In [16]:

    

%autosave 20
import matplotlib.pyplot as plt
import numpy as np
import astropy.units as u
from astropy.coordinates import SkyCoord
from astroquery.vizier import Vizier

from sklearn import cluster
from sklearn import mixture


    

    















    




Autosaving every 20 seconds

In [12]:

    

center_coord = SkyCoord('02h21m00s +57d07m42s')
vizier = Vizier(
    column_filters={'Bmag': '<13'},  # число больше — звёзд больше
    row_limit=10000
)
stars = vizier.query_region(
    center_coord,
    width=1.5 * u.deg,
    height=1.5 * u.deg,
    catalog='USNO-A2.0',
)[0]
ra = stars['RAJ2000']._data  # прямое восхождение, аналог долготы
dec = stars['DEJ2000']._data  # склонение, аналог широты

x = np.stack((ra, dec), axis=1)
i = np.random.choice(x.shape[0], size=x.shape[0], replace=False)
x = x[i]
print(x.shape)

plt.scatter(*x.T)


    

    




(688, 2)






    
Out[12]:





<matplotlib.collections.PathCollection at 0x7f15d41da2b0>






    

In [17]:

    

colors = np.array([[0., 0., 1.], [1., 0., 0.]])

kmeans = cluster.KMeans(n_clusters=2, n_jobs=-1)
y = kmeans.fit_predict(x)
plt.scatter(*x.T, color=colors[y])


    

    
Out[17]:





<matplotlib.collections.PathCollection at 0x7f15d42cdac8>






    

In [19]:

    

gm = mixture.GaussianMixture(n_components=2)
gm.fit(x)
y = gm.predict(x)
plt.scatter(*x.T, color=colors[y])


    

    
Out[19]:





<matplotlib.collections.PathCollection at 0x7f15d417fda0>






    

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