def test_iam_wrapper_without_prefix(sim_config, host, comp, tmpdir):
simulators = sim_config
simulators.paths["output_dir"] = str(tmpdir)
host_params = [5600, 4.5, 0.0]
comp_params = [[2300, 4.5, 0.0], [2400, 4.5, 0.0]]
host.wav_select(2110, 2115)
comp.wav_select(2110, 2115)
obs_spec = host.copy()
obs_spec.flux += comp.flux
obs_spec.header.update({"OBJECT": "Test_object", "MJD-OBS": 56114.31674297})
setup_iam_dirs("Test_object")
result = iam_wrapper(0, host_params, comp_params, obs_spec=obs_spec,
gammas=[0, 1, 2], rvs=[-1, 1], norm=True,
save_only=True, chip=1)
assert result is None
def test_setup_dirs_creates_dirs(sim_config, tmpdir):
simulators = sim_config
simulators.paths["output_dir"] = str(tmpdir)
star = "TestStar"
assert not tmpdir.join(star.upper(), "iam").check(dir=True)
assert not tmpdir.join(star.upper(), "iam", "plots").check(dir=True)
assert not tmpdir.join(star.upper(), "iam", "grid_plots").check(dir=True)
assert not tmpdir.join(star.upper(), "iam", "fudgeplots").check(dir=True)
result = setup_iam_dirs(star)
assert tmpdir.join(star.upper(), "iam").check(dir=True)
assert tmpdir.join(star.upper(), "iam", "plots").check(dir=True)
assert tmpdir.join(star.upper(), "iam", "grid_plots").check(dir=True)
assert tmpdir.join(star.upper(), "iam", "fudgeplots").check(dir=True)
assert result is None
def test_iam_db_main_multiple_host_model(sim_config, tmpdir):
simulators = sim_config
simulators.paths["output_dir"] = str(tmpdir)
# Setup
star = "test_star"
star = star.upper()
obsnum = "11"
suffix = "_test"
# Gen fake param file
print("before dirs")
list_files(str(tmpdir))
setup_iam_dirs(star)
print("after dirs")
list_files(str(tmpdir))
num = 20
# Standard values
teff = np.linspace(3000, 5000, 4)
logg = np.linspace(3.5, 4.5, 3)
feh = np.linspace(-0.5, 0.5, 2)
teff2 = np.linspace(2300, 4300, num)
logg2 = np.linspace(1.5, 5, num)
feh2 = np.linspace(-2, 2, num)
rv = np.linspace(-15, 15, num)
gamma = np.linspace(-20, 20, num)
import itertools
for chip in range(1, 5):
for t, l, f in itertools.product(teff, logg, feh):
fname = tmpdir.join(star, "iam",
"{0}-{1}_{2}_iam_chisqr_results{3}[{4}_{5}_{6}].csv".format(star, obsnum, chip, suffix,
t, l, f))
chi2 = chip + (f + gamma + t / l) * (feh2 + rv + teff2 / logg2)
npix = (985 - chip) * np.ones_like(chi2)
# print("chi2 shape", chi2.shape)
# print("tshape", t.shape)
# print("tgamma shape", gamma.shape)
df = pd.DataFrame({'gamma': gamma,
'teff_2': teff2, 'logg_2': logg2, 'feh_2': feh2, "rv": rv,
'chi2': chi2, "npix": npix})
df["teff_1"] = t
df["logg_1"] = l
df["feh_1"] = f
df.to_csv(fname)
print("after df.to_csv")
list_files(str(tmpdir))
expected_db_name = tmpdir.join(star, "iam",
"{0}-{1}_coadd_iam_chisqr_results{2}.db".format(star, obsnum, suffix))
assert expected_db_name.check(file=0)
# make 4 databases to add together()
res = iam_db_main(star, obsnum, suffix, replace=False, verbose=False, chunksize=5,
move=False) # move=True does not test well.
