def test_compare_spec_type_inFOV(self):
"""
Test for compare_spec_type. Inputs and expected outputs created by
running generate_files_for_tests.py in beast-examples/metal_small.
In this version, the stars are in the imaging field of view.
"""
# download cached file
compare_spec_type_fname = download_rename(
f"{self.basename}_compare_spec_type.asdf")
with asdf.open(compare_spec_type_fname) as af:
compare_spec_type_info = copy.deepcopy(af.tree)
# run compare_spec_type
spec_type = compare_spec_type(
self.obs_fname_cache,
self.stats_fname_cache,
**compare_spec_type_info["input"],
)
# expected output table
expected_table = Table(compare_spec_type_info["output"])
# compare to new table
compare_tables(expected_table, Table(spec_type), rtol=2e-3)
def test_compare_spec_type_inFOV():
"""
Test for compare_spec_type. The spectrally-typed stars aren't real sources,
they're just invented for the purposes of documenting/testing the code.
In this version, the stars are in the imaging field of view.
"""
# download the needed files
obs_fname = download_rename("b15_4band_det_27_A.fits")
stats_fname = download_rename("beast_example_phat_stats.fits")
# run compare_spec_type
spec_type = compare_spec_type(
obs_fname,
stats_fname,
[11.2335881, 11.23342557], # RA
[41.9001895, 41.90006316], # Dec
['A', 'G'], # Spectral type
[2, 7], # Subtype
['II', 'II'], # Luminosity class
match_radius=0.2 # Match radius (arcsec)
)
# expected output table
expected_table = Table({
'spec_ra': [11.2335881, 11.23342557],
'spec_dec': [41.9001895, 41.90006316],
'spec_type': ['A 2 II', 'G 7 II'],
'spec_teff': [9000.0, 4916.666666666667],
'spec_logg': [2.7164474106543732, 1.7184474106543735],
'phot_cat_ind': [27, 8],
'stats_cat_ind': [27, 8],
'beast_teff_p50': [9046.250020338754, 4528.230977991138],
'beast_teff_p16': [8643.670633196869, 4335.617282355577],
'beast_teff_p84': [9536.391362054928, 4729.401710221546],
'beast_logg_p50': [2.714286917261312, 1.7684285714285717],
'beast_logg_p16': [2.636272525730954, 1.7014832653061227],
'beast_logg_p84': [2.799534708811963, 1.8353738775510207],
'teff_sigma': [-0.11488422362383206, 1.9308757510045778],
'logg_sigma': [0.025343687546173433, -0.7465969411324851]
})
# compare to new table
compare_tables(expected_table, Table(spec_type), rtol=2e-3)
def test_compare_spec_type_notFOV():
"""
Test for compare_spec_type. The spectrally-typed stars aren't real sources,
they're just invented for the purposes of documenting/testing the code.
In this version, the stars are NOT in the imaging field of view.
"""
# download the needed files
obs_fname = download_rename("b15_4band_det_27_A.fits")
stats_fname = download_rename("beast_example_phat_stats.fits")
# run compare_spec_type
spec_type = compare_spec_type(
obs_fname,
stats_fname,
[1.0], # RA
[1.0], # Dec
['B'], # Spectral type
[4], # Subtype
['V'], # Luminosity class
match_radius=0.2 # Match radius (arcsec)
)
# expected output table
expected_table = Table({
'spec_ra': [1.0],
'spec_dec': [1.0],
'spec_type': ['B 4 V'],
'spec_teff': [None],
'spec_logg': [None],
'phot_cat_ind': [None],
'stats_cat_ind': [None],
'beast_teff_p50': [None],
'beast_teff_p16': [None],
'beast_teff_p84': [None],
'beast_logg_p50': [None],
'beast_logg_p16': [None],
'beast_logg_p84': [None],
'teff_sigma': [None],
'logg_sigma': [None],
})
# compare to new table
compare_tables(expected_table, Table(spec_type))
def test_compare_spec_type_notFOV(self):
"""
Test for compare_spec_type. In this version, the stars are NOT in the
imaging field of view.
"""
# run compare_spec_type
spec_type = compare_spec_type(
self.obs_fname_cache,
self.stats_fname_cache,
[1.0], # RA
[1.0], # Dec
["B"], # Spectral type
[4], # Subtype
["V"], # Luminosity class
match_radius=0.2, # Match radius (arcsec)
)
# expected output table
expected_table = Table(
{
"spec_ra": [1.0],
"spec_dec": [1.0],
"spec_type": ["B 4 V"],
"spec_teff": [None],
"spec_logg": [None],
"phot_cat_ind": [None],
"stats_cat_ind": [None],
"beast_teff_p50": [None],
"beast_teff_p16": [None],
"beast_teff_p84": [None],
"beast_logg_p50": [None],
"beast_logg_p16": [None],
"beast_logg_p84": [None],
"teff_sigma": [None],
"logg_sigma": [None],
}
)
# compare to new table
compare_tables(expected_table, Table(spec_type))
def test_compare_spec_type_inFOV(self):
"""
Test for compare_spec_type. The spectrally-typed stars aren't real sources,
they're just invented for the purposes of documenting/testing the code.
In this version, the stars are in the imaging field of view.
