#! /usr/bin/env python2
# -*- coding: utf-8 -*-


__version__ = '$Revision: 1.7 $'
__date__    = '$Date: 2014/10/06 12:06:58 $'

"""
Obdela eno sliko iz VEGE.
Vrne  match, število zvezd v fitu

Oktober 2014
Bojan Dintinjana 

"""


import os, sys
import getopt
import time
import pyfits
import math
import re
import string
import commands
import glob
import numpy as np
from pyraf import iraf




def __main():
	global dat, verbose, all
	
	all = 0
	verbose = 0
	
	opts,args = getopt.getopt(sys.argv[1:], "hva", ["help","verbose","all"])
	for o,a in opts:
		if o in ("-h", "--help"):
			__usage()
			sys.exit()
		if o in ("-v", "--verbose"):
			verbose = 1
		if o in ("-a", "--all"):
			all = 1
	if not args:
		__usage()
		sys.exit()  

	for image in args:
		print "Obdelujem sliko: ", image
		ProcessOne(image)


def ProcessOne(image):
	global fits, crval1, crval2,cd1_1,cd2_2,xref,yref   

	order=4
	vp = pipeline()

	fits = pyfits.open(image)
	try:
		matchx = fits[0].header['MATCHEDX']
		if matchx=='T' and not all:
			print "..je že obdelana."
			return
	except:
		pass
	
	crval1 = fits[0].header['CRVAL1']
	crval2 = fits[0].header['CRVAL2']
	xref   = fits[0].header['CRPIX1']
	yref   = fits[0].header['CRPIX2']
	
	try:
		cd1_1  = fits[0].header['CD1_1']
		cd2_2  = fits[0].header['CD2_2']
	except:
		cd1_1  = fits[0].header['CDELT1']
		cd2_2  = fits[0].header['CDELT2']
	
	ra=to_hms(crval1/15.)
	de=to_dms(crval2)
	
	#print("Slika v obdelavi je "+ image + "\n")
	#print ("scat -c ua2 -n 170 -mx 17 -r -700 %s %s J2000 > starlist.wcs" % (ra,de))
	
	o=commands.getstatusoutput("scat -c ua2 -n 200 -mx 18 -r -680 %s %s J2000 > starlist.wcs" % (ra,de))
	if o[0]==0:
		print "Katalog USNO_A2 ok."
	else:
		print "Napaka: "+o[1]
	
	

	match=False
	vp.dofind(image+'[1:2048,1:2048]')
	#order=2 #za linearno tan projekcijo
	n=vp.domatch(image,30)
	if n<7:
		print "Prvi match ni uspel, poizkušam znova"
		n = vp.domatch(image,60)
	if n>=7:
		#if n<12:
		#	order=3
		vp.domap(image,order)
		match=True
	else:
		print "Drugi match ni uspel, končujem."
	if match:
		print "Match: ", image, "narejeno.\n"
	else:
		print "Ni matcha: ", image, "\n"
	return match,n
 

	

	
class pipeline:
	def __init__(self):
		
		iraf.cl.menus  = "no"

		# da iraf ne spreminja lokalnih uparam, naj ima svojo tmp mapo
		#iraf.set(uparm="/home/vega/tmp/uparm/")
		
		iraf.digiphot()
		iraf.apphot()
		iraf.unlearn(iraf.apphot)
		iraf.apphot.verify = "no"
		iraf.apphot.verbose= "no"
		
		iraf.unlearn('imstat')
		
		iraf.unlearn(iraf.datapars)
		iraf.datapars.scale = 1.
		iraf.datapars.fwhmpsf = 5.0
		iraf.datapars.sigma = 15.
		iraf.datapars.datamin = 10.
		iraf.datapars.datamax = 65500.
		iraf.datapars.exposure = "EXPOSURE"
		iraf.datapars.obstime = "JD"

		iraf.unlearn(iraf.findpars)
		iraf.findpars.threshold = 10.
		iraf.findpars.nsigma = 1.5
	
