In [1]:
import vaex as vx
import pylab
%matplotlib inline
In [2]:
ds = vx.zeldovich(scale=100, t=1e1).concat(vx.example())
#ds = vx.example()
ds("x", "y").bounded_by_sigmas(square=True).gridded()
Out[2]:
In [3]:
ds.export_hdf5("concat.hdf5", column_names=["x", "y"], shuffle=True, selection=False)
In [4]:
shuffled = vx.open("concat.hdf5")
xy = shuffled("x", "y")
shuffled.set_active_fraction(0.1)
limits = xy.limits_sigma()
xy.bounded_by(limits).gridded()
Out[4]:
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