GaiaClusterFit 0.0.6

Matching gaia clustered stars to known clusters

GaiaClusterFit

GaiaClusterFit is a Python library for dealing cluster

Installation

Use the package manager pip to install foobar.

pip install GaiaClusterFit

Usage

Import library

from  GaiaClusterFit import GCA

Specify Gaia query

#GAIA database query

query ="""SELECT TOP 1000  source_id, b, l, parallax,phot_g_mean_mag,pmra,pmdec, RUWE, bp_rp,phot_g_mean_mag+5*log10(parallax)-10 as mg

FROM gaiadr3.gaia_source

WHERE l < 275 AND l > 240 

AND b < 5 AND b > -15

AND phot_g_mean_mag < 18

AND RUWE < 1.4

AND parallax < 4 AND parallax > 1.8

AND parallax_error/parallax < 0.02""" 

Create an instance and import data

#Create instance

job = GCA.GCAinstance(RegionName = "Char")



#Login and fetch GAIA Data

job.GaiaLogin(username='username', password='password')

job.FetchQueryAsync(query)



#Import known cluster

job.ImportRegion("G:/path/known_cluster.fits")

Setting up basic cluster fit function to clustered GAIA data to known clusters

#Parameters to optimize Cluster function over (HDBscan by default)

parameters = [{"variable": "min_cluster_size", "min":10, "max":100}]

Renaming cluster table columns to match GAIA column names

job.RenameCol(job.regiondata, [["Source", "source_id"],["Pop", "population"]])

Optimizing cluster function(HDBscan) over GAIA data to match known clusters

optimal = job.optimize_grid(fit_params=parameters, scoring_function)

Scoring function returns a score for the fit based by default on homogeneity self-made score functions can be passed and recieve an astropy gaia table and an astropy region table. optimize_grid returns parameters for the highest score

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT