def display(self, band="g_SDSS", bands=["g_SDSS", "r_SDSS", "i_SDSS"]):
if self.surveyname == "Euclid": bands = ["VIS", "VIS", "VIS"]
import pylab as plt
plt.ion()
plt.figure(1)
plt.imshow(self.makeColorLens(bands=bands), interpolation="none")
plt.figure(2)
import colorImage
self.color = colorImage.ColorImage(
) #sigma-clipped single band residual
plt.imshow(self.color.createModel(self.fakeResidual[0][band],
self.fakeResidual[0][band],
self.fakeResidual[0][band])[:, :, 0],
interpolation="none")
plt.figure(3)
plt.imshow(self.fakeResidual[0][band], interpolation="none")
try:
self.fakeResidual[1]["RF"]
plt.figure(4)
plt.imshow(self.fakeResidual[1]["RF"], interpolation="none")
except KeyError:
pass
plt.draw()
raw_input()
plt.ioff()
def makeColorLens(self,
bands=["g_SDSS", "r_SDSS", "i_SDSS"],
recolourize=True):
if self.surveyname == "Euclid" and bands == [
"g_SDSS", "r_SDSS", "i_SDSS"
]:
bands = ["VIS", "VIS", "VIS"]
import colorImage
goodbands = []
for band in bands:
try:
self.image[band]
goodbands.append(band)
except KeyError:
pass
bands = goodbands
if len(bands) == 1:
bands = [bands[0], bands[0], bands[0]]
if len(bands) == 2:
bands = [bands[0], "dummy", bands[1]]
self.ml["dummy"] = (self.ml[bands[0]] + self.ml[bands[2]]) / 2
self.image["dummy"] = (self.image[bands[0]] +
self.image[bands[2]]) / 2
if recolourize:
self.color = colorImage.ColorImage()
self.color.bMinusr = (self.ml[bands[0]] - self.ml[bands[2]]) / 4.
self.color.bMinusg = (self.ml[bands[0]] - self.ml[bands[1]]) / 4.
self.color.nonlin = 4.
self.colorimage = self.color.createModel(\
self.image[bands[0]],self.image[bands[1]],self.image[bands[2]])
else:
self.colorimage = self.color.colorize(\
self.image[bands[0]],self.image[bands[1]],self.image[bands[2]])
return self.colorimage
sigg = pyfits.open("%s/clip_%s_weight_g.fits" %
(ddir, pref))[0].data.copy() #[a:-a,a:-a]**-0.5
sigr = pyfits.open("%s/clip_%s_weight_r.fits" %
(ddir, pref))[0].data.copy() #[a:-a,a:-a]**-0.5
sigi = pyfits.open("%s/clip_%s_weight_i.fits" %
(ddir, pref))[0].data.copy() #[a:-a,a:-a]**-0.5
sigz = pyfits.open("%s/clip_%s_weight_z.fits" %
(ddir, pref))[0].data.copy() #[a:-a,a:-a]**-0.5
psfg = pyfits.open("%s/clip_%s_psf_g.fits" % (ddir, pref))[0].data.copy()
psfr = pyfits.open("%s/clip_%s_psf_r.fits" % (ddir, pref))[0].data.copy()
psfi = pyfits.open("%s/clip_%s_psf_i.fits" % (ddir, pref))[0].data.copy()
psfz = pyfits.open("%s/clip_%s_psf_z.fits" % (ddir, pref))[0].data.copy()
import colorImage
color = colorImage.ColorImage()
colorimage = color.createModel(imgg, imgr, imgi)
#plt.imshow(colorimage,interpolation="none")
#plt.show()
psfmode = "crossconvolve"
RF = RingFinder(imgg,
imgi,
sigg,
sigi,
psfg,
psfi,
0.265,
1e12,
1e12,
visualize=False,
psfmode=psfmode)
sigg=pyfits.open("../dessims/weight_fits/%s_weight_g.fits"%pref)[0].data.copy()[a:-a,a:-a]**-0.5
sigr=pyfits.open("../dessims/weight_fits/%s_weight_r.fits"%pref)[0].data.copy()[a:-a,a:-a]**-0.5
sigi=pyfits.open("../dessims/weight_fits/%s_weight_i.fits"%pref)[0].data.copy()[a:-a,a:-a]**-0.5
psfg=pyfits.open("../dessims/psf_fits/%s_psf_g.fits"%pref)[0].data.copy()
psfr=pyfits.open("../dessims/psf_fits/%s_psf_r.fits"%pref)[0].data.copy()
psfi=pyfits.open("../dessims/psf_fits/%s_psf_i.fits"%pref)[0].data.copy()
#plt.imshow(imgg)
#plt.show()
#make colour image:
import colorImage
color = colorImage.ColorImage()
colorimage = color.createModel(imgg,imgr,imgi)
#plt.imshow(colorimage,interpolation="none")
#plt.savefig("colour.png"%pref)
#plt.show()
RF=RingFinder(imgg,imgi,sigg,sigi,psfg,psfi,0.265,1e12,1e12,visualize=False,psfmode="crossconvolve")
RFres=RF.ringfind(vb=True)
#ax=plt.subplot(1,3,count)
ax=plt.subplot(1,1,1)
size=colorimage.shape[0]
b=a*1