def coords_in_image(xc,yc,header,coordsys='celestial'):
"""
Determine whether the coordinates are within the boundaries of the image
"""
try:
wcs = pywcs.WCS(header)
except: # if the header isn't WCS compatible, we don't want it
return False
try:
if coordsys=='celestial' and wcs.wcs.lngtyp=='GLON':
xc,yc = coords.Position((xc,yc),system=coordsys).galactic()
elif coordsys=='galactic' and wcs.wcs.lngtyp=='RA':
xc,yc = coords.Position((xc,yc),system=coordsys).j2000()
xp,yp = wcs.wcs_sky2pix(xc,yc,0)
except:
return False
if xp > wcs.naxis1 or xp < 0:
return False
elif yp > wcs.naxis2 or yp < 0:
return False
else:
return True
def posang(l1, b1, l2, b2, system='galactic', **kwargs):
"""
Return the position angle between two points assuming a rectilinear
coordinate system (I think; at the very least I am making no corrections
for wcs).
INPUT:
longitude1, latitude1, longitude2, latitude2
Defaults to GALACTIC coordinates. **kwargs are passed to coords.Position
"""
if not coordsOK:
raise ImportError("posang requires coords.")
pos1 = coords.Position([l1, b1], system=system, **kwargs)
ra1, dec1 = pos1.j2000()
pos2 = coords.Position([l2, b2], system=system, **kwargs)
ra2, dec2 = pos2.j2000()
radiff = (ra1 - ra2) / 180. * pi
angle = arctan2(
sin(radiff),
cos(dec1 * pi / 180.) * tan(dec2 * pi / 180.) -
sin(dec1 * pi / 180.) * cos(radiff)) / pi * 180
return angle
def cenfile_overlays(cenfile):
cen = readcol(cenfile, comment="#", asStruct=True)
for name, ra, dec, obra, obdec in zip(cen.filename, cen.radeg, cen.decdeg,
cen.obj_ra, cen.obj_dec):
print name
pos = coords.Position((ra, dec))
xc, yc = pos.galactic()
objpos = coords.Position((obra, obdec))
xtr, ytr = objpos.galactic()
make_overlay(name.tolist(), xc, yc, xtr, ytr)
pylab.figure(0)
pylab.clf()
def position_region(reg):
"""
small wrapper to get a Position object using the correct coordinate system
reg must by a pyregion Shape instance
"""
x, y = reg.coord_list[:2]
posn = coords.Position([x, y], system=coords_format(reg.coord_format))
return posn
def list_targets(sdfitsfile, doprint=True):
"""
List the targets, their location on the sky...
"""
bintable = _get_bintable(sdfitsfile)
# Things to include:
# Scan Source Vel Proc Seqn RestF nIF nInt nFd Az El
# 1 G33.13-0.09 87.4 Nod 1 14.488 4 15 2 209.7 47.9
strings = [
"\n%18s %10s %10s %26s%8s %9s %9s %9s" %
("Object Name", "RA", "DEC", "%12s%14s" %
("RA", "DEC"), "N(ptgs)", "Exp.Time", "requested", "n(ints)")
]
for objectname in uniq(bintable.data['OBJECT']):
whobject = bintable.data['OBJECT'] == objectname
RA, DEC = bintable.data['TRGTLONG'][whobject], bintable.data[
'TRGTLAT'][whobject]
RADEC = zip(RA, DEC)
midRA, midDEC = np.median(RA), np.median(DEC)
npointings = len(set(RADEC))
if coords is not None:
sexagesimal = coords.Position((midRA, midDEC)).hmsdms()
else:
sexagesimal = ""
firstsampler = bintable.data['SAMPLER'][whobject][0]
whfirstsampler = bintable.data['SAMPLER'] == firstsampler
exptime = bintable.data['EXPOSURE'][whobject * whfirstsampler].sum()
duration = bintable.data['DURATION'][whobject * whfirstsampler].sum()
n_ints = count_integrations(bintable, objectname)
strings.append("%18s %10f %10f %26s%8i %9g %9g %9i" %
(objectname, midRA, midDEC, sexagesimal, npointings,
exptime, duration, n_ints))
if doprint:
print "\n".join(strings)
return strings
def cutout(filename,
xc,
yc,
xw=25,
yw=25,
units='pixels',
outfile=None,
clobber=True,
coordsys='celestial',
verbose=False):
"""
Inputs:
file - .fits filename or pyfits HDUList (must be 2D)
xc,yc - x and y coordinates in the fits files' coordinate system (CTYPE)
xw,yw - x and y width (pixels or wcs)
units - specify units to use: either pixels or wcs
outfile - optional output file
"""
if isinstance(filename, str):
file = pyfits.open(filename)
opened = True
elif (isinstance(filename, pyfits.HDUList)
or isinstance(filename, pyfits.hdu.hdulist.HDUList)):
file = filename
opened = False
else:
raise Exception(
"cutout: Input file is wrong type (string or HDUList are acceptable)."
