JhBbpUHgiCEW5FgT73ldmnyCdo7LYSLxEvsGng/mcnBy1Dg+veIJJCeglgLYF87ZjKjtOjhFyjLPv5egYRxITS99WnD59Ou655x74+5cCuYEiAZReb00GKS4APp5YD2l7jCiK0FSKiDnPhBMn0hHEP9Tk4fZIVJfYJsnbsE2SN/jnpxAU5sfAqAFFZh3+/C4TXS8pquvT8ksyi1fZemHuoHMxZZ5p9gESzPsi6bmPjo72+Z756n4p0Ol0ajiELXhK3Qac3KdDkVkKnOhgCNJw+lAQLDkJSJCUKiIPtkeiusQ2Sd6GbZK8QcQVwHfP6VQmZ1CwBX2uiEZkPf6/XVtTg0sxcfue+bIdkK4wWFwsZsc0+8AI5iMjI9U6Ly+vwufk5uaqtfTK2x9jO84+sK7oGGfey9Exjkjav6P39HcSPEngZAueYuI1FJgAuVmn0wCDUYcmbYHGbQC9nuNkyLPtkaiusU2St2GbpLqm12uwfSOUtU7H/7drS1hYmFrOXHv3fD+yFbSrLo0F8Jzm099kW7SwzouWmppaYYAtKfZxcXElQbYE0jExMZUeZ9tvf0eqqvdydAxVbM86QIbGyx9nfRFw4Sjg7vc4xzwRERERATtWyFhu65WQLM6dK3hVfI1MPe3qQgEQzHfo0EGlqJ84cQKHDx8u9/imTZvU2lbEzqZbt26lHrdXXFyMbdu2qenp2rdv79Qxlb0XOdZpIBD67w1AuRHY8woG8kRERERk910x1PpzSKiGjgN5ZYj8KpiXdJBBgwapn7/44otyjy9cuLBkbviyc8nbP27vu+++U9PSDR48WAX0ZY+ROevtqz2K48ePY+XKlSoDoH///m75bP4uIk6HJ1YBl9wOtY63Jj4QEREREZV8V7xotAV3Lj6BiDheFF+jM+tcXigAgnkxbdo0tZ41axb27NlTsn/NmjV466231Bj1cePGlTrm1ltvVen2X3/9NRYtWlSyPy0tDffdd19JlXl7vXv3VoG6POf+++8v2W8ymTBx4kTVoz958mQEBQXV2mf1xz/Sfa+1riNi+Y+WiIiIiM4ICtMhLBaVznSUl84r5q0M5uotpza8iR3vdMeuD9g56iydJvMzeZHvv/9eVVS0WbdunZpCqk+fPiX7ZsyYUdJTLqZOnYo5c+aoaeOGDBmCoqIiLF26VB0nve9XX311uff58ssvcc0116jnXHDBBahfvz6WLVumxtjLDQJH0zPIzYK+ffvi1KlT6Nq1K5KSkrB+/Xrs378f/fr1w/LlyyusTC9VIWWsvkyJFWgF8KQqrtwESUhIYMExqnNsj+Rt2CbJ27BNkjeQKvavXg8c3qEhoW0xpn5uRGh46X7I4nxg969A+wsl8K+zU/U7NY1bbMeffUcaDCHVP95cmIWNbyQEZNzk89XsZfz7n3/+WW6//T55jr2XX34Z3bt3x2uvvaaC+ODgYJUmL0G/BNmOjBw5EitWrFA9+mvXrlU3ACQ4v/POOzF69GiHx7Rr1w5//fUXHn30USxZsgSL/7+9e4GOojwbOP5sbtxJggQRCZdwvxgQBEG0qK0IiFAQQcEKYlEEFNSi50OprdTaWgHFE/2Uo1AoIIIC0pRWWo+XitJwqQjIxXAHgYBAuAeS+c7z5tt1k92EzWazO5v5/84Zl52Zd2YYHt+dZ9533lm61AyMp/uZPHlypX/FXHmdPSFSs07ReWdOiNRIitQRAQAAwI4OfydyaIeIVSCSsytOjmSLNLqmaCL/1gCR7zeLXNVO5KHlJPR24ypwSUwQXeYLeDVd9LbMV1ZOb5k/sPeInNxST1rdEuO5c6p3XLd+LtL6Jh38LtJHCaegxQl2Q0zCbohJ2Kll/uA2S1LSfFvmD2wU+d87RC6dF4mrKjImU+RqxqG2Vcv8dQ/nSFxC2ctfysuVtW+mODJvivqWeVQ+eud08YN15Nh3LqnfRmTMUhHL5a6gRRq0Enl0IQk9AAAACmlDj14ffvuZJXVa/iAJVesVOTXJDUWsGJFLlkhsTOF32IuroHAKphwCQzKPCnfkO5GjO+LEyhc5vFXkyA6RgpjCrlMFlwo/tStVanv+MQAAAPBjQp/WReRM0RdJGcf3i2j34piYwk/9Xr3Y45yILPfAdmWlOQMcMpp9tOnSpYt5Nj8jI0OcQu+U1royX2JiRa5sLVKvhciVzUXqtxCJiSv81O8AAACAtxqJJV9fxl4UiTlf+EnLfPlpfqJ5iuYroaDPywc7ITC0zIeZjn7vpGc/tIv93CEuObs3VpJTRR5c8OPgJNp1imfmAQAAUFYn9hW2SmrDUMz/f6dlvnzGjRtnJvcz7+UVk184BVMOgaFlHhUqZ7vIka2F3WVOHSisaL27TjXrwrPyAAAAKJuUliIprcT0/NRP/Q44Dck8KpRWrPVai7hiRWo1EElKLbqc19IBAAAgGNq93j3Bftwt88FMCAzJPCqUdqm/f5ElNa7Ol5OHRGbfU9j1HgAAAAhWzjaRo1tFJL/wU7/DXnhmvuKRzKPCndgvcvpwrBR4jWYPAAAABMt0rW8l4nL9+GfYS0xBkC3zvJouYAyAhwqX1FCk5pX5cuZwnGc0ewAAAKA8XJaIK7/wE/ZjEvMgmo7pZh84WuZRobRL/cIBLsnLjpUr6og88O6Po9kDAAAAwTBd67cUDrKsn6bLPeAwtMyjQmnFemSLiFwSObNP5OQeXhsCAACA8klsLOLS7tgXRFwJhd9hL64gW+a1HAJDMo8KVVe71bcVOfSNSL12hd8BAACA8tAGIpd2M44v/KTByKYD4MXov05gdu98XXbvekMs7W6BgNDNHhVKu9QPXmRJ86GnzSdd7AEAABCSBqN2IrEJNBjZVVkHvktrPFZuvfkb+cmNX0X60KMGLfOoUGd/EJl5rUvyztSS7ctEJm2jmz0AAABC8Prjj0V2fiSS1osxmeyIAfAqHi3zqFA7VonknSn8s37qdwAAACAUCX1KexJ5OBfJfJh16dJF2rZtKxkZGeIELW4TSahe+OeEGoXfAQAAgJDgtXQho/mJ5imar4QC75mveHSzD7OsrCypXbu2OOmO6YBXLdm77aTc+liiVK8T+CAYAAAAQGmvQM7ZLFLralrnQ2HcuHFmys3NlcTExNAMgOdyBVUOgSGZR4VWsHNvFTm8ySVJzWtI/NOcbAAAAITyOlPkyvaFz88z0LINn5l3BVcOgaGbPSr8HfMFl0ROfBdnvgMAAAChus60LhV+cp0Z/aPZe0+lWbdunfzhD3+QQYMGScOGDcXlcpnJiWiZR4W/Y17vmCa3uiR1WxNuAAAACO11pn7qdzjD1KlTZfny5ZE+DFsgu0KFvzIk+yNLaqb/IPHV6nG2AQAAELLrTF5N57xu9t27d5f09HQzUJ9OTZo0kQsXLogTkcyjwiva1BtFTl3kRAMAACC015mNbuJZebtyBZnMa7nSPP00A3G5kcyjwlVLFjl1hBMNAACAEF9n1uGM2lVMgSuokem1HAJDMg8AAAAACH03+yDLITCMZg8AAAAAQJShZR4AAAAAEJGW+fyCC5Jv/TiA3aX8XP4lAkQyDwAAAACISDK/4fCLsiHnec5+EEjmw0xfnxAbGyvjxo0zEwAAAABEWkZGhpny8/PDmsx3qvM/0iH5Cc/3vPxcWZDdKCTHUNmRzIdZVlaW1K5dO9y7BQAAAIASuRsbc3NzJTExMWzJfIxUkXip4vUdgeJcAQAAAAAQZWiZBwAAAACElGmZt4IoV8A/RKBI5gEAAAAAIRWT75IYy1X2cgVlL+NUJPMAAAAAgJByBdky77pMy3xmZqZMnTrV8z0vL898duvWzTNvypQpcscdd0hlRzIPAAAAAIiKbvY5OTmyZs0an/ne83QdJyCZBwAAAABEhZEjR5oJJPMAAAAAgBBjALyKR8s8AAAAACCkSOYrHsk8AAAAACCk9Nn3oJ6ZD6KMU5HMAwAAAABC3zIfxFvmSOYDF1OGdRECXbp0kbZt20pGRgbnEwAAAIAtaH6ieYrmK4gOJPNhlpWVJVu2bJFx48aJU1y4cEFefvll8wlEGvEIuyEmYTfEJOyEeAwfzU80T9F8JRRiLgU/ITAuy7J4KiEMcnNzJTExUU6ePCm1a9cWJzlx4oQkJyfL8ePHJSkpKdKHA4cjHmE3xCTshpiEnRCP0Ze3uMtPij8pVVyBl1+bn2GmAsmXH2S7I/OmsqJl3gHo0m+f88Ax2Oc8RJodzgHHYJ/zYAd2OA8cg33Ogx1E+jxEev8cg70QD0E+M1+GqauMk7GxW2R0TGh6BjgBybwD2KHysQM7nAeOwT7nIdLscA44BvucBzuww3ngGOxzHuwg0uch0vvnGOyFeCg7V0HZE3qdtBwCw2j2YeJ+mkG7nYRbfn5+RPbr5t63fsbERO7+UaTPA8dgj/NAPNrj34Fj+BExSTzY7f8LYtIe/w4cQyHiMfzx4N5HeZ/GviC5YS3nRDwzHyb79++X1NTUcO0OAAAAAIK2b98+adiwYZnLnT9/Xpo2bSqHDh0Ket/169eXXbt2SdWqVYPehhOQzIdJQUGBHDx4UGrVqiUuVxAvXAQAAACACqYt8qdOnZIGDRoE3atWE/q8vLygjyEhIYFEPgAk8wAAAAAARBkGwAMAAAAAIMqQzAMAAAAAEGVI5h0oJydHfvWrX0mrVq2kWrVqUqdOHenUqZNMmjTJ7/orVqyQnj17Su3atc108803S2ZmZqnjA7z55pvSvXt3s74+86KDZwwbNkz++9//+i2j4wiUNulzN/6cO3dOfv3rX0vLli3NczX6bM+oUaPkwIEDQZ4dVMaYVPPnz5cePXqYcStq1qwpXbp0kVmzZpU6Umuw8TVnzhzp2rWr2Y/+Xfr27SurV68O8Gwg0uwYj7rN0urIv//97yXui3h0TkwePXpU3n77bXnooYekY8eOEhcXZ+JDY+ByNm/eLHfffbekpKSYfVxzzTXyyiuvmN/0khw/flwmTJggjRs3lipVqpjPiRMnyokTJ0odjXvGjBlm+7of3d+QIUPk22+/LeNZQSTZMSabNGlSaj25detWv+WISUQ1C46ydu1a64orrtCrRatdu3bW0KFDrT59+liNGze2YmNjfdafMWOGWTcuLs7q3bu3NWDAAKtatWpm3muvveazfkFBgTVw4ECzXNfr1auXdffdd1tt2rQx8+Lj463MzEyfcrqsRo0a1ogRI/xOeXl5PmXOnTtndevWzZS96qqrrCFDhlhdu3Y131NSUqzs7OwQnjlEa0yqMWPGmOUJCQlWz549rb59+1pJSUlmnsaXP8HG14QJEzzxr8d2++23m2PVv8vSpUvLebbg1HjU9XT5XXfd5beO3Lhxo99yxKOzYlLrGF2v+DR79uxS97F69WpP3Go9p/Vd/fr1zXf9Ddff9uJycnKs5s2bm3XS0tJMGT0+/d6yZUvr2LFjPmXy8/M91wga8xrPGtsul8uqXr26tWbNmhCcMTg1JnX/7nrU33Tw4EGfMsQkoh3JvIMcOXLEqlu3rvnBXL58uc/y4j+iW7duNZVylSpVTKXqtm3bNlOJ68Xrjh07ipTR7WpF2qRJE+vAgQNFlv3xj3/0LCtO52slXBbPPPOMKde9e3fr1KlTnvnTpk0z8/UCAfYWjphcsmSJiYfk5GRzAeKmP+rt27c3yxYsWBCS+Fq1apVZpseyfft2z3w9Vk3c9OL1+PHjZTpHCB87x6M7md+1a1fAfx/i0XkxqXE4duxY65133rG++eYba/To0ZdNnPRmedOmTc1606dP98zXek/rv5LKDx8+3CwbNGiQdfHiRc/8Rx99tMQbU7NmzTLLWrRoYR06dMjn/wu9OeC9LdiPnWPSncyXBTGJaEcy7yCPPPKIqeQyMjLKtL627BSnlasuGz9+fJH5Tz75pJn/4osv+pTRu6iJiYlm+eHDh8uVzF+4cMGzrfXr1/ssT09PN8u8L5bhzJj86U9/aua/8MILPmU++ugjs6xjx44hiS9tmdD52lpb3GOPPWaWvfzyywH9XRF+do3HYJN54tF5MVncww8/fNnEadGiRWadDh06+Cxbt26dWaY3mrzpzaeYmBhzk9I7KVfnz583vZf0Rlfx33p3Lz1/vZT69+9vlmliD/uya0wGm8wTk4h2JPMOcfbsWatWrVqmK7v+ORCNGjUyleLnn3/us2zv3r1+E/DJkyeXmMwrbZnUH3j9sS9PMv/xxx+bMs2aNfO7/PnnnzfLn3vuuYC3icoZk+7uy1988YVPGU3a9YJUl+/Zs6dc8aV/B22h1fn79u3zKfPZZ5/RY8TG7ByPwSTzxKMzYzKYxOn+++8360ydOtXvcu1CXzz2tJVV5+nNKX9GjRrls9+dO3d6HkHy9+jc3LlzS33UBJFn55gMJpknJlEZxEX6mX2Ex9q1a+XUqVNy4403mkFEVq5cKatWrTIDy+ngXjr4jA7u5aaD1+zdu9f8+dprr/XZXmpqqtStW1f27Nkjubm5ZtAn1atXL/n9739vBsC7//77i2zzpZdeMtsdMWKEGSinuDNnzsgLL7xg9lu9enWz30GDBpnBoYr7+uuvzacOtuKPe/7GjRuDOFuoTDGpcaWSk5N9yujgjBpfur7GVKNGjYKOr23btsmFCxfMQD064GMgZWAfdo5HbzqQ1LFjxyQmJsYc189//nO/6xGPzovJYAVS3+3cudPUXTrAWKBl3nnnnSL1nbtM+/btJT4+3m8ZRR1pX3aOSW9/+tOfJDs721xrtmvXTgYOHGh+m0vaDzGJaEYy7xBbtmwxn/Xq1TMXf8uXLy+yfPLkyeYi8d577zXf3RepesFZo0YNv9vUhEVHKdWLVR1hVOmIzjqSqVakzZs3l5/85CfmInbTpk3y3XffyciRI+X111/3uz3d1rPPPltk3hNPPCF//vOf5Y477igy3318/pIm7/l6bHB2TOoP+MGDB828Nm3aFFn/hx9+MIlT8VgJJr4uV0aPOSkpyYz+rBdDOoo57MPO8ejtd7/7XZHvOpr0lClTzOSNeHReTAarIuq7UJWBvdg5Jr099dRTRb4//vjj8tprr5m30YRyP4Ad8Go6h9AEQn344YfmFUYZGRly5MgR2b17t7kY1FdwaYu5+9Vxp0+fNp/aQl4S9wWsJibetAVeXx1y8eJF+cc//iGLFy82r5zRV9bcdttt5m5ucdqKr8elr/zSfW/YsEF+8YtfmBYobZ3Pysoqsv7ljq+kY4PzYlJvKCl/r8HRliM37zLBxFd5/p9B5Nk5Ht3l5s2bZ1qbzp49a1retSeTvuZJX5/46quvFlmfeHReTAarIuq7UJWBvdg5JlX//v3lgw8+MMm31pPakKSNQtpr7pe//KXPzQdiEpUBybxDuN/JeenSJXn++edl7NixpoVIE2xtRdf3eGryrX8uD60whw4dKk8++aS5Q7tr1y7T0vTxxx+b93QPHz7c7z609f3222833bO0ktZ3kc6dO9dsIy8vz6fFHtEvXDGpFxia8CxatMjcrdc78dpaqo+CaBKky5R2W4Zz2T0e9Zjuu+8+SUtLMzdEtUur1o/Lli0zy3/zm9+YC2lUHuGKSaCyxOTMmTNNl3p99EjrSe1iP23aNHnjjTf0QXp5+umnI3JcQEXi6tUhvJ87f+CBB3yWu+d9+umnRdbXO5slcT/76d1d+MUXX5T33ntPxo8fL7/97W