do_alipy3.py

import alipy
import glob

images_to_align = sorted(glob.glob("../ASTR101/lab2/data/sliced/*.fits"))
ref_image = "../ASTR101/lab2/data/sliced/ref.fits"

identifications = alipy.ident.run(ref_image, images_to_align, visu=False)
# That's it !
# Put visu=True to get visualizations in form of png files (nice but much slower)
# On multi-extension data, you will want to specify the hdu (see API doc).

# The output is a list of Identification objects, which contain the transforms :
for id in identifications: # list of the same length as images_to_align.
        if id.ok == True: # i.e., if it worked

#This is the old Python 2 print statement:
#                print "%20s : %20s, flux ratio %.2f" % (id.ukn.name, id.trans, id.medfluxratio)
                print("%20s : %20s, flux ratio %.2f" % (id.ukn.name,
                                                        id.trans,
                                                        id.medfluxratio))

#		print("%20s : %20s, flux ratio %.2f" % (id.ukn.name, id.trans, id.medfluxratio))
                # id.trans is a alipy.star.SimpleTransform object. Instead of printing it out as a string,
                # you can directly access its parameters :
                #print id.trans.v # the raw data, [r*cos(theta)  r*sin(theta)  r*shift_x  r*shift_y]
                #print id.trans.matrixform()
                #print id.trans.inverse() # this returns a new SimpleTransform object

        else:
#                print "%20s : no transformation found !" % (id.ukn.name)
                print ("%20s : no transformation found !" % (id.ukn.name))

# Minimal example of how to align images :

outputshape = alipy.align.shape(ref_image)
# This is simply a tuple (width, height)... you could specify any other shape.

for id in identifications:
        if id.ok == True:

                # Variant 1, using only scipy and the simple affine transorm :
                alipy.align.affineremap(id.ukn.filepath, id.trans, shape=outputshape, makepng=True)

                # Variant 2, using geomap/gregister, correcting also for distortions :
		#                alipy.align.irafalign(id.ukn.filepath, id.uknmatchstars, id.refmatchstars, shape=outputshape, makepng=False)
                # id.uknmatchstars and id.refmatchstars are simply lists of corresponding Star objects.

                # By default, the aligned images are written into a directory "alipy_out".

# To be continued ...