I am trying to get the flux of a star in an image. I have been using numpy and pyfits and have the code. def distance(im,xc,yc): (rows,cols) = im.shape dist = zeros([rows,cols]).astype(Float64) for row in range(rows): for col in range(cols): dist[row,col] = sqrt(((row + 0.5) - yc)**2 + ((col + 0.5) - xc)**2) return dist def apphot(im,x,y,r): dist = distance(im,x,y) appmask = where(dist <= r,1,0) fluxim = where(appmask,im,0) appflux = sum(sum(fluxim)) skymask = where(dist > r, 1,0) skyim = where(skymask,im,0) sky = mean(skyim) print skyim print sky return 1 Output: > array (20,20) , type = f, has 400 elements > [ 45.89742126, 45.92555847, 45.8874054 , 45.88538208, 45.88244934, 45.9353241 , 36.75245361, 29.85816345, 27.53547668, 22.93712311, 22.93178101, 22.93699799, 22.91038208, 27.4988739 , 29.84021606, 36.71789551, 45.86646729, 45.86741638, 45.85328979, 45.823349 ,] where im is a ndarray, x and y are the position of the star and r is the radius of the aperture. I calculate the flux inside the aperture, but when I want to calculate the mean of the pixels outside the aperture I run into problems as the pixels values inside the aperture is 0 and is still considered in the mean calculation. Is there a way to do this without using masked arrays? How would I use a masked array to do it? Cheers Tommy "Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius -- and a lot of courage -- to move in the opposite direction" -- Albert Einstein |
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