def skysub(self):
firstdat = self.niimage.get_data()
seconddat = self.nisky.get_data()
finaldat = firstdat - seconddat
final_image = dp.make_image(finaldat,
self.niimage, {},
pfx='subtracted')
name = dp.get_image_name(final_image)
self.fv.add_image(name, final_image, chname='Image')
def subimg(self):
first = self.fv.load_file(self.w.first.get_text(), chname = '1')
second = self.fv.load_file(self.w.second.get_text(), chname = '2')
firstdat = first.get_data()
seconddat = second.get_data()
finaldat = firstdat - seconddat
final_image = dp.make_image(finaldat, first, {}, pfx='subtracted')
name = dp.get_image_name(final_image)
self.fv.add_image(name, final_image, chname='4')
def set_flat_cb(self, w):
# Current image is a flat field we should set
self.flat = self.fitsimage.get_image()
flatname = dp.get_image_name(self.flat, pfx='flat')
self.w.flat_image.set_text(flatname)
self.update_status("Set flat field.")
def set_bias_cb(self, w):
# Current image is a bias image we should set
self.bias = self.fitsimage.get_image()
biasname = dp.get_image_name(self.bias, pfx='bias')
self.w.bias_image.set_text(biasname)
self.update_status("Set bias image.")
def show_result(self, image):
chname = self.fv.get_channelName(self.fitsimage)
name = dp.get_image_name(image)
self.imglist.insert(0, image)
self.update_stack_gui()
self.fv.add_image(name, image, chname=chname)
def multimos(self, filename):
hdulist = fits.open(filename)
files = np.sum([
1 for hdu in hdulist if
type(hdu) in [fits.hdu.image.PrimaryHDU, fits.hdu.image.ImageHDU]
and hdu.data is not None
])
k = 0
j = 0
ra_deg = 0.5
dec_deg = 0.5
fov_deg = 0.2
header = hdulist[1].header
(rot_deg, cdelt1,
cdelt2) = wcs.get_rotation_and_scale(header, skew_threshold=1)
px_scale = math.fabs(cdelt1)
cdbase = [np.sign(cdelt1), np.sign(cdelt2)]
###Sorting Images###
imagesort = [[0 for x in range(4)] for y in range(files)]
for i in range(1, files + 1):
imagesort[i - 1][0] = hdulist[i]
df = hdulist[i].header['DETSEC']
cpos = df.index(':')
epos = df.index(',')
dflow = ''.join(df[1:cpos])
dflow = int(dflow)
dfhigh = ''.join(df[cpos + 1:epos])
dfhigh = int(dfhigh)
imagesort[i - 1][1] = dflow + dfhigh
ncpos = df.index(':', cpos + 1)
nepos = df.index(']')
yflow = ''.join(df[epos + 1:ncpos])
yflow = int(yflow)
yhigh = ''.join(df[ncpos + 1:nepos])
yhigh = int(yhigh)
imagesort[i - 1][2] = yflow + yhigh
ccd = hdulist[i].header['CCDNAME']
imagesort[i - 1][3] = ccd
sortedim = sorted(imagesort, key=lambda x: x[1])
###Putting images together###
#2D#
if sortedim[0][1] == sortedim[1][1]:
for i in range(1, files + 1):
dr = sortedim[i - 1][0].header['DATASEC']
colpos = dr.index(':')
endpos = dr.index(',')
drlow = ''.join(dr[1:colpos])
drlow = int(drlow)
drhigh = ''.join(dr[colpos + 1:endpos])
drhigh = int(drhigh)
imdata = sortedim[i - 1][0].data[:, drlow:drhigh]
gapxdim = np.size(imdata, 0)
gapx = np.zeros((gapxdim, 30))
gapx[:, :] = np.nan
gapydim = np.size(imdata, 1) + 30
gapy = np.zeros((20, gapydim))
gapy[:, :] = np.nan
fgapy = np.zeros((20, gapydim - 30))
fgapy[:, :] = np.nan
#image flips#
df = sortedim[i - 1][0].header['DETSEC']
cpos = df.index(':')
epos = df.index(',')
dflow = ''.join(df[1:cpos])
dflow = int(dflow)
