# (e.g. ra,dec = 230,-30 will return a valid pixel even though it is exactly
# 180 degrees away from actual valid coordinates of ra,dec = 50,+30
from readcmd import ReadCmd
spec = """# Overlap coordinates in a file with a FITS image
in = ??? # Input file
col = 1,2 # Column numbers to read for RA,DEC
fits = ??? # Input FITS image(s)
out = ??? # Output file(s) of sources inside(,outside) image(s)
logic = and # 'and' = in all image(s), 'or' = in any image(s)"""
# null = NaN # Pixels with this value are considered outside"""
arg = ReadCmd(spec)
infile = arg.getstr("in",exist=True)
col = arg.getlistint("col",length=2,min=1)
fits = arg.getliststr("fits",exist=True)
out = arg.getliststr("out",length=[1,2],exist=False)
logic = arg.getstr("logic",option=['and','or'])
#null = arg.getstr("null")
import pyfits,pywcs
from numpy import loadtxt,transpose,ones,zeros,array,where,isnan
# read in ra/dec only
data = loadtxt(infile,usecols=[col[0]-1,col[1]-1])
mask = zeros(data.shape[0])
for f in fits:
header = pyfits.getheader(f)
fitsdata = pyfits.getdata(f)
wcs = pywcs.WCS(header)
maxy = max(data[2])
for i in reversed(range(len(data[0]))):
if data[2][i] <= 0:
del(data[0][i])
del(data[1][i])
del(data[2][i])
del[data[3][i]]
else:
data[2][i] = data[2][i]/maxy
data[3][i] = data[3][i]/(maxy*math.sqrt(data[1][i])) #std.dev. mean
return data
### Start Program ###
arg = ReadCmd(spec)
image = arg.getliststr('in',exist=True)
bin = arg.getlistfloat('bin',length=3)
unit = arg.getstr('unit',option=['nbin','step'])
offset = arg.getlistfloat('offset',length=2)
outplot = arg.getstr('out')
junk = arg.getlistfloat('range',length=2)
xmin = junk[0]
xmax = junk[1]
step = arg.getstr('step',option=['b','p'])
if 'b' in step: # do binning
outdata = []
from pyraf import iraf
for i in image:
#!/usr/bin/env python
from readcmd import ReadCmd
spec = """# Copy header keywords from input file to output file
in = ??? # Input file (from file)
inext = 1 # Extension name/number of input file
key = ??? # Header key(s) to copy (all for all keywords)
out = ??? # Output file (to file, must exist)
outext = 1 # Output extension(s) to modify"""
arg = ReadCmd(spec)
inFile = arg.getstr('in',exist=True)
inext = arg.getstr('inext')
junk = arg.getliststr('key')
outFile = arg.getstr('out',exist=True)
outext = arg.getliststr('outext')
hist = arg.getkeys(comment='CPHEAD.PY:',format=72,time=True).strip().split('\n')
import nlcastro
import pyfits
keylist = [a.lower() for a in junk]
img = pyfits.open(inFile)
idx = nlcastro.findExt(img,inext)
head1 = img[idx].header
img.close()
junk = [a.lower() for a in head1.keys()]
#!/usr/bin/env python
"""Simple script to do subimages of a larger FITS"""
from readcmd import ReadCmd
import sys
spec = """in = ??? # Input filename
region = ??? # Region to clip, as xmin:xmax,ymin:ymax
out = ??? # Output filename
wcs = True # Compute new WCS for output image?"""
