def make_RGB():
Blue,header = pf.getdata('Blue.fit',0,header=True)
Green,header = pf.getdata('Green.fit',0,header=True)
Red,header = pf.getdata('Red.fit',0,header=True)
G = h.pyfits.open('Green.fit')
Gh = h.pyfits.getheader('Green.fit')
B = h.pyfits.open('Blue.fit')
Bh = h.pyfits.getheader('Blue.fit')
R = h.pyfits.open('Red.fit')
Rh = h.pyfits.getheader('Red.fit')
Bnew = h.hcongrid(B[0].data,B[0].header,Gh)
Rnew = h.hcongrid(R[0].data,R[0].header,Gh)
Blue = Bnew
Green,header = readimage('Green.fit')
Red = Rnew
bmed = np.median(Blue)
gmed = np.median(Green)
rmed = np.median(Red)
bsig = rb.std(Blue)
gsig = rb.std(Green)
rsig = rb.std(Red)
final = np.zeros((Blue.shape[0],Blue.shape[1],3),dtype=float)
sigmin = 1.25
sigmax = 15
final[:,:,0] = img_scale.sqrt(Red,scale_min=rmed+sigmin*rsig,scale_max=rmed+0.6*sigmax*rsig)
final[:,:,1] = img_scale.sqrt(Green,scale_min=gmed+sigmin*gsig,scale_max=gmed+0.6*sigmax*gsig)
final[:,:,2] = img_scale.sqrt(Blue,scale_min=bmed+sigmin*bsig,scale_max=bmed+0.6*sigmax*bsig)
plt.ion()
plt.figure(99)
#plt.imshow(img,aspect='equal')
plt.xlim(250,1550)
plt.ylim(288,1588)
plt.xticks([])
plt.yticks([])
plt.imshow(final,aspect='equal')
return
def makeband(band='V'):
files = glob.glob('Mantis*[0-9]'+band+'_cal.fit*')
zsz = len(files)
reffile = files[zsz/2]
image0,header0 = readimage(reffile)
ysz,xsz = np.shape(image0)
refim = h.pyfits.open(reffile)
refh = h.pyfits.getheader(reffile)
stack = np.zeros((xsz,ysz,zsz))
for i in range(zsz):
im = h.pyfits.open(files[i])
newim = h.hcongrid(im[0].data,im[0].header,refh)
stack[:,:,i] = newim
final = np.median(stack,axis=2)
if band == 'V':
tag = 'Blue'
if band == 'R':
tag = 'Green'
if band == 'ip':
tag = 'Red'
test = glob.glob(tag+'.fit')
if test:
os.remove(tag+'.fit')
pf.writeto(tag+'.fit',final,header0)
def project_to_header(fitsfile,
header,
use_montage=True,
quiet=True,
**kwargs):
"""
Light wrapper of montage with hcongrid as a backup
kwargs will be passed to `~hcongrid.hcongrid` if ``use_montage==False``
Parameters
----------
fitsfile : string
a FITS file name
header : `~astropy.io.fits.Header`
A fits Header instance with valid WCS to project to
use_montage : bool
Use montage or hcongrid (based on `~scipy.ndimage.interpolation.map_coordinates`)
quiet : bool
Silence Montage's output
Returns
-------
image : `~numpy.ndarray`
image projected to header's coordinates
"""
try:
import montage
montageOK = True
except ImportError:
montageOK = False
try:
from hcongrid import hcongrid
hcongridOK = True
except ImportError:
hcongridOK = False
import tempfile
if montageOK and use_montage:
temp_headerfile = tempfile.NamedTemporaryFile()
header.toTxtFile(temp_headerfile.name)
outfile = tempfile.NamedTemporaryFile()
montage.wrappers.reproject(fitsfile,
outfile.name,
temp_headerfile.name,
exact_size=True,
silent_cleanup=quiet)
image = fits.getdata(outfile.name)
outfile.close()
temp_headerfile.close()
elif hcongridOK:
# only works for 2D images
image = hcongrid(
fits.getdata(fitsfile).squeeze(),
flatten_header(fits.getheader(fitsfile)), header, **kwargs)
return image
def cal_image(filepath,plot = True,path=None,band='gp',source='BD710031',bias=None,dark=None,flat=None):
if not path:
path = set_path()
if length(bias) == 1:
bias = make_bias(path=path)
if length(dark) == 1:
dark = make_dark(path=path)
if length(flat) == 1:
flat = make_flat(path=path,band=band,bias=bias,dark=dark)
image0, header0 = qi.readimage(filepath)
refh = h.pyfits.getheader(filepath)
im = h.pyfits.open(filepath)
newim = h.hcongrid((im[0].data-dark-bias)/flat, im[0].header,refh)
if plot:
qi.display_image(newim)
return newim,header0
def stack_ims(path=None,band='gp',source='NGC188',bias=None,dark=None,flat=None):
if not path:
path = set_path()
if length(bias) == 1:
bias = make_bias(path=path)
if length(dark) == 1:
dark = make_dark(path=path)
if length(flat) == 1:
flat = make_flat(path=path,band=band,bias=bias,dark=dark)