)
head = file[0].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
if (cd1 is None or cd2 is None) and units == 'wcs':
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
if coordsys == 'celestial' and wcs.wcs.lngtyp == 'GLON':
xc, yc = coords.Position((xc, yc), system=coordsys).galactic()
elif coordsys == 'galactic' and wcs.wcs.lngtyp == 'RA':
xc, yc = coords.Position((xc, yc), system=coordsys).j2000()
if units == 'pixels':
xx, yy = xc, yc
xmin, xmax = numpy.max([0,
xx - xw]), numpy.min([head['NAXIS1'], xx + xw])
ymin, ymax = numpy.max([0,
yy - yw]), numpy.min([head['NAXIS2'], yy + yw])
elif units == 'wcs':
xx, yy = wcs.wcs_sky2pix(xc, yc, 0)
xmin, xmax = numpy.max([0, xx - xw / numpy.abs(cd1)]), numpy.min(
[head['NAXIS1'], xx + xw / numpy.abs(cd1)])
ymin, ymax = numpy.max([0, yy - yw / numpy.abs(cd2)]), numpy.min(
[head['NAXIS2'], yy + yw / numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." %
(xmax, ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." %
(xmin, ymin))
if head.get('CRPIX1'):
head['CRPIX1'] -= xmin
head['CRPIX2'] -= ymin
head['NAXIS1'] = int(xmax - xmin)
head['NAXIS2'] = int(ymax - ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." %
(head.get('NAXIS1'), head.get('NAXIS2')))
img = file[0].data[ymin:ymax, xmin:xmax]
newfile = pyfits.PrimaryHDU(data=img, header=head)
if verbose:
print "Cut image %s with dims %s to %s. xrange: %f:%f, yrange: %f:%f" % (
filename, file[0].data.shape, img.shape, xmin, xmax, ymin, ymax)
head['comment'] = "Original: %s" % (file.filename())
head['comment'] = "Cropped: %d %d - %d %d" % (xmin, xmax, ymin, ymax)
if isinstance(outfile, str):
newfile.writeto(outfile, clobber=clobber)
if opened:
file.close()
return newfile
def cutoutimg(filename,
xc,
yc,
xw=25,
yw=25,
units='pixels',
outfile=None,
overwrite=True,
useMontage=False,
coordsys='celestial',
verbose=False,
centerunits=None):
"""
Simple cutout function. Should be replaced by a function in astropy
eventually - keep an eye on
https://github.com/astropy/astropy/pull/3823
Parameters
----------
file : str or fits.HDUList
.fits filename or pyfits HDUList (must be 2D)
xc,yc : float,float
x and y coordinates in the fits files' coordinate system (CTYPE)
or in pixel units
xw,yw : float
x and y half-width (pixels or wcs)
(the output file will be size xw*2 * yw*2)
units : str
specify units to use: either pixels or wcs
outfile : str
optional output file
centerunits : None or str
If None, is the same as 'units'. Can be 'wcs' or 'pixels'
"""
if centerunits is None:
centerunits = units
if units not in ('wcs', 'pixels'):
raise ValueError("units must be wcs or pixels")
if isinstance(filename, str):
file = pyfits.open(filename)
opened = True
elif isinstance(filename, pyfits.HDUList):
file = filename
opened = False
else:
raise Exception(
"cutout: Input file is wrong type (string or HDUList are acceptable)."
)
head = file[0].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
if cd1 is None or cd2 is None:
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
if coordsys == 'celestial' and wcs.wcs.lngtyp == 'GLON':
xc, yc = coords.Position((xc, yc), system=coordsys).galactic()
elif coordsys == 'galactic' and wcs.wcs.lngtyp == 'RA':
xc, yc = coords.Position((xc, yc), system=coordsys).j2000()
if useMontage and CanUseMontage:
head['CRVAL1'] = xc
head['CRVAL2'] = yc
if units == 'pixels':
head['CRPIX1'] = xw
head['CRPIX2'] = yw
head['NAXIS1'] = int(xw * 2)
head['NAXIS2'] = int(yw * 2)
elif units == 'wcs':
cdelt = numpy.sqrt(cd1**2 + cd2**2)
head['CRPIX1'] = xw / cdelt
head['CRPIX2'] = yw / cdelt
head['NAXIS1'] = int(xw * 2 / cdelt)
head['NAXIS2'] = int(yw * 2 / cdelt)
head.toTxtFile('temp_montage.hdr', overwrite=True)
newfile = montage.wrappers.reproject_hdu(file[0],
header='temp_montage.hdr',
exact_size=True)
os.remove('temp_montage.hdr')
else:
if centerunits == 'wcs':
xx, yy = wcs.wcs_world2pix(xc, yc, 0)
else:
xx, yy = xc, yc
if units == 'pixels':
xmin, xmax = numpy.max([0, xx - xw
]), numpy.min([head['NAXIS1'], xx + xw])
ymin, ymax = numpy.max([0, yy - yw
]), numpy.min([head['NAXIS2'], yy + yw])
elif units == 'wcs':
xmin, xmax = numpy.max([0, xx - xw / numpy.abs(cd1)]), numpy.min(
[head['NAXIS1'], xx + xw / numpy.abs(cd1)])
ymin, ymax = numpy.max([0, yy - yw / numpy.abs(cd2)]), numpy.min(
[head['NAXIS2'], yy + yw / numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." %
(xmax, ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." %
(xmin, ymin))
head['CRPIX1'] -= xmin
head['CRPIX2'] -= ymin
head['NAXIS1'] = int(xmax - xmin)
head['NAXIS2'] = int(ymax - ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." %
(head.get('NAXIS1'), head.get('NAXIS2')))
img = file[0].data[int(ymin):int(ymax), int(xmin):int(xmax)]
newfile = pyfits.PrimaryHDU(data=img, header=head)
if verbose:
print(
"Cut image %s with dims %s to %s. xrange: %f:%f, yrange: %f:%f"
% (filename, file[0].data.shape, img.shape, xmin, xmax, ymin,
ymax))
if isinstance(outfile, str):
newfile.writeto(outfile, overwrite=overwrite)
if opened:
file.close()
return newfile
def cutout(filename, xc, yc, xw=25, yw=25, units='pixels', outfile=None,
clobber=True, useMontage=False, coordsys='celestial', verbose=False, extension=0):
"""
Inputs:
file - .fits filename or pyfits HDUList (must be 2D)
xc,yc - x and y coordinates in the fits files' coordinate system (CTYPE)
xw,yw - x and y width (pixels or wcs)
units - specify units to use: either pixels or wcs
outfile - optional output file
KBS:
For wcs mode use xy,xc,xw,xy (width is actually "radius") in degrees, e.g.,
>>> import cutout
>>> cutout.cutout('image.fits',189.24,62.23,xw=0.00139,yw=0.00139,units='wcs',outfile='testfile.fits')
gives a cutout of 10x10 arcsec 2*5/3600x2*5/3600)
140227 Added extension keyword for multi-extension fits Kasper B. Schmidt (UCSB)
"""
if isinstance(filename,str):
file = pyfits.open(filename)
opened=True
elif isinstance(filename,pyfits.HDUList):
file = filename
opened=False
else:
raise Exception("cutout: Input file is wrong type (string or HDUList are acceptable).")
head = file[extension].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
# KBS cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
# KBS cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
# KBS --- use CD1_1 and CD2_2 over CDELT1 and CDELT2 ---
cd1 = head.get('CD1_1') if head.get('CD1_1') else head.get('CDELT1')
cd2 = head.get('CD2_2') if head.get('CD2_2') else head.get('CDELT2')
if cd1 is None or cd2 is None:
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
if coordsys=='celestial' and wcs.wcs.lngtyp=='GLON':
xc,yc = coords.Position((xc,yc),system=coordsys).galactic()
elif coordsys=='galactic' and wcs.wcs.lngtyp=='RA':
xc,yc = coords.Position((xc,yc),system=coordsys).j2000()
if useMontage and CanUseMontage:
head['CRVAL1'] = xc
head['CRVAL2'] = yc
if units == 'pixels':
head['CRPIX1'] = xw
head['CRPIX2'] = yw
head['NAXIS1'] = int(xw*2)
head['NAXIS2'] = int(yw*2)
elif units == 'wcs':
cdelt = numpy.sqrt(cd1**2+cd2**2)
head['CRPIX1'] = xw / cdelt
head['CRPIX2'] = yw / cdelt
head['NAXIS1'] = int(xw*2 / cdelt)
head['NAXIS2'] = int(yw*2 / cdelt)
head.toTxtFile('temp_montage.hdr',clobber=True)
newfile = montage.wrappers.reproject_hdu(file[extension],header='temp_montage.hdr',exact_size=True)
os.remove('temp_montage.hdr')
else:
#KBS160818 xx,yy = wcs.wcs_sky2pix(xc,yc,0)
xx,yy = wcs.wcs_world2pix(xc,yc,0)
if units=='pixels':
xmin,xmax = numpy.max([0,xx-xw]),numpy.min([head['NAXIS1'],xx+xw])
ymin,ymax = numpy.max([0,yy-yw]),numpy.min([head['NAXIS2'],yy+yw])
elif units=='wcs':
xmin,xmax = numpy.max([0,xx-xw/numpy.abs(cd1)]),numpy.min([head['NAXIS1'],xx+xw/numpy.abs(cd1)])
ymin,ymax = numpy.max([0,yy-yw/numpy.abs(cd2)]),numpy.min([head['NAXIS2'],yy+yw/numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." % (xmax,ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." % (xmin,ymin))
head['CRPIX1']-=xmin
head['CRPIX2']-=ymin
head['NAXIS1']=int(xmax-xmin)
head['NAXIS2']=int(ymax-ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." % (head.get('NAXIS1'),head.get('NAXIS2')))
img = file[extension].data[ymin:ymax,xmin:xmax]
newfile = pyfits.PrimaryHDU(data=img,header=head)
if verbose: print "Cut image %s with dims %s to %s. xrange: %f:%f, yrange: %f:%f" % (filename, file[extension].data.shape,img.shape,xmin,xmax,ymin,ymax)
if isinstance(outfile,str):
newfile.writeto(outfile,clobber=clobber)
if opened:
file.close()
return newfile
def cempno_control_starlist():
names = np.array([
'HE0132-2429', 'HE1347-1025', 'HE1356-0622', 'HE1424-0241',
'BS16467-062', 'G64-12', 'CS29518-051', 'CS29502-042', 'CS22953-003',
'CS22896-154', 'CS22183-031', 'CS29491-069', 'CS29497-004',
'CS31082-001', 'HE0430-4901', 'HE0432-0923', 'HE1127-1143',
'HE1219-0312', 'HE2224+0143', 'HE2327-5642'
])
d = load_frebel_table()
idx = np.array([], dtype=int)
for ii in range(len(names)):
foo = np.where(d.name == names[ii])[0]
if len(foo) == 0:
print 'No star %s' % names[ii]
idx = np.append(idx, foo)
sdx = d.ra[idx].argsort()
idx = idx[sdx]
# Trim out what we need
ra = d.ra[idx]
dec = d.dec[idx]
V = d.V[idx]
B = d.B[idx]
R = d.R[idx]
FeH = d.FeH[idx]
CFe = d.CFe[idx]
BaFe = d.BaFe[idx]
simbad = d.simbad[idx]
# Fix the RA and Dec for CEMP-s and CEMP-no stars
ra, dec = getCoordsFromSimbad(d.simbad[idx])
# Make a LaTeX table of the targets we want to observe
_out = open('control_starlist.tel', 'w')
_out2 = open('control_simbadnames.tel', 'w')
for ii in range(len(names)):
hmsdms = coords.Position((ra[ii], dec[ii])).hmsdms().split()
ra_hex = hmsdms[0].replace(':', ' ')
dec_hex = hmsdms[1].replace(':', ' ')
print ii, names[ii], simbad[ii]
_out.write('%-16s %12s %12s 2000.0 vmag=%5.2f\n' %
(names[ii], ra_hex, dec_hex, V[ii]))
_out2.write('%s\n' % simbad[ii])
_out.close()
_out2.close()
# Now lets loop through and plot when these targets are observable.
py.clf()
py.subplots_adjust(left=0.05, right=0.95, top=0.95)
# Calculate the hour angle at which the object goes above airmass = 2.
# Relevant equations are:
# airmass = 1 / cos(z)
# hour angle = sidereal time - RA
# cos z = sin L sin Dec + cos L cos Dec cos HA
# We will solve for HA.
iraf.noao()
obs = iraf.noao.observatory
obs(command="set", obsid="keck")
airmassLim = 2.0
latRad = np.radians(obs.latitude)
decRad = np.radians(dec)
top = (1.0 / airmassLim) - np.sin(latRad) * np.sin(decRad)
bot = np.cos(latRad) * np.cos(decRad)
hangle = np.degrees(np.arccos(top / bot))
madeLegend = False
for ii in range(len(names)):
minLST = (ra[ii] - hangle[ii]) / 15.
maxLST = (ra[ii] + hangle[ii]) / 15.
