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astro_fuse.py
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astro_fuse.py
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#!/usr/bin/python3
# *********************************************************************
# * Copyright (C) 2015 Jacopo Nespolo <j.nespolo@gmail.com> *
# * *
# * For the license terms see the file LICENCE, distributed *
# * along with this software. *
# *********************************************************************
#
# This file is part of astrotools.
#
# Astrotools is free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# Astrotools is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE.
# See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with astrotools. If not, see <http://www.gnu.org/licenses/>
#
from sys import exit, stdin, stdout, stderr, argv
import numpy as np
import argparse as ap
import pyfits
import re
par = ap.ArgumentParser(prog="astro_fuse",
description=("Combine different frames into a single "
"image."))
par.add_argument("filenames", nargs='+', help="Files to be processed")
par.add_argument("-a", "--average", default=True, action="store_true",
help=("Average together the input frames "
"(this is the default behaviour)."))
par.add_argument("-m", "--median", default=False, action="store_true",
help="Median of the input frames.")
par.add_argument("-r", '--rows', type=int, default=None,
help="Average this many rows at a time. (Default: optimise)")
par.add_argument("-v", '--verbose', default=False, action='store_true',
help="Print verbose output.")
par.add_argument("-o", "--output-file", default="output.fits",
help="Output file name.")
par.add_argument("-j", "--join-channels", default=False, action='store_true',
help="Join THREE frames into an RGB tiff image.")
def fuse_median(frames, args):
output = np.zeros(frames[0].shape, dtype=np.float32)
Nframes = len(frames)
shape = frames[0].shape
chunks = shape[0] // args.rows
remainder = shape[0] % args.rows
for i in range(chunks):
start_row = i * args.rows
end_row = (i + 1) * args.rows
output[start_row:end_row, ...] = \
np.median([f.data[start_row:end_row, ...] for f in frames],
axis=0)
if args.verbose:
msg = "approximately {:.1%} done.\r"
stderr.write(msg.format(end_row/shape[0]))
if remainder != 0:
output[end_row:, ...] = \
np.median([f.data[end_row:, ...] for f in frames],
axis=0)
return output
def fuse_mean(input_frames, args):
# determine number of input files
N_frames = len(input_frames)
# Check the size of the first frame, and use it as output frame size.
# If not all the frames share the same size, something bad is going to
# happen by the time numpy comes into play. Hence, we do not worry about it
# here, and instead wait for an exception to be raised somewhere.
size = input_frames[0].data.shape
# create the output array
out_frame = np.zeros(shape=size, dtype=np.float32)
# average the input frames
for n, frame in enumerate(input_frames):
if args.verbose:
stderr.write("Averaging frame {}/{}\n".format(n, N_frames))
out_frame += frame.data
out_frame /= N_frames
return out_frame
def fuse_join_channels(frames, args):
'''
Use three frames to pack an RGB tiff.
the highlight is stretched to the highest value representable in 16
bits.
'''
from skimage.io import imsave
clip = 2**16 - 1
red = input_frames[0].data
red_scale = clip / np.max(red)
red = np.uint16(red * red_scale)
green = input_frames[1].data
green_scale = clip / np.max(green)
green = np.uint16(green * green_scale)
blue = input_frames[2].data
blue_scale = clip / np.max(blue)
blue = np.uint16(blue * blue_scale)
out = np.dstack((red, green, blue))
imsave(args.output_file.replace("fits", "tiff"), out, plugin='freeimage')
if __name__ == "__main__":
args = par.parse_args()
# make sure the output is well formatted
if not re.search("\.fits$", args.output_file):
args.output_file += ".fits"
input_frames = []
# Read files
for fname in args.filenames:
# open the FITS file. We assume a single HDU, and add it to the
# input_frames list.
frame_hdulist = pyfits.open(fname, memmap=True, mode='readonly')
input_frames.append(frame_hdulist[0])
if args.join_channels:
fuse_join_channels(input_frames, args)
exit(0)
# if not provided by user, optimise the number of rows to average at once.
# TODO: write an optimiser that automatically calculates the optimal number
# of rows to compute at once. Also, double check the actual working
# of the FITS buffering: chances are that this is overkill and
# automatic FITS buffering already takes care of not crashing the
# machine.
if args.rows == None:
args.rows = 100
if args.median:
out_frame = fuse_median(input_frames, args=args)
args.average = False
elif args.average:
out_frame = fuse_mean(input_frames, args=args)
# write output FITS
hdu = pyfits.PrimaryHDU(out_frame)
hdu.header = input_frames[0].header
hdu.writeto(args.output_file, clobber=True)
exit(0)