def make_plots(dirname, fnames):
# get the highest-level directory, assume it is the target source ID
obj = os.path.split(dirname)[-1]
for fn in fnames:
# each band gets listed...
if 'band0' not in fn or '.sav' not in fn:
continue
# templates:
# coadd_cleanband0in_clean_music_20130815_jk000.sav
# 130820_ob1_band0i_clean_music_20130815_map.sav
obs = "_".join(fn.split("_")[:2])
#obs = fn[:11]
print "Working on file ", os.path.join(dirname, obs)
data = load_data(os.path.join(dirname, obs))
sm, us = convolve_and_match(data, obj, writefits=False)
flux, bg, err = sed_from_dict(sm)
pl.clf()
plot_sed(flux, bg, err, label='Smooth')
flux, bg, err = sed_from_dict(us)
plot_sed(flux, bg, err, label='Unsharp')
pl.title(obj)
pl.legend(loc='best')
pl.savefig(os.path.join(dirname, obj + obs) + "_SED.png",
bbox_inches='tight')
def make_plots(dirname, fnames):
# get the highest-level directory, assume it is the target source ID
obj = os.path.split(dirname)[-1]
for fn in fnames:
# each band gets listed...
if 'band0' not in fn or '.sav' not in fn:
continue
# templates:
# coadd_cleanband0in_clean_music_20130815_jk000.sav
# 130820_ob1_band0i_clean_music_20130815_map.sav
obs = "_".join(fn.split("_")[:2])
#obs = fn[:11]
print "Working on file ",os.path.join(dirname,obs)
data = load_data(os.path.join(dirname,obs))
sm,us = convolve_and_match(data,obj,writefits=False)
flux,bg,err = sed_from_dict(sm)
pl.clf()
plot_sed(flux,bg,err, label='Smooth')
flux,bg,err = sed_from_dict(us)
plot_sed(flux,bg,err, label='Unsharp')
pl.title(obj)
pl.legend(loc='best')
pl.savefig(os.path.join(dirname,obj+obs)+"_SED.png",bbox_inches='tight')
def make_plots(dirname, fnames):
obj = os.path.split(dirname)[-1]
for fn in fnames:
# each band gets listed...
if 'band0' not in fn:
continue
obs = fn[:11]
print "Working on file ", os.path.join(obj, obs)
data = load_data(os.path.join(obj, obs))
sm, us = convolve_and_match(data, 'W49', writefits=False)
flux, bg, err = sed_from_dict(sm)
pl.clf()
plot_sed(flux, bg, err, label='Smooth')
flux, bg, err = sed_from_dict(us)
plot_sed(flux, bg, err, label='Unsharp')
pl.title(obj)
pl.legend(loc='best')
pl.savefig(os.path.join(obj, obs) + "_SED.png", bbox_inches='tight')
def make_plots(dirname, fnames):
obj = os.path.split(dirname)[-1]
for fn in fnames:
# each band gets listed...
if 'band0' not in fn:
continue
obs = fn[:11]
print "Working on file ",os.path.join(obj,obs)
data = load_data(os.path.join(obj,obs))
sm,us = convolve_and_match(data,'W49',writefits=False)
flux,bg,err = sed_from_dict(sm)
pl.clf()
plot_sed(flux,bg,err, label='Smooth')
flux,bg,err = sed_from_dict(us)
plot_sed(flux,bg,err, label='Unsharp')
pl.title(obj)
pl.legend(loc='best')
pl.savefig(os.path.join(obj,obs)+"_SED.png",bbox_inches='tight')
def make_plots(dirname, fnames):
# get the highest-level directory, assume it is the target source ID
obj = os.path.split(dirname)[-1]
for fn in fnames:
# each band gets listed...
if 'band0' not in fn or '.sav' not in fn:
continue
# templates:
# coadd_cleanband0in_clean_music_20130815_jk000.sav
# 130820_ob1_band0i_clean_music_20130815_map.sav
obs = "_".join(fn.split("_")[:2])
#obs = fn[:11]
print "Working on file ",os.path.join(dirname,obs)
data = load_data(os.path.join(dirname,obs))
headers = {k: load_header(data[k].mapstruct) for k in data}
sm,us = convolve_and_match(data,obj,headers=headers,writefits=True,savepath=dirname)
vmin = -1000 #max([sm[2].min(),-1000])
vmax = max([sm[2].max(),5000])
print obj, obs, vmin, vmax
prefix = os.path.join(dirname,obj+obs)
pl.clf()
viewer(data, vmin=vmin, vmax=vmax, cb=True)
pl.suptitle(obj)
pl.savefig(prefix+"_quicklook.png",bbox_inches='tight')
pl.clf()
dictviewer(sm, vmin=vmin, vmax=vmax, cb=True)
pl.suptitle(obj)
pl.savefig(prefix+"_quicklook_smooth.png",bbox_inches='tight')
pl.clf()
dictviewer(us, vmin=vmin, vmax=vmax, cb=True)
pl.suptitle(obj)
pl.savefig(prefix+"_quicklook_unsharp.png",bbox_inches='tight')
from astropy.io import fits
import idlsave
import itertools
import scipy.ndimage
from astropy.nddata.convolution import make_kernel,convolve
import numpy as np
import sys
import os
sys.path.append(os.path.split(os.getcwd())[0])
from convolve_match_makefits import convolve_and_match
data_g010_1 = {k:idlsave.read('gal_010.47+00.03/130820_ob3_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
data_g010_2 = {k:idlsave.read('gal_010.47+00.03/130820_ob4_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
data_g000_1 = {k:idlsave.read('gal_0.253+0.016/130820_ob1_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
data_g000_2 = {k:idlsave.read('gal_0.253+0.016/130820_ob2_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
data_g012_1 = {k:idlsave.read('gal_012.21-00.10/130820_ob5_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
data_g012_2 = {k:idlsave.read('gal_012.21-00.10/130820_ob6_band%ii_clean_music_20130815_map.sav' % k) for k in xrange(4)}
datasets = dict(zip(['G010_1','G010_2','G000_1','G000_2','G012_1','G012_2'],
[data_g010_1, data_g010_2, data_g000_1, data_g000_2, data_g012_1, data_g012_2]))
for jj,(k,data) in enumerate(datasets.iteritems()):
print(jj)
convolve_and_match(data,k)
data_g000_1 = {
k: idlsave.read(
'gal_0.253+0.016/130820_ob1_band%ii_clean_music_20130815_map.sav' % k)
for k in xrange(4)
}
data_g000_2 = {
k: idlsave.read(
'gal_0.253+0.016/130820_ob2_band%ii_clean_music_20130815_map.sav' % k)
for k in xrange(4)
}
data_g012_1 = {
k: idlsave.read(
'gal_012.21-00.10/130820_ob5_band%ii_clean_music_20130815_map.sav' % k)
for k in xrange(4)
}
data_g012_2 = {
k: idlsave.read(
'gal_012.21-00.10/130820_ob6_band%ii_clean_music_20130815_map.sav' % k)
for k in xrange(4)
}
datasets = dict(
zip(['G010_1', 'G010_2', 'G000_1', 'G000_2', 'G012_1', 'G012_2'], [
data_g010_1, data_g010_2, data_g000_1, data_g000_2, data_g012_1,
data_g012_2
]))
for jj, (k, data) in enumerate(datasets.iteritems()):
print(jj)
convolve_and_match(data, k)