hix = 360.0 / 15.0
if (minLST >= 0) and (maxLST < hix):
if madeLegend == True:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black')
else:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black',
label='CEMP-no stars')
madeLegend = True
if minLST < 0:
py.plot([0, maxLST], [ii + 1, ii + 1], linewidth=5, color='black')
py.plot([minLST + hix, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
if maxLST > hix:
py.plot([minLST, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.plot([0, maxLST - hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.xlim(0, hix)
# Get the LST ranges for March, May, July
months = np.array([3, 5, 7])
days = np.array([1, 1, 1])
years = np.array([2012, 2012, 2012])
colors = ['red', 'green', 'blue']
labels = ['Mar 1, 2012 (HST)', 'May 1, 2012 (HST)', 'Jul 1, 2012 (HST)']
rng = py.axis()
for ii in range(len(months)):
twi = get_twilight_lst(years[ii], months[ii], days[ii])
minLST = twi[0] * 15.0
maxLST = twi[1] * 15.0
ypos = rng[3] + 2 * (len(months) - ii)
if minLST < 0:
minLST += 360.0
if maxLST > 360:
maxLST -= 360.0
x1 = np.array([minLST, maxLST]) / 15.0
x2 = None
y = np.array([ypos, ypos])
if minLST > 0 and maxLST < 360 and minLST > maxLST:
x1 = np.array([0, maxLST]) / 15.0
x2 = np.array([minLST, 360]) / 15.0
py.plot(x1, y, linewidth=10, color=colors[ii], label=labels[ii])
if x2 != None:
py.plot(x2, y, linewidth=10, color=colors[ii])
py.ylim(0, rng[3] + 7 * len(months))
py.legend(loc='upper left')
# py.xlim(0, 360)
py.xlim(0, 24)
py.xlabel('LST (hours)')
py.gca().yaxis.set_visible(False)
py.savefig('obs_ra_v_control_new.png')
import numpy as np
import coords
# Read in initial coordinates as J2000 coordinates
data_j2000 = np.loadtxt('../initial_coords.txt')
f = {}
f['galactic'] = open('coords_galactic.txt', 'wb')
f['b1950'] = open('coords_b1950.txt', 'wb')
f['ecliptic'] = open('coords_ecliptic.txt', 'wb')
for i in range(len(data_j2000)):
ra_j2000, dec_j2000 = data_j2000[i, 0], data_j2000[i, 1]
j2000 = coords.Position((ra_j2000, dec_j2000))
# Convert to Galactic coordinates
l, b = j2000.galactic()
f['galactic'].write("%20.15f %20.15f\n" % (l, b))
# Convert to B1950
ra_b1950, dec_b1950 = j2000.b1950()
f['b1950'].write("%20.15f %20.15f\n" % (ra_b1950, dec_b1950))
# Convert to ecliptic
elon, elat = j2000.ecliptic()
f['ecliptic'].write("%20.15f %20.15f\n" % (elon, elat))
for system in f:
f[system].close()
def cemp_no_properties():
d = load_frebel_table()
# Lets identify some sub-samples. Criteria from Beers 2008.
emp = np.where((d.CFe < 0.9) & (d.ra != -999) & (d.V > 0) & (d.FeH != -999)
& (d.CFe != -999) & (d.BaFe != -999))[0]
empr = np.where((d.CFe < 0.9) & (d.ra != -999) & (d.V > 0)
& (d.FeH != -999) & (d.CFe != -999) & (d.BaFe != -999)
& (d.BaEu < 0))[0]
cemp = np.where(d.CFe >= 0.9)[0]
cempr = np.where((d.CFe >= 0.9) & (d.EuFe > 1))[0]
cemps = np.where((d.CFe >= 0.9) & (d.BaFe > 1) & (d.EuFe > -999)
& (d.BaEu > 0.5))[0]
cempno = np.where((d.CFe >= 0.9) & (d.BaFe > -999) & (d.BaFe < 0))[0]
# Plot up the histogram of Iron abundances:
bins_FeH = np.arange(-7, 1, 0.5)
py.clf()
py.hist(d.FeH,
histtype='step',
bins=bins_FeH,
label='%d stars' % len(d.name))
py.hist(d.FeH[cemp],
histtype='step',
bins=bins_FeH,
label='%d CEMP' % len(cemp))
py.hist(d.FeH[cemps],
histtype='step',
bins=bins_FeH,
label='%d CEMP-s' % len(cemps))
py.hist(d.FeH[cempno],
histtype='step',
bins=bins_FeH,
label='%d CEMP-no' % len(cempno))
py.xlabel('[Fe/H]')
py.ylabel('Number')
py.legend(loc='upper left')
py.ylim(0, 100)
py.savefig(dir + 'hist_FeH.png')
# Fix the ones with no V-band magnitudes
bad_s = np.where(d.V[cemps] < 0)[0]
bad_no = np.where(d.V[cempno] < 0)[0]
# Bad CEMP-s stars
print ''
print '## Bad CEMP-s'
for ii in bad_s:
print '%20s %10.5f %10.5f %5.2f' % \
(d.name[cemps[ii]], d.ra[cemps[ii]],
d.dec[cemps[ii]], d.V[cemps[ii]])
print '## Bad CEMP-no'
for ii in bad_no:
print '%20s %10.5f %10.5f %5.2f' % \
(d.name[cempno[ii]], d.ra[cempno[ii]],
d.dec[cempno[ii]], d.V[cempno[ii]])
# Get rid of the stars without info.
cemps = np.delete(cemps, bad_s)
cempno = np.delete(cempno, bad_no)
# Fix the RA and Dec for CEMP-s and CEMP-no stars
d.ra[cemps], d.dec[cemps] = getCoordsFromSimbad(d.simbad[cemps])
d.ra[cempno], d.dec[cempno] = getCoordsFromSimbad(d.simbad[cempno])
py.clf()
py.plot(d.V[cemps], d.FeH[cemps], 'rs', label='CEMP-s')
py.plot(d.V[cempno], d.FeH[cempno], 'bo', label='CEMP-no')
py.legend(loc='upper left', numpoints=1)
py.xlabel('V magnitude')
py.ylabel('[Fe/H]')
py.savefig('v_vs_feh_cemp_s_no.png')
