rail.interactive.creation.degraders.observing_condition_degrader module

rail.interactive.creation.degraders.observing_condition_degrader.obs_condition(**kwargs)

Photometric errors based on observation conditions

This degrader calculates spatially-varying photometric errors using input survey condition maps. The error is based on the LSSTErrorModel from the PhotErr python package.

mask: str, optional
    Path to the mask covering the survey
    footprint in HEALPIX format. Notice that
    all negative values will be set to zero.
weight: str, optional
    Path to the weights HEALPIX format, used
    to assign sample galaxies to pixels. Default
    is weight="", which uses uniform weighting.
    tot_nVis_flag: bool, optional
    If any map for nVisYr are provided, this flag
    indicates whether the map shows the total number of
    visits in nYrObs (tot_nVis_flag=True), or the average
    number of visits per year (tot_nVis_flag=False). The
    default is set to True.
map_dict: dict, optional
    A dictionary that contains the paths to the
    survey condition maps in HEALPIX format. This dictionary
    uses the same arguments as LSSTErrorModel (from PhotErr).
    The following arguments, if supplied, may contain either
    a single number (as in the case of LSSTErrorModel), or a path:
    [m5, nVisYr, airmass, gamma, msky, theta, km, tvis, EBV]
    For the following keys:
    [m5, nVisYr, gamma, msky, theta, km]
    numbers/paths for specific bands must be passed.
    Example:
    {"m5": {"u": path, ...}, "theta": {"u": path, ...},}
    Other LSSTErrorModel parameters can also be passed
    in this dictionary (e.g. a necessary one may be [nYrObs]
    or the survey condition maps).
    If any argument is not passed, the default value in
    PhotErr's LsstErrorModel is adopted.

—

The main interface method for Noisifier.

Adds noise to the input catalog

This will attach the input to this Noisifier

Then it will call the _initNoiseModel() and _addNoise(), which need to be implemented by the sub-classes.

The _initNoiseModel() method will initialize the noise model of the sub-classes, and store the noise model as self.noiseModel

The _addNoise() method will add noise to the flux and magnitude of the column of the catalog.

The finalize() method will check the end results (like preserving number of rows)

Finally, this will return a PqHandle providing access to that output data.

—

This function was generated from the function rail.creation.degraders.observing_condition_degrader.ObsCondition.__call__

Parameters:

  • sample (TableLike, required) – The sample to be degraded.

  • seed (int, optional) – random seed for reproducibility Default: 42 An integer to set the numpy random seed, by default None.

  • nside (int, optional) – nside for the input maps in HEALPIX format. Default: 128

  • mask (str, optional) – mask for the input maps in HEALPIX format. Default: rail/examples_data/creation_data/data/survey_conditions/DC2-mask-neg- nside-128.fits

  • weight (str, optional) – weight for assigning pixels to galaxies in HEALPIX format. Default: rail/examples_data/creation_data/data/survey_conditions/DC2-dr6- galcounts-i20-i25.3-nside-128.fits

  • tot_nVis_flag (bool, optional) – flag indicating whether nVisYr is the total or average per year if supplied. Default: True

  • map_dict (dict, optional) – dictionary containing the paths to the survey condition maps and/or additional LSSTErrorModel parameters. Default: {‘m5’: {‘i’:…}

Returns:

A handle giving access to a table with degraded sample.

Return type:

pandas.core.frame.DataFrame