files,sz = tp.get_files(dir=path, tag=source+'.'+band)
# Designate reference file
reffile = files[sz/2]
image0, header0 = qi.readimage(reffile)
ysz, xsz = np.shape(image0)
refim = h.pyfits.open(reffile)
refh = h.pyfits.getheader(reffile)
stack = np.zeros((xsz,ysz,sz))
for i in range(sz):
im = h.pyfits.open(files[i])
newim = h.hcongrid((im[0].data-dark-bias)/flat, im[0].header,refh)
stack[:,:,i] = newim
final = np.median(stack, axis=2)
return final,refh
def project_to_header(fitsfile, header, use_montage=True, quiet=True,
**kwargs):
"""
Light wrapper of montage with hcongrid as a backup
kwargs will be passed to `~hcongrid.hcongrid` if ``use_montage==False``
Parameters
----------
fitsfile : string
a FITS file name
header : `~astropy.io.fits.Header`
A fits Header instance with valid WCS to project to
use_montage : bool
Use montage or hcongrid (based on `~scipy.ndimage.interpolation.map_coordinates`)
quiet : bool
Silence Montage's output
Returns
-------
image : `~numpy.ndarray`
image projected to header's coordinates
"""
try:
import montage
montageOK=True
except ImportError:
montageOK=False
try:
from hcongrid import hcongrid
hcongridOK=True
except ImportError:
hcongridOK=False
import tempfile
if montageOK and use_montage:
temp_headerfile = tempfile.NamedTemporaryFile()
header.toTxtFile(temp_headerfile.name)
outfile = tempfile.NamedTemporaryFile()
montage.wrappers.reproject(fitsfile, outfile.name,
temp_headerfile.name, exact_size=True,
silent_cleanup=quiet)
image = fits.getdata(outfile.name)
outfile.close()
temp_headerfile.close()
elif hcongridOK:
# only works for 2D images
image = hcongrid(fits.getdata(fitsfile).squeeze(),
flatten_header(fits.getheader(fitsfile)),
header,
**kwargs)
return image
def project_to_header(fitsfile,
header,
use_montage=True,
quiet=True,
**kwargs):
"""
Light wrapper of montage with hcongrid as a backup
Parameters
----------
fitsfile : string
a FITS file name
header : pyfits.Header
A pyfits Header instance with valid WCS to project to
use_montage : bool
Use montage or hcongrid (scipy's map_coordinates)
quiet : bool
Silence Montage's output
Returns
-------
np.ndarray image projected to header's coordinates
"""
try:
import montage
montageOK = True
except ImportError:
montageOK = False
try:
from hcongrid import hcongrid
hcongridOK = True
except ImportError:
hcongridOK = False
import tempfile
if montageOK and use_montage:
temp_headerfile = tempfile.NamedTemporaryFile()
header.toTxtFile(temp_headerfile.name)
outfile = tempfile.NamedTemporaryFile()
montage.wrappers.reproject(fitsfile,
outfile.name,
temp_headerfile.name,
exact_size=True,
silent_cleanup=quiet)
image = pyfits.getdata(outfile.name)
outfile.close()
temp_headerfile.close()
elif hcongridOK:
image = hcongrid(load_data(fitsfile), load_header(fitsfile), header)
return image
def project_to_header(fitsfile, header, use_montage=True, quiet=True, **kwargs):
"""
Light wrapper of montage with hcongrid as a backup
Parameters
----------
fitsfile : string
a FITS file name
header : pyfits.Header
A pyfits Header instance with valid WCS to project to
use_montage : bool
Use montage or hcongrid (scipy's map_coordinates)
quiet : bool
Silence Montage's output
Returns
-------
np.ndarray image projected to header's coordinates
"""
try:
import montage
montageOK=True
except ImportError:
montageOK=False
try:
from hcongrid import hcongrid
hcongridOK=True
except ImportError:
hcongridOK=False
import tempfile
if montageOK and use_montage:
temp_headerfile = tempfile.NamedTemporaryFile()
header.toTxtFile(temp_headerfile.name)
outfile = tempfile.NamedTemporaryFile()
montage.wrappers.reproject(fitsfile,
outfile.name,
temp_headerfile.name,
exact_size=True,
silent_cleanup=quiet)
image = pyfits.getdata(outfile.name)
outfile.close()
temp_headerfile.close()
elif hcongridOK:
image = hcongrid(load_data(fitsfile),
load_header(fitsfile),
header)
return image
