def test_modelgrid_object():
"""Test to see that ModelGrid object can be created"""
print('Testing ModelGrid object creation...')
# Load model grid
mgrid = mg.ModelGrid(resource_filename('exoctk', 'data/core/modelgrid/'))
assert isinstance(mgrid, mg.ModelGrid)
def test_model_getter_off_grid():
"""Test to see that an off-grid model can be pulled from a ModelGrid
object"""
print('Testing off-grid model getter from ModelGrid object...')
# Load model grid
mgrid = mg.ModelGrid(resource_filename('exoctk', 'data/core/modelgrid/'))
# Fetch model
model = mgrid.get(4023, 4.1, -0.1)
assert isinstance(model.get('flux'), np.ndarray)
suppress verbose output to stdout):
::
pytest -s test_limb_darkening.py
"""
import os
from pkg_resources import resource_filename
from svo_filters import Filter
from exoctk import modelgrid as mg
from exoctk.limb_darkening import limb_darkening_fit as ldf
# Load local modelgrid
MODELGRID = mg.ModelGrid(resource_filename('exoctk', 'data/core/modelgrid/'))
def test_ldc_object():
"""Test to see that an LDC object can be loaded"""
print('Testing LDC object creation...')
ld_session = ldf.LDC(MODELGRID)
assert isinstance(ld_session, ldf.LDC)
def test_ldc_plot():
"""Test that the LDC plots work"""
print('Testing LDC object plotting...')
def generate_SOSS_ldcs(wavelengths,
ld_profile,
grid_point,
model_grid='',
subarray='SUBSTRIP256',
n_bins=100,
plot=False,
save=''):
"""
Generate a lookup table of limb darkening coefficients for full
SOSS wavelength range
Parameters
----------
wavelengths: sequence
The wavelengths at which to calculate the LDCs
ld_profile: str
A limb darkening profile name supported by
`ExoCTK.ldc.ldcfit.ld_profile()`
grid_point: dict, sequence
The stellar parameters [Teff, logg, FeH] or stellar model
dictionary from `ExoCTK.modelgrid.ModelGrid.get()`
n_bins: int
The number of bins to break up the grism into
save: str
The path to save to file to
Example
-------
from awesimsoss.sim2D import awesim
lookup = awesim.soss_ldc('quadratic', [3300, 4.5, 0])
"""
try:
from exoctk import modelgrid
from exoctk.limb_darkening import limb_darkening_fit as lf
except ImportError:
return
# Get the model grid
if not isinstance(model_grid, modelgrid.ModelGrid):
model_grid = modelgrid.ModelGrid(os.environ['MODELGRID_DIR'],
resolution=700)
# Load the model grid
model_grid = modelgrid.ModelGrid(os.environ['MODELGRID_DIR'],
resolution=700,
wave_rng=(0.6, 2.8))
# Get the grid point
if isinstance(grid_point, (list, tuple, np.ndarray)):
grid_point = model_grid.get(*grid_point)
# Abort if no stellar dict
if not isinstance(grid_point, dict):
print(
'Please provide the grid_point argument as [Teff, logg, FeH] or ExoCTK.modelgrid.ModelGrid.get(Teff, logg, FeH).'
)
return
# Break the bandpass up into n_bins pieces
bandpass = svo.Filter('NIRISS.GR700XD', n_bins=n_bins, verbose=False)
# Calculate the LDCs
ldc_results = lf.ldc(None,
None,
None,
model_grid, [ld_profile],
bandpass=bandpass,
grid_point=grid_point.copy(),
mu_min=0.08,
verbose=False)
# Interpolate the LDCs to the desired wavelengths
coeff_table = ldc_results[ld_profile]['coeffs']
coeff_cols = [c for c in coeff_table.colnames if c.startswith('c')]
coeffs = [
np.interp(wavelengths, coeff_table['wavelength'], coeff_table[c])
for c in coeff_cols
]
return np.array(coeffs).T