# Now lets figure out what is observable this semester.
py.clf()
py.plot(d.ra[cemps], d.dec[cemps], 'rs', label='CEMP-s')
py.plot(d.ra[cempno], d.dec[cempno], 'bo', label='CEMP-no')
py.xlabel('R.A. (degrees)')
py.ylabel('Dec. (degrees)')
py.legend(loc='upper right', numpoints=1)
lim_RA_mar01 = [90, 237]
lim_RA_may01 = [156, 284]
lim_RA_jul01 = [223, 342]
py.plot(lim_RA_mar01, [10, 10], 'm-', linewidth=3)
py.plot(lim_RA_may01, [20, 20], 'k-', linewidth=3, color='cyan')
py.plot(lim_RA_jul01, [30, 30], 'g-', linewidth=3)
py.text(95, 12, 'Mar 01, 2012', color='magenta')
py.text(160, 22, 'May 01, 2012', color='cyan')
py.text(235, 32, 'Jul 01, 2011', color='green')
py.xlim(0, 360)
py.ylim(-30, 70)
py.savefig('ra_dec_cemp_s_no.png')
# RA vs. V-band
py.clf()
py.plot(d.ra[cemps], d.V[cemps], 'rs', label='CEMP-s')
py.plot(d.ra[cempno], d.V[cempno], 'bo', label='CEMP-no')
py.xlabel('R.A. (degrees)')
py.ylabel('V Magnitude')
py.gca().set_ylim(py.gca().get_ylim()[::-1])
py.legend(loc='upper right', numpoints=1)
py.plot(lim_RA_mar01, [12, 12], 'm-', linewidth=3)
py.plot(lim_RA_may01, [11, 11], 'k-', linewidth=3, color='cyan')
py.plot(lim_RA_jul01, [10, 10], 'g-', linewidth=3)
py.text(95, 11.9, 'Mar 01, 2012', color='magenta')
py.text(160, 10.9, 'May 01, 2012', color='cyan')
py.text(235, 9.9, 'Jul 01, 2011', color='green')
py.xlim(0, 360)
py.ylim(17, 6)
py.savefig('ra_v_cemp_s_no.png')
print('')
print 'After removing stars without info:'
hdrfmt = '{:16s} {:^15s} {:^15s} {:^5s} {:^5s} {:^5s} {:^5s}'
starfmt = '{:<16s} {:15s} {:15s} {:5.2f} {:5.2f} {:5.2f} {:5.2f}'
# Print out all the emp-r stars
print('')
print(' {:d} EMP-r stars (non-Carbon enhanced)'.format(len(empr)))
print(hdrfmt.format('Name', 'RA', 'Dec', 'Vmag', 'Fe/H', 'C/Fe', 'Ba/Fe'))
for ii in empr:
hmsdms = coords.Position((d.ra[ii], d.dec[ii])).hmsdms().split()
ra_hex = hmsdms[0].replace(':', ' ')
dec_hex = hmsdms[1].replace(':', ' ')
print(
starfmt.format(d.name[ii], ra_hex, dec_hex, d.V[ii], d.FeH[ii],
d.CFe[ii], d.BaFe[ii]))
print('')
print(' {:d} CEMP-s stars'.format(len(cemps)))
print(hdrfmt.format('Name', 'RA', 'Dec', 'Vmag', 'Fe/H', 'C/Fe', 'Ba/Fe'))
for ii in cemps:
hmsdms = coords.Position((d.ra[ii], d.dec[ii])).hmsdms().split()
ra_hex = hmsdms[0].replace(':', ' ')
dec_hex = hmsdms[1].replace(':', ' ')
print(
starfmt.format(d.name[ii], ra_hex, dec_hex, d.V[ii], d.FeH[ii],
d.CFe[ii], d.BaFe[ii]))
# Print out all the cemp-no stars
print('')
print(' {:d} CEMP-no stars'.format(len(cempno)))
print(hdrfmt.format('Name', 'RA', 'Dec', 'Vmag', 'Fe/H', 'C/Fe', 'Ba/Fe'))
for ii in cempno:
print ii, d.ra[ii], d.dec[ii]
hmsdms = coords.Position((d.ra[ii], d.dec[ii])).hmsdms().split()
ra_hex = hmsdms[0].replace(':', ' ')
dec_hex = hmsdms[1].replace(':', ' ')
print(
starfmt.format(d.name[ii], ra_hex, dec_hex, d.V[ii], d.FeH[ii],
d.CFe[ii], d.BaFe[ii]))
def cempno_table():
names = [
'CD-38_245', 'CS22942-019', 'HD6755', 'CS22958-042', 'BD+44_493',
'BS16545-089', 'HE1150-0428', 'BS16920-005', 'HE1300+0157',
'BS16929-005', 'HE1300-0641', 'CS22877-001', 'CS22880-074',
'CS29498-043', 'CS29502-092', 'CS22949-037', 'CS22957-027',
'HE2356-0410', 'HE1012-1540', 'HE1330-0354'
]
d = load_frebel_table()
idx = np.array([], dtype=int)
for ii in range(len(names)):
foo = np.where(d.name == names[ii])[0]
idx = np.append(idx, foo)
sdx = d.ra[idx].argsort()
idx = idx[sdx]
# Trim out what we need
ra = d.ra[idx]
dec = d.dec[idx]
V = d.V[idx]
B = d.B[idx]
R = d.R[idx]
FeH = d.FeH[idx]
CFe = d.CFe[idx]
BaFe = d.BaFe[idx]
# Fix the RA and Dec for CEMP-s and CEMP-no stars
ra, dec = getCoordsFromSimbad(d.simbad[idx])
# Make a LaTeX table of the targets we want to observe
_out = open('table_cemp_no.tex', 'w')
_out.write('\\begin{deluxetable}{lrrrrrr}\n')
_out.write('\\tablewidth{0pt}\n')
_out.write('\\tablecaption{CEMP-no Stars}\n')
_out.write('\\tablehead{\n')
_out.write(' \\colhead{Name} &\n')
_out.write(' \\colhead{R.A. (J2000)} &\n')
_out.write(' \\colhead{Dec. (J2000)} &\n')
_out.write(' \\colhead{V} &\n')
_out.write(' \\colhead{[Fe/H]} &\n')
_out.write(' \\colhead{[C/Fe]} &\n')
_out.write(' \\colhead{[Ba/Fe]}\n')
_out.write('}\n')
_out.write('\\startdata\n')
for ii in range(len(names)):
hmsdms = coords.Position((ra[ii], dec[ii])).hmsdms().split()
ra_hex = hmsdms[0]
dec_hex = hmsdms[1]
_out.write('%25s & %15s & %15s & ' %
(names[ii].replace('_', '\_'), ra_hex, dec_hex))
_out.write('%5.2f & %5.2f & %5.2f & %5.2f \\\\ \n' %
(V[ii], FeH[ii], CFe[ii], BaFe[ii]))
_out.write('\\enddata\n')
_out.write('\\end{deluxetable}\n')
_out.close()
# Now lets loop through and plot when these targets are observable.
py.clf()
py.subplots_adjust(left=0.05, right=0.95, top=0.95)
# Calculate the hour angle at which the object goes above airmass = 2.
# Relevant equations are:
# airmass = 1 / cos(z)
# hour angle = sidereal time - RA
# cos z = sin L sin Dec + cos L cos Dec cos HA
# We will solve for HA.
iraf.noao()
obs = iraf.noao.observatory
obs(command="set", obsid="keck")
airmassLim = 2.0
latRad = np.radians(obs.latitude)
decRad = np.radians(dec)
top = (1.0 / airmassLim) - np.sin(latRad) * np.sin(decRad)
bot = np.cos(latRad) * np.cos(decRad)
hangle = np.degrees(np.arccos(top / bot))
madeLegend = False
for ii in range(len(names)):
minLST = (ra[ii] - hangle[ii]) / 15.
