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#!/usr/bin/env python3
#
# Copyright (c) 2017 Weitian LI <liweitianux@live.com>
# MIT license
"""
Calculate the coordinate of the emission centroid within the image.
The image are smoothed first, and then an iterative procedure with
two phases is applied to determine the emission centroid.
"""
import os
import sys
import argparse
import subprocess
import tempfile
from _context import acispy
from acispy.manifest import get_manifest
from acispy.pfiles import setup_pfiles
from acispy.ds9 import ds9_view
from acispy.region import Regions
def smooth_image(infile, outfile=None,
kernelspec="lib:gaus(2,5,1,10,10)", method="fft",
clobber=False):
"""
Smooth the image by a Gaussian kernel using the ``aconvolve`` tool.
Parameters
----------
infile : str
Path to the input image file
outfile : str, optional
Filename/path of the output smoothed image
(default: build in format ``<infile_basename>_aconv.fits``)
kernelspec : str, optional
Kernel specification for ``aconvolve``
method : str, optional
Smooth method for ``aconvolve``
Returns
-------
outfile : str
Filename/path of the smoothed image
"""
clobber = "yes" if clobber else "no"
if outfile is None:
outfile = os.path.splitext(infile)[0] + "_aconv.fits"
subprocess.check_call(["punlearn", "aconvolve"])
subprocess.check_call([
"aconvolve", "infile=%s" % infile, "outfile=%s" % outfile,
"kernelspec=%s" % kernelspec, "method=%s" % method,
"clobber=%s" % clobber
])
return outfile
def get_peak(image):
"""
Get the peak coordinate on the image.
Returns
-------
peak : 2-float tuple
(Physical) coordinate of the peak.
"""
subprocess.check_call(["punlearn", "dmstat"])
subprocess.check_call([
"dmstat", "infile=%s" % image,
"centroid=no", "media=no", "sigma=no", "clip=no", "verbose=0"
])
peak = subprocess.check_output([
"pget", "dmstat", "out_max_loc"
]).decode("utf-8").strip()
peak = peak.split(",")
return (float(peak[0]), float(peak[1]))
def get_centroid(image, center, radius=50):
"""
Calculate the centroid on image within the specified circle.
Parameters
----------
image : str
Path to the image file.
center : 2-float tuple
Central (physical) coordinate of the circle.
radius : float
Radius (pixel) of the circle.
Returns
-------
centroid : 2-float tuple
(Physical) coordinate of the centroid.
"""
x, y = center
with tempfile.NamedTemporaryFile(mode="w+") as fp:
fp.file.write("circle(%f,%f,%f)\n" % (x, y, radius))
fp.file.flush()
subprocess.check_call(["punlearn", "dmstat"])
subprocess.check_call([
"dmstat", "infile=%s[sky=region(%s)]" % (image, fp.name),
"centroid=yes", "media=no", "sigma=no", "clip=no", "verbose=0"
])
centroid = subprocess.check_output([
"pget", "dmstat", "out_cntrd_phys"
]).decode("utf-8").strip()
centroid = centroid.split(",")
return (float(centroid[0]), float(centroid[1]))
def main():
parser = argparse.ArgumentParser(
description="Calculate the emission centroid within the image")
parser.add_argument("-i", "--infile", dest="infile", required=True,
help="input image file (e.g., 0.7-2.0 keV)")
parser.add_argument("-o", "--outfile", dest="outfile",
default="centroid.reg",
help="output centroid region file " +
"(default: centroid.reg")
parser.add_argument("-R", "--radius1", dest="radius1",
type=float, default=100,
help="circle radius [pixel] for first phase " +
"centroid calculation (default: 100 pixel)")
parser.add_argument("-r", "--radius2", dest="radius2",
type=float, default=50,
help="circle radius [pixel] for second phase " +
"calculation to tune centroid (default: 50 pixel)")
parser.add_argument("-n", "--niter", dest="niter",
type=int, default=10,
help="iterations for each phase (default: 10)")
parser.add_argument("-s", "--start", dest="start",
help="a region file containing a circle/point " +
"that specifies the starting point " +
"(default: using the peak of the image)")
parser.add_argument("-V", "--view", dest="view", action="store_true",
help="open DS9 to view output centroid")
parser.add_argument("-C", "--clobber", dest="clobber", action="store_true",
help="overwrite existing files")
args = parser.parse_args()
setup_pfiles(["aconvolve", "dmstat"])
print("Smooth input image using 'aconvolve' ...", file=sys.stderr)
img_smoothed = smooth_image(args.infile, clobber=args.clobber)
if args.start:
print("Get starting point from region file: %s" % args.start,
file=sys.stderr)
region = Regions(args.start).regions[0]
center = (region.xc, region.yc)
else:
print("Use peak as the starting point ...", file=sys.stderr)
center = get_peak(img_smoothed)
print("Starting point: (%f, %f)" % center, file=sys.stderr)
centroid = center
for phase, radius in enumerate([args.radius1, args.radius2]):
print("Calculate centroid phase %d (circle radius: %.1f)" %
(phase+1, radius), file=sys.stderr)
for i in range(args.niter):
print("%d..." % (i+1), end="", flush=True, file=sys.stderr)
centroid = get_centroid(img_smoothed, center=centroid,
radius=radius)
print("Done!", file=sys.stderr)
with open(args.outfile, "w") as f:
f.write("point(%f,%f)\n" % centroid)
print("Saved centroid to file:", args.outfile, file=sys.stderr)
if args.view:
ds9_view(img_smoothed, regfile=args.outfile)
# Add calculated centroid region to manifest
manifest = get_manifest()
key = "reg_centroid"
manifest.setpath(key, args.outfile)
if __name__ == "__main__":
main()
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