Use the STScI PHOENIX grid

This example shows how to use the ST grid.

from astropy import units as u
import numpy as np
import matplotlib.pyplot as plt

from GridPolator import GridSpectra
from GridPolator import config

Load the PHOENIX grid

Load the default VSPEC PHOENIX grid.

wave_short = 1*u.um
wave_long = 2*u.um
resolving_power = 100
teffs = [3000,3100]
metalicities = [-1.0,-0.5]
loggs = [3.5,4.0]

spec = GridSpectra.from_st(
    w1=wave_short,
    w2=wave_long,
    resolving_power=resolving_power,
    teffs=teffs,
    metalicities=metalicities,
    loggs=loggs,
    impl_bin='rust',
    impl_interp='scipy',
)

Loading Teff Axis:   0%|          | 0/2 [00:00<?, ?it/s]

Loading Metallicity Axis:   0%|          | 0/2 [00:00<?, ?it/s]PHOENIX grid for 3000 -1.0 not found. Downloading...



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Loading Metallicity Axis:  50%|█████     | 1/2 [00:00<00:00,  5.38it/s]PHOENIX grid for 3000 -0.5 not found. Downloading...



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Loading Metallicity Axis:   0%|          | 0/2 [00:00<?, ?it/s]PHOENIX grid for 3100 -1.0 not found. Downloading...



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Loading Metallicity Axis:  50%|█████     | 1/2 [00:00<00:00,  8.92it/s]PHOENIX grid for 3100 -0.5 not found. Downloading...



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Recall a spectrum from the grid

GridSpectra will resample the grid with your supplied wavelength array as well as interpolate between \(T_{eff}\) values.

low_res:u.Quantity = np.linspace(1.2,1.8,20) * u.um
hi_res:u.Quantity = np.linspace(1.2,1.8,200) * u.um
teff = np.array([3050.])
metalicity = np.array([-0.6])
logg = np.array([3.7])

low_res = np.array(low_res.to_value(config.wl_unit))
hi_res = np.array(hi_res.to_value(config.wl_unit))

flux_lo = spec.evaluate((teff,metalicity,logg), low_res)[0]
flux_hi = spec.evaluate((teff,metalicity,logg), hi_res)[0]

plt.plot(low_res, flux_lo)
plt.plot(hi_res, flux_hi)
plt.xlabel(f'Wavelength ({config.wl_unit:latex})')
_=plt.ylabel(f'Flux ({config.flux_unit:latex})')