Hi James,

Did you know there's an ellipsoid data object? You could do something like this:

In [14]: el = ds.ellipsoid(ds.domain_center, 0.5, 0.25, 0.1, np.array([1, 1, 1]), np.pi/4)

In [15]: el['cell_mass'] Out[15]: YTArray([4.45777680e+38, 4.45778381e+38, 4.45778677e+38, ..., 6.03437074e+36, 8.52994081e+36, 5.87109032e+37]) g

In [16]: el['cell_volume'].to('cm**3') Out[16]: YTArray([8.96887209e+68, 8.96887209e+68, 8.96887209e+68, ..., 5.34586435e+61, 5.34586435e+61, 5.34586435e+61]) cm**3

In [17]: for ax in 'xyz': ...: plot = yt.SlicePlot(ds, ax, ('gas', 'density'), data_source=el) ...: plot.save()

(see https://imgur.com/a/nqfl7yi for the resulting images using the enzo IsolatedGalaxy dataset from yt-project.org/data)

I think you could just use the same script you use with spheres but use an ellipsoid instead.

Note that in the example above I'm specifying the parameters of the ellipsoid (the first three arguments) in code units, which in Enzo are scaled to box size, your dataset might be different (for example if it uses CGS units internally).

I don't the ellipsoid data object is as commonly used as the rest of the yt data objects, if you notice any weirdness or bugs we'd love to hear about it in the form of e-mails here or issues on github.

-Nathan

On Tue, Jul 31, 2018 at 5:21 AM, James Cook jamescook.106@gmail.com wrote:

Hi All

I have been searching the documentation and can’t seem to figure out how to do this! Essentially I have a star defined via its density, and I define the edge of the star as to where the density has fallen to 5% of the max value. I calculate this radius using rays. The star has a different ‘edge’ depending on what direction (x,y,z) you take the ray as it is the result of a collision. I want to take in the 3 values for the edges, and sketch an ellipsoid that covers this definition. I then want to integrate this ellipsoid to find the total value of density. I use amr so total_quantity won’t work.

So I essentially want a weighted variable sum for an ellipsoid.

Can anyone help?

Thanks

James

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