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[READ-ONLY] Mirror of https://github.com/emilyhunt/hr_selection_function. Selection function for the Hunt & Reffert 2024 open cluster catalogue.
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4.2 kB · 175 lines
Python
at main
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176from hr_selection_function.gaia import ( M10Estimator, MSubsampleEstimator, GaiaDensityEstimator,)import numpy as npimport healpy as hp
pixels_for_testing = [0, 57, 5893, 58932, 3, 382, 382, 159532, 9694, 196607]
def test_M10Estimator(): model = M10Estimator()
# Some values looked up manually from the GaiaUnlimited package test_values = [ 21.0278, 20.9648, 21.0118, 20.9611, 20.9353, 20.9351, 20.9351, 21.0907, 20.9455, 21.0904, ]
# Convert into ra/dec ra, dec = hp.pix2ang(2**7, pixels_for_testing, nest=True, lonlat=True)
result = model(ra, dec) np.testing.assert_allclose(result, test_values)
def test_MSubsampleEstimator(): model = MSubsampleEstimator()
# Some values looked up manually from the dataframe test_values = [ 20.473399, 20.460272, 20.783859, 20.615404, 20.396479, 20.648832, 20.648832, 20.727514, 20.797851, 20.266360, ]
# Convert into ra/dec l, b = hp.pix2ang(2**7, pixels_for_testing, nest=True, lonlat=True) # noqa: E741
result = model(l, b) np.testing.assert_allclose(result, test_values)
def test_GaiaDensityEstimator(): l, b, pmra, pmdec, parallax, result_expected = _get_test_density_data()
model = GaiaDensityEstimator() result_actual = model(l, b, pmra, pmdec, parallax)
np.testing.assert_allclose(result_actual, result_expected)
def _get_test_density_data(l_and_b=True): l = [ 162.9045963311823, 222.2312721732947, 128.44871235039162, 160.9499288226896, 213.06037341723444, 199.36275026706875, 128.60961396338558, 136.28666583570796, 125.97131795417525, 213.97631324679773, ] b = [ -0.9346927099010592, 3.6108482027563507, 1.9453330185828903, 0.2056845242850199, 1.1661362043217294, 19.410708776697685, 0.12021936533026821, 1.3539080788454123, -1.75718947932212, 1.1693380678294931, ] ra = [ 73.32579352199228, 110.35512999194107, 25.645086126893748, 72.82866993029752, 103.95590766540087, 114.8592052923773, 25.208684973667218, 41.51797920137684, 19.128741698462704, 104.3764145121306, ] dec = [ 42.41642894773442, -6.5928011091731085, 64.26790490403921, 44.650500836239445, 0.4174126564070922, 20.39438531322255, 62.44618488047631, 61.2175017009223, 60.966482841194676, -0.39608875827834383, ]
x, y = ra, dec if l_and_b: x, y = l, b
return [ x, y, [ -0.7766432588848509, -0.915231855730751, -1.6372068440755732, -0.2305765209103827, -0.4524758968610532, -0.9638938991196692, -0.5086517349842387, -1.0101726801170998, 0.0820812064803136, 0.6355885023846625, ], [ -0.14081969572092248, 0.9609431030745171, 0.12285028500838725, -0.024477925088355806, -0.0185474630769482, -0.8602342854349014, -0.3938208999571014, 0.5334403415731419, -0.1922518589849786, -0.6764031476209058, ], [ 0.08060393781080663, 0.12747343843901612, 0.1004291966661565, 0.08204558753982645, 0.11759992793618043, 0.15105175627504655, 0.07888521783700321, 0.09479025225955634, 0.11303189760716631, 0.06938962146299331, ], [ 32393.884212237157, 161238.37642755947, 223081.47449782598, 51176.42713227133, 111278.63400948483, 3853.1979999303608, 123062.78494792822, 76527.43449485092, 142593.45652828, 49079.85544204984, ], ]