def test_target_completeness_constrainOrbits(self):
"""
Compare calculated completenesses for multiple targets with constrain orbits set to true
"""
with RedirectStreams(stdout=self.dev_null):
TL = TargetList(ntargs=100,
constrainOrbits=True,
**copy.deepcopy(self.spec))
mode = filter(lambda mode: mode['detectionMode'] == True,
TL.OpticalSystem.observingModes)[0]
IWA = mode['IWA']
OWA = mode['OWA']
rrange = TL.PlanetPopulation.rrange
maxd = (rrange[1] / np.tan(IWA)).to(u.pc).value
mind = (rrange[0] / np.tan(OWA)).to(u.pc).value
#want distances to span from outer edge below IWA to inner edge above OWA
TL.dist = np.logspace(np.log10(mind / 10.), np.log10(maxd * 10.),
TL.nStars) * u.pc
Brown = EXOSIMS.Completeness.BrownCompleteness.BrownCompleteness(
constrainOrbits=True, **copy.deepcopy(self.spec))
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(
constrainOrbits=True, **copy.deepcopy(self.spec))
cBrown = Brown.target_completeness(TL)
cGarrett = Garrett.target_completeness(TL)
np.testing.assert_allclose(cGarrett, cBrown, rtol=0.1, atol=1e-6)
def test_target_completeness_def(self):
"""
Compare calculated completenesses for multiple targets under default population
settings.
"""
with RedirectStreams(stdout=self.dev_null):
TL = TargetList(ntargs=100, **copy.deepcopy(self.spec))
mode = list(
filter(lambda mode: mode['detectionMode'] == True,
TL.OpticalSystem.observingModes))[0]
IWA = mode['IWA']
OWA = mode['OWA']
rrange = TL.PlanetPopulation.rrange
maxd = (rrange[1] / np.tan(IWA)).to(u.pc).value
mind = (rrange[0] / np.tan(OWA)).to(u.pc).value
#want distances to span from outer edge below IWA to inner edge above OWA
TL.dist = np.logspace(np.log10(mind / 10.), np.log10(maxd * 10.),
TL.nStars) * u.pc
Brown = EXOSIMS.Completeness.BrownCompleteness.BrownCompleteness(
**copy.deepcopy(self.spec))
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(
**copy.deepcopy(self.spec))
cBrown = Brown.target_completeness(TL)
cGarrett = Garrett.target_completeness(TL)
np.testing.assert_allclose(cGarrett, cBrown, rtol=0.1, atol=1e-6)
# test when scaleOrbits == True
TL.L = np.exp(
np.random.uniform(low=np.log(0.1),
high=np.log(10.),
size=TL.nStars))
Brown.PlanetPopulation.scaleOrbits = True
Garrett.PlanetPopulation.scaleOrbits = True
cBrown = Brown.target_completeness(TL)
cGarrett = Garrett.target_completeness(TL)
cGarrett = cGarrett[cBrown != 0]
cBrown = cBrown[cBrown != 0]
meandiff = np.mean(np.abs(cGarrett - cBrown) / cBrown)
self.assertLessEqual(meandiff, 0.1)
def test_target_completeness_scaleOrbits(self):
"""
Compare calculated completenesses for multiple targets with scale orbits set to true
"""
with RedirectStreams(stdout=self.dev_null):
TL = TargetList(ntargs=100,**copy.deepcopy(self.spec))
TL.dist = np.exp(np.random.uniform(low=np.log(1.0), high=np.log(30.), size=TL.nStars))*u.pc
TL.L = np.exp(np.random.uniform(low=np.log(0.1), high=np.log(10.), size=TL.nStars))
Brown = EXOSIMS.Completeness.BrownCompleteness.BrownCompleteness(scaleOrbits=True,**copy.deepcopy(self.spec))
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(scaleOrbits=True,**copy.deepcopy(self.spec))
cBrown = Brown.target_completeness(TL)
cGarrett = Garrett.target_completeness(TL)
cGarrett = cGarrett[cBrown != 0 ]
cBrown = cBrown[cBrown != 0]
meandiff = np.mean(np.abs(cGarrett - cBrown)/cBrown)
self.assertLessEqual(meandiff,0.1)
def test_target_completeness_varrange(self):
"""
Garrett completeness takes different logical pathways depending on which parameters are
held constant. Checking all of these against BrownCompleteness would take multiple hours
so we'll just run through the Garrett logical branches and check for self-consistency.
The comparison tests already cover Rp and p constant, so we need to check a constant, e constant
a + e constant.
"""
with RedirectStreams(stdout=self.dev_null):
TL = TargetList(ntargs=100,**copy.deepcopy(self.spec))
mode = filter(lambda mode: mode['detectionMode'] == True, TL.OpticalSystem.observingModes)[0]
IWA = mode['IWA']
OWA = mode['OWA']
rrange = TL.PlanetPopulation.rrange
maxd = (rrange[1]/np.tan(IWA)).to(u.pc).value
mind = (rrange[0]/np.tan(OWA)).to(u.pc).value
#want distances to span from outer edge below IWA to inner edge above OWA
TL.dist = np.logspace(np.log10(mind/10.),np.log10(maxd*10.),TL.nStars)*u.pc
#a constant, everything else var
spec = copy.deepcopy(self.spec)
spec['arange'] = [1,1]
spec['Rprange'] = [1,10]
spec['prange'] = [0.2,0.5]
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(**copy.deepcopy(spec))
cGarrett = Garrett.target_completeness(TL)
self.assertTrue(np.all(cGarrett[TL.dist > maxd*u.pc] == 0))
#e constant everything else var
spec = copy.deepcopy(self.spec)
spec['erange'] = [0,0]
spec['Rprange'] = [1,10]
spec['prange'] = [0.2,0.5]
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(**copy.deepcopy(spec))
cGarrett = Garrett.target_completeness(TL)
self.assertTrue(np.all(cGarrett[TL.dist > maxd*u.pc] == 0))
#a and e constant, everything else var
spec = copy.deepcopy(self.spec)
spec['arange'] = [1,1]
spec['erange'] = [0,0]
spec['Rprange'] = [1,10]
spec['prange'] = [0.2,0.5]
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(**copy.deepcopy(spec))
cGarrett = Garrett.target_completeness(TL)
self.assertTrue(np.all(cGarrett[TL.dist > maxd*u.pc] == 0))
#a constant and constrainOrbits
spec = copy.deepcopy(self.spec)
spec['arange'] = [1,1]
spec['constrainOrbits'] = True
spec['Rprange'] = [1,10]
spec['prange'] = [0.2,0.5]
Garrett = EXOSIMS.Completeness.GarrettCompleteness.GarrettCompleteness(**copy.deepcopy(spec))
cGarrett = Garrett.target_completeness(TL)
self.assertTrue(np.all(cGarrett[TL.dist > maxd*u.pc] == 0))