Source code for rubin_sim.maf.maf_contrib.star_count_metric

__all__ = ("StarCountMetric",)

import numpy as np

from rubin_sim.maf.metrics import BaseMetric

from .star_counts import starcount

# Example for CountMetric
# Mike Lund - Vanderbilt University
# mike.lund@gmail.com
# Last edited 8/15/2015
# Motivation: The distances to stars in LSST will be significant enough
# that the structure of the Galaxy will be readily apparent because of
# its influence on the number of stars in a given field.
# Any metric concerned with the number of potential objects to be
# detected will need to feature not only the effects of the cadence
# but also the number of objects per field.
# This metric identifies the number of stars in a given field in a
# particular distance range.
# D1 and D2 are the close and far distances in parsecs.
# Requires StarCounts.StarCounts

# NOTE
# There are stellar luminosity function maps available within MAF
# that may supersede these StarCount functions




class StarCountMetric(BaseMetric):
    """Find the number of stars in a given field between d1 and d2 in parsecs.

    This metric uses the stellar distance and luminosity equations
    contributed by Mike Lund, which are based on the Galfast model.
    There are some imposed limitations on the expected magnitudes
    of the stars included for the metric, based on assuming saturation
    at 16th magnitude and not considering stars with magnitude
    uncertainties greater than 0.03 (based on photometry/m5 alone).


    Parameters
    ----------
    d1 : `float`
        d1 in parsecs
    d2 : `float`
        d2 in parsecs
    """

    def __init__(self, d1=100, d2=1000, **kwargs):
        self.d1 = d1
        self.d2 = d2
        super(StarCountMetric, self).__init__(col=[], **kwargs)



    def run(self, data_slice, slice_point=None):
        self.dec_col = np.degrees(data_slice[0][3])
        self.ra_col = np.degrees(data_slice[0][2])
        return starcount(self.ra_col, self.dec_col, self.d1, self.d2)