def object_plot(fitsfile, catalog):
image = f2n.fromfits(fitsfile, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
print('\033[1;34mPlotting sources on {0}...\033[0m'.format(catalog))
extension = os.path.splitext(os.path.basename(catalog))[1]
if extension == '.pysexcat':
coordinates = np.genfromtxt(catalog, delimiter=None,
comments='#')[:, [1, 2]]
elif extension == '.cnd':
coordinates = np.genfromtxt(catalog,
delimiter=',',
comments='#',
skip_header=1)[:, [1, 2]]
for i, coordinate in enumerate(coordinates):
x, y = coordinate[0], coordinate[1]
label = '{0}'.format(i + 1)
image.drawcircle(x, y, r=10, colour=(0, 255, 0), label=label)
image.writetitle(os.path.basename(fitsfile))
fitshead, fitsextension = os.path.splitext(fitsfile)
image.tonet('{0}.png'.format(fitshead))
print('\033[1;34mAll sources plotted on: {0}.png\033[0m'.format(fitshead))
return True
def fits2png(self, image_path):
"""
Source plot module.
@param image_data: data part of the FITS image
@type image_data: numpy array
@param ra: RA coordinate of object, skycoords.
@type ra: string
@param dec: DEC coordinate of object, skycoords.
@type dec: string
@param mark_color: Color of the plot marks
@type mark_color: str
@returns: boolean
"""
try:
import f2n
except ImportError:
print('Python cannot import f2n. Make sure f2n is installed.')
raise SystemExit
if image_path:
hdu = fits.open(image_path)[0]
else:
print("No image provided!")
raise SystemExit
image = f2n.fromfits(image_path, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
image.writetitle(os.path.basename(image_path))
fitshead, fitsextension = os.path.splitext(image_path)
image.tonet('{0}.png'.format(fitshead))
return True
def make_png(filename):
myimage = f2n.fromfits(filename)
myimage.makepilimage("log", negative = False)
try:
filepng = filename.replace('.fits','.png')
myimage.tonet(filepng)
except Exception, err:
print(str(err))
sys.exit(2)
def object_plot(self, image_path, ra, dec, mark_color="red"):
"""
Source plot module.
@param image_data: data part of the FITS image
@type image_data: numpy array
@param ra: RA coordinate of object, skycoords.
@type ra: string
@param dec: DEC coordinate of object, skycoords.
@type dec: string
@param mark_color: Color of the plot marks
@type mark_color: str
@returns: boolean
"""
try:
import f2n
except ImportError:
print('Python cannot import f2n. Make sure f2n is installed.')
raise SystemExit
if image_path:
hdu = fits.open(image_path)[0]
else:
print("No image provided!")
raise SystemExit
wcs = WCS(hdu.header)
# plot an ellipse for each object
if ":" not in (ra or dec):
co = coordinates.SkyCoord('{0} {1}'.format(ra, dec),
unit=(u.deg, u.deg),
frame='icrs')
else:
co = coordinates.SkyCoord('{0} {1}'.format(ra, dec),
unit=(u.hourangle, u.deg),
frame='icrs')
print('Target Coordinates:', co.to_string(style='hmsdms', sep=':'))
image = f2n.fromfits(image_path, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
ac = AstCalc()
x, y = ac.sky2xy(image_path, ra, dec)
label = '{0}'.format(co.to_string(style='hmsdms', sep=':'))
image.drawcircle(x, y, r=10, colour=(0, 255, 0), label=label)
image.writetitle(os.path.basename(image_path))
fitshead, fitsextension = os.path.splitext(image_path)
image.tonet('{0}.png'.format(fitshead))
print('\033[1;34mSource plotted on: {0}.png\033[0m'.format(fitshead))
return True
def pngGet(self,ra,dec,size,name=""):
if name=="":
name=str(ra)+"_"+str(dec)+"_x"+str(size)
url=self.ESOgetURL(ra,dec,size)
urllib.urlretrieve(url,name+'.fit')
myimage= f2n.fromfits(name+'.fit')
myimage.setzscale("auto")
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("log", negative = True)
# We can choose to make a negative image.
myimage.tonet(name+".png")
def fits2png(fitsfile,
outdir,
asteroid=None,
SPEED_MIN=float(config.get('asteroids', 'SPEED_MIN'))):
'''
Transforms FITS images into PNG files.
@param fitsfile: FITS file.
@type fitsfile: string
@param outdir: Output directory for the png files.
@type outdir: string
@param asteroid: numpy array for the moving objects.
@type asteroid: numpy.ndarray
@param SPEED_MIN: Minimum speed of a moving object.
@type SPEED_MIN: float
'''
try:
import f2n
except ImportError:
print('Python cannot import f2n. Make sure f2n is installed.')
raise SystemExit
image = f2n.fromfits(fitsfile, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
if asteroid.size:
for i in range(len(asteroid)):
x = asteroid.iloc[i]['x']
y = asteroid.iloc[i]['y']
speed = asteroid.iloc[i]['Speed(px/min)']
label = '{0}'.format(int(asteroid.iloc[i]['ObjectID']))
if speed >= SPEED_MIN:
color = (0, 255, 0)
else:
color = (255, 0, 0)
image.drawcircle(x, y, r=10, colour=color, label=label)
image.writetitle(os.path.basename(fitsfile))
fits_head = os.path.splitext(os.path.basename(fitsfile))[0]
hdu = fits.open(fitsfile)
obs_date = hdu[0].header['date-obs']
image.writeinfo([obs_date], colour=(255, 100, 0))
image.tonet(os.path.join(outdir, fits_head + '.png'))
def convert(image):
myimage = f2n.fromfits(image)
cContours = cv2.drawContour(img, [cnt],0,(255,0,0),-1 )
for cnt in cContours:
leftmost = tuple(cnt[cnt[:,:,0].argmin()][0])
rightmost = tuple(cnt[cnt[:,:,0].argmax()][0])
topmost = tuple(cnt[cnt[:,:,1].argmin()][0])
bottommost = tuple(cnt[cnt[:,:,1].argmax()][0])
print(leftmost, rightmost, topmost, bottommost)
myimage.setzscale()
myimage.makepilimage("log", negative = False)
myimage.tonet((imageName+".png"))
def fitsPNGs(self):
bining=int(cfg['rebin'])
self.png_dest=map(lambda x:cfg["dir_image_base"]+"/"+self.getToday()+"/"+cfg["dir_image_png"]+"/"+os.path.basename(x),self.pngs)
for i,fits in enumerate(self.solvefits):
print "Generating PNG from:",fits
myimage = f2n.fromfits(fits)
myimage.setzscale("auto")
myimage.rebin(bining,method="max")
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("log", negative = False)
# We can choose to make a negative image.
#myimage.writeinfo([fits,"DATE:"+self.dates[i]+" EXP="+str(self.exposures[i]),"TELE:"+self.telescopes[i]], colour=(255,100,0))
dir_dest=os.path.dirname(self.png_dest[i])
if not os.path.exists( dir_dest):
os.makedirs(dir_dest)
myimage.tonet(self.png_dest[i])
def fitsPNGs(self):
bining=int(cfg['rebin'])
self.png_dest=map(lambda x:cfg["dir_image_base"]+"/"+self.getToday()+"/"+cfg["dir_image_png"]+"/"+os.path.basename(x),self.pngs)
for i,fits in enumerate(self.solvefits):
print "Generating PNG from:",fits
myimage = f2n.fromfits(fits)
myimage.setzscale("auto")
myimage.rebin(bining,method="max")
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("log", negative = False)
# We can choose to make a negative image.
#myimage.writeinfo([fits,"DATE:"+self.dates[i]+" EXP="+str(self.exposures[i]),"TELE:"+self.telescopes[i]], colour=(255,100,0))
dir_dest=os.path.dirname(self.png_dest[i])
if not os.path.exists( dir_dest):
os.makedirs(dir_dest)
myimage.tonet(self.png_dest[i])
def pngGet(self,ra,dec,size,name=""):
try:
if name=="":
name=str(ra)+"_"+str(dec)+"_x"+str(size)
url=self.ESOgetURL(ra,dec,size)
print url
urllib.urlretrieve(url,name+'.fit')
myimage= f2n.fromfits(name+'.fit')
#myimage.setzscale("auto")
myimage.setzscale(z1="auto",z2="flat",samplesizelimit=10000,nsig=3)
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("lin", negative = False)
# We can choose to make a negative image.
myimage.tonet(name+".png")
except:
print "FAIL to get DSS image"
def catalog_plot(self, fitsfile, catalog):
try:
import f2n
except ImportError:
print('Python cannot import f2n. Make sure f2n is installed.')
raise SystemExit
image = f2n.fromfits(fitsfile, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
print('\033[1;34mPlotting sources on {0}...\033[0m'.format(catalog))
extension = os.path.splitext(os.path.basename(catalog))[1]
if extension == '.cat':
coordinates = np.genfromtxt(catalog, delimiter=None,
comments='#')[:, [1, 2]]
elif extension == '.txt':
coordinates = np.genfromtxt(catalog, delimiter=None,
comments='#')[:, [0, 1]]
elif extension == '.cnd':
coordinates = np.genfromtxt(catalog,
delimiter=',',
comments='#',
skip_header=1)[:, [1, 2]]
for i, coordinate in enumerate(coordinates):
x, y = coordinate[0], coordinate[1]
label = '{0}'.format(i + 1)
image.drawcircle(x, y, r=10, colour=(0, 255, 0), label=label)
image.writetitle(os.path.basename(fitsfile))
fitshead, fitsextension = os.path.splitext(fitsfile)
image.tonet('{0}.png'.format(fitshead))
print('\033[1;34mAll sources plotted on: {0}.png\033[0m'.format(
fitshead))
return True
def aperturesPNGs(self):
bining=int(cfg['rebin'])
self.apertures_dest=map(lambda x:cfg["dir_image_base"]+"/"+self.getToday()+"/"+cfg["dir_image_apertures"]+"/"+os.path.basename(x),self.pngsApertures)
for i,fits in enumerate(self.aperturesfiles):
print "Generating PNG from:",fits
try:
myimage = f2n.fromfits(fits)
except:
return
myimage.setzscale( z1=50,z2="auto")
myimage.rebin(bining,method="max")
#z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("log", negative = True)
# We can choose to make a negative image.
#myimage.writetitle(fits, colour=(200, 0, 0))
#myimage.writeinfo([fits,"DATE:"+self.dates[i]+" EXP="+str(self.exposures[i]),"TELE:"+self.telescopes[i]], colour=(255,100,0))
dir_dest=os.path.dirname(self.apertures_dest[i])
if not os.path.exists( dir_dest):
os.makedirs(dir_dest)
#myimage.pilimage=myimage.pilimage.convert("L")
myimage.tonet(self.apertures_dest[i])
def aperturesPNGs(self):
bining=int(cfg['rebin'])
self.apertures_dest=map(lambda x:cfg["dir_image_base"]+"/"+self.getToday()+"/"+cfg["dir_image_apertures"]+"/"+os.path.basename(x),self.pngsApertures)
for i,fits in enumerate(self.aperturesfiles):
print "Generating PNG from:",fits
try:
myimage = f2n.fromfits(fits)
except:
return
myimage.setzscale( z1=50,z2="auto")
myimage.rebin(bining,method="max")
#z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("log", negative = True)
# We can choose to make a negative image.
#myimage.writetitle(fits, colour=(200, 0, 0))
#myimage.writeinfo([fits,"DATE:"+self.dates[i]+" EXP="+str(self.exposures[i]),"TELE:"+self.telescopes[i]], colour=(255,100,0))
dir_dest=os.path.dirname(self.apertures_dest[i])
if not os.path.exists( dir_dest):
os.makedirs(dir_dest)
#myimage.pilimage=myimage.pilimage.convert("L")
myimage.tonet(self.apertures_dest[i])
def pngGet(self, ra, dec, size, name=""):
try:
if name == "":
name = str(ra) + "_" + str(dec) + "_x" + str(size)
url = self.ESOgetURL(ra, dec, size)
print url
urllib.urlretrieve(url, name + '.fit')
myimage = f2n.fromfits(name + '.fit')
#myimage.setzscale("auto")
myimage.setzscale(z1="auto",
z2="flat",
samplesizelimit=10000,
nsig=3)
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("lin", negative=False)
# We can choose to make a negative image.
myimage.tonet(name + ".png")
return True
except:
print "FAIL to get DSS image"
return False
def showstars(self, verbose=True):
"""
Uses f2n to write a png image with circled stars.
"""
try:
import f2n
except ImportError:
print "Couldn't import f2n -- install it !"
return
if verbose:
print "Writing png ..."
myimage = f2n.fromfits(self.filepath, verbose=False)
#myimage.rebin(int(myimage.xb/1000.0))
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative=False)
#myimage.upsample()
myimage.drawstarlist(self.starlist, r=8, autocolour="flux")
myimage.writetitle(os.path.basename(self.filepath))
#myimage.writeinfo(["This is a demo", "of some possibilities", "of f2n.py"], colour=(255,100,0))
if not os.path.isdir("alipy_visu"):
os.makedirs("alipy_visu")
myimage.tonet(os.path.join("alipy_visu", self.name + "_stars.png"))
def showstars(self, verbose=True):
"""
Uses f2n to write a png image with circled stars.
"""
try:
import f2n
except ImportError:
print "Couldn't import f2n -- install it !"
return
if verbose:
print "Writing png ..."
myimage = f2n.fromfits(self.filepath, verbose=False)
#myimage.rebin(int(myimage.xb/1000.0))
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative = False)
#myimage.upsample()
myimage.drawstarlist(self.starlist, r=8, autocolour="flux")
myimage.writetitle(os.path.basename(self.filepath))
#myimage.writeinfo(["This is a demo", "of some possibilities", "of f2n.py"], colour=(255,100,0))
if not os.path.isdir("alipy_visu"):
os.makedirs("alipy_visu")
myimage.tonet(os.path.join("alipy_visu", self.name + "_stars.png"))
def FitsCutToPng(inputfile, outputfile, x, y, a, s):
"""
convert fits file to png/jpg with assigned size
-inputfile the input fits file name including path
-outputfile the output png file name including path
-x coordinate x
-y coordinate y
-a border of the square picture around (x, y)
-s the string under the circled star
"""
if (x < 0 or x > 3056 or y < 0 or y > 3056 or a < 0 or a > 3056):
print "x or y or a is out of border, please check!"
return
# if(x-a<0 or x+a>3056 or y-a<0 or y+a>3056):
# print "x-a or x+a or y-a or y+a is out of border, please check!"
if x - a < 0:
left = 0
p = a - x
else:
left = x - a
p = 0
if x + a > 3056:
right = 3056
else:
right = x + a
if y - a < 0:
top = 0
q = y
else:
top = y - a
q = a
if y + a > 3056:
bottom = 3056
q = a - (3056 - y)
else:
bottom = y + a
q = 0
# print "-----"
# print p
# print q
# print len(sys.argv)
# print "-----"
tmpImage = f2n.fromfits(inputfile)
tmpImage.crop(left, right, top, bottom)
tmpImage.setzscale("auto", "flat", 3, 100000, 300)
#tmpImage.setzscale("flat", "flat", 2, 100000, 300, 65000)
tmpImage.makepilimage("lin", negative=False)
if s != "":
#tmpImage.drawcircle(x, y, 3, (0,255,0), s)
#modified by xlp at 20150206
tmpImage.drawcircle(x, y, 5, (0, 255, 0), None)
tmpImage.tonet("tmp.png")
# tmpImage.pilimage.save("tmp", "FIT")
fgImg = Image.open("tmp.png")
bgImg = Image.new("RGB", (2 * a, 2 * a), (100, 100, 100))
bgImg.paste(fgImg, (p, q))
bgImg.save(outputfile, "JPEG")
os.system("rm tmp.png")
plotskim.append("""
<area shape="rect" COORDS="%i,%i,%i,%i" href="" onClick="return false" onmouseover="plotskim.src='%s';" alt="">
""" % (xmin, ymin, xmax, ymax, pngimage))
plotskim.append("</map>")
filldict["zoomplot"] = "".join(plotskim)
filldict["overviewplot"] = '<img src="overview.png" class="imgmargin">'
##########################################
# PREPARING THE FITS IMAGES
##########################################
# Deconvolution images :
f2ng = f2n.fromfits(os.path.join(decdir,
"g" + image[deckeyfilenum] + ".fits"),
verbose=False)
f2ng.setzscale(-30.0, "ex")
f2ng.makepilimage(scale="log", negative=False)
f2ng.upsample(4)
f2ng.drawstarlist(objcosmicslist)
f2ng.writetitle("Object")
f2ng.tonet(os.path.join(destdir, "g.png"))
f2nresi = f2n.fromfits(os.path.join(
decdir, "resi" + image[deckeyfilenum] + ".fits"),
verbose=False)
f2nresi.setzscale(-30, +30)
f2nresi.makepilimage(scale="lin", negative=True)
f2nresi.upsample(2)
f2nresi.writetitle("Residues", colour=(255))
def FitsCutToPng(inputfile, outputfile, x, y, a, s):
"""
convert fits file to png/jpg with assigned size
usage: inputfile outputfile x y border string
-inputfile the input fits file name including path
-outputfile the output png file name including path
-x coordinate x
-y coordinate y
-a border of the square picture around (x, y)
-s the string under the circled star
"""
if(x<0 or x>3056 or y<0 or y>3056 or a<0 or a>3056):
print "x or y or a is out of border, please check!"
return
# if(x-a<0 or x+a>3056 or y-a<0 or y+a>3056):
# print "x-a or x+a or y-a or y+a is out of border, please check!"
if x-a<0:
left=0
p=a-x
else:
left=x-a
p=0
if x+a>3056:
right=3056
else:
right=x+a
if y-a<0:
top=0
q=y
else:
top=y-a
q=a
if y+a>3056:
bottom=3056
q=a-(3056-y)
else:
bottom=y+a
q=0
# print "-----"
# print p
# print q
# print len(sys.argv)
# print "-----"
# open input file
tmpImage = f2n.fromfits(inputfile)
tmpImage.crop(left, right, top, bottom)
tmpImage.setzscale("auto", "flat", 3, 100000, 300, 65000)
tmpImage.makepilimage("lin", negative = False)
if s!="":
tmpImage.drawcircle(x, y, 5, (0,255,0), s)
if x==1528 and y==1528 and a==1528:
Info = inputfile
tmpImage.writeinfo([Info], colour=(255,0,0))
tmpImage.tonet("tmp.png")
# convert png to jpg
fgImg=Image.open("tmp.png")
bgImg=Image.new("RGB", (2*a, 2*a), (100,100,100))
bgImg.paste(fgImg,(p,q))
bgImg.save(outputfile, "JPEG")
os.system("rm tmp.png")
# The following two lines are only needed if f2n.py and f2n_fonts
# are not yet copied somewhere into your usual python path !
import sys
sys.path.append("../.") # The directory that contains f2n.py and f2n_fonts !
import f2n
import copy
myimage = f2n.fromfits("example.fits")
mylargeimage = copy.deepcopy(myimage)
myimage.crop(70, 170, 60, 160)
myimage.setzscale("auto", "ex")
linimage = copy.deepcopy(myimage)
logimage = copy.deepcopy(myimage)
linimage.makepilimage("lin", negative = False)
logimage.makepilimage("log", negative = False)
linimage.upsample(2)
linimage.writetitle("lin")
linimage.drawcircle(112, 101, r=15)
logimage.upsample(2)
logimage.writetitle("log")
mylargeimage.crop(30, 230, 60, 160)
print "- " * 30
print i + 1, image['imgname']
toreport = str(image['imgname']) + '\t' + str(i + 1)
report.write(toreport)
imgpsfdir = os.path.join(psfdir, image['imgname'])
resultsdir = os.path.join(imgpsfdir, "results")
pngpath = os.path.join(pngdir, image['imgname'] + ".png")
blank256 = f2n.f2nimage(shape=(256, 256), fill=0.0, verbose=False)
blank256.setzscale(0.0, 1.0)
blank256.makepilimage(scale="lin", negative=False)
totpsfimg = f2n.fromfits(os.path.join(resultsdir, "psf_1.fits"),
verbose=False)
#totpsfimg.rebin(2)
totpsfimg.setzscale(1.0e-7, 1.0e-3)
totpsfimg.makepilimage(scale="log", negative=False)
totpsfimg.upsample(2)
totpsfimg.writetitle("Total PSF")
numpsfimg = f2n.fromfits(os.path.join(resultsdir, "psf_num_1.fits"),
verbose=False)
numpsfimg.setzscale(-0.02, 0.02)
numpsfimg.makepilimage(scale="lin", negative=False)
numpsfimg.upsample(2)
numpsfimg.writetitle("Numerical PSF")
txtendpiece = f2n.f2nimage(shape=(256, 256), fill=0.0, verbose=False)
txtendpiece.setzscale(0.0, 1.0)
plotskim.append("""
<area shape="rect" COORDS="%i,%i,%i,%i" href="" onClick="return false" onmouseover="plotskim.src='%s';" alt="">
""" % (xmin, ymin, xmax, ymax, pngimage))
plotskim.append("</map>")
filldict["zoomplot"] = "".join(plotskim)
filldict["overviewplot"] = '<img src="overview.png" class="imgmargin">'
##########################################
# PREPARING THE FITS IMAGES
##########################################
# Deconvolution images :
f2ng = f2n.fromfits(os.path.join(decdir, "g" +image[deckeyfilenum]+".fits"), verbose=False)
f2ng.setzscale(-50, "ex")
f2ng.makepilimage(scale = "log", negative = False)
f2ng.upsample(4)
f2ng.drawstarlist(objcosmicslist)
f2ng.writetitle("Object")
f2ng.tonet(os.path.join(destdir, "g.png"))
f2nresi = f2n.fromfits(os.path.join(decdir, "resi" +image[deckeyfilenum]+".fits"), verbose=False)
f2nresi.setzscale(-10, 10)
f2nresi.makepilimage(scale = "lin", negative = False)
f2nresi.upsample(2)
f2nresi.writetitle("Residues")
f2nresi.tonet(os.path.join(destdir, "resi.png"))
momentsml.tools.table.addstats(cat, "snr")
momentsml.tools.io.writepickle(cat, catpath)
print momentsml.tools.table.info(cat)
writecat = cat["tru_flux", "snr_mean"]
print writecat
writecat.write(writecatpath, format="ascii")
if name == "shearw":
momentsml.tools.io.writepickle(cat, catpath)
print momentsml.tools.table.info(cat)
writecat = cat["x", "y", "snr"]
print writecat
writecat.write(writecatpath, format="ascii")
for icas in range(ncas):
myimage = f2n.fromfits(fitsimgpath)
myimage.crop(0, stampsize * nrea, icas * stampsize, (icas + 1) * stampsize)
#myimage.setzscale(-0.1, 3)
#myimage.makepilimage("log", negative = False)
myimage.setzscale(-0.3, 1.0)
myimage.makepilimage("lin", negative=False)
myimage.upsample(5)
pngimgpath = os.path.join(workdir, "case_{}.png".format(icas))
myimage.tonet(pngimgpath)
subprocess.Popen("display {}".format(pngimgpath), shell=True)
def irafalign(filepath,
uknstarlist,
refstarlist,
shape,
alifilepath=None,
outdir="alipy_out",
makepng=False,
hdu=0,
verbose=True):
"""
Uses iraf geomap and gregister to align the image. Three steps :
* Write the matched source lists into an input file for geomap
* Compute a geomap transform from these stars.
* Run gregister
:param filepath: FITS file to be aligned
:type filepath: string
:param uknstarlist: A list of stars from the "unknown" image to be aligned,
that matches to ...
:type uknstarlist: list of Star objects
:param refstarlist: ... the list of corresponding stars in the reference
image.
:type refstarlist: list of Star objects
:param shape: Output shape (width, height)
:type shape: tuple
:param alifilepath: where to save the aligned image. If None, I put it in
the default directory.
:type alifilepath: string
:param makepng: If True I make a png of the aligned image as well.
:type makepng: boolean
:param hdu: The hdu of the fits file that you want me to use.
0 is primary. If multihdu, 1 is usually science.
"""
try:
from pyraf import iraf
except ImportError:
print("Couldn't import pyraf !")
return
assert len(uknstarlist) == len(refstarlist)
if len(uknstarlist) < 2:
if verbose:
print("Not enough stars for using geomap !")
return
basename = os.path.splitext(os.path.basename(filepath))[0]
geomapinpath = basename + ".geomapin"
geodatabasepath = basename + ".geodatabase"
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
# Step 1, we write the geomap input.
table = []
for (uknstar, refstar) in zip(uknstarlist, refstarlist):
table.append([refstar.x, refstar.y, uknstar.x, uknstar.y])
geomap = open(geomapinpath, "w")
writer = csv.writer(geomap, delimiter="\t")
writer.writerows(table)
geomap.close()
# Step 2, geomap
iraf.unlearn(iraf.geomap)
iraf.geomap.fitgeom = "rscale"
# You can change this to:
# shift, xyscale, rotate, rscale
iraf.geomap.function = "polynomial" # Surface type
iraf.geomap.maxiter = 3 # Maximum number of rejection iterations
iraf.geomap.reject = 3.0 # Rejection limit in sigma units
# other options you could specify :
# (xxorder= 2) Order of x fit in x
# (xyorder= 2) Order of x fit in y
# (xxterms= half) X fit cross terms type
# (yxorder= 2) Order of y fit in x
# (yyorder= 2) Order of y fit in y
# (yxterms= half) Y fit cross terms type
# (calctyp= real) Computation type
iraf.geomap.transfo = "broccoli" # keep it
iraf.geomap.interac = "no" # keep it
iraf.geomap.verbose = "yes" # keep it
# iraf.geomap.results = "bla.summary" # The optional results summary files
geomapblabla = iraf.geomap(input=geomapinpath,
database=geodatabasepath,
xmin=1,
xmax=shape[0],
ymin=1,
ymax=shape[1],
Stdout=1)