/Ns0y6/JZbbpHMzEyTqOtFp168BkIvdmNjY+WTTz4xSX3xv09Jx+fv2ODMmOzcubPMnj3b3EzSCwy96NCLjzFjxsitt94q/fr183mGOZj4Cvb4YA92jsfS6Dgl1113nXmGf82aNT5/H+LROTFZ3v2Esr4LVRnYi51jsjQPPvigeTRAezRpL4KK2g8QCSTzDqEXjO4uS/4GAXEPIKLdpZR7QCXtUuWuzIrbv39/kW0r7QaqBg8e7LO+bvP66683lea6desCOu7ExERTAWsir13uvbflfQyBHBucGZNKWzR1zIbp06ebpGnixImyYsUKM+Xk5Jh19A5+eeLrcmX0mDXh0iSNCwP7sXM8Xk6LFi3M5/fff++ZRzw6LyaDVRH1XajKwF7sHJOl0Z5OzZo1K3M9SUwiGpDMO4R7tGXthqld4YvTgZe871LqQF3uSk6fXy9u3759pnVdK1L3KM3eFZ8m4f6457ufuwqkS5d7QCjvQaY6dOhgPtevX++3nHt+enp6QPtB5Y1Jt6uvvtoMgqPd7WbMmGFaQHUEXn22T5Nr71Fzg4mvVq1amZFzNRnTsR8CKQP7sHM8Xo67PvWuI4lH58VksIKp78pTRp9j1q7YgZSBvdg5JoOpJ4lJVAYk8w6hF51aaekzQ/66P7nneb9iyT2C/JIlS3zWd8+78847i8yvX7++5/UlxeXn53suev29SsQfHWBFW730jqr3BXGPHj3MjQEdDMrfQCslHR+cF5Ol0QHHNL50sEXvgRmDiS8tr92klQ76GIrjQ/jYOR5LozePPv/8c/Nn7xsAxKMzYzIYpcWx/mbrK8D01V3ev9u9e/c2rZ0ae8VbYTXJ014m+ohc3759PfObNm1q3uCgiaA+dlccdaT92TkmS7N582bTxV57FLRu3dozn5hEpRDpF90jfObPn2/pP/k111xjHTx40DN/w4YNVp06dcyy9957zzN/69atVmxsrFWlShXryy+/9Mzfvn27dcUVV1hxcXHWjh07iuzjscceM9tp2LChtW3bNs/8S5cuWU899ZRZ1rhxY+vixYueZQsXLrT+85//+BzvJ598YjVo0MCUmT59us/yZ555xiy74YYbrNOnT3vmT5s2zczv2bNn0OcKlScmVVZWls+8ZcuWWdWrV7fq1q1r5eTkhCS+Vq1aZZbpsegxua1evdocc1JSknX8+PEynSOEj13j8YsvvrCWLl1q6lFvu3btsnr06GGOq3///j7bJB6dF5PFPfzww2ad2bNnl7hOXl6e1bRpU5/fWq33unfvXmL54cOHm2V33XVXkd9093XAiBEjfMrMmjXLLGvRooV1+PBhz/z333/fzG/evHmRbcF+7BqTmZmZ1r/+9S+fbX399ddWmzZtTBmNzeKISUQ7knmH0R9XrdA0qejbt691yy23mAtRnTd69Gif9bUS1WV6UdqnTx9rwIABVrVq1cy8mTNn+qx/9OhRq1WrVma5ble3rz/0aWlpZp6WLV7Zuo+pZcuW1sCBA60hQ4ZYHTt2NPN0uueee6z8/HyffZ07d866/vrrzTpXXXWVKef+npKSYmVnZ4f47CEaY1LpsmbNmln9+vWzhg4darVr186TdPtLrMoTXxMmTDDraGKmx6bHqMeqSZ8mZLA3O8ajXrTq8vr165tjGjZsmEniq1atauZree/EyBvx6LyY1HrKPdWrV8+sp7/B7nmPPPKITxm9YeSOW11H6zut9/T74MGDrYKCAp8yetNJ49gdzxrL7du39yTrx44d8ymjv+X6O6/rJCcnm23ffPPNlsvlMvv/6quvQnjm4KSYfO655zwNRnpzU68du3btaupmna9xdvbsWZ/9EJOIdiTzDqOV31tvvWV17tzZJBs1atQwdznnzJlTYpkPP/zQuummm6yaNWuaSf+8YsWKEtfPzc01