import numpy as np

from astropy.io import ascii

from astropy.io import fits

import catalog_match_sky_trans as cmts

from pyraf import iraf

import os

#routine to read catalogs - done

#rouine to match catalogs and plot result - done

#output geomap input file - done

#routine to run geomap and transform catalogs - done

#routine to match transformed catalogs - done

#routine to plot result - done

#routine to write transform full photometric catalog. - done

#for some reason I can't show the plots interactively and have to just

#save them.

#match new catalog against original catalog - done

#plot residuals - done

#Modify the geoxytran calls to indicate the column number of the input file

#figure out whether I should be transforming "forward" or "backward"

#make x-y plot file for new transformed catalog to see where the

#poorly transformed galaxies are

#make x and y coordinate catalog for z-band image

#rename all functions in preimage_coord_transform_<clust> to have "sky" in the name

#rename catalog_match_trans to catalog_match_sky_trans and rename all

#routines to have sky in name

#go through new preimage_coord_transform_sky_<clust> and change cmt

#routines to have "sky" in name

#check that code works

#**************

#make version of catalog_match_sky_trans to catalog_match_im_trans and rename all

#routines to have im in name. Make sure they work on x and y-coordinates.

#make new modules that transform image called

#preimage_coord_transform_im_<clust>.py and do everything in x and y

#coordinates

#write cat_im_match (version of cat_sky_match) with lims in x and

#y coordinate. Part of this matches against existing photometric

#catalog in z-band to get an identical set of coordinates.

#test on x and y catalogs

#transform z-band image

#move generic routines to separate module and keep cluster-specific

#routines as a file with cluster name

'''Run with

import preimage_coord_transform_sky_SpARCS0035 as pcts

#this matches the input and reference catalog and runs geomap and

#geoxytran on these catalogspct.cat_match_SpARCS0035(septol, fullcat_trans = 1)

pcts.cat_match_sky_SpARCS0035(3.0, fullcat_trans = 1)

'''

def cat_match_sky_SpARCS0035(septol, **kwargs):

decmax = lims['decmax'])

# #transform image using geotran

# if 'im_trans' in kwargs.keys():

# if kwargs['im_trans'] == 1:

# impath = preimage_read(clustname)

# imtrans(impath, dbfile,geomap_infile,lims)

# def imtrans(impath, dbfile, geomap_infile, lims):

# '''Run geotran on an image

# INPUT:

# impath : the full path to the image

# dbfile: the geomap database file

# geomap_infile: the name of the input coordinate file for the

# geomap transformation, which is used as the record identifier for

# the transfor

# lims: a dictionary that defines the minimum and maximum

# '''

# iraf.geotran(impath, './test.fits', dbfile, geomap_infile)

def georun_sky(clustname, lims):

return dbfile, geomap_infile

#def cat_trans_sky_run():

# cat_trans_sky('/Users/grudnick/Work/GOGREEN/Catalogs/Preimaging/SpARCS0035/SPARCS0035_phot_v2.0_USE.fits', 'SpARCS0035_geomap.db', './geomap_coords.SpARCS0035.in','./SpARCS0035_J1.v0.cat', 'SpARCS0035', 3.0)

def cat_trans_sky(incat, dbfile, geomap_infile, refcat, clustname, septol, **kwargs):

cmts.match_diff_sky_plot(rarefm,decrefm,ratransm,dectransm, plotfile = allcattrans_plotfile)

def speczcat_trans_sky(incat, dbfile, geomap_infile, refcat, clustname, septol, **kwargs):

cmts.match_diff_sky_plot(rarefm,decrefm,ratransm,dectransm, plotfile = allcattrans_plotfile)

def cat_read_SpARCS0035():

return gg_dat, ref_dat, catgogreen, refcat, zcat_dat, zcat, speczcat;

# def preimage_read(clustname):

# '''

# Read in the correct preimage using the GOGREEN.fits file.

# INPUT PARAMETERS:

# clustname: the name of the cluster that is used in the GOGREEN.fits file

# OUTPUT

# the name and path of the fits image.

# '''

# configpath = '/Users/grudnick/Work/GOGREEN/Repo/gogreen/config/GOGREEN.fits'

# info_hdul = fits.open(configpath)

# info_dat = info_hdul[1].data

# i = np.where(info_dat['cluster'] == clustname)

# imdir = '/Users/grudnick/Work/GOGREEN/Data/Preimaging/' + clustname + '/GMOS/Z/'

# imroot = info_dat['z_image'][i[0]]

# imroot = imroot[0]

# imname = imroot + '.fits[1]'

# impath = imdir + imname

# return impath