# We read this output ...
for line in geomapblabla:
if "X and Y scale:" in line:
mapscale = line.split()[4:6]
if "Xin and Yin fit rms:" in line:
maprmss = line.split()[-2:]
if "X and Y axis rotation:" in line:
mapangles = line.split()[-4:-2]
if "X and Y shift:" in line:
mapshifts = line.split()[-4:-2]
# not used?
geomaprms = math.sqrt(
float(maprmss[0]) * float(maprmss[0]) +
float(maprmss[1]) * float(maprmss[1]))
geomapangle = float(mapangles[0]) # % 360.0
geomapscale = 1.0 / float(mapscale[0])
if mapscale[0] != mapscale[1]:
raise RuntimeError("Error reading geomap scale")
if verbose:
print(("IRAF geomap : Rotation %+11.6f [deg], "
"scale %8.6f, RMS %.3f [pixel]") %
(geomapangle, geomapscale, geomaprms))
# Step 3
if alifilepath is None:
alifilepath = os.path.join(outdir, basename + "_gregister.fits")
else:
outdir = os.path.split(alifilepath)[0]
if not os.path.isdir(outdir):
os.makedirs(outdir)
if os.path.isfile(alifilepath):
os.remove(alifilepath)
iraf.unlearn(iraf.gregister)
iraf.gregister.geometry = "geometric" # linear, distortion, geometric
iraf.gregister.interpo = "spline3" # linear, spline3
iraf.gregister.boundary = "constant" # padding with zero
iraf.gregister.constant = 0.0
iraf.gregister.fluxconserve = "yes"
if verbose:
print("IRAF gregister ...")
regblabla = iraf.gregister(input='%s[%s]' % (filepath, hdu),
output=alifilepath,
database=geodatabasepath,
transform="broccoli",
Stdout=1)
# not used?
if verbose:
print("IRAF gregister done !")
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
if makepng:
try:
import f2n
except ImportError:
print("Couldn't import f2n -- install it !")
return
myimage = f2n.fromfits(alifilepath, verbose=False)
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative=False)
myimage.writetitle(os.path.basename(alifilepath))
if not os.path.isdir(outdir):
os.makedirs(outdir)
myimage.tonet(
os.path.join(outdir,
os.path.basename(alifilepath) + ".png"))
#images = db.select(imgdb, ['gogogo', 'ell'], [True, ">0.65"], returnType='dict', sortFields=['mjd'])
#images = db.select(imgdb, ['recno'], ['*'], returnType='dict', sortFields=['mjd'])
print "I will treat", len(images), "images."
proquest(askquestions)
starttime = datetime.now()
for i, image in enumerate(images):
print "- " * 40
print i + 1, "/", len(images), ":", image['imgname']
fitsfile = image['rawimg']
f2nimg = f2n.fromfits(fitsfile)
if crop:
f2nimg.irafcrop(cropregion)
f2nimg.setzscale(z1, z2)
f2nimg.rebin(rebin)
f2nimg.makepilimage(scale="log", negative=False)
f2nimg.writetitle(image['imgname'])
date = image['datet']
seeing = "Seeing : %4.2f" % image['seeing']
ell = "Ellipticity : %4.2f" % image['ell']
skylevel = "Sky level : %4.2f" % image['skylevel']
stddev = "Preali sky stddev : %4.2f" % image['prealistddev']
airmass = "Airmass : %4.2f" % image['airmass']
az = "Azimuth : %6.2f" % image['az']
# If cosmics are detected, we want to know where :
cosmicslistpath = os.path.join(objdir, image['imgname'], "cosmicslist.pkl")
if os.path.exists(cosmicslistpath):
cosmicslist = readpickle(cosmicslistpath, verbose=False)
else:
cosmicslist = []
# And there number :
ncosmics = "Cosmics : %i" % image[objcosmicskey]
gpath = os.path.join(objdir, image['imgname'], "g.fits")
sigpath = os.path.join(objdir, image['imgname'], "sig.fits")
# First we build the image for g :
g = f2n.fromfits(gpath, verbose=False)
g.setzscale(z1, z2)
g.makepilimage(scale = "log", negative = False)
g.upsample(4)
g.drawstarlist(cosmicslist)
g.writetitle("g.fits")
# We write long image names on two lines ...
if len(image['imgname']) > 25:
infolist = [image['imgname'][0:25], image['imgname'][25:]]
else:
infolist = [image['imgname']]
g.writeinfo(infolist)
# And now for sig :
errmsg = ''
for i,image in enumerate(images):
try:
print "+ " * 30
print "%5i/%i : %s" % (i+1, nbrimages, image["imgname"])
pngpath = os.path.join(pngdirpath, "%s_sky.png" % image['imgname'])
if os.path.isfile(pngpath) and not redofromscratch:
print "File exists, I skip..."
continue
skyimagepath = os.path.join(alidir, image["imgname"] + "_sky.fits")
skysubimagepath = os.path.join(alidir, image["imgname"] + "_skysub.fits")
skyimage = f2n.fromfits(skyimagepath)
skyimage.setzscale("ex", "ex")
skyimage.rebin(3)
skyimage.makepilimage(scale = "lin", negative = False)
skyimage.upsample(2)
skyimage.writetitle("Sky", colour=(255, 0, 0))
skysubimage = f2n.fromfits(skysubimagepath)
skysubimage.setzscale("auto", "auto")
skysubimage.rebin(3)
skysubimage.makepilimage(scale = "log", negative = False)
skysubimage.upsample(2)
skysubimage.writetitle("Skysubtracted image")
# We read the 20 strongest stars from sextractor :
sexcatpath = os.path.join(alidir, image['imgname'] + ".cat")
import f2n
myimage = f2n.fromfits("20131203_m06-0848+50_1053.fit")
# We crop the FITS image (xmin, xmax, ymin, ymax).
myimage.crop(70, 170, 60, 160)
# The image is now 100 x 100 pixels.
myimage.setzscale(4500, "ex")
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("lin", negative = False)
# We can choose to make a negative image.
myimage.showcutoffs(redblue = True)
# Pixels below z1 will be blue, above z2 will be red.
# We upsample (= "zoom" without interpolation) the pixels.
myimage.upsample(5)
# The image is now 500 x 500
# We draw some labels and circles.
# myimage.drawstarsfile("stars.cat", r=3, colour=(255, 0,0))
# Note that all the coordinates are those from the original image !
# Of course, the function drawstars allows you to the same
# without any catalog file.
# Same for drawing a rectangle...
myimage.drawrectangle(118, 149, 137, 155, colour=(0,255,0), label="Empty region")
myimage.writetitle("Hello World !", colour=(200, 200, 0))
myimage.writeinfo(["This is a demo", "of some possibilities",
cosmicslistpath = os.path.join(workdir, objkey, image['imgname'],
"cosmicslist.pkl")
if os.path.exists(cosmicslistpath):
cosmicslist = readpickle(cosmicslistpath, verbose=False)
else:
cosmicslist = []
# To get the number of cosmics is easier ...
objcosmicskey = objkey + "_cosmics" # objkey is redefined up there...
ncosmics = image[objcosmicskey]
pngpath = os.path.join(pngdir, image['imgname'] + ".png")
if deconvonly:
f2ndec = f2n.fromfits(os.path.join(decdir, "dec" + code + ".fits"),
verbose=False)
f2ndec.setzscale(-20, "auto")
f2ndec.makepilimage(scale="exp", negative=False)
f2ndec.upsample(8)
#f2ndec.writeinfo(["Deconvolution"])
decpngpath = os.path.join(pngdir, image['imgname'] + "_deconly.png")
f2n.compose([[f2ndec]], pngpath)
continue
#else...
f2ndec = f2n.fromfits(os.path.join(decdir, "dec" + code + ".fits"),
verbose=False)
f2ndec.setzscale(-20, "auto")
f2ndec.makepilimage(scale="log", negative=False)
f2ndec.upsample(2)
def run_fits2png(input):
image = f2n.fromfits(input[0]) #colour=( The way to read a FITS file.
image.setzscale() # By default, automatic cutoffs will be calculated.
makepilimage(image) # linear scale
# image.writetitle(input[0], colour=(0,50,250))
image.tonet(input[1]) # write the png file
# The following two lines are only needed if f2n.py and f2n_fonts
# are not yet copied somewhere into your usual python path !
import sys
sys.path.append("../.") # The directory that contains f2n.py and f2n_fonts !