dfhigh = ''.join(df[cpos + 1:epos])
dfhigh = int(dfhigh)
ncpos = df.index(':', cpos + 1)
nepos = df.index(']')
yflow = ''.join(df[epos + 1:ncpos])
yflow = int(yflow)
yhigh = ''.join(df[ncpos + 1:nepos])
yhigh = int(yhigh)
if dflow > dfhigh:
findatx = np.fliplr(imdata)
else:
findatx = imdata
if yflow > yhigh:
findat = np.flipud(findatx)
else:
findat = findatx
fm = files - 1
if i != files:
if i != fm:
if sortedim[i - 1][3] != sortedim[i][3]:
findat = np.column_stack((findat, gapx))
if i == 1:
vert = findat
elif sortedim[i - 1][1] == sortedim[i - 2][1]:
if sortedim[i - 1][2] > sortedim[i - 2][2]:
if i == files:
vert = np.vstack((vert, fgapy))
vert = np.vstack((vert, findat))
if i == files:
final = np.column_stack((final, vert))
else:
vert = np.vstack((vert, gapy))
vert = np.vstack((vert, findat))
if i == files:
final = np.column_stack((final, vert))
else:
findat = np.vstack((findat, gapy))
vert = np.vstack((findat, vert))
if i == files:
final = np.column_stack((final, vert))
else:
k = k + 1
if k == 1:
final = vert
vert = findat
else:
final = np.column_stack((final, vert))
vert = findat
else:
#1d#
for i in range(1, files + 1):
#data ranges#
dr = sortedim[i - 1][0].header['DATASEC']
colpos = dr.index(':')
endpos = dr.index(',')
drlow = ''.join(dr[1:colpos])
drlow = int(drlow)
drhigh = ''.join(dr[colpos + 1:endpos])
drhigh = int(drhigh)
imdata = sortedim[i - 1][0].data[:, drlow:drhigh]
gapxdim = np.size(imdata, 0)
gapx = np.zeros((gapxdim, 30))
gapx[:, :] = np.nan
#image flips#
df = sortedim[i - 1][0].header['DETSEC']
cpos = df.index(':')
epos = df.index(',')
dflow = ''.join(df[1:cpos])
dflow = int(dflow)
dfhigh = ''.join(df[cpos + 1:epos])
dfhigh = int(dfhigh)
ncpos = df.index(':', cpos + 1)
nepos = df.index(']')
yflow = ''.join(df[epos + 1:ncpos])
yflow = int(yflow)
yhigh = ''.join(df[ncpos + 1:nepos])
yhigh = int(yhigh)
if dflow > dfhigh:
findatx = np.fliplr(imdata)
else:
findatx = imdata
if yflow > yhigh:
findat = np.flipud(findatx)
else:
findat = findatx
#final image
if i == 1:
final = findat
else:
final = np.append(final, findat, axis=1)
if i != files and sortedim[i - 1][3] != sortedim[i][3]:
final = np.append(final, gapx, axis=1)
#finalimage#
#plt.imshow(final)
#plt.show()
#finalimage = fits.ImageHDU()
#finalimage.data = final
oldim = dp.create_blank_image(ra_deg,
dec_deg,
fov_deg,
px_scale,
rot_deg,
cdbase=cdbase,
logger=None)
finalimage = dp.make_image(final, oldim, {}, pfx='mosaic')
name = dp.get_image_name(finalimage)
self.fv.add_image(name, finalimage, chname='Mosaic')
def set_flat_cb(self, w):
# Current image is a flat field we should set
self.flat = self.fitsimage.get_image()
flatname = dp.get_image_name(self.flat, pfx='flat')
self.w.flat_image.set_text(flatname)
self.update_status("Set flat field.")
def set_bias_cb(self, w):
# Current image is a bias image we should set
self.bias = self.fitsimage.get_image()
biasname = dp.get_image_name(self.bias, pfx='bias')
self.w.bias_image.set_text(biasname)
self.update_status("Set bias image.")
def show_result(self, image):
chname = self.fv.get_channelName(self.fitsimage)
name = dp.get_image_name(image)
self.imglist.insert(0, image)
self.update_stack_gui()
self.fv.add_image(name, image, chname=chname)
