[yt-users] Profile plot of a 2d projection FRB object

John ZuHone jzuhone at gmail.com
Fri Jan 16 19:31:49 PST 2015


This is a bit of a long way around, but you could write the FRB to a FITS file and read it in as a dataset. You would get the coordinate system, units, etc., and the whole YT machinery.

Use the export_fits method:

my_frb.export_fits("myfile.fits", fields)

Then:

ds = yt.load("my_file.fits")

I'm not at a computer so I don't remember the exact signature, but it should be in the code and you can check using help(my_frb.export_fits). If you're interested I can write back with more info later.

The other advantage of this is that you can store the data to disk. You'll have to install the AstroPy package.

Kavli Center for Astrophysics and Space Research
Massachusetts Institute of Technology
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> On Jan 16, 2015, at 8:34 PM, Ben Thompson <bthompson2090 at gmail.com> wrote:
> 
> Hey guys.
> 
> I have a solution together for myself involving the new particle_position_relative_[xyz] fields and multiple instances of np.histogram and np.linspace which seems to do the trick.
> 
> Although I would not complain if a piece of code that would be more native to the inner workings of YT existed that made use of the FRB data objects :). So that would be very nice Cameron. Don't feel the need to rush with it though, as I made a numpy solution for myself. But I would be interested to see that code.
> 
> Ben
> 
>> On 17 Jan 2015 01:27, "Britton Smith" <brittonsmith at gmail.com> wrote:
>> Hi Ben,
>> 
>> I seem to recall people on this list doing similar things in the past with their own external code.  Does anyone still have their 2D radial profile code around anymore?
>> 
>> Would it perhaps work to create a uniform grid dataset from an FRB array?
>> 
>> Britton
>> 
>>> On Tue, Jan 13, 2015 at 12:49 PM, Ben Thompson <bthompson2090 at gmail.com> wrote:
>>> Hello everyone.
>>> 
>>> I was wondering if anyone has had experience with producing a profile plot from a 2d projection object (FRB object).
>>> 
>>> Essentially, what I am trying to do is plot the stellar surface density of a galaxy as a function of radius.
>>> 
>>> This is achieved by doing the following from a disk YT object called cylinder (in which the origional simulation object is called shot)
>>> 
>>> center = cylinder.get_field_parameter("center")
>>> normal = cylinder.get_field_parameter("normal")
>>> image_width = (100,"kpc")
>>> three_image_width = YTArray((image_width[0], image_width[0], image_width[0]),image_width[1])
>>> left = center - image_width
>>> right = center + image_width
>>> region = shot.region(center, left, right)
>>> 
>>> proj = yt.ProjectionPlot(cylinder.ds,"z",[("deposit","stars_density")],center=center,width=image_width,data_source=region,axes_unit="kpc")
>>> 
>>> the error arrises here
>>> 
>>> prof = yt.create_profile(proj,bin_fields="cylindrical_r",fields=[("deposit","stars_density")],n_bins=128,weight_field=None )
>>> 
>>> where I get the error
>>> 
>>> 
>>> /gpfs/home/........./profiles.pyc in create_profile(data_source, bin_fields, fields, n_bins, extrema, logs, units, weight_field, accumulation, fractional)
>>>    1304     else:
>>>    1305         raise NotImplementedError
>>> -> 1306     bin_fields = data_source._determine_fields(bin_fields)
>>>    1307     fields = data_source._determine_fields(fields)
>>>    1308     if units is not None:
>>> 
>>> AttributeError: 'FixedResolutionBuffer' object has no attribute '_determine_fields'
>>> 
>>> Any ideas how to get around this error? 
>>> 
>>> 
>>> Also some other things to add as a postscript. Since how the projection works, if I provide weights=None as a keyword argument within the ProjectionPlot object, I get a surface density (g/cm^2). But also a "cylindrical_r" in cm^2 as well. I *think* the way to get around this is to do another projection where weights="ones", get the radius values out of that profile.. and then in matplotlib, useing the surface density array from the former profile, and the radius bin array from the latter... Produce a plot of the surface density as a function of radius from those two arrays (I might check by hand afterwards to see if this does the trick). This seems kinda convoluted so I am wondering if there is an easier way than this.
>>> 
>>> 
>>> 
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>> 
>> 
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