import f2n
myimage = f2n.fromfits("example.fits")
# We crop the FITS image (xmin, xmax, ymin, ymax).
myimage.crop(70, 170, 60, 160)
# The image is now 100 x 100 pixels.
myimage.setzscale(4500, "ex")
# z2 = "ex" means extrema -> maximum in this case.
myimage.makepilimage("lin", negative=False)
# We can choose to make a negative image.
myimage.showcutoffs(redblue=True)
# Pixels below z1 will be blue, above z2 will be red.
# We upsample (= "zoom" without interpolation) the pixels.
myimage.upsample(5)
# The image is now 500 x 500
# We draw some labels and circles.
myimage.drawstarfile("stars.cat", r=3, colour=(255, 0, 0))
# Note that all the coordinates are those from the original image !
# Of course, the function drawstars allows you to the same
# without any catalog file.
preciserefmanstarsasdicts = [{
"name": s.name,
"x": s.x,
"y": s.y
} for s in preciserefmanstars]
refautostarsasdicts = [{
"name": s.name,
"x": s.x,
"y": s.y
} for s in refautostars]
#print refmanstarsasdicts
combifitsfile = os.path.join(workdir, "%s.fits" % combibestkey)
#combifitsfile = os.path.join(workdir, "ali", "%s_ali.fits" % refimgname)
f2nimg = f2n.fromfits(combifitsfile)
f2nimg.setzscale(z1=-5, z2=1000)
#f2nimg.rebin(2)
f2nimg.makepilimage(scale="log", negative=False)
#f2nimg.drawstarlist(refautostarsasdicts, r = 30, colour = (150, 150, 150))
#f2nimg.drawstarlist(preciserefmanstarsasdicts, r = 7, colour = (255, 0, 0))
#f2nimg.writeinfo(["Sextractor stars (flag-filtered) : %i" % len(refautostarsasdicts)], colour = (150, 150, 150))
#f2nimg.writeinfo(["","Identified alignment stars with corrected sextractor coordinates : %i" % len(preciserefmanstarsasdicts)], colour = (255, 0, 0))
# We draw the rectangles around qso and empty region :
lims = [map(int, x.split(':')) for x in lensregion[1:-1].split(',')]
#f2nimg.drawrectangle(lims[0][0], lims[0][1], lims[1][0], lims[1][1], colour=(0,255,0), label = "Lens")
# usage: read_fits file.fits file.png
import sys
sys.path.append("/data/wwwhelio/html/gui/f2n") # The directory that contains f2n.py and f2n_fonts !
sys.path.append("/usr/local/www/apache22/data/hfc-gui/f2n") # The directory that contains f2n.py and f2n_fonts !
import pyfits,numpy,f2n
import Image,ImageOps,ImageDraw
# Converts the FITS file to PNG
#if 'efz' in sys.argv[1] :
# data = pyfits.getdata(sys.argv[1])
# im = Image.fromarray(numpy.uint8(data))
# im = im.transpose(Image.FLIP_TOP_BOTTOM)
# im.save(sys.argv[2])
#else :
myimage = f2n.fromfits(sys.argv[1])
myimage.setzscale("ex", "ex")
myimage.makepilimage("lin")
myimage.tonet(sys.argv[2])
# Get the P_ANGLE value from the FITS header
hdulist = pyfits.open(sys.argv[1])
hd = hdulist[0].header
if hd.has_key('p_angle') :
angle = hdulist[0].header['p_angle']
# Rotate the PNG file from P_ANGLE
if angle != 0 :
im = Image.open(sys.argv[2])
im_rot = im.rotate(angle)
im_rot.save(sys.argv[2])
# Get the SC_ROLL value from the FITS header
# and diff with ignored folders
dirs_to_parse = source_dirs.difference(ignore_folders)
print dirs_to_parse
print ignore_folders
print source_dirs
# go through new folders
for dir in dirs_to_parse:
for fits_object in fits_parser.index_directory_of_fits_files(
os.path.join(args.fits[0], dir), completed)['files']:
out_stem = os.path.join(args.fits[1], 'images',
str(fits_object['epoch']))
# json dump
with open(out_stem + '.json', 'w') as file:
json.dump(fits_object, file)
# convert and dump image
myimage = f2n.fromfits(fits_object['path'])
myimage.setzscale()
myimage.makepilimage('lin')
print "------"
myimage.tonet(out_stem + '.png')
# add path to completed list
completed.append(str(fits_object['path']))
with open(completed_path, "w+") as file:
json.dump(completed, file)
# refresh index of out dir
with open(os.path.join(args.fits[1], 'images', 'index.json'), 'w') as file:
json.dump([
f.replace('.json', '')
for f in os.listdir(os.path.join(args.fits[1], 'images'))
if f.endswith('json') and not f == 'ignore_folders.json'
and not f == 'index.json'
def loadImageFromFits(self,fits): self.fitsToCrop = f2n.fromfits(fits)
def asteroids_phot(self,
image_path,
multi_object=True,
target=None,
aper_radius=None,
plot_aper_test=False,
radius=11,
exposure=None,
sqlite_file=None,
table_name="asteroids",
gain=0.57,
max_mag=20,
comp_snr=50):
"""
Photometry of asteroids.
@param image_path: Path of FITS file.
@type image_path: path
@param multi_object: Apply photometry for other asteroids in the frame?
@type multi_object: float
@param target: Target object that photometry applied. If None,
will be taken form FITS header.
@type target: float
@param radius: Aperture radius
@type radius: float
@param exposure: Exposure keyword of phot images.
@type exposure: float
@param plot_aper_test: Plot aperture test graph
@type plot_aper_test: bloean
@param exportdb: Export results SQLite3 database
@type exportdb: path
@param db_table: SQLite3 database table
@type db_table: path
@param gain: gain value for the image expressed in electrons per adu.
@type gain: float
@param max_mag: Faintest object limit.
@type max_mag: float
@param comp_snr: Minimum SNR of detected comparison star.
@type comp_snr: float
@return: bolean and file
"""
if ".fit" in os.path.basename(image_path):
fitslist = sorted(glob.glob(image_path))
if fitslist == 0:
print('No image FITS found in the {0}'.format(image_path))
raise SystemExit
else:
fitslist = sorted(glob.glob(image_path + '/*.fit?'))
if fitslist == 0:
print('No image FITS found in the {0}'.format(image_path))
raise SystemExit
# aper_trigger check count
aper_count = 0
for id, fitsfile in enumerate(fitslist):
if fitsfile:
hdu = fits.open(fitsfile)[0]
else:
print("FITS image has not been provided by the user!")
raise SystemExit
sb = Query()
ac = AstCalc()
to = TimeOps()
fo = FitsOps(fitsfile)
header = hdu.header
w = WCS(header)
naxis1 = fo.get_header('naxis1')
naxis2 = fo.get_header('naxis2')
odate = fo.get_header('date-obs')
t1 = Time("{0}".format(odate), out_subfmt="date")
dt = TimeDelta(12 * 3600, format='sec')
onight = t1 - dt
exptime = fo.get_header('exptime')
if exptime is not None and exposure is not None:
if float(exptime) != exposure:
continue
if aper_count == 0:
aper_trigger = id
aper_count += 1
if target is None:
objct = fo.get_header('object')
else:
objct = str(target)
filter = fo.get_header('filter').replace(" ", "_")
# t1 = Time(odate.replace('T', ' '))
# exptime = fo.get_header('exptime')
# dt = TimeDelta(exptime / 2.0, format='sec')
# odate_middle = t1 + dt
# jd = to.date2jd(odate_middle.value)
jd = to.date2jd(odate)
ra_dec = ac.center_finder(fitsfile, wcs_ref=True)
image = f2n.fromfits(fitsfile, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
request = sb.find_skybot_objects(odate,
ra_dec[0].degree,
ra_dec[1].degree,
radius=radius)
if request[0]:
if multi_object:
asteroids = Table(np.sort(request[1][::-1], order=['m_v']))
else:
asteroids = Table(np.sort(request[1], order=['num']))
mask = asteroids['num'] == str(objct).upper()
asteroids = asteroids[mask]
elif request[0] is False:
print(request[1])
raise SystemExit
data = hdu.data.astype(float)
bkg = sep.Background(data)
data_sub = data - bkg
for i in range(len(asteroids)):
if float(asteroids['m_v'][i]) <= max_mag:
c = coordinates.SkyCoord('{0} {1}'.format(
asteroids['ra(h)'][i], asteroids['dec(deg)'][i]),
unit=(u.hourangle, u.deg),
frame='icrs')
# asteroid's X and Y coor
a_x, a_y = w.wcs_world2pix(c.ra.degree, c.dec.degree, 1)
if naxis1 < a_x or naxis2 < a_y or a_x < 0 or a_y < 0:
continue
# phot asteroids
flux, fluxerr, flag = sep.sum_circle(data_sub,
a_x,
a_y,
6,
err=bkg.globalrms,
gain=gain)
if flux == 0.0 or fluxerr == 0.0:
print("Bad asteroid selected (out of frame!)!")
