def irafalign(filepath,
uknstarlist,
refstarlist,
shape,
alifilepath=None,
outdir="alipy_out",
makepng=False,
hdu=0,
verbose=True):
"""
Uses iraf geomap and gregister to align the image. Three steps :
* Write the matched source lists into an input file for geomap
* Compute a geomap transform from these stars.
* Run gregister
:param filepath: FITS file to be aligned
:type filepath: string
:param uknstarlist: A list of stars from the "unknown" image to be aligned,
that matches to ...
:type uknstarlist: list of Star objects
:param refstarlist: ... the list of corresponding stars in the reference
image.
:type refstarlist: list of Star objects
:param shape: Output shape (width, height)
:type shape: tuple
:param alifilepath: where to save the aligned image. If None, I put it in
the default directory.
:type alifilepath: string
:param makepng: If True I make a png of the aligned image as well.
:type makepng: boolean
:param hdu: The hdu of the fits file that you want me to use.
0 is primary. If multihdu, 1 is usually science.
"""
try:
from pyraf import iraf
except ImportError:
print("Couldn't import pyraf !")
return
assert len(uknstarlist) == len(refstarlist)
if len(uknstarlist) < 2:
if verbose:
print("Not enough stars for using geomap !")
return
basename = os.path.splitext(os.path.basename(filepath))[0]
geomapinpath = basename + ".geomapin"
geodatabasepath = basename + ".geodatabase"
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
# Step 1, we write the geomap input.
table = []
for (uknstar, refstar) in zip(uknstarlist, refstarlist):
table.append([refstar.x, refstar.y, uknstar.x, uknstar.y])
geomap = open(geomapinpath, "w")
writer = csv.writer(geomap, delimiter="\t")
writer.writerows(table)
geomap.close()
# Step 2, geomap
iraf.unlearn(iraf.geomap)
iraf.geomap.fitgeom = "rscale"
# You can change this to:
# shift, xyscale, rotate, rscale
iraf.geomap.function = "polynomial" # Surface type
iraf.geomap.maxiter = 3 # Maximum number of rejection iterations
iraf.geomap.reject = 3.0 # Rejection limit in sigma units
# other options you could specify :
# (xxorder= 2) Order of x fit in x
# (xyorder= 2) Order of x fit in y
# (xxterms= half) X fit cross terms type
# (yxorder= 2) Order of y fit in x
# (yyorder= 2) Order of y fit in y
# (yxterms= half) Y fit cross terms type
# (calctyp= real) Computation type
iraf.geomap.transfo = "broccoli" # keep it
iraf.geomap.interac = "no" # keep it
iraf.geomap.verbose = "yes" # keep it
# iraf.geomap.results = "bla.summary" # The optional results summary files
geomapblabla = iraf.geomap(input=geomapinpath,
database=geodatabasepath,
xmin=1,
xmax=shape[0],
ymin=1,
ymax=shape[1],
Stdout=1)
# We read this output ...
for line in geomapblabla:
if "X and Y scale:" in line:
mapscale = line.split()[4:6]
if "Xin and Yin fit rms:" in line:
maprmss = line.split()[-2:]
if "X and Y axis rotation:" in line:
mapangles = line.split()[-4:-2]
if "X and Y shift:" in line:
mapshifts = line.split()[-4:-2]
# not used?
geomaprms = math.sqrt(
float(maprmss[0]) * float(maprmss[0]) +
float(maprmss[1]) * float(maprmss[1]))
geomapangle = float(mapangles[0]) # % 360.0
geomapscale = 1.0 / float(mapscale[0])
if mapscale[0] != mapscale[1]:
raise RuntimeError("Error reading geomap scale")
if verbose:
print(("IRAF geomap : Rotation %+11.6f [deg], "
"scale %8.6f, RMS %.3f [pixel]") %
(geomapangle, geomapscale, geomaprms))
# Step 3
if alifilepath is None:
alifilepath = os.path.join(outdir, basename + "_gregister.fits")
else:
outdir = os.path.split(alifilepath)[0]
if not os.path.isdir(outdir):
os.makedirs(outdir)
if os.path.isfile(alifilepath):
os.remove(alifilepath)
iraf.unlearn(iraf.gregister)
iraf.gregister.geometry = "geometric" # linear, distortion, geometric
iraf.gregister.interpo = "spline3" # linear, spline3
iraf.gregister.boundary = "constant" # padding with zero
iraf.gregister.constant = 0.0
iraf.gregister.fluxconserve = "yes"
if verbose:
print("IRAF gregister ...")
regblabla = iraf.gregister(input='%s[%s]' % (filepath, hdu),
output=alifilepath,
database=geodatabasepath,
transform="broccoli",
Stdout=1)
# not used?
if verbose:
print("IRAF gregister done !")
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
if makepng:
try:
import f2n
except ImportError:
print("Couldn't import f2n -- install it !")
return
myimage = f2n.fromfits(alifilepath, verbose=False)
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative=False)
myimage.writetitle(os.path.basename(alifilepath))
if not os.path.isdir(outdir):
os.makedirs(outdir)
myimage.tonet(
os.path.join(outdir,
os.path.basename(alifilepath) + ".png"))
def irafalign(filepath, uknstarlist, refstarlist, shape,
alifilepath=None, outdir="alipy_out",
makepng=False, hdu=0, verbose=True):
"""
Uses iraf geomap and gregister to align the image. Three steps :
* Write the matched source lists into an input file for geomap
* Compute a geomap transform from these stars.
