survey.basesurvey

survey.basesurvey#

This module defines the generic Survey and GridSurvey classes, combining healpix and polygon survey capabilities with a camera footprint.

class skysurvey.survey.basesurvey._FootPrintHandler_[source]#

Bases: object

Mixin class handling footprint geometries for survey objects.

Parameters:

_FOOTPRINT (shapely.geometry.base.BaseGeometry or None) – Default camera footprint geometry used if no footprint is provided during initialization. Usually a Polygon or MultiPolygon.

_FOOTPRINT = None#
show_footprint(ax=None, add_text=False, **kwargs)[source]#

Shows the survey footprint.

Parameters:

  • ax (matplotlib.axes) – axes to plot the footprint on.

  • add_text (bool) – if True, adds text to the plot.

  • facecolor (**kwargs goes to matplotlib (e.g.)

  • edgecolor)

Return type:

matplotlib.figure

get_skyarea(as_multipolygon=True)[source]#

Multipolygon (or list) of field geometries.

Parameters:

as_multipolygon (bool) – if True, returns a multipolygon. Otherwise, returns a list of polygons.

Return type:

shapely.geometry.MultiPolygon or list

property footprint#

Camera footprint (geometry).

class skysurvey.survey.basesurvey.Survey(footprint=None, nside=200, data=None)[source]#

Bases: HealpixSurvey, _FootPrintHandler_

The Survey class.

Parameters:

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

  • nside (int) – healpix nside parameter

  • data (pandas.DataFrame) – observing data.

classmethod from_random(*args, **kwargs)[source]#

Not implemented

classmethod from_data(data, footprint=None, nside=200)[source]#

Load an instance given survey data and healpix size (nside) .

Parameters:

  • data (pandas.DataFrame) – observing data.

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

  • nside (int) – healpix nside parameter

Return type:

instance

See also

from_random

generate random observing data and loads the instance.

classmethod from_pointings(data, footprint=None, rakey='ra', deckey='dec', nside=200, backend='polars', use_pyarrow_extension_array=True, **kwargs)[source]#

Loads an instance given observing poitings of a survey.

This loads an polygon.PolygonSurvey using from_pointing and converts that into an healpix using the to_healpix() method.

Parameters:

  • data (pandas.DataFrame or dict) – observing data, must contain the rakey and deckey columns.

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

  • rakey (str) – name of the R.A. column (in deg)

  • deckey (str) – name of the Declination column (in deg)

  • nside (int) – healpix nside parameter

  • backend (str) – which backend to use to merge the data (speed issue): - polars (fastest): requires polars installed -> converted to pandas at the end - pandas (classic): the normal way - dask (lazy): as persisted dask.dataframe is returned

  • use_pyarrow_extension_array (bool) – = ignored in backend != ‘polars’ or polars_to_pandas is not True = should the pandas dataframe be based on numpy array (slow to load but faster then) or based on pyarrow array (like in polars) ; faster but numpy.asarray will be used by pandas when need (which will then slow things down).

  • polygon.PolygonSurvey.from_pointings (**kwargs goes to)

Return type:

instance

classmethod from_healpix(healpixsurvey, footprint)[source]#

Creates an instance given a heapixsurvey and a footprint.

Parameters:

  • healpixsurvey (HealpixSurvey) – healpix survey instance

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

Return type:

Survey

class skysurvey.survey.basesurvey.GridSurvey(data=None, fields=None, footprint=None, **kwargs)[source]#

Bases: PolygonSurvey, _FootPrintHandler_

The GridSurvey class.

Parameters:

  • data (pandas.DataFrame) – observing data.

  • fields (geodataframe) – field definitions.

  • footprint (shapely.geometry) – footprint in the sky of the observing camera.

classmethod from_pointings(data, fields_or_coords=None, footprint=None, **kwargs)[source]#

Loads an instance given observing poitings of a survey.

Parameters:

  • data (pandas.DataFrame or dict) – observing data, must contain the rakey and deckey columns.

  • fields_or_coords (geodataframe or dict) – field definitions or coordinates.

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

  • super().__init__ (**kwargs goes to)

Return type:

GridSurvey

classmethod from_logs(**kwargs)[source]#

Not implemented

classmethod _parse_fields(fields_or_coords, footprint=None)[source]#

Parse the fields from coordinates.

Parameters:

  • fields_or_coords (geodataframe or dict) – field definitions or coordinates.

  • footprint (shapely.geometry) – footprint in the sky of the observing camera

Return type:

geopandas.GeoDataFrame

property fields#

Geodataframe containing the fields coordinates.