lWp6errZfnx8vNWoUSNT+W/ZssVn/b/97W/mDn/r1q3ND4NWvFrZ64Xx4sWLS/37aMU8ZcoUcyGRkJBgLnZHjhxp7du3r4xnBpU5Jh9//HHr2muvNfGlFxx6ofnEE0+UmACVN740+XL/fXSfvXv3NhcmsD87xqPWm3qx26lTJ3MjSevIxMREq1u3bqaniL8LVG/Eo7Ni0n0jvKSppF5rmzZtMjff9aaS3ijSm0R6s8rfzXQ3TdgfffRRKzU11dSR+qmtn6X1QNIeJhq3un3dj+5Pk7PNmzcHcXYQCXaMSe0BN2rUKNNjwN0zSnsKaBKvre/FezZ5IyYRzVz6n0h39QcAAAAAAIFjADwAAAAAAKIMyTwAAAAAAFGGZB4AAAAAgChDMg8AAAAAQJQhmQcAAAAAIMqQzAMAAAAAEGVI5gEAAAAAiDIk8wAAAAAARBmSeQAAAAAAogzJPAAAAAAAUYZkHgAAG5gzZ464XC4z/fvf//ZZblmWpKammuX9+vXzzNfv48eP93zfvXu3Zzs6xcfHS926deWGG26QyZMny969e8P2dwIAABWHZB4AABupWrWqLFiwwGf+p59+Kvv375cqVaoEtJ17771X5s2bJ2+//bZMmTJF0tLS5JVXXpE2bdrIu+++WwFHDgAAwikurHsDAACl6tu3ryxevFhmzpwpcXE//kxrgt+5c2c5evRoQGewU6dOct999xWZt2fPHunVq5eMGDHCJPUdOnTgXwMAgChFyzwAADaiLerHjh2TVatWeebl5eXJkiVLZNiwYeXaduPGjU13ft3eSy+9FIKjBQAAkUIyDwCAjTRp0kS6d+8uCxcu9MxbuXKlnDx5Uu65555yb1+33axZsyI3CwAAQPQhmQcAwGa0BX7ZsmVy7tw5833+/PnSs2dPadCgQUi23759e8nJyZHc3NyQbA8AAIQfyTwAADYzZMgQk8j/9a9/lVOnTpnP8nax91azZk3zqdsGAADRiQHwAACwmZSUFPnZz35mBr07e/as5Ofny+DBg0O2/dOnT5vPWrVqhWybAAAgvEjmAQCwIW2JHz16tBw6dEj69OkjSUlJIdv2pk2bpF69elK7du2QbRMAAIQX3ewBALChgQMHSkxMjHz11Vch7WL/5ZdfSnZ2tnlFHQAAiF60zAMAYEP6XPsbb7whu3fvljvvvDMk29T3zI8cOVISEhJk0qRJIdkmAACIDJJ5AABsasSIEUGXXb9+vfzlL3+RgoICOXHihGRlZcn7778vLpdL5s2bJ+np6SE9VgAAEF4k8wAARCnLssxnbGyszzJ9T71OcXFx5tn4Fi1ayMSJE2XMmDHSqFGjCBwtAAAIJZflvhIAAABRRd8Tn5iYKM8++6xMnTo10ocDAADCiAHwAACIUtp1XrVt2zbShwIAAMKMlnkAAKLMxo0b5Z///KdMnz5dzp8/Lzt37uQ1cwAAOAwt8wAARJkPPvhAJk+eLE2aNJGVK1eSyAMA4EC0zAMAAAAAEGVomQcAAAAAIMqQzAMAAAAAEGVI5gEAAAAAiDIk8wAAAAAARBmSeQAAAAAAogzJPAAAAAAAUYZkHgAAAACAKEMyDwAAAACARJf/A4Sg5B6WIdEsAAAAAElFTkSuQmCC",
      "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_73894/2193692466.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: -1.82%\n",
      "Std flux difference: 10.04%\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"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}