"""
# run compare_spec_type
spec_type = compare_spec_type(
self.obs_fname_cache,
self.stats_fname_cache,
[11.2335881, 11.23342557], # RA
[41.9001895, 41.90006316], # Dec
["A", "G"], # Spectral type
[2, 7], # Subtype
["II", "II"], # Luminosity class
match_radius=0.2, # Match radius (arcsec)
)
# expected output table
expected_table = Table({
"spec_ra": [11.2335881, 11.23342557],
"spec_dec": [41.9001895, 41.90006316],
"spec_type": ["A 2 II", "G 7 II"],
"spec_teff": [9000.0, 4916.666666666667],
"spec_logg": [2.7164474106543732, 1.7184474106543735],
"phot_cat_ind": [27, 8],
"stats_cat_ind": [27, 8],
"beast_teff_p50": [9046.250020338754, 4528.230977991138],
"beast_teff_p16": [8643.670633196869, 4335.617282355577],
"beast_teff_p84": [9536.391362054928, 4729.401710221546],
"beast_logg_p50": [2.714286917261312, 1.7684285714285717],
"beast_logg_p16": [2.636272525730954, 1.7014832653061227],
"beast_logg_p84": [2.799534708811963, 1.8353738775510207],
"teff_sigma": [-0.11488422362383206, 1.9308757510045778],
"logg_sigma": [0.025343687546173433, -0.7465969411324851],
})
# compare to new table
compare_tables(expected_table, Table(spec_type), rtol=2e-3)
def generate_files_for_tests(run_beast=True, run_tools=True):
"""
Use the metal_small example to generate a full set of files for the BEAST
regression tests.
Parameters
----------
run_beast : boolean (default=True)
if True, run the BEAST
run_tools : boolean (default=True)
if True, run the code to generate things for tools
"""
# read in BEAST settings
settings_orig = beast_settings.beast_settings("beast_settings.txt")
# also make a version with subgrids
settings_subgrids = copy.deepcopy(settings_orig)
settings_subgrids.n_subgrid = 2
settings_subgrids.project = f"{settings_orig.project}_subgrids"
# ==========================================
# run the beast for each set of settings
# ==========================================
if run_beast:
for settings in [settings_orig, settings_subgrids]:
# -----------------
# physics model
# -----------------
create_physicsmodel.create_physicsmodel(
settings,
nsubs=settings.n_subgrid,
nprocs=1,
)
# -----------------
# ASTs
# -----------------
# currently only works for no subgrids
if settings.n_subgrid == 1:
make_ast_inputs.make_ast_inputs(settings,
pick_method="flux_bin_method")
# -----------------
# obs model
# -----------------
create_obsmodel.create_obsmodel(
settings,
use_sd=False,
nsubs=settings.n_subgrid,
nprocs=1,
use_rate=True,
)
# -----------------
# trimming
# -----------------
# make file names
file_dict = create_filenames.create_filenames(
settings, use_sd=False, nsubs=settings.n_subgrid)
# read in the observed data
obsdata = Observations(settings.obsfile, settings.filters,
settings.obs_colnames)
for i in range(settings.n_subgrid):
# get the modesedgrid on which to generate the noisemodel
modelsedgridfile = file_dict["modelsedgrid_files"][i]
modelsedgrid = SEDGrid(modelsedgridfile)
# read in the noise model just created
noisemodel_vals = noisemodel.get_noisemodelcat(
file_dict["noise_files"][i])
# trim the model sedgrid
sed_trimname = file_dict["modelsedgrid_trim_files"][i]
noisemodel_trimname = file_dict["noise_trim_files"][i]
trim_grid.trim_models(
modelsedgrid,
noisemodel_vals,
obsdata,
sed_trimname,
noisemodel_trimname,
sigma_fac=3.0,
)
# -----------------
# fitting
# -----------------
run_fitting.run_fitting(
settings,
use_sd=False,
nsubs=settings.n_subgrid,
nprocs=1,
pdf2d_param_list=["Av", "M_ini", "logT"],
pdf_max_nbins=200,
)
# -----------------
# merging
# -----------------
# it'll automatically skip for no subgrids
merge_files.merge_files(settings,
use_sd=False,
nsubs=settings.n_subgrid)
print("\n\n")
# ==========================================
# reference files for assorted tools
# ==========================================
if run_tools:
# -----------------
# compare_spec_type
# -----------------
# the input settings
input = {
"spec_ra": [72.67213351],
"spec_dec": [-67.71720515],
"spec_type": ["A"],
"spec_subtype": [0],
"lumin_class": ["IV"],
"match_radius": 0.2,
}
# run it
output = compare_spec_type.compare_spec_type(
settings_orig.obsfile,
"{0}/{0}_stats.fits".format(settings_orig.project),
**input,
)
# save the inputs and outputs
asdf.AsdfFile({
"input": input,
"output": output
}).write_to("{0}/{0}_compare_spec_type.asdf".format(
settings_orig.project))
# -----------------
# star_type_probability
# -----------------
# input settings
input = {
"output_filebase": None,
"ext_O_star_params": {
"min_M_ini": 10,
"min_Av": 0.5,
"max_Av": 5
},
}
# run it
output = star_type_probability.star_type_probability(
"{0}/{0}_pdf1d.fits".format(settings_orig.project),
"{0}/{0}_pdf2d.fits".format(settings_orig.project),
**input,
)
# save the inputs and outputs
asdf.AsdfFile({
"input": input,
"output": output
}).write_to("{0}/{0}_star_type_probability.asdf".format(
settings_orig.project))
# ==========================================
# asdf file permissions
# ==========================================
# for unknown reasons, asdf currently writes files with permissions set
# to -rw-------. This changes it to -rw-r--r-- (like the rest of the
# BEAST files) so Karl can easily copy them over to the cached file
# website.
# list of asdf files
asdf_files = glob.glob("*/*.asdf")
# go through each one to change permissions
for fname in asdf_files:
os.chmod(fname,
stat.S_IRUSR | stat.S_IWUSR | stat.S_IRGRP | stat.S_IROTH)