		iraf.unlearn(iraf.centerpars)
		iraf.centerpars.cbox = 6.
		iraf.centerpars.cmaxiter = 10
		iraf.centerpars.maxshift = 3.
		iraf.centerpars.clean = "yes"

		iraf.photpars.apertures = "1.3"

		self.output1='_image_.coo.1'
		self.output2='_image_.coo.2'

		self.field  = "ID,OTIME,XC,YC,MSKY,STDEV,FLUX,MAG,MERR,ITIME,VMAG,BVMAG,AIRMASS,NAME"
		self.fields = string.split(self.field,',')
		self.expr = "PERROR='NoError' & CERROR='NoError' & SERROR='NoError' & MAG!=INDEF & MSKY!=INDEF & MERR!=INDEF"
		self.mstar= 0
		self.ra_rms = 0.0
		self.de_rms = 0.0
		self.imag  = 0.0
		self.iflux = 0.0
		
		
	
	def dofind(self,image):
		iraf.unlearn(iraf.daofind)
		self.clean(self.output1)
		stdev = iraf.imstat(image,fields='stddev',nclip=5,format='no',Stdout=1)
		print "Stdev. neba: %5.1f"%float(stdev[0])
		iraf.datapars.sigma = float(stdev[0])
		iraf.daofind(image,output=self.output1)
		iraf.psort(self.output1,field='MAG')
		commands.getstatusoutput('head -n 240  %s > %s' % (self.output1,self.output2))

	def domatch(self,image,nmatch):

		self.clean("_image_.mat.1")
		iraf.imcoords()
		iraf.unlearn(iraf.ccxymatch)
		iraf.ccxymatch.input = self.output2
		iraf.ccxymatch.reference = "starlist.wcs"
		iraf.ccxymatch.output = "_image_.mat.1"
		iraf.ccxymatch.tolerance = 7.
		iraf.ccxymatch.ptolerance = 10.
		iraf.ccxymatch.refpoints = ""
		iraf.ccxymatch.xin = xref
		iraf.ccxymatch.yin = yref
		iraf.ccxymatch.xmag = cd1_1*3600.
		iraf.ccxymatch.ymag = cd2_2*3600.
		iraf.ccxymatch.xrotation = 0.
		iraf.ccxymatch.yrotation = 0.
		iraf.ccxymatch.projection = "tnx"
		iraf.ccxymatch.lngref = crval1/15.
		iraf.ccxymatch.latref = crval2
		iraf.ccxymatch.lngcolumn = 2
		iraf.ccxymatch.latcolumn = 3
		iraf.ccxymatch.xcolumn = 1
		iraf.ccxymatch.ycolumn = 2
		iraf.ccxymatch.lngunits = "hours"
		iraf.ccxymatch.latunits = "degrees"
		iraf.ccxymatch.separation = 20
		iraf.ccxymatch.pseparation = 20
		iraf.ccxymatch.matching = "triangles"
		iraf.ccxymatch.nmatch = nmatch
		iraf.ccxymatch.ratio = 10.
		iraf.ccxymatch.nreject = 10
		iraf.ccxymatch.verbose = "yes"
		msg=iraf.ccxymatch(self.output2,"starlist.wcs","_image_.mat.1",7.,10.,Stdout=1)
		#print msg
		p=re.match(r'[\s+]?(?P<n>\d*)[\s+]reference coordinates matched.*',msg[-1])
		if p:
			self.mstar = int(p.group('n'))
			print "Število prepoznanih zvezd je ",self.mstar
		return self.mstar

