#print len(para)
ln=len(para)
for l in range(ln):
filename='../fits/add-{0}.fits'.format(l+1) # take one image
d = pyfits.open(filename)[0].data.copy()
d = concatenate([d,zeros([10,len(d.T)])])
d = concatenate([d,zeros([len(d),10])],axis=1) #expand the array
#print sum(d[65:69,67:71])
#[0:136] x ,y -> y, x
#### y x
#0:174
a=[0,3,0,3,2,5,2,5,4,1,4,1]
b=[0,0,3,3,4,4,1,1,2,2,5,5] #from the info. given by kai
for i in range(len(a)):
dd=d[a[i]:360+a[i],b[i]:360+b[i]] #the size before bin
aaa=block(dd,(60,60))
pyfits.PrimaryHDU(aaa).writeto('../fits/binall/sam-{0}-{1}.fits'.format(l+1,i+1),clobber=True)
filename='../fits/spsf-{0}.fits'.format(l+1) # take one image
p = pyfits.open(filename)[0].data.copy()
p = concatenate([p,zeros([10,len(p.T)])])
p = concatenate([p,zeros([len(p),10])],axis=1) #expand the array
#print sum(d[65:69,67:71])
#[0:136] x ,y -> y, x
#### y x
#0:174
a=[0,3,0,3,2,5,2,5,4,1,4,1]
b=[0,0,3,3,4,4,1,1,2,2,5,5] #from the info. given by kai
for i in range(len(a)):
pp=p[a[i]:360+a[i],b[i]:360+b[i]] #the size before bin
bbb=block(pp,(60,60))
pyfits.PrimaryHDU(bbb).writeto('../fits/binall/sam_psf-{0}-{1}.fits'.format(l+1,i+1),clobber=True)
from numpy import *
from block import *
import pyfits
filename='../fits/sub400.fits'
d = pyfits.open(filename)[0].data.copy()
#d = concatenate([zeros([4,len(d.T)]),d])
#d = concatenate([zeros([len(d),4]),d],axis=1) #expand the array to use '-' drizzle
d = concatenate([d,zeros([10,len(d.T)])])
d = concatenate([d,zeros([len(d),10])],axis=1) #expand the array
sc=(len(d.T)-10)/4
#print sum(d[65:69,67:71])
#[0:136] x ,y -> y, x
#### y x
#0:174
a=[0,2,0,2,1,3,1,3]
b=[0,0,2,2,3,3,1,1] #from the info. given by observation
#a=[-2+4,-2+4,-2+4,-1+4,-1+4,0+4,0+4,1+4,1+4,2+4,2+4,2+4]
#b=[-2+4,0+4,-2+4,-1+4,1+4,-2+4,2+4,-1+4,1+4,-2+4,0+4,2+4]
for i in range(len(a)):
dd=d[a[i]:sc*4+a[i],b[i]:sc*4+b[i]]
aaa=block(dd,(sc,sc))
pyfits.PrimaryHDU(aaa).writeto('../fits/binpsf/psf{0}.fits'.format(i+1),clobber=True)
#from high resoluted images (sub=6) to lower one (bin together)
from numpy import *
from block import *
import pyfits
file1 = open('../pylens/WFI2033.txt','r')
para = loadtxt(file1)
file1.close()
#print len(para)
ln=len(para)
for l in range(ln):
filename='../fits/HE_arc-{0}.fits'.format(l+1) # take one image
d = pyfits.open(filename)[0].data.copy()
d = concatenate([d,zeros([10,len(d.T)])])
d = concatenate([d,zeros([len(d),10])],axis=1) #expand the array
#print sum(d[65:69,67:71])
#[0:136] x ,y -> y, x
#### y x
#0:174
a=[0,2,0,2,1,3,1,3]
b=[0,0,2,2,3,3,1,1] #from the info. given by observation
for i in range(len(a)):
dd=d[a[i]:240+a[i],b[i]:240+b[i]] #the size before bin
aaa=block(dd,(60,60))
pyfits.PrimaryHDU(aaa).writeto('../fits/binall/arc-{0}-{1}.fits'.format(l+1,i+1),clobber=True)
from numpy import *
from block import *
import pyfits
filename='sub400.fits'
d = pyfits.open(filename)[0].data.copy()
#d = concatenate([zeros([4,len(d.T)]),d])
#d = concatenate([zeros([len(d),4]),d],axis=1) #expand the array to use '-' drizzle
d = concatenate([d,zeros([10,len(d.T)])])
d = concatenate([d,zeros([len(d),10])],axis=1) #expand the array
print d.shape
#print sum(d[65:69,67:71])
#[0:136] x ,y -> y, x
#### y x
#0:174
a=[0,1,0,1,2,0,2,3,0,3,1,3]
b=[0,0,1,1,0,2,2,0,3,3,3,1]
#a=[-2+4,-2+4,-2+4,-1+4,-1+4,0+4,0+4,1+4,1+4,2+4,2+4,2+4]
#b=[-2+4,0+4,-2+4,-1+4,1+4,-2+4,2+4,-1+4,1+4,-2+4,0+4,2+4]
for i in range(len(a)):
dd=d[a[i]:108+a[i],b[i]:108+b[i]]
aaa=block(dd,(27,27))
pyfits.PrimaryHDU(aaa).writeto('binpsf/psf{0}.fits'.format(i+1),clobber=True)