print("After iam db main")
assert res is None
assert expected_db_name.check(file=1)
db_table = load_sql_table(expected_db_name)
assert isinstance(db_table, sa.Table)
df = pd.read_sql(
sa.select(db_table.c), db_table.metadata.bind)
print("df head", df.head())
print("types", df.dtypes)
assert isinstance(df, pd.DataFrame)
assert len(df) == num * (len(teff) * len(feh) * len(logg))
x = (df.feh_1 + df.gamma + df.teff_1 / df.logg_1) * (df.feh_2 + df.rv + df.teff_2 / df.logg_2)
assert np.allclose(df.chi2_1, 1 + x)
assert np.allclose(df.chi2_2, 2 + x)
assert np.allclose(df.chi2_3, 3 + x)
assert np.allclose(df.chi2_4, 4 + x)
assert np.allclose(df.coadd_chi2, 10 + 4 * x)
assert np.all(df.npix_1 == (985 - 1))
assert np.all(df.npix_2 == (985 - 2))
assert np.all(df.npix_3 == (985 - 3))
assert np.all(df.npix_4 == (985 - 4))
assert np.allclose(np.unique(df.teff_1.values), teff)
assert np.allclose(np.unique(df.logg_1.values), logg)
assert np.allclose(np.unique(df.feh_1.values), feh)
assert np.allclose(np.unique(df.teff_2.values), teff2)
assert np.allclose(np.unique(df.logg_2.values), logg2)
assert np.allclose(np.unique(df.feh_2.values), feh2)
assert np.allclose(np.unique(df.gamma.values), gamma)
assert np.allclose(np.unique(df.rv.values), rv)
def test_iam_db_main_single_host_model(sim_config, tmpdir):
simulators = sim_config
simulators.paths["output_dir"] = str(tmpdir)
# Setup
star = "test_star"
star = star.upper()
obsnum = "11"
suffix = "_test"
# Gen fake param file
setup_iam_dirs(star)
list_files(str(tmpdir))
num = 20
# Setting values
teff = 3000
logg = 4.5
feh = 0.0
teff2 = np.linspace(2300, 4300, num)
logg2 = np.linspace(1.5, 5, num)
feh2 = np.linspace(-2, 2, num)
rv = np.linspace(-15, 15, num)
gamma = np.linspace(-20, 20, num)
for chip in range(1, 5):
fname = tmpdir.join(star, "iam",
"{0}-{1}_{2}_iam_chisqr_results{3}[{4}_{5}_{6}].csv".format(
star, obsnum, chip, suffix, teff, logg, feh))
chi2 = chip + (feh + gamma + teff / logg) * (feh2 + rv + teff2 / logg2)
npix = (985 - chip) * np.ones_like(teff)
df = pd.DataFrame({'gamma': gamma, 'teff_2': teff2, 'logg_2': logg2, 'feh_2': feh2, "rv": rv,
'chi2': chi2, "npix": npix})
df.to_csv(fname)
list_files(str(tmpdir))
expected_db_name = tmpdir.join(star, "iam",
"{0}-{1}_coadd_iam_chisqr_results{2}.db".format(star, obsnum, suffix))
assert expected_db_name.check(file=0)
# make 4 databases to add together()
res = iam_db_main(star, obsnum, suffix, replace=False, verbose=True, chunksize=5, move=False)
assert res is None
assert expected_db_name.check(file=1)
db_table = load_sql_table(expected_db_name)
assert isinstance(db_table, sa.Table)
df = pd.read_sql(
sa.select(db_table.c), db_table.metadata.bind)
assert isinstance(df, pd.DataFrame)
assert np.all(df.teff_1.values == teff)
assert np.all(df.logg_1.values == logg)
assert np.all(df.feh_1.values == feh)
assert np.allclose(df.teff_2.values, teff2)
assert np.allclose(df.logg_2.values, logg2)
assert np.allclose(df.feh_2.values, feh2)
assert np.allclose(df.gamma.values, gamma)
assert np.allclose(df.rv.values, rv)
assert len(df) == num
x = (feh + gamma + teff / logg) * (feh2 + rv + teff2 / logg2)
assert np.allclose(df.chi2_1, 1 + x)
assert np.allclose(df.chi2_2, 2 + x)
assert np.allclose(df.chi2_3, 3 + x)
assert np.allclose(df.chi2_4, 4 + x)
assert np.allclose(df.coadd_chi2, 10 + 4 * x)
assert np.all(df.npix_1 == (985 - 1))
assert np.all(df.npix_2 == (985 - 2))
assert np.all(df.npix_3 == (985 - 3))
assert np.all(df.npix_4 == (985 - 4))