lsdb.core.search

lsdb.core.search#

Submodules#

Classes#

`BoxSearch`	Perform a box search to filter the catalog. This type of search is used for a
`ConeSearch`	Perform a cone search to filter the catalog
`IndexSearch`	Find rows by ids (or other value indexed by a catalog index).
`OrderSearch`	Filter the catalog by HEALPix order.
`PixelSearch`	Filter the catalog by HEALPix pixels.
`PolygonSearch`	Perform a polygonal search to filter the catalog.

Package Contents#

class BoxSearch(ra: tuple[float, float], dec: tuple[float, float], fine: bool = True)[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Perform a box search to filter the catalog. This type of search is used for a range of right ascension or declination, where the right ascension edges follow great arc circles and the declination edges follow small arc circles.

Filters to points within the ra / dec region, specified in degrees. Filters partitions in the catalog to those that have some overlap with the region.

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → mocpy.MOC[source]#: Filters catalog pixels according to the box

search_points(frame: nested_pandas.NestedFrame, metadata: hats.catalog.TableProperties) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame

class ConeSearch(ra: float, dec: float, radius_arcsec: float, fine: bool = True)[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Perform a cone search to filter the catalog

Filters to points within radius great circle distance to the point specified by ra and dec in degrees. Filters partitions in the catalog to those that have some overlap with the cone.

ra#

dec#

radius_arcsec#

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → mocpy.MOC[source]#: Filters catalog pixels according to the cone

search_points(frame: nested_pandas.NestedFrame, metadata: hats.catalog.TableProperties) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame

_perform_plot(ax: astropy.visualization.wcsaxes.WCSAxes, **kwargs)[source]#: Perform the plot of the search region on an initialized WCSAxes

class IndexSearch(ids, catalog_index: hats.catalog.index.index_catalog.IndexCatalog, fine: bool = True)[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Find rows by ids (or other value indexed by a catalog index).

Filters partitions in the catalog to those that could contain the ids requested. Filters to points that have matching values in the id field.

NB: This requires a previously-computed catalog index table.

ids#

catalog_index#

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → lsdb.types.HCCatalogTypeVar[source]#: Determine the target partitions for further filtering.

search_points(frame: nested_pandas.NestedFrame, _) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame

class OrderSearch(min_order: int = 0, max_order: int | None = None)[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Filter the catalog by HEALPix order.

Filters partitions in the catalog to those that are in the orders specified. Does not filter points inside those partitions.

min_order = 0#

max_order = None#

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → lsdb.types.HCCatalogTypeVar[source]#: Determine the target partitions for further filtering.

search_points(frame: nested_pandas.NestedFrame, _) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame.

class PixelSearch(pixels: tuple[int, int] | hats.pixel_math.HealpixPixel | list[tuple[int, int] | hats.pixel_math.HealpixPixel])[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Filter the catalog by HEALPix pixels.

Filters partitions in the catalog to those that are in a specified pixel set. Does not filter points inside those partitions.

classmethod from_radec(ra: float | list[float], dec: float | list[float]) → PixelSearch[source]#

Create a pixel search region, based on radec points.

Parameters:

ra (float|list[float]) – celestial coordinates, right ascension in degrees
dec (float|list[float]) – celestial coordinates, declination in degrees

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → lsdb.types.HCCatalogTypeVar[source]#: Determine the target partitions for further filtering.

search_points(frame: nested_pandas.NestedFrame, _) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame

class PolygonSearch(vertices: list[tuple[float, float]], fine: bool = True)[source]#

Bases: lsdb.core.search.abstract_search.AbstractSearch

Perform a polygonal search to filter the catalog.

Filters to points within the polygonal region specified in ra and dec, in degrees. Filters partitions in the catalog to those that have some overlap with the region.

vertices#

polygon#

filter_hc_catalog(hc_structure: lsdb.types.HCCatalogTypeVar) → lsdb.types.HCCatalogTypeVar[source]#: Filters catalog pixels according to the polygon

search_points(frame: nested_pandas.NestedFrame, metadata: hats.catalog.TableProperties) → nested_pandas.NestedFrame[source]#: Determine the search results within a data frame