import meds

# create a MEDS object for the given MEDS file
m = meds.MEDS(filename)

# read a cutout for object 35, cutout index 5
object_index = 35
cutout_index = 5
image = m.get_cutout(object_index, cutout_index)

# read the second cutout for this object
cutout_index = 1
im = m.get_cutout(object_index, cutout_index)

# get other image types
seg = m.get_cutout(object_index, cutout_index, type=’seg’)
wt = m.get_cutout(object_index, cutout_index, type=’weight’)
mask = m.get_cutout(object_index, cutout_index, type=’bmask’)

# get a python list of all cutouts for this object
imlist = m.get_cutout_list(object_index)
seglist = m.get_cutout_list(object_index, type=’seg’)

# The contents of the object data table is loaded when the MEDS object is
# created, and are accessible by name.

# number of cutouts
ncutout = m[’ncutout’][object_index]
for i in range(ncutout):
    cutout = m.get_cutout(object_index, i)
    # process the image

# get the jacobian of the WCS transformation
# as a dict
j = m.get_jacobian(object_index, cutout_index)

# as a numpy matrix
j = m.get_jacobian_matrix(object_index, cutout_index)

# list for all cutouts
jlist = m.get_jacobian_list(object_index)

# get the "ubserseg" weight map
wt = m.get_cweight_cutout_nearest(object_index, cutout_index)