def makeCat(self, imgfile, instdet, weightfile=None, extref=False):
"""Makes a catalog of objects to be used for input to superalign and creates a DS9 region file of objects"""
imgfile_cat = '%s.cat' % imgfile.replace('.fits', '')
imgfile_reg = '%s.reg' % imgfile.replace('.fits', '')
o_radec = []
ext = 0
objectlist = self.findSources('%s[%s]' % (imgfile, ext), imgfile_cat, instdet, weightfile, extref=extref)
cleanobjectlist = self.removeCloseSources(objectlist)
print 'Found %s sources' % len(cleanobjectlist)
wcs = HSTWCS(str(imgfile))
for obj in cleanobjectlist:
sky = wcs.all_pix2world(np.array([[obj.x, obj.y]]), 1)
o_radec.append([obj.ra[0], obj.dec[0]])
obj.ra = sky[0][0]
obj.dec = sky[0][1]
# Write out a ds9 region file of object selected for alignment
regout = open(imgfile_reg, 'w')
regout.write('global color=green font="helvetica 8 normal" edit=1 move=1 delete=1 include=1 fixed=0\nfk5\n')
for i,rd in enumerate(o_radec):
oid = i+1
regout.write('circle(%s,%s,%s") # color=%s text={%s}\n' % (rd[0], rd[1], 0.5, 'red', oid))
regout.close()
# Now we need to write out the catalog in the reference image coords in arcseconds with respect to center of the image
catout = open(imgfile_cat, 'w')
for i,obj in enumerate(cleanobjectlist):
oid = i+1
catout.write('%i %.9f %.9f %.4f %.4f %.4f\n' % (oid, obj.ra, obj.dec, obj.x, obj.y, obj.mag))
catout.close()
return
def stars2cat(drzfile, refwcs):
"""
Makes catalog file from a superalign .stars file
"""
wcs = HSTWCS(fits.open(drzfile))
starsfile = drzfile.replace('.fits', '_sa.cat.stars')
catfile = '%s.cat' % starsfile
rcat = np.genfromtxt(starsfile, usecols=(1, 2))
rrdcat = wcs.all_pix2world(
(rcat / wcs.pscale) + [wcs.naxis1 / 2, wcs.naxis2 / 2], 1).tolist()
xy = refwcs.all_world2pix(rrdcat, 1).tolist()
with open(catfile, 'w') as catout:
for i, rd in enumerate(rrdcat):
catout.write('%d %.8f %.8f %.3f %.3f %d\n' %
(i, rd[0], rd[1], xy[i][0], xy[i][1], i))
def makeSAin(visit, imgs, refwcs, refcat_sa):
sa_file = '%s_superalign.in' % visit
print('Creating %s' % sa_file)
sa_in = open(sa_file, 'w')
sa_in.write('%s 1\n' % str(len(imgs) + 1))
sa_in.write('%s 0.000 0.000 0.000\n' % refcat_sa)
for drz in imgs:
f = os.path.basename(drz)
wcs = HSTWCS(fits.open(drz))
sky = wcs.all_pix2world([[wcs.naxis1 / 2, wcs.naxis2 / 2]], 1)
arc = (refwcs.all_world2pix(sky, 1) -
[refwcs.naxis1 / 2, refwcs.naxis2 / 2]) * refwcs.pscale
rot = round(refwcs.orientat - wcs.orientat, 3)
sa_in.write('%s %s %s %s\n' %
(f.replace('.fits', '_sa.cat'), round(
arc[0][0], 3), round(arc[0][1], 3), rot))
sa_in.close()
def makeCat(self, imgfile, instdet, weightfile=None, extref=False):
"""Makes a catalog of objects to be used for input to superalign and creates a DS9 region file of objects"""
imgfile_cat = '%s_all.cat' % imgfile.replace('.fits', '')
imgfile_reg = '%s_all.reg' % imgfile.replace('.fits', '')
o_radec = []
ext = 0
objectlist = self.findSources('%s[%s]' % (imgfile, ext),
imgfile_cat,
instdet,
weightfile,
extref=extref)
cleanobjectlist = self.removeCloseSources(objectlist)
print('Found %s sources' % len(cleanobjectlist))
wcs = HSTWCS(str(imgfile))
for obj in cleanobjectlist:
sky = wcs.all_pix2world(np.array([[obj.x, obj.y]]), 1)
o_radec.append([obj.ra[0], obj.dec[0]])
obj.ra = sky[0][0]
obj.dec = sky[0][1]
# Write out a ds9 region file of object selected for alignment
regout = open(imgfile_reg, 'w')
regout.write(
'global color=green font="helvetica 8 normal" edit=1 move=1 delete=1 include=1 fixed=0\nfk5\n'
)
for i, rd in enumerate(o_radec):
oid = i + 1
regout.write('circle(%s,%s,%s") # color=%s text={%s}\n' %
(rd[0], rd[1], 0.5, 'red', oid))
regout.close()
# Now we need to write out the catalog in the reference image coords in arcseconds with respect to center of the image
catout = open(imgfile_cat, 'w')
for i, obj in enumerate(cleanobjectlist):
oid = i + 1
catout.write('%i %.9f %.9f %.4f %.4f %.4f\n' %
(oid, obj.ra, obj.dec, obj.x, obj.y, obj.mag))
catout.close()
return
def make_grismcat(self,
data_name,
data_angle,
grism_cat,
mdrizzle_image,
odd_signs=None):
"""
Input:
data_name - filename of the position data
data_angle - filename of the displaced positions
grism_cat - refernece to the axecat object
mdrizzle_image - name of the multidrizzled image
Return:
-
Description:
The method creates a new input object list. The positional
information on objects in a multidrizzled image are projected
back into the coordinate system of one nput image.
