`cadence`#

Module Contents#

Classes#

Attributes#

class cadence.LSSTCadence(out_dir)[source]#

min_mjd = 59580.139555[source]#

nside_in = 32[source]#

nested = False[source]#

fov_radius = 1.75[source]#

bp_to_int[source]#

int_to_bp[source]#

bp[source]#

get_pointings_single_hp(hp: int, n_pointings_init: int)[source]#

Get pointing positions from a single healpix, upgrading it if necessary

hpint: a single healpix id in DC2 (NSIDE=32, nested)
n_pointings_initint: how many pointings to get from this healpix

tuple: ra, dec of pointings

get_pointings(n_pointings_init: int)[source]#

Get pointing positions all over the DC2 field

n_pointings_initint: how many pointings to get

tuple: ra, dec of pointings

get_obs_info(ra: numpy.ndarray, dec: numpy.ndarray, skip_existing=True, min_visits=0, skip_ddf=True)[source]#

Loop through pointings and query visits that fall inside FOV (run at generation time)

After DDF rejection, we might end up with a final n_pointings different from n_pointings_init

bin_by_day(bandpasses=list('ugrizy'), skip_existing=True)[source]#

Bin the observations by day, trimming days that weren’t observed in any filter and in any pointing (run at generation time)

bandpasseslist: Bandpasses to base binning on
skip_existingbool, optional: whether to skip operations for pointings already saved to disk

get_observed_mask()[source]#: Get trimmed MJD that is observed in at least one band at all times

get_trimmed_mjd()[source]#: Get trimmed MJD that is observed in at least one band at all times

get_trimmed_mask(i: int, as_tensor=False)[source]#: Get trimmed mask that has times corresponding to trimmed_mjd

get_mjd_single_pointing(i: int, rounded: bool)[source]#

get_mjd_i_band_pointing(i: int, rounded: bool)[source]#

get_mask_single_pointing(i: int)[source]#

load_opsim_db()[source]#: Load the OpSim database with relevant columns as an iterator

cadence.cadence_obj[source]#