maxLST = (ra[ii] + hangle[ii]) / 15.
hix = 360.0 / 15.0
if (minLST >= 0) and (maxLST < hix):
if madeLegend == True:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black')
else:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black',
label='CEMP-no stars')
madeLegend = True
if minLST < 0:
py.plot([0, maxLST], [ii + 1, ii + 1], linewidth=5, color='black')
py.plot([minLST + hix, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
if maxLST > hix:
py.plot([minLST, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.plot([0, maxLST - hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.xlim(0, hix)
# Get the LST ranges for March, May, July
months = np.array([3, 5, 7])
days = np.array([1, 1, 1])
years = np.array([2012, 2012, 2012])
colors = ['red', 'green', 'blue']
labels = ['Mar 1, 2012 (HST)', 'May 1, 2012 (HST)', 'Jul 1, 2012 (HST)']
rng = py.axis()
for ii in range(len(months)):
twi = get_twilight_lst(years[ii], months[ii], days[ii])
minLST = twi[0] * 15.0
maxLST = twi[1] * 15.0
ypos = rng[3] + 2 * (len(months) - ii)
if minLST < 0:
minLST += 360.0
if maxLST > 360:
maxLST -= 360.0
x1 = np.array([minLST, maxLST]) / 15.0
x2 = None
y = np.array([ypos, ypos])
if minLST > 0 and maxLST < 360 and minLST > maxLST:
x1 = np.array([0, maxLST]) / 15.0
x2 = np.array([minLST, 360]) / 15.0
py.plot(x1, y, linewidth=10, color=colors[ii], label=labels[ii])
if x2 != None:
py.plot(x2, y, linewidth=10, color=colors[ii])
py.ylim(0, rng[3] + 7 * len(months))
py.legend(loc='upper left')
# py.xlim(0, 360)
py.xlim(0, 24)
py.xlabel('LST (hours)')
py.gca().yaxis.set_visible(False)
py.savefig('obs_ra_v_cemp_s_no.png')
def cutout(filename,
outfile,
xc,
yc,
xw=25,
yw=25,
units='pixels',
clobber=True,
coordsys='celestial',
verbose=False):
"""
Inputs:
file - .fits filename or pyfits HDUList (must be 2D)
xc,yc - x and y coordinates in the fits files' coordinate system (CTYPE)
xw,yw - x and y width (pixels or wcs)
units - specify units to use: either pixels or wcs
outfile - optional output file
"""
if isinstance(filename, str):
file = pyfits.open(filename)
opened = True
elif isinstance(filename, pyfits.HDUList):
file = filename
opened = False
else:
raise Exception(
"cutout: Input file is wrong type (string or HDUList are acceptable)."
)
head = file[0].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
if cd1 is None or cd2 is None:
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
print 'using wcs conversion'
if coordsys == 'celestial' and wcs.wcs.lngtyp == 'GLON':
xc, yc = coords.Position((xc, yc), system=coordsys).galactic()
elif coordsys == 'galactic' and wcs.wcs.lngtyp == 'RA':
xc, yc = coords.Position((xc, yc), system=coordsys).j2000()
xx, yy = wcs.wcs_sky2pix(xc, yc, 0)
elif units == 'pixels':
xx, yy = xc, yc
if units == 'pixels':
xmin, xmax = numpy.max([0,
xx - xw]), numpy.min([head['NAXIS1'], xx + xw])
ymin, ymax = numpy.max([0,
yy - yw]), numpy.min([head['NAXIS2'], yy + yw])
elif units == 'wcs':
xmin, xmax = numpy.max([0, xx - xw / numpy.abs(cd1)]), numpy.min(
[head['NAXIS1'], xx + xw / numpy.abs(cd1)])
ymin, ymax = numpy.max([0, yy - yw / numpy.abs(cd2)]), numpy.min(
[head['NAXIS2'], yy + yw / numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." %
(xmax, ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." %
(xmin, ymin))
head['CRPIX1'] -= xmin
head['CRPIX2'] -= ymin
head['NAXIS1'] = int(xmax - xmin)
head['NAXIS2'] = int(ymax - ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." %
(head.get('NAXIS1'), head.get('NAXIS2')))
# use imcopy insstead
filesection = filename + '[%i:%i,%i:%i]' % (xmin, xmax, ymin, ymax)
print filesection, xc, yc
if os.path.exists(outfile):
os.remove(outfile)
imcopy(filesection, outfile)
def cempno_starlist():
names = np.array([
'CD-38_245', 'CS22942-019', 'HD6755', 'CS22958-042', 'BD+44_493',
'BS16545-089', 'HE1150-0428', 'BS16920-005', 'HE1300+0157',
'BS16929-005', 'HE1300-0641', 'CS22877-001', 'CS22880-074',
'CS29498-043', 'CS29502-092', 'CS22949-037', 'CS22957-027',
'HE2356-0410', 'HE1012-1540', 'HE1330-0354'
])
d = load_frebel_table()
idx = np.array([], dtype=int)
for ii in range(len(names)):
foo = np.where(d.name == names[ii])[0]
idx = np.append(idx, foo)
# sdx = d.ra[idx].argsort()
# idx = idx[sdx]
# Trim out what we need
ra = d.ra[idx]
dec = d.dec[idx]
V = d.V[idx]
B = d.B[idx]
R = d.R[idx]
FeH = d.FeH[idx]
CFe = d.CFe[idx]
BaFe = d.BaFe[idx]
simbad = d.simbad[idx]
# Make a LaTeX table of the targets we want to observe
_out = open('cemp_no_starlist.tel', 'w')
_out2 = open('cemp_no_simbadnames.tel', 'w')
for ii in range(len(names)):
hmsdms = coords.Position((ra[ii], dec[ii])).hmsdms().split()
ra_hex = hmsdms[0].replace(':', ' ')
dec_hex = hmsdms[1].replace(':', ' ')
print ii, names[ii], simbad[ii]
_out.write('%-16s %12s %12s 2000.0 vmag=%5.2f\n' %
(names[ii], ra_hex, dec_hex, V[ii]))
_out2.write('%s\n' % simbad[ii])
_out.close()
_out2.close()
# Now lets loop through and plot when these targets are observable.
py.clf()
py.subplots_adjust(left=0.05, right=0.95, top=0.95)
# Calculate the hour angle at which the object goes above airmass = 2.
# Relevant equations are:
# airmass = 1 / cos(z)
# hour angle = sidereal time - RA
# cos z = sin L sin Dec + cos L cos Dec cos HA
# We will solve for HA.
iraf.noao()
obs = iraf.noao.observatory
obs(command="set", obsid="keck")
airmassLim = 2.0
latRad = np.radians(obs.latitude)
decRad = np.radians(dec)
top = (1.0 / airmassLim) - np.sin(latRad) * np.sin(decRad)
bot = np.cos(latRad) * np.cos(decRad)
hangle = np.degrees(np.arccos(top / bot))
madeLegend = False
for ii in range(len(names)):
minLST = (ra[ii] - hangle[ii]) / 15.
maxLST = (ra[ii] + hangle[ii]) / 15.
hix = 360.0 / 15.0
if (minLST >= 0) and (maxLST < hix):
if madeLegend == True:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black')
else:
py.plot([minLST, maxLST], [ii + 1, ii + 1],
linewidth=5,
color='black',
label='CEMP-no stars')
madeLegend = True
if minLST < 0:
py.plot([0, maxLST], [ii + 1, ii + 1], linewidth=5, color='black')
py.plot([minLST + hix, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
if maxLST > hix:
py.plot([minLST, hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.plot([0, maxLST - hix], [ii + 1, ii + 1],
linewidth=5,
color='black')
py.xlim(0, hix)
# Get the LST ranges for mid-August, early-November, and mid-January.
months = np.array([8, 11, 1])
days = np.array([1, 1, 31])
years = np.array([2011, 2011, 2012])
colors = ['red', 'green', 'blue']
labels = ['Aug 1, 2011 (HST)', 'Nov 1, 2011 (HST)', 'Jan 31, 2012 (HST)']
rng = py.axis()
for ii in range(len(months)):
twi = get_twilight_lst(years[ii], months[ii], days[ii])
minLST = twi[0] * 15.0
maxLST = twi[1] * 15.0
ypos = rng[3] + 2 * (len(months) - ii)
if minLST < 0:
minLST += 360.0
if maxLST > 360:
maxLST -= 360.0
x1 = np.array([minLST, maxLST]) / 15.0
x2 = None
y = np.array([ypos, ypos])
if minLST > 0 and maxLST < 360 and minLST > maxLST:
x1 = np.array([0, maxLST]) / 15.0
x2 = np.array([minLST, 360]) / 15.0
py.plot(x1, y, linewidth=10, color=colors[ii], label=labels[ii])
if x2 != None:
py.plot(x2, y, linewidth=10, color=colors[ii])
py.ylim(0, rng[3] + 7 * len(months))
py.legend(loc='upper left')
# py.xlim(0, 360)
py.xlim(0, 24)
py.xlabel('LST (hours)')
py.gca().yaxis.set_visible(False)
py.savefig('obs_ra_v_cemp_s_no_new.png')
stddc = header['STDDC']
try:
rad_as = header['MASKRAD']
masked = True
except:
try:
rad_as = float(
re.compile('maske?d?([0-9]*)').search(file).groups()[0])
masked = True
except:
rad_as = 80.0
masked = False
try:
tgtra = header['TGT_RA']
tgtdec = header['TGT_DEC']
l, b = coords.Position([tgtra, tgtdec]).galactic()
if masked:
ff.show_circles(numpy.array([l]),
numpy.array([b]),
rad_as / 3600.0,
edgecolor='blue')
ff.show_circles(numpy.array([l]),
numpy.array([b]),
300.0 / 3600.0,
edgecolor='purple')
except KeyError:
print "No TGT_RA found"
wcshead = pywcs.WCS(header)
lbfit = wcshead.wcs_pix2sky(fitpars[2:3], fitpars[3:4], 0)
def cutout(filename,
xc,
yc,
xw=25,
yw=25,
units='pixels',
outfile=None,
clobber=True,
useMontage=False,
coordsys='celestial',
verbose=False):
#Inputs:
#file - .fits filename or pyfits HDUList (must be 2D)
#xc,yc - x and y coordinates in the fits files' coordinate system (CTYPE)
#xw,yw - x and y width (pixels or wcs)
#units - specify units to use: either pixels or wcs
#outfile - optional output file
if isinstance(filename, str):
file = pyfits.open(filename)
opened = True
elif isinstance(filename, pyfits.HDUList):
file = filename
opened = False
else:
raise Exception(
"cutout: Input file is wrong type (string or HDUList are acceptable)."
)
head = file[0].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
if cd1 is None or cd2 is None:
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
if coordsys == 'celestial' and wcs.wcs.lngtyp == 'GLON':
xc, yc = coords.Position((xc, yc), system=coordsys).galactic()
elif coordsys == 'galactic' and wcs.wcs.lngtyp == 'RA':
xc, yc = coords.Position((xc, yc), system=coordsys).j2000()
if useMontage and CanUseMontage:
head['CRVAL1'] = xc
head['CRVAL2'] = yc
if units == 'pixels':
head['CRPIX1'] = xw
head['CRPIX2'] = yw
head['NAXIS1'] = int(xw * 2)
head['NAXIS2'] = int(yw * 2)
elif units == 'wcs':
cdelt = numpy.sqrt(cd1**2 + cd2**2)
head['CRPIX1'] = xw / cdelt
head['CRPIX2'] = yw / cdelt
head['NAXIS1'] = int(xw * 2 / cdelt)
head['NAXIS2'] = int(yw * 2 / cdelt)
head.toTxtFile('temp_montage.hdr', clobber=True)
newfile = montage.wrappers.reproject_hdu(file[0],
header='temp_montage.hdr',
exact_size=True)
os.remove('temp_montage.hdr')
else:
xx, yy = wcs.wcs_world2pix(xc, yc, 0)
if units == 'pixels':
xmin, xmax = numpy.max([0, xx - xw
]), numpy.min([head['NAXIS1'], xx + xw])
ymin, ymax = numpy.max([0, yy - yw
]), numpy.min([head['NAXIS2'], yy + yw])
elif units == 'wcs':
xmin, xmax = numpy.max([0, xx - xw / numpy.abs(cd1)]), numpy.min(
[head['NAXIS1'], xx + xw / numpy.abs(cd1)])
ymin, ymax = numpy.max([0, yy - yw / numpy.abs(cd2)]), numpy.min(
[head['NAXIS2'], yy + yw / numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." %
(xmax, ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." %
(xmin, ymin))
head['CRPIX1'] -= xmin
head['CRPIX2'] -= ymin
head['NAXIS1'] = int(xmax - xmin)
head['NAXIS2'] = int(ymax - ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." %
(head.get('NAXIS1'), head.get('NAXIS2')))
img = file[0].data[ymin:ymax, xmin:xmax]
newfile = pyfits.PrimaryHDU(data=img, header=head)
if verbose:
print "Cut image %s with dims %s to %s. xrange: %f:%f, yrange: %f:%f" % (
filename, file[0].data.shape, img.shape, xmin, xmax, ymin,
ymax)
if isinstance(outfile, str):
newfile.writeto(outfile, clobber=clobber)
if opened:
file.close()
return newfile
def cut_fits_downloaded(filename, xc, yc, xw=1, yw=1, units='pixels', outfile=None, clobber=True, useMontage=False, coordsys='celestial', verbose=False):
"""
credit: http://code.google.com/p/agpy/source/browse/trunk/agpy/cutout.py
changed by Hongquan on 25 May 2015: move the imports into the defination part
Generate a cutout image from a .fits file
Inputs:
file - .fits filename or pyfits HDUList (must be 2D)
xc,yc - x and y coordinates in the fits files' coordinate system (CTYPE)
xw,yw - x and y width (pixels or wcs); xw and yw is half width of the output file
units - specify units to use: either pixels or wcs
outfile - optional output file
"""
try:
import astropy.io.fits as pyfits
import astropy.wcs as pywcs
except ImportError:
import pyfits
import pywcs
import numpy
try:
import coords
except ImportError:
pass # maybe should do something smarter here, but I want agpy to install...
try:
import montage_wrapper as montage
import os
CanUseMontage=True
except ImportError:
CanUseMontage=False
class DimensionError(ValueError):
pass
if isinstance(filename,str):
file = pyfits.open(filename)
opened=True
elif isinstance(filename,pyfits.HDUList):
file = filename
opened=False
else:
raise Exception("cutout: Input file is wrong type (string or HDUList are acceptable).")
head = file[0].header.copy()
if head['NAXIS'] > 2:
raise DimensionError("Too many (%i) dimensions!" % head['NAXIS'])
cd1 = head.get('CDELT1') if head.get('CDELT1') else head.get('CD1_1')
cd2 = head.get('CDELT2') if head.get('CDELT2') else head.get('CD2_2')
if cd1 is None or cd2 is None:
raise Exception("Missing CD or CDELT keywords in header")
wcs = pywcs.WCS(head)
if units == 'wcs':
if coordsys=='celestial' and wcs.wcs.lngtyp=='GLON':
xc,yc = coords.Position((xc,yc),system=coordsys).galactic()
elif coordsys=='galactic' and wcs.wcs.lngtyp=='RA':
xc,yc = coords.Position((xc,yc),system=coordsys).j2000()
if useMontage and CanUseMontage:
head['CRVAL1'] = xc
head['CRVAL2'] = yc
if units == 'pixels':
head['CRPIX1'] = xw
head['CRPIX2'] = yw
head['NAXIS1'] = int(xw*2)
head['NAXIS2'] = int(yw*2)
elif units == 'wcs':
cdelt = numpy.sqrt(cd1**2+cd2**2)
head['CRPIX1'] = xw / cdelt
head['CRPIX2'] = yw / cdelt
head['NAXIS1'] = int(xw*2 / cdelt)
head['NAXIS2'] = int(yw*2 / cdelt)
head.toTxtFile('temp_montage.hdr',clobber=True)
newfile = montage.wrappers.reproject_hdu(file[0],header='temp_montage.hdr',exact_size=True)
os.remove('temp_montage.hdr')
else:
xx,yy = wcs.wcs_world2pix(xc,yc,0)
if units=='pixels':
xmin,xmax = numpy.max([0,xx-xw]),numpy.min([head['NAXIS1'],xx+xw])
ymin,ymax = numpy.max([0,yy-yw]),numpy.min([head['NAXIS2'],yy+yw])
elif units=='wcs':
xmin,xmax = numpy.max([0,xx-xw/numpy.abs(cd1)]),numpy.min([head['NAXIS1'],xx+xw/numpy.abs(cd1)])
ymin,ymax = numpy.max([0,yy-yw/numpy.abs(cd2)]),numpy.min([head['NAXIS2'],yy+yw/numpy.abs(cd2)])
else:
raise Exception("Can't use units %s." % units)
if xmax < 0 or ymax < 0:
raise ValueError("Max Coordinate is outside of map: %f,%f." % (xmax,ymax))
if ymin >= head.get('NAXIS2') or xmin >= head.get('NAXIS1'):
raise ValueError("Min Coordinate is outside of map: %f,%f." % (xmin,ymin))
head['CRPIX1']-=xmin
head['CRPIX2']-=ymin
head['NAXIS1']=int(xmax-xmin)
head['NAXIS2']=int(ymax-ymin)
if head.get('NAXIS1') == 0 or head.get('NAXIS2') == 0:
raise ValueError("Map has a 0 dimension: %i,%i." % (head.get('NAXIS1'),head.get('NAXIS2')))
img = file[0].data[ymin:ymax,xmin:xmax]
newfile = pyfits.PrimaryHDU(data=img,header=head)
if verbose: print("Cut image %s with dims %s to %s. xrange: %f:%f, yrange: %f:%f" % (filename, file[0].data.shape,img.shape,xmin,xmax,ymin,ymax))
if isinstance(outfile,str):
newfile.writeto(outfile,clobber=clobber)
if opened:
file.close()
return newfile
