Dark Energy Survey (DES)

The des module provides access to data from the Dark Energy Survey (DES). It includes photometric data used in the cosmological analysis from the first 3 years of spectroscopically classified supernovae (SNe).

Data Release Class Name Data Type Publication
Third Year Cosmology Release SN3YR Photometric Brout et al. 2019

Third Year Cosmology Release

class sndata.des.SN3YR[source]

The SN3YR class provides access to data from the first public data release of the Dark Energy Survey Supernova Program, DES-SN3YR. It includes griz light curves of 251 supernovae from the first 3 years of the Dark Energy Survey Supernova Program’s (DES-SN) spectroscopically classified sample. (Source: Brout et al. 2019)

Deviations from the standard UI:
  • None
Cuts on returned data:
  • None
delete_module_data() → None

Delete any data for the current survey / data release

download_module_data(force: bool = False, timeout: float = 15)

Download data for the current survey / data release

Parameters:
  • force – Re-Download locally available data
  • timeout – Seconds before timeout for individual files/archives
get_available_ids() → List[str]

Return a list of target object IDs for the current survey

Returns:A list of object IDs as strings
get_available_tables() → List[Union[str, int]]

Get Ids for available vizier tables published by this data release

get_data_for_id(obj_id: str, format_table: bool = True) → astropy.table.table.Table

Returns data for a given object ID

See get_available_ids() for a list of available ID values.

Parameters:
  • obj_id – The ID of the desired object
  • format_table – Format data into the sndata standard format
Returns:

An astropy table of data for the given ID

classmethod get_zp_for_band(band: str) → str

Get the zeropoint for a given band name

Parameters:band – The name of the bandpass
iter_data(verbose: bool = False, format_table: bool = True, filter_func: bool = None) → astropy.table.table.Table

Iterate through all available targets and yield data tables

An optional progress bar can be formatted by passing a dictionary of tqdm arguments. Outputs can be optionally filtered by passing a function filter_func that accepts a data table and returns a boolean.

Parameters:
  • verbose – Optionally display progress bar while iterating
  • format_table – Format data for SNCosmo (Default: True)
  • filter_func – An optional function to filter outputs by
Yields:

Astropy tables

load_table(table_id: Union[int, str]) → astropy.table.table.Table

Return a Vizier table published by this data release

Parameters:table_id – The published table number or table name
register_filters(force: bool = False)

Register filters for this survey / data release with SNCosmo

Parameters:force – Re-register a band if already registered