raise SystemExit
if id == aper_trigger:
snr = []
for aper in range(30):
# phot asteroids
flux_test, fluxerr_test, flag_test = sep.sum_circle(
data_sub,
a_x,
a_y,
aper,
err=bkg.globalrms,
gain=gain)
snr.append([aper, (flux_test / fluxerr_test)])
npsnr = np.array(snr)
maxtab, mintab = peakdet(npsnr[:, 1], 0.1)
try:
aper_radius = maxtab[:, 0][0]
print("Aperture calculated: {0} px".format(
aper_radius))
except IndexError:
continue
if plot_aper_test:
plt.title(asteroids['num'][i])
plt.xlabel('Aperture (px)')
plt.ylabel('SNR')
plt.scatter(npsnr[:, 0], npsnr[:, 1])
plt.scatter(maxtab[:, 0],
maxtab[:, 1],
color='red')
plt.scatter(mintab[:, 0],
mintab[:, 1],
color='yellow')
plt.show()
magt_i = ac.flux2mag(flux, float(exptime))
magt_i_err = fluxerr / flux * 2.5 / math.log(10)
min_mag_ast = float(asteroids['m_v'][i]) - 2
label = '{0}'.format(asteroids['num'][i])
image.drawcircle(a_x,
a_y,
r=aper_radius,
colour=(255, 0, 0),
label=label)
if i == 0 and id == aper_trigger:
comptable = sb.query_color(c.ra.degree,
c.dec.degree,
5.0 / 60.0,
min_mag=min_mag_ast,
max_mag=19.5)
s_comptable = sb.sort_stars(comptable, min_mag_ast)
if len(s_comptable) == 0:
continue
phot_res_list = []
# phot comp. stars
for j in range(len(s_comptable)):
# star's X and Y coor
s_x, s_y = w.wcs_world2pix(s_comptable['RAJ2000'][j],
s_comptable['DEJ2000'][j],
1)
if naxis1 < s_x or naxis2 < s_y or s_x < 0 or s_y < 0:
continue
# print('Circle', s_x, s_y, 10)
flux, fluxerr, flag = sep.sum_circle(data_sub,
s_x,
s_y,
aper_radius,
err=bkg.globalrms,
gain=gain)
if flux == 0.0 or fluxerr == 0.0:
print("Bad star selected!")
raise SystemExit
if (flux / fluxerr) <= comp_snr:
continue
magc_i = ac.flux2mag(flux, float(exptime))
magc_i_err = fluxerr / flux * 2.5 / math.log(10)
try:
magt = (float(magt_i) -
float(magc_i)) + s_comptable['Rmag'][j]
magt_err = math.sqrt(
math.pow(float(magt_i_err), 2) +
math.pow(float(magc_i_err), 2))
except:
continue
label = '{0}'.format(s_comptable['NOMAD1'][j])
image.drawcircle(s_x,
s_y,
r=aper_radius,
colour=(0, 255, 0),
label=label)
phot_res_list.append([
asteroids['num'][i], jd, onight.iso,
float(magt_i),
float(magt_i_err),
float(magc_i),
float(magc_i_err),
float(magt),
float(magt_err), asteroids['m_v'][i],
s_comptable['NOMAD1'][j], s_comptable['Rmag'][j]
])
np_phot_res = np.array(phot_res_list)
if len(np_phot_res) == 0:
continue
# magnitude average
magt_avr = np.average(np_phot_res[:, 7].astype(float),
weights=np_phot_res[:,
8].astype(float))
# magt_std calc.
magt_std = np.std(np_phot_res[:, 7].astype(float))
np_magt_avr_std = [[magt_avr, magt_std, filter, exptime]
for i in range(len(np_phot_res))]
k = np.array(np_magt_avr_std).reshape(
len(np_magt_avr_std), 4)
# numpy array with magt_avr
np_phot_res_avg_std = np.concatenate((np_phot_res, k),
axis=1)
phot_res_table = Table(
np_phot_res_avg_std,
names=('ast_num', 'jd', 'onight', 'magt_i',
'magt_i_err', 'magc_i', 'magc_i_err', 'magt',
'magt_err', 'ast_mag_cat', 'nomad1',
'star_Rmag', 'magt_avr', 'magt_std', 'filter',
'exposure'),
dtype=('U10', 'S25', 'U10', 'f8', 'f8', 'f8', 'f8',
'f8', 'f8', 'f8', 'U20', 'f8', 'f8', 'f8',
'U20', 'f8'))
phot_res_table['magt_i'].format = '.3f'
phot_res_table['magt_i_err'].format = '.3f'
phot_res_table['magc_i'].format = '.3f'
phot_res_table['magc_i_err'].format = '.3f'
phot_res_table['magt'].format = '.3f'
phot_res_table['magt_err'].format = '.3f'
phot_res_table['magt_avr'].format = '.3f'
phot_res_table['magt_std'].format = '.3f'
with open(
'{0}/{1}.txt'.format(os.getcwd(),
asteroids['num'][i]),
'a') as f_handle:
f_handle.seek(0, os.SEEK_END)
if not os.path.isfile(str(f_handle)):
phot_res_table.write(
f_handle, format='ascii.commented_header')
else:
phot_res_table.write(f_handle,
format='ascii.no_header')
if sqlite_file is not None:
self.table_to_database(phot_res_table,
sqlite_file=sqlite_file,
table_name=table_name)
# Test
time.sleep(0.2)
self.update_progress(
"Photometry is done for: {0}".format(fitsfile),
id / len(fitslist))
image.writetitle(os.path.basename(fitsfile))
fitshead, fitsextension = os.path.splitext(fitsfile)
image.writeinfo([odate], colour=(255, 100, 0))
image.tonet('{0}.png'.format(fitshead))
self.update_progress("Photometry done!", 1)
return (True)
def asteroids_phot(self, image_path,
multi_object=True,
target=None,
aper_radius=None,
plot_aper_test=False,
radius=11,
exposure=None,
sqlite_file=None,
table_name="asteroids",
gain=0.57,
max_mag=20,
comp_snr=50):
"""
Photometry of asteroids.
@param image_path: Path of FITS file.
@type image_path: path
@param multi_object: Apply photometry for other asteroids in the frame?
@type multi_object: float
@param target: Target object that photometry applied. If None,
will be taken form FITS header.
@type target: float
@param radius: Aperture radius
@type radius: float
@param exposure: Exposure keyword of phot images.
@type exposure: float
@param plot_aper_test: Plot aperture test graph
@type plot_aper_test: bloean
@param exportdb: Export results SQLite3 database
@type exportdb: path
@param db_table: SQLite3 database table
@type db_table: path
@param gain: gain value for the image expressed in electrons per adu.
@type gain: float
@param max_mag: Faintest object limit.
@type max_mag: float
@param comp_snr: Minimum SNR of detected comparison star.
@type comp_snr: float
@return: bolean and file
"""
if ".fit" in os.path.basename(image_path):
fitslist = sorted(glob.glob(image_path))
if fitslist == 0:
print('No image FITS found in the {0}'.format(image_path))
raise SystemExit
else:
fitslist = sorted(glob.glob(image_path + '/*.fit?'))
if fitslist == 0:
print('No image FITS found in the {0}'.format(image_path))
raise SystemExit
# aper_trigger check count
aper_count = 0
for id, fitsfile in enumerate(fitslist):
if fitsfile:
hdu = fits.open(fitsfile)[0]
else:
print("FITS image has not been provided by the user!")
raise SystemExit
sb = Query()
ac = AstCalc()
to = TimeOps()
fo = FitsOps(fitsfile)
header = hdu.header
w = WCS(header)
naxis1 = fo.get_header('naxis1')
naxis2 = fo.get_header('naxis2')
odate = fo.get_header('date-obs')
t1 = Time("{0}".format(odate),
out_subfmt="date")
dt = TimeDelta(12 * 3600, format='sec')
onight = t1 - dt
exptime = fo.get_header('exptime')
if exptime is not None and exposure is not None:
if float(exptime) != exposure:
continue
if aper_count == 0:
aper_trigger = id
aper_count += 1
if target is None:
objct = fo.get_header('object')
else:
objct = str(target)
filter = fo.get_header('filter').replace(" ", "_")
# t1 = Time(odate.replace('T', ' '))
# exptime = fo.get_header('exptime')
# dt = TimeDelta(exptime / 2.0, format='sec')
# odate_middle = t1 + dt
# jd = to.date2jd(odate_middle.value)
jd = to.date2jd(odate)
ra_dec = ac.center_finder(fitsfile, wcs_ref=True)
image = f2n.fromfits(fitsfile, verbose=False)
image.setzscale('auto', 'auto')
image.makepilimage('log', negative=False)
request = sb.find_skybot_objects(odate,
ra_dec[0].degree,
ra_dec[1].degree,
radius=radius)
if request[0]:
if multi_object:
asteroids = Table(np.sort(request[1][::-1],
order=['m_v']))
else:
asteroids = Table(np.sort(request[1],
order=['num']))
mask = asteroids['num'] == str(objct).upper()
asteroids = asteroids[mask]
elif request[0] is False:
print(request[1])
raise SystemExit
data = hdu.data.astype(float)
bkg = sep.Background(data)
data_sub = data - bkg
for i in range(len(asteroids)):
if float(asteroids['m_v'][i]) <= max_mag:
c = coordinates.SkyCoord('{0} {1}'.format(
asteroids['ra(h)'][i],
asteroids['dec(deg)'][i]),
unit=(u.hourangle, u.deg),
frame='icrs')
# asteroid's X and Y coor
a_x, a_y = w.wcs_world2pix(c.ra.degree, c.dec.degree, 1)
if naxis1 < a_x or naxis2 < a_y or a_x < 0 or a_y < 0:
continue
# phot asteroids
flux, fluxerr, flag = sep.sum_circle(
data_sub,
a_x,
a_y,
6,
err=bkg.globalrms,
gain=gain)
if flux == 0.0 or fluxerr == 0.0:
print("Bad asteroid selected (out of frame!)!")
