lspitler / huntsman-dust Goto Github PK

First just run it on a normal image, without attempting to mask the image.

Maybe a few panels:

• original image
• zoomed smaller section of image, showing masked sources
• power spectrum

Aim is to create a set of fake images that have different levels of intrinsic spatial scale fluctuations. These will be used for testing out whether the power spectrum code can recover input fluctuations. Initially it should have no statistical noise. It might be that the sky background needs to be close to zero or not negative, but that is something you'll have to figure out.

Read about it online, but basically you'll need to create an empty __init__.py file where you code is. Then run python setup.py install (or python setup.py develop if still testing, writing code). This means you can just do an import anywhere:

from dustyhunts import main
main()

You'll have to modify the code imports to e.g.: import dustyhunts.util

Its hard to judge whether or not the detection code is getting all the objects or detecting non-objects like noise. A simple export to ds9 region would help.