	def domap(self,image,order):
		iraf.unlearn(iraf.ccmap)	
		iraf.ccmap.input = "_image_.mat.1"
		iraf.ccmap.database = "database.db"
		iraf.ccmap.solutions = image
		iraf.ccmap.images = image
		iraf.ccmap.results = ""
		iraf.ccmap.xcolumn = 3
		iraf.ccmap.ycolumn = 4
		iraf.ccmap.lngcolumn = 1
		iraf.ccmap.latcolumn = 2
		iraf.ccmap.refpoint = "user"
		iraf.ccmap.xref = "CRPIX1"
		iraf.ccmap.yref = "CRPIX2"
		iraf.ccmap.lngref = "CRVAL1"
		iraf.ccmap.latref = "CRVAL2"
		iraf.ccmap.refsystem = "J2000"
		iraf.ccmap.lngrefunits = "degrees"
		iraf.ccmap.latrefunits = "degrees"
		iraf.ccmap.projection = "tnx"
		iraf.ccmap.fitgeometry = "general"
		iraf.ccmap.function = "polynomial"
		iraf.ccmap.xxorder = order
		iraf.ccmap.xyorder = order
		iraf.ccmap.xxterms = "half"
		iraf.ccmap.yxorder = order
		iraf.ccmap.yyorder = order
		iraf.ccmap.yxterms = "half"
		iraf.ccmap.maxiter = 0
		iraf.ccmap.reject = 3.
		iraf.ccmap.update = "yes"
		iraf.ccmap.pixsystem = "logical"
		iraf.ccmap.verbose = "yes"
		iraf.ccmap.interactive = "no"
		iraf.ccmap.graphics = "stdgraph"
		iraf.ccmap.cursor = ""
		msg=iraf.ccmap("_image_.mat.1","database.db",Stdout=1)
		#print msg
		for i in range(len(msg)):
			p=re.match(r'\s+XI fit ok\.  ETA fit ok\.',msg[i])
		 	if p:
				print "Fit ok, ",
				iraf.hedit.add = "yes"
				iraf.hedit.addonly = "no"
				iraf.hedit.verify = "no"
				iraf.hedit.show = "no"
				iraf.hedit.update = "yes"
				iraf.hedit(image,"MATCHED","T")
				iraf.hedit(image,"MATCHEDX","T")
				
			rrms,drms =0.,0.
			p=re.match(r'.*fit rms:\s+(?P<rrms>\d*(\.\d*)?)\s+(?P<drms>\d*(\.\d*)?)',msg[i])
			if p:
				self.ra_rms = float(p.group('rrms'))
				self.de_rms = float(p.group('drms'))
				print 'napaka rms Ra/Dec: %6.3f" %6.3f"' %(self.ra_rms,self.de_rms)
				

	

	def clean(self,file):
		if os.access(file,os.F_OK):
			os.remove(file)



def to_hms(x):
	h = int(x)
	x -= h
	x *= 60.0
	m = int(x + 1e-6)
	s = int((x - m - 1e-6)*6000)/100.0
	return "%02d:%02d:%05.2f" % (h, m, s)

def to_dms(x):
	if (x>0):
		znak="+"
	else:
		znak="-"
	x=math.fabs(x)
	h = int(x)
	x -= h
	x *= 60.0
	m = int(x + 1e-6)
	s = int((x - m - 1e-6)*600)/10.0
	return "%1s%02d:%02d:%04.1f" % (znak, h, m, s)

def str_to_dec(x):
	z=1.0
	z1,z2,z3='','',''
	p=re.match(r'(?P<z1>[+-])?(?P<h>\d{1,2})[: ](?P<z2>[+-])?(?P<m>\d{1,2})[: ](?P<z3>[+-])?(?P<s>\d{1,2}(\.\d*)?)',x)
	if p:
		if p.group('z1')=='-' or p.group('z2')=='-' or p.group('z3')=='-' : z=-1.0
		return z*(float(p.group('h'))+float(p.group('m'))/60+float(p.group('s'))/3600)

def __usage():
	print >> sys.stderr, 'Uporaba: %s [opcije] slike' % sys.argv[0]
	print >> sys.stderr, '''Opcije:
	-h,--help		to navodilo
	-v,--verbose		vec izpisa
	-a,--all                obdela ponovno
	
Uporaba:
	$ VegaMatch.py ime_slike.fts		(Obdelava ene slike)
	$ VegaMatch.py imena_slik*.fts		(Obdelava serije slik)
	'''


if __name__ == '__main__':
	__main()

'''
$Log: AllSkyMatch.py,v $
	
'''