raise SystemExit
if id == aper_trigger:
snr = []
for aper in range(30):
# phot asteroids
flux_test, fluxerr_test, flag_test = sep.sum_circle(
data_sub,
a_x,
a_y,
aper,
err=bkg.globalrms,
gain=gain)
snr.append([aper, (flux_test/fluxerr_test)])
npsnr = np.array(snr)
maxtab, mintab = peakdet(npsnr[:, 1], 0.1)
try:
aper_radius = maxtab[:, 0][0]
print("Aperture calculated: {0} px".format(
aper_radius))
except IndexError:
continue
if plot_aper_test:
plt.title(asteroids['num'][i])
plt.xlabel('Aperture (px)')
plt.ylabel('SNR')
plt.scatter(npsnr[:, 0],
npsnr[:, 1])
plt.scatter(maxtab[:, 0], maxtab[:, 1],
color='red')
plt.scatter(mintab[:, 0], mintab[:, 1],
color='yellow')
plt.show()
magt_i = ac.flux2mag(flux, float(exptime))
magt_i_err = fluxerr / flux * 2.5 / math.log(10)
min_mag_ast = float(asteroids['m_v'][i]) - 2
label = '{0}'.format(asteroids['num'][i])
image.drawcircle(a_x, a_y, r=aper_radius,
colour=(255, 0, 0), label=label)
if i == 0 and id == aper_trigger:
comptable = sb.query_color(c.ra.degree,
c.dec.degree,
5.0 / 60.0,
min_mag=min_mag_ast,
max_mag=19.5)
s_comptable = sb.sort_stars(comptable, min_mag_ast)
if len(s_comptable) == 0:
continue
phot_res_list = []
# phot comp. stars
for j in range(len(s_comptable)):
# star's X and Y coor
s_x, s_y = w.wcs_world2pix(s_comptable['RAJ2000'][j],
s_comptable['DEJ2000'][j],
1)
if naxis1 < s_x or naxis2 < s_y or s_x < 0 or s_y < 0:
continue
# print('Circle', s_x, s_y, 10)
flux, fluxerr, flag = sep.sum_circle(
data_sub,
s_x,
s_y,
aper_radius,
err=bkg.globalrms,
gain=gain)
if flux == 0.0 or fluxerr == 0.0:
print("Bad star selected!")
raise SystemExit
if (flux / fluxerr) <= comp_snr:
continue
magc_i = ac.flux2mag(flux, float(exptime))
magc_i_err = fluxerr / flux * 2.5 / math.log(10)
try:
magt = (float(magt_i) -
float(magc_i)) + s_comptable['Rmag'][j]
magt_err = math.sqrt(
math.pow(float(magt_i_err), 2) +
math.pow(float(magc_i_err), 2))
except:
continue
label = '{0}'.format(s_comptable['NOMAD1'][j])
image.drawcircle(s_x, s_y, r=aper_radius,
colour=(0, 255, 0), label=label)
phot_res_list.append([asteroids['num'][i],
jd,
onight.iso,
float(magt_i),
float(magt_i_err),
float(magc_i),
float(magc_i_err),
float(magt),
float(magt_err),
asteroids['m_v'][i],
s_comptable['NOMAD1'][j],
s_comptable['Rmag'][j]])
np_phot_res = np.array(phot_res_list)
if len(np_phot_res) == 0:
continue
# magnitude average
magt_avr = np.average(np_phot_res[:, 7].astype(float),
weights=np_phot_res[:, 8].astype(
float))
# magt_std calc.
magt_std = np.std(np_phot_res[:, 7].astype(float))
np_magt_avr_std = [[magt_avr,
magt_std,
filter,
exptime] for i in range(
len(np_phot_res))]
k = np.array(np_magt_avr_std).reshape(
len(np_magt_avr_std), 4)
# numpy array with magt_avr
np_phot_res_avg_std = np.concatenate(
(np_phot_res,
k),
axis=1)
phot_res_table = Table(np_phot_res_avg_std,
names=('ast_num',
'jd',
'onight',
'magt_i',
'magt_i_err',
'magc_i',
'magc_i_err',
'magt',
'magt_err',
'ast_mag_cat',
'nomad1',
'star_Rmag',
'magt_avr',
'magt_std',
'filter',
'exposure'),
dtype=('U10',
'S25',
'U10',
'f8',
'f8',
'f8',
'f8',
'f8',
'f8',
'f8',
'U20',
'f8',
'f8',
'f8',
'U20',
'f8'))
phot_res_table['magt_i'].format = '.3f'
phot_res_table['magt_i_err'].format = '.3f'
phot_res_table['magc_i'].format = '.3f'
phot_res_table['magc_i_err'].format = '.3f'
phot_res_table['magt'].format = '.3f'
phot_res_table['magt_err'].format = '.3f'
phot_res_table['magt_avr'].format = '.3f'
phot_res_table['magt_std'].format = '.3f'
with open('{0}/{1}.txt'.format(
os.getcwd(),
asteroids['num'][i]), 'a') as f_handle:
f_handle.seek(0, os.SEEK_END)
if not os.path.isfile(str(f_handle)):
phot_res_table.write(
f_handle,
format='ascii.commented_header')
else:
phot_res_table.write(f_handle,
format='ascii.no_header')
if sqlite_file is not None:
self.table_to_database(phot_res_table,
sqlite_file=sqlite_file,
table_name=table_name)
# Test
time.sleep(0.2)
self.update_progress(
"Photometry is done for: {0}".format(fitsfile),
id / len(fitslist))
image.writetitle(os.path.basename(fitsfile))
fitshead, fitsextension = os.path.splitext(fitsfile)
image.writeinfo([odate], colour=(255, 100, 0))
image.tonet('{0}.png'.format(fitshead))
self.update_progress("Photometry done!", 1)
return(True)
def loadImageFromFits(self, fits):
self.fitsToCrop = f2n.fromfits(fits)
def get_cropped_image(filepath, xmin, xmax, ymin, ymax): im = f2n.fromfits(filepath) # TODO don't read the file each time im.crop(xmin, xmax, ymin, ymax) return im
"y": s.y
} for s in preciserefmanstars]
refautostarsasdicts = [{
"name": s.name,
"x": s.x,
"y": s.y
} for s in refautostars]
#print refmanstarsasdicts
if defringed:
reffitsfile = os.path.join(alidir, refimage['imgname'] + "_defringed.fits")
else:
reffitsfile = os.path.join(alidir, refimage['imgname'] + "_skysub.fits")
f2nimg = f2n.fromfits(reffitsfile)
f2nimg.setzscale(z1=0, z2=1000)
#f2nimg.rebin(2)
f2nimg.makepilimage(scale="log", negative=False)
f2nimg.drawstarlist(refautostarsasdicts, r=30, colour=(150, 150, 150))
#f2nimg.drawstarlist(refmanstarsasdicts, r = 25, colour = (0, 0, 255))
f2nimg.drawstarlist(preciserefmanstarsasdicts, r=5, colour=(255, 0, 0))
f2nimg.writeinfo(
["Sextractor stars (flag-filtered) : %i" % len(refautostarsasdicts)],
colour=(150, 150, 150))
#f2nimg.writeinfo(["", "Stars that you dutifully wrote in the alignment star catalog : %i" % len(refmanstarsasdicts)], colour = (0, 0, 255))
f2nimg.writeinfo([
"",
"Identified alignment stars with corrected sextractor coordinates : %i" %
hdu = pyfits.PrimaryHDU(pixelarray.transpose(), hdr)
hdu.verify("fix")
hdu.writeto(newfitsfilepath)
print "Filter histo :"
filterhisto = [(f, filterlist.count(f)) for f in sorted(list(set(filterlist)))]
print "\n".join(["%s : %i" % h for h in filterhisto])
########
print "\n Now I make pngs of these croped images vs raw images"
proquest(askquestions)
if not os.path.isdir(pngdir):
os.mkdir(pngdir)
croppaths = os.popen('ls '+destdir)
croppaths = [os.path.join(destdir,croppath).split('\n')[0] for croppath in croppaths]
for origpath, croppath in zip(origpaths,croppaths):
cropimage = f2n.fromfits(croppath)
cropimage.setzscale("auto", "auto")
cropimage.makepilimage(scale = 'log', negative = False)
pngpath = os.path.join(pngdir,os.path.basename(croppath)).split('.fits')[0]+'.png'
cropimage.tonet(pngpath)
ignore_folders_path = os.path.join(args.fits[1], 'ignore_folders.json')
source_dirs = set([name for name in os.listdir(args.fits[0]) if os.path.isdir(os.path.join(args.fits[0], name))])
# and diff with ignored folders
dirs_to_parse = source_dirs.difference(ignore_folders)
print dirs_to_parse
print ignore_folders
print source_dirs
# go through new folders
for dir in dirs_to_parse:
for fits_object in fits_parser.index_directory_of_fits_files(os.path.join(args.fits[0], dir), completed)['files']:
out_stem = os.path.join(args.fits[1], 'images', str(fits_object['epoch']))
# json dump
with open(out_stem + '.json', 'w') as file:
json.dump(fits_object, file)
# convert and dump image
myimage = f2n.fromfits(fits_object['path'])
myimage.setzscale()
myimage.makepilimage('lin')
print "------"
myimage.tonet(out_stem + '.png')
# add path to completed list
completed.append(str(fits_object['path']))
with open(completed_path, "w+") as file:
json.dump(completed, file)
# refresh index of out dir
with open(os.path.join(args.fits[1], 'images', 'index.json'), 'w') as file:
json.dump([f.replace('.json', '')
for f
in os.listdir(os.path.join(args.fits[1], 'images')) if f.endswith('json') and not f == 'ignore_folders.json' and not f == 'index.json'], file)
if args.init is not None:
# The following two lines are only needed if f2n.py and f2n_fonts
# are not yet copied somewhere into your usual python path !
import sys
sys.path.append("../.") # The directory that contains f2n.py and f2n_fonts !
# Now we can go on as usual :
import f2n
# And show a minimalistic exemple :
myimage = f2n.fromfits("example.fits") # The way to read a FITS file.
myimage.setzscale() # By default, automatic cutoffs will be calculated.
myimage.makepilimage("lin") # By default, a log transformation would be used.
myimage.tonet("1_simple.png") # We write the png.
def irafalign(filepath, uknstarlist, refstarlist, shape,
alifilepath=None, outdir="alipy_out",
makepng=False, hdu=0, verbose=True):
"""
Uses iraf geomap and gregister to align the image. Three steps :
* Write the matched source lists into an input file for geomap
* Compute a geomap transform from these stars.
* Run gregister
:param filepath: FITS file to be aligned
:type filepath: string
:param uknstarlist: A list of stars from the "unknown" image to be aligned,
that matches to ...
:type uknstarlist: list of Star objects
:param refstarlist: ... the list of corresponding stars in the reference
image.
:type refstarlist: list of Star objects
:param shape: Output shape (width, height)
:type shape: tuple
:param alifilepath: where to save the aligned image. If None, I put it in
the default directory.
:type alifilepath: string
:param makepng: If True I make a png of the aligned image as well.
:type makepng: boolean
:param hdu: The hdu of the fits file that you want me to use.
0 is primary. If multihdu, 1 is usually science.
"""
try:
from pyraf import iraf
except ImportError:
print("Couldn't import pyraf !")
return
assert len(uknstarlist) == len(refstarlist)
if len(uknstarlist) < 2:
if verbose:
print("Not enough stars for using geomap !")
return
basename = os.path.splitext(os.path.basename(filepath))[0]
geomapinpath = basename + ".geomapin"
geodatabasepath = basename + ".geodatabase"
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
# Step 1, we write the geomap input.
table = []
for (uknstar, refstar) in zip(uknstarlist, refstarlist):
table.append([refstar.x, refstar.y, uknstar.x, uknstar.y])
geomap = open(geomapinpath, "wb") # b needed for csv
writer = csv.writer(geomap, delimiter="\t")
writer.writerows(table)
geomap.close()
# Step 2, geomap
iraf.unlearn(iraf.geomap)
iraf.geomap.fitgeom = "rscale"
# You can change this to:
# shift, xyscale, rotate, rscale
iraf.geomap.function = "polynomial" # Surface type
iraf.geomap.maxiter = 3 # Maximum number of rejection iterations
iraf.geomap.reject = 3.0 # Rejection limit in sigma units
# other options you could specify :
# (xxorder= 2) Order of x fit in x
# (xyorder= 2) Order of x fit in y
# (xxterms= half) X fit cross terms type
# (yxorder= 2) Order of y fit in x
# (yyorder= 2) Order of y fit in y
# (yxterms= half) Y fit cross terms type
# (calctyp= real) Computation type
iraf.geomap.transfo = "broccoli" # keep it
iraf.geomap.interac = "no" # keep it
iraf.geomap.verbose = "yes" # keep it
# iraf.geomap.results = "bla.summary" # The optional results summary files
geomapblabla = iraf.geomap(input=geomapinpath,
database=geodatabasepath,
xmin=1, xmax=shape[0],
ymin=1, ymax=shape[1],
Stdout=1)
# We read this output ...
for line in geomapblabla:
if "X and Y scale:" in line:
mapscale = line.split()[4:6]
if "Xin and Yin fit rms:" in line:
maprmss = line.split()[-2:]
if "X and Y axis rotation:" in line:
mapangles = line.split()[-4:-2]
if "X and Y shift:" in line:
mapshifts = line.split()[-4:-2]
# not used?
geomaprms = math.sqrt(float(maprmss[0]) * float(maprmss[0]) +
float(maprmss[1]) * float(maprmss[1]))
geomapangle = float(mapangles[0]) # % 360.0
geomapscale = 1.0 / float(mapscale[0])
if mapscale[0] != mapscale[1]:
raise RuntimeError("Error reading geomap scale")
if verbose:
print(("IRAF geomap : Rotation %+11.6f [deg], "
"scale %8.6f, RMS %.3f [pixel]") % (geomapangle,
geomapscale,
geomaprms))
# Step 3
if alifilepath is None:
alifilepath = os.path.join(outdir, basename + "_gregister.fits")
else:
outdir = os.path.split(alifilepath)[0]
if not os.path.isdir(outdir):
os.makedirs(outdir)
if os.path.isfile(alifilepath):
os.remove(alifilepath)
iraf.unlearn(iraf.gregister)
iraf.gregister.geometry = "geometric" # linear, distortion, geometric
iraf.gregister.interpo = "spline3" # linear, spline3
iraf.gregister.boundary = "constant" # padding with zero
iraf.gregister.constant = 0.0
iraf.gregister.fluxconserve = "yes"
if verbose:
print("IRAF gregister ...")
regblabla = iraf.gregister(input='%s[%s]' % (filepath, hdu),
output=alifilepath,
database=geodatabasepath,
transform="broccoli",
Stdout=1)
# not used?
if verbose:
print("IRAF gregister done !")
if os.path.isfile(geomapinpath):
os.remove(geomapinpath)
if os.path.isfile(geodatabasepath):
os.remove(geodatabasepath)
if makepng:
try:
import f2n
except ImportError:
print("Couldn't import f2n -- install it !")
return
myimage = f2n.fromfits(alifilepath, verbose=False)
myimage.setzscale("auto", "auto")
myimage.makepilimage("log", negative=False)
myimage.writetitle(os.path.basename(alifilepath))
if not os.path.isdir(outdir):
os.makedirs(outdir)
myimage.tonet(
os.path.join(outdir, os.path.basename(alifilepath) + ".png"))
import momentsml
import matplotlib.pyplot as plt
import numpy as np
import config
import os
import f2n
filepath = os.path.join(config.workdir, "psf.fits")
psf = momentsml.tools.io.fromfits(filepath)
print psf.shape
#plt.matshow(np.log10(psf), cmap=plt.get_cmap("gray"))
#plt.show()
myimage = f2n.fromfits(filepath)
#crop = 1
#myimage.crop(crop, -crop, crop, -crop)
myimage.setzscale(1.0e-5, 0.001)
myimage.makepilimage("log", negative=False)
#myimage.setzscale(-0.3, 1.0)
#myimage.makepilimage("lin", negative = False)
myimage.upsample(5)
pngimgpath = os.path.join(config.workdir, "psf.png")
myimage.tonet(pngimgpath)