Ctrl+K

asteca.synthetic

asteca.synthetic#

Module Contents#

Classes#

synthetic

Define a synthetic object.
class asteca.synthetic.synthetic#

Define a synthetic object.

Use the isochrones loaded in the asteca.isochrones object to generate a asteca.synthetic object. This object is used to generate synthetic clusters given a asteca.cluster object and a set of input fundamental parameters (metallicity, age, distance, extinction, etc.).

See the Synthetic clusters section for more details.

Parameters:

  • isochs (isochrones) – asteca.isochrones object with the loaded files for the theoretical isochrones.

  • ext_law (str, {"CCMO", "GAIADR3"}, default="CCMO") – Extinction law. If “GAIADR3” is selected, the magnitude and first color defined in isochrones and cluster are assumed to be Gaia’s (E)DR3 G and (BP-RP) respectively. The second color (if defined) will always be affected by the “CCMO” model.

  • DR_distribution (str, {"uniform", "normal"}, default="uniform") – Distribution function for the differential reddening.

  • IMF_name (str, {"salpeter_1955", "kroupa_2001", "chabrier_2014"}, default="chabrier_2014") – Name of the initial mass function used to populate the isochrones.

  • max_mass (int, default=100_000) – Maximum total initial mass. Should be large enough to allow generating as many synthetic stars as observed stars.

  • gamma (str, float, {"D&K", "fisher_stepped", "fisher_peaked", "raghavan"}, default="D&K") – Distribution function for the mass ratio of the binary systems.

  • seed (int, optional, default=None) – Random seed. If None a random integer will be generated and used.

calibrate(cluster, fix_params: dict = {})#

Calibrate a asteca.synthetic object based on a asteca.cluster object and a dictionary of fixed fundamental parameters (fix_params).

Use the data obtained from your observed cluster stored in the asteca.cluster object, to calibrate a asteca.synthetic object. Additionally, a dictionary of fixed fundamental parameters (metallicity, age, distance, extinction, etc.) can be passed.

See the Synthetic clusters section for more details.

Parameters:

  • cluster (cluster) – asteca.cluster object with the processed data from your observed cluster.

  • fix_params (dict, optional, default={}) – Dictionary with the values for the fixed parameters (if any).

generate(fit_params: dict) → numpy.ndarray#

Generate a synthetic cluster.

The synthetic cluster is generated according to the parameters given in the fit_params dictionary and the already calibrated asteca.synthetic object.

Parameters:

fit_params (dict) – Dictionary with the values for the fundamental parameters that were not included in the fix_params dictionary when the asteca.synthetic object was calibrated (synthetic.calibrate() method).

Returns:

Return a np.array containing a synthetic cluster with the shape [mag, c1, (c2)], where mag is the magnitude dimension, and c1 and c2 (last one is optional) are the color dimension(s).

Return type:

array[mag, c1, (c2)]

synthplot(ax, fit_params, color_idx=0, isochplot=False)#

Generate a color-magnitude plot for a synthetic cluster.

The synthetic cluster is generated using the fundamental parameter values given in the fit_params dictionary.

Parameters:

  • ax (matplotlib.axis, optional, default=None) – Matplotlib axis where to draw the plot.

  • fit_params (dict) – Dictionary with the values for the fundamental parameters that were not included in the fix_params dictionary when the asteca.synthetic object was calibrated (synthetic.calibrate() method).

  • color_idx (int, default=0) – Index of the color to plot. If 0 (default), plot the first color. If 1 plot the second color.

  • isochplot (bool, default=False) – If True, the accompanying isochrone will be plotted.

Returns:

Matplotlib axis object

Return type:

matplotlib.axis

masses_binary_probs(model, model_std)#

Estimate individual masses for the observed stars, along with their binary probabilities (if binarity was estimated).

Parameters:

  • model (dict) – Dictionary with the values for the fundamental parameters that were not included in the fix_params dictionary when the asteca.synthetic object was calibrated (synthetic.calibrate() method).

  • model_std (dict) – Dictionary with the standard deviations for the fundamental parameters in the model argument.

Returns:

  • pandas.DataFrame – Data frame containing per-star primary and secondary masses along with their uncertainties, and their probability of being a binary system.

  • numpy.array – Distribution of total binary fraction values for the cluster.

Contents