HEALPix Finalize

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finalize_statistics

 finalize_statistics
                      (state:Dict[int,healpyxel.accumulator.CellAccumulato
                      r], percentiles:Optional[List[float]]=None,
                      min_count:int=1)

*Convert accumulator state to final statistics DataFrame.

Args: state: Accumulator state dictionary {healpix_id: CellAccumulator} percentiles: List of percentiles to compute (e.g., [25, 50, 75]) min_count: Minimum observations required per cell (cells below this are NaN)

Returns: DataFrame indexed by healpix_id with statistics columns: - {col}_n: observation count - {col}_mean: mean value - {col}_std: standard deviation - {col}_min: minimum value - {col}_max: maximum value - {col}_p{N}: percentile (if T-Digest available)*

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densify_healpix_map

 densify_healpix_map (sparse_df:pandas.core.frame.DataFrame, nside:int,
                      fill_value:float=nan)

*Create a complete HEALPix grid by filling empty cells with fill_value.

Args: sparse_df: DataFrame with healpix_id index (sparse) nside: HEALPix nside parameter fill_value: Value for empty cells (default: NaN)

Returns: Dense DataFrame with all 12*nside**2 cells*

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export_to_geotiff

 export_to_geotiff (df:pandas.core.frame.DataFrame, column:str,
                    output_path:pathlib.Path, nside:int,
                    crs:str='IAU:19900')

*Export a column to GeoTIFF format (requires rasterio and healpy).

Note: This creates an equirectangular projection from HEALPix data.*

	Type	Default	Details
df	DataFrame
column	str
output_path	Path
nside	int
crs	str	IAU:19900	Mercury IAU CRS

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main

 main (argv=None)

Usage Example

See the main() function for CLI usage, or import functions directly for programmatic use.