fastar.SemiresolvedSSPSynthesizer

fastar.SemiresolvedSSPSynthesizer#

class fastar.SemiresolvedSSPSynthesizer(model_label=None, imf_function=None)[source]#

Bases: BaseSSPSynthesizer

Class for generating synthetic semi-resolved stellar populations spectroscopic and photometric predictions with a PCA-based stellar spectral model and a stochastic IMF sampling.

__init__(model_label=None, imf_function=None)#

Methods

__init__([model_label, imf_function])

predict_spectrum(logg, teff, fmet)

Predict stellar spectra given logg, Teff, and [Fe/H] using the PCA regressor.

synthesize(age, met, num_stars, key[, ...])

Generate synthetic semi-resolved population spectrum for a given age and metallicity.

synthesize_large(age, met, num_stars, key[, ...])

synthesize(age, met, num_stars, key, imf_params=None, out_masses=False)[source]#

Generate synthetic semi-resolved population spectrum for a given age and metallicity.

Parameters:

  • age (float) – Stellar population age (in Gyr).

  • met (float) – Metallicity [M/H].

  • num_stars (int) – Number of stars to sample.

  • key (PRNGKey) – Random key for JAX sampling.

  • imf_params (dict, optional) – Parameters for the initial mass function.

  • out_masses (bool, optional) – If True, return array of sampled stellar masses instead of the total mass. Default is False.

Returns:

(spectrum, total stellar mass) or (spectrum, sampled stellar masses) depending on out_masses.

Return type:

tuple

synthesize_large(age, met, num_stars, key, batch_size=10000, out_masses=False, imf_params=None)[source]#