arg = ReadCmd(spec,head=__doc__)
inFile = arg.getstr('in',exist=True)
region = arg.getliststr('region',length=2)
outFile = arg.getstr('out',exist=False)
wcsFlag = arg.getbool('wcs')
keys = arg.getkeys(comment='IMSUB.PY:',format=80,time=True).strip().split('\n')
import pyfits,pywcs
from numpy import where,nan
# open FITS image and read header
if inFile == '-':
fp = sys.stdin
else:
fp = pyfits.open(inFile)
header = fp[0].header
# read and interpret region keyword
tmp1 = region[0].split(':')
#!/usr/bin/env python
from readcmd import ReadCmd
spec = """# compute statistics on an image or subregion of an image
in = ??? # Input image
ext = 1 # Extension number to read from in file
reg = None # subregion given as xmin:xmax,ymin:ymax (pixels)"""
arg = ReadCmd(spec)
infile = arg.getstr("in",exist=True,type='file')
reg = arg.getliststr('reg',length=[0,2])
ext = arg.getstr("ext")
import nlclib
import pyfits
from numpy import isfinite,where,nanmin,nanmax,median,average,std
ext = nlclib.findExt(infile,ext)
reg = nlclib.readRegion(reg)
header = pyfits.getheader(infile,ext=ext)
data = pyfits.getdata(infile,ext=ext)
if reg is None:
minval = nanmin(data)
maxval = nanmax(data)
mask = where(isfinite(data))
medval = median(data[mask])
avgval = average(data[mask])
stdval = std(data[mask],ddof=1)
#!/usr/bin/env python
"""Parse extension(s) from one or more files and combine into a cube"""
from readcmd import ReadCmd
import sys
spec = """in = ??? # Input file(s) to process
ext = ??? # Extension(s) to extract (start at 1)
out = ??? # Output filename"""
arg = ReadCmd(spec,head=__doc__)
infiles = arg.getliststr('in',exist=True)
ext = arg.getliststr('ext')
outfile = arg.getstr('out',exist=False)
hist = arg.getkeys(comment='IMEXTRACT.PY:',format=72,time=True).strip().split('\n')
next = len(ext)
nfiles = len(infiles)
import pyfits
import nlcastro
from numpy import zeros
# do first file, need outside loop in case there is only one file in total
idx = nlcastro.findExt(infiles[0],ext)
header = [pyfits.getheader(infiles[0],idx[i]) for i in xrange(next)]
# compile list with names of extensions. Read from first file
img = pyfits.open(infiles[0])
extname = [img[idx[i]].name for i in xrange(next)]
img.close()
ycol = 2 # Y column number(s)
dycol = None # Y error column number(s)
ylabel = None # Y-axis label"""
def error(text):
"""Write out error message and quit"""
sys.stderr.write("### Fatal Error! %s\n" %text)
sys.exit()
arg = ReadCmd(spec)
infile = arg.getstr('in',exist=True)
xcol = arg.getlistint('xcol',min=1)
ycol = arg.getlistint('ycol',min=1)
dxcol = arg.getlistint('dxcol',min=1)
dycol = arg.getlistint('dycol',min=1)
style = arg.getliststr('style')
color = arg.getliststr('color')
limits = arg.getlistfloat('limits',length=4)
out = arg.getstr('out')
xlab = arg.getstr('xlabel')
ylab = arg.getstr('ylabel')
mytext = arg.getliststr('text')
mytitle = arg.getstr('title')
mywidth = arg.getliststr('width')
legloc = arg.getlistfloat('legend',length=2)
nx = len(xcol)
ny = len(ycol)
ndx = len(dxcol)
ndy = len(dycol)
nstyle = len(style)
#!/usr/bin/env python
from readcmd import ReadCmd
spec = """# Edit, add, or delete one or more FITS header keywords and values
in = ??? # Input FITS file(s)
ext = 1 # FITS extension(s) to edit (name or number)
key = ??? # FITS keyword(s) to edit (or add) prepend '-' to delete
value = ??? # values for each keyword (or 1 for all keywords)
out = ??? # Output FITS file"""
### Main Program ###
arg = ReadCmd(spec)
infile = arg.getliststr('in',exist=True)
ext = arg.getliststr('ext')
junk = arg.getliststr('key')
value = arg.getliststr('value',length=[1,len(junk)])
outfile = arg.getliststr('out',exist=False,length=len(infile))
histroot = arg.getkeys(comment='HEDIT.PY:',format=72,time=True).strip().split('\n')
keylist = [a.lower() for a in junk]
if len(value) == 1:
value = len(junk)*value
import pyfits
import nlcastro
for inname,outname in zip(infile,outfile):
print "%s -> %s" %(inname,outname)
img = pyfits.open(inname)
extnames = [nlcastro.findExt(inname,e) for e in ext]
# avg will compute unweighted average, and produce uncertainty map from normal
# propagation of error.
# wgtavg will compute weighted average
from readcmd import ReadCmd
import nlclib
spec = """# Combine FITS images into one
in = ??? # Input images
err = None # Optional error images for input images
oper = avg # Can compute sum, avg, or wgtavg (weighted average)
out = ??? # Output image
outerr = None # Optional output error image (coverage map if no err)"""
arg = ReadCmd(spec)
inFiles = arg.getliststr('in',exist=True)
errFiles = arg.getliststr('err',exist=True,length=[1,len(inFiles)])
oper = arg.getstr('oper',option=['avg','sum','wgtavg'])
outFile = arg.getstr('out',exist=False)
outErr = arg.getstr('outerr',exist=False)
nimages = len(inFiles)
errFlag = False
if len(errFiles) > 0:
errFlag = True
if len(errFiles) == 1:
errFiles = nimages*errFiles
import pyfits
from numpy import zeros,isfinite,where,sqrt
