Exo-REM

Example on how to access to the atmospheric grid info to check the parameters and their ranges.

Imports

import xarray as xr
import matplotlib.pyplot as plt

Open the grid

You can check the free parameters names, ranges and units together with the wavelength range and spectral resolution.

grid_path = '/EXOREM_native.nc'
ds = xr.open_dataset(grid_path, decode_cf=False)
print(ds)

<xarray.Dataset>
Dimensions:     (wavelength: 29922, par1: 33, par2: 5, par3: 4, par4: 15)
Coordinates:
  * wavelength  (wavelength) float64 0.6667 0.6667 0.6667 ... 245.4 248.4 251.6
  * par1        (par1) float64 400.0 450.0 500.0 ... 1.9e+03 1.95e+03 2e+03
  * par2        (par2) float64 3.0 3.5 4.0 4.5 5.0
  * par3        (par3) float64 -0.5 0.0 0.5 1.0
  * par4        (par4) float64 0.1 0.15 0.2 0.25 0.3 ... 0.6 0.65 0.7 0.75 0.8
Data variables:
    grid        (wavelength, par1, par2, par3, par4) float64 ...
Attributes:
    key:      ['par1', 'par2', 'par3', 'par4']
    par:      ['teff', 'logg', 'mh', 'co']
    title:    ['Teff', 'log(g)', '[M/H]', 'C/O']
    unit:     ['(K)', '(dex)', '', '']
    res:      [29999.50000004 29998.49999991 29997.50000002 ...    80.5\n    ...

Get a spectrum for specific values

# Open the grid
grid = ds['grid']

# get wavelength
wave = grid['wavelength'].values

# for Exo-REM par1=Teff, par2=logg, par3=[M/H], par4=C/O
# get flux by selecting a value for each parameter
flux = grid.sel(par1=1700,par2=4.0, par3=0., par4=0.55, method="nearest")

# Plot the spectrum
plt.figure(figsize=(7,3))
plt.plot(wave, flux*wave, 'k')
plt.xlabel('Wavelength (µm)')
plt.ylabel('Flux')
plt.xlim(0.5,5)
plt.yticks([])
plt.title('Exo-REM at Teff=1700K, logg=4, and solar [M/H] and C/O')
plt.show()