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lsdb.loaders.hipscat

lsdb.loaders.hipscat#

Submodules#

Package Contents#

Functions#

read_hipscat

read_hipscat(path: str, catalog_type: Type[lsdb.catalog.dataset.dataset.Dataset] | None = None, search_filter: lsdb.core.search.abstract_search.AbstractSearch | None = None, columns: List[str] | None = None, margin_cache: lsdb.catalog.margin_catalog.MarginCatalog | None = None, dtype_backend: str | None = 'pyarrow', storage_options: dict | None = None, **kwargs) → lsdb.catalog.dataset.dataset.Dataset#

Load a catalog from a HiPSCat formatted catalog.

Typical usage example, where we load a catalog with a subset of columns:

lsdb.read_hipscat(path=”./my_catalog_dir”, columns=[“ra”,”dec”])

Typical usage example, where we load a catalog from a cone search:
lsdb.read_hipscat_subset(

path=”./my_catalog_dir”, catalog_type=lsdb.Catalog, columns=[“ra”,”dec”], filter=lsdb.core.search.ConeSearch(ra, dec, radius_arcsec),

)

Parameters:

  • path (str) – The path that locates the root of the HiPSCat catalog

  • catalog_type (Type[Dataset]) – Default None. By default, the type of the catalog is loaded from the catalog info and the corresponding object type is returned. Python’s type hints cannot allow a return type specified by a loaded value, so to use the correct return type for type checking, the type of the catalog can be specified here. Use by specifying the lsdb class for that catalog.

  • search_filter (Type[AbstractSearch]) – Default None. The filter method to be applied.

  • columns (List[str]) – Default None. The set of columns to filter the catalog on.

  • margin_cache (MarginCatalog) – The margin cache for the main catalog

  • dtype_backend (str) – Backend data type to apply to the catalog. Defaults to “pyarrow”. If None, no type conversion is performed.

  • storage_options (dict) – Dictionary that contains abstract filesystem credentials

  • **kwargs – Arguments to pass to the pandas parquet file reader

Returns:

Catalog object loaded from the given parameters

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