[yt-users] Projection disagrees with original data.

[Nathan Goldbaum]

On Mon, Jun 27, 2016 at 12:14 PM, Nathan Goldbaum <nathan12343 at gmail.com>
wrote:

>
>
> On Mon, Jun 27, 2016 at 11:59 AM, Hansheng Chen <jasonhs1221 at gmail.com>
> wrote:
>
>> Hello yt users,
>>
>> I have a question about projection. I used ds.proj() and to_frb() to get
>> an image array of the projected 'Electron_Density' of an entire dataset. I
>> multiplied the mean of projected 'Electron_Density' by the entire area of
>> x-y plane and got a sum of total mass of electrons. Then, I used
>> ds.all_data() and mean() to get the mean of 'Electron_Density' in
>> 3-dimensional. I multiplied the mean by the volume of the entire box of the
>> dataset and got another sum of total mass of electrons. However, this sum
>> did not match the sum I got from the projected 'Electron_Density'
>> previously. Here are the codes I used:
>>
>> import yt
>> import numpy as np
>> ds = yt.load("redshift0100/redshift0100")
>> print("Redshift =", ds.current_redshift)
>>
>> p = yt.ProjectionPlot(ds, 2, 'Electron_Density')
>> density_image = p.frb['Electron_Density']
>> ed = density_image['Electron_Density'].convert_to_cgs()
>>
>
> Are you sure this code would run? I'm pretty sure this line would produce
> an IndexError, since you can't use a string to index into an array.
>
>
>> ed_ndarr = ed.to_ndarray()
>> sum1 = ed_ndarr.mean() * ((105.82 * 3.085677581e+24)**2)
>> print(sum1)
>>
>> dd = ds.all_data()
>> ed_3d = dd['Electron_Density'].convert_to_cgs()
>> sum2 = ed_3d.mean() * ((105.82 * 3.085677581e+24)**3)
>> print(sum2)
>>
>
> You're not comparing apples and oranges here.
>

Oops, meant to say "you're comparing apples and oranges here"


> In particular, in this section, you've found the mean density of cells in
> your simulation. If you have an AMR simulation, each cell is not
> necessarily the same size, so they do not contribute equally if you want to
> find the true, volume or mass-weighted mean density in your simulation.
>
> It would be a closer comparison to use a covering grid, or you could ask
> for a volume-weighted mean:
>
> In [18]: dd.quantities.weighted_average_quantity('El_density',
> weight='cell_volume
>     ...: ')
> Out[18]: 5.54459040433e-34 g/cm**3
>
> This script makes use of a public test dataset from yt-project.org/data
> and illustrates the point I'm making:
>
> https://bpaste.net/show/2eab176d8128
>
> On my machine, both operations print out the same result to machine
> precision.
>
>
>> (105.82 * 3.085677581e+24) is the width of entire box in cm. I think sum1
>> and sum2 should be close to each other, but the result was that the two
>> values did not match with each other. Is there any problem in the codes I
>> used to get the values of sum1 and sum2? Could some one give me some help?
>>
>> Thank you very much!
>>
>> Sincerely,
>> Hansheng
>>
>>
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>>
>>
>
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