def setUpClass(ModelTestCase):
""" Setup the tmap grid as it is smaller and thus faster as kurucz"""
model.set_defaults(grid='kurucztest')
grid1 = dict(grid='tmaptest')
grid2 = dict(grid='tmaptest')
model.set_defaults_multiple(grid1,grid2)
model.copy2scratch(z='*', Rv='*')
def testiGrid_searchBinary(self):
""" INTEGRATION igrid_search binary star (kurucz-tmap) """
sed = builder.BinarySED(ID='TEST', load_fits=False)
np.random.seed(111)
meas = self.measBin + np.random.uniform(0, 0.04, size=len(self.measBin)) * self.measBin
emeas = meas / 100.0
units = ['erg/s/cm2/AA' for i in meas]
source = ['SYNTH' for i in meas]
sed.add_photometry_fromarrays(meas, emeas, units, self.photbands, source)
grid1 = dict(grid='kurucztest')
grid2 = dict(grid='tmaptest')
model.set_defaults_multiple(grid1,grid2)
np.random.seed(111)
sed.igrid_search(points=100000,teffrange=[(5000, 7000),(25000, 35000)],
loggrange=[(3.5, 4.5),(5.0, 6.0)],
ebvrange=[(0.005, 0.015), (0.005, 0.015)],
zrange=[(0,0),(0,0)],
radrange=[(0,10),(0,10)],
masses=self.masses,
df=None,CI_limit=0.95,set_model=False)
teff = sed.results['igrid_search']['CI']['teff']
logg = sed.results['igrid_search']['CI']['logg']
ebv = sed.results['igrid_search']['CI']['ebv']
teff2 = sed.results['igrid_search']['CI']['teff2']
logg2 = sed.results['igrid_search']['CI']['logg2']
ebv2 = sed.results['igrid_search']['CI']['ebv2']
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff'], 6134, delta=50)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg'], 4.38, delta=0.25)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv'], 0.008, delta=0.002)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff_l'], 5826, delta=50)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg_l'], 4.35, delta=0.1)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv_l'], 0.005, delta=0.002)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff_u'], 6291, delta=50)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg_u'], 4.40, delta=0.1)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv_u'], 0.015, delta=0.002)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff2'], 32195, delta=250)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg2'], 5.97, delta=0.25)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv2'], 0.008, delta=0.002)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff2_l'], 26820, delta=250)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg2_l'], 5.70, delta=0.1)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv2_l'], 0.005, delta=0.002)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['teff2_u'], 33025, delta=250)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['logg2_u'], 5.99, delta=0.1)
self.assertAlmostEqual(sed.results['igrid_search']['CI']['ebv2_u'], 0.015, delta=0.002)
def setUpClass(cls):
if not noMock:
sesame.search = mock.Mock(return_value={'plx':(0.0,0.0)})
if not noIntegration:
# ==== COLD model ====
model.set_defaults(grid='kurucztest')
model.copy2scratch(z='*', Rv='*')
measCold = model.get_itable_pix(photbands=cls.photbands, teff=array([6000]), \
logg=array([4.0]),ebv=array([0.01]), rv=array([2.8]), z=array([-0.25]))[0][:,0]
np.random.seed(111)
cls.measCold = measCold
# ==== HOT model ====
model.set_defaults(grid='tmaptest')
model.copy2scratch(z='*', Rv='*')
measHot = model.get_itable_pix(photbands=cls.photbands, teff=array([30000]), \
logg=array([5.5]),ebv=array([0.01]), rv=3.1, z=0.0)[0][:,0]
np.random.seed(111)
cls.measHot = measHot
# ==== BINARY model ====
grid1 = dict(grid='kurucztest')
grid2 = dict(grid='tmaptest')
model.set_defaults_multiple(grid1,grid2)
model.clean_scratch(z='*', Rv='*')
model.copy2scratch(z='*', Rv='*')
G, Msol, Rsol = constants.GG_cgs, constants.Msol_cgs, constants.Rsol_cgs
masses = [0.85, 0.50]
rad = array([np.sqrt(G*masses[0]*Msol/10**4.0)/Rsol])
rad2 = array([np.sqrt(G*masses[1]*Msol/10**5.5)/Rsol])
measBin = model.get_itable_pix(photbands=cls.photbands, teff=array([6000]), \
logg=array([4.0]),ebv=array([0.01]), teff2=array([30000]),
logg2=array([5.5]), ebv2=array([0.01]), rad=rad,
rad2=rad2)[0][:,0]
np.random.seed(111)
cls.measBin = measBin
cls.masses = masses