A selection is done on the basis of the projected coordinates,
and the selected objects are stored to a new IOL file
"""
import os
import os.path
import math
from . import awtran
print('')
print(' >>>> Working on Input Object List: ', self.iol_name, '>>>>')
print('')
#------------------------------------------------------------------------
# newer faster version from aXe-1.7 on:
#
if (self.useMdriz):
print("Using multidrizzle coeffs for coordinate transformation\n")
dir_pts = awtran.b(mdrizzle_image + "[SCI]",
self.header_name,
List=data_name)
ang_pts = awtran.b(mdrizzle_image + "[SCI]",
self.header_name,
List=data_angle)
else:
#use HSTWCS instead for the astrodrizzle image
#read in the data_name file
# awtran gives back this format: all_out.append("%10.3f %10.3f %10.3f %10.3f" % (xin,yin,xout,yout))
hstimage = HSTWCS(mdrizzle_image, ext=1)
datanamefile = open(data_name, 'r')
datapoints = datanamefile.readlines()
data = [list(map(float, line.split())) for line in datapoints]
skypoints = hstimage.all_pix2world(
data,
1) #trans points are now in ra and dec from mdrizzle_image
#now translate to new image pixel points
newhstimage = HSTWCS(self.header_name)
trans_pts = newhstimage.all_world2pix(skypoints[:, 0],
skypoints[:, 1], 1)
#pix2sky returns (2,len) array of points, reshape for what awtran returned
dir_pts = list()
for i in range(0, len(trans_pts[0])):
dir_pts.append("%10.8g %10.8g %10.8g %10.8g" %
(trans_pts[0][i], trans_pts[1][i],
skypoints[i, 0], skypoints[i, 1]))
#now the same for the ang file points
angfile = open(data_angle, 'r')
angpoints = angfile.readlines()
data = [list(map(float, line.split())) for line in datapoints]
ang_pts = list()
for i in range(0, len(trans_pts[0])):
ang_pts.append(
"%10.8g %10.8g %10.8g %10.8g" %
(data[i][0], data[i][1], trans_pts[0][i], trans_pts[1][i]))
# delete the first element,
# which contains a description only
# but only for the multidrizzle version
#-------------------------------------------------------------------------
if self.useMdriz:
del (dir_pts[0])
del (ang_pts[0])
# start the reverse index;
# iterate over all objects
r_index = len(dir_pts) - 1
for index in range(grism_cat.nrows):
# extract the projected object positions
x_ori = float(dir_pts[r_index].split()[0])
y_ori = float(dir_pts[r_index].split()[1])
# check whether the object position is
# range to be stored
if x_ori >= self.dim_info[0] and x_ori <= self.dim_info[1] and \
y_ori >= self.dim_info[2] and y_ori <= self.dim_info[3]:
# extract the displaced projected position
x_ang = float(ang_pts[r_index].split()[0])
y_ang = float(ang_pts[r_index].split()[1])
# compute the new object angle
dx = x_ang - x_ori
dy = y_ang - y_ori
angle = math.atan2(dy, dx) / math.pi * 180.0
# Note: this correction is only necessary
# as long as there are two different
# flavors in pydrizzle and iraf.drizzle
if (self.useMdriz):
if odd_signs != None:
if odd_signs[0]:
x_ori -= 0.5
if odd_signs[1]:
y_ori -= 0.5
# fill in the new position and angle
grism_cat['X_IMAGE'][r_index] = x_ori
grism_cat['Y_IMAGE'][r_index] = y_ori
grism_cat['THETA_IMAGE'][r_index] = angle
# delete outside entries
else:
grism_cat.delete(r_index)
# decrease the reverse index
r_index -= 1
# save the new IOL
grism_cat.writeto(self.iol_name)
print('')
print(' >>>> Catalog: ', self.iol_name, 'written with ',
grism_cat.nrows, 'entries.>>>>')
print('')