* Run gregister
:param filepath: FITS file to be aligned
:type filepath: string
:param uknstarlist: A list of stars from the "unknown" image to be aligned,
that matches to ...
:type uknstarlist: list of Star objects
:param refstarlist: ... the list of corresponding stars in the reference
image.
:type refstarlist: list of Star objects
:param shape: Output shape (width, height)
:type shape: tuple
:param alifilepath: where to save the aligned image. If None, I put it in
the default directory.
:type alifilepath: string
:param makepng: If True I make a png of the aligned image as well.
:type makepng: boolean
:param hdu: The hdu of the fits file that you want me to use.
0 is primary. If multihdu, 1 is usually science.
"""
try:
from pyraf import iraf
except ImportError:
print("Couldn't import pyraf !")
return
assert len(uknstarlist) == len(refstarlist)
if len(uknstarlist) < 2:
if verbose:
print("Not enough stars for using geomap !")
return
basename = os.path.splitext(os.path.basename(filepath))[0]
geomapinpath = basename + ".geomapin"
geodatabasepath = basename + ".geodatabase"
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
# Step 1, we write the geomap input.
table = []
for (uknstar, refstar) in zip(uknstarlist, refstarlist):
table.append([refstar.x, refstar.y, uknstar.x, uknstar.y])
geomap = open(geomapinpath, "wb") # b needed for csv
writer = csv.writer(geomap, delimiter="\t")
writer.writerows(table)
geomap.close()
# Step 2, geomap
iraf.unlearn(iraf.geomap)
iraf.geomap.fitgeom = "rscale"
# You can change this to:
# shift, xyscale, rotate, rscale
iraf.geomap.function = "polynomial" # Surface type
iraf.geomap.maxiter = 3 # Maximum number of rejection iterations
iraf.geomap.reject = 3.0 # Rejection limit in sigma units
# other options you could specify :
# (xxorder= 2) Order of x fit in x
# (xyorder= 2) Order of x fit in y
# (xxterms= half) X fit cross terms type
# (yxorder= 2) Order of y fit in x
# (yyorder= 2) Order of y fit in y
# (yxterms= half) Y fit cross terms type
# (calctyp= real) Computation type
iraf.geomap.transfo = "broccoli" # keep it
iraf.geomap.interac = "no" # keep it
iraf.geomap.verbose = "yes" # keep it
# iraf.geomap.results = "bla.summary" # The optional results summary files
geomapblabla = iraf.geomap(input=geomapinpath,
database=geodatabasepath,
xmin=1, xmax=shape[0],
ymin=1, ymax=shape[1],
Stdout=1)
# We read this output ...
for line in geomapblabla:
if "X and Y scale:" in line:
mapscale = line.split()[4:6]
if "Xin and Yin fit rms:" in line:
maprmss = line.split()[-2:]
if "X and Y axis rotation:" in line:
mapangles = line.split()[-4:-2]
if "X and Y shift:" in line:
mapshifts = line.split()[-4:-2]
# not used?
geomaprms = math.sqrt(float(maprmss[0]) * float(maprmss[0]) +
float(maprmss[1]) * float(maprmss[1]))
geomapangle = float(mapangles[0]) # % 360.0
geomapscale = 1.0 / float(mapscale[0])
if mapscale[0] != mapscale[1]:
raise RuntimeError("Error reading geomap scale")
if verbose:
print(("IRAF geomap : Rotation %+11.6f [deg], "
"scale %8.6f, RMS %.3f [pixel]") % (geomapangle,
geomapscale,
geomaprms))
# Step 3
if alifilepath is None:
alifilepath = os.path.join(outdir, basename + "_gregister.fits")
else:
outdir = os.path.split(alifilepath)[0]
if not os.path.isdir(outdir):
os.makedirs(outdir)
if os.path.isfile(alifilepath):
os.remove(alifilepath)
iraf.unlearn(iraf.gregister)
iraf.gregister.geometry = "geometric" # linear, distortion, geometric
iraf.gregister.interpo = "spline3" # linear, spline3
iraf.gregister.boundary = "constant" # padding with zero
iraf.gregister.constant = 0.0
iraf.gregister.fluxconserve = "yes"
if verbose:
print("IRAF gregister ...")
regblabla = iraf.gregister(input='%s[%s]' % (filepath, hdu),
output=alifilepath,
database=geodatabasepath,
transform="broccoli",
Stdout=1)
# not used?
if verbose:
print("IRAF gregister done !")
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
if makepng:
try:
import f2n
except ImportError:
print("Couldn't import f2n -- install it !")
return
myimage = f2n.fromfits(alifilepath, verbose=False)
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative=False)
myimage.writetitle(os.path.basename(alifilepath))
if not os.path.isdir(outdir):
os.makedirs(outdir)
myimage.tonet(
os.path.join(outdir, os.path.basename(alifilepath) + ".png"))
})
print "geomap done"
iraf.unlearn(iraf.gregister)
iraf.gregister.geometry = "geometric" # linear, distortion, geometric
iraf.gregister.interpo = "spline3" # linear, spline3
iraf.gregister.boundary = "constant" # padding with zero
iraf.gregister.constant = 0.0
iraf.gregister.fluxconserve = "yes"
regblabla = iraf.gregister(input=imgtorotate,
output=aliimg,
database=databasename,
transform="broccoli",
xmin=1,
xmax=dimx,
ymin=1,
ymax=dimy,
Stdout=1)
print "gregister done"
if os.path.isfile(databasename):
os.remove(databasename)
db.pack(imgdb)
endtime = datetime.now()
timetaken = nicetimediff(endtime - starttime)