In light of the upcoming Gaia DR3, it might be nice to enable 3D spatial distribution of stellar populations.

If these distributions could be assigned differently for each sub-population (say young\old, low\high metallicity, etc.), and easily reflect the structure of the Solar neighborhood, it would be extremely nice :)

We should add a user warning when the sampling grid size of xy_from_grid reaches some large value.

The select phase method of an ssp be inherited by a composite population?

For example, following the tutorial example of combining young, intermediate and old populations, we do something like
csp = ssp_old + ssp_intermediate + ssp_young

Then, is there an option to select the phases directly on the resulting population, rather than going back to the single ones and combining them again? For example:

# generate boolean phase masks
MS  = csp.select_phase('MS')
RGB = csp.select_phase('RGB')
AGB = csp.select_phase('AGB')

Firstly, I built stellar populations and drew HR-diagram of the stellar evolution stages that interest me.

Then I wanted to generate a source with only the main sequence star, and I used the following code, but there were errors. How can I input the values of labels to obtain the desired results?

Thank you very much for your help!

Python 3.8.5

See attached error screen prints below

Hello, I am wondering if there is a way to include new filters in addition to those on the phot_system_list
I would like to use ArtPop for my stellar astrophysics class and compare with open clusters from Gaia. Is there a way for a user to add filters, like the Gaia filters, if the transmission curves exist?

Thanks!

Currently, the Sersic spatial sampling uses xy_from_grid, with the parameter num_r_eff setting how large of a grid to use. There are three downsides of this approach:

• the xy positions are discrete integers (works okay if your PSF is well-sampled)
• the number of sampled stars is fixed regardless of the size of the sampling grid (e.g., you could have all the stars packed into one effective radius if num_r_eff = 1)
• the memory requirements can become extreme if r_eff is large in pixel space

One simple way to solve the second and third issues is to use the input Sersic distribution to calculate the fraction of stars that will fall outside the image and reduce the number of sampled stars by this factor.

Note: the implementation may require some more thought when total_mass given instead of num_stars.