A python package for painting the sky
You can install AstroPaint by running the following in the command line:
git clone https://github.com/syasini/AstroPaint.git
pip install [-e] .
-e argument will install the package in editable mode which is suitable for developement. If you want to modify the code use this option.
If you want the sample catalogs to be cloned automatically
along with the
rest of the repository, make sure you have Git Large File Storage (
git lfs) installed.
If you are a conda user, please consider creating a new environment before installation:
conda create -n astropaint python=3.7
conda activate astropaint
Converting catalogs to mock maps with AstroPaint is extremely simple. Here is what an example session looks like:
from astropaint import Catalog, Canvas, Painter catalog = Catalog(data=your_input_data) canvas = Canvas(catalog, nside) painter = Painter(template=your_radial_profile) painter.spray(canvas)
That's it! Now you can check out your masterpiece using
What is AstroPaint?
AstroPaint is a python package for generating and visualizing sky maps of a wide range of astrophysical signals originating from dark matter halos or the gas that they host. AstroPaint creates a whole-sky mock map of the target signal/observable, at a desired resolution, by combining an input halo catalog and the radial/angular profile of the astrophysical effect. The package also provides a suite of tools that can facilitate analysis routines such as catalog filtering, map manipulation, and cutout stacking. The simulation suite has an Object-Oriented design and runs in parallel, making it both easy to use and readily scalable for production of high resolution maps with large underlying catalogs. Although the package has been primarily developed to simulate signals pertinent to galaxy clusters, its application extends to halos of arbitrary size or even point sources.
Here's an example script that paints a nonsense template on a 10 x 10 [sqr deg]
patch of the
import numpy as np from astropaint import Catalog, Canvas, Painter # Load the Sehgal catalog catalog = Catalog("Sehgal") # cutout a 10x10 sqr degree patch of the catalog catalog.cut_lon_lat(lon_range=[0,10], lat_range=[0,10]) # pass the catalog to canvas canvas = Canvas(catalog, nside=4096, R_times=5) # define a nonsense template and plot it def a_nonsense_template(R, R_200c, x, y, z): return np.exp(-(R/R_200c/3)**2)*(x+y+z) # pass the template to the painter painter = Painter(template=a_nonsense_template) # plot the template for halos #0, #10, and #100 for R between 0 to 5 Mpc R = np.linspace(0,5,100) painter.plot_template(R, catalog, halo_list=[0,10,100])
# spray the template over the canvas painter.spray(canvas) # show the results canvas.show_map("cartview", lonra=[0,10], latra=[0,10])
You can use the
n_cpus argument in the spray function to paint in parallel and speed things up!
n_cpus=-1 uses all the available cpus.
You can easily stack cutouts of the map using the following:
deg_range = [-0.2, 0.2] # deg halo_list = np.arange(5000) # stack the first 5000 halos # stack the halos and save the results in canvas.stack stack = canvas.stack_cutouts(halo_list=halo_list, lon_range=deg_range, lat_range=deg_range) plt.imshow(canvas.stack)
Line-Of-Sight integration of 3D profiles
AstroPaint only allows you to paint 2D (line-of-sight integrated) profiles on
your catalog halos, so if you already have the analytical expression of
the projected profile you want to paint, we are in business. However, not
all 3D profiles can be LOS integrated analytically (e.g. generalized NFW
or Einasto, etc), and integrating profiles numerically along every
single LOS is generally expensive. In order to alleviate this problem, AstroPaint offers two python decorators
@interpolate which make 3D -> 2D projections effortless.
To convert a 3D profile into a 2D LOS integrated profile, all you need to do
is add the
@LOS_integrate to the definition.
For example, here's how you can turn a 3D top hat profile
def tophat_3D(r, R_200c): """Equals 1 inside R_200c and 0 outside""" tophat = np.ones_like(r) tophat[r > R_200c]=0 return tophat
into a 2D projected one:
from astropaint.lib.utilities import LOS_integrate @LOS_integrate def tophat_2D(R, R_200c): """project tophat_3D along the line of sight""" return tophat_3D(R, R_200c)
This function integrates the
tophat_3D function along every single line of
sight. If you have many halos in a high resolution map, this can take
forever. The trick to make this faster would be to integrate along a
several LOSs and interpolate the values in between. This is what the
@interpolate decorator does. So, a faster version of the
tophat_2D function can be constructed as the following:
from astropaint.lib.utilities import interpolate @interpolate(n_samples=20) @LOS_integrate def tophat_2D_interp(R, R_200c): """project and interpolate tophat_3D along the line of sight""" return tophat_3D(R, R_200c)
This is much faster, but the speed comes at a small price. If your 3D profile is not smooth, the interpolated 2D projection will slightly deviate from the exact integration.
Does this plot agree with what you would expect a LOS integrated top hat profile (a.k.a. a solid sphere) to look like?
Painting Optical Depth and kSZ Profiles on the WebSky Catalog
Let's use the
Battaglia16 gas profiles to paint tau (optical depth) and
kinetic Sunyaev-Zeldovich (kSZ) on the WebSky catalog halos.
from astropaint.profiles import Battaglia16 tau_painter = Painter(Battaglia16.tau_2D_interp)
Since the shape of the profile is smooth, we won't lose accuracy by using the interpolator.
Let's paint this on a 5x5 sqr deg patch of the WebSky catalog with a mass cut of 8E13 M_sun.
catalog = Catalog("WebSky_lite") catalog.cut_lon_lat(lon_range=[5,10], lat_range=[5,10]) catalog.cut_M_200c(8E13) canvas = Canvas(catalog, nside=8192, R_times=3) tau_painter.spray(canvas)
kSZ_painter = Painter(Battaglia16.kSZ_T) kSZ_painter.spray(canvas)
And here is what it looks like:
Just because AstroPaint is developed for probing new science and doing serious stuff, it doesn't mean you can't have fun with it! Check out our cool web app to get your hands dirty with some paint.
Made with AstroPaint
How to contribute
If you would like to contribute to AstroPaint, take the following steps:
- Fork this repository
- Clone it on your local machine
- Create a new branch (be as explicit as possible with the branch name)
- Add and Commit your changes to the local branch
- Push the branch to your forked repository
- Submit a pull request on this repository
Developement happens on the
develop branch, so make sure you are always in sync with the latest version and submit your pull requests to this branch.