%matplotlib inline
import numpy as np
from fitsio import read
import sep
from matplotlib import pyplot as plt

data = read("/home/kyle/code/sep/data/image.fits")

fig = plt.figure(figsize=(10., 10.))
plt.imshow(data, cmap='gray', vmin=6500., vmax=7000., interpolation='nearest')

bkg = sep.Background(data)  # measure background

bkg.globalback, bkg.globalrms  # global statistics

bkgim = bkg.back()  # evaluate background

# plot background
fig = plt.figure(figsize=(10., 10.))
plt.imshow(bkgim, cmap='gray')

bkg.subfrom(data)  # subtract background directly from data; no intermediate array

# detect objects
objects = sep.extract(data, 1.5 * bkg.globalrms)

# objects is a numpy structured array
len(objects)

# position of 31st object
objects[30]['x'], objects[30]['y']

# fields available
objects.dtype.names

# circular aperture photometry: radius=3 pixels, background annulus between 5 pixels and 8 pixels
flux, fluxerr, flags = sep.sum_circle(data, objects['x'], objects['y'], 3.0, bkgann=(5., 8.))

flux

!cd /home/kyle